While British women were perhaps the first to be evacuated with their children to the countryside, Stephenson (date, p.218) notes how evacuation was far more prominent within Germany from December 1942, with over 10 million German women and children evacuated by the end of the war, compared to Britains 4 million. As such, we could argue some difference in experience.

Good quote if i wanted to talk about the experience of a lack of men?

Stephenson notes 5 features shared amoung women in germany and britain * conscription meant the absence of male family members * presence of native and allied soliders, POWs and in germany foreign civilian workers * bombing of civilians needing large-scale relief work and evacuation * total economic warfare meant shortages, rationing and a black market * men conscription meant the mobilization of women in vicilian employment in work with the armed forces and voluntary work

impact varied

Implied to have been far less involved in the war effort, German women, Stephenson (date, p.207) notes that German women

Different experience

With men at war, the homefront was disproportionatly made up of 'women, children and older men' (Stephenson, date, p.209)

I always say every good leader wear different hats. Everyone grew up in different ways and not everyone will see your leadership as leadership. Its vital as leaders to look at those around you and see life through their eyes. It is also vital for leaders to look at themselves at times to grow as a leader. Leaders should always be looking at growth because sometimes who you lead is always changing.

How can the word authority make some people feel like they cannot be a leader?

Why is it easier for us to trust our rationalization of others' situations than their own thoughts about their identities and experiences? Why do we tend to judge and separate ourselves from those who have different life experiences than us instead of appreciating a diversity approach that allows us to challenge ourselves alongside those who are different than us?

These are "common-sensims" I often see faced with conflicting sides. One conflict I repeatedly see is "Won't prioritizing diversity take away from prioritizing the best available?" This is especially present in talks of employment. I believe prioritizing diversity means no bias is present when making an evaluation, broaden where you are looking for options, and don't overlook qualified options because they do not fit a mold. Diversity means having "various intersectional identities in a given space." This is important because we can receive ideas, thought processes, and perspectives from minds that have experienced many different practices, cultures, and experiences instead of creating products that come from similar minds, meaning a more restricted and less challenging process.

Going through the differences between diversity, equity, and inclusion made me realize why representation alone ininstitutions is often seen as insufficient. I have seen many organizations focus solely on the physical presence of people (the "who") without asking whether these people actually experience power, safety, or influence once they are there. After further thought, this led me to consider that systems can differ radically on the surface while still preserving the same old hierarchies. The framing questions in the text, especially those revolving around who is given the right to the decision, making the table, and whose ways of being are appreciated, serve to reveal that inclusion is not just about the count; it is about the radical change of structures. This is tightly linked to the fact that leadership is very often presented as being neutral or objective, whereas in truth it reflects the values of the dominant culture. The focus on cultural humility and accountability shifted leadership from a possession or personal attribute to an engagement or doing. Instead of assuming that what is fair is already there, leaders must be ready to interrogate policies, practices, and norms that give advantages to some groups rather than others. Such a stance aligns with justice-oriented and systems-based approaches that emphasize the well-being of the community as a whole and simultaneously address the root causes of inequality. This section really made me think about how my own experiences as a young woman influence the way I navigate different spaces. I have had moments when I was expected to change myself to fit existing norms to be accepted, rather than places changing to accommodate new perspectives or different ways of being. Learning about equity, inclusion, and cultural humility gave me the words to describe why those moments felt likea threat or a limitation to me. This chapter reminded me that leadership is not just a matter of the right intention, but also of being attentive to those who arepressured to conform and those who feel comfortable being themselves.

Counterintuitive solidarity involves people in powerful positions trusting the experiences of oppressed people over their own gut feelings. However, what does this mean inreal leadership contexts, particularly when it conflicts with a leader's feeling of control or authority? How can leaders genuinely do this and not just superficially listen?

Separating diversity, equity, and inclusion helped me to see that it is very common for institutions to think only about who is there without considering power or participation. What is your opinion about organizations' preference for putting diversity ahead of equity or inclusion when equity and inclusion entail significant structural changes?

This thought made me reflect on the fact that common sense is usually assumed to be neutral, while it is actually influenced by culture, power, and socialization. How can leaders tell that a common-sense thing is actually continuing dominant norms instead of being fair or inclusive? What kind of accountability do leaders have to the act of questioning the norms that are natural to them but may be harmful to others?

Be careful. This is true for vectors

$$\vec{H}-\vec{P}=\left(-\vec{P}\right)+\vec{H}=\vec{H}+\left(-\vec{P}\right)$$

but not exactly the same for numbers: $$7-2.2\ne2.2-7$$

eLife Assessment

This useful study by Palo et al proposes that FRG1 functions as a negative regulator of Nonsense-Mediated mRNA decay (NMD) by associating with the exon junction complex (EJC) and destabilizing UPF1 independently of DUX4. The authors present solid evidence to dissect the relationship between FRG1 and DUX4 in NMD. However, the evidence to support the claim that FRG1 is a component of the EJC or the NMD machinery is incomplete.

Reviewer #1 (Public review):

Summary:

In this manuscript, Dixit and colleagues investigate the role of FRG1 in modulating nonsense-mediated mRNA decay using human cell lines and zebrafish embryos. They present data from experiments that test the effect of normal, reduced or elevated levels of FRG1 on NMD of a luciferase-based NMD reporter and on endogenous mRNA substrates of NMD. They also carry out experiments to investigate FRG1's influence on UPF1 mRNA and protein levels, with a particular focus on the possibility that FRG1 regulates UPF1 protein levels through ubiquitin-mediated proteolysis of UPF1. The experiments described also test whether DUX4's effect on UPF1 protein levels and NMD could be mediated through FRG1. Finally, the authors also present experiments that test for physical interaction between UPF1, the spliceosome and components of the exon junction complex.

Strengths:

A key strength of the work is its focus on an intriguing model of NMD regulation by FRG1, which is of particular interest as FRG1 is positively regulated by DUX4, which has been previously implicated in subjecting UPF1 to proteosome-mediated degradation and thereby causing NMD inhibition. The data that shows that DUX4-mediated effect on UPF1 levels is diminished upon FRG1 depletion suggests that DUX4's regulation of NMD could be mediated by FRG1.

Weaknesses:

A major weakness and concern is that many of the key conclusions drawn by the authors are not supported by the data, and there are also some significant concerns with experimental design. More specific comments below describe these issues:

(1) Multiple issues lower the confidence in the experiments testing the effect of FRG1 on NMD.

(a) All reporter assays presented in the manuscript are based on quantification of luciferase activity, and in most cases, the effect on luciferase activity is quite small. This assay is the key experimental approach throughout the manuscript. However, no evidence is provided that the effect captured by this assay is due to enhanced degradation of the mRNA encoding the luciferase reporter, which is what is implied in the interpretation of these experiments. Crucially, there is also no control for the reporter that can account for the effects of experimental manipulations on transcriptional versus post-transcriptional effects. A control reporter lacking a 3'UTR intron is described in Barid et al, where the authors got their NMD reporter from. Due to small effects observed on luciferase activity upon FRG1 depletion, it is necessary to not only measure NMD reporter mRNA steady state levels, but it will be equally important to ascertain that the effect of FRG1 on NMD is at the level of mRNA decay and not altered transcription of NMD substrates. This can be accomplished by testing decay rates of the beta-globin reporter mRNA.

(b) It is unusual to use luciferase enzymatic activity as a measurement of RNA decay status. Such an approach can at least be justified if the authors can test how many-fold the luciferase activity changes when NMD is inhibited using a chemical inhibitor (e.g., SMG1 inhibitor) or knockdown of a core NMD factor.

(c) The concern about the direct effect of FRG1 on NMD is further amplified by the small effects of FRG1 knockout on steady-state levels of endogenous NMD targets (Figure 1A and B: ~20% reduction in reporter mRNA in MCF7 cells; Figure 1M, only 18 endogenous NMD targets shared between FRG1_KO and FRG1_KD).

(d) The question about transcriptional versus post-transcriptional effects is also important in light of the authors' previous work that FRG1 can act as a transcriptional regulator.

(2) In the experiments probing the relationship between DUX4 and FRG1 in NMD regulation, there are some inconsistencies that need to be resolved.

(a) Figure 3 shows that the inhibition of NMD reporter activity caused by DUX4 induction is reversed by FRG1 knockdown. Although levels of FRG1 and UPF1 in DUX4 uninduced and DUX4 induced + FRG1 knockdown conditions are similar (Figure 5A), why is the reporter activity in DUX4 induced + FRG1 knockdown cells much lower than DUX4 uninduced cells in Figure 3?

(b) In Figure 3, it is important to know the effect of FRG1 knockdown in DUX4 uninduced conditions.

(c) On line 401, the authors claim that MG132 treatment leads to "time-dependent increase in UPF1 protein levels" in Figure 5C. However, upon proteasome inhibition, UPF1 levels significantly increase only at 8h time point, while the change at 12 and 24 hours is not significantly different from the control.

(3) There are multiple issues with experiments investigating ubiquitination of UPF1:

(a) Ubiquitin blots in Figure 6 are very difficult to interpret. There is no information provided either in the text or figure legends as to which bands in the blots are being compared, or about what the sizes of these bands are, as compared to UPF1. Also, the signal for Ub in most IP samples looks very similar to or even lower than the input.

(b) Western blot images in Figure 6D appear to be adjusted for brightness/contrast to reduce background, but are done in such a way that pixel intensities are not linearly altered. This image appears to be the most affected, although some others have also similar patterns (e.g., Figure 5C).

(4) The experiments probing physical interactions of FRG1 with UPF1, spliceosome and EJC proteins need to consider the following points:

(a) There is no information provided in the results or methods section on whether immunoprecipitations were carried out in the absence or presence of RNases. Each RNA can be bound by a plethora of proteins that may not be functionally engaged with each other. Without RNase treatment, even such interactions will lead to co-immunoprecipitation. Thus, experiments in Figure 6 and Figure 7A-D should be repeated with and without RNase treatment.

(b) Also, the authors claim that FRG1 is a "structural component" of EJC and NMD complexes seems to be an overinterpretation. As noted in the previous comment, these interactions could be mediated by a connecting RNA molecule.

(c) A negative control (non-precipitating protein) is missing in Figure 7 co-IP experiments.

(d) Polysome analysis is missing important controls. FRG1 and EIF4A3 co-sedimentation with polysomes could simply be due to their association with another large complex (e.g., spliceosome), which will also co-sediment in these gradients. This possibility can at least be tested by Western blotting for some spliceosome components across the gradient fractions. More importantly, a puromycin treatment control needs to be performed to confirm that FRG1 and EIF4A3 are indeed bound to polysomes, which are separated into ribosome subunits upon puromycin treatment. This leads to a shift of the signal for ribosomal proteins and any polysome-associated proteins to the left.

Reviewer #2 (Public review):

Summary:

In this manuscript, Palo et al present a novel role for FRG1 as a multifaceted regulator of nonsense-mediated mRNA decay (NMD). Through a combination of reporter assays, transcriptome-wide analyses, genetic models, protein-protein interaction studies, ubiquitination assays, and ribosome-associated complex analyses, the authors propose that FRG1 acts as a negative regulator of NMD by destabilizing UPF1 and associating with spliceosomal, EJC, and translation-related complexes. Overall, the data, while consistent with the authors' central conclusions, are undermined by several claims-particularly regarding structural roles and mechanistic exclusivity. To really make the claims presented, further experimental evidence would be required.

Strengths:

(1) The integration of multiple experimental systems (zebrafish and cell culture).

(2) Attempts to go into a mechanistic understanding of the relationship between FGR1 and UPF1.

Weaknesses:

(1) Overstatement of FRG1 as a structural NMD component.

Although FRG1 interacts with UPF1, eIF4A3, PRP8, and CWC22, core spliceosomal and EJC interactions (PRP8-CWC22 and eIF4A3-UPF3B) remain intact in FRG1-deficient cells. This suggests that, while FRG1 associates with these complexes, this interaction is not required for their assembly or structural stability. Without further functional or reconstitution experiments, the presented data are more consistent with an interpretation of FRG1 acting as a regulatory or accessory factor rather than a core structural component.

(2) Causality between UPF1 depletion and NMD inhibition is not fully established.

While reduced UPF1 levels provide a plausible explanation for decreased NMD efficiency, the manuscript does not conclusively demonstrate that UPF1 depletion drives all observed effects. Given FRG1's known roles in transcription, splicing, and RNA metabolism, alterations in transcript isoform composition and apparent NMD sensitivity may arise from mechanisms independent of UPF1 abundance. To directly link UPF1 depletion to altered NMD efficiency, rescue experiments testing whether UPF1 re-expression restores NMD activity in FRG1-overexpressing cells would be important.

(3) Mechanism of FRG1-mediated UPF1 ubiquitination requires clarification.

The ubiquitination assays support a role for FRG1 in promoting UPF1 degradation; however, the mechanism underlying this remains unexplored. The relationship between FRG1-UPF1 what role FRG1 plays in this is unclear (does it function as an adaptor, recruits an E3 ubiquitin ligase, or influences UPF1 ubiquitination indirectly through transcriptional or signaling pathways?).

(4) Limited transcriptome-wide interpretation of RNA-seq data.

Although the RNA-seq data analysis relies heavily on a small subset of "top 10" genes. Additionally, the criteria used to define NMD-sensitive isoforms are unclear. A more comprehensive transcriptome-wide summary-indicating how many NMD-sensitive isoforms are detected and how many are significantly altered-would substantially strengthen the analysis.

(5) Clarification of NMD sensor assay interpretation.

The logic underlying the NMD sensor assay should be explained more clearly early in the manuscript, as the inverse relationship between luciferase signal and NMD efficiency may be counterintuitive to readers unfamiliar with this reporter system. Inclusion of a schematic or brief explanatory diagram would improve accessibility.

(6) Potential confounding effects of high MG132 concentration.

The MG132 concentration used (50 µM) is relatively high and may induce broad cellular stress responses, including inhibition of global translation (its known that proteosome inhibition shuts down translation). Controls addressing these secondary effects would strengthen the conclusion that UPF1 stabilization specifically reflects proteasome-dependent degradation would be essential.

(7) Interpretation of polysome co-sedimentation data.

While the co-sedimentation of FRG1 with polysomes is intriguing, this approach does not distinguish between direct ribosomal association and co-migration with ribosome-associated complexes. This limitation should be explicitly acknowledged in the interpretation.

(8) Limitations of PLA-based interaction evidence.

The PLA data convincingly demonstrate close spatial proximity between FRG1 and eIF4A3; however, PLA does not provide definitive evidence of direct interaction and is known to be susceptible to artefacts. Moreover, a distance threshold of ~40 nm still allows for proteins to be in proximity without being part of the same complex. These limitations should be clearly acknowledged, and conclusions should be framed accordingly.

Reviewer #3 (Public review):

The manuscript by Palo and colleagues demonstrates identification of FRG1 as a novel regulator of nonsense-mediated mRNA decay (NMD), showing that FRG1 inversely modulates NMD efficiency by controlling UPF1 abundance. Using cell-based models and a frg1 knockout zebrafish, the authors show that FRG1 promotes UPF1 ubiquitination and proteasomal degradation, independently of DUX4. The work further positions FRG1 as a structural component of the spliceosome and exon junction complex without compromising its integrity. Overall, the manuscript provides mechanistic insight into FRG1-mediated post-transcriptional regulation and expands understanding of NMD homeostasis. The authors should address the following issues to improve the quality of their manuscript.

(1) Figure 7A-D, appropriate positive controls for the nuclear fraction (e.g., Histone H3) and the cytoplasmic fraction (e.g., GAPDH or α-tubulin) should be included to validate the efficiency and purity of the subcellular fractionation.

(2) To strengthen the conclusion that FRG1 broadly impacts the NMD pathway, qRT-PCR analysis of additional core NMD factors (beyond UPF1) in the frg1⁻/⁻ zebrafish at 48 hpf would be informative.

(3) Figure labels should be standardized throughout the manuscript (e.g., consistent use of "Ex" instead of mixed terms such as "Oex") to improve clarity and readability.

(4) The methods describing the generation of the frg1 knockout zebrafish could be expanded to include additional detail, and a schematic illustrating the CRISPR design, genotyping workflow, and validation strategy would enhance transparency and reproducibility.

(5) As FRG1 is a well-established tumor suppressor, additional cell-based functional assays under combined FRG1 and UPF1 perturbation (e.g., proliferation, migration, or survival assays) could help determine whether FRG1 influences cancer-associated phenotypes through modulation of the NMD pathway.

(6) Given the claim that FRG1 inversely regulates NMD efficacy via UPF1, an epistasis experiment such as UPF1 overexpression in an FRG1-overexpressing background followed by an NMD reporter assay would provide stronger functional validation of pathway hierarchy.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this manuscript, Dixit and colleagues investigate the role of FRG1 in modulating nonsense-mediated mRNA decay using human cell lines and zebrafish embryos. They present data from experiments that test the effect of normal, reduced or elevated levels of FRG1 on NMD of a luciferase-based NMD reporter and on endogenous mRNA substrates of NMD. They also carry out experiments to investigate FRG1's influence on UPF1 mRNA and protein levels, with a particular focus on the possibility that FRG1 regulates UPF1 protein levels through ubiquitin-mediated proteolysis of UPF1. The experiments described also test whether DUX4's effect on UPF1 protein levels and NMD could be mediated through FRG1. Finally, the authors also present experiments that test for physical interaction between UPF1, the spliceosome and components of the exon junction complex.

Strengths:

A key strength of the work is its focus on an intriguing model of NMD regulation by FRG1, which is of particular interest as FRG1 is positively regulated by DUX4, which has been previously implicated in subjecting UPF1 to proteosome-mediated degradation and thereby causing NMD inhibition. The data that shows that DUX4-mediated effect on UPF1 levels is diminished upon FRG1 depletion suggests that DUX4's regulation of NMD could be mediated by FRG1.

Weaknesses:

A major weakness and concern is that many of the key conclusions drawn by the authors are not supported by the data, and there are also some significant concerns with experimental design. More specific comments below describe these issues:

(1) Multiple issues lower the confidence in the experiments testing the effect of FRG1 on NMD.

(a) All reporter assays presented in the manuscript are based on quantification of luciferase activity, and in most cases, the effect on luciferase activity is quite small. This assay is the key experimental approach throughout the manuscript. However, no evidence is provided that the effect captured by this assay is due to enhanced degradation of the mRNA encoding the luciferase reporter, which is what is implied in the interpretation of these experiments. Crucially, there is also no control for the reporter that can account for the effects of experimental manipulations on transcriptional versus post-transcriptional effects. A control reporter lacking a 3'UTR intron is described in Barid et al, where the authors got their NMD reporter from. Due to small effects observed on luciferase activity upon FRG1 depletion, it is necessary to not only measure NMD reporter mRNA steady state levels, but it will be equally important to ascertain that the effect of FRG1 on NMD is at the level of mRNA decay and not altered transcription of NMD substrates. This can be accomplished by testing decay rates of the beta-globin reporter mRNA.

We thank the reviewer for raising these points and for the careful evaluation of our experimental approach. Here we provide our response to comment (a) in three parts

Reliance on luciferase-based reporter assays

While luciferase-based NMD reporter assays represent an important experimental component of this study, our conclusions do not rely exclusively on this approach. The reporter-based findings are independently supported by RNA sequencing analyses of FRG1-perturbed cells, which demonstrate altered abundance of established PTC-containing NMD target transcripts. This genome-wide analysis provides an unbiased and physiologically relevant validation of FRG1 involvement in NMD regulation.

All reporter assays presented in the manuscript are based on quantification of luciferase activity, and in most cases, the effect on luciferase activity is quite small.

We respectfully disagree with the comment that the magnitude of the luciferase effects is low. Increased expression of FRG1, which leads to reduced UPF1 levels, results in a ~3.5-fold increase in relative luciferase activity (Fig. 1C), indicating a robust effect. Furthermore, in the in vivo zebrafish model, FRG1 knockout causes a pronounced decrease in relative luciferase activity (Fig. 1H), consistent with elevated UPF1 levels and enhanced NMD activity.

It is also important to note that FRG1 functions as a negative regulator of UPF1; therefore, its depletion is expected to increase UPF1 levels. However, excessive elevation of UPF1 is likely constrained by additional regulatory mechanisms, which may limit the observable effects of FRG1 knockdown or knockout. In line with this, our previous study (1) demonstrated that FRG1 positively regulates multiple NMD factors while exerting an inverse regulatory effect on UPF1. This dual role suggests that FRG1 may act as a compensatory modulator of the NMD machinery, which likely explains the relatively subtle net effects observed in FRG1 knockdown/knockout conditions in vitro (Fig. 1A and 1B). This interpretation is explicitly discussed in the manuscript (Discussion, paragraph para 4).

However, no evidence is provided that the effect captured by this assay is due to enhanced degradation of the mRNA encoding the luciferase reporter, which is what is implied in the interpretation of these experiments. Crucially, there is also no control for the reporter that can account for the effects of experimental manipulations on transcriptional versus post-transcriptional effects. A control reporter lacking a 3'UTR intron is described in Barid et al, where the authors got their NMD reporter from. Due to small effects observed on luciferase activity upon FRG1 depletion, it is necessary to not only measure NMD reporter mRNA steady state levels, but it will be equally important to ascertain that the effect of FRG1 on NMD is at the level of mRNA decay and not altered transcription of NMD substrates. This can be accomplished by testing decay rates of the beta-globin reporter mRNA.

Thank you for your suggestion. We will test decay rates of the beta-globin reporter mRNA.

(b) It is unusual to use luciferase enzymatic activity as a measurement of RNA decay status. Such an approach can at least be justified if the authors can test how many-fold the luciferase activity changes when NMD is inhibited using a chemical inhibitor (e.g., SMG1 inhibitor) or knockdown of a core NMD factor.

We respectfully disagree that the use of luciferase enzymatic activity as a readout for NMD is unusual. Multiple prior studies have successfully employed identical or closely related luciferase-based/fluorescence-based reporters to quantify NMD activity (2–5). Importantly, the goal of our study was not to measure RNA decay kinetics per se, but rather to assess how altered FRG1 levels influence the functional efficiency of the NMD pathway. Given that FRG1 is a structural component of the spliceosome C complex (6) and is previously indirectly linked to NMD regulation (1,7) this approach was well-suited to address our central question.

As suggested by the reviewer, we will also assess luciferase activity following pharmacological inhibition of NMD to further validate the reporter system's responsiveness.

(c) The concern about the direct effect of FRG1 on NMD is further amplified by the small effects of FRG1 knockout on steady-state levels of endogenous NMD targets (Figure 1A and B: ~20% reduction in reporter mRNA in MCF7 cells; Figure 1M, only 18 endogenous NMD targets shared between FRG1_KO and FRG1_KD).

The modest changes observed upon FRG1 loss do not preclude a direct role in NMD. As detailed in our response to comment (a) and discussed in paragraph 4 of the Discussion, limited effects on steady-state levels of endogenous NMD targets are expected given the buffering capacity of the NMD pathway and the contribution of compensatory regulatory mechanisms.

(d) The question about transcriptional versus post-transcriptional effects is also important in light of the authors' previous work that FRG1 can act as a transcriptional regulator.

We agree that distinguishing between transcriptional and post-transcriptional effects is important, particularly in light of our previous work demonstrating that FRG1 can function as a transcriptional regulator of multiple NMD genes (1). Consistent with this, the current manuscript shows that FRG1 influences the transcript levels of UPF1. In addition, we demonstrate that FRG1 regulates UPF1 at the protein level. We therefore conclude that FRG1 regulates UPF1 dually, at both transcriptional and post-transcriptional levels, supporting a dual role for FRG1 in the regulation of NMD.

This conclusion is further supported by prior studies indicating post-transcriptional functions of FRG1. FRG1 is a nucleocytoplasmic shuttling protein(8), interacts with the NMD factor ROD1 (7), and has been identified as a component of the spliceosomal C complex (6). FRG1 has also been reported to associate with the hnRNPK family of proteins (8), which participate in extensive protein–protein interaction networks. Collectively, these observations are consistent with a role for FRG1 in regulating NMD components at multiple levels.

(2) In the experiments probing the relationship between DUX4 and FRG1 in NMD regulation, there are some inconsistencies that need to be resolved.

(a) Figure 3 shows that the inhibition of NMD reporter activity caused by DUX4 induction is reversed by FRG1 knockdown. Although levels of FRG1 and UPF1 in DUX4 uninduced and DUX4 induced + FRG1 knockdown conditions are similar (Figure 5A), why is the reporter activity in DUX4 induced + FRG1 knockdown cells much lower than DUX4 uninduced cells in Figure 3?

We appreciate the reviewer’s comment. Figures 3 and 5A represent independent experiments in which FRG1 knockdown was achieved by transient transfection. As such, variability in transfection efficiency is expected and likely accounts for the quantitative difference. We want to highlight that compared to DUX4_induced lane (Fig. 5A, lane 2), when we knock down FRG1 on the DUX4_induced background, it shows a clear increase in the UPF1 level (Fig. 5A, lane 3). We will add one more replicate to 5 A with better FRG1_KD transfection to the experiment.

(b) In Figure 3, it is important to know the effect of FRG1 knockdown in DUX4 uninduced conditions.

We thank the reviewer for this thoughtful suggestion. The effect of FRG1 knockdown under DUX4-uninduced conditions is presented in Figure 1A, where FRG1 levels are reduced without altering DUX4 expression. In contrast, Figure 3 is specifically designed to assess the rescue effect—namely, how reduction of FRG1 expression under DUX4-induced conditions influences NMD efficiency. Therefore, inclusion of an FRG1 knockdown–only group in Figure 3 was not relevant to the objective of this experiment.

(c) On line 401, the authors claim that MG132 treatment leads to "time-dependent increase in UPF1 protein levels" in Figure 5C. However, upon proteasome inhibition, UPF1 levels significantly increase only at 8h time point, while the change at 12 and 24 hours is not significantly different from the control.

We thank the reviewer for this observation and agree that the statement of a “time-dependent increase in UPF1 protein levels” was inaccurate. A significant increase is observed only at the 8 h time point following MG132 treatment, with no significant changes at 12 h or 24 h. The text will be revised accordingly to reflect Figure 5C.

(3) There are multiple issues with experiments investigating ubiquitination of UPF1:

(a) Ubiquitin blots in Figure 6 are very difficult to interpret. There is no information provided either in the text or figure legends as to which bands in the blots are being compared, or about what the sizes of these bands are, as compared to UPF1. Also, the signal for Ub in most IP samples looks very similar to or even lower than the input.

We agree that the ubiquitin blots in Figure 6 require clearer presentation. In the revised figure, we will annotate the ubiquitin immunoblots to indicate the region corresponding to UPF1 (~140 kDa), which is the relevant molecular weight for interpretation. Because UPF1 is polyubiquitinated, ubiquitinated species are expected to appear as multiple bands rather than a single discrete signal; therefore, ubiquitination was assessed across the full blot. Importantly, interpretation is based on comparisons between UPF1 immunoprecipitated samples within each panel (Fig. 6C–F), rather than between input and IP lanes. For example, in Figure 6 C UPF1 IP FRG1_KD compared to UPF1 IP FRG1_Ex, in Figure 6 D UPF1 IP FRG1_WT compared to UPF1 IP FRG1_KO, in Figure 6 E UPF1 IP FRG1_KO compared to UPF1 IP FRG1_KO+FRG1_Ex, and in Figure 6 F UPF1 IP FRG1_Ex compared to UPF1 IP FRG1_Ex+MG132 TRT.

(b) Western blot images in Figure 6D appear to be adjusted for brightness/contrast to reduce background, but are done in such a way that pixel intensities are not linearly altered. This image appears to be the most affected, although some others have also similar patterns (e.g., Figure 5C).

We thank the reviewer for raising this point. The appearance noted in Figure 6D was not due to non-linear alteration of pixel intensities, but rather resulted from the poor quality of the ubiquitin antibody, which required prolonged exposure times. To address this, we replaced the antibody and repeated the ubiquitin immunoblots shown in Figures 6D, 6E, and 6F.

For Figure 5C, only uniform contrast adjustment was applied for clarity. Importantly, all adjustments were performed linearly and applied to the entire image. Raw, unprocessed images for all blots are provided in the Supplementary Information. Updated versions of Figures 5 and 6 will be included in the revised manuscript.

(4) The experiments probing physical interactions of FRG1 with UPF1, spliceosome and EJC proteins need to consider the following points:

(a) There is no information provided in the results or methods section on whether immunoprecipitations were carried out in the absence or presence of RNases. Each RNA can be bound by a plethora of proteins that may not be functionally engaged with each other. Without RNase treatment, even such interactions will lead to co-immunoprecipitation. Thus, experiments in Figure 6 and Figure 7A-D should be repeated with and without RNase treatment.

We thank the reviewer for this important point. The co-immunoprecipitation experiments shown in Figures 6 and 7A–D were performed in the absence of RNase treatment; this information was inadvertently omitted and will be added to the Methods section and the relevant figure legends. To directly assess whether the observed interactions are RNA-dependent, we will repeat the key co-immunoprecipitation experiments in the presence of RNase treatment and include these results in the revised manuscript.

(b) Also, the authors claim that FRG1 is a "structural component" of EJC and NMD complexes seems to be an overinterpretation. As noted in the previous comment, these interactions could be mediated by a connecting RNA molecule.

We thank the reviewer for this insightful comment. As noted, previous studies have suggested that FRG1 interacts with components of the EJC and NMD machinery. Specifically, Bertram et al. (6) identified FRG1 as a component of the spliceosomal C complex via Cryo-EM structural analysis, and pull-down studies have shown direct interaction between FRG1 and ROD1, a known EJC component (7). These findings support a protein-protein interaction rather than one mediated solely by RNA. To further address the reviewer’s concern, we will perform key co-immunoprecipitation experiments in the presence of RNase treatment to distinguish RNA-dependent from RNA-independent interactions.

(c) A negative control (non-precipitating protein) is missing in Figure 7 co-IP experiments.

We agree that including a non-precipitating protein as a negative control is important, and we will perform the co-IP experiment incorporating this control.

(d) Polysome analysis is missing important controls. FRG1 and EIF4A3 co-sedimentation with polysomes could simply be due to their association with another large complex (e.g., spliceosome), which will also co-sediment in these gradients. This possibility can at least be tested by Western blotting for some spliceosome components across the gradient fractions. More importantly, a puromycin treatment control needs to be performed to confirm that FRG1 and EIF4A3 are indeed bound to polysomes, which are separated into ribosome subunits upon puromycin treatment. This leads to a shift of the signal for ribosomal proteins and any polysome-associated proteins to the left.

As recommended, we will examine the distribution of a spliceosome component across the gradient fractions to assess potential co-sedimentation. Additionally, we will perform a puromycin treatment control to confirm that FRG1 and EIF4A3 are genuinely associated with polysomes.

Reviewer #2 (Public review):

Summary:

In this manuscript, Palo et al present a novel role for FRG1 as a multifaceted regulator of nonsense-mediated mRNA decay (NMD). Through a combination of reporter assays, transcriptome-wide analyses, genetic models, protein-protein interaction studies, ubiquitination assays, and ribosome-associated complex analyses, the authors propose that FRG1 acts as a negative regulator of NMD by destabilizing UPF1 and associating with spliceosomal, EJC, and translation-related complexes. Overall, the data, while consistent with the authors' central conclusions, are undermined by several claims-particularly regarding structural roles and mechanistic exclusivity. To really make the claims presented, further experimental evidence would be required.

Strengths:

(1) The integration of multiple experimental systems (zebrafish and cell culture).

(2) Attempts to go into a mechanistic understanding of the relationship between FGR1 and UPF1.

Weaknesses:

(1) Overstatement of FRG1 as a structural NMD component.

Although FRG1 interacts with UPF1, eIF4A3, PRP8, and CWC22, core spliceosomal and EJC interactions (PRP8-CWC22 and eIF4A3-UPF3B) remain intact in FRG1-deficient cells. This suggests that, while FRG1 associates with these complexes, this interaction is not required for their assembly or structural stability. Without further functional or reconstitution experiments, the presented data are more consistent with an interpretation of FRG1 acting as a regulatory or accessory factor rather than a core structural component.

We thank the reviewer for this clarification. We would like to emphasize that we do not claim FRG1 to be a core structural component of either the spliceosome or the EJC. Consistent with the reviewer’s interpretation, our data indicate that FRG1 deficiency does not disrupt the structural integrity of these complexes. Our intended conclusion is that FRG1 functions as a regulatory or accessory factor in NMD rather than being required for complex assembly or stability. We will carefully revise the manuscript to remove any language that could be interpreted as an overstatement. In addition, we are currently performing further experiments to better define the association of FRG1 with the EJC.

(2) Causality between UPF1 depletion and NMD inhibition is not fully established.

While reduced UPF1 levels provide a plausible explanation for decreased NMD efficiency, the manuscript does not conclusively demonstrate that UPF1 depletion drives all observed effects. Given FRG1's known roles in transcription, splicing, and RNA metabolism, alterations in transcript isoform composition and apparent NMD sensitivity may arise from mechanisms independent of UPF1 abundance. To directly link UPF1 depletion to altered NMD efficiency, rescue experiments testing whether UPF1 re-expression restores NMD activity in FRG1-overexpressing cells would be important.

As suggested, to directly test causality, we will perform rescue experiments to determine whether UPF1 re-expression restores NMD activity in FRG1-overexpressing MCF7 cells.

(3) Mechanism of FRG1-mediated UPF1 ubiquitination requires clarification.

The ubiquitination assays support a role for FRG1 in promoting UPF1 degradation; however, the mechanism underlying this remains unexplored. The relationship between FRG1-UPF1 what role FRG1 plays in this is unclear (does it function as an adaptor, recruits an E3 ubiquitin ligase, or influences UPF1 ubiquitination indirectly through transcriptional or signaling pathways?).

We agree with the reviewer that the precise mechanism by which FRG1 promotes UPF1 ubiquitination remains to be defined. Our ubiquitination assays support a role for FRG1 in facilitating UPF1 degradation; however, whether FRG1 functions directly as an adaptor or E3 ligase, or instead influences UPF1 stability indirectly, is currently unclear. Notably, a prior study by Geng et al. reported that DUX4 expression alters the expression of numerous genes involved in protein ubiquitination, including multiple E3 ubiquitin ligases (9), and FRG1 itself has been reported to be upregulated upon DUX4 expression in muscle cells. We will expand the Discussion to address these potential mechanisms and place our findings in the context of indirect transcriptional or signaling pathways that may regulate UPF1 proteolysis. A detailed mechanistic dissection of FRG1-mediated ubiquitination is beyond the scope of the present study.

(4) Limited transcriptome-wide interpretation of RNA-seq data.

Although the RNA-seq data analysis relies heavily on a small subset of "top 10" genes. Additionally, the criteria used to define NMD-sensitive isoforms are unclear. A more comprehensive transcriptome-wide summary-indicating how many NMD-sensitive isoforms are detected and how many are significantly altered-would substantially strengthen the analysis.

We thank the reviewer for this comment and agree that the current presentation may place a disproportionate emphasis on a limited subset of genes. These genes were selected as illustrative examples from an isoform-level analysis performed using IsoformSwitchAnalyzeR (ISAR) (10); however, we acknowledge that this approach does not fully convey the transcriptome-wide scope of the analysis.

Using quantified RNA-seq data, ISAR was employed to identify significant isoform switches and transcripts predicted to be NMD-sensitive. Isoforms were annotated using GENCODE v47, and NMD sensitivity was assigned based on the established 50-nucleotide rule, as described in the Materials and Methods. To address the reviewer’s concern, we will revise the Results section to include a transcriptome-wide summary derived from the ISAR analysis.

(5) Clarification of NMD sensor assay interpretation.

The logic underlying the NMD sensor assay should be explained more clearly early in the manuscript, as the inverse relationship between luciferase signal and NMD efficiency may be counterintuitive to readers unfamiliar with this reporter system. Inclusion of a schematic or brief explanatory diagram would improve accessibility.

We agree with the reviewer and would provide a schematic as well as the experimental setup diagram to improve accessibility to the readers.

(6) Potential confounding effects of high MG132 concentration.

The MG132 concentration used (50 µM) is relatively high and may induce broad cellular stress responses, including inhibition of global translation (its known that proteosome inhibition shuts down translation). Controls addressing these secondary effects would strengthen the conclusion that UPF1 stabilization specifically reflects proteasome-dependent degradation would be essential.

We acknowledge the reviewer’s concern regarding the relatively high concentration of MG132 used in this study. While proteasome inhibition can indeed induce global translation inhibition, our interpretation is based on the specific stabilization of UPF1 observed under these conditions. Since inhibition of global translation would generally reduce protein levels rather than cause selective accumulation, the observed increase in UPF1 is unlikely to result from translational effects. To address this point, we plan to repeat selected experiments using a lower MG132 concentration to further confirm that UPF1 stabilization reflects proteasome-dependent degradation.

(7) Interpretation of polysome co-sedimentation data.

While the co-sedimentation of FRG1 with polysomes is intriguing, this approach does not distinguish between direct ribosomal association and co-migration with ribosome-associated complexes. This limitation should be explicitly acknowledged in the interpretation.

We acknowledge that polysome co-sedimentation alone cannot definitively distinguish between direct ribosomal binding and co-migration with ribosome-associated complexes. Importantly, our interpretation does not rely solely on this assay; when combined with co-immunoprecipitation and proximity ligation assay results, the data consistently support an association of FRG1 with the exon junction complex. We are also conducting additional experiments with appropriate controls to further validate the specificity of FRG1’s association with ribosomes and to address the possibility of nonspecific co-migration.

(8) Limitations of PLA-based interaction evidence.

The PLA data convincingly demonstrate close spatial proximity between FRG1 and eIF4A3; however, PLA does not provide definitive evidence of direct interaction and is known to be susceptible to artefacts. Moreover, a distance threshold of ~40 nm still allows for proteins to be in proximity without being part of the same complex. These limitations should be clearly acknowledged, and conclusions should be framed accordingly.

We thank the reviewer for highlighting this important point. We agree that PLA indicates close spatial proximity but does not constitute definitive evidence of direct interaction and can be susceptible to artefacts. We will explicitly acknowledge this limitation in the revised manuscript. Importantly, our conclusions are not solely based on PLA data; they are supported by complementary co-immunoprecipitation and polysome co-sedimentation assays, which provide biochemical evidence consistent with an association between FRG1 and eIF4A3.

Reviewer #3 (Public review):

The manuscript by Palo and colleagues demonstrates identification of FRG1 as a novel regulator of nonsense-mediated mRNA decay (NMD), showing that FRG1 inversely modulates NMD efficiency by controlling UPF1 abundance. Using cell-based models and a frg1 knockout zebrafish, the authors show that FRG1 promotes UPF1 ubiquitination and proteasomal degradation, independently of DUX4. The work further positions FRG1 as a structural component of the spliceosome and exon junction complex without compromising its integrity. Overall, the manuscript provides mechanistic insight into FRG1-mediated post-transcriptional regulation and expands understanding of NMD homeostasis. The authors should address the following issues to improve the quality of their manuscript.

(1) Figure 7A-D, appropriate positive controls for the nuclear fraction (e.g., Histone H3) and the cytoplasmic fraction (e.g., GAPDH or α-tubulin) should be included to validate the efficiency and purity of the subcellular fractionation.

We thank the reviewer for the suggestion. We will include appropriate positive controls for the nuclear fraction (Histone H3) and the cytoplasmic fraction (GAPDH or α-tubulin) in Figure 7A–D to validate the efficiency and purity of the subcellular fractionation.

(2) To strengthen the conclusion that FRG1 broadly impacts the NMD pathway, qRT-PCR analysis of additional core NMD factors (beyond UPF1) in the frg1⁻/⁻ zebrafish at 48 hpf would be informative.

We appreciate the reviewer’s insightful comment. We will perform qRT-PCR analysis of additional core NMD factors in the frg1⁻/⁻ zebrafish at 48 hpf to further strengthen the conclusion that FRG1 broadly impacts the NMD pathway.

(3) Figure labels should be standardized throughout the manuscript (e.g., consistent use of "Ex" instead of mixed terms such as "Oex") to improve clarity and readability.

We thank the reviewer for noticing the inconsistency. We will ensure that all figure labels are standardized throughout the manuscript (e.g., using “Ex” consistently) to improve clarity and readability.

(4) The methods describing the generation of the frg1 knockout zebrafish could be expanded to include additional detail, and a schematic illustrating the CRISPR design, genotyping workflow, and validation strategy would enhance transparency and reproducibility.

We appreciate the reviewer’s suggestion and will expand the Methods section to provide additional detail on the generation of the frg1 knockout zebrafish. A schematic illustrating the CRISPR design, genotyping workflow, and validation strategy will also be included to enhance transparency and reproducibility.

(5) As FRG1 is a well-established tumor suppressor, additional cell-based functional assays under combined FRG1 and UPF1 perturbation (e.g., proliferation, migration, or survival assays) could help determine whether FRG1 influences cancer-associated phenotypes through modulation of the NMD pathway.

We thank the reviewer for this thoughtful and constructive suggestion. While FRG1 is indeed a well-established tumor suppressor, incorporating additional cell-based functional assays under combined FRG1 and UPF1 perturbation would significantly broaden the scope of the current study. The present work is focused on elucidating the molecular relationship between FRG1 and the NMD pathway. Investigation of downstream cancer-associated phenotypes represents an important and interesting direction for future studies, but is beyond the scope of the current manuscript.

(6) Given the claim that FRG1 inversely regulates NMD efficacy via UPF1, an epistasis experiment such as UPF1 overexpression in an FRG1-overexpressing background followed by an NMD reporter assay would provide stronger functional validation of pathway hierarchy.

We agree with the reviewer’s suggestion. To strengthen the functional validation of the proposed pathway hierarchy, we will perform an epistasis experiment by overexpressing UPF1 in an FRG1-overexpressing background and assess NMD activity using an established NMD reporter assay. The results of this experiment will be included in the revised manuscript.

References

(1) Palo A, Patel SA, Shubhanjali S, Dixit M. Dynamic interplay of Sp1, YY1, and DUX4 in regulating FRG1 transcription with intricate balance. Biochim Biophys Acta Mol Basis Dis. 2025 Mar;1871(3):167636.

(2) Sato H, Singer RH. Cellular variability of nonsense-mediated mRNA decay. Nat Commun. 2021 Dec 10;12(1):7203.

(3) Baird TD, Cheng KCC, Chen YC, Buehler E, Martin SE, Inglese J, et al. ICE1 promotes the link between splicing and nonsense-mediated mRNA decay. eLife. 2018 Mar 12;7:e33178.

(4) Chu V, Feng Q, Lim Y, Shao S. Selective destabilization of polypeptides synthesized from NMD-targeted transcripts. Mol Biol Cell. 2021 Dec 1;32(22):ar38.

(5) Udy DB, Bradley RK. Nonsense-mediated mRNA decay uses complementary mechanisms to suppress mRNA and protein accumulation. Life Sci Alliance. 2022 Mar;5(3):e202101217.

(6) Bertram K, El Ayoubi L, Dybkov O, Agafonov DE, Will CL, Hartmuth K, et al. Structural Insights into the Roles of Metazoan-Specific Splicing Factors in the Human Step 1 Spliceosome. Mol Cell. 2020 Oct 1;80(1):127-139.e6.

(7) Brazão TF, Demmers J, van IJcken W, Strouboulis J, Fornerod M, Romão L, et al. A new function of ROD1 in nonsense-mediated mRNA decay. FEBS Lett. 2012 Apr 24;586(8):1101–10.

(8) Sun CYJ, van Koningsbruggen S, Long SW, Straasheijm K, Klooster R, Jones TI, et al. Facioscapulohumeral muscular dystrophy region gene 1 is a dynamic RNA-associated and actin-bundling protein. J Mol Biol. 2011 Aug 12;411(2):397–416.

(9) Geng LN, Yao Z, Snider L, Fong AP, Cech JN, Young JM, et al. DUX4 activates germline genes, retroelements, and immune mediators: implications for facioscapulohumeral dystrophy. Dev Cell. 2012 Jan 17;22(1):38–51.

(10) Vitting-Seerup K, Sandelin A. The Landscape of Isoform Switches in Human Cancers. Mol Cancer Res MCR. 2017 Sep;15(9):1206–20.

eLife Assessment

This study presents a valuable finding on maternal SETDB1 as a key chromatin repressor that shuts down the 2C gene program and enables normal mouse embryonic development. The evidence supporting the claims of the authors is solid, although the inclusion of a causality test, a mechanistic understanding of SETDB1 targeting, and phenotypic quantification would have greatly strengthened the study. The work will be of broad interest to biologists working on embryonic development, stem cells and gene regulation.

Reviewer #1 (Public review):

Summary:

During the earliest stages of mouse development, the zygote and 2-cell (2C) embryo are totipotent, capable of generating all embryonic and extra-embryonic lineages, and they transiently express a distinctive set of "2C-stage" genes, many driven by MERVL long terminal repeat (LTR) promoters. Although activation of these transcripts is a normal feature of totipotency, they must be rapidly silenced as development proceeds to the 4-cell and 8-cell stages; failure to shut down the 2C program results in developmental arrest. This study examines the role of maternal SETDB1, a histone H3K9 methyltransferase, in suppressing the 2C transcriptional network. Using an oocyte-specific conditional knockout that removes maternal Setdb1 while leaving the paternal allele intact, the authors demonstrate that embryos lacking maternal SETDB1 arrest during cleavage, with very few progressing beyond the 8-cell stage and no morphologically normal blastocysts forming. Transcriptomic analyses reveal persistent expression of MERVL-LTR-driven transcripts and other totipotency markers, indicating a failure to terminate the totipotent state. Together, the data demonstrate that maternally deposited SETDB1 is required to silence the MERVL-driven 2C program and enable the transition from totipotency to pluripotency. More broadly, the work identifies maternal SETDB1 as a key chromatin repressor that deposits repressive H3K9 methylation to shut down the transient 2C gene network and to permit normal preimplantation development.

Strengths:

(1) Closes a key knowledge gap.

The study tackles a central open question - how embryos exit the totipotent 2-cell (2C) state - and provides direct in vivo evidence that epigenetic repression is required to terminate the 2C program for development to proceed. By identifying maternal SETDB1 as the responsible factor, the work substantially advances our understanding of the maternal-to-zygotic transition and early lineage specification.

(2) Clean genetics paired with rigorous genomics.

An oocyte-specific Setdb1 knockout cleanly isolates a maternal-effect requirement, ensuring that early phenotypes arise from loss of maternal protein. The resulting cleavage-stage arrest is unambiguous (most embryos stall before or around the 8-cell stage). State-of-the-art single-embryo RNA-seq across stages - well-matched to low-cell-number constraints - captures genome-wide mis-expression, including persistent 2C transcripts in mutants, strongly supporting the conclusions.

(3) Compelling molecular linkage to phenotype.

Transcriptome data show that without maternal SETDB1, embryos fail to repress a suite of 1-cell/2C-specific genes by the 8-cell stage. The tight correlation between continued activation of the MERVL-driven totipotency network and developmental arrest provides a specific molecular explanation for the observed failure to progress.

(4) Mechanistic insight grounded in chromatin biology.

SETDB1, a H3K9 methyltransferase classically linked to heterochromatin and transposon repression, targets MERVL LTRs and MERVL-driven chimeric transcripts in early embryos. Bioinformatic evidence indicates that these loci normally acquire H3K9me3 during the 2C→4C transition. The data articulate a coherent mechanism: maternal SETDB1 deposits repressive H3K9me3 at 2C gene loci to shut down the totipotency network, extending observations from ESC systems to bona fide embryos.

(5) Broad implications for development and stem-cell biology.

By pinpointing a maternal gatekeeper of the totipotent-to-pluripotent transition, the work suggests that some cases of cleavage-stage arrest (e.g., in IVF) may reflect faulty epigenetic silencing of transposon-driven genes. It also informs stem-cell efforts to control totipotent-like states in vitro (e.g., 2C-like cells), linking epigenetic reprogramming, transposable-element regulation, and developmental potency.

Weaknesses:

(1) Causality not directly demonstrated.

The link among loss of SETDB1, persistence of 2C transcripts, and developmental arrest is compelling but remains correlative. No rescue experiments test whether dampening the 2C/MERVL program restores development. Targeted interventions-e.g., knocking down key 2C drivers (such as Dux) or pharmacologically curbing MERVL-linked transcription in maternal Setdb1 mutants-would strengthen the claim that unchecked 2C activity is causal rather than a by-product of other SETDB1 functions.

(2) Limited mechanistic resolution of SETDB1 targeting.

The study establishes a requirement for maternal SETDB1 but does not define how it is recruited to MERVL loci. Given SETDB1's canonical cooperation with TRIM28/KAP1 and KRAB-ZNFs, upstream sequence-specific factors and/or pre-existing chromatin features likely guide targeting. Direct occupancy and mark-placement evidence (e.g., SETDB1/TRIM28 CUT&RUN or ChIP, and H3K9me3 profiling at MERVL LTRs during the 2C→4C window) would convert inferred mechanisms into demonstrated ones.

(3) Narrow scope on MERVL; broader epigenomic consequences underexplored.

Maternal SETDB1 may restrain additional repeat classes or genes beyond the 2C network. A systematic repeatome analysis (LINEs/SINEs/ERV subfamilies) would clarify specificity versus a general loss of heterochromatin control. Moreover, potential effects on imprinting or DNA methylation balance are not examined; perturbations there could also contribute to arrest. Bisulfite-based DNA methylation maps at imprinted loci and allele-specific expression analyses would help rule in/out these mechanisms.

(4) Phenotype quantitation and transcriptomic breadth could be clearer.

The developmental phenotype is described qualitatively ("very few beyond 8-cell") without precise stage-wise arrest rates or representative morphology. Tabulated counts (2C/4C/8C/blastocyst), images, and statistics would increase clarity. On the RNA-seq side, the narrative emphasizes known 2C markers; reporting novel/unannotated misregulated transcripts, as well as downregulated pathways (e.g., failure to activate normal 8-cell programs, metabolism, or early lineage markers), would present a fuller portrait of the mutant state.

Reviewer #2 (Public review):

Zeng et al. report that Setdb1-/- embryos fail to extinguish the 1- and 2-cell embryo transcriptional program and have permanent expression of MERVL transposable elements. The manuscript is technically sound and well performed, but, in my opinion, the results lack conceptual novelty.

(1) The manuscript builds on previous observations that: 1, Setbd1 is necessary for early mouse development, with knockout embryos rarely reaching the 8-cell stage; 2, SETB1 mediates H3K9me3 deposition at transposable elements in mouse ESCs; 3, SETB1silences MERVLs to prevent 2CLC-state acquisition in mouse ESCs. The strength of the current work is the demonstration that this is not due to a general transcriptional collapse; but otherwise, the findings are not surprising. The well-known (several Nature papers of years ago) crosstalk between m6A RNA modification and H3K9me3 in preventing 2CLC generation also partly compromises the novelty of this work.

(2) The conclusions regarding H3K9me3 deposition are inferred based on previously reported datasets, but there is no direct demonstration.

(3) The detection of chimeric transcripts is somewhat unreliable using short-read sequencing.

Author response:

eLife Assessment 

This study presents a valuable finding on maternal SETDB1 as a key chromatin repressor that shuts down the 2C gene program and enables normal mouse embryonic development. The evidence supporting the claims of the authors is solid, although the inclusion of a causality test, a mechanistic understanding of SETDB1 targeting, and phenotypic quantification would have greatly strengthened the study. The work will be of broad interest to biologists working on embryonic development, stem cells and gene regulation.

Thank you for this positive evaluation of our work. Please find the point-by point responses to the Reviewer’s comments below.

Public Reviews:

Reviewer #1 (Public review):

Summary: 

During the earliest stages of mouse development, the zygote and 2-cell (2C) embryo are totipotent, capable of generating all embryonic and extra-embryonic lineages, and they transiently express a distinctive set of "2C-stage" genes, many driven by MERVL long terminal repeat (LTR) promoters. Although activation of these transcripts is a normal feature of totipotency, they must be rapidly silenced as development proceeds to the 4-cell and 8-cell stages; failure to shut down the 2C program results in developmental arrest. This study examines the role of maternal SETDB1, a histone H3K9 methyltransferase, in suppressing the 2C transcriptional network. Using an oocyte-specific conditional knockout that removes maternal Setdb1 while leaving the paternal allele intact, the authors demonstrate that embryos lacking maternal SETDB1 arrest during cleavage, with very few progressing beyond the 8-cell stage and no morphologically normal blastocysts forming. Transcriptomic analyses reveal persistent expression of MERVL-LTR-driven transcripts and other totipotency markers, indicating a failure to terminate the totipotent state. Together, the data demonstrate that maternally deposited SETDB1 is required to silence the MERVL-driven 2C program and enable the transition from totipotency to pluripotency. More broadly, the work identifies maternal SETDB1 as a key chromatin repressor that deposits repressive H3K9 methylation to shut down the transient 2C gene network and to permit normal preimplantation development. 

Strengths: 

(1) Closes a key knowledge gap. 

The study tackles a central open question - how embryos exit the totipotent 2-cell (2C) state - and provides direct in vivo evidence that epigenetic repression is required to terminate the 2C program for development to proceed. By identifying maternal SETDB1 as the responsible factor, the work substantially advances our understanding of the maternal-to-zygotic transition and early lineage specification. 

(2) Clean genetics paired with rigorous genomics. 

An oocyte-specific Setdb1 knockout cleanly isolates a maternal-effect requirement, ensuring that early phenotypes arise from loss of maternal protein. The resulting cleavage-stage arrest is unambiguous (most embryos stall before or around the 8-cell stage). State-of-the-art single-embryo RNA-seq across stages - well-matched to low-cell-number constraints - captures genome-wide mis-expression, including persistent 2C transcripts in mutants, strongly supporting the conclusions. 

(3) Compelling molecular linkage to phenotype. 

Transcriptome data show that without maternal SETDB1, embryos fail to repress a suite of 1-cell/2C-specific genes by the 8-cell stage. The tight correlation between continued activation of the MERVL-driven totipotency network and developmental arrest provides a specific molecular explanation for the observed failure to progress. 

(4) Mechanistic insight grounded in chromatin biology. 

SETDB1, a H3K9 methyltransferase classically linked to heterochromatin and transposon repression, targets MERVL LTRs and MERVL-driven chimeric transcripts in early embryos. Bioinformatic evidence indicates that these loci normally acquire H3K9me3 during the 2C→4C transition. The data articulate a coherent mechanism: maternal SETDB1 deposits repressive H3K9me3 at 2C gene loci to shut down the totipotency network, extending observations from ESC systems to bona fide embryos. 

(5) Broad implications for development and stem-cell biology. 

By pinpointing a maternal gatekeeper of the totipotent-to-pluripotent transition, the work suggests that some cases of cleavage-stage arrest (e.g., in IVF) may reflect faulty epigenetic silencing of transposon-driven genes. It also informs stem-cell efforts to control totipotent-like states in vitro (e.g., 2C-like cells), linking epigenetic reprogramming, transposable-element regulation, and developmental potency.

We thank Reviewer 1 for recognizing the strengths in our work and for the suggestions below.

Weaknesses: 

(1) Causality not directly demonstrated. 

The link among loss of SETDB1, persistence of 2C transcripts, and developmental arrest is compelling but remains correlative. No rescue experiments test whether dampening the 2C/MERVL program restores development. Targeted interventions-e.g., knocking down key 2C drivers (such as Dux) or pharmacologically curbing MERVL-linked transcription in maternal Setdb1 mutants-would strengthen the claim that unchecked 2C activity is causal rather than a by-product of other SETDB1 functions.

We agree that rescue experiments might strengthen causality. Those experiments, however, would be extremely challenging technically because the knockdowns would need to be precisely timed to follow (and not prevent) the wave of 2c-specific activation. Knocking down 2c drivers in the zygote, for example, may prevent switching on the totipotency program. In addition, while sustained MERVL expression—such as that induced by forced DUX expression—disrupts totipotency exit and embryo development (1, 2), derepression of transcription is very broad in Setdb1^mat-/+ embryos and knocking down individual 2C drivers may not be sufficient to rescue development or restore the exit from totipotency.

(2) Limited mechanistic resolution of SETDB1 targeting. 

The study establishes a requirement for maternal SETDB1 but does not define how it is recruited to MERVL loci. Given SETDB1's canonical cooperation with TRIM28/KAP1 and KRAB-ZNFs, upstream sequence-specific factors and/or pre-existing chromatin features likely guide targeting. Direct occupancy and mark-placement evidence (e.g., SETDB1/TRIM28 CUT&RUN or ChIP, and H3K9me3 profiling at MERVL LTRs during the 2C→4C window) would convert inferred mechanisms into demonstrated ones.

We do show H3K9me3 patterns at MERVL LTRs during the early2c-late2c-2c-4c-8c-morula window from a published dataset. Please see the genome browser images in Figures 4C, 4D, 4E, 6D, 6E and Figure S6. We agree that mapping of SETDB1/TRIM28 to those locations would strengthen the mechanistic insight. However, ChIPseq or CUT&RUN of those proteins in preimplantation embryos are not technically feasible. We do provide genetic evidence for the collaboration between SETDB1 and DUXBL, a DNA-binding factor, by showing that DUXBL cannot switch off its top targets without SETDB1 (Figure 6). Future studies will characterize the molecular mechanisms underlying this (likely indirect) collaboration. We do not think that DUXBL and SETDB1 directly interact, because such interaction was not detected by DUXBL IP-MS (3).

(3) Narrow scope on MERVL; broader epigenomic consequences underexplored. 

Maternal SETDB1 may restrain additional repeat classes or genes beyond the 2C network. A systematic repeatome analysis (LINEs/SINEs/ERV subfamilies) would clarify specificity versus a general loss of heterochromatin control. Moreover, potential effects on imprinting or DNA methylation balance are not examined; perturbations there could also contribute to arrest. Bisulfite-based DNA methylation maps at imprinted loci and allele-specific expression analyses would help rule in/out these mechanisms.

We did examine genes and repeat elements beyond the 2c network. We evaluated gene and TE expression changes using four-way comparisons. Please find the results regarding gene expression in Figure 1C-J, Figure S2, Figure S3, Figure S4., Table S2, Table S3, and Table S4. Please find results on TE expression in Figure S5. Table S6, Table S7, and Table S8 and in the text. We agree that DNA methylation may be altered in Setdb1^mat-/+ embryos. In our hands, evaluating this possibility using bisulfite sequencing requires a larger number of embryos than what we can feasibly obtain (the number of obtained mutant embryos is very small). Regarding imprinted gene expression, one cannot fully assess and interpret imprinted gene expression in preimplantation stage embryos before the maternally deposited transcripts are gone. We reported earlier that clear somatic parental-specific patterns of imprinted gene expression may only start later in development, around 8.5 dpc (4).

(4) Phenotype quantitation and transcriptomic breadth could be clearer. 

The developmental phenotype is described qualitatively ("very few beyond 8-cell") without precise stage-wise arrest rates or representative morphology. Tabulated counts (2C/4C/8C/blastocyst), images, and statistics would increase clarity. On the RNA-seq side, the narrative emphasizes known 2C markers; reporting novel/unannotated misregulated transcripts, as well as downregulated pathways (e.g., failure to activate normal 8-cell programs, metabolism, or early lineage markers), would present a fuller portrait of the mutant state.

Tabulated counts are displayed in Figure 1A, and morphology is shown in Figure S1A. We do say that 4% Setdb1^mat-/+ embryos reached the 8-cel stage by 2.5 dpc. We recovered zero Setdb1^mat-/+ blastocysts at 4.5 dpc (not shown). On the RNA-seq side we do report a more global assessment of transcription of genes and TEs (please see above at point 3), including novel chimeric transcripts (Table S6). Developmental pathways are shown in Figure S3 and Figure S4. Metabolic pathways are displayed in Figure S2.

Reviewer #2 (Public review): 

Zeng et al. report that Setdb1-/- embryos fail to extinguish the 1- and 2-cell embryo transcriptional program and have permanent expression of MERVL transposable elements. The manuscript is technically sound and well performed, but, in my opinion, the results lack conceptual novelty.

(1) The manuscript builds on previous observations that: 1, Setbd1 is necessary for early mouse development, with knockout embryos rarely reaching the 8-cell stage; 2, SETB1 mediates H3K9me3 deposition at transposable elements in mouse ESCs; 3, SETB1silences MERVLs to prevent 2CLC-state acquisition in mouse ESCs. The strength of the current work is the demonstration that this is not due to a general transcriptional collapse; but otherwise, the findings are not surprising. The well-known (several Nature papers of years ago) crosstalk between m6A RNA modification and H3K9me3 in preventing 2CLC generation also partly compromises the novelty of this work.

We thank the Reviewer for appreciating the technical quality of our work. Regarding novelty, please consider that prior work in ES cells included contradictory findings (please see our Introduction). Prior embryology work (please see our Introduction) did not explain the preimplantation-stage phenotype. We highly appreciate those earlier works. Our work here answers the expectations drawn from prior studies and unequivocally shows that SETDB1 carries out the developmentally essential function of suppressing MERVLs and the 2-cell program in the mouse embryo.

(2) The conclusions regarding H3K9me3 deposition are inferred based on previously reported datasets, but there is no direct demonstration.

Dynamic H3K9me3 deposition is displayed at MERVL LTRs during the early2c-late2c-2c-4c-8c-morula window (Figures 4C, 4D, 4E, 6D, 6E and Figure S6) from a published work that has very high-quality data. We agree that demonstrating loss off H3K9me3 in Setdb1^mat-/+ embryos would confirm that the H3K9me3 histone methyltransferase function of SETDB1 (as opposed to any, yet unidentified, non-HMT specific activity of SETDB1) is responsible for shutting down MERVL LTRs. However, ChIP-seq, CUT&RUN, or similar assays are not feasible due to the rarity of Setdb1^mat-/+ embryos.

(3) The detection of chimeric transcripts is somewhat unreliable using short-read sequencing.

We used single embryo total RNA-seq and we report detecting chimeric transcripts (Table S6), which is considered more reliable than mRNA-seq for detecting chimeric transcripts, because many are not polyadenylated. We acknowledge, however, that long-read sequencing, which recently is becoming available, but which is still very expensive, is currently the most powerful method for detecting chimeric transcripts. This, however, does not affect the major conclusions or the significance of our work.

EC designates WhatsApp as a VLOP under the DSA. Meta has until May to establish and show compliance.

This is based on the Channels functionality (the online platform part, next to the private messaging part), as it reached the threshold 45M users in the EU.

Can we update text to something more general

fix stretched background image image

eLife Assessment

This study presents a method for expressing single-stranded DNA fluorescent aptamers in E. coli using a retron-based strategy. The evidence supporting the successful expression and folding of DNA aptamers is solid, with clear demonstration of fluorescence after extraction, though the aptamers do not function in living cells. The method represents an important technical advance that will likely become standard for DNA aptamer expression in bacterial systems.

Reviewer #1 (Public review):

Summary:

The authors use an interesting expression system called a retron to express single-stranded DNA aptamers. Expressing DNA as a single-stranded sequence is very hard - DNA is naturally double stranded. However, the successful demonstration by the authors of expressing Lettuce, which is a fluorogenic DNA aptamer, allowed visual demonstration of both expression and folding, but only after extraction in cells, but not in vivo (possibly because of the low fluorescence of Lettuce, or perhaps more likely, some factor in cells preventing Lettuce fluorescence). This method will likely be the main method for expressing and testing DNA aptamers of all kinds, including fluorogenic aptamers like Lettuce and the future variants / alternatives.

Strengths:

This has an overall simplicity which will lead to ready adoption. I am very excited about this work. People will be able to express other fluorogenic aptamers or DNA aptamers tagged with Lettuce with this system.

Weaknesses:

Some things could be addressed/shown in more detail, e.g. half-lives of different types of DNA aptamers and ways to extend this to mammalian cells.

Reviewer #2 (Public review):

Summary:

This manuscript explores a DNA fluorescent light up aptamer (FLAP) with the specific goal of comparing activity in vitro to that in bacterial cells. In order to achieve expression in bacteria, the authors devise an expression strategy based on retrons and test four different constructs with the aptamer inserted at different points in the retron scaffold.

The initial version of this manuscript made several claims about the fluorescence activity of the aptamers in cells, and the observed fluorescence signal has now been found to result from cellular auto-fluorescence. Thus, all data regarding the function of the aptamers in cells have been removed.

Negative data are important to the field, especially when it comes to research tools that may not work as many people think that they will. Thus, there would have been an opportunity here for the authors to dig into why the aptamers don't seem to work in cells.

In the absence of insight into the negative result, the manuscript is now essentially a method for producing aptamers in cells. If this is the main thrust, then it would be beneficial for the authors to clearly outline why this is superior to other approaches for synthesizing aptamers.

Author response:

The following is the authors’ response to the original reviews

Comment to both reviewers:

We are very grateful for the thoughtful and constructive comments from both reviewers. During the revision, and in direct response to these comments, we performed additional control experiments for the cellular fluorescence measurements. These new data revealed that the weak increase in green fluorescence reported in our original submission does not depend on retron-expressed Lettuce RT-DNA or the DFHBI-1T fluorophore, but instead reflects stress-induced autofluorescence of E. coli (e.g. upon inducer and antibiotic treatment).

We also benchmarked the fluorogenic properties of Lettuce against the RNA FLAP Broccoli and found that Lettuce is ~100-fold less fluorogenic under optimal in vitro conditions. Consequently, with the currently available, in vitro- but not in vivo-optimized Lettuce variants, intracellular fluorescence cannot be reliably detected by microscopy or flow cytometry. We have therefore removed the original flow cytometry / and in-culture-fluorescence data and no longer claim detectable intracellular Lettuce fluorescence.

In the revised manuscript, we now directly demonstrate that retron-produced Lettuce RT-DNA can be purified from cells and remains functional ex vivo with a gel-based fluorophore-binding assays. Together, these data clarify the current limitations of DNA-based FLAPs for in vivo imaging, while still establishing retrons as a viable platform for intracellular production of functional DNA aptamers.

Reviewer #1 (Public Review):

Summary:

The authors use an interesting expression system called a retron to express single-stranded DNA aptamers. Expressing DNA as a single-stranded sequence is very hard - DNA is naturally double-stranded. However, the successful demonstration by the authors of expressing Lettuce, which is a fluorogenic DNA aptamer, allowed visual demonstration of both expression and folding. This method will likely be the main method for expressing and testing DNA aptamers of all kinds, including fluorogenic aptamers like Lettuce and future variants/alternatives.

Strengths:

This has an overall simplicity which will lead to ready adoption. I am very excited about this work. People will be able to express other fluorogenic aptamers or DNA aptamers tagged with Lettuce with this system.

We thank the reviewer for their thoughtful assessment and appreciate their encouraging remarks.

Weaknesses:

Several things are not addressed/shown:

(1) How stable are these DNA in cells? Half-life?

We thank the reviewer for this insightful question.

Retron RT-DNA forms a phage surveillance complex with the associated RT and effector protein[1-4]. Moreover, considering the unique ‘closed’ structure of RT-DNA[5] (with the ends of msr and msd bound either by 2’-5’ linkage and base paired region) and its noncoding function, we hypothesized that the RT-DNA must be exceptionally stable. Nevertheless, we attempted to determine half-life of the RT-DNA using qPCR for Eco2 RT-DNA. To this end, we designed an assay where we would first induce RT-DNA expression, use the induced cells to start a fresh culture without the inducers. We would then take aliquots from this fresh culture at different timepoints and determine RT-DNA abundance by qPCR.

We induced RT-DNA expression of retron Eco2 in BL21AI cells as described in the Methods. After overnight induction, cells were washed to remove IPTG and arabinose, diluted to OD₆₀₀ = 0.2 into fresh LB without inducers, and grown at 37°C. At the indicated time points, aliquots corresponding to OD₆₀₀ = 0.1 were boiled (95°C, 5 min), and 1 µL of the lysate was used as template in 20 µL qPCR reactions (see revised Methods for details).

Assuming RT-DNA degradation would occur by active degradation mechanisms (nuclease-mediated degradation) and dilution (cell growth and division), we determined the rate of degradation by the following equation

where  is the degradation rate constant and the ratio is the dilution factor which takes into account dilution by cell division. OD₆₀₀(t) was determined by fitting the OD₆₀₀ measurements by the following the equation describing logistic growth:

Which yields the plots shown in Figure 2–figure supplement 1.

After substituting OD₆₀₀(t) by the function in equation (2), we fit the experimental data for the fold-change of the RT-DNA to equation (1). Interestingly, the best fit (red) was obtained with a  converging towards zero suggesting that the half-life of the RT-DNA is beyond the detection limit of our assay. To showcase typical half-lives of RNA, which are in the range of minutes in growing E. coli cells[6], we refitted the data using constant half-life of 15 and 30 minutes. In both cases, simulated curve deviated significantly from the experimental data further confirming that the half-life of the RT-DNA is probably orders of magnitude higher than the doubling time of E. coli under these optimal conditions. While we cannot exclude that the RT-DNA is still produced as a result of promotor leakiness, but we expect this effect to be low as the expression of RT-DNA in E. coli AI cells requires both the presence of IPGT and arabinose, which were thoroughly removed before inoculating the growth media with the starter culture. Overall, our data therefore argues for an exceptional stability of the RT-DNA in growing bacterial cells.

We have now included this new experimental data in the supplementary information.

(2) What concentration do they achieve in cells/copy numbers? This is important since it relates to the total fluorescence output and, if the aptamer is meant to bind a protein, it will reveal if the copy number is sufficient to stoichiometrically bind target proteins. Perhaps the gels could have standards with known amounts in order to get exact amounts of aptamer expression per cell?

The copy number of RT-DNA can be estimated based on the qPCR experiments. We use a pET28a plasmid, which is low-copy with typical copy number 15-20 per cell[7]. We determined the abundance of RT-DNA over plasmid/RT-DNA, upon induction, to be 8-fold, thereby indicating copy number of Eco2 RT-DNA to be roughly around 100-200. Assuming an average aqueous volume of E. coli of 1 femtoliter[6], the concentration of RT-DNA is ~250-500 nM. We have added this information to the revised version of the manuscript.

(3) Microscopic images of the fluorescent E. coli - why are these not shown (unless I missed them)? It would be good to see that cells are fluorescent rather than just showing flow sorting data.

In the original submission, we used flow cytometry as an orthogonal method to quantify the fluorescence output of intracellularly expressed Lettuce aptamer, anticipating that it would provide high-throughput, quantitative information on a large population of cells. During the revision, additional controls revealed that the weak increase in fluorescence we had previously attributed to Lettuce expression was in fact a stress-induced autofluorescence signal that occurred independently of retron RT-DNA and DFHBI-1T. We have therefore removed these data from the manuscript and no longer claim detectable intracellular Lettuce fluorescence.

To understand this limitation, we compared the in vitro fluorescence of Lettuce with that of the RNA FLAP Broccoli, which is commonly used for RNA live-cell imaging. Under optimal in vitro conditions, Lettuce shows ~100-fold lower fluorescence output than Broccoli (new Figure 3–figure supplement 5). Given this poor fluorogenicity and the low intracellular concentration of retron RT-DNA (now derived from the qPCR experiments), we conclude that the current Lettuce variants are below the detection threshold for in vivo imaging in our system. We now explicitly discuss this limitation and the need for further (in vivo) evolution of DNA-based FLAPs in the revised manuscript.

(4) I would appreciate a better Figure 1 to show all the intermediate steps in the RNA processing, the subsequent beginning of the RT step, and then the final production of the ssDNA. I did not understand all the processing steps that lead to the final product, and the role of the 2'OH.

We thank the referee for this comment. We have now made changes to Figure 1, showing the intermediate steps as well as a better illustration of the 2’-5’ linkage.

(5) I would like a better understanding or a protocol for choosing insertion sites into MSD for other aptamers - people will need simple instructions.

We appreciate the reviewer for bringing up this important point. We simulated the ssDNA structure using Vienna RNA fold with DNA parameters. Based on the resulting structure, we inserted Lettuce sequence in the single stranded and/or loop regions to minimise interference with the native msd fold. We have now included this information in the description of Figure 3.

(6) Can the gels be stained with DFHBI/other dyes to see the Lettuce as has been done for fluorogenic RNAs?

Yes. We have now included experiments where we performed in-gel staining with DFHBI-1T for both chemically synthesized Eco2-Lettuce surrogates as well as the heterologously expressed Eco2-Lettuce RT-DNA. We have added this data to the revised Figure 3 (panel C and E).

(7) Sometimes FLAPs are called fluorogenic RNA aptamers - it might be good to mention both terms initially since some people use fluorogenic aptamer as their search term.

We thank the referee for this useful suggestion. We have now included both terms in the introduction of the revised version.

(8) What E coli strains are compatible with this retron system?

Experimental and bioinformatic analysis have shown that retrons abundance varies drastically across different strains of E. coli[8-10]. For example, in an experimental investigation of 113 independent clinical isolates of E. coli, only 7 strains contained RT-DNA[8]. In our experiments, we have found that BL21AI strain is compatible with plasmid-borne Eco2. The fact that this strain has a native retron system (Eco1) allowed us to use it as internal standard. However, we were also able express Eco2 RT-DNA in conventional lab strains such as E. coli Top 10 (data not shown), indicating both ncRNA and the RT alone are sufficient for intracellular RT-DNA synthesis.

(9) What steps would be needed to use in mammalian cells?

We appreciate the reviewer’s thoughtful inquiry. Expression of retrons has been demonstrated in mammalian cells by Mirochnitchenko et al[11] and Lopez et al[12]. For example, Lopez et al demonstrate expression of retrons in mammalian cell lines using the Lipofectamine 3000 transfection protocol (Invitrogen) and a PiggyBac transposase system[12]. We also mention this in the discussion section of the revised manuscript. Expression of retron-encoded DNA aptamers in mammalian cells should be possible with these systems.

(10) Is the conjugated RNA stable and does it degrade to leave just the DNA aptamer?

We are grateful to the reviewer for their perceptive question. This usually depends on the specific retron system. For example, in case of certain retron systems such as retron Sen2, Eco4 and Eco7, the RNA is cleaved off, leaving behind just the ssDNA. In our case, with retron Eco2, the RNA remains stably bound to the ssDNA, thereby maintaining a stable hybrid RNA-DNA structure[10,13]. During the extraction of RT-DNA, the conjugated RNA is degraded during the RNase digestion step, and therefore is not visible in the gel images.

Reviewer #2 (Public Review):

Summary:

This manuscript explores a DNA fluorescent light-up aptamer (FLAP) with the specific goal of comparing activity in vitro to that in bacterial cells. In order to achieve expression in bacteria, the authors devise an expression strategy based on retrons and test four different constructs with the aptamer inserted at different points in the retron scaffold. They only observe binding for one scaffold in vitro, but achieve fluorescence enhancement for all four scaffolds in bacterial cells. These results demonstrate that aptamer performance can be very different in these two contexts.

Strengths:

Given the importance of FLAPs for use in cellular imaging and the fact that these are typically evolved in vitro, understanding the difference in performance between a buffer and a cellular environment is an important research question.

The return strategy utilized by the authors is thoughtful and well-described.

The observation that some aptamers fail to show binding in vitro but do show enhancement in cells is interesting and surprising.

We appreciate the reviewer’s thorough assessment.

Weaknesses:

This study hints toward an interesting observation, but would benefit from greater depth to more fully understand this phenomenon. Particularly challenging is that FLAP performance is measured in vitro by affinity and in cells by enhancement, and these may not be directly proportional. For example, it may be that some constructs have much lower affinity but a greater enhancement and this is the explanation for the seemingly different performance.

We thank the reviewer for this insightful comment. In response, we conducted a series of additional control experiments to better understand the apparent discrepancy between the in vitro and in vivo data. These experiments revealed that the previously reported increase in intracellular green fluorescence is independent of retron-expressed Lettuce RT-DNA and DFHBI-1T, and instead reflects stress-induced autofluorescence of E. coli upon inducer and antibiotic treatment. Our original negative controls (empty wild-type Eco2, uninduced cells in the presence of DFHBI-1T) were therefore not sufficient to rule out this effect.

As a consequence, we have removed the earlier FACS data from the manuscript and no longer claim detectable intracellular Lettuce fluorescence. The reviewer’s comment prompted us to re-examine the fluorogenicity of our constructs in vitro. We found that the 4Lev4 construct folds poorly and produces very low signal in in-gel staining assays with DFHBI-1T. In contrast, the 8LE variant (8-nt P1 stem at position v4) shows the highest fluorescence in these in-gel assays (new Figure 3C). Nevertheless, even this construct remains 100-fold less fluorogenic than the RNA-based FLAP Broccoli (new Figure 3–figure supplement 5), and we were unable to detect its intracellular fluorescence above background (new Figure 3–figure supplement 4).

To still directly demonstrate that retron-embedded Lettuce domains that are synthesized under intracellular conditions are functional, we modified our strategy in the revision and purified the expressed RT-DNA from E. coli, followed by in-gel staining with DFHBI-1T (new Figure 3E). Despite the challenge of obtaining sufficient amounts of ssDNA, this ex vivo approach clearly shows that the retron-produced Lettuce RT-DNA retains fluorogenic activity.

The authors only test enhancement at one concentration of fluorophore in cells (and this experimental detail is difficult to find and would be helpful to include in the figure legend). This limits the conclusions that can be drawn from the data and limits utility for other researchers aiming to use these constructs.

We appreciate this excellent suggestion. In the original experiments, the DFHBI-1T concentration in cells was chosen based on published conditions for live-cell imaging of the Broccoli RNA aptamer[14], which is substantially more fluorogenic than Lettuce. Motivated by the reviewer’s comment, we explored different fluorophore concentrations and additional controls to optimize the in vivo readout. These experiments showed that the weak intracellular fluorescence signal is dominated by stress-induced autofluorescence[15] (possibly due to the weaker antitoxin activity of the modified msd) and does not depend on the presence of Lettuce RT-DNA or DFHBI-1T.

Given the combination of low Lettuce fluorogenicity and low intracellular RT-DNA levels, we concluded that varying the fluorophore concentration alone does not provide a meaningful way to deconvolute these confounding factors in cells. Instead, we shifted our focus to a more direct assessment of Lettuce activity: we now demonstrate that retron-produced Lettuce RT-DNA can be purified from E. coli and retains fluorogenic activity in an in-gel staining assay with DFHBI-1T (new Figure 3E). We believe this revised strategy provides a clearer and more quantitative characterization of the system’s capabilities and limitations than the initial in vivo fluorescence measurements.

The FLAP that is used seems to have a relatively low fluorescence enhancement of only 2-3 fold in cells. It would be interesting to know if this is also the case in vitro. This is lower than typical FLAPs and it would be helpful for the authors to comment on what level of enhancement is needed for the FLAP to be of practical use for cellular imaging.

In the revised manuscript, we directly address this point by comparing the in vitro fluorescence of Lettuce (DNA) and Broccoli (RNA) under optimized buffer conditions. These experiments show that Broccoli is nearly two orders of magnitude more fluorogenic than Lettuce (new Figure 3-figure supplement 5). Thus, the low enhancement observed for Lettuce in cells is consistent with its intrinsically poor fluorogenicity in vitro.

Based on this comparison and on reported properties of RNA FLAPs such as Broccoli, we conclude that robust cellular imaging typically requires substantially higher fluorogenicity and dynamic range than currently provided by DNA-based Lettuce. In other words, under our conditions, Lettuce is close to or below the practical detection limit for in vivo imaging, whereas Broccoli performs well. We now explicitly state in the Discussion that further evolution and optimization of DNA FLAPs will be required to achieve fluorescence enhancements that are suitable for routine cellular imaging, and we position our work as a first demonstration that functional DNA aptamers can be produced in cells via retrons, while also delineating the current sensitivity limits.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Addgene accession numