Good afternoon it shows that access to information is equal. It made me think about how some people have more opportunities to share or learn than others.

eLife Assessment

The authors collected time-course RNA-seq data from four tree species in natural environments and analyzed seasonal patterns of gene expression. This fundamental study substantially advances our understanding of how seasonal environments shape gene expression. The evolutionary effects of seasonal environments on gene expression are rarely studied at this scale and the dataset is extensive. The evidence supporting the conclusions is compelling, with caveats and limitations clearly described. The work will be of broad interest to colleagues studying evolution and gene expression.

Reviewer #2 (Public review):

This study investigates how seasonal environments shape the evolution of gene expression by analyzing two-year time-series transcriptomes from leaves and buds of four Fagaceae tree species. The revised manuscript incorporates additional data and analyses that directly address earlier concerns about sampling design and environmental variation, thereby strengthening the robustness of the conclusions.

The major strengths of this work are the scale and quality of the dataset, the integration of genome assemblies with time-series transcriptomics, and the careful analyses showing that winter bud expression is strongly conserved across species. The additional samples and re-analyses demonstrate convincingly that these results are not artifacts of sampling period or site differences. The study also links gene expression dynamics to phenological observations and frames its findings in relation to broader evolutionary concepts such as phenological synchrony and the developmental hourglass model.

Remaining limitations include the absence of direct mechanistic analyses of cis-regulatory and chromatin-level processes, the relatively coarse resolution of phenological trait measurements, and the weak association between seasonal expression divergence and sequence divergence. Importantly, these limitations are now explicitly acknowledged in the revised Discussion and framed as directions for future research.

Overall, the authors have substantially achieved their aims. This revised version represents a robust and convincing contribution that provides valuable data resources and conceptual insights into how seasonal environments constrain and shape gene expression. It will be of interest not only to evolutionary biologists and plant scientists, but also to researchers considering the broader role of environmental cycles in gene regulatory evolution.

Author response:

The following is the authors’ response to the original reviews

Public Reviews

Reviewer #1 (Public review):

Summary:

The authors performed genome assemblies for two Fagaceae species and collected transcriptome data from four natural tree species every month over two years. They identified seasonal gene expression patterns and further analyzed species-specific differences.

Strengths:

The study of gene expression patterns in natural environments, as opposed to controlled chambers, is gaining increasing attention. The authors collected RNA-seq data monthly for two years from four tree species and analyzed seasonal expression patterns. The data are novel. The authors could revise the manuscript to emphasize seasonal expression patterns in three species (with one additional species having more limited data). Furthermore, the chromosome-scale genome assemblies for the two Fagaceae species represent valuable resources, although the authors did not cite existing assemblies from closely related species.

Thank you for your careful assessment of our manuscript.

Weaknesses:

Comment; The study design has a fundamental flaw regarding the evaluation of genetic or evolutionary effects. As a basic principle in biology, phenotypes, including gene expression levels, are influenced by genetics, environmental factors, and their interaction. This principle is well-established in quantitative genetics.

In this study, the four species were sampled from three different sites (see Materials and Methods, lines 543-546), and additionally, two species were sampled from 2019-2021, while the other two were sampled from 2021-2023 (see Figure S2). This critical detail should be clearly described in the Results and Materials and Methods. Due to these variations in sampling sites and periods, environmental conditions are not uniform across species.

Even in studies conducted in natural environments, there are ways to design experiments that allow genetic effects to be evaluated. For example, by studying co-occurring species, or through transplant experiments, or in common gardens. To illustrate the issue, imagine an experiment where clones of a single species were sampled from three sites and two time periods, similar to the current design. RNA-seq analysis would likely detect differences that could qualitatively resemble those reported in this manuscript.

One example is in line 197, where genus-specific expression patterns are mentioned. While it may be true that the authors' conclusions (e.g., winter synchronization, phylogenetic constraints) reflect real biological trends, these conclusions are also predictable even without empirical data, and the current dataset does not provide quantitative support.

If the authors can present a valid method to disentangle genetic and environmental effects from their dataset, that would significantly strengthen the manuscript. However, I do not believe the current study design is suitable for this purpose.

Unless these issues are addressed, the use of the term "evolution" is inappropriate in this context. The title should be revised, and the result sections starting from "Peak months distribution..." should be either removed or fundamentally revised. The entire Discussion section, which is based on evolutionary interpretation, should be deleted in its current form.

If the authors still wish to explore genetic or evolutionary analyses, the pair of L. edulis and L. glaber, which were sampled at the same site and over the same period, might be used to analyze "seasonal gene expression divergence in relation to sequence divergence." Nevertheless, the manuscript would benefit from focusing on seasonal expression patterns without framing the study in evolutionary terms.

We sincerely thank the reviewer for the detailed and thoughtful comments. We fully recognize the importance of carefully distinguishing genetic and environmental contributions in transcriptomic studies, particularly when addressing evolutionary questions. The reviewer identified two major concerns regarding our study design: (1) the use of different monitoring periods across species, and (2) the use of samples collected from different study sites. We addressed both concerns with additional analyses using 112 new samples and now present new evidence that supports the robustness of our conclusions.

(1) Monitoring period variation does not bias our conclusions<br /> To address concerns about the differing monitoring periods, we added new RNA-seq data (42 samples each for bud and leaf samples for L. glaber and 14 samples each for bud and leaf samples for _L. eduli_s) collected from November 2021 to November 2022, enabling direct comparison across species within a consistent timeframe. Hierarchical clustering of this expanded dataset (Fig. S6) yielded results consistent with our original findings: winter-collected samples cluster together regardless of species identity. This strongly supports our conclusion that the seasonal synchrony observed in winter is not an artifact of the monitoring period and demonstrates the robustness of our conclusions across datasets.

(2) Site variation is limited and does not confound our findings<br /> Although the study included three sites, two of them (Imajuku and Ito Campus) are only 7.3 km apart, share nearly identical temperature profiles (see Fig. S2), and are located at the edge of similar evergreen broadleaf forests. Only Q. acuta was sampled from a higher-altitude, cooler site. To assess whether the higher elevation site of Q. acuta introduced confounding environmental effects, we reanalyzed the data after excluding this species. Hierarchical clustering still revealed that winter bud samples formed a distinct cluster regardless of species identity (Fig. S7), consistent with our original finding.

Furthermore, we recalculated the molecular phenology divergence index D (Fig. 4C) and the interspecific Pearson’s correlation coefficients (Fig. 5A) without including Q. acuta. These analyses produced results that were similar to those obtained from the full dataset (Fig. S12; Fig. S14), indicating that the observed patterns are not driven by environmental differences associated with elevation.

(3) Justification for our approach in natural systems<br /> We agree with the reviewer that experimental approaches such as common gardens, reciprocal transplants, and the use of co-occurring species are valuable for disentangling genetic and environmental effects. In fact, we have previously implemented such designs in studies using the perennial herb Arabidopsis halleri (Komoto et al., 2022, https://doi.org/10.1111/pce.14716) and clonal Someiyoshino cherry trees (Miyawaki-Kuwakado et al., 2024, https://doi.org/10.1002/ppp3.10548) to examine environmental effects on gene expression. However, extending these approaches to long-lived tree species in diverse natural ecosystems poses significant logistical and biological challenges. In this study, we addressed this limitation by including three co-occurring species at the same site, which allowed us to evaluate interspecific differences under comparable environmental conditions. Importantly, even when we limited our analyses to these co-occurring species, the results remained consistent, indicating that the observed variation in transcriptomic profiles cannot be attributed to environmental factors alone and likely reflects underlying genetic influences.

Accordingly, we added four new figures (Fig. S6, Fig. S7, Fig. S12 and Fig. S14) and revised the manuscript to clarify the limitations and strengths of our design, to tone down the evolutionary claims where appropriate, and to more explicitly define the scope of our conclusions in light of the data. We hope that these efforts sufficiently address the reviewer’s concerns and strengthen the manuscript.

To better support the seasonal expression analysis, the early RNA-seq analysis sections should be strengthened. There is little discussion of biological replicate variation or variation among branches of the same individual. These could be important factors to analyze. In line 137, the mapping rate for two species is mentioned, but the rates for each species should be clearly reported. One RNA-seq dataset is based on a species different from the reference genome, so a lower mapping rate is expected. While this likely does not hinder downstream analysis, quantification is important.

We thank the reviewer 1 for the helpful comment. To evaluate the variation among biological replicates, we compared the expression level of each gene across different individuals. We observed high correlation between each pair of individuals (Q. glauca (n=3): an average correlation coefficient r = 0.947; Q. acuta (n=3): r = 0.948; L. glaber (n=3): r = 0.948)). This result suggests that the seasonal gene expression pattern is highly synchronized across individuals within the same species. We mentioned this point in the Result section in the revised manuscript. We also calculated the mean mapping rates for each species. As the reviewer expected, the mapping rate was slightly lower in Q. acuta (88.6 ± 2.3%) and L. glaber (84.3 ± 5.4%), whose RNA-Seq data were mapped to reference genomes of related but different species, compared to that in Q. glauca (92.6 ± 2.2%) and L. edulis (89.3 ± 2.7%). However, we minimized the impact of these differences on downstream analysis. These details have been included in the revised main text.

In Figures 2A and 2B, clustering is used to support several points discussed in the Results section (e.g., lines 175-177). However, clustering is primarily a visualization method or a hypothesis-generating tool; it cannot serve as a statistical test. Stronger conclusions would require further statistical testing.

We thank the reviewer for the helpful comment. As noted, we acknowledge that hierarchical clustering (Fig. 2A) is primarily a visualization and hypothesis-generating method. To assess the biological relevance of the clusters identified, we conducted a Mann-Whitney U test or the Steel-Dwass test to evaluate whether the environmental temperatures at the time of sample collection differed significantly among the clusters. This analysis (Fig. 2B) revealed statistically significant differences in temperature in the cluster B3 (p < 0.01), indicating that the gene expression clusters are associated with seasonal thermal variation. These results support the interpretation that the clusters reflect coordinated transcriptional responses to environmental temperature. We revised the Results section to clarify this point.

The quality of the genome assemblies appears adequate, but related assemblies should be cited and discussed. Several assemblies of Fagaceae species already exist, including Quercus mongolica (Ai et al., Mol Ecol Res, 2022), Q. gilva (Front Plant Sci, 2022), and Fagus sylvatica (GigaScience, 2018), among others. Is there any novelty here? Can you compare your results with these existing assemblies?

We agree that genome assemblies of Fagaceae species are becoming increasing available. However, our study does not aim to emphasize the novelty of the genome assemblies per se. Rather, with the increasing availability of chromosome-level genomes, we regard genome assembly as a necessary foundation for more advanced analyses. The main objective of our study is to investigate how each gene is expressed in response to seasonal environmental changes, and to link genome information with seasonal transcriptomic dynamics. To address the reviewer’s comment in line with this objective, we added a discussion on the syntenic structure of eight genome assemblies spanning four genera within the Fagaceae, including a species from the genus Fagus (Ikezaki et al. 2025, https://doi.org/10.1101/2025.07.31.667835). This addition helps to position our work more clearly within the context of existing genomic resources.

Most importantly, Figure 1B-D shows synteny between the two genera but also indicates homology between different chromosomes. Does this suggest paleopolyploidy or another novel feature? These chromosome connections should be interpreted in the main text-even if they could be methodological artifacts.

A previous study on genome size variation in Fagaceae suggested that, given the consistent ploidy level across the family, genome expansion likely occurred through relatively small segmental duplications rather than whole-genome duplications. Because Figure 1B-D supports this view, we cited the following reference in the revised version of the manuscript. Chen et al. (2014) https://doi.org/10.1007/s11295-014-0736-y

In both the Results and Materials and Methods sections, descriptions of genome and RNA-seq data are unclear. In line 128, a paragraph on genome assembly suddenly introduces expression levels. RNA-seq data should be described before this. Similarly, in line 238, the sentence "we assembled high-quality reference genomes" seems disconnected from the surrounding discussion of expression studies. In line 632, Illumina short-read DNA sequencing is mentioned, but it's unclear how these data were used.

We relocated the explanation regarding the expression levels of single-copy and multi-copy genes to the section titled “Seasonal gene expression dynamics.” Additionally, we clarified in the Materials and Methods section that short-read sequencing data were used for both genome size estimation and phylogenetic reconstruction.

Reviewer #2 (Public review):

Summary:

This study explores how gene expression evolves in response to seasonal environments, using four evergreen Fagaceae species growing in similar habitats in Japan. By combining chromosome-scale genome assemblies with a two-year RNA-seq time series in leaves and buds, the authors identify seasonal rhythms in gene expression and examine both conserved and divergent patterns. A central result is that winter bud expression is highly conserved across species, likely due to shared physiological demands under cold conditions. One of the intriguing implications of this study is that seasonal cycles might play a role similar to ontogenetic stages in animals. The authors touch on this by comparing their findings to the developmental hourglass model, and indeed, the recurrence of phenological states such as winter dormancy may act as a cyclic form of developmental canalization, shaping expression evolution in a way analogous to embryogenesis in animals.

Strengths:

(1) The evolutionary effects of seasonal environments on gene expression are rarely studied at this scale. This paper fills that gap.

(2) The dataset is extensive, covering two years, two tissues, and four tree species, and is well suited to the questions being asked.

(3) Transcriptome clustering across species (Figure 2) shows strong grouping by season and tissue rather than species, suggesting that the authors effectively controlled for technical confounders such as batch effects and mapping bias.

(4) The idea that winter imposes a shared constraint on gene expression, especially in buds, is well argued and supported by the data.

(5) The discussion links the findings to known concepts like phenological synchrony and the developmental hourglass model, which helps frame the results.

We are grateful for the reviewer for the detailed and thoughtful review of our manuscript.

Weaknesses:

(1) While the hierarchical clustering shown in Figure 2A largely supports separation by tissue type and season, one issue worth noting is that some leaf samples appear to cluster closely with bud samples. The authors do not comment on this pattern, which raises questions about possible biological overlap between tissues during certain seasonal transitions or technical artifacts such as sample contamination. Clarifying this point would improve confidence in the interpretation of tissue-specific seasonal expression patterns.

Leaf samples clustered into the bud are newly flushed leaves collected in April for Q. glauca, May for Q. acuta, May and June for L. edulis, and August and September for L. glaber. To clarify this point, we highlighted these newly flushed leaf samples as asterisk in the revised figure (Fig. 2A).

(2) While the study provides compelling evidence of conserved and divergent seasonal gene expression, it does not directly examine the role of cis-regulatory elements or chromatin-level regulatory architecture. Including regulatory genomic or epigenomic data would considerably strengthen the mechanistic understanding of expression divergence.

We thank the reviewer for this insightful comment. As noted in the Discussion section, we hypothesize that such genome-wide seasonal expression patterns—and their divergence across species—are likely mediated by cis-regulatory elements and chromatin-level mechanisms. While a direct investigation of regulatory architecture was beyond the scope of the present study, we fully agree that incorporating regulatory genomic and epigenomic data would significantly deepen the mechanistic understanding of expression divergence. In this regard, we are currently working to identify putative cis-regulatory elements in non-coding regions and are collecting epigenetic data from the same tree species using ChIP-seq. We believe the current study provide a foundation for these future investigations into the regulatory basis of seasonal transcriptome variation. We made a minor revision to the Discussion to note that an important future direction is to investigate the evolution of non-coding sequences that regulate gene expression in response to seasonal environmental changes.

(3) The manuscript includes a thoughtful analysis of flowering-related genes and seasonal GO enrichment (e.g., Figure 3C-D), providing an initial link between gene expression timing and phenological functions. However, the analysis remains largely gene-centric, and the study does not incorporate direct measurements of phenological traits (e.g., flowering or bud break dates). As a result, the connection between molecular divergence and phenotypic variation, while suggestive, remains indirect.

We would like to note that phenological traits have been observed in the field on a monthly basis throughout the sampling period and the phenological data were plotted together with molecular phenology (e.g. Fig. 2A, C; Fig. 3C, D). Although the temporal resolution is limited, these observations captured species-specific differences in key phenological events such as leaf flushing and flowering times. We revised the manuscript to clarify this point.

(4) Although species were sampled from similar habitats, one species (Q. acuta) was collected at a higher elevation, and factors such as microclimate or local photoperiod conditions could influence expression patterns. These potential confounding variables are not fully accounted for, and their effects should be more thoroughly discussed or controlled in future analyses.

We fully agree with the reviewer that local environmental conditions, including microclimate and photoperiod differences, could potentially influence gene expression patterns. To assess whether the higher elevation site of Q. acuta introduced confounding environmental effects, we reanalyzed the data after excluding this species. Hierarchical clustering still revealed that winter bud samples formed a distinct cluster regardless of species identity (Fig. S7), consistent with our original finding.

Furthermore, we recalculated the molecular phenology divergence index D (Fig. 4C) and the interspecific Pearson’s correlation coefficients (Fig. 5A) without including Q. acuta. These analyses produced results that were qualitatively similar to those obtained from the full dataset (Fig. S12; Fig. S14), indicating that the observed patterns are not driven by environmental differences associated with elevation.

We believe these additional analyses help to decouple the effects of environment and genetics, and support our conclusion that both seasonal synchrony and phylogenetic constraints play key roles in shaping transcriptome dynamics. We added four new figures (Fig. S6, Fig. S7, Fig. S12 and Fig. S14) and revised the text accordingly to clarify this point and to acknowledge the potential impact of site-specific environmental variation.

(5) Statistical and Interpretive Concerns Regarding Δφ and dN/dS Correlation (Figures 5E and 5F):

a) Statistical Inappropriateness: Δφ is a discrete ordinal variable (likely 1-11), making it unsuitable for Pearson correlation, which assumes continuous, normally distributed variables. This undermines the statistical validity of the analysis.

We thank the reviewer for the insightful comment. We would like to clarify that the analysis presented in Figures 5E and 5F was based on linear regression, not Pearson’s correlation. Although Δ_φ_ is a discrete variable, it takes values from 0 to 6 in 0.5 increments, resulting in 13 levels. We treated it as a quasi-continuous variable for the purposes of linear regression analysis. This approach is commonly adopted in practice when a discrete variable has sufficient resolution and ordering to approximate continuity. To enhance clarity, we revised the manuscript to explicitly state that linear regression was used, and we now reported the regression coefficient and associated p-value to support the interpretation of the observed trend.

b) Biological Interpretability: Even with the substantial statistical power afforded by genome-wide analysis, the observed correlations are extremely weak. This suggests that the relationship, if any, between temporal divergence in expression and protein-coding evolution is negligible.

Taken together, these issues weaken the case for any biologically meaningful association between Δφ and dN/dS. I recommend either omitting these panels or clearly reframing them as exploratory and statistically limited observations.

We agree with the reviewer’s comment. While we retained the original panels, we reframed our interpretation to emphasize that, despite statistical significance, the observed correlation is very weak—suggesting that coding region variation is unlikely to be the primary driver of seasonal gene expression patterns. Accordingly, we revised the “Relating seasonal gene expression divergence to sequence divergence” section in the Results, as well as the relevant part of the Discussion.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Sentences around lines 250-251 are incomplete and need revision.

We thank the reviewer for pointing this out. We revised the sentences in the subsection “Peak month distribution of rhythmic genes and intra-genus and inter-genera comparison” in the Results section to ensure clarity and completeness. In addition, to improve the interpretability of the peak month distribution, we added arrows to indicate the major peaks in the circular histograms shown in Fig. 3C and 3D.

Reviewer #2 (Recommendations for the authors):

(1) In Figure 1E-G, the term Copy number or Copy number variation could be misleading, as it is commonly associated with inter-individual gene copy number variation in a population. Since the analysis here refers to orthology relationships rather than population-level variation, a more precise term, such as orthogroup classification, may be preferable.

We thank the reviewer for this helpful suggestion. We agree that the term “copy number” could be misleading in this context. Accordingly, we updated the labeling in Fig. 1 to reflect the more precise term “orthogroup classification.”

(2) In Figure 3A, the x-axis label Period (month) may be misleading, as it could be mistaken for calendar months rather than referring to the periodicity of gene expression cycles. A more explicit label, such as Expression periodicity (months), might improve clarity for the reader.

We thank the reviewer for this valuable suggestion. In the original version of Fig. 3A, we used the label “Period (month),” which could indeed be misinterpreted as referring to calendar months. To clarify that this axis represents the length of gene expression cycles, we revised the label to “Period length (months).” This change also aligns with the terminology used throughout the manuscript, where “Period” refers specifically to cycle length, and “Periodicity” denotes the presence or absence of rhythmic expression.

Other minor revisions

We also made minor revisions for the reference list and the grant number details, and included the accession numbers for all DNA and RNA sequence data deposited in the DNA Data Bank of Japan (DDBJ) in the Data deposition and code availability section, in addition to the BioProject ID.

The cherry picking and warping of data is such a big issue, because you can never be sure what the motive behind it is, and just how truthful the stats are. Context is so important to truly understanding facts.

Contradiction is the source of knew discovery, and pushes us to continue to search for answers and the truth, and examine all possibilities.

This is so important to me, and drives most of my academic pursuits as a double major in Physics and Philosophy. The philosophical side of things can sometimes be the most informative.

The basis of all discovery is first asking questions and challenging what is already known, continuing to dig deeper into things, even if they are already known.

U osób z ADHD Theta może "przesówać się" i być mierzona w zakresie "Alpha"

components of works cited entry

Torre Pacheco, Asalto al Capitolio, Portugal Lula de Silva. Milei is famously anarcho-capitalist. Alt right is presenting itself as anti-bureaucracy, anti-state.

Does it?

Popular examples/representation of extended family: Modern Family Full House Tia and Tamera Raven's Home Friends and Greys Anatomy (show family that isn't necessarily blood related) Home Alone Charlie and the Chocolate Factory Harry Potter Two and a Half Men

I would say this is a concise, effective definition of extended family.

I don't really watch any of these shows, but ** I think ** this is the only one that shows more downsides to extended family

While I've only seen clips, I find this family to be the most relatable and similar to mine, I think it's good representation personally

Some benefits of extended family: connection with family, greater financial security, increased sharing of family values, and more role models for younger family members

I didn't think of this factor, I probably would relate to it more if I wasn't so young when it happened

Some reasons for extended family to be prominent or important: Cultural, economic, health, divorce

You'd find extended families to be more common with people of color in America, backed up by a lot of sources I've found but didn't necessarily choose to use.

One role of extended family is the ** head of the household. ** Can be determined by age (who is the oldest/most senior), who contributes most significant finances ("breadwinner"), or who's home it is/was initially.

I don't think I'd personally count close friends and/or close co-workers but everyone is different.

Every family looks different. But typically, extended family is made up of one married couple per generation.

can include grandparents, great-grandparents, aunts, uncles, cousins, nieces, nephews, in laws, etc.

What kind of responsibilities do extended families take on? Does it vary between families?

Both of these questions are answered in the text.

One example of extended families' responsibilities is providing financial aid. extended family and their roles do vary with each family.

Summary: Extended family involves additional relatives aside from the core nuclear family (parents and their children) that live with or close by who might take on parent-like roles or shared responsibilities. Typically includes relatives like grandparents, aunts, uncles, cousins, etc. The key characteristic of extended family is that there are multiple adults that aren't the parents of the children

Technology made it easier for family members who live farther away to keep close ties and contribute to the family

This source will help define what exactly extended family is and which members to consider when evaluating their effects on children's well-being

1st

eLife Assessment

The authors used comprehensive approaches to identify Gyc76C as an ITPa receptor in Drosophila. They revealed that ITPa acts via Gyc76C in the renal tubules and fat body to modulate osmotic and metabolic homeostasis. The designed experiments, data, and analyses convincingly support the main claims. The findings are important to help us better understand how ITP signals contributes to systemic homeostasis regulation.

Reviewer #1 (Public review):

Summary:

In Drosophila melanogaster, ITP has functions in feeding, drinking, metabolism, excretion, and circadian rhythm. In the current study, the authors characterized and compared the expression of all three ITP isoforms (ITPa and ITPL1&2) in the CNS and peripheral tissues of Drosophila. An important finding is that they functionally characterized and identified Gyc76C as an ITPa receptor in Drosophila using both in vitro and in vivo approaches. In vitro, the authors nicely confirmed that the inhibitory function of recombinant Drosophila ITPa on MT secretion is Gyc76C-dependent (knockdown of Gyc76C specifically in two types of cells abolished the anti-diuretic action of Drosophila ITPa on renal tubules). They also confirmed that ITPa activates Gyc76C in a heterologous system. The authors used a combination of multiple approaches to investigate the roles of ITPa and Gyc76C on osmotic and metabolic homeostasis modulation in vivo. They revealed that ITPa signaling to renal tubules and fat body modulates osmotic and metabolic homeostasis via Gyc76C.

Furthermore, they tried to identify the upstream and downstream of ITP neurons in the nervous system by using connectomics and single-cell transcriptomic analysis. I found this interesting manuscript to be well-written and described. The findings in this study are valuable to help understand how ITP signals work on systemic homeostasis regulation. Both anatomical and single-cell transcriptome analysis here should be useful to many in the field.

Strengths:

The question (what receptors of ITPa in Drosophila) that this study tries to address is important. The authors ruled out the Bombyx ITPa receptor orthologs as potential candidates. They identified a novel ITP receptor by using phylogenetic, anatomical analysis, and both in vitro and in vivo approaches.

The authors exhibited detailed anatomical data of both ITP isoforms and Gyc76C (in the main and supplementary figures), which helped audiences understand the expression of the neurons studied in the manuscript.

They also performed connectomes and single-cell transcriptomics analyses to study the synaptic and peptidergic connectivity of ITP-expressing neurons. This provided more information for better understanding and further study of systemic homeostasis modulation.

Comments on revisions:

In the revised manuscript, the authors addressed all my concerns.

There is one more suggestion: The scale bar for fly and ovary images should be included in Figures 9, 10, and 12.

Reviewer #2 (Public review):

The physiology and behaviour of animals are regulated by a huge variety of neuropeptide signalling systems. In this paper, the authors focus on the neuropeptide ion transport peptide (ITP), which was first identified and named on account of its effects on the locust hindgut (Audsley et al. 1992). Using Drosophila as an experimental model, the authors have mapped the expression of three different isoforms of ITP, all of which are encoded by the same gene.

The authors then investigated candidate receptors for isoforms of ITP. Firstly, Drosophila orthologs of G-protein coupled receptors (GPCRs) that have been reported to act as receptors for ITPa or ITPL in the insect Bombyx mori were investigated. Importantly, the authors report that ITPa does not act as a ligand for the GPCRs TkR99D and PK2-R1. Therefore, the authors investigated other putative receptors for ITPs. Informed by a previously reported finding that ITP-type peptides cause an increase in cGMP levels in cells/tissues (Dircksen, 2009, Nagai et al., 2014), the authors investigated guanylyl cyclases as candidate receptors for ITPs. In particular, the authors suggest that Gyc76C may act as an ITP receptor in Drosophila. Evidence that Gyc76C may be involved in mediating effects of ITP in Bombyx was first reported by Nagai et al. (2014) and here the authors present further evidence, based on a proposed concordance in the phylogenetic distribution ITP-type neuropeptides and Gyc76C and experimental demonstration that ITPa causes dose-dependent stimulation of cGMP production in HEK cells expressing Gyc76C. Having performed detailed mapping of the expression of Gyc76C in Drosophila, the authors then investigated if Gyc76C knockdown affects the bioactivity of ITPa in Drosophila. The inhibitory effect of ITPa on leucokinin- and diuretic hormone-31-stimulated fluid secretion from Malpighian tubules was found to be abolished when expression of Gyc76C was knocked down in stellate cells and principal cells, respectively.

Having investigated the proposed mechanism of ITPa signalling in Drosophila, the authors then investigate its physiological roles at a systemic level. The authors present evidence that ITPa is released during desiccation and accordingly overexpression of ITPa increases survival when animals are subjected to desiccation. Furthermore, knockdown of Gyc76C in stellate or principal cells of Malphigian tubules decreases survival when animals are subject to desiccation. Furthermore, the relevance of the phenotypes observed to potential in vivo actions of ITPa is also explored and publicly available connectomic data and single-cell transcriptomic data are analysed to identify putative inputs and outputs of ITPa expressing neurons.

Strengths of this paper.

(1) The main strengths of this paper are:

i) the detailed analysis of the expression and actions of ITP and the phenotypic consequences of over-expression of ITPa in Drosophila.

ii). the detailed analysis of the expression of Gyc76C and the phenotypic consequences of knockdown of Gyc76C expression in Drosophila.

iii). the experimental demonstration that ITPa causes dose-dependent stimulation of cGMP production in HEK cells expressing Gyc76C, providing biochemical evidence that the effects of ITPa in Drosophila are, at least in part, mediated by Gyc76C.

(2) Furthermore, the paper is generally well written and the figures are of good quality.

Weaknesses of this paper.

A weakness of this paper is the phylogenetic analysis to investigate if there is correspondence in the phylogenetic distribution of ITP-type and Gyc76C-type genes/proteins. Unfortunately, the evidence presented is rather limited in scope. Essentially, the authors report that they only found ITP-type and Gyc76C-type genes/proteins in protostomes, but not in deuterostomes. What is needed is a more fine-grained analysis at the species level within the protostomes. However, I recognise that such a detailed analysis may extend beyond the scope of this paper, which is already rich in data.

Reviewer #3 (Public review):

Summary:

The goal of this paper is to characterize an anti-diuretic signaling system in insects using Drosophila melanogaster as a model. Specifically, the authors wished to characterize a role for ion transport peptide (ITP) and its isoforms in regulating diverse aspects of physiology and metabolism. The authors combined genetic and comparative genomic approaches with classical physiological techniques and biochemical assays to provide a comprehensive analysis of ITP and its role in regulating fluid balance and metabolic homeostasis in Drosophila. The authors further characterized a previously unrecognized role for Gyc76C as a receptor for ITPa, an amidated isoform of ITP, and in mediating the effects of ITPa on fluid balance and metabolism. The evidence presented in favor of this model is very strong as it combines multiple approaches and employs ideal controls. Taken together, these findings represent an important contribution to the field of insect neuropeptides and neurohormones and has strong relevance for other animals. The authors have addressed all weaknesses raised in my previous review.

Author Response:

The following is the authors’ response to the current reviews.

Reviewer #1 (Public review):

The scale bar for fly and ovary images should be included in Figures 9, 10, and 12.

We agree with this comment and apologize for the oversight. We have now modified Figures 9, 10, and 12 to include the scale bars for the ovary images. The fly images were acquired using a stereo microscope where scale bar calculation was not possible. However, all images were acquired at the same magnification for consistency.

Reviewer #2 (Public review):

A weakness of this paper is the phylogenetic analysis to investigate if there is correspondence in the phylogenetic distribution of ITP-type and Gyc76C-type genes/proteins. Unfortunately, the evidence presented is rather limited in scope. Essentially, the authors report that they only found ITP-type and Gyc76C-type genes/proteins in protostomes, but not in deuterostomes. What is needed is a more fine-grained analysis at the species level within the protostomes. However, I recognise that such a detailed analysis may extend beyond the scope of this paper, which is already rich in data.

We thank the reviewer for their comment and the suggestion to perform a fine-grained species level comparison of ITP and Gyc76C genes across protostomes. We are unsure of the utility of this analysis for the present study given that we have now shown that ITPa can activate Gyc76C using both an ex vivo and a heterologous assay, the latter being the gold standard in GPCR and guanylate cyclase discovery (see Huang et al 2025 https://doi.org/10.1073/pnas.2420966122; Beets et al 2023 https://doi.org/10.1016/j.celrep.2023.113058); Chang et al 2009 https://doi.org/10.1073/pnas.0812593106.

Additionally, absence of a gene in a genome/proteome is hard to prove especially when many/most of the protostomian datasets are not as high-quality as those of model systems (e.g. Drosophila melanogaster and Caenorhabditis elegans). Secondly, based on previous findings in Bombyx mori (Nagai et al. 2014 https://doi.org/10.1074/jbc.m114.590646 and Nagai et al. 2016 https://doi.org/10.1371/journal.pone.0156501) and Drosophila (Xu et al. 2023 https://doi.org/10.1038/s41586-023-06833-8 and our study) it is evident that different products of the ITP gene (ITPa and ITPL) could signal via different receptor types depending on the species. Hence, we would need to explore the presence of several genes (ITP, tachykinin, pyrokinin, tachykinin receptor, pyrokinin receptor, CG30340 orphan receptor and Gyc76C) to fully understand which components of these diverse signaling systems are present in a given species to decipher the potential for cross-talk.

While this species-level comparison will certainly be useful in the context of ITP-Gyc76C evolution, it will not alter the conclusions of the present study – ITPa acts via Gyc76C in Drosophila. We therefore agree with the reviewer that these analyses are beyond the scope of this paper.

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):  

Summary:  

In Drosophila melanogaster, ITP has functions on feeding, drinking, metabolism, excretion, and circadian rhythm. In the current study, the authors characterized and compared the expression of all three ITP isoforms (ITPa and ITPL1&2) in the CNS and peripheral tissues of Drosophila. An important finding is that they functionally characterized and identified Gyc76C as an ITPa receptor in Drosophila using both in vitro and in vivo approaches. In vitro, the authors nicely confirmed that the inhibitory function of recombinant Drosophila ITPa on MT secretion is Gyc76C-dependent (knockdown Gyc76C specifically in two types of cells abolished the anti-diuretic action of Drosophila ITPa on renal tubules). They also used a combination of multiple approaches to investigate the roles of ITPa and Gyc76C on osmotic and metabolic homeostasis modulation in vivo. They revealed that ITPa signaling to renal tubules and fat body modulates osmotic and metabolic homeostasis via Gyc76C.  

Furthermore, they tried to identify the upstream and downstream of ITP neurons in the nervous system by using connectomics and single-cell transcriptomic analysis. I found this interesting manuscript to be well-written and described. The findings in this study are valuable to help understand how ITP signals work on systemic homeostasis regulation. Both anatomical and single-cell transcriptome analysis here should be useful to many in the field. 

We thank this reviewer for the positive and thorough assessment of our manuscript.  

Strengths:  

The question (what receptors of ITPa in Drosophila) that this study tries to address is important. The authors ruled out the Bombyx ITPa receptor orthologs as potential candidates. They identified a novel ITP receptor by using phylogenetic, anatomical analysis, and both in vitro and in vivo approaches. 

The authors exhibited detailed anatomical data of both ITP isoforms and Gyc76C (in the main and supplementary figures), which helped audiences understand the expression of the neurons studied in the manuscript.  

They also performed connectomes and single-cell transcriptomics analysis to study the synaptic and peptidergic connectivity of ITP-expressing neurons. This provided more information for better understanding and further study on systemic homeostasis modulation.  

Weaknesses:  

In the discussion section, the authors raised the limitations of the current study, which I mostly agree with, such as the lack of verification of direct binding between ITPa and Gyc76C, even though they provided different data to support that ITPa-Gyc76C signaling pathway regulates systemic homeostasis in adult flies. 

We now provide evidence of Gyc76C activation by ITPa in a heterologous system (new Figure 7 and Figure 7 Supplement 1).

Reviewer #2 (Public Review):  

Summary:  

The physiology and behaviour of animals are regulated by a huge variety of neuropeptide signalling systems. In this paper, the authors focus on the neuropeptide ion transport peptide (ITP), which was first identified and named on account of its effects on the locust hindgut (Audsley et al. 1992). Using Drosophila as an experimental model, the authors have mapped the expression of three different isoforms of ITP (Figures 1, S1, and S2), all of which are encoded by the same gene.  

The authors then investigated candidate receptors for isoforms of ITP. Firstly, Drosophila orthologs of G-protein coupled receptors (GPCRs) that have been reported to act as receptors for ITPa or ITPL in the insect Bombyx mori were investigated. Importantly, the authors report that ITPa does not act as a ligand for the GPCRs TkR99D and PK2-R1 (Figure S3). Therefore, the authors investigated other putative receptors for ITPs. Informed by a previously reported finding that ITP-type peptides cause an increase in cGMP levels in cells/tissues (Dircksen, 2009, Nagai et al., 2014), the authors investigated guanylyl cyclases as candidate receptors for ITPs. In particular, the authors suggest that Gyc76C may act as an ITP receptor in Drosophila.  

Evidence that Gyc76C may be involved in mediating effects of ITP in Bombyx was first reported by Nagai et al. (2014) and here the authors present further evidence, based on a proposed concordance in the phylogenetic distribution ITP-type neuropeptides and Gyc76C (Figure 2). Having performed detailed mapping of the expression of Gyc76C in Drosophila (Figures 3, S4, S5, S6), the authors then investigated if Gyc76C knockdown affects the bioactivity of ITPa in Drosophila. The inhibitory effect of ITPa on leucokinin- and diuretic hormone-31-stimulated fluid secretion from Malpighian tubules was found to be abolished when expression of Gyc76C was knocked down in stellate cells and principal cells, respectively (Figure 4). However, as discussed below, this does not provide proof that Gyc76C directly mediates the effect of ITPa by acting as its receptor. The effect of Gyc76C knockdown on the action of ITPa could be an indirect consequence of an alteration in cGMP signalling.  

Having investigated the proposed mechanism of ITPa in Drosophila, the authors then investigated its physiological roles at a systemic level. In Figure 5 the authors present evidence that ITPa is released during desiccation and accordingly, overexpression of ITPa increases survival when animals are subjected to desiccation. Furthermore, knockdown of Gyc76C in stellate or principal cells of Malphigian tubules decreases survival when animals are subject to desiccation. However, whilst this is correlative, it does not prove that Gyc76C mediates the effects of ITPa. The authors investigated the effects of knockdown of Gyc76C in stellate or principal cells of Malphigian tubules on i). survival when animals are subject to salt stress and ii). time taken to recover from of chill coma. It is not clear, however, why animals overexpressing ITPa were also not tested for its effect on i). survival when animals are subject to salt stress and ii). time taken to recover from of chill coma. In Figures 6 and S8, the authors show the effects of Gyc76C knockdown in the female fat body on metabolism, feeding-associated behaviours and locomotor activity, which are interesting. Furthermore, the relevance of the phenotypes observed to potential in vivo actions of ITPa is explored in Figure 7. The authors conclude that "increased ITPa signaling results in phenotypes that largely mirror those seen following Gyc76C knockdown in the fat body, providing further support that ITPa mediates its effects via Gyc76C." Use of the term "largely mirror" seems inappropriate here because there are opposing effects- e.g. decreased starvation resistance in Figure 6A versus increased starvation resistance in Figure 7A. Furthermore, as discussed above, the results of these experiments do not prove that the effects of ITPa are mediated by Gyc76C because the effects reported here could be correlative, rather than causative. 

We thank this reviewer for an extremely thorough and fair assessment of our manuscript. 

We have now performed salt stress tolerance and chill coma recovery assays using flies over-expressing ITPa (new Figure 10 Supplement 1).

We agree that the use of the term “largely mirrors” to describe the effects of ITPa overexpression and Gyc76C knockdown is not appropriate and have changed this sentence. We also agree that the experiments did not provide direct evidence that the effects of ITPa are mediated by Gyc76C. To address this, we now provide evidence of Gyc76C activation by ITPa in a heterologous system (new Figure 7 and Figure 7 Supplement 1).

Lastly, in Figures 8, S9, and S10 the authors analyse publicly available connectomic data and single-cell transcriptomic data to identify putative inputs and outputs of ITPa-expressing neurons. These data are a valuable addition to our knowledge ITPa expressing neurons; but they do not address the core hypothesis of this paper - namely that Gyc76C acts as an ITPa receptor.  

The goal of our study was to comprehensively characterize an anti-diuretic system in Drosophila. Hence, in addition to identifying the receptor via which ITPa exerts its effects, we also wanted to understand how ITPa-producing neurons are regulated. Connectomic and single-cell transcriptomic analyses are highly appropriate for this purpose. We have now updated the connectomic analyses using an improved connectome dataset that was released during the revision of this manuscript. Our new analysis shows that lNSC^ITP are connected to other endocrine cells that produce other homeostatic hormones (new Figure 13F). We also identify a pathway through which other ITP-producing neurons (LNd^ITP) receive hygrosensory inputs to regulate water seeking behavior (new Figure 13E). Moreover, we now include results which showcase that ITPa-producing neurons (l-NSC^ITP) are active (new Figure 8A and B) and release ITPa under desiccation. Together with other analyses, these data provide a comprehensive outlook on the when, what and how ITPa regulates systemic homeostasis.  

Strengths:  

(1) The main strengths of this paper are i) the detailed analysis of the expression and actions of ITP and the phenotypic consequences of overexpression of ITPa in Drosophila. ii). the detailed analysis of the expression of Gyc76C and the phenotypic consequences of knockdown of Gyc76C expression in Drosophila.  

(2) Furthermore, the paper is generally well-written and the figures are of good quality. 

We thank this reviewer for highlighting the strengths of this manuscript.

