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Reply to the reviewers

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Reply to the Reviewers

I thank the Referees for their...

Referee #1

1. The authors should provide more information when...

Responses + The typical domed appearance of a hydrocephalus-harboring skull is apparent as early as P4, as shown in a new side-by-side comparison of pups at that age (Fig. 1A). + Though this is not stated in the MS 2. Figure 6: Why has only...

Response: We expanded the comparison

Minor comments:

1. The text contains several...

Response: We added...

Referee #2

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Referee #3

Evidence, reproducibility and clarity

Dr. Ancheta et al. designed several parameters to assess different velocity algorithms, including local consistency, method agreement, overlap of derived genes, and robustness to sequencing depth. Generally, this helps scientists understand the performance of each software. However, I don't think this is enough to help scientists judge which one is better. The biggest problem in the manuscript is the lack of a ground truth. I suggest the authors choose tissues with reliable ground truth, such as spermiogenesis, which has a single lineage direction. You would see a clear streamline from pachytene spermatocytes to sperm, or embryonic cells with different culture days, where the direction should go from earlier to later stages. I strongly suggest the authors use clear lineage samples like spermiogenesis. After that, I think it will be a very helpful paper for scientists.

1. Local consistency is a useful parameter that helps scientists determine which one has more uniform directions.

2. Method agreement is problematic because I don't know which one is ground truth. If you cannot get ground truth, you could use the average direction or angle as the ground truth to see which one is significantly biased from the averages.

3. The overlap of the driver genes also lacks ground truth. Fig4C is good; we could use the overlap of all methods' genes as ground truth to see which one is too biased. I suggest you perform a GO term analysis to see the driver gene distribution and count how many genes are related to the expected GO term. That would also provide evidence to support the ground truth.

4. Robustness to sequencing depth is a good parameter. No comment.

5. The discussion could include more about other methods, such as nascent RNA single-cell sequencing methods and full-length single-cell sequencing methods, which improve the estimation of alpha, beta, and gamma. This could help delve deeper into enhancing the velocity program.

Significance

The biggest problem in the manuscript is the lack of a ground truth. I suggest the authors choose tissues with reliable ground truth, such as spermiogenesis, which has a single lineage direction. You would see a clear streamline from pachytene spermatocytes to sperm, or embryonic cells with different culture days, where the direction should go from earlier to later stages. I strongly suggest the authors use clear lineage samples like spermiogenesis. After that, I think it will be a very helpful paper for scientists.

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Referee #2

Evidence, reproducibility and clarity

The authors present a comparative statistical analysis of five RNA velocity methods using two datasets and a single performance metric. Using the selected statistical metric, they describe the variable performance of RNA velocity methods, their variable robustness across different cell states, and the discrepancy of sets of identified lineage-specific driver genes.

At this point, the scientific community extensively documented limitations and lack of stability of RNA velocity performance across methods and datasets. In that context, the manuscript lacks clear theoretical and practical conclusions that would be beneficial to the scientific community.

The choice to focus on only a subset of RNA velocity methods is not discussed. Recent and important extensions, such as VeloVAE, VeloVI, LatentVelo, and Pyro-Velocity, are omitted, which limits the generality of the analysis. The statistical properties of the chosen consistency metric are not explored. The authors do not provide a justification for why this metric is appropriate for comparative analysis. Additionally, the authors do not present how the consistency score can be utilized to evaluate RNA velocity performance on user datasets. Overall, a discussion of the pressing issue of choosing statistical metrics to interpret RNA velocity results is lacking. The pros and cons of different RNA velocity methods, especially in light of the various statistical metrics, are not discussed. The manuscript does not present conclusions from the sampling analysis of sequencing depth. For instance, formalizing these findings with code that users can employ for their datasets would enhance the manuscript's practical utility. Overall, the manuscript would benefit from a thorough benchmark of the methodological approaches in the RNA velocity field, and testing various methods to evaluate RNA veloicty performance.

Significance

At this point, the scientific community extensively documented limitations and lack of stability of RNA velocity performance across methods and datasets. In that context, the manuscript lacks clear theoretical and practical conclusions that would be beneficial to the scientific community.

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Referee #1

Evidence, reproducibility and clarity

The authors present a survey of RNA velocity methods, evaluate them on a variety of model datasets, and introduce metrics to determine the local consistency of each individual method. They investigate differences between the methods with a separate metric that identifies consistency across methods, and using this, comment on applicability of each method to novel datasets. The effect of these differences on a downstream driver-gene identification task is also evaluated, and further conclusions are drawn related to this, particularly related to variability as a function of sequencing depth.

Major comments:

• There are a few changes that could be made to improve future applicability. One assumption seems to be that consistency between methods will indicate the most likely trajectory, however without a number of ground truth trajectories it seems that this is difficult to justify. In fact, there are probably good reasons why this would not be the case and that some methods might well be expected to underperform in certain cases. A deep comparison of the mechanics of the methods, or validating a robust set of novel ground truth trajectories, is probably beyond the scope of this paper, but it would be good to make some reference to the fact that these methods do differ in ways that might lead one to expect that some outperform others for good reasons.

• Related to this, it's still tricky to identify a clear path between the underlying approaches of the methods, the empirical observations in Fig 6, and how a reader coming cold to the field could match these aspects to the aims for the analysis of their own dataset. Though, I think that this might well be solved by rephrasing Fig 6 to include statements on the dataset itself - e.g., if you have large transcriptional diversity and a smaller dataset, then probably you would disfavour DeepVelo.

• One other suggestion relates to the uncertainties in the trajectories. This is touched upon in the case of the 'DeepVelo' method, where, for example, it's mentioned that these have a large number of parameters and could be prone to overfitting. However, the paper doesn't go as far to suggest that this could result in the trajectories having a much higher variance, which is is potentially evident in the sequencing depth study. This is perhaps a confounding issue in the comparisons in, for example, Fig 1a, where it seems that there is much more dynamical structure in the DeepVelo plot, but in reality this may be due to a higher degree of variance in the predictions. In this case, it may be that, in fact, all of the trajectories are perfectly consistent between the methods, within their uncertainties, despite the 'mean' values displayed in the plot looking quite different.

• Likely a full accounting of the uncertainties on all of the outputs of these models is also beyond the scope of the paper, however some indication of what the variance of these trajectories looks like (or the average value of this across the UMAMP plot, etc), although optional, would also be another valuable point of comparison between the methods. Bootstrap resampling of the data and re-running the methods, for example, would likely give a good indication of the consequences of the behaviour seen in the sequencing depth studies.

Minor comments on specific sections:

Intro:

It would be good to define exactly what you mean by 'state' with respect to the expression (or expression programs, etc) up front here.

• lineages between states' sounds a little awkward to me, I would suggest something like 'state lineages' instead.
• During cellular transitions' - suggest removing and starting with 'scRNASeq data...'
• Also would be good to define concretely what you mean by 'trajectory' with respect to expression
• inconsistent or incorrect directionalities' - suggest 'inconsistent or incorrect trajectories'?

Perhaps move 'RNA velocity has been applied...' after the description of RNA velocity

• Given these limitations...' - it would perhaps be nice to give some vignettes of how the methods differ before discussing their limitations
• As the mRNA matures...' - perhaps mention the key piece of information is the splicing out of introns, and this permits identification of the mature and immature mRNA (otherwise it seems a bit vague), and/or define splicing in the text
• The method yields...' - redundant?
• ...linear differential equations with constant slope...' - unclear what 'constant slope' means here
• steady state solution' - not clear whether 'steady state' here is synonymous with 'equilibrium', so it would be good to define (e.g., whether this means alpha = gamma, or whether this is a statement on beta, etc).
• ..the directionality in the cell-cell graph,...' - not clear how this becomes a graph, so it would be good to expand on how this is obtained
• the results depend heavily on chosen hyperparameters' - not clear that the other methods don't have this issue. I would guess that this is a matter of degree, but it would be good to indicate whether there are specific reasons why some models are expected to be less sensitive by construction.
• treating them as probabilistic events and resulting in a Markov process' -> 'treating them as probabilistic events in a Markov process
• a dynamic model (scv-Dyn) to address many of the original issues' - not clear from this description how the methods fixes these issues. Perhaps also talk a bit more about this 'latent time' parameter, if it's useful to contextualise the results later.
• deriving gene-specific splicing parameters in a single step,' - not clear what doing this in a 'single step' is, or why it might be advantageous.
• graph convolution' -> graph convolutional
• ...but also its neighbors...' - neighbours in what space?
• the mouse pancreas, a well studied lineage' - phrasing sounds a bit weird, maybe 'with a well studied lineage'?
• RNA velocity streams' -> trajectories? (if defined before)
• Therefore, a general benchmark that compares RNA velocity methods...' It might be nice here also to explain what exactly one might expect to be the ground truth in this case, as it's not particularly clear that something like VeloCyto that apparently predicts basically nothing is a 'bad' result compared to something like scv-Sto which predicts much more complicated dynamics where there may not be any.
• Disparate or contradictory results from various RNA velocity methods undermine our confidence in the predicted trajectories.' -

As mentioned before, I think it is important here to add that these methods were each individually developed for a specific purpose, and likely with an aim to improve upon previous techniques in the literature. So I think this kind of statement would have to be motivated a bit better, if claiming this without specific reference to the designs of each of the techniques on their own merit. For example, one could imagine in future an 'oracle' method that somehow predicts all trajectories with 100% accuracy, but its results are rejected because they don't align with the earlier and more primitive methods in the field. Equivalently, it could be such that one model is designed specifically for a specific type of dataset, or in the low data size regime, so a comparison using other datasets is more unfair (I don't think that is necessarily the case here, but without surveying the rest of the literature, a reader would not know that).

Results:

• 30 nearest neighbors' - With a fixed number of neighbours rather than a fixed similarity, it seems like you might end up getting results that are hard to compare if this is calculated in a sparse region (or the datasets have significantly different sizes)?
• Cell types from well-defined lineages...', '...those with more complex cellular heterogeneity...' - it would be good to indicate how these are considered 'well defined' and what 'more complex cellular heterogeneity' refers to (whether this is just from the UMAP, or whether these are statements that include prior biological assumptions that are used to evaluate the method).
• ...their differentiation process is more complex..' ... '..lineages with complex diversity...' - is this a statement based purely on the variation in expression? If so, it would be good to be clear here.
• ...the landscape's smoothness varies depending on cell type.' - it's been a while since you mentioned 'landscape', so it would be good to remind the reader that this is the distribution of expression in your high dimensional space.
• correlated with cell diversity' -> cell type diversity? Although 'notochord, endoderm and hindbrain' have already been indicated as 'cell types' here, so this is a little confusing
• ...can indicate overtraining or over smoothing...' - this seems a little contradictory, where I would assume that overtraining would result in higher variance, and oversmoothing would give the opposite effect?
• Altogether, the variation in agreement...' - it would be nice to go a little further here and make specific recommendations, even if it's something very vague, as there will be cases where there are no clear biological clues.

Downstream:

• ..overlap in macrostates...' - even if macrostates is a term defined in CellRank, it would be good to redefine it here for the reader
• ..scv-Dyn and UniTVelo both utilize a shared latent time variable..' - is it possible to give any indication why this might lead to a difference? Or even which might be more plausible?
• RNA Velocity' -> RNA velocity

Robustness to sequencing depth:

• DeepVelo, scv-Dyn, and UniTVelo maintained low levels of correlation with the magnitudes from the full reads... - this seems like quite a startling effect. It seems like this indicates the models are really quite unstable, if the removal of 2% of the dataset gives such a considerable difference.

Discussion:

• Our research emphasizes the importance of implementing a method that best fits the dataset...' - You don't indicate any goodness of fit metrics prior to this, so it's not really clear what this means in practice.

• Because the pancreas dataset is often used as a benchmark dataset for RNA velocity methods...' - presumably also this could mean that methods are developed to overfit to this dataset?

• Capturing the full splicing dynamics..' - not clear what 'full splicing dynamics' means here

Fig 1c. (and elsewhere):

Often it's hard to see the trajectory arrows in the rasterised plots. If this isn't just an issue with the review PDF, in Matplotlib it's possible to rasterise the points without rasterising the annotations and axes (https://matplotlib.org/stable/gallery/misc/rasterization_demo.html), which makes things a lot easier to read, but also doesn't leave you with giant file sizes.

Fig 2a.: The equation is a bit confusing, as k seems to be the size of the set of neighbours and the set itself, where in the text k is only ever the number of neighbours. Perhaps it would be better to have something like a set K of neighbours k (where k ∈ K), and then the sum is normalised by |K| and the sum is over k (or alternatively have k = |K| to be consistent with the text).

Fig 2d. (and others) A label on the z axis would be good here

Significance

This is a commendable effort, and will be of use to practitioners navigating the properties of current and future RNA velocity methods, particularly those without a background in the more advanced mathematical formulations of the newer methods. It also is the first time, to my knowledge, that a systematic comparison has been performed using a number of real datasets and with a novel metric.

However, the paper does not go as far as to link specific approaches or assumptions within the methods directly to their empirical observations, which could limit the applicability of the conclusions to only datasets and methods similar to those studied.

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Reply to the reviewers

Manuscript number: RC-2024-02640

Corresponding author(s): Purusharth I, Rajyaguru; Stephan Vagner

1. General Statements

This section is optional. Insert here any general statements you wish to make about the goal of the study or about the reviews.

In the manuscript titled, "RGG motif-containing Scd6/LSM14A proteins regulate the translation of specific mRNAs in response to hydroxyurea-induced genotoxic stress" we elucidate a conserved role of an RNA-binding protein with low-complexity sequences (RGG-motifs) in genotoxic stress response. This work uncovers HU-stress mediated translation regulation of SRS2, Ligase IV and RTEL1 transcripts by Scd6 (yeast)/LSM14 (human). It further identifies RNP condensates and arginine methylation as sites and means of this regulation.

We heartily thank all three reviewers for their overall encouraging comments about the significance of this manuscript. Specifically, we appreciate their view that the manuscript provides new functional insights into the role of RGG-motif-containing RNA-binding protein in genotoxic stress response. They further agree that such knowledge will impact and interest the general audience of RNA biology and stress biology.

We have carefully noted all the comments raised by three reviewers. We have addressed almost all the comments, including several by performing new experiments. The new results and their analysis have helped us improve the manuscript, allowing us to provide a stronger mechanistic and functional insight underlying the findings presented in this work. We thank the reviewers for their insightful comments. Below, we provide a point-by-point response to each of the comments.

2. Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

Reviewer 3

Major Comment 4: Page 7, top: '...indicating that Scd6 regulated the expression of SRS2 in a HU-dependent manner.' In my opinion, the results so far suggest that Scd6 and SRS2 are somehow functionally connected during HU-treatment. To substantiate the statement of the authors, they should provide a Western blot showing that the levels of SRS2 change upon Scd6 KO or OE during HU-treatment. This will also substantiate the results shown in Figs 2G-H.

Response: We thank the reviewer for this comment. Detecting Srs2 protein has been technically challenging. The SRS2 construct used in this study is untagged. Unfortunately, the commercial SRS2 antibody has been discontinued. We requested several groups who have used SRS2 antibody in their past studies but they have either closed down their labs or are unable to find an aliquot to share. We have tried tagging SRS2 with 6xHis/1XFLAG/3xFLAG tags at N and C-terminal, but unfortunately, the protein was undetectable in the Western blot analysis using either of the tag-specific antibodies. We have also tried western blot analysis using SRS2-GFP strain, but the protein does not get detected by anti-GFP antibody, probably because of very low expression.

Since we will not be able to provide western blots for Srs2 protein levels due to technical challenges, we shall provide western blots for RTEL1 (human homolog of Srs2) protein levels upon Lsm14A knockdown in the presence and absence of HU. This will validate the polysome data we have of RTEL1 regulation by LSM14A, and would, by extension, substantiate the SRS2 polysome data.

Major Comment 5: Figs 3: How are the localization of Scd6 protein and SRS2 mRNA to granules, and the levels of Srs2 protein, in cells exposed to HU after deletion of Hmt1? This would substantiate a role of Hmt1 in vivo.

Response: We will provide the data for Scd6 protein localization and SRS2 mRNA localization in granule enriched fraction upon HU treatment in Δhmt1 background. This experiment is ongoing.

3. Description of the revisions that have already been incorporated in the transferred manuscript

Reviewer 1

Major Comment 1: Fig. 1 F/G: were the delta RGG and LSM variants expressed at an equivalent level to the WT protein in these experiments?

Response: We thank the reviewer for this comment. We have quantified the total fluorescence intensity of GFP from the existing microscopy images for WT and domain deletion mutants for both Scd6 and Sbp1 (Now Figure 3A and 3D). This result (added as a new figure panel Fig 3C and 3F) indicates that the levels of Scd6∆RGG mutant is more whereas Scd6∆Lsm protein levels are comparable than WT. Similarly, Sbp1∆RGG mutant expression is comparable to WT in the given experimental conditions.

Major Comment 2: Fig. 3G: The 6 data points for the delta LSM variant are literally spread evenly up and down the graph, making these data appear highly questionable as to whether one can draw a definitive conclusion from them.

Response: We agree with the reviewer that the data points are varied. To address the scatter in data, we have performed additional experiments and added those to the existing results. Even though there is a spread in the points, except for one data point, all others show an increase in methylation of LSM domain deletion mutant compared to WT, which is statistically significant. The old blot and graph (Old Figure 3F and 3G) have now been replaced with new ones (Figure 5F and 5G) which look more convincing. The result and conclusion derived from it remain unchanged.

Minor Comments

Comment 1: Abstract: the acronym NHEJ likely will need to be defined for the general reader.

Response: The acronym has been expanded in the abstract and explained in the introduction.

Comment 2: Introduction, first paragraph: change gene expression to 'transcription' in the phrase 'Even if the contribution of gene expression to GSR..' as I assume this is what is meant here. Gene expression consists of synthesis, processing, translation and decay.

Response: The required change has been made.

Comment 3: Pg. 3 Introduction: Since they are liquid-liquid phase condensates and ribonucleoproteins (RNPs) refer to any protein-RNA interaction, I think that referring to PBs and SGs as mRNPs is a bit misleading (especially the 'major mRNPs').

Response: The statement has been rewritten.

Comment 4: Introduction: are PBs truly 'sites' of mRNA decay as stated? There are papers in the literature that would argue otherwise.

Response: The statement has been modified with more citations.

Comment 5: Pg. 3, three lines from bottom. Change LSM14 to LSM14A

Response: The addition has been done.

Comment 6: Pg. 4 top - What is an 'LCS' - containing protein? The acronym has not been defined

Response: The acronym has been defined now. We have also defined acronyms wherever they were missing.

Comment 7: Fig. S1 - there are a lot of important data in this figure that demonstrate the coordinated movement of Scd6 and Sbp1 to granules. They should be moved into the main body of the manuscript in my opinion. Likewise, a whole section of the Results is dedicated to Fig. S2 - thus I would suggest moving these data into the main body of the manuscript to assist the reader.

Response: We thank the reviewer for pointing this out. Figure S1 has now been added to the main body of the manuscript as Figure 2. Figure S2 has now been added to Figure 1 and new Figure 3. This rearrangement has improved the flow of the manuscript.

Comment 8: Fig. 1F should be flipped in the figure with panel G since G is discussed in the results section before F

Response: Figure 1F and 1G are now Figure 3A and 3D and in the same order as mentioned in the text.

Comment 9: Be sure to define all acronyms for the reader.

Response: All acronyms in the manuscript have been defined wherever applicable.

Comment 11: Fig. 3H/I: It might be optimal to calculate and compare Kd's for the methylated and unmethylated variants. Also, the labels at the top of 3H do not line up with the wells of the EMSA gel.

Response: We have calculated the Kd’s for the EMSA, and it has been added to the results section. We have also aligned the labels at the top of the EMSA gel (now Figure 5I) to match with the wells.

Reviewer 2

Major Comment 1: Fig. 2A, B. While there seems to be an effect on the lag phase, it could be revealing if the authors pls. calculate the doubling times for the strains and treatments (taking through the exponential growth phase). Furthermore, it would be good if the authors can show the rescue of phenotypes for deletion strains (ie. reintroduction of respective gene on ARS-CEN based plasmids or (if not available) with the OE plasmids.

Response: We thank the reviewer for this remark. We have calculated the doubling times for the strains in the tested conditions and added in the text. We have analyzed the effect of complementing the deletion strains with the respective genes on the CEN plasmid. We observe that Δscd6 shows tolerance to HU stress as previously seen, which gets rescued almost completely upon complementation with WT SCD6. This result has been included in the manuscript as a new figure panel (Figure S1A) . Δsbp1 also shows marginal tolerance to HU stress, but complementation with WT SBP1 only slightly rescues the phenotype, which is not statistically significant (Figure S1B). This result highlights a more important role of Scd6 as compared to Sbp1 in genotoxic stress response.

Major Comment 2 (part 1): Fig. 3H. The authors tested the 5'UTR of SRS2 for interaction with recombinant Scd6. Firstly, it is unclear why the authors have chosen the 5'UTR for investigation? Can the authors explain.

Response: We thank the reviewer for this important comment. During experimentation and analysis, we assayed Scd6 binding to two different fragments of SRS2 mRNA: 5’ and 3’UTR of same lengths (200 bases). We used the UTR fragments because there are numerous reports indicating the role of UTRs in the regulation by RNA binding proteins (https://doi.org/10.1093/bfgp/els056, https://doi.org/10.1126/science.aad9868, https://doi.org/10.1093/jxb/erae073). RNA EMSAs with purified Scd6 and in vitro transcribed UTR RNA fragments revealed a significantly better binding of Scd6 with the 5’ UTR fragment of SRS2 mRNA compared to the 3’ UTR. Therefore, we proceeded with the 5’ UTR fragment for further analysis. We have now added this as a supplementary figure panel and explanation in the manuscript text (Figure S2B).

Major Comment 2 (part 2): Secondly, the affinities are relatively low (µM), and the gel shift assay lacks a negative control. The authors should test an unrelated RNA fragment of approximately the same size to control for specificity (negative control). It is unclear whether the protein could interact with any RNA fragment through a charged RNA backbone.

Response: Our in vivo data suggests that the binding of Scd6 with SRS2 mRNA is condition and RNA-specific and is regulated by methylation (now Figure 5C, S2A and 5E). As the reviewer mentioned, Scd6, in principle, could bind to any RNA molecule given the affinity of an RNA-binding protein (with positively charged amino acids such as arginine) to RNA molecule. Nevertheless, the significant difference in the binding of Scd6 to the 5’UTR and 3’UTR fragments itself acts as a relative control for EMSA. The aim of the in vitro experiment (EMSA) was to establish the difference, if any, in the binding affinities of unmethylated vs methylated Scd6, like the in vivo data, where we observe significantly increased binding to SRS2 mRNA upon decreased Scd6 methylation.

Major Comment 2 (part 3): Thirdly, it would be good if the authors could show a Coomassie gel for the recombinant protein used in those assays.

Response: The Coomassie gel which was provided as part the supplementary data (now Figure S2C), have now been added as another gel image to the main figure (Figure 5H), next to the EMSA, for better clarity.

Major Comment 3: Methods and Materials: The Materials and Methods section lacks important information and requires further details to evaluate the study (see below 11 – 17)

Response: The comment has been duly noted.

Minor Comments

Results:

Comment 4: The numbering of Figure S1, S2 is confused in the first part of the results section. The authors should check numbering. In general, numbering should follow in the order of the text - pls. check.

Response: Based on the comment#7 by Reviewer 1, Figure S1 and S2 have now been added to the main figure, and the changes in the text have been made accordingly.

Comment 5: Pg. 5. CHX treatment leads to a decrease in Scd6-GFP and SBP-1 GFP granules. Essentially, CHX blocks translation elongation so the result indicates that puncta depend on active translation. The authors may want to add this liaising point towards the claim that mRNAs could be present in those puncta. How this results integrates with data shown in Fig. S5B*.

*

Response: We thank the reviewer for this comment. Since granules are dynamic structures that depend on active translation, CHX treatment leads to the dissociation of Scd6 and Sbp1 granules. This indicate that most of the mRNAs present in these granules could be recycled for translation in polysomes. This strategy has been used in multiple research articles for similar deductions (10.1091/mbc.E08-05-0499, https://doi.org/10.1083/jcb.151.6.1257, https://doi.org/10.1093/nar/gku582). We have now modified the text in the manuscript to accommodate this point. It has been previously reported that core components of stress granules, once formed are stable and resistant to RNase, EDTA and NaCl treatment ex vivo (https://doi.org/10.1016/j.cell.2015.12.038), even when these structures have RNA. Figure S5B (now S3C) indicates that the granule enriched fraction derived from untreated and treated cells indeed behaves like stress granule cores and not protein aggregates allowing us to proceed with downstream experiments.

Comment 6: Fig. 2H. It would be helpful to the reader, if the authors could mark the respective fraction in the polysomes taken for analysis of relative enrichments. How was this relative enrichment was calculated needs further description.

Response: The modification has been made (now Figure 4G) and added to the methods and materials.

Comment 7: Fig. S5B. 1% SDS treatment cause absence for Scd6 signal from the pellet fraction. Based on this result, I am not clear how based on this result they can claim for presence of higher order mRNA-protein complexes? Why does it exclude the possibility for Scd6 aggregates accumulating in the pellet? The authors need to explain/ modify this statement. Related to earlier findings that showed dependency of puncta upon CHX treatment, one wonders how this result matches to this earlier observation (ie.EDTA should dissassemble ribosomes)? Can the authors explain?

Response: The very stable β-zipper interactions present in prion like domains, which leads to aggregation, is resistant to 1-2% SDS treatment (https://doi.org/10.1016/j.cell.2015.12.038). Hence, we think that solubilization upon 1% SDS treatment indicates that these are not aggregates. EDTA and NaCl are capable of disrupting interactions, which are stabilized mainly by electrostatic forces. Our observations (now Figure S3C) indicate that Scd6 could be part of the more stable mRNP condensate core structure and are therefore resistant to these treatments. Such observations have been previously reported, for example, stress granules in yeast are not affected by EDTA and NaCl treatments (https://doi.org/10.1016/j.cell.2015.12.038).

Comment 8 (part 1): Fig. 5E, F. For the RNA-seq, the authors compared polysomes with free RNAs (up to 80S) and found enrichment of LIG4 and RTEL1. However, the polysomal profiling mainly shows a slight shift of those mRNAs in higher polysomes; while there is no difference compared to free fractions. How can this be explained?

Response: We observed a shift from lower polysome fractions (11-12-13) (not from free fractions) to higher polysome fractions (14-15) indicating an increased number of ribosomes translating the RTEL1 mRNA.

Comment 8 (part 2): On the line, the authors should indicate clearly what fractions were pooled for RNA seq analysis. It is also not clear how the authors quantified percentage of RNA in individual fractions (have they spiked-in an RNA?) - this needs to be stated in the M&M section.

Response: We have now added the requested information in the Materials and Methods section. Fractions 13 to 17 were pooled for RNAseq analysis. The % of RNA in each fraction was calculated as described in Panda AC et al. Bio Protoc . 2017 Feb 5;7(3):e2126. doi: 10.21769/BioProtoc.2126

Comment 9: At the end, if may be beneficial to the reader if the authors could provide a simple scheme depicting the model develop during this study.

Response: We thank the reviewer for this comment. We have included a model derived from our study as a new figure (Figure 8).

Comment 10: Supplemental Data set (.xls) The adjusted p-values are clustered and >0.05. Can the authors check and describe how those were calculated. How does it match with Volcano plots.

Response: The adjusted p-values are indeed >0.05. The p-values (and not the adjusted p-values) are plotted in the Volcano plot (now Fig. 7E)

Materials and Methods:

Comment 11: A list of primers should be given with specification of their use.

Response: The list has been added in the supplementary files (Table S3)

Comment 12: The plasmids constructed for (over)expression of proteins/ production of recombinant proteins should be added. If published, references should be added accordingly.

Response: The list has been added in the supplementary files (Table S4)

Comment 13: RIP: the media for growing yeast cells should be added. Check also other section if defined.

Response: The information has been added wherever required.

Comment 14: RT-qPCR is not sufficiently described. RT kit needs specification, PCR reaction cycles should be given.

Response: The information has been added

Comment 15: Quantification of mRNA levels in polysomes is unclear. How was the distribution of mRNA profiles determined? Have the authors added some RNA spikes to fractions?

See above.

Response: The % of RNA in each fraction was calculated as described in Panda AC et al. Bio Protoc . 2017 Feb 5;7(3):e2126. doi: 10.21769/BioProtoc.2126. Details have now been added in the Mat and Meth section.

Comment 16: The calculation for the enrichments in IPs is not described conclusively and should be added.

Response: The calculation has now been elaborated and added to the methods and materials section.

Comment 17: Polysomes fractionation (mammalian). It is indicated that the resultant supernatant was adjusted to 5M NaCl and 1 M MgCl2. This seems to be very high - is this a typo? OR why such high concentrations have been chosen?

Response: The sentence has been removed. There is no need for such adjustment.

Review 3

Major Comment 2: Fig 2A-F: The effects of Scd6 and Sbp1 deletion upon HU-treatment are very small. A more convincing effect is observed upon over-expression of both SRS2 and SCD6. What is the effect of over-expression of SCD6 and SBP1 alone (i.e. without SRS2 over-expression)?

Response: We thank the reviewer for this comment. The effects are indeed small but consistent and reproducible with two different kinds of assays (growth curve and plating assay, now Figure 4A-C). Overexpression of Scd6 or Sbp1 alone when expressed from a CEN/2u plasmid does not have any phenotype in the presence of HU (Figure S1A and S1B). Although, it has been previously reported that galactose-inducible Scd6 causes a severe growth defect (https://doi.org/10.1093/nar/gkw762), we performed spot assays with galactose inducible Scd6 and Sbp1 on control and HU plates, but did not see any difference in the extent of growth upon HU treatment. This data has now been presented as Figure S1C.

Major Comment 3: Fig 2E: Why is there an opposite effect of deletion of Scd6 and Sbp1in the SRS2 over-expression background?

Response: We thank the reviewer for this comment; however, we respectfully disagree with the idea that overexpression of SRS2 yields opposite phenotypes in SCD6 and SBP1 deletion backgrounds. Figure 2E (now Figure 4E) gives the impression that SRS2 overexpression in SBP1 deletion grows significantly more for two reasons. There was an increased spotting of Dsbp1 cells overexpressing SRS2 (row#6) as compared to Dscd6 cells overexpressing SRS2 (row#4), which is evident in the plate without HU (left panel). Additionally, there is also reduced spotting of wild-type cells overexpressing SRS2 (row#2) as compared to Dscd6 cells overexpressing SRS2 (row#4). We have now replaced these panels with another image with better loadings. Quantitation of five experiments (Figure S1F) indicates that Dsbp1 grows slightly better in both EV and SRS2 over-expression background, but the increase is not statistically significant. We interpret this data to suggest that SRS2 is not a direct target of Sbp1. Another protein perhaps performs the specific role of Sbp1 in assisting Scd6 in genotoxic stress response in Dsbp1 background.

Major Comment 6: Fig 3C: Is the increased interaction of SRS2 mRNA with Scd6 due to increased levels of SRS2 mRNA upon HU treatment? See also comment below.

Response: Based on RT-qPCR of total RNA, SRS2 mRNA levels do not seem to increase, which has now been added as a Supplementary figure (Figure S3D, left panel). Moreover, quantification of SRS2 mRNA from the FISH data also does not support an increase in mRNA levels (Figure 6D, left panel).

Major Comment 7: Fig 4A: There seems to be an enrichment of SRS2 mRNA both in the granule-enriched pellet and in the supernatant upon HU treatment in the Scd6-GFP context, suggesting increased SRS2 mRNA levels altogether. The enrichment in granules upon HU is difficult to see, as one should measure the distribution of the mRNA in the pellet relative to the supernatant. Can the authors represent the ratio pellet/supernatant normalized to a control transcript? A similar calculation can be done for the protein normalized to a control protein.

Response: As mentioned earlier, RT-qPCR data with SRS2 mRNA levels in total lysate has been added to supplementary data (Figure S3D, left panel). Based on RT-qPCR of total RNA, SRS2 mRNA levels do not seem to increase.

The quantification of SRS2 mRNA and Scd6 protein enrichment is done such that the supernatant and pellet fractions are separately normalized to their respective controls (Scd6GFP, untreated sample) and therefore do not represent the mRNA distribution but relative mRNA enrichment. However, as per the recommendation by the reviewer, the data has been replotted as a ratio of supernatant and pellet with the addition of two more data points and has been added in the main figure (Figure 6E). The data concludes increased enrichment of SRS2 mRNA in granules upon HU treatment. The previous data has been included in the supplementary data as Supplementary figure (Figure S3D, right panel).

Major Comment 8: Fig 4B: Increased juxtaposition of SRS2 mRNA and Scd6 granules upon HU treatment does not really mean increased colocalization. Granules are likely significantly apart such that increased interactions between the two partners are not explained by increased juxtaposition. Please, comment, tune-down and provide examples where increased granule juxtaposition is associated with increased interaction.

Response: We believe that the usage of term ‘juxtaposition’ is leading to misinterpretation of the data. Therefore, we have replaced it with ‘percentage area overlap’ analysis to demonstrate that the SRS2 mRNA foci indeed overlap/localize with Scd6GFP foci up to an average of 43.5% in HU stress. This analysis has been added as an additional panel (Figure 6C), indicating that the SRS2 mRNA interacts with Scd6 in the granules. Even though the granules do not overlap/localize completely, the observed area of granule overlap (43.5%) is functionally effective as it leads to the physical interaction of Scd6 and SRS2 (Figure 6E & 5C) and, consequently, repression (Figure 4H). The FISH data, granule enrichment, and RNA immunoprecipitation data demonstrate Scd6 protein and SRS2 mRNA interaction in granules.

Major Comment 9: Fig 4D: These results are in direct contradiction with those shown in Fig 1C.

Response: We thank the reviewer for this comment. Figure 1C (now Figure 1B and 1C) demonstrates that Scd6 localization to puncta, when expressed from a CEN plasmid, significantly increases upon HU stress. The same trend is visible in Figure 4D (now Figure 6D) where Scd6 is expressed from a 2μ plasmid; however, it is not significant. The data in 1C and 4D (now 1C and 6D respectively) are rather inconsistent with each other than being contradictory. Nevertheless, we understand this reviewer’s concern and address it below.

The initial localization experiments were performed using Scd6 expressed from CEN plasmid or genomically tagged Scd6. Since both these versions of Scd6 are not detectable using western blotting, we used Scd6 expressed from 2μ plasmid. Localization to condensates by liquid-liquid phase separation is a concentration-driven phenomenon. Therefore, when Scd6 is expressed from a 2μ plasmid amounting to increased protein levels, its localization to puncta increases even in the absence of stress, which is visible in the quantitation provided in the figure (Figure 6D) as compared to Figure 1C. We have now analyzed the percentage granular localization (granule intensity) of Scd6 (2µ), which significantly increases upon HU stress (Figure S3A). Thus although number of Scd6 granules does not increase upon HU stress when expressed from a 2µ plasmid, there is significant increase in localization of Scd6 to granule upon HU stress (Figure S3A).

Major comment 10: Fig 5E: Can the authors provide a GO analysis of the up- and down- regulated transcripts?

Response: We have now provided a GO analysis (Table S2). However, due to the low number of regulated genes, only a few GO terms with weak scores appeared in the analysis.

Minor comments:

Comment 11: Figures S1 and S2 seem to be swapped. Please make sure that Figures and panels are arranged in the order they are mentioned in the main text.

Response: We thank the reviewer for pointing it out. Based on the comment#7 by Reviewer 1, Figure S1 and S2 have now been added to the main figure, and the changes in the text have been made accordingly. We have ensured that the order of figures matches the text.

Comment 12: Page 5, sentence: 'our results argue for the role of Scd6 and Sbp1 in HU-mediated stress response'. I do not agree, as no functional assays showing that these proteins affect HU-mediated stress response have been provided at this point of the story. Please, delete.

Response: We have removed the sentence from the existing paragraph.

Comment 13: Page 6: The authors state 'Since Dscd6 and Dsbp1 showed tolerance to chronic HU exposure...'. Where is this shown?

Response: The growth curve in Figure 2A and 2B (now Figure 4A and 4B) and the plating assay in Figure 2C (now Figure 4C) was done with hydroxyurea in the media/plate. Hence, we state that deletion of either SCD6 or SBP1 shows tolerance to chronic (or continuous) HU stress.

Comment 14: Fig 2F: The rescue by SCD6 OE is not complete, as mentioned in the main text.

Response: We have now included the quantification of the spot assay in 2F (now Figure 4F) to show that the rescue by SCD6 overexpression is complete (Fig S1G).

Comment 15: Figure 2G-H: Please, indicate in the figure what the authors consider 'translated' and 'untranslated’ fractions.

Response: The fractions have now been labelled to indicate the missing information in Figure 2G (now Figure 4G).

4. Description of analyses that authors prefer not to carry out

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Review 1

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Minor Comment 10: Pg. 8/Fig. S3D/4A: It would be interesting to complete the story and determine the functional relationship of Scd6 to the DNL4 mRNA

Response: It is indeed an interesting observation and is currently being pursued as part of another story. We believe it is beyond the scope of the current manuscript.

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Review 3

Major Comment 1: Page 5 and Fig S2E-F: The CLHX experiment to conclude that mRNA is present in Scd6 and Sbp1 puncta is rather indirect. The fact that RNase treatment of a granule-enriched pellet has no effect (Fig S5B) does not help. The authors should perform RNase treatment of intact cells and see that the puncta disappear.

Response: We thank the reviewer for this comment. Cycloheximide treatment is a well-accepted assay to detect the presence of mRNA in granules. Since granules are dynamic structures, and these depend on active translation, CHX treatment leads to the dissociation of Scd6 and Sbp1 granules. This indicates that granule assembly depends on the availability of mRNA derived from translating ribosomes. The observation that Scd6 puncta are sensitive to cycloheximide but not to RNase A treatment is not surprising. It indeed is consistent with the properties of some of the condensates reported in the literature. For example, stress granule cores that are sensitive to cycloheximide, like Scd6 puncta, are resistant to RNase treatment in lysate, indicating that once formed, these structures are quite stable (https://doi.org/10.1016/j.cell.2015.12.038). It is interpreted to suggest that the RNAs in these condensates are protected by the RNA-binding proteins. Also, subsequently, in the study, we do RNA immunoprecipitation and granule enrichment experiments and show specific RNA enrichment with Scd6 (Figure 5C, 6A).

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Referee #3

Evidence, reproducibility and clarity

In this manuscript, Rajyaguru, Vagner and colleagues address the role of yeast Scd6 in translation regulation during hydroxyurea (HU) stress response. They first show that Scd6 associates to puncta upon HU-treatment, in a manner that depends on the RGG and LSm domains of the protein. They then show that deletion of Scd6 has a mild effect on cell survival under HU-treatment, and over-expression of SCD6 restores the defects observed upon over-expression of SRS2 (a known regulator of the DNA damage response-DDR), suggesting that SRS2 is an SCD6 target, and that SCD6 negatively regulates SRS2. The authors further show that SCD6 binds to SRS2 mRNA and inhibits its translation. Binding to mRNA is somewhat regulated by methylation of the RGG domain, and methylation seems to be controlled by the LSm domain. Finally, the role of SCD6 as a translation regulator during HU-response is conserved, because its mammalian homolog, LSM14A, stimulates the translation of DDR factors under similar conditions. Altogether, this is a nice report showing a function of Scd6/LSM14A in regulation of translation upon HU treatment. However, there are some contradictions that need to be resolved, and the role of puncta in the whole picture is not clear.

Major comments:

1. Page 5 and Fig S2E-F: The CLHX experiment to conclude that mRNA is present in Sdc6 and Sbp1 puncta is rather indirect. The fact that RNase treatment of a granule-enriched pellet has no effect (Fig S5B) does not help. The authors should perform RNase treatment of intact cells and see that the puncta disappear.
2. Fig 2A-F: The effects of Scd6 and Sbp1 deletion upon HU-treatment are very small. A more convincing effect is observed upon over-expression of both SRS2 and SCD6. What is the effect of over-expression of SDC6 and SBP1 alone (i.e. without SRS2 over-expression)?
3. Fig 2E: Why is there an opposite effect of deletion of Scd6 and Sbp1in the SRS2 over-expression background?
4. Page 7, top: '...indicating that Scd6 regulated the expression of SRS2 in a HU-dependent manner.' In my opinion, the results so far suggest that Scd6 and SRS2 are somehow functionally connected during HU-treatment. To substantiate the statement of the authors, they should provide a Western blot showing that the levels of SRS2 change upon Scd6 KO or OE during HU-treatment. This will also substantiate the results shown in Figs 2G-H.
5. Figs 3: How are the localization of Scd6 protein and SRS2 mRNA to granules, and the levels of SRS2 protein, in cells exposed to HU after deletion of Hmt1? This would substantiate a role of Hmt1 in vivo.
6. Fig 3C: Is the increased interaction of SRS2 mRNA with Scd6 due to increased levels of SRS2 mRNA upon HU treatment? See also comment below.
7. Fig 4A: There seems to be an enrichment of SRS2 mRNA both in the granule-enriched pellet and in the supernatant upon HU treatment in the Scd6-GFP context, suggesting increased SRS2 mRNA levels altogether. The enrichment in granules upon HU is difficult to see, as one should measure the distribution of the mRNA in the pellet relative to the supernatant. Can the authors represent the ratio pellet/supernatant normalized to a control transcript? A similar calculation can be done for the protein normalized to a control protein.
8. Fig 4B: Increased juxtaposition of SRS2 mRNA and Scd6 granules upon HU treatment does not really mean increased colocalization. Granules are likely significantly apart such that increased interactions between the two partners are not explained by increased juxtaposition. Please, comment, tune-down and provide examples where increased granule juxtaposition is associated with increased interaction.
9. Fig 4D: These results are in direct contradiction with those shown in Fig 1C.
10. Fig 5E: Can the authors provide a GO analysis of the up- and down- regulated transcripts?

Minor comments:

1. Figures S1 and S2 seem to be swapped. Please make sure that Figures and panels are arranged in the order they are mentioned in the main text.
2. Page 5, sentence: 'our results argue for the role of Scd6 and Sbp1 in HU-mediated stress response'. I do not agree, as no functional assays showing that these proteins affect HU-mediated stress response have been provided at this point of the story. Please, delete.
3. Page 6: The authors state 'Since scd6 and sbp1 showed tolerance to chronic HU exposure...'. Where is this shown?
4. Fig 2F: The rescue by SCD6 OE is not complete, as mentioned in the main text.
5. Figure 2G-H: Please, indicate in the figure what the authors consider 'translated' and 'untranslated´fractions.

Significance

The findings provide a new function for Scd6/LSM14A in regulation of translation upon HU treatment. There are limitations regarding the strength of effects in some cases, and the integration of the role of granule formation. These findings are useful for scientists working on genotoxic stress, RNA-binding proteins and/or translation.

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Referee #2

Evidence, reproducibility and clarity

The authors describe a novel role for the RGG-box containing RNA-binding protein Scd6 and its human ortholog LSM14A in the genotoxic stress to HU treatment. The proteins accumulate in granules upon HU treatment and may be involved in the translational repression of mRNAs coding for relevant factors mediating the HU response. For instance, they show that yeast Scd6 interact with SRS2 mRNA and represses translation during HU response. Interestingly, the also show that interaction with RNAs is dependent on arginine methylation in the LSM domain, which greatly affects interaction with the RNA though specificity needs to be shown. At the end, the authors performed initial analysis with the human ortholog LSM14A, indicating that the cellular function of the protein is evolutionary conserved.

The study is interesting and adds new aspects for understanding RGG-containing proteins and their molecular functions. While it has been previously known that Scd6 accumulates in granules and acts as a translational repressor via eIF4G, this study reveals the regulation of a particular target (SRS2) in context of a relevant stress response. The experiments are usually well performed, though some controls and descriptions need to be added.

Major points:

1. Fig. 2A, B. While there seems to be an effect on the lag phase, it could be revealing if the authors pls. calculate the doubling times for the strains and treatments (taking through the exponential growth phase). Furthermore, it would be good if the authors can show the rescue of phenotypes for deletion strains (ie. reintroduction of respective gene on ARS-CEN based plasmids or (if not available) with the OE plasmids.
2. Fig. 3H. The authors tested the 5'UTR of SRS2 for interaction with recombinant Scd6. Firstly, it is unclear why the authors have chosen the 5'UTR for investigation? Can the authors explain. Secondly, the affinities are relatively low (µM) and the gel shift assay lacks a negative control. The authors should test an unrelated RNA fragment of approximately the same size to control for specificity (negative control). It is unclear whether the protein could interact with any RNA-fragment through charged RNA backbone. Thirdly, it would be good if the authors could show a Coomassie gel for the recombinant protein used in those assays.
3. The Materials and Methods section lacks important information and requires further details to evaluate the study (see below 10 - 17).

Minor points:

Results:

1. The numbering of Figure S1, S2 is confused in the first part of the results section. The authors should check numbering. In general, numbering should follow in the order of the text - pls. check.
2. Pg. 5. CHX treatment leads to a decrease in Scd6-GFP and SBP-1 GFP granules. Essentially, CHX blocks translation elongation so the result indicates that puncta depend on active translation. The authors may want to add this liaising point towards the claim that mRNAs could be present in those puncta. How this results integrates with data shown in Fig. 5S5.
3. Fig. 2H. It would be helpful to the reader, if the authors could mark the respective fraction in the polysomes taken for analysis of relative enrichments. How was this relative enrichment was calculated needs further description.
4. Fig. S5B. 1% SDS treatment cause absence for Scd6 signal from the pellet fraction. Based on this result, I am not clear how based on this result they can claim for presence of higher order mRNA-protein complexes? Why does it exclude the possibility for Scd6 aggregates accumulating in the pellet? The authors need to explain/ modify this statement. Related to earlier findings that showed dependency of puncta upon CHX treatment, one wonders how this result matches to this earlier observation (ie.EDTA should dissassemble ribosomes)? Can the authors explain?
5. Fig. 5E, F. For the RNA-seq, the authors compared polysomes with free RNAs (up to 80S) and found enrichement of LIG4 and RTEL1. However, the polysomal profiling mainly shows a slight shift of those mRNAs in higher polysomes; while there is no difference compared to free fractions. How can this be explained? On the line, the authors should indicate clearly what fractions were pooled for RNA seq analysis. It is also not clear how the authors quantified percentage of RNA in individual fractions (have they spiked-in an RNA?)
   • this needs to be stated in the M&M section.
6. At the end, if may be beneficial to the reader if the authors could provide a simple scheme depicting the model develop during this study.
7. Supplemental Data set (.xls) The adjusted p-values are clustered and >0.05. Can the authors check and describe how those were calculated. How does it match with Volcano plots.

Materials and Methods:

1. A list of primers should be given with specification of their use.
2. The plasmids constructed for (over)expression of proteins/ production of recombinant proteins should be added. If published, references should be added accordingly.
3. RIP: the media for growing yeast cells should be added. Check also other section if defined.
4. RT-qPCR is not sufficiently described. RT kit needs specification, PCR reaction cycles should be given.
5. Quantification of mRNA levels in polysomes is unclear. How was the distribution of mRNA profiles determined? Have the authors added some RNA spikes to fractions?
6. The calculation for the enrichments in IPs is not described conclusively and should be added.
7. Polysomes fractionation (mammalian). It is indicated that the resultant supernatant was adjusted to 5M NaCl and 1 M MgCl2. This seems to be very high - is this a typo? OR why such high concentrations have been chosen?

Significance

The study appears solid and well done, except some weaknesses that need to be addressed (see above section). Overall, the interplay with translation could be better investigated and the involvement for interactions with eIF4G/ ribosomes could be better investigated but possibly beyond this study.

Essentially, the study adds a nice mix of experimental approaches to manifeste the linkage between granules formation, translation and the physiological implications for genotoxic stress response. However, it is not clear how the chosen conditions reflect any natural conditions (yeast may never be exposed to 100-200 mM HU) and hence, it is unclear howfar the observations reflect nature and occur like that. It is certainly a limitiation that only one particual stress condition was investigated and it is unclear whether it is also seen with other genotoxic stress inducing agents.

Audience: The study will attract the interest of researchers working with cytoplasmic RBPs, translation and stress granules. The latter topic is currently on a high wave as many researchers jumped on this topic. The study may though remain within this circle as the analysis is rather specialised and contrained on one stress (genotoxic) and wider implications of the findings in a physiological context are unclear.

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Referee #1

Evidence, reproducibility and clarity

This manuscript demonstrates that RGG containing proteins (Sbp1, Scd6/LSM14A) localize to granules upon treatment with hydroxyurea, Scd6 binds and regulates SRS2 in a manner that is regulated by arginine methylation of the RGG motif, that the RGG and LSM motifs are crucial for the process, and that NHEJ is influenced by LSM14A, suggesting the functional significance of this regulation. Overall the data generally support the conclusions that are drawn. In terms of overall presentation, the manuscript is a bit of a dense read and some of the supplementary figures should be moved to the main body of the manuscript to reflect their importance to the story. I do believe the manuscript will have impact to field, particularly to the specialized RGG protein and stress response niche. I do have several suggestions to polish the manuscript/study:

Major Points:

1. Fig. 1 F/G: were the delta RGG and LSM variants expressed at an equivalent level to the WT protein in these experiments?
2. Fig. 3G: The 6 data points for the delta LSM variant are literally spread evenly up and down the graph, making these data appear highly questionable as to whether one can draw a definitive conclusion from them.

Minor Points:

1. Abstract: the acronym NHEJ likely will need to be defined for the general reader.
2. Introduction, first paragraph: change gene expression to 'transcription' in the phrase 'Even if the contribution of gene expression to GSR..' as I assume this is what is meant here. Gene expression consists of synthesis, processing, translation and decay.
3. Pg. 3 Introduction: Since they are liquid-liquid phase condensates and ribonucleoproteins (RNPs) refers to any protein-RNA interaction, I think that referring to PBs and SGs as mRNPs is a bit misleading (especially the 'major mRNPs').
4. Pg. 3 Introduction: are PBs truly 'sites' of mRNA decay as stated? There are papers in the literature that would argue otherwise.
5. Pg. 3, three lines from bottom. Change LSM14 to LSM14A
6. Pg. 4 top - What is an 'LCS' - containing protein? The acronym has not been defined
7. Fig. S1 - there are a lot of important data in this figure that demonstrate the coordinated movement of Scd6 and Sbp1 to granules. They should be moved into the main body of the manuscript in my opinion. Likewise, a whole section of the Results is dedicated to Fig. S2 - thus I would suggest moving these data into the main body of the manuscript to assist the reader.
8. Fig. 1F should be flipped in the figure with panel G since G is discussed in the results section before F
9. Be sure to define all acronyms for the reader.
10. Pg. 8/Fig. S3D/4A: It would be interesting to complete the story and determine the functional relationship of Scd6 to the DNL4 mRNA
11. Fig. 3H/I: It might be optimal to calculate and compare Kd's for the methylated and unmethylated variants. Also the labels at the top of 3H do not line up with the wells of the EMSA gel.

Significance

Overall the data generally support the conclusions that are drawn. In terms of overall presentation, the manuscript is a bit of a dense read and some of the supplementary figures should be moved to the main body of the manuscript to reflect their importance to the story. I do believe the manuscript will have impact to field, particularly to the specialized RGG protein and stress response niche

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Reply to the reviewers

1. General Statements [optional]

We are grateful to the reviewers for their many valuable suggestions for improving this paper. In particular, we fully understand the points raised by Reviewers #1 and #2 regarding the insufficient data analysis and the points raised by Reviewers #2 and #3 regarding the insufficient analysis of the mechanism. In future revisions, we will perform sufficient analysis of our datasets and we will also conduct an analysis focusing on Dmrt3 to investigate the mechanisms for chromatin accessibility and changes in gene expression during neuronal differentiation. We will also make revisions to address other minor points.

2. Description of the planned revisions

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

The authors have developed a method for labeling a specific stage of differentiating neurons. Using this approach, they tracked the four-day differentiation process of deep-layer excitatory neurons in the mouse embryonic cortex. They investigated genome-wide changes in transcription patterns and chromatin accessibility using RNA-seq and DNase-seq. Additionally, they provided H3K4me3 and H3K27me3 ChIP-seq data from E12.0 NPCs. This resulting omics data would be a valuable resource for the field. While initial data analyses show potentially interesting findings, only part of the analyses are presented in the figures, lacking sufficient detail. Before publishing the manuscript, the authors should include more comprehensive analyses of their datasets. Specific suggestions are below.

We appreciate this reviewer's positive comments describing our study as 'a valuable resource for the field.' We plan to revise the paper, as noted below, to address this reviewer's concerns.

Figure 4 focuses on promoter-specific chromatin accessibility analysis. The author can process the data similarly to the transcription data. They should identify differentially accessible promoter regions across E13.0 to E16.0 and generate a heatmap with clustering. Additionally, the author should provide matched gene expression data, either in the form of a heatmap or box plot, corresponding to those differentially accessible promoter regions. Currently, Figure 4 only presents E16.0 data compared to E12.0, which is not comprehensive.

We thank the reviewer for the useful suggestions. In the following submission, we will determine gene sets for all chromatin accessibility change patterns, not just open/closed gene sets from E12 to E16. We will then illustrate the changes in gene expression for each gene set.

Reviewer #1 (Significance (Required)):

Multi-omics data from the differentiation process of deep-layer excitatory neurons would be a valuable resource for the field.

Once again, we would like to thank the reviewers for their positive comments.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary: The manuscript from Sakai et al. examines changes in chromatin accessibility during the differentiation of deep-layer excitatory neurons in the neocortex. The authors establish a novel genetic labelling method that tracks differentiating neurons based on their birthdates allowing following neuronal differentiation in vivo. By combining RNA-seq and DNase-seq they provide a comprehensive dataset of gene expression and chromatin accessibility changes during neuronal differentiation of deep-layer neurons and reveal that key genes linked to mature neuronal functions and bivalent genes in neural precursor cells become accessible during early differentiation. These findings underscore the crucial role of chromatin regulation in preparing neurons for maturation and unravel novel key insights into the regulatory mechanisms governing deep-layer neuronal differentiation.

Overall, this manuscript presents a novel technique for tracking neuron development from NPCs with specific birthdates. However, in its current form, it is largely descriptive and relies on correlative observations rather than elucidating a clear mechanism underlying chromatin and transcriptional changes. The provided data could be further leveraged to gain deeper insights into the molecular mechanisms governing deep-layer neuron development.

We would like to thank the reviewer for recognizing the methods used in this paper as 'a novel technique for tracking neuron development from NPCs with specific birthdates'. As the reviewer commented, this paper was descriptive, and we plan to prepare a revised version that includes results that approach 'the molecular mechanisms governing deep-layer neuron development' by analyzing the role of Dmrt3 in neuronal differentiation, as shown in the response below, especially for point 9.

Major comments:

The authors have generated extensive RNA- and DNAse-seq datasets across different developmental time points following birthdate labelling. However, the bioinformatics analyses and interpretations are limited and need further clarification and refinement:

The violin plots used to demonstrate expression and accessibility changes across developmental time points and the conclusions drawn from them are not convincing. The authors used a rank test to assess significant changes in expression, which only indicates the enrichment of genes with increased or decreased expression in each group. This cannot be directly interpreted as "significant upregulation." For instance, in Figures 4a and 4b, similar violin plots yield different statistical outcomes. The mean values on both graphs are comparable, yet Figure 4a suggests significant changes, while Figure 4b does not conclude significant downregulation of closing DHS genes. This is unconvincing. A more robust approach would be identifying DEGs between time points and analysing functional terms associated with these genes. The current plots do not support interpretations of gene upregulation, as each dot represents a gene, and the violin plot serves more as a population representation. The authors should either revisit their explanations and conclusions or include additional analyses and appropriate plots that support their claims of significant upregulation and downregulation of specific genes during development. We would like to thank the reviewer for their helpful suggestions on presenting the data in Figure 4 more effectively. In future reanalysis, we will add an analysis focusing on DEGs, as suggested by the reviewer. Specifically, we will examine the overlap between DEGs identified by RNA-seq and genes with altered chromatin accessibility and test this using Fisher's exact test and other methods. This will allow us to verify the conclusions of this paper from multiple perspectives.

Figure 6b lacks clarity regarding the cutoff value used to categorise genes as K4me3 and K27me3 negative or positive from the heatmap. Even the "K4me3 negative" cluster displays a detectable signal of the mark, albeit at lower levels. Since only one plot of the entire gene body is provided, it is unclear what levels of enrichment are present, particularly at the promoter region. The authors are encouraged to provide additional informative plots and analyses of this ChIP-seq experiment, as this is a critical point where they draw conclusions about bivalent genes. This would not only strengthen their claims but could also uncover additional findings with more detailed analyses. A heatmap of clustered ChIP-seq signals of K4me3 and K27me3 alongside expression levels of the same genes (similar to Figure 2c) and differential accessibility (e.g., between NPC and E16) would better visualise and correlate histone modifications with chromatin and gene expression states.

We would also like to thank this reviewer for their useful suggestions regarding Figure 6. In the next submission, we will try different methods to quantify H3K4me3 and H3K27me3 signals. Specifically, we plan to try methods using peak calling and methods that quantify signals in promoter regions.

We also plan to show new figures for changes in gene expression and chromatin accessibility in gene sets categorized by H3K4me3 and H3K27me3 signals.

The DNase-seq dataset can be better utilised to investigate differentially accessible motifs through development. Is this something the authors already looked into? This could strengthen mechanism investigation together with the ChIP-atlas results in Fig.6a

In the revised version, we will perform motif analysis and ChIP-atlas analysis for all genomic region sets showing differential accessibility. We will then use the results obtained to discuss the mechanisms of chromatin accessibility changes during the neuronal differentiation process in more depth.

The two distinct modes of H3K4me3 enrichment observed are not addressed and should be explained. Which genes belong to these two clusters? Is there a difference in DHS and gene expression between them?

In relation to point 2 of this reviewer, we will also re-analyze the differences in H3K4me3 patterns and changes in gene expression and chromatin accessibility. We believe that we can answer this reviewer's questions through the analyses using peak calling and signal quantification, as described in point 2.

The same concern regarding the use of violin plots to correlate gene expression with bivalent genes through development (Figure 6c) as mentioned earlier. It would be better to use DEGs and intersect them. This is particularly important given the wide range of gene expression levels in the already poised state.

In relation to this reviewer's point 1, we will also perform a reanalysis focusing on DEGs in Figure 6.

The authors limited their analyses to promoter/gene body regions. A survey of the bivalent marks and accessibility at enhancer regions would be also beneficial for understanding the changes at the chromatin landscape through development.

The results of Figure 3 showed that chromatin accessibility in the promoter region changes significantly during neuronal differentiation, and this paper has focused on the promoter region. However, as this reviewer has commented, we have realized that analysis of enhancers is also useful. We plan to re-analyze the changes in chromatin accessibility in the enhancer region for the revised version.

The mechanisms driving the activation and expression of poised neuronal genes through the development of deep-layer neurons is not uncovered. The authors suggest certain histone modifiers and the DNA methyltransferase Dnmt3 as potential drivers of chromatin landscape and transcriptional regulation changes; however, this remains speculative, as there is no direct evidence or validation of these factors binding to the identified target regions or changes in DNA methylation states. The authors should provide validation of their candidate factors' presence at potential targets, as well as changes in DNA methylation if they want to conclude these as the mechanisms driving deep-layer neuron development.

We thank the reviewer for pointing out the critical issue of the mechanism for the activation of poised genes. We agree that investigating the mechanism in more depth would improve our paper.

To this end, we will analyze the role of Dmrt3, not Dnmt3, in activating poised genes. Dmrt3 is a transcription factor mainly involved in transcriptional repression, and our RNA-seq results indicate that it is highly expressed in NPCs, and its expression decreases during neuronal differentiation. Therefore, Dmrt3 may suppress poised genes in NPCs. Indeed, our preliminary results using public data have shown that knocking out Dmrt3 increased the expression of poised genes.

In future analyses, we plan to analyze the role of Dmrt3 using RNA-seq data from Dmrt3 knockout NPCs and Dmrt3 ChIP-seq data from NPCs.

Minor comments:

The motif analysis can be included in the main figures.

We appreciate the reviewer's positive suggestions. Regarding point 9, we will move the results of the motif analysis to the main figure after reanalysis about Dmrt3.

Reviewer #2 (Significance (Required)):

By introducing a novel genetic labelling method that tracks neurons based on their birthdates, the study provides a precise way to examine differentiation in vivo, adding valuable insights beyond traditional in vitro approaches. The combination of RNA-seq and DNase-seq analyses reveals how chromatin accessibility changes, particularly in bivalent genes, play a crucial role in neuronal maturation. This work highlights the importance of chromatin dynamics in establishing neuronal identity. The techniques and findings provide a useful framework for future studies, offering a path for deeper exploration of chromatin regulation across different neuronal types, stages of development, or disease contexts, making it a valuable contribution to the field of developmental neurobiology.

While the manuscript suggests the involvement of chromatin regulators such as Trithorax and Polycomb proteins, as well as Dnmt3 and DNA methylation, it lacks direct mechanistic evidence, such as ChIP-seq, bisulfite-seq, or loss-of-function experiments, to substantiate these claims.

The bioinformatics analyses and interpretations are limited and require further clarification and refinement.

The proposed mechanisms are not fully explored, leaving the manuscript largely descriptive rather than providing a detailed mechanistic understanding.

We would like to thank the reviewer again for their various suggestions for improving our manuscript. By performing the experimental plan described above, we try to resolve the reviewer's concerns and improve this paper.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

In this manuscript the authors use in utero electroporation of tamoxifen inducible reporters to permanently mark cortical neurons with a common birthdate. They then FACS harvest these cells for bulk DNAse seq and RNA seq to see changes in chromatin regulation and gene expression as these newborn immature cortical neurons become deep layer neurons. As has been shown in prior studies that have addressed other neuronal types or used different methods to isolate developmental cell stages in the CNS, the authors find correlated changes between the opening or closing of chromatin with changes in gene expression. They use this information to localize chromatin marks that are associated with the differential expression of genes and conclude that many of the differential genes are bivalent for active and repressive chromatin marks. Finally the authors cross this dataset with a microarray they did of BDNF-inducible genes in cortical culture and suggest enrichment of this program in the differentially regulated gene set from in vivo.

Reviewer #3 (Significance (Required)):

The idea that chromatin regulation coordinates developmental changes in gene expression in neurons has been addressed with several different strategies over the past decade including prior strategies that allow for isolation of neurons with common birth dates. Many current strategies (well cited by the authors) use single cell sequencing and computational algorithms to deconvolve differentiation state from complex mixtures. This study takes an alternative approach to experimentally label these developmental stages which is nice to see for the validation of ground truth. However the study does not go far beyond current knowledge to use this method to add new concepts to the field. The main point of innovation seems to be the observation that the newborn neurons are primed at the chromatin level to express deep layer markers at the time they are born during embryonic life. This is useful to see but not unexpected on the basis of large scale single cell datasets. They also show that bivalent promoters prime developmental stage specific gene expression (in addition to the well-established function of this form of regulation in fate determination), however this too has been shown already in other neuron types.

We are very pleased that the reviewer evaluated our method as 'nice to see for the validation of ground truth' and distinguished it from the current mainstream method to trace the differentiation process computationally using single-cell analysis that tracks. On the other hand, we also agree with the reviewer's assessment that our results do not exceed previous knowledge. Therefore, as mentioned in our response to Reviewer #2, we plan to analyze the role of Dmrt3 in gene expression and chromatin structure during the neuronal differentiation process. This will allow us to clarify the novel insight into the neuronal differentiation process.

In addition to these conceptual limitations, there are some poorly supported comments in the text. For example, the fact that their microarray shows some genes in a category called "apoptosis" that are BDNF-sensitive does not meaningful suggest that BDNF induces excitotoxicity in embryonic cortical culture. BDNF has been well established as a survival factor for many kinds of neurons and is a common additive to serum-free media supplements (like B27). The appearance of "apoptosis" terms in the upregulated genes on the microarray more likely suggests either that the microarray is a poor detector of differential gene expression or that the genes in question are inaccurately categorized as "apoptotic" (GO terms are not terribly specific indicators of gene function). If the authors really wanted to test if BDNF was inducing apoptosis their cultures they could test this. However to use only the GO term data in such a strong statement about the biology of their system caused me to question the rigor of either their data or their analysis.

We are grateful to the reviewers for their important comments. We also agree that BDNF is an important neurotrophic factor and do not believe that it induces cell death. Therefore, we checked the following 40 genes, which showed chromatin closing from E12 to E16, upregulation upon BDNF stimulation, and the GO term 'programmed cell death'.

Cdip1, Diablo, Pla2g6, Braf, Tnfrsf25, Pa2g4, Mcl1, Hpn, Cebpb, Epha2, Plk3, Herpud1, Crip1, Dusp1, Sphk1, Irf5, Bag3, Stil, Fosl1, Cadm1, Lhx3, Hip1r, Relt, Irs2, Bmp8a, Ptcra, Mef2d, Prkcz, Rnf41, Pcid2

As a result, we found that there were no genes involved in the main pathway of apoptosis. From this, we understand that the GO terms related to cell death are listed in Figure 5f because 'the genes in question are inaccurately categorized as "apoptotic" ', as this reviewer pointed out.

We apologize for the misleading discussion in the previous manuscript and would like to thank the reviewer again for realizing this important point. We have corrected this in the new manuscript (page 9, line 263).

In addition, we will perform a reanalysis to confirm this conclusion of chromatin opening at neuronal activity-associated gene loci using public gene expression analysis data of neuronal stimulation.

A second example is the section about promoters being the focus of their discussion for DHS sites. Sure figure 3c shows promoters are more likely to be open compared with their contribution to the genome overall, but this is entirely expected since they are major gene TF binding sites, which is what DNAse detects. However promoters do not look to be more likely to be differentially regulated over time (3c vs 3e), and the statement that promoters are more enriched in opening compared with closing sites would require a statistical statement. Distal DHS sites appear equally more abundant in opening sites too.

We thank the reviewer for their thoughtful comments on our results. As the reviewer points out, the proportion of promoter regions in the opening DHS in Figure 3e is not so high compared to that in Figure 3c. However, as described in the Abstract and Introduction sections, we are interested in how neurons acquire their function during the differentiation process, and our main focus was on comparing neuron-specific and NPC-specific DHS here. In the comparison within Figure 3e, it is clear that the opening DHS has a higher proportion of promoter regions than the closing DHS. We made the necessary revisions to avoid any misunderstanding on this point (page 7, line 192).

On the other hand, as noted in the discussion, we are also interested in the role of the alteration in distal DHS. As in our response to Reviewer #2, we also plan to analyze changes in DHS in enhancer regions.

• *

3. Description of the revisions that have already been incorporated in the transferred manuscript

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

In Figure 1c, the actual values of the differentially expressed genes are unclear. Is this a Z-score? Please provide the log2 expression values and specify the scale used for the heatmap and clustering.

We apologize for the unclear expression value of Figure 2c. As this reviewer pointed out, the heatmap shows the Z-score, and we provided the actual scale in the new figure.

• *

Figure 5: It is somewhat unusual that the authors used microarray instead of RNA-seq for the BDNA stimulation of in vitro cortical neurons. Please provide a justification for this choice.

Gene expression analysis using microarrays is a well-established technique, though it is currently unfamiliar. Compared to RNA-seq, microarrays have the disadvantage that they can analyze only RNAs with probes and have a lower dynamic range. However, on the other hand, they have the advantages of reasonable cost and a simpler analysis method. In this paper, we performed microarray analysis for BDNF experiment, considering these advantages.

Figure 6: again, the data analyses are not comprehensively presented. What are the gene expression profiles of the other clusters (H3K27me3+, H3K4me3-/H3K27me3-, H3K4me3+)? Additionally, the sequencing data is inaccessible, and it is unclear how many samples (e.g., replicates) were used in this study for RNA-seq, DNase-seq, and ChIP-seq.

We apologize for the lack of gene expression patterns of other clusters in Figure 6c. We provided them in the new figure and confirmed that only bivalent genes (H3K4me3+, H3K27me3+) showed increased gene expression levels during neuronal differentiation and other clusters slight reduction (new Figure 6c). This result again suggests that the bivalent state in NPCs contributes to their activation during neuronal differentiation.

          We described these data in the revised manuscript (page 10, line 296).

Raw sequence datasets (fastq files) and processed data were deposited in the DNA Data Bank of Japan (DDBJ) Sequence Read Archive, a partner of International Nucleotide Sequence Database Collaboration (INSDC), as already described in the Data Availability section. Although DDBJ does not provide a reviewer access system for raw sequence datasets,

the reviewer's access to the processed data is as follows.

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To review GEA accession E-GEAD-803, E-GEAD-859, E-GEAD-860:

• Go to https://ddbj.nig.ac.jp/gea/reviewer

• Enter accession E-GEAD-803, E-GEAD-859, or E-GEAD-860 and 20 characters access token into the boxes

Please see the instructions below.

https://www.ddbj.nig.ac.jp/gea/reviewer-access-e.html

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We will provide the access tokens in the final revised manuscript.

For replicate numbers, we apologize for forgetting to describe them for the BDNF microarray experiment, though those for RNA-seq, DNase-seq, and ChIP-seq were already described in the Methods section. The replicates numbers are as follows:

RNA-seq: two replicates

DNase-seq: two replicates

Microarray: three replicates

ChIP-seq: two replicates

We provided the replicate number of the microarray experiment in the revised manuscript (page 17, line 543).

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Major comments:

The authors begin by examining TFs enriched at E16 DHS regions and suggest that TrxG and PcG factors are highly enriched in neurons, initiating their investigation of bivalent marks. However, they later conclude that bivalent marks are present in the NPC state and later become accessible. It is unclear why PRC factors would be enriched at the neuronal stage when the authors conclude that the chromatin becomes more open (potentially by removal of K27me3). The authors should refine this section of the manuscript to better rationalise their methodology and results.

We are grateful to the reviewers for pointing out our poor explanation in Figure 6.

This section aimed to investigate the mechanism by which open genomic regions in E16 were established. We used ChIP-atlas to investigate the transcription factors enriched in the E16 DHS and found many of the components of TrxG and PcG in the previous experiments using ES cells, which are the stem cells as NPCs. Therefore, we hypothesized that binding both TrxG and PcG, meaning a bivalent state, in NPCs may be important for chromatin opening until E16.Therefore, we analyzed bivalent genes in NPCs rather than E16 neurons in Figure 6b-d.

We explained the rationale in detail in the revised version (page 9-10, line 269-288).

Do the authors find any expressional changes of the suggested candidate proteins at the RNA or protein levels through development?

We thank this reviewer for the useful suggestions. We agree that changes in the expression of TrxG and PcG components during neuronal differentiation are important information for considering the mechanism of chromatin structural changes in bivalent genes. Therefore, we checked the expression levels of genes encoding components of PcG or TrxG, determined by Schuettengruber et al., Cell, 2017, in our RNA-seq dataset (new Supplementary Data 5). More than half of them showed significant alteration, suggesting the possible contribution of alteration in the activity of PcG or TrxG or both on chromatin opening.

          We described this point in the revised manuscript (page 12, line 370).

Minor comments:

1. The manuscript would improve with proofreading by a native English speaker.

We have already had proofreading by a native English speaker performed. We will also do it when submitting the revised version.

4. Description of analyses that authors prefer not to carry out

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

One additional point, which may be beyond the scope of this paper, is that to demonstrate the temporal resolution of this birthdate tracking method robustly, the authors should also apply the technique to upper-layer neuron development and compare developmental differences that were previously challenging to capture due to lower resolution.

Reviewer #2 (Significance (Required)):

The study focuses exclusively on deep-layer excitatory neurons, without comparisons to other neuronal subtypes or non-neuronal cells. Including such comparisons would help determine whether the observed chromatin changes are unique to this specific population or part of a broader developmental process.

We are grateful for the reviewer's meaningful suggestions. We also think that by comparing with upper-layer neurons and non-neuronal cells, we can more comprehensively understand the development of the cerebral cortex . However, this paper primarily focuses on deep-layer neurons, and analysis of upper-layer neurons and non-neuronal cells will be future work.

We described this point in the revised manuscript (page 13, line 384).

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Referee #3

Evidence, reproducibility and clarity

In this manuscript the authors use in utero electroporation of tamoxifen inducible reporters to permanently mark cortical neurons with a common birthdate. They then FACS harvest these cells for bulk DNAse seq and RNA seq to see changes in chromatin regulation and gene expression as these newborn immature cortical neurons become deep layer neurons. As has been shown in prior studies that have addressed other neuronal types or used different methods to isolate developmental cell stages in the CNS, the authors find correlated changes between the opening or closing of chromatin with changes in gene expression. They use this information to localize chromatin marks that are associated with the differential expression of genes and conclude that many of the differential genes are bivalent for active and repressive chromatin marks. Finally the authors cross this dataset with a microarray they did of BDNF-inducible genes in cortical culture and suggest enrichment of this program in the differentially regulated gene set from in vivo.

Significance

The idea that chromatin regulation coordinates developmental changes in gene expression in neurons has been addressed with several different strategies over the past decade including prior strategies that allow for isolation of neurons with common birth dates. Many current strategies (well cited by the authors) use single cell sequencing and computational algorithms to deconvolve differentiation state from complex mixtures. This study takes an alternative approach to experimentally label these developmental stages which is nice to see for the validation of ground truth. However the study does not go far beyond current knowledge to use this method to add new concepts to the field. The main point of innovation seems to be the observation that the newborn neurons are primed at the chromatin level to express deep layer markers at the time they are born during embryonic life. This is useful to see but not unexpected on the basis of large scale single cell datasets. They also show that bivalent promoters prime developmental stage specific gene expression (in addition to the well-established function of this form of regulation in fate determination), however this too has been shown already in other neuron types.

In addition to these conceptual limitations, there are some poorly supported comments in the text. For example, the fact that their microarray shows some genes in a category called "apoptosis" that are BDNF-sensitive does not meaningful suggest that BDNF induces excitotoxicity in embryonic cortical culture. BDNF has been well established as a survival factor for many kinds of neurons and is a common additive to serum-free media supplements (like B27). The appearance of "apoptosis" terms in the upregulated genes on the microarray more likely suggests either that the microarray is a poor detector of differential gene expression or that the genes in question are inaccurately categorized as "apoptotic" (GO terms are not terribly specific indicators of gene function). If the authors really wanted to test if BDNF was inducing apoptosis their cultures they could test this. However to use only the GO term data in such a strong statement about the biology of their system caused me to question the rigor of either their data or their analysis.

A second example is the section about promoters being the focus of their discussion for DHS sites. Sure figure 3c shows promoters are more likely to be open compared with their contribution to the genome overall, but this is entirely expected since they are major gene TF binding sites, which is what DNAse detects. However promoters do not look to be more likely to be differentially regulated over time (3c vs 3e), and the statement that promoters are more enriched in opening compared with closing sites would require a statistical statement. Distal DHS sites appear equally more abundant in opening sites too.

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Referee #2

Evidence, reproducibility and clarity

Summary:

The manuscript from Sakai et al. examines changes in chromatin accessibility during the differentiation of deep-layer excitatory neurons in the neocortex. The authors establish a novel genetic labelling method that tracks differentiating neurons based on their birthdates allowing following neuronal differentiation in vivo. By combining RNA-seq and DNase-seq they provide a comprehensive dataset of gene expression and chromatin accessibility changes during neuronal differentiation of deep-layer neurons and reveal that key genes linked to mature neuronal functions and bivalent genes in neural precursor cells become accessible during early differentiation. These findings underscore the crucial role of chromatin regulation in preparing neurons for maturation and unravel novel key insights into the regulatory mechanisms governing deep-layer neuronal differentiation.

Overall, this manuscript presents a novel technique for tracking neuron development from NPCs with specific birthdates. However, in its current form, it is largely descriptive and relies on correlative observations rather than elucidating a clear mechanism underlying chromatin and transcriptional changes. The provided data could be further leveraged to gain deeper insights into the molecular mechanisms governing deep-layer neuron development.

One additional point, which may be beyond the scope of this paper, is that to demonstrate the temporal resolution of this birthdate tracking method robustly, the authors should also apply the technique to upper-layer neuron development and compare developmental differences that were previously challenging to capture due to lower resolution.

Major comments:

The authors have generated extensive RNA- and DNAse-seq datasets across different developmental time points following birthdate labelling. However, the bioinformatics analyses and interpretations are limited and need further clarification and refinement:

1. The violin plots used to demonstrate expression and accessibility changes across developmental time points and the conclusions drawn from them are not convincing. The authors used a rank test to assess significant changes in expression, which only indicates the enrichment of genes with increased or decreased expression in each group. This cannot be directly interpreted as "significant upregulation." For instance, in Figures 4a and 4b, similar violin plots yield different statistical outcomes. The mean values on both graphs are comparable, yet Figure 4a suggests significant changes, while Figure 4b does not conclude significant downregulation of closing DHS genes. This is unconvincing. A more robust approach would be identifying DEGs between time points and analysing functional terms associated with these genes. The current plots do not support interpretations of gene upregulation, as each dot represents a gene, and the violin plot serves more as a population representation. The authors should either revisit their explanations and conclusions or include additional analyses and appropriate plots that support their claims of significant upregulation and downregulation of specific genes during development.
2. Figure 6b lacks clarity regarding the cutoff value used to categorise genes as K4me3 and K27me3 negative or positive from the heatmap. Even the "K4me3 negative" cluster displays a detectable signal of the mark, albeit at lower levels. Since only one plot of the entire gene body is provided, it is unclear what levels of enrichment are present, particularly at the promoter region. The authors are encouraged to provide additional informative plots and analyses of this ChIP-seq experiment, as this is a critical point where they draw conclusions about bivalent genes. This would not only strengthen their claims but could also uncover additional findings with more detailed analyses. A heatmap of clustered ChIP-seq signals of K4me3 and K27me3 alongside expression levels of the same genes (similar to Figure 2c) and differential accessibility (e.g., between NPC and E16) would better visualise and correlate histone modifications with chromatin and gene expression states.
3. The DNase-seq dataset can be better utilised to investigate differentially accessible motifs through development. Is this something the authors already looked into? This could strengthen mechanism investigation together with the ChIP-atlas results in Fig.6a
4. The two distinct modes of H3K4me3 enrichment observed are not addressed and should be explained. Which genes belong to these two clusters? Is there a difference in DHS and gene expression between them?
5. The same concern regarding the use of violin plots to correlate gene expression with bivalent genes through development (Figure 6c) as mentioned earlier. It would be better to use DEGs and intersect them. This is particularly important given the wide range of gene expression levels in the already poised state.
6. The authors limited their analyses to promoter/gene body regions. A survey of the bivalent marks and accessibility at enhancer regions would be also beneficial for understanding the changes at the chromatin landscape through development.
7. The authors begin by examining TFs enriched at E16 DHS regions and suggest that TrxG and PcG factors are highly enriched in neurons, initiating their investigation of bivalent marks. However, they later conclude that bivalent marks are present in the NPC state and later become accessible. It is unclear why PRC factors would be enriched at the neuronal stage when the authors conclude that the chromatin becomes more open (potentially by removal of K27me3). The authors should refine this section of the manuscript to better rationalise their methodology and results.
8. Do the authors find any expressional changes of the suggested candidate proteins at the RNA or protein levels through development?
9. The mechanisms driving the activation and expression of poised neuronal genes through the development of deep-layer neurons is not uncovered. The authors suggest certain histone modifiers and the DNA methyltransferase Dnmt3 as potential drivers of chromatin landscape and transcriptional regulation changes; however, this remains speculative, as there is no direct evidence or validation of these factors binding to the identified target regions or changes in DNA methylation states. The authors should provide validation of their candidate factors' presence at potential targets, as well as changes in DNA methylation if they want to conclude these as the mechanisms driving deep-layer neuron development.

Minor comments:

1. The manuscript would improve with proofreading by a native English speaker.
2. The motif analysis can be included in the main figures.

Significance

By introducing a novel genetic labelling method that tracks neurons based on their birthdates, the study provides a precise way to examine differentiation in vivo, adding valuable insights beyond traditional in vitro approaches. The combination of RNA-seq and DNase-seq analyses reveals how chromatin accessibility changes, particularly in bivalent genes, play a crucial role in neuronal maturation. This work highlights the importance of chromatin dynamics in establishing neuronal identity. The techniques and findings provide a useful framework for future studies, offering a path for deeper exploration of chromatin regulation across different neuronal types, stages of development, or disease contexts, making it a valuable contribution to the field of developmental neurobiology.

While the manuscript suggests the involvement of chromatin regulators such as Trithorax and Polycomb proteins, as well as Dnmt3 and DNA methylation, it lacks direct mechanistic evidence, such as ChIP-seq, bisulfite-seq, or loss-of-function experiments, to substantiate these claims.

The study focuses exclusively on deep-layer excitatory neurons, without comparisons to other neuronal subtypes or non-neuronal cells. Including such comparisons would help determine whether the observed chromatin changes are unique to this specific population or part of a broader developmental process. The bioinformatics analyses and interpretations are limited and require further clarification and refinement. The proposed mechanisms are not fully explored, leaving the manuscript largely descriptive rather than providing a detailed mechanistic understanding.

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Referee #1

Evidence, reproducibility and clarity

The authors have developed a method for labeling a specific stage of differentiating neurons. Using this approach, they tracked the four-day differentiation process of deep-layer excitatory neurons in the mouse embryonic cortex. They investigated genome-wide changes in transcription patterns and chromatin accessibility using RNA-seq and DNase-seq. Additionally, they provided H3K4me3 and H3K27me3 ChIP-seq data from E12.0 NPCs. This resulting omics data would be a valuable resource for the field. While initial data analyses show potentially interesting findings, only part of the analyses are presented in the figures, lacking sufficient detail. Before publishing the manuscript, the authors should include more comprehensive analyses of their datasets. Specific suggestions are below.

In Figure 1c, the actual values of the differentially expressed genes are unclear. Is this a Z-score? Please provide the log2 expression values and specify the scale used for the heatmap and clustering.

Figure 4 focuses on promoter-specific chromatin accessibility analysis. The author can process the data similarly to the transcription data. They should identify differentially accessible promoter regions across E13.0 to E16.0 and generate a heatmap with clustering. Additionally, the author should provide matched gene expression data, either in the form of a heatmap or box plot, corresponding to those differentially accessible promoter regions. Currently, Figure 4 only presents E16.0 data compared to E12.0, which is not comprehensive.

Figure 5: It is somewhat unusual that the authors used microarray instead of RNA-seq for the BDNA stimulation of in vitro cortical neurons. Please provide a justification for this choice.

Figure 6: again, the data analyses are not comprehensively presented. What are the gene expression profiles of the other clusters (H3K27me3+, H3K4me3-/H3K27me3-, H3K4me3+)? Additionally, the sequencing data is inaccessible, and it is unclear how many samples (e.g., replicates) were used in this study for RNA-seq, DNase-seq, and ChIP-seq.

Significance

Multi-omics data from the differentiation process of deep-layer excitatory neurons would be a valuable resource for the field.

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Reply to the reviewers

The authors do not wish to provide a response at this time.

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Referee #4

Evidence, reproducibility and clarity

In this manuscript by Torres Esteban et. al., the authors investigate how Pellino1/2 are recruited to chromatin surrounding DSBs. These two proteins contain the well-established FHA phospho-peptide binding domain that are present in other DDR chromatin binding such as RNF8. These two proteins were recently implicated as being involved in the DNA damage response, however, the exact phosphorylation-dependent recruitment method Pellino1/2 is not well defined.

The authors first attempt to identify proteins that bind to the multiple MDC1 TQXF motif, specifically when phosphorylated on the Threonine residue. In two independent experiments both Pellino1 and Pellino2 were pulled down with a phosphorylated MDC1 pTQXF peptide along with RNF8, as expected. They further show that this interaction between Pellino1/2 and the MDC1 is not specific to just a single MDC1 TQXF motif and that it requires a phosphorylated Threonine residue both from nuclear extracts and an in-vitro binding assay. The authors also show that Pellino1/2 cannot be pulled down from nuclear extracts using a pS139 H2AX peptide, as had been suggested by immunoprecipitation methods previously. Next, in Figure 2 the authors investigate if any of the 4 MDC1 TQXF motifs are preferentially bound by Pellino1/2 in comparison to RNF8. The authors further provide evidence for this phosphor-dependent interaction with a crystal structure of Pellino2-FHA along with a pTQXF MDC1 peptide. They then show that while this Pel1/2-MDC1 interaction can be observed using immunoprecipitation of HA/Flag-MDC1, it appears to be IR-induced DNA damage independent with this method. Using PLA as a second approach they validate that Pellino1 and MDC1 can be found in close proximity within the nucleus in cells and that this interaction is enhanced upon IR-induced DNA damage. As a control they see no PLA foci in MDC1 KO U2OS cells. The authors further this notion that MDC1 is important for Pellino1/2 recruitment to DSBs with laser micro-irradiation and see that GFP-Pellino1 is recruited to DNA damage in an MDC1-dependent manner. They further show that this MDC1-dependent recruitment of Pellino1 requires the TQXF motif of MDC1 as mutation of all 4 TQXF residues to AQXF abolished Pellino1 recruitment to laser induced DNA damage. The authors then show that this same AQXF mutant is also devoid of Pellino1 recruitment ability using IR.

Overall, the manuscript is very clear and concise and presents a reasonable model that MDC1 pTQXF motifs are required for recruitment of Pellino1/2 to DSBs. The explanations of data and figures, including the rationale behind experiments are easily understood and well presented. There are a few points that should be addressed.

Major Comments:

1. What were the other proteins that came down with the phospho-MDC1 pTQXF peptide pulldown, and what were the statistics of the pulldowns from the mass spectrometry experiments (i.e. number of distinct peptides, coverage, etc, for all of the interacting proteins that were identified. I was not able find a table showing all of the other interactors (Table S1? Not included in the files). These data are critical and need to be presented in the manuscript.

2. Given that the FHA domain structure primarily recognizes the three amino acids C-terminal to the pThr residue, why do the authors think that the measured KD for the pT765 site (pTQPF) is 5-fold lower than the measured KD for the pT752 site (pTQPF)? Please provide some rationale for this in the text. (See point 4 below as well)

3. In Figure 2, the pT699 peptide binds strongest to RNF8 and PELI1/2. Is this a consequence of other factors (conformational or allosteric changes, or other modifications on these proteins from the nuclear extracts) in the full length proteins compared to the isolated FHA domains? If the authors repeat this pulldown experiment using only the isolated FLAG- or GST-tagged FHA domains, do they also get the same result? The data in Table T1 suggests this will not be the case. Please confirm this, and if the data and discordant, please comment on the difference in full-length RNF8 and PELI1/2 binding from the HeLa nuclear extracts versus the isolated FHA domains in the text.

4. In Figure 3, I am confused by the reference to Asp+5. The sequence around pT765 is pTQPFDT, so isn't the critical Asp in the +4 position? Is this interaction sufficient to account for the 5-fold tighter binding of this site than to the pT752 site? Or is this higher affinity a consequence of the pT-1 Glu residue, or both? Perhaps showing a full side chain interaction map would help here.

5. It would be helpful if the authors looked at RNF8 levels in the FLAG Ips shown in Figure 4A. It looks like DNA damage slightly reduced PELI1/2 binding which might be accounted for by RNF8 competition.

6. Do the authors have any data, or can they speculate, on whether the entire MDC1 699-770 region can simultaneously bind to both RNF8 and PELI1/2 though different sites at the same time on a single MDC1 molecule or is the RNF8-PELI1/2 co-localization from adjacent MDC1 molecules? While clearly not required, it would be interesting to ask whether transfecting MDC1-knockout cells with variations of MDC1 containing 1, 2, or 3 Thr-Ala mutations at these sites compromises co-localization and DNA damage responses? Can co-transfection of two constructs containing distinct single TQXF sites - one optimized for RNF8 binding and one optimized for PELI1/2 binding, can rescue the co-localization phenotype.

7. What effect does the combined knock-down of PELI1/2 have on some aspect of DNA damage signaling or cell cycle progression? Is the repair/loss of gH2AX or 53BP1 foci delayed if PELI1/2 are absent?

8. Figure 4A shows that the interaction between MDC1 and Pellino1/2 is independent of IR-induced DNA damage as observed using immunoprecipitation. 4B shows that PLA foci between MDC1 and Strep-HA-GFP-Pellino1 can be observed in undamaged cells and PLA foci are increased when observed 3h post 3Gy IR damage. Is this discrepancy explainable by differences between PELI1/2 recruitment given that the antibody in 4A used recognizes both isoforms but the PLA in 4B is specific to Pellino1? It would be nice to see if there are any differences between Pellino1/2 by performing IP +/- DNA damage using exogenously expressed Pelliono1 or 2 variants. Additionally, repeating PLA in 4B with a Pellino2 construct would help address this question.

9. Similar to the comment above, a further investigation into if there are any differences in recruitment between Pellino1/2 using the experimental systems used in Figure 5 would greatly support the model presented, particularly since the crystal structure presented in Figure 3 is with Pellino2. Is there any rationale for this based upon amino acid sequence differences between Pellino1/2?

10. Using the experimental approaches in Figures 4 & 5 and the insight from the crystal structure in Figure 3, making point mutations in Pellino1/2 that would be predicted to disrupt the phospho-specific interaction would provide further confidence in the model proposed.

Minor Comments:

1. Could the authors please comment on if Pellino3a/b came down in the initial IP experiment and if not, is there potentially an explanation based upon sequence similarities/differences as inferred by the crystal structure of Pellino2?

2. Is there a rationale for why only single TQXF motifs were tested in isolation for binding in 2A? Given the proximity of the TQXF sites one could imagine that 2 or 3 TQXF sites being simultaneously phosphorylated could provide an even better peptide for Pellino1/2 FHA binding.

3. In Figure 2B, how is the data "Adjusted"?

4. Table T2 is provided twice, but the Table of co-precipitating proteins from the mass spectrometry experiments is not shown.

REFEREE CROSS-COMMENTS

It seems that most of us hit on the same set of core issues - whether the MDC stretch of 4 pTQxF motifs simutaneously recruits RNF8 and Pellino1/2 to the same MDC1 molecules or not, a few more mutational studies, and whether the Pellino recruitment is important in events downstream of MDC1 binding. This latter issue could entail significantly more work, though its inclusion would likely influence which of the journals that use Review Commons was interested in pursuing the paper. A purely biochemical study is fine, at least in my opinion, depending on the type of journal, but adding some functional DNA damage context and relevant cell biology would bring the work to a deeper level. Just my thoughts, of course....

Significance

The general significance of the data presented by Torres Esteban et. al., provide a mechanistic understanding of how Pellino1/2 are recruited to DNA damage, a role that has previously not been characterized. While this manuscript does not delve into the role of Pellino1/2 downstream of its recruitment, much of this has been investigated by a paper by Ha et. al., 2019 as cited in this manuscript. In fact, the Ha et. al., propose that Pellino1/2 directly interacts with pS139 H2AX. Torres Esteban et. al., convincingly show that this is likely not the case and provide robust biochemical and cellular evidence to support their mechanistic model, very nicely contributing to the body of knowledge regarding Pellino1/2 in the DDR. The audience that this paper would be important for would be those in the DNA damage field or structural biologists interested in phospho-peptide binding domains.

Our expertise is in DNA damage signaling, FHA and other protein modular domains, and determination of protein structure by X-ray crystallography.

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Referee #3

Evidence, reproducibility and clarity

The authors in this work provide compelling evidence to support a critical role of MDC1 as a molecular scaffold that dock Pellino1/2 at DSBs. Using an unbiased approach Pellino1/2, alongside RNF8, were identified as FHA-containing DNA damage responsive factors that bear affinity for an MDC1 TQXF phospho-peptide. Results from a series of interaction studies suggest that Pellino1/2 highly likely interact with MDC1 in a phosphorylation-dependent manner. Consistently, Pellino1/2 assembly at DSBs required MDC1 and its TQXF phosphorylation. Overall the work is of high quality and observations that highlight the MDC1-Pellino1/2 interaction are solid.

Significance

The work offers an alternative perspective that details MDC1 as an important molecular scaffold that allows DSB targeting of Pellino1/2. I have only two minor comments -

1) As opposed to examining interaction between Pellino1/2 and the MDC1 fragment (Figure 4A), to unequivocally demonstrate that Pellino1/2 interacts with MDC1 in response to genotoxic stress the authors should show that Pellino1/2 interacts with full-length MDC1 but not its AQXF mutant. In this setting IR should further enhance the Pellino1/2-MDC1 interaction.

2) For visualisation purpose the authors should provide density map that shows the MDC1-pTQXF and the key interacting residues on the PELI2 FHA.

OPTIONAL:

Given the plausibility that Pellino1/2 may co-occupy MDC1 with NBS1 and RNF8 it would be of interest to examine if that is indeed the case. & Does Pellino1/2 expression affect RNF8-dependent ubiquitylation?

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Referee #2

Evidence, reproducibility and clarity

The authors present a series of experiments demonstrating a physical interaction between the phosphorylated TQXF motifs of MDC1 and Pellino1 / Pellino 2 proteins (PELI1/PELI2). Both proteins are enriched in a peptide pull-down mass spectrometry experiment using HeLa nuclear extracts, and shown to bind preferentially to MDC1-pThr699 and -pThr765. These data are nicely supported by iso-thermal titration calorimetry experiments with a dissociation constant of 230nM determined for interaction with a synthetic pT765 phospho-peptide. The authors go on to determine an X-ray crystal structure of the FHA domain from PELI2 in complex with the MDC1-pThr765, to reveal the molecular determinants underpinning the interaction. Additional experiments, including immunoprecipitation, proximity ligation assay, and laser micro-irradiation support a phospho-specific interaction, driven by DNA damage, between MDC1 and PELI1/2 - and discount a direct interaction of PELI1/2 with the phosphorylated tail of histone H2AX as proposed previously in Ha et al (2019).

Major comments:

a) In all cases, RNF8 binds more tightly to the MDC1-pTQXF motifs, with the notable exception of pThr765; however, the affinity of RNF8 for the MDC1-pThr765 peptide has not been determined by ITC, which would be a useful comparator. Esp., given the question of how the authors envisage the interchange between binding to RNF8 vs PELI1/2?

b) Does Wing-II of PELI1/2 provide a secondary interaction pocket, capable of interacting with an extended bis-phosphorylated peptide? Is it highly conserved in terms of amino acid sequence?

c) Do the authors findings support the idea of PELI1 acting as part of a positive feedback mechanism that functions via PELI1-dependent ubiquitylation of NBS1?

d) The manuscript appears a little truncated, and does not explore the downstream (cellular) effects of disrupting the PELI1/2 - MDC1 interaction.

Significance

Overall, the manuscript contains a robust and well-controlled set of experiments that confirm a direct interaction between the PELI1/2 protein and MDC1, dependent on prior phosphorylation of MDC1 (at its TQXF ) sites in response to DNA damage. With that said, it is somewhat limited in scope, and does not explore the cellular consequences of breaking/interfering with the ability of PELI1/2 to interact with MDC1 and how this might be integrated into our understanding of the mammalian DNA damage response.

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Referee #1

Evidence, reproducibility and clarity

Summary:

The manuscript by Esteban et al. provides compelling evidence that MDC1, in addition to its well-known interaction with the E3 ligase RNF8, also directly binds to the E3 ubiquitin ligases Pellino1 and Pellino2, both of which have recently emerged as important players in the DNA damage response. The authors convincingly show that MDC1 mediates the recruitment of Pellino1/2 to sites of DNA double-strand breaks (DSBs) via a phosphorylation-dependent interaction.

Major Comments:

1. Competitive Binding Dynamics: The manuscript should address whether RNF8 and Pellino1/2 compete for binding to phosphorylated MDC1. Understanding whether these interactions are competitive, cooperative, or mutually exclusive is crucial for deciphering the functional implications of MDC1's ability to interact with multiple E3 ligases.

2. DNA Damage-Independent Interaction: The observation that MDC1 and Pellino1/2 interact in the absence of DNA damage (as depicted in Figure 4A) is unexpected. While the authors note that MDC1 is phosphorylated to some degree in non-irradiated cells, this explanation does not fully clarify the mechanism or significance of this interaction in the absence of DNA damage. Since DNA damage typically enhances MDC1 phosphorylation, one would anticipate a corresponding increase in the interaction between MDC1 and Pellino1/2. Further investigation into this aspect is needed to better understand the context in which these interactions occur.

Minor Comments:

Figure 1E Labeling: There is a labeling error in Figure 1E; the labels should be corrected to "H2AX" and "pS139-H2AX."

Significance

While the discovery of this interaction is intriguing, the manuscript would benefit from a more thorough exploration of its physiological significance.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

miRNAs are important for the control of many cellular processes, with the miR-29 family of miRNAs implicated in the regulation of cell growth in different cell types in both the epidermis and dermis of the skin. However, the roles of miRNAs in specific cell types in general, and of the miR-29 family in the skin, are currently unknown. Here, the authors use a range of cellular and molecular techniques, including miRNA cross-linking and immunoprecipitation (miRNA-CLIP) and antisense oligonucleotides (ASO), as well as RNA-Seq, qPCR, Western blotting, in situ hybridization, adhesion and ECM assays, ELISA and immunofluorescence, to interrogate the roles of the miR-29 family of miRNAs in controlling cell growth in epidermal keratinocytes and dermal fibroblasts, using 2D and 3D ex vivo models. The coupling of miR-CLIP with functional assays allowed the authors to identify both miRNA-mRNA complexes, and the biological pathways that these ultimately manipulate.

The authors report the identification of unbiased, tangible miR-29/mRNA pairs, together with functional roles in cell adhesion, ECM regulation and fibroblast proliferation, that are distinct between keratinocytes and fibroblasts. miR-29 is identified as a valuable target for interventions that seek to promote healthy skin regeneration, including applications for wound healing. Many of the pathways identified here have previously been described, but the novelty of this manuscript lies in the innovative combination of miR-CLIP with functional assays, the application of these in combination to specific cell types, the identification of miR-29 as a novel master regulator of epidermal keratinocyte adhesion via a range of different pathways, and the demonstration that miR-29 inhibition in fibroblasts can influence keratinocyte adhesion via paracrine signalling.

The experiments are well designed and reported. The interpretations are sound and appropriate for the data presented (though see the comment on potential normalisation of ECM data to cell numbers in cultures for the miR-29 mimic/inhibitor data for fibroblasts and the query about the number of direct miR-29 targets in fibroblasts that are ECM-related).

Major Comments: I have no major concerns to raise over this manuscript. The claims and conclusions are supported by the data and no additional experiments are required (though please note the comment on normalisation mentioned above and detailed below). The methods are clearly reported and statistical reporting is adequate.

Minor Comments: Pg3, 7th line from the bottom: "processed into three functional miRNA..." - minor edit needed here, it looks like there's a word missing somewhere. Pg3, last line on the page: "results supported..." - is there a missing 'are' here? Pg5, 15th line of the main text: "of miRNA-29-mediate repression..." - is there a missing 'd' here ('-mediated...')? There is lots on minor presentation errors like this throughout the manuscript - I won't point them out exhaustively, but the manuscript needs a good thorough proof-read, maybe from a fresh pair of eyes? - We fully agree with the reviewer. The manuscript has been proofread and corrected throughout. Fig. 1C: Can the figure be edited to better highlight the basal layer with lack of (nsm image) and expression of (abm image) K10? Maybe a box around that layer, rather than the current arrows only on the abm image (which are not particularly closely indicating the basal layer)? We thank the reviewer for this suggestion. The arrows on the Fig.1C point to the areas where keratin K10 filaments are reaching the basal membrane (indicated by collagen IV staining). It was difficult to box out the basal level without covering the K10 signal. We decided to explain this in the legend to clarify how the data shows this pre-mature expression of keratin K10 in the miR-29ab mimic sample. ____The basal layer of the control (nsm) sample thus remains K10-free and only shows nuclear DAPI staining. Fig. 2 legend should include definitions of abbreviations shown on the figure. - Added Pg8/Fig. 4A: Can the reporting of shared transcript targets of miR-29 in IFK/HFK/DF cells be better communicated? Maybe just adding the actual percentage overlap in transcriptomes for IFK/HFL and keratinocytes/fibroblasts to the main text would help . – Actual percentages of the overlaps added in the text. Similarly, I think a direct report somewhere (in the main text?) of total number for relevant groups shown in Fig. 4E would also be useful - e.g. there are 45 transcripts that are direct targets of miR-29 in keratinocytes and also associated with ECM, and 190 that are direct targets of miR-29 in keratinocytes and also associated with cell adhesion, but these number are difficult to come by quickly at the moment. It would be nice to be able to quickly compare these numbers for keratinocytes to their equivalents for fibroblasts__. – This is a very helpful suggestion with a good example. We incorporated the suggestion into the text and made changes to the figure to make it easier to compare pro-adhesive and miR-29-regulated functions in keratinocytes and fibroblasts. Fig. 4B: It's interesting that ~15% of miR-29 binding targets identified using miR-CLIP are not predicted targets based on TargetScan/microT-CDS. I'd like to see a little more information on this added to the manuscript - perhaps listing some of these or including a table of them? And perhaps some discussion of this could be added also. - Indeed, almost 170 mRNAs are in this category and are now listed in a table in Suppl. File 1. Non-canonical binding is briefly discussed in the text. Fig. 4E: I would be nice to see the Venn numbers for keratinocyte proliferation (either is a supp figure, or addition to the main text?), to help illustrate the lack of a role for miR-29 in the regulation of keratinocyte proliferation. – It is an interesting point; the cell proliferation seems to be a function of miR-29 in fibroblasts but not in keratinocytes. We did not detect cell proliferation as a significantly enriched function among keratinocyte mRNAs directly regulated by miR-29. It is consistent with the lack of change in BrdU incorporation in keratinocytes grown in 3D (Figure 2). We also never noticed any change in keratinocyte proliferation while expanding them in 2D after miR-29 transfection or inhibition. This has been further highlighted in the text. Fig. 4E: Is the reported number of direct miR-29 targets in fibroblasts that are ECM-related correct? This number is reported as 10 in the main text (pg10, 3rd paragraph), but it looks like 10 is only for direct miR-29 targets in fibroblasts that are ECM-related AND related to proliferation. Should this number be 58? The 10 that are direct miR-29 targets in fibroblasts that are ECM-related AND related to proliferation can be reported in the next sentence, where this group is specifically referred to. – This has now been amended in the text according to the reviewer’s suggestion. Fig. 7 (and related main text): Did you take any steps to normalise ECM measurements to cell numbers present in cultures in the miR-29 mimic/inhibition experiments in fibroblasts? This should really be included as it would provide an answer to the speculation of whether the effects of manipulating miR-29 on ECM are due to proliferation or classical pro-fibrotic pathways - it is probably based on proliferation not pro-fibrosis because TGFb is one of the most pro-fibrotic cytokine known and it’s response is abrogated by miR-29KD. Need to check the original excel for Fig. 7D. – Yes, the concentration of the ECM was measured in ng/ml and normalized per number of cells. We calculated the concentration of oligonucleotides per cell by dividing the amount of transfected oligo per number of transfected cells counterstained with nuclear DAPI signal. We could do so because every cell showed a similar transfection rate by calculating fluorescence of Cy3 conjugated to the miR oligos. Then, we divided the ECM concentration by the number of transfected cells per well, thus normalizing the ECM deposition to the cell number. The reviewer is correct, both the increase in ECM after miRNA-29 KD and the decrease in ECM after miRNA-29 overexpression is consistent with increased and decreased cell numbers, correspondingly. As suggested, we later confirm that the increased deposition of the ECM was not a result of activated pro-fibrotic pathway (Figure 7).__

Fig. 8E: The upper and lower image need to have nsa/abc labels added to them. – This has been done, thank you for noticing! Pg12, 1st sub-heading: typo (cell-specific). -corrected.

**Referees cross-commenting**

All reviews appear to be fair and balanced to me. I agree that in places wording could be amended to temper the strengths of some claims, and it would also be nice to see some additional functional assays included, to complement the adhesion and ECM deposition assays that are currently presented, though I do not think this should necessarily be a requirement for publication and could be included in subsequent follow-up work from the group. I did not spot the reuse of images between Fig. 1 and 2, but clearly this should be addressed - either by replacing one set of images, or by removing the relevant panels from Fig. 1 and changing in-text reference to guide the reader to Fig. 2A. I also agree that it would be nice to see miR-29 staining of mouse dermal fibroblasts during wound healing, to complement the images already shown for keratinocytes, and to see miR-29 staining in human skin__. – We thank Reviewer 1 for cross-checking other reviews, and we address these comments in response to Reviewers 2 and 3. __

Reviewer #1 (Significance (Required)):

miR-CLIP is a powerful, recently developed technique, with enormous promise for the identification of true miRNA-mRNA pairs, that has not yet been widely adopted by the research community. As such, its application here is itself relatively novel, adding enormously to our existing knowledge of likely miR-29 targets, providing tangible information in miR-29/mRNA pairs in specific cell types in different layers of the skin, but also further adding novel functional information to this, with demonstrations of the regulation of specific relevant biological pathways through manipulation of targets identified using miR-CLIP. The methods are sound (and impressive), results are reported well and not over-interpreted. There is the potential for better characterisation of the relative importance of canonical pro-fibrotic pathways vs proliferation-related effects on ECM production, and this should not be difficult to address. This paper will be on interest to a wide readership, including those engaged in fundamental research and clinicians.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary:

The article entitled, "miRNA-29-CLIP uncovers new targets and functions to improve skin repair", by Thiagarajan et al. describes the characterization of the functions of miRNA-29 in keratinocytes and fibroblasts, its RNA interactors and potential mechanisms of action. Using candidate interactors and 2D cell culture and 3D skin equivalents combined with loss-of-function (inhibitor) and gain-of-function (mimic), and changes in expression analyses, the authors conclude that the major function of miRNA-29 is to regulate cell-substrate adhesion.

Major comments:

• While the interactors and expression changes are useful resources, the claims and the conclusions that are based on them are exaggerated. The treatments are associated with changes in expression, but no functional data support the conclusions. Additional functional experiments are required to assertively make the claims. The title is misleading when stating "to improve skin repair" and the abstract also makes some bold general claims, which are tangentially supported by the findings. For example, "protein folding" only appears in the abstract and "RNA processing" is in the abstract and figures but not referred to in the text__. – We thank the reviewer for valid criticism. While this manuscript was in preparation, we were publishing our other study showing the function of miRNA-29 in wound healing in cutaneous mouse-based model. This study demonstrated an improved re-epithelialization and wound closure in Mir29ab1 KO mice (Robinson et al, Am. J. of Pathology 2024). It was difficult not to think about the role of miR-29 in a wider context of skin repair, which was the goal of the in vivo part of the project. We could not cite the other manuscript at that time as a reference and should have toned down our claims to improved skin repair in this manuscript.__

• The authors may want to tune their language that their data suggest the conclusions as opposed to being definitive and assertive. This should be done in the Discussion, while the Results should represent the direct conclusions__. – This has now been amended accordingly (highlighted in green).__

• A couple of examples to the above, in the conclusion to section 1 of the Results, how was the "loss of basal adhesion" assessed? Is it by beta1-integrin localization changes? – We have not performed assays specific to activated integrins, but this is planned studies where we will address the molecular details of the miRNA-29-controlled cell-to-cell and cell-to-matrix adhesion mechanism. Also, how is "growth" defined"? proliferation is not changed and a more accurate way to describe the result is to refer to thickness__. – Indeed, our results clearly demonstrate no change in keratinocyte proliferation in response to a change in miRNA-29 levels either way. We therefore speculate that the reason for differences in 3D cultures of keratinocytes (the SEs) is pre-mature differentiation, induced by miRNA-29. While we do not have a mechanistic answer to this observation (e.g., keratin K14 is not a direct target of miRNA-29), premature expression of K10 in the basal layer may be a consequence of altered adhesion mechanisms in the basal layer. As noted earlier, we are currently investigating the mechanism of miRNA-29-regulated adhesion of mouse and human keratinocytes, but this was beyond the scope of presented study, which has identified the phenomenon at the first instance using organismal and tissue-level approach.__

• The images in Fig 1C are reused in Fig 2A, where new examples should be shown instead. – We had erroneously inserted the same panel as in Figure 2. The correct day 6 panel is now inserted instead in Figure 1C, along with an additional control of normal human skin.

• Fig 1C and Fig 2A are not quantified to make the claims about premature differentiation and integrin expression changes. – We struggled to find an accurate method of quantifying the fluorescent signal coming from varied cell shapes and the basal lamina of human SEs. We however see certain consistency in deposition of integrin beta 1 and alpha 6 (ITGB1and ITGA6) in our SEs. The signal for ITGB1 completely disappears in miRNA-29 treated SEs while ITGA6 goes down. Conversely, increased ITGB1 after inhibition of miR-29 coincides with a higher signal of ITGA6 (Figure 2A). ITGB1 and ITGA6 are co-expressed in basal layer of ____human skin____ and ____SEs____(____Solé-Boldo et al, Comm. Biology 2020, ____Fig. 1c____; Stabel et al, Cell Rep. 2023, Fig. 3E) and can heterodimerize to form integrin α6β1 in various tissues (____reviewed by Zhou et al. Stem Cell Res Ther. 2018____). We have changed the way we discuss the results in the text.

• Fig 3: It is not clear from the figure legends what statistical methods were used for which experiment or how many times the experiment was performed (not just biological replicates), especially given the variability among experiments in Fig 3C. - Adhesion assay in Fig. 3A was performed in four biological replicates with one batch of primary human keratinocytes (pooled neonatal), and in 3C, as two independent experiments (exp) with two different batches of keratinocytes (exp 1 and exp 2). Lower numbers of cells in exp 1 as compared to expt 2 are due to an unfortunate but usual variability between batches of primary cells. The variability noted by the reviewer is most likely coming from lower numbers of cells in exp 1 as compared to exp 2. We have now clarified this in the figure legend.

Minor comments:

• The Introduction is focused on methodology and should include elements that pave the way to the Results. Some information that belongs in the introduction are present in the Results section. In this respect, please define the miRNA processing Dicer pathway and its components in the introduction so that the reader can follow the nomenclature (AGO2, RISC, etc.). Also, introduce human skin equivalents or organotypic culture as a model system in the Introduction.

• Some information in the Results belongs in the Introduction, for example, the first seven lines of the Results section. - We have changed the introduction accordingly

• The authors might want to consider including quantifications in the main figures, so they are immediately apparent to the reader, for example, Fig S1C. Also, Fig S2B is an important measure for the immediate outcome of the treatment on miRNA-29__. – We have included the quantification of the SE epidermal thickness in Fig. 1D and emphasized the KD effect of miR-29 anti-sense oligos in the text.__

• Please change "imidiate" to "immediate", "sculp" to "scalp", "has to be releaved of miRNA-29-mediate repression" to "has to be relieved of miRNA-29-mediated repression" - Done.

**Referees cross-commenting**

I agree with my colleagues' assessments and suggestions. The miRNA-CLIP data in keratinocytes and fibroblasts are important resources. The figures and text require reconsideration to more accurately represent the data as detailed in our collective reviews

Reviewer #2 (Significance (Required)):

The study utilizes 2D and 3D cultures and presents an important resource for miRNA-29 interactors in keratinocytes and fibroblasts, as well as the expression changes associated with its inhibition and overexpression. However, the conclusions are exaggerated and based on expression changes. If the conclusions are rephrased, the findings would be of interest to a broad audience interested in miRNA, cell adhesion and epithelial and mesenchymal biology.

My expertise is in skin development and maintenance, genetics and cell biology. I have limited knowledge in RNA biology.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary:

Thiagarajan et al. report on the functions and molecular targets of miR-29 in human primary skin cells. They first focus on the potential role of miR-29 in wound healing and in the adhesion of keratinocytes to the basement membrane using both in vivo wounding assays in the mouse and human cultures/skin equivalents. The authors report that miR-29 negatively affects adhesion in vivo and in vitro and characterise the transcriptome of fast and slow-adhering cells with or without miR-29inhibition. They proceed to identify miR-29 targets in three primary skin cell types (follicular keratinocytes, interfollicular keratinocytes and fibroblasts) by performing miRNA-clip. By comparing these targets to genes altered in keratinocytes with high adhesion capacity after miR-29 inhibition or fibroblasts after miR-29 inhibition, the authors describe a model in which miR-29 inhibits multiple adhesion-associated pathways in keratinocytes and negatively regulates proliferation and ECM deposition by dermal fibroblasts.

Major comments:

Overall, the paper is interesting, and the experiments performed are generally sensible for the questions being investigated. However, I thought the data was presented in a very confusing and unclear way, both in the main text and in the figures. I found the paper quite difficult to navigate, with contradictory statements between text and figures, cryptic or confounding graphs or arrangement of the figures and, in at least one instance, re-use of the same image with inconsistent labelling. The paper will thus greatly benefit from extensive tidying up and review of both text and figures to improve clarity. I highlight several points below, with many being related to this overarching issue, and I try to offer suggestions to the authors improve the quality of the manuscript.

• The stainings in Figure 1A should be repeated in intact sections as it is difficult to understand the exact distribution of miR-29 when the whole epidermis appears to be falling apart in the section. It is possible to see the pattern the authors are describing based on the current images, but it is not convincing. – We fully agree with the reviewers that an intact section would inform the reader on the distribution of miRNA-29 inside the wound much better when the wound morphology is preserved. We have tried repeating the staining (fluorescent in situ hybridization coupled with the antibody staining). The protocol involves multiple washing steps performed at high temperature (for the FISH) and detergent (for the immunodetection step) to ensure specific miRNA probe binding and a low background for the antibody binding. As a result, we could not get a more intact section at the end unfortunately. We have however published a miRNA-29 FISH only stained mouse wounds in ____Robinson et al, Am Journal of Pathology 2024, Figure 1C and Suppl. Fig. 1B____ showing more intact sections with miRNA-29 signal against DAPI. There, one can see the same pattern of miRNA-29 expression as in Figure 1 of this manuscript, with less miRNA in the basal layer of wound keratinocytes vs more miRNA-29 in the skin peripheral to the wound.

The authors should comment on the fact that miR-29 signal in the inset (at the edge of the wound) appears more basal than in the wound epidermis or in the unwounded__. – We have now inserted this suggestion and discussed it where appropriate (highlighted in cyan)__

Quantifications and statistical analysis of the intensity and distribution of miR-29 for panels A and B and K10 for panel C will need to be included to help get a better sense of the data in its entirety and strengthen the observations. – We agree with the reviewer that such quantifications would be extremely helpful. The nature of the miRNA FISH protocol relies on signal amplification, allowing detection of mature miRNA specifically despite their short length. We could not therefore rely on conventional methods to quantify the fluorescence reliably as it can only be interpreted relatively to other areas/sections stained at the same time. We have attempted to do the miRNA FISH without amplifying the signal by attaching the FITC probe directly to the miRNA-29 probe but the signal was too weak to reliably detect and quantify miRNA-29 expression in wounds. Importantly, Figure 1C is described as staining after 6 days of skin equivalent cultures, but the same images are used in Figure 2A, where they are described as stainings after 11 days of culture. The authors should try to harmonise the data presentation so that the same data is not presented multiple times if possible. If repeated data presentation is necessary, it should be clearly stated and justified, and the authors should be careful to correctly indicate what the images represent. – This has been corrected.

• ITGB1 stainings in Figure 2 do not convincingly match the statements in the main text ("miRNA-29 mimic-transfected SE struggled to attach through the integrin beta1 (ITGB1)-mediated adhesion__"). – This should have been phrased rather as a suggestion. We detected virtually no integrin beta 1 in miRNA-29 overexpressing cells, which strongly suggested that high levels of miRNA-29 prevent ITGB1-mediated adhesion of keratinocytes to the basal membrane. __

All stainings, or at least the most important ones, like ITGB1, should have quantifications and statistical analyses of their intensity and distribution to support any observations. – We thank the reviewer for this comment and fully agree it would be ideal to have quantifications of all staining. We have tried to do so but were able to reliably quantify only BrdU, ITGB1, and ITGA6. The data has now been added to results and discussion.

Staining of basement membrane proteins at 6 days could help better visualize if indeed there are any attachment defects in the mimic-overexpressing cells – We stained 6 day section for basement proteins collagen IV and laminin 5 but could not detect any differences in attachment (data added below). Since both keratinocytes and fibroblasts contribute to the epidermal-dermal adhesion on the BM, a more sophisticated method of detecting adhesion in human skin equivalents may be needed following miRNA-29 manipulation (e.g., electron microscopy of keratinocyte-BM contacts like hemidesmosomes).

Since the authors use transient transfections, the significance ant interpretation of the stainings performed at 11 days will be reliant on the transfection strategy employed, the rate of proliferation of the cells, and the half-life of the proteins stained.

The transfection strategy is not clearly explained (this is a more general problem, see below) and staining for miR-29 in these sections is necessary to ensure that the treatments are still in effect after this prolonged time in culture__. – We have now clarified the transfection protocol and added the quantification of miRNA-29 levels in skin equivalents at day 6 and day 11 (Figure S2D). The overexpression and the inhibition of miRNA-29 is still evident at day 6 and day 11, probably because of the high levels of miRNA mimics and the stabilizing chemistry of miRNA-29 anti-sense oligos (MOE-PS modifications). - The mimic/inhibitor transfection strategy employed by the authors throughout the paper is not clearly explained and this is a very important detail to understand the results of many of the assays they perform. The methods and Figures S2/S3 describe a 'double transfection' transfected twice on D2 and D4 strategy for the inhibitors, but it is unclear if the same approach was used for the mimics (which is important since some of the experiments where they are employed have functional assays that can last longer than a week). Additionally, the strategy used for the inhibitors described in the methods section seems different than the one described in Figure S3. In the methods, the cells are transfected at day 1 and day 3 and collected for functional assays at day 5. Figure S3 instead shows two transfections at 'day 0' and an additional one at 'day 4' with miRNA levels measured at day 0 and day 8 (this bar plot should be modified to better reflect that measurements were only taken on specific days). The legend for Figure S3 reads "keratinocytes (P3/4) were transfected twice on subsequent days" and mentions "representative images of the cells from each treatment after the third transfection". This is all extremely confusing. The authors should make sure they explain what they did clearly and univocally, for both mimics and inhibitors, and they should add a time course with miR-29 levels following transfections of mimics and inhibitors covering the span of their longest assay. – We thank the reviewer for carefully checking the flow and apologize for the confusion. The successful transfection of primary keratinocytes with miRNA mimics is more straightforward than with the anti-sense oligos as the chemistry quite differ. Mimics go in as a ‘stem loop’ RNA structures _and require only one transfection round. Anti-sense ‘inhibitors’ oligos (ASOs) are 15-16 nt single-stranded, _phosphorothioate (PS)-methoxyethyl (MOE)-modified ASO_ require a double-transfection. This way, ASO remain in ‘fast’ cells for days and during adhesion assay as shown here._ The additional experiment for the cell viability and proliferation was following the 2nd transfection, which is now clarified in the text and in the Suppl. Figure S3.__

• Figure 3 includes reference to morphological parameters that would be predictive of a keratinocyte ability to form a holoclone (red arrows). While the larger size and low nucleus-to-cytoplasm ratio of differentiated cells is well-established, to my knowledge there is no accepted consensus about strong predictive capacity of simple morphological parameters when it comes to holoclone formation. The consensus regarding keratinocyte clonogenicity is generally missing in the field, relying primarily on early passage, low cytoplasm/nucleus ratio, and colony boundaries. Another important characteristic is the number of passages that the cells can undergo before they growth arrest or die. We are currently performing follow up experiments to characterize the miRNA-29 KD (abc) clones and consistently observe higher growth capacity (longevity) of the miRNA-29 depleted keratinocytes. This is also consistent with the data shown in Figure 3A and S3A.

• The inhibition of miR-29 in experiment 1 of the growth factor depletion assay seems to have failed according to Figure S2C, so the results of experiment 1 (-GF) in Figure 3 should be disregarded and the experiment repeated. We have disregarded the failed experiment and repeated adhesion assays under -GF conditions with more controls. While the improved adhesion upon depletion of miRNA-29 was reproducible, we also found that the growth factor depletion using a specific inhibitor of epidermal growth factor receptor (EGFR) AG-1478 abrogated the fast ____adhesion effect of miRNA-29 inhibition. It possibly means that miRNA-regulated adhesion requires EGF (but not other GF) signaling; however, more experiments would be needed to uncouple the role of GF in miRNA-29 adhesion.

• The authors report reduced keratinocyte differentiation in the miR-29 inhibited cells. This statement is mostly supported by the cell number time course shown in Figure S3B, but this experiment is not mentioned in the main text, which instead focuses on (less reliable) morphological parameters alone. Moreover, Figure S3 only shows the morphology of cells at day 4 and does not provide any information about the cell morphology at day 6 or day 8 as suggested by the main text. Assessing differentiation based on morphology alone is prone to inaccuracy and while the cell number experiment is good support for the stated decrease in differentiation in the miR-29 inhibited cells, it should be complemented with differentiation marker staining and/or clonogenicity assays. - We agreed with the reviewer and made the appropriate changes in the text. Figure S3 has been updated as well, and we also ran a side analysis of differentiation markers (keratin K10 and loricrin). We found that miRNA-29 does not change significantly during keratinocyte differentiation in 2D (please, see the Support Figure A below).

• The authors' claim that their results "revealed the direct in vivo targetome and functions of miRNA-29 in three types of cells isolated from human skin" is not accurate. While their experiments are indeed compelling, they are performed in cultured primary cells grown for at least 3 passages, which are akin, but not the same as cells in vivo and may behave differently. – We agree and have changed this now in the text. On a similar note, while there is some evidence from mouse that miR-29 may intervene in the regulation of the wound healing response in keratinocytes in vivo (Figure 1A), no analogous in vivo data is presented for fibroblasts. The authors should consider showing miR-29 stainings of mouse dermal fibroblasts and the potential variation in its level during wound healing. - While this manuscript was in preparation, we were in the process of publishing our study showing the function of miRNA-29 in wound healing in cutaneous mouse-based model. This study shows the staining for miRNA-29 in mouse wounds during healing and includes the staining in dermal fibroblasts (____Robinson et al, Am. J. of Pathology 2024, Figure S1B____). We have isolated total RNA from mouse wounds at different points of healing and checked miRNA-29a/b levels using TaqMan assays. While we detected a change in miRNA-29 expression (Support Figure C, D), this possibly included miRNA-29 in the normal surrounding skin, inevitably present in a wound biopsy. __They should also show miR-29 staining of normal human skin to confirm that its expression pattern mimics the mouse. - We could not cite the other manuscript at that time, but it shows lower levels of miRNA-29 in dermal fibroblasts compared to keratinocytes in the epidermis by FISH (_Robinson et al, Am. J. of Pathology 2024, Figure S1B_). We also quantified levels of miRNA-29a/b in primary mouse keratinocytes and fibroblasts using TaqMan assays, and consistently with FISH, detected more miRNA-29 in keratinocytes (Support Figure B). The FISH for miRNA-29 in human skin was published earlier, also showing much lower signal of miRNA-29 in the dermis (Kurinna, S. Nuc. Acid Res. 2021, Supplementary Figure S3A). If possible, they could also 'wound' human skin explants and check what happens during re-epithelialisation to miR-29 expression and to the key targets they identified (explants may be challenging to obtain, though). These experiments could provide some more compelling (though inevitably correlative) suggestion that miR-29 could intervene in the wound healing response in vivo in humans. – This is a very good experiment suggested by the reviewer. The human skin explants were indeed challenging to obtain. We could only get a few sections of paraffin-embedded samples, which were suboptimal for miRNA-29 FISH. We included the data as Figure S1A. __

Minor comments:

• I would encourage the authors to avoid, when possible, the use of red/green colour palettes both in stainings and in graphs, as it makes the paper less accessible to colourblind individuals. – We sincerely apologise for the use of these colours in many stainings. We substituted red and green everywhere we could, but our technical capabilities did not permit changing colours on all Figures.

• I would suggest avoiding the use of "stacked" bar plots to show data as they might lend themselves to misinterpretation. It would likely increase clarity if the bars for different conditions were plotted next to rather than on top of one another. - We replaced the stacked plots as suggested on Figures 3, 6, and Figure 8. We kept one stacked plot in Figure 6D to show variability in the nsa-treated samples for some mRNAs. The control samples on these plots were set to one (nsa) and the stacked part on top reflected the fold increase in mRNA levels after knock-down of miRNA-29 (abc).

• The first inset in Figure 1B does not appear to match the box in the lower magnification image. – We moved the inset to the correct location.

• The title of the section "Rescue of miRNA-29 mRNA targets improves basal adhesion of human keratinocytes" should be changed, as no rescue experiments are performed. The term is used again in the text when referring to targets upregulated (or "de-repressed") after miR-29 inhibition, but it is not accurate and should be changed__. – We followed the suggestion and highlighted changes throughout the text.__

• The authors should specify the most important details of the adhesion assay in the Results section (for example the fact that the assay is carried out on fibronectin). – We added this to the Results.

• The main text is imprecise when describing the RNAseq of fast/slow attaching keratinocytes, because it does not mention that the assay also includes miR-29 inhibition. - We have amended this and highlighted the changes in the text.

• The insets in the middle of Figure 3 are not described in the figure legend and it is unclear what they are meant to be highlighting. The Authors should also double-check the accuracy of the scale bars across Figure 3A. - We described the insets in the legend and double-checked the scale bars in Figure 3A.

• The pattern in the "abc" bars in Figure 3C makes it difficult to see the symbols – We increased the font and adjusted the label.

• The area overlaps in the Venn diagram in Figure 4A should reflect the numbers. Since the diagram is comparing only three sets, accurate overlaps should improve the representation of the data. – We have re-created the Venn diagram to reflect the representation of the data on Figure 4A.

• The colour scheme of the label borders in Figure 4E does not match the colour of set for the right-most sets in both keratinocyte and fibroblast Venn diagrams, leading to confusion. – We adjusted the colours to match the diagram in Figure 4E.

• The figure legend for Figure 6E reads "Ingenuity Pathway Analysis (IPA) generated heat map of diseases and functions from the fast keratinocytes (abc) versus control (nsa)", but this is not what is displayed in the figure panel at all. - We apologise for the mistake; we corrected the legend.

• The methods section for the miRNA-CLIP should include information about the number of cells used in each experiment. – The change is highlighted in the Methods.

• The authors should carefully review the text for typos and misspellings and try to improve the readability of the manuscript__. – The manuscript has been carefully reviewed for these.__

**Referees cross-commenting**

I generally agree with the comments of the other reviewers: I think the paper is interesting and a valuable contribution to the field, particularly with regard to the role of miRNAs in the skin and the application of miRNA-CLIP to primary skin cells. While I did not remark on any gross overstatements, I agree that the data needs some strengthening to more adequately support some of the author's claims (I have tried to offer some realistic suggestions). There seems to be some difference of opinion regarding the data presentation, but all Reviewers thought it needed improvement in some capacity. While the way in which the paper is laid out and the results are displayed will be perceived subjectively by different readers, I believe it is in the best interest of the authors to try to reach the widest readership and thus I would maintain that the manuscript requires adjustments to increase clarity. I have tried to indicate specific sources of confusion and offer appropriate suggestions in my review.

Reviewer #3 (Significance (Required)):

This paper complements previous work that highlighted the role of miR-29 in desmosome formation in keratinocytes (Kurinna et al., 2014) and in skin repair in the mouse (Robinson et al., 2024), adding depth to these findings by understanding the molecular details of the key genes regulated by miR-29 in primary human skin cells. While the influence of miRNA on skin biology is well known, the details of which miRNAs and molecular mechanisms are involved are somewhat understudied. For this, I believe this paper, adequately amended, could be an interesting and useful contribution to the field and help highlight the role of miRNAs in the skin. This is also, to my knowledge, the first use of miRNA-CLIP in primary keratinocytes or fibroblasts and can provide a useful precedent for other studies looking to investigate miRNA interactomes in these cells.

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Referee #3

Evidence, reproducibility and clarity

Summary:

Thiagarajan et al. report on the functions and molecular targets of miR-29 in human primary skin cells. They first focus on the potential role of miR-29 in wound healing and in the adhesion of keratinocytes to the basement membrane using both in vivo wounding assays in the mouse and human cultures/skin equivalents. The authors report that miR-29 negatively affects adhesion in vivo and in vitro and characterise the transcriptome of fast and slow-adhering cells with or without miR-29inhibition. They proceed to identify miR-29 targets in three primary skin cell types (follicular keratinocytes, interfollicular keratinocytes and fibroblasts) by performing miRNA-clip. By comparing these targets to genes altered in keratinocytes with high adhesion capacity after miR-29 inhibition or fibroblasts after miR-29 inhibition, the authors describe a model in which miR-29 inhibits multiple adhesion-associated pathways in keratinocytes and negatively regulates proliferation and ECM deposition by dermal fibroblasts.

Major comments:

Overall, the paper is interesting, and the experiments performed are generally sensible for the questions being investigated. However, I thought the data was presented in a very confusing and unclear way, both in the main text and in the figures. I found the paper quite difficult to navigate, with contradictory statements between text and figures, cryptic or confounding graphs or arrangement of the figures and, in at least one instance, re-use of the same image with inconsistent labelling. The paper will thus greatly benefit from extensive tidying up and review of both text and figures to improve clarity. I highlight several points below, with many being related to this overarching issue, and I try to offer suggestions to the authors improve the quality of the manuscript.

• The stainings in Figure 1A should be repeated in intact sections as it is difficult to understand the exact distribution of miR-29 when the whole epidermis appears to be falling apart in the section. It is possible to see the pattern the authors are describing based on the current images, but it is not convincing. The authors should comment on the fact that miR-29 signal in the inset (at the edge of the wound) appears more basal than in the wound epidermis or in the unwounded. Quantifications and statistical analysis of the intensity and distribution of miR-29 for panels A and B and K10 for panel C will need to be included to help get a better sense of the data in its entirety and strengthen the observations. Importantly, Figure 1C is described as stainings after 6 days of skin equivalent cultures, but the same images are used in Figure 2A, where they are described as stainings after 11 days of culture. The authors should try to harmonise the data presentation so that the same data is not presented multiple times if possible. If repeated data presentation is necessary, it should be clearly stated and justified, and the authors should be careful to correctly indicate what the images represent.
• ITGB1 stainings in Figure 2 do not convincingly match the statements in the main text ("miRNA-29 mimic-transfected SE struggled to attach through the integrin beta1 (ITGB1)-mediated adhesion"). All stainings, or at least the most important ones, like ITGB1, should have quantifications and statistical analyses of their intensity and distribution to support any observations. Staining of basement membrane proteins at 6 days could help better visualise if indeed there are any attachment defects in the mimic-overexpressing cells. Since the authors use transient transfections, the significance ant interpretation of the stainings performed at 11 days will be reliant on the transfection strategy employed, the rate of proliferation of the cells, and the half-life of the proteins stained. The transfection strategy is not clearly explained (this is a more general problem, see below) and staining for miR-29 in these sections is necessary to ensure that the treatments are still in effect after this prolonged time in culture.
• The mimic/inhibitor transfection strategy employed by the authors throughout the paper is not clearly explained and this is a very important detail to understand the results of many of the assays they perform. The methods and Figures S2/S3 describe a 'double transfection' strategy for the inhibitors, but it is unclear if the same approach was used for the mimics (which is important since some of the experiments where they are employed have functional assays that can last longer than a week). Additionally, the strategy used for the inhibitors described in the methods section seems different than the one described in Figure S3. In the methods, the cells are transfected at day 1 and day 3 and collected for functional assays at day 5. Figure S3 instead shows two transfections at 'day 0' and an additional one at 'day 4' with miRNA levels measured at day 0 and day 8 (this bar plot should be modified to better reflect that measurements were only taken on specific days). The legend for Figure S3 reads "keratinocytes (P3/4) were transfected twice on subsequent days" and mentions "representative images of the cells from each treatment after the third transfection". This is all extremely confusing. The authors should make sure they explain what they did clearly and univocally, for both mimics and inhibitors, and they should add a time course with miR-29 levels following transfections of mimics and inhibitors covering the span of their longest assay.
• Figure 3 includes reference to morphological parameters that would be predictive of a keratinocyte ability to form a holoclone (red arrows). While the larger size and low nucleus-to-cytoplasm ratio of differentiated cells is well-established, to my knowledge there is no accepted consensus about strong predictive capacity of simple morphological parameters when it comes to holoclone formation.
• The inhibition of miR-29 in experiment 1 of the growth factor depletion assay seems to have failed according to Figure S2C, so the results of experiment 1 (-GF) in Figure 3 should be disregarded and the experiment repeated.
• The authors report reduced keratinocyte differentiation in the miR-29 inhibited cells. This statement is mostly supported by the cell number time course shown in Figure S3B, but this experiment is not mentioned in the main text, which instead focuses on (less reliable) morphological parameters alone. Moreover, Figure S3 only shows the morphology of cells at day 4 and does not provide any information about the cell morphology at day 6 or day 8 as suggested by the main text. Assessing differentiation based on morphology alone is prone to inaccuracy and while the cell number experiment is good support for the stated decrease in differentiation in the miR-29 inhibited cells, it should be complemented with differentiation marker staining and/or clonogenicity assays.
• The authors' claim that their results "revealed the direct in vivo targetome and functions of miRNA-29 in three types of cells isolated from human skin" is not accurate. While their experiments are indeed compelling, they are performed in cultured primary cells grown for at least 3 passages, which are akin, but not the same as cells in vivo and may behave differently. On a similar note, while there is some evidence from mouse that miR-29 may intervene in the regulation of the wound healing response in keratinocytes in vivo (Figure 1A), no analogous in vivo data is presented for fibroblasts. The authors should consider showing miR-29 stainings of mouse dermal fibroblasts and the potential variation in its level during wound healing. They should also show miR-29 stainings of normal human skin to confirm that its expression pattern mimics the mouse. If possible, they could also 'wound' human skin explants and check what happens during re-epithelielisation to miR-29 expression and to the key targets they identified (explants may be challenging to obtain, though). These experiments could provide some more compelling (though inevitably correlative) suggestion that miR-29 could intervene in the wound healing response in vivo in humans.

Minor comments:

• I would encourage the authors to avoid, when possible, the use of red/green colour palettes both in stainings and in graphs, as it makes the paper less accessible to colourblind individuals.
• I would suggest avoiding the use of "stacked" bar plots to show data as they might lend themselves to misinterpretation. It would likely increase clarity if the bars for different conditions were plotted next to rather than on top of one another.
• The first inset in Figure 1B does not appear to match the box in the lower magnification image.
• The title of the section "Rescue of miRNA-29 mRNA targets improves basal adhesion of human keratinocytes" should be changed, as no rescue experiments are performed. The term is used again in the text when referring to targets upregulated (or "de-repressed") after miR-29 inhibition, but it is not accurate and should be changed.
• The authors should specify the most important details of the adhesion assay in the Results section (for example the fact that the assay is carried out on fibronectin).
• The main text is imprecise when describing the RNAseq of fast/slow attaching keratinocytes, because it does not mention that the assay also includes miR-29 inhibition.
• The insets in the middle of Figure 3 are not described in the figure legend and it is unclear what they are meant to be highlighting. The Authors should also double-check the accuracy of the scale bars across Figure 3A.
• The pattern in the "abc" bars in Figure 3C makes it difficult to see the symbols.
• The area overlaps in the Venn diagram in Figure 4A should reflect the numbers. Since the diagram is comparing only three sets, accurate overlaps should improve the representation of the data.
• The colour scheme of the label borders in Figure 4E does not match the colour of set for the right-most sets in both keratinocyte and fibroblast Venn diagrams, leading to confusion.
• The figure legend for Figure 6E reads "Ingenuity Pathway Analysis (IPA) generated heat map of diseases and functions from the fast keratinocytes (abc) versus control (nsa)", but this is not what is displayed in the figure panel at all.
• The methods section for the miRNA-CLIP should include information about the number of cells used in each experiment.
• The authors should carefully review the text for typos and misspellings and try to improve the readability of the manuscript.

Referees cross-commenting

I generally agree with the comments of the other reviewers: I think the paper is interesting and a valuable contribution to the field, particularly with regard to the role of miRNAs in the skin and the application of miRNA-CLIP to primary skin cells.

While I did not remark on any gross overstatements, I agree that the data needs some strengthening to more adequately support some of the author's claims (I have tried to offer some realistic suggestions). There seems to be some difference of opinion regarding the data presentation, but all Reviewers thought it needed improvement in some capacity. While the way in which the paper is laid out and the results are displayed will be perceived subjectively by different readers, I believe it is in the best interest of the authors to try to reach the widest readership and thus I would maintain that the manuscript requires adjustments to increase clarity. I have tried to indicate specific sources of confusion and offer appropriate suggestions in my review.

Significance

This paper complements previous work that highlighted the role of miR-29 in desmosome formation in keratinocytes (Kurinna et al., 2014) and in skin repair in the mouse (Robinson et al., 2024), adding depth to these findings by understanding the molecular details of the key genes regulated by miR-29 in primary human skin cells. While the influence of miRNA on skin biology is well known, the details of which miRNAs and molecular mechanisms are involved are somewhat understudied. For this, I believe this paper, adequately amended, could be an interesting and useful contribution to the field and help highlight the role of miRNAs in the skin. This is also, to my knowledge, the first use of miRNA-CLIP in primary keratinocytes or fibroblasts and can provide a useful precedent for other studies looking to investigate miRNA interactomes in these cells.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #2

Evidence, reproducibility and clarity

Summary:

The article entitled, "miRNA-29-CLIP uncovers new targets and functions to improve skin repair", by Thiagarajan et al. describes the characterization of the functions of miRNA-29 in keratinocytes and fibroblasts, its RNA interactors and potential mechanisms of action. Using candidate interactors and 2D cell culture and 3D skin equivalents combined with loss-of-function (inhibitor) and gain-of-function (mimic), and changes in expression analyses, the authors conclude that the major function of miRNA-29 is to regulate cell-substrate adhesion.

Major comments:

• While the interactors and expression changes are useful resources, the claims and the conclusions that are based on them are exaggerated. The treatments are associated with changes in expression, but no functional data support the conclusions. Additional functional experiments are required to assertively make the claims. The title is misleading when stating "to improve skin repair" and the abstract also makes some bold general claims, which are tangentially supported by the findings. For example, "protein folding" only appears in the abstract and "RNA processing" is in the abstract and figures but not referred to in the text.
• The authors may want to tune their language that their data suggest the conclusions as opposed to being definitive and assertive. This should be done in the Discussion, while the Results should represent the direct conclusions.
• A couple of examples to the above, in the conclusion to section 1 of the Results, how was the "loss of basal adhesion" assessed? Is it by beta1-integrin localization changes? Also, how is "growth" defined"? proliferation is not changed and a more accurate way to describe the result is to refer to thickness.
• The images in Fig 1C are reused in Fig 2A, where new examples should be shown instead.
• Fig 1C and Fig 2A are not quantified to make the claims about premature differentiation and integrin expression changes.
• Fig 3: It is not clear from the figure legends what statistical methods were used for which experiment or how many times the experiment was performed (not just biological replicates), especially given the variability among experiments in Fig 3C.

Minor comments:

• The Introduction is focused on methodology and should include elements that pave the way to the Results. Some information that belongs in the introduction are present in the Results section. In this respect, please define the miRNA processing Dicer pathway and its components in the introduction so that the reader can follow the nomenclature (AGO2, RISC, etc.). Also, introduce human skin equivalents or organotypic culture as a model system in the Introduction.
• Some information in the Results belongs in the Introduction, for example, the first seven lines of the Results section.
• The authors might want to consider including quantifications in the main figures, so they are immediately apparent to the reader, for example, Fig S1C. Also, Fig S2B is an important measure for the immediate outcome of the treatment on miRNA-29.
• Please change "imidiate" to "immediate", "sculp" to "scalp", "has to be releaved of miRNA-29-mediate repression" to "has to be relieved of miRNA-29-mediated repression"

Referees cross-commenting

I agree with my colleagues' assessments and suggestions. The miRNA-CLIP data in keratinocytes and fibroblasts are important resources. The figures and text require reconsideration to more accurately represent the data as detailed in our collective reviews

Significance

The study utilizes 2D and 3D cultures and presents an important resource for miRNA-29 interactors in keratinocytes and fibroblasts, as well as the expression changes associated with its inhibition and overexpression. However, the conclusions are exaggerated and based on expression changes. If the conclusions are rephrased, the findings would be of interest to a broad audience interested in miRNA, cell adhesion and epithelial and mesenchymal biology.

My expertise is in skin development and maintenance, genetics and cell biology. I have limited knowledge in RNA biology.

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Referee #1

Evidence, reproducibility and clarity

miRNAs are important for the control of many cellular processes, with the miR-29 family of miRNAs implicated in the regulation of cell growth in different cell types in both the epidermis and dermis of the skin. However, the roles of miRNAs in specific cell types in general, and of the miR-29 family in the skin in particular, are currently unknown. Here, the authors use a range of cellular and molecular techniques, including miRNA cross-linking and immunoprecipitation (miRNA-CLIP) and antisense oligonucleotides (ASO), as well as RNASeq, qPCR, Western blotting, in situ hybridization, adhesion and ECM assays, ELISA and immunofluorescence, to interrogate the roles of the miR-29 family of miRNAs in controlling cell growth in epidermal keratinocytes and dermal fibroblasts, using 2D and 3D ex vivo models. The coupling of miR-CLIP with functional assays allowed the authors to identify both miRNA-mRNA complexes, and the biological pathways that these ultimately manipulate.

The authors report the identification of unbiased, tangible miR-29/mRNA pairs, together with functional roles in cell adhesion, ECM regulation and fibroblast proliferation, that are distinct between keratinocytes and fibroblasts. miR-29 is identified as a valuable target for interventions that seek to promote healthy skin regeneration, including applications for wound healing. Many of the pathways identified here have previously been described, but the novelty of this manuscript lies in the innovative combination of miR-CLIP with functional assays, the application of these in combination to specific cell types, the identification of miR-29 as a novel master regulator of epidermal keratinocyte adhesion via a range of different pathways, and the demonstration that miR-29 inhibition in fibroblasts can influence keratinocyte adhesion via paracrine signalling.

The experiments are well designed and reported. The interpretations are sound and appropriate for the data presented (though see the comment on potential normalisation of ECM data to cell numbers in cultures for the miR-29 mimic/inhibitor data for fibroblasts and the query about the number of direct miR-29 targets in fibroblasts that are ECM-related).

Major Comments:

I have no major concerns to raise over this manuscript. The claims and conclusions are supported by the data and no additional experiments are required (though please note the comment on normalisation mentioned above and detailed below). The methods are clearly reported and statistical reporting is adequate.

Minor Comments:

Pg3, 7th line from the bottom: "processed into three functional miRNA..." - minor edit needed here, it looks like there's a word missing somewhere.

Pg3, last line on the page: "results supported..." - is there a missing 'are' here?

Pg5, 15th line of the main text: "of miRNA-29-mediate repression..." - is there a missing 'd' here ('-mediated...')? There is lots on minor presentation errors like this throughout the manuscript - I won't point them out exhaustively, but the manuscript needs a good thorough proof-read, maybe from a fresh pair of eyes?

Fig. 1C: Can the figure be edited to better highlight the basal layer with lack of (nsm image) and expression of (abm image) K10? Maybe a box around that layer, rather than the current arrows only on the abm image (which are not particularly closely indicating the basal layer)?

Fig. 2 legend should include definitions of abbreviations shown on the figure.

Pg8/Fig. 4A: Can the reporting of shared transcript targets of miR-29 in IFK/HFK/DF cells be better communicated? Maybe just adding the actual percentage overlap in transcriptomes for IFK/HFL and keratinocytes/fibroblasts to the main text would help. Similarly, I think a direct report somewhere (in the main text?) of total number for relevant groups shown in Fig. 4E would also be useful - e.g. there are 45 transcripts that are direct targets of miR-29 in keratinocytes and also associated with ECM, and 190 that are direct targets of miR-29 in keratinocytes and also associated with cell adhesion, but these number are difficult to come by quickly at the moment. It would be nice to be able to quickly compare these numbers for keratinocytes to their equivalents for fibroblasts.

Fig. 4B: It's interesting that ~15% of miR-29 binding targets identified using miR-CLIP are not predicted targets based on TargetScan/microT-CDS. I'd like to see a little more information on this added to the manuscript - perhaps listing some of these or including a table of them? And perhaps some discussion of this could be added also.

Fig. 4E: I would be nice to see the Venn numbers for keratinocyte proliferation (either is a supp figure, or addition to the main text?), to help illustrate the lack of a role for miR-29 in the regulation of keratinocyte proliferation.

Fig. 4E: Is the reported number of direct miR-29 targets in fibroblasts that are ECM-related correct? This number is reported as 10 in the main text (pg10, 3rd paragraph), but it looks like 10 is only for direct miR-29 targets in fibroblasts that are ECM-related AND related to proliferation. Should this number be 58? The 10 that are direct miR-29 targets in fibroblasts that are ECM-related AND related to proliferation can be reported in the next sentence, where this group is specifically referred to.

Fig. 7 (and related main text): Did you take any steps to normalise ECM measurements to cell numbers present in cultures in the miR-29 mimic/inhibition experiments in fibroblasts? This should really be included as it would provide an answer to the speculation of whether the effects of manipulating miR-29 on ECM are due to proliferation or classical pro-fibrotic pathways.

Fig. 8E: The upper and lower image need to have nsa/abc labels added to them.

Pg12, 1st sub-heading: typo (cell-specifcic).

Referees cross-commenting

All reviews appear to be fair and balanced to me. I agree that in places wording could be amended to temper the strengths of some claims, and it would also be nice to see some additional functional assays included, to complement the adhesion and ECM deposition assays that are currently presented, though I do not think this should necessarily be a requirement for publication and could be included in subsequent follow-up work from the group. I did not spot the reuse of images between Fig. 1 and 2, but clearly this should be addressed - either by replacing one set of images, or by removing the relevant panels from Fig. 1 and changing in-text reference to guide the reader to Fig. 2A. I also agree that it would be nice to see miR-29 staining of mouse dermal fibroblasts during wound healing, to complement the images already shown for keratinocytes, and to see miR-29 staining in human skin.

Significance

miR-CLIP is a powerful, recently developed technique, with enormous promise for the identification of true miRNA-mRNA pairs, that has not yet been widely adopted by the research community. As such, its application here is itself relatively novel, adding enormously to our existing knowledge of likely miR-29 targets, providing tangible information in miR-29/mRNA pairs in specific cell types in different layers of the skin, but also further adding novel functional information to this, with demonstrations of the regulation of specific relevant biological pathways through manipulation of targets identified using miR-CLIP. The methods are sound (and impressive), results are reported well and not over-interpreted. There is the potential for better characterisation of the relative importance of canonical pro-fibrotic pathways vs proliferation-related effects on ECM production, and this should not be difficult to address. This paper will be on interest to a wide readership, including those engaged in fundamental research and clinicians.

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Reply to the reviewers

1. General Statements

We are very grateful for the three reviewers’ positive and considered comments. We copy specific comments below in bold font, and address them in turn including quotations from the revised manuscript in italics.

2. Description of the planned revisions

One Supplementary Figure could be copied from an earlier manuscript to show the model circuits, please see Reviewer 3 comment 1, below.

3. Description of the revisions that have already been incorporated in the transferred manuscript

Reviewer 1

Major 1. In this work, the authors observed discrepancies between the estimated and actual values of DNA-binding dissociation constant (Kd). Such inconsistencies may arise if the model used to simulate Kd omits certain regulatory mechanisms. For example, previous studies (_https://doi.org/10.1371/journal.pcbi.1008340, ____https://doi.org/10.1098/rsfs.2021.0084_) showed that when specific gene regulatory mechanisms are missing, the dissociation constant required for generating oscilla-tions can be underestimated. Thus, the inconsistency between the estimated and ac-tual Kd values might result from missing mechanisms in the model. It would be benefi-cial if the authors could discuss this possibility. __

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We thank the reviewer for these examples, which illustrate the relevant point that multiple biochemical processes can contribute to the non-linearity required to simulate a particular clock behaviour within biochemically-reasonable parameter values. We now cite both, along with the original Buchler & Louis paper on the titration mechanism in general, as follows:

“It is possible that the measured, bulk clock protein levels might over-estimate the protein available for promoter binding due to mechanisms absent from the model, such as protein partitioning outside the nucleus (Yakir et al, 2009), protein titration (Buchler & Louis, 2008), clustering of proteins within the nucleus, a processing step akin to the formation of a smaller EC pool from a fraction of the bulk LUX protein or any combination of these mechanisms (Jeong et al, 2022b; Yao et al, 2022).”

__ Minor 1. The order in which the figures are mentioned does not match the order of the figures. Please adjust the sequence of the figures accordingly. __

• The amalgamated PDF for review presented the Figures and Supplementary Figures in the order of citation, which we intended for the reviewers’ convenience. As this didn’t help two of the reviewers, they are now in numerical sequence.

__ In the last paragraph of Introduction, the authors state, 'The absolute numbers of proteins directly constrain their possible biochemical activities (Kim & Forger, 2012)'. It would be helpful to also cite Jeong et al. (_https://doi.org/10.1073/pnas.2113403119_), who showed that two circadian neuronal groups in Drosophila, containing different amount of clock proteins, exhibit distinct molecular properties within the circadian clock. __

• Added a citation to this relevant example later in that sentence.

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__ In the title of the first section of Results, 'Predicting clock proteins levels' should be revised to 'Predicting clock protein levels.' __

• Done

__ The description of the results in Figure 4 is unclear. Please, refer to the color and shape of the points when explaining the results for better clarity.__

• The legend of Figure 4 now refers to both characteristics. Reviewer 2

__2.1. Limited Generalizability of Some Assumptions: __

__The translation and degradation rate assumptions are based on data from specific temperature and light conditions, which may not generalize well to other growth conditions. The authors could address this point by explicitly stating this limitation and explaining how variable conditions would affect the model's underlying assumptions. __

• To address this point, we now note in Discussion: “For example, the reporter assays could quickly test protein numbers under different conditions from those reported here, to understand the biochemical mechanisms for the canonical ‘temperature compensation’ of circadian period in constant conditions (as modelled in Gould et al, 2013) and/or the adaptation to fluctuating, natural conditions (see Future perspectives: models informed by genome sequence, below).”

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__2.5. Simplified Model for Translational Efficiency: __

__The model simplifies translational efficiency, which may not fully capture the complexity of clock protein synthesis. A more comprehensive approach, considering factors like ribosome density variation across transcripts, would add depth to the protein quantification model. Experiments are not required here. But it'd be nice to explain how a more complex model involving differential ribosomal density per transcript could affect the overall conclusions. __

• The ‘simple model’ is intentionally simple. We note in the Results that it even ignores the published light/dark-regulation of translation rate, both generally in Arabidopsis and specifically for LHY. To address this point, we have added in Discussion, “In other words, the bulk levels of these clock proteins might be rather simply regulated. The simple model’s approach could justifiably be repeated to estimate the levels of other proteins, and extended to test where more complex biochemical mechanisms, such as translational regulation, are functionally significant.”

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__ Minor Points __

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__- Figure Legends: Several figures lack sufficient detail in legends, particularly Figures 3 and 5, where the methodology for generating the predicted protein levels and Kd values could be described a bit more, without majorly elongating the caption length. __

• Both legends have been updated. However, the methods are described in detail in the Supplementary Information, which provides much more space. - Unclear Units in Supplementary Table 1: Some units in Supplementary Table 1 for translation and degradation rates are not clearly specified.

• Units seem clear in the column headings, as follows:

s (proteins per mRNA per hour)

k or klight (per hour)

kdark (per hour)

The reviewer might be highlighting that some values of kdark were given as “-“ because that protein did not have light-regulated degradation in the simple model, so degradation rate was just k rather than klight and kdark. This notation has been updated to NA, with an explanatory note in the supplementary table legend.

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Reviewer 3

1. __ I would have appreciated inclusion of an additional figure describing the U2019 and U2020 that were previously published by this group in 2021, along with a brief clarification of the differences between the simple and full versions of these models (Beyond the small summary presented in Figure 8). __ Supplementary Figure 3 of Urquiza and Millar 2021 shows simplified circuit diagrams of the two models and could be added as a new Supplementary Figure in this manuscript, as the editor prefers. To address this point, we added an introduction to the detailed models in the Results: “Our detailed models of the clock gene circuit (see Introduction) are not driven by rhythmic data input like the simple model, but rather use ordinary differential equations to recapitulate the dynamics of each RNA and protein component in the clock circuit, along with their interconnected feedback loops and their regulation by light signals. The models autonomously generate rhythmic patterns of RNA and protein expression that match the rhythmic data. The gene circuits in models U2019 and U2020 differ only in the regulation of daytime processes, involving LHY/CCA1 and the PRR genes (Urquiza-García & Millar, 2021). The circuit of U2019 is closer to its antecedent model P2011 (Pokhilko et al, 2011), using gene activation, whereas U2020 uses repression (for circuit diagrams, see Supplementary Figure 3 of (Urquiza-García & Millar, 2021). Repression is better supported by molecular data but U2020 simulations fit the data no better than, or slightly worse than, the activation-based model U2019 (consistent with Fogelmark & Troein, 2014), so we use both circuits here.”

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__Minor comments __

__Supplemental figure 2 is partially cut off __

• Corrected. Only the edge of a label was affected. It would be useful if figures/supplemental figures were provided in order.

• Corrected, see reviewer 1 above.

4. Description of analyses that authors prefer not to carry out

Reviewer 1

N/A

Reviewer 2

__2.2. Discrepancies in CCA1 Binding Affinity: __

__The model's simulated Kd values for CCA1 largely deviate from empirical measurements, suggesting missing mechanisms that may impact protein binding affinity. This might be due to some structural or environmental factors influencing CCA1 binding. No experiments are needed here but some plausible explanations would enhance the manuscript. __

• This point is addressed in the section ‘Future perspectives: investigating Kd in vivo’, now enhanced by our response to reviewer 1’s major comment, as noted above. __2.3. Limited Data for Evening Complex Proteins: __

__The model assumptions for ELF3, ELF4, and LUX rely on estimated degradation rates, which could introduce inaccuracies in the predictions. Empirical quantification of these rates would strengthen the reliability of these protein dynamics in the model. If these experiments are too resource and time intensive, then include some explanation of how changing these estimated degradation rates would affect the overall result. __

• We assume that the reviewer is referring to the k parameters of the simple model driven by RNA data, as in Figure 2, which gives the predicted protein levels that we compare to measured protein levels in Table 1. Both the prior degradation rate data and our NanoLUC reporter measurements are strongest for LHY, CCA1, PRR7 and TOC1, so these are our focus. New measurements of degradation rate for ELF3, ELF4 and LUX are indeed beyond our scope. Our reporter methods might facilitate future measurement of such parameters by other researchers. In the Supplementary Information, we outline the estimation of degradation rates k, which returned biologically plausible protein half-lives for LUX = 3.7 h, ELF4 = 1.3 h and ELF3 8.7 h. We have no data for ELF4 and we highlight the specific limitations of our ELF3 and LUX data in the Results and Discussion text, Table 1, Methods and Supplementary Information. Taking the in vivo data for ELF3 for example (Table 1), the protein levels predicted by the simple model using that degradation rate were within 6% to 7% of the measured levels at the peak and at the trough under LD. This independent result supports the estimated degradation rate: varying the estimated degradation rate for ELF3 would not maintain a prediction so remarkably close to the data.

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__2.4. Unexplained Variability in Reporter Data: __

__The NanoLUC reporter assays show some variability that the model does not account for, possibly due to factors like differential protein stability or folding in vivo. Further tests across different expression contexts, or including protein stability measurements, would clarify these inconsistencies. If these experiments are too resource and time intensive, then include some explanation of how changing these estimated degradation rates would affect the overall result. __

• This comment cannot be addressed without knowing which of the many possible data series the reviewer is referring to, and whether the variability of interest is in level, timing or a higher-order dynamic behaviour. For example, we discuss three specific instances where reporter and model behaviour differs, in detail, in Discussion section ‘Refining the modelled protein profiles’ (726 words).

Reviewer 3

__ It would have been useful to quantify the mRNA expression levels in the rescued transgenic lines to enable direct comparison to WT. The use of multiple independent transgenic lines supports the authors' conclusions but this characterisation would aid future research. __

The proposed study most directly addresses whether RNA from the reporter transgene is functionally equivalent to wild-type RNA, whereas the focus of this article is at the protein level. As the reviewer notes, the proposed study would principally be an aid to future research, so we prefer not to start that additional experimental work.

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Referee #3

Evidence, reproducibility and clarity

Summary

This is a valuable manuscript that begins to factorise the plant circadian model according to estimated protein translation and degradation rates. These models are iterative by nature, but the latest models provide a significant advance in our understanding and highlight avenues for future exploration. The use of Nanoluc protein:reporter fusions enables estimation of protein abundance, providing additional support for the modelled biological process.

The latest models highlight discrepancies between protein abundance predicted in the model compared to the experimental evidence, and sensible suggestions are discussed to prioritise experiments to enable greater biological understanding.

Major comments

1. I would have appreciated inclusion of an additional figure describing the U2019 and U2020 that were previously published by this group in 2021, along with a brief clarification of the differences between the simple and full versions of these models (Beyond the small summary presented in Figure 8).
2. It would have been useful to quantify the mRNA expression levels in the rescued transgenic lines to enable direct comparison to WT. The use of multiple independent transgenic lines supports the authors' conclusions but this characterisation would aid future research.

Minor comments

Supplemental figure 2 is partially cut off

It would be useful if figures/supplemental figures were provided in order.

Significance

This work extends models of the plant circadian system to assess absolute protein numbers. This enables the biological 'plausibility' of the model to be assessed and also highlights where the model diverges from experimental data, indicating where additional understanding is required.

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Referee #2

Evidence, reproducibility and clarity

1. Summary of this work

This manuscript delves into the Arabidopsis circadian clock by addressing a major gap in plant gene circuit models-particularly, the lack of absolute units for protein quantification, which has historically hindered comparisons to biochemical data. By recalibrating two mathematical models of Arabidopsis thaliana's circadian clock from relative to absolute units, the authors introduce a framework that allows protein levels to be quantified in terms of copies per cell. This approach facilitates more direct comparisons between model predictions and empirical measurements.

The core of the study involves both analytical predictions and experimental validation to quantify protein levels for key clock proteins (such as LHY, CCA1, PRR7, and TOC1) using RNA data and luciferase reporter protein fusions. The simple model predicts the abundance of clock proteins, suggesting that the protein concentration may reach up to 100,000 copies per cell, which was then verified through experiments involving NanoLUC reporters. The recalibration of detailed mathematical models enabled the calculation of DNA-binding dissociation constants (Kd) based on empirical data, establishing a bridge between theoretical and experimental insights for understanding plant circadian rhythms.

The authors further explore how recalibrated models align with data by focusing on Kd values associated with DNA binding, particularly with LUX and CCA1 proteins. In vitro binding assays validated these predictions, while certain discrepancies emerged for CCA1 binding, implying other mechanisms could be influencing the observed results. Importantly, the recalibrated models provide a more realistic representation of protein-DNA interactions within the circadian clock, and the framework can be applied to understand other plant gene regulatory networks.

Overall, the authors demonstrate how absolute protein quantification can advance our understanding of circadian rhythm dynamics in Arabidopsis. This study highlights the broader applicability of their methods, suggesting potential adaptations for investigating gene regulation across plant species and evolutionary contexts. The integration of empirical data with mathematical models introduces a new standard for rigor in plant gene circuit modeling and opens up avenues for exploring gene regulation in crop species and adaptive evolution in plants. 2. Major points

2.1. Limited Generalizability of Some Assumptions:

The translation and degradation rate assumptions are based on data from specific temperature and light conditions, which may not generalize well to other growth conditions. The authors could address this point by explicitly stating this limitation and explaining how variable conditions would affect the model's underlying assumptions.

2.2. Discrepancies in CCA1 Binding Affinity:

The model's simulated Kd values for CCA1 largely deviate from empirical measurements, suggesting missing mechanisms that may impact protein binding affinity. This might be due to some structural or environmental factors influencing CCA1 binding. No experiments are needed here but some plausible explanations would enhance the manuscript.

2.3. Limited Data for Evening Complex Proteins:

The model assumptions for ELF3, ELF4, and LUX rely on estimated degradation rates, which could introduce inaccuracies in the predictions. Empirical quantification of these rates would strengthen the reliability of these protein dynamics in the model. If these experiments are too resource and time intensive, then include some explanation of how changing these estimated degradation rates would affect the overall result.

2.4. Unexplained Variability in Reporter Data:

The NanoLUC reporter assays show some variability that the model does not account for, possibly due to factors like differential protein stability or folding in vivo. Further tests across different expression contexts, or including protein stability measurements, would clarify these inconsistencies. If these experiments are too resource and time intensive, then include some explanation of how changing these estimated degradation rates would affect the overall result.

2.5. Simplified Model for Translational Efficiency:

The model simplifies translational efficiency, which may not fully capture the complexity of clock protein synthesis. A more comprehensive approach, considering factors like ribosome density variation across transcripts, would add depth to the protein quantification model. Experiments are not required here. But it'd be nice to explain how a more complex model involving differential ribosomal density per transcript could affect the overall conclusions. 3. Minor Points - Figure Legends: Several figures lack sufficient detail in legends, particularly Figures 3 and 5, where the methodology for generating the predicted protein levels and Kd values could be described a bit more, without majorly elongating the caption length. - Unclear Units in Supplementary Table 1: Some units in Supplementary Table 1 for translation and degradation rates are not clearly specified.

Significance

1. Overall Evaluation

The recalibration of models to absolute units for protein quantification is a novel advancement in the field, allowing more direct comparison to experimental data. The study's combination of modeling and empirical validation is robust, and the use of quantitative NanoLUC reporters adds rigor to the experimental design. The study offers a clear protocol for estimating Kd values by integrating Protein-Binding Microarray (PBM) data and Surface Plasmon Resonance (SPR) data, which is a significant methodological contribution. These approaches could become a new standard for studies aiming to link molecular and phenotypic traits in plants. Moreover, through NanoLUC reporter assays, the study provides empirical data for protein levels that align closely with the model's predictions, enhancing the validity of their model. Additionally, by creating a framework that can be adapted to other plant gene regulatory networks, the authors extend the impact of their work beyond the Arabidopsis circadian clock, hinting at potential applications in agriculture and crop science.

I recommend this study with a minor revision, addressing the points below.

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Referee #1

Evidence, reproducibility and clarity

Major

1. In this work, the authors observed discrepancies between the estimated and actual values of DNA-binding dissociation constant (Kd). Such inconsistencies may arise if the model used to simulate Kd omits certain regulatory mechanisms. For example, previous studies (https://doi.org/10.1371/journal.pcbi.1008340, https://doi.org/10.1098/rsfs.2021.0084) showed that when specific gene regulatory mechanisms are missing, the dissociation constant required for generating oscilla-tions can be underestimated. Thus, the inconsistency between the estimated and ac-tual Kd values might result from missing mechanisms in the model. It would be benefi-cial if the authors could discuss this possibility.

Minor

1. The order in which the figures are mentioned does not match the order of the figures. Please adjust the sequence of the figures accordingly.
2. In the last paragraph of Introduction, the authors state, 'The absolute numbers of proteins directly constrain their possible biochemical activities (Kim & Forger, 2012)'. It would be helpful to also cite Jeong et al. (https://doi.org/10.1073/pnas.2113403119), who showed that two circadian neuronal groups in Drosophila, containing different amount of clock proteins, exhibit distinct molecular properties within the circadian clock.
3. In the title of the first section of Results, 'Predicting clock proteins levels' should be revised to 'Predicting clock protein levels.'
4. The description of the results in Figure 4 is unclear. Please, refer to the color and shape of the points when explaining the results for better clarity.

Significance

In the manuscript by U. Urquiza-Garcia et al., entitled "Abundant clock proteins point to missing molecular regulation in the plant circadian clock," the authors refactored two models of the plant circadian clock to use absolute units, allowing direct comparison with biochemical data. This study significantly advances the integration of experimental data into computational models.

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Reply to the reviewers

'The authors do not wish to provide a response at this time.'

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Referee #3

Evidence, reproducibility and clarity

In this manuscript, Takenaka et al revisits the role of the maternal-effect gene abnormal oocyte (ao) in the regulation of canonical histone gene expression in Drosophila. The authors generated both a knockout allele of ao and a V5-tagged ao allele using CRISPR/Cas9. They show that (i) loss of ao results in maternal-effect lethality; (ii) Ao protein is localised to histone locus bodies; (iii) an increased dosage of AO heterochromatin partially rescues maternal-effect lethality. These results are consistent with previous reports. However, this study convincingly demonstrates that ao is not required to suppress histone expression, which is in contrast to previous suggestions.

The manuscript is well structured and written. The conclusions are supported by the data. However, I have a few comments that may help to improve the manuscript:

1. Localisation of the Ao-V5 protein: Ao-V5 co-localises with Mxc, a marker for the histone locus body. The authors state that some Ao-V5 puncta are without Mxc colocalisation. As far as I can see, it looks more like the other way around - Ao-V5 co-localises with Mxc, but there are some Mxc-marked HLBs without Ao-V5, which would imply that Ao-V5 does not have any other additional genomic loci as suggested. Therefore, I think a quantification of the existing images would be beneficial.
2. qPCR analysis of histone gene expression in ao mutant ovaries shows that histone H1 RNA is slightly upregulated, while all other canonical histones remain unchanged compared to control. However, Western blot analysis shows a significant decrease in histone H3 protein levels (~50%), which the authors describe as 'slightly decreased'. This result needs to be considered in more detail, as it would suggest that Ao is required to maintain (at least) histone H3 protein levels?
3. Some of the supplementary figures are not referenced in the main text (only in the figure legends).
4. Ao deletion (Figure S1): I suggest including the Sanger sequencing results (as mentioned in the text) to demonstrate that neighbouring gene sequences remain unaffected.

Referees cross-commenting

I also think that all reviews are consistent with only a few suggestions for improving the manuscript.

Significance

Strength: This paper shows that ao is not a histone gene repressor, as previously thought, which is an important finding. It also describes new alleles of ao, which are valuable tools for the Drosophila research community.

Limitations: The study lacks insight into the actual molecular role of ao. The finding that H3 protein levels are considerably reduced in ao ovaries could be further investigated.

Advances and audience: As described above, this paper extends our knowledge of the role of ao by showing that it is not a histone gene repressor, which is of interest to the scientific community working in the fields of chromatin and development.

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Referee #2

Evidence, reproducibility and clarity

This study by Takenaka et al. explores the role of the abnormal oocyte (ao) gene in Drosophila melanogaster. Historically, ao was thought to regulate histone gene expression, causing maternal-effect lethality when disrupted. However, the lack of critical reagents including some alleles limited further testing of this hypothesis. In this study, the authors created new CRISPR/Cas9-generated ao knockouts and an epitope-tagged allele to clarify its role. Findings confirmed ao's maternal-effect lethality, which can be rescued by reducing histone copy number or increasing Y-chromosome heterochromatin. Contrary to previous studies, they found ao does not repress histone transcript levels, leaving its lethality mechanism unresolved. This work challenges the previously assumed role of ao in histone regulation at the level of transcription.

Major comments: Overall, this manuscript was a joy to read, and the experiments are well controlled and done and presented in a clear and precise manner.

Minor comments: My only two suggestions are if there is a way to include that ao is a conserved gene in the introduction that may broaden the readership of this manuscript. Also, there are many supplementary data panels showing Ao expression that could be condensed.

Referees cross-commenting

All the comments sound good to me.

Significance

The significance of the study lies in its challenge to the previously accepted role of ao gene in regulating histone expression. While earlier research suggested ao acted as a repressor of histone expression, this study, using new and well-controlled tools, did not find evidence supporting that role. The findings not only question the previous assumptions but also emphasize the complexity of ao's function, highlighting the need for further exploration of the mechanisms underlying maternal-effect lethality and its genetic interactions with heterochromatin and histone genes. This will contribute to a better understanding of gene regulation during early development.

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Referee #1

Evidence, reproducibility and clarity

Summary: In this manuscript Takenaka et al address the function of the gene abnormal oocyte (ao, formerly abo) in Drosophila oogenesis. Previous reports implicated ao as a negative regulator of histone biogenesis based on its localization to the histone locus body (HLB), rescue by reduction of histone copy number, and reports that histone production is increased in ao mutants. Only one of the two original ao mutants are still available and the other has been lost. The authors sought to confirm ao's mechanism of action by generating a CRISPR null allele for ao. They also generate a tagged rescue construct which allows them to visualize ao localization. First, they confirm that a clean deletion of ao does indeed confer maternal lethality and that their tagged construct does localize to the HLB. Next they test histone expression levels in ao null ovaries and find that histones are not, in fact, overexpressed at the RNA or protein level. They also test the RNA levels in unfertilized embryos and find that H2B is decreased rather than increased. Finally, they confirm the previous report that histone deficiency or reduced copy number reduces ao's maternal effect lethality indicating that there is a relationship between ao and the histone locus.

Major comments: I have only one suggestion and a possible extension of the work.

Suggestion: Since ao localizes to the HLB it presumably only affects the replication coupled histones. It would be very interesting to know how replication independent histone RNAs change (or do not) in ao null ovaries.

Extension: (This may be beyond the scope of this work). One wonders if the partial rescue of ao mutants by the histone deficiency/reduced histone copy number is due to a change in the localization of other HLB components in the absence of ao. To test this the authors could image Mxc in the ao null.

Minor comments: None

Significance

General assessment: Overall, I think that this is an important story that sets the record straight about the molecular function of ao, particularly because it was recently suggested as a tool to manipulate histone levels. The experiments appear to be carefully done and provide good support for the claims. The manuscript is clearly written and easy to interpret.

Advance: The main takehome of this story is that the previously described and long-standing mechanism of ao on histone biogenesis and oogenesis is flawed. This story will be the starting point for future characterization of this mutant.

Audience: Those interested in histone biogenesis, especially in flies, will be interested in this story. It does not provide an alternative molecular mechanism (nor does it claim to) which will somewhat limit the general interest. However, this story provides a vital correction to the record.

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Reply to the reviewers

Reviewer #1 The manuscript by Consorte and coworkers focusses on the role of the tudor-doman containing proteins, Tdrd6a and Tdrd6c in Germplasm stability in zebrafish. Single mutants for each protein do not affect germ plasm stability or germ cell fates, Through the use of double mutants lacking the function of both proteins, the authors find that germ plasm complexes form and the Balbiani body of mutant oocytes are unaffected. However, the germ plasm complexes disperse during early development, leading to loss of primordial germ cells and eventually sterility of adult double mutant fish. Domain analysis of Tdrd6c showed that the Tudor domains are not required for interactions with the germ plasm organiser Bucky ball (Buc), but function in germ plasm dynamics. The prion-like domains of Tdrd6c were found to be required for interactions with Buc. Tdrd6c protein localizes to perinuclear granules in germ cells, but not in the Bb, unlike Tdrd6a. The manuscript is generally well done, and the findings are of interest to researchers interested in germline development, RNA-protein complexes and intrinsically disordered /prion-like proteins. Some further work would bolster the findings and support the main conclusions better. Major comments:

• Regarding the 6a6c double mutants, figure 3 and S4 show preliminary evidence that the gonads are severely underdeveloped. However it is unclear when/what stage the gonads are arrested and whether there is a loss of germline stem cells. This can be shown.

Reply:

As the PCGs are already missing at 1 day post fertilization, there will be no germ cells in the gonads, leading to the rudimentary gonad structures we show in Figure S4. This phenotype has been described before by us and others (PMID: 17418787; PMID: 12932328; PMID: 15728735). Hence, a tissue analysis would not yield any further information.

• The authors show that germplasm forms in single mutants for 6a and 6c and Buc-eGFP reporter transgene localization does not show overt germpalsm defects in the single mutant embryos. But PGC numbers are reduced by larval stages. Are germplasm RNAs destabilised to some extent in the single mutants? This should be examined.

Reply:

Thanks for bringing up this interesting point. In Roovers et al. (PMID: 30086300) we did an extensive analysis in tdrd6a mutants in this regard, showing that indeed germ plasm transcripts were generally reduced in PGCs. We do not plan to repeat such analysis for tdrd6c mutants. However, we propose to address this by smFISH experiments on known germ plasm transcripts, like vasa and dazl. This would not only reveal potential abundance issues, but also localization issues.

• Relevant to the PGC defects shown in Fig 3, is there is more male bias or earlier defects in the 6c single mutants ? What is the tissue shown in Fig S4 B in the double mutant? Some sections and markers would be useful.

Reply:

In figure 3D that no male bias was observed in the offspring of single mutant females. While we cannot exclude earlier defects, these will be minor as no fertility defects have been noted. Hence, we do not plan to look at gonad development in offspring of single mutants.

• Regarding expressing of the Tdrd6c constructs in BmN4 cells: the expression levels do not appear uniform and the background fluorescence is very high in some images, making comparisons and differences in expression levels/distribution difficult to see.eg Fig S6. These images (eg S6 6c and 6a6c double mutant images) should be assessed carefully and replaced with better representative images.

Reply:

Thank you for pointing this out. We fully agree, and we plan to quantify the images we have on these experiments to provide a more complete and possibly less biased results.

Minor comments:

• Fig 1 a: spelling error in the schematic "Antibody Binging site" should be changed to "Antibody binding site".

Reply:

This will be fixed.

Reviewer #1 (Significance (Required)): How germ plasm stability is controlled is not well understood. In this manuscript, the role of the related Tudor-domain proteins, Tdrd6a and 6c proteins are compared. The proteins have redundant roles in germplasm stability and germ cells in early zebrafish embryos, and the combined loss of the proteins leads to germplasm destabilisation, germ cell loss and sterility. The manuscript is generally well done, and the findings are of interest to researchers interested in germline development, RNA-protein complexes and intrinsically disordered /prion-like proteins. Some further work would bolster the findings and support the main conclusions better (as detailed in major and minor comments above).

Reviewer #2

In this report, the authors utilize the zebrafish model to examine two multi-Tudor proteins, Tdrd6a and Tdrd6c, demonstrating that both are essential for the stability of germplasm during primordial germ cell (PGC) formation. They reveal that the Prion-like domain of Tdrd6c is key to Tdrd6c's self-interaction and its interaction with Bucky ball, a key organizer of germplasm in zebrafish, and that these interactions are regulated by the Tudor domains of Tdrd6c. These findings provide new insights into the mechanisms governing this phase-separated structure during development. Overall, the results are interesting, and the manuscript is generally well-written. However, additional experimental evidence is required to substantiate these findings.

Major Points 1. Compared to single mutations in tdrd6a or tdrd6c, the tdrd6a/tdrd6c double mutations result in more severe PGC defects. Is there evidence for genetic compensation in single tdrd6 mutations? This needs to be clarified.

Reply:

This is an interesting point. We plan to do RT-qPCR on tdrd6a and tdrd6c in the single mutants to test this idea.

In Figure 3, can injecting another tdrd6 mRNA into single mutant embryos for tdrd6a or tdrd6c rescue the PGC defect?

Reply:

Thank you for pointing out this idea. We had contemplated the idea, but reasoned that most likely any injected mRNA would be expressed too late to make a difference. However, we should just try it, because if it works it opens up possibilities (as also brought up by other reviewers). Hence, we plan to test this by injecting mRNAs for tdrd6a and/or tdrd6c in embryos derived from double mutant females. We believe that this approach would be more sensitive than a potential rescue on single mutants as the phenotype of the double is simply much stronger and consistent.

Given the distinct subcellular localization of Tdrd6a and Tdrd6c during oocyte stages, it is suggested that Tdrd6a, Tdrd6c, and Buc may interact differently. This variation might contribute to differences in germplasm distribution in early embryonic development. It would be useful to assess germplasm levels and distribution in the different mutants using single-molecule fluorescence in situ hybridization (smFISH).

Reply:

This is a good idea, and we will test this as suggested, with smFISH.

In Figure 5, co-immunoprecipitation (Co-IP) experiments are recommended to further confirm the interaction between Buc and Tdrd6a.

Reply:

Most likely the reviewer refers to Tdrd6c, and not Tdrd6a. For Tdrd6a we have shown before that it co-IPs with Buc (Roovers et al.(2018) Figure 5). Also Tdrd6c comes down in these IPs. In panel 5H we furthermore show that the coIP between Tdrd6a and Tdrd6c is disrupted in absence of Buc, implying that Tdrd6a and Tdrd6c interact with each other via Buc. Hence, we will not perform further coIP experiments from the artificial setting of BmN4 cells.

The functional role of zebrafish Tdrd6c may not be fully elucidated through cellular experiments alone. Would injecting mutant variants of tdrd6c into tdrd6a mutant embryos rescue the PGC defects?

Reply:

Thank you for the good suggestion. We plan to try such rescue experiments by injection of mRNAs

Line 368, improper writing style. "I selected, cloned and expressed...". The sentence should not use "I" as the subject.

Reply:

This will be fixed.

Minor Points 1. The fonts in Figures 3C, 3D, 5B, 6B, etc., are too small and difficult to read. 2. Figure 3C and other charts are somewhat rough in appearance; optimization is recommended. 3. In line 171, an inappropriate reference is cited and should be revised.

Reply:

These will be addressed in the revision.

Reviewer #2 (Significance (Required)): Strength and limitation: Strength: showing that Tdrd6a and Tdrd6c contribute to the stability of germplasm is novel. Limitation: the direct interaction between Tdrd6c and Buc is not fully supported by the experiments and results.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

The manuscript "Germplasm stability in zebrafish requires maternal Tdrd6a and Tdrd6c" by Consorte and colleagues explores the poorly understood process of how the formation of the germ plasm, a collection of phase-separated RNA and protein components that segregate asymmetrically in the embryo to the future germ cells in many vertebrates, is regulated. In this study, the authors show that Tdrd6a and Tdrd6c are necessary to stabilize the germplasm in zebrafish embryos, while they are not required for the formation of a related structure during oogenesis, the Balbiani body. Interestingly, Tdrd6a and Tdrd6c are not required for the initial formation of the germ plasm in the embryo, but rather for stabilizing the germ plasm after its initial segregation from the rest of the cytoplasm: the absence of both of these proteins together in the oocyte causes a dispersal of the germ plasm during the first hours of embryogenesis, and consequently an absence of primordial germ cells in the larvae as well as sterility of the adult fish (fish looking like males were sterile, and no adult female fish in line with severely diminished gonad formation). The authors further imply a role of the prion-like domain of Tdrd6c in mediating self-interaction (clustering in the cytoplasm) as well as interaction with Bucky ball, and that these dynamics are modulated by Tdrd6c Tudor domains1-3 and lead, again in cells, to an immobilization of the Buc-Tdrd6c complex. The main new finding in this study is that Tdrd6a and Tdrd6c act redundantly and are together required for germ plasm stabilization in zebrafish. The mutant phenotype of Tdrd6a had already been previously published by the lab (and the authors introduce their prior work in the introduction). In prior work, the authors had shown that absence of Tdrd6a caused a mild phenotype in germ plasm assembly and loss of PGCs in the embryo, similar as they show now for the single Tdrd6c mutant. Moreover, Tdrd6a was also shown to interact with Buc, albeit via its Tudor domain, which is in contrast to the new finding that Tdrd6c interacts with Buc not with its Tudor but instead with its prion-like domain, which is absent in Tdrd6a. Together with the new findings presented here, this identifies Tdrd6a and Tdrd6c as redundantly acting factors that can both interact with Buckyball and can stabilize the germ plasm in the embryo.

Major comments: The authors provide a careful analysis of the mutants, and most of the claims are fully supported by data. The data presented is very clear and the paper is well written. There is one aspect that I think would require further in vivo evidence, and that is the analysis of the interaction between Tdrd6c and Buc, which is currently performed only in vitro in the Bombyx cell line, which has clear limitations regarding conclusion that can be drawn for the in vivo situation. The observation that Tdrd6c-PrLD-TDR123 and Buc condensates localize adjacently/colocalize and that Buc condensates are immobilized on Tdrd6c granules via its PrLD domain do in my opinion suggest that Bb interacts with Tdrd6c via its PrLD domain, but this could still be indirect or an overexpression effect. To really show this, the authors should consider performing at some experiment in this regard in zebrafish embryos. I realize this is tricky given that the double mutants do not give you oocytes/embryos to work with, but maybe also here the overexpression in a single mutant would at least have the in vivo normal environment and endogenous (or transgenically labelled) Buc there. This could be either via imaging, or IPs (e.g. using the tagged line or AB). Potential AlphaFold modeling could also help though this might not result in anything given the unstructured nature of both proteins. Another alternative to show direct interaction could be a peptide-Spot-assay that might be able to detect direct interaction between those two proteins (and/or protein domains)?

Reply:

We believe the main point of the reviewer is that the interaction between Tdrd6c and Buc may be indirect. This is a valid point, but hard to address. As indicated in our replies to reviewer 2, we did already publish IP-MS data suggesting that Tdrd6a and Tdrd6c interact likely directly with Buc (Roovers et al.(2018)). First, a pull-down with a Buc-peptide pulled down Tdrd6a. Second, Tdrd6a and Tdrd6c interact with each other via Buc. There is no experiment that does not include artificial setting that would help us further here. However, we did recently manage to make full length Buc and Tdrd6c, and plan to use these in in vitro Buc phase-separation assays (which are working) to test if Tdrd6c may participate in Buc granules under our experimental conditions.

Suggestion for additional experiments:

• The authors show that ziwi-driven transgenic Tdrd6c is expressed during oogenesis but does not localize to the Balbiani body, which is rather surprising given that Tdrd6a localizes there (also confirmed again in this manuscript). Is (endogenous) Tdrd6c present already during oogenesis, and does it localize there to the Balbiani body? The authors should check this with AB staining for Tdrd6c in ovaries.

Reply:

This is an excellent point. We will put renewed effort in getting our Tdrd6c antibody to work on ovary samples.

• It is currently unclear whether (endogenous) Tdrd6c is indeed already present and required in the ovary/oocyte, or whether very early expression in the embryo could be sufficient for rescuing the mutant phenotype, particularly since the initial germ plasm forms rather normally in the embryo in the double mutant. Can the authors attempt to rescue the double mutant phenotype by zygotic expression of either Tdrd6a and Tdrd6c (e.g. mRNA injection)?

Reply:

The phenotype we observed is strictly maternal. Zygotic, wild-type tdrd6a/c cannot not rescue the phenotype. Nevertheless, as also requested by the other reviewers, attempting rescue by mRNA injection is worthwhile, and we plan to do this.

Minor comments: - The videos were not labelled with the respective numbers (only Movie 3 was assigned as Movie 3) - please assign them the corresponding numbers.

Reply:

This will be fixed.

• In Fig 2B, DAPI would be nice to show to see directly where the nuclei are.

Reply:

DAPI does not stain the DNA in oocytes because the nuclei are so large. Nevertheless, we will use a Lamin antibody, or other suitable antibody, to indicate the nuclei.

• In Fig 2C, indicate with a box the area of the zoom in D; plus make the contrast particularly for red brighter in 2C since the red is almost invisible

Reply:

This will be fixed.

• Fig 4B, I would suggest still showing the 'no volume measured' data (=0) for the double mutant for the 3h timepoint (or at least indicate in the right blot as 'no data'), otherwise it's easy to miss if one just looks at the figure

Reply:

This will be fixed.

• Fig 5d/E: the phenotype is visible, but it's unclear from the figure whether these images are cherry-picked and how penetrant it is; thus some quantification would be helpful (e.g. clustering amount? Relative percentage of area of the cytoplasm of a cell pink? Or granularity of the cytoplasm?)

Reply:

This comment was also raised by other reviewers. We will quantify the imaging we have performed.

• Fig 6A: any speculation what is different in the few cells that have the colocalization of Buc and Tdrd6c (full-length) vs those that don't? could it be the level of the protein, or something else? In addition, I was missing to see just the Buc as a control on its own (without the co-transfection of Tdrd6c); and same comment as before, also here some quantification of changes to the Buc localization could be helpful (and changes/quantification of the Tdrd6c localization)

Reply:

We apologies we leaving out our Buc-only control. We have done that experiment, showing Buc alone yields nice round foci in these cells. Will include that in the revision.

The variability in co-localization we believe indeed stems from expression levels.

• This is more of a comment: I find it surprising that the two similar proteins would use different motifs/domains for interacting with Bb. Can it be ruled out that the previously found interaction between Tdrd6a and Bb could be mediated by Tdrd6c (via an interaction of Tdrd6a and Tdrd6c via their Tudor domains)? I assume Tdrd6c was not present in those cells during the previous assay, but could there have been another Tdrd6-like (endogenous) protein in the cells that could take 'Tdrd6c's' spot', making the interaction with Tdrd6a and Bb potentially indirect? Given this difference in domains and the in vitro overexpression cell-based assay as main evidence for this point, I do think this will require some experimental work to confirm the present model.

Reply:

Please see our reply to the general comments: in Roovers et al. (2018) we showed that Tdrd6a and Tdrd6c coIP with each other via Buc. Hence, Tdrd6a seems not to need Tdrd6c for Buc binding.

*Reviewer #3 (Significance (Required)): Overall, this manuscript identifies and provides an initial characterization of two factors that are required for germ plasm stabilization and thus reproductive ability in zebrafish. The paper is solid in what it shows. It's main limitation is that the conceptual insights it provides in its current stage are rather limited. However, it does provide a useful and important foundation for future work, that will need to address how these factors regulate germ plasm condensation, and why there is a specific requirement in the embryo (but not during oogenesis). *

Reviewer #4 (Evidence, reproducibility and clarity (Required)):

This is an excellent manuscript from the Ketting lab describing generation of a double mutant of tdrd6a and tdrd6c and showing that PGCs fail to form in their absence, whereas PGCs are present and functional in each single maternal-zygotic mutant, although PGCs are reduced in number. The Ketting lab previously published the tdrd6a mutant and here they describe the tdrd6c mutant and the double mutant. They find that Buc-GFP aggregation occurs normally in the double mutant but fails to persist to 3 hpf presumably due to a role of Tdrd6a/c in stabilizing the germplasm granules that have formed. The Balbiani while mildly affected in tdrd6a mutants is little or not affected in the double mutant. They perform co-localization and aggregation analysis in a cell culture system, which suggests that the Tdrd6c prion-like domain (PrLD) can self-aggregate, although not in the context of the full-length Tdrd6c. Further, the Tdrd6c PrLD with the Tudor domains 1,2, 3 co-localizes fully with Buc-GFP in granules in the cell system, while the Tdrd6c PrLD domain alone only leads to Buc-GFP docking on the Tdr6c-PrLD large aggregate. Interestingly, Tdrd6a and Tdrd6c appear to associate via distinct mechanisms to Buc, since Tdrd6a does not contain a PrLD. The points below would strengthen the manuscript.

1. The authors should examine Tdrd6c localization in oocytes using their antibody to ensure that the Tdrd6c-mKate fusion is accurately reflecting endogenous Tdrd6c localization.

Reply:

This is an excellent point. We plan to do these experiments. This antibody thus far failed to work on ovary samples, but we will give it some more effort.

The authors should test if the Tdrd6c-mKate transgene can rescue the tdrd6c mutant to ensure the mKate fusion is not altering its function, which could lead to mis-localization.

Reply:

This is an excellent point. We plan to do these experiments. The crossing schemes will, however, take significant time. Nevertheless, this is an important suggestion and we will try it.

Please describe in fig 3 legend or methods the exact locations of the sequences deleted in the crispr allele generated in tdrd6c.

Reply:

This will be addressed.

Line 152-153, is it not indicative of maternal expression of both tdrda and c being important, since each one alone is sufficient?

Reply:

Exactly, and therefore it follows that '*maternal inheritance of at least one of the Tdrd6 proteins is crucial for the specification of PGCs.' When embryo lack only one, they do relatively fine. We will look at this passage, however, to phrase it in an easier manner. *

Lines 202-204, what percent of cells showed colocalization of Tdrdc with Buc-GFP and include the number of cells examined in a particular area. Quantitation would make more clear what is meant by 'occasional'.

Reply:

We will quantify the imaging experiments on the BmN4 cells.

1. The authors previously published a balbiani body defect in the tdrda mutant in Roovers et al, 2018. The authors state in lines 235-236 that there is no Balbiani body defect in the double mutant? Is there not the same balbiani defect in the double mutant as found in the tdrd6a mutant? The authors should show their data for the normal Balbiani body and comment on this point.

Reply:

Thank you for pointing this out. The balbiani body defect in tdrd6a mutants is not an easy one, and we have not analysed the balbiani body in as much detail in this study as we did before for the tdrd6a mutant, as the major defect was observed in the germ plasm. However, we agree we should also addres the balbiani body in more detail. We plan to address this by looking at balbiani body morphology using smFISH markers in the various mutants.

The authors previously published that Tdrd6a localizes around Buc droplets, at the periphery of the Buc aggregate. Tdrd6c localization in the embryo germplasm appears different and to be fully within the Buc aggregate. The authors should discuss this point, if it still holds.

Reply:

We will repeat the stainings at higher resolution to address this.

Minor points:

1. End of Introduction lines 65-67, 'demonstrate' is too strong here, since the work was done in a heterologous cell system, not the embryo, and their correct association requires both Tdrd domains 1-3 and the PrLD.

2. Figure 1A has a typo in 'binding' site.

3. How were the fish lines genotyped? The exact method should be included and if by PCR, the primer sequences used.

4. Only one of the five supplementary movies is labelled, rest are all identically named, so this reviewer could not be sure of what video corresponded to what data. Also the two AVI videos did not run on the website, so could not be viewed by this reviewer.

Reply:

These minor issues will be resolved in the revision.

**Referees cross-commenting** Reviewer 1: the PGCs/germline stem cells were shown to be absent at 1 dpf, re comment 1. Comment 4, Fig S6 is Zili IF in oocytes, not BmN4, although it does see a lot of background without a control of a zili mutant. Reviewer 2: I agree with point 5. For a higher impact paper, this would be required in my view. Data in cells is not necessarily reflective of in vivo. The authors are generally cautious in their interpretation though. Reviewer 3 also raises this point, although incorrectly states that there are not embryos to work with from the double mutant--they could indeed inject Tdrdc FL and the fragments as mRNA into the early embryo and test for colocalization with Buc in the germplasm at the cleavage furrows to provide in vivo evidence and increase the impact of the manuscript and then it could be appropriate for a higher impact journal. REviewer 3, I agree with point on Fig 5d/E, some measure and quantification would be helpful. I agree with comment on Fig 6A too, I thought the same. Reviewer 3 refers to the Bb multiple times, when I believe they mean the embryo germ plasm, including their last comment before Signifance. This is a good point too that Tdrd6a and c may interact with each other and only one interacts with Buc. I agree with their Significance statements.

Reviewer #4 (Significance (Required)): This manuscript will be of interest to those studying germ cells, as well as the Piwi pathway and phase separation. The advance is an important first step to understanding how Tdrd6 proteins function in germ plasm persistence or stability in the early embryo. Interesting self-aggregation and interaction with Bucky ball studies are shown in a cell culture system that suggests the Prion-like domain of Tdrdc is important for its co-localization with Buc in droplet-like puncta, a mechanism distinct from Tdrd6a which does not contain a PrLD.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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---

Referee #4

Evidence, reproducibility and clarity

This is an excellent manuscript from the Ketting lab describing generation of a double mutant of tdrd6a and tdrd6c and showing that PGCs fail to form in their absence, whereas PGCs are present and functional in each single maternal-zygotic mutant, although PGCs are reduced in number. The Ketting lab previously published the tdrd6a mutant and here they describe the tdrd6c mutant and the double mutant. They find that Buc-GFP aggregation occurs normally in the double mutant but fails to persist to 3 hpf presumably due to a role of Tdrd6a/c in stabilizing the germplasm granules that have formed. The Balbiani while mildly affected in tdrd6a mutants is little or not affected in the double mutant. They perform co-localization and aggregation analysis in a cell culture system, which suggests that the Tdrd6c prion-like domain (PrLD) can self-aggregate, although not in the context of the full-length Tdrd6c. Further, the Tdrd6c PrLD with the Tudor domains 1,2, 3 co-localizes fully with Buc-GFP in granules in the cell system, while the Tdrd6c PrLD domain alone only leads to Buc-GFP docking on the Tdr6c-PrLD large aggregate. Interestingly, Tdrd6a and Tdrd6c appear to associate via distinct mechanisms to Buc, since Tdrd6a does not contain a PrLD. The points below would strengthen the manuscript.

1. The authors should examine Tdrd6c localization in oocytes using their antibody to ensure that the Tdrd6c-mKate fusion is accurately reflecting endogenous Tdrd6c localization.
2. The authors should test if the Tdrd6c-mKate transgene can rescue the tdrd6c mutant to ensure the mKate fusion is not altering its function, which could lead to mis-localization.
3. Please describe in fig 3 legend or methods the exact locations of the sequences deleted in the crispr allele generated in tdrd6c.
4. Line 152-153, is it not indicative of maternal expression of both tdrda and c being important, since each one alone is sufficient?
5. Lines 202-204, what percent of cells showed colocalization of Tdrdc with Buc-GFP and include the number of cells examined in a particular area. Quantitation would make more clear what is meant by 'occasional'.
6. The authors previously published a balbiani body defect in the tdrda mutant in Roovers et al, 2018. The authors state in lines 235-236 that there is no Balbiani body defect in the double mutant? Is there not the same balbiani defect in the double mutant as found in the tdrd6a mutant? The authors should show their data for the normal Balbiani body and comment on this point.
7. The authors previously published that Tdrd6a localizes around Buc droplets, at the periphery of the Buc aggregate. Tdrd6c localization in the embryo germplasm appears different and to be fully within the Buc aggregate. The authors should discuss this point, if it still holds.

Minor points:

1. End of Introduction lines 65-67, 'demonstrate' is too strong here, since the work was done in a heterologous cell system, not the embryo, and their correct association requires both Tdrd domains 1-3 and the PrLD.
2. Figure 1A has a typo in 'binding' site.
3. How were the fish lines genotyped? The exact method should be included and if by PCR, the primer sequences used.
4. Only one of the five supplementary movies is labelled, rest are all identically named, so this reviewer could not be sure of what video corresponded to what data. Also the two AVI videos did not run on the website, so could not be viewed by this reviewer.

Referees cross-commenting

Reviewer 1: the PGCs/germline stem cells were shown to be absent at 1 dpf, re comment 1. Comment 4, Fig S6 is Zili IF in oocytes, not BmN4, although it does see a lot of background without a control of a zili mutant.

Reviewer 2: I agree with point 5. For a higher impact paper, this would be required in my view. Data in cells is not necessarily reflective of in vivo. The authors are generally cautious in their interpretation though. Reviewer 3 also raises this point, although incorrectly states that there are not embryos to work with from the double mutant--they could indeed inject Tdrdc FL and the fragments as mRNA into the early embryo and test for colocalization with Buc in the germplasm at the cleavage furrows to provide in vivo evidence and increase the impact of the manuscript and then it could be appropriate for a higher impact journal.

REviewer 3, I agree with point on Fig 5d/E, some measure and quantification would be helpful. I agree with comment on Fig 6A too, I thought the same. Reviewer 3 refers to the Bb multiple times, when I believe they mean the embryo germ plasm, including their last comment before Signifance. This is a good point too that Tdrd6a and c may interact with each other and only one interacts with Buc. I agree with their Significance statements.

Significance

This manuscript will be of interest to those studying germ cells, as well as the Piwi pathway and phase separation. The advance is an important first step to understanding how Tdrd6 proteins function in germ plasm persistence or stability in the early embryo. Interesting self-aggregation and interaction with Bucky ball studies are shown in a cell culture system that suggests the Prion-like domain of Tdrdc is important for its co-localization with Buc in droplet-like puncta, a mechanism distinct from Tdrd6a which does not contain a PrLD.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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---

Referee #3

Evidence, reproducibility and clarity

The manuscript "Germplasm stability in zebrafish requires maternal Tdrd6a and Tdrd6c" by Consorte and colleagues explores the poorly understood process of how the formation of the germ plasm, a collection of phase-separated RNA and protein components that segregate asymmetrically in the embryo to the future germ cells in many vertebrates, is regulated. In this study, the authors show that Tdrd6a and Tdrd6c are necessary to stabilize the germplasm in zebrafish embryos, while they are not required for the formation of a related structure during oogenesis, the Balbiani body. Interestingly, Tdrd6a and Tdrd6c are not required for the initial formation of the germ plasm in the embryo, but rather for stabilizing the germ plasm after its initial segregation from the rest of the cytoplasm: the absence of both of these proteins together in the oocyte causes a dispersal of the germ plasm during the first hours of embryogenesis, and consequently an absence of primordial germ cells in the larvae as well as sterility of the adult fish (fish looking like males were sterile, and no adult female fish in line with severely diminished gonad formation). The authors further imply a role of the prion-like domain of Tdrd6c in mediating self-interaction (clustering in the cytoplasm) as well as interaction with Bucky ball, and that these dynamics are modulated by Tdrd6c Tudor domains1-3 and lead, again in cells, to an immobilization of the Buc-Tdrd6c complex.

The main new finding in this study is that Tdrd6a and Tdrd6c act redundantly and are together required for germ plasm stabilization in zebrafish. The mutant phenotype of Tdrd6a had already been previously published by the lab (and the authors introduce their prior work in the introduction). In prior work, the authors had shown that absence of Tdrd6a caused a mild phenotype in germ plasm assembly and loss of PGCs in the embryo, similar as they show now for the single Tdrd6c mutant. Moreover, Tdrd6a was also shown to interact with Buc, albeit via its Tudor domain, which is in contrast to the new finding that Tdrd6c interacts with Buc not with its Tudor but instead with its prion-like domain, which is absent in Tdrd6a. Together with the new findings presented here, this identifies Tdrd6a and Tdrd6c as redundantly acting factors that can both interact with Buckyball and can stabilize the germ plasm in the embryo.

Major comments:

The authors provide a careful analysis of the mutants, and most of the claims are fully supported by data. The data presented is very clear and the paper is well written. There is one aspect that I think would require further in vivo evidence, and that is the analysis of the interaction between Tdrd6c and Buc, which is currently performed only in vitro in the Bombyx cell line, which has clear limitations regarding conclusion that can be drawn for the in vivo situation. The observation that Tdrd6c-PrLD-TDR123 and Buc condensates localize adjacently/colocalize and that Buc condensates are immobilized on Tdrd6c granules via its PrLD domain do in my opinion suggest that Bb interacts with Tdrd6c via its PrLD domain, but this could still be indirect or an overexpression effect. To really show this, the authors should consider performing at some experiment in this regard in zebrafish embryos. I realize this is tricky given that the double mutants do not give you oocytes/embryos to work with, but maybe also here the overexpression in a single mutant would at least have the in vivo normal environment and endogenous (or transgenically labelled) Buc there. This could be either via imaging, or IPs (e.g. using the tagged line or AB). Potential AlphaFold modeling could also help though this might not result in anything given the unstructured nature of both proteins. Another alternative to show direct interaction could be a peptide-Spot-assay that might be able to detect direct interaction between those two proteins (and/or protein domains)?

Suggestion for additional experiments:

• The authors show that ziwi-driven transgenic Tdrd6c is expressed during oogenesis but does not localize to the Balbiani body, which is rather surprising given that Tdrd6a localizes there (also confirmed again in this manuscript). Is (endogenous) Tdrd6c present already during oogenesis, and does it localize there to the Balbiani body? The authors should check this with AB staining for Tdrd6c in ovaries.
• It is currently unclear whether (endogenous) Tdrd6c is indeed already present and required in the ovary/oocyte, or whether very early expression in the embryo could be sufficient for rescuing the mutant phenotype, particularly since the initial germ plasm forms rather normally in the embryo in the double mutant. Can the authors attempt to rescue the double mutant phenotype by zygotic expression of either Tdrd6a and Tdrd6c (e.g. mRNA injection)?

Minor comments:

• The videos were not labelled with the respective numbers (only Movie 3 was assigned as Movie 3) - please assign them the corresponding numbers.
• In Fig 2B, DAPI would be nice to show to see directly where the nuclei are.
• In Fig 2C, indicate with a box the area of the zoom in D; plus make the contrast particularly for red brighter in 2C since the red is almost invisible
• Fig 4B, I would suggest still showing the 'no volume measured' data (=0) for the double mutant for the 3h timepoint (or at least indicate in the right blot as 'no data'), otherwise it's easy to miss if one just looks at the figure
• Fig 5d/E: the phenotype is visible, but it's unclear from the figure whether these images are cherry-picked and how penetrant it is; thus some quantification would be helpful (e.g. clustering amount? Relative percentage of area of the cytoplasm of a cell pink? Or granularity of the cytoplasm?)
• Fig 6A: any speculation what is different in the few cells that have the colocalization of Buc and Tdrd6c (full-length) vs those that don't? could it be the level of the protein, or something else? In addition, I was missing to see just the Buc as a control on its own (without the co-transfection of Tdrd6c); and same comment as before, also here some quantification of changes to the Buc localization could be helpful (and changes/quantification of the Tdrd6c localization)
• This is more of a comment: I find it surprising that the two similar proteins would use different motifs/domains for interacting with Bb. Can it be ruled out that the previously found interaction between Tdrd6a and Bb could be mediated by Tdrd6c (via an interaction of Tdrd6a and Tdrd6c via their Tudor domains)? I assume Tdrd6c was not present in those cells during the previous assay, but could there have been another Tdrd6-like (endogenous) protein in the cells that could take 'Tdrd6c's' spot', making the interaction with Tdrd6a and Bb potentially indirect? Given this difference in domains and the in vitro overexpression cell-based assay as main evidence for this point, I do think this will require some experimental work to confirm the present model.

Significance

Overall, this manuscript identifies and provides an initial characterization of two factors that are required for germ plasm stabilization and thus reproductive ability in zebrafish. The paper is solid in what it shows. It's main limitation is that the conceptual insights it provides in its current stage are rather limited. However, it does provide a useful and important foundation for future work, that will need to address how these factors regulate germ plasm condensation, and why there is a specific requirement in the embryo (but not during oogenesis).

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #2

Evidence, reproducibility and clarity

In this report, the authors utilize the zebrafish model to examine two multi-Tudor proteins, Tdrd6a and Tdrd6c, demonstrating that both are essential for the stability of germplasm during primordial germ cell (PGC) formation. They reveal that the Prion-like domain of Tdrd6c is key to Tdrd6c's self-interaction and its interaction with Bucky ball, a key organizer of germplasm in zebrafish, and that these interactions are regulated by the Tudor domains of Tdrd6c. These findings provide new insights into the mechanisms governing this phase-separated structure during development. Overall, the results are interesting, and the manuscript is generally well-written. However, additional experimental evidence is required to substantiate these findings.

Major Points

1. Compared to single mutations in tdrd6a or tdrd6c, the tdrd6a/tdrd6c double mutations result in more severe PGC defects. Is there evidence for genetic compensation in single tdrd6 mutations? This needs to be clarified.
2. In Figure 3, can injecting another tdrd6 mRNA into single mutant embryos for tdrd6a or tdrd6c rescue the PGC defect?
3. Given the distinct subcellular localization of Tdrd6a and Tdrd6c during oocyte stages, it is suggested that Tdrd6a, Tdrd6c, and Buc may interact differently. This variation might contribute to differences in germplasm distribution in early embryonic development. It would be useful to assess germplasm levels and distribution in the different mutants using single-molecule fluorescence in situ hybridization (smFISH).
4. In Figure 5, co-immunoprecipitation (Co-IP) experiments are recommended to further confirm the interaction between Buc and Tdrd6a.
5. The functional role of zebrafish Tdrd6c may not be fully elucidated through cellular experiments alone. Would injecting mutant variants of tdrd6c into tdrd6a mutant embryos rescue the PGC defects?
6. Line 368, improper writing style. "I selected, cloned and expressed...". The sentence should not use "I" as the subject.

Minor Points

1. The fonts in Figures 3C, 3D, 5B, 6B, etc., are too small and difficult to read.
2. Figure 3C and other charts are somewhat rough in appearance; optimization is recommended.
3. In line 171, an inappropriate reference is cited and should be revised.

Significance

Strength and limitation:

*Strength: showing that Tdrd6a and Tdrd6c contribute to the stability of germplasm is novel.

Limitation: the direct interaction between Tdrd6c and Buc is not fully supported by the experiments and results.

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Referee #1

Evidence, reproducibility and clarity

The manuscript by Consorte and coworkers focusses on the role of the tudor-doman containing proteins, Tdrd6a and Tdrd6c in Germplasm stability in zebrafish. Single mutants for each protein do not affect germ plasm stability or germ cell fates, Through the use of double mutants lacking the function of both proteins, the authors find that germ plasm complexes form and the Balbiani body of mutant oocytes are unaffected. However, the germ plasm complexes disperse during early development, leading to loss of primordial germ cells and eventually sterility of adult double mutant fish. Domain analysis of Tdrd6c showed that the Tudor domains are not required for interactions with the germ plasm organiser Bucky ball (Buc), but function in germ plasm dynamics. The prion-like domains of Tdrd6c were found to be required for interactions with Buc. Tdrd6c protein localizes to perinuclear granules in germ cells, but not in the Bb, unlike Tdrd6a. The manuscript is generally well done, and the findings are of interest to researchers interested in germline development, RNA-protein complexes and intrinsically disordered /prion-like proteins. Some further work would bolster the findings and support the main conclusions better.

Major comments:

• Regarding the 6a6c double mutants, figure 3 and S4 show preliminary evidence that the gonads are severely underdeveloped. However it is unclear when/what stage the gonads are arrested and whether there is a loss of germline stem cells. This can be shown.
• The authors show that germplasm forms in single mutants for 6a and 6c and Buc-eGFP reporter transgene localization does not show overt germpalsm defects in the single mutant embryos. But PGC numbers are reduced by larval stages. Are germplasm RNAs destabilised to some extent in the single mutants? This should be examined.
• Relevant to the PGC defects shown in Fig 3, is there is more male bias or earlier defects in the 6c single mutants ? What is the tissue shown in Fig S4 B in the double mutant? Some sections and markers would be useful.
• Regarding expressing of the Tdrd6c constructs in BmN4 cells: the expression levels do not appear uniform and the background fluorescence is very high in some images, making comparisons and differences in expression levels/distribution difficult to see.eg Fig S6. These images (eg S6 6c and 6a6c double mutant images) should be assessed carefully and replaced with better representative images.

Minor comments:

• Fig 1 a: spelling error in the schematic "Antibody Binging site" should be changed to "Antibody binding site".

Significance

How germ plasm stability is controlled is not well understood. In this manuscript, the role of the related Tudor-domain proteins, Tdrd6a and 6c proteins are compared. The proteins have redundant roles in germplasm stability and germ cells in early zebrafish embryos, and the combined loss of the proteins leads to germplasm destabilisation, germ cell loss and sterility. The manuscript is generally well done, and the findings are of interest to researchers interested in germline development, RNA-protein complexes and intrinsically disordered /prion-like proteins. Some further work would bolster the findings and support the main conclusions better (as detailed in major and minor comments above).

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Reply to the reviewers

We thank the reviewers for their thorough review of our manuscript and believe it has been much improved based on their comments.

A detailed response to each comment is itemized below.

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Reviewer #1 (Evidence, reproducibility and clarity (Required)):

This is an interesting manuscript where the authors systematically measure rG4 levels in brain samples at different ages of patients affected by AD. To the best of my knowledge this is the first time that BG4 staining is used in this context and the authors provide compelling evidence to show an association with BG4 staining and age or AD progression, which interestingly indicates that such RNA structure might play a role in regulating protein homeostasis as previously speculated. The methods used and the results reported seem robust and reproducible.

In terms of the conclusions, however, I think that there are 2 main things that need addressing prior to publication:

1) Usually in BG4 staining experiments to ensure that the signal detected is genuinely due to rG4 an RNase treatment experiment is performed. This does not have to be extended to all the samples presented but having a couple of controls where the authors observe loss of staining upon RNase treatment will be key to ensure with confidence that rG4s are detected under the experimental conditions. This is particularly relevant for this brain tissue samples where BG4 staining has never been performed before.

Response____: With what is now known about RNA rG4s and the recent reconciliation of the controversy on rG4 formation (Kharel, Nature Communications 2023), this experiment is no longer strictly required for demonstration of rG4 formation. Despite this change, we did attempt this experiment at the reviewer's suggestion, but the controls were not successful, suggesting it may not be feasible with our fixing and staining conditions. That said, we agree that despite the G4 staining appearing primarily outside the nucleus, it would be helpful to have some direct indication of whether we were observing primarily RNA or DNA G4s, and so we performed an alternate experiment to determine this.

In our previous submission, we had performed ribosomal RNA staining (Figure S7), and the staining patterns were similar to that of BG4, especially the punctate pattern near the nuclei. Therefore, we directly asked whether the BG4 was largely binding to rRNA and have now shown the resulting co-stain in Figure 3b. These results show that at least a large amount of the BG4 staining does arise from rG4s in ribosomes. At high magnification, we observe that the BG4 stains a subset of the ribosomes, consistent with previous observations of high rG4 levels in ribosomes both in vitro and in cells (Mestre-Fos, 2019 J Mol Biol, Mestre-Fos 2019 PLoS One, Mestre-Fos 2020 J Biol Chem), but this had never been demonstrated in tissue. This experiment has therefore both answered the primary question of whether we are primarily observing rG4s, as well as provided more detailed information on the cellular sublocalization of rG4 formation, and provided the first evidence of rG4 formation on ribosomes in tissue.

2) The authors have an association between rG4-formation and age/disease progression. They also observe distribution dependency of this, which is great. However, this is still an association which does not allow the model to be supported. This is not something that can be fixed with an easy experiment and it is what it is, but my point is that the narrative of the manuscript should be more fair and reflect the fact that, although interesting, what the authors are observing is a simple correlation. They should still go ahead and propose a model for it, but they should be more balanced in the conclusion and do not imply that this evidence is sufficient to demonstrate the proposed model. It is absolutely fine to refer to the literature and comment on the fact that similar observations have been reported and this is in line with those, but still this is not an ultimate demonstration.

Response: ____We agree that these are correlative studies (of necessity when studying human tissue), but recent experiments have shown that rG4s affect the aggregation of Tau in vitro - and we have now better clarified this in the text itself. We have now also been more careful in drawing causative conclusions as shown in the revised text (see yellow highlighted portions of the text).

Minor point:

3) rG4s themselves have been shown to generate aggregates in ALS models in the absence of any protein (Ragueso et al. Nat Commun 2023). I think this is also important in the light of my comment on the model, could well be that these rG4s are causing aggregates themselves that act as nucleation point for the proteins as reported in the paper I mentioned. Providing a broader and more unbiased view of the current literature on the topic would be fair, rather than focusing on reports more in line with the model proposed.

__Response: ____ We agree and have modified the discussion and added a broader context, including the Ragueso report described above. __

__Reviewer #1 (Significance (Required)): __ This is a significant novel study, as per my comments above. I believe that such a study will be of impact in the G4 and neurodegenerative fields. Providing that the authors can address the criticisms above, I strongly believe that this manuscript would be of value to the scientific community. The main strength is the novelty of the study (never done before) the main weakness is the lack of the RNase control at the moment and the slightly over interpretation of the findings (see comments above).

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

RNA guanine-rich G-quadruplexes (rG4s) are non-canonical higher order nucleic acid structures that can form under physiological conditions. Interestingly, cellular stress is positively correlated with rG4 induction. In this study, the authors examined human hippocampal postmortem tissue for the formation ofrG4s in aging and Alzheimer Disease (AD). rG4 immunostaining strongly increased in the hippocampus with both age and with AD severity. 21 cases were used in this study (age range 30-92). This immunostaining co-localized with hyper-phosphorylated tau immunostaining in neurons. The BG4 staining levels were also impacted by APOE status. rG4 structure was previously found to drive tau aggregation. Based on these observations, the authors propose a model of neurodegeneration in which chronic rG4 formation drives proteostasis collapse. This model is interesting, and would explain different observations (e.g., RNA is present in AD aggregates and rG4s can enhance protein oligomerization and tau aggregation).

Main issue: There is indeed a positive correlation between Braak stage severity and BG4 staining, but this correlation is relatively weak and borderline significant ((R = 0.52, p value = 0.028). This is probably the main limitation of this study, which should be clearly acknowledged (together with a reminder that "correlation is not causality".

__Response: _ We believe that we had not explained this clearly enough in the text (based on the reviewer's comment), as the correlation mentioned by the Reviewer was for the CA4 region only, and not the OML, which was substantially more correlated and statistically significant (_Spearman R= 0.72, p = 0.00086). As a result, we believe this was a miscommunication that is rectified by the revised text: __

"In the OML, plotting BG4 percent area versus Braak stage demonstrated a strong correlation (Spearman R= 0.72) with highly significantly increased BG4 staining with higher Braak stages (p = 0.00086) (Fig. 2b)."

Related to this, here is no clear justification to exclude the four individuals in Fig 1d (without them R increases to 0.78). Please remove this statement. On the other hand, the difference based on APOE status is more striking.

Response: We did not mean to imply that deleting these outliers was correct, but merely were demonstrating that they were in fact outliers. To avoid this misinterpretation, we have now deleted the sentence in the Figure 1d caption mentioning the outliers.

Minor suggestions - "BG4 immunostaining was in many cases localized in the cytoplasm near the nucleus in a punctate pattern". Define "many"

Response: This is seen in nearly every cells and this is now altered in the text and is now identified as ribosomes containing rG4s using the rRNA antibody (Fig. 3b).

• Specify that MABE917 corresponds to the specific single-chain version of the BG4 antibody

__Response:____ Yes, this is correct, and this clarification has been added to the manuscript __

• Define PMI, Braak, CERAD (add a list of acronyms or insert these definitions in Fig 1b legend)

Response: ____These definitions have all been added when they first appear.

• Fig 3: scale bar legend missing (50 micrometers?)

Response:____ This has been added, and the reviewer was correct that it was 50 micrometers.

• Supplementary data Table 1: indicate target for all antibodies

Response: ____The target for each antibody has been added to supplementary Table 1.

• Supplementary data Table 2: why give ages with different levels of precision? (e.g. 90.15 vs 63)

Response:____ We apologize for this oversight and have altered the ages to the same (whole years) in the figure.

• Supplementary data Fig 1 X-axis legend: add "(nm)" after wavelength. Sequence can also be added in the legend. Why this one? Max/Min Wavelengths in the figure do not match indications in the experimental part. Not sure if that part is actually relevant for this study.

Response: The CD spectrum in Sup Fig 1 is the sequence that had previously been shown to aid in tau aggregation seeding, but had not been suspected by those authors to be a quadruplex. So we tested that here and showed it is a quadruplex, as described at the end of the introduction. We have added wording to the figure legend to clarify where its corresponding description in the main text can be found. We have also checked and corrected the wavelength and units.

• Supplementary data Fig 7: Which ribosomal antibody was used?

Response: The details of this antibody have now been added to Supplementary Table 2 which lists all the antibodies used.

Reviewer #2 (Significance (Required)):

Provide a link between Alzheimer disease and RNA G-quadruplexes.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This study investigated the formation of RNA G quadruplexes (rG4) in aging and AD in human hippocampal postmortem tissue. The rG4 immunostaining in the hippocampus increases strongly with age and with the severity of AD. Furthermore, rG4 is present in neurons with an accumulation of phosphorylated tau immunostaining.

Major comments 1.The method used in this study is primarily immunostaining of BG4, and the results cannot be considered correct without additional data from more multifaceted analyses (biochemical analysis, RNA expression analysis, etc.).

__Response: ____We respectfully disagree with the Reviewer's assessment of the value of these experiments. The most relevant biochemical experiments at the cellular and molecular level showing the role of G4s in aggregation in general and Tau in particular have been done and are referenced in the text. The results here stand on their own and are highly novel and significant, as evaluated by both of the other reviewers. There has been no previous work demonstrating the presence of rG4s in human brain - either in controls or in patients with AD. AD is a complex condition that only occurs spontaneously in the human brain and no other species; because of this complexity, novel aspects are best first studied in human brain tissue using the methods employed here. __

Overall, the quality of the stained images is poor, and detailed quantitative analysis using further high quality data is essential to conclude the authors' conclusions.

Response:____ We have again looked at our images and they are not poor quality -they are confocal images taken at recommended resolution of the confocal microscope. It is possible the poor quality came from pdf compression by the manuscript submission portal, which is beyond our control as they were uploaded at high resolution. These data were quantified by scientists who were blinded to the diagnosis of each case.____ The level of description on the detailed quantification is higher than we have observed in similar studies. We therefore disagree with the reviewer's conclusion.

Reviewer #3 (Significance (Required)):

Overall, this study is not a deeply analyzed study. In addition, the authors of this study need further understanding regarding G4.

__Response____: It is also unclear why the reviewer believes that we do not have sufficient understanding of G4s, and would request that the reviewer instead provides specific comments regarding what is lacking in terms of knowledge on G4s, as we respectfully disagree with this judgement of our knowledge-base (see other G4 papers from the Horowitz lab, Begeman, 2020, Litberg 2023, Son, 2023 referenced below). __

__ ____Litberg TJ, Sannapureddi RKR, Huang Z, Son A, Sathyamoorthy B, Horowitz S. Why are G-quadruplexes good at preventing protein aggregation? Jan;20(1):495-509. doi: 10.1080/15476286.2023.2228572. RNA Biol. (2023)​__

__ ____Son A*, Huizar Cabral V*, Huang Z, Litberg TJ, Horowitz S. G-quadruplexes rescuing protein folding. May 16;120(20):e2216308120. doi: 10.1073/pnas.2216308120. Proc Natl Acad Sci U S A (2023)__

​____Guzman BB*, Son A*, Litberg TJ*, Huang Z*, Dominguez ‡, Horowitz S. Emerging Roles for G-Quadruplexes in Proteostasis FEBS J​.doi: 10.1111/febs.16608. (2022)

__ ____Begeman A*, Son A*, Litberg TJ, Wroblewski TH, Gehring T, Huizar Cabral V, Bourne J, Xuan Z, Horowitz S‡. G-Quadruplexes Act as Sequence Dependent Protein Chaperones. EMBO Reports Sep 18;e49735. doi: 10.15252/embr.201949735. (2020)__

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Referee #3

Evidence, reproducibility and clarity

This study investigated the formation of RNA G quadruplexes (rG4) in aging and AD in human hippocampal postmortem tissue. The rG4 immunostaining in the hippocampus increases strongly with age and with the severity of AD. Furthermore, rG4 is present in neurons with an accumulation of phosphorylated tau immunostaining.

Major comments

1.The method used in this study is primarily immunostaining of BG4, and the results cannot be considered correct without additional data from more multifaceted analyses (biochemical analysis, RNA expression analysis, etc.). 2. Overall, the quality of the stained images is poor, and detailed quantitative analysis using further high quality data is essential to conclude the authors' conclusions.

Significance

Overall, this study is not a deeply analyzed study. In addition, the authors of this study need further understanding regarding G4.

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Referee #2

Evidence, reproducibility and clarity

RNA guanine-rich G-quadruplexes (rG4s) are non-canonical higher order nucleic acid structures that can form under physiological conditions. Interestingly, cellular stress is positively correlated with rG4 induction. In this study, the authors examined human hippocampal postmortem tissue for the formation ofrG4s in aging and Alzheimer Disease (AD). rG4 immunostaining strongly increased in the hippocampus with both age and with AD severity. 21 cases were used in this study (age range 30-92).

This immunostaining co-localized with hyper-phosphorylated tau immunostaining in neurons. The BG4 staining levels were also impacted by APOE status. rG4 structure was previously found to drive tau aggregation. Based on these observations, the authors propose a model of neurodegeneration in which chronic rG4 formation drives proteostasis collapse. This model is interesting, and would explain different observations (e.g., RNA is present in AD aggregates and rG4s can enhance protein oligomerization and tau aggregation).

Main issue

There is indeed a positive correlation between Braak stage severity and BG4 staining, but this correlation is relatively weak and borderline significant ((R = 0.52, p value = 0.028). This is probably the main limitation of this study, which should be clearly acknowledged (together with a reminder that "correlation is not causality"). Related to this, here is no clear justification to exclude the four individuals in Fig 1d (without them R increases to 0.78). Please remove this statement. On the other hand, the difference based on APOE status is more striking.

Minor suggestions

• "BG4 immunostaining was in many cases localized in the cytoplasm near the nucleus in a punctate pattern". Define "many"
• Specify that MABE917 corresponds to the specific single-chain version of the BG4 antibody
• Define PMI, Braak, CERAD (add a list of acronyms or insert these definitions in Fig 1b legend)
• Fig 3: scale bar legend missing (50 micrometers?)
• Supplementary data Table 1: indicate target for all antibodies
• Supplementary data Table 2: why give ages with different levels of precision? (e.g. 90.15 vs 63)
• Supplementary data Fig 1 X-axis legend: add "(nm)" after wavelength. Sequence can also be added in the legend. Why this one? Max/Min Wavelengths in the figure do not match indications in the experimental part. Not sure if that part is actually relevant for this study.
• Supplementary data Fig 7: Which ribosomal antibody was used?

Significance

Provide a link between Alzheimer disease and RNA G-quadruplexes.

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Referee #1

Evidence, reproducibility and clarity

This is an interesting manuscript where the authors systematically measure rG4 levels in brain samples at different ages of patients affected by AD. To the best of my knowledge this is the first time that BG4 staining is used in this context and the authors provide compelling evidence to show an association with BG4 staining and age or AD progression, which interestingly indicates that such RNA structure might play a role in regulating protein homeostasis as previously speculated. The methods used and the results reported seems robust and reproducible. In terms of the conclusions,. however, I think that there are 2 main things that need addressing prior publication:

1. Usually in BG4 staining experiments to ensure that the signal detected is genuinely due to rG4 an RNase treatment experiment is performed. This does not have to be extended to all the samples presented but having a couple of controls where the authors observe loss of staining upon RNase treatment will be key to ensure with confidence that rG4s are detected under the experimental conditions. This is particularly relevant for this brain tissue samples where BG4 staining has never been performed before.
2. The authors have an association between rG4-formation and age/disease progression. They also observe distribution dependency of this, which is great. However, this is still an association which does not allow the model to be supported. This is not something that can be fixed with an easy experiment and it is what it is, but my point is that the narrative of the manuscript should be more fair and reflect the fact that, although interesting, what the authors are observing is a simple correlation. They should still go ahead and propose a model for it, but they should be more balanced in the conclusion and do not imply that this evidence is sufficient to demonstrate the proposed model. It is absolutely fine to refer to the literature and comment on the fact that similar observation have been reported and this is in line with those, but still this is not an ultimate demonstration.

Minor point:

1. rG4s themselves have been shown to generate aggregates in ALS models in the absence of any protein (Ragueseo et al. Nat Commun 2023). I think this is also important in the light of my comment on the model, could well be that these rG4s are causing aggregates themselves that act as nucleation point for the proteins as reported in the paper I mentioned. Providing a broader and more unbiased view of the current literature on the topic would be fair, rather than focusing on reports more in line with the model proposed.

Significance

This is a significant novel study, as per my comments above. I believe that such a study will be of impact in the G4 and neurodegenerative fields. Providing that the authors can address the criticisms above, I strongly believe that this manuscript would be of value to the scientific community. The main strength is the novelty of the study (never done before) the main weakness is the lack of the RNase control at the moment and the slightly over interpretation of the findings (see comments above).

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Reply to the reviewers

__Dear Reviewers, __

We would like to thank you for the time and attention dedicated to reviewing our manuscript. We have taken all the questions and comments into consideration, which we believe have helped us to improve the paper.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

The study by Aguirre-Botero et al. shows the dynamics of 3D11 anti-CSP monoclonal antibody (mAb) mediated elimination of rodent malaria Plasmodium berghei (Pb) parasites in the liver. The authors show that the anti-CSP mAb could protect against intravenous (i.v.) Pb sporozoite challenge along with the cutaneous challenge, but requires higher concentration of antibody. Importantly, the study shows that the anti-CSP mAb not only affects sporozoite motility, sinusoidal extravasation, and cell invasion but also partially impairs the intracellular development inside the liver parenchyma, indicating a late effect of this antibody during liver stage development. While the study is interesting and conducted well, the only novel yet very important observation made in this manuscript is the effect of the anti-CSP mAb on liver stage development.

Major This observation is highlighted in the manuscript title but is supported by only limited data. A such it needs to be substantiated and a mechanism should be investigated. The phenomenon of intracellular effects of the anti-CSP mAb should be analyzed in much more detail. For example, can the authors demonstrate uptake of the Ab together with the parasite during hepatocyte invasion? What cellular mechanism leads to elimination?

Lines 234 - 243; 308 - 325: These results are the gist of the entire study and also defined the title of the manuscript. Thus, it would be pre-mature to claim the substantial effect of 3D11 antibody in late killing of the parasite in the infected hepatocytes just by looking at the decreased GFP fluorescence. The authors need to at least verify the fitness of the liver stages by measuring the size of the developing parasites as well as using different parasite specific markers (UIS4, MSP1, HSP70 etc.) in immunofluorescence assays on the infected liver sections and in vitro infections.

Response

We greatly appreciate the comments. We have taken the suggestions into consideration and deepened the characterization of 3D11's late killing of parasites. We first analyzed the presence of 3D11 in the intracellular parasite after the invasion and compared it with the CSP expression on the surface of control parasites (new Fig. 4F). Next, we tested a potential action of 3D11 added in the cell culture after the invasion (new Fig. 4G). The two new panels and the text accompanying them are shown below.

*“Post-invasion labeling of 3D11 bound to the membrane of intracellular parasites revealed a strong staining surrounding the parasite at 2 and 15h, but only punctual traces of 3D11 at 44h (Figure 4F, 3D11, 3D11). Of note, CSP was detected surrounding the control parasites at all time-points indicating that the lack of staining at 44h is not due to a decrease in the CSP amount on the parasite surface (Figure 4F, CSP, Control). To evaluate the potential post-invasion entry of 3D11 into the PV of infected cells and posterior neutralization of intracellular parasites, we incubated invaded cells from 2 to 44 h with 3D11, but no effect on the parasite intracellular development was observed (Figure 4G, 2h p.i.). 3D11 incubated for 2 h with sporozoites and cells elicited, as expected, a dose-dependent inhibition of parasite development. Altogether, our results indicate that the late inhibition of parasite development is already achieved at 15h and likely caused by antibodies dragged inside cells bound to sporozoites before or during the invasion.” *

Finally, we better characterized the parasite loss of fitness caused by 3D11 in infected cells by quantifying the parasite size, GFP intensity and the presence and intensity of UIS4, a parasitophorous vacuole membrane developmental marker at 2, 4 and 44h as described below in the new figure 5 and accompanying text.

“*To further characterize the killing of intracellular parasites by 3D11 in HepG2 cells, we next evaluated the expression of the parasitophorous vacuole membrane (PVM) marker, UIS4 37, to infer the parasite intracellular development at 2, 4 and 44h. HepG2 cells were incubated with Pb-GFP expressing sporozoites in the absence (Control, Figure 5) or presence of 1.25 µg/mL of 3D11 during the first two hours of incubation (3D11, Figure 5). The chosen 3D11 concentration led to ~50% decrease in cell invasion (Figure 4C, 2h) and ~30% decrease in the post-invasion number of EEFs (Figure 4D), leaving enough parasites to be analyzed by microscopy. To distinguish between extracellular and intracellular parasites at 2h, washed and fixed samples were incubated with mouse 3D11 mAb (1µg/mL) and revealed with a fluorescent anti-mouse secondary antibody (Figure 5A, 3D11 in blue). Samples were then permeabilized and incubated with a goat anti-UIS4 polyclonal antibody revealed with a fluorescent anti-goat secondary antibody (Figure 5A, UIS4 in red). DNA was stained with Hoechst (Figure 5A, DNA in white). *

*Extracellular GFP+ sporozoites were identified by their 3D11+UIS4- phenotype (Figure 5A, 2h, extracellular). Conversely, intracellular parasites were identified by their 3D11- phenotype and stained positive or negative for UIS4 (Figure 5A, 2h and 44h, intracellular). UIS4+ PVM is normally associated with a productive cell infection 37. However, a small number of EEFs can develop in the absence of UIS4 37 , likely inside the host cell nucleus (Figure 5A, 44h, intranuclear). *

*In the control and 3D11-treated groups, the percentage of intracellular UIS4- parasites decreased 2 to 3-fold from 2 to 44h, as expected of a parasite population negative for a marker of productive infection (Figure 5B). However, while at 2h in the control group, this population represented 14% of intracellular parasites, in the 3D11-treated group, it reached 48% (Figure 5B). This ~3-fold increase in the UIS4 negative population could explain the late killing of intracellular sporozoites by 3D11. Whether this population is constituted by intracellular transmigratory sporozoites lacking a PVM or parasites surrounded by a PVM, but incapable of secreting UIS4 still needs to be determined. At 44h, surviving EEFs in the 3D11-treated samples presented a similar area and UIS4 staining intensity than control parasites (Figure 5C, D). However, as observed by flow cytometry (Figure 4D), the GFP intensity of 3D11-treated parasites was significantly lower than control EEFs, indicating that 3D11 can somehow affect protein expression with undetermined effects in the genesis of red blood cell infecting stages.” *

____Reviewer #1__ Minor comments __

• Line 44 - 43: The statement is applicable only to the rodent infecting Plasmodium parasites. The authors need to clarify that.

Responses

This is an important clarification. We have modified the text that now reads:

"The sporozoite surface is covered by a dense coat of the immunodominant circumsporozoite protein (CSP), shown to be an immunodominant protective antigen using a rodent malaria model".

• Line 68: Replace the second 'against' after the CSP with 'of'.

It is done.

• Line 141 - 143: The 3D11 mAb does affect the homing and killing in the blood of cutaneous injected sporozoites. The authors need to clearly state that the statement is true only for i.v. injected sporozoites.

Thank you for the comment. Now the text reads "Altogether, these data indicate that 3D11 rather than having an early effect on i.v. inoculated sporozoites, e.g. in the homing or killing in the blood, requires more than 4 h to eliminate most parasites in the liver."

• Figure 3B: The numbers of sporozoites detected in the experiment varies from 0 h (line 172) to 2 h (line 184). Therefore, the numbers need to be mentioned on all the bars of each timepoint.

This information was missing but now we have added the numbers to Figure 3B.

• Figure 3C: If the authors have used flk1-GFP mice, then how well they were able to detect the Pb-PfCSP GFP parasites in the vessel vs. parenchyma in the intravital imaging? The representative images for Pb-PfCSP GFP should also be included.

Since 3D11 does not target PbPf parasites most of them are motile in the movies, making them easily distinguishable from the endothelial cells. In addition, the stronger GFP intensity of sporozoites make them easily detectable in the sinusoids. Representative images were added in the supplementary figures (now Figure S3).

• It is not mentioned anywhere how the viability of the sporozoites was determined. This has to be described especially in the methods section.

• Also, the flow acquisition and data analysis of the sporozoites and infected HepG2 cells must be described in the method section.

__We briefly mentioned it in the results (line 228- 230): “____In addition, by comparing the total number of recovered GFP+ sporozoites at 2 h in the two studied conditions, we measured the early lethality (%viable sporozoites, Figure 4B) of the anti-CSP Ab on the extracellular forms of the parasite (Figure 4A).” __

A more detailed description has been added in the methods section that now reads:

“After 2 h, the supernatant was collected, and the culture was washed 2x with 0.5 volume of PBS. The cells were subsequently trypsinized. The supernatant plus the washing steps and the trypsinized cells were analyzed by flow cytometry to quantify the amount of GFP+ events inside and outside cells (Figure 3A and Figure S4). Viability was then quantified by the sum of the total number of sporozoites (GPF+ events) in the supernatant, inside and outside the cells. We calculated the percentage of parasite viability by dividing the average of the total number of sporozoites in the treated samples by the average in controls using three technical replicates for each condition. Additionally, we quantified the percentage of infected cells using the total number of GFP+ events in the HepG2 gate (Figure S4). To compare the biological replicates, we further normalized to the control of each experiment. For the samples used to analyze parasite development, the cells were incubated for 15 or 44 h after sporozoite addition, and the medium was changed after 2 and 24 h. The cells were trypsinized and the percentage of intracellular parasites was determined by flow cytometry as described above (Figure S4). The prolonged effect between 2 h and 15/44 h was calculated by normalizing the percentage of infected cells at 15/44 h to that of 2 h. For all flow cytometry measurements, the same volume was acquired.”

• Figure 4: The flow layouts should be included for at least comparing the 0 vs. 5 μg/ml of 3D11 mAb concentrations.

Flow layouts were added in the supplementary figures.

• Line 651 (Figure S1 legend): Typographical error '14'.

Thank you for noticing. We corrected it.

Reviewer #2 (Evidence, reproducibility and clarity (Required____)):

Aguirre-Botero and collaborators report on the dynamics of Plasmodium parasite elimination in the liver using the 3D11 anti-CSP monoclonal antibody (mAb). By using microscopy and bioluminescence imaging in the P. berghei rodent malaria model, the authors first demonstrate that higher antibody concentrations are required for protection against intravenous sporozoite challenge, when compared to cutaneous challenge, which is not surprising. The study also shows that the 3D11 mAb reduces sporozoite motility, impairs hepatic sinusoidal barrier crossing, and more relevantly inhibits intracellular development of liver stages through its cytotoxic activity. These findings highlight the role of this specific monoclonal antibody, 3D11 mAb against CSP, in targeting sporozoites in the liver.


Major Comments

The study provides valuable insights into the mechanisms of protection conferred by the 3D11 anti-CSP monoclonal antibody against P. berghei sporozoites and this finding allow the field to speculate that other monoclonal antibodies against CSP of P. Falciparum may act similarly. However, an important experiment is missing that would significantly strengthen the conclusions. Specifically, the authors should perform experiments where the monoclonal antibody is added immediately after the sporozoites have completed invasion. This should be done both in vitro and in vivo to show whether the antibody has any effect on intracellular development of liver stages when added after invasion.

While the claims are generally supported by the data presented, to comprehensively conclude the late cytotoxic effects of 3D11, the additional experiment of post-invasion antibody application is relevant. This would help determine if the observed effects are due to the antibody's action during invasion or its continued action post-invasion.

The data and methods are presented in a manner that allows for reproducibility. The use of microscopy and bioluminescence imaging is well-documented. The experiments appear adequately replicated, and statistical analyses are appropriate.

Response

We thank reviewer 2 for these important suggestions. To be sure that the effect might not come from the internalization of the antibodies after sporozoite invasion, we tested the amount of 3D11 bound to the parasite following invasion (new Fig. 4F) and the potential post-invasion neutralizing effect of 3D11 ____in vitro____. The results obtained are presented below.

*“Post-invasion labeling of 3D11 bound to the membrane of intracellular parasites revealed a strong staining surrounding the parasite at 2 and 15h, but only punctual traces of 3D11 at 44h (Figure 4F, 3D11, 3D11). Of note, CSP was detected surrounding the control parasites at all time-points indicating that the lack of staining at 44h is not due to a decrease in the CSP amount on the parasite surface (Figure 4F, CSP, Control). To evaluate the potential post-invasion entry of 3D11 into the PV of infected cells and posterior neutralization of intracellular parasites, we incubated invaded cells from 2 to 44 h with 3D11, but no effect on the parasite intracellular development was observed (Figure 4G, 2h p.i.). 3D11 incubated for 2 h with sporozoites and cells elicited, as expected, a dose-dependent inhibition of parasite development. Altogether, our results indicate that the late inhibition of parasite development is already achieved at 15h and likely caused by antibodies dragged inside cells bound to sporozoites before or during the invasion.” *

__Reviewer #2 ____Minor Comments __

• The text and figures are clear and accurate. Some minor typographical errors should be corrected.

Thank you for the remark, we have worked on that and hope that the text reads better now.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Aguirre-Botero et al have studied the effect of a potent monoclonal antibody against the circumsporozoite protein, the major surface protein of the malaria sporozoite. This is an elegantly designed, performed, and analyzed study. They have efficiently delineated the mode of action of anti-CSP repeat mAb and confirmed previous in vitro work (not cited) that demonstrated the same intracellular effect. Specific comments :

• Line 51: The authors claim a correlation between high antibody levels and protection. However, they did not provide direct proof that these antibodies were responsible for protection, nor did they establish a cut-off level of anti-CSP antibodies that would distinguish between protected and unprotected individuals.

We would first like to thank reviewer 3 for the comments. Indeed, we agree with reviewer 3, these are correlative studies where the causality cannot be established. We modified the ensuing sentence to specify the causality between anti-CSP mAbs and in vivo protection against sporozoite infection. Now the text reads: "Extensive research has demonstrated a positive correlation between high levels of anti-CSP antibodies (Abs) induced by the RTS,S/AS01 vaccine and its efficacy against malaria 11-13. Remarkably, anti-CSP monoclonal Abs (mAbs) have been proven to protect in vivo against malaria in various experimental settings, including, mice 14-21, monkeys 23, and humans 24-26"

• Line 326: The late intrahepatic effect of mAb against the CSP repeat has been previously reported (see Figure 2, Nudelman et al, J Immunol, 1989). The effect was shown to affect the transition from liver trophozoites to liver schizonts. This study should be cited and discussed.

Thank you for the remark. Now the text reads: Notably, a similar effect has been previously reported using sera from mice immunized with PfCSP or mAb against P. yoelii (Py) CSP. Incubation of Pf or Py sporozoites with the immune sera or mAbs not only affected sporozoite invasion in vitro but continued to affect intracellular forms for several days after invasion38,39. Additionally, using anti-PfCSP sera, it was also observed that late EEFs from sera-treated sporozoites had abnormal morphology38. Altogether, it was thus concluded that the anti-CSP Abs present in the sera had a long-term effect on the parasites38,39.

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Referee #3

Evidence, reproducibility and clarity

Aguirre-Botero et al have studied the effect of a potent monoclonal antibody against the circumsporozoite protein, the major surface protein of the malaria sporozoite. This is an elegantly designed, performed, and analyzed study. They have efficiently delineated the mode of action of anti-CSP repeat mAb and confirmed previous in vitro work (not cited) that demonstrated the same intracellular effect.

Specific comments

Line 51: The authors claim a correlation between high antibody levels and protection. However, they did not provide direct proof that these antibodies were responsible for protection, nor did they establish a cut-off level of anti-CSP antibodies that would distinguish between protected and unprotected individuals.

Lone 326: The late intrahepatic effect of mAb against the CSP repeat has been previously reported (see Figure 2, Nudelman et al, J Immunol, 1989). The effect was shown to affect the transition from liver trophozoites to liver schizonts. This study should be cited and discussed.

Significance

A well-done study that elucidates the mechanisms of a protective monoclonal antibody against malaria sporozoites. These data are important and will interest a large audience of researchers working in infectious diseases and immunology.

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Referee #2

Evidence, reproducibility and clarity

Aguirre-Botero and collaborators report on the dynamics of Plasmodium parasite elimination in the liver using the 3D11 anti-CSP monoclonal antibody (mAb). By using microscopy and bioluminescence imaging in the P. berghei rodent malaria model, the authors first demonstrate that higher antibody concentrations are required for protection against intravenous sporozoite challenge, when compared to cutaneous challenge, which is not surprising. The study also shows that the 3D11 mAb reduces sporozoite motility, impairs hepatic sinusoidal barrier crossing, and more relevantly inhibits intracellular development of liver stages through its cytotoxic activity. These findings highlight the role of this specific monoclonal antibody, 3D11 mAb against CSP, in targeting sporozoites in the liver.


Major Comments

The study provides valuable insights into the mechanisms of protection conferred by the 3D11 anti-CSP monoclonal antibody against P. berghei sporozoites and this finding allow the field to speculate that other monoclonal antibodies against CSP of P. Falciparum may act similarly. However, an important experiment is missing that would significantly strengthen the conclusions. Specifically, the authors should perform experiments where the monoclonal antibody is added immediately after the sporozoites have completed invasion. This should be done both in vitro and in vivo to show whether the antibody has any effect on intracellular development of liver stages when added after invasion.

While the claims are generally supported by the data presented, to comprehensively conclude the late cytotoxic effects of 3D11, the additional experiment of post-invasion antibody application is relevant. This would help determine if the observed effects are due to the antibody's action during invasion or its continued action post-invasion.

The data and methods are presented in a manner that allows for reproducibility. The use of microscopy and bioluminescence imaging is well-documented. The experiments appear adequately replicated, and statistical analyses are appropriate.

Minor Comments

The text and figures are clear and accurate. Some minor typographical errors should be corrected.

Significance

The study's strengths lie in its detailed analysis of the 3D11 mAb's effect on sporozoite motility and liver stage development. The use of advanced imaging techniques adds robustness to the findings. The main limitation is the lack of data on the antibody's effect post-invasion. Additionally, the study's conclusions are based on a single monoclonal antibody and its target region, which may not be representative of other anti-CSP antibodies. Still, the findings offer insights into the cytotoxic action of anti-CSP antibodies, which could inform the development of more effective malaria vaccines and therapeutic antibodies.

This research will primarily interest a specialized audience in malaria research, particularly those focused on vaccine development and antibody therapeutics. It also holds value for broader audiences in immunology and infectious disease research.

My expertise: Malaria research and liver invasion by Plasmodium sporozoites

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Referee #1

Evidence, reproducibility and clarity

The study by Aguirre-Botero et al. shows the dynamics of 3D11 anti-CSP monoclonal antibody (mAb) mediated elimination of rodent malaria Plasmodium berghei (Pb) parasites in the liver. The authors show that the anti-CSP mAb could protect against intravenous (i.v.) Pb sporozoite challenge along with the cutaneous challenge, but requires higher concentration of antibody. Importantly, the study shows that the anti-CSP mAb not only affects sporozoite motility, sinusoidal extravasation, and cell invasion but also partially impairs the intracellular development inside the liver parenchyma, indicating a late effect of this antibody during liver stage development. While the study is interesting and conducted well, the only novel yet very important observation made in this manuscript is the effect of the anti-CSP mAb on liver stage development.

Major

This observation is highlighted in the manuscript title but is supported by only limited data. A such it needs to be substantiated and a mechanism should be investigated.

• The phenomenon of intracellular effects of the anti-CSP mAb should be analyzed in much more detail. For example, can the authors demonstrate uptake of the Ab together with the parasite during hepatocyte invasion? What cellular mechanism leads to elimination?

Minor

• Line 44 - 43: The statement is applicable only to the rodent infecting Plasmodium parasites. The authors need to clarify that.
• Line 68: Replace the second 'against' after the CSP with 'of'.
• Line 141 - 143: The 3D11 mAb does affect the homing and killing in the blood of cutaneous injected sporozoites. The authors need to clearly state that the statement is true only for i.v. injected sporozoites.
• Figure 3B: The numbers of sporozoites detected in the experiment varies from 0 h (line 172) to 2 h (line 184). Therefore, the numbers need to be mentioned on all the bars of each timepoint.
• Figure 3C: If the authors have used flk1-GFP mice, then how well they were able to detect the Pb-PfCSP GFP parasites in the vessel vs. parenchyma in the intravital imaging? The representative images for Pb-PfCSP GFP should also be included.
• It is not mentioned anywhere how the viability of the sporozoites was determined. This has to be described especially in the methods section.
• Also, the flow acquisition and data analysis of the sporozoites and infected HepG2 cells must be described in the method section.
• Figure 4: The flow layouts should be included for at least comparing the 0 vs. 5 μg/ml of 3D11 mAb concentrations.
• Lines 234 - 243; 308 - 325: These results are the gist of the entire study and also defined the title of the manuscript. Thus, it would be pre-mature to claim the substantial effect of 3D11 antibody in late killing of the parasite in the infected hepatocytes just by looking at the decreased GFP fluorescence. The authors need to at least verify the fitness of the liver stages by measuring the size of the developing parasites as well as using different parasite specific markers (UIS4, MSP1, HSP70 etc.) in immunofluorescence assays on the infected liver sections and in vitro infections.
• Line 651 (Figure S1 legend): Typographical error '14'.

Significance

The phenomenon of intracellular effects of the anti-CSP Ab is the only novel observation and as such, should be analyzed in much more detail. For example, can the authors demonstrate uptake of the Ab together with the parasite during hepatocyte invasion? What cellular mechanism leads to elimination?

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Reply to the reviewers

Reply to the Reviewers

I would like to thank the reviewers for their comments and interest in the manuscript and the study.

Referee #1

1. I would assume that there are RNA-seq and/or ChIP-seq data out there produced after knockdown of one or more of these DBPs that show directional positioning.

Response: As the reviewer pointed out, a wet experimental validation of the results of this study would give an opportunity for more biological researchers to have an interest in the study. I plan to promote the wet experimental analysis in collaboration with biological experimental researchers as a next step of this study. The same analysis would be performed in immortalized cells for CRISPR experiment (e.g. Guo Y et al. Cell 2015).

1. Figure 6 should be expanded to incorporate analysis of DBPs not overlapping CTCF/cohesin in chromatin interaction data that is important and potentially more interesting than the simple DBPs enrichment reported in the present form of the figure.

Response: Following the reviewer's advice, I performed the same analysis with the DNA-binding sites that do no overlap with the DNA-binding sites of CTCF and cohesin (RAD21 and SMC3) (Fig. 6 and Supplementary Fig. 3). The result showed the same tendency in the distribution of DNA-binding sites. The height of a peak on the graph became lower for some DNA-binding proteins after removing the DNA-binding sites that overlapped with those of CTCF and cohesin. I have added the following sentence on lines 359 and 705: For the insulator-associated DBPs other than CTCF, RAD21, and SMC3, the DNA-binding sites that do not overlap with those of CTCF, RND21, and SMC3 were used to examine their distribution around interaction sites.

1. Critically, I would like to see use of Micro-C/Hi-C data and ChIP-seq from these factors, where insulation scores around their directionally-bound sites show some sort of an effect like that presumed by the authors - and many such datasets are publicly-available and can be put to good use here.

Response: As suggested by the reviewer, I have added the insulator scores and boundary sites from the 4D nucleome data portal as tracks in the UCSC genome browser. The insulator scores seem to correspond to some extent to the H3K27me3 histone marks from ChIP-seq (Fig. 4a and Supplementary Fig. 2). The direction of DNA-binding sites on the genome can be shown with different colors (e.g. red and green), but the directionality is their overall tendency, and it may be difficult to notice the directionality from each binding site.

I found that the CTCF binding sites examined by a wet experiment in the previous study may not always overlap with the boundary sites of chromatin interactions from Micro-C assay (Guo Y et al. Cell 2015). The chromatin interaction data do not include all interactions due to the high sequencing cost of the assay. The number of the boundary sites may be smaller than that of CTCF binding sites acting as insulators and/or some of the CTCF binding sites may not be locate in the boundary sites. It may be difficult for the boundary location algorithm to identify a short boundary location. Due to the limitations of the chromatin interaction data, I planned to search for insulator-associated DNA-binding proteins without using chromatin interaction data in this study.

1. The suggested alternative transcripts function, also highlighted in the manuscripts abstract, is only supported by visual inspection of a few cases for several putative DBPs. I believe this is insufficient to support what looks like one of the major claims of the paper when reading the abstract, and a more quantitative and genome-wide analysis must be adopted, although the authors mention it as just an 'observation'.

Response: According to the reviewer's comment, I performed the genome-wide analysis of alternative transcripts where the DNA-binding sites of insulator-associated proteins are located near splicing sites. The DNA-binding sites of insulator-associated DNA-binding proteins were found within 200bp centered on splice sites more significantly than the other DNA-binding proteins (Fig. 4E and Table 2). I have added the following sentences on lines 329 - 337: We performed the statistical test to estimate the enrichment of insulator-associated DNA-binding sites compared to the other DNA-binding proteins, and found that the insulator-associated DNA-binding sites were significantly more abundant at splice sites than the DNA-binding sites of the other proteins (Fig 4e and Table 2; Mann‒Whitney U test, p value 5. Figure 1 serves no purpose in my opinion and can be removed, while figures can generally be improved (e.g., the browser screenshots in Figs 4 and 5) for interpretability from readers outside the immediate research field.

Response: I believe that the Figure 1 would help researchers in other fields who are not familiar with biological phenomena and functions to understand the study. More explanation has been included in the Figures and legends of Figs. 4 and 5 to help readers outside the immediate research field understand the figures.

1. Similarly, the text is rather convoluted at places and should be re-approached with more clarity for less specialized readers in mind.

Response: Reviewer #2's comments would be related to this comment. I have introduced a more detailed explanation of the method in the Results section, as shown in the responses to Reviewer #2's comments.

Referee #2

1. Introduction, line 95: CTCF appears two times, it seems redundant.

Response: On lines 91-93, I deleted the latter CTCF from the sentence "and examined the directional bias of DNA-binding sites of CTCF and insulator-associated DBPs, including those of known DBPs such as RAD21 and SMC3".

1. Introduction, lines 99-103: Please stress better the novelty of the work. What is the main focus? The new identified DPBs or their binding sites? What are the "novel structural and functional roles of DBPs" mentioned?

Response: Although CTCF is known to be the main insulator protein in vertebrates, we found that 97 DNA-binding proteins including CTCF and cohesin are associated with insulator sites by modifying and developing a machine learning method to search for insulator-associated DNA-binding proteins. Most of the insulator-associated DNA-binding proteins showed the directional bias of DNA-binding motifs, suggesting that the directional bias is associated with the insulator.

I have revised the statement in lines 97-104 as follows: To validate these findings, we demonstrate that the DNA-binding sites of the identified insulator-associated DBPs are located within potential insulator sites, and some of the DNA-binding sites in the insulator site are found without the nearby DNA-binding sites of CTCF and cohesin. Our method and analyses contribute to the identification of insulator- and chromatin-associated DNA-binding sites that influence EPIs and reveal novel functional roles and molecular mechanisms of DBPs associated with transcriptional condensation, phase separation and transcriptional regulation.

1. Results, line 111: How do the SNPs come into the procedure? From the figures it seems the input is ChIP-seq peaks of DNBPs around the TSS.

Response: On lines 115-118, to explain the procedure for the SNP of an eQTL, I have added the sentence in the Methods: "If a DNA-binding site was located within a 100-bp region around a single-nucleotide polymorphism (SNP) of an eQTL, we assumed that the DNA-binding proteins regulated the expression of the transcript corresponding to the eQTL".

1. Again, are those SNPs coming from the different cell lines? Or are they from individuals w.r.t some reference genome? I suggest a general restructuring of this part to let the reader understand more easily. One option could be simplifying the details here or alternatively including all the necessary details.

Response: On line 113, I have included the explanation of the eQTL dataset of GTEx v8 as follows: "The GTEx v8 dataset, after quality control, consists of 838 donors and 17,382 samples from 52 tissues and two cell lines". On lines 569 and 753, I have added the filename of the eQTL data "(GTEx_Analysis_v8_eQTL.tar)".

1. Figure 1: panel a and b are misleading. Is the matrix in panel a equivalent to the matrix in panel b? If not please clarify why. Maybe in b it is included the info about the SNPs? And if yes, again, what is then difference with a.

Response: The reviewer would mention Figure 2, not Figure 1. If so, the matrices in panels a and b in Figure 2 are equivalent. The green boxes in the matrix show the regions with the ChIP-seq peak of a DNA-binding protein overlapping with a SNP of an eQTL. I used eQTL data to associate a gene with a ChIP-seq peak that was more than 2 kb upstream and 1 kb downstream of a transcriptional start site of a gene. For each gene, the matrix was produced and the gene expression levels in cells were learned and predicted using the deep learning method. I have added the following sentences to explain the method in lines 125 - 131: Through the training, the tool learned to select the binding sites of DNA-binding proteins from ChIP-seq assays that were suitable for predicting gene expression levels in the cell types. The binding sites of a DNA-binding protein tend to be observed in common across multiple cell and tissue types. Therefore, ChIP-seq data and eQTL data in different cell and tissue types were used as input data for learning, and then the tool selected the data suitable for predicting gene expression levels in the cell types.

1. Line 386-388: could the author investigate in more detail this observation? Does it mean that loops driven by other DBPs independent of the known CTCF/Cohesin? Could the author provide examples of chromatin structural data e.g. MicroC?

Response: As suggested by the reviewer, to help readers understand the observation, I have added Supplementary Fig. S3c to show the distribution of DNA-binding sites of "CTCF, RAD21, and SMC3" and "BACH2, FOS, ATF3, NFE2, and MAFK" around chromatin interaction sites. I have modified the following sentence to indicate the figure on line 417: Although a DNA-binding-site distribution pattern around chromatin interaction sites similar to those of CTCF, RAD21, and SMC3 was observed for DBPs such as BACH2, FOS, ATF3, NFE2, and MAFK, less than 1% of the DNA-binding sites of the latter set of DBPs colocalized with CTCF, RAD21, or SMC3 in a single bin (Fig. S3c).

In Aljahani A et al. Nature Communications 2022, we find that depletion of cohesin causes a subtle reduction in longer-range enhancer-promoter interactions and that CTCF depletion can cause rewiring of regulatory contacts. Together, our data show that loop extrusion is not essential for enhancer-promoter interactions, but contributes to their robustness and specificity and to precise regulation of gene expression. Goel VY et al. Nature Genetics 2023 mentioned in the abstract: Microcompartments frequently connect enhancers and promoters and though loss of loop extrusion and inhibition of transcription disrupts some microcompartments, most are largely unaffected. These results suggested that chromatin loops can be driven by other DBPs independent of the known CTCF/Cohesin. I added the following sentence on 470: The depletion of cohesin causes a subtle reduction in longer-range enhancer-promoter interactions and that CTCF depletion can cause rewiring of regulatory contacts. The loop extrusion is not essential for enhancer-promoter interactions, but contributes to their robustness and specificity and to precise regulation of gene expression.

FOXA1 pioneer factor functions as an initial chromatin-binding and chromatin-remodeling factor and has been reported to form biomolecular condensates (Ji D et al. Molecular Cell 2024). CTCF have also found to form transcriptional condensate and phase separation (Lee R et al. Nucleic acids research 2022). FOS was found to be an insulator-associated DNA-binding protein in this study and is potentially involved in chromatin remodeling, transcription condensation, and phase separation with the other factors such as BACH2, ATF3, NFE2 and MAFK. I have added the following sentence on line 467: FOXA1 pioneer factor functions as an initial chromatin-binding and chromatin-remodeling factor and has been reported to form biomolecular condensates.

1. In general, how the presented results are related to some models of chromatin architecture, e.g. loop extrusion, in which it is integrated convergent CTCF binding sites?

Response: Goel VY et al. Nature Genetics 2023 identified highly nested and focal interactions through region capture Micro-C, which resemble fine-scale compartmental interactions and are termed microcompartments. In the section titled "Most microcompartments are robust to loss of loop extrusion," the researchers noted that a small proportion of interactions between CTCF and cohesin-bound sites exhibited significant reductions in strength when cohesin was depleted. In contrast, the majority of microcompartmental interactions remained largely unchanged under cohesin depletion. Our findings indicate that most P-P and E-P interactions, aside from a few CTCF and cohesin-bound enhancers and promoters, are likely facilitated by a compartmentalization mechanism that differs from loop extrusion. We suggest that nested, multiway, and focal microcompartments correspond to small, discrete A-compartments that arise through a compartmentalization process, potentially influenced by factors upstream of RNA Pol II initiation, such as transcription factors, co-factors, or active chromatin states. It follows that if active chromatin regions at microcompartment anchors exhibit selective "stickiness" with one another, they will tend to co-segregate, leading to the development of nested, focal interactions. This microphase separation, driven by preferential interactions among active loci within a block copolymer, may account for the striking interaction patterns we observe.

The authors of the paper proposed several mechanisms potentially involved in microcompartments. These mechanisms may be involved in looping with insulator function. Maz and MyoD1 among the identified insulator-associated DNA-binding proteins form loops without CTCF (Xiao T et al. Proc Natl Acad Sci USA 2021 ; Ortabozkoyun H et al. Nature genetics 2022 ; Wang R et al. Nature communications 2022). If chromatin loop anchors have some structural conformation, as shown in the paper entitled "The structural basis for cohesin-CTCF-anchored loops" (Li Y et al. Nature 2020), directional DNA binding would occur similarly to CTCF binding sites. I have included the following explanation on line 476: Maz and MyoD1 among the identified insulator-associated DNA-binding proteins form loops without CTCF.

1. Do the authors think that the identified DBPs could work in that way as well?

Response: Liquid-liquid phase separation was shown to occur through CTCF-mediated chromatin loops and to act as an insulator (Lee, R et al. Nucleic Acids Research 2022). Among the identified insulator-associated DNA-binding proteins, CEBPA has been found to form hubs that colocalize with transcriptional co-activators in a native cell context, which is associated with transcriptional condensate and phase separation (Christou-Kent M et al. Cell Reports 2023). The proposed microcompartment mechanisms are also associated with phase separation. Thus, the same or similar mechanisms are potentially associated with the insulator function of the identified DNA-binding proteins. I have included the following information on line 465: CEBPA in the identified insulator-associated DNA-binding proteins was also reported to be involved in transcriptional condensates and phase separation.

1. Also, can the authors comment about the mechanisms those newly identified DBPs mediate contacts by active processes or equilibrium processes?

Response: Snead WT et al. Molecular Cell 2019 mentioned that protein post-transcriptional modifications (PTMs) facilitate the control of molecular valency and strength of protein-protein interactions. O-GlcNAcylation as a PTM inhibits CTCF binding to chromatin (Tang X et al. Nature Communications 2024). I found that the identified insulator-associated DNA-binding proteins tend to form a cluster at potential insulator sites (Supplemental Fig. 2d). These proteins may interact and actively regulate chromatin interactions, transcriptional condensation, and phase separation by PTMs. I have added the following explanation on lines 478-484: Furthermore, protein post-transcriptional modifications (PTMs) facilitate control over the molecular valency and strength of protein-protein interactions. O-GlcNAcylation as a PTM inhibits CTCF binding to chromatin. We found that the identified insulator-associated DNA-binding proteins tend to form a cluster at potential insulator sites (Supplementary Fig. 2d). These proteins may interact and actively regulate chromatin interactions, transcriptional condensation, and phase separation through PTMs.

1. Can the author provide some real examples along with published structural data (e.g. the mentioned micro-C data) to show the link between protein co-presence, directional bias and contact formation?

Response: Structural molecular model of cohesin-CTCF-anchored loops has been published by Li Y et al. Nature 2020. The structural conformation of CTCF and cohesin in the loops would be the cause of the directional bias of CTCF binding sites, which I mentioned in lines 454 - 458.

Referee #3

1. Some of these TFs do not have specific direct binding to DNA (P300, Cohesin). Since the authors are using binding motifs in their analysis workflow, I would remove those from the analysis.

Response: When a protein complex binds to DNA, one protein of the complex binds to the DNA directory, and the other proteins may not bind to DNA. However, the DNA motif sequence bound by the protein may be registered as the DNA-binding motif of all the proteins in the complex. The molecular structure of the complex of CTCF and Cohesin showed that both CTCF and Cohesin bind to DNA (Li Y et al. Nature 2020). I think there is a possibility that if the molecular structure of a protein complex becomes available, the previous recognition of the DNA-binding ability of a protein may be changed. Therefore, I searched the Pfam database for 99 insulator-associated DNA-binding proteins identified in this study. I found that 97 are registered as DNA-binding proteins and/or have a known DNA-binding domain, and EP300 and SIN3A do not directory bind to DNA, which was also checked by Google search. I have added the following explanation in line 239 to indicate direct and indirect DNA-binding proteins: Among 99 insulator-associated DBPs, EP300 and SIN3A do not directory interact with DNA, and thus 97 insulator-associated DBPs directory bind to DNA. I have updated the sentence in line 22 of the Abstract as follows: We discovered 97 directional and minor nondirectional motifs in human fibroblast cells that corresponded to 23 DBPs related to insulator function, CTCF, and/or other types of chromosomal transcriptional regulation reported in previous studies.

1. I am not sure if I understood correctly, by why do the authors consider enhancers spanning 2Mb (200 bins of 10Kb around eSNPs)? This seems wrong. Enhancers are relatively small regions (100bp to 1Kb) and only a very small subset form super enhancers.

Response: As the reviewer mentioned, I recognize enhancers are relatively small regions. In the paper, I intended to examine further upstream and downstream of promoter regions where enhancers are found. Therefore, I have modified the sentence in line 805 of the Fig. 2 legend as follows: Enhancer-gene regulatory interaction regions consist of 200 bins of 10 kbp between -1 Mbp and 1 Mbp region from TSS, not including promoter.

1. I think the H3K27me3 analysis was very good, but I would have liked to see also constitutive heterochromatin as well, so maybe repeat the analysis for H3K9me3.

Response: Following the reviewer's advice, I have added the ChIP-seq data of H3K9me3 as a truck of the UCSC Genome Browser. The distribution of H3K9me3 signal was different from that of H3K27me3 in some regions. I also found the insulator-associated DNA-binding sites close to the edges of H3K9me3 regions, but the number of the sites may be less than for H3K27me3. I took some screenshots of the UCSC Genome Browser of the regions around the sites in Supplementary Fig. 2b. I have modified the following sentence on line 853 in the legend of Fig. 4: a Distribution of histone modification marks H3K27me3 (green color) and H3K9me3 (turquoise color) and transcript levels (pink color) in upstream and downstream regions of a potential insulator site (light orange color). I have also added the following result on lines 313 - 316: The same analysis was performed using H3K9me3 marks, instead of H3K27me3. We found that the distribution of H3K9me3 signal was different from that of H3K27me3 in some regions, and discovered the insulator-associated DNA-binding sites close to the edges of H3K9me3 regions (Fig. S2b).

1. I was not sure I understood the analysis in Figure 6. The binding site is with 500bp of the interaction site, but micro-C interactions are at best at 1Kb resolution. They say they chose the centre of the interaction site, but we don't know exactly where there is the actual interaction. Also, it is not clear what they measure. Is it the number of binding sites of a specific or multiple DBP insulator proteins at a specific distance from this midpoint that they recover in all chromatin loops? Maybe I am missing something. This analysis was not very clear.

Response: The resolution of the Micro-C assay is considered to be 100bp and above, as the human nucleome core particle contains 145bp (and 193bp with linker) of DNA. However, internucleosomal DNA is cleaved by endonuclease into fragments of multiples of 10 nucleotides (Pospelov VA et al. Nucleic Acids Research 1979). Highly nested focal interactions were observed (Goel VY et al. Nature Genetics 2023). Base pair resolution was reported using Micro Capture-C (Hua P et al. Nature 2021). Sub-kilobase (20bp resolution) chromatin topology was reported using an MNase-based chromosome conformation capture (3C) approach (Aljahani A et al. Nature Communications 2022). On the other hand, Hi-C data was analyzed at 1kb resolution. (Gu H et al. bioRxiv 2021). If the resolution of Micro-C interactions is at best at 1kb, the binding sites of a DNA-binding protein will not show a peak around the center of the genomic locations of interaction edges. Each panel shows the number of binding sites of a specific DNA-binding protein at a specific distance from the midpoint of all chromatin interaction edges. I have modified and added the following sentences in 487-491: High-resolution chromatin interaction data from a Micro-C assay indicated that most of the predicted insulator-associated DBPs showed DNA-binding-site distribution peaks around chromatin interaction sites, suggesting that these DBPs are involved in chromatin interactions and that the chromatin interaction data has a high degree of resolution. Base pair resolution was reported using Micro Capture-C.

Minor comments:

1. PIQ does not consider TF concentration. Other methods do that and show that TF concentration improves predictions (e.g., https://www.biorxiv.org/content/10.1101/2023.07.15.549134v2 or https://pubmed.ncbi.nlm.nih.gov/37486787/). The authors should discuss how that would impact their results.

Response: The directional bias of CTCF binding sites was identified by ChIA-pet interactions of CTCF binding sites. The analysis of the contribution scores of DNA-binding sites of proteins considering the binding sites of CTCF as an insulator showed the same tendency of directional bias of CTCF binding sites. In the analysis, to remove the false-positive prediction of DNA-binding sites, I used the binding sites that overlapped with a ChIP-seq peak of the DNA-binding protein. This result suggests that the DNA-binding sites of CTCF obtained by the current analysis have sufficient quality. Therefore, if the accuracy of prediction of DNA-binding sites is improved, althought the number of DNA-binding sites may be different, the overall tendency of the directionality of DNA-binding sites will not change and the results of this study will not change significantly.

As for the first reference in the reviewer's comment, chromatin interaction data from Micro-C assay does not include all chromatin interactions in a cell or tissue, because it is expensive to cover all interactions. Therefore, it would be difficult to predict all chromatin interactions based on machine learning. As for the second reference in the reviewer's comment, pioneer factors such as FOXA are known to bind to closed chromatin regions, but transcription factors and DNA-binding proteins involved in chromatin interactions and insulators generally bind to open chromatin regions. The search for the DNA-binding motifs is not required in closed chromatin regions.

1. DeepLIFT is a good approach to interpret complex structures of CNN, but is not truly explainable AI. I think the authors should acknowledge this.

Response: In the DeepLIFT paper, the authors explain that DeepLIFT is a method for decomposing the output prediction of a neural network on a specific input by backpropagating the contributions of all neurons in the network to every feature of the input (Shrikumar A et al. ICML 2017). DeepLIFT compares the activation of each neuron to its 'reference activation' and assigns contribution scores according to the difference. DeepLIFT calculates a metric to measure the difference between an input and the reference of the input.

Truly explainable AI would be able to find cause and reason, and to make choices and decisions like humans. DeepLIFT does not perform causal inferences. I did not use the term "Explainable AI" in our manuscript, but I briefly explained it in Discussion. I have added the following explanation in lines 503-508: AI (Artificial Intelligence) is considered as a black box, since the reason and cause of prediction are difficult to know. To solve this issue, tools and methods have been developed to know the reason and cause. These technologies are called Explainable AI. DeepLIFT is considered to be a tool for Explainable AI. However, DeepLIFT does not answer the reason and cause for a prediction. It calculates scores representing the contribution of the input data to the prediction.

Furthermore, to improve the readability of the manuscript, I have included the following explanation in lines 152-158: we computed DeepLIFT scores of the input data (i.e., each binding site of the ChIP-seq data of DNA-binding proteins) in the deep leaning analysis on gene expression levels. DeepLIFT compares the importance of each input for predicting gene expression levels to its 'reference or background level' and assigns contribution scores according to the difference. DeepLIFT calculates a metric to measure the difference between an input and the reference of the input.

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Referee #3

Evidence, reproducibility and clarity

Summary:

Osato and Hamada propose a systematic approach to identify DNA binding proteins that display directional binding. They used a modified Deep Learning method (DEcode) to investigate binding profiles of 1356 DBP from GTRD database at promoters (30 of 100bp bins around TSS) and enhancers (200 bins of 10Kb around eSNPs) and use this to predict expression of 25,071 genes in Fibroblasts, Monocytes, HMEC and NPC. This method achieves a good prediction power (Spearman correlation between predicted and actual expression of 0.74). They then use PIQ, and overlap predicted binding sites with actual ChIP-seq data to investigate the motifs of TFs that are controlling gene expression. They find 99 insulator proteins showing either a specific directional bias or minor non-directional bias, corresponding to 23 DBP previously reported to have insulator function. Of the 23 proteins they identify as regulating enhancer promoter interactions, 13 are associated with CTCF. They also show that there are significantly more insulator proteins binding sites at borders of polycomb domains, transcriptionally active or boundary regions based on chromatin interactions than other proteins.

Major Comments:

1. Some of these TFs do not have specific direct binding to DNA (P300, Cohesin). Since the authors are using binding motifs in their analysis workflow, I would remove those from the analysis.
2. I am not sure if I understood correctly, by why do the authors consider enhancers spanning 2Mb (200 bins of 10Kb around eSNPs)? This seems wrong. Enhancers are relatively small regions (100bp to 1Kb) and only a very small subset form super enhancers.
3. I think the H3K27me3 analysis was very good, but I would have liked to see also constitutive heterochromatin as well, so maybe repeat the analysis for H3K9me3.
4. I was not sure I understood the analysis in Figure 6. The binding site is with 500bp of the interaction site, but micro-C interactions are at best at 1Kb resolution. They say they chose the centre of the interaction site, but we don't know exactly where there is the actual interaction. Also, it is not clear what they measure. Is it the number of binding sites of a specific or multiple DBP insulator proteins at a specific distance from this midpoint that they recover in all chromatin loops? Maybe I am missing something. This analysis was not very clear.

Minor comments:

1. PIQ does not consider TF concentration. Other methods do that and show that TF concentration improves predictions (e.g., https://www.biorxiv.org/content/10.1101/2023.07.15.549134v2 or https://pubmed.ncbi.nlm.nih.gov/37486787/). The authors should discuss how that would impact their results.
2. DeepLIFT is a good approach to interpret complex structures of CNN, but is not truly explainable AI. I think the authors should acknowledge this.

Referee Cross-Commenting

I would like to mention that I agree with the comments of reviewers 1 and 2.

Significance

General assessment:

This is the first study to my knowledge that attempts to use Deep Learning to identify insulators and directional biases in binding. One of the limitations is that no additional methods were used to show that these DBP have directional binding bias. It is not necessarily to employ additional methods, but it would definitely strengthen the paper.

Advancements:

This is a useful catalogue of potential DNA binding proteins of interest, beyond just CTCF. Some known TFs are there, but also new ones are found.

Audience:

Basic research mainly, with particular focus on chromatin conformation and TF binding fields.

My expertise:

ML/AI methods in genomics, TF binding models, epigenetics and 3D chromatin interactions.

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Referee #2

Evidence, reproducibility and clarity

In this work, the authors describe a deep learning computational tool to identity binding motifs of DNA binding proteins associated to insulators that led to the discovery of 99 motifs related to insulation. This is in turn related to chromatin architecture and highlight the importance of directional bias in order to form chromatin loops.

In general, there are some aspects to be clarified and better explored to make stronger conclusions. In particular, there are some aspects to clarify in the text about the Machine Learning procedure (see my points below). In addition, I have some general questions about the biological implications of the discussed findings, listed in detail in the following list.

Also, I encourage the authors to integrate the current presentation of the data with other (published) data about chromatin architecture, to make more robust the claims and go deeper into the biological implications of the current work. Se my list below.

It follows a specific list of relevant points to be addressed:

Specific points:

1. Introduction, line 95: CTCF appears two times, it seems redundant;
2. Introduction, lines 99-103: Please stress better the novelty of the work. What is the main focus? The new identified DPBs or their binding sites? What are the "novel structural and functional roles of DBPs" mentioned?
3. Results, line 111: How do the SNPs come into the procedure? From the figures it seems the input is ChIP-seq peaks of DNBPs around the TSS;
4. Again, are those SNPs coming from the different cell lines? Or are they from individuals w.r.t some reference genome? I suggest a general restructuring of this part to let the reader understand more easily. One option could be simplifying the details here or alternatively including all the necessary details;
5. Figure 1: panel a and b are misleading. Is the matrix in panel a equivalent to the matrix in panel b? If not please clarify why. Maybe in b it is included the info about the SNPs? And if yes, again, what is then difference with a.
6. Line 386-388: could the author investigate in more detail this observation? Does it mean that loops driven by other DBPs independent of the known CTCF/Cohesin? Could the author provide examples of chromatin structural data e.g. MicroC?
7. In general, how the presented results are related to some models of chromatin architecture, e.g. loop extrusion, in which it is integrated convergent CTCF binding sites?
8. Do the authors think that the identified DBPs could work in that way as well?
9. Also, can the authors comment about the mechanisms those newly identified DBPs mediate contacts by active processes or equilibrium processes?
10. Can the author provide some real examples along with published structural data (e.g. the mentioned micro-C data) to show the link between protein co-presence, directional bias and contact formation?

Significance

In this work, the authors describe a deep learning computational tool to identity binding motifs of DNA binding proteins associated to insulators that led to the discovery of 99 motifs related to insulation. This is in turn related to chromatin architecture and highlight the importance of directional bias in order to form chromatin loops.

In general, chromatin organization is an important topic in the context of a constantly expanding research field. Therefore, the work is timely and could be useful for the community. The paper appears overall well written and the figures look clear and of good quality. Nevertheless, there are some aspects to be clarified and better explored to make stronger conclusions. In particular, there are some aspects to clarify in the text about the Machine Learning procedure (see list of specific points). In addition, I have some general questions about the biological implications of the discussed findings, listed in detail in the above reported points.

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Referee #1

Evidence, reproducibility and clarity

The study by Osato and Hamada aims at computationally identifying a set of novel putative insulator-associated DNA binding proteins (DBPs) via estimation of their contribution to the expression of genes in the same chromosome region of their binding sites (+- 1Mbp from TSS). To achieve this, the authors leverage a deep learning architecture already published via which ChIP-seq peaks of DBPs in the TSS of a given gene are used to predict its expression level in four human cell lines.

Building on this, the authors used another tool called DeepLIFT to evaluate the weight of each DBP binding site on the final gene expression value. Hence they made the assumption that if a given DBP had an insulator function they could restrict the prediction of the gene's expression to the region included between pairs of that DBP binding sites, and evaluate the pair's motif directionality bias in the distribution of weights. They exemplify their approach's validity by the fact that they can predict the known directionality bias of CTCF/cohesin-bound sites as the highest of the lot, with the F-R orientation of the pairs the most enriched, recapitulating what already known in literature: i.e., that F-R chromatin interaction peaks are the most enriched. In addition, they find several new DBPs showing significant directionality bias; hence they could be candidates for insulation activity. They then provide correlation between these putative insulator binding sites and sites of transition between euchromatin and heterochromatin by independently using histone mark and gene expression datasets. This, of course, is not surprising because (a) there is insulation between regions with heterotypic chromatin identities, and (b) it was already known from the first papers describing insulated chromatin domains that their boundaries were well-enriched for active transcription and transcriptional regulators (e.g., Dixon et al, Nature 2012).

Finally, they use chromatin interaction (looping) sites to check the overlap between CTCF and all other DBPs and define a subset of putative insulator DBPs not overlapping CTCF peaks, suggesting potentially new insulatory mechanisms. These factors were all known transcriptional activators, but this part of the findings carry most of the novelty in the work and have the potential of opening up new directions for research in chromatin organization.

Overall, the methodology applied here is adequate, clear, and reproducible. The major issue, in our view, is that the entire manuscript's findings relies on the usage of deepLIFT, a tool which was not benchmarked previously or by the current study. In fact, deepLIFT is public as regards its code, and also appears as a preprint from 2017 on biorXiv and published in the Proceedings of Machine Learning Research conference. Also, this key tool was developed by the Kundaje lab (who produce high quality alogrithms), and not by the authors. Therefore, the manuscript is predominantly based on the execution of existing workflows to publicly-available data. This does not take anything away from the interesting question posed here, but at the same time does not provide the community with any new algorithm/workflow.

Finally, although I appreciate that the authors are purely computational and have likely no capacity for experimental validation of their claims of new DBPs having insulator roles, I would assume that there are RNA-seq and/or ChIP-seq data out there produced after knockdown of one or more of these DBPs that show directional positioning. Using this kind of data, effects on gene expression can at least be tested in regard to the authors' predictions. Moreover, in terms of validation, Figure 6 should be expanded to incorporate analysis of DBPs not overlapping CTCF/cohesin in chromatin interaction data that is important and potentially more interesting than the simple DBPs enrichment reported in the present form of the figure. Critically, I would like to see use of Micro-C/Hi-C data and ChIP-seq from these factors, where insulation scores around their directionally-bound sites show some sort of an effect like that presumed by the authors - and many such datasets are publicly-available and can be put to good use here.

As secondary issues, we would point out that:

• The suggested alternative transcripts function, also highlighted in the manuscript;s abstract, is only supported by visual inspection of a few cases for several putative DBPs. I believe this is insufficient to support what looks like one of the major claims of the paper when reading the abstract, and a more quantitative and genome-wide analysis must be adopted, although the authors mention it as just an 'observation'.
• Figure 1 serves no purpose in my opinion and can be removed, while figures can generally be improved (e.g., the browser screenshots in Figs 4 and 5) for interpretability from readers outside the immediate research field.
• Similarly, the text is rather convoluted at places and should be re-approached with more clarity for less specialized readers in mind.

Significance

The scientific novelty of the work lies primarily in the identification of a set of DBPs that are proposed to confer insulator activity genome-wide. This has been long sought after in human data (whilst it is well understood and defined in Drosophila). The authors produce a quantitative ranking of the putative insulation effect of these DBPs and, most importantly, go on to identify a smaller subset that are apparently non-overlapping with anchors of CTCF-cohesin loop anchors; the presence of strong motif orientation biases in many DBPs can also be of broad interest, especially those that cannot be trivially ascribable to the loop extrusion process.

However, although these findings open the way for speculation on multiple insulation mechanisms via proteins with multiple regulatory functions, the manuscript provide no experimental or computational means to test the proposed roles of these DBPs - and, as such, this limits the potential impact of the work and mostly targets researchers in the field of genome organization that can test these findings. Having said this, if validated, this work can significantly broaden our understanding of how chromatin is organized in 3D nuclear space.

I typically identify myself to the authors: A. Papantonis, expertise in 3D genome architecture, chromatin biology, and genomics/bioinformatics.

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Reply to the reviewers

We sincerely thank all three reviewers for their professional and constructive feedback. We appreciate the thorough evaluation of our manuscript and are committed to revising both the manuscript and supplemental materials based on the suggestions. We have carefully considered each comment and have addressed most of them in the initial revised version, which has been transferred. Additionally, we are currently conducting new experiments to provide the requested data to address a few comments. We are confident that these revision experiments will be completed in a couple of months or so, which will significantly enhance the quality of our study.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

In the manuscript by Agarwal and Ghosh, the authors examine yeast Scm3 function in the DNA damage response. They show that Scm3 loss results in DNA damage sensitivity and more Rad52 foci. Importantly, Scm3 is recruited to DSB sites using an HO-cut site and its loss results in an attenuated DNA damage checkpoint as measured by Rad53 phosphorylation. The authors demonstrate convincingly that Scm3, like its human counterpart HJURP, plays a role in the DNA damage response through altered Rad53 activation. However, what its specific role in DNA repair is remains ambiguous.

Major comments:

1. It is unusual to see multiple DNA repair foci as those observed in Figure 2B. What is the distribution of cells with 1, 2, 3, 4, or more foci? Are more observed in SCM3-AID cells perhaps suggesting that the DSB ends are not being clustered as would be expected in WT cells exposed to DNA damage?

Response: As per the reviewer’s comment, we have included a graph (Figure R2) showing the distribution of cells with 1, 2, 3, 4, or more Rad52-GFP foci when they are treated with MMS. There are more cells with 4 or more foci when Scm3 is depleted (SCM3-AID + Auxin) compared to the wild type (SCM3-AID). The average number of Rad52-GFP foci per cell presented in Figure 2B (2.8 in the mutant vs. 1.9 in the wild type) is well in accord with the previous report (Conde and San-Segundo, 2008), where the same was reported as ~2.5 in the cells lacking a methyl transferase Dot1, vs ~ 1.5 in the wild type. More Rad52-GFP foci in MMS-treated cells lacking Scm3 may arise due to the creation of too many damaged sites to be accommodated in 1-2 foci and/or due to the inability of the cells to cluster the DSB ends.

This result has been incorporated as a new supplementary Figure S4C and new text has been added in the revised manuscript as: “We further quantified the distribution of cells with 1, 2, 3, or >4 Rad52-GFP foci in wild type (SCM3-AID) or Scm3 depleted (SCM3-AID + auxin) cells treated with MMS. Scm3 depleted cells showed a significantly higher number of cells with more than >4 Rad52-GFP foci, suggesting the possibility of the creation of too many damaged sites to be accommodated in 1-2 foci or the inability of such cells to cluster the DSB ends.” in page 7, lines: 237-241.

2. The peaks with increased Scm3 recruitment by ChIP-seq upon MMS is confusing as MMS does not induce specific damage at genomic locations. Is Scm3 being recruited at other genomic sites that might be more susceptible to DNA damage? Is Scm3 recruited to Pol2 sites for example? Or fragile sites?

__Response: __We believe that the MMS induced increase in association of Scm3 with the non-centromeric chromatin loci depends on MMS sensitive vulnerable chromosomal sites. We agree with the reviewer that MMS might cause DNA damage at these sites, leading to Scm3 occupancy at those sites. Therefore, we compared the sites of Scm3 occupancy with possible such sites available from the literature that include fragile sites, RNA Pol II binding sites, double strand break hotspots, and coldspots. Based on our analysis, we have included the following lines in the ‘discussion’ section in page 16-17, lines 566-594 as follows:

“Moreover, an overall increase in the chromatin association of Scm3 in response to MMS also suggests that Scm3 might be recruited to several repair centers or sites that are susceptible to DNA damage, for example, the fragile sites (Figure 3B, C, E, S6). These sites in yeast are DNA regions prone to breakage under replication stress, often corresponding to replication-slow zones (RSZs) (Lemoine et al., 2005). These regions include replication termination (TER) sequences, tRNA genes, long-terminal repeats (LTRs), highly transcribed genes, inverted repeats/palindromes, centromeres, autonomously replicating sequences (ARS), telomeres, and rDNA (Song et al., 2014). Since the helicase Rrm3 is often associated with these fragile regions (Song et al., 2014), we compared Scm3 binding sites with the top 25 Rrm3 binding sites from the literature (Azvolinsky et al., 2009). In untreated cells, Scm3 sites overlapped with three Rrm3 sites on chromosomes X, XII, and XIV. Whereas in MMS treated cells, overlapping was found with four Rrm3 sites, with two (on chromosomes XII and XIV) shared with untreated cells and two new sites were observed on chromosomes II and XII (Table R1). Mapping of the Scm3 sites with the tRNA genes and LTRs revealed that these sites from the untreated cells did not overlap with the LTRs (Raveendranathan et al., 2006). However, the same from the treated cells showed overlap with two LTRs on chromosome XVI. No overlap with tRNA genes was observed in the treated cells (Table R1). We next examined Scm3 occupancy at 71 TERs documented in the literature (Fachinetti et al., 2010). Scm3 was found to bind to 6 TERs in both untreated and MMS-treated cells. Notably, MMS treatment resulted in three new peaks, while three peaks were shared with untreated samples (Table R1). Lastly, we compared Scm3 sites with top 25 RNA Pol II sites obtained from the literature (Azvolinsky et al., 2009). In untreated cells, Scm3 was found at only one of these Pol II sites, whereas after MMS treatment, Scm3 sites overlapped with four such sites (Table R1). We further checked the occupancy of Scm3 at a few DSB hotspots (BUD23, ECM3, and CCT6) and DSB coldspot (YCR093W) as mentioned in the literature (Dash et al., 2024; Nandanan et al., 2021). However, we did not find Scm3 binding to these sites. Overall, in-silico analysis of the binding sites indicates that the non-centromeric enrichment of Scm3 occurs at sites that are amenable to DNA damage.”

Table R1: The table summarising the occupancy of Scm3 in untreated or MMS treated conditions at the indicated regions

Region

Chromosome

Scm3 occupancy

Untreated

MMS treated

Rrm3 binding sites

Chr II

YES

Chr X

YES

Chr XII

YES

Chr XII

YES

YES

Chr XIV

YES

YES

LTRs

Chr XVI

YES

Chr XVI

YES

tRNA

Chr XV

YES

TERs

Chr IV

YES

Chr V

YES

Chr VI

YES

YES

Chr VII

YES

Chr X

YES

Chr X

YES

Chr XIV

YES

YES

Chr XV

YES

YES

Chr XVI

YES

Pol II binding sites

Chr II

YES

Chr X

YES

Chr XII

YES

Chr XII

YES

Chr XV

YES

The Table R1 has been incorporated as Table S1 in the revised manuscript.

3. The phosphorylation aspect of Scm3 is intriguing and the authors show that Mec1 is not responsible for mediating its phosphorylation. Tel1 is another kinase that should be examined.

__Response: __We thank the reviewer for the suggestion. We are in the process of examining the role of Tel1 kinase on Scm3 phosphorylation. The results from the experiment will be incorporated in the manuscript.

Minor comment: 1. It is hard to see what MMS resistance the authors state is observed in Mif2-depleted cells in Figure S3. Perhaps this could be better explained or the claim removed.

__Response: __We agree with the comment and have removed the claim from the manuscript.

2. Protein levels of Scm3 or any of the other factors depleted with AID were never assessed.

__Response: __We have assessed the protein level of Scm3 and a control protein, tubulin using western blotting as per the reviewer’s suggestion (Figure R3). We did not observe any significant change in the protein levels in SCM3-HA or SCM3-HA-AID cells, suggesting that the AID tagging of Scm3 per se did not make the cells non-functional and the protein was degraded as expected upon addition of auxin. Moreover, the SCM3-AID cells were used previously to examine the effect of Scm3 on kinetochore assembly (Lang et al., 2018).

This result has been incorporated as Figure S2C, and new text has been added in the revised manuscript as: “The depletion of Scm3 was verified by observing a higher percentage of G2/M arrested cells and by western blot analysis verifying degradation of Scm3-AID after auxin treatment (Figure S2B, C).” in page 5, lines: 150-152.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

This manuscript describes a study implicating the Scm3 protein from budding yeast in the DNA damage response (DDR). Scm3 is a chaperone protein, whose main role is considered to be the loading of CENP-A(Cse4) at centromeres to facilitate chromosome segregation. However, the human ortholog of Scm3, HJURP, is known to have a role in DDR and in this study the authors provide evidence that Scm3 is also involved in the DDR in yeast. For the most part, the results presented support the conclusions made.

Main Points

1. Figure 1 Could depletion of Scm3 arrest cells in late G2/M and it is this delay that causes increased sensitivity to DNA damaging agents? A control with nocodazole or other means - that also arrests cells at this point - might provide a nice control for this. Perhaps the other kinetochore mutants, used therein, achieve this control - but cell cycle phase would need to be assessed.

__Response: __ We thank the reviewer for pointing out to a probable effect of the cell cycle stage on the observed MMS sensitivity. In fact, we were also concerned that the observed DNA damage sensitivity in Scm3 depleted cells might be due to G2/M arrest. To rule out this possibility, we monitored Rad52-GFP foci as a marker for DNA damage in the wild type and Scm3 depleted cells both arrested at G2/M using nocodazole (Figure S4). While Scm3 depleted condition exhibited >20% Rad52-GFP positive cells, less than 10% wild type cells showed the same in the absence of any DNA damaging agents (Figure S4E, no MMS, 60 mins). Upon challenging these cells with MMS in the presence of nocodazole, Scm3 depleted condition exhibited over 40% Rad52-GFP positive cells, whereas less than 20% wild-type cells harboured Rad52-GFP. This significant increase in Rad52-GFP positive cells when Scm3 is depleted clearly indicates that the observed MMS sensitivity in these cells is due to the absence of Scm3 rather than due to an effect of a cell cycle stage. Furthermore, we have also used Cdc20 depleted G2/M arrested cells as a wild type control to test the activation of the DNA damage checkpoint by Rad53 phosphorylation. These cells showed robust Rad53 activation in response to MMS, in contrast to poor activation in Scm3 depleted cells (Figure 6), suggesting that G2/M arrest is not the reason for the DNA damage sensitivity observed in the latter cells.

However, as per the reviewer's suggestion, we examined the MMS sensitivity of the wild type cells arrested at G2/M by nocodazole. As expected, these cells did not show increased sensitivity which further confirms that the DNA damage sensitivity observed in the scm3 mutant is not due to G2/M arrest (Figure R4B). This result has been incorporated within Figure S3, replacing the earlier Figure S3.

To include this result, we have included new text, and revised the result section in page 5-6, lines 160-181 as follows:

“The increased sensitivity of scm3-depleted cells to DNA-damaging agents could be due to the weakening of the kinetochores as Scm3-mediated deposition of Cse4 promotes kinetochore assembly or due to the delay in cell cycle, as Scm3 depleted cells arrest in late G2/M phase (Camahort et al., 2007; Cho and Harrison, 2011). If either of these holds true, perturbation of the kinetochore by degradation of other kinetochore proteins or wild type cells arrested at metaphase must show a similar sensitivity to MMS. In budding yeast, Ndc10 is recruited to the centromeres upstream of Scm3 (Lang et al., 2018), whereas the centromeric localization of Mif2, another essential inner kinetochore protein, depends on Scm3 and Cse4 (Xiao et al., 2017). We constructed NDC10-AID and MIF2-AID strains and used them for our assay to represent the proteins independent or dependent on Scm3 for centromeric localization, respectively. We also included one non-essential kinetochore protein, Ctf19, a protein of the COMA complex, to remove any possible mis-judgement in distinguishing cell-growth-arrest phenotype occurring due to drug-sensitivity vs. auxin-mediated degradation of essential proteins. The COMA complex is directly recruited to the centromeres through interaction with the N terminal tail of Cse4, hence dependent on Scm3 (Chen et al., 2000; Fischböck-Halwachs et al., 2019). Mid-log phase cells were harvested and spotted on the indicated plates, however, we did not observe any increased sensitivity of such cells to MMS (Figure S3). Further, wild type cells, when challenged in the presence of nocodazole and MMS, also did not show any increased sensitivity to MMS. Therefore, the increased sensitivity to MMS in scm3 mutant but not in other kinetochore mutant or metaphase arrested cells indicates that Scm3 possesses an additional function in genome stability besides its role in kinetochore assembly.”

Further we have also revised the discussion section to include the observed results in page 15, lines 502-510 as follows:

“However, since the primary function of Scm3 is to promote kinetochore formation by depositing Cse4 at the centromeres, it is important to address if the observed sensitivity is due to perturbation in kinetochores or due to cell cycle delay imposed in the absence of Scm3. Therefore, we similarly partially depleted two essential kinetochore proteins, Ndc10 and Mif2, and deleted one non-essential kinetochore protein, Ctf19, in separate cells and also challenged wild type cells to metaphase block but failed to detect any increased sensitivity to DNA damage stress (Figure S3). These results indicate that the drug sensitivity phenotype of Scm3 depleted cells is not due to weakly formed kinetochores or cell cycle delay.”

2. Mutants of the HR pathway in yeast (e.g. rad52∆ with mre11∆ for example) are typically epistatic. The observation that Scm3 depletion is not epistatic with rad52∆ (Figure 1C) suggests the Scm3 acts via another pathway than the classic Rad52 HR pathway. This should be pointed out and discussed.

__Response: __We have now included the discussion “In yeast, although HR is the preferred repair pathway, in the case of perturbed HR, an alternate pathway named non-homologous end joining (NHEJ) can occur. The absence of epistatic interaction between SCM3 and RAD52 (Figure 1C) suggests that Scm3 may function in ways other than the Rad52-mediated classical HR pathway. In this context, it would be interesting to test how Scm3 might interact with the key proteins of the NHEJ pathway, such as Ku70/Ku80 and Lig4 (Gao et al., 2016). It is possible that Scm3 may promote a certain chromatin architecture facilitating the DSB ends to stay together to be accessible for NHEJ-mediated end joining.” in page 16, lines 541-548.

3. Figure 2 should include auxin treatment of RAD52-GFP cells (without the Scm3 degron) to show that the auxin treatment alone does not increase Rad52 foci.

__Response: __ We performed the suggested experiment and did not observe any significant increase in Rad52-GFP positive cells when treated the cells with auxin+DMSO as compared to only DMSO (Figure R5).

This result has been incorporated as a new supplementary Figure S4A,B and new text has been added in the revised manuscript as “To rule out the possibility that auxin treatment alone can cause increased Rad52-GFP foci formation, we challenged the wild type (RAD52-GFP) cells with auxin or DMSO and counted the number of cells with Rad52-GFP foci. We did not observe any increase in Rad52-GFP positive cells when treated with auxin+DMSO as compared to only DMSO (Figure S4A, B).” in page 7, lines: 233-236.

4. Line 246-247 For the data presented, it seems to me possible that Scm3 depleted cells may indicate a defective DDR pathway (as stated) or may indicate defects in DNA replication or an increase in some other form of DNA damage?

__Response: __We agree with the reviewer’s comment that the depletion of Scm3 can cause replication error or other form of DNA damage in addition to the defect in DDR pathway. To include this, we have modified the sentence as “Taken together, Scm3 depleted cells exhibit more Rad52 foci, indicating a compromised DDR pathway in these cells. Although, defects in DNA replication or creation of other DNA lesions producing more foci also cannot be ruled out.” in page 8, lines 255-257.

5. In Figure 1 and throughout, please describe in the figure legends how error bars and p values are derived, and the number of experiments involved.

__Response: __We have now verified all the figure legends and described how error bars and p values are derived and have mentioned the number of experiments involved.

Minor points Line 35 replace 'cell survival' with 'cell division' - non-dividing cells can survive fine without chromosome segregation. See also line 62.

__Response: __We have now changed ‘cell survival’ with ‘cell division’ in lines 35 and 62.

Line 52 and throughout, I suggest replacing CenH3 with CENP-A or Cse4. The term CenH3 is confusing since regional centromeres contain both CENP-A nucleosomes and H3 nucleosomes - the latter of which can also be called CenH3 nucleosomes.

__Response: __We have replaced CenH3 with CENP-A or Cse4 at the appropriate locations.

Lines 69-79 specific references are needed for the sentences starting "HJURP was so named...", "In addition,...", "As a corollary,..." and "Finally,..." The final sentence of this paragraph, starting "Perhaps due to..." is unclear.

__Response: __We have included the reference as mentioned by the reviewer. Also, we have changed the last line as “Notably, HJURP has been visualized to be diffusely present throughout the nucleus (Dunleavy et al., 2009; Kato et al., 2007), which may be due to its global chromatin binding and involvement in DDR.” in page 3, lines 77-79.

Line 96 "gross chromatin" is unclear; also line 476.

__Response: __We have changed gross chromatin to “bulk of the chromatin.” and incorporated it into the main text.

Line 103 "dimerize"

__Response: __We have replaced ‘dimerizes’ with ‘dimerize’

Line 109 "most" and "highly" don't work together - perhaps better to say "the functions appear conserved from humans to yeast".

__Response: __We have changed the wording as the reviewer suggested.

Line 175 "grown" to "phase", see also line 223.

__Response: __We have changed the wording as the reviewer suggested.

Line 293 delete "besides"

__Response: __We have deleted the word ‘besides’.

Figure 5 - panels C & D, please make x axis labels clearer - they are directly underneath the 2kb ChIP. They should include a horizontal bar to indicate that all 5 ChIP experiments are included in each time point.

__Response: __We have now included a horizontal bar in both Figure 5 and the corresponding supplementary Figure S8, to better represent the ChIP experiments. We thank the reviewer for pointing this out.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary This manuscript studies the role of the Cse4 histone chaperone Scm3 in the S. cerevisiae DNA damage response. The authors show that decreased Scm3 levels exhibit genetic interactions with mutations in the Rad52 gene and sensitivity to MMS. They go on to show that some Scm3 co-localizes with sites of DNA damage using spreads and ChIP-seq techniques and that decreased levels of Scm3 have a reduced DNA damage checkpoint response. The Scm3 protein is also phosphorylated in response to DNA damage. Taken together, the authors propose a model whereby DNA damage recruits the Scm3 protein and Scm3 then helps mediate the checkpoint response. Overall, the data make a case that Scm3 has a relationship to the DNA damage checkpoint but the authors should be careful not to over-conclude that it has a precise role in checkpoint activation based on the data.

Major Comments 1. The western blots in the paper are not always entirely convincing. In addition, they are not described in enough detail to understand if a membrane was cut or if multiple gels were run. For example, the tubulin loading in Figure 6D is interrupted toward the end of the blot and the bands in Figure 7D go in different directions for the two blots for the MMS treated cells. In figure 6B, there are no detectable phospho-forms of Rad53 detected on the upper blot for the WT and scm3 lanes even though quantification is given on the right. It would be good to present better examples of the westerns or at least better describe what the reader is visualizing so the quantification and conclusions can be understood. How were the blots quantified? How were the westerns run and processed?

Response: We have now included a separate paragraph in materials and methods regarding the gel run, processing and quantification of the western blots in the revised manuscript for better understanding of the readers:

“To detect Scm3-6HA, Rad53, and g-H2A, the total proteins isolated from the appropriate cells were run on 12%, 8%, and 15% SDS gels, respectively. The proteins were transferred to the membranes, which were cut to detect the above proteins and the control protein tubulin separately. For the quantification of the bands on the western blots, a region of interest (ROI) was made around the band of interest, and the intensity of the band was calculated using ImageJ. A same ROI from a no-band area of the blot was used to calculate the background intensity. The background intensity was subtracted from the band intensity. The same process was done for the tubulin bands. The intensity of the target bands (Scm3-6HA, Rad53, and g-H2A) was divided by control tubulin band intensity to get the normalized values for the target bands, which were plotted using GraphPad Prism 9.0 (Version 9.4.1) software.” This has been added in page 25, lines: 881-890.

Furthermore, we will again perform the experiments for a better representation of the western blots in figures 6B, D, and 7D.

2. The argument that scm3 depletion leads to a defect in DNA damage checkpoint activation is not strongly supported. Monitoring exit from the cell cycle by multibudding is not the most rigorous assay, especially since the image shows one cell with 5 nuclei. The authors should release cells from G1 into auxin and MMS and monitor cell cycle progression at least one other cell cycle marker, such as anaphase onset, DNA replication and/or Pds1 levels.

Response: As per the reviewer’s suggestion, in order to support our argument that the absence of Scm3 causes a defect in DNA damage checkpoint activation, we will examine if these cells abrogate G2/M arrest and show an early anaphase onset. For this, we will monitor the levels of Pds1, as a marker of anaphase onset, along the cell cycle in wild type and Scm3-depleted cells both deleted for Mad2 to remove any inadvertent effect of spindle assembly checkpoint. The schematics of the experimental workflow is given in Figure R1. Typically, the cells will be released from alpha factor arrest in the absence or presence of auxin (for the depletion of Scm3) and in the absence or presence of MMS. The samples will be harvested at the indicated time points and will be analyzed for:

1. Western blot: Pds1-Myc (to detect anaphase onset)
2. Western blot: Rad53 and p-Rad53 (to detect DNA damage activation)
3. Immunofluorescence: Tubulin (to detect cell cycle stages) The results of the above experiment will be incorporated in the revised manuscript.

3. The quantification in Figure 3B is not clear. Is it done on a per/nuclei basis? What pools of Scm3 and Ndc10 are being normalized?

Response: The intensity was calculated as done before (Mittal et al., 2020, Shah et al., 2023). Typically, the intensity was first measured from the total signal of Scm3/Ndc10 from each chromatin mass or spread (DAPI) by making a polygon (ROI) around the Scm3/Ndc10+DAPI signal. The same ROI was dragged to the background area, from where two separate intensities were calculated. The average of the background intensities was then subtracted from the Scm3/Ndc10 intensity obtained from the same spread to get the normalized intensity depicting each dot in the box plot of Figure 3B. At least 30 spreads were quantified in a similar manner.

We have mentioned this in the materials and methods section under “Microscopic image analysis.” section in page 22, lines 770-777 as follows: “For intensity calculation, a Region of Interest (ROI) was drawn around the Scm3/Ndc10/g-H2A+DAPI signal, and the intensity of Scm3/Ndc10/g-H2A was measured from each chromatin mass or spread (DAPI). An ROI of the same size was put elsewhere in the background area, from where two separate intensities were calculated. The average of the background intensities was then subtracted from the Scm3/Ndc10/g-H2A intensity obtained from the same spread to get the normalized intensity depicting each dot in the box plot of the respective figures as mentioned previously (Mittal et al., 2020; Shah et al., 2023).”

Minor Comments 1. The model is elegant but there are chromatin pools (beyond the kinetochore pool) of Scm3 that do not contain Rad52 and/or gamma-H2X and vice versa. It would be helpful if the authors could speculate on how to reconcile these different pools. It might be premature to suggest such a detailed model at this point since the function of Scm3 in the checkpoint is still very unclear so I would encourage the authors to make a less detailed model.

Response: By showing the green hallow, we have depicted the nuclear pool of Scm3, and we have not shown that the pool contains DDR proteins viz., Rad52 or g-H2A. Rather, we have shown the recruitment of these proteins at the DNA damage sites. Since the focus of this manuscript is on the non-centromeric functions of Scm3, we have not shown the kinetochore pool of Scm3. Although the model is a detailed one, the contribution from this work has been mentioned legitimately at every stage so that the readers can judge the merit of this work. We believe that a detailed model would provide a better perspective to the readers to correlate the revealed as well as yet-to-reveal functions of Scm3 in a spatiotemporal manner with the other players of the DDR pathway. Therefore, we prefer to keep the model in a detailed form.

2. The chip-seq data is not publicly accessible. There is no reference to the data being available to review.

__Response: __The data will be uploaded to the public domain.

3. Line 103: not clear what "both the proteins dimerize" means...probably should be "both proteins dimerize"

__Response: __We have changed the wording to “both proteins dimerize”.

4. The argument that Ndc10 does not have a growth defect on MMS is a weak conclusion given that almost no control cells grow on auxin in the absence of MMS.

__Response: __We have now repeated the spotting assay with a lesser concentration of auxin and replaced Figure S3 with a new Figure S3 (Figure R4) to better represent and conclude that the loss of Ndc10 does not cause MMS sensitivity.

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Referee #3

Evidence, reproducibility and clarity

Summary

This manuscript studies the role of the Cse4 histone chaperone Scm3 in the S. cerevisiae DNA damage response. The authors show that decreased Scm3 levels exhibit genetic interactions with mutations in the Rad52 gene and sensitivity to MMS. They go on to show that some Scm3 co-localizes with sites of DNA damage using spreads and ChIP-seq techniques and that decreased levels of Scm3 have a reduced DNA damage checkpoint response. The Scm3 protein is also phosphorylated in response to DNA damage. Taken together, the authors propose a model whereby DNA damage recruits the Scm3 protein and Scm3 then helps mediate the checkpoint response. Overall, the data make a case that Scm3 has a relationship to the DNA damage checkpoint but the authors should be careful not to over-conclude that it has a precise role in checkpoint activation based on the data.

Major Comments

1. The western blots in the paper are not always entirely convincing. In addition, they are not described in enough detail to understand if a membrane was cut or if multiple gels were run. For example, the tubulin loading in Figure 6D is interrupted toward the end of the blot and the bands in Figure 7D go in different directions for the two blots for the MMS treated cells. In figure 6B, there are no detectable phospho-forms of Rad53 detected on the upper blot for the WT and scm3 lanes even though quantification is given on the right. It would be good to present better examples of the westerns or at least better describe what the reader is visualizing so the quantification and conclusions can be understood. How were the blots quantified? How were the westerns run and processed?

2. The argument that scm3 depletion leads to a defect in DNA damage checkpoint activation is not strongly supported. Monitoring exit from the cell cycle by multibudding is not the most rigorous assay, especially since the image shows one cell with 5 nuclei. The authors should release cells from G1 into auxin and MMS and monitor cell cycle progression at least one other cell cycle marker, such as anaphase onset, DNA replication and/or Pds1 levels.

3. The quantification in Figure 3B is not clear. Is it done on a per/nuclei basis? What pools of Scm3 and Ndc10 are being normalized?

Minor Comments

1. The model is elegant but there are chromatin pools (beyond the kinetochore pool) of Scm3 that do not contain Rad52 and/or gamma-H2X and vice versa. It would be helpful if the authors could speculate on how to reconcile these different pools. It might be premature to suggest such a detailed model at this point since the function of Scm3 in the checkpoint is still very unclear so I would encourage the authors to make a less detailed model.

2. The chip-seq data is not publicly accessible. There is no reference to the data being available to review.

3. Line 103: not clear what "both the proteins dimerize" means...probably should be "both proteins dimerize"

4. The argument that Ndc10 does not have a growth defect on MMS is a weak conclusion given that almost no control cells grow on auxin in the absence of MMS.

Significance

Significance

This is the first examination of the role of Scm3 in the DNA damage response in S. cerevisiae. My expertise is in the chromatin and segregation fields, but I believe this work will be of interest to the DNA damage field as well. While the homologs of Scm3 are known to have a role in DNA damage, it was unclear if this was conserved in budding yeast. The data in this manuscript are consistent with findings in other organisms but the precise role of the chaperone in the DNA damage response is still unclear.

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Referee #2

Evidence, reproducibility and clarity

This manuscript describes a study implicating the Scm3 protein from budding yeast in the DNA damage response (DDR). Scm3 is a chaperone protein, whose main role is considered to be the loading of CENP-A(Cse4) at centromeres to facilitate chromosome segregation. However, the human ortholog of Scm3, HJURP, is known to have a role in DDR and in this study the authors provide evidence that Scm3 is also involved in the DDR in yeast. For the most part, the results presented support the conclusions made.

Main Points:

1. Figure 1 Could depletion of Scm3 arrest cells in late G2/M and it is this delay that causes increased sensitivity to DNA damaging agents? A control with nocodazole or other means - that also arrests cells at this point - might provide a nice control for this. Perhaps the other kinetochore mutants, used therein, achieve this control - but cell cycle phase would need to be assessed.

2. Mutants of the HR pathway in yeast (e.g. rad52∆ with mre11∆ for example) are typically epistatic. The observation that Scm3 depletion is not epistatic with rad52∆ (Figure 1C) suggests the Scm3 acts via another pathway than the classic Rad52 HR pathway. This should be pointed out and discussed.

3. Figure 2 should include auxin treatment of RAD52-GFP cells (without the Scm3 degron) to show that the auxin treatment alone does not increase Rad52 foci.

4. Line 246-247 For the data presented, it seems to me possible that Scm3 depleted cells may indicate a defective DDR pathway (as stated) or may indicate defects in DNA replication or an increase in some other form of DNA damage?

5. In Figure 1 and throughout, please describe in the figure legends how error bars and p values are derived, and the number of experiments involved.

Minor points:

1. Line 35 replace 'cell survival' with 'cell division' - non-dividing cells can survive fine without chromosome segregation. See also line 62.

2. Line 52 and throughout, I suggest replacing CenH3 with CENP-A or Cse4. The term CenH3 is confusing since regional centromeres contain both CENP-A nucleosomes and H3 nucleosomes - the latter of which can also be called CenH3 nucleosomes.

3. Lines 69-79 specific references are needed for the sentences starting "HJURP was so named...", "In addition,...", "As a corollary,..." and "Finally,..." The final sentence of this paragraph, starting "Perhaps due to..." is unclear.

4. Line 96 "gross chromatin" is unclear; also line 476.

5. Line 103 "dimerize"

6. Line 109 "most" and "highly" don't work together - perhaps better to say "the functions appear conserved from humans to yeast".

7. Line 175 "grown" to "phase", see also line 223.

8. Line 293 delete "besides"

9. Figure 5 - panels C & D, please make x axis labels clearer - they are directly underneath the 2kb ChIP. They should include a horizontal bar to indicate that all 5 ChIP experiments are included in each time point.

Significance

This is a nice complement to the human work on HJURP and provides convincing evidence that Scm3 can be used to model the function of HJURP. Since yeast is such a tractable model, this work provides a route to study the role of this chaperone in DNA damage repair, which may also be true for human HJURP. The work itself is perhaps not too surprising, but is a solid advance in our understanding of the role of Scm3.

My own expertise is in yeast DNA repair and chromosome segregation.

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Referee #1

Evidence, reproducibility and clarity

In the manuscript by Agarwal and Ghosh, the authors examine yeast Scm3 function in the DNA damage response. They show that Scm3 loss results in DNA damage sensitivity and more Rad52 foci. Importantly, Scm3 is recruited to DSB sites using an HO-cut site and its loss results in an attenuated DNA damage checkpoint as measured by Rad53 phosphorylation. The authors demonstrate convincingly that Scm3, like its human counterpart HJURP, plays a role in the DNA damage response through altered Rad53 activation. However, what its specific role in DNA repair is remains ambiguous.

Major comment:

1. It is unusual to see multiple DNA repair foci as those observed in Figure 2B. What is the distribution of cells with 1, 2, 3, 4, or more foci? Are more observed in SCM3-AID cells perhaps suggesting that the DSB ends are not being clustered as would be expected in WT cells exposed to DNA damage?

2. The peaks with increased Scm3 recruitment by ChIP-seq upon MMS is confusing as MMS does not induce specific damage at genomic locations. Is Scm3 being recruited at other genomic sites that might be more susceptible to DNA damage? Is Scm3 recruited to Pol2 sites for example? Or fragile sites?

3. The phosphorylation aspect of Scm3 is intriguing and the authors show that Mec1 is not responsible for mediating its phosphorylation. Tel1 is another kinase that should be examined.

Minor comment:

1. It is hard to see what MMS resistance the authors state is observed in Mif2-depleted cells in Figure S3. Perhaps this could be better explained or the claim removed.

2. Protein levels of Scm3 or any of the other factors depleted with AID were never assessed.

Significance

As mentioned above, a clear link for Scm3 in DNA damage repair has now been established in this work but its function in this process is descriptive.

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Reply to the reviewers

Response to Reviewer Comments:

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Reviewer #1 (Evidence, reproducibility and clarity (Required)):

*Glaucoma-associated optineurin mutations increase transmitophagy in vertebrate optic nerve.

Summary In Jeong et al., the authors perform live imaging of the X. laevis optic nerve to track neuronal mitochondrial movement and expulsion in an intact nervous system. The authors observe similar mitochondrial dynamics in vivo as previously described in other systems. They find that stationary mitochondria are more likely to be associated with OPTN, suggestive of mitochondria undergoing mitophagy. Forced expression of OPTN mutations results in a larger pool of stationary mitochondria that colocalize withLC3B, and OPTN. Finally, the authors argue that extra-axonal mitochondria are observed more frequently in OPTN mutants, suggesting that mutations in OPTN that are associated with disease can lead to an increase in the expulsion of mitochondria through exopher-like structures.

Major Findings and impact: • The authors establish that mitochondria dynamics can be tracked in the X. laevis optic nerve. • OPTN mutations increase the stationary pool of mitochondria and likely result in increased rates of mitophagy. • Exopher-like structures containing mitochondria and LC3 can be expelled from the optic nerve and increase in the presence of OPTN mutations. These structures were observed in a living system and have interesting implications in the context of disease.

Concerns: • The authors state in their results that the secreted blebs are exophers. While these initial observations are consistent with exophers, additional data are needed to strengthen this claim. For example: what are the sizes of secreted vesicles? Do all express LC3? How frequently do these occur? From where are they expelling? Alternatively, the discussion of exophers could be moved to the discussion.*

We agree that calling the axon shedding intermediates “exophers” was an overreach on our part. While we believe that in all probability time will demonstrate this to be the case, reviewers are correct in stating that putting our work in the context of exophers is best left to the discussion. We have removed all mention of exophers from the results and graphical abstract and now use the term only once in the discussion. We do provide detail as to the frequency of the structures, what fraction contain mitochondria, and morphological parameters of the contained mitochondria. And while all of these new data support them being exophers, the point remains that the use of the nomenclature “exopher” in the results section was inappropriate.

• Quantifications in sparse labeling experiments seem quite surprising and concerns related to these findings should be addressed. As the authors used LC3b expression to represent axonal volume, the authors should demonstrate that this is the case using an axonal fill or membrane marker in both the wt and E50K conditions. This is important as it is unclear whether LC3b expression is consistent between the wild type and the E50K conditions. Lower expression of LC3b in E50K could account for the large changes in axonal width that seem to be observed and could confound the measured amount of expelled mitochondria.*
• *

We agree that using EGFP-LC3b as a “cell fill” was problematic in a situation where the interventions likely perturb autophagy/mitophagy and therefore might have also perturbed LC3b. We do provide some axon width and LC3b-EGFP intensity data for a partial dataset that had been imaged side-by-side, showing that expression of LC3b is not different in the two conditions. We also provide independent measures of extra-axonal mitochondria based on a membrane-GFP reporter. While in principle there would be value to repeat the studies of Wt vs. E50K in the context of the membrane-GFP reporter, these experiments would involve new constructs and new breedings, and would likely take months to years to complete.

• • Could large amounts of exogenous mitochondria in explant experiments be from cells that died during the plantation?* The concern that some of the exogenous mitochondria signal might derive from degenerating axons is one that we worry much about, and not only in the transplantation experiments. In our sparse labeling experiments we do occasionally see axons undergoing Wallerian degeneration, but it is rare and does not appear to be more common in the expression of the mutated OPTN, at least not at the stage after transgene expression that the analyses were performed. We do provide new data that expression of E50K OPTN does not compromise vision at the time that experiments were carried out, ruling out that extra-axonal mitochondria are the result of large-scale degeneration. However, from other data we know that axon loss would likely need to be very extensive to manifest itself in functional vision loss in our behavioral assay, so milder axon loss contributing some noise to the measures cannot be excluded. But, the point raised is heard, and now we include a sentence in the discussion acknowledging that some of the signal outside of axons could have been due to degenerating axons, but still contend that our documentation of shedding intermediates support the view that many of the axonal mitochondria outside of axons were shed from otherwise intact axons.

Suggested experiments/quantifications: • In OPTN/MITO/LC3b trafficking experiments, does flux/number of events change? Representative kymograph in Figure 2D seems to show far more OPTN-positive mitochondria which is opposite of what is shown in Figure 2C.

Multiple reviewers rightfully point out that we did not carry out the flux experiments which would be necessary to make definitive statements regarding the amount of mitophagy. New experiments show that inhibiting lysosomal activity through chloroquine does increase the amount of astrocytic autophagosomes not yet acidified as expected, and that they contain axonal mitochondria signal, supporting the idea that astrocytes are involved in the degradation of axonal mitochondria. However, they did not show changes in the amount of stopped mitochondria, supporting the view that the co-localization of OPTN and mitochondria in axons is not conventional autophagy. This is a very important point that affects the interpretation of our results, and we thank reviewers for suggesting this experiment.

• Demonstrate that axonal width measured with LC3B is representative of axonal fill/membrane marker in wt and E50K. Axonal area appears to change, is this accurate? This appears to be the case for both figure 3 and figure 4.* Addressed above.

• Raw images in addition to the reconstruction would be beneficial.* Now include raw images beside the reconstruction at the first use of reconstructions.

• Further characterization of exopher-like structures.**

* Addressed above.

***Referees cross-commenting**

I agree with the concerns of the other reviewers, and perhaps was over-optimistic about a timeline for revision. However, I do think the work is worth the effort, and I hope to see a revised manuscript published somewhere, as these observations are novel

Reviewer #1 (Significance (Required)):

This work reports potentially novel biology, and thus will be of interest to the field. The strength of the study is that it is an initial description of this biology, rather than a complete analysis. The work raises many more questions than it answers, and much further work on this topic is required to support these initial findings, but the manuscript will likely be of interest to many. Revisions are required to improve the rigor and clarity of the work, but following these revisions we recommend publication to facilitate follow-up work.*

Fully agree that our study raises far more questions than it answers. Believe that the revisions made to address reviewer comments go a long way to improve rigor and clarity of the work. We hope that the reviewers agree and deem the changes sufficient.

*Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary: This article studied transmitophagy in xenopus optic nerves in the context of overexpressing glaucoma-associated optineurin mutations. Using a series of labeling, imaging and transplantation techniques, the authors found that overexpressing mutated optineurins stops mitochondria movements and potentially induces transmitophagy, and that astrocytes are responsible for taking up the extra-axonal mitochondria. Below are my comments on this article.

Major comments: 1. Identifying extra-axonal mitochondria is key to this research. In Figure 3, the authors used EGFP-LC3B as a marker for RGC boundaries. However, it is unconvincing how perfect LC3B is as a cell membrane marker. Particularly in the case of OPTN E50K OE, it seems that the optic nerve is thinner than the WT condition, which makes the quantification of extra-axonal OPTN less convincing. The authors should detect extra-axonal mitochondria with an RGC membrane marker or cytosolic marker. In addition, in Figure 3, the extra-axonal mitochondria seem to localize mostly on the dorsal surface. Why is there such a polarity?*

As stated above, we acknowledge that the use of LC3b as both an autophagosome marker and a cell fill was somewhat problematic and now provide additional experiments ruling out that the LC3b expression or axon thickness in our sparse axon labeling experiments, or that E50K might affect the thickness of the optic nerve. In addition, we also provide additional new data using a bona fide membrane marker together a transgenic labeling or RGC mitochondria that also shows under the “baseline state” extensive mitochondria signal outside the axons on the surface of the optic nerve (New Fig. 6A and new Suppl Fig. 3D). All the new data are consistent with the previous data and support the view that using LC3b potentially could have been problematic, for the reasons reviewers state, but in practice it was not.

The reviewer observes that the E50K optic nerve appears thinner--this observation is not a consistent difference in optic nerves across the experimental groups. The images we show are always near the mean values for the quantitative results presented, and we rather not include prettier nerves that are not representative of the whole datasets.

As for why the extra-axonal mitochondria localize mostly to the dorsal surface, it remains undetermined. There are dorsoventral differences in the optic nerve established during development, as developmental Sonic hedgehog signaling emanating from the midline appears to affect dorsoventral aspects of the optic nerve differentially. Early axon loss in humans and some models of glaucoma do show a dorsal bias, and there may be optic nerve lymphatic structure reported in mice that also may be preferentially dorsal. However, it is not known whether any of these observations are connected, so we did not want to speculate beyond what the data say. We do now explicitly mention the dorsoventral difference in the discussion, and state why we think it may be worth further study.

• The experiment in Figure 5 is very important as it gives direct evidence of transmitophagy. However, one caveat is that the mitotracker injection is done after the transplantation. If in rare cases the dye is leaky after injection and is taken up by astrocytes directly, then the conclusion that mitochondria from RGCs are phagocytosed by astrocytes will be flawed. The authors should either use a transgene in the donor to label mitochondria or inject mitotracker into the donor before the transplantation and repeat the experiments. In addition, in Figure 5E, what is the large membranous structure inside the highlighted astrocyte? Is it associated with phagocytosis?*

We fully agree that MitoTracker is an imperfect tool, both for the reason stated here that the dye may get into the astrocytes directly (or may label astrocyte mitochondria after it is released from degrading RGC mitochondria), and, also as stated by reviewer 3, that it requires healthy mitochondria for labeling. For this reason, we have added new datasets that rely on RGC mitochondria labeling not by Mitotracker but through a genetic reporter. As to identity of the conspicuous structure shown inside the astrocytes, it remains an open question, and we are avidly pursuing what astrocytic organelles are involved through additional transgenic reporters and correlated-light-EM studies, but those are complicated experiments that are beyond the scope of the current manuscript.

• This research is entirely based on overexpression of OPTN. Since overexpressing WT OPTN does seem to affect mito trafficking (Figure S2G, and the description in the manuscript is often inconsistent with this result), it is unclear what the increased stalled mitochondria really mean when overexpressing mutated OPTN. Similarly, the authors examined extra-axonal mitochondria in Figures 3 and 4 all in overexpressing conditions, and made the connection that increased stalled mitochondria lead to transmitophagy. However, this conclusion will be better supported by using mutant animals rather than overexpression. The authors should consider using OPTN mutant xenopus if available or using CRISPR to introduce the specific mutations and repeat mitochondria trafficking and transmitophagy.*

• *

We thank this reviewer by pointing out an important detail that we failed to highlight, namely that transgenic overexpression of Wt OPTN (and/or Wt LC3B) does have a small but significant effect on mitochondria trafficking. Interestingly, it is affecting just the speed of retrogradely transported mitochondria, which based on the elegant work of Holzbaur and colleagues, include mitochondria destined for degradation. So, we now acknowledge more explicitly that, since our studies involve expression of OPTN and LC3b transgenes (fluorophore tagged human genes, no less), that some caution should be exercised in not overinterpreting the results. Nonetheless, since we show that expression of Wt OPTN behaves similarly to expression of a mitochondria reporter (Tom20-mCherry) in not affecting either stopped mitochondria or extra-axonal mitochondria, we believe that our results still stand. Nonetheless, we now make mention of the effect Wt OPTN on retrograde mitochondria movement. We have embarked on OPTN loss-of-function studies and have some founder animals carrying CRISPR-generated mutations; however, these experiments will take additional time, and based on the results in mammals may or may not show any measurable effects in our assays, not only because of possible redundancy by the other damaged mitochondria adaptors that we mention in the introduction, but also because the mutations that affect the shedding process (as well as cause glaucoma) are thought to be gain-of-function mutations. However, we decided not to dwell on these complexities in the discussion, as the discussion was previously quite extensive and now is even moreso with the added discussion on how our studies relate to those of exophers.

• On Page 12, the authors claim that even overexpressing WT OPTN causes extra-axonal mitochondria in the optic nerve. However, there is no control condition without OE to support this conclusion. It is thus unclear to what extent extra-axonal mitochondria occur at baseline and how many extra-axonal mitochondria can be induced by overexpression. The authors should include, in Figure 3 and 4, controls without overexpression.*

We acknowledge that our language was confusing and somewhat misleading on this point. With the caveat mentioned above that WT OPTN expression does perturb the system somewhat (by increasing the speed of mitochondria retrograde transport, perhaps by increasing the proportion of retrograde moving mitochondria tagged for degradation), we still contend that the state observed after WT OPTN expression is close to the “baseline” state. In support of that, in the new data included in response to the LC3b concern, we observe plentiful shedding events in the absence of any OPTN or LC3b transgenes. Indeed, what may be the most surprising finding of our studies is that in the absence of any significant perturbation of OPTN, there is already a large fraction of axonal mitochondria that are outside of axons and inside of astrocytes, which is consistent with what we previously observed in the optic nerve head of mice; however, the current studies provide much more rigorous quantification of the process and live imaging of intermediates, but also provide for an intervention that increases the process. While there are many more questions to answer, we do believe our studies contribute mechanistic insights.

• A technical question regarding kymographs: Based on Figure 2C, it looks that OPTN and LC3B labeling are pretty diffuse in axons and this makes sense since they may only be associated with damaged mitos. But this raises a question about how accurate the kymograph assay is. It may significantly underestimate the fraction of OPTN/LC3B that is stationary since they appeared diffusedon the kymograph. This may explain why the percentage of stationary OPTN/LC3B is so small when the authors OE WT OPTN in Figure 2E and 2E', compared to the percentage of moving mitochondria shown in Figure 1E.*

We fully agree that the kymograph studies likely underestimate the amounts of stationary mitochondria for the reasons stated. However, we interpret the discrepancy between Figure 1E and 2E and 2E’ differently. We believe that the value of stopped mitochondria in the sparse labeling experiments are actually more accurate, as the value of stopped mitochondria in the whole nerve experiments likely include mitochondria stopped within the axons, but also mitochondria recently shed either by those or nearby axons which are perceived to be in axons due to limitations of imaging resolution. In the discussion we now make very explicit that all the measures we provide need should be interpreted as estimates, as every experiment relies on assumptions and is subject to technical limitations.

Minor: 1. Figure 2E and 2E' do not agree with the text on page 7 and page 8. Not only F178A, but also H486R and D474N have no effect on OPTN trafficking. The authors should make their conclusions more accurate.

F178 was the only mutation that had no effect on either OPTN or LC3b in either F0 or F1 experiments. However, we agree that our language should have been clearer, and now we have made our description of the results (and conclusions) more accurate.

• Figure S2E-F: why does OE of mutated OPTN in F1s but not in F0s reduce trafficking speed compared to WT?*

We do not know the reason for this discrepancy. Though it does not wholly agree with the rest of the story, we felt it important to include all relevant data, not only that which perfectly fit our interpretation. One possible reason may be that the F1 data derives from a single integration event, which is the reason why we trust more the F0 data that derive from multiple integrations, in what are essentially outbred animals, which is the reason we present the F0 data as the primary results where possible.

* In movie 5, fusion of exopher with other structures is not clear and also the GFP signal does not disappear, which is in contrast to the statement in the text that the GFP signal is quenched in acidified environment. To confirm that LC3B leaves RGC axons in exophers, the authors should consider switching the fluorophores and examine LC3B localization during exopher formation.*

This too is a valid point, and we have amended our description of these results. While swapping fluorophores between OPTN and LC3b is a highly worthy experiment, for technical reasons it likely would take many months to carry out just because of how involved it is to make the relevant constructs (recombineering details provided in the methods section).

• In figure 6, to better show exopher formation and the pinching-off step, the authors should consider labeling the membrane and mitochondria instead of using the LC3B and OPTN marker.*

This arguably was the biggest weakness of our initial submission, and now provide new experiments using a bona fide membrane marker. We have not yet captured a pinching-off event with these better reporters, but that is not surprising given how rare they are, which we now quantify. Indeed, a membrane reporter and a mitochondria transgene in sparsely labeled axons are the ideal tool for figuring out the frequency of these structures and what fraction contain mitochondria, data which we now provide.

***Referees cross-commenting**

Generally agree with the criticisms voiced by the other reviewers; in aggregate the reviews indicate the manuscript needs more than just a quick fix.

Reviewer #2 (Significance (Required)):

Previous literature has already described the transmitophagy process in the optic nerve. The significance of this paper lies in the observation that overexpressing glaucoma-associated OPTN mutants can induce increased transmitophagy through astrocytes, which points to a potential role of OPTN in glaucoma. A highlight of this paper is the use of correlated light SBEM to directly show transmitophagy in astrocytes. However, the significance of this paper may be limited for the following reasons: 1. everything is based on overexpression of mutated OPTN, which makes it hard to translate the results to real disease conditions; 2. The consequence of increased transmitophagy on RGC survival or visual functions is unclear.

*

While we agree that much of the paper is based on OPTN overexpression, we did have experiments and now provide more that that were not based on OPTN overexpression. Some of these still involve expression of a different transgene (Tom20-mCherry) that might in principle perturb the system, though we show that expression of Tom20-mCherry does not affect mitochondria movement parameters as measured by Mitotracker. As to “the consequence of increased transmitophagy”, we do now provide data showing that there is no vision loss suggestive of axon loss or severe dysfunction at the time that the imaging studies were carried out. Whether longer term expression of these OPTN transgenes lead to axon degeneration and visual dysfunction are studies that are ongoing, but those studies involve extensive characterizations and controls that are beyond what could be included in this study.

*Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary In this work, Jeong et al describe the effect of Optineurin (OPTN) mutations in the transcellular degradation of retinal ganglion cell (RGC) mitochondria by astrocytes at the Optic Nerve (ON), a process previously described this group and referred as "transmitophagy" (Davis et al 2014). Here, authors use Xenopus laevis animal model to image the optic nerve of animals carrying different OPTN mutations associated to disease or with compromised function and explore its effect in mitochondria dynamics at the RGC axons. They find that OPTN mutants lead to increased stationary mitochondria in the nerve and affect their co-localization with mitophagy-related markers, suggesting alterations in this pathway. Finally, they found that mitochondria co-localizing with OPTN can be found in the periphery of the ON under different conditions and this is particularly increased in glaucoma-associated E50K mutation. This extracellular mitochondria are transferred in vesicles to astrocytes, as they previously described in mice (Davis 2014), where they are presumably degraded. Major comments - OPTN levels at a given time point cannot be used as readout for mitophagy level/flux. Both OPTN and LC3b are degraded upon fusion with acidic compartment (i.e. lysosomes, PMID: 33783320, 33634751) and that is the reason why the field of autophagy /mitophagy blocks lysosomal activity to measure autophagy/mitophagy flux (PMID: 33634751). In this document, authors claim that there is low levels of mitophagy in RGC axons at baseline and increased levels of mitophagy in glaucoma associated perturbations just based on increased presence of OPTN+ mitochondria in this condition. This could be also interpreted as an accumulation of non-degraded defective mitochondria due to a mitophagy block in neurons carrying the glaucoma associated mutation, which is the opposite of what they propose. If authors want to evaluate mitophagy levels in this system, mitophagy/autophagy flux experiments should be performed.*

In response to reviewers, we do now include “lysosome inhibition” experiment, using chloroquine at doses modestly above those used in aquaculture as an anti-parasitic. After testing various chemical means to inhibit lysosome activity, it was the only one that did not adversely affect the animals. We know the chloroquine intervention works because we see the expected increase in autophagosomes using the standard LC3b-tandem reporter, and in those unacidified astrocytic autophagosomes we do indeed find axonal mitochondria signal. However, since the amount of mitochondria signal there is small relative to the total amount of axonal mitochondria in the astrocytes, we do not feel it would be appropriate to make mechanistic claims, for example claiming this to be related to LC3b associated phagocytosis; much more work would be needed to make that claim. However, we were surprised to find no alteration in either stopped mitochondria in axons or axonal mitochondria material within the astrocytes. There are technical reasons why this result might be difficult to interpret, but now having done it (as we should have before), we are even more careful in describing the process as transcellular degradation rather than transmitophagy. We elaborate further on this point in the next response.

- I find inappropriate the use of the term "transmitophagy". Although this term transmits very well the message that the authors try to strength, the term "mitophagy" refers to the specific elimination of mitochondria through autophagy (PMID: 21179058). There are many reasons why I think that "transmitophagy" is not adequate to describe this phenomena but I will just refer to these three: First, authors do not provide data showing that this mechanism is specific for mitochondria as they have never checked for the presence of other type of cargo in the vesicles produced by RGCs. If these are related to exophers as they suggest in the document, is very probable that they contain other type of cargo; Second, if the final destiny for those particles is the acidic compartment of astrocytes, this process may have nothing to do with autophagy/mitophagy and just share some molecular mediators with those pathways; Third, they should explore if other canonical mitophagy molecular mediators (i.e. Parkin/Pink) are regulating the production or the mitochondria recruitment to this extracellular particles.

We too struggle with our own “transmitophagy” term, for the very reasons stated. To address this concern, we now refer to the process as “transcellular degradation of mitochondria”, which is how we described it initially in mice as well. We do present new data that show that while the majority of axonal outpocketings contain mitochondria, not all do. This suggests that the others may contain other cargo, which supports the view that what we are dealing with in axons are indeed exophers. And yet, since what we measure is mitochondria, we think most appropriate to describe the process narrowly and not extrapolate to other types of exophers. We agree that what we originally discovered in mice and now live image and perturb in frog, may not be “autophagy” according to the strict definition of the term, but rather a process that uses some of the same molecular machinery, which given the evolutionary link between autophagy and phagocytosis that should be no surprise. Terminology can be tricky, and we thank the reviewer for calling us out on this point. We now use the term “transmitophagy” only once in the discussion section making the link between our work and the emerging field of exopher biology, and use that occasion to elaborate the point that the more descriptive term “transcellular degradation of mitochondria” is more appropriate in our case.

*- In several experiments, authors use Mitotracker instead of genetic tools to quantify the amount of mitochondria co-localizing with OPTN (Fig2, Fig3) or being transferred to astrocytes (Fig4). A problem here is that Mitotracker needs the mitochondria to be active at the time of injection in order to label them (PMID: 21807856) and it has a clear effect in mitochondria dynamics in their setting, as pointed by the authors. Since most mitochondria transferred to astrocytes would be presumably damaged and not able to import Mitotracker, I am concern about how this is affecting their quantifications and the conclusions.

*

We agree. The use of Mitotracker to label the RGC mitochondria can be problematic for the reasons stated by reviewers 1 and 3. Indeed, our opinion is that many of the studies out there that claim to demonstrate transfer of mitochondria between cells likely are just showing the transfer of the dye rather than the mitochondria. While the previous submission included a number of controls to address this concern, we now provide multiple new experiments that measure the transfer of mitochondria through a transgene rather than Mitotracker. The provided experiments use a new Tom20-mCherry transgene which is highly specific to mitochondria due to the use of an SOD2 UTR. We have similar data using RGC-expressed Mito-mCherry and Mito-EGFP-mCherry (using the commonly used Cox8 mitochondria matrix targeting sequence); we do not include such data because we find the provided data sufficiently compelling, and the story is already sufficiently long and complicated.

- Some conclusions are based on single images with no quantifications or statistics. This is the case for: 1) Page 6) "Most of the mCherry and Mitotracker objects colocalized with each other both in the merged images (Fig. S1C) and kymographs (Fig. S1D), indicating that the mitochondria-targeted transgene and Mitotracker similarly label the RGC axonal mitochondria".

That is a fair comment. After reanalyzing the original dataset used, it would be very difficult to quantify that statement, largely because the Tom20-mCherry expression was relatively weak in those particular animals. We are confident that we could generate a new dataset to provide support for this statement, but instead chose to just provide side-by-side movies of mitochondria labeled by Mitotracker or the Tom20-mCherry transgenes, which we believe is far more compelling than any quantification we could provide.

2) Page 8) "In the nerves labeled by Mitotracker, visual inspection of the raw images (Fig. 2C) and the derived kymographs (Fig. 2D) showed that OPTN and the Mitotracker labeled mitochondria often co-localized, particularly in the stopped populations, and more so in the animals expressing E50K OPTN, further suggesting that at least a fraction of the stopped LC3b, OPTN and mitochondria might represent mitophagy occurring in the axons".

While we have made a minor change to this sentence, we feel that it is appropriate given that it serves just as a justification to carry out the quantitative studies that follow. We would not have quantified the process had it not been obvious to the eye. However, we do not interpret the results as supporting that mitophagy occurs in axons, for the reasons explained above.

3) Page 14) "We also observed similar axonal dystrophies and exopher-like structures in E50K OPTN under similar imaging settings, but with 2-min intervals and additional Mitotracker labeling (Mov. 6), demonstrating that these structures not only contain OPTN but also mitochondria or mitochondria remnants". Image in video is not clear and there is not quantification for OPTN or OPTN+ mitochondria.*

*

We have removed Mov. 6.

*Minor comments

• In Figures showing the reconstruction of OPTN+ mitochondria outside nerve (Fig.3 and Fig.4), those seem to be present only in one lateral of the nerve. Is this process polarized in any way (i.e. faced to astrocytes) or is the result of a technical issue (i.e. difference in laser penetration for blue vs Yellow lasers)? I think it will be important to include this in the discussion.*

This was also pointed out by reviewer 1, and we agree that it is worth including in the discussion, which we now do. While we do not believe it to be a light penetration issue (based on fluorescence intensities and apparent spatial resolution), we also do not yet have an explanation. Having studied dorsoventral differences in the visual pathway both during my graduate and post-doctoral years, I am very interested in this asymmetry, and we have some theories that might explain it, mentioned above. The asymmetry is obvious and thus we think it would have been inappropriate not to show, but it also be inappropriate to be overly speculative.

- In Pag.13 authors claim "OPTN and mitochondria leave RGC axons in the form of exophers". After "exophers" were coined by the Driscoll lab in 2017, too few people has adopted this terminology and the molecular machinery involved in this process is still under research. It is clear that the particles described here share some similarities with exophers like size (in the range of microns) and cargo (mitochondria), but you have not demonstrated if they share the same origin or are part of the same phenomena. For that reason, I recommend to be more cautious with this statement and point these limitations in the discussion. Additionally, since Exophers are not a consensus or well defined particles, authors should include an introductory paragraph at the beginning of this section for readers to understand what they are talking about.

We wholly agree with all points. We now have moved all mention of exophers to just the discussion.

- Exophers described by Monica Driscoll and Andres Hidalgo laboratories are presented as "garbage bags" that help cells to stay fit through elimination of unwanted material. If the extracellular vesicles presented here are part of the same mechanism and potentially beneficial for the RGCs, why are they increased in OPTN mutants? Is it part of RGCs response to a proteomic stress generated by malfunctioning OPTN? I think that is critical to understand this to figure out the relevance of your findings.

• *

Our personal opinion is that the OPTN mutants most likely lead to stress focally in the axons, thus triggering exopher generation. We are carrying additional experiments to determine whether too much exopher generation or their insufficient degradation by astrocytes might be deleterious (by causing inflammation). However, those are big stories that would not stand on their own were we not able to first rigorously demonstrate that certain OPTN mutants increase exopher generation, which I believe our study demonstrates, albeit now without calling them exophers.

- Related to Fig.5G, authors say "The soma of the astrocytes were located at the optic nerve periphery but had processes that extended deep into the parenchyma". This is very interesting and opens the possibility that many mitochondria are directly transferred to astrocytes through that processes instead of the lateral of the nerve, meaning that your quantifications of "transmitophagy" may be underestimated.

* *We also agree that this. Our limited optical resolution, and limitations intrinsic to carrying out quantifications with Imaris software, are likely the main reasons for the discrepancy between the whole nerve and sparse-labelled-axon estimates of how much axonal material is outside of axons. Our view is that most of the transcellular degradation occurs within fine astrocyte processes, and that only in the case of failure to degrade material in these fine processes that significant amounts accumulate in the cell body (optic nerve periphery), and that in the cell body additional or different degradative pathways are utilized. Experiments using various transgenes and correlated EM as well as perturbation experiments are ongoing attempting to firmly establish what organelles are used in processes versus soma. However, we believe that such studies are well beyond the scope of this manuscript..

- Reference to Fig. S2G is missing. Now mentioned twice. Thank you.

- I cannot find in Fig.5 E-I legends what are the cells/structures labelled in Green and Red. Thank you.

***Referees cross-commenting**

In agreement with my colleagues, I think that a revision is needed to support some important points of the paper. The the work is interesting and I think it deserves a chance for revision. Having that said, I am not familiar with the breeding and experimental times when working with Xenopus but, considering the amount of work requested, it may require more than 3 months to have the work done.

*

*Reviewer #3 (Significance (Required)):

Until not very long ago, it was thought that mitochondria could not cross cell barriers. In recent years however, there has been an explosion in the number of works showing mitochondria transfer between different cell types in vivo. This may happen either as an organelle donation to improve energy production or as a quality control mechanism to get rid of damaged mitochondria, as it is the case in this work. The laboratory of Nicholas Marsh-Armstrong was pioneer in this field with a foundational work in 2014 where they show how RGC-derived mitochondria are captured and eliminated by astrocytes in mice (PMID: 24979790). This work was particularly relevant because it proposed for the first time that mitochondrial degradation can occur in RGC axons far from the cell soma, and surrogated in a different cell type, something that changed completely the view of how quality control is maintained in neurons and other cell types. In the present study, Jeong and collaborators explore how Glaucoma-associated Optineurin mutations affect this process, which is of potential interest for the broad cell biologist community due to its possible implications in other tissues and cell types (OPTN is broadly expressed), but especially for those researchers interested in neurobiology, quality control mechanisms and mitochondria biology. Since some OPTN mutations studied here cause disease, they are also relevant for the clinic. This work provides a thorough characterization of how relevant Optineurin mutations affect mitochondria dynamics in RGCs and their transference to astrocytes, as fairly claimed in the title. However, the mechanism by which they result in pathology is not either explored or carefully discussed, making this a descriptive work with no much conceptual insight. In addition, conclusions are often not unambiguously stated and the results part contains a lot of large sentences and unnecessary technical data that hinders reading and difficult the transmission of the key messages. Even if it stands as a descriptive work, the physiological and clinical relevance of these findings is not clear. There are some claims related with mitophagy activity that may require more sophisticated experiments (mitophagy flux with lysosomal inhibitors). Please see comments above. A critical point to understand the relevance of this work would be to demonstrate if alterations in transmitophagy are either causing or involved in the disease generated by these OPTN mutations in any way, or just a correlative phenomenon. To help authors contextualize my point of view, my field of expertise includes cell biology, imaging, quality control pathways, mitochondria biology and phagocytosis, among others. I am not familiar with Xenopus Laevis genetics or the limitations to work with this animal model.*

• *

We appreciate both the complements and the critiques. To a fault, we rather undersell than oversell. We are actively pursuing the possibility that dysregulation of this process is disease causing, and not just for glaucoma. However, those studies will not stand without a strong foundation, which we believe this study provides.

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Referee #3

Evidence, reproducibility and clarity

Summary

In this work, Jeong et al describe the effect of Optineurin (OPTN) mutations in the transcellular degradation of retinal ganglion cell (RGC) mitochondria by astrocytes at the Optic Nerve (ON), a process previously described this group and referred as "transmitophagy" (Davis et al 2014). Here, authors use Xenopus laevis animal model to image the optic nerve of animals carrying different OPTN mutations associated to disease or with compromised function and explore its effect in mitochondria dynamics at the RGC axons. They find that OPTN mutants lead to increased stationary mitochondria in the nerve and affect their co-localization with mitophagy-related markers, suggesting alterations in this pathway. Finally, they found that mitochondria co-localizing with OPTN can be found in the periphery of the ON under different conditions and this is particularly increased in glaucoma-associated E50K mutation. This extracellular mitochondria are transferred in vesicles to astrocytes, as they previously described in mice (Davis 2014), where they are presumably degraded.

Major comments

• OPTN levels at a given time point cannot be used as readout for mitophagy level/flux. Both OPTN and LC3b are degraded upon fusion with acidic compartment (i.e. lysosomes, PMID: 33783320, 33634751) and that is the reason why the field of autophagy /mitophagy blocks lysosomal activity to measure autophagy/mitophagy flux (PMID: 33634751). In this document, authors claim that there is low levels of mitophagy in RGC axons at baseline and increased levels of mitophagy in glaucoma associated perturbations just based on increased presence of OPTN+ mitochondria in this condition. This could be also interpreted as an accumulation of non-degraded defective mitochondria due to a mitophagy block in neurons carrying the glaucoma associated mutation, which is the opposite of what they propose. If authors want to evaluate mitophagy levels in this system, mitophagy/autophagy flux experiments should be performed.
• I find inappropriate the use of the term "transmitophagy". Although this term transmits very well the message that the authors try to strength, the term "mitophagy" refers to the specific elimination of mitochondria through autophagy (PMID: 21179058). There are many reasons why I think that "transmitophagy" is not adequate to describe this phenomena but I will just refer to these three: First, authors do not provide data showing that this mechanism is specific for mitochondria as they have never checked for the presence of other type of cargo in the vesicles produced by RGCs. If these are related to exophers as they suggest in the document, is very probable that they contain other type of cargo; Second, if the final destiny for those particles is the acidic compartment of astrocytes, this process may have nothing to do with autophagy/mitophagy and just share some molecular mediators with those pathways; Third, they should explore if other canonical mitophagy molecular mediators (i.e. Parkin/Pink) are regulating the production or the mitochondria recruitment to this extracellular particles.
• In several experiments, authors use Mitotracker instead of genetic tools to quantify the amount of mitochondria co-localizing with OPTN (Fig2, Fig3) or being transferred to astrocytes (Fig4). A problem here is that Mitotracker needs the mitochondria to be active at the time of injection in order to label them (PMID: 21807856) and it has a clear effect in mitochondria dynamics in their setting, as pointed by the authors. Since most mitochondria transferred to astrocytes would be presumably damaged and not able to import Mitotracker, I am concern about how this is affecting their quantifications and the conclusions.
• Some conclusions are based on single images with no quantifications or statistics. This is the case for:
  1. Page 6) "Most of the mCherry and Mitotracker objects colocalized with each other both in the merged images (Fig. S1C) and kymographs (Fig. S1D), indicating that the mitochondria-targeted transgene and Mitotracker similarly label the RGC axonal mitochondria".
  2. Page 8) "In the nerves labeled by Mitotracker, visual inspection of the raw images (Fig. 2C) and the derived kymographs (Fig. 2D) showed that OPTN and the Mitotracker labeled mitochondria often co-localized, particularly in the stopped populations, and more so in the animals expressing E50K OPTN, further suggesting that at least a fraction of the stopped LC3b, OPTN and mitochondria might represent mitophagy occurring in the axons".
  3. Page 14) "We also observed similar axonal dystrophies and exopher-like structures in E50K OPTN under similar imaging settings, but with 2-min intervals and additional Mitotracker labeling (Mov. 6), demonstrating that these structures not only contain OPTN but also mitochondria or mitochondria remnants". Image in video is not clear and there is not quantification for OPTN or OPTN+ mitochondria.

Minor comments

• In Figures showing the reconstruction of OPTN+ mitochondria outside nerve (Fig.3 and Fig.4), those seem to be present only in one lateral of the nerve. Is this process polarized in any way (i.e. faced to astrocytes) or is the result of a technical issue (i.e. difference in laser penetration for blue vs Yellow lasers)? I think it will be important to include this in the discussion.
• In Pag.13 authors claim "OPTN and mitochondria leave RGC axons in the form of exophers". After "exophers" were coined by the Driscoll lab in 2017, too few people has adopted this terminology and the molecular machinery involved in this process is still under research. It is clear that the particles described here share some similarities with exophers like size (in the range of microns) and cargo (mitochondria), but you have not demonstrated if they share the same origin or are part of the same phenomena. For that reason, I recommend to be more cautious with this statement and point these limitations in the discussion. Additionally, since Exophers are not a consensus or well defined particles, authors should include an introductory paragraph at the beginning of this section for readers to understand what they are talking about.
• Exophers described by Monica Driscoll and Andres Hidalgo laboratories are presented as "garbage bags" that help cells to stay fit through elimination of unwanted material. If the extracellular vesicles presented here are part of the same mechanism and potentially beneficial for the RGCs, why are they increased in OPTN mutants? Is it part of RGCs response to a proteomic stress generated by malfunctioning OPTN? I think that is critical to understand this to figure out the relevance of your findings.
• Related to Fig.5G, authors say "The soma of the astrocytes were located at the optic nerve periphery but had processes that extended deep into the parenchyma". This is very interesting and opens the possibility that many mitochondria are directly transferred to astrocytes through that processes instead of the lateral of the nerve, meaning that your quantifications of "transmitophagy" may be underestimated.
• Reference to Fig. S2G is missing.
• I cannot find in Fig.5 E-I legends what are the cells/structures labelled in Green and Red.

Referees cross-commenting

In agreement with my colleagues, I think that a revision is needed to support some important points of the paper. The the work is interesting and I think it deserves a chance for revision. Having that said, I am not familiar with the breeding and experimental times when working with Xenopus but, considering the amount of work requested, it may require more than 3 months to have the work done.

Significance

Until not very long ago, it was thought that mitochondria could not cross cell barriers. In recent years however, there has been an explosion in the number of works showing mitochondria transfer between different cell types in vivo. This may happen either as an organelle donation to improve energy production or as a quality control mechanism to get rid of damaged mitochondria, as it is the case in this work. The laboratory of Nicholas Marsh-Armstrong was pioneer in this field with a foundational work in 2014 where they show how RGC-derived mitochondria are captured and eliminated by astrocytes in mice (PMID: 24979790). This work was particularly relevant because it proposed for the first time that mitochondrial degradation can occur in RGC axons far from the cell soma, and surrogated in a different cell type, something that changed completely the view of how quality control is maintained in neurons and other cell types.

In the present study, Jeong and collaborators explore how Glaucoma-associated Optineurin mutations affect this process, which is of potential interest for the broad cell biologist community due to its possible implications in other tissues and cell types (OPTN is broadly expressed), but especially for those researchers interested in neurobiology, quality control mechanisms and mitochondria biology. Since some OPTN mutations studied here cause disease, they are also relevant for the clinic.

This work provides a thorough characterization of how relevant Optineurin mutations affect mitochondria dynamics in RGCs and their transference to astrocytes, as fairly claimed in the title. However, the mechanism by which they result in pathology is not either explored or carefully discussed, making this a descriptive work with no much conceptual insight. In addition, conclusions are often not unambiguously stated and the results part contains a lot of large sentences and unnecessary technical data that hinders reading and difficult the transmission of the key messages.

Even if it stands as a descriptive work, the physiological and clinical relevance of these findings is not clear. There are some claims related with mitophagy activity that may require more sophisticated experiments (mitophagy flux with lysosomal inhibitors). Please see comments above. A critical point to understand the relevance of this work would be to demonstrate if alterations in transmitophagy are either causing or involved in the disease generated by these OPTN mutations in any way, or just a correlative phenomenon. To help authors contextualize my point of view, my field of expertise includes cell biology, imaging, quality control pathways, mitochondria biology and phagocytosis, among others. I am not familiar with Xenopus Laevis genetics or the limitations to work with this animal model.

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Referee #2

Evidence, reproducibility and clarity

Summary: This article studied transmitophagy in xenopus optic nerves in the context of overexpressing glaucoma-associated optineurin mutations. Using a series of labeling, imaging and transplantation techniques, the authors found that overexpressing mutated optineurins stops mitochondria movements and potentially induces transmitophagy, and that astrocytes are responsible for taking up the extra-axonal mitochondria. Below are my comments on this article.

Major comments:

1. Identifying extra-axonal mitochondria is key to this research. In Figure 3, the authors used EGFP-LC3B as a marker for RGC boundaries. However, it is unconvincing how perfect LC3B is as a cell membrane marker. Particularly in the case of OPTN E50K OE, it seems that the optic nerve is thinner than the WT condition, which makes the quantification of extra-axonal OPTN less convincing. The authors should detect extra-axonal mitochondria with an RGC membrane marker or cytosolic marker. In addition, in Figure 3, the extra-axonal mitochondria seem to localize mostly on the dorsal surface. Why is there such a polarity?
2. The experiment in Figure 5 is very important as it gives direct evidence of transmitophagy. However, one caveat is that the mitotracker injection is done after the transplantation. If in rare cases the dye is leaky after injection and is taken up by astrocytes directly, then the conclusion that mitochondria from RGCs are phagocytosed by astrocytes will be flawed. The authors should either use a transgene in the donor to label mitochondria or inject mitotracker into the donor before the transplantation and repeat the experiments. In addition, in Figure 5E, what is the large membranous structure inside the highlighted astrocyte? Is it associated with phagocytosis?
3. This research is entirely based on overexpression of OPTN. Since overexpressing WT OPTN does seem to affect mito trafficking (Figure S2G, and the description in the manuscript is often inconsistent with this result), it is unclear what the increased stalled mitochondria really mean when overexpressing mutated OPTN. Similarly, the authors examined extra-axonal mitochondria in Figures 3 and 4 all in overexpressing conditions, and made the connection that increased stalled mitochondria lead to transmitophagy. However, this conclusion will be better supported by using mutant animals rather than overexpression. The authors should consider using OPTN mutant xenopus if available or using CRISPR to introduce the specific mutations and repeat mitochondria trafficking and transmitophagy.
4. On Page 12, the authors claim that even overexpressing WT OPTN causes extra-axonal mitochondria in the optic nerve. However, there is no control condition without OE to support this conclusion. It is thus unclear to what extent extra-axonal mitochondria occur at baseline and how many extra-axonal mitochondria can be induced by overexpression. The authors should include, in Figure 3 and 4, controls without overexpression.
5. A technical question regarding kymographs: Based on Figure 2C, it looks that OPTN and LC3B labeling are pretty diffuse in axons and this makes sense since they may only be associated with damaged mitos. But this raises a question about how accurate the kymograph assay is. It may significantly underestimate the fraction of OPTN/LC3B that is stationary since they appeared diffusedon the kymograph. This may explain why the percentage of stationary OPTN/LC3B is so small when the authors OE WT OPTN in Figure 2E and 2E', compared to the percentage of moving mitochondria shown in Figure 1E.

Minor:

1. Figure 2E and 2E' do not agree with the text on page 7 and page 8. Not only F178A, but also H486R and D474N have no effect on OPTN trafficking. The authors should make their conclusions more accurate.
2. Figure S2E-F: why does OE of mutated OPTN in F1s but not in F0s reduce trafficking speed compared to WT?
3. In movie 5, fusion of exopher with other structures is not clear and also the GFP signal does not disappear, which is in contrast to the statement in the text that the GFP signal is quenched in acidified environment. To confirm that LC3B leaves RGC axons in exophers, the authors should consider switching the fluorophores and examine LC3B localization during exopher formation.
4. In figure 6, to better show exopher formation and the pinching-off step, the authors should consider labeling the membrane and mitochondria instead of using the LC3B and OPTN marker.

Referees cross-commenting

Generally agree with the criticisms voiced by the other reviewers; in aggregate the reviews indicate the manuscript needs more than just a quick fix.

Significance

Previous literature has already described the transmitophagy process in the optic nerve. The significance of this paper lies in the observation that overexpressing glaucoma-associated OPTN mutants can induce increased transmitophagy through astrocytes, which points to a potential role of OPTN in glaucoma. A highlight of this paper is the use of correlated light SBEM to directly show transmitophagy in astrocytes. However, the significance of this paper may be limited for the following reasons: 1. everything is based on overexpression of mutated OPTN, which makes it hard to translate the results to real disease conditions; 2. The consequence of increased transmitophagy on RGC survival or visual functions is unclear.

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Referee #1

Evidence, reproducibility and clarity

Glaucoma-associated optineurin mutations increase transmitophagy in vertebrate optic nerve.

Summary

In Jeong et al., the authors perform live imaging of the X. laevis optic nerve to track neuronal mitochondrial movement and expulsion in an intact nervous system. The authors observe similar mitochondrial dynamics in vivo as previously described in other systems. They find that stationary mitochondria are more likely to be associated with OPTN, suggestive of mitochondria undergoing mitophagy. Forced expression of OPTN mutations results in a larger pool of stationary mitochondria that colocalize withLC3B, and OPTN. Finally, the authors argue that extra-axonal mitochondria are observed more frequently in OPTN mutants, suggesting that mutations in OPTN that are associated with disease can lead to an increase in the expulsion of mitochondria through exopher-like structures.

Major Findings and impact:

• The authors establish that mitochondria dynamics can be tracked in the X. laevis optic nerve.
• OPTN mutations increase the stationary pool of mitochondria and likely result in increased rates of mitophagy.
• Exopher-like structures containing mitochondria and LC3 can be expelled from the optic nerve and increase in the presence of OPTN mutations. These structures were observed in a living system and have interesting implications in the context of disease.

Concerns:

• The authors state in their results that the secreted blebs are exophers. While these initial observations are consistent with exophers, additional data are needed to strengthen this claim. For example: what are the sizes of secreted vesicles? Do all express LC3? How frequently do these occur? From where are they expelling? Alternatively, the discussion of exophers could be moved to the discussion.
• Quantifications in sparse labeling experiments seem quite surprising and concerns related to these findings should be addressed. As the authors used LC3b expression to represent axonal volume, the authors should demonstrate that this is the case using an axonal fill or membrane marker in both the wt and E50K conditions. This is important as it is unclear whether LC3b expression is consistent between the wild type and the E50K conditions. Lower expression of LC3b in E50K could account for the large changes in axonal width that seem to be observed and could confound the measured amount of expelled mitochondria.
• Could large amounts of exogenous mitochondria in explant experiments be from cells that died during the plantation?

Suggested experiments/quantifications:

• In OPTN/MITO/LC3b trafficking experiments, does flux/number of events change? Representative kymograph in Figure 2D seems to show far more OPTN-positive mitochondria which is opposite of what is shown in Figure 2C.
• Demonstrate that axonal width measured with LC3B is representative of axonal fill/membrane marker in wt and E50K. Axonal area appears to change, is this accurate? This appears to be the case for both figure 3 and figure 4.
• Raw images in addition to the reconstruction would be beneficial.
• Further characterization of exopher-like structures.

Referees cross-commenting

I agree with the concerns of the other reviewers, and perhaps was over-optimistic about a timeline for revision. However, I do think the work is worth the effort, and I hope to see a revised manuscript published somewhere, as these observations are novel

Significance

This work reports potentially novel biology, and thus will be of interest to the field. The strength of the study is that it is an initial description of this biology, rather than a complete analysis. The work raises many more questions than it answers, and much further work on this topic is required to support these initial findings, but the manuscript will likely be of interest to many. Revisions are required to improve the rigor and clarity of the work, but following these revisions we recommend publication to facilitate follow-up work.

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Reply to the reviewers

Reviewer #1

Evidence, reproducibility and clarity

Summary:

This manuscript by Xu, Hörner, Schüle and colleagues is an RNA-seq study focusing characterization of axonal transcriptomes from human iPSC-derived cortical neurons. The authors have differentiated iPSC into neurons, cultured them in microfluidic devices and isolated axonal RNA, comparing this to corresponding cell soma transcriptomes. Second, axonal transcriptomes are compared between wild type and Kif1c knockout axons to determine Kif1c-dependently localized transcripts. Characterization of the latter allows the authors to suggest differentially expressed transcripts in Kif1c-KO axons can be mRNAs relevant for motor neuron degeneration owing to Kif1c mutations in hereditary spastic paraplegias.

Major comments: Overall, his manuscript reads like work in (early) progress. This manuscript provides an interesting dataset, but needs substantial additional experimental and/or bioinformatic work to merit publication. The technical complexity of steps that have led to obtaining axonal transcriptomes can be appreciated, the soundness of generating these data is beyond doubt. However, the study stops at the point of generating axonal transcriptomes from wild type and Kif1c axons. No follow-up experiments are performed to study genes of interest found in RNA-seq. This could be compensated by in-depth bioinformatic analysis (e.g. comparisons with the many different datasets in known in the field), but this is clearly lacking as well. The results section only contains minimal bioinformatic analysis and nothing else. Introduction and discussion are well, clearly written and are in good dialogue with the existing body of work. To improve the manuscript, at minimum these two aspects should be addressed: 1. Characterization of the iPSC-derived neurons is missing (immunostaining with neuronal markers, e.g. Tau, MAP2, exclusion of glial markers, and lack of stem cell markers) 2. Validation of candidates of interest (e.g. FISH analysis in axons vs somata, Kif1c vs wt). Very specific requests from the review are useless at this point, as the authors should have the liberty to focus.

Thank you for the review of our manuscript. We appreciate your recognition of the technical complexity involved in generating axonal transcriptomes and the clarity of our introduction and discussion sections.

__Characterization of iPSC-derived neurons: __We acknowledge the importance of immunostaining with neuronal markers to ensure the purity of our neuronal population. We included this characterization in our revised manuscript and added it into the results and methods section of the paper (Supplementary Figure S1). Additionally, we included RT-qPCR analysis that confirmed the presence of cortical markers and added these to the results and method section of the paper (Supplementary Figure S2).

Additional bioinformatic work: We agree that additional bioinformatic work will greatly benefit this paper. Therefore, we compared our datasets to all additional datasets that we were able to retrieve. This was added to the main text (results and discussion) and supplementary material (Supplementary Figure S5 and S6). We believe this strengthens the merit of our paper, and adds a lot of new unpublished information to the manuscript

__Validation of candidates of interest: __We understand the necessity of validating our RNA-seq findings through experimental approaches such as FISH analysis and comparisons between KIF1C knockout and wild-type neurons. While we appreciate the comment and agree on the importance of high-resolution RNA FISH, we believe it is beyond the scope of this manuscript due to the considerable complexity of these experiments in human iPSC-derived cortical neurons. We will focus on incorporating this aspect into future studies and added a corresponding statement outlining the limitations of our study in the discussion stressing the importance of this.

Minor comments: 1. Details of RNA seq technicalities are redundant in the results section, e.g. „Our RNA-seq pipeline encompassed read quality control (QC), RNA-seq mapping, and gene quantification" (p. 7) is a trivial description - this and similar details should be skipped or described in methods.

We will ensure that technical details are appropriately placed in the methods section and avoid redundancy in the results. Technical details included in the results section have been moved to the methods.

1. Fig1A: Y axis should start from 0

We adjusted Figure 1A to start the Y-axis from 0.

1. Too much interpretational voice in figure legends (e.g. see Fig. 1, „PC1 clearly distinguishes the soma (blue)"

We revised the interpretational voice in the figure legends to maintain objectivity.

1. PCA analysis seems redundant in Fig. 2C

We removed the PCA analysis in Fig. 2A (2C corresponds to Gene ontology term enrichment analysis).

1. Subheading „Human motor axons show a unique transcription factor profile" is misleading - you are not dealing with motor iPS-derived motoneurons (Isl-1 positive), but cortical neurons (again, no marker information provided to assess this!)

The subheading „Human motor axons show a unique transcription factor profile" was adjusted. Furthermore, validation of neuronal identity has been added to the supplementary figures (Supplementary Figure S1 and S2), as well as main text and methods section.

1. Fig. 3: Just by comparing top expressed factors in axonal samples is not informative - overall high expression of a certain transcript likely makes it easier for it to be picked up in the axonal compartment. Axon/soma ratios would perhaps be more appropriate.

After careful consideration, we decided that we will not change the data presentation in Figure 3. Our aim in this figure was not to compare axon and soma but to see highly expressed transcripts in the axon, regardless of whether they are highly expressed in the soma as well. We think that looking at transcripts present in the axon can give information about axonal function, that we might lose when we only consider transcripts that are upregulated compared to the soma. The fact that 25 out of 50 transcription factor RNAs detected in the axon are actually specific to the axons supports this point of view. The comparison between transcripts expressed in axon and soma are presented in Figure 2.

1. Figure 4 (KIF1C modulates the axonal transcriptome): you should show also data for the same genes in the soma, axonal data only is misleading (is overall expression changed?)

We appreciate your suggestion. This data was already included in Supplementary Figure S6 (now Supplementary Figure S9). To make this easier to find, we've added a section to the results part to more clearly state how transcript expression changes in the soma.

Significance

Axonal transcriptomes have been studied since early 2010s by a number of groups and several datasets exist from different model systems. The authors know these studies well, address their findings and cite them appropriately. Is the dataset in this manuscript novel? Does it contribute to the field? Several axonal transcriptomes have been characterized in thorough studies, and even in the specific niche (human IPS-derived motoneurons) a point of reference exists - as the authors themselves point out, it is the Nijssen 2018 study. With appropriate presentation and follow-up experiments this material could have merit as a replication study.

Audience: specialized

We appreciate the reviewer's suggestion to clarify the differences between our findings and previously published data. In response, we have added a dedicated section to the discussion, where we provide a more detailed comparison of our results with existing research. This includes an in-depth examination of the methodologies, experimental conditions, and biological contexts that may explain the observed discrepancies (e.g., variations in methods, neuronal types, and disease contexts). As prior studies primarily focused on mouse-derived neurons, we have included a new section in both the results (Supplementary Figure S6) and the discussion to highlight the limited overlap in gene expression between the axons of mouse- and human-derived neurons. Furthermore, previous studies on human-derived cells either investigated i3 neurons -induced by transcription factors but not fully representative of human-derived CNS-resident neurons - or neurons of the peripheral nervous system (lower motor neurons). In contrast, our study focuses on human-derived CNS-resident cortical neurons (Supplementary Figure S1, S2; comparison shown in Supplementary Figure S5), emphasizing the greater translatability of our findings.

Moreover, we have expanded our bioinformatic analyses and compared our dataset with additional datasets to further substantiate our conclusions (Supplementary Figure S5, S6)

We believe that these revisions significantly enhance the clarity, quality, and impact of our manuscript. We sincerely thank the reviewer for their constructive feedback.

Reviewer #2

Evidence, reproducibility and clarity

This study seeks to identify axonal transcriptome by RNA-sequencing of the iPSC-derived cortical neuron axons. This is achieved by comparing the RNA expressions between the axonal and soma compartments using microfluid system. The specific expression of axon specific RNAs in the axonal compartment validate the specificity of the approach. Some unique RNAs including TF specific RNAs are identified. Furthermore, this study compared the KIF1C-knockout neurons (which models hereditary spastic paraplegia characterized by axonal degeneration) with wildtype (WT) control neurons, which led to the identification of specific down-regulated RNAs involved in axonal development and guidance, neurotransmission, and synaptic formation.

The data of this study are interesting and clearly presented. The major concerns are the lack of characterization of the neuron identities and the examination of functional deficits in the KIF1C-knockout neurons. For example: 1) are these neurons express layer V/VI markers at protein levels, and the proportion of positive neurons (efficiency of cortical neuron differentiation); 2) What are the phenotypic changes in the KIF1C-knockout neurons; are there change sin axonal growth or transport? 3) Day 58 was selected for collecting RNA for sequencing study: how this time point is selected? And are there phenotypic differences between the WT and knockout neurons at this time point?

We appreciate the favorable review of our manuscript and the insightful comments:

Characterization of neuron identities: We agree on the importance of validating neuron identities and included protein-level characterization of layer V/VI markers and efficiency of cortical neuron differentiation in our revised manuscript: We conducted immunohistochemical staining for layer V/VI and other neuronal markers, as well as qRT-PCR to validate the identity of the neurons, ensuring a comprehensive characterization of our neuronal population.

Functional deficits in KIF1C-knockout neurons: We have conducted phenotypic examinations of the neurons but did not observe gross differences in differentiation, axon growth or axon length. We added a corresponding statement to the results section. Neurons were harvested at DAI 58 because at this time we achieved a nearly confluent chamber that yielded enough material for in-depth RNA-sequencing. We did not observe phenotypic differences between wt and KIF1C-KO neurons at this time point. We added a statement to the method section outlining this.

Some minor comments:1. The protein levels of some critical factors needs to be validated.

We validated neuronal identities on qRT-PCR level (Supplementary Figure S2). While we understand the necessity of validating our RNA-seq findings on protein level, we believe it is beyond the scope of this manuscript. However, we will focus on incorporating this aspect into future studies and added a corresponding statement outlining the limitations of our study in the discussion stressing the importance of this.

1. Figure 4C, for the list genes, statistical analyses between WT and knockout groups are required.

In Figure 4C we only included differentially expressed genes with a p-value We added a corresponding statement in the main text and figure legend.

1. Page 15, the 5th to last sentence: "nucleus nucleus" (repeat)

The repeat word on page 15 was deleted.

1. The sequencing data requires public links to the deposited library

We will provide public links to the deposited library for the sequencing data once the data is submitted to a journal (depending on journal guidelines).

Significance

The strength of this study is the combinations of iPSC differentiation, gene editing (KIF1C knockout iPSC) and microfluidic system. This allows the identification of specific axonal transcriptomes. Moreover, the comparisons of control and KIF1C knockout neurons at both axon and soma compartments enables the identification of RNAs and pathways caused by the loss of KIF1C.

The limitation is the lack of functional assessment of the iPSC-derived neurons, especially phenotypic changes in the KIF1C-knockout neurons. Only one time point is selected for comparing the WT and KIF1C knockout neurons, and the relationship between this time point and disease phenotypes is unclear.

This study will be of interest to researchers from both basic and translational fields, and in the fields of stem cells, neuroscience, neurology and genetics.

My expertise includes stem cells, iPSC modeling, motor neuron diseases, and nerve degeneration.

We appreciate the favorable significance statement and believe addressing these points will strengthen the scientific rigor and impact of our study. Thank you for your valuable feedback.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):  Using microfluidics chambers and RNA sequencing (RNA-seq) of axons from iPSC-derived human cortical neurons, authors use RNA profiling to investigate the RNAs present in the soma and axons and the impact of KIF1C molecular motor downregulation (KIF1CKO) on the axonal transcriptome. The rationale is that mutations in KIF1C are associated with an autosomal recessive form of hereditary spastic paraplegia, and KIF1C is implicated in the long-range directional transport of APC-dependent mRNAs and RNA-dependent transport of the exon junction complex into neurites.  Employing a well-defined RNA-seq pipeline for analysis, they obtained RNA sequences particular to axonal samples, outperforming previous studies. They detected over 16,000 genes in the soma (which includes axons) and RNA for more than 5,000 genes in axons. A comparison of the list of axonal genes revealed a strong correlation with previous publications, but they detected more genes overall. They identified transcripts enriched in axons compared to somas, notably those for ribosomal and mitochondrial proteins. Indeed, they observed enrichment for ribosomal subunits, respiratory chain complexes, ion transport, and mRNA splicing.  The study also found that human axons exhibit a unique RNA transcription profile of transcription factors (TFs), with TFs such as GTF3A and ATF4 predominant in axons. At the same time, CREB3 was highly expressed in the soma.  Upon analyzing the soma and axon transcriptomes from KIF1CKO cultures, they identified 189 differentially regulated transcripts: 89 downregulated and 100 upregulated in the KIF1CKO condition. Some of these transcripts are critical for synaptic growth and neurotransmission. Notably, only two targets of APC-target RNAs were downregulated, contrary to their expectation. Their data indicates that KIF1C downregulation significantly alters the axonal transcriptome landscape.  Reviewer #3 (Significance (Required)):  The study is well-performed and informative, particularly for researchers interested in the local translation of axonal proteins and the axonal transcriptome. However, the authors did not validate their findings for any transcripts and did not perform any functional assays, so the manuscript lacks mechanistic insight. Interestingly, GTF3A is a transcription factor that stimulates polymerase III transcription of ribosomal proteins, and mRNAs for ribosomal proteins are enriched in human axons. Maybe there is an interesting story there. 

We appreciate the favorable significance statement and the valuable feedback. We have conducted phenotypic examinations of the neurons but did not observe gross differences in differentiation, axon growth or axon length. We added a corresponding statement to the results section. While we understand the necessity of validating our RNA-seq findings on protein level, we believe it is beyond the scope of this manuscript. However, we will focus on incorporating this aspect into future studies and added a corresponding statement outlining the limitations of our study in the discussion stressing the importance of this.

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Referee #3

Evidence, reproducibility and clarity

Using microfluidics chambers and RNA sequencing (RNA-seq) of axons from iPSC-derived human cortical neurons, authors use RNA profiling to investigate the RNAs present in the soma and axons and the impact of KIF1C molecular motor downregulation (KIF1CKO) on the axonal transcriptome. The rationale is that mutations in KIF1C are associated with an autosomal recessive form of hereditary spastic paraplegia, and KIF1C is implicated in the long-range directional transport of APC-dependent mRNAs and RNA-dependent transport of the exon junction complex into neurites.

Employing a well-defined RNA-seq pipeline for analysis, they obtained RNA sequences particular to axonal samples, outperforming previous studies. They detected over 16,000 genes in the soma (which includes axons) and RNA for more than 5,000 genes in axons. A comparison of the list of axonal genes revealed a strong correlation with previous publications, but they detected more genes overall. They identified transcripts enriched in axons compared to somas, notably those for ribosomal and mitochondrial proteins. Indeed, they observed enrichment for ribosomal subunits, respiratory chain complexes, ion transport, and mRNA splicing. The study also found that human axons exhibit a unique RNA transcription profile of transcription factors (TFs), with TFs such as GTF3A and ATF4 predominant in axons. At the same time, CREB3 was highly expressed in the soma. Upon analyzing the soma and axon transcriptomes from KIF1CKO cultures, they identified 189 differentially regulated transcripts: 89 downregulated and 100 upregulated in the KIF1CKO condition. Some of these transcripts are critical for synaptic growth and neurotransmission. Notably, only two targets of APC-target RNAs were downregulated, contrary to their expectation. Their data indicates that KIF1C downregulation significantly alters the axonal transcriptome landscape.

Significance

The study is well-performed and informative, particularly for researchers interested in the local translation of axonal proteins and the axonal transcriptome. However, the authors did not validate their findings for any transcripts and did not perform any functional assays, so the manuscript lacks mechanistic insight. Interestingly, GTF3A is a transcription factor that stimulates polymerase III transcription of ribosomal proteins, and mRNAs for ribosomal proteins are enriched in human axons. Maybe there is an interesting story there.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #2

Evidence, reproducibility and clarity

This study seeks to identify axonal transcriptome by RNA-sequencing of the iPSC-derived cortical neuron axons. This is achieved by comparing the RNA expressions between the axonal and soma compartments using microfluid system. The specific expression of axon specific RNAs in the axonal compartment validate the specificity of the approach. Some unique RNAs including TF specific RNAs are identified. Furthermore, this study compared the KIF1C-knockout neurons (which models hereditary spastic paraplegia characterized by axonal degeneration) with wildtype (WT) control neurons, which led to the identification of specific down-regulated RNAs involved in axonal development and guidance, neurotransmission, and synaptic formation.

The data of this study are interesting and clearly presented. The major concerns are the lack of characterization of the neuron identities and the examination of functional deficits in the KIF1C-knockout neurons. For example: 1) are these neurons express layer V/VI markers at protein levels, and the proportion of positive neurons (efficiency of cortical neuron differentiation); 2) What are the phenotypic changes in the KIF1C-knockout neurons; are there change sin axonal growth or transport? 3) Day 58 was selected for collecting RNA for sequencing study: how this time point is selected? And are there phenotypic differences between the WT and knockout neurons at this time point?

Some minor comments:

1. The protein levels of some critical factors needs to be validated.
2. Figure 4C, for the list genes, statistical analyses between WT and knockout groups are required.
3. Page 15, the 5th to last sentence: "nucleus nucleus" (repeat)
4. The sequencing data requires public links to the deposited library

Significance

The strength of this study is the combinations of iPSC differentiation, gene editing (KIF1C knockout iPSC) and microfluidic system. This allows the identification of specific axonal transcriptomes. Moreover, the comparisons of control and KIF1C knockout neurons at both axon and soma compartments enables the identification of RNAs and pathways caused by the loss of KIF1C.

The limitation is the lack of functional assessment of the iPSC-derived neurons, especially phenotypic changes in the KIF1C-knockout neurons. Only one time point is selected for comparing the WT and KIF1C knockout neurons, and the relationship between this time point and disease phenotypes is unclear.

This study will be of interest to researchers from both basic and translational fields, and in the fields of stem cells, neuroscience, neurology and genetics.

My expertise includes stem cells, iPSC modeling, motor neuron diseases, and nerve degeneration.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #1

Evidence, reproducibility and clarity

Summary:

This manuscript by Xu, Hörner, Schüle and colleagues is an RNA-seq study focusing characterization of axonal transcriptomes from human iPSC-derived cortical neurons. The authors have differentiated iPSC into neurons, cultured them in microfluidic devices and isolated axonal RNA, comparing this to corresponding cell soma transcriptomes. Second, axonal transcriptomes are compared between wild type and Kif1c knockout axons to determine Kif1c-dependently localized transcripts. Characterization of the latter allows the authors to suggest differentially expressed transcripts in Kif1c-KO axons can be mRNAs relevant for motor neuron degeneration owing to Kif1c mutations in hereditary spastic paraplegias.

Major comments:

Overall, his manuscript reads like work in (early) progress. This manuscript provides an interesting dataset, but needs substantial additional experimental and/or bioinformatic work to merit publication. The technical complexity of steps that have led to obtaining axonal transcriptomes can be appreciated, the soundness of generating these data is beyond doubt. However, the study stops at the point of generating axonal transcriptomes from wild type and Kif1c axons. No follow-up experiments are performed to study genes of interest found in RNA-seq. This could be compensated by in-depth bioinformatic analysis (e.g. comparisons with the many different datasets in known in the field), but this is clearly lacking as well.

The results section only contains minimal bioinformatic analysis and nothing else. Indroduction and discussion are well, clearly written and are in good dialogue with the existing body of work. To improve the manuscript, at minimum these two aspects should be addressed:

1. Characterization of the iPSC-derived neurons is missing (immunostaining with neuronal markers, e.g. Tau, MAP2, exclusion of glial markers, and lack of stem cell markers)
2. Validation of candidates of interest (e.g. FISH analysis in axons vs somata, Kif1c vs wt). Very specific requests from the review are useless at this point, as the authors should have the liberty to focus.

Minor comments:

1. Details of RNA seq technicalities are redundant in the results section, e.g. „Our RNA-seq pipeline encompassed read quality control (QC), RNA-seq mapping, and gene quantification" (p. 7) is a trivial description - this and similar details should be skipped or described in methods.
2. Fig1A: Y axis should start from 0
3. Too much interpretational voice in figure legends (e.g. see Fig. 1, „PC1 clearly distinguishes the soma (blue)"
4. PCA analysis seems redundant in Fig. 2C
5. Subheading „Human motor axons show a unique transcription factor profile" is misleading - you are not dealing with motor iPS-derived motoneurons (Isl-1 positive), but cortical neurons (again, no marker information provided to assess this!)
6. Fig. 3: Just by comparing top expressed factors in axonal samples is not informative - overall high expression of a certain transcript likely makes it easier for it to be picked up in the axonal compartment. Axon/soma ratios would perhaps be more appropriate.
7. Figure 4 (KIF1C modulates the axonal transcriptome): you should show also data for the same genes in the soma, axonal data only is misleading (is overall expression changed?)

Significance

Axonal transcriptomes have been studied since early 2010s by a number of groups and several datasets exist from different model systems. The authors know these studies well, address their findings and cite them appropriately. Is the dataset in this manuscript novel? Does it contribute to the field? Several axonal transcriptomes have been characterized in thorough studies, and even in the specific niche (human IPS-derived motoneurons) a point of reference exists - as the authors themselves point out, it is the Nijssen 2018 study. With appropriate presentation and follow-up experiments this material could have merit as a replication study.

Audience: specialized

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The authors do not wish to provide a response at this time.

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Referee #3

Evidence, reproducibility and clarity

In this study, the authors investigate potential developmental changes in Leishmania infantum isolates from different regions of Brazil (plus a single isolate from Portugal) both in vitro and in vivo. The manuscript present interesting phenotypic comparisons between isolates with a 12-kb deletion of a subtelomeric region on Chr31 and isolates with a complete sequence. The authors suggest that distinctions associated with the presence or absence of that region may potentially be linked with fitness in the wild. A more detailed analysis of such valuable sample cohort would increase the significance of this research. Therefore, I highlight a few important concerns that need to be addressed, as well as a disconnect between the presented data and conclusions made.

Major issues

• The % of metacyclics in all the sand fly infection experiments was extremely low ( <6%). The only exception was NonDEL_PI_2972, which showed around 16% metacyclics. This tells me that the parasites did not develop properly inside any of the 3 vectors used. Does an increase from 2% to 4% make any difference in vector competence? If metacyclogenesis is not significantly higher in DEL isolates, then there will most likely not be an increase in fitness concerning transmission. Also, I assume that both the stomodeal valve infection and the metacyclic % were assessed at 192h p.i., but this must be clearly stated in the text. At what time-point were parasites per gut counted at Charles Univ.? The parameters used in all the different sand fly experiments should be clearly labeled.
• If the metacyclic % data are available for the Fiocruz colony experiments, then it will be important to present those. Conversely, are the #s of parasites/gut available using another time point at Charles Univ.?
• It is mentioned that at least 3 independent sand fly infections were performed, so the data points should be shown for each of the replicates where applicable. A bar plot without error bars is not ideal for representing the stomodeal valve and metacyclic % data either. Based on the current plots, it is difficult to infer biological significance.
• The entire presentation of the sand fly infection experiments is confusing and does not provide consistent findings to support the conclusions, which should be toned down. The whole rationale for the different vector species should be better explained.
• The 3'NT activity in two HTZ isolates is as high as in some NonDEL, while in one HTZ strain it is as low as the DEL isolates. Is there any genomic difference between the HTZ to justify this difference? Since 3254 HTZ was not included in the qPCR analysis presented in Schwabl, et al. 2021, it is difficult to see any correlation.
• Pg. 16 ln.398: The authors conclude that DEL isolates cause effective, yet less pathogenic infection compared to NonDEL isolates. However, it is not possible to reach that conclusion based on the early-infection data presented. For that, i.v.-infected mice would have to be monitored for several weeks and assessed for visceralization and VL severity.
• The most relevant data in this work suggest that metacyclics in nonDEL vs DEL might present important differences. The META2 gene expression, the different M0 infection% rather than different # of intracellular amastigotes, and increases in parasite #s in the draining lymph node at 13-16 hours after ear inoculation suggest to me that the metacyclics could have different infection competence. That possibility should be addressed. Do they display similar morphology? Do they differentiate at similar rates to axenic amastigotes? SHERP transcript levels should be quantified in metacyclics from the different isolates.

Minor issues

• Gene IDs of the transcripts measured should be listed somewhere.
• Fig.1C, Fig2A&B: missing p-value labels.
• Fig.1B needs more detail on the statistical test used. Is it One-way ANOVA? What post-hoc test was used?
• Figs. 2 & 3: "Mann Whitney Rank Sum", "Mann Whitney t-test". The name of the statistical test is either Mann Whitney U test or Wilcoxon rank-sum test.
• Figs. 4 & 5: information missing on statistical tests used in both.
• Pg.8 ln.212: The NT1 median FC in the NonDEL group does not seem to be 0.8 in Fig.2B.

Typos:

• Fig.2 title: "promastigotes harvest from" -> harvested
• Fig2. legend: "Paraflagellar". Is this a paraflagellar rod protein (PFR)? If so, it should be specified throughout the text.
• Fig 2 & 3: "ns = no significant" -> not significant
• Different parts of the text: "alfa-tubulin" -> alpha-tubulin
• Fig.4A: Y-axis reads "Inspected sand flies"

Significance

Despite constituting the same species, significant genetic differences exist in Leishmania infantum variants found in the American continent compared to those in Europe, Africa and Asia. Phenotypic comparison studies such as reported here are relevant to the Parasitology field and may lead to new insights on the pathogenesis of specific clinical outcomes of leishmaniasis disease. The authors attempt to associate a major genetic deletion found in specific neotropical Leishmania infantum strains, isolated in Brazil, with phenotypic changes that could potentially lead to fitness increase during cyclical transmission in the wild.

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Referee #2

Evidence, reproducibility and clarity

In this manuscript the authors have investigated the role of sub chromosomal deletion found in new world Leishmania infantum species. The deletion (12 kb) spans over across the four copies of tetrasomic chromosome 31 which includes the loss of four open reading frames (ORF) LinJ.31.2370 (ecto-3ʹ-nucleotidase/nuclease), LinJ.31.2380 (ecto-3'-nucleotidase precursor), LinJ.31.2390 (helicase-like protein) and LinJ.31.2400 (3,2-trans-enoyl-CoA isomerase). The ecto-3'-nucleotidase/nuclease (3'NU/NT) activity has been shown to have an important role in trypanosomatids in the purine salvage pathway implicated as virulence factor affecting the parasite's ability to infect macrophages. The authors showed that having such deletions enhances the metacyclogenesis in vitro but are highly susceptible to killing by neutrophils and macrophages. In addition, they are also less virulent in vivo. The authors claim that enhanced metacyclogenesis increases its transmissibility in the invertebrate host but may not be highly infectious in the vertebrate host. They speculate that that such parasites may provide immune response that may control the infection in endemic population by having large group of asymptomatic individuals. These outcomes are highly speculative. This study is thought provoking but needs to be studied thoroughly.

Following are the comments:

1. Leishmania 3"NU/NT plays an important role in virulence of the parasite and its survival,

a. how do 3'-NU/NT DEL parasites survive in the host which lack all the 4 copies of NT?

b. what is the advantage of having such parasites circulating in the endemic areas? 2. Since metacyclics are important for the pathogenesis of the parasites,

a. What is the mechanism of increased metacyclogenesis of L. Infantum 3'-NU/NT DEL parasites in the absence of 3'-NU/NT activity which is essential for the virulence? 3. How does lack of 3'NU/NT enhance transmissibility since such metacyclics from 3'-NU/NT DEL parasites barely survive in vivo?

a. the parasites are less resistant to NET and are killed easily.

b. there is reduced recruitment of neutrophils (NT) and monocytes in the ear. 4. Fig.7C: what is the reason for higher parasite load of DEL in dLN? 5. Do you think there is reduced recruitment of NT in the infected site which would have controlled the parasites, hence they migrate quickly in the dLN? To test this possibility the authors should perform an in vitro NT recruitment assay. 6. Line 417: How are the 3'-NU/NT DEL parasites continuous source for infection in sand flies, If such parasites are not infectious and will be cleared by the host? 7. Line 400: Is it possible that having 3'-NU/NT DEL parasites in circulation dampens the infectivity of the NON-DEL and thus over all infection rate in the population goes down? 8. Could the 3'-NU/NT DEL parasites be the source of asymptomatic infections? 9. Is there literature evidence for such a possibility in the endemic region?

Significance

The authors claim that enhanced metacyclogenesis increases transmissibility of Leishmania in the invertebrate host but may not be highly infectious in the vertebrate host. They speculate that that such parasites may provide immune response that may control the infection in endemic population by having large group of asymptomatic individuals. These outcomes are highly speculative. This study is thought provoking but needs to be studied thoroughly.

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Referee #1

Evidence, reproducibility and clarity

Florencio et al., presented a detailed analysis of Brazilian L. infantum isolates with about half with a 4 gene deletion on chromosome 31 and the other half without that deletion. This deletion was first observed in the context of miltefosine responsiveness by the Mottram group. Here a multinational team is concluding that this deletion is associated with increased metacyclogenesis, increase parasite load in some sandfly vector species factors that contribute to their prevalence in South American. Yet the deleted strains show decreased survival invitro including in macrophages, but from what I understand increased load in an animal model, possibly in line with their reduced efficacy in attracting/activating key immune cells.

The authors provide an interesting hypothesis on the equilibrium between pathogenesis (virulence) and capacity to transmit. The perfect parasite would like to infect as many hosts as possible while not killing them. I will try to provide the pro and cons.

1. Obviously (and as acknowledged on p. 344-346) the conclusive experiment would be to add the 4 gene locus (the authors believe that it is the 3'NU/NT gene, so a single gene would even be simpler) in a DEL strain or alternatively KO the locus in a nonDEL strain. This would prove that the phenotype observed is indeed due to the loss of this locus. I understand that this is additional work but it would provide a definite answer. Now we have to rely on associations but alas the associations are not as tight as one would wish.
2. Not sure if it is a dichotomy but they show decreased survival in the presence of NET (Fig. 6A) in vitro but reducing the attraction of immune cells including neutrophils in vivo (Fig. 7). For the nonDEL strain they observe no effect of NET in vitro (Fig. 6) while they seem to attract more immune cells (Fig. 7) in vivo. The in vitro data seems to reach significance for the three group of strains but not for the in vivo work (one out of three).
3. The authors can be lauded for adding more pair of strains but this also adds to the complexity and frankly raises questions. The two strains derived from the PI and MT location differs in many aspects compared to the MS-Rj comparators.
4. It is remarkable that the authors have tested other sandfly vector species (Fig. 5) but what is the conclusion and does it help in our understanding? I see variations in the figure between strains and vectors but not sure what it means.

Secondary points

1. Please confirm that the data in Fig. 1D and 1E are all the DEL and nonDEL strains. The number of dots does not match with the number of strains tested.
2. Do we really need Fig. 2 and 3? Not part of the main message.
3. Why is Fig. 4A only parasite count and 4B,C parasite count (please specify the number of hours) and additional information about stomodeal valve and metacyclics?
4. Please explain sentence on p. 374-375. I thought that DEL is associated with increased metacyclics and increase parasite count in the sandfly
5. Just for curiosity, have the authors try to rescue the phenotype in vitro by adding purines in the medium with the DEL strains?

Significance

Florencio et al., presented a detailed analysis of Brazilian L. infantum isolates with about half with a 4 gene deletion on chromosome 31 and the other half without that deletion. This deletion was first observed in the context of miltefosine responsiveness by the Mottram group. Here a multinational team is concluding that this deletion is associated with increased metacyclogenesis, increase parasite load in some sandfly vector species factors that contribute to their prevalence in South American. Yet the deleted strains show decreased survival invitro including in macrophages, but from what I understand increased load in an animal model, possibly in line with their reduced efficacy in attracting/activating key immune cells.

The authors provide an interesting hypothesis on the equilibrium between pathogenesis (virulence) and capacity to transmit. The perfect parasite would like to infect as many hosts as possible while not killing them.

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Reply to the reviewers

We thank both reviewers for their detailed and critical assessment of our work. Below we provide a step-by-step response to your concerns.

Reviewer #1

Evidence, reproducibility and clarity

The manuscript presents data demonstrating the function of BRI1 in removing the H3K27me3 epigenetic marks in genes involved in seed coat development in Arabidopsis. The results support that BRI1 may function here independently of brassinosteroid. The work combines genetics with a large panel of mutant lines, phenotyping by quantitative microscopy and chemical treatment, H3K27me3 profiling by CUT&TAG, and data mining for published gene profiling. The introduction is adequately informative, complete and explaining the state-of-the-art to the readers. The result part may be a bit lengthy (especially the first part) and some parts may be a bit repetitive.

Thank you for your positive assessment of our work and for the constructive criticism. Below we respond to each of your points.

Major

1. Seed size is dependent of multiple factors. And few are explained here, notably the number of seeds per silique, the number of ovule per silique, the position of the silique of the branch (related to the age of the meristem), the total number of produced siliques (fertilised flowers) by the inflorescence meristem and the plant. And maybe if produced by the main and lateral branches. Were the authors consistent in the evaluation of analyzed siliques coming from the same type of branches, same age of the meristem, etc? Especially as some of the analysed mutants are dwarf, which is a sign of different plant fitness compared to WT.

This is a valid point. We did aim to analyze seeds coming from the main inflorescences of the plants and at similar stages of shoot development. This was harder to achieve in some genotypes, as indeed some BR and JMJ mutants have different plant architectures. However, we did repeat those experiments multiple times and always found consistent differences between the WTs and the mutants. See also our response to your next point and to the first point raised by Reviewer 2, as well as our new Fig. S6.

1. The seed perimeter measurements in BR mutant seeds (Figure S6) are variable. Are you sue the ovule size does not have any influence? What about presenting the relative size as earlier in the text?

Yes, this is particularly true for the Col-0 vs dwf5 comparison. The reason for this is that a different growth chamber was used for this experiment (greenhouse vs a climate chamber). We have observed that absolute seed growth phenotypes can change depending on the environmental conditions, which is something we are currently studying. However, importantly, we do not see changes in relative growth of the mutants when compared to the WT, independently of the growth conditions. That is, BR mutants produce consistently smaller seeds than the WT, independently of the conditions in which the plants are grown. To illustrate this point, we now add a new Figure, Fig. S6, where we show four independent biological replicates of assays comparing seed size between WT and det2 or bri1. These replicates were done in different growth chambers.

Indeed, presenting the data as relative size would solve this issue, but we worried that we would be hiding the "real" values by doing so. However, if the Reviewer and Editor deem it necessary, we could replot the data as relative to WT.

1. The number of evaluated samples is often {plus minus} n = 30, sometimes less, meaning less than what a silique contains of seeds. Did the authors evaluate the variability and reproductibility of their measurements, e.g, how many siliques per plant, how many plants, how many biological repeats? For example, in Figure S6, the number of measured ovules were as low as 16, which could be the reason why no significant difference in size were observed (low statitical strength). The variation in the Col WT is already visible. Is this variation significant?

On average we pooled seeds from 6-10 siliques coming from 2-3 different plants of the same genotype. We then took microscopic photos of 60 to 100 random seeds in those pools. Out of those, 30 random photos were used for the measurements. You are right this is an important point. We now added this information to the Methods section.

Moreover, we did calculate whether the sample size we were using provided enough statistical power. For the differences that we see, of around 50 um in perimeter, 26 samples would have been enough to achieve 80% statistical power, which most studies use as standard. In most of our experiments we used closer to 30 samples, which gives us 95% power.

Indeed, the left-most panel on Fig S6B is the exception. With that plot we mostly wanted to test if ovules produced by BR mutants were smaller than those of WT plants. That does not seem to be the case, even if the sample size is small. However, if deemed necessary, we can repeat those measurements with a higher sample number.

1. You indicate (line 149) that REF6 is not expressed in the gametophyte but GFP signal is observed in the cytoplasm for the central cell in Fig 1. The same goes for the expression pattern with the GUS line in Figure S2. (Line 290) One can not exclude expression in the endosperm or embryo with the presented pictures, or in the seed coat in older seeds.

We interpreted those diffuse signals in the cytoplasm of the gametophyte as background noise, as REF6 should be nuclearly localized. But we could be wrong. We therefore made changes to the text in lines 150-152 to reflect this.

And you are right that REF6 is expressed in the endosperm and embryo in later stages of development. We mention this in lines 157-159.

1. Make sure that you do not overstate your result conclusions, or add a reference to some of the statements. For example, line 185, for the choice of 3 DAP time point and the fact that seed coat development is based on cell expansion and interaction with the endosperm. Another example, in line 262, is where it is stated that the jmj mutants are compromised in ovule and pollen development. This was not assessed. You only checked the reduced seed set, not the fitness of the gametophytes. Or in line 337, where you indicate that KLUH is not expressed in all integument layers.

Thank you for pointing this out. For the claim that seed size at early time points is dictated only by the seed coat and endosperm, and not by the embryo, we added the appropriate reference. For the claim that jmj mutants are compromised in ovule development, this was based on our observations of Fig. S3C. We do see malformed or absent megagametophytes in jmj mutants. For pollen development, you are correct that we did not formally address this. We rephrased the sentence to reflect that. For the statement that KLU is not expressed in all integument cell layers, we added the reference.

1. Another example of this is in line 289 where you stated "a sporophytic function of JMJs at early stages of seed development, [..] and to a zygotic function at the later stages of seed development". I am not sure on what data do you base this conclusion as in all three categories (endosperm, embryo, seed coat) in Fig 2 and S5, genes are expressed in pre-globular stages. And again in line 475: "seed coat growth genes are expressed independentlyof fertilization". Do you have any evidence, a reference?

The evidence for a sporophytic JMJ function at early stages of seed development, and zygotic function at later stages, comes from our observations that jmj seed phenotypes are maternal in origin at early stages, but become zygotic later in development. But you are correct that we have to be careful with this interpretation. We now modified that sentence accordingly.

For the data of Fig 2E and Fig S5, we cannot rule out that some putative REF6 target genes are also expressed even when in the absence of REF6. The expression of those genes is also likely controlled by other factors. The point we wanted to make with those plots is that REF6 may have different target genes in different seed tissues, thus potentially regulating different developmental processes in a tissue-specific manner. We mention this in lines 288-290.

For your second point, we added the adequate reference.

1. (around lines 461) I understand that using a 35S promoter is not a good strategy as it would affect many other tissues. Did you consider using a tissue-specific approach as presented in Figure 4?

We suppose you mean the 35S::ELF6 construct. Yes, this makes sense and we did spend quite some time trying to come up with a good strategy. However, we failed to find a suitable promoter. The issue is that we would need a promoter that is active in all (or most) seed coat layers, but only after fertilization. There are promoters like those of TT genes which are active post-fertilization, but only in one cell layer, and thus likely not useful for our purpose. And there are other promoters, like those of STK or ANT, which are expressed in most integument cell layers, but are also expressed during integument development, and not just after fertilization. So they would have the same issue as the 35S promoter. Unfortunately, so far we have not identified a promoter that would be useful for this kind of experiment, which is why we went with a constitutive promoter, but which is specific to the sporophytic tissues.

1. You observed that the triple swn clf bri mutant is less dwarf than bri1 mutant and stated in line 483 that it is larger, has more leaves, grow tallerm and flower later and longer. Do you have any qunatitative data? If not, I would state that these observations are qualitative from growing plant aside.

You are correct that this was based on qualitative assessments, rather than on quantitative data (as it was not the point of the manuscript). We now indicate this in lines 489-490.

Minor: 1. The title should precise the studies species, here Arabidopsis thaliana. Also the title of one of the part could be rephrased. "in a zygotic manner" sounds strange.

We modified both title and subtitle, as suggested.

1. Scale bars are missing in many figures.

Fixed.

1. The font size in the graphs is small. The authors may use the empty space of the figures to increase the size of the graphs for clarity. Guidelines could be found here https://tpc.msubmit.net/html/TPC_Detailed_Figure_Guidelines.pdf, as example of good practices.

You are right. We revised all the figures and increased the font size, especially in the plot labels.

1. Be consitent in the mutant name, e.g., brz1-D is also presented as brz1-d.

Fixed.

1. Figure legend S1: I would not use the word "extremely" while you still have 30% seed set. Extremely would qualifiy for

We suppose you mean Fig. S3. We corrected the legend.

1. Figure S8 is missing the WT control for comparison.

Fixed.

1. Figure S12, stats are missing

Fixed.

1. I would recommend to add a line in the Supplemental tables with the name as this name disappears from the file name during upload. It would help the readers to navigate the data.

We now made it so the top line is static and is always visible.

1. Methods: Are all the lines listed used in the study? SR2200 is missing for the method, and please indicate the selection marker for each of the generated lines for open-access of the data if other researchers later use your lines.

You are right that some references had been left over from a previous document. We now updated the list of lines.

And indeed, we forgot to mention the use of SR2200. It is now added to the Methods section. We also added the information on the selection markers for the lines we generated.

1. You have a duplicate for reference Vukašinovíc et al.

Fixed.

1. Line 393, remove "s" in embryo and endosperm, in coat (line 674), in size (lines 684, 686

Fixed.

1. Line 410, write RPS5A in upper case.

Fixed throughout the manuscript.

1. LIne 676, the sentence "...H3K27me3 to be removed from the integuments." I would recomend to be more precise. For example "H3K27mme3 marks to be removed from genes to be expressed in the integuments" or something like that.

We rephrased this sentence to "We thus hypothesized that BR signaling would be required for JMJ function, allowing for H3K27me3 to be removed from genes necessary for seed coat formation."

Significance

The authors provide novel information on the step-wise regulation of seed coat development and its influence on seed size. This is a topic of general interest, beyond the plant model Arabidopsis, especially in the context of reduced seed set caused by (a)biotic stress. The results of this study are valuable to understand seed size regulation in differnet growth context or species. The group previously showed that the auxin phytohormone is necessary after fertilization to initiate seed coat differentiation by inhibiting PRC2. However, as seed coat develops mainly as cell elongation, the epigenetic marks are not diluted by cell division and needs to be actively removed. This study provides insight into this process by identifcation 2 JMJ proteins responsible for removing H3K27me3 marks in the seed coat after fertilization to initiation seed coat development and regulating seed size. BRI1, BES1 and BZR1 are involved in this process, indepently of brassinosteroid, to guide JMJ to their target loci. While the study bring some genetic evidence of this process, molecular insight is still missing. Notably the identification of the target genes and how BRI1 is regulated/activated upon fertilization. Or how auxin and BRI1 co-regulate the process. These questions appear how of scope of this current study.

Thank you for the assessment. Indeed, the identification of BRI1 downstream genes is out of scope of this work. As you point out earlier in the review, the manuscript is already quite long, and adding such data would make it even more so.

Reviewer #2

In this study, Pankaj et al. investigate the role of brassinosteroids and H3K27me3 in seed development, particularly in controlling seed size. They demonstrate that defects in these pathways affect seed size control and suggest that this control occurs in the maternal seed coat. This paper presents novel findings that merit publication and would be of interest to the plant community. However, the data interpretation and presentation could be improved. Additionally, I have a few comments that necessitate further analysis and revision.

Thank you for the careful and critical assessment of our work. Below we respond to each of the points you raised.

Major Comments

1. My main concern is the use of seed size measurement as a proxy for seed coat development. Mature seed size measurements can vary significantly with growth conditions, so it is crucial that the authors present at least three independent experiments (wild type and mutant grown in parallel) in a single box plot to ensure data reliability. Additionally, due to the high number of seeds analyzed, significant changes are often observed, though they are not always reproducible. The authors should standardize their seed measurements, using either seed area or seed perimeter.

You are right that we do see some variation in seed size between experiments. And, indeed, we suspect this is due to slightly different plant growth conditions, for example when different growth chambers are used. As you suggest, we now show data from four independent biological replicates of seed size comparisons of WT and BR mutants. This is in the new Fig. S6. As you can see, although we do see variations in absolute seed sizes, depending on the growth conditions, there is a consistent difference between WT and mutant seeds across experiments.

1. It would be beneficial to include data on cell division and cell elongation in the seed coat if the authors aim to extend the seed size phenotype to a seed coat phenotype.

This is indeed a good point. However, we already showed in a previous publication that seed coat growth is driven by cell elongation and not cell division (https://elifesciences.org/articles/20542). But you are right that this is important to point out. We mention it in lines 66-67.

1. It is challenging to be fully convinced by the seed coat specificity of the phenotype, as the authors observe variations in total seed set and phenotypic differences in self-crosses and when the mutants are used paternally. Some of the observed phenotypes do not support their hypothesis. In all mutant analyses, the authors should complement their phenotype analysis using seed coat-specific promoters and include heterozygote measurements, as done in some figures.

We assume you mean the effect of jmj mutations. For BR mutants, we do show data supporting a seed coat effect (Fig. 4). For PRC2 mutants, that has also been previously described (doi.org/10.7554/eLife.20542 and doi.org/10.1073/pnas.1117111108).

For the JMJ mutants, you are right that we cannot be 100% sure that their effect is purely sporophytic. We now modified the text accordingly to reflect this (see also the response to point 6 of Reviewer 1). We indeed show that REF6 and ELF6 are expressed in the sporophytic tissues of the ovule and that the double mutant has seed coat defects (smaller seed coats and defects in accumulation of proanthocyanidins). And although we can say that those defects are maternal in nature, we can not 100% conclude that they are simply due to the effect of those JMJs in the sporophyte. There may be gametophytic effects that we cannot rule out, even though we do not see either protein expressed in embryo sacs. Thank you for pointing this out.

Doing a tissue-specific rescue of these phenotypes would be very informative indeed, but also very hard. As we mention in the response to point 7 of Reviewer 1, we do not currently have suitable promoters for this. So we simply cannot run such experiments in a reasonable time frame.

Overall, we now tried to be more careful in our conclusions and avoid claiming that the effect of JMJs is purely sporophytic. We can make that argument for the BR machinery and for PRC2, but not necessarily for JMJs. You are correct in that assessment.

1. The authors need to include a fluorescent reporter for ELF6; tissue-specific expression cannot be conclusively determined with the GUS reporter.

We did obtain an ELF6::GFP line from Caroline Dean's lab (https://www.pnas.org/doi/full/10.1073/pnas.1605733113), but could not see much expression during endosperm or seed coat development. As you can see from that publication, even in embryos and in roots the expression of ELF6:GFP is very blurry. It seems ELF6 is simply expressed at very low levels. We therefore used the GUS reporter, as a more sensitive means to visualize where ELF6 is expressed. You are right that the results are not as precise as that obtained with a fluorescent reporter. However, note that we simply claim that ELF6 is expressed in the integuments and seed coat (line 155). This can be clearly seen in Fig. 1B. The blue product of the β-glucuronidase reaction should be immotile and not travel between tissues (also note that there are no plasmodesmata between endosperm and seed coat). Therefore, we believe that GUS is a suitable reporter to test the seed coat expression of ELF6.

1. Text editing: In some places, the text is unclear and could benefit from simplification. The authors should replace the term "seed coat formation," as developmentally, integuments are already present before fertilization. The authors are not studying the formation of the seed coat but rather its growth. They should also clarify the term "PRC2 removal." It is unclear whether the authors mean PRC2 lack of expression in the integument, PRC2 eviction from chromatin, or removal of H3K27me3.

Thank you for noting that. It is very important to us that the text is clear to the reader. If you could indicate where the text is unclear, we are happy to simplify it.

Regarding the wording, we refer to "seed coat formation" because the seed coat only indeed forms after fertilization. Before fertilization, the sporophytic tissues that cover the megagametophyte are called integuments, and not seed coat. Therefore, we see the seed coat as "forming" from the integuments (i.e., the integuments become seed coat via growth and differentiation).

With PRC2 removal we indeed mean reduction of expression of PRC2 components. We now make this clear in lines 54-55.

Minor Comments

1. L151: Is REF6 expressed in zygotic tissues?

Reviewer 1 also raised this question. We now added this information to lines 148-150.

1. Confirm mutant complementation with the different reporter lines.

All mutant lines that we used have been previously described to be either loss-of-function or hypomorphic mutants. We did not use any mutant line that has not been previously described. We added all references to the corresponding publications in the Methods.

1. Confirm by qPCR that JMJ13 is indeed not expressed in seeds.

We tested JMJ13 as a possible factor involved in H3K27me3 removal in the seed coat due to it being described, together with ELF6 and REF6, as one of the three main H3K27 demethylases. But there are, in fact, transcriptomic datasets showing that the expression of JMJ13 is indeed very low or absent in seeds: see RNAseq data in Table S3 in doi.org/10.3389/fpls.2022.998664. Moreover we checked CPMs on published seed scRNAseq datasets (doi.org/10.1038/s41477-021-00922-0) and JMJ13 (AT5G46910) has zero transcript counts in these datasets.

Because of these two independent instances showing that the expression of JMJ13 is extremely low in seeds (or even totally absent), together with the analysis that we did of the fluorescent reporter line, we believe this is sufficient evidence that this JMJ is specific to the pollen during reproductive development. Note that the reporter that we used is strongly expressed in pollen grains, as had been previously described (doi.org/10.1038/s41556-020-0515-y).

Even so, if the Reviewer and the Editor deem it necessary that we check JMJ13 expression by qPCR, we can of course do so.

1. Fig1a and Fig1b: Align the panels in the figure.

Done.

1. L183-189: This section is unclear.

I am sorry that the section is not clear. If you direct us to the points that need to be cleared, we are happy to make changes.

1. There may be a PDF artifact, but most figures have unattractive misaligned boxes.

We went through every figure and made slight modifications to avoid such artifacts. We hope they now appear more clear in the new version.

1. Change the color in Fig 2a.

Fixed.

1. The introduction is heavily self-cited. The authors should try to include a broader range of literature.

It is not clear to us why the Reviewer sees it like that. We only refer to three of our publications in the Introduction. One review manuscript and two research manuscripts. We cite almost 40 manuscripts in the introduction. Therefore, citing three of our works does not seem out of line to us, especially since those manuscripts laid the foundation for this work.

1. Fig3F: Typo in "microM."

Fixed.

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Referee #2

Evidence, reproducibility and clarity

Review of "BRI1-mediated removal of seed coat H3K27me3 marks is a brassinosteroid-independent process" In this study, Pankaj et al. investigate the role of brassinosteroids and H3K27me3 in seed development, particularly in controlling seed size. They demonstrate that defects in these pathways affect seed size control and suggest that this control occurs in the maternal seed coat. This paper presents novel findings that merit publication and would be of interest to the plant community. However, the data interpretation and presentation could be improved. Additionally, I have a few comments that necessitate further analysis and revision.

Major Comments

• My main concern is the use of seed size measurement as a proxy for seed coat development. Mature seed size measurements can vary significantly with growth conditions, so it is crucial that the authors present at least three independent experiments (wild type and mutant grown in parallel) in a single box plot to ensure data reliability. Additionally, due to the high number of seeds analyzed, significant changes are often observed, though they are not always reproducible. The authors should standardize their seed measurements, using either seed area or seed perimeter.

• It would be beneficial to include data on cell division and cell elongation in the seed coat if the authors aim to extend the seed size phenotype to a seed coat phenotype.

• It is challenging to be fully convinced by the seed coat specificity of the phenotype, as the authors observe variations in total seed set and phenotypic differences in self-crosses and when the mutants are used paternally. Some of the observed phenotypes do not support their hypothesis. In all mutant analyses, the authors should complement their phenotype analysis using seed coat-specific promoters and include heterozygote measurements, as done in some figures.

• The authors need to include a fluorescent reporter for ELF6; tissue-specific expression cannot be conclusively determined with the GUS reporter.

• Text editing: In some places, the text is unclear and could benefit from simplification. The authors should replace the term "seed coat formation," as developmentally, integuments are already present before fertilization. The authors are not studying the formation of the seed coat but rather its growth. They should also clarify the term "PRC2 removal." It is unclear whether the authors mean PRC2 lack of expression in the integument, PRC2 eviction from chromatin, or removal of H3K27me3.

Minor Comments:

• L151: Is REF6 expressed in zygotic tissues?

• Confirm mutant complementation with the different reporter lines.

• Confirm by qPCR that JMJ13 is indeed not expressed in seeds.

• Fig1a and Fig1b: Align the panels in the figure.

• L183-189: This section is unclear.

• There may be a PDF artifact, but most figures have unattractive misaligned boxes.

• Change the color in Fig 2a.

• The introduction is heavily self-cited. The authors should try to include a broader range of literature.

• Fig3F: Typo in "microM."

Cross-commenting:

I think our reviews highlight the same issues. For me, the first point is definitely the most critical.

Significance

This paper presents novel findings that merit publication and would be of interest to the plant community. However, the data interpretation and presentation could be improved. Additionally, I have a few comments that necessitate further analysis and revision.

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Referee #1

Evidence, reproducibility and clarity

The manuscript presents data demonstrating the function of BRI1 in removing the H3K27me3 epigenetic marks in genes involved in seed coat development in Arabidopsis. The results support that BRI1 may function here independently of brassinosteroid. The work combines genetics with a large panel of mutant lines, phenotyping by quantitative microscopy and chemical treatment, H3K27me3 profiling by CUT&TAG, and data mining for published gene profiling. The introduction is adequately informative, complete and explaining the state-of-the-art to the readers. The result part may be a bit lengthy (especially the first part) and some parts may be a bit repetitive.

Major comments:

1. Seed size is dependent of multiple factors. And few are explained here, notably the number of seeds per silique, the number of ovule per silique, the position of the silique of the branch (related to the age of the meristem), the total number of produced siliques (fertilised flowers) by the inflorescence meristem and the plant. And maybe if produced by the main and lateral branches. Were the authors consistent in the evaluation of analyzed siliques coming from the same type of branches, same age of the meristem, etc? Especially as some of the analysed mutants are dwarf, which is a sign of different plant fitness compared to WT.

2. The seed perimeter measurements in BR mutant seeds (Figure S6) are variable. Are you sue the ovule size does not have any influence? What about presenting the relative size as earlier in the text?

3. The number of evaluated samples is often {plus minus} n = 30, sometimes less, meaning less than what a silique contains of seeds. Did the authors evaluate the variability and reproductibility of their measurements, e.g, how many siliques per plant, how many plants, how many biological repeats? For example, in Figure S6, the number of measured ovules were as low as 16, which could be the reason why no significant difference in size were observed (low statitical strength). The variation in the Col WT is already visible. Is this variation significant?

4. You indicate (line 149) that REF6 is not expressed in the gametophyte but GFP signal is observed in the cytoplasm for the central cell in Fig 1. The same goes for the expression pattern with the GUS line in Figure S2. (Line 290) One can not exclude expression in the endosperm or embryo with the presented pictures, or in the seed coat in older seeds.

5. Make sure that you do not overstate your result conclusions, or add a reference to some of the statements. For example, line 185, for the choice of 3 DAP time point and the fact that seed coat development is based on cell expansion and interaction with the endosperm. Another example, in line 262, is where it is stated that the jmj mutants are compromised in ovule and pollen development. This was not assessed. You only checked the reduced seed set, not the fitness of the gametophytes. Or in line 337, where you indicate that KLUH is not expressed in all integument layers.

6. Another example of this is in line 289 where you stated "a sporophytic function of JMJs at early stages of seed development, [..] and to a zygotic function at the later stages of seed development". I am not sure on what data do you base this conclusion as in all three categories (endosperm, embryo, seed coat) in Fig 2 and S5, genes are expressed in pre-globular stages. And again in line 475: "seed coat growth genes are expressed independentlyof fertilization". Do you have any evidence, a reference?

7. (around lines 461) I understand that using a 35S promoter is not a good strategy as it would affect many other tissues. Did you consider using a tissue-specific approach as presented in Figure 4?

8. You observed that the triple swn clf bri mutant is less dwarf than bri1 mutant and stated in line 483 that it is larger, has more leaves, grow tallerm and flower later and longer. Do you have any qunatitative data? If not, I would state that these observations are qualitative from growing plant aside.

Minor comments:

1. The title should precise the studies species, here Arabidopsis thaliana. Also the title of one of the part could be rephrased. "in a zygotic manner" sounds strange.

2. Scale bars are missing in many figures.

3. The font size in the graphs is small. The authors may use the empty space of the figures to increase the size of the graphs for clarity. Guidelines could be found here https://tpc.msubmit.net/html/TPC_Detailed_Figure_Guidelines.pdf, as example of good practices.

4. Be consitent in the mutant name, e.g., brz1-D is also presented as brz1-d.

5. Figure legend S1: I would not use the word "extremely" while you still have 30% seed set. Extremely would qualifiy for <5%, I guess.

6. Figure S8 is missing the WT control for comparison.

7. Figure S12, stats are missing

8. I would recommend to add a line in the Supplemental tables with the name as this name disappears from the file name during upload. It would help the readers to navigate the data.

9. Methods: Are all the lines listed used in the study? SR2200 is missing for the method, and please indicate the selection marker for each of the generated lines for open-access of the data if other researchers later use your lines.

10. You have a duplicate for reference Vukašinovíc et al.

11. Line 393, remove "s" in embryo and endosperm, in coat (line 674), in size (lines 684, 686

12. Line 410, write RPS5A in upper case.

13. LIne 676, the sentence "...H3K27me3 to be removed from the integuments." I would recomend to be more precise. For example "H3K27mme3 marks to be removed from genes to be expressed in the integuments" or something like that.

Cross-commenting:

I have been comparing our peer-review reports of the manuscript and found much similarity on our assessment:

1. The seed size assemment and how this relates to seed coat development

2. The GUS expression of ELF6 is not sufficient for the provided conclusion of the ELF6 expression

3. The same would be for REP6

4. Use of tissue-specific (seed coat specific) promoters to confirm the conclusion.

Significance

The authors provide novel information on the step-wise regulation of seed coat development and its influence on seed size. This is a topic of general interest, beyond the plant model Arabidopsis, especially in the context of reduced seed set caused by (a)biotic stress. The results of this study are valuable to understand seed size regulation in differnet growth context or species. The group previously showed that the auxin phytohormone is necessary after fertilization to initiate seed coat differentiation by inhibiting PRC2. However, as seed coat develops mainly as cell elongation, the epigenetic marks are not diluted by cell division and needs to be actively removed. This study provides insight into this process by identifcation 2 JMJ proteins responsible for removing H3K27me3 marks in the seed coat after fertilization to initiation seed coat development and regulating seed size. BRI1, BES1 and BZR1 are involved in this process, indepently of brassinosteroid, to guide JMJ to their target loci. While the study bring some genetic evidence of this process, molecular insight is still missing. Notably the identification of the target genes and how BRI1 is regulated/activated upon fertilization. Or how auxin and BRI1 co-regulate the process. These questions appear how of scope of this current study.

My filed of expertise: hormones, plant reproduction, Arabidopis, oilseed rape, microscopy, transformation

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Reply to the reviewers

Thank you very much for your editorial handling of our manuscript entitled 'A conserved fungal Knr4/Smi1 protein is vital for maintaining cell wall integrity and host plant pathogenesis'. We have taken on board the reviewers' comments and thank them for their diligence and time in improving our manuscript.

Please find our responses to each of the comments below.

Reviewer(s)' comments

Reviewer #1

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Major comments:

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__1.1. As a more critical comment, I find the presentation of the figures somewhat confusing, especially with the mixing of main figures, supplements to the main figures, and actual supplemental data. On top of that, the figures are not called up in the right order (e.g. Figure 4 follows 2D, while 3 comes after 4; Figure 6 comes before 5...), and some are never called up (I think) (e.g. Figure 1B, Figure 2B). __

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__Response: __The figure order has been revised according to the reviewer's suggestion, while still following eLife's formatting guidelines for naming supplementals. Thank you.

1.2. I agree that there should be more CWI-related genes in the wheat module linked to the FgKnr4 fungal module, or, vice-versa, CW-manipulating genes in the fungal module. It would at least be good if the authors could comment further on if they find such genes, and if not, how this fits their model.

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Response: Thank you for your insightful suggestion regarding the inclusion of more CWI-related genes in the wheat module linked to the FgKnr4 fungal module F16, or vice versa. We did observe a co-regulated response between the wheat module W05 which is correlated to the FgKnr4 module F16. Namely, we observed an enrichment of oxidative stress genes including respiratory burst oxidases and two catalases (lines 304 - 313) in the correlated wheat module (W05). Early expression of these oxidative stress inducing genes likely induces the CWI pathway in the fungus, which is regulated by FgKnr4. Knr4 functions as both a regulatory protein in the CWI pathway and as a scaffolding protein across multiple pathways in S. cerevisiae (Martin-Yken et al., 2016, https://onlinelibrary.wiley.com/doi/10.1111/cmi.12618 ). Scaffolding protein-encoding genes are typically expressed earlier than the genes they regulate to enable pre-assembly with their interacting partners, ensuring that signaling pathways are ready to activate when needed. In this context, the CWI integrity MAPKs Bck1 and Mkk1 are part of module F05, which includes two chitin synthases and a glucan synthase. This module is highly expressed during the late symptomless phase. The MAPK Mgv1, found in module F13, is expressed consistently throughout the infection process, which aligns with the expectation that MAPKs are mainly post-transcriptionally regulated. Thank you for bringing our attention to this, this is now included in the discussion (lines 427 - 443) along with eigengene expression plots of all modules added to the supplementary (Figure 3 - figure supplement 1).

To explore potential shared functions of FgKnr4 with other genes in its module, we re-analyzed the high module membership genes within module F16, which includes FgKnr4, using Knetminer (Hassani-Pak et al., 2021; https://onlinelibrary.wiley.com/doi/10.1111/pbi.13583 ). This analysis revealed that 8 out of 15 of these genes are associated with cell division and ATP binding. Four of the candidate genes are also part of a predicted protein-protein interaction subnetwork of genes within module F16, which relate to cell cycle and ATP binding. In S. cerevisiae, the absence of Knr4 results in cell division dysfunction (Martin-Yken et al., 2016, https://onlinelibrary.wiley.com/doi/10.1111/cmi.12618 ). Accordingly, we tested sensitivity of ΔFgknr4 to microtubule inhibitor benomyl (a compound commonly used to identify mutants with cell division defects; Hoyt et al., 1991 https://www.cell.com/cell/pdf/0092-8674(81)90014-3.pdf). We found that the ΔFgknr4 mutant was more susceptible to benomyl, both when grown on solid agar and in liquid culture. This data has now been added Figure 7, and referred to in lines 338-348.

__Specific issues: __

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1.3. In the case of figure 5, I generally find it hard to follow. In the text (line 262/263), the authors state that 5C shows "eye-shaped lesions" caused by ΔFgknr4 and ΔFgtri5, but I can't see neither (5C appears to be a ΔFgknr4 complementation experiment). The figure legend also states nothing in this regard.

__Response: __Thank you for your suggestion. We have amended the manuscript to include an additional panel that shows the dissected spikelet without its outer glumes, making the eye shaped diseased regions more visible in Figure 5.

__1.4. Figure 5D supposedly shows 'visibly reduced fungal burden' in ΔFgknr4-infected plants, but I can't really see the fungal burden in this picture, but the infected section looks a lot thinner and more damaged than the control stem, so in a way more diseased. __

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Response: __Thank you for your insight. We have revised our conclusions based on this image to state that while ΔFgknr4 can colonise host tissue, it does so less effectively compared to the wild-type strain as we are unable to quantitatively evaluate fungal burden using image-colour thresholding due to the overlapping colours of the fungal cells and wheat tissues. Decreased host colonisation is evidenced by (i) reduced fungal hyphae proliferation, particularly in the thicker adaxial cell layer, (ii) collapsed air spaces in wheat cells, and (iii) increased polymer deposition at the wheat cell walls, indicating an enhanced defence response. __Figure 5 has been amended to include these observations in the corresponding figure legend and the resin images now include insets with detailed annotation.

__1.5. The authors then go on to state (lines 272-273) that they analyzed the amounts of DON mycotoxin in infected tissues, but don't seem to show any data for this experiment. __

Response: __We have amended this to now include the data in __Figure 5 - figure supplement 2B, thank you.

Reviewer #2

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__Major issues: __

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2.1 If Knf4 is involved in the CWI pathway, what other genes involved in the CWI pathway are in this fungal module? one of the reasons for developing modules or sub-networks is to assign common function and identify new genes contributing to the function. since FgKnr4 is noted to play a role in the CWI pathways, then genes in that module should have similar functions. If WGCN does not do that, what is the purpose of this exercise?

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Response: __Thank you for raising this point regarding the role of FgKnr4 in the CWI pathway and the expectations for genes of shared function within the FgKnr4 module F16. We did observe that the module containing FgKnr4 (F16) was also correlated to a wheat module (W05) which was significantly enriched for oxidative stress genes. This pathogen-host correlated pattern led us to study module F16, which otherwise lacks significant gene ontology term enrichment, unique gene set enrichments, and contains few characterised genes. This is now highlighted in __lines 233-246. This underscores the strength of the WGCNA. By using high-resolution RNA-seq data to map modules to specific infection stages, we identified an important gene that would have otherwise been overlooked. This approach contrasts with other network analyses that often rely on the guilt-by-association principle to identify novel virulence-related genes within modules containing known virulence factors, potentially overlooking significant pathways outside the scope of prior studies. Therefore, our analysis has already benefited from several advantages of WGCNA, including the identification of key genes with high module membership that may be critical for biological processes, as well as generating a high-resolution, stage-specific co-expression map of the F. graminearum infection process in wheat. This point is now emphasised in lines 233-252. As discussed in response to reviewer 1, Knr4 functions as both a regulatory protein in the CWI pathway and as a scaffolding protein across multiple pathways in S. cerevisiae (Martin-Yken et al., 2016, https://onlinelibrary.wiley.com/doi/10.1111/cmi.12618 ) which would explain its clustering separate from the CWI pathway genes. The high module membership genes within module F16 containing FgKnr4 were re-analysed using Knetminer (Hassani-Pak et al., 2021; https://onlinelibrary.wiley.com/doi/10.1111/pbi.13583 ), which found that 8/15 of these genes were related to cell division and ATP binding. Four of the candidate genes are also part of a predicted protein-protein interaction subnetwork of genes within module F16, which relate to cell cycle and ATP binding. In S. cerevisiae, the absence Knr4 leads to dysfunction in cell division. Accordingly, we tested sensitivity of ΔFgknr4 to the microtubule inhibitor benomyl (a compound commonly used to identify mutants with cell division defects; Hoyt et al., 1991 https://www.cell.com/cell/pdf/0092-8674(81)90014-3.pdf). We found that the ΔFgknr4 mutant was more susceptible to benomyl, both when grown on solid agar and in liquid culture. This data has now been added as Figure 7 and referred to in lines 338-348.

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2.2. Due to development defects in the Fgknr1 mutant, I would not equate to as virulence factor or an effector gene.

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__Response: __We are in complete agreement with the reviewer and are not suggesting that FgKnr4 is an effector or virulence factor, we have been careful with our wording to indicate that FgKnr4 is simply necessary for full virulence and its disruption results in reduced virulence and have outlined how we believe FgKnr4 participates in a fungal signaling pathway required for infection of wheat.

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2.3. What new information is provided with WGCN modules compared with other GCN network in Fusarium (examples of GCN in Fusarium is below) ____https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069591/ https://doi.org/10.1186/s12864-020-6596-y____ DOI: 10.1371/journal.pone.0013021. The GCN networks from Fusarium have already identified modules necessary/involved in pathogenesis.

Response: __The 2016 New Phytologist gene regulatory network (GRN) by Guo et al. is large and comprehensive. However, only three of the eleven datasets are in planta, with just one dataset focusing on F. graminearum infection on wheat spikes. The other two in planta datasets involve barley infection and Fusarium crown rot. By combining numerous in planta and in vitro datasets, the previous GRNs lack the fine resolution needed to identify genetic relationships under specific conditions, such as the various stages of symptomatic and symptomless F. graminearum infection of mature flowering wheat plants. This limitation is highlighted in the 2016 paper itself. This network is expanded in the Guo et al., 2020 BMC genomics paper where it includes one additional in planta and nine in vitro datasets. However, the in planta dataset involves juvenile wheat coleoptile infection, which serves as an artificial model for wheat infection but is not on mature flowering wheat plants reminiscent of Fusarium Head Blight of cereals in the field. This model differs significantly in the mode of action of F. graminearum, notably DON mycotoxin is not essential for virulence in this context (Armer et al. 2024, https://pubmed.ncbi.nlm.nih.gov/38877764/ ). The Guo et al., 2020 paper still faces the same issues in terms of resolution and the inability to draw conclusions specific to the different stages of F. graminearum infection. Additionally, these GRNs use Affymetrix data, which miss over 400 genes (~ 3 % of the genome) from newer gene models. In contrast, our study addresses these limitations by analysing a meticulously sampled, stage- and tissue-specific in planta RNA-seq dataset using the latest reference annotation. Our approach provides higher resolution and insights into host transcriptomic responses during the infection process. The importance of our study in the context of these GRNs is now addressed in the introduction (__lines 85-92).

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2.4. Ideally, the WGCN should have been used identify plant targets of Fusarium pathogenicity genes. This would have provided credibility and usefulness of the WGCN. Many bioinformatic tools are available to identify virulence factors and the utility of WGCN in this regard is not viable. However, if the authors had overlapped the known virulence factors in a fungal module to a particular wheat module, the impact of the WGCN would be great. The module W12 has genes from numerous traits represented and WGCN could have been used to show novel links between Fg and wheat. For example, does tri5 mutant affect genes in other traits?

__Response: __Thank you for your suggestions. In this study we have shown the association between the main fungal virulence factor of F. graminearum, DON mycotoxin, with wheat detoxification responses. Through this we have identified a set of tri5 responsive genes and validated this correlation in two genes belonging to the phenylalanine pathway and one transmembrane detoxification gene. Although we could validate more genes in this tri5 responsive wheat module, our paper aimed to investigate previously unstudied aspects of the F. graminearum infection process and how the fungus responded to changing conditions within the host environment. We accomplished this by characterising a gene within a fungal module that had limited annotation enrichment and few characterised genes. Tri5 on the other hand is the most extensively studied gene in F. graminearum and while the network we generated may offer new insights into tri5 responsive genes, this is beyond the scope of our current study. In addition to the tri5 co-regulated response, we have also demonstrated the coordinated response between the fungal module F16, which contains FgKnr4 that is necessary for tolerance to oxidative stress, and the wheat module W05, which is enriched for oxidative stress genes.

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While our co-expression network approach can be used to explore and validate other early downstream signaling and defense components in wheat cells, several challenges must be considered: (a) the poor quality of wheat gene calls, (b) genetic redundancy due to both homoeologous genes and large gene families, and (c) the presence of DON, which can inhibit translation and prevent many transcriptional changes from being realised within the host responses. Additionally, most plant host receptors are not transcriptionally upregulated in response to pathogen infection (most R gene studies for the NBS-LRR and exLRR-kinase classes), making their discovery through a transcriptomics approach unlikely. These points will be included in our discussion (lines 408-413), thank you.

Specific issues

• *

2.5. Since tri5 mutant was used a proof of concept to link wheat/Fg modules, it would have been useful to show that TRI14, which is not involved DON biosynthesis, but involved in virulence ( https://doi.org/10.3390/applmicrobiol4020058____) impact the wheat module genes.

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Response: __Our goal was to show that wheat genes respond to the whole TRI cluster, not just individual TRI genes. Therefore, the tri5 mutant serves as a solid proof-of-concept, because TRI5 is essential for DON biosynthesis, the primary function of the TRI gene cluster, thereby representing the function of the cluster as a whole. This is now clarified in __lines 217-219. Additionally, the uncertainties surrounding other TRI mutants would complicate the question we were addressing-namely, whether a wheat module enriched in detoxification genes is responding to DON mycotoxin, as implied by shared co-expression patterns with the TRI cluster. For instance, the referenced TRI14 paper indicates that DON is produced in the same amount in vitro in a single media. Although the difference is not significant, the average DON produced is lower for the two Δtri14 transformants tested. Therefore, we cannot definitively rule out that TRI14 is involved in DON biosynthesis and extrapolate this to DON production in planta. Despite this, the suggestion is interesting, and would make a nice experiment but we believe it does not contribute to the overall aim of this study.

2.6. Moreover, prior RNAseq studies with tri5 mutant strain on wheat would have revealed the expression of PAL and other phenylpropanoid pathway genes?

__Response: __We agree that this would be an interesting comparison to make but unfortunately no dataset comparing in planta expression of the tri5 mutant within wheat spikes exists.

2.7. Table S1 lists 15 candidate genes of the F16 module; however, supplementary File 1 indicates 74 genes in the same module. The basis of exclusion should be explained. The author has indicated genes with high MM was used as representative of the module. The 59 remaining genes of this module did not meet this criteria? Give examples.

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Response: __The 15 genes with the highest module membership were selected as initial candidates for further shortlisting from the 74 genes within module F16. In WGCNA, genes with high module membership (MM) (i.e. intramodular connectivity) are predicted to be central to the biological functions of the module (Langfelder and Horvath, 2008; https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-559 ) and continues to be a metric to identify biologically significant genes within WGCN analyses (https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-024-05366-0 Tominello-Ramirez et al., 2024; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9151341/ ;Zheng et al., 2022; https://www.nature.com/articles/s41598-020-80945-3 Panahi and Hejazi et al 2021). Following methods by Mateus et al. (2019) (https://academic.oup.com/ismej/article/13/5/1226/7475138 ) key genes were defined as those exhibiting elevated MM within the module, which were also strongly correlated (R > |0.70|) with modules of the partner organism (wheat). We have clarified this point in the manuscript. Thank you for the suggestion. (__Lines 253-263).

2.____8. A list from every module that pass this criteria will be useful resource for functional characterization studies.

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__Response: __A supplementary spreadsheet has been generated which includes full lists of the top 15 genes with the highest module membership within the five fungal modules correlated to wheat modules and a summary of shared attributes among them. Thank you for this suggestion.

2.9. Figure 3 indicates TRI genes in the module F12; your PHI base in Supp File S2 lists only TRI14. Why other TRI genes such as TRI5 not present in this File?

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Response: For clarity, the TRI genes in module F12 are TRI3, TRI4, TRI11, TRI12, and TRI14 which was stated in Table 1. TRI5 clusters with its neighboring regulatory gene TRI6 in module F11, which exhibits a similar but reduced expression pattern compared to module F12. To improve clarity on this the TRI genes in module F12 are also listed in-text in line 168 and added to Figure 4. The enrichment and correlated relationship of W12 to a cluster's expression still imply a correlated response of the wheat gene to the TRI cluster's biosynthetic product (DON), which is absent in the Δtri5 mutant.

TRI14 and TRI12 are listed in PHI-base. TRI12 was mistakenly excluded due to an unmapped Uniprot ID, which were added separately in the spreadsheet. We will recheck all unmapped ID lists to ensure all PHI-base entries are included in the final output. Thank you for pointing out this error.

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2.10. What is purpose of listing the same gene multiple times? Example, osp24 (a single gene in Fg) is listed 13 times in F01 module.

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__Response: __This is a consequence of each entry having a separate PHI ID, which represents different interactions including inoculations on different cultivar. Cultivar and various experimental details were omitted from the spreadsheet to reduce information density, however the multiple PHI base ID's will be kept separate to make the data more user friendly when working with the PHI-base database. An explanation for this is now provided in the file's explanatory worksheet, thank you.

Reviewer #3:

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3.1. Why only use of high confidence transcripts maize to map the reads and not the full genome like Fusarium graminearum? I have never analyzed plant transcriptome.

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__Response: __ In the wheat genome, only high-confidence gene calls are used by the global community (Choulet et al., 2023; https://link.springer.com/chapter/10.1007/978-3-031-38294-9_4 ) until a suitable and stable wheat pan-genome becomes available.

3.2. The regular output of DESeq are TPMs, how did the authors obtain the FPKM used in the analysis?

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Response: FPKM was calculated using the GenomicFeatures package and included on GitHub to enhance accessibility for other users. However, the input for WGCNA and this study as a whole was normalised counts rather than FPKM. The FPKM analysis was done to improve interoperability of the data for future users and made available on Github. To complement this, the information regarding FPKM calculation is now included in the methods section of the revised manuscript (line 491).

3.3. Do the authors have a Southern blot to prove the location of the insertion and number of insertions in Zymoseptoria tritici mutant and complemented strains?

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__Response: __No, but the phenotype is attributed to the presence or absence of ZtKnr4, as the mutant was successfully complemented in multiple phenotypic aspects. This satisfies Koch's postulates which is the gold standard for reverse genetics experimentation (Falkow 1988; https://www.jstor.org/stable/4454582 ).

__3.4. Boxplots and bar graphs should have the same format. In Figures 5 B and F and supplementary figure 6.3 the authors showed the distribution of samples but it is lacking in figure 3 B and all bar graphs. __

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__Response: __Graphs have been modified to display the distribution of all samples, thank you.

3.5. Line 247 FGRAMPH1_0T23707 should be FGRAMPH1_01T23707

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__Response: __Thank you this has now been amended.

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Referee #3

Evidence, reproducibility and clarity

The authors of the manuscript entitled "A conserved fungal Knr4/Smi1 protein is vital for maintaining cell wall integrity and host plant pathogenesis" used a weighted gene co-expression network to identify Fusarium graminearum genes highly expressed during early symptomless infection of wheat. Based on its sequence and previous studies, authors selected FgKnr4 from the early symptomless Fusarium modules. The characterization of knockout strains revealed a role in morphogenesis, growth, cell wall stress tolerance, and virulence in F. graminearum and the phylogenetically distant fungus Zymoseptoria tritici.

The methods are properly described and statistical analysis are reasonable so reproducibility is possible. The RNA-seq dataset is already published and the authors provided a repository with the code used to create the co-expression network. However, I have the following questions:

• Why only use of high confidence transcripts maize to map the reads and not the full genome like Fusarium graminearum? I have never analyzed plant transcriptome.
• The regular output of DESeq are TPMs, how did the authors obtain the FPKM used in the analysis?
• Do the authors have a southern blot to prove the location of the insertion and number of insertions in Zymoseptoria tritici mutant and complemented strains?
• Boxplots and bar graphs should have the same format. In Figures 5 B and F and supplementary figure 6.3 the authors showed the distribution of samples but it is lacking in figure 3 B and all bar graphs.
• Line 247 FGRAMPH1_0T23707 should be FGRAMPH1_01T23707

Referees cross-commenting

I agree with reviewer 1, the order in which the figures are called in the text is confusing. Regardless of figures 5C-D I am no expert in the field therefore I can only say they look like they have not been edited.

I agree with reviewer 1, data of DON mycotoxin production in infected issues is need it to support statement in line 272-273.

I agree with Reviewer 2, the criteria to exclude genes from the final selection list should be explained.

Significance

The study showed, once again, that a weighted gene co-expression network is a great method to identify new genes of interest regardless of the organism or condition even if not very popular in the fungal pathogen field yet. The study proved that functions identified in a WGCN module from a pathogen have their opposite in the host module. The authors go beyond the theory and demonstrate the effect of the highest expressed gene during the early symptomless stage of infection in maize and wheat fungal pathogens.

Fungal pathogen, RNA-seq, metabolic models, metabolism, comparative genomics

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Referee #2

Evidence, reproducibility and clarity

Summary: The authors in this manuscript use "dual weighting" to identify clusters or modules of genes from the fungus F. graminearum (Fg) with coordinated expression patterns with genes in wheat modules - potentially uncover key regulators or pathways linking Fg genes with plant traits, including plant pathogenesis. As proof of concept, the authors use one of the fungal genes FgKnr4 identified in a fungal module that has strong link with the wheat module. They were able to show that this gene is likely involved in CWI pathway and affects virulence properties of the fungus

Major comments:

Does the WGCN provide useful framework to link fungal genes affecting plant traits? If Knf4 is involved in the CWI pathway, what other genes involved in the CWI pathway are in this fungal module? This is not forthcoming. Due to development defects in the Fgknr1 mutant, I would not equate to as virulence factor or an effector gene.

Since tri5 mutant was used a proof of concept to link wheat/Fg modules, it would have been useful to show that TRI14, which is not involved DON biosynthesis, but involved in virulence ( https://doi.org/10.3390/applmicrobiol4020058) impact the wheat module genes. Moreover, prior RNAseq studies with tri5 mutant strain on wheat would have revealed the expression of PAL and other phenylpropanoid pathway genes?

Table S1 lists 15 candidate genes of the F16 module; however, supplementary File 1 indicates 74 genes in the same module.

The basis of exclusion should be explained. The author has indicated genes with high MM was used as representative of the module. The 59 remaining genes of this module did not meet this criteria? Give examples. Did similar exclusion criteria used for other modules and if so, how many genes in each module pass the criteria? For example, Did TRI5 in module F12 pass this criteria. A list from every module that pass this criteria will be useful resource for functional characterization studies.

Minor comments:

Figure 3 indicates TRI genes in the module F12; your PHI base in Supp File S2 lists only TRI14. Why other TRI genes such as TRI5 not present in this File? What is purpose of listing the same gene multiple times? Example, osp24 (a single gene in Fg) is listed 13 times in F01 module.

Referees cross-commenting

agree with both reviewers regarding clarification of Figures.

one of the reasons for developing modules or sub-networks is to assign common function and identify new genes contributing to the function. since FgKnr4 is noted to play a role in the CWI pathways, then genes in that module should have similar functions. If WGCN does not do that, what is the purpose of this exercise?

Significance

What new information is provided with WGCN modules compared with other GCN network in Fusarium (examples of GCN in Fusarium is below)

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069591/ https://doi.org/10.1186/s12864-020-6596-y DOI: 10.1371/journal.pone.0013021

The GCN networks from Fusarium have already identified modules necessary/involved in pathogenesis. Ideally, the WGCN should have been used identify plant targets of Fusarium pathogenicity genes. This would have provided credibility and usefulness of the WGCN.

Many bioinformatic tools are available to Identify virulence factors and the utility of WGCN in this regard is not viable. However, if the authors had overlapped the known virulence factors in a fungal module to a particular wheat module, the impact of the WGCN would be great. The module W12 has genes from numerous traits represented and WGCN could have been used to show novel links between Fg and wheat. For example, does tri5 mutant affect genes in other traits?

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Referee #1

Evidence, reproducibility and clarity

Summary:

A public mRNA-seq dataset from Dilks et al. (2019) for wheat spikelets infected by Fusarium graminearum was used to generate a dual weighted gene co-expression network (WGCN). Since colonization of the spike by F. graminearum progresses from spikelet to spikelet, thereby forming an infection-gradient from early to late stages, quasi spatio-temporal resolution for the transcriptomic dataset can be achieved by cutting the spike into equal pieces along this gradient (in this case cuts were done at rachis internodes 1-2, 3-4, 5-6, and 7-8. The authors created co-expression networks for both, fungal and plant genes, and cross-correlated them. They identify several modules specific for each infection stage. For further analysis, the authors focus on two module pairs. (1) the wheat module 12 (W12), which correlates to Fusarium module 12 (F12), and (2) the Fusarium module 16 (F16) and the correlated wheat modules 1 and 5 (W01/W05). The W12/F12 modules were deemed of interest because they were specific to the transition from symptomless to symptomatic infection stage. Here, the authors find genes related to mycotoxin production to be upregulated in the F12 module, while the W12 is enriched in genes involved in detoxification. F16 and W01/W05 are specific to the earliest stages of infection, and thus most likely involved in fungal virulence. Here, one of the key genes identified is FgKnr4, which the authors show to be important for fungal virulence, as gene knockout leads to a premature stop of disease progression. As the authors show that FgKnr4 is involved in activating cell wall-integrity mechanisms, and may function in oxidative stress-resistance, this reduced virulence may be the result a reduced ability of the fungus to withstand plant defense mechanisms. Interestingly, knocking out an orthologue of FgKnr4 in Zymoseptoria tritici led to similarly reduced virulence of this pathogenic fungus on wheat plant.

Comments:

Overall, I find the WGCN analysis to be very interesting and informative, especially because of the different stages of infection. As the dataset is made public (I believe), I think that this will be a really important resource for the community. The exemplary functional analysis of the F16/W01/W05 modules via FgKnr4 is very interesting and demonstrates that novel genes involved in virulence can be identified via this approach. A similar more detailed analysis of the W12/F12 modules with a focus on detoxification mechanisms in the plant (i.e. the W12 module) would be a very interesting bonus, but as much as I would be interested in reading about it, functional gene analyses in wheat are obviously time-consuming, and it is not essential to this manuscript. As a more critical comment, I find the presentation of the figures somewhat confusing, especially with the mixing of main figures, supplements to the main figures, and actual supplemental data. On top of that, the figures are not called up in the right order (e.g. Figure 4 follows 2D, while 3 comes after 4; Figure 6 comes before 5...), and some are never called up (I think) (e.g. Figure 1B, Figure 2B). In the case of figure 5, I generally find it hard to follow. In the text (line 262/263), the authors state that 5C shows "eye-shaped lesions" caused by ΔFgknr4 and ΔFgtri5, but I can't see neither (5C appears to be a ΔFgknr4 complementation experiment). The figure legend also states nothing in this regard. Figure 5D supposedly shows 'visibly reduced fungal burden' in ΔFgknr4-infected plants, but I can't really see the fungal burden in this picture, but the infected section looks a lot thinner and more damaged than the control stem, so in a way more diseased. The authors then go on to state (lines 272-273) that they analyzed the amounts of DON mycotoxin in infected tissues, but don't seem to show any data for this experiment. In contrast to the sometimes confusing data presentation, I find the table of correlated modules (table 1) very helpful, and obviously am happy to see that all data is available in the first author's GitHub account.

Referees cross-commenting

just to clarify in regards to my comment on Figures 5C-D, and Reviewer #3's comment "Regardless of figures 5C-D I am no expert in the field therefore I can only say they look like they have not been edited." - I didn't want to insinuate that the images have been edited. Based on the images provided, I just can't see what the authors state is shown. So this is not about editing/manipulation - just about image quality/choice. The phenotypic descriptions by the authors are quite detailed ("eye-shaped lesions", 'visibly reduced fungal burden'...), but at least for me, the images aren't good enough to illustrate and underpin their statements. Maybe better images are needed, maybe magnifications of the exact regions showing the phenotypes? But this is simply a matter of presentation, not of editing/manipulation.

Second, I agree that there should be more CWI-related genes in the wheat module linked to the FgKnr4 fungal module, or, vice-versa, CW-manipulating genes in the fungal module. It would at least be good if the authors could comment further on if they find such genes, and if not, how this fits their model.

Significance

In summary, I think that the presented WGCN analysis of mRNA-seq data with quasi-spatio-temporal resolution is a very helpful approach to identify novel fungal virulence and plant immunity genes, and with the created datasets made public, this will be an interesting and valuable resource for the community. The identification and functional analysis of FgKnr4 works as proof-of-principle. If the data presentation is improved, I believe that this will be an interesting publication.

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The authors do not wish to provide a response at this time.

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Referee #3

Evidence, reproducibility and clarity

This study identified Cpn1, a fission yeast ortholog of human Caprin1, to be involved in heterochromatin re-establishment in S. pompe by potentially regulating heterochromatic transcript stability and localization. Moreover, Cpn1 was shown to be important for stress granule formation. Although the role of Cpn1 for heterochromatin establishment and granule formation is strong, the point that there is a crosstalk between the two is weaker and could be explained through multiple independent effects. Overall, the manuscript provides interesting new observations with regards to Cpn1 function that are adequate for publication, however, a few additional validations need to be performed to strengthen the crosstalk conclusion, which could be a new significant connection.

The following comments could be addressed before publication to improve the manuscript.

Specific Comments

1. The point that there is a "Crosstalk between heterochromatin integrity and cytoplasmic RNP granule formation" could be strengthened before publication, or the tone of the manuscript revised to reflect the issues below.

A) There is no data in this section showing a direct crosstalk between heterochromatin integrity and granules. The results show that certain mutants alter heterochromatin integrity the formation of PABP-containing granules. However, those proteins could have different functions in the nucleus, cytoplasm and upon stress. Thus, granule formation could be independent of heterochromatin perturbation. E.g. Loss of Ago1 could impact cytoplasmic RNA abundance/ stability and this therefore influence granule assembly. Similarly, Cpn1/Caprin could be a multifunctional protein in S. pombe and affect various aspects of RNA metabolism. The possibility, that these proteins have multiple different functions in the cell and heterochromatin integrity and cytoplasmic RNP granule formation could be due to different functions of those proteins and not due to a crosstalk should be discussed as well.

B) Figure 5 title says that "disruption of heterochromatin alters the formation of PABP-containing RNP granules". There is no data in this figure that shows that "disruption of heterochromatin" directly causes granules. Its rather that heterochromatin mutants show altered PABP-containing RNP granules. While this is fine, it should be pointed out that this is a correlation, with a direct connection being inferred.

C) The strongest connection of heterochromatin integrity to RNP granules is the accumulation of heterochromatic transcripts in those granules. Therefore, the manuscript could be strengthened by rearranging the sections/figures.

In addition, Fig. 5A shows PABP containing granules in unstressed conditions for rik1, clr4, ago1 loss. This suggests that those granules contain lots of polyadenylated RNA. Evidence is needed that the mutations studied are not affecting global cytoplasmic translation or mRNA decay (e.g. by puromycin staining and smRNA-FISH staining or qPCR (e.g. GAPDH)). Moreover, it needs to be shown that endogenous expression of Cpn1 is unchanged. If those perturbations affect Cpn1 (or Nxt3) levels, the granule phenotype could be solely due to changes in stress granule promoting proteins. 2. The work would be strengthened by adding some additional experiments. Specifically:

A) "Previous studies by ourselves and others have provided evidence that accumulation of transcripts on chromatin can impair heterochromatin assembly, possibly through increased formation of RNA-DNA hybrids". Increased RNA-DNA hybrids/ R-loop structures were shown to lead to genomic instability, which could lead to micronuclei formation and nuclei leakage in the cytoplasm during stress. It would be nice to provide close-up view images of those stress induced cytoplasmic granules, that contain cenRNA. Do they contain weaker DAPI signal in those granules, which would be indicative of micronuclei? Moreover, providing an additional stain using either an R-loop antibody, cGAS, or a nuclei membrane marker such as LAMIN B1 could be used to rule out micronuclei/ membranous assemblies.

B) RNA FISH and quantification for PABP foci in unstressed and stressed clr4Δ dhp1-2 cells is key, which should show the highest changes in foci and RNA accumulation in foci. Are those cells showing an even stronger effect on heterochromatin establishment?

C) Compared to clr4Δ cpn1Δ, do clr4Δ dhp1-2 cpn1Δ (or cpn1Δ and dhp1-2 cpn1Δ) form more stress induced granules? And do those granules contain more heterochromatic transcripts?

D) Is heterochromatic transcripts localization in -glucose induced granules also seen with heat shock? 3. Additional tests and quantification is needed to support that conclusion: "...whereas heterochromatin mutants show increased Pabp granule formation in absence of stress, they show a significant reduction in the average number of Pabp foci formed in the presence of stress,...". Different proteins could regulate/loss of proteins impact granule assembly in different manners, for example RNA localization, assembly, disassembly, foci number, foci size, % cells with foci etc. It looks like rik1Δ shows larger foci. Therefore, upon stress, there could be indeed fewer foci because they are larger. A quantification of foci area and total foci area per cell should support or reject that conclusion. Moreover, is the same trend also observed with starvation stress, or only heat shock? 4. The field generally believes G3BP1 is not an endonuclease, and therefore the authors might want to edit the section: " ...these could include, for example, Cpn1 binding partner Nxt3, the human ortholog of which, G3BP1, has been shown to function as an endoribonuclease for degradation of selected RNAs (63)." Although, it was shown that G3BP1 has endoribonuclease activity in that reference, this was never reproduced and is generally now accepted in the field that G3BP1 does not function as a endoribonuclease to regulate RNA homeostasis.

Minor comment:

1. Fig. 2 is a bit confusing. Maybe it could help if the controls - to rule out heterochromatin maintenance (B, C,D) - could be better grouped together or put into supplementary.
2. Fig 4 A, figures for Cpn1R6A-GFP upon glucose starvation is missing.
3. Fig 4 D, intensity is weaker in mkt1Δ, its difficult to see the granules. It looks like based on the image that there are less granules, but the quantification shows unchanged granules.
4. Fig 5 D/ Supl S5A, images with stress are missing for rik1 loss (the ones leading to qualifications in 5D)
5. Fig 5 C, rik1Δ, ago1Δ, co-colocalised with Cpn1-GFP are missing
6. Fig.6D, one arrow showing cytoplasmic foci is shifted. PABP stain needs to be added to highlight these are cytoplasmic PABP foci.
7. cen(dg) transcripts show lack of localization in granules in unstressed cells. The explanation why is a bit unclear. "It remained possible that these foci might rather be associated with RNA degradation, ...". Or RNA degradation happens in the nucleoplasm or cytoplasm. Moreover, in the discussion: "Although we were not able to detect stable accumulation of heterochromatic RNAs in these granules by RNA-FISH, we suspect that this may be because these granules are associated with RNA turnover, although it is also possible that they arise as a result of altered RNP homeostasis more broadly." This is confusing. If those granules form due to accumulation of heterochromatic RNAs, then they cannot be the sites for their degradation, because then they would disassemble, if heterochromatic RNAs are degraded.
8. Clr4Δ and other conditions shows accumulation of cen(dg) RNA-FISH at the centromeres. It would be informative to see if Cpn1-GFP shows colocalization, which could provide additional evidence for the two models in Fig. 7.
9. Fig. 6D/E: Its difficult to see changes of cen(dg) RNA-FISH intensity at the centromeres in the images. A close-up view should be provided without overexposure to indicate differences.

Significance

This manuscript begins to address a possible relationship between stress granule formation and the regulation of heterochromatin. This is an interesting connection, although the mechanism by which such these two processes are connected is unclear at this time.

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Referee #2

Evidence, reproducibility and clarity

In their manuscript titled "Fission yeast Caprin protein is required for efficient heterochromatin establishment", Zhang and colleagues describe the role of Caprin1 (Cpn1), the fission yeast ortholog of mammalian CAPRIN1, in the de novo establishment of heterochromatin. Using reporter assays for heterochromatin formation, they found that deletion of Cpn1 reduces H3K9 methylation, thereby impairing the de novo establishment of silencing, while the maintenance of silencing at centromeric repeats remains unaffected.

The authors demonstrate that Cpn1 interacts with the fission yeast orthologs of known human CAPRIN1 interaction partners, Nxt3 and Ubp3. These factors are then tested for their influence on the establishment of silencing.

Using microscopy to observe tagged Cpn1 and known stress granule markers, the authors show that Cpn1 localizes to stress granules. They also quantitatively assess the impact of Cpn1 interactors on stress granule formation. Additionally, the authors note that different RNAi mutants have stress granules even in the absence of envirmental stresses.

Finally, they investigate the subcellular localization of the cen(dg) transcript using single-molecule RNA FISH. They find that in heterochromatin mutant cells, cen(dg) transcripts localize to the nucleus and exhibit both nuclear and cytoplasmic localization under glucose starvation conditions. The authors also show, through quantification of RNA FISH and RT-qPCR, that cen(dg) transcripts accumulate in Cpn1 mutants.

Major comments:

The authors suggest that Cpn1 is requried for efficient degradation of RNA which in-turn helps the establishemnt of heterochromatin potentially by preventing the formation of R-loops. Yet the localization of Cpn1 under non-stressed conditions is cytoplasmic. Additionally the authors show that Cpn1 helps to limit the accumulation of heterochromatic trancripts on chromatin, yet there is no evidence for a nuclear pool of Cpn1 in these condtions.

In order to strengthen the link between these nuclear processes it is important that the authors follow up on some of the aspects detailed below.

Is Cpn1 also present in the nucleus in non-stressed conditions? This would be a pre-requesit for a direct mechanisic link for the model that the authors suggest. This could be, for example, adressed by LeptomycinB treatment followed by imaging of Cpn1. Such an experiment could reveal if the protein is shutteling between the nucleus and the cytoplasm.

In Fig 6 C the authors show co-localization of dh-transcripts with Papb1 under glucose starvation conditions. To strengthen their hypothesis of cen(dg) RNA binding/regulation by Cpn1 show and quantify co-localization of Cpn1 and cen(dg) transcripts.

The authors observe cytoplasmic cenRNA in Clr4-delta dhp1-2 cells. To substantiate the hypothesis that Cpn1 binds such transcript co-localization of Cpn1-GFP with cen(dg) transcripts should be examined.

Can the authors rule out that deletion of Cpn1 affects the RNA levels of proteins important for heterochromatin establishment? As Cpn1 could regulate the stability of mRNAs in the cytoplasm it might be worthwhile to consider also an indirect effect of Cpn1 deletion on the process of heterochromatin establishment. The study would benefit from a genomic characterization of Cpn1-delta cells using RNAseq or an extended discussion of this potential caveat.

Minor comments:

RNA-FISH images are labeled cen RNA, please provide consistent lables for the transcript throught the manuscript (cen(dg)).

Please display individual data points for replicate experiments when displaying qPCR results. This would give the reader more opportunities to judge the distribution of the data points. (Fig2 C,D,F,G,H, Fig6 F)

Fig 2 G: it is not immediately obvious that the two bar plots display different HOOD amplicons. The presentation of the data could be improved.

Significance

In the presented manuscript Zhang and colleauges place Cpn1 as a novel factor into the fission yeast RNAi pathway. This study suggests a link between RNAi and stress granule biology which would provide a novel connection of these fields. The manuscript will be of interest to a specialized audience, both in RNAi/heterochromation formation and stress granule biology and additionally would provide a novel function of a CAPRIN ortholog.

The manuscript is well written and overall the data is presented well. Furthermore the authors provide a solid genetic characterization of Cpn1's effect on heterochromatin establishment. While the manuscript provides several interesting observations their mechanistic link remains unclear and I belive that it would be very important to substaniate their observations with experiments supporting a direct mechanistic link between heterochromatin establishemnt and Cpn1.

Field of expertise: small RNA mediated heterochromatin formation, RNA biology, chromatin biology

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Referee #1

Evidence, reproducibility and clarity

Summary:

In this study, Zhang et al. identified a novel factor named Cpn1 promoting de novo heterochromatin establishment in the fission yeast Schizosaccharomyces pombe. The authors established an elegant genetic approach to identify mutants impaired in the de novo heterochromatin assembly, allowing the quantitative assessment of heterochromatin establishment in a highly reproducible manner. This approach allowed them to revisit potential candidates for heterochromatin establishment from a previous study, leading to the identification of Cpn1. Cells lacking Cpn1 display primarily defects in heterochromatin establishment but not maintenance at constitutive heterochromatin. While the function of Cpn1 was unknown, the authors established a functional link to stress granule formation, demonstrating that Cpn1 is the ortholog of the human RNA-binding protein CAPRIN1, likewise forming a complex with two other factors, Nxt3 and Ubp3. Mutating a putative RNA-binding RRG motif in Cpn1 largely phenocopied the establishment defect seen in the deletion mutant. Moreover, Cpn1 and its complex members co-localize with the stress granule marker poly(A)-binding protein, Pabp. Conversely, deleting Cpn1 or mutating its RRG motif resulted in a reduced number of stress granule formation.

Providing a further link between heterochromatin and stress granules, the authors showed that heterochromatin-deficient mutants accumulate Papb foci in the absence of stress cells, which was largely dependent on Cpn1. Conversely, the number of stress granules was reduced under stress conditions in these mutants, suggesting that heterochromatic transcripts compete with canonical RNPs that form stress granules. The molecular mechanism by which Cpn1 contributes to heterochromatin establishment remains unclear, though. In contrast to Mkt1, another establishment factor previously studied by the authors, no heterochromatic transcripts were found to be associated with Cpn1 when performing RNA-IP (RIP) experiments. The authors then analyzed pericentromeric transcripts (cen RNA) by smRNA-FISH. Deleting the H3K9 methyltransferase Clr4 resulted in the formation of nuclear foci that co-localized with the centromeric histone variant CENP-A. Glucose starvation increased the number of foci, which were also found in the cytoplasm under this stress condition and partially co-localized with Pabp. Notably, inactivating the exoribonuclease Dph1/Xrn2 also resulted in increased nuclear foci formation and accumulation in the cytosol, which was prevented when Cnp1 was absent. Hence, the authors proposed a model, by which Cpn1 limits accumulation of heterochromatic transcripts on chromatin by facilitating their export and cytoplasmic degradation by Dhp1.

Major comments

1. The authors suggest that Cnp1 contributes to heterochromatin establishment by facilitating the removal of excessive heterochromatic transcripts from chromatin. Nevertheless, despite the accumulation of pericentromeric transcripts inside the nucleus in clr4∆, direct evidence for their accumulation on chromatin remains elusive. While the authors cautiously avoid assigning Cnp1 a definite role in heterochromatic transcripts removal, investigating RNA:DNA hybrid accumulation through DNA-RNA immunoprecipitation (DRIP) could strengthen their conclusions. Given the successful application of DRIP by the authors in their Mkt1 study (Taglini et al., 2020) and its prior used by others (PMID: 28404620), this approach appears feasible and judicious when appropriate controls are implemented.
2. While the data support the hypothesis that Cpn1 binds RNA, the authors could not detect Cpn1 association with heterochromatin transcripts. This could be due to transient interactions and their fast turnover, as the authors suggested. The authors could repeat the RIP experiments in mutants that prevents turnover of transcripts, for instance in dhp1-2 and rrp6∆ mutants.

Minor comments:

1. How was the quantification of Pabp and Cpn1 foci performed? Little information is provided ("images were [...] exported to ImageJ analysis"). Given the presence of additional (diffuse) signals even under stress conditions, I'm wondering how foci were distinguished from background? Was there a threshold for signals considered to be 'foci' versus background? The authors should give a more detailed description in the figure legends or Materials & Methods section.
2. How was the relative sm-FISH intensity in Figure 6D and E determined? Have there been internal controls to ensure that hybridization efficiency was comparable for different strains/samples?

Significance

The is an intriguing study that provides several functional links between heterochromatin establishment and stress responses, using a combination of elegant yeast genetics, imaging, biochemical approaches and proteomics. While it was previously shown that heterochromatic transcripts can accumulate on chromatin interfering with heterochromatin assembly (Broenner et al., 2017), this study conceptionally advances our understanding of this process by describing a potential role for Cpn1 in facilitating nuclear export of heterochromatic transcripts. This study further describes the conservation of the human CAPRIN1 complex and its role in cytosolic stress granule assembly in yeast and therefore will be of broad interest for researchers interested in heterochromatin assembly and RNP homeostasis. A limitation of this study is the lack of a distinct molecular mechanism by which Cpn1 promotes heterochromatin establishment. Performing additional experiments could strengthen the authors' arguments and contribute to a better understanding of the underlying mechanism(s).

I have a longstanding expertise in heterochromatin assembly, transcriptional silencing and yeast genetics using S. pombe and S. cerevisiae as model systems.

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Reply to the reviewers

Manuscript number: RC-2024-02546

Corresponding author: Woo Jae, Kim

1. General Statements

The goal of this study is to provide the insights of one specific neuron ‘SIFa’ controls interval timing behavior by its receptor ‘SIFaR’ through neuropeptide relay. Interval timing, or the sense of time in the seconds to hours range, is important in foraging, decision making, and learning in humans via activation of cortico-striatal circuits. Interval timing requires completely distinct brain processes from millisecond or circadian timing. In summary, interval timing allows us to subjectively sense the passage of physical time, allowing us to integrate action sequences, thoughts, and behavior, detect developing trends, and predict future consequences.

Many researchers have tried to figure out how animals, including humans, can estimate time intervals with such precision. However, most investigations have been conducted in the realm of psychology rather than biology thus far. Because the study of interval timing was limited in its ability to intervene in the human brain, many psychologists concentrated on developing convincing theoretical models to explain the known occurrence of interval timing.

To overcome the limits of studying interval timing in terms of genetic control, we have reported that the time investment strategy for mating in Drosophila males can be a suitable behavioral platform to genetically dissect the principle of brain circuit mechanism for interval timing. For example, we previously reported that males prolong their mating when they have previously been exposed to rivals (Kim, Jan & Jan, "Contribution of visual and circadian neural circuits to memory for prolonged mating induced by rivals" Nature Neuroscience, 2012) (Kim et al, 2012), and this behavior is regulated by visual stimuli, clock genes, and neuropeptide signaling in a subset of neurons (Kim, Jan & Jan, “A PDF/NPF Neuropeptide Signaling Circuitry of Male Drosophila melanogaster Controls Rival-Induced Prolonged Mating” Neuron, 2013) (Kim et al, 2013). And we also reported that the sensory inputs are required for sexual experienced males to shorten their mating time (Lee, Sun, et al, “Taste and pheromonal inputs govern the regulation of time investment for mating by sexual experience in male Drosophila melanogaster” PLOS genetics, 2023) (Lee et al, 2023).

Throughout their lives, all animals must make decisions in order to optimize their utility function. Male reproductive success is determined by how many sperms successfully fertilize an egg with a restricted number of investment resources. To optimize male reproductive fitness, a time investment strategy has been devised. As a consequence, we believe that the flexible responses of mating duration to different environmental contexts in Drosophila males might be an excellent model to investigate neural circuits for interval timing.

The most well-known features of mammalian modulating energy homeostasis between the gut and the brain is one of the most intensively studied neuro-modulatory circuits via the neuronal relay of neuropeptides. In this article, we report that SIFa controls two alternate interval timing behaviors through neuropeptide relay signaling by SIFaR and other important neuropeptides and transmits the internal states of the male brain into decision making. According to our findings, male Drosophila utilize SIFa-SIFaR signaling modulating LMD and SMD behaviors. During our investigation in this regulation, we found a subset of cells that express SIFaR in SOG and AG region are important for the modulation of interval timing behaviors. Furthermore, we discovered a neuropeptide named Corazonin (Crz) which expressed in SIFaR is important for both LMD and SMD behaviors.

Our discovery of neuropeptide relay of SIFa-SIFaR-Crz-CrzR in male Drosophila in modulating interval timing behaviors will be a huge step forward in our knowledge of interval timing behavior.

2. Point-by-point description of the revisions

Reviewer #1

Comment 1. The authors are to be commended for the sheer quantity of data they have generated, but I was often overwhelmed by the figures, which try to pack too much into the space provided. As a result, it is often unclear what components belong to each panel. Providing more space between each panel would really help.

__ Answer:__ We are grateful for the insightful feedback regarding the structure of our data presentation. In response to your valuable suggestion, we have made adjustments in this revised version by downsizing the diagram and ensuring the spacing between the panels.

Comment 2. The use of three independent RNAi lines to knock down SIFaR expression is experimentally solid, as the common phenotype observed with all 3 lines supports the conclusion that the SIFaR is important for mating duration choice. However, the authors have not tested whether these lines effectively reduce SIFaR expression, nor whether the GAL80 constructs used to delimit knockdown are able to effectively do so. This makes it hard to make definitive conclusions with these manipulations, especially in the face of negative results. A lack of complete knockdown is suggested by the fact that the F24F06 driver rescues lethality when used to express SIFaR in the B322 mutant background, but does not itself produce lethality when used to express SIFaR RNAi. The authors should either conduct experiments to determine knockdown efficiency or explicitly acknowledge this limitation in drawing conclusions from their experiments. A similar concern relates to the CrzR knockdown experiments (eg Figure 7).

   __Answer:__ We appreciate the reviewer's attention to the details of our experimental design. Indeed, the validation of SIFaR-RNAi efficiency is crucial for interpreting our results accurately. In our initial experiments, we focused on the consistent phenotypic outcomes across the three independent RNAi lines, which collectively suggest the importance of SIFaR in LMD and SMD behaviors. However, we recognize the importance of confirming the effectiveness of our RNAi constructs in reducing SIFaR expression. Initially, we incorporated experiments utilizing *elav-GAL80* to demonstrate that the SIFaR knockdown mediated by the *elavc155* driver is sufficient to eliminate LMD and SMD behaviors. The corresponding results are presented in Figure 1C-D, with a detailed description provided in the manuscript as detailed below.

"The inclusion of elav-GAL80, which suppresses GAL4 activity in a pan-neuronal context, was found to restore both LMD and SMD behaviors when SIFaR was knocked down by a pan-neuronal elavc155 driver (Fig. 1C-D). This observation suggests that the reduction in SIFaR expression mediated by the elavc155 driver is sufficient to significantly impair LMD and SMD behaviors."

   In response to the comments, we have conducted a thorough reevaluation in our revised manuscript. Specifically, we have confirmed the efficiency of the SIFaR-RNAi line HMS00299, which exhibited the most pronounced phenotype when co-expressed with the tub-GAL4 and nSyb-GAL4 drivers, using quantitative real-time PCR (qRT-PCR). It has come to our attention that we omitted mentioning the embryonic lethality induced by the HMS00299 line when combined with either tub-GAL4 or nSyb-GAL4 drivers, which is consistent with the homozygous lethality observed in the *SIFaRB322* mutant. To address this, we have performed qRT-PCR experiments by crossing the HMS00299 line with tub-GAL4; tub-GAL80ts, allowing for the temporary knockdown of SIFaR specifically during the adult stage. We utilized w-/SIFaR-RNAis as a control in these experiments. The outcomes are illustrated in Figure 1E, and we have made the necessary modifications and additions to the manuscript to accurately reflect the efficiency of the SIFaR-RNAi line as detailed below.

"To ensure that RNAi did not have an off-target effect, we tested three independent RNAi strains and found that all three RNAi successfully disrupted LMD/SMD when expressed in neuronal populations. (Fig. S1E-J). We chose to use the HMS00299 line as SIFaR-RNAi for all our experiments because it efficiently disrupts LMD/SMD without UAS-dicer expression. Employment of broad drivers, including the tub-GAL4 and the strong neuronal driver nSyb-GAL4, with HMS00299 line consistently results in 100% embryonic lethality (data not shown). This phenotype mirrors the homozygous lethality observed in the SIFaRB322 mutant. The efficiency of HMS00299 SIFaR-RNAi lines was also validated through quantitative PCR analysis (Fig. 1E). Consequently, we infer that the knockdown of SIFaR using the HMS00299 line nearly completely diminishes the levels of the SIFaR protein."

We also examined the knockdown efficiency of CrzR in the experiments related to Figure 8 (revised version), following a similar approach (Fig. S7K).

Comment 3. Most of the behavioral experiments lack traditional controls, for example flies that contain either the GAL4 or UAS elements alone. The authors should explain their decision to omit these control experiments and provide an argument for why they are not necessary to correctly interpret the data. In this vein, the authors have stated in the methods that stocks were outcrossed at least 3x to Canton-S background, but 3 outcrosses is insufficient to fully control for genetic background.

• *Answer: We sincerely thank the reviewer for insightful comments regarding the absence of traditional genetic controls in our study of LMD and SMD behaviors. We acknowledge the importance of such controls and wish to clarify our rationale for not including them in the current investigation. The primary reason for not incorporating all genetic control lines is that we have previously assessed the LMD and SMD behaviors of GAL4/+ and UAS/+ strains in our earlier studies. Our past experiences have consistently shown that 100% of the genetic control flies for both GAL4 and UAS exhibit normal LMD and SMD behaviors. Given these findings, we deemed the inclusion of additional genetic controls to be non-essential for the present study, particularly in the context of extensive screening efforts. Consequently, in accordance with the reviewer's recommendation, we conducted genetic validation experiments on novel genetic crosses, including SIFaR-RNAi/+, CrzR-RNAi/+, and GAL4NP5270/+, and incorporated the results in the supplementary figures (Supplementary information 1). We have made the necessary modifications and additions to the manuscript as below.

"Given those genetic controls, as evidenced by consistent exhibition of normal LMD and SMD behaviors (Supplemental information 1), the observed reduction in SIFaR expression, driven by elavc155, is deemed sufficient to induce significant disruptions in LMD and SMD behaviors."

However, we understand the value of providing a clear rationale for our methodology choices. To this end, we have added a detailed explanation in the "MATERIALS AND METHODS" section and the figure legends of Figure 1. This clarification aims to assist readers in understanding our decision to omit traditional controls, as outlined below.

"__Mating Duration Assays for Successful Copulation__The mating duration assay in this study has been reported (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023). To enhance the efficiency of the mating duration assay, we utilized the Df(1)Exel6234 (DF here after) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR) (Parks et al. 2004; Yapici et al. 2008). Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males (Yapici et al. 2008). We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For group reared (naïve) males, 40 males from the same strain were placed into a vial with food for 5 days. For single reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. 40 DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for mating duration assays. At the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO2. After placing a single female into the mating chamber, we inserted a transparent film then placed a single male to the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25℃ incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 sec, and total mating duration was calculated for each couple. Genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023; Huang et al. 2024; Zhang et al. 2024). Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test."

   We appreciate the reviewer's inquiry regarding the genetic background of our experimental lines. In response to the comments, we would like to clarify the following. All of our GAL4, UAS, or RNAi lines, which were utilized as the virgin female stock for outcrosses, have been backcrossed to the Canton-S (CS) genetic background for over ten generations. The majority of these lines, particularly those employed in LMD assays, have been maintained in a CS backcrossed status for several years, ensuring a consistent genetic background across multiple generations. Our experience has indicated that the genetic background, particularly that of the X chromosome inherited from the female parent, plays a pivotal role in the expression of certain behavioral traits. Therefore, we have consistently employed these fully outcrossed females as virgins for conducting experiments related to LMD and SMD behaviors. It is noteworthy that, in contrast to the significance of genetic background for LMD behaviors, we have previously established in our work (Lee *et al*, 2023) that the genetic background does not significantly influence SMD behaviors. This distinction is important for the interpretation of our findings. To provide a comprehensive understanding of our experimental design, we have detailed the genetic background considerations in the __"Materials and Methods"__ section, specifically in the subsection __"Fly Stocks and Husbandry"__ as outlined below.

"To reduce the variation from genetic background, all flies were backcrossed for at least 3 generations to CS strain. For the generation of outcrosses, all GAL4, UAS, and RNAi lines employed as the virgin female stock were backcrossed to the CS genetic background for a minimum of ten generations. Notably, the majority of these lines, which were utilized for LMD assays, have been maintained in a CS backcrossed state for long-term generations subsequent to the initial outcrossing process, exceeding ten backcrosses. Based on our experimental observations, the genetic background of primary significance is that of the X chromosome inherited from the female parent. Consequently, we consistently utilized these fully outcrossed females as virgins for the execution of experiments pertaining to LMD and SMD behaviors. Contrary to the influence on LMD behaviors, we have previously demonstrated that the genetic background exerts negligible influence on SMD behaviors, as reported in our prior publication (Lee et al, 2023). All mutants and transgenic lines used here have been described previously."

Comment 4. Throughout the manuscript, the authors appear to use a single control condition (sexually naïve flies raised in groups) to compare to both males raised singly and males with previous sexual experience. These control conditions are duplicated in two separate graphs, one for long mating duration and one for short mating duration, but they are given different names (group vs naïve) depending on the graph. If these are actually the same flies, then this should be made clear, and they should be given a consistent name across the different "experiments".

* * Answer: We are grateful to the reviewer for highlighting the potential for confusion among readers regarding the visualization methods used in our figures. In response to this valuable feedback, we have now included a more detailed explanation of the graph visualization techniques in the legends of Figure 1, as detailed below. This additional information should enhance the clarity and understanding of the figure for all readers.

"In the mating duration (MD) assays, light grey data points denote males that were group-reared (or sexually naïve), whereas blue (or pink) data points signify males that were singly reared (or sexually experienced). The dot plots represent the MD of each male fly. The mean value and standard error are labeled within the dot plot (black lines). Asterisks represent significant differences, as revealed by the unpaired Student’s t test, and ns represents non-significant differences (*p* *

Comment 5.* The authors have consistently conflated overlap of neuronal processes with synaptic connections. Claims of synaptic connectivity deriving solely from overlap of processes should be tempered and qualified.

• For example, they say (Lines 201-202) "These findings suggest that SIFa neurons and GAL424F06-positive neurons form more synapses in the VNC than in the brain." This is misleading. Overlap of 24F06-LexA>CD8GFP and SIFa-GAL4>CD8RFP tells us nothing about synapse number, or even whether actual synapses are being formed.*

• *Answer: We sincerely thank the reviewer for their insightful and constructive feedback regarding the interpretation of our data. We acknowledge the important point raised about the limitations of inferring synapse numbers from the overlap of membrane GFP and RFP signals. We fully concur that more specific techniques, such as the GRASP method, are necessary to accurately quantify synapse numbers, as we have demonstrated in subsequent sections of our manuscript. In the section where we describe the SIFa-SIFaR neuronal architecture labeled with membrane GFP and RFP, we recognize the need for caution in not overstating the implications of these findings as indicative of synapse formation. In light of the reviewer's comments, we have revised our discussion to more accurately reflect the nature of the SIFa-SIFaR neuronal arborizing patterns, as detailed below. This revision aims to provide a more nuanced interpretation of our observations and to align with the current scientific understanding of synaptic quantification.

"As previously reported, SIFa neurons arborize extensively throughout the CNS, but the neuronal processes of GAL424F06-positive neurons are enriched in the optic lobe (OL), sub-esophageal ganglion (SOG), and abdominal ganglion (AG) (GFP signal in Fig. 2F). Neuronal processes that are positive for SIFa and SIFaR strongly overlap in the prow (PRW), prothoracic and metathoracic neuromere (ProNm and MesoNm), and AG regions (yellow signals in Fig. S3A). We quantified these overlapping neuronal processes between SIFa- and SIFaR-positive neurons and found that approximately 18% of SIFa neurons and 52% of GAL424F06-positive neurons overlap in brain (Fig. S3B, C), whereas approximately 48% of SIFa and 54% of GAL424F06-positive neurons overlap in VNC (Fig. S3D, E). These findings suggest that SIFa neurons and GAL424F06-positive neurons form more neuronal processes in the VNC than in the brain."

• * Lines 210-211: "The overlap of DenMark and syt.EGFP signals was highly enriched in both SOG and ProNm regions, indicating that these regions are where GAL424F06 neurons form interconnected networks". This is misleading. Overlap of DenMark and syt.EGFP does not indicate synapses (especially since these molecules can be expressed outside the expected neuronal compartment if driven at high enough levels).*

• *Answer: We are grateful for the reviewer's critical insights regarding our interpretation of the DenMark and syt.eGFP experiments. We acknowledge the reviewer's point that the overlap of DenMark and syt.eGFP signals does not conclusively indicate synapses and that some of these signals can be expressed outside the expected neuronal compartments, particularly at high levels.

  It is important to note that DenMark and syt.eGFP are markers of synaptic polarity. In the original publication of DenMark, the authors demonstrated that while these two markers are closely apposed, they do not necessarily overlap, as seen in the labeled yellow areas. They concluded that these areas could represent closely apposed regions where "LNv neurons establish presynaptic contacts within the aMe, suggesting that these contacts are on the postsynaptic sites of the LNv neurons themselves. (Nicolaï et al, 2010)" The authors also observed that DenMark-enriched structures appear juxtaposed to, rather than coexpressed with, syt.eGFP, indicating a potential for synapse formation between R neurons within the eb. In contrast, projections to the suboesophageal ganglion, which show strong Syt–GFP expression, are devoid of DenMark, suggesting a different interpretation of the signals (Nicolaï et al, 2010).

  Building on these findings, we have reanalyzed our data with caution (as shown in Figure S3). In the SOG region, where we observed strong yellow signals, these were not limited to cell bodies but also extended to the middle region filled with neural processes. Upon close examination of the DenMark and syt.eGFP signals, we confirmed that these yellow signals are closely juxtaposed, suggesting the possibility of synapse formation between SIFaR24F06 neurons within the SOG. We emphasize that this interpretation is based on the original findings from the DenMark study. To provide clarity for general readers, we have added further explanations regarding the interpretation of these signals, as detailed below. We believe that our revised analysis and the additional explanations will help to clarify the potential implications of our findings, while also acknowledging the limitations and the need for further investigation.

"DenMark-enriched structures, localized within the SOG, are observed in close apposition to syt.eGFP signals, as indicated by the white-dashed circles (Fig. S3Fa). This spatial relationship suggests that SIFaR-expressing neurons, identified by GAL424F06 labeling, may form synapses with one another within the SOG. The colocalization of yellow signals resulting from the interaction between DenMark and syt.eGFP has been previously interpreted and validated by other researchers, supporting our observation (Nicolaï 2010,Kennedy 2018). In contrast to the yellow signals observed in the SOG, which are indicative of neural processes, the yellow signals detected in the ProNm appear to be associated with cell bodies rather than neural processes, as DenMark signals are often observed to leak out (as shown in Fig. S3Fb) (Nicolaï 2010,Kennedy 2018). Despite the presence of juxtaposed DenMark and syt.GFP signals in the ProNm, the interpretation of the yellow signals as potential synapses between SIFaR neurons remains an open question (indicated by the question mark in Fig. S3K).

• • Lines 320-322: "Neurons expressing Crz exhibit robust synaptic connections with SIFaR24F06 neurons located in the PRW region of the SOG in the brain (panels of Brain and SOG in Fig. 5A)". This is again misleading. They are not actually measuring synapses here, but instead looking at area of overlap between neuronal processes of Crz and SIFaR cells.*

  Answer: We sincerely appreciate the reviewer's critical feedback regarding our initial data interpretation. We acknowledge the important distinction that overlapping membrane markers do not provide a direct measure of synapse formation. In line with the reviewer's suggestion, we have revised the relevant sentence to more accurately reflect this understanding, as detailed below.

"Neurons expressing Crz were observed in close proximity to SIFaR24F06-expressing neurons within the PRW-SOG of the brain (panels of Brain and SOG in Fig. 6A)."

• * In Figs 3B and S4A, they are claiming that all neuronal processes within a given delineated brain area are synapses. The virtual fly brain and hemibrain resource have a way to actually identify synapses. This should be used in addition to the neuron skeleton. Otherwise, it is misleading to label these as synapses.*

  Answer: We are grateful for the reviewer's insightful comments that highlighted the potential for misleading information in our previous submission. Upon careful reexamination of the virtual fly brain model, we have made the necessary corrections and updated the figures in our revised manuscript (Figure 3B and S4B). This reanalysis has allowed us to further substantiate our findings, confirming that SIFa neurons indeed establish dense synaptic connections with multiple regions of the central brain.

• * Furthermore, measuring the area of GRASP signal is not the same as quantifying synapses. We don't know if synapse number changes (eg in lines 240-242).*

• Answer: We sincerely appreciate the reviewer's valuable suggestion regarding our quantification methods for assessing synaptic changes using GRASP signals. We acknowledge the reviewer's accurate observation that GRASP signals alone cannot provide an exact quantification of synapse number changes. In response to this feedback, we have employed the 'Particle analysis' function of ImageJ to infer the number of synapses from GRASP signals, clearly labeling them as 'number of particles' (as exemplified in Figures S4G and S4J). Additionally, we have compared the average size of each particle to enable a more precise comparison of synapse number changes (as shown in Figures S4H and S4K). While it is true that GRASP signals should not be directly equated with synapse counts, the quantification of GRASP signal intensity can still provide insights into the underlying synaptic connectivity, as described in the original GRASP paper (Feinberg et al, 2008a). Following this approach, previous studies have used signal intensity quantifications to draw conclusions about changes in synaptic specificity in various mutants. Since our methods for measuring GRASP intensity are consistent with the original techniques, we have updated our Y-axis labeling to reflect 'normalized GFP intensity (Norm. GFP Int.)', as exemplified in Figure 4. This change aims to provide a clearer and more accurate representation of our data.

Comment 6.* In general, the first part of the manuscript (implicating SIFaR in mating duration) is much stronger than the second part, which attempts to demonstrate that SIFa acts through Crz-expressing neurons to induce its effects. The proof that SIFa acts through Crz-expressing neurons to modify mating duration is tenuous. The most direct evidence of this, achieved via knockdown on Crz in SIFaR-expressing cells, is relegated to supplemental figures. The calcium response of the Crz neurons to SIFa neuron activation (Fig. 6) is more of a lack of a decrease that is observed in controls. Also, this is only done in the VNC. Why not look in the brain, because the authors previously stated a hypothesis that the "transmission of signals through SIFaR in Crz-expressing neurons is limited to the brain" (lines 381-382)?

Furthermore, the authors suggest that Crz acts on cells in the heart to regulate mating duration. It would be useful to add a discussion/speculation as to possible mechanisms for heart cells to regulate mating decisions. Is there evidence of CrzR in the heart? The SCope data presented in Fig. 7I-L and S7G-H is hard to read.*

• Answer: We sincerely appreciate the reviewer's constructive feedback on the section of our manuscript that discusses the role of the SIFa-SIFaR connection in regulating mating duration. We understand that the initial presentation may not have been sufficiently convincing. As we detailed in our previous biorXiv preprint (Wong et al, 2019), we conducted a comprehensive screen of numerous neuropeptides and their receptors that mediate SIFa signals through SIFaR and added those data in Supplementary Table S1 and S2. Among these, Crz was identified as a key neuropeptide in this pathway and is also well-documented for its role in mating duration (Tayler et al, 2012). Our data clearly demonstrate that Crz neurons are responsive to the activity of SIFa neurons, supporting the validity of this connection. Additionally, in another manuscript focusing on the input signals for SIFa (Kim et al*, 2024), we established that CrzR does not function in SIFa neurons, confirming the bidirectional nature of SIFa-to-Crz signaling.

  Inadvertently, we had relegated the Crz knockdown results to supplementary figures, under the assumption that our screening results regarding the relationship between SIFaR and neuropeptides were already well-covered (Wong et al, 2019). In light of the reviewer's comments, we have now relocated the Crz knockdown results, particularly those involving SIFaR-expressing cells, to the main figures (Figure 6F-G). We have also included a more detailed description of our previous screening results within the manuscript, as outlined below, to provide a more comprehensive understanding of our findings.

"Furthermore, the Crz peptide and Crz-expressing neurons have been characterized as pivotal relay signals in the SIFa-to-SIFaR pathway, which is essential for modulating interval timing behaviors (Wong 2019)."

   We greatly appreciate the reviewer's critical and constructive feedback regarding the detection of SIFa-to-Crz long-distance signaling, particularly their observation that this signaling is detectable from the brain to the VNC but not between brain regions. In response to the reviewer's suggestions, we have made the following adjustments to our manuscript:

1. We have relocated our SIFa-Crz GCaMP data pertaining to the VNC region to the Figures 6L-O) to maintain focus on the primary findings within the main text.
2. Our deeper analysis has led to the identification of two cells in the Super Intermediate Protocerebrum (SIP) regions that coexpress both Crz and SIFaR24F06, as well as OL cells (Figure 6D-E).
3. We have included GCaMP data from the brain region in the main figure to provide a comprehensive view of the signaling dynamics (Fig. 6P-R and Fig. S6N-P).
4. Upon examining the SIFa-to-Crz signaling through GCaMP calcium imaging, we observed that the calcium levels in Crz+/SIFaR+ SIP neurons consistently decreased upon SIFa activation (Figure 6P-R). In contrast, the calcium signals in Crz+/SIFaR+ OL neurons increased upon SIFa activation, similar to the pattern observed in Crz+ AG neurons in the VNC (Figure 6M-O and Figure S6N-P).

5. We have summarized these findings in Figure 6S and provided a detailed description of the results in the manuscript, as outlined below. "To elucidate the direct response of Crz neurons to the activity of SIFa neurons, we conducted live calcium (Ca2+) imaging in the Super Intermediate Protocererbrum (SIP), OL and AG region of the VNC, where Crz neurons are situated (Fig. 6D, Fig. S6M). Upon optogenetic stimulation of SIFa neurons, we observed a significant increase in the activity of Crz in OL and AG region (Fig. 6L-O, Fig. S6N-P), evidenced by a sustained elevation in intracellular Ca2+ levels that persisted in a high level before gradually declining to baseline levels, where the cells in top region of the SIP exhibit consistently drop down after stimulated the SIFa neurons (Fig. 6P-R). These calcium level changes were in contrast to the control group (without all-trans retinal, ATR) (Fig. 6L-R, Fig. S6N-P). These findings confirm that Crz neurons in OL and AG are activated in response to SIFa neuronal activity, but the activity of Crz neurons in SIP are inhibited by the activition of SIFa neuron, reinforcing their role as postsynaptic effectors in the neural circuitry governed by SIFa neurons. Moreover, these results provide empirical support for the hypothesis that SIFa-SIFaR/Crz-CrzR long-range neuropeptide relay underlies the neuronal activity-based measurement of interval timing."

   We are grateful for the reviewer's opportunity to elaborate on the intriguing findings concerning the expression of CrzR in the heart and its potential link to mating duration. In the context of traditional interval timing models (Meck et al, 2012; Matell, 2014; Buhusi & Meck, 2005), the role of a pacemaker in generating a temporal flow for measuring time is considered essential. The heart, being a well-known pacemaker organ in animals, provides a compelling framework for our discussion. In response to the reviewer's insightful comments, we have expanded upon our hypotheses in the DISCUSSION section, exploring the possible connections between cardiac function and the regulation of mating duration. Our reflections on this topic are detailed as follows:

---

"It has been reported that the interaction between the brain and the heart can influence time perception in humans (Khoshnoud et al, 2024). Heart rate is governed by intrinsic mechanisms, such as the muscle pacemaker, as well as extrinsic factors including neural and hormonal inputs (Andersen et al, 2015). Moreover, the pacemaker function is essential for the generation of interval timing capabilities (Meck et al, 2012; Matell, 2014; Buhusi & Meck, 2005), with the heart being recognized as the primary pacemaker organ within the animal body. Consequently, the CrzR in the fly heart may respond to the Crz signal sent by SIFaR+/Crz+ cells and modulate the heart rate, thereby impacting the perception of time in male flies."

   We appreciate the reviewer's interest in the expression of CrzR in the heart and its potential implications for our study. In response to the reviewer's comments, we have conducted a thorough examination of the fly SCope RNAseq dataset. Our analysis revealed that CrzR is indeed broadly expressed in heart tissue, particularly in areas where the Hand gene is also expressed. This significant finding has been incorporated into our manuscript and is depicted in Figure 8L. As illustrated in Figures 8I-L, which present the SCope tSNE plot for various cell types including neurons, glial cells, muscle systems, and heart, the heart tissue exhibits the most robust expression of CrzR. This observation suggests that the Hand-GAL4 mediated CrzR knockdown experiments may provide insights into the role of CrzR expression in the heart and its influence on the interval timing behavior of male fruit flies. We have expanded upon this interpretation in the relevant sections of our manuscript to ensure a clear and comprehensive understanding of our results.

• *

Comment 7. In several cases, the effects of being raised single are opposite the effects of sexual experience. For example, in Fig. 4T, calcium activity is increased in the AG following sexual experience, but decreased in flies raised singly. Likewise, Crz-neurons in the OL have increased CaLexA signal in singly-raised flies but reduced signals in flies with previous sexual experience. In some cases, manipulations selectively affect LMD or SMD. It would be useful to discuss these differences and consider the mechanistic implications of these differential changes, when they all result in decreased mating duration. This could help to clarify the big picture of the manuscript.

   __Answer:__ We sincerely appreciate the reviewer's insightful suggestions regarding the potential mechanistic underpinnings of how differential calcium activities may modulate LMD and SMD behaviors. In response to this valuable input, we have expanded our discussion to include a hypothesis on how neuropeptide relays could potentially induce context-dependent modulation of synaptic changes and calcium activities within distinct neuronal subsets. This addition aims to provide a more comprehensive understanding of the complex interactions at play, as detailed in the revised manuscript.

"Employing two distinct yet comparable models of interval timing behavior, LMD and SMD, we demonstrated that differential SIFa to SIFaR signaling is capable of modulating context-dependent behavioral responses. Synaptic strengths between SIFa and SIFaR neurons was notably enhanced in group-reared naive males. However, these synaptic strengths specifically diminished in the OL, CB, and AG when males were singly reared, with a particular decrease in the AG region when males were sexually experienced (Fig. 4A-J). Intriguingly, overall calcium signaling within SIFaR24F06 neurons was significantly reduced in group-reared naive males, yet these signals surged dramatically in the OL with social isolation and in the AG with sexual experience (Fig. 4K-T). These calcium signals, as reported by the transcriptional calcium reporter CaLexA, were corroborated by GCaMP live imaging in both the AG and OL regions (Fig. 6L-O and Fig. S6N-P), indicating a close association between elevated calcium levels and LMD and SMD behaviors. The modulation of context-dependent synaptic plasticity and calcium dynamics by the SIFa neuropeptide through a single SIFaR receptor raises the question of how a single receptor can elicit such diverse responses. Recent neuroscientific studies in Drosophila have shown that individual neurons can produce multiple neurotransmitters and that neuropeptides are often colocalized with small molecule neurotransmitters (Nässel 2018,Deng 2019,Croset 2018,Kondo 2020). Consistent with this, we have previously reported that SIFa neurons utilize a variety of neurotransmitters, including glutamate, dopamine, and tyramine (Kim 2024). Therefore, we propose that the SIFa-SIFaR-Crz-CrzR neuropeptidergic relay circuitry may interact with different neurotransmitters in distinct neuronal subpopulations to regulate context-dependent behaviors. Supporting this hypothesis, glutamate, known to function as an inhibitory neurotransmitter in the olfactory pathway of Drosophila (Liu 2013), may be one such candidate. We speculate that neuropeptide cotransmission could underlie the mechanisms facilitating these complex, context-dependent behavioral patterns. Further research is warranted to elucidate how such cotransmission contributes to the intricate behavioral repertoire of the fly."

Minor Comments: Comment 8. For CaLexA experiments (eg Fig 7A-D), signal intensity should be quantified in addition to area covered. Increased intensity would indicate greater calcium activity within a particular set of neurons.

• *Answer: We appreciate the reviewer's insightful comments and acknowledge the importance of using intensity measurements in our analysis of CaLexA signals. We concur that the intensity of these signals is indeed correlated with the area measurements, which is a critical factor to consider. In response to the reviewer's valuable suggestion, we have revised our approach and now present our data based on intensity measurements. These have been incorporated as a primary dataset in all our CaLexA results to provide a more accurate representation of our findings. Additionally, we have updated the labeling of our Y-axis to "Norm. GFP Int.", which stands for "normalized GFP intensity". This change ensures clarity and consistency in the presentation of our data, aligning with the reviewer's recommendations and enhancing the overall quality of our manuscript.

Comment 9. In Figure 5K: quantification of cell overlap is missing. In the text they state that there are ~100 neurons that co-express SIFaR24F06 and Crz. How was this determined? Is there a graph or numerical summary of this assertion?

    __Answer:__ We sincerely thank the reviewer for pointing out the oversight in our initial submission regarding the quantification data. In response to this valuable feedback, we have now included the quantification of neurons co-expressing SIFaR24F06 and Crz in the optic lobe (OL) within Figure 6E. This addition ensures that the figure is complete and provides the necessary numerical support for our observations.

Comment 10. In lines 709-711: "Our experience suggests that the relative mating duration differences between naïve and experienced condition and singly reared are always consistent; however, both absolute values and the magnitude of the difference in each strain can vary. So, we always include internal controls for each treatment as suggested by previous studies." I had trouble understanding this section of methods. What is done with the data from the internal controls?

   __Answer:__ We appreciate the reviewer's attention to the methodology of our study, particularly regarding the use of internal controls in our mating duration assays. As referenced in our cited work by Bretman et al. (2011) (Bretman *et al*, 2011), our internal control strategy involves a comparison of mating durations between males that have been presented with specific sensory cues and those that have not. This approach includes assessing both males that have been exposed to signals and those that have not, which serves as an internal control for each experimental setup. The purpose of this design is to isolate the effects of our manipulations from other potential confounding factors. In response to the reviewer's comments, we have provided a more detailed description of our mating duration assay in the Methods section. We have also expanded our explanation to clarify how this internal control mechanism ensures that any observed differences in mating duration are attributable to the experimental manipulations and not to extraneous variables. This additional information should provide a clearer understanding of our methodology and the rationale behind our experimental design.

Comment 11. Could the authors comment on why the brain GRASP signal is so different in Figures 3A and 4A? I realize that different versions of GRASP were used in these experiments, but I would expect broad agreement between the different approaches.

   __Answer: __We appreciate the reviewer’s insight. GRASP and t-GRASP are similar technologies that can clearly show the synaptic connection between neurons. GRASP technology was first generated and performed in *C. elegens* (Feinberg *et al*, 2008b). In 2018, the researchers developed a targeted GFP Reconstitution Across Synaptic Partners method, t-GRASP, which resulted in a strong preferential GRASP signal in synaptic regions.

   In our study, we utilized both techniques because of the limitations of the chromosomes where GAL4 and lexA lines located. We also found that during data processing, our method could clearly distinguish the changes in GRASP and t-GRASP signals across three different conditions (naïve, single, and exp.). Therefore, we do not have a particular preference for one technique over the other; both methods are applicable to our experiment.

   The genotype we used in Figure 3A is *SIFa2A-lexA, GAL424F06; lexAop-nSyb-spGFP1-10, UAS-CD4-spGFP11*, where the synaptic transmission occurs from *SIFa2A-lexA *to* GAL424F06*. In Figure 4A, the genotype we used is *GAL4SIFa.PT, lexASIFaR-2A; lexAop-2-post-t-GRASP, UAS-pre-t-GRASP*, where the synaptic transmission occurs from SIFa. PT to SIFaR-2A.

   In our back-to-back submission paper, “Peptidergic neurons with extensive branching orchestrate the internal states and energy balance of male *Drosophila melanogaster,*” (Kim *et al*, 2024) we identified that *SIFa2A* can label posterior-ventral SIFa neurons (SIFaVP), which can only project to ellipsoid body and fan-shaped body. Combining the GRASP technique, Figure 3A cannot show a strong signal as in Figure 4A. We’ve shown in Figure 1G that *SIFaR-2A *covers almost the whole CNS in *Drosophila*. Thus, the synaptic transmission from SIFa. PT (label 4 SIFa neurons) to SIFaR-2A shows a strong signal under the use of the t-GRASP technique. In this case, the GRASP signals in Figure 3A and Figure 4A are so different because of the usage of different GRASP techniques and different fly lines. We appreciate the reviewer's attention to the clarity of our presentation. In response to the comments, we have taken the opportunity to meticulously revise the figure legends to ensure that the differences are explicitly highlighted and easily understood by the readers.

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Reviewer #2

Major concerns: Comment 1.* It is highly interesting that the duration of mating behavior is dependent on external and motivational factors. In fact, that provides an elegant way to study which neuronal mechanisms orchestrate these factors. However, it remains elusive why the authors link the differentially motivated durations of mating behavior to the psychological concept of interval timing. This distracts from the actually interesting neurobiology, and is not necessary to make the study interesting. *

* * Answer: We are grateful for the opportunity provided by the reviewer to elaborate on our rationale for utilizing the mating duration of male fruit flies as an exemplary genetic model for studying interval timing. At the outset, we would like to acknowledge that mating duration has gained recognition as a valuable genetic model for interval timing, as evidenced by the NIH-NIGMS R01 grant awarded to Michael Crickmore. This grant, which can be reviewed at the provided link (https://grantome.com/grant/NIH/R01-GM134222-01), underscores the significance of this model. Crickmore and colleagues have described in the grant's abstract that "mating duration in Drosophila offers a powerful system for exploring changes in motivation over time as behavioral goals are achieved," and it has the potential to provide "the first mechanistic description of a neuronal interval timing system."

   In light of this, we have incorporated our rationale into the INTRODUCTION section of our manuscript, as detailed below. We believe that our argumentation, supported by the grant's emphasis on the topic, will not only address the reviewer's concerns but also demonstrate to the broader scientific community the significance of the fruit fly's mating duration as a model for interval timing. This concept has been a cornerstone in the historical development of neuroscientific understanding of time perception. We hope that our expanded discussion will effectively convey the potential of the fruit fly mating duration as a genetic model to offer profound insights into the neural mechanisms underlying interval timing, a concept of enduring importance in the field of neuroscience.

"The dimension of time is the fundamental basis for an animal's survival. Being able to estimate and control the time between events is crucial for all everyday activities (RICHELLE & LEJEUNE, 1980). The perception of time in the seconds-to-hours range, referred to as ‘interval timing’, is involved in foraging, decision making, and learning via activation of cortico-striatal circuits in mammals (Golombek et al, 2014). Interval timing requires entirely different neural mechanisms from millisecond or circadian timing (Meck et al, 2012; Merchant et al, 2012; Buhusi & Meck, 2005). There is abundant psychological research on time perception because it is a universal cognitive dimension of experience and behavioral plasticity. Despite decades of research, the genetic and neural substrates of temporal information processing have not been well established except for the molecular bases of circadian timing (Buhusi et al, 2009; Tucci et al, 2014). Thus, a simple genetic model system to study interval timing is required. Considering that the mating duration in fruit flies, which averages approximately 20 minutes, is well within the range addressed by interval timing mechanisms, this behavioral parameter provides a relevant context for examining the neural circuits that modulate the Drosophila's perception of time intervals. Such an investigation necessitates an understanding of the extensive neural and behavioral plasticity underlying interval timing (Thornquist et al, 2020; Gautham et al, 2024; Crickmore & Vosshall, 2013)."

Comment 2.* In figure 4 A and 4K, fluorescence microscopy images of brains and ventral nerve chords are shown, one illustrating GRASP experiments, and one showing CaLexA experiments. The extreme difference between the differentially treated flies (bright fluorescence versus almost no fluorescence) is - in its drastic form- surprising. Online access to the original confocal microscopy images (raw data) might help to convince the reader that these illustrations do not reflect the most drastic "representative" examples out of a series of brain stainings. *

* * Answer: We sincerely appreciate the reviewer's thoughtful suggestion to enhance the accessibility of our microscopy images for readers who may be interested. In response to this valuable feedback, we have compiled all of our quantified image files into zip format and included them as Supplementary Information 2 and 3. We believe that this additional material will be beneficial for readers seeking a more in-depth view of our data.

Comment 3. In particular for behavioral experiments, genetic controls should always be conducted. That is, both the heterozygous Gal4-line as well as the heterozygous UAS-line should be used as controls. This is laborious, but important.

   __Answer:__ We sincerely appreciate the reviewer's critical feedback regarding the genetic controls in our study. We acknowledge the importance of this aspect and wish to clarify that we have indeed conducted a substantial number of genetic control experiments for both LMD and SMD behaviors. It is worth noting that much of this data has been previously published in other works. Recognizing the interest from another reviewer on the same topic, we have chosen to reiterate our response here for clarity and convenience. Our comprehensive approach to genetic controls ensures the robustness of our findings, and we believe that the published data further substantiates the reliability of our experimental procedures.

   We sincerely thank the reviewer for insightful comments regarding the absence of traditional genetic controls in our study of LMD and SMD behaviors. We acknowledge the importance of such controls and wish to clarify our rationale for not including them in the current investigation. The primary reason for not incorporating all genetic control lines is that we have previously assessed the LMD and SMD behaviors of GAL4/+ and UAS/+ strains in our earlier studies. Our past experiences have consistently shown that 100% of the genetic control flies for both GAL4 and UAS exhibit normal LMD and SMD behaviors. Given these findings, we deemed the inclusion of additional genetic controls to be non-essential for the present study, particularly in the context of extensive screening efforts. However, in accordance with the reviewer's recommendation, we conducted genetic validation experiments on novel genetic crosses, including SIFaR-RNAi/+, CrzR-RNAi/+, and GAL4NP5270/+, and incorporated the results in the supplementary figures (Supplementary information 1). We have made the necessary modifications and additions to the manuscript as below.

"Given those genetic controls, as evidenced by consistent exhibition of normal LMD and SMD behaviors (Supplemental information. 1), the observed reduction in SIFaR expression, driven by elavc155, is deemed sufficient to induce significant disruptions in LMD and SMD behaviors."

We understand the value of providing a clear rationale for our methodology choices. To this end, we have added a detailed explanation in the "MATERIALS AND METHODS" section and the figure legends of Figure 1. This clarification aims to assist readers in understanding our decision to omit traditional controls, as outlined below.

"__Mating Duration Assays for Successful Copulation__The mating duration assay in this study has been reported (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023). To enhance the efficiency of the mating duration assay, we utilized the Df(1)Exel6234 (DF here after) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR) (Parks et al. 2004; Yapici et al. 2008). Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males (Yapici et al. 2008). We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For group reared (naïve) males, 40 males from the same strain were placed into a vial with food for 5 days. For single reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. 40 DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for mating duration assays. At the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO2. After placing a single female into the mating chamber, we inserted a transparent film then placed a single male to the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25℃ incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 sec, and total mating duration was calculated for each couple. Genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023; Huang et al. 2024; Zhang et al. 2024). Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test."

Minor comments: Comment 4.* Line 75: word missing ("...including FEEDING-RELATED BEHAVIOR, courtship, ..."). *

   __Answer:__ We appreciate your vigilance in identifying this error. We have made the necessary correction to ensure the accuracy of our manuscript.*

*

Comment 5.* Line 120: word missing ("SIFaR expression in adult neurons BUT not glia..."). *

   __Answer:__ We appreciate your careful review and attention to detail. Thank you for bringing this to our notice. We have made the necessary corrections to address the error.*

*

Comment 6.* I find the figures often to be quite overloaded, and anatomical details often very small (e.g., figure 7A). *

* * Answer: We appreciate the constructive critique on the layout of our data presentation. Following your insightful recommendation, we have revised the manuscript to enhance clarity. Specifically, we have resized the diagram to be more compact and have also increased the spacing between the panels for better readability.

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Reviewer #3

Major Comments Comment 1.* Are the key conclusions convincing? The key conclusions are intriguing but require more robust data to be fully convincing. While the study presents compelling evidence for the involvement of SIFa and SIFaR in mating behaviors, additional experiments are needed to firmly establish the proposed mechanisms. *

* * Answer: We are deeply grateful for the insightful and constructive feedback provided by the reviewer on the SIFa-to-SIFaR signaling pathway. We are particularly encouraged by the reviewer's agreement with our findings that support the role of SIFa and SIFaR in regulating mating duration. We concur with the reviewer's suggestion that additional experiments and mechanistic insights are essential to substantiate our conclusions. To this end, we have conducted and included several new experiments, particularly GCaMP data, in the main figures (Figure 6 and S6). Our focus has been intensified on the SIFa-to-Crz signaling, given Crz's established role in controlling mating duration behavior. Below is a summary of the additional experiments we have incorporated:

1. We have repositioned the SIFa-Crz GCaMP data related to the VNC to Figures 6L-O to ensure that the main text highlights our primary findings.
2. Our more detailed analysis has identified two cells in the Super Intermediate Protocerebrum (SIP) regions that co-express Crz and SIFaR24F06, along with OL cells (Figure 6D-E).
3. To provide a complete view of the signaling dynamics, we have included GCaMP data from the brain region in the main figure (Figure 6P-R and Supplementary Figure S6N-P).
4. Through GCaMP calcium imaging to assess SIFa-to-Crz signaling, we found that calcium levels in Crz+/SIFaR+ SIP neurons consistently decreased with SIFa activation (Figure 6P-R). Conversely, calcium signals in Crz+/SIFaR+ OL neurons increased with SIFa activation, mirroring the pattern seen in Crz+ AG neurons in the VNC (Figure 6M-O and Supplementary Figure S6N-P).

5. A synthesis of these results is presented in Figure 6S, and we have elaborated on these findings in the manuscript with a detailed description, as detailed below. "To elucidate the direct response of Crz neurons to the activity of SIFa neurons, we conducted live calcium (Ca2+) imaging in the Super Intermediate Protocererbrum (SIP), OL and AG region of the VNC, where Crz neurons are situated (Fig. 6D, Fig. S6M). Upon optogenetic stimulation of SIFa neurons, we observed a significant increase in the activity of Crz in OL and AG region (Fig. 6L-O, Fig. S6N-P), evidenced by a sustained elevation in intracellular Ca2+ levels that persisted in a high level before gradually declining to baseline levels, where the cells in top region of the SIP exhibit consistently drop down after stimulated the SIFa neurons (Fig. 6P-R). These calcium level changes were in contrast to the control group (without all-trans retinal, ATR) (Fig. 6L-R, Fig. S6N-P). These findings confirm that Crz neurons in OL and AG are activated in response to SIFa neuronal activity, but the activity of Crz neurons in SIP are inhibited by the activition of SIFa neuron, reinforcing their role as postsynaptic effectors in the neural circuitry governed by SIFa neurons. Moreover, these results provide empirical support for the hypothesis that SIFa-SIFaR/Crz-CrzR long-range neuropeptide relay underlies the neuronal activity-based measurement of interval timing."

   We are truly grateful for the reviewer's perceptive recommendations concerning the possible mechanisms of LMD and SMD behaviors. In light of this constructive feedback, we have enhanced our discussion to encompass a theoretical framework on the potential role of neuropeptide relays in mediating context-dependent adjustments of synaptic plasticity and calcium signaling within specific neuronal populations. This supplementary perspective is designed to elucidate the intricate dynamics involved, as further elaborated in the updated manuscript.

"Employing two distinct yet comparable models of interval timing behavior, LMD and SMD, we demonstrated that differential SIFa to SIFaR signaling is capable of modulating context-dependent behavioral responses. Synaptic strengths between SIFa and SIFaR neurons was notably enhanced in group-reared naive males. However, these synaptic strengths specifically diminished in the OL, CB, and AG when males were singly reared, with a particular decrease in the AG region when males were sexually experienced (Fig. 4A-J). Intriguingly, overall calcium signaling within SIFaR24F06 neurons was significantly reduced in group-reared naive males, yet these signals surged dramatically in the OL with social isolation and in the AG with sexual experience (Fig. 4K-T). These calcium signals, as reported by the transcriptional calcium reporter CaLexA, were corroborated by GCaMP live imaging in both the AG and OL regions (Fig. 6L-O and Fig. S6N-P), indicating a close association between elevated calcium levels and LMD and SMD behaviors. The modulation of context-dependent synaptic plasticity and calcium dynamics by the SIFa neuropeptide through a single SIFaR receptor raises the question of how a single receptor can elicit such diverse responses. Recent neuroscientific studies in Drosophila have shown that individual neurons can produce multiple neurotransmitters and that neuropeptides are often colocalized with small molecule neurotransmitters (Nässel 2018,Deng 2019,Croset 2018,Kondo 2020). Consistent with this, we have previously reported that SIFa neurons utilize a variety of neurotransmitters, including glutamate, dopamine, and tyramine (Kim 2024). Therefore, we propose that the SIFa-SIFaR-Crz-CrzR neuropeptidergic relay circuitry may interact with different neurotransmitters in distinct neuronal subpopulations to regulate context-dependent behaviors. Supporting this hypothesis, glutamate, known to function as an inhibitory neurotransmitter in the olfactory pathway of Drosophila (Liu 2013), may be one such candidate. We speculate that neuropeptide cotransmission could underlie the mechanisms facilitating these complex, context-dependent behavioral patterns. Further research is warranted to elucidate how such cotransmission contributes to the intricate behavioral repertoire of the fly."

• *

Comment 2. Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? The authors should qualify certain claims as preliminary or speculative. Specifically, the proposed SIFa-SIFaR/Crz-CrzR neuropeptide relay pathway is only investigated via imaging approach. More experiments using behavioral tests are needed to confirm that Crz relays the SIFa signaling pathway. For example, Crz-Gal4>UAS-SIFaR RNAi should be done to show that SIFaR+ Crz+ cells are necessary for LMD and SMD.

   __Answer:__ We are grateful for the reviewer's constructive suggestion regarding the need to provide additional behavioral assays using RNAi knockdown to substantiate the SIFa-SIFaR/Crz-CrzR neuropeptide relay. Following the reviewer's advice, we have conducted experiments involving SIFaR24F06/Crz-RNAi and Crz-GAL4/SIFaR-RNAi. The outcomes of these experiments have been detailed and are now presented in a clear and comprehensive manner.

   To further aid in the understanding of our results, we have also included a summary diagram in Figure 6S, which illustrates the key findings from these assays. This visual representation is intended to provide a concise overview of the data and to highlight the significance of the SIFa-SIFaR/Crz-CrzR neuropeptide relay in the context of our study.

Comment 3.* Would additional experiments be essential to support the claims of the paper? Yes, additional experiments are essential. Detailed molecular and imaging studies are needed to support claims about synaptic reorganization. For example: ○ More controls are needed for RNAi and Gal80ts experiments, such as Gal4-only control, RNAi-only control, etc. *

   __Answer:__ We sincerely appreciate the reviewer's critical feedback regarding the genetic controls in our study. We acknowledge the importance of this aspect and wish to clarify that we have indeed conducted a substantial number of genetic control experiments for both LMD and SMD behaviors. It is worth noting that much of this data has been previously published in other works. Recognizing the interest from another reviewer on the same topic, we have chosen to reiterate our response here for clarity and convenience. Our comprehensive approach to genetic controls ensures the robustness of our findings, and we believe that the published data further substantiates the reliability of our experimental procedures.

   We sincerely thank the reviewer for insightful comments regarding the absence of traditional genetic controls in our study of LMD and SMD behaviors. We acknowledge the importance of such controls and wish to clarify our rationale for not including them in the current investigation. The primary reason for not incorporating all genetic control lines is that we have previously assessed the LMD and SMD behaviors of GAL4/+ and UAS/+ strains in our earlier studies. Our past experiences have consistently shown that 100% of the genetic control flies for both GAL4 and UAS exhibit normal LMD and SMD behaviors. Given these findings, we deemed the inclusion of additional genetic controls to be non-essential for the present study, particularly in the context of extensive screening efforts. However, in accordance with the reviewer's recommendation, we conducted genetic validation experiments on novel genetic crosses, including SIFaR-RNAi/+, CrzR-RNAi/+, and GAL4NP5270/+, and incorporated the results in the supplementary figures (Supplementary information 1). We have made the necessary modifications and additions to the manuscript as below.

"Given those genetic controls, as evidenced by consistent exhibition of normal LMD and SMD behaviors (Supplemental information 1), the observed reduction in SIFaR expression, driven by elavc155, is deemed sufficient to induce significant disruptions in LMD and SMD behaviors."

We understand the value of providing a clear rationale for our methodology choices. To this end, we have added a detailed explanation in the "MATERIALS AND METHODS" section and the figure legends of Figure 1. This clarification aims to assist readers in understanding our decision to omit traditional controls, as outlined below.

"__Mating Duration Assays for Successful Copulation__The mating duration assay in this study has been reported (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023). To enhance the efficiency of the mating duration assay, we utilized the Df(1)Exel6234 (DF here after) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR) (Parks et al. 2004; Yapici et al. 2008). Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males (Yapici et al. 2008). We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For group reared (naïve) males, 40 males from the same strain were placed into a vial with food for 5 days. For single reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. 40 DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for mating duration assays. At the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO2. After placing a single female into the mating chamber, we inserted a transparent film then placed a single male to the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25℃ incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 sec, and total mating duration was calculated for each couple. Genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023; Huang et al. 2024; Zhang et al. 2024). Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test."

*○ Using synaptic markers and high-resolution imaging to observe synaptic changes directly. *

   __Answer:__ We sincerely appreciate the reviewer's constructive suggestion to provide high-resolution imaging for a more direct observation of synaptic changes. While we have already included high-resolution imaging data showcasing postsynaptic and presynaptic alterations using Denmark and syt.eGFP (Figure S3), GRASP (Figure 3A-D), and tGRASP (Figure 4A-J), we recognize the value of further elucidation. Consequently, we have conducted additional experiments to examine the presynaptic changes in SIFaR24F06 neurons under varying social contexts, as presented in Figure 5A-G. We are confident that the comprehensive dataset we have now provided, which includes these new findings, will not only address the reviewer's concerns but also effectively convey to the readers the dynamic and critical nature of SIFa-SIFaR synaptic changes in modulating interval timing behaviors.

*○ Electrophysiological recordings from neurons expressing SIFa and SIFaR to analyze their functional connectivity and activity patterns. *

   __Answer:__ We sincerely appreciate the reviewer's constructive suggestions regarding the inclusion of electrophysiological recordings from neurons expressing SIFa and SIFaR to analyze functional connectivity and activity patterns. In response to this valuable feedback, we have conducted *in vivo* calcium imaging using the GCaMP indicator. The results have been incorporated into our manuscript, demonstrating SIFa-SIFaR connectivity and alterations in activity patterns (Figure 5H-L), as well as SIFa-Crz connectivity and changes in activity patterns (Figure 6 and Figure S6). We are confident that these additional data provide compelling evidence supporting the notion that the SIFa-SIFaR/Crz-CrzR neuropeptide relay circuits are robustly interconnected and exhibit activity changes in concert with the observed neuronal modifications.

• *

Comment 4.* Are the suggested experiments realistic in terms of time and resources? The suggested experiments are realistic but will require considerable time and resources. Detailed molecular interaction studies, imaging synaptic plasticity, and electrophysiological recordings could take several months to over a year, depending on the complexity and availability of necessary equipment and expertise. The cost would be moderate to high, involving expenses for reagents, imaging equipment, and animal husbandry for maintaining Drosophila stocks. *

* * Answer: We are grateful for the reviewers' understanding and support for our additional analysis in the revision experiments. While we have already conducted a multitude of experiments pertinent to this manuscript, we are well-positioned to provide a comprehensive revision of the data within a relatively short timeframe.

Comment 5. Are the data and the methods presented in such a way that they can be reproduced? The methods are generally described in detail, allowing for potential reproducibility. However, more precise documentation of certain experimental conditions, such as the timing and conditions of RNAi induction and temperature controls, is necessary. The methods about imaging analysis are too detailed. The exact steps about how to use ImageJ should be removed.

* * Answer: We sincerely appreciate the reviewer's meticulous comments regarding the omission of certain methodological details in our manuscript. In response, we have now included a detailed description of the temperature control procedures for conditional RNAi induction in the "Fly Stocks and Husbandry" section, as detailed below.

"For temperature-controlled experiments, including those utilizing the temperature-sensitive tub-GAL80ts driver, the flies were initially crossed and maintained at a constant temperature of 22℃ within an incubator. The temperature shift was initiated post-eclosion. Once the flies had emerged, they were transferred to an incubator set at an elevated temperature of 29℃ for a defined period, after which the experimental protocols were carried out. Wild-type flies were Canton-S (CS)."

   We appreciate the reviewer's guidance on refining our manuscript. In response to the suggestion, we have streamlined the image analysis methods section, removing excessive details to present the information in a more concise and clear manner as below.

"Quantitative analysis of fluorescence intensity

To ascertain calcium levels and synaptic intensity from microscopic images, we dissected and imaged five-day-old flies of various social conditions and genotypes under uniform conditions. The GFP signal in the brains and VNCs was amplified through immunostaining with chicken anti-GFP primary antibody. Image analysis was conducted using ImageJ software. For the quantification of fluorescence intensities, an investigator, blinded to the fly's genotype, thresholded the sum of all pixel intensities within a sub-stack to optimize the signal-to-noise ratio, following established methods (Feinberg 2008). The total fluorescent area or region of interest (ROI) was then quantified using ImageJ, as previously reported. For CaLexA signal quantification, we adhered to protocols detailed by Kayser et al. (Kayser et al, 2014), which involve measuring the ROI's GFP-labeled area by summing pixel values across the image stack. This method assumes that changes in the GFP-labeled area are indicative of alterations in the CaLexA signal, reflecting synaptic activity. ROI intensities were background-corrected by measuring and subtracting the fluorescent intensity from a non-specific adjacent area, as per Kayser et al. (Kayser et al, 2014). For the analysis of GRASP or tGRASP signals, a sub-stack encompassing all synaptic puncta was thresholded by a genotype-blinded investigator to achieve the optimal signal-to-noise ratio. The fluorescence area or ROI for each region was quantified using ImageJ, employing a similar approach to that used for CaLexA quantification (Feinberg 2008)."

Comment 6. Are the experiments adequately replicated and statistical analysis adequate? Most figures in the manuscript need to be re-plotted. The right y-axis "Difference between means" is not necessary, if not confusing. The image panels are too small to see, while the quantification of overlapping cells are unnecessarily large. The figures are too crowded with labels and texts, which makes it extremely difficult to comprehend the data.

   __Answer:__ We appreciate the reviewer's suggestion to refine our figures, and we have indeed reformatted them to provide clearer presentation and improved readability. Regarding the removal of dot blot membranes (DBMs), we have given this considerable thought. While we understand the recommendation, we have chosen to retain the DBMs in our manuscript. Our decision is based on the fact that our analysis encompasses not only traditional t-tests but also incorporates estimation statistics, which have been demonstrated to be effective for biological data analysis (Claridge-Chang & Assam, 2016). The inclusion of DBMs is essential for the accurate interpretation of these estimation statistics, ensuring a comprehensive representation of our findings.

Minor Comments Comment 7. Specific experimental issues that are easily addressable. Clarify the timing of RNAi induction and provide more detailed figure legends for better understanding and reproducibility.

   __Answer:__ We sincerely appreciate the reviewer's suggestion aimed at enhancing our manuscript. As previously addressed in our response to __*Comment 5*__, we have incorporated additional details regarding the timing of RNAi induction within the Methods section. Furthermore, we have expanded upon the figure legends to provide a clearer understanding of our findings, ensuring that the content is accessible to a broader readership.

* Comment 8. Are prior studies referenced appropriately? Yes. *

__ Answer:__ We are grateful for the reviewer's acknowledgment that our references have been appropriately included and integrated into the manuscript.

* Comment 9. Are the text and figures clear and accurate? The text is generally clear, but the figures need re-work. See comment above. *

• *Answer: We appreciate the feedback from the reviewers regarding the clarity of our figures. In response to other reviewers' concerns about the figures appearing too crowded, we have carefully revised the layout of all figures to ensure they are more spacious and aesthetically improved for better readability and visual appeal.

* Comment 10. Suggestions to improve the presentation of data and conclusions. Use smaller fonts in the bar plots and make the plots smaller. Enlarge the imaging panels and let the pictures tell the story. *

* * Answer: We sincerely appreciate the reviewer's constructive suggestion. In response, we have revised the figures by enlarging the images and adjusting the font sizes in the bar plots to enhance readability and clarity.

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Kim WJ, Jan LY & Jan YN (2013) A PDF/NPF Neuropeptide Signaling Circuitry of Male Drosophila melanogaster Controls Rival-Induced Prolonged Mating. Neuron 80: 1190–1205

Kim WJ, Song Y, Zhang T, Zhang X, Ryu TH, Wong KC, Wu Z, Wei Y, Schweizer J, Nguyen K-NH, et al (2024) Peptidergic neurons with extensive branching orchestrate the internal states and energy balance of male Drosophila melanogaster. bioRxiv: 2024.06.04.597277

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Matell MS (2014) Neurobiology of Interval Timing. Adv Exp Med Biol: 209–234

Meck WH, Doyère V & Gruart A (2012) Interval Timing and Time-Based Decision Making. Frontiers Integr Neurosci 6: 13

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Referee #3

Evidence, reproducibility and clarity

Summary

The article investigates the role of the neuropeptide SIFa and its receptor SIFaR in regulating two distinct mating duration behaviors in male Drosophila melanogaster, Longer-Mating-Duration (LMD) and Shorter-Mating-Duration (SMD). The study reveals that SIFaR expression in specific neurons is required for both behaviors. It shows that social context and sexual experience lead to synaptic reorganization between SIFa and SIFaR neurons, altering internal brain states. The SIFa-SIFaR/Crz-CrzR neuropeptide relay pathway is essential for generating these behaviors, with Crz neurons responding to SIFa neuron activity. Furthermore, CrzR expression in non-neuronal cells is critical for regulating LMD and SMD behaviors. The study utilizes neuropeptide RNAi screening, chemoconnectome (CCT) knock-in, and genetic intersectional methods to elucidate these findings.

Major Comments

• Are the key conclusions convincing? The key conclusions are intriguing but require more robust data to be fully convincing. While the study presents compelling evidence for the involvement of SIFa and SIFaR in mating behaviors, additional experiments are needed to firmly establish the proposed mechanisms.
• Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? The authors should qualify certain claims as preliminary or speculative. Specifically, the proposed SIFa-SIFaR/Crz-CrzR neuropeptide relay pathway is only investigated via imaging approach. More experiments using behavioral tests are needed to confirm that Crz relays the SIFa signaling pathway. For example, Crz-Gal4>UAS-SIFaR RNAi should be done to show that SIFaR+ Crz+ cells are necessary for LMD and SMD.
• Would additional experiments be essential to support the claims of the paper? Yes, additional experiments are essential. Detailed molecular and imaging studies are needed to support claims about synaptic reorganization. For example:
  • More controls are needed for RNAi and Gal80ts experiments, such as Gal4-only control, RNAi-only control, etc.
  • Using synaptic markers and high-resolution imaging to observe synaptic changes directly.
  • Electrophysiological recordings from neurons expressing SIFa and SIFaR to analyze their functional connectivity and activity patterns.
• Are the suggested experiments realistic in terms of time and resources? The suggested experiments are realistic but will require considerable time and resources. Detailed molecular interaction studies, imaging synaptic plasticity, and electrophysiological recordings could take several months to over a year, depending on the complexity and availability of necessary equipment and expertise. The cost would be moderate to high, involving expenses for reagents, imaging equipment, and animal husbandry for maintaining Drosophila stocks.
• Are the data and the methods presented in such a way that they can be reproduced? The methods are generally described in detail, allowing for potential reproducibility. However, more precise documentation of certain experimental conditions, such as the timing and conditions of RNAi induction and temperature controls, is necessary. The methods about imaging analysis are too detailed. The exact steps about how to use ImageJ should be removed.
• Are the experiments adequately replicated and statistical analysis adequate? Most figures in the manuscript need to be re-plotted. The right y-axis "Difference between means" is not necessary, if not confusing. The image panels are too small to see, while the quantification of overlapping cells are unnecessarily large. The figures are too crowded with labels and texts, which makes it extremely difficult to comprehend the data.

Minor Comments

• Specific experimental issues that are easily addressable. Clarify the timing of RNAi induction and provide more detailed figure legends for better understanding and reproducibility.
• Are prior studies referenced appropriately? Yes.
• Are the text and figures clear and accurate? The text is generally clear, but the figures need re-work. See comment above.
• Suggestions to improve the presentation of data and conclusions. Use smaller fonts in the bar plots and make the plots smaller. Enlarge the imaging panels and let the pictures tell the story.

Significance

Nature and Significance of the Advance

This study aims to advance understanding of how neuropeptides modulate context-dependent behaviors in Drosophila. It provides novel insights into the role of SIFa and SIFaR in interval timing behaviors, contributing to the broader field of neuropeptide research and behavioral neuroscience. However, the significance of the findings is limited by the preliminary nature of some claims and the need for additional supporting data.

Context in Existing Literature

The work builds on previous studies that identified various roles of neuropeptides in behavior modulation but lacked detailed mechanistic insights. By elucidating the SIFa-SIFaR/Crz-CrzR pathway, this study attempts to fill a gap in the literature, but more robust evidence is required to solidify its contributions.

Interested Audience

The findings will interest neuroscientists, behavioral biologists, and researchers studying neuropeptides and their roles in behavior and neural circuitry. Additionally, this research may have implications for understanding neuropeptidergic systems in other organisms, making it relevant to a broader audience in the fields of neurobiology and physiology.

Field of Expertise

Keywords: Neuropeptides, Drosophila melanogaster, Behavioral Neuroscience. Areas without sufficient expertise: courtship behavior.

Recommendation

I recommend a major revision of this manuscript. The study presents intriguing findings, but several key claims are preliminary and require additional experiments for support. The data is poorly presented and the figures can be significantly improved. Detailed molecular and imaging studies, as well as more rigorous statistical analyses, are necessary to strengthen the conclusions. Addressing these concerns will significantly improve the robustness and impact of the paper.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #2

Evidence, reproducibility and clarity

Zhang et al., "Long-range neuropeptide relay as a central-peripheral communication mechanism for the context-dependent modulation of interval timing behaviors".

The authors investigate mating behavior in male fruit flies, Drosophila melanogaster, and test for a role of the SIFamide receptor (SIFaR) in this type of behavior, in particular mating duration in dependence of social isolation and prior mating experience. The anatomy of SIFamide-releasing neurons in comparison with SIFamide receptor-expressing neurons is characterized in a detail-rich manner. Isolating males or exposing them to mating experience modifies the anatomical organization of SIFamidergic axon termini projecting onto SIFamide receptor-expressing neurons. This structural synaptic plasticity is accompanied by changes in calcium influx. Lastly, it is shown that corazonin-releasing neurons are modulated by SIFamide releasing neurons and impact the duration of mating behavior.

Overall, this highly interesting study advances our knowledge about the behavioral roles of SIFamide, and contributes to an understanding how motivated behavior such as mating is orchestrated by modulatory peptides. The approach to take the entire organism, including peripheral tissue, into consideration, is very good and a rather unique point. The manuscript has only some points that are less convincing, and these should be addressed.

Major concerns:

• It is highly interesting that the duration of mating behavior is dependent on external and motivational factors. In fact, that provides an elegant way to study which neuronal mechanisms orchestrate these factors. However, it remains elusive why the authors link the differentially motivated durations of mating behavior to the psychological concept of interval timing. This distracts from the actually interesting neurobiology, and is not necessary to make the study interesting.
• In figure 4 A and 4K, fluorescence microscopy images of brains and ventral nerve chords are shown, one illustrating GRASP experiments, and one showing CaLexA experiments. The extreme difference between the differentially treated flies (bright fluorescence versus almost no fluorescence) is - in its drastic form- surprising. Online access to the original confocal microscopy images (raw data) might help to convince the reader that these illustrations do not reflect the most drastic "representative" examples out of a series of brain stainings.
• In particular for behavioral experiments, genetic controls should always be conducted. That is, both the heterozygous Gal4-line as well as the heterozygous UAS-line should be used as controls. This is laborious, but important.

Minor comments:

• Line 75: word missing ("...including FEEDING-RELATED BEHAVIOR, courtship, ...").
• Line 120: word missing ("SIFaR expression in adult neurons BUT not glia...").
• I find the figures often to be quite overloaded, and anatomical details often very small (e.g., figure 7A).

Significance

Overall, this highly interesting study advances our knowledge about the behavioral roles of SIFamide, and contributes to an understanding how motivated behavior is orchestrated by modulatory peptides. The approach to take the entire organism, including peripheral tissue, into consideration, is very good and a rather unique point.

Since decades it has been investigated how sensory stimuli are processed and encoded by the brain, and how behavioral actions are executed. Likewise, principles underlying learning and memory, sleep, orentation, circadian rhythms, etc. are subject to intense investigation. However, how motivational factors (sleep pressure, hunger, sexual drive) are actually "encoded", signaled and finally used to orchstrate behavior and guide decision-making is, to a very large degree, unknown - in any species. The model use here (Drosophila and its peptidergic system wit SIFamide as a central hub) represents actually a ideal entry point to study just this question. In this sense, the manuscript is at the forefront of modern, state-of-the-art neurobiology.