Weaknesses:  

(1) The main weakness of this paper is that the data obtained do not prove that Gyc76C acts as a receptor for ITPa. Therefore, the following statement in the abstract is premature: "Using a phylogenetic-driven approach and the ex vivo secretion assay, we identified and functionally characterized Gyc76C, a membrane guanylate cyclase, as an elusive Drosophila ITPa receptor." Further experimental studies are needed to determine if Gyc76C acts as a receptor for ITPa. In the section of the paper headed "Limitations of the study", the authors recognise this weakness. They state "While our phylogenetic analysis, anatomical mapping, and ex vivo and in vivo functional studies all indicate that Gyc76C functions as an ITPa receptor in Drosophila, we were unable to verify that ITPa directly binds to Gyc76C. This was largely due to the lack of a robust and sensitive reporter system to monitor mGC activation." It is not clear what the authors mean by "the lack of a robust and sensitive reporter system to monitor mGC activation". The discovery of mGCs as receptors for ANP in mammals was dependent on the use of assays that measure GC activity in cells (e.g. by measuring cGMP levels in cells). Furthermore, more recently cGMP reporters have been developed. The use of such assays is needed here to investigate directly whether Gyc76C acts as a receptor for ITPa. In summary, insufficient evidence has been obtained to conclude that Gyc76C acts as a receptor for ITPa. Therefore, I think there are two ways forward, either:  

(a) The authors obtain additional biochemical evidence that ITPa is a ligand for Gyc76C.  

or  

(b) The authors substantially revise the conclusions of the paper (in the title, abstract, and throughout the paper) to state that Gyc76C MAY act as a receptor for ITPa, but that additional experiments are needed to prove this. 

We thank the reviewer for this comment and agree with the two options they propose. We had previously tried different a cGMP reporter (Promega GloSensor cGMP assay) to monitor activation of Gyc76C by ITPa in a heterologous system. Unfortunately, we were not successful in monitoring Gyc76C activation by ITPa. We now utilized another cGMP sensor, Green cGull, to show that ITPa can indeed activate Gyc76C heterologously expressed in HEK cells (new Figure 7 and Figure 7 Supplement 1). However, we still cannot rule out the possibility that ITPa can act on additional receptors in vivo. This is based on our ex vivo Malpighian tubule assays (new Figure 6E and F). ITPa inhibits DH31- and LK-stimulated secretion and we show that this effect is abolished in Gyc76C knockdown specifically in principal and stellate cells, respectively. Interestingly, application of ITPa alone can stimulate secretion when Gyc76C is knocked down in principal cells (new Figure 6E). This could be explained by: 1) presence of another receptor for ITPa which results in diuretic actions and/or 2) low Gyc76C signaling activity (RNAi based knockdown lowers signaling but does not abolish it completely) could alter other intracellular messenger pathways that promote secretion. We have added text to indicate the possibility of other ITPa receptors. Nonetheless, our conclusions are supported by the heterologous assay results which indicate that ITPa can activate Gyc76C. Therefore, we do not alter the title. 

(2) The authors state in the abstract that a phylogenetic-driven approach led to their identification of Gyc76C as a candidate receptor for ITPa. However, there are weaknesses in this claim. Firstly, because the hypothesis that Gyc76C may be involved in mediating effects of ITPa was first proposed ten years ago by Nagai et al. 2014, so this surely was the primary basis for investigating this protein. Nevertheless, investigating if there is correspondence in the phylogenetic distribution of ITP-type and Gyc76C-type genes/proteins is a valuable approach to addressing this issue. Unfortunately, the evidence presented is rather limited in scope. Essentially, the authors report that they only found ITP-type and Gyc76C-type genes/proteins in protostomes, but not in deuterostomes. What is needed is a more fine-grained analysis at the species level within the protostomes. Thus, are there protostome species in which both ITP-type and Gyc76C-type genes/proteins have been lost? Furthermore, are there any protostome species in which an ITP-type gene is present but an Gyc76C-type gene is absent, or vice versa? If there are protostome species in which an ITP-type gene is present but a Gyc76C-type gene is absent or vice versa, this would argue against Gyc76C being a receptor for ITPa. In this regard, it is noteworthy that in Figure 2A there are two ITP-type precursors in C. elegans, but there are no Gyc76Ctype proteins shown in the tree in Figure 2B. Thus, what is needed is a more detailed analysis of protostomes to investigate if there really is correspondence in the phylogenetic distribution of Gyc76C-type and ITP-type genes at the species level. 

We thank the reviewer for this comment. While the previous study by Nagai et al had implicated Gyc76C in the ITP signaling pathway, how they narrowed down Gyc76C as a candidate was not reported. Therefore, our unbiased phylogenetic approach was necessary to ensure that we identified all suitable candidate receptors. Indeed, our phylogenetic analysis also identified Gyc32E as another candidate ITP receptor. However, we did not pursue this receptor further as our expression data (new Figure 4 Supplement 2) indicated that Gyc32E is not expressed in osmoregulatory tissues and therefore likely does not mediate the osmotic effects of ITPa. 

We also appreciate the suggestion to perform a more detailed phylogenetic analysis for the peptide and receptor. We did not include C. elegans receptors in the phylogenetic analysis because they tend to be highly evolved and routinely cause long-branch attraction (see: Guerra and Zandawala 2024: https://doi.org/10.1093/gbe/evad108). We (specifically the senior author) have previously excluded C. elegans receptors in the phylogenetic analysis of GnRH and Corazonin receptors for similar reasons (see: Tian and Zandawala et al. 2016: 10.1038/srep28788). 

Unfortunately, absence of a gene in a genome is hard to prove especially when they are not as high-quality as the genomes of model systems (e.g. Drosophila and mice). Moreover, given the concern of this reviewer that our physiological and behavioral data on ITPa and Gyc76C only provide correlative evidence, we decided against performing additional phylogenetic analysis which also provides correlative evidence. Our only goal with this analysis was to identify a candidate ITPa receptor. Since we have now functionally characterized this receptor using a heterologous system, we feel that the current phylogenetic analysis was able to successfully serve its purpose.  

(3) The manuscript would benefit from a more comprehensive overview and discussion of published literature on Gyc76C in Drosophila, both as a basis for this study and for interpretation of the findings of this study.  

We thank the reviewer for this comment. We have now included a broader discussion of Gyc76C based on published literature.  

Reviewer #3 (Public Review):  

Summary:  

The goal of this paper is to characterize an anti-diuretic signaling system in insects using Drosophila melanogaster as a model. Specifically, the authors wished to characterize a role of ion transport peptide (ITP) and its isoforms in regulating diverse aspects of physiology and metabolism. The authors combined genetic and comparative genomic approaches with classical physiological techniques and biochemical assays to provide a comprehensive analysis of ITP and its role in regulating fluid balance and metabolic homeostasis in Drosophila. The authors further characterized a previously unrecognized role for Gyc76C as a receptor for ITPa, an amidated isoform of ITP, and in mediating the effects of ITPa on fluid balance and metabolism. The evidence presented in favor of this model is very strong as it combines multiple approaches and employs ideal controls. Taken together, these findings represent an important contribution to the field of insect neuropeptides and neurohormones and have strong relevance for other animals. 

We thank this reviewer for the positive and thorough assessment of our manuscript.

Strengths:  

Many approaches are used to support their model. Experiments were wellcontrolled, used appropriate statistical analyses, and were interpreted properly and without exaggeration.  

Weaknesses:  

No major weaknesses were identified by this reviewer. More evidence to support their model would be gained by using a loss-of-function approach with ITPa, and by providing more direct evidence that Gyc76C is the receptor that mediates the effects of ITPa on fat metabolism. However, these weaknesses do not detract from the overall quality of the evidence presented in this manuscript, which is very strong.  

We agree with this reviewer regarding the need to provide additional evidence using a loss-of-function approach with ITPa. We now characterize the phenotypes following knockdown of ITP in ITP-producing cells (new Figure 9). Our results are in agreement with phenotypes observed following Gyc76C knockdown, lending further support that ITPa mediates its effects via Gyc76C. Unfortunately, we are not able to provide evidence that ITPa acts on Gyc76C in the fat body using the assay suggested by this reviewer (explained in detail below). Instead, we now provide direct evidence of Gyc76C activation by ITPa in a heterologous system (new Figure 7 and Figure 7 Supplement 1).

Reviewer #1 (Recommendations For The Authors):  

Here, I have several extra concerns about the work as below:  

(1) The authors confirmed the function of ITPa in regulating both osmotic and metabolic homeostasis by specifically overexpressing ITPa driven by ITP-RCGal4 in adult flies (Figures. 5 and 7). Have authors ever tried to knock down ITP in ITP-RC-Gal4 neurons? What was the phenotype? Especially regarding the impact on metabolic homeostasis, does knocking down ITP in ITP neurons mimic the phenotypes of Gyc76C fat body knockdown flies? 

We thank the reviewer for this suggestion. We now characterize the phenotypes following knockdown of ITP using ITP-RC-Gal4 (new Figure 9). Our results are in agreement with phenotypes observed following Gyc76C knockdown, lending further support that ITPa mediates its effects via Gyc76C.

The authors mentioned that the existing ITP RNAi lines target all three isoforms. It would be interesting if the authors could overexpress ITPa in ITPRC-Gal4>ITP-RNAi flies and confirm whether any phenotypes induced by ITP knockdown could be rescued. It will further confirm the role of ITPa in homeostasis regulation.  

We thank the reviewer for this suggestion. Unfortunately, this experiment is not straightforward because knockdown with ITP RNAi does not completely abolish ITP expression (see Figure 9A). Hence, the rescue experiment needs to be ideally performed in an ITP mutant background. However, ITP mutation leads to developmental lethality (unpublished observation) so we cannot generate all the flies necessary for this experiment. Therefore, we cannot perform the rescue experiments at this time. In future studies, we hope to perform knockdown of specific ITP isoforms using the transgenes generated here (Xu et al 2023: 10.1038/s41586-023-06833-8).   

(2) In Figures 5A and B, the authors nicely show the increased release of ITPa under desiccation by quantifying the ITPa immunolabelling intensity in different neuronal populations. It may be induced by the increased neuronal activity of ITPa neurons under the desiccated condition. Have the authors confirmed whether the activity of ITPa-expressing neurons is impacted by desiccation?  

The TRIC system may be able to detect the different activity of those neurons before and after desiccation. This may further explain the reduced ITPa peptide levels during desiccation.  

We thank the reviewer for this suggestion. We have now monitored the activity of ITPa-expressing neurons using the CaLexA system (Masuyama et al 2012: 10.3109/01677063.2011.642910). Our results indicate that ITPa neurons are indeed active under desiccation (new Figure 8A and B). These results are also in agreement with ITPa immunolabelling showing increased peptide release during desiccation (new Figure 8C and D). Together, these results show that ITPa neurons are activated and release ITPa under desiccation.  

(3) What about the intensity of ITPa immunolabelling in other ITPa-positive neurons (e.g., VNC) under desiccation? If there is no change in other ITPa neurons, it will be a good control. 

We thank the reviewer for this suggestion. Unfortunately, ITPa immunostaining in VNC neurons is extremely weak preventing accurate quantification of ITPa levels under different conditions. We did hypothesize that ITPa immunolabelling in clock neurons (5^th-LN_v and LN<Sub>d</sub>^ITP) would not change depending on the osmotic state of the animal. However, our results (Figure 8C and D) indicate that ITPa from these neurons is also released under desiccation. Interestingly, LNd^ITP, which also coexpress Neuropeptide F (NPF) have recently been implicated in water seeking during thirst (Ramirez et al, 2025: 10.1101/2025.07.03.662850). Our new connectomic-driven analysis shows that these neurons can receive thermo/hygrosensory inputs (new Figure 13E). Hence, it is conceivable that other ITPa-expressing neurons also release ITPa during thirst/desiccation.

(4) The adult stage, specifically overexpression of ITPa in ITP neurons, does show significant phenotypes compared to controls in both osmotic and metabolic homeostasis-related assays. It would be helpful if authors could show how much ITPa mRNA levels are increased in the fly heads with ITPa overexpression (under desiccation & starvation or not). 

We thank the reviewer for this suggestion. We have now included immunohistochemical evidence showing increase in ITPa peptide levels in flies with ITPa overexpression (new Figure 10A). We feel that this is a better indicator of ITPa signaling level instead of ITPa mRNA levels.   

(5) Another question concerns the bloated abdomens of ITPa-overexpressing flies. Are the bloated abdomens of ITPa OE female flies (Figure 5E) due to increased ovary size (Figure 7G)? Have the authors also detected similar bloated abdomens in male flies with ITPa overexpression? Since both male and female flies show more release of ITPa during the desiccation.  

We thank the reviewer for this comment. The bloated abdomen phenotype seen in females can be attributed to increased water content since we see a similar phenotype in males (see Author response image 1 below).

Author response image 1.

Reviewer #2 (Recommendations For The Authors):  

(1) Page 1 - change "Homeostasis is obtained by" to "Homeostasis is achieved by".  

Changed

(2) Page 1 - change "Physiological responses" to "Physiological processes". 

Changed

(3) Page 2 - Change "Recently, ITPL2 was also shown to mediate anti-diuretic effects via the tachykinin receptor" to "Recently, ITPL2 was also shown to exert anti-diuretic effects via the tachykinin receptor". 

Changed

(4) Page 9 - "(C) Adult-specific overexpression of ITPa using ITP- RC-GAL4TS (ITP-RC-T2A-GAL4 combined with temperature-sensitive tubulinGAL80) increases desiccation" Unless I am misunderstanding Fig 5C, I think what is shown is that overexpression of ITPa prolongs survival during a period of desiccation. I am not sure what the authors mean by "increases desiccation". In the text (page 9) the authors state "ITPa overexpression improves desiccation tolerance, which is a much clearer statement than what is in the figure legend. 

We thank the reviewer for identifying this oversight. We have now changed the caption to “increases desiccation tolerance”.  

(5) Page 11 - The authors conclude that "increased ITPa signaling results in phenotypes that largely mirror those seen following Gyc76C knockdown in the fat body, providing further support that ITPa mediates its effects via Gyc76C." Use of the term "largely mirror" seems inappropriate here because there are opposing effects- e.g. decreased starvation resistance in Figure 6A versus increased starvation resistance in Figure 7A.  

Perhaps there is a misunderstanding of what is meant by "mirroring" - it means the same, not the opposite. 

We thank the reviewer for this comment. We agree that the use of the term “largely mirrors” to describe the effects of ITPa overexpression and Gyc76C knockdown is not appropriate and have changed this sentence as follows: “Taken together, the phenotypes seen following Gyc76C knockdown in the fat body largely mirror those seen following ITP knockdown in ITP-RC neurons, providing further support that ITPa mediates its effects via Gyc76C.”

(6) Page 12 - There appear to be words missing between "neurons during desiccation, as well as their downstream" and "the recently completed FlyWire adult brain connectome" 

We thank the reviewer for highlighting this mistake. We have changed the sentence as following: “Having characterized the functions of ITP signaling to the renal tubules and the fat body, we wanted to identify the factors and mechanisms regulating the activity of ITP neurons during desiccation, as well as their downstream neuronal pathways. To address this, we took advantage of the recently completed FlyWire adult brain connectome (Dorkenwald et al., 2024, Schlegel et al., 2024) to identify pre- and post-synaptic partners of ITP neurons.”

(7) Page 15 - "can release up to a staggering 8 neuropeptides" - I suggest that the word "staggering" is removed. The notion that individual neurons release many neuropeptides is now widely recognised (both in vertebrates and invertebrates) based on analysis of single-cell transcriptomic data. 

Removed staggering.

(8) Page 16 - "(Farwa and Jean-Paul, 2024)" - this citation needs to be added to the reference list and I think it needs to be changed to "Sajadi and Paluzzi, 2024". 

We thank the reviewer for highlighting this oversight. The correct citation has now been added.

(9) It is noteworthy that, based on a PubMed search, there are at least thirteen published papers that report on Gyc76C in Drosophila (PMIDs: 34988396, 32063902, 27642749, 26440503, 24284209, 23862019, 23213443,  21893139, 21350862, 16341244, 15485853, 15282266, 7706258). However, none of these papers are discussed/cited by the authors. This is surprising because the authors' hypothesis that Gyc76C acts as a receptor for ITPa surely needs to be evaluated and discussed with reference to all the published insights into the developmental/physiological roles of this protein. 

We thank the reviewer for this comment. Some of the references mentioned above (21350862, 16341244, 15485853) mainly report on soluble guanylyl cyclases and not membrane guanylyl cyclase like Gyc76C. Based on other studies on Gyc76C and its role in immunity and development, we have now expanded the discussion on additional roles of ITPa.

Reviewer #3 (Recommendations For The Authors):  

I have only a few comments that will help the authors strengthen a couple of aspects of their model.  

(1) The case for Gyc76C as a receptor for ITPa in regulating fluid homeostasis is clear, given the experiments the authors carried out where they applied ITPa to tubules and showed that the effects of ITPa on tubule secretion were blocked if Gyc76C was absent in tubules. This approach, or something similar, should be used to provide conclusive proof that ITPa's metabolic effects on the fat body go through Gyc76C.  

At present (unless I missed it) the authors only show that gain of ITPa has the opposite phenotype to fat body-specific loss of Gyc76C. While this would be the expected result if ITPa/Gyc76C is a ligand-receptor pair, it is not quite sufficient to conclusively demonstrate that Gyc76C is definitely the fat body receptor. Ex vivo experiments such as soaking the adult fat body carcasses with and without Gyc76C in ITPa and monitoring fat content via Nile Red could be one way to address this lack of direct evidence. The authors could also make text changes to explicitly mention this lack of conclusive evidence and suggest it as a future direction.

We thank the reviewer for this comment. We have now conclusively demonstrated that Gyc76C is activated by ITPa in a heterologous assay (new Figure 7 and Figure 7 Supplement 1). With this evidence, we can confidently claim that ITPa can mediate its actions via Gyc76C in various tissues including the Malpighian tubules and fat body. Nonetheless, we liked the suggestion by this reviewer to perform the ex vivo assay and test the effect of ITPa on the fat body. Unfortunately, it is challenging to do this because increased ITPa signaling (chronically using ITPa overexpression) results in increased lipid accumulation in the fat body in vivo. Therefore, we would likely not see the effect of ITPa addition in an ex vivo fat body preparation since lipogenesis will not occur in the absence of glucose. However, ITPa could counteract the effects of other lipolytic factors such as adipokinetic hormone (AKH). To test this hypothesis, we monitored fat content in the fat body incubated with and without AKH (see Author response image 2 below showing representative images from this experiment). Since we did not observe any differences in fat levels between these two conditions, we were unable to test the effects of ITPa on AKH-activity using this assay.

Author response image 2.

(2) I did not see any loss of function data for ITPa - is this possible? If so this would strengthen the case for a 1:1 relationship between loss of ligand and loss of receptor. Alternatively, the authors could suggest this as an important future direction. 

We agree with this reviewer regarding the need to provide additional evidence using a loss-of-function approach with ITPa. We have now characterized the phenotypes following knockdown of ITP in ITP-producing cells (new Figure 9). Our results are in agreement with phenotypes observed following Gyc76C knockdown, lending further support that ITPa mediates its effects via Gyc76C.

(3) For clarity, please include the sex of all animals in the figure legend. Even though the methods say 'females used unless otherwise indicated' it is still better for the reader to know within the figure legend what sex is displayed. 

We thank the reviewer for this suggestion and have now included sex of the animals in the figure legends.  

(4) Please state whether females are mated or not, as this is relevant for taste preferences and food intake. 

We apologize for this oversight. We used mated females for all experiments. This has now been included in the methods.  

(5) More discussion on the previous study on metabolic effects of ITP in this study compared with past studies would help readers appreciate any similarities and/or differences between this study and past work (Galikova 2018, 2022) 

We thank the reviewer for this suggestion. Unfortunately, it is difficult to directly compare our phenotypes with the metabolic effects of ITP reported in Galikova and Klepsatel 2022 because the previous study used a ubiquitous driver (Da-GAL4) to manipulate ITP levels. Ectopically overexpressing ITPa in non-ITP producing cells can result in non-physiological phenotypes. This is evident in their metabolic measurements where both global overexpression and knockdown of ITP results in reduced glycogen and fat levels, and starvation tolerance. Moreover, ITP-RC-GAL4 used in our study to overexpress and knockdown ITPa is more specific than the Da-GAL4 used previously. Da-GAL4 would include other ITP cells (e.g. ITP-RD producing cells). Since ITP is broadly expressed across the animal, it is difficult to parse out the phenotypes of ITPa and other isoforms using manipulations performed with Da-GAL4. We have mentioned this limitation in the results for ITP knockdown as follows: “A previous study employing ubiquitous ITP knockdown and overexpression suggests that Drosophila ITP also regulates feeding and metabolic homeostasis (Galikova and Klepsatel, 2022) in addition to osmotic homeostais (Galikova et al., 2018). However, given the nature of the genetic manipulations (ectopic ITPa overexpression and knockdown of ITP in all tissues) utilized in those studies, it is difficult to parse the effects of ITP signaling from ITPa-producing neurons.”

prem 1

As the author stroke his beam of his lamp on the flank, what he was doing can be looking back the wounds and emotions he had. And it's something that comes and never goes, unlike fish or weed, which doesn't leave lasting impact to our brain.

eLife Assessment

This study provides convincing evidence that homologous recombination can occur in telophase-arrested cells, independently of cohesin subunits Smc 1-3. These findings are valuable as they point to investigate the role of cohesins re-association with chromatin in the allelic inter-sister repair by homologous recombination.

Reviewer #1 (Public review):

Summary

The cohesin complex is essential for maintaining sister chromatid cohesion from S phase until anaphase. Beyond this canonical role, it is also recruited to double-strand breaks (DSBs), supporting both local and global post-replicative cohesion, a phenomenon first reported in 2004. In a previous study, Ayra-Plasencia et al. demonstrated that in telophase, DSBs can be repaired by homologous recombination (HR) through re-coalescence of sister chromatids (Ayra-Plasencia & Machín, 2019). In the present work, the authors provide further insights into DSB repair in late mitosis, showing that:

Scc1 is reloaded and reconstituted on chromatin together with Smc1.

HR occurs with high efficiency.

HR-driven MAT switching can occur in an Smc3-independent manner.

Strengths

The authors take full advantage of the yeast model system, employing the HO endonuclease to generate a single, site-specific DSB at the MAT locus on chromosome III. Combined with careful cell synchronization, this setup allows them to monitor HR-mediated repair events specifically in G2/M and late mitosis. Their demonstration that full-length Scc1 can be recovered upon DSB induction is compelling. Most importantly, the finding that efficient HR can take place during M phase is significant, as HR has long been thought to be largely inhibited at this stage of the cell cycle.

Weaknesses

While the authors provide evidence for Scc1 recovery and efficient HR in late mitosis, some critical points need to be clarified to improve the impact and interpretability of the study.

Reviewer #2 (Public review):

Cohesin drive inter-sister repair of DNA breaks by homologous recombination (HR) in G2/M. Cohesion is lost at the metaphase to anaphase transition upon digestion of the Scc1 subunit of cohesin by Esp1, raising the question as to whether and how break repair by HR could occur in late mitosis (late-M).

Here the author investigate the behavior of cohesin in cells arrested in telophase and experiencing a DNA break at the mating-type locus on chr. III (a specialized recombination process required for mating-type switching) or upon random DNA break formation with the drug phleomycin.

The revised version of the manuscript now convincingly establishes three facts:

- The cohesin subunit Scc1 can re-associate with chromatin and the other Smc1-3 subunits upon formation of an unrepairable DSB at MAT in telophase.<br /> - HR can occur in telophase-arrested cells<br /> - Cohesin (an a fortiori cohesin that reassociated with chromatin) plays no role in non-allelic HR in telophase in the specific context of MAT switching.

Unfortunately, the role of cohesin re-association with chromatin for the allelic inter-sister repair by HR is not addressed. In the absence of such evidence, the main claims of the paper making up the title (cohesin re-association and HR repair) appear disconnected. Even if the very last sentence of the abstract corrects the false sense from the title and the rest of the abstract that cohesin reconstitution has somehow something to do with efficient HR in late mitosis, I think a general rewriting of the abstract and a different title would better lift any ambiguity about the conclusions of the paper.

Author response:

The following is the authors’ response to the original reviews

We would like to thank the reviewers for taking the time to thoroughly revise our work. We have considered their suggestions carefully and tried our best to respond to them point by point. Based on their recommendations, two major issues came forward: (1) the strength of our claims about the involvement of cohesin in HR-driven repair in late mitosis; and (2) the underlying mechanism that reconstitutes cohesin in late mitosis after DNA damage. In this revision, we focused on the former and left the latter out (yet it is discussed). We considered that the question of how cohesin returns in late mitosis after DNA damage is important and worthy of further research, but it is beyond the scope of this study (as it is the putative role of condensin). Thus, we have focused on buttressing our main claims, as otherwise pointed out by the reviewers. What have we done to strengthen the role of cohesin in late mitotic DSB repair?

(1) We have biologically replicated and quantified the reappearance of Scc1 after DSB generation (new Figure 1e). We have also quantified changes for the other core subunits (new Figure 1c-e).

(2) We now show that the newly synthetized Scc1 serves to assemble back the cohesin complex (new Figure 2a and S1).

(3) We have performed chromatin fractionation and show that cohesin binding to chromatin increases after the HO-induced DSB (new Figure 2b and S2).

(4) We have performed ChIP assays and show that, despite the increase in the chromatin-bound fraction, the HOcs DSB does not recruit new cohesin to the locus (new Figure 2c and S3).

(5) A key assertion in the preprint version was that depleting cohesin using the auxin degron system impairs HR-driven MAT switching. This claim was based on a direct comparison of cultures treated or not with auxin (-/+ IAA). However, during the revision process, we realized that auxin treatment itself could interfere with MAT switching. Firstly, we noticed a diminished HOcs cutting efficiency by HO in +IAA cultures (Figure S6). Secondly, the apparently dramatic delay in gene conversion to MAT_α could actually be related to other undesirable effects of IAA downstream in the repair process. Thus, we decided to repeat this experiment with strains that differ in their response to auxin, so that we could compare all strains in the presence of auxin. We compared four isogenic strains: _SMC3; SMC3-aid*; SMC3 + OsTIR1; and SMC3-aid* + OsTIR1. As a result, we can now show that cohesin depletion does not affect MAT switching (see new Figure 4b-d).

(6) We recently reported a negative chemical interaction between auxin and phleomycin. Auxin appears to diminish the ability of phleomycin to generate DSBs (Comm Biol 2025, doi: 10.1038/s42003-025-08416-x; see Figures S14 and S15 in that paper). While the underlying nature of this interaction is unknown to us (we are working on it), this leads us to omit the coalescence assay included in the preprint version (old Figure 4c), as the diminished coalescence upon IAA addition is actually due to this effect rather than cohesin depletion. This is also in agreement with the new data we include in the revised version, in which we observed only minor changes in cohesin reconstitution and chromatin binding after phleomycin (Figure 2a,b; S1 and S2).  

(7) In addition to addressing these reviewers’ requests, we have better characterized the MAT switching in late mitosis by incorporating the kinetics of _rad9_Δ (deficient in the DNA damage checkpoint), _yku70_Δ (deficient in non-homologous end joining) and _mre11_Δ (deficient in DSB end tethering). The effect of _rad52_Δ (deficient in HR) has been described elsewhere (our iScience 2024, 10.1016/j.isci.2024.110250).

As a result of these new experiments, new figure panels have been added in the main figures and as supplementary figures. To make room for the these panels in the main figures and keep the short report format, the following changes have been made: (i) old figures and new panels have been combined into four main figures, (ii) some panels from the old figures have been moved to supplementary figures, and (iii) some panels have been reordered for the sake of simplicity and fluidity in the main text. 

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The cohesin complex maintains sister chromatid cohesion from S phase to anaphase. Beyond that, DSBs trigger cohesin recruitment and post-replication cohesion at both damage sites and globally, which was originally reported in 2004. In their recent study, Ayra-Plasencia et al reported in telophase, DSBs are repaired via HR with re-coalesced sister chromatids (Ayra-Plasencia & Machín, 2019). In this study, they show that HR occurs in a Smc3-dependent way in late mitosis.

Strengths:

The authors take great advantage of the yeast system, they check the DSB processing and repair of a single DSB generated by HO endonuclease, which cuts the MAT locus in chromosome III. In combination with cell synchronization, they detect the HR repair during G2/M or late mitosis. and the cohesin subunit SMC3 is critical for this repair. Beyond that, full-length Scc1 protein can be recovered upon DSBs.

Weaknesses:

These new results basically support their proposal although with a very limited molecular mechanistic progression, especially compared with their recent work.

Reviewer #2 (Public Review):

Summary:

The manuscript "Cohesin still drives homologous recombination repair of DNA double-strand breaks in late mitosis" by Ayra-Plasencia et al. investigates regulations of HR repair in conditional cdc15 mutants, which arrests the cell cycle in late anaphase/telophase. Using a non-competitive MAT switching system of S. cerevisiae, they show that a DSB in telophase-arrested cells elicits a delayed DNA damage checkpoint response and resection. Using a degron allele of SMC3 they show that MATa-to-alpha switching requires cohesin in this context. The presence of a DSB in telophase-arrested cells leads to an increase in the kleisin subunit Scc1 and a partial rejoining of sister chromatids after they have separated in a subset of cells.

Strengths:

The experiments presented are well-controlled. The induction systems are clean and well thought-out.

Weaknesses:

The manuscript is very preliminary, and I have reservations about its physiological relevance. I also have reservations regarding the usage of MAT to make the point that inter-sister repair can occur in late mitosis.

Regarding these two weaknesses:

- Physiological relevance: This is something we already addressed in our previous research work (Nat Commun. 2019; 10(1):2862. doi: 10.1038/s41467-019-10742-8), and which was further discussed in a follow-up theoretical paper (Bioessays. 2020 ;42(7):e2000021. doi: 10.1002/bies.202000021). In summary, this is physiologically relevant because a DSB in anaphase activates a late-mitotic checkpoint so the DSB can be repaired before cytokinesis. The fact that anaphase is quick and only a minor fraction of cells get a DSB in this cell cycle stage in an asynchronous population does not preclude its importance since it is enough a single mis-repaired DSB in hundreds of cells to mutate a population in an health- or evolution-relevant way.

- MAT system in late mitosis: It was not our intention to use the MAT switching assay to state that inter-sister repair can occur in late-M. The purpose was to address whether HR was fully functional in this non-G2/M non-G1 stage. Having said that, it is very challenging to design a strategy based on sequence-specific DSB to tackle the inter-sister repair in late-M. Any endonuclease-generated DSB is going to cut in both sisters. This is something we also deeply discussed in our previous works (Nat Commun & Bioessays).    

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Major points:

(1) Smc3 degradation affects Rad53 activation upon DSBs, and this may directly lead to HR repair deficiency. Smc3 also could be phosphorylated by ATM and functions in DNA damage checkpoint activation, these alternative possibilities should also be tested before addressing the bona fide role of Smc3 in this context.

Our previous data already suggested that Rad53 hyperphosphorylation still occurs after Smc3 degradation (Figure S6). Regardless, the question of whether the DNA damage checkpoint (DDC) may play a distinct role in the MAT switching has been addressed in this revision by comparing RAD9 versus rad9_Δ. Rad9 is a mediator in the DDC required for the activation of Rad53. We have seen that MAT switching in _rad9_Δ is as efficient as in _RAD9 (new Figure S5d-f).

On the other hand, our new results, in which we have compared four different strains with all auxin system combinations in the presence of auxin, show that cohesin depletion does not affect MAT switching. Previously, we compared minus versus plus auxin and noticed diminished HO cutting efficiency. Thus, we repeated this experiment with four isogenic strains (SMC3; SMC3-aid*; SMC3 + OsTIR1; and SMC3-aid* + OsTIR1) that differ in their response to auxin and ability to degrade cohesin, so that we could compare all strains in the presence of auxin. As a result, we can now affirm that cohesin depletion does not affect MAT switching (see new Figure 4b-d). Therefore, HR appears efficient after cohesin depletion.

(2) The requirement of cohesin subunit Smc3 and "coincidently" recovery of Scc1 are not sufficient to claim they act as a cohesin complex in this scenario. CoIP in the chromatin fraction after DSBs to prove the cohesin complex formation is recommended. If they act as a complex, are cohesin loader Scc2/4 required?

We have constructed a SMC3-HA SCC1-myc strain. We have purified the chromatin-bound fraction as well as performing the co-IP. We have found Smc1-acSmc3-Scc1 forms a complex after Scc1 returns, and that at least a fraction of this complex binds to the chromatin in our HO model of DSBs in late anaphase (the cdc15-2 arrest). This is now shown in the new Figures 2a,b and S1,S2.

As for the requirement of Scc2/4, we consider that the mechanisms underlying how Scc1 comes back, how a new cohesin complex is reassembled, and how it can partly bind to the chromatin in late anaphase are beyond the scope of this study and worth pursuing in a follow-up story.

(3) Figure 3b. acetylated SMC3 was prominently detected in the absence of DSBs. During the cohesion cycle, the cohesin was released from chromatin in a separase-dependent manner at the anaphase onset. Released Smc3 was deacetylated by Hos1 subsequently. In principle, the acSMC3 level could be very low in late mitosis.

In that figure (now renumbered as Fig S6), we did detect acetylated Smc3 for the remnant Smc3 still found in late mitosis, however, a direct comparison between the acetylated versus non-acetylated pools was not performed, and would require more sophisticated approaches. Note that blots are distinctly exposed until the band is detected, and that signal intensity is antibody-specific. The presence of an acSmc3 pool in the cdc15-2 arrest is now further confirmed by the new blots in Figures 2a, S1 and S2b.

On the other hand, previous time course experiments from G1 and G2/M releases point out that Smc3 deacetylation is incomplete in anaphase, with up to 30% of acetylated Smc3 remaining (Beckouët et al, 2010 doi:10.1016/j.molcel.2010.08.008). This is consistent with the presence of acSmc3 in the cdc15-2 arrest.   

(4) Did the author examine the acSMC3 levels returning after DSB, as Scc1's levels? If so, how about the Eco1's protein level? Chromatin fractionation could be conducted to check the chromatin-bound SMC3, acSMC3/Eco1, SCC1, SCC1 phosphorylation, and SMC1. These results will tell us whether cohesin functions in DSB repair in late M in a cohesion state.

As stated above, we have now determined that cohesin depletion does not affect HR-driven MAT switching. As for the other questions, yes, we have performed both an assessment of acSmc3 in the pull down and chromatin fractionation, before and after DSBs (new Figures 2a, S1 and S2b). Interestingly, we have noticed a difference between the HO-generated and the phle-generated DSBs. It appears that the former leads to a better reconstituted Smc1-acSmc3-Scc1 complex and more chromatin-bound cohesin. The overall acSmc3 levels do not appear to significantly change in the whole cell extracts, although there could be further posttranslational modifications in telophase (see the changes in intensity between the two acSmc3 bands in Figure S1).

The role of Eco1 has not been directly addressed but is discussed. The main point here is that Eco1 levels may be low after G2/M (e.g., Lyons and Morgan, 2011), but there is still a significant acSmc3 pool in anaphase as Hof1 does not deacetylate all Smc3 (Beckouët et al., 2010). 

(5) Figure 4a, the return of full-length Scc1 is based on a single experiment. What's the mechanism? Inhibition of cleavage or re-expression? How about its mRNA levels?

We have repeated the full-length Scc1 experiment two more times. Now, an expression graph is included as a new Figure 1e. The two other subunits, Smc1 and Smc3, have been assessed as well, with no major changes in abundance (new Figure 1c and d).

We feel that the exact molecular mechanism of how Scc1 returns is beyond the scope of this study, but we discuss that the DDC may either inactivate separase or protect Scc1 against it. Indeed, there is literature that supports both mechanisms (e.g., Heidinger-Pauli et al., 2008 doi:10.1016/j.molcel.2008.06.005; Yam et al., 2020 doi:10.1093/nar/gkaa355).   

Minor points:

(6) FACS data should be shown for all cell synchronization experiments.

From our previous own works, FACS profiles add little to late-M experiments. To properly confirm late-M, microscopy is a must. FACS cannot differentiate between G2/M (metaphase-like), anaphase, telophase and the ensuing G1 (as cdc15-2 cells do not immediately split apart after re-entering G1). In all experiments, Tel samples (late-M cdc15-2 arrest) were characterized by >95% large budded binucleated cells.

(7) Figure 1d, A loading control of Rad53-P in is missing. The "Arrest" samples should be loaded again on the right to confirm the shift of Rad53, but not due to "smiling gels".

It is true that the blot on the right has a right-handed smile; however, it is very clear the presence of the Rad53/Rad53-P partner. Because there is not a full shift from Rad53 to Rad53-P, the concern of misidentifying Rad53-P as a result of a blot smile is unfounded.

(8) Figure 1c, After the HO cut, the resected DNA at the 726 bp site reaches to platform at about 4 hrs, while it still increases at the 5.6 kb site. Thus, it is difficult to conclude that "The time to reach half of the maximum possible resection (t1/2) was ~1 h at 0.7 Kb and ~2.5 h at 5.7 Kb from the DSB, respectively".

We assumed that both loci reach the plateau at 0.8 (which is consistent with other studies), so the t1/2 was calculated when the resected intersected 0.4.

(9) Figure 2b and 2c are wrongly labeled.

We have fixed this (now Fig. 3d and e).

(10) Figure 2d, Double check and make sure the quantitative data reflects the representative result. E.g. in Figure 2b (in fact should be 2c). For instance, in Figure 2b, the MATα signals seem to remain stable from 60' to 180', but they keep increasing in Figure 2d. In Yamaguchi & James E. Haber's paper, the signals and changes of MATa and MATα over time are way stronger compared to this study.

We have double checked this. It is true that the sum of MATα, MATalpha and cut HOcs bands throughout the assay does not have the intensity seen for MATa before the HO induction (Tel), but MATalpha and HOcs signals cannot be established based on the equimolarity of the reaction as all band signals are probe-specific (the best indication of this can be seen in the signal comparison between MAT_α and _MAT distal at Tel). Alternatively, some resected HOcs may remain unrepaired.

As for the referred example (now Figure 3e), note that they are double normalized to ACT1 and MAT_α (Tel), and the _ACT1 band gets fainter after 60’. This explains the increase in the MATalpha quantification in spite of what is apparently seen in the blot.

(11) Typos and fonts: e.g. lines 111-112; line 76 "his link".

We have fixed this. Thanks.

Reviewer #2 (Recommendations For The Authors):

Major concerns:

(1) Physiological relevance. The authors show that HR can happen in the anaphase to telophase interval, yet does it outside of an hours-long artificial arrest upon inactivation of Cdc15? It is this reviewer's understanding that the duration of the anaphase to telophase transition is short, in the order of minutes. In fact, break signaling and resection are delayed by ~1 hour (Fig. 1), which suggests that cells avoid dealing with the damage and engaging in HR in the anaphase-telophase interval. Is there any described physiological context or checkpoint that blocks this transition for extended periods, that would make any of the findings in this paper relevant?

This concern about the physiological relevance was addressed in our previous study (Nat Commun. 2019; 10(1):2862. doi: 10.1038/s41467-019-10742-8). In that paper’s Figure 1, we showed that G1 re-entry after a cdc15-2 release was delayed by several hours when DSBs had been previously generated at the cdc15-2 arrest. We also showed that such a delay depended on Rad9 (i.e., the DNA damage checkpoint). In addition, synchronized (not arrested) cells transiting through anaphase responded to DSB generation by slowing anaphase transition while partly regressing chromosome segregation (Figure S7 in that paper).

(2) Methodological caveats. It is unclear why the authors chose to study DSB-repair in the context of MATa-to-alpha switching (which uses an ectopic donor on the other chromosome arm) as a model for inter-sister repair. It creates a disconnect in the claims of the paper, which means to study inter-sister repair. Studying the kinetics of DSB repair by cytology following low-dose irradiation or radiomimetic drugs would have been a better option. Phleomycin is used in Fig. 4, but the repair kinetics (e.g. Rad52 foci) is not studied.

The MAT switching assay was used here to address how much HR was functional in late-M compared to G2/M (metaphase-like). Then, it was employed to check how cohesin depletion hampers HR in late-M. Even though this is something we already deeply discussed previously (Nat Commun. 2019; 10(1):2862. doi: 10.1038/s41467-019-10742-8; Bioessays. 2020 ;42(7):e2000021. doi: 10.1002/bies.202000021), it is worth recapitulating the methodological challenges that the study of inter-sister repair has in late-M: (i) endonuclease-based DSBs are going to generate two DSBs, one per sister chromatid; (ii) the use of a homologous chromosome without the cutting site as a template is pointless because a sister of the homolog is always going to co-segregate with the broken chromatid, and the same caveat applies for any other ectopic sequence. In this context, the MATa with the HML ectopic intrachromosomal sequence is as valid as any other option, with the advantage that it is a very well-known system.

On the other hand, most of the reviewer’s concerns about the inter-sister repair by cytology and the role of Rad52 was addressed in our previous paper (Nat Commun). Note that our new results about the cohesin role on MAT switching show that this HR-mediated DSB repair does not depend on cohesin (new Figure 4b-d).

(3) Preliminary work. The requirement of cohesin for MAT switching in cdc15 mutants would have warranted several additional experiments. Indeed, Cohesin has been shown to regulate homology search in multiple ways upon DNA damage checkpoint-induced metaphase-arrest (see Piazza et al. Nat Cell Biol 2021 (10.1038/s41556-021-00783-x), not cited in the current manuscript). Consequently, is the effect of cohesin observed in the MAT system specific to telophase or is it true in other cell-cycle phases? What is the mechanism behind this requirement (one may expect it not to depend on the sister since the HML donor is available within the damaged chromatid)? Does cohesin re-accumulate around the DSB site or genome-wide? How does the Esp1 activity decay from anaphase onset? Is cohesin required for the horseshoe folding of chr. III involved in MATa-to-alpha switching? Furthermore, condensin is involved in MATa-specific switching (Li et al. PLoS Genet 2019, 10.1371/journal.pgen.1008339), and condensin remains active on chromatin in cdc15 arrested cells, as shown on chr. XII (Lazar-Stefanita et al. EMBO J. 2017 10.15252/embj.201797342), which calls for determining the impact contribution of condensin in the recoil of the right ch.XII arm (Fig 4c) and on MAT switching.

There are several points here:

- Is the effect of cohesin observed in the MAT system specific to telophase or is it true in other cell-cycle phases?

Our new results show that cohesin depletion does not affect MAT switching when four different strains with all auxin system combinations are compared in the presence of auxin. Previously, when we compared minus versus plus auxin, we noticed diminished HO cutting efficiency. Therefore, we repeated the experiment using four isogenic strains (SMC3, SMC3-aid*, SMC3 + OsTIR1, and SMC3-aid* + OsTIR1), which differ in their response to auxin and ability to degrade cohesin. This allowed us to compare all strains in the presence of auxin. As a result, we can now confirm that cohesin depletion does not affect MAT switching (see the new Figures 4b–d). Therefore, HR appears efficient after cohesin depletion. In agreement, the new ChIPs we have performed do not detect an increment in local cohesin after the HO DSB in telophase (but it does in cells arrested in G2/M).

- What is the mechanism behind this requirement (one may expect it not to depend on the sister since the HML donor is available within the damaged chromatid)?

As just said, we have changed our previous conclusion on cohesin and MAT switching. It was an effect of auxin addition rather than cohesin depletion.

- Does cohesin re-accumulate around the DSB site or genome-wide?

We have performed ChIP around the HOcs. We have found that it does accumulate in G2/M after HO induction, but it does not in telophase (new Figures 2c and S3). As for the global binding of cohesin, our chromatin fractionation data suggest there is ~2-fold increase in Smc1-Smc3, which also binds to the newly formed Scc1, rendering an overall increase in the chromatin-bound canonical complex (new Figures 2b and S2). Altogether, this suggests a genome-wide binding but with little role in the repair of HO DSBs.

- How does the Esp1 activity decay from anaphase onset?

We have not checked this here but it is an interesting question for a follow-up story.

- Is cohesin required for the horseshoe folding of chr. III involved in MATa-to-alpha switching?

Probably not in view of our new data in Figures 2c and 4b-d. The Piazza papers are cited and discussed.

- Contribution of condensin in the recoil of the right ch.XII arm (Fig 4c) and on MAT switching.

The role of condensin, which overtakes some cohesin function in late-M as the reviewer reminds, is worth studying indeed. However, we feel this deserves a separate and focus-on study. We does discuss, though, that condensin loading onto the arms in anaphase may prevent Smc1-Smc3 from loading after DSBs.

Other points:

(4) Is the retrograde behavior in Fig. 4c dependent on recombination?

No, this is something we addressed in our previous paper (see Figure 4 in Nat Commun. 2019; 10(1):2862. doi: 10.1038/s41467-019-10742-8).

(5) Fig 3c: add a scheme of the system.

A scheme was already shown in the old Figure 2a (note that the old Fig 3c is now Fig S6).

(6) Fig 3b: annotate as in Fig 2b.

We have fixed this (now the referred figures are S6a and 3d, respectively).

(7) Authors used IAA concentrations 4- to 8-fold higher than commonly used. Given the solubility of IAA in DMSO (the most commonly used solvent), it is likely that authors treated their cells with >2% DMSO. This is expected to have broad transcriptional and physiological effects on yeast. A comparison of +IAA samples with a mock (DMSO) treatment would be more appropriate than a lack of treatment.

The IAA stock solution was 500 mM in DMSO, so the final DMSO concentration for an 8 mM IAA solution was 1.6% (v/v). Although the stock concentration was high and some precipitation was observed during preparation, we always heated, sonicated, and vigorously vortexed the stock tube before adding IAA to the cultures. Thus, we kept the uncertainty in the final IAA concentration to a minimum.

thanks...!!!

precisely. if you do not understand technically how the "tool" or "system" works, then your use is necessarily easily misguidable

because you don't know what you don't know?

For accessibility purposes, URL should not be written out like this. Maybe instead: "See details at our Open Access Publishing Partnerships LibGuide." with "Open Access Publishing Partnerships LibGuide" linking to that site through the tinyurl

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Тут говорится, что SendToGroup блокируется до получения подтверждений от r узлов. Интересно, насколько это замедляет работу?

А что если sequencer станет bottleneck при большой нагрузке? Все сообщения проходят через одну машину. Может, стоило распределить нагрузку как-то между несколькими sequencer'ами?

eLife Assessment

This important study by Zheng et al characterizes a novel Legionella pneumophila effector, Llfat1 (Lpg1387), which binds actin through a newly identified actin-binding domain. Data is convincing; structural analysis of the Llfat1 ABD-F-actin complex enabled the development of this domain as a probe for F-actin. Additionally, the authors show that Llfat1 functions as a lysine fatty acyltransferase targeting small GTPases, highlighting its importance in both bacterial pathogenesis and cytoskeletal biology.

Reviewer #1 (Public review):

The manuscript by Zeng et al. describes the discovery of an F-actin-binding Legionella pneumophila effector, which they term Lfat1. Lfat1 contains a putative fatty acyltransferase domain that structurally resembles the Rho-GTPase Inactivation (RID) domain toxin from Vibrio vulnificus, which targets small G-proteins. Additionally, Lfat1 contains a coiled-coil (CC) domain.

The authors identified Lfat1 as an actin-associated protein by screening more than 300 Legionella effectors, expressed as GFP-fusion proteins, for their co-localization with actin in HeLa cells. Actin binding is mediated by the CC domain, which specifically binds to F-actin in a 1:1 stoichiometry. Using cryo-EM, the authors determined a high-quality structure of F-actin filaments bound to the actin-binding domain (ABD) of Lfat1. The structure reveals that actin binding is mediated through a hydrophobic helical hairpin within the ABD (residues 213-279). A Y240A mutation within this region increases the apparent dissociation constant by two orders of magnitude, indicating a critical role for this residue in actin interaction.

The ABD alone was also shown to strongly associate with F-actin upon overexpression in cells. The authors used a truncated version of the Lfat1 ABD to engineer an F-actin-binding probe, which can be used in a split form. Finally, they demonstrate that full-length Lfat1, when overexpressed in cells, fatty acylates host small G-proteins, likely on lysine residues.

Comments on revisions:

Since LFAT1 cannot be produced in E. coli, it may be worth considering immunoprecipitating the protein from mammalian cells to see if it has activity in vitro. Presumably, actin will co-IP but the actin binding mutant can also be used. These are just suggestions to improve an already solid manuscript. Otherwise, I am happy with the paper.

Reviewer #2 (Public review):

Summary:

The manuscript by Zheng et al reports the structural and biochemical study of a novel effectors from the bacterial pathogen Legionella pneumophila. The authors continued from results from their earlier screening for L. pneumophila proteins that that affect host F-actin dynamics to show that Llfat1 (Lpg1387) interacts with actin via a novel actin-binding domain (ABD). The authors also determined the structure of the Lfat1 ABD-F-actin complex, which allowed them to develop this ABD as probe for F-actin. Finally, the authors demonstrated that Llfat1 is a lysine fatty acyltransferase that targets several small GTPases in host cells. Overall, this is a very exciting study and should be of great interest to scientists in both bacterial pathogenesis and actin cytoskeleton of eukaryotic cells.

Author response:

The following is the authors’ response to the original reviews

Reviewer #1:

(1) Legionella effectors are often activated by binding to eukaryote-specific host factors, including actin. The authors should test the following: a) whether Lfat1 can fatty acylate small G-proteins in vitro; b) whether this activity is dependent on actin binding; and c) whether expression of the Y240A mutant in mammalian cells affects the fatty acylation of Rac3 (Figure 6B), or other small G-proteins.

We were not able to express and purify the full-length recombinant Lfat1 to perform fatty acylation of small GTPases in vitro. However, In cellulo overexpression of the Y240A mutant still retained ability to fatty acylate Rac3 and another small GTPase RheB (see Figure 6-figure supplement 2). We postulate that under infection conditions, actin-binding might be required to fatty acylate certain GTPases due to the small amount of effector proteins that secreted into the host cell.

(2) It should be demonstrated that lysine residues on small G-proteins are indeed targeted by Lfat1. Ideally, the functional consequences of these modifications should also be investigated. For example, does fatty acylation of G-proteins affect GTPase activity or binding to downstream effectors?

We have mutated K178 on RheB and showed that this mutation abolished its fatty acylation by Lfat1 (see Author response image 1 below). We were not able to test if fatty acylation by Lfat1 affect downstream effector binding.

Author response image 1.

(3) Line 138: Can the authors clarify whether the Lfat1 ABD induces bundling of F-actin filaments or promotes actin oligomerization? Does the Lfat1 ABD form multimers that bring multiple filaments together? If Lfat1 induces actin oligomerization, this effect should be experimentally tested and reported. Additionally, the impact of Lfat1 binding on actin filament stability should be assessed. This is particularly important given the proposed use of the ABD as an actin probe.

The ABD domain does not form oligomer as evidenced by gel filtration profile of the ABD domain. However, we do see F-actin bundling in our in vitro -F-actin polymerization experiment when both actin and ABD are in high concentration (data not shown). Under low concentration of ABD, there is not aggregation/bundling effect of F-actin.

(4) Line 180: I think it's too premature to refer to the interaction as having "high specificity and affinity." We really don't know what else it's binding to.

We have revised the text and reworded the sentence by removing "high specificity and affinity."

(5) The authors should reconsider the color scheme used in the structural figures, particularly in Figures 2D and S4.

Not sure the comments on the color scheme of the structure figures.

(6) In Figure 3E, the WT curve fits the data poorly, possibly because the actin concentration exceeds the Kd of the interaction. It might fit better to a quadratic.

We have performed quadratic fitting and replaced Figure 3E.

(7) The authors propose that the individual helices of the Lfat1 ABD could be expressed on separate proteins and used to target multi-component biological complexes to F-actin by genetically fusing each component to a split alpha-helix. This is an intriguing idea, but it should be tested as a proof of concept to support its feasibility and potential utility.

It is a good suggestion. We plan to thoroughly test the feasibility of this idea as one of our future directions.

(8) The plot in Figure S2D appears cropped on the X-axis or was generated from a ~2× binned map rather than the deposited one (pixel size ~0.83 Å, plot suggests ~1.6 Å). The reported pixel size is inconsistent between the Methods and Table 1-please clarify whether 0.83 Å refers to super-resolution.

Yes, 0.83 Å is super-resolution.  We have updated in the cryoEM table

Reviewer #2:

Weaknesses:

(1) The authors should use biochemical reactions to analyze the KFAT of Llfat1 on one or two small GTPases shown to be modified by this effector in cellulo. Such reactions may allow them to determine the role of actin binding in its biochemical activity. This notion is particularly relevant in light of recent studies that actin is a co-factor for the activity of LnaB and Ceg14 (PMID: 39009586; PMID: 38776962; PMID: 40394005). In addition, the study should be discussed in the context of these recent findings on the role of actin in the activity of L. pneumophila effectors.

We have new data showed that Actin binding does not affect Lfat1 enzymatic activity. (see response to Reviewer #1). We have added this new data as Figure S7 to the paper. Accordingly, we also revised the discussion by adding the following paragraph.

“The discovery of Lfat1 as an F-actin–binding lysine fatty acyl transferase raised the intriguing question of whether its enzymatic activity depends on F-actin binding. Recent studies have shown that other Legionella effectors, such as LnaB and Ceg14, use actin as a co-factor to regulate their activities. For instance, LnaB binds monomeric G-actin to enhance its phosphoryl-AMPylase activity toward phosphorylated residues, resulting in unique ADPylation modifications in host proteins  (Fu et al, 2024; Wang et al, 2024). Similarly, Ceg14 is activated by host actin to convert ATP and dATP into adenosine and deoxyadenosine monophosphate, thereby modulating ATP levels in L. pneumophila–infected cells (He et al, 2025). However, this does not appear to be the case for Lfat1. We found that Lfat1 mutants defective in F-actin binding retained the ability to modify host small GTPases when expressed in cells (Figure S7). These findings suggest that, rather than serving as a co-factor, F-actin may serve to localize Lfat1 via its actin-binding domain (ABD), thereby confining its activity to regions enriched in F-actin and enabling spatial specificity in the modification of host targets.”

(2) The development of the ABD domain of Llfat1 as an F-actin domain is a nice extension of the biochemical and structural experiments. The authors need to compare the new probe to those currently commonly used ones, such as Lifeact, in labeling of the actin cytoskeleton structure.

We fully agree with the reviewer’s insightful suggestion. However, a direct comparison of the Lfat1 ABD domain with commonly used actin probes such as Lifeact, as well as evaluation of the split α-helix probe (as suggested by Reviewer #1), would require extensive and technically demanding experiments. These are important directions that we plan to pursue in future studies.

For all other minors, we have made corrections/changes in our revised text and figures.

少し読みづらかったので、以下みたいにするのどうでしょうか？ 「複数の属性にまたがるデータ検証を行いたい場合は、@model_validator デコレータを使用します。」

or

onderstreepte dingen zijn echt belangrijk

I just realized, why does my toes ate people. Is I normal? I think Shedletsky doed this

{[inject:un-greyLR]}

hi

moet T zijn!!!!!!

Shift-Command-Period (.): Show or hide hidden files and folders in Finder

robo world

The entire poem culminates in the phrase “shantih shantih shantih,” meaning “the peace that passeth understanding.” This comes from biblical origin, specifically Phillippians 4:7 which says “and the peace of God, which passeth all understanding, shall keep your hearts and minds though Christ Jesus.” I was struck by past scholars thoughts on this line, especially those of Sonia Rashid ‘25. She wrote “this triplet of peace is both a culmination and an invitation, suggesting that true tranquility may lie not in resolution but in the ongoing quest for harmony.” In her interpretation, the ending of the poem is both a conclusion and a continuation. After the reader has made the long journey through the poem, they expect an end destination. However, Eliot presents the reader with an expansion out to an existential question: what is the true nature of tranquility and harmony? It does not, in TWL, come from a definite conclusion. The poem does not provide a clean tie-up to all of the loose strands led dangling along the way. Instead, it is left in a state of limbo, forcing the reader back to the beginning. Re-reading the poem is the only way to find more clarity, as it is not given through the ending. The reader must dig deeper and further into all of the sources at play, in an attempt to make some semblance of meaning out of them. Alternatively, Eliot offers the option of “the peace that passeth understanding,” allowing the reader to stop and bask in the peace of an ending that requires nothing, that allows, as Sonia puts it, “ending [that] lead to new beginnings.”

I think it is particularly significant that the poem ends with not one, but two triplets, two sets of three: “Datta. Dayadhvam. Damyata.” and then “Shantih shantih shantih.” As I explored in a previous annotation—and as is very much relevant across the poem—three functions as a number of disruption—it unsettles the stability of two, breaking the pair or the binary or the dipole. And it is from two that a third can be formed—from both, as a mix. (Think Tiresias (man x woman), the mysterious third who is marked as neither man nor woman). Three is also a journey: low to middle to high. Or, in this case, it is middle to low to high (Datta then Dayadhvam then Damyata—address to humans, demons, gods). This is hopeful; there is movement, and trajectory.

Then there is the “Shantih shantih shantih.” As Lucas notes, shantih means peace in Sanskrit, and this connects to Philippians 4:7. It appears, as Lucas says, to be a continuum—both a culmination and a continued search for peace. But given the above, I actually find the third repetition ominous. What kind of disruption is the third “shantih” bringing, or what kind of distorted mixing? What tumultuous motion is to ensue? Unfortunately, I think it is clear that all is in fact not peaceful, with “Hieronymo’s mad againe.”

Again, Celina ’23 had me thinking more about this number. She notes other triplets in the poem which I would like to explore: the three questions asked in lines 121-123, the repetition of “Unreal” three times (as in “Unreal City” two of the times), and more.

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eLife Assessment

This study provides important insights into bacterial genome evolution by analyzing single-cell genome sequences of cyanobacteria from Yellowstone hot springs. Using compelling evidence, the authors demonstrate that both homologous recombination within species and frequent hybridization across species are major drivers of genome diversification. Despite the challenges that are inherent to sparse and fragmented single-cell data, the analyses are thorough, carefully controlled, and supported by multiple complementary approaches, making the conclusions highly robust. This work represents a significant advance in our understanding of microbial evolution in natural environments.

Reviewer #1 (Public review):

Summary:

What are the overarching principles by which prokaryotic genomes evolve? This fundamental question motivates the investigations in this excellent piece of work. While it is still very common in this field to simply assume that prokaryotic genome evolution can be described by a standard model from mathematical population genetics, and fit the genomic data to such a model, a smaller group of researchers rightly insists that we should not have such preconceived ideas and instead try to carefully look at what the genomic data tell us about how prokaryotic genomes evolve. This is the approach taken by the authors of this work. Lacking a tight theoretical framework, the challenge of such approaches is to device analysis methods that are robust to all our uncertainties about what the underlying evolutionary dynamics might be.

The authors here focus on a collection of ~300 single-cell genomes from a relatively well-isolated habitat with a relatively simple species composition, i.e. cyanobacteria living in hot springs in Yellowstone National Park. They convincingly demonstrate that the relative simplicity of this habitat increases our ability to interpret what the genomic data tells us about the evolutionary dynamics.

Using a very thorough and multi-faceted analysis of these data, the authors convincingly show that there are three main species of Synechococcus cyanobacteria living in this habitat, and that apart from very frequent recombination within each species (which is in line with insights from other recent studies) there is also a remarkably frequent occurrence of hybridization events between the different species, and with as of yet unindentified other genomes. Moreover, these hybridization events drive much of the diversity within each species. The authors also show convincing evidence that many of these hybridization events are not neutral but are driven by natural selection.

Strengths:

The great strength of this paper is that, by not making any preconceived assumptions about what the evolutionary dynamics is expected to look like, but instead devicing careful analysis methods to tease apart what the data tells us about what has happened in the evolution in these genomes, highly novel and unexpected results are obtained, i.e. the major role of hybridization across the 3 main species living in this habitat.

The analysis is very thorough and reading the detailed descriptions in the appendices it is clear that these authors took a lot of care in using these methods and avoiding the pitfalls that unfortunately affect many other studies in this research area.

The picture of the evolutionary dynamics of these three Synechococcus species that emerges from this analysis is quite novel and surprising. I think this study is a major stepping stone toward development of more realistic quantitative theories of genome evolution in prokaryotes.

The analysis methods that the authors employ are also partially quite novel and will no doubt by very valuable for analysis of many other datasets.

Weaknesses:

The main text is tight and concise, but this sort of hides the very large amount of careful complementary analyses that went into the conclusions presented in the main text. The appendices are quite well written but they are substantial, so that really understanding the paper is not an easy read. However, I do not really think the authors can be faulted for this. The topic is complex and a lot of care is required to make sure conclusions are valid.

A very interesting observation is that a lot of hybridization events (i.e. about half) originate from species other than the alpha, beta, and gamma Synechococcus species from which the genomes that are analyzed here derive. For this to occur, these other species must presumably also be living in the same habitat and must be relatively abundant. But if they are, why are they not being captured by the sampling? I did not see a clear explanation for this very common occurrence of hybridization events from outside of these Synechococcus species. The authors raise the possibility that these other species used to live in these hot springs but are now extinct or that the occur in other pools. I guess this is possible but I still find it puzzling and wonder if these donors could have been filtered out at some step of the experimental and/or analysis procedures.

Reviewer #2 (Public review):

Summary.

Birzu et al. describe two sympatric hotspring cyanobacterial species ("alpha" and "beta") and infer recombination across the genome, including inter-species recombination events (hybridization) based on single-cell genome sequencing. The evidence for hybridization is strong and the authors took care to control for artefacts such as contamination during sequencing library preparation. Despite hybridization, the species remain genetically distinct from each other. The authors also present evidence for selective sweeps of genes across both species - a phenomenon which is widely observed for antibiotic resistance genes in pathogens, but rarely documented in environmental bacteria.

Strengths.

This manuscript describes some of the most thorough and convincing evidence to date of recombination happening within and between co-habitating bacteria in nature. Their single-cell sequencing approach allows them to sample the genetic diversity from two dominant species. Although single-cell genome sequences are incomplete, they contain much more information about genetic linkage than typical short-read shotgun metagenomes, enabling a reliable analysis of recombination. The authors also go to great lengths to quality-filter the single-cell sequencing data and to exclude contamination and read mismapping as major drivers of the signal of recombination. This is a fascinating dataset with intricate analyses showing the great extent of between-species hybridization that is possible in nature.

Weaknesses.

This revised version is much improved, with a much clearer flow and organisation within both the main text and supplement. The remaining weaknesses that I note below are certainly not critical, but are simply useful context for the reader to keep in mind.

My main concern is that the evidence for selection on the hybridized genes is incomplete and statements about the 'overwhelming evidence for the crucial role played by selection' (lines 334-5) are a bit overstated. What fraction of the hybridization events were driven by positive selection? The breakdown of hard (15%) vs soft (85%) sweeps is given, out of 153 (as sidenote, it is not clear if this is 153 genes or events, troughs, etc.). But how many of the hybridization events (or genes) have evidence for a selective sweep relative to those that do not? I recognize that this may be a hard question to answer, because it may be statistically easier to identify a hybridization event that rises to high frequency due to positive selection from a neutral event that remains rare. Even a rough estimate would be useful; would it be something like 153 out of the number of core genes tested (~700)?

Regardless, I think that Figure 6 (A and B) could benefit from comparison to a neutral model, including hybridization but no selection to see if a similar pattern (notably, higher synonymous diversity in alpha troughs compared to the backbone) could arise due to hybridization alone without selection.

An implicit assumption in microbiology is often that cross-species recombination events are driven by selection. The authors recognize that "diversity troughs resulted from selective sweeps [...] likely overcame mechanistic barriers to recombination, genetic incompatibilities, and ecological differences" (lines 335-7) and thus would not be retained unless they had some strong adaptive value to offset these costs. There are surprisingly few tests of the hypothesis that cross-species recombination events tend to be driven by selection. An analysis of Streptococcus spp. genomes showed that between-species recombination events tended to be accompanied by positive selection, whereas most within-species events were not (Shapiro et al. Trends in Microbiology 2009; reanalysis of data from Lefebure & Stanhope, Genome Biology 2007). There are probably other examples out there, but the authors could highlight that they provide rare data to support a common expectation.

Author response:

The following is the authors’ response to the original reviews

Public Reviews:

Reviewer #1 (Public Review):

Summary:

What are the overarching principles by which prokaryotic genomes evolve? This fundamental question motivates the investigations in this excellent piece of work. While it is still very common in this field to simply assume that prokaryotic genome evolution can be described by a standard model from mathematical population genetics, and fit the genomic data to such a model, a smaller group of researchers rightly insists that we should not have such preconceived ideas and instead try to carefully look at what the genomic data tell us about how prokaryotic genomes evolve. This is the approach taken by the authors of this work. Lacking a tight theoretical framework, the challenge of such approaches is to devise analysis methods that are robust to all our uncertainties about what the underlying evolutionary dynamics might be.

The authors here focus on a collection of ~300 single-cell genomes from a relatively well-isolated habitat with relatively simple species composition, i.e. cyanobacteria living in hotsprings in Yellowstone National Park, and convincingly demonstrate that the relative simplicity of this habitat increases our ability to interpret what the genomic data tells us about the evolutionary dynamics.

Using a very thorough and multi-faceted analysis of these data, the authors convincingly show that there are three main species of Synechococcus cyanobacteria living in this habitat, and that apart from very frequent recombination within each species (which is in line with insights from other recent studies) there is also a remarkably frequent occurrence of hybridization events between the different species, and with as of yet unidentified other genomes. Moreover, these hybridization events drive much of the diversity within each species. The authors also show convincing evidence that these hybridization events are not neutral but are driven by selected by natural selection.

Strengths:

The great strength of this paper is that, by not making any preconceived assumptions about what the evolutionary dynamics is expected to look like, but instead devising careful analysis methods to tease apart what the data tells us about what has happened in the evolution in these genomes, highly novel and unexpected results are obtained, i.e. the major role of hybridization across the 3 main species living in this habitat.

The analysis is very thorough and reading the detailed supplementary material it is clear that these authors took a lot of care in devising these methods and avoiding the pitfalls that unfortunately affect many other studies in this research area.

The picture of the evolutionary dynamics of these three Synechococcus species that emerge from this analysis is highly novel and surprising. I think this study is a major stepping stone toward the development of more realistic quantitative theories of genome evolution in prokaryotes.

The analysis methods that the authors employ are also partially novel and will no doubt be very valuable for analysis of many other datasets.

We thank the reviewer for their appreciation of our work.

Weaknesses:

I feel the main weakness of this paper is that the presentation is structured such that it is extremely difficult to read. I feel readers have essentially no chance to understand the main text without first fully reading the 50-page supplement with methods and 31 supplementary materials. I think this will unfortunately strongly narrow the audience for this paper and below in the recommendations for the authors I make some suggestions as to how this might be improved.<br /> A very interesting observation is that a lot of hybridization events (i.e. about half) originate from species other than the alpha, beta, and gamma Synechococcus species from which the genomes that are analyzed here derive. For this to occur, these other species must presumably also be living in the same habitat and must be relatively abundant. But if they are, why are they not being captured by the sampling? I did not see a clear explanation for this very common occurrence of hybridization events from outside of these Synechococcus species. The authors raise the possibility that these other species used to live in these hot springs but are now extinct. I'm not sure how plausible this is and wonder if there would be some way to find support for this in the data (e.g that one does not observe recent events of import from one of these unknown other species). This was one major finding that I believe went without a clear interpretation.

We agree with the reviewer that the extent of hybridization with other species is surprising. While we do feel that our metagenome data provide convincing evidence that “X” species are not present in MS or OS, we cannot currently rule out the presence of X in other springs. In the revision we explicitly mention the alternative hypothesis (Lines 239-242).

The core entities in the paper are groups of orthologous genes that show clear evidence of hybridization. It is thus very frustating that exactly the methods for identifying and classifying these hybridization events were really difficult to understand (sections I and V of the supplement). Even after several readings, I was unsure of exactly how orthogroups were classified, i.e. what the difference between M and X clusters is, what a `simple hybrid' corresponds to (as opposed to complex hybrids?), what precisely the definitions of singlet and non-singlet hybrids are, etcetera. It also seems that some numbers reported in the main text do not match what is shown in the supplement. For example, the main text talks about "around 80 genes with more than three clusters (SM, Sec. V; fig. S17).", but there is no group with around 80 genes shown in Fig S17! And similarly, it says "We found several dozen (100 in α and 84 in β) simple hybrid loci" and I also cannot match those numbers to what is shown in the supplement. I am convinced that what the authors did probably made sense. But as a reader, it is frustrating that when one tries to understand the results in detail, it is very difficult to understand what exactly is going on. I mention this example in detail because the hybrid classification is the core of this paper, but I had similar problems in other sections.

We thank the reviewer for pointing out these issues with our original presentation. In the revision, we have redone most of the analysis to simplify the methods and check the consistency of the results. We did not find any qualitative differences in our results after reanalysis, but some of the numbers for different hybridization patterns have changed. The most notable difference is an increase in the number of alpha-gamma simple hybrids and a corresponding decrease in mixed-species clusters (now labeled mosaic hybrids). These transfers are difficult to assign because we only have access to a single gamma genome. We have added a short explanation of this point in Lines 219-222.

To improve the presentation, we significantly expanded the “Results” section to better explain our analysis and the different steps we take. We included two additional figures (Figs. 3 and 4) that illustrate the different types of hybrids and the heterogeneity in the diversity of alpha which is discussed in the main text and is important for interpreting our results. We also included two additional figures (Figs. 2 and 6) that were previously in the Appendix but were mentioned in the main text. We believe these changes should address most of the issues raised by the reviewer and hopefully make the manuscript easier to read.

Although I generally was quite convinced by the methods and it was clear that the authors were doing a very thorough job, there were some instances where I did not understand the analysis. For example, the way orthogroups were built is very much along the lines used by many in the field (i.e. orthoMCL on the graph of pairwise matchings, building phylogenies of connected components of the graph, splitting the phylogenies along long branches). But then to subdivide orthogroups into clusters of different species, the authors did not use the phylogenetic tree already built but instead used an ad hoc pairwise hierarchical average linkage clustering algorithm.

The reviewer is correct that there is an unexplained discrepancy between the clustering methods we used at different steps in our pipeline. We followed previous work by using phylogenetic distances for the initial clustering of orthogroups. On these scales we expect hybridization to play a minor role and phylogenetic distances to correlate reasonably well with evolutionary divergence. However, because of the extensive hybridization we observed, the use of phylogenetic models for species clustering is more difficult to justify. We therefore chose to simply use pairwise nucleotide distances, which make fewer assumptions about the underlying evolutionary processes and should be more robust. We have briefly explained our reasoning and the details of our clustering method in the revision (Lines 182-190).

Reviewer #2 (Public Review):

Summary:

Birzu et al. describe two sympatric hotspring cyanobacterial species ("alpha" and "beta") and infer recombination across the genome, including inter-species recombination events (hybridization) based on single-cell genome sequencing. The evidence for hybridization is strong and the authors took care to control for artefacts such as contamination during sequencing library preparation. Despite hybridization, the species remain genetically distinct from each other. The authors also present evidence for selective sweeps of genes across both species - a phenomenon which is widely observed for antibiotic resistance genes in pathogens, but rarely documented in environmental bacteria.

Strengths:

This manuscript describes some of the most thorough and convincing evidence to date of recombination happening within and between cohabitating bacteria in nature. Their single-cell sequencing approach allows them to sample the genetic diversity from two dominant species. Although single-cell genome sequences are incomplete, they contain much more information about genetic linkage than typical short-read shotgun metagenomes, enabling a reliable analysis of recombination. The authors also go to great lengths to quality-filter the single-cell sequencing data and to exclude contamination and read mismapping as major drivers of the signal of recombination.

We thank the reviewer for their appreciation of our work.

Weaknesses:

Despite the very thorough and extensive analyses, many of the methods are bespoke and rely on reasonable but often arbitrary cutoffs (e.g. for defining gene sequence clusters etc.). Much of this is warranted, given the unique challenges of working with single-cell genome sequences, which are often quite fragmented and incomplete (30-70% of the genome covered). I think the challenges of working with this single-cell data should be addressed up-front in the main text, which would help justify the choices made for the analysis.

We have significantly expanded the “Results” section to better justify and explain the choices we made during our analysis. We hope these changes address the reviewer’s concerns and make the manuscript more accessible to readers.

The conclusions could also be strengthened by an analysis restricted to only a subset of the highest quality (>70% complete) genomes. Even if this results in a much smaller sample size, it could enable more standard phylogenetic methods to be applied, which could give meaningful support to the conclusions even if applied to just ~10 genomes or so from each species. By building phylogenetic trees, recombination events could be supported using bootstraps, which would add confidence to the gene sequence clustering-based analyses which rely on arbitrary cutoffs without explicit measures of support.

It seems to us that the reviewer’s suggestion presupposes that the recombination events we find can be described as discrete events on an asexual phylogeny, similar to how rare mutations are treated in standard phylogenetic inference. Popular tools, such as ClonalFrame and its offshoots, have attempted to identify individual recombination events starting from these assumptions. But the main conclusion of both our linkage and SNP block analysis is that the ClonalFrame assumptions do not hold for our data. Under a clonal frame, the SNP blocks we observe should be perfectly linked, similar to mutations on an asexual tree. But our results in Fig. 7D show the opposite. Part of the issue may have been that in our original presentation, we only briefly discuss the results of our linkage analysis and refer readers to the Appendix for more details. To fix this issue we have added an extra figure (Fig. 2), showing rapid linkage decrease in both species and that at long distances the linkage values are essentially identical to the unlinked case, similar to sexual populations. We hope that this change will help clarify this point.

The manuscript closes without a cartoon (Figure 4) which outlines the broad evolutionary scenario supported by the data and analysis. I agree with the overall picture, but I do think that some of the temporal ordering of events, especially the timing of recombination events could be better supported by data. In particular, is there evidence that inter-species recombination events are increasing or decreasing over time? Are they currently at steady-state? This would help clarify whether a newly arrived species into the caldera experiences an initial burst of accepting DNA from already-present species (perhaps involving locally adaptive alleles), or whether recombination events are relatively constant over time.

The reviewer raises some very interesting questions about the dynamics of recombination in the population, which we hope to pursue in future work. We have added this as an open question in the Discussion (Lines 365-382).

These questions could be answered by counting recombination events that occur deeper or more recently in a phylogenetic tree.

The reviewer here seems to presuppose that recombination is rare enough that a phylogenetic tree can reliably be inferred, which is contrary to our linkage analysis (see the response to an earlier comment). Perhaps the reviewer missed this point in our original manuscript since it was discussed primarily in the Appendix. See also our response to a previous comment by the reviewer.

The cartoon also shows a 'purple' species that is initially present, then donates some DNA to the 'blue' species before going extinct. In this model, 'purple' DNA should also be donated to the more recently arrived 'orange' species, in proportion to its frequency in the 'blue' genome. This is a relatively subtle detail, but it could be tested in the real data, and this may actually help discern the order of the inferred recombination events.

We have included an extra figure in the main text (Fig. 6) that addresses the question of timing of events. A quantitative test of our cartoon model along the lines the reviewer suggested would certainly be worthwhile and we hope to do that in future work.  

The abstract also makes a bold claim that is not well-supported by the data: "This widespread mixing is contrary to the prevailing view that ecological barriers can maintain cohesive bacterial species..." In fact, the two species are cohesive in the sense that they are identifiable based on clustering of genome-wide genetic diversity (as shown in Fig 1A). I agree that the mixing is 'widespread' in the sense that it occurs across the genome (as shown in Figure 2A) but it is clearly not sufficient to erode species boundaries. So I believe the data is consistent with a Biological Species Concept (sensu Bobay & Ochman, Genome Biology & Evolution 2017) that remains 'fuzzy' - such that there are still inter-species recombination events, just not sufficient to erode the cohesion of genomic clusters. Therefore, I think the data supports the emerging picture of most bacteria abiding by some version of a BSC, and is not particularly 'contrary' to the prevailing view.

We have revised the phrase mentioned by the reviewer to “prevent genetic mixture between bacterial species,” which more accurately represents our conclusions. 

The final Results paragraph begins by posing a question about epistatic interactions, but fails to provide a definitive answer to the extent of epistasis in these genomes. Quantifying epistatic effects in bacterial genomes is certainly of interest, but might be beyond the scope of this paper. This could be a Discussion point rather than an underdeveloped section of the Results.

We agree with the reviewer that an exhaustive analysis of epistasis in the population is beyond the scope of the manuscript. Our original intention was to answer whether SNP blocks we discovered showed evidence of strong linkage, as might be expected if only a small number of strains are present in the population. In light of the previous comments by the reviewer regarding the consistency with the clonal frame hypothesis, we believe this is especially relevant for our results. Moreover, the results we found‑especially for the beta population‑were quite conclusive: SNP block linkages in beta are indistinguishable from an unlinked model. To avoid misdirecting the reader about the significance of our results, we have revised the relevant paragraph (Lines 316-319).

Recommendations For The Authors:

Reviewer #1 (Recommendations For The Authors):

Although I am entirely convinced of the validity of the results, methodology, and interpretations presented in this work, I must say I found the paper very hard to read. And I think I am really quite familiar with these kinds of approaches. I fear that for people other than experts on these kinds of comparative genomic analyses, this paper will be almost impossible to read. With the aim of expanding the audience for this compelling work, I think the authors might want to consider ways to improve the presentation.

At the end of a long project, the obtained results typically form a web of mutual interconnections and dependencies and one of the key challenges in presenting the results in a paper is having to untangle this web of connected results and analysis into a linear ordered narrative so that, at any point in the narrative, understanding the next point only depends on previous points in the narrative. I frankly feel that this paper fails at this.

The paper reads to me as if one author put together the supplement by essentially writing a report of all the analyses that were done together with supplementary figures summarizing all those analyses, and that another author then wrote the main text by using the materials in the supplement almost in the way a cook uses ingredients for a dish. Almost every other sentence in the main text refers to results in the (31!) supplementary figures and can only be understood by reading the appropriate corresponding sections in the supplementary materials. I found it essentially impossible to read the main text without having first read the entire 50-page supplement.

I think the paper could be hugely improved by trying to restructure the presentation so as to make it more linear. The main text can be expanded to include a summary of the crucial methods and analysis results from the supplement needed to understand the narrative in the main text. For example, as it currently stands it is really challenging to understand what is shown in figures 2 and 3 of the main text without having to first read a very substantial part of the supplement. Figure 3, even after having read the relevant sections in the supplement, took me quite a while to understand and almost felt like a puzzle to decypher. Rethinking which parts of the supplement are really necessary would also help. Finally, it would also help if the terminology was kept as simple, transparent, and consistent as possible.

I understand that my suggestion to thoroughly reorganize the presentation may feel like a big hassle, but I am afraid that in its current form, these important results are essentially rendered inaccessible to all but a small group of experts in this area. This paper deserves a wider readership.

We thank the reviewer for these valuable suggestions. In the revision, we have significantly expanded and restructured the “Results” section to make the presentation more linear, as the reviewer suggested (see our reply to the public comment by the reviewer for details). We hope these changes will make the manuscript easier to read.

Reviewer #2 (Recommendations For The Authors):

I found this paper challenging to follow since the main text was so condensed and the supplementary material so extensive. Given that eLife does not impose strong limits on the length of the main text, I suggest moving some key sections from the supplement into the main text to make it easier for the reader to follow rather than flipping back and forth. Adding to the confusion, supplementary figures were referenced out of order in the main text (e.g. S23 is referenced before S1). Please check the numbering and ensure figures are mentioned in the main text in the correct order.

We thank the reviewer for their feedback on the presentation of the results. In response to similar comments from Reviewer #1, we have significantly expanded and restructured the “Results” section to make it easier to read (see also our responses to Reviewer #1).

Page 2: The term 'coevolution' is typically reserved for two species that mutually impose selective pressures on one another (e.g. predator-prey interactions; see Janzen, Evolution 1980). In the context of these two cyanobacterial species, it's not clear that this is the case so I would simply refer to them 'cohabitating' or being sympatric in the same environment.

It is true that the term "coevolution” has become associated with predator-prey interactions, as the reviewer said. However, we feel that in our case “coevolution” fairly accurately describes the continual hybridization over long time scales we observe. We have therefore chosen to keep the term.

Page 3: The authors mention that the gamma SAG is ~70% complete, which turns out to be quite high. It would be useful to mention early in the Results the mean/median completeness across SAGs, and how this leads to some challenges in analysing the data. Some of the material from the Supplement could be moved into the Results here.

We have added a short note on the completeness in the Results (Lines 153-154). We have also added an extra figure in Appendix 1 with the completeness of all the SAGs for interested readers.

I was left puzzled by the sentence: "Alternatively, high rates of recombination could generate different genotypes within each genome cluster that are adapted to different temperatures, with the relative frequencies of each cluster being only a correlated and not a causal driver of temperature adaptation." This is suggesting that individual genes or alleles, rather than entire genomes, could be adapted to temperature. But figure 1B seems to imply that the entire genome is adapted to different temperatures. Anyway, this does not seem to be a key point and could probably be removed (or clarified if the authors deem this an important point, which I failed to understand).

We have revised this section to clarify the alternative hypothesis mentioned by the reviewer (Lines 100-103).

Page 4. 'Several dozen' hybrid genes were found, but please also specify how many genes were tested. In general, it would be good to briefly outline the sample size (SAGs or genes) considered for each analysis.

We have added the total numbers of genes we analyzed at each step of our analysis.

'Mosaic hybrid loci' are mentioned alongside the issue of poor alignment. Presumably, the mosaic hybrid loci are first filtered to remove the poor alignments? This should be specified, and please mention how many loci are retained before/after this filter.

We thank the reviewer for highlighting this important point. In the revision, we have implemented a more aggressive filtering of genes with poor alignments. We have added an extra paragraph to Appendix 1 (step 5 in the pipeline analysis) briefly explaining the issue.

Page 5. "By contrast, the diversity of mosaic loci was typical of other loci within beta, suggesting most of the beta genome has undergone hybridization." Please point to the data (figure) to support this statement.

We have restructured our discussion of the different hybrid loci so this comment is no longer relevant. In case the reviewer is interested, the synonymous diversity within beta was 0.047, while in mosaic hybrids it was 0.064.

Page 6. "The largest diversity trough contained 28 genes." Since this trough is discussed in detail and seems to be of interest, it would be nice to illustrate it, perhaps as an inset in Figure 2 or as a separate figure. If I understood correctly, this trough includes genes (in a nitrogen-fixation pathway) that are present in all genomes, but are exchanged by homologous recombination. So I don't think it's correct to say that the "ancestors acquired the ability to fix nitrogen." Rather, the different alleles of these same genes were present in the ancestor. So perhaps there was a selective sweep involving alleles in this region that provided adaptation to local nitrogen sources or concentrations, but not a gain of new genes. Perhaps I misunderstood, in which case clarification would be appreciated.

The reviewer raises an interesting possibility. We agree that it is in principle possible that the ancestor contained the nitrogen fixation genes and the selective sweep simply replaced the ancestral alleles. In this particular case, there is additional evidence that the entire pathway was acquired around roughly the same time from gene order. The gene order between alpha and beta is almost entirely different, with only a few segments containing more than 2-3 genes in the same order, as shown by Bhaya et al. 2007 and confirmed by additional unpublished analysis of the SAGs. One of the few exceptions is the nitrogen fixation pathway, which has essentially the same gene order over more than 20 kbp. Thus, if the ancestor of both alpha and beta contained the nitrogen-fixation pathway, we would expect these genes to be scatter across the genome. We have revised the sentences in question to clarify this point (Lines 260-271).

Page 6. Last paragraph on epistasis references Fig 3C, but I believe it should be Fig 3D.

Fixed.

Page 7. Figure 3 legend. "Note that alpha-2 is identical to gamma here." I believe it should be beta, not gamma.

The reviewer is correct. We have fixed this error.

Page 8. What is the evidence for "at least six independent colonizers"? I could not find the data supporting this claim.

The statement mentioned by the reviewer was based on the maximum number of species clusters we identified in different core genes. However, during the revision, we found that only a handful of genes contained five or more clusters. We did find several tens of genes with four clusters. In addition, Rosen et al. (2018) also found additional 16S clusters at low frequency in the same springs. Based on these results we conservatively estimate that at least four independent strains colonized the caldera, but the number could be much greater. We have revised the text in question accordingly (Lines 336-339) and added Fig. 2 in Appendix 1 to support the conclusion.

Page 9. Line 200: "acting to homogenize the population." It should be specified that the population is only homogenized at these introgressed loci, not genome-wide. Otherwise, the genome-wide species clusters seen in Fig 1 would not be maintained.

It is true that the selective sweeps that lead to diversity throughs only homogenize the introgressed loci. But other hybrid segments could also rise to high frequency in the population during the sweep through hitchhiking. The fact that we observe SNP blocks generated through secondary recombination events of introgressed segments throughout the genome supports this view. While we do not fully understand the dynamics of this process currently, we do feel that the current evidence supports the statement that mixing is occurring throughout the genome and not just at a few loci so we have kept the original statement.

The final sentence (lines 221-222) is vague and uninformative. On the one hand, "investigating whether hybridization plays a major role" is what the current manuscript has already done - depending on what is meant by 'major' (how much of the genome? Or whether there are ecological implications?). It is also not clear what is meant by a predictive theory and 'possible evolutionary scenarios. This should be elaborated upon, otherwise, it is not clear what the authors mean. Otherwise, this sentence could be cut.

We thank the reviewer for their feedback. One possible source of confusion could be that in this sentence we were referring to detecting hybridization in other communities. We have changed “these communities” to “other communities” to make this clearer.

Supplement.

Broadly speaking, I appreciate the thorough and careful analysis of the single cell data. On the other hand, it is hard to evaluate whether these custom analyses are doing what is intended in many cases. Would it be possible to consider an analysis using more established methods, e.g. taking a subset of genomes with 'good' completeness and using Panaroo to find the core and accessory genome, then ClonalFrameML or Gubbins to infer a phylogeny and recombination events? Such analyses could probably be applied to a subset of the sample with relatively complete genomes. I don't want to suggest an overly time-consuming analysis, but the authors could consider what would be feasible.

We have added a comparison between our analysis and that from two other methods, including ClonalFrameML mentioned by the author. One important point that we feel might have been lost in the first version is that our linkage results imply that recombination is not rare such that it can be mapped onto an asexual tree as assumed by ClonalFrameML. Note that this is not simply due to technical limitations due to incomplete coverage and is instead a consequence of the evolutionary dynamics of the population. Consistent with this, we found several inconsistencies in how recombination events were assigned by ClonalFrameML. We have summarized these conclusions in Appendix 7 of the revised manuscript.

Page 8. Line 190. What is meant by 'minimal compositional bias'?

We mean that the sample is not biased towards strains that grow in the lab. We have revised the sentence to clarify.

Page 25. Figure S14 is not referenced in the text.

We have added part of this figure to the main text since it illustrates one of our main results, namely that sites at long genomic distances are essentially unlinked.

Page 26. The 'unlinked controls' (line 530) are very useful, but it would be even more informative to see if these controls also show the same decline in linkage with distance in the genome as observed in the real data. In particular, it would be good to know if the observed rapid decline in linkage with distance in the low-diversity regions is also observed in controls. Currently, it is unclear if this observation might be due to higher uncertainty in inferring linkage in low-diversity regions, which by definition have less polymorphism to include in the linkage calculation.

We thank the reviewer for the suggestion. After further consideration, we have decided to remove the subsection on linkage decrease in the low-diversity regions. We feel such detailed quantitative analysis would be better suited for a more technical paper, which we hope to do at a later time.

Page 26. There are some sections with missing identifiers (Sec ??).

Fixed.

Page 27. The information about the typical breadth of SAG coverage (~30%) would be better to include earlier in the Supplement, and also mentioned in the main text so the reader can more easily understand the nature of the dataset.

We have added an extra figure with the SAG coverages to Appendix 1.

Page 29. Any sensitivity analysis around the S = 0.9 value? Even if arbitrary, could the authors provide justification why they think this value is reasonable?

We have significantly revised this section in response to earlier comments by one of the reviewers. We hope that this would clarify the details of our methods to interested readers. To answer the reviewer’s specific question, we chose this heuristic after examining the fraction of cells of each species in different species clusters. For the clusters assigned to alpha and beta, we found a sharp peak near one and that a cutoff of 0.9 captured most clusters while still being high enough to inconsistent with a mixed cluster.

Page 30. I could not see where Fig. S17 was mentioned in the text. Also, how are 'simple hybrid genes' defined?

We have removed this figure in the revision. The definition of the different types of hybrid genes have been added to the main text in response to a comment from the other reviewer.

Page 36. It is hard to see that divergence is 'high' relative to what reference. Would it be possible to include the expected value (from ref. 12) in the plot, or at least explicitly mentioned in the text?

We have added the mean synonymous and non-synonymous divergences between alpha and beta to the figures for reference.

Page 38. Line 770 "would be comparable to that of beta." This is not necessarily the case since beta could have a different time to its most recent common ancestor. It could have a different time to the last bottleneck or selective sweep, etc.

We thank the reviewer for pointing out this misleading statement. Our point here was that in the first scenario the TMRCA of alpha and beta would be similar since the diversity in the high-diversity alpha genes is similar to beta. We have clarified this statement in the revision.

Page 39. Line 793. The use of the term 'genomic backbone' implies the presence of a clonal frame, which is not what the data seems to support. Perhaps another term such as 'genetic diversity' would more appropriately capture the intended meaning here.

We agree with the reviewer that the low-diversity regions may not be asexual. We used “genomic backbone” to distinguish from the “clonal frame,” which is usually used to mean that the backbone is asexual. We have added a note in the revision to clarify this point.

Page 39. Lines 802-805. I found this explanation hard to follow. Could the logic be clarified?

We simply meant that although the beta distribution is unimodal, it is not consistent with a simple Poisson distribution, unlike in alpha. We have added an extra sentence to clarify this.

eLife Assessment

This valuable study uses tools of population and functional genomics to examine long non-coding RNAs (lncRNAs) in the context of human evolution. Analyses of computationally predicted human-specific lncRNAs and their genomic targets lead to the development of hypotheses regarding the potential roles of these genetic elements in human biology. The conclusions regarding evolutionary acceleration and adaptation, however, only incompletely take data and literature on human/chimpanzee genetics and functional genomics into account.

Reviewer #2 (Public review):

In this valuable manuscript, Lin et al attempt to examine the role of long non coding RNAs (lncRNAs) in human evolution, through a set of population genetics and functional genomics analyses that leverage existing datasets and tools. Although the methods are incomplete and at times inadequate, the results nonetheless point towards a possible contribution of long non coding RNAs to shaping humans, and suggest clear directions for future, more rigorous study.

Comments on revisions:

I thank the authors for their revision and changes in response to previous rounds of comments. As before, I appreciate the changes made in response to my comments, and I think everyone is approaching this in the spirit of arriving at the best possible manuscript, but we still have some deep disagreements on the nature of the relevant statistical approach and defining adequate controls. I highlight a couple of places that I think are particularly relevant, but note that given the authors disagree with my interpretation, they should feel free to not respond!

(1) On the subject of the 0.034 threshold, I had previously stated:<br /> "I do not agree with the rationale for this claim, and do not agree that it supports the cutoff of 0.034 used below."

In their reply to me, the authors state:<br /> "What we need is a gene number, which (a) indicates genes that effectively differentiate humans from chimpanzees, (b) can be used to set a DBS sequence distance cutoff. Since this study is the first to systematically examine DBSs in humans and chimpanzees, we must estimate this gene number based on studies that identify differentially expressed genes in humans and chimpanzees. We choose Song et al. 2021 (Song et al. Genetic studies of human-chimpanzee divergence using stem cell fusions. PNAS 2021), which identified 5984 differentially expressed genes, including 4377 genes whose differential expression is due to trans-acting differences between humans and chimpanzeees. To the best of our knowledge, this is the only published data on trans-acting differences between humans and chimpanzeees, and most HS lncRNAs and their DBSs/targets have trans-acting relationships (see Supplementary Table 2). Based on these numbers, we chose a DBS sequence distance cutoff of 0.034, which corresponds to 4248 genes (the top 20%), slightly fewer than 4377."

I have some notes here. First, Agoglia et al, Nature, 2021, also examined the nature of cis vs trans regulatory differences between human and chimps using a very similar set up to Song et al; their Supplementary Table 4 enables the discovery of genes with cis vs trans effects although admittedly this is less straightforward than the Song et al data. Second, I can't actually tell how the 4377 number is arrived at. From Song et al, "Of 4,671 genes with regulatory changes between human-only and chimpanzee-only iPSC lines, 44.4% (2,073 genes) were regulated primarily in cis, 31.4% (1,465 genes) were regulated primarily in trans, and the remaining 1,133 genes were regulated both in cis and in trans (Fig. 2C). This final category was further broken down into a cis+trans category (cis- and trans-regulatory changes acting in the same direction) and a cis-trans category (cis- and trans-regulatory changes acting in opposite directions)." Even when combining trans-only and cis&trans genes that gives 2,598 genes with evidence for some trans regulation. I cannot find 4,377 in the main text of the Song et al paper.

Elsewhere in their response, the authors respond to my comment that 0.034 is an arbitrary threshold by repeating the analyses using a cutoff of 0.035. I appreciate the sentiment here, but I would not expect this to make any great difference, given how similar those numbers are! A better approach, and what I had in mind when I mentioned this, would be to test multiple thresholds, ranging from, eg, 0.05 to 0.01 at some well-defined step size.

(2) The authors have introduced a new TFBS section, as a control for their lncRNAs - this is welcome, though again I would ask for caution when interpreting results. For instance, in their reply to me the authors state:<br /> "The number of HS TFs and HS lncRNAs (5 vs 66) alone lends strong evidence suggesting that HS lncRNAs have contributed more significantly to human evolution than HS TFs (note that 5 is the union of three intersections between and the three )."

But this assumes the denominator is the same! There are 35899 lncRNAs according to the current GENCOVE build; 66/35899 = 0.0018, so, 0.18% of lncRNAs are HS. The authors compare this to 5 TFs. There are 19433 protein coding genes in the current GENCOVE build, which naively (5/19433) gives a big depletion (0.026%) relative to the lnc number. However, this assumes all protein coding genes are TFs, which is not the case. A quick search suggests that ~2000 protein coding genes are TFs (see, eg, https://pubmed.ncbi.nlm.nih.gov/34755879/); which gives an enrichment (although I doubt it is a statistically significant one!) of HS TFs over HS lncRNAs (5/2000 = 0.0025). Hence my emphasis on needing to be sure the controls are robust and valid throughout!

(3) In my original review I said:<br /> line 187: "Notably, 97.81% of the 105141 strong DBSs have counterparts in chimpanzees, suggesting that these DBSs are similar to HARs in evolution and have undergone human-specific evolution." I do not see any support for the inference here. Identifying HARs and acceleration relies on a far more thorough methodology than what's being presented here. Even generously, pairwise comparison between two taxa only cannot polarise the direction of differences; inferring human-specific change requires outgroups beyond chimpanzee.

In their reply to me, the authors state:<br /> Here, we actually made an analogy but not an inference; therefore, we used such words as "suggesting" and "similar" instead of using more confirmatory words. We have revised the latter half sentence, saying "raising the possibility that these sequences have evolved considerably during human evolution".

Is the aim here to draw attention to the ~2.2% of DBS that do not have a counterpart? In that case, it would be better to rewrite the sentence to emphasise those, not the ones that are shared between the two species? I do appreciate the revised wording, though.

(4) Finally, Line 408: "Ensembl-annotated transcripts (release 79)" Release 79 is dated to March 2015, which is quite a few releases and genome builds ago. Is this a typo? Both the human and the chimpanzee genome have been significantly improved since then!

Author response:

The following is the authors’ response to the previous reviews

Public Reviews:

Reviewer #2 (Public review):

In this valuable manuscript, Lin et al attempt to examine the role of long non coding RNAs (lncRNAs) in human evolution, through a set of population genetics and functional genomics analyses that leverage existing datasets and tools. Although the methods are incomplete and at times inadequate, the results nonetheless point towards a possible contribution of long non coding RNAs to shaping humans, and suggest clear directions for future, more rigorous study.

Comments on revisions:

I thank the authors for their revision and changes in response to previous rounds of comments. As it had been nearly two years since I last saw the manuscript, I reread the full text to familiarise myself again with the findings presented. While I appreciate the changes made and think they have strengthened the manuscript, I still find parts of it a bit too speculative or hyperbolic. In particular, I think claims of evolutionary acceleration and adaptation require more careful integration with existing human/chimpanzee genetics and functional genomics literature.

We thank the reviewer heartfully for the great patience and valuable comments, which have helped us further improve the manuscript. Before responding to comments point by point, we provide a summary here.

(1) On parameters and cutoffs.

Parameters and cutoffs influence data analysis. The large number of Supplementary Notes, Supplementary Figures, and Supplementary Tables indicates that we paid great attention to the influence of parameters and robustness of analyses. Specifically, here we explain the DBS sequence distance cutoff of 0.034, which determines the top 20% genes that most differentiate humans from chimpanzees and influences the gene set enrichment analysis (Figure 2). As described in the revised manuscript, we estimated this cutoff based on Song et al., verified its rationality based on Prufer et al. (Song et al. 2021; Prufer et al. 2017), and measured its influence by examining slightly different cutoff values (e.g., 0.035).

(2) Analyses of HS TFs and HS TF DBSs.

It is desirable to compare the contribution of HS lncRNAs and HS TFs to human evolution. Identifying HS TFs faces the challenges that different institutions (e.g., NCBI and Ensembl) annotate orthologous genes using different criteria, and that multiple human TF lists have been published by different research groups. Recently, Kirilenko et al. identified orthologous genes in hundreds of placental mammals and birds and organized different types of genes into datasets of parewise comparison (e.g., hg38-panTro6) using humans and mice as references (Kirilenko et al. Integrating gene annotation with orthology inference at scale. Science 2023). Based on (a) the many2zero and one2zero gene lists in the “hg38-panTro6” dataset, (b) three human TF lists reported by two studies (Bahram et al. 2015; Lambert et al. 2018) and used in the SCENIC package, we identified HS TFs. The number of HS TFs and HS lncRNAs (5 vs 66) alone lends strong evidence suggesting that HS lncRNAs have contributed more significantly to human evolution than HS TFs (note that 5 is the union of three intersections between <many2zero + one2zero> and the three <human TF list>).

TF DBS (i.e., TFBS) prediction has also been challenging because they are very short (mostly about 10 bp) and TF-DNA binding involves many cofactors (Bianchi et al. Zincore, an atypical coregulator, binds zinc finger transcription factors to control gene expression. Science 2025). We used two TF DBS prediction programs to predict HS TF DBSs, including the well-established FIMO program (whose results have been incorporated into the JASPAR database) (Rauluseviciute et al. JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles Open Access. NAR 2023) and the recently reported CellOracle program (Kamimoto et al. Dissecting cell identity via network inference and in silico gene perturbation. Nature 2023). Then, we performed downstream analyses and obtained two major results. One is that on average (per base), fewer selection signals are detected in HS TF DBSs (anyway, caution is needed because TF DBSs are very short); the other is that HS TFs and HS lncRNAs contribute to human evolution in quite different ways (Supplementary Figs. 25 and 26).

(3) On genes with more transcripts may appear as spurious targets of HS lncRNAs.

Now, the results of HS TF DBSs allow us to address the question of whether genes with more transcripts may appear as spurious targets of HS lncRNAs. We note that (a) we predicted HS lncRNA DBSs and HS TF DBSs in the same promoter regions before the same 179128 Ensembl-annotated transcripts (release 79), (b) we used the same GTEx transcript expression matrices in the analyses of HS TF DBSs and HS lncRNA DBSs (the GTEx database includes gene expression matrices and transcript expression matrices, the latter includes multiple transcripts of a gene). Thus, the analyses of HS TF DBSs provide an effective control for examining the question of whether genes with more transcripts may appear as spurious targets of HS lncRNAs, and consequently, cause the high percentages of HS lncRNA-target transcript pairs that show correlated expression in the brain (Figure 3). We find that the percentages of HS TF-target transcript pairs that show correlated expression are also high in the brain, but the whole profile in GTEx tissues is significantly different from that of HS lncRNA DBSs (Figure 3A; Supplementary Figure 25). On the other hand, on the distribution of significantly changed DBSs in GTEx tissues, the difference between HS lncRNA DBSs and HS TF DBSs is more apparent (Figure 3B; Supplementary Figure 26). Together, these suggest that the brain-enriched distribution of co-expressed HS lncRNA-target transcript pairs must arise from HS lncRNA-mediated transcriptional regulation rather than from the transcript number difference.

(4) Additional notes on HS TFs and HS TF DBSs.

First, the “many2zero” and “one2zero” gene lists in the “hg38-panTro6” dataset of Kirilenko et al. provide the most update, but not most complete, data on human-specific genes because “hg38-panTro6” is a pairwise comparison. On the other hand, the Ensembl database also annotates orthologous genes, but lacks such pairwise comparisons as “hg38-panTro6”. Therefore, not all HS genes based on “hg38-panTro6” agree with orthologous genes in the Ensembl database. Second, if HS genes are identified based on both Ensembl and Kirilenko et al., HS TFs will be fewer.

(5) On speculative or hyperbolic claims.

First, the title “Human-specific lncRNAs contributed critically to human evolution by distinctly regulating gene expression” is now further supported by HS TF DBSs analyses. Second, we have carefully revised the entire manuscript, trying to make it more readable, accurate, logically reasonable, and biologically acceptable. Third, specifically, in the revision, we avoid speculative or hyperbolic claims in results, interpretations, and discussions as possible as we can. This includes the tone-down of statements and claims, for example, using “reshape” to replace “rewire” and using “suggest” to replace “indicate”. Since the revisions are pervasive, we do not mark all of them, except those that are directly relevant to the reviewer’s comments.

(1) Line 155: "About 5% of genes have significant sequence differences in humans and chimpanzees," This statement needs a citation, and a definition of what is meant by 'significant', especially as multiple lines below instead mention how it's not clear how many differences matter, or which of them, etc.

Different studies give different estimates, from 1.24% (Ebersberger et al. Genomewide Comparison of DNA Sequences between Humans and Chimpanzees. Am J Hum Genet. 2002) to 5% (Britten RJ. Divergence between samples of chimpanzee and human DNA sequences is 5%, counting indels. PNAS 2002). The 5% for significant gene sequence differences arises when considering a broader range of genetic variations, particularly insertions and deletions of genetic material (indels). To provide more accurate information, we have replaced this simple statement with a more comprehensive one and cited the above two papers.

(2) line 187: "Notably, 97.81% of the 105141 strong DBSs have counterparts in chimpanzees, suggesting that these DBSs are similar to HARs in evolution and have undergone human-specific evolution." I do not see any support for the inference here. Identifying HARs and acceleration relies on a far more thorough methodology than what's being presented here. Even generously, pairwise comparison between two taxa only cannot polarise the direction of differences; inferring human-specific change requires outgroups beyond chimpanzee.

Here, we actually made an analogy but not an inference; therefore, we used such words as “suggesting” and “similar” instead of using more confirmatory words. We have revised the latter half sentence, saying “raising the possibility that these sequences have evolved considerably during human evolution”.

(3) line 210: "Based on a recent study that identified 5,984 genes differentially expressed between human-only and chimpanzee-only iPSC lines (Song et al., 2021), we estimated that the top 20% (4248) genes in chimpanzees may well characterize the human-chimpanzee differences". I do not agree with the rationale for this claim, and do not agree that it supports the cutoff of 0.034 used below. I also find that my previous concerns with the very disparate numbers of results across the three archaics have not been suitably addressed.

(1) Indeed, “we estimated that the top 20% (4248) genes in chimpanzees may well characterize the human-chimpanzee differences” is an improper claim; we made this mistake due to the flawed use of English.

(2) What we need is a gene number, which (a) indicates genes that effectively differentiate humans from chimpanzees, (b) can be used to set a DBS sequence distance cutoff. Since this study is the first to systematically examine DBSs in humans and chimpanzees, we must estimate this gene number based on studies that identify differentially expressed genes in humans and chimpanzees. We choose Song et al. 2021 (Song et al. Genetic studies of human–chimpanzee divergence using stem cell fusions. PNAS 2021), which identified 5984 differentially expressed genes, including 4377 genes whose differential expression is due to trans-acting differences between humans and chimpanzeees. To the best of our knowledge, this is the only published data on trans-acting differences between humans and chimpanzeees, and most HS lncRNAs and their DBSs/targets have trans-acting relationships (see Supplementary Table 2). Based on these numbers, we chose a DBS sequence distance cutoff of 0.034, which corresponds to 4248 genes (the top 20%), slightly fewer than 4377.

(3) If we chose DBS sequence distance cutoff=0.033 or 0.035, slightly more or fewer genes would be determined, raising the question of whether they would significantly influence the downstream gene set enrichment analysis (Figure 2). We found that 91 genes have a DBS sequence distance of 0.034. Thus, if cutoff=0.035, 4248-91=4157 genes were determined, and the influence on gene set enrichment analysis was very limited.

(4) On the disparate numbers of results across the three archaics. Figure 1A is based on Figure 2 in Prufer et al. 2017. At first glance, our Figure 1A indicates that Altai Neanderthal is older than Denisovan (upon kya), making our result “identified 1256, 2514, and 134 genes in Altai Neanderthals, Denisovans, and Vindija Neanderthals” unreasonable. However, Prufer et al. (2017) reported that “It has been suggested that Denisovans received gene flow from a hominin lineage that diverged prior to the common ancestor of modern humans, Neandertals, and Denisovans……In agreement with these studies, we find that the Denisovan genome carries fewer derived alleles that are fixed in Africans, and thus tend to be older, than the Altai Neandertal genome”. This note by Prufer et al. provides an explanation for our result, which is that more genes with large DBS sequence distances were identified in Denisovans than in Altai Neanderthals. Of course, the 1256, 2514, and 134 depend on the cutoff of 0.034. If cutoff=0.035, these numbers change slightly, but their relationships remain (i.e., more genes in Denisovans). We examined multiple cutoff values and found that more genes in Denisovans have large DBS sequence distances than in Altai Neanderthals.

(4) I also think that there is still too much of a tendency to assume that adaptive evolutionary change is the only driving force behind the observed results in the results. As I've stated before, I do not doubt that lncRNAs contribute in some way to evolutionary divergence between these species, as do other gene regulatory mechanisms; the manuscript leans down on it being the sole, or primary force, however, and that requires much stronger supporting evidence. Examples include, but are not limited to:

(1) Indeed, the observed results are also caused by other genomic elements and mechanisms (but it is hardly feasible to identify and differentiate them in a single study), and we do not assume that adaptive evolutionary change is the only driving force. Careful revisions have been made to avoid leaving readers the impression that we have this tendency or hold the simple assumption.

(2) Comparing HS lncRNAs to HS TFs is critical, and we have done this.

(5) line 230: "These results reveal when and how HS lncRNA-mediated epigenetic regulation influences human evolution." This statement is too speculative.

We have toned down the statement, just saying “These results provide valuable insights into when and how HS lncRNA-mediated epigenetic regulation impacts human evolution”.

Line 268: "yet the overall results agree well with features of human evolution." What does this mean? This section is too short and unclear.

(1) First, the sentence “Selection signals in YRI may be underestimated due to fewer samples and smaller sample sizes (than CEU and CHB), yet the overall results agree well with features of human evolution” has been deleted, because CEU, CHB, and YRI samples are comparable (100, 99, and 97, respectively).

(2) Now the sentence has been changed to “These results agree well with findings reported in previous studies, including that fewer selection signals are detected in YRI (Sabeti et al., 2007; Voight et al., 2006)”.

(3) On “This section is too short and unclear” - To make the manuscript more readable, we adopt short sections instead of long ones. This section expresses that (a) our finding that more selection signals were detected in CEU and CHB than in YRI agrees with well-established findings (Voight et al. A Map of Recent Positive Selection in the Human Genome. PLoS Biology 2006; Sabeti et al. Genome-wide detection and characterization of positive selection in human populations. Nature 2007), (b) in considerable DBSs, selection signals were detected by multiple tests.

Line 325: "and form 198876 HS lncRNA-DBS pairs with target transcripts in all tissues." This has not been shown in this paper - sequence based analyses simply identify the “potential” to form pairs.

This section describes transcriptomic analysis using the GTEx data. Indeed, target transcripts of HS lncRNAs are results of sequence-based analysis, and a predicted target is not necessarily regulated by the HS lncRNA in a tissue. Here, “pair” means a pair of HS lncRNA-target transcript whose expression shows significant Pearson correlation in a GTEx tissue (by the way, we do not mean correlation equals regulation; actually, we identified HS lncRNA-mediated transcriptional regulation upon both DBS-targeting relationship and correlation relationship).

Line 423: "Our analyses of these lncRNAs, DBSs, and target genes, including their evolution and interaction, indicate that HS lncRNAs have greatly promoted human evolution by distinctly rewiring gene expression." I do not agree that this conclusion is supported by the findings presented - this would require significant additional evidence in the form of orthogonal datasets.

(1) As mentioned above, we have used “reshape” to replace “rewire” and used “suggest” to replace “indicate”. In addition, we have substantially revised the Discussion, in which this sentence is replaced by “our results suggest that HS lncRNAs have greatly reshaped (or even rewired) gene expression in humans”.

(2) Multiple citations have been added, including Voight et al. 2006 (Voight et al. A Map of Recent Positive Selection in the Human Genome. PLoS Biology 2006) and Sabeti et al. 2007 (Sabeti et al. Genome-wide detection and characterization of positive selection in human populations. Nature 2007).

(3) We have analyzed HS TF DBSs, and the obtained results also support the critical contribution of HS lncRNAs.

I also return briefly to some of my comments before, in particular on the confounding effects of gene length and transcript/isoform number. In their rebuttal the authors argued that there was no need to control for this, but this does in fact matter. A gene with 10 transcripts that differ in the 5' end has 10 times as many chances of having a DBS than a gene with only 1 transcript, or a gene with 10 transcripts but a single annotated TSS. When the analyses are then performed at the gene level, without taking into account the number of transcripts, this could introduce a bias towards genes with more annotated isoforms. Similarly, line 246 focuses on genes with "SNP numbers in CEU, CHB, YRI are 5 times larger than the average." Is this controlled for length of the DBS? All else being equal a longer DBS will have more SNPs than a shorter one. It is therefore not surprising that the same genes that were highlighted above as having 'strong' DBS, where strength is impacted by length, show up here too.

(1) In gene set enrichment analysis (Figure 2, which is a gene-level analysis), when determining genes differentiating humans from chimpanzees based on DBS sequence distance, if a gene has multiple transcripts/DBSs, we choose the DBS with the largest distance. That is, the input to g:Profiler is a non-redundant gene list.

(2) In GTEx data analysis (Figure 3, which is a transcriptome-level analysis), the analyses of HS TF DBSs using the GTEx data provide evidence suggesting that different DBS/transcript numbers of genes are unlikely to cause confounding effects. As explained above, we predicted HS TF DBSs in the same promoter regions of 179128 Ensembl-annotated transcripts (release 79), but Supplementary Figures 25 and 26 are distinctly different from Figure 3AB.

(3) In evolutionary analysis, a gene with 10 DBSs has a higher chance of having selection signals than a gene with 1 DBS. This is biologically plausible, because many conserved genes have novel transcripts whose expression is species-, tissue-, or developmental period-specific, and DBSs before these novel transcripts may differ from DBSs before conserved transcripts.

(4) “line 246 focuses on genes with "SNP numbers in CEU, CHB, YRI are 5 times larger than the average." Is this controlled for the length of the DBS?” - This is a defect. We have now computed SNP numbers per base and used the new table to replace the old Supplementary Table 8. After examining the new table, we find that the major results of SNP analysis remain.

(5) On “Is this controlled for length of the DBS? All else being equal a longer DBS will have more SNPs than a shorter one” - We do not think there are reasons to control for the length of DBSs; also, what “All else being equal” means matters. First, DBS sequences have specific features; thus, the feature of a long DBS is stronger than the feature of a short one, making a long DBS less likely to be generated by chance in the genome and less likely to be predicted wrongly than a short one. This means that longer DBSs are less likely to be false ones (note our explanation that the chance of a DBS of 147 bp, the mean length of DBSs, to be wrongly predicted is extremely low, p<8.2e-19 to 1.5e-48). Second, the difference in length suggests a difference in binding affinity, which in turn influences the regulation of the specific transcripts and influences the analysis of GTEx data. Third, it cannot be excluded that some SNPs may be selection signals (detecting selection signal is challenging, and many selection signals cannot be detected by statistical tests, see Grossman et al. A composite of multiple signals distinguishes causal variants in regions of positive selection. Science 2010).

(6) On “It is therefore not surprising that the same genes that were highlighted above as having 'strong' DBS, where strength is impacted by length” - Indeed, strength is influenced by length, see the above response.

Recommendations for the authors:

Reviewer #2 (Recommendations for the authors):

Finally, figure 1 panels D and F are not legible - the font is tiny! There's also a typo in panel A, where "Homo Sapien" should be "Homo sapiens".

(1) “Homo sapien” is changed to “Homo sapiens”.

(2) Even if we double the font size, they are still too small. Inserting a very large panel D into Figure 1 will make Figure 1 ugly, and converting Figure 1D into an independent figure is unnecessary. Actually, panels 1D and F are illustrative figures; the full Fig.1D is Supplementary Figure 6, and the full Fig.1F is Figure 3. We have revised Fig.1’s legend to explain these.

Dit is de scope. Val het harmoniseren van databestanden zodat softwarematig de bestanden zonder problemen worden ingelezen, binnen de scope?

Is plan van aanpak niet een betere titel?

Dit is het doel.

Dit valt onder aanleiding.

Dat zijn geen doelen. Het doel is onderzoeken welke data noodzakelijk zijn in het informatiemodel en op welke wijze die data moeten worden aangeleverd. De beschreven opsommingen is het plan van aanpak (noodzakelijke acties) om dat doel te bereiken.

In het Voorwoord staat dat dit document beschrijft de verkenning naar nut en noodzaak voor het opstellen va een informatiemodel voor civiele kunstwerken i.h.k.v. de vervangings- en renovatieopgave. Dat match dus niet met elkaar. In de Inleiding wordt geïnsinueerd dat de verkenning al gedaan is, conclusie is dat het opstellen van een informatiemodel noodzakelijk is en gewenst is bij verschillende partijen (TNO, RWS en Platform Bruggen) en dat dit document onderzoekt welke data vast gelegd dienen te worden.

het zoeken naar informatie en het afstemmen en vertalen ervan. Dat leest makkelijker

weghalen

, vervangen door 'en'

minus spatie

spatie

de constructie EN de ... of de ... VAN de constructie. Lijkt een woord te ontbreken

indien mogelijk refereren naar een daadwerkelijke doc nr en of titel ipv 'eigen boekje' dat klinkt wat minder

ik twijfel even of je dit al zo feitelijk neer kunt zetten ivm dat het doc nog in ontwikkeling is. Of je moet doelen op de basis die er al is, maar dat is verweven in de algemene BS

uitlijning

typo

typo

persoonlijk zou ik hier 'het' tussenzetten

omdat de informatie 'platgeslagen' is en dus niet in te laden als data in modellen?

ontbreekt een '.'

typo

ik heb hier ook eens aan gerefereerd en kreeg toen de wind van voren over de uitvoering van dit onderzoek en dat gemeenten echt wel weten hoe en wat

typo

overweeg: door aan de markt de geoogste materialen aan te bieden

uitlijning klopt niet

bewust met hoofdletter? Later ook bij Constructieberekeningen

dit stuk loop niet soepel. Dus tenzij dat de bedoeling is, moet het herschreven worden

typo

deze zin is te lang en daardoor lastig te begrijpen. Opdelen in meerdere zinnen

ontbreekt 'de'

rond of rondom

klopt het dat hier 2x hetzelfde staat?

snap deze opsomming hier niet goed

volgens mij is 'lijnen' beter

for - linguistically motivated information retrieval

• Via de regra, o doador não está sujeito à responsabilização por evicção ou vício redibitório.

• Contudo, em caso de doação para casamento com pessoa determinada e certa, se não haver estipulação em contrário, haverá sim responsabilidade do doador quanto à evicção.

Mesmo que adquirido o bem em leilão, a lei assegura a responsabilidade pela evicção.

for - language - linguistic normalization - different phrases with the same meaning - different syntax, similar semantics

eLife Assessment

This valuable study is a comprehensive investigation into the regulatory mechanisms and regional distribution of enteroendocrine cell subtypes in the Drosophila midgut, significantly advancing the understanding of how WNT and BMP gradients contribute to EE diversity. The methodological foundation and robust genetic evidence are solid in supporting the key roles of compartment boundary signals, particularly WNT and BMP, in specifying EE subtypes and division modes. However, there is a lack of full mechanistic insight regarding Notch pathway involvement, incomplete quantification of phenotype data, and insufficient global pattern analysis, which detracts from fully supporting some proposed models. Overall, the study provides a platform for future work but would benefit from stronger data integration and expanded mechanistic exploration.

Reviewer #1 (Public review):

This valuable study explores the regulatory mechanisms underlying the regional distribution of enteroendocrine cell subtypes in the Drosophila midgut. The regional distribution of EE cell subtypes is carefully documented, and the data convincingly show that each EE cell subtype has a unique spatial pattern. The study aims at determining how the spatial distribution of EE cell subtypes is established and maintained, and explores the roles of three pathways: Notch, WNT, and BMP. The data show evidence that Notch signaling regulates the subtype specificity, being necessary for the specification of Type II, but not Type I and III EE cell subtype specification. The immunofluorescence data in Figure 3 are convincing, but the analysis is incomplete due to a lack of quantification. How Notch signaling activity relates to the emergence of the regional EE cell patterns remains unclear.

As WNT and BMP are known as morphogens, the study explores their expression patterns and their roles in establishing and maintaining the subtype identities. The observed patterns of WNT and BMP are consistent with earlier studies. Manipulation of WNT and BMP pathway activities in intestinal stem cells is shown to have some region-specific effects on specific EE cell subtypes. The overall conclusion that both WNT and BMP have local effects on EE cell subtypes is based on solid evidence. However, the study falls short in achieving its main objective, i.e., to explain the regional subtype patterns by the action of WNT and BMP gradients. Despite displaying a large volume of phenotypic data in Figures 4-7, the study remains incomplete in providing sufficient evidence to support the models shown in Figures 7 M and N. The main challenge is that the reader is provided with a large volume of individual data fragments of selected regions (e.g., Figures 4 and 5) or images of whole midgut without proper quantification (Figure 7). There is not sufficient effort made to display the data in a way that allows observing changes in the global patterns of EE cell subtypes throughout the midgut and compare these patterns with the observed WNT and BMP gradients.

Reviewer #2 (Public review):

Summary:

By labeling the three major enteroendocrine cell markers - AstC, Tk, and CCHa2-the authors systematically investigated the distribution of distinct EE subtypes along the Drosophila midgut, as well as their emergence via symmetric and asymmetric divisions of enteroendocrine progenitor cells. Moreover, they dissected the molecular mechanisms underlying regional patterning by modulating Wnt and BMP signaling pathways, revealing that these compartment boundary signals play key roles in regulating EE subtype diversity.

Strengths:

This work establishes a solid methodological and conceptual foundation for future studies on how stem cells acquire positional identity and modulate region-specific behaviors.

Weaknesses:

Given that the transcriptional profiles of intestinal stem cells across different regions are highly similar, it is reasonable to hypothesize that the behavior of ISCs and enteroendocrine precursor cells may be regulated non-autonomously, potentially through interactions with enterocytes, which exhibit more distinct region-specific characteristics.

Reviewer #3 (Public review):

Summary:

The authors aimed to elucidate the mechanisms underlying the regional patterning of enteroendocrine cell (EE) subtypes along the Drosophila midgut. Through detailed immunohistochemical mapping and genetic perturbation of Notch, WNT, and BMP signaling pathways, they sought to determine how extrinsic morphogen gradients and intrinsic stem cell identity contribute to EE diversity.

Strengths:

A major strength of this work is the meticulous regional analysis of EE pairs and the use of multiple genetic tools to manipulate signaling pathways in a spatiotemporally controlled manner. The data robustly demonstrate that WNT and BMP signaling gradients play key roles in specifying EE subtypes and division modes across different gut regions.

Weaknesses:

However, the study does not fully explore the mechanistic basis for the region-specific dependence on Notch signaling. Additionally, while the authors propose that symmetric divisions occur in R1a and R4b, the observed heterogeneity in CCHa2 expression within AstC+ pairs in R4b suggests that asymmetric mechanisms may still be at play, possibly involving apical-basal polarity as previously reported.

Appraisal of achievements:

The authors successfully achieve their aims by providing a compelling model in which intercalated WNT and BMP gradients regulate EE subtype specification and EEP division modes. The genetic data strongly support the conclusion that these pathways are central to establishing regional EE diversity during pupal development.

Author response:

We would like to express our gratitude to all three reviewers for their time and valuable feedback on the manuscript. Below, we provide our point-by-point responses to their comments. Additionally, we summarize here the experiments we plan to conduct in accordance with the reviewers' suggestions:

Revision plan 1. To further explore the mechanisms of Notch signaling in the decision of regional EE pattern.

Our observation of EE subtype changes in Notch mutant clones revealed that Notch is required for the specification of Type II EEs, but whether it promotes the generation of Type III EEs is not quite clear. In this revision, we will complete the quantification of Type I and Type III EEs in Notch mutant clones to demonstrate whether Notch signaling participate the determination of these two EE subtypes. Further, we will attempt to combine Notch mutant with different manipulation of WNT and BMP gradients to investigate their interplays.

Revision plan 2. To supplement the global pattern of WNT and BMP gradient along the whole gut.

The levels of WNT and BMP gradients are variable in different gut regions both under normal condition and genetic manipulation, leading to different outcomes of EE subtype composition. To further support our model, we will supply the changes of WNT and BMP gradients along the whole gut after genetic manipulation, and perform semi-quantification of their levels to correlate with EE subtype compositions. Additionally, we will also test the gradient levels at different time point during pupal stage to interpret the establishment of regional identity during the development.

Revision plan 3. To investigate the involvement of apical-basal polarity in the determination of regional EE diversity.

Although we have demonstrated WNT and BMP gradients orchestrate the regional EE identity, but some observations cannot be fully explained by their roles, such as asymmetric expression of CCHa2 in EE pairs from R4b. A potential mechanism is apical-basal polarity, which has been reported to determine cell fate of ISC progenies at pupal stage. We will specifically knockdown or overexpress key genes related to apical-basal polarity in ISCs or EEs to test whether they are involved preliminarily.

Please find our detailed point-by-point responses below.

Public Reviews:

Reviewer #1 (Public review):

This valuable study explores the regulatory mechanisms underlying the regional distribution of enteroendocrine cell subtypes in the Drosophila midgut. The regional distribution of EE cell subtypes is carefully documented, and the data convincingly show that each EE cell subtype has a unique spatial pattern. The study aims at determining how the spatial distribution of EE cell subtypes is established and maintained, and explores the roles of three pathways: Notch, WNT, and BMP. The data show evidence that Notch signaling regulates the subtype specificity, being necessary for the specification of Type II, but not Type I and III EE cell subtype specification. The immunofluorescence data in Figure 3 are convincing, but the analysis is incomplete due to a lack of quantification. How Notch signaling activity relates to the emergence of the regional EE cell patterns remains unclear.

Indeed, the role of Notch signaling in regional EE determination was not fully characterized in this work. As the requirement of Notch activation for the differentiation of enterocytes, introduction of Notch or Delta mutant led to rapid accumulation of ISCs and EEs, making it being a challenge to dive into the details of how EE subtypes were generated. We will try to complete the quantification of Type I and Type III EEs in the Notch mutant clones from different gut regions to figure out whether Notch could influence the specification of these two EE subtypes. Additionally, different from WNT and BMP gradients, Notch signaling can only function locally and is not significantly changed along the whole gut, including Type II EE-enriched R1a and Type I EE-enriched R4b, which implies that function of Notch signaling may can be overridden by the impact of specific combination of WNT and BMP gradients. To test this hypothesis, we will attempt to combine Notch mutant with the activation or inhibition of WNT and BMP signaling since pupal stage, and further examine whether the regional EE identity could be altered, especially in R1a and R4b regions.

As WNT and BMP are known as morphogens, the study explores their expression patterns and their roles in establishing and maintaining the subtype identities. The observed patterns of WNT and BMP are consistent with earlier studies. Manipulation of WNT and BMP pathway activities in intestinal stem cells is shown to have some region-specific effects on specific EE cell subtypes. The overall conclusion that both WNT and BMP have local effects on EE cell subtypes is based on solid evidence. However, the study falls short in achieving its main objective, i.e., to explain the regional subtype patterns by the action of WNT and BMP gradients. Despite displaying a large volume of phenotypic data in Figures 4-7, the study remains incomplete in providing sufficient evidence to support the models shown in Figures 7 M and N. The main challenge is that the reader is provided with a large volume of individual data fragments of selected regions (e.g., Figures 4 and 5) or images of whole midgut without proper quantification (Figure 7). There is not sufficient effort made to display the data in a way that allows observing changes in the global patterns of EE cell subtypes throughout the midgut and compare these patterns with the observed WNT and BMP gradients.

As the variation of WNT and BMP gradients along the whole gut, manipulating these two pathways is not able to align their activation levels in different gut regions. This forced us to analyze the change of each region separately, making it to be a challenge to provide a comprehensive global overview. We will supplement the comprehensive profile of WNT and BMP activity under the manipulation of these two signaling pathways to correlated with the change of EE identity, and also try to perform a semi-quantitative interpretation to further support the model in Figure 7M and 7N.

Reviewer #2 (Public review):

Summary:

By labeling the three major enteroendocrine cell markers - AstC, Tk, and CCHa2-the authors systematically investigated the distribution of distinct EE subtypes along the Drosophila midgut, as well as their emergence via symmetric and asymmetric divisions of enteroendocrine progenitor cells. Moreover, they dissected the molecular mechanisms underlying regional patterning by modulating Wnt and BMP signaling pathways, revealing that these compartment boundary signals play key roles in regulating EE subtype diversity.

Strengths:

This work establishes a solid methodological and conceptual foundation for future studies on how stem cells acquire positional identity and modulate region-specific behaviors.

Weaknesses:

Given that the transcriptional profiles of intestinal stem cells across different regions are highly similar, it is reasonable to hypothesize that the behavior of ISCs and enteroendocrine precursor cells may be regulated non-autonomously, potentially through interactions with enterocytes, which exhibit more distinct region-specific characteristics.

This is a quite complicated point to discuss. Drosophila adult midgut is established by pISCs (pupal ISCs), which arise from AMPs (adult midgut progenitors) in larval midgut. AMPs are encased by PCs (peripheral cells) to be islands, scattered throughout the entire larval midgut by mid L3 stage (Mathur D. et al. Science. 2010). After pupariation, larval midgut is delaminated to become the yellow body and finally meconium in the pupal midgut. Simultaneously, PCs break down and die, allowing AMPs to give rise to the presumptive adult epithelium (generating enterocyte precursors) and the specification of ISCs in the adult midgut (Jiang H, Edgar BA. Development. 2009; Micchelli CA. et al. Gene Expr Patterns. 2011). During the pupal stage, pISCs only proliferate to generate new ISCs and EE lineages, while adult enterocytes start to appear after eclosion (Takashima S. et al. Dev Biol. 2011). This rules out the possibility that the interaction with enterocytes regulates regional ISC identity during pupal stage.

However, whether AMPs already acquire the regional identity during larval stage, and whether pISCs interact with enterocyte precursors at pupal stage, are not quite clear. Our study revealed that pISCs can be influenced by WNT and BMP gradients to acquire regional identity, and further establish regional EE diversity. The change of WNT and BMP gradients during the metamorphosis will be supplemented in revision. While WNT and BMP signaling ligands are provided by muscles and adult enterocytes, and even other surrounding tissues, to regulate regional ISC identity, which indicates that non-autonomous mechanisms indeed exist.

Reviewer #3 (Public review):

Summary:

The authors aimed to elucidate the mechanisms underlying the regional patterning of enteroendocrine cell (EE) subtypes along the Drosophila midgut. Through detailed immunohistochemical mapping and genetic perturbation of Notch, WNT, and BMP signaling pathways, they sought to determine how extrinsic morphogen gradients and intrinsic stem cell identity contribute to EE diversity.

Strengths:

A major strength of this work is the meticulous regional analysis of EE pairs and the use of multiple genetic tools to manipulate signaling pathways in a spatiotemporally controlled manner. The data robustly demonstrate that WNT and BMP signaling gradients play key roles in specifying EE subtypes and division modes across different gut regions.

Weaknesses:

However, the study does not fully explore the mechanistic basis for the region-specific dependence on Notch signaling. Additionally, while the authors propose that symmetric divisions occur in R1a and R4b, the observed heterogeneity in CCHa2 expression within AstC+ pairs in R4b suggests that asymmetric mechanisms may still be at play, possibly involving apical-basal polarity as previously reported.

As previously mentioned, we acknowledge that the role of Notch signaling in regional EE determination remains further exploration. We will supplement the quantification of Type I and Type III EEs in Figure 3 and Figure S4, and further combine Notch mutant with activation or inhibition of WNT and BMP signaling to test whether they have any interplays, especially in R1a and R4b.

Apical-basal polarity has been reported to determine the precise segregation of Pros to control ISC number and cell fate at the pupal stage (Wu S. et al. Cell Rep. 2023). During this time, generation of regional EEs are completed and may also be affected except for the influence of Notch, WNT and BMP pathways. Therefore, the apical-basal polarity is quite a potential mechanism to induce asymmetric cell division in R4b, which we will perform experiments to test.

Appraisal of achievements:

The authors successfully achieve their aims by providing a compelling model in which intercalated WNT and BMP gradients regulate EE subtype specification and EEP division modes. The genetic data strongly support the conclusion that these pathways are central to establishing regional EE diversity during pupal development.

eLife Assessment

This valuable study addresses the effects of selection on aggression on fitness and life-history trade-offs in Drosophila melanogaster. However, the evidence presented is incomplete and does not support the claims proposed in the study of increased survival of highly aggressive males at the expense of reproductive success and shorter mating duration. The main limitation of the study is the choice to use males from only one aggressive Drosophila line in combination with CantonS females, that do not allow disambiguation between nonaggression-related factors, such as hybrid vigor and aggression-related factors influencing mating and lifespan.

Reviewer #1 (Public review):

Summary:

This study asks how selection for male aggressiveness affects life-history and reproductive fitness traits in Drosophila melanogaster males.

Strengths:

Multiple comprehensive assays are used to address the question.

Weaknesses:

(1) The flies used for comparisons are inadequate. Behavioral assays compare Bully males mated to non-coevolved Cs females with Cs males mated to coevolved Cs females.

(2) Lifespan analysis is done on male progeny of Cs females mated to either genetically more distant Bully or co-evolved Cs males; the longer lifespan and performance on the former is interpreted as a trade-off with aggressiveness, rather than a simple explanation of hybrid vigor.

(3) Differences in CHCs between Bully and Cs males and Cs females mated to those males are not shown to cause differences in measured behavioral outcomes.

Reviewer #2 (Public review):

Summary:

The authors compare "Bully" lines, selected for male aggression, to Canton-S controls and find that Bully males have lower mating success, shorter mating durations, and remate sooner. Chemical analyses show Bully males have distinct cuticular hydrocarbons (CHC) signatures and transfer markedly less cVA to females, offering a plausible mechanistic link to weaker mate-guarding.

Paradoxically, Bully males live longer and remain fertile at older ages when CS males no longer mate, indicating a shift in the reproduction-survival trade-off in aggression-selected populations.

Importantly, the work sheds light on proximate mechanisms, demonstrating that shifts in CHCs and pheromone transfer co-occur with changes in fitness traits, thus offering new entry points for understanding life-history evolution.

Strengths:

The manuscript's strengths lie in its comprehensive and integrative approach framed within an evolutionary context. By combining behavioral assays, chemical profiling, and lifespan measurements, the authors reveal a coherent pattern linking aggression selection to life-history trade-offs. The direct quantification of cVA in female reproductive tracts after mating provides a particularly compelling mechanistic correlate, strengthening the link between behavior and chemical signaling. Findings on altered 5-T and 5-P levels further highlight how chemical communication shapes mating and mate-guarding strategies. Analytical approaches are largely rigorous, and the results provide valuable insights into the pleiotropic effects of selection on socially relevant traits. The study will be of interest to Drosophila biologists working on sexual selection, behavioral evolution, and aging.

Weaknesses:

The weaknesses are primarily conceptual rather than procedural. The generality of the findings is uncertain, as selection appears to be represented by only one (and a second closely related) Bully line, limiting conclusions about selection responses versus line-specific drift or founder effects. The causal link between aggression selection and increased longevity is not established: the data show a correlated shift but do not identify mechanisms underlying lifespan extension. In several places, the manuscript uses causal language (e.g., that selection 'influences' longevity or mating strategy) where association would be more accurate; this should be toned down to avoid overstatement. Ecological relevance is also not addressed, since laboratory conditions may bias the balance between costs and benefits of aggression compared with variable natural environments. Addressing these points would strengthen both the impact and clarity of the study.

Author response:

eLife Assessment

This valuable study addresses the effects of selection on aggression on fitness and life-history trade-offs in Drosophila melanogaster. However, the evidence presented is incomplete and does not support the claims proposed in the study of increased survival of highly aggressive males at the expense of reproductive success and shorter mating duration. The main limitation of the study is the choice to use males from only one aggressive Drosophila line in combination with CantonS females, that do not allow disambiguation between nonaggression-related factors, such as hybrid vigor and aggression-related factors influencing mating and lifespan.

We would like to clarify the points raised in the eLife assessment.

The report states that we relied on a single line of hyper-aggressive males tested with CantonS females, and implies that Bully and Cs have not co-evolved. This is a misunderstanding: Bully flies were derived from Cs population. Thus, Bully and Cs have co-evolved. In addition to the Bully A line presented in the main figures of the manuscript, we replicated several of our findings with a second independent selected line, Bully B. Results from courtship assays involving both Bully A and Bully B couples males and females were presented in Figure Supp1. We apologies for not having made this more explicit in the original manuscript, which we will correct. These experiments should alleviate the concerns from the reviewers; they demonstrate that our conclusions are supported by two independent hyper-aggressive lines, and these include assays with selected male and female flies.

Public Reviews:

Reviewer #1 (Public review):

Summary:

This study asks how selection for male aggressiveness affects life-history and reproductive fitness traits in Drosophila melanogaster males.

Strengths:

Multiple comprehensive assays are used to address the question.

We thank the reviewer for recognizing these strengths.

Weaknesses:

(1) The flies used for comparisons are inadequate. Behavioral assays compare Bully males mated to non-coevolved Cs females with Cs males mated to coevolved Cs females.

We thank the reviewer for this comment, which made us realize that we had not sufficiently highlighted some of our experiments. The Bully lines used in our work were derived from Canton-S flies and thus did co-evolve with Cs. As originally described by Penn et al. (2010), highly aggressive “Bully” lines were generated through selective breeding from Canton-S males that consistently won aggressive encounters. After 34–37 generations, stable Bully lines were established. Thus, Bully and Cs flies have co-evolved and 2) the selection applied was male-specific. Independent selection replicates produced distinct lines, including Bully A and Bully B. Previous studies only characterized Bully A (Penn et al., 2010; Chowdhury et al., 2017), but our work includes both Bully A and Bully B (Fig. S1).

The rationale for pairing Bully or Cs males with Cs females (with which both male types co-evolved) follows the approach used by Dierick et al. (2006), who investigated how the male-specific selection for aggression affected courtship and mating behaviors by testing them with standard Canton-S females. This design allows to isolate the effects of male genotype and behavior on courtship and mating outcomes, avoiding confounding effects from female behavioral changes.

We initially compared selected Bully pairs (Bully males × Bully females) (Fig. S1) with Cs pairs and observed similarly shortened mating durations in both Bully × Bully and Bully × Cs matings (Fig. S1, Fig. 1F and G). Thus, the reduction in mating duration arises specifically from Bully males. We therefore chose to use Cs females as a standard background to assess the consequences of male-specific selection for aggression on reproductive behaviors.

(2) Lifespan analysis is done on male progeny of Cs females mated to either genetically more distant Bully or co-evolved Cs males; the longer lifespan and performance on the former is interpreted as a trade-off with aggressiveness, rather than a simple explanation of hybrid vigor.

We appreciate this comment, which again stems from a poor explanation from our part about the origin of the Bully line in the original manuscript. The Bully flies were derived from the same original population as the Cs line. Hybrid vigor typically arises when crossing individuals from distinct populations, which is not the case here as both Bully and CS come from the same population.

To further support our conclusions, we conducted additional experiments using progeny from within-line crosses (Bully males × Bully females) and results revealed the same phenotype: the progeny of these flies also exhibited significantly longer lifespans than Cs males x Cs females progeny. This finding argues against hybrid vigor as the main explanation for the observed phenotype, since both the Bully and Cs crosses result in inbreeding, yet give longer lifespan in Bully. We will include these additional longevity data (currently not included in the manuscript) to strengthen our results and reinforce our interpretation.

(3) Differences in CHCs between Bully and Cs males and Cs females mated to those males are not shown to cause differences in measured behavioral outcomes.

We thank the reviewer for raising this important point regarding causality. One way to establish a causal link between differences in CHCs observed in Bully and Cs flies and the corresponding behavioral outcomes would be to experimentally manipulate CHC profiles. For instance, one could perfume oenocyte-less males with the compounds found in higher abundance in Bully flies, then perform behavioral assays to assess causality. We agree that such experiments would be highly informative in determining the functional roles of specific CHCs elevated in Bully males. However, this approach is technically challenging, as the perfuming technique must be optimized to transfer precise amounts of each compound. For example, this method can be used to gradually perfume flies to assess dose–response behavioral effects, whereas matching exactly the natural concentrations found in individuals, especially given inter-individual variability, remains difficult.

We considered conducting such experiments during our study but did not pursue them for these technical reasons. Nevertheless, we can include a statement in the Discussion acknowledging this as an important future direction to test the causal relationship between CHC variation and behavior.

Reviewer #2 (Public review):

Summary:

The authors compare "Bully" lines, selected for male aggression, to Canton-S controls and find that Bully males have lower mating success, shorter mating durations, and remate sooner. Chemical analyses show Bully males have distinct cuticular hydrocarbons (CHC) signatures and transfer markedly less cVA to females, offering a plausible mechanistic link to weaker mate-guarding.

Paradoxically, Bully males live longer and remain fertile at older ages when CS males no longer mate, indicating a shift in the reproduction-survival trade-off in aggression-selected populations.

Importantly, the work sheds light on proximate mechanisms, demonstrating that shifts in CHCs and pheromone transfer co-occur with changes in fitness traits, thus offering new entry points for understanding life-history evolution.

We thank the reviewer for this positive summary of our work.

Strengths:

The manuscript's strengths lie in its comprehensive and integrative approach framed within an evolutionary context. By combining behavioral assays, chemical profiling, and lifespan measurements, the authors reveal a coherent pattern linking aggression selection to life-history trade-offs. The direct quantification of cVA in female reproductive tracts after mating provides a particularly compelling mechanistic correlate, strengthening the link between behavior and chemical signaling. Findings on altered 5-T and 5-P levels further highlight how chemical communication shapes mating and mate-guarding strategies. Analytical approaches are largely rigorous, and the results provide valuable insights into the pleiotropic effects of selection on socially relevant traits. The study will be of interest to Drosophila biologists working on sexual selection, behavioral evolution, and aging.

We thank the reviewer for recognizing the integrative design and mechanistic contributions of our study.

Weaknesses:

The weaknesses are primarily conceptual rather than procedural. The generality of the findings is uncertain, as selection appears to be represented by only one (and a second closely related) Bully line, limiting conclusions about selection responses versus line-specific drift or founder effects. The causal link between aggression selection and increased longevity is not established: the data show a correlated shift but do not identify mechanisms underlying lifespan extension. In several places, the manuscript uses causal language (e.g., that selection 'influences' longevity or mating strategy) where association would be more accurate; this should be toned down to avoid overstatement. Ecological relevance is also not addressed, since laboratory conditions may bias the balance between costs and benefits of aggression compared with variable natural environments. Addressing these points would strengthen both the impact and clarity of the study.

(1) Generality of findings and potential line effects

We agree that our results presented in the main figures of the manuscript relied mainly on one Bully line (Bully A). To address potential line-specific effects, we replicated key courtship experiments with another independent line, Bully B, selected in parallel from the same Canton-S stock but through distinct selection replicates. The results obtained from Bully B closely matched those from Bully A, suggesting that the observed phenotypes are consistent consequences of aggression selection rather than random drift or founder effects.

(2) Causality versus correlation

We concur that some sentences in the manuscript could overstate causal interpretations. We will revise the text to clearly distinguish correlation from causation and to avoid implying direct causal relationships where data only support association.

(3) Ecological relevance

We appreciate this point. Our experiments were performed under controlled laboratory conditions, which may not fully capture the ecological contexts shaping the costs and benefits of aggression. We will acknowledge this limitation and expand the Discussion to consider how environmental variability could modulate the fitness trade-offs associated with aggression in natural populations.

We thank both reviewers for their constructive feedback, which will help us strengthen the rigor and clarity of the manuscript. We believe that the additional results and revisions will satisfactorily address their concerns.

Sans "le". Ou bien, reformuler la question : "Pourquoi est-ce qu'on le laisse vide ?"

Quelle est l'utilité de l'attribut "value" ici ?

Sans "s".

Sans "s".

https://via.hypothes.is/https://hyperpost.peergos.me/%F0%9F%8E%AD/gyuri/%F0%9F%93%93/0/

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utilizing

Clue/Trail/Plex Mark Atomic Terms used for naming

info-morphic units of information that are high-resolution addressable high fildeilty meaning/intentfully deeply intertwingled named info-morphic-colab-orative interpersonal nterplanetary structures amenable to muassive multiplayer interplays that plays nicely with other structures

eLife Assessment

This valuable study examines how mammals descend effectively and securely along vertical substrates. The conclusions from comparative analyses based on behavioral data and morphological measurements collected from 21 species across a wide range of taxa are convincing, making the work of interest to all biologists studying animal locomotion.

Reviewer #1 (Public review):

Summary:

This unique study reports original and extensive behavioral data collected by the authors on 21 living mammal taxa in zoo conditions (primates, tree shrew, rodents, carnivorans, and marsupials) on how descent along a vertical substrate can be done effectively and securely using gait variables. Ten morphological variables reflecting head size and limb proportions are examined in relationship to vertical descent strategies and then applied to reconstruct modes of vertical descent in fossil mammals.

Strengths:

This is a broad and data-rich comparative study, which requires a good understanding of the mammal groups being compared and how they are interrelated, the kinematic variables that underlie the locomotion used by the animals during vertical descent, and the morphological variables that are associated with vertical descent styles. Thankfully, the study presents data in a cogent way with clear hypotheses at the beginning, followed by results and a discussion that addresses each of those hypotheses using the relevant behavioral and morphological variables, always keeping in mind the relationships of the mammal groups under investigation. As pointed out in the study, there is a clear phylogenetic signal associated with vertical descent style. Strepsirrhine primates much prefer descending tail first, platyrrhine primates descend sideways when given a choice, whereas all other mammals (with the exception of the raccoon) descend head first. Not surprisingly, all mammals descending a vertical substrate do so in a more deliberate way, by reducing speed, and by keeping the limbs in contact for a longer period (i.e., higher duty factors).

Weaknesses:

The different gait patterns used by mammals during vertical descent are a bit more difficult to interpret. It is somewhat paradoxical that asymmetrical gaits such as bounds, half bounds, and gallops are more common during descent since they are associated with higher speeds and lower duty factors. Also, the arguments about the limb support polygons provided by DSDC vs. LSDC gaits apply for horizontal substrates, but perhaps not as much for vertical substrates.

The importance of body mass cannot be overemphasized as it affects all aspects of an animal's biology. In this case, larger mammals with larger heads avoid descending head-first. Variation in trunk/tail and limb proportions also covaries with different vertical descent strategies. For example, a lower intermembral index is associated with tail-first descent. That said, the authors are quick to acknowledge that the five lemur species of their sample are driving this correlation. There is a wide range of intermembral indices among primates, and this simple measure of forelimb over hindlimb has vital functional implications for locomotion: primates with relatively long hindlimbs tend to emphasize leaping, primates with more even limb proportions are typically pronograde quadrupeds, and primates with relatively long forelimbs tend to emphasize suspensory locomotion and brachiation. Equally important is the fact that the intermembral index has been shown to increase with body mass in many primate families as a way to keep functional equivalence for (ascending) climbing behavior (see Jungers, 1985). Therefore, the manner in which a primate descends a vertical substrate may just be a by-product of limb proportions that evolved for different locomotor purposes. Clearly, more vertical descent data within a wider array of primate intermembral indices would clarify these relationships. Similarly, vertical descent data for other primate groups with longer tails, such as arboreal cercopithecoids, and particularly atelines with very long and prehensile tails, should provide more insights into the relationship between longer tail length and tail-first descent observed in the five lemurs. The relatively longer hallux of lemurs correlates with tail-first descent, whereas the more evenly grasping autopods of platyrrhines allow for all four limbs to be used for sideways descent. In that context, the pygmy loris offers a striking contrast. Here is a small primate equipped with four pincer-like, highly grasping autopods and a tail reduced to a short stub. Interestingly, this primate is unique within the sample in showing the strongest preference for head-first descent, just like other non-primate mammals. Again, a wider sample of primates should go a long way in clarifying the morphological and behavioral relationships reported in this study.

Reconstruction of the ancient lifestyles, including preferred locomotor behaviors, is a formidable task that requires careful documentation of strong form-function relationships from extant species that can be used as analogs to infer behavior in extinct species. The fossil record offers challenges of its own, as complete and undistorted skulls and postcranial skeletons are rare occurrences. When more complete remains are available, the entire evidence should be considered to reconstruct the adaptive profile of a fossil species rather than a single ("magic") trait.

Reviewer #2 (Public review):

Summary:

This paper contains kinematic analyses of a large comparative sample of small to medium-sized arboreal mammals (n = 21 species) traveling on near-vertical arboreal supports of varying diameter. This data is paired with morphological measures from the extant sample to reconstruct potential behaviors in a selection of fossil euarchontaglires. This research is valuable to anyone working in mammal locomotion and primate evolution.

Strengths:

The experimental data collection methods align with best research practices in this field and are presented with enough detail to allow for reproducibility of the study as well as comparison with similar datasets. The four predictions in the introduction are well aligned with the design of the study to allow for hypothesis testing. Behaviors are well described and documented, and Figure 1 does an excellent job in conveying the variety of locomotor behaviors observed in this sample. I think the authors took an interesting and unique angle by considering the influence of encephalization quotient on descent and the experience of forward pitch in animals with very large heads.

Weaknesses:

The authors acknowledge the challenges that are inherent with working with captive animals in enclosures and how that might influence observed behaviors compared to these species' wild counterparts. The number of individuals per species in this sample is low; however, this is consistent with the majority of experimental papers in this area of research because of the difficulties in attaining larger sample sizes.

Figure 2 is difficult to interpret because of the large amount of information it is trying to convey.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

This unique study reports original and extensive behavioral data collected by the authors on 21 living mammal taxa in zoo conditions (primates, tree shrew, rodents, carnivorans, and marsupials) on how descent along a vertical substrate can be done effectively and securely using gait variables. Ten morphological variables reflecting head size and limb proportions are examined in relationship to vertical descent strategies and then applied to reconstruct modes of vertical descent in fossil mammals.

Strengths:

This is a broad and data-rich comparative study, which requires a good understanding of the mammal groups being compared and how they are interrelated, the kinematic variables that underlie the locomotion used by the animals during vertical descent, and the morphological variables that are associated with vertical descent styles. Thankfully, the study presents data in a cogent way with clear hypotheses at the beginning, followed by results and a discussion that addresses each of those hypotheses using the relevant behavioral and morphological variables, always keeping in mind the relationships of the mammal groups under investigation. As pointed out in the study, there is a clear phylogenetic signal associated with vertical descent style. Strepsirrhine primates much prefer descending tail first, platyrrhine primates descend sideways when given a choice, whereas all other mammals (with the exception of the raccoon) descend head first. Not surprisingly, all mammals descending a vertical substrate do so in a more deliberate way, by reducing speed, and by keeping the limbs in contact for a longer period (i.e., higher duty factors).

Weaknesses:

The different gait patterns used by mammals during vertical descent are a bit more difficult to interpret. It is somewhat paradoxical that asymmetrical gaits such as bounds, half bounds, and gallops are more common during descent since they are associated with higher speeds and lower duty factors. Also, the arguments about the limb support polygons provided by DSDC vs. LSDC gaits apply for horizontal substrates, but perhaps not as much for vertical substrates.

We analyzed gait patterns using methods commonly found in the literature and discussed our results accordingly. However, the study of limbs support polygons was indeed developed specifically for studying locomotion on horizontal supports, and may not be applicable for studying vertical locomotion, which is in fact a type of locomotion shared by all arboreal species. In the future, it would be interesting to consider new methods for analyzing vertical gaits.

The importance of body mass cannot be overemphasized as it affects all aspects of an animal's biology. In this case, larger mammals with larger heads avoid descending head-first. Variation in trunk/tail and limb proportions also covaries with different vertical descent strategies. For example, a lower intermembral index is associated with tail-first descent. That said, the authors are quick to acknowledge that the five lemur species of their sample are driving this correlation. There is a wide range of intermembral indices among primates, and this simple measure of forelimb over hindlimb has vital functional implications for locomotion: primates with relatively long hindlimbs tend to emphasize leaping, primates with more even limb proportions are typically pronograde quadrupeds, and primates with relatively long forelimbs tend to emphasize suspensory locomotion and brachiation. Equally important is the fact that the intermembral index has been shown to increase with body mass in many primate families as a way to keep functional equivalence for (ascending) climbing behavior (see Jungers, 1985). Therefore, the manner in which a primate descends a vertical substrate may just be a by-product of limb proportions that evolved for different locomotor purposes. Clearly, more vertical descent data within a wider array of primate intermembral indices would clarify these relationships. Similarly, vertical descent data for other primate groups with longer tails, such as arboreal cercopithecoids, and particularly atelines with very long and prehensile tails, should provide more insights into the relationship between longer tail length and tail-first descent observed in the five lemurs. The relatively longer hallux of lemurs correlates with tail-first descent, whereas the more evenly grasping autopods of platyrrhines allow for all four limbs to be used for sideways descent. In that context, the pygmy loris offers a striking contrast. Here is a small primate equipped with four pincer-like, highly grasping autopods and a tail reduced to a short stub. Interestingly, this primate is unique within the sample in showing the strongest preference for head-first descent, just like other non-primate mammals. Again, a wider sample of primates should go a long way in clarifying the morphological and behavioral relationships reported in this study.

We agree with this statement. In the future, we plan to study other species, particularly large-bodied ones with varied intermembral indexes.

Reconstruction of the ancient lifestyles, including preferred locomotor behaviors, is a formidable task that requires careful documentation of strong form-function relationships from extant species that can be used as analogs to infer behavior in extinct species. The fossil record offers challenges of its own, as complete and undistorted skulls and postcranial skeletons are rare occurrences. When more complete remains are available, the entire evidence should be considered to reconstruct the adaptive profile of a fossil species rather than a single ("magic") trait.

We completely agree with this, and we would like to emphasize that our intention here was simply to conduct a modest inference test, the purpose of which is to provide food for thought for future studies, and whose results should be considered in light of a comprehensive evolutionary model.

Reviewer #2 (Public review):

Summary:

This paper contains kinematic analyses of a large comparative sample of small to medium-sized arboreal mammals (n = 21 species) traveling on near-vertical arboreal supports of varying diameter. This data is paired with morphological measures from the extant sample to reconstruct potential behaviors in a selection of fossil euarchontaglires. This research is valuable to anyone working in mammal locomotion and primate evolution.

Strengths:

The experimental data collection methods align with best research practices in this field and are presented with enough detail to allow for reproducibility of the study as well as comparison with similar datasets. The four predictions in the introduction are well aligned with the design of the study to allow for hypothesis testing. Behaviors are well described and documented, and Figure 1 does an excellent job in conveying the variety of locomotor behaviors observed in this sample. I think the authors took an interesting and unique angle by considering the influence of encephalization quotient on descent and the experience of forward pitch in animals with very large heads.

Weaknesses:

The authors acknowledge the challenges that are inherent with working with captive animals in enclosures and how that might influence observed behaviors compared to these species' wild counterparts. The number of individuals per species in this sample is low; however, this is consistent with the majority of experimental papers in this area of research because of the difficulties in attaining larger sample sizes.

Yes, that is indeed the main cost/benefit trade-off with this type of study. Working with captive animals allows for large comparative studies, but there is a risk of variations in locomotor behavior among individuals in the natural environment, as well as few individuals per species in the dataset. That is why we plan and encourage colleagues to conduct studies in the natural environment to compare with these results. However, this type of study is very time-consuming and requires focusing on a single species at a time, which limits the comparative aspect.

Figure 2 is difficult to interpret because of the large amount of information it is trying to convey.

We agree that this figure is dense. One possible solution would be to combine species by phylogenetic groups to reduce the amount of information, as we did with Fig. 3 on the dataset relating to gaits. However, we believe that this would be unfortunate in the case of speed and duty factor because we would have to provide the complete figure in SI anyway, as the species-level information is valuable. We therefore prefer to keep this comprehensive figure here and we will enlarge the data points to improve their visibility, and provide the figure with a sufficiently high resolution to allow zooming in on the details.

• Informativo nº 815
• 11 de junho de 2024.
• TERCEIRA TURMA
• Processo: REsp 2.136.190-RS, Rel. Ministra Nancy Andrighi, Terceira Turma, por unanimidade, julgado em 4/6/2024, DJe 6/6/2024.

Ramo do Direito DIREITO PROCESSUAL CIVIL

TemaPaz, Justiça e Instituições Eficazes <br /> Ação de produção antecipada de prova. Local da realização da perícia diverso do local de sede da empresa ré e de eleição. Foro do objeto a ser periciado. Questão de praticidade da instrução. Inexistência de prejuízo.

Destaque - A produção antecipada de prova pericial pode ser processada no foro onde situado o objeto a ser periciado ao invés do foro de sede da empresa ré, que coincide com o foro eleito em contrato.

Informações do Inteiro Teor - Ressalta-se de início que a norma de competência (i) do juízo do foro onde a prova deva ser produzida ou (ii) do juízo do foro de domicílio do réu, para fins de apreciar ação de produção antecipada de provas (art. 381, § 2º, do CPC/2015), não possui norma equivalente no CPC/1973.

• O CPC/1973 tinha como regra geral para fixar a competência do juízo cautelar como sendo a mesma do juízo da ação principal (art. 800 do referido código). Esta Corte, contudo, já permitia a relativização da competência do juízo da ação principal em relação aos procedimentos cautelares, especialmente em se tratando de produção cautelar de provas na forma antecipada.

• Nesse sentido, o STJ entendia que "poderá haver a mitigação da competência prevista no art. 800 do CPC/1973 quando se tratar de ação cautelar de produção antecipada de provas, podendo ser reconhecida a competência do foro em que se encontra o objeto da lide, por questões práticas e processuais, notadamente para viabilizar a realização de diligências e perícias" (AgInt no AREsp n. 1.321.717/SP, Terceira Turma, DJe de 19/10/2018).

• A relativização da competência estava igualmente fundamentada na facilitação de inspeção judicial "possibilitando maior celeridade à prestação jurisdicional" em hipótese de ação cautelar de produção antecipada de provas (AgRg no Ag n. 1.137.193/GO, Quarta Turma, DJe de 16/11/2009).

• Nesse sentido, a facilitação da realização da perícia <u>prevalece</u> sobre a regra geral do ajuizamento no foro do réu por envolver uma questão de ordem prática tendo em vista a necessidade de exame no local onde está situado o objeto a ser periciado.

• Diferentemente do código anterior, o CPC/2015 expressamente dispõe que o foro de exame prévio de prova não torna ele prevento para a futura eventual ação principal (art. 381, § 3º, do CPC/2015).

• Dessa forma, inexiste prejuízo presumido neste procedimento prévio, pois - a depender do resultado da perícia - a ação principal sequer poderá ser ajuizada, ou, caso seja ajuizada, o foro de eleição - que coincide com o foro do local de sede da empresa ré - poderá prevalecer.

• Informativo nº 832
• 5 de novembro de 2024.
• QUARTA TURMA
• Processo: REsp 2.152.938-DF, Rel. Ministro Antonio Carlos Ferreira, Quarta Turma, por unanimidade, julgado em 22/10/2024.

Ramo do Direito DIREITO PROCESSUAL CIVIL

TemaPaz, Justiça e Instituições Eficazes <br /> Localização do réu. Tentativas infrutíferas. Cadastro de órgãos públicos. Concessionárias de serviços públicos. Ofício. Expedição antes da citação por edital. Obrigatoriedade. Ausência. Avaliação do magistrado. Possibilidade.

Destaque - A expedição de ofícios a cadastros públicos e concessionárias de serviços públicos para localizar o réu antes da citação por edital não é obrigatória, mas uma <u>possibilidade</u> a ser avaliada pelo magistrado.

Informações do Inteiro Teor - O tema em discussão consiste em definir se há obrigatoriedade de expedição de ofício a cadastros de órgãos públicos e concessionárias de serviços públicos para localizar o réu antes da citação por edital.

• Segundo a jurisprudência do STJ, a citação por edital pressupõe o esgotamento dos meios necessários para localização do réu, sob pena de nulidade. Isso porque a citação por edital é uma forma de citação presumida, utilizada em caráter extremamente excepcional. Sua aplicação é restrita às seguintes situações enumeradas no art. 256 do Código de Processo Civil: (i) quando o réu for desconhecido ou sua identidade incerta; (ii) quando seu paradeiro for ignorado, incerto ou inacessível; ou (iii) nas demais hipóteses previstas em lei.

• No mais, o § 3º do art. 256 do mesmo dispositivo dispõe que o réu será considerado em local ignorado ou incerto se resultarem infrutíferas as tentativas de sua localização, "inclusive mediante requisição pelo juízo de informações sobre seu endereço nos cadastros de órgãos públicos ou de concessionárias de serviços públicos." Note-se que o legislador empregou o termo "inclusive", o que indica que essa providência é uma possibilidade, mas não necessariamente uma imposição.

• O princípio da celeridade processual, previsto no art. 4º do CPC/2015, determina que o processo deve se desenvolver de maneira eficiente e ágil, evitando formalismos excessivos. Se as tentativas de localização do réu forem suficientes e conduzidas de maneira razoável, a ausência de requisição às concessionárias ou órgãos públicos não implica invalidade do procedimento.

• A expedição de ofícios a órgãos públicos e concessionárias, embora recomendável na maioria das situações, <u>não é uma exigência automática</u>. O Julgador tem discricionariedade para avaliar, caso a caso, se a requisição de tais informações é necessária, conforme o contexto fático e as tentativas já realizadas. A obrigatoriedade absoluta dessas medidas oneraria o processo com formalidades que, em muitos casos, não trariam resultados práticos.

• Portanto, a norma processual não obriga à expedição de ofícios a cadastros públicos e concessionárias de serviços públicos antes da citação por edital, mas prevê essa possibilidade como uma ferramenta importante, a ser utilizada conforme o juízo de valor do Magistrado, sempre levando em consideração a razoabilidade e a celeridade do processo.

• Informativo nº 645
• 26 de abril de 2019.
• TERCEIRA TURMA
• Compartilhe:
• Processo: REsp 1.799.166-GO, Rel. Min. Nancy Andrighi, por unanimidade, julgado em 02/04/2019, DJe 04/04/2019

Ramo do Direito DIREITO PROCESSUAL CIVIL

Tema <br /> Tempestividade. Suspensão do prazo recursal. Nascimento do filho do único patrono da causa. Comunicação imediata ao juízo. Desnecessidade.

Destaque - A suspensão do processo em razão da paternidade do único patrono da causa se opera tão logo ocorra o fato gerador (nascimento ou adoção), <u>independentemente da comunicação imediata ao juízo</u>.

• Informativo nº 771
• 25 de abril de 2023.
• SEGUNDA SEÇÃO
• Compartilhe:
• Processo: AR 6.463-SP, Rel. Ministra Maria Isabel Gallotti, Segunda Seção, por unanimidade, julgado em 12/4/2023.

Ramo do Direito DIREITO PROCESSUAL CIVIL

TemaPaz, Justiça e Instituições Eficazes <br /> Ação rescisória. Decisão rescindenda publicada em nome de advogado que nunca representou o autor nos autos da ação originária. Nulidade. Determinação de nova publicação da decisão rescindenda com reabertura do prazo do recurso.

Destaque - A ausência de intimação da decisão que implicou o provimento parcial do recurso interposto pela parte contrária é <u>sempre prejudicial</u> ao recorrido, sendo <u>cabível</u> o manejo de ação rescisória.

Informações do Inteiro Teor - Cinge-se a controvérsia a analisar a rescisão da decisão impugnada por ausência de intimação válida do advogado na ação originária.

• Em caso versando sobre "a possibilidade do manejo da ação rescisória, no caso de reconhecimento de nulidade absoluta, pela falta de intimação do procurador do recorrente acerca dos atos processuais praticados", esta Corte concluiu que "a exclusividade da querela nullitatis para a declaração de nulidade de decisão proferida sem regular citação das partes, representa solução extremamente marcada pelo formalismo processual. [...] A desconstituição do acórdão rescindendo pode ocorrer tanto nos autos de ação rescisória ajuizada com fundamento no art. 485, V, do CPC/1973 quanto nos autos de ação anulatória, declaratória ou de qualquer outro remédio processual" (STJ, REsp 1.456.632/MG, Rel. Ministra Nancy Andrighi, Terceira Turma, julgado em 7/2/2017, DJe 14/2/2017).

• Assim sendo, é admissível a presente ação rescisória para declarar a nulidade da intimação do autor após o julgamento unipessoal do recurso especial interposto pelo réu.

• Na hipótese, após o julgamento unipessoal do AREsp 1.370.930/SP em 29/11/2018, a Secretaria desta Corte, em virtude de equívoco na autuação, efetuou a publicação, em 7/12/2018, em nome de advogado que não tinha e nunca teve representação nos autos e não em nome do único advogado constituído pelo autor na ação originária.

• O § 2º do art. 272 do CPC 2015 dispõe que: "Sob pena de nulidade, é indispensável que da publicação constem os nomes das partes e de seus advogados, com o respectivo número de inscrição na Ordem dos Advogados do Brasil, ou, se assim requerido, da sociedade de advogados". Assim, a publicação da decisão unipessoal desta Corte em nome de advogado que nunca representou o autor nos autos da ação originária implicou violação manifesta ao disposto no § 2º do art. 272 do CPC 2015.

• Como decidido por esta Corte, em mais de uma oportunidade, a ausência de intimação da parte em virtude de equívoco na autuação autoriza a rescisão do julgado. "A ausência de intimação do recorrido, por erro na autuação do recurso especial, para a apresentação de contrarrazões e demais atos da parte constitui violação literal ao disposto no § 1º do art. 236 do Código de Processo Civil de 1973, possibilitando-se a rescisão do julgado com fundamento no art. 485, V, do mesmo estatuto".

• Em suma, a ausência de intimação da decisão que implicou o provimento parcial do recurso interposto pela parte contrária <u>é sempre prejudicial</u> ao recorrido. Nessa direção, esta Corte já observou que "o defeito ou a ausência de intimação - requisito de validade do processo (arts. 236, § 1º, e 247 do CPC/1973) - impedem a constituição da relação processual e constituem temas passíveis de exame em qualquer tempo e grau de jurisdição, independentemente de forma, alegação de prejuízo ou provocação da parte. <u>Trata-se de vícios transrescisórios</u>".

• Impõe-se concluir pela procedência do primeiro pedido rescisório (CPC 2015, art. 968, inciso I) para reconhecer que a publicação da decisão rescindenda em nome de advogado que nunca representou o autor nos autos da ação originária violou literalmente o disposto no art. 272, § 2º, do CPC 2015.

Muito embora o prazo seja decadencial - acaso o prazo para ação rescisória se expire em férias forenses, recesso, feriado ou quando não houver expediente forense - será prorrogado até o primeiro dia útil subsequente.

This article is about if Facebook really collects non-users' data, how does Facebook collect these data, and how does Facebook use these data. After reading this article, I knew that Facebook does collect non-users' data, but it doesn't create shadow profiles for non-users. The purpose Facebook uses these data is to connect two Facebook user through a non-user since they might know each other, and these data will be deleted in 10 days. But the thing is, they are collecting data all the time, so these data about non-users will not be deleted completely. When I use Instagram and TikTok, the app recommended friends to me. And sometimes I was very confused about how the apps know that I knew these people even it showed that we don't have any common friends on the apps. After reading this article, I guess sometimes they recommend friends through non-users.

This article was mainly about even though we did not intend to show some personal information online, people can still get it from other methods, such as our friends' connections. Researchers studied how social networks map out who is connected to whom. It also proves that privacy isn't just about what we share, it’s also about what our friends share or connect with. Because our friends build the network around us, their actions can indirectly show more personal information about ourselves.

This article discusses recent advancements in AI to create technologies that can perform actions like identifying criminals and monitoring students' attention during class or tests via facial observation and recognition. This technology uses many problematic methods tied to phrenology and eugenics.

[h14] Read about false correlations. For example, "Maine divorce rate" and "per capita margarine consumption" have a 99.26% correlation, but no causal relationship. Implications for social media data mining: First, formulate hypotheses, perform multiple comparison corrections, and use a holdout set for validation to avoid mistaking coincidence for a pattern. This is consistent with what we discussed in class about "correlation ≠ causation" and "p-hacking."

• Informativo 1157
• ADPF 1178 MC-Ref / DF
• Órgão julgador: Tribunal Pleno
• Relator(a): Min. FLÁVIO DINO
• Julgamento: 05/11/2024 (Virtual)
• Ramo do Direito: Processual Civil
• Matéria: Jurisdição e competência; litígios perante jurisdições estrangeiras; ajuizamento por ente subnacional; contratos de risco; pagamento de honorários de êxito

Litígios internacionais: pagamento de honorários advocatícios contratuais com base em cláusula “ad exitum”

Resumo Encontram-se presentes os requisitos para a concessão da medida cautelar, pois: (i) há plausibilidade jurídica no que se refere à vedação, em princípio, de pagamento por entes públicos dos chamados honorários de êxito, notadamente quando associados a elevadas taxas de retorno sobre o valor obtido em favor do Poder Público; e (ii) há perigo da demora na prestação jurisdicional, consubstanciado na proximidade de possível julgamento de demandas ajuizadas por municípios pátrios perante tribunais estrangeiros com pedido de indenização de elevada proporção.

• Conforme entendimento do Tribunal de Contas da União, as estipulações de êxito em contratos com a Administração Pública constituem atos ilegais, ilegítimos e antieconômicos. Nesse contexto, a celebração de contratos de risco, baseados em honorários de êxito (“taxa de sucesso”), com previsão de pagamento de elevado percentual do valor indenizatório eventualmente alcançado aos escritórios de advocacia contratados, representa grave risco de lesão econômica às vítimas e aos cofres públicos, porque permite que os próprios causídicos se tornem os grandes beneficiários de eventual reparação obtida judicialmente.

• Na espécie, diversos municípios ajuizaram ações de ressarcimento em virtude de desastres socioambientais, especialmente com relação aos acidentes nos municípios mineiros de Mariana e Brumadinho, de modo que é pertinente a aferição das condições dos contratos eventualmente celebrados, com vistas a proteger o patrimônio público nacional e a efetiva e integral reparação de danos perpetrados em solo brasileiro.

• Com base nesses e em outros entendimentos, o Plenário, por maioria, referendou a decisão que deferiu em parte medida liminar, para determinar aos municípios relacionados como interessados nos autos que (i) juntem cópias dos contratos porventura celebrados com os escritórios de advocacia para atuarem em outros países; e (ii) se abstenham de efetuar qualquer pagamento de honorários, contratados ad exitum, relativos às ações judiciais perante tribunais estrangeiros, sem que previamente haja o exame da legalidade por parte das instâncias soberanas do País, sobretudo o próprio STF.

eLife Assessment

This important study provides a systematic investigation of parent-of-origin (POE) effects on gene expression using large trio-based data from the Framingham Heart Study, uncovering thousands of potentially novel associations. While the findings are potentially significant, the statistical support for classifying POE eQTLs and some downstream analyses is incomplete, and more stringent re-analysis is needed. With such revisions, the work would serve as a foundation for advancing understanding of POEs and their role in gene regulation.

Reviewer #1 (Public review):

Summary:

This study presents a systematic investigation of parent-of-origin effects on gene expression using trio-based data from the Framingham Heart Study, which is notable for its relatively large number of trios. By combining whole-genome and RNA sequencing data, the authors examined the extent to which gene expression is influenced by whether genetic variants are inherited maternally or paternally.

The authors report that parent-of-origin eQTLs are widespread, identifying 15,893 eQTLs from 14,733 variants and 1,824 genes that were significant in paternal, maternal, or joint tests but not detected by traditional eQTL approaches. They further classified these associations based on the relative strength and direction of paternal and maternal effects, highlighting a subset with opposing directions. The study also highlighted eGenes linked to known imprinted genes as well as those with opposing parent-specific effects, and observed that paternal eGenes are enriched for drug targets. Finally, the work revisits previous findings in which eQTL studies were used to interpret disease-associated loci, emphasizing that conventional eQTL analyses without testing the parent-of-origin may mislead gene prioritization efforts. The study recommends that future downstream analyses, such as Mendelian randomization, take into account the provided lists of SNPs and eGenes and exclude those with strong parent-of-origin effects when linking genetic regulation to disease risk.

Strengths:

The major strength of the study lies in the scale and quality of the dataset, the trio-based design, and the systematic application of statistical tests for parent-of-origin effects. The strengths thoughtfully employed Bayes factors rather than p-values to provide stronger evidence of association, which adds rigor to their analyses. These design choices provide compelling evidence that parent-of-origin effects are widespread and that conventional eQTL analyses miss a substantial fraction of regulatory variation. The results are clearly presented and supported by robust analyses, including the identification of opposing parental effects and the enrichment of paternal eGenes for drug targets. Notably, the two examples demonstrating how these findings can reshape disease gene prioritization highlight the broader impact of the study and encourage further work in the community to incorporate parent-of-origin effects.

Weaknesses:

The main limitations of the study are threefold. First, there is a lack of replication in independent cohorts, which is understandable given the difficulty of identifying datasets with a comparable number of trios, but replication would help establish the generalizability of the findings. Second, while Bayes factors are thoughtfully used to assess evidence of association, the paper does not fully explore how the chosen thresholds translate to the expected rate of false positives. For example, a minor allele frequency cutoff of 1% was applied, which seems somewhat arbitrary, and without reporting the allele frequency distribution of the identified eQTLs, it is unclear whether rare variants disproportionately contribute to the signals, potentially affecting the reliability of discoveries. Third, the ancestry background of the study samples is not reported, which could be a confounding factor in the genetic analyses.

Reviewer #2 (Public review):

Summary:

The authors have used 1477 sequenced trios with available gene expression data in the offspring to discover eQTLs that act in a parent-of-origin specific manner. The classified associated SNPs are tested for enrichment for GWAS hits, drug target genes, etc.

Strengths:

The manuscript presents an impressive analysis of a very rich data set of parent-of-origin eQTLs. To my knowledge, it is one of the largest studies of its kind, most analyses are sound, and the results are of interest to many in the field and potentially beyond. The different ideas of follow-up analyses are useful and make sense.

Weaknesses:

While in general the analyses are well-conducted, I noticed a major issue with the POE eQTL classification, which puts into question most of the downstream analysis. In light of this problem, most of the analysis would need to be rerun, which represents a major revision of the paper, but is straightforward to repair.

The major problem with the classification of POEs is that simply having significant maternal, but insignificant paternal effect is not an indicator of POE, this happens widely for SNPs with no POE whatsoever (it can happen by chance even when both maternal and paternal effects are the same and non-zero - the authors can see it via simulations under the null [maternal=paternal effect]). In order to be able to talk about POE, first, a significant difference between maternal and paternal effects needs to be claimed. Therefore, none of the 4 sets of POE eQTLs are justified. To me, the only relevant criterion to pick POE SNPs is the P-value when comparing the maternal and paternal effects. The definitions of the 4 groups are based on somewhat ad hoc priors, BF thresholds, etc. Also, in Section 4.6, the value of theta is arbitrarily chosen (along with the threshold of 4 to declare POE). In my opinion, the clean treatment of the 4 groups would start with a significant P-value (beta_maternal vs beta_paternal). Within this set, you can then use the original criteria presented in the paper, but only among these associations where there is solid evidence of different parental effects.

Author response:

We thank the two anonymous reviewers who took the time and effort to read and evaluate our work. We look forward to submitting a revised version of the manuscript that addresses their comments.

A major concern shared between both reviewers is our use of Bayes factors instead pvalues to measure the strength of association. In revision, we will add a section in Supplementary to compare and constrast Bayes factor and p-values. Very briefly here, p-value is the tail probability under the null. Formally, it is defined as P(T > t|H₀), for a test statistic T with obvserved value t computed from data D. But our interest is P(H₀|D) and P(H₁|D), posterior probabilities of the null and alternative models, about which p-value says nothing. With FDR approach, a q-value, the minium FDR at which a null is rejected, which can be estimated from a collection of p-values, has a Bayesian interpretation as the probability that H₀ is true conditioning on rejecting that H₀. This is not quite P(H₀|D) but nevertheless a useful probabilistic statement. For FDR approach to work, however, the collection of tests need to be reasonably independent, and their effect sizes need to be mixed. Both implicit assumptions can fail for cis eQTL analysis.

On the other hand, with Bayes factors we can compute posterior probability P(H₀|D) and P(H₁|D) after specifying prior odds P(H₁)/P(H₀) (or equivalently P(H₁) since P(H₀)+ P(H₁) = 1). In our manuscript, the prior odds used to determined Bayes factor threshold is 1/1000, or about 1 cis eQTL per gene. Bayes factor also allows us to directly compare two non-nested alternative models P(paternal effect|D) and P(maternal effect|D), which is difficult to do using p-values.

It was suggested (by reviewer 2) that POE eQTL should be defined by testing H₀ : θ₀ = θ₁ against H₁ : θ₀ ̸= θ₁ where θ₀ and θ₁ are maternal and paternal effects respectively. This indeed was our initial approach, as evidenced in Table 1 (last column) and Section 4.5 in Methods. Our final approach is more stringent: H₀ : β₀ = β₁ = 0 against H₁ : β₀ = 0,β₁/= 0, to use test for paternal effect as an example (the test for maternal effect can be obtained in a similar fashion). That is, we not only require that paternal and maternal effects be the same, as suggested by reviewer, but also require that they are both 0 under the null. This is partially motivated by an example in Table 1 (Gene ZNF890P) where both β₀ > 0 and β₁ > 0, and β₀/= β₁. In other words, examples like this where both paternal and maternal effects are significant and their differences are also significant were not included in our downstream classification and further analysis.

This paragraph illuminated the fact behind some social media such as TikTok. As a TikTok user, I spend so much time on scrolling everyday, but I didn't know why only videos on TikTok are so attracting me so much until I read this chapter. The platform collects the data about what kind of videos I watch the most and uses algorithm to recommend videos to me. For instance, I really like playing pool and watching pool games on TikTok, so when I scroll, some ads about pool products such as pool cues, tips, and gloves show up. And the way that TikTok increase the time users spend on scrolling is also about this. We don't know what video will show up before we scroll, but when we scroll to the next video and get the video that we are interested in, we just keep scrolling.

当解析器被创建时，Document 节点 也随之被创建。在树构建阶段，以 Document 为根的 DOM 树将被修改，节点 会被添加到其中。词法分析器发出的每个 标记 都将由树构造器处理。对于每个 标记，规范定义了与之相关的 DOM 节点类型，并将为该 标记 创建此 节点。该 节点 会被添加到 DOM 树中，如果它是元素节点，则同时也会被添加到开放 元素 栈中。这个栈用于纠正嵌套不匹配和未闭合的标签。该算法也被描述为一个状态机，其状态被称为"插入模式"。

Mandato dos eleitos para CIPA = 1 ano, passível de 1 reeleição.

• Presidente CIPA = Representa empregador;

• Vice-Presidente CIPA = Representa <u>empregados</u>.

• ARE 1018459 ED
• Órgão julgador: Tribunal Pleno
• Relator(a): Min. GILMAR MENDES
• Julgamento: 12/09/2023

• Publicação: 30/10/2023

• Embargos de declaração em processo paradigma da sistemática da repercussão geral.

• Direito do Trabalho. Tema 935.

• Alegação de omissão, contradição ou obscuridade.

• Efeitos infringentes. Admissão da cobrança da contribuição assistencial prevista no art. 513 da Consolidação das Leis do Trabalho, inclusive aos não filiados ao sistema sindical, assegurado ao trabalhador o direito de oposição.

• A constitucionalidade das contribuições assistenciais, respeitado o direito de oposição, faculta a trabalhadores e sindicatos instrumento capaz de, ao mesmo tempo, recompor a autonomia financeira do sistema sindical e concretizar o direito à representação sindical sem ferir a liberdade de associação dos trabalhadores.

• Embargos de declaração conhecidos e providos em parte para retificar a tese da repercussão geral, que passa a ter a seguinte redação: “É constitucional a instituição, por acordo ou convenção coletivos, de contribuições assistenciais a serem impostas a todos os empregados da categoria, <u>ainda que não sindicalizados</u>, desde que <u>assegurado o direito de oposição</u>.”

eLife Assessment

This important study shows that retinal bipolar cell subtype-specific differences in the size of synaptic ribbon-associated vesicle pools contribute to the transient versus sustained kinetics of the responses of retinal ganglion cells. The data are extensive and compelling. This work will be of broad interest to researchers working on synaptic transmission, retinal signal processing, and sensory neurobiology.

Reviewer #1 (Public review):

Summary:

In the retina, parallel processing of cone photoreceptor output under bright light conditions dissects critical features of our visual environment, and fundamental to visual function. Cone photoreceptor signals are sampled by several types of bipolar cells and passed onto the ganglion cells. At the output of retinal processing, retinal ganglion cells send about 40 different codes of the visual scene to the brain for further processing. In this study, the authors focus on whether subtype-specific differences in the size of synaptic ribbon-associated vesicle pools of bipolar cells contribute to different retinal ganglion cell (RGC) responses.

Specifically, inputs to ON alpha RGCs producing transient versus sustained kinetics (ON-S vs. ON-T, respectively) are compared. The authors first demonstrate that ON-S vs. ON-T RGCs are readily identifiable in a whole mount preparation and respond differently to both static and to a spatially uniform, randomly fluctuating (Gaussian noise) light stimulus. Liner-nonlinear (LN) models were used to estimate the transformation between visual input and excitatory synaptic input for each RGCs; these models suggested the presence of transient versus sustained kinetics already in the excitatory inputs to ON-T and ON-S RGCs.

Indeed, the authors show that (glutamatergic) excitatory inputs to ON-S vs. ON-T RGCs are of distinct kinetics. The subtypes of bipolar cells providing input to ON-S are known (i.e., type 6 and 7), but the source of excitatory bipolar inputs to ON-T RGCs needed to be determined. In a tedious process, it is elegantly shown here that ON-T RGCs receive most of their excitatory inputs from type 5 and 6 bipolars. Interestingly, the temporal properties of light-evoked responses of type 5, 6 and 7 bipolars recorded from the somas were indistinguishable and rather sustained, suggesting that the origin of transient kinetics of excitatory inputs to ON-T RGCs suggested by the LN model might be found in the processing of visual signals at the bipolar cell axon terminal. Blocking GABA- or glycinergic inhibitory inputs did not alter the light-evoked excitatory input kinetics to ON-T and ON-S RGCs. Two-photon glutamate sensor imaging revealed significantly faster kinetics of light-evoked glutamate signals at ON-T versus ON-S RGCs, and that differences in glutamate release from presynaptic bipolar cells are retained without amacrine feedback to bipolar cells. Detailed EM analysis of bipolar cell ribbon synapses onto ON-T and ON-S RGCs revealed fewer ribbon-associated vesicles at ON-T synapses, that is consistent with stronger paired-flash depression of light-evoked excitatory currents in ON-T RGCS versus ON-S RGCs. This study suggests that bipolar subtype-specific differences in the size of synaptic ribbon-associated vesicle pools contributes to transient versus sustained kinetics in RGCs.

Strengths:

The use of multiple, state-of-the-art tools and approaches to address the kinetics of bipolar to ganglion cell synapse in an identified circuit.

Reviewer #2 (Public review):

Summary:

Goal of the study. The authors tried to pinpoint the origins of transient and sustained responses measured at retinal ganglion cells (rgcs), which is the output layer of the retina. Response characteristics of rgcs are used to group them into different types. The diversity of rgc types represents the ability of the retina to transform visual inputs into distinct output channels. They find that the physical dimensions of bipolar cell's synaptic ribbons (specialized release sites/active zones) vary across the different types of cone on-bpcs, in ways that they argue could facilitate transient or sustained release. This diversity of release output is what they argue underlies the differences in on-rgcs response characteristics, and ultimately represents a mechanism for creating parallel cone-driven channels.

Strengths:

The major strengths of the study are the anatomical approaches employed and the use of the "glutamate sniffer" to assay synaptic glutamate levels. The outline of the study is elegant and reflects the strengths of the authors.

Comments on revised version:

The authors have addressed my comments either through new experiments and/or with additional citations.

Explanation of the studies significance. I think the study provides a solid set of data, acquired through exceptional methodologies, and delivers a compelling hypothesis. This is an exceptionally talented group of systems level thinkers and experimentalists, who are now pointing to smaller scale biophysical principles of synaptic transmission.

Reviewer #3 (Public review):

Summary:

Different types of retinal ganglion cell (RGC) have different temporal properties - most prominently a distinction between sustained vs. transient responses to contrast. This has been well established in multiple species, including mouse. In general, RGCs with dendrites that stratify close to the ganglion cell layer (GCL) are sustained; whereas those that stratify near the middle of the inner plexiform layer (IPL) are transient. This difference in RGC spiking responses aligns with similar differences in excitatory synaptic currents as well as with differences in glutamate release in the respective layers - shown previously and here, with a glutamate sensor (iGluSnFR) expressed in the RGCs of interest. Differences in glutamate release were not explained by differences in the distinct presynaptic bipolar cells' voltage responses, which were quite similar to one another. Rather, the difference in transient vs. sustained responses seems to emerge at the bipolar cell axon terminals in the form of glutamate release. This difference in the temporal pattern of glutamate release was correlated with differences in the size of synaptic ribbons (larger in the bipolar cells with more sustained responses), which also correlated with a greater number of vesicles in the vicinity of the larger ribbons.

The main conclusion of the study relates to a correlation (because it is difficult to manipulate ribbon size or vesicle density experimentally): the bipolar cells with increased ribbon size/vesicle number would have a greater possibility of sustained release, which would be reflected in the postsynaptic RGC synaptic currents and RGC firing rates. This model proposes a mechanism for temporal channels that is independent of synaptic inhibition. Indeed, some experiments in the paper suggest that inhibition cannot explain the transient nature of glutamate release onto one of the RGC types. Still, it is surprising that such a diverse set of inhibitory interneurons in the retina would not play some role in diversifying the temporal properties of RGC responses.

Strengths:

(1) The study uses a systematic approach to evaluating temporal properties of retinal ganglion cell (RGC) spiking outputs, excitatory synaptic inputs, presynaptic voltage responses, and presynaptic glutamate release. The combination of these experiments demonstrates an important step in the conversion from voltage to glutamate release in shaping response dynamics in RGCs.

(2) The study uses a combination of electrophysiology, two-photon imaging and scanning block face EM to build a quantitative and coherent story about specific retinal circuits and their functional properties.

Weaknesses:

(1) There were some interesting aspects of the study that were not completely resolved, and resolving some of these issues may go beyond the current study. For example, it was interesting that different extracellular media (Ames medium vs. ACSF) generated different degrees of transient vs. sustained responses in RGCs, but it was unclear how these media might have impacted ion channels at different levels of the circuit that could explain the effects on temporal tuning.

(2) It was surprising that inhibition played such a small role in generating temporal tuning. The authors explored this further in the revision, which supported the original claim that inhibition plays a minor role in glutamate release dynamics from the bipolar cells under study.

Author response:

The following is the authors’ response to the current reviews.

Reviewer #2 had several remaining suggestions:

In some instances, the authors face well-known limitations. For example, bath application of drugs. Blockers of Gly and Gaba receptors are likely problematic when studying a network that includes a diverse set of inhibitory interneurons. Likewise, the results derived from application of AMPAR and KAR blockers should impact HC cell fxn, and presumably inner retina interneuron networks. In the Discussion the authors are encouraged to address more of these concerns (e.g., Discussion line 709).

Rather than concluding that the bath application of drugs is without complications, they can conclude that under the experimental conditions, glutamate release from these On-bipolars continues to exhibit Transient and Sustained release. This is really the key point of their study.

This is a good suggestion.  We have added a discussion of the complications of the pharmacology starting on line 754.  

If indeed sustained release is a reflection of higher release rates, ribbon size is what point to but, there are many other possibilities, such as SV recycling, or recruitment of reserve pools of SVs, fusion machinery, Cav channel behavior. The authors could cite more literature in the Discussion.

We added a sentence to this effect in the discussion, starting on line 866.

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review): 

Summary: 

In the retina, parallel processing of cone photoreceptor output under bright light conditions dissects critical features of our visual environment and is fundamental to visual function. Cone photoreceptor signals are sampled by several types of bipolar cells and passed onto the ganglion cells. At the output of retinal processing, retinal ganglion cells send about 40 different codes of the visual scene to the brain for further processing. In this study, the authors focus on whether subtype-specific differences in the size of synaptic ribbon-associated vesicle pools of bipolar cells contribute to different retinal ganglion cell (RGC) responses. Specifically, inputs to ON alpha RGCs producing transient versus sustained kinetics (ON-S vs. ON-T, respectively) are compared. The authors first demonstrate that ON-S vs. ON-T RGCs are readily identifiable in a whole mount preparation and respond differently to both static and to a spatially uniform, randomly fluctuating (Gaussian noise) light stimulus. Liner-nonlinear (LN) models were used to estimate the transformation between visual input and excitatory synaptic input for each RGCs; these models suggested the presence of transient versus sustained kinetics already in the excitatory inputs to ON-T and ON-S RGCs. Indeed, the authors show that (glutamatergic) excitatory inputs to ON-S vs. ON-T RGCs are of distinct kinetics. The subtypes of bipolar cells providing input to ON-S are known (i.e., type 6 and 7), but the source of excitatory bipolar inputs to ON-T RGCs needed to be determined. In a tedious process, it is elegantly shown here that ON-T RGCs receive most of their excitatory inputs from type 5 and 6 bipolars. Interestingly, the temporal properties of light-evoked responses of type 5, 6, and 7 bipolars recorded from the somas were indistinguishable and rather sustained, suggesting that the origin of transient kinetics of excitatory inputs to ON-T RGCs suggested by the LN model might be found in the processing of visual signals at the bipolar cell axon terminal. Blocking GABA- or glycinergic inhibitory inputs did not alter the light-evoked excitatory input kinetics to ON-T and ON-S RGCs. Twophoton glutamate sensor imaging revealed significantly faster kinetics of light-evoked glutamate signals at ON-T versus ON-S RGCs. Detailed EM analysis of bipolar cell ribbon synapses onto ON-T and ON-S RGCs revealed fewer ribbon-associated vesicles at ON-T synapses, which is consistent with stronger paired-flash depression of lightevoked excitatory currents in ON-T RGCS versus ON-S RGCs. This study suggests that bipolar subtype-specific differences in the size of synaptic ribbon-associated vesicle pools contribute to transient versus sustained kinetics in RGCs. 

Strengths: 

The use of multiple, state-of-the-art tools and approaches to address the kinetics of bipolar to ganglion cell synapse in an identified circuit. 

Weaknesses: 

For the most part, the data in the paper support the conclusions, and the authors were careful to try to address questions in multiple ways. Two-photon glutamate sensor imaging experiment showing that blocking GABA- and glycinergic inhibition does not change the kinetics of light-evoked glutamate signals at ON-T RGCs would strengthen the conclusion that bipolar subtype-specific differences in the size of synaptic ribbon-associated vesicle pools contribute to transient versus sustained kinetics in RGCs. 

Thank you for this suggestion. We have revised the text throughout to be careful not to imply that amacrine cells have no role in shaping EPSCs and spike output, but instead that the transience of the On-T responses persists without amacrine cells (see for example lines 91, 450-453, 514-518, 696-714). We have also added additional iGluSnFR experiments to the paper to further test this conclusion (new Figure 7). The new data shows that the transience of glutamate release from the On-T cells is retained when 1) spiking amacrine cell activity is suppressed by blocking voltage-gated Na⁺ channels with TTX or 2) all amacrine cell activity is suppressed by blocking AMPA receptors with NBQX. This does provide nice additional evidence that amacrine cells are not necessary for the sustained/transient distinction.

Reviewer #2 (Public Review): 

Summary: 

Goal of the study. The authors tried to pinpoint the origins of transient and sustained responses measured at retinal ganglion cells (rgcs), which is the output layer of the retina. Response characteristics of rgcs are used to group them into different types. The diversity of rgc types represents the ability of the retina to transform visual inputs into distinct output channels. They find that the physical dimensions of bipolar cell's synaptic ribbons (specialized release sites/active zones) vary across the different types of cone on-bpcs, in ways that they argue could facilitate transient or sustained release. This diversity of release output is what they argue underlies the differences in on-rgcs response characteristics, and ultimately represents a mechanism for creating parallel cone-driven channels. 

Strengths: 

The major strengths of the study are the anatomical approaches employed and the use of the "glutamate sniffer" to assay synaptic glutamate levels. The outline of the study is elegant and reflects the strengths of the authors. 

Weaknesses: 

The major weakness is that the ambitious outline is not matched with a complete set of results, and the set of physiological protocols is disjointed, not sufficient to bridge the systems-level question with the presynaptic release question. 

Thank you for this comment as it provides an opportunity (here and in the paper) for us to clarify our main goal. We wanted to link the well-established distinction between transient and sustained retinal responses to anatomy. This required locating where this difference arises within the circuitry – which we show to be at least largely the bipolar output synapse – and then examining the structure of this synapse in detail. While we would certainly be interested in connecting our results to a biophysical description of the synapse, that was not the primary focus of our study and was not something we could add without substantial additional work.  

Major comments on the results and suggestions. 

The ribbon model of release has been explored for decades and needs to be further adapted to systems-level work. The study under consideration by Kuo et al. takes on this task. Unfortunately, the experimental design does not permit a level of control over presynaptic/bpc behavior that is comparable to earlier studies, nor do they manipulate release in ways that test the ribbon model (i.e., paired recordings or Ribeye-ko). Furthermore, the data needs additional evaluation, and the presentation and interpretations should draw on published biophysical and molecular studies. 

As described above, our goal was to test several possible explanations for the difference between transient and sustained responses in OnT and OnS ganglion cells: (1) differences in the light responses of the bipolar cells that convey photoreceptor signals to the relevant ganglion cells; (2) shaping of bipolar transmitter release by presynaptic inhibition; (3) shaping of ganglion cell responses by postsynaptic inhibition or spike generation; (4) differences in feedforward bipolar synapses. We were surprised to find that the feedforward bipolar synapses play a central role in this difference, and your comment nicely prompts us to relate this to the large literature on biophysical studies of release from ribbon synapses. We have made substantial revisions in the text to do this. This includes anticipating the importance of feedforward synaptic properties in the abstract and introduction (lines 36-37 and 61-64), pointers in the results (lines 539-548), and several new paragraphs in the discussion (starting on lines 751, 773 and 787). By showing that the transient/sustained differences originates largely at feedforward bipolar synapses, we set the stage for future work that shows how biophysical properties of the synapse shape physiological signals that traverse it.

To build a ribbon-centric context, consider recent literature that supports the assertion that ribbons play a role in forming AZ release sites and facilitating exocytosis. Reference Ribeye-ko studies. For example, ribbonless bpcs show an 80% reduction in release (Maxeiner et al EMBO J 2016), the ribbonless retina exhibits signaling deficits at the output layer (Okawa et al ...Rieke, ..Wong Nat Comm 2019), and ribbonless rods show an 80% reduction the readily releasable pool (RRP) of SVs (Grabner Moser, elife 2021). In addition, the authors could refer to whole-cell membrane capacitance studies on mammalian rods, cones, and bpcs, because the size of the RRP of SVs scales with the dimensions and numbers of ribbons (total ribbon footprint). For comparison, bipolars see the review by Wan and Heidelberger 2011. For a comparison of mammalian rods and cones, see, rods: Grabner and Moser (2021 eLife), Mueller.. Regus Leidig et al. (2019; J Neurosci) and cones Grabner ...DeVries (Nat Comm 2023). A comparison of cell types shows that the extent of release is (1) proportional to the total size of the ribbon footprint, and (2) less release is witnessed when ribbons are deleted (also see photo ablation studies by Snellman.... And Mehta..Zenisek, Nat Neurosci and Neuron).

Thank you for these pointers into the literature.  We have included much of this work in the revised Discussion (see three paragraphs starting on line 751). The revised text focuses on the evidence that larger and more numerous ribbons lead to increased release. The direct evidence from previous work for this relationship supports our (indirect) conclusions in the current paper about the role of ribbon size and associated vesicle pools in transient vs sustained responses.  

Ribbon morphology may change in an activity-dependent manner. The rod ribbon AZ has been reported to lengthen in the dark (Dembla et al 2020), and deletion of the ribbon shortens the length of the AZ (defined by Cav1,4 or RIM2); in addition, the Ribeye-ko AZs fail to change in size with light and dark conditioning. Furthermore, EM studies on rod and cone AZs in light and dark argue that the number of SVs at the base of the ribbon increases in the dark, when PRs are depolarized (see Figure 10, Babai et al 2016 JNeurosci). Lastly, using goldfish Mb1 on-bipolars, Hull et al (2006, J Neurophysio) correlated an increase in release efficiency with an increase in ribbon numbers, which accompanied daylight. >> When release activity is high, ribbon AZ length increases (Dembla, rods), the number of docked SVs increases (Babai, rods cones), and the number of ribbons increases (Hull, diurnal Mb1s). 

We have extensively revised the discussion section to include more discussion of ribbons, particularly emphasizing evidence supporting the general argument that larger ribbons support higher release rates. We focused on studies that provided direct links between release rates and ribbon size or number of ribbon-associated vesicles.  This includes studies that pair electrophysiology and anatomy and those that measure the consequences of ablating ribbons,

The results under review, Kuo et al., were attained with SBF-SEM, which has the benefit of addressing large-volume questions as required here, yet it achieves lower spatial resolution than what is attained with TEM tomography and FIB-EM. Ideally, the EM description would include SV size, and the density of ribbon-tethered SVs that are docked at the plasma membrane, because this is where the SVs fuse (additional non-ribbon release sites may also exist? Mehta ... Singer 2014 J Neurosci). Studies by Graydon et al 2011 and 2014 (both in J Neurosci), and Jean ... Moser et al 2018 (eLife) are good examples of quantitative estimates of SVs docking sites at ribbons. SBF-SEM does not allow for an assessment of SVs within 5 nm of the PM, but if the authors can identify the number of SVs that appear within the limit of resolution (10 to 15 nm) from the PM, then this data would be useful. Also, what dimension(s) of the large ribbons make them larger? Typically, ribbons are fixed in height (at least in the outer retina, 200 to 250 nm), but their length varies and the number ribbons per terminal varies. Is the larger ribbon size observed in type 6 bpcs do to longer ribbons, or taller ribbons? A longer ribbon likely has more docked SVs. An additional possibility is that more SVs are about the ribbon-PM footprint, either more densely packed and/or expanding laterally (see definitions in Jean....Moser, elife 2018). 

We have included an additional analysis of ribbon surface area from our 3D SBFSEM reconstructions. As with the volume measurements included in the original submission, ribbon surface areas are distinct between type 5i and type 6 bipolar cells (Fig. S10A), ON-T RGCs on average receive input from ribbons with smaller surface area than ON-S RGCs (Fig. S10B), and ribbon surface area predicts the number of adjacent vesicles across bipolar cell types (Fig. S10C).  We agree that a higher resolution view of presynaptic structures would be very helpful, but the resolution of our SBF-SEM data is limited (e.g. each pixel is 40 nm on a side).  This resolution does not allow us to distinguish between vesicles at vs near the membrane. 

In our observations, both length and height of the ribbons showed variability across individual bipolar cells. And ribbons in type 6 bipolar cells tended to be either longer and/or taller compared to those in type 5 cells. We agree that a longer ribbon may accommodate more docked SVs. A more definitive analysis would benefit from higher-resolution, isotropic 3D reconstructions of ribbons, which would allow more precise shape analysis and ,together with a detailed assessment of docked SVs at the ribbons.

The ribbon literature given above makes the argument that ribbons increase exocytotic output, and morphological studies suggest that release activity enhances 1) ribbon length (Dembla) and 2) the density of SVs near the PM (Babai). These findings could lead one to propose that type 6 bpcs (inputs to On-sustained) are more active than type 5i (feed into On-transient). Here Kuo et al. show that the bpcs have similar Vm (measured from the soma) in response to light stimulation. Does Vm predict release? Not entirely as the authors acknowledge, because: Cav channel properties, SV availability, and negative feedback are all downstream of bpc Vm. The only experiment performed to test downstream factors focused on negative feedback from amacrines. The data presented in Figures 5C-F led me to conclude the opposite of what the authors concluded. My impression is that the T-ON rgc exhibits strong disinhibition when GABA-blockers are applied (the initial phase is greatly increased in amplitude and broadened with the drug), which contrasts with the S-On rgc responses that show a change in the amplitude of the initial phase but not its width (taus would be nice). Here and in many places the authors refer to changes in release kinetics, without implementing a useful description of kinetics. For instance, take the cumulative current (charge) in Figure 5C and fit the control and drug traces to arrive at taus, and their respective amplitudes, and use these values to describe kinetic phases. One final point, the summary in Figure 5D has a p: 0.06, very close to the cutoff for significance, which begs for more than an n = 5. Given that previous studies have shown that bpc output is shaped by immediate msec GABA feedback, in ways that influence kinetic phases of release (..Mb1 bipolars, see Vigh et al 2005 Neuron), more attention to this matter is needed before the authors rule out feedback inhibition in favor of ribbon size. If by chance, type 5i bpcs are under uniquely strong feedback inhibition, then ribbon size may result from less activity, not less output resulting from smaller ribbons.

The text surrounding Figure 5 led to some confusion, and we have revised that text and the figure for clarity.  First, the data in that figure is entirely from On-T cells (the upper and lower panels show block of GABA and glycine receptors separately).  Second, the observation that we make there is that block of inhibitory receptors increases the transience of the On-T excitatory input, rather than decreasing it as would be expected if the transience is created by presynaptic inhibition. We have added additional data and that increase in transience is now significant. Inhibitory block does substantially increase the amplitude of the postsynaptic response, and a likely origin of this change in response is inhibitory feedback to the bipolar synaptic terminal. We now indicate this in the text on page 13, lines 438-453. 

The key result of this figure for our purposes here is that the transience of the excitatory input to the OffT cell remains with inhibitory input blocked. We have clarified throughout the text that our results indicate that inhibitory feedback is not necessary for the difference between transient release into On-T and sustained release onto On-S. This does not mean that inhibitory feedback does not shape the responses in other ways or contribute to the transient/sustained difference - just that for the specific stimuli we use that difference is retained without presynaptic inhibition. We have also added citations to past work showing that activity of amacrine cells can modulate bipolar transmitter release. 

Whether strong feedback inhibition limits activity and therefore limits ribbon size in an activity-dependent way is an intriguing possibility. Indeed, addressing why ribbons are larger in type 6 bipolar cells vs. other bipolar types will be an interesting avenue of further study. However, it would be surprising if ribbon sizes changed during the acute pharmacological block conditions (~10-15 minutes) we employed in our study. Our point here is that there is an interesting correlation between presynaptic ribbon size and the kinetics of glutamate release. We do not think that the two possibilities stated in the last sentence (“…ribbon size may result from less activity, not less output resulting from smaller ribbons”) are mutually exclusive.

We have not further quantified the response kinetics in the experiments of Figure 5 as the large changes induced by the pharmacology (especially GABA receptor block) make it unclear how to interpret quantitative differences.  In other places we have quantified kinetics through the STA or specified that our focus was more qualitative (i.e. transient vs sustained kinetics). 

As mentioned above, the behavior of Cav channels is important here. This is difficult to address with voltage clamps from the soma, especially in the Vm range relevant to this study. Given that it has previously been modeled that the rod bpc to AII pathway adapts to prolonged depolarization of rbcs through downregulating Cav channel-mediated Ca²⁺ influx (Grimes ....Rieke 2014 Neuron), it seems important for Kou et al to test if there is a difference in Cav regulation between type 6 and 5i bpcs. Ca²⁺  imaging with a GCaMP strategy (Baden....Lagnado Current Biology, 2011) or filling the presynapse with Ca dyes (see inner hair cells: Ozcete and Moser, EMBO J 2020) would allow for the correlation of [Ca]intra with GluSnf signals (both local readouts).

This is a good suggestion but is outside the scope of our current paper. Our focus was on the circuit origin of the difference in response of the OnT and OnS responses rather than the specific biophysical mechanism.  We are of course interested in the mechanism, but the additional experiments needed to pin that down would need to be a part of future experiments. The work here represents an important step in that direction as it greatly reduces the number of possible locations and mechanisms for the sustained/transient difference and hence serves to focus any future mechanistic investigations.

Stimulation protocol and presentation of Glutamate Sniffer data in Figure 6. In all of your figures where you state steady st as a % of pk amplitude, please indicate in the figure where you estimate steady state. Alternatively, if you take the cumulative dF/F signal, then you can fit the different kinetic phases. From the appearance of the data, the Sustained Glu signals look like square waves (Figure 6B ROI1-4), without a transient at onset, which is not predicted in your ribbon model that assumes different kinetic phases (1. depletion of docked SVs, and 2. refilling and repriming). The Transient responses (Figure 6B ROI5-8) are transient and more compatible with a depressing ribbon scheme. If you take the cumulative, for all of the On-S and compare it to all of the On-T responses, my guess is the cumulative dF/F will be 10 to 20 larger for the S-On. Would you conclude that bpc inputs to On-S (type 6) release 20fold more SVs per 4 seconds on a per ribbon basis, and does the surface area of the type 6 bpcs account for this difference? From Figures 8B and D, the volume of the ribbon is ~2 fold greater for type 6 vs 5i, but the Surface Area (both faces of ribbon) is more relevant to your model that claims ribbon size is the pivotal factor. If making cumulative traces, and comparisons on an absolute scale is unfounded, then we need to know how to compare different observations. The classic ribbon models always have a conversion factor such as the capacitance of an SV or q size that is used to derive SV numbers from total dCm or Qcontent. See Kim ....et al von Gersdorff, 2023, Cell Reports. Why not use the Gaussian noise stimulus in Fig 6 as in Figure 1 and 2? 

For iGluSnFR recordings, steady-state responses were measured from the mean fluorescence over the last 1 sec of the light step (2 sec duration) response. We have included this information in the figure caption and in the Methods. 

There is a good deal of variability in the iGluSnR responses from one ROI to another, and the ROIs shown in the original submission had a less prominent transient component than many other ROIs. We have replaced this figure with another that is more representative of the average behavior across ROIs. The full range of behavior is captured in Figure 6C; it is clear across ROIs that glutamate release near ON-S dendrites shows both sustained and transient components. The new experiments in which we block amacrine cell activity also include a few more example ROIs from ON-S cells, and those also show both transient and sustained components.

Your suggestion to integrate the iGluSnFR signals to compare to our structural analysis of ribbons is interesting. However, we are hesitant to make a quantitative comparison between the two without further experiments to validate how the iGluSnFR signals we measure relate to release of single vesicles. For example, a quantitative measure of release based on the iGluSnR experiments would require accounting for possible differences in the expression of the indicator - which could differ both in overall level and/or location relative to release sites. 

This comment and one above highlight the importance of measures of ribbon surface area, which we now provide (Figure S10).

Figure 7. What is the recovery time for mammalian cones derived from ribbon-based models? There are estimates from membrane capacitance studies. Ground squirrel cones take 0.7 to 1 sec to recover the ultrafast, primed pool of SVs when probed with a paired-pulse protocol (Grabner ...DeVries 2016, Neuron). Their off-bpcs take anywhere from under 0.2 sec to a second to recover, which is a combination of many synaptic factors (Grabner ...DeVries Nat Comm 2023). Rod On bpcs take over a second (Singer Diamond 2006, reviewed Wan and Heidelberger 2011). In Figure 7B, the recovery time is ~150 ms for the responses measured at rgcs. This brief recovery time is incompatible with existing ribbon models of release. Whole-cell membrane capacitance measurements would be helpful here.

Thanks for drawing our attention to this issue. Indeed, we see a relatively rapid recovery in the paired-flash experiments. We now discuss this recovery time in the context of past measurements of recovery of responses in cones and bipolar cells (paragraph starting on line 773). There are many factors that could contribute to the relatively rapid recovery we observe - including synaptic factors such as those highlighted by Grabner et al., (2016) either at the cone-to-bipolar synapses or the bipolar-to-RGC synapses. We are certainly interested in a more detailed understanding of this issue, but the additional experiments are outside the scope of this paper.  

Experimental Suggestion: Add GABA blockers and see if type 5i bpc responds with more release (GluSniff) and prolonged [Ca2+] intra (GCaMP). Compare this to type 6 bpc behavior with GABA/gly blockers. This will rule in or out whether feedback inhibition is involved. 

Figure 7 in the revised manuscript includes two new experiments examining glutamate release (without the simultaneous measurement of bipolar cell intracellular calcium) while blocking (1) all/most amacrine cell-mediated inhibition via inclusion of NBQX in the bath solution, and (2) blocking spiking amacrine cells via inclusion of TTX in the bath solution. The transient vs sustained difference in light-evoked glutamate release around ON-T and ON-S RGC dendrites remained with amacrine activity suppressed. These new results are consistent with the anatomical and pharmacological data that were included in the initial submission of the manuscript (Fig. 5) that indicate presynaptic inhibition does not have a major role in shaping release kinetics at these synapses. 

Reviewer #3 (Public Review): 

Summary: 

Different types of retinal ganglion cell (RGC) have different temporal properties - most prominently a distinction between sustained vs. transient responses to contrast. This has been well established in multiple species, including mice. In general, RGCs with dendrites that stratify close to the ganglion cell layer (GCL) are sustained; whereas those that stratify near the middle of the inner plexiform layer (IPL) are transient. This difference in RGC spiking responses aligns with similar differences in excitatory synaptic currents as well as with differences in glutamate release in the respective layers - shown previously and here, with a glutamate sensor (iGluSnFR) expressed in the RGCs of interest. Differences in glutamate release were not explained by differences in the distinct presynaptic bipolar cells' voltage responses, which were quite similar to one another. Rather, the difference in transient vs. sustained responses seems to emerge at the bipolar cell axon terminals in the form of glutamate release. This difference in the temporal pattern of glutamate release was correlated with differences in the size of synaptic ribbons (larger in the bipolar cells with more sustained responses), which also correlated with a greater number of vesicles in the vicinity of the larger ribbons. 

The main conclusion of the study relates to a correlation (because it is difficult to manipulate ribbon size or vesicle density experimentally): the bipolar cells with increased ribbon size/vesicle number would have a greater possibility of sustained release, which would be reflected in the postsynaptic RGC synaptic currents and RGC firing rates. This model proposes a mechanism for temporal channels that is independent of synaptic inhibition. Indeed, some experiments in the paper suggest that inhibition cannot explain the transient nature of glutamate release onto one of the RGC types. Still, it is surprising that such a diverse set of inhibitory interneurons in the retina would not play some role in diversifying the temporal properties of RGC responses. 

Strengths: 

(1) The study uses a systematic approach to evaluating temporal properties of retinal ganglion cell (RGC) spiking outputs, excitatory synaptic inputs, presynaptic voltage responses, and presynaptic glutamate release. The combination of these experiments demonstrates an important step in the conversion from voltage to glutamate release in shaping response dynamics in RGCs. 

(2) The study uses a combination of electrophysiology, two-photon imaging, and scanning block-face EM to build a quantitative and coherent story about specific retinal circuits and their functional properties. 

Weaknesses: 

(1) There were some interesting aspects of the study that were not completely resolved, and resolving some of these issues may go beyond the current study. For example, it was interesting that different extracellular media (Ames medium vs. ACSF) generated different degrees of transient vs. sustained responses in RGCs, but it was unclear how these media might have impacted ion channels at different levels of the circuit that could explain the effects on temporal tuning.

We do not have an explanation for the quantitative differences in response kinetics we observed in Ames’ medium vs. ACSF. There are modest differences in calcium and magnesium concentration and a larger difference in potassium (2.5 mM in ACSF vs 3.6 mM in Ames). It would be interesting to test which of these (or other) differences accounts for the difference in response kinetics.

(2) It was surprising that inhibition played such a small role in generating temporal tuning. At the same time, there were some gaps in the investigation of inhibition (e.g., IPSCs were not measured in either of the RGC types; pharmacology was used to investigate responses only in the transient RGCs).

We were also surprised at this result. We have included additional data on inhibition in the revised manuscript. Figure S3 shows light-evoked IPSC data from both RGC types (Fig. S3) and Fig. 7 shows additional iGluSnFR measurements around both ON-T and ON-S RGC dendrites with inhibition blocked via bath application of NBQX (Fig. 7) and separately with inhibition from spiking amacrine cells blocked with TTX. These experiments provide additional evidence for the small role of inhibition. We attempted to measure the kinetics of excitatory input to ON-S cells with inhibition blocked, but we found that the excitatory input showed strong spontaneous oscillations under these conditions and the light responses were changed so drastically that we did not feel we could make a clear comparison with control conditions.

(3) There could be additional discussion and references to the literature describing several topics, including: temporal dynamics of glutamate release at different levels of the IPL; previous evidence that release sites from a single presynaptic neuron can differ in their temporal properties depending on the postsynaptic target; previous investigations of the role of inhibition in temporal tuning within retinal circuitry. 

Thanks, we have included more discussion and references to the relevant literature as you have suggested in the recommendations to authors.

Reviewer #1 (Recommendations For The Authors): 

The presented raw data of the pharmacological experiments show that SR95531 and TPMPA robustly increased both the amplitude and duration of the transient component of the light step-evoked excitatory currents, with slight, if any enhancement of the sustained component in ON-T RGCs Figure 5C. Statistical analysis of the population data (n=5) with Wilcoxon signed rank test yielded no significant difference (ln 363). However, reanalyzing the data extracted from the graph (Figure 5D) revealed that the difference between the paired observations is normally distributed (Shapiro-Wilk normality test, P=0.48) allowing parametric statistics to be used, which provides higher statistical power. Accordingly, reanalyzing the presented data with paired Student's t-test data revealed significant differences (P=0.01) in the steady-state amplitude normalized to that of the peak, recorded in the presence of SR95531 and TPMPA. In other words, based on the (rough) analysis of the presented pharmacology data GABAergic feedback inhibition significantly contributes to shaping the transient portion of the light-evoked excitatory currents in ON-T RGCs, by making it more transient. I believe a similar analysis based on the actual data is necessary, and the results should be communicated either way. However, if warranted, two-photon glutamate sensor imaging experiments showing that blocking GABA- and glycinergic inhibition does not change the kinetics of light-evoked glutamate signals at ON-T RGCs should also be performed, as these would be critical in drawing a conclusion regarding the effect of feedback inhibition on glutamate release from bipolar cells.

Thanks for this feedback. We have added another cell to the data set in Fig. 5D. With this addition, SR95531/TPMPA application significantly increases the response transience of excitatory currents measured in ON-T RGCs compared to control. This enhanced transience in GABA_A/C receptor blockers is due to an increase in the amplitude of the initial peak component of the response (control peak amplitude: -833.7±103.3 pA; SR95531+TPMPA peak amplitude: 2023±372.7pA; p=0.03, Wilcoxon signed rank test), with no change to the later sustained component (control plateau amplitude: -200.7±14.71pA; SR95531+TPMPA plateau amplitude: -290.9±43.69pA; p=0.15, Wilcoxon signed rank test).

We should clarify that this result indicates that GABAergic inhibition makes the excitatory inputs to ON-T RGCs less transient. Block of GABA receptors increased transience, thus intact GABAergic transmission appears to limit the initial peak of the response and therefore make excitatory currents more sustained. We unfortunately were not able to examine whether sustained excitatory currents in ON-S RGCs would become more transient using the same approach. In our hands, bath application of SR95531+TPMPA led to the generation of large-amplitude (>1nA) oscillatory bursts of excitatory input that developed within 5 minutes and persisted for the duration of the incubation (up to ~30 min) in drugs. Further, presentation of light steps tended to induce variable amplitude responses, likely dependent on the presence of spontaneous bursts; when large amplitude responses were evoked, these typically oscillated for several seconds after the step.

To examine a potential role for presynaptic inhibition in transient vs. sustained bipolar cell output, we therefore chose to eliminate amacrine cell-mediated inhibition by bath application of the AMPA/kainate receptor antagonist NBQX in additional iGluSnFR measurements. This manipulation should leave ON bipolar cell responses intact while eliminating most amacrine cell-mediated responses (and OFF bipolar cell driven responses). In separate experiments, we also eliminated inhibition from spiking amacrine cells by bath application of TTX. As shown in new Fig. 7, sustained and transient responses persisted in distal versus proximal RGC dendrites, respectively. Compared to SR95531/TPMPA, bath application of NBQX was not associated with spontaneous bursts of glutamate release around ON-S dendrites. These results show that amacrine cell-mediated inhibition is not required for either sustained or transient glutamate release from bipolar cells that provide input to ON-S and ON-T RGCs.

Small points: 

(1) The legend of Figure 1 (D) refers to shaded areas to show {plus minus} SEM, but no shade is visible (at least in my printout).

The SEM shading is there in Fig. 1D but is mostly obscured by the mean lines for the respective RGC types. We have added this to the figure caption.

(2) I found the reported Vrest for the ON bipolar cells somewhat depolarized. Perhaps due to the uncompensated junction potentials? 

These measurements are indeed not corrected for the liquid junction potential (which is approximately -10.8 mV between K-gluconate internal and Ames’ solution). We did not apply this correction since the appropriate value is not clear in perforated patch recordings as the intracellular chloride concentration is unknown (and can differ from that in the pipette solution). We have clarified this in the results text where we describe the Vrest values (lines 335-338).

(3) It is Wilcoxon signed rank test, not Wilcoxan. 

Thanks for catching this. This has been corrected in the revised manuscript.

Reviewer #2 (Recommendations For The Authors): 

Some amacrines express vesicular Glut-3 transporter and are reported to release glutamate (Marshak, Vis Neurosci 2016). Are Amacrine vGlut3 signals postsynaptic (within ~0.5 um) to cone bpc ribbons?

We did not characterize VgluT3-expressing amacrine cells in our SEM datasets. A recent study by Friedrichson et al. (Nat. Comm. 2024; PMID 38580652) using 3D SEM reconstructions found that Vglut3-amacrines are postsynaptic to both type 5i and type 6 bipolar cells, as well as other type 5/xbc bipolar cells (and receive >50% of their input from type 3a OFF bipolar cells).

How far apart are the postsynaptic targets from the ribbon release sites? The ribbons at type 5i bpc/On-T input appear separated from the dendrites of On-T rgcs (Figure 8C). At least further away than the type 6 bpc ribbons are from On-S rgc dendrites (Figure 8C). Distance may create a thresholding phenomenon, whereby only multivesicular bouts at the onset of depolarization are able to elevate synaptic Glu to levels needed to activate On-T GluRs. See Grabner et al Nat Comm 2023 for such scenarios in the outer retina.

This is an intriguing possibility, but we should point out that the presynaptic ribbons in Fig. 9C (former Fig. 8C) are similar distances (within the resolution of our reconstructions) from the ON-T and ON-S dendrites. We have increased the brightness of the dendrite segments for both RGC types in the resubmission figure; note that ON-T RGCs have spine-like protrusions that may not have been as apparent in the previously submitted version of our manuscript.

In Figures 1 and 2, Sustained responses look like the derivative of Transient responses, minus the negative going inflection. In addition, the sustained responses appear to have a lower threshold of activation than the transient On rgcs, because there are more bouts of action potentials (and membrane depol in V-clamp) with earlier onset in sustained than transients traces. It would be great if the GLuSniff data captured these differences. Take cumulative dF/F and see what the onset time is, or an initial tau if possible.

This is a good suggestion. However, we are reluctant to make detailed quantitative comparisons such as this without further validation of how the kinetics of the iGluSnFR signals relate to kinetics of glutamate release.  A specific concern is that differences in the location and amount of iGluSnFR expression could impact any such comparisons.

A recent study by Kim et al von Gersdorff (Cell Reports, 2023) presents interesting phases of release in response to light flashes, measured from AIIs, and complementary results from pairs of rbcs-AIIs. The findings highlight the complexity of SV pools under well-controlled experiments. Could their results be explained as variations in rbc ribbon size through development, and possibly between rbcs or within an rbc? 

This certainly seems possible and would be consistent with the dependence of release on ribbon size that our results support.  It would be interesting to see if there are clear anatomical correlates of that change in release properties.  

Figure 5 is a pivotal point in the study, but my review has identified numerous weaknesses. The feedback inhibition onto bipolar cell terminals is likely to sculpt glutamate release, and the results do not convincingly rule out this possibility. The suggestions for improvements range from the data needing to be reanalyzed with regard to statistical tests, and/or adding a few more data points (n = 5) before concluding a p: 0.06 is insignificant. 

We have added an additional recording to this data set. With n= 6 cells, there is now a statistically significant difference between ON-T RGC excitatory currents measured in control conditions versus during GABA_A/C receptor blockade. Please note that all the recordings shown in Figure 5C-F are from ON-T RGCs (the two panels show separately block of GABergic and glycinergic receptors). We did not make it sufficiently clear that the original trend (now statistically significant) is opposite of that expected if presynaptic GABAergic inhibition contributes to response transience in ON-T RGCs.  What we see is that excitatory synaptic inputs to ON-T RGCs become more transient (rather than mpre sustained) during GABA_A/C receptor blockade. We have revised the text in that section to make this point more clearly.

We have also included new data from iGluSnFR measurements showing that bath application of NBQX does not affect light step-evoked glutamate release kinetics at proximal (sustained) or distal (transient) RGC dendrites (control: steady-state amp. as % of peak amp. 13 ± 10; mean ± S.D.; n = 189 ROIs/4 FOVs for ON-T dendrites vs 40 ± 12; mean ± S.D.; n = 287 ROIs/8 FOVs for ON-S dendrites; NBQX: 6 ± 3; mean ± S.D.; n = 112 ROIs/1 FOV for ON-T dendrites vs 23 ± 9; mean ± S.D.; n = 97 ROIs/2 FOVs for ON-S dendrites; *p<0.001). By blocking glutamate receptors on amacrine cells, NBQX (AMPA/KAR antagonist) eliminates all/most amacrine cell-mediated signaling in the retina and should therefore abolish presynaptic inhibitory input to bipolar cell terminals across the IPL. Taken together, our results indicate that presynaptic inhibition does not play a critical role in establishing transient versus sustained kinetics for the stimulus conditions we employed in our study.

There is a need to cite more recent literature on bipolar cell ribbons (e.g. see Wakeham et al., Front. Cell. Neurosci., 2023), in order to support experimental design and interpretation of the results. The authors should discuss their Ribeye-KO data from Okawa et al 2019 Nat Comm, Figure 7, in the context of their new iGluSnFR results. 

Thank you for prompting us on this issue. We have expanded the discussion regarding ribbons and included more citations to the ribbon literature. That is largely in the three paragraphs starting on line 727.

One point deserves emphasis because it is central to the authors' ribbon model but not consistent with their data. The ribbon model as they put it, and as commonly stated, holds that a transient phase of release at the onset of depolarization indicates the depletion of the primed SVs, and the subsequent slower rate of release (steady state release in the authors' terms) reflects recruiting, priming, and release of new SVs. The On-transient dendrite GluSnf responses agree with this multiphasic process, but the sustained responses show only an elevation in glutamate without a pronounced initial peak, creating a square-wave-shaped response (Figure 6B). This does not agree with the simple ribbon-based release model. I would expect the signals from the T- and S-on dendrites to have a comparable initial phase, while the sustained phase should be greater in amplitude for the S-on dendrites. More discussion may clarify possible mechanisms.

Thanks for pointing this out. The example iGluSnFR traces we originally included in the manuscript were not entirely representative in that they did not show much initial transient phase. Note there is a distribution of steady-state amplitudes for proximal dendrites in Fig. 6C; the examples are from ROIs from the upper end of the distribution. In the new Figure 7, we have included some additional examples that show both a clear transient and sustained component. The summary data in Figure 6C shows the distribution of sustained/transient ratios across ROIs.  

Reviewer #3 (Recommendations For The Authors): 

(1) It would be interesting to understand the differences in IPSCs in the two RGC types. Perhaps they are small in both types, which would explain their apparent lack of impact on temporal tuning. The authors may already have these data.

We did make measurements of noise-evoked IPSCs (as well as EPSCs) in a subset of ON-T and ON-S recordings. We have now included this data as Figure S3. There are slight differences in the kinetics of inhibition between RGC types (Fig. S3C) and there is a trend towards stronger inhibition (relative to excitation) in ON-T RGCs compared to ON-S RGCs (Fig. S3E), although there is not a statistically significant difference. In both cases excitatory synaptic currents are as large or larger than inhibitory currents, and this does not include the difference in driving force near spike threshold which will favor excitatory input by a factor of 2-3.  Hence our data suggests that postsynaptic inhibition does not play a major role in generating the differential temporal spiking responses of ON-T and ON-S RGCs. However, additional experiments examining the relative contribution of excitation and inhibition to spiking output in these RGCs would be needed to reach a firm conclusion.

The pharmacological experiments in which we blocked inhibition (Fig. 5C-F, new Fig. 7) were designed to test the effect of presynaptic inhibition on bipolar cell output (voltage-clamp isolation of excitatory currents in Fig. 5; iGluSnFR measurements of glutamate release in Fig. 7). We do not mean to suggest that postsynaptic inhibition does not have any role in shaping the spiking behavior of these RGC types, but that transient vs. sustained kinetics are already present in the bipolar cell output and that presynaptic inhibition of bipolar cell terminals does not appear to account for this difference.  We have revised the text throughout to be clearer on this point.

(2) It could be convincing to show transient/sustained differences between RGC types in dim light, where the response would depend on the rod bipolar/AII circuit. In this case, any difference in temporal properties would presumably be explained by differences that localize to the cone bipolar cell axon terminals. Indeed, is that the result in Figure 1B? This seems to be a dim stimulus presented on darkness, which may be driven through the rod bipolar pathway. The authors could then discuss the interpretation of this data in terms of the rod bipolar circuit. 

Yes, Figure 1B is a dim light step (~30R*/rod/s) presented from darkness and the distinction between cells is clear down at still lower light levels that more effectively isolate signaling through the rod bipolar pathway. Thanks for making this point that observation of distinct temporal responses under scotopic conditions where signals suggests these differences must arise at and/or downstream of cone bipolar cell output. We have included additional text (lines 361-365) in the results describing bipolar cell responses that raise this point.

(3) Glutamate release was already measured across the full IPL depth by Borghuis et al. (2013) and Franke et al. (2017). It would be appropriate to better motivate the current study based on these existing measurements.

We have clarified that these important studies provided important motivation for measuring excitatory synaptic input to ON-T vs. ON-S RGCs (lines 165-169).   

(4) Line 212/213. It would be appropriate to add to the list of papers showing the different stratification of transient vs. sustained responses: Borghuis et al. (2013) and Beaudoin et al. (2019).

Thank you - these references have been added.  

(5) Line 635-638. It would be useful to discuss papers by Pottackal et al. (2020, 2021), which suggested that a single presynaptic cell (starburst) can signal with different temporal properties depending on the postsynaptic target (other starburst vs. DSGCs). The mechanism was not completely resolved (i.e., it was not explained by differences in presynaptic Ca channels at the two synapse types), but it at least shows that neurotransmitter release can show different filtering depending on the postsynaptic target from the same presynaptic neuron. (This could also be at play for the type 6 bipolar cell inputs to ON-S vs. ON-T RGCs in the present study.)

We have added a reference to Pottackal et al 2021 in this section.

(6) Line 714. Should describe the procedure for embedding the tissue in agarose. 

We have added more detail regarding agarose embedding for preparation of retinal slices in the methods.

(7) Line 775. Need a better description of the virus (not the construct), what serotype? Provide the Addgene number if available. 

This has been added to the methods.

(8) Line 808. Was the SD for the gaussian really 50%? That would cut off a lot of the distribution, i.e., it would get clipped at 0. 

Yes, the SD for Gaussian noise was 50%. This high contrast stimulus was used in part to achieve measurable signals from bipolar cells. You are correct that some of the distribution was clipped at 0 (it was also clipped at twice the mean to make sure that the distribution remained symmetrical). The clipping was accounted for during our LN analyses.

(9) The paper should discuss Swygart et al. (2024) results showing different spatial surround properties of neighboring synapses from a type 6 bipolar cell. Based on this result, it would seem very likely that amacrine cells could play a role in shaping the temporal processing of bipolar cell glutamate release as well. Indeed, spatial and temporal processing will not be completely independent in a typical experiment. For example, with the spot stimulus used in the present study, bipolar cells within the center versus the edge of the spot will have different balances of center/surround activation, which could potentially influence their temporal processing.

We have included discussion of results from Swygart et al 2024 in the section of the Discussion in which we point out differences in surround inhibition between ON-S and ON-T RGCs (lines 710-714). We agree that spatial and temporal processing are not completely independent. Our results with SR95531/TPMPA indicate ON-T RGCs receive stronger GABAergic surround inhibition than ON-S RGCs (Fig. S8). However, our results in Fig. 5C-D show GABAergic surround inhibition makes ON-T excitation more sustained rather than more transient. So even though bipolar cells presynaptic to ON-T RGCs receive stronger surround inhibition (Fig. S8), this inhibition does not establish the transient kinetics of glutamate release from these bipolar cells (in fact, it works to make release more sustained). Additional iGluSnFR experiments where we used NBQX to block all/most amacrine cell-mediated responses also suggest presynaptic inhibition does not have an important role in establishing differential glutamate release kinetics onto ON-S vs. ON-T RGC dendrites (Fig. 7).

(10) Cui et al. 2016 described ON-S Alpha as having a divisive suppression mechanism that explained the temporal properties of white-noise response better than a standard LN model. Do the authors think the divisive suppression reflects a property of the excitatory synapses independent of inhibition?

This is an interesting question, but one for which we don’t have a good answer for now. As mentioned in some of the above responses and as we have tried to clarify in the manuscript, we do not mean to imply that there is no role for presynaptic inhibition in modulating bipolar cell output, including for the divisive suppression described by Cui et al. Rather, our point is that the distinction between transient and sustained excitatory input to ON-T and ON-S RGCs does not require presynaptic inhibition and is more likely an intrinsic property of the bipolar cell synapses. 

(11) Do the authors mean to imply that the pool size at bipolar cell ribbon synapses could depend on the use of Ames vs. ACSF? 

For now, we do not have a good answer as to why there are quantitative differences in response kinetics between Ames and ACSF. We have not done any experiments to investigate whether ribbon sizes or ribbon pools are different in the different solutions.

(12) More generally, different mean luminance levels could drive different levels of baseline glutamate release, which could alter the available pool of vesicles at bipolar cell ribbon synapses. Can we explain varying degrees of transient/sustained in the same cell at different levels of mean luminance based on this mechanism (e.g., Grimes et al., 2014)?

Yes, the emergence of a transient component of excitatory input to ON-S RGCs at ~100 R*/rod/s versus at scotopic levels (0.5 R*/rod/s) in Grimes et al. (2014) could be due to differences in the number of releasable vesicles (due to different type 6 bipolar cell axon terminal membrane potentials and hence differences in spontaneous release rates) at the different light levels.

We should note that although ON-T and ON-S RGCs exhibit some changes in transient/sustained kinetics across different light levels, the relative differences between these RGC types are preserved across light levels. We have included a statement about this in the text (lines 361-367).

(13) Figure 1. Have the authors considered performing the LN analysis of the firing responses, to compare the degree of rectification between the two RGC types?

This is a good suggestions. From an LN analysis of spiking responses, we do not observe a clear difference between the static nonlinearity component of the model for ON-T and ON-S RGCs. Both RGC types are strongly rectified under our experimental conditions.  

(14) Figure 5. Do the authors have the pharmacology data for the ON-S cells? There are examples of sustained EPSCs in amacrine cells that become more transient after blocking inhibition, which at least suggests that inhibition can play some role in the transient/sustained nature of glutamate release (Park et al., 2015, Figure 3). Perhaps ON-S cells likewise become more transient with inhibition blocked. 

(The colored symbols in A were not visible in a printout. It would be useful to indicate the cell type (ON-T) in C and E). 

As described above in the response to reviewer 1’s recommendation for authors, we were not able to use SR95531/TPMPA for recordings from ON-S RGCs. Bath application of these drugs led to oscillatory bursts of excitatory input to ON-S RGCs. However, the lack of effect of bath-applied NBQX on the kinetics of glutamate release around either ON-T or ON-S RGC dendrites (new Fig. 7) suggests that presynaptic inhibition does not contribute to generating sustained excitation to ON-S RGCs (or transient excitation to ON-T RGCs).  

We have corrected Fig. 5A to include the referenced colored symbols and have also edited Fig 5C and E to clarify that measurements in Fig. 5C-F are from ON-T RGCs.

(15) Figure 6 legend. Should be Kcng4-Cre, not KCNG-Cre. Also, it should make clear that this is cre-dependent expression of iGluSnFR. For C, were the statistics based on the number of FOVs? 

Thanks for catching this, we have corrected Figure 6 legend. The methods section includes a description of how we achieved iGluSnFR expression on alpha RGC dendrites via a cre-dependent viral strategy in Kcng4-Cre mice.  We have also clarified that the statistics are based on ROIs in Figure 6C.

(16) Figure 7, Flashes were apparently 400% contrast on a dim background. What was the background? Is there a rod component to the response in this case? 

In Figure 7 (now Figure 8), the same background (~3300 R*/rod/s; 2000 P*/Scone/s) was used as in the Gaussian noise and step response experiments. At this light level, the response should be primarily be mediated by cones.

(17) Figure S1. The colors here differ from those in previous figures (Here, ON-T, magenta; ON-S, cyan). Is something mislabeled? 

Thanks for catching this. We mistakenly swapped the labels in the legend for Fig. S1. The figure colors were correct, but we have corrected the legend in the revised manuscript.

(18) Figure S2. For the LN model for RGC synaptic currents, the ON-S are more rectified than some previous recordings (Cui et al., 2016). Is this perhaps explained by different light levels?

We aren’t sure why ON-S excitatory currents are more strongly rectified in our recordings compared to Cui et al., 2016. Cui et al. used an ~20-fold higher background light intensity (~40,000 P*/cone/s vs. ~2000 P*/cone/s in our study), so different light levels may be a factor (although we should point out that rectification increases in these RGCs between scotopic to low photopic light levels (see Grimes et al., 2014 and Kuo et al., 2016).

(19) The study is apparently comparing PV1 and PV2 described in Farrow et al. (2013; see Supplementary information for stratification analysis), which should be cited.

Thanks, we have corrected this oversight in the revised manuscript. We now cite Farrow et al and mention the connection to PV1 and PV2 in the first paragraph of Results (lines 104-108).

• The article describes the case of a user (Mateusz) whose Google account was hijacked after he ran malware (a stealer) sent from a compromised friend's Discord account.
• The malware stole the user's active session cookie, not their password. This allowed the attacker to bypass all login protections, including 2-Step Verification (like a YubiKey), because they were able to take over an already-authenticated session without needing to log in.
• Using this hijacked session, the attacker convinced Mateusz to join a "Family Group" (Google Family Link) and simultaneously changed his account's birth date to an age under 13.
• This action immediately flagged the account as a "child's account," with the attacker as the "parent/guardian," which locked Mateusz out and triggered a 14-day permanent deletion process.
• Mateusz is now in a "digital Catch-22": standard account recovery forms do not work for "child accounts," and Google's support (including YouTube and Google Play) has been unhelpful, closing his tickets despite him having proof of ownership.
• The article criticizes Google for an "astounding oversight" in its business logic that allows an adult account's age to be so easily changed to a child's, creating a major vulnerability.
• As a result, Mateusz lost 13 years of data (Gmail, Drive, Contacts) and access to all his purchases on Google Play.
• The article concludes that since 2FA can't stop session hijacking, the only effective way to protect against the data loss from this specific attack is to regularly back up your Google account data using Google Takeout.

m

eLife Assessment

This important work provides a new method to extract cfDNA from residual plasma from heparin separators for molecular testing. The evidence supporting the authors' claims is convincing, although some further metrics should also be evaluated. This finding will be interesting to people working in epigenomics and infectious disease diagnostics.

Reviewer #1 (Public review):

Summary:

The manuscript "Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies" addresses a timely and practical question: whether residual plasma from heparin separator tubes can serve as a source of cfDNA for molecular profiling. This idea is attractive, since such samples are routinely generated in clinical chemistry labs and would represent a vast and accessible resource for liquid biopsy applications. The preliminary results are encouraging, but in its current form, the study feels incomplete and requires additional work.

My major concerns/suggestions are as follows:

(1) Context and literature

The introduction provides only limited background on prior attempts to use heparinized plasma for cfDNA work. It is well known that heparin can inhibit PCR and sequencing library preparation, which has historically discouraged its use. The authors should summarize the relevant literature more comprehensively and explain clearly why this approach has not been widely adopted until now, and how their work differs from or overcomes these earlier challenges.

(2) Genome-wide coverage

The analyses focus on correlations in methylation patterns and fragmentation metrics, but there is no evaluation of sequencing coverage across the genome. For both WGS and WMS, it would be important to demonstrate whether cfDNA from heparin plasma provides unbiased coverage, or whether certain genomic regions are systematically under-represented. A comparison against coverage profiles from cell-derived DNA (e.g., PBMC genomic DNA) would help to put the results in context and assess whether the material is suitable for whole-genome applications.

(3) Viral detection sensitivity

The study shows strong concordance in viral detection between EDTA and heparin samples, but the sensitivity analysis is lacking. For clinical relevance, it is critical to demonstrate how well heparin-derived plasma performs in low viral load cases. A quantitative comparison of viral read counts and genome coverage across tube types would strengthen the conclusions.

Reviewer #2 (Public review):

Summary:

The authors propose that leftover heparin plasma can serve as a source for cfDNA extraction, which could then be used for downstream genomic analyses such as methylation profiling, CNV detection, metagenomics, and fragmentomics. While the study is potentially of interest, several major limitations reduce its impact; for example, the study does not adequately address key methodological concerns, particularly cfDNA degradation, sequencing depth limitations, statistical rigor, and the breadth of relevant applications.

Strengths:

The paper provides a cheap method to extract cfDNA, which has broad application if the method is solid.

Weaknesses:

(1) The introduction lacks a sufficient review of prior work. The authors do not adequately summarize existing studies on cfDNA extraction, particularly those comparing heparin plasma and EDTA plasma. This omission weakens the rationale for their study and overlooks important context.

(2) The evaluation of cfDNA degradation from heparin plasma is incomplete. The authors did not compare cfDNA integrity with that extracted from EDTA plasma under realistic sample handling conditions. Their analysis (lines 90-93) focuses only on immediate extraction, which is not representative of clinical workflows where delays are common. This is in direct conflict with findings from Barra et al. (2025, LabMed), who showed that cfDNA from heparin plasma is substantially more degraded than that from EDTA plasma. A systematic comparison of cfDNA yields and fragment sizes under delayed extraction conditions would be necessary to validate the feasibility of their proposed approach.

(3) The comparison of methylation profiles suffers from the same limitation. The authors do not account for cfDNA degradation and the resulting reduced input material, which in turn affects sequencing depth and data quality. As shown by Barra et al., quantifying cfDNA yield and displaying these data in a figure would strengthen the analysis. Moreover, the statistical method applied is inappropriate: the authors use Pearson correlation when Spearman correlation would be more robust to outliers and thus more suitable for methylation and other genomic comparisons.

(4) The CNV analysis also raises concerns. With low-coverage WGS (~5X) from heparin-derived cfDNA, only large CNVs (>100 kb) are reliably detectable. The authors used a 500 kb bin size for CNV calling, but they did not acknowledge this as a limitation. Evaluating CNV detection at multiple bin sizes (e.g., 1 kb, 10 kb, 50 kb, 100 kb, 250 kb) would provide a more complete picture. In addition, Figure 3 presents CNV results from only one sample, which risks bias. Similar bias would exist for illustrations of CNVs from other samples in the supplementary figures provided by the authors. Again, Spearman correlation should be applied in Figure 3c, where clear outliers are visible.

(5) It is important to point out that depth-based CNV calling is just one of the CNV calling methods. Other CNV calling software using SNVs, pair-reads, split-reads, and coverage depth for calling CNV, such as the software Conserting, would be severely affected by the low-quality WGS data. The authors need to evaluate at least two different software with specific algorithms for CNV calling based on current WGS data.

(6) The authors omit an important application of cfDNA: somatic mutation detection. Degraded cfDNA and reduced sequencing depth could substantially impact SNV calling accuracy in terms of both recall and precision. Assessing this aspect with their current dataset would provide a more comprehensive evaluation of heparin plasma-derived cfDNA for genomic analyses.

Author response:

Reviewer #1 (Public review):

Summary:

The manuscript "Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies" addresses a timely and practical question: whether residual plasma from heparin separator tubes can serve as a source of cfDNA for molecular profiling. This idea is attractive, since such samples are routinely generated in clinical chemistry labs and would represent a vast and accessible resource for liquid biopsy applications. The preliminary results are encouraging, but in its current form, the study feels incomplete and requires additional work.

We thank the reviewer for the encouragement and for recognizing the potential of clinical chemistry plasma as an accessible source for cfDNA-based analyses. We look forward to addressing the gaps described below.

My major concerns/suggestions are as follows:

(1) Context and literature

The introduction provides only limited background on prior attempts to use heparinized plasma for cfDNA work. It is well known that heparin can inhibit PCR and sequencing library preparation, which has historically discouraged its use. The authors should summarize the relevant literature more comprehensively and explain clearly why this approach has not been widely adopted until now, and how their work differs from or overcomes these earlier challenges.

We thank the reviewer for their valuable comments and agree that the review of prior work needs to be more thorough, with the gaps clearly identified. In the revised manuscript, we will expand the introduction to include a more comprehensive summary of prior studies. Some of the material was in the Discussion, but we will move it to the introduction in the revision. In general, we will comment briefly here about the novelty of this work and the previous gap in the literature:

(1) Previous pre-analytical studies use DNA fluorometry and qPCR, which cannot distinguish between genomic DNA contamination (from cells) and cfDNA. In contrast, our study uses adapter-based NGS with DNA spike-ins, which can exclude genomic DNA contamination and enable precise quantification of cfDNA input and measurement of their lengths. In Figure 5b-c, we demonstrate that we were able to match our paired sample results only under the measurements of our NGS study, not in previous attempts. Note the current Fig. 5 captions b&c should be swapped and will be corrected in the revision.

(2) As the reviewer has astutely mentioned, heparin is a well-recognized inhibitor of PCR, and heparinized specimens are historically contraindicated for molecular testing. However, most modern cfDNA assays now use NGS, which includes multiple purification steps before PCR amplification, minimizing the impact of heparin interference.

(3) Previous clinical chemistry tests used serum tubes, which are known to generate background gDNA during clotting and are therefore unsuitable for cfDNA-based analyses. In recent years, modern hospital chemistry laboratories, especially those supporting emergency departments, have gradually transitioned to heparin separator tubes for faster turnaround. Hence, residual plasma from heparin separator tubes is a more recent option, one that was not widely available when key pre-analytical studies on cfDNA were performed.

(2) Genome-wide coverage

The analyses focus on correlations in methylation patterns and fragmentation metrics, but there is no evaluation of sequencing coverage across the genome. For both WGS and WMS, it would be important to demonstrate whether cfDNA from heparin plasma provides unbiased coverage, or whether certain genomic regions are systematically under-represented. A comparison against coverage profiles from cell-derived DNA (e.g., PBMC genomic DNA) would help to put the results in context and assess whether the material is suitable for whole-genome applications.

Thank you for the insightful comment. We agree that evaluating sequencing coverage across the genome is important for assessing the suitability of cfDNA from heparin separators. In response, we are performing additional, in-depth runs to compare genome-wide coverage profiles in the Hospital Cohort. The results of these analyses will be included in the revised version of the manuscript.

(3) Viral detection sensitivity

The study shows strong concordance in viral detection between EDTA and heparin samples, but the sensitivity analysis is lacking. For clinical relevance, it is critical to demonstrate how well heparin-derived plasma performs in low viral load cases. A quantitative comparison of viral read counts and genome coverage across tube types would strengthen the conclusions.

We agree that evaluating analytical sensitivity in cases with low viral loads is important for understanding clinical performance. To address this point, we plan to include additional paired cases with viral loads below 1,000 IU/mL and examine the correlation of viral read counts between EDTA and heparin separators in this subset.

Reviewer #2 (Public review):

Summary:

The authors propose that leftover heparin plasma can serve as a source for cfDNA extraction, which could then be used for downstream genomic analyses such as methylation profiling, CNV detection, metagenomics, and fragmentomics. While the study is potentially of interest, several major limitations reduce its impact; for example, the study does not adequately address key methodological concerns, particularly cfDNA degradation, sequencing depth limitations, statistical rigor, and the breadth of relevant applications.

We thank the reviewer for the insightful comments and will work to clarify and address the mentioned issues. We do not find the residual plasma from the heparin separator to be a replacement for gold standard methods. Instead, we take it as a practical and complementary resource that may help broaden the accessibility of samples. Comparable cfDNA metrics highlight its potential to serve as an additional source for biobanking and research applications.

Strengths:

The paper provides a cheap method to extract cfDNA, which has broad application if the method is solid.

We thank the reviewer for the encouraging comment. While cost-effectiveness is a practical advantage, we believe the greater strength of this approach lies in the accessibility of sampling. Residual plasma from routine clinical tests offers an opportunity to include patients or time points that would otherwise be difficult to capture, such as those with severe illness or those sampled before treatment.

Weaknesses:

(1) The introduction lacks a sufficient review of prior work. The authors do not adequately summarize existing studies on cfDNA extraction, particularly those comparing heparin plasma and EDTA plasma. This omission weakens the rationale for their study and overlooks important context.

We thank both reviewers for this comment. See above under Reviewer 1’s responses for our provisional perspective on the background literature and gap. We will expand the Introduction to provide a more comprehensive summary of prior studies.

(2) The evaluation of cfDNA degradation from heparin plasma is incomplete. The authors did not compare cfDNA integrity with that extracted from EDTA plasma under realistic sample handling conditions. Their analysis (lines 90-93) focuses only on immediate extraction, which is not representative of clinical workflows where delays are common. This is in direct conflict with findings from Barra et al. (2025, LabMed), who showed that cfDNA from heparin plasma is substantially more degraded than that from EDTA plasma. A systematic comparison of cfDNA yields and fragment sizes under delayed extraction conditions would be necessary to validate the feasibility of their proposed approach.

We appreciate this thoughtful comment, which highlights reasonable concerns about cfDNA degradation in heparin. We would like to clarify that the Hospital Cohort, which only used leftover plasma in the clinical lab, was designed to reflect real-world clinical workflows, where unavoidable delays before plasma processing are already incorporated. In the Healthy Cohort, a subset of samples is also processed after controlled delays, as shown in Supplementary Figure 2.

Regarding the differing results in Barra et al. (2025, LabMed), where heparin tubes showed 85% cfDNA degradation, it is important to note that samples were incubated at 37 °C for 24 hours. We anticipate that endogenous nuclease would be active under 37 °C and would cause cfDNA degradation. However, this condition differs markedly from the relevant clinical workflows we describe here. In the routine hospital settings, blood samples are typically kept at room temperature for up to 60 minutes during transport and waiting. The outpatient setting can be more variable, but samples here are supposed to be refrigerated during transportation. They are then processed in high-throughput, fully automated systems that comply with nationally standardized quality regulations in the United States (CLIA). The resultant plasma will be physically separated from cellular components because of the gel in the heparin separators. The processed tubes are subsequently transferred to refrigerated storage at 4 °C. Under these conditions, samples do not experience prolonged exposure to elevated temperatures such as 37 °C, and refrigeration usually occurs within two hours of collection. We will incorporate these details in the revised manuscript.

Also, as we mentioned in our reply to Reviewer 1, Barra et al. used qPCR like most cfDNA pre-analytical studies, but qPCR is not a perfect DNA quantification method for NGS-based downstream analyses because it measures both cfDNA and contaminating genomic DNA. The latter can be excluded by most NGS assays. By using constant spike-in internal controls, our approach directly quantifies the amount of sequenceable cfDNA, providing a more accurate estimate of input DNA (Figure 5c). In one possible future experiment, the same sample in the Healthy Cohort can be delayed by 1-2 hours prior to processing (centrifugation and refrigeration) and kept at room temperature rather than 4 °C to mimic real-world delays. Outputs would be cfDNA yields and fragment sizes, and we would use constant spike-ins to quantify the amount of sequenceable DNA.

(3) The comparison of methylation profiles suffers from the same limitation. The authors do not account for cfDNA degradation and the resulting reduced input material, which in turn affects sequencing depth and data quality. As shown by Barra et al., quantifying cfDNA yield and displaying these data in a figure would strengthen the analysis. Moreover, the statistical method applied is inappropriate: the authors use Pearson correlation when Spearman correlation would be more robust to outliers and thus more suitable for methylation and other genomic comparisons.

We appreciate the reasonable concerns regarding cfDNA degradation and agree that the methylation profile is not an adequate metric for degradation. To evaluate for degradation, we will focus on NGS-derived length profiles (WGS data) and constant spike-in DNA. We appreciate the reviewer’s suggestion to use the Spearman correlation, and this will be incorporated.

(4) The CNV analysis also raises concerns. With low-coverage WGS (~5X) from heparin-derived cfDNA, only large CNVs (>100 kb) are reliably detectable. The authors used a 500 kb bin size for CNV calling, but they did not acknowledge this as a limitation. Evaluating CNV detection at multiple bin sizes (e.g., 1 kb, 10 kb, 50 kb, 100 kb, 250 kb) would provide a more complete picture. In addition, Figure 3 presents CNV results from only one sample, which risks bias. Similar bias would exist for illustrations of CNVs from other samples in the supplementary figures provided by the authors. Again, Spearman correlation should be applied in Figure 3c, where clear outliers are visible.

We appreciate the reviewer’s constructive comments regarding the CNV analysis. We agree that the use of low-coverage WGS (~5×) limits the reliable detection of small CNVs, and we will acknowledge this as a limitation in the revised manuscript. To address this point, we will perform additional analyses using 50kb as bin sizes. To reduce potential bias from single-sample representation, we will show the aggregated CNV plots for all CNA-positive cases along with their log₂ copy ratio correlations, and Spearman’s correlation will be applied as suggested.

(5) It is important to point out that depth-based CNV calling is just one of the CNV calling methods. Other CNV calling software using SNVs, pair-reads, split-reads, and coverage depth for calling CNV, such as the software Conserting, would be severely affected by the low-quality WGS data. The authors need to evaluate at least two different software with specific algorithms for CNV calling based on current WGS data.

Thank you for this suggestion. We will evaluate CNV profiles using alternative informatics methods.

(6) The authors omit an important application of cfDNA: somatic mutation detection. Degraded cfDNA and reduced sequencing depth could substantially impact SNV calling accuracy in terms of both recall and precision. Assessing this aspect with their current dataset would provide a more comprehensive evaluation of heparin plasma-derived cfDNA for genomic analyses.

We thank the reviewer for emphasizing SNVs as an important application of cfDNA. We agree that the limited volume of residual plasma is a constraint. Routine chemistry tests leave ~1–2 mL of plasma, and this limited volume places an upper limit on performing SNV analysis. We will expand the discussion of this limitation in the paper. Our approach is not intended to replace specialized tubes for large-volume cfDNA collection but rather to complement them by enabling the use of residual material.

See this for reference: https://filippo.io/linux-syscall-table/

the event to be logged should occur when a system call finishes, rather than when it starts or during its execution

always monitor

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Reply to the reviewers

Reviewer #1

Major comments:

(comment #1)- It is interesting that TRF2 loss not only fails to increase γH2AX/53BP1 levels but may even slightly reduce them (e.g., Fig. S2c and the IF images). While the main hypothesis is that TRF2 loss does not trigger telomere dysfunction in NSCs, this observation raises the possibility that TRF2 itself contributes to DDR signaling (ATM-P, γH2AX, 53BP1) in these cells and that in its absence, cells are not able to form those foci. To exclude the possibility that telomere-specific DDR is being missed due to an overall dampened DDR response in the absence of TRF2, it would be informative to induce exogenous DSBs in TRF2-depleted cells and test DDR competence (e.g., IF for γH2AX/53BP1). In other words, are those NSC lacking TRF2 even able to form H2AX/53BP1 foci when damaged? In addition, it would be interesting to perform telomere fusion analysis in TRF2 silenced cells (and TRF1 silenced cells as a positive control).

We acknowledge a slight reduction; however, this difference is not statistically significant (Fig S2c,e). We will quantify the levels of DDR markers upon TRF2 loss and exogenous DSBs and include it in the subsequent revision.

(comment #2)-A TRF2 ChIP-seq should be performed in NSC as this list of genes (named TAN genes in the text) was determined using a ChIP performed in another cell line (HT1080). For the ChIP-qPCR in the various conditions, primers for negative control regions should be included to show the specific binding of TRF2 to the promoter of the genes associated with neuronal differentiation. For example, an intergenic region and/or promoters of genes that are not associated with neuronal differentiation (or don't contain a potential G4). The same comment goes true for the gene expression analysis: a few genes that are not bound by TRF2 should be included as negative controls to exclude a potential global effect of TRF2 loss on gene expression (ideally a RNA-seq would be performed instead). We have performed NSC-specific TRF2 ChIP-seq for an upcoming manuscript, which confirms TRF2 occupancy at multiple promoters of differentiation-associated genes. These data are provided solely for confidential evaluation by the designated reviewers.

Regarding the ChIP-qPCR control experiments: We thank reviewer for pointing this out, indeed we included controls in our PCR assays as positive (telomeric) and TRF2-nonbinding loci (GAPDH, RPS18, and ACTB, based on HT1080 TRF2 ChIP-seq data) as negative controls. These results were not included earlier for clarity given that we were presenting several ChIP-PCR figures - in response to the comment we have included this now in the revised version (Fig. S3d,e). Gene expression analyses show selective upregulation of the TAN genes upon TRF2 loss (data normalised to GAPDH); whereas negative control genes lacking TRF2 binding (RPS18, ACTB) remain unchanged, ruling out non-specific effects. (Fig S3f,g,j,k).

-(comment #3) A co-IP should be performed between the TRF2 PTM mutant K176R or WT TRF2 and REST and PRC2 components to directly show a defect of interaction between them when TRF2 is mutated (a co-IP with DNase/RNase treatment to exclude nucleic-acid bridging). The TRF2 PTM mutant T188N also seems to lead to an increased differentiation (Fig. S5a). Could the author repeat the measure of gene expression and co-IP with REST upon the overexpression of this mutant too?

We confirm that DNase/RNase is routinely included in our pull-down experiments to exclude nucleic-acid bridging, with detailed methodology now elaborated in the Methods section. Not including this in the manuscript Methods was an oversight from our side. Our data demonstrate that only REST directly interacts with TRF2, while TRF2 engages PRC2 indirectly via REST, as also previously shown by us and others (page 6; ref. [62]; Sharma et al., ref. [15]).

We thank the reviewer for noting the apparent differentiation in Fig. S5a. However, this observation represents rare spontaneous differentiation event and is not statistically significant (as shown in Fig S5b). Consistently, gene expression analysis of the TRF2-T188N mutant shows no significant change in TRF2-associated neuronal differentiation (TAN) genes. Therefore, Co-IP for TRF2-T188N with REST was not done.

(comment #4) - The authors show that the G4 ligands SMH14.6 and Bis-indole carboxamide upregulate TAN genes and promote neuronal differentiation, but the underlying mechanism remains unclear. Bis-indole carboxamide is generally considered a G4 stabilizer, while SMH14.6 is less characterized and should be better introduced. The authors should clarify how G4 stabilization would interfere with TRF2 binding, it seems that it would likely be by blocking access. A more detailed discussion, and ideally TRF2 ChIP after ligand treatment and/or G4 helicase treatment, would strengthen the model.

We clarify that Bis-indole carboxamide acts as a G4 stabilizer, while SMH14.6 is also a noted G4-binding ligand that stabilizes G4s (ref. [15]). The exclusion of TRF2 from G4 motifs in gene promoters by G4-binding ligands has also been documented previously (ref. [18]). In line with these findings, ChIP experiments performed following ligand treatment revealed a decreased occupancy of TRF2 at TAN gene promoters, supporting the proposed mechanism (added Fig. 6h).

Minor comments:

• Supp Figures related to the scRNA-seq are difficult to read (blurry).

Corrected

• Fig S1h: The red box mentioned in the legend is not visible

Corrected

• In the text, the Figures 1 f-g are misannotated as Fig 1m and l

Corrected

• The symbol γ of γH2AX is missing in the text

Corrected

• Fig.3d, please indicate in the legend that it is done in SH-SY5Y.

Added SH-SY5Y in the legend of Fig. 3d.

• Fig. S3b: Please consider replotting this panel with an increased y-axis scale. As currently presented, the TRF2 ChIP-seq peaks at several promoters appear truncated by the scaling.

Corrected

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

1. For most of the data graphs in the manuscript, there is no indication of the number of independent biological replicates carried out (which should ideally be plotted as individual dots overlaying the column graphs), or what the error bars represent, or what statistical test was used. All the figure legends and methods have now been updated with the corresponding biological replicates per experiment, with error bars as SD/SEM and the corresponding statistical test along with p values.

Figure S1.1a: needs a marker to show that the tissue is dentate gyrus.

We acknowledge the reviewers' concern that high-magnification images alone make it difficult to verify whether the fields are taken from the correct anatomical location. The dentate gyrus (DG) of the hippocampus is a well-defined structure. In the revised figure (Fig S1.1a), we now include a low-magnification image showing the entire hippocampus, including the CA fields, along with two high-magnification fields specifically from the DG region. Consistent with our claim, the co-immunostaining demonstrates that Sox2-positive neural stem cells in the DG are also positive for TRF2.

Figure 1c (and all other flow cytometry panels throughout the manuscript): it is not clear if the expression of any of these proteins, except maybe MAP2, are significantly different in the presence or absence of TRF2. These differences need to be presented more quantitatively, with the results compiled from multiple biological replicates and analysed statistically. I am not sure that flow cytometry is the best way to determine differences in protein expression levels for non-surface proteins, because many of the reported differences are not at all convincing.

To detect intracellular/nuclear proteins by flow cytometry, cells were permeabilized using pre-chilled 0.2% Triton X-100 for 10 minutes, as described in the Methods section.

We have revised the figures (Fig 1c,e) and now included statistical analysis from three independent biological replicates for these experiments.(Fig S1.4h-j, S2e, S6d)

Fig 1d: has TRF2 been effectively silenced in this experiment? There appears to be just as many TRF2+ nuclei in the "TRF2 silenced" panel vs the control, including in the cells with neurite outgrowths.

Quantification of nuclear levels of TRF2 showing decrease in nuclear TRF2 has been included in supplementary Fig S1g.

Fig 2a-c: these experiments need a positive control, showing increased expression of these proteins in mNSC and SH-SY5Y cells in response to a DNA damaging agent. Again, flow cytometry may not be the best method for this; immunofluorescence combined with telomere FISH would be more convincing.

We confirm that doxorubicin induces 53BP1 foci (IF-FISH Sup Fig. S2b) and TRF1 silencing elevates γH2AX (Sup Fig. S2c) validating DDR sensitivity. Unlike TRF2 loss (Fig. 2a-c), no TIFs appear with IF and telomere probes (Fig. 2d, Sup Fig. 2a), and without TIFs, there is no telomeric fusion. Flow cytometry was performed with Triton X- 100 to target nuclear protein. These findings adequately address the concern; therefore, further IF-FISH experiments were not included in the present study.

To conclude that telomere damage is not occurring, an independent marker of such damage, such as telomere fusions, should also be measured.

In response to uncapped telomeres, ATM kinase activates the DNA damage response (DDR), recruiting γH2AX and 53BP1 to telomeres, which precedes the end-to-end fusions (Takai et al., 2003; Maciejowski & de Lange, 2015; Takai et al., 2003; d'Adda di Fagagna et al., 2003; Cesare & Reddel, 2010; Hayashi et al., 2012; Sarek et al., 2015). We observe no DDR activation or foci (Fig. 2; Sup. Fig. 2). This absence of a DDR response and TIFs indicates no telomere uncapping, negating the need for direct telomere fusion analysis.

Figure S2b is lacking a no-doxorubicin control.

Untreated control has been included Fig. S2b.

Figures 3a and 3b need a positive control (e.g. TRF2 binding to telomeric DNA) and a negative control (e.g. a promoter that did not show any TRF2 binding in the HT1080 ChiP-seq experiment in Fig S3).

We have included positive (telomere) and negative (GAPDH) controls (based on HT1080 TRF2 ChIP-seq data) for the TRF2 ChIP assay in Supplementary Fig. S3d,e. Additionally, positive and negative controls for all ChIP experiments conducted in this study are presented in Supplementary Figs. S3d, S3e, S3h, S3i, S4c-h, and S5c-e

The data in Figure 3 would be more compelling if all experiments were also performed in fibroblasts to confirm the cell-type specificity of the effect.

Our HT1080 fibrosarcoma ChIP-seq data (ref. [18]; Sup. Fig. 3a,b) show TRF2 binding to TAN gene promoters in a fibroblast-derived model, with enrichment in neurogenesis-related genes (refs. [19,20]). In fibroblasts TRF2 depletion, as expected, induce telomere dysfunction and DDR (Fig. 2d; Sup. Fig. 2a), and eventually cell-cycle arrest and cell death as also reported earlier (van Steensel et al., 1998; Smogorzewska & de Lange, 2002). Therefore, the suggested experiments which would require sustained TRF2-depletion are not possible to perform in fibroblasts. TRF2 occupancy on the promoter of the genes in question in cells other than NSC was noted in HT1080 cells (ref. [18]; Sup. Fig. 3a,b).

No references are provided for the TRF2 posttranslational modifications on R17, K176, K190 and T188. What is the evidence for these modifications, and is it known if they participate in the telomeric role of TRF2?

These lines with references have been included in the manuscript (highlighted in blue).

R17 methylation enhances telomere stability (66). K176/K190 acetylation stabilizes telomeres and is deacetylated by SIRT6 (67). T188 phosphorylation facilitates telomere repair after DSBs(68). These PTMs primarily support telomeric roles.

The experiments in Fig 5 should also be performed with WT TRF2, to confirm that effects are not due to the overexpression of TRF2.

WT TRF2 shows no differentiation phenotype and change in TAN gene expression (Fig. 1f,g; 3h, Sup Fig. 5a). Confirming effects are not due to TRF2 overexpression.

Fig 5c has not been described in the text, and there are multiple technical problems with the TRF2 WT experiment: i) There appears to be significant background binding of REST to the IgG beads, though this blot has such high background it is hard to tell (the REST blot in Fig S4b is also of poor quality), ii) TRF2 is migrating at two different positions in the Input and IP lanes, and the TRF2 band in the K176R blot is at a different position to either, and iii) the relative loading of the Input and IP lanes is not indicated, so it's not clear why K176R appears to be so enriched in the IP.

We acknowledge the oversight in not citing Fig 5c in the manuscript. This has been corrected, and, highlighted in blue in the revised manuscript.

i) Multiple optimization attempts were made for the Co-IP experiments, and the presented figure reflects the best achievable result despite REST blot smearing, a pattern also reported previously (Ref. 65). The TRF2-REST interaction is well established, and a similar background was also observed in the cited study

ii)Variable migration patterns of TRF2 were also noted in the cited study (Ref. 65), consistent with our observations. Our primary emphasis, however, is on the TRF2 K176R mutant, which clearly disrupts its interaction with REST.

iii)The input loading corresponds to 10% of the total lysate. As the experiments were conducted independently, variations in transfection and pull-down efficiencies may account for observed differences.

To rule out indirect effects of the G4 ligands on the results in Fig 6g, the binding of BG4 and TRF2 at the promoters of these genes should be measured by ChIP.

To confirm that G4 ligand effects on TAN gene promoters are direct, TRF2 occupancy was assessed using ChIP. Significantly decreased occupancy of TRF2 was noted at TAN gene promoters, (added Fig. 6h). This implies that ligand-induced changes in TRF2 binding are directly linked to promoter-level G4 stabilization.

Minor comments:

1. The size of all the size markers in western blots should be added to the figures. Size has been included in all the western blots

2. There are several figure panels that are incorrectly referenced in the text, e.g. Fig S1.1 (e-f) should be Fig S1.1 (e-h); Fig. 1m should be Fig. 1f; Figs 5e and 5f have been swapped.

Corrected.

1. Fig S1.4 is not referred to in the text. It is not clear what the purpose of Fig S1.4a is.

The following line has been included in the manuscript highlighted in blue.

Neurospheres were characterized using PAX6, a NSC marker (Fig S1.4a).

Are the experiments in Figs 3e, 4a, 4c and 4e using 4-OHT treatment, or siRNA? If the latter, I don't think a control for the effectiveness of the knockdown in this cell type has been included anywhere in the manuscript.

It is using siRNA, a western blot showing the effectiveness of knockdown is presented in supplementary figure S4c (now S4a).

The lanes of the western blots in Fig S4c are not labelled.

Corrected.

1. Given that the experiments in Fig 5 were carried out on a background of endogenous WT TRF2 expression, presumably the K176R mutant is having a dominant negative effect. To understand the mechanism of this effect (e.g, is it simply due to replacement of endogenous WT TRF2 at its genomic binding sites by a large excess of exogenous K176R, or is dimerisation with WT TRF2 needed?) it would be helpful to know the relative expression levels of endogenous and K176R TRF2.

To address the query, qRT-PCR with 3′ UTR-specific primers showed no change in endogenous TRF2 mRNA upon K176R expression in SH-SY5Y cells, while primers detecting total TRF2 revealed ~10-fold higher expression of K176R compared to control (Figure below). This indicates the absence of suppression of endogenous TRF2 mRNA. Given that the mutant's DNA binding is intact (Fig. 5f), the dominant-negative effect of K176R likely arises from overexpression of the exogenous mutant.

For the sentence "...and critical for transcription factor binding including epigenetic functions that are G4 dependent" (bottom of page 3 of the PDF), the authors cite only their own prior papers, but there are examples from others that could be cited.

We have incorporated citations from other research groups, now included as references 23-26.

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Referee #2

Evidence, reproducibility and clarity

This manuscript examines the effects of depletion of the telomeric protein TRF2 in mouse neural stem cells, using mice carrying a floxed allele of TRF2 and inducible Cre recombinase under the control of the stem cell-specific Nestin promoter. The results are also backed up in a human neuroblastoma cell line that has progenitor-like properties. There is no apparent induction of telomere damage in either of these cell types, but there is an increase in expression of neurogenesis genes. This is accompanied by an increase in binding of TRF2 to the relevant promoters, and evidence is provided that this binding involves G-quadruplexes in the promoters.

On the whole, these core findings of this study are interesting, and reasonably robust. However, the study as a whole is marred by a large number of technical issues and missing controls which should be addressed prior to publication:

1. For most of the data graphs in the manuscript, there is no indication of the number of independent biological replicates carried out (which should ideally be plotted as individual dots overlaying the column graphs), or what the error bars represent, or what statistical test was used.
2. Figure S1.1a: needs a marker to show that the tissue is dentate gyrus.
3. Figure 1c (and all other flow cytometry panels throughout the manuscript): it is not clear if the expression of any of these proteins, except maybe MAP2, are significantly different in the presence or absence of TRF2. These differences need to be presented more quantitatively, with the results compiled from multiple biological replicates and analysed statistically. I am not sure that flow cytometry is the best way to determine differences in protein expression levels for non-surface proteins, because many of the reported differences are not at all convincing.
4. Fig 1d: has TRF2 been effectively silenced in this experiment? There appears to be just as many TRF2+ nuclei in the "TRF2 silenced" panel vs the control, including in the cells with neurite outgrowths.
5. Fig 2a-c: these experiments need a positive control, showing increased expression of these proteins in mNSC and SH-SY5Y cells in response to a DNA damaging agent. Again, flow cytometry may not be the best method for this; immunofluorescence combined with telomere FISH would be more convincing.
6. To conclude that telomere damage is not occurring, an independent marker of such damage, such as telomere fusions, should also be measured.
7. Figure S2b is lacking a no-doxorubicin control.
8. Figures 3a and 3b need a positive control (e.g. TRF2 binding to telomeric DNA) and a negative control (e.g. a promoter that did not show any TRF2 binding in the HT1080 ChiP-seq experiment in Fig S3).
9. The data in Figure 3 would be more compelling if all experiments were also performed in fibroblasts to confirm the cell-type specificity of the effect.
10. No references are provided for the TRF2 postranslational modifications on R17, K176, K190 and T188. What is the evidence for these modifications, and is it known if they participate in the telomeric role of TRF2?
11. The experiments in Fig 5 should also be performed with WT TRF2, to confirm that effects are not due to the overexpression of TRF2.
12. Fig 5c has not been described in the text, and there are multiple technical problems with the TRF2 WT experiment: i) There appears to be significant background binding of REST to the IgG beads, though this blot has such high background it is hard to tell (the REST blot in Fig S4b is also of poor quality), ii) TRF2 is migrating at two different positions in the Input and IP lanes, and the TRF2 band in the K176R blot is at a different position to either, and iii) the relative loading of the Input and IP lanes is not indicated, so it's not clear why K176R appears to be so enriched in the IP.
13. To rule out indirect effects of the G4 ligands on the results in Fig 6g, the binding of BG4 and TRF2 at the promoters of these genes should be measured by ChIP.

Minor comments:

1. The size of all the size markers in western blots should be added to the figures.
2. There are several figure panels that are incorrectly referenced in the text, e.g. Fig S1.1 (e-f) should be Fig S1.1 (e-h); Fig. 1m should be Fig. 1f; Figs 5e and 5f have been swapped.
3. Fig S1.4 is not referred to in the text. It is not clear what the purpose of Fig S1.4a is.
4. Are the experiments in Figs 3e, 4a, 4c and 4e using 4-OHT treatment, or siRNA? If the latter, I don't think a control for the effectiveness of the knockdown in this cell type has been included anywhere in the manuscript.
5. The lanes of the western blots in Fig S4c are not labelled.
6. Given that the experiments in Fig 5 were carried out on a background of endogenous WT TRF2 expression, presumably the K176R mutant is having a dominant negative effect. To understand the mechanism of this effect (e.g is it simply due to replacement of endogenous WT TRF2 at its genomic binding sites by a large excess of exogenous K176R, or is dimerisation with WT TRF2 needed?) it would be helpful to know the relative expression levels of endogenous and K176R TRF2.
7. For the sentence "...and critical for transcription factor binding including epigenetic functions that are G4 dependent" (bottom of page 3 of the PDF), the authors cite only their own prior papers, but there are examples from others that could be cited.

Significance

The protein TRF2 was first identified as one of the core proteins that bind to the double-stranded region of telomeric DNA, and its many-faceted role in telomere protection has been well studied over the last 3 decades. More recent data from several labs indicate that TRF2 has additional roles outside the telomere, including in regulating gene expression, but these roles are so far much less characterised. Also, it has recently been shown that mouse ES cells, unexpectedly, do not require TRF2 for telomere protection (references 3 and 4 in this paper).

The findings of the current findings expand the type of stem cells in which TRF2 is likely to be playing more of a role elsewhere in the genome, and not at telomeres, and hence is likely to be of high interest to both researchers of telomere biology, and those interested in the regulation of stem cell biology and neurogenesis.

The strengths of the study are its novelty, its use of an inducible system to knock out TRF2 in the mouse neural stem cells of interest, and a thorough analysis of changes in gene expression and promoter occupancy across a range of genes of relevance to neurogenesis. The major weakness of the study, as descibed above, is the large number of technical problems, missing controls and missing indications of biological reproducibility.

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Referee #1

Evidence, reproducibility and clarity

In this study, the authors show that TRF2 binds non-telomeric G-quadruplexes in promoters of a set of genes ("TAN" genes for TRF2-associated neuronal differentiation) and recruits REST/chromatin remodelers to repress those genes in neural stem cells, thereby maintaining the NSC state in a telomere-independent manner. They show that the loss of TRF2 derepresses TAN genes and promotes neuronal differentiation.

However, key experiments are missing to fully support the claims: a genome-wide TRF2 ChIP-seq in NSC to validate binding beyond a restricted set of TAN genes, more robust evidence confirming the absence of telomeric dysfunction, and mechanistic clarification of the effects of G4 ligands on TRF2 binding.

Major comments:

• It is interesting that TRF2 loss not only fails to increase γH2AX/53BP1 levels but may even slightly reduce them (e.g., Fig. S2c and the IF images). While the main hypothesis is that TRF2 loss does not trigger telomere dysfunction in NSCs, this observation raises the possibility that TRF2 itself contributes to DDR signaling (ATM-P, γH2AX, 53BP1) in these cells and that in its absence, cells are not able to form those foci. To exclude the possibility that telomere-specific DDR is being missed due to an overall dampened DDR response in the absence of TRF2, it would be informative to induce exogenous DSBs in TRF2-depleted cells and test DDR competence (e.g., IF for γH2AX/53BP1). In other words, are those NSC lacking TRF2 even able to form H2AX/53BP1 foci when damaged? In addition, it would be interesting to perform telomere fusion analysis in TRF2 silenced cells (and TRF1 silenced cells as a positive control).
• A TRF2 ChIP-seq should be performed in NSC as this list of genes (named TAN genes in the text) was determined using a ChIP performed in another cell line (HT1080). For the ChIP-qPCR in the various conditions, primers for negative control regions should be included to show the specific binding of TRF2 to the promoter of the genes associated with neuronal differentiation. For example, an intergenic region and/or promoters of genes that are not associated with neuronal differentiation (or don't contain a potential G4). The same comment goes true for the gene expression analysis: a few genes that are not bound by TRF2 should be included as negative controls to exclude a potential global effect of TRF2 loss on gene expression (ideally a RNA-seq would be performed instead).
• A co-IP should be performed between the TRF2 PTM mutant K176R or WT TRF2 and REST and PRC2 components to directly show a defect of interaction between them when TRF2 is mutated (a co-IP with DNase/RNase treatment to exclude nucleic-acid bridging). The TRF2 PTM mutant T188N also seems to lead to an increased differentiation (Fig. S5a). Could the author repeat the measure of gene expression and co-IP with REST upon the overexpression of this mutant too?
• The authors show that the G4 ligands SMH14.6 and Bis-indole carboxamide upregulate TAN genes and promote neuronal differentiation, but the underlying mechanism remains unclear. Bis-indole carboxamide is generally considered a G4 stabilizer, while SMH14.6 is less characterized and should be better introduced. The authors should clarify how G4 stabilization would interfere with TRF2 binding, it seems that it would likely be by blocking access. A more detailed discussion, and ideally TRF2 ChIP after ligand treatment and/or G4 helicase treatment, would strengthen the model.

Minor comments:

• Supp Figures related to the scRNA-seq are difficult to read (blurry).
• Fig S1h: The red box mentioned in the legend is not visible
• In the text, the Figures 1 f-g are misannotated as Fig 1m and l
• The symbol  of H2AX is missing in the text
• Fig.3d, please indicate in the legend that it is done in SH-SY5Y.
• Fig. S3b: Please consider replotting this panel with an increased y-axis scale. As currently presented, the TRF2 ChIP-seq peaks at several promoters appear truncated by the scaling.
• Fig S4b: the legends should be fixed, the figure shows TRF2 occupancy upon REST silencing and not the other way around.

Significance

Non-telomeric roles of TRF2 have been reported before: in repressing neuronal genes and promoting a stem-like state by stabilizing REST (PMID: 18818083), in promoter G4 binding and recruitment of chromatin repressors (previous studies from the same lab), and TRF2 was shown to be dispensable for telomere protection in pluripotent stem cells (ES). The novelty of the current study lies primarily in extending/combining these mechanisms to NSCs.

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eLife Assessment

The characterization of a dissociable Mediator subunit implicated in cellular pathways, particularly lung alveolar function and HIV latency, would be conceptually interesting. The authors have preliminary evidence for a stable Med16 subcomplex that may regulate specific genes. This work is useful in that it points to interactions between Med16 and UBP1, but the evidence is preliminary and incomplete.

Reviewer #1 (Public Review):

Summary:

Characterization of a dissociable Mediator subunit implicated in cellular pathways, particularly lung alveolar function, and HIV latency is conceptually interesting.

Strengths:

The strengths of this study are:

(1) Demonstration of MED16 dissociation from the core Mediator complex and formation of a subcomplex containing MED16, upstream-binding protein 1 (UBP1), and transcription factor cellular promoter 2 (TFCP2) by elegant biochemical fractionation and immunoblotting analysis.

(2) Defining nine N-terminal WD-40 repeats (WDRs) of MED16 as a Mediator-incorporating module and the C-terminal ⍺β-domain (157 amino acids) important for interaction with the UBP1-TFCP2 heterodimeric complex.

(3) Illustration of a weak hydrophobic interaction between MED16 and the Mediator core that could be disrupted by 1,6-hexanediol, but not by its 2,5-hexanediol isomer nor by high salt (500 mM NaCl) disruption.

(4) Classification of UBP1-upregulated cellular genes typically containing binding sites flanking the transcription start site (TSS) in contrast to UBP1-downregulated genes often containing a TSS-overlapping UBP1-binding site

(5) Presenting evidence for Mediator complex-dissociated free MED16-repressed HIV promoter activity through functional association with UBP1 and showing bromodomain-containing protein 4 (BRD4) inhibitor JQ1 that potentially disrupts BRD4-inhibited HIV-1 transcription elongation could lead to reversal of HIV-1 latency.

Weaknesses:

Nevertheless, foreseeable weaknesses include:

(1) No clear demonstration of MED16-UBP1-TFCP2 indeed forming a trimeric core subcomplex in regulating cellular gene transcription and HIV-1 promoter inhibition

(2) No validation of transcriptomic datasets and pathways identified.

(3) Use of mostly artificial reporter gene constructs and non-HIV host cells (e.g., human 293T embryonic kidney cells, human HeLa cervical cancer cells, and mouse HT pancreatic cancer cells) for examining MED16/UBP1-regulated HIV transcription.

(4) Inconsistent use of 293T and HeLa cells in the characterization of dissociated MED16 interaction with UBP1 and TFCP2.

(5) In vitro transcription using immobilized DNA templates was not performed to a high standard, thus failing to convincingly show MED16/UBP1-inhibited HIV-1 transcription preinitiation complex formation.

Reviewer #2 (Public Review):

Summary:

The article from Zheng et al. proposes an interesting hypothesis that the Med16 subunit of Mediator detaches from the complex, associates with transcription factor UBP1, and this complex activates or represses specific sets of genes in human cells. Despite my excitement upon reading the abstract, I was concerned by the lack of rigor in the experimental design. The only statement in the abstract that has some experimental support is the finding that Med16 dissociates from the Mediator and forms a subcomplex, but the data shown remain incomplete.

Strengths:

The authors have preliminary evidence that a stable Med16 complex may exist and that it may regulate specific sets of genes.

Weaknesses:

The experiments are poorly designed and can only infer possible roles for Med16 or UBP1 at this point. Furthermore, the data are often of poor quality and lack replication and quantitation. In other cases, key data such as MS results aren't even shown. Instead, we are given a curated list of only about 6 proteins (Figure S1), a subset of which the authors chose to pursue with follow-up experiments. This is not the expected level of scientific process.

(1) The data supporting the Med16 dissociation and co-association with UBP1 are incomplete and not convincing at this stage. According to the Methods and text, the gel filtration column was run with "un-dialyzed HeLa cell nuclear extract" and eluted in 300mM KCl buffer. The extracts were generated with the Dignam/Roeder method according to the text. Undialyzed, that means the extract would be between 0.4 - 0.5M NaCl. Under these high salt conditions (not physiological), it's possible and even plausible that Mediator subunits could separate over time. This caveat is not mentioned or controlled for by the authors. Because a putative Med16 subcomplex is a foundational point of the article, this is concerning.

The data are incomplete because a potential Med16 complex is not defined biochemically. The current state suggests a smaller Med16-containing complex that may also contain UBP1 and other factors, but its composition is not determined. This is important because if you're going to conclude a new and biologically relevant Med16 complex, which is a point of the article, then readers will expect you to do that.

Equally concerning are the IP-western results shown in Figure 1. In my opinion, these experiments do nothing to support the claims of the authors. The authors use hexanediols at 5% or 10% in an effort to disrupt the Mediator complex. Assuming this was weight/volume, that means ~400 to 800mM hexanediol solution, which is fairly high and can be expected to disrupt protein complexes, but the effects haven't been carefully assessed as far as I'm aware. The 2,5 HD (Figure 1B) experiments appear to simply contain greater protein loading, and this may contribute to the apparent differential results. In fact, in looking at the data, it seems that all MED subunits probed show the same trend as Med16. They are all reduced in the 1,6HD experiment relative to the 2,5 HD experiment. But it's hard to know, because replicates weren't completed and quantitation was not done. There aren't even loading controls. Other concerns about the IP-Western experiments are outlined in point 2.

(2) At no point do the authors apply rigorous methods to test their hypothesis. Instead, methods are applied that have been largely discredited over time and can only serve as preliminary data for pilot studies, and cannot be used to draw definitive conclusions about protein function.

a) IP-westerns are fraught with caveats, especially the way they were performed here, in which the beads were washed at relatively low salt and then eluted by boiling the beads in loading buffer. This will "elute" bound proteins, but also proteins that non-specifically interact with or precipitate on the beads. And because Westerns are so sensitive, it is easy to generate positive results. It's just not a rigorous experiment.

b) Many conclusions relied on transient transfection experiments, which are problematic because they require long timeframes, during which secondary/indirect effects from expression/overexpression will result. This is especially true if the proteins being artificially expressed/overexpressed are major transcription regulators, which is the case here. It is simply impossible to separate direct from indirect effects with these types of experiments. Another concern is that there was no effort to assess whether the induced protein levels were near physiological levels. Protein overexpression, especially if the protein is a known regulator of pol2 transcription (e.g., UBP1 or Med16), will create many unintended consequences.

c) Many conclusions were made based upon shRNA knockdown experiments, which are problematic because they require long timeframes (see above point), which makes it nearly impossible to identify effects that are direct vs. indirect/secondary/tertiary effects. Also, shRNA experiments will have off-target effects, which have been widely reported for well over a decade. An advantage of shRNA knockdowns is that they prevent genetic adaptation (a caveat with KO cell lines). A minimal test would be to show phenotypic rescue of the knockdown by expressing a knockdown-resistant Med16 (for example), but these types of experiments were not done.

d) Many experiments used reporter assays, which involved artificial, non-native promoters. Reporters are good for pilot studies, but they aren't a rigorous test of direct regulatory roles for Med16 or other proteins. Reporters don't even measure transcription directly. In fact, no experiment in this study directly measures transcription. An RNA-seq experiment was done with overexpressed or Med16 knockdown cells, but these required long timeframes and RNA-seq measures steady-state mRNA, which doesn't test the potential direct effects of these proteins on nascent transcription.

e) The MS experiments show promise, but the data were not shown, so it's hard to judge. The reader cannot compare/contrast the experiments, and we have no indication of the statistical confidence of the proteins identified. How many biological replicate MS experiments were performed?

(3) The data are over-interpreted, and alternative (and more plausible) hypotheses are ignored. Many examples of this, some of which are alluded to in the points above. For example, Med16 loss or overexpression will cause compensatory responses in cells. An expected result is that Mediator composition will be disrupted, since Med16 directly interacts with several other subunits. Also in yeast, the Robert, Gross, and Morse labs showed that loss of Med16/Sin4 causes loss of other tail module subunits, and this would be expected to cause major changes in the transcriptome. The authors also mention that yeast Med16/Sin4 "alters chromatin accessibility globally" and this would be expected to cause major changes in the transcriptome, leading to unintended consequences that will make data analysis and identification of direct Med16 effects impossible. The unintended consequences will be magnified with prolonged disruption of MED16 levels in cells (e.g., longer than 4h). These unintended consequences are hard to predict or define, and are likely to be widespread given the pivotal role of Mediator in gene expression. One unintended consequence appears to be loss of pol2 upon Med16 over-expression, as suggested by the western blot in Figure 8B. I point this out as just one example of the caveats/pitfalls associated with long-term knockdowns or over-expression.

Reviewer #3 (Public Review):

Summary:

There are two major flaws that fundamentally undermine the value of the study. First, nearly all the central conclusions drawn here rely on the unfounded assumption that the effects observed are direct. No rigorous cause-and-effect relationships are established to support the claims. Second, the quality of the experimental data is substandard. Collectively, these concerns significantly limit any advances that might be gained in our understanding of the UBP1 pathway or Mediator function.

Weaknesses:

(1) The decrease in 1,6-hexanediol-treated cells of MED16 is modest, variable, not quantified, and internally inconsistent. For example, in Figure 1A, 1,6-hexanediol treatment should not have an impact on the level of the protein being directly IP. For MED12 (and CDK8 and MED1 to a lesser extent), 1,6-hexanediol treatment alters the level of the target protein in the IP. Along these lines, Figure 1A shows a no 1,6H-D dependent decrease in MED1 or MED12 levels in the CDK8 IP, whereas Figure 1B does show a decrease. Figure 1A shows no 1,6H-D dependent decrease in CDK8 levels in the MED1 IP, whereas Figure 1B shows a dramatic decrease. MED24 levels in the MED12 IP increase upon 1,6H-D in Figure 1A, but decrease in Figure 1B. Internal inconsistencies of this nature persist in the other Figures.

(2) Undermining the value of Figure 1E/F, UBP1 and TFCP2 may also associate with the small amount of MED16 in the 2MDa fractions. This is not tested, and therefore, the conclusion that they just associate with the dissociable form of MED16 is not supported.

(3) Domain mapping studies in Figure 2 are overinterpreted. Since the interactions could be indirect, it is not accurate to conclude "Therefore, the N-terminal WDR domain of MED16 is crucial for its integration into the Mediator complex, while the C-terminal αβ-domain is essential for interacting with UBP1-TFCP2. "

(4) A close examination of Figure 2C undermines confidence in the association studies. The bait protein in lanes 5-8 should be equal. Also, there is significant binding of GST to UBP1 and TFCP2, in roughly the same patterns as they bind to GST-MED16 αβ. The absence of input samples makes the results even more difficult to interpret.

(5) The domain deletion mutants are utilized throughout the manuscript as evidence of the importance of the UBP1-MED16 interaction. However, in Figure 2F lanes 7 and 8, the delta-S mutant binds MED16 as well as full-length UBP1. This undermines much of the subsequent data and conclusions about specificity.

(6) Even if the delta-S mutant were defective for MED16 binding, the result in Figure 3B does not "confirm that MED16 is required for the transcriptional activity of UBP1,". Removal of that domain may have other effects.

(7) As Mediator is critical for the activation of many genes, it is not accurate to assume that the impact of its deletion in Figure 3E/F demonstrates a direct requirement in UBP1-driven transcription. This could easily be an indirect effect.

(8) Without documenting the relative protein expression levels in Figure 3G/H, conclusions cannot be drawn about the titration experiments, nor the co-expression experiments. These findings are likely the result of squelching or some form of competition that is not directly related to the UBP1-mediated transcription. A great deal of validation would be required in order to support the model that these effects are a result of MED16 overexpression sequestering UBP1 away from holo-Mediator.

(9) The lack of any documentation of expression levels for the various ectopic proteins in the majority of Figures, renders mechanistic claims meaningless (Figures 3, 4, 5, 6, 7, S2, S3). This is particularly relevant since the model presented for many of the results invokes concentration-dependent competition.

eLife Assessment

This study offers a valuable methodological advance by introducing a gene panel selection approach that captures combinatorial specificity to define cell identity. The findings address key limitations of current single-gene marker methods. The evidence is compelling, but would be strengthened by further validation of rare cell states and unexpected marker categories.

Joint Public Review:

In this study, the authors introduce CellCover, a gene panel selection algorithm that leverages a minimal covering approach to identify compact sets of genes with high combinatorial specificity for defining cell identities and states. This framework addresses a key limitation in existing marker selection strategies, which often emphasize individually strong markers while neglecting the informative power of gene combinations. The authors demonstrate the utility of CellCover through benchmarking analyses and biological applications, particularly in uncovering previously unresolved cell states and lineage transitions during neocorticogenesis.

The major strengths of the work include the conceptual shift toward combinatorial marker selection, a clear mathematical formulation of the minimal covering strategy, and biologically relevant applications that underscore the method's power to resolve subtle cell-type differences. The authors' analysis of the Telley et al. dataset highlights intriguing cases of ribosomal, mitochondrial, and tRNA gene usage in specific cortical cell types, suggesting previously underappreciated molecular signatures in neurodevelopment. Additionally, the observation that outer radial glia markers emerge prior to gliogenic progenitors in primates offers novel insights into the temporal dynamics of cortical lineage specification.

However, several aspects of the study would benefit from further elaboration. First, the interpretability of gene panels containing individually lowly expressed genes but high combinatorial specificity could be improved by providing clearer guidelines or illustrative examples. Second, the utility of CellCover in identifying rare or transient cell states should be more thoroughly quantified, especially under noisy conditions typical of single-cell datasets. Third, while the findings on unexpected gene categories are provocative, they require further validation - either through independent transcriptomic datasets or orthogonal methods such as immunostaining or single-molecule FISH-to confirm their cell-type-specific expression patterns.

Specifically, the manuscript would benefit from further clarification and additional validation in the following areas:

• A more in-depth explanation of marker panel applications is needed. Specifically, how should users interpret gene panels where individual genes show only moderate or low expression levels, but the combination provides high specificity? Providing a concrete example, along with guidelines for interpreting such combinatorial signatures, would enhance the practical utility of the method.

• Further quantification of CellCover's sensitivity in detecting rare cell subtypes or states would strengthen the evaluation of its performance. Additionally, it would be helpful to assess how CellCover performs under noisy conditions, such as low cell numbers or read depths, which are common challenges in scRNA-seq datasets.

• It is intriguing and novel that CellCover analysis of the dataset from Telley et al. suggests cell-type-specific expression of ribosomal, mitochondrial, or tRNA genes. These findings would be significantly strengthened by additional validation. For example, the reported radial glia-specific expression of Rps18-ps3 and Rps10-ps1, as well as the postmitotic neuron-specific expression of mt-Tv and mt-Nd4l, should be corroborated using independent scRNA-seq or spatial transcriptomic datasets of the developing neocortex. Alternatively, these expression patterns could be directly examined through immunostaining or single-molecule FISH analysis.

• The observation that outer radial glia (oRG) markers are expressed in neural progenitors before the emergence of gliogenic progenitors in primates and humans is compelling. This could be further supported by examining the temporal and spatial expression patterns of early oRG-specific markers versus gliogenic progenitor markers in recent human spatial transcriptomic datasets - such as the one published by Xuyu et al. (PMID: 40369074) or Wang et al. (PMID: 39779846).

Summary:

Overall, this work provides a conceptually innovative and practically useful method for cell type classification that will be valuable to the single-cell and developmental biology communities. Its impact will likely grow as more researchers seek scalable, interpretable, and biologically informed gene panels for multimodal assays, diagnostics, and perturbation studies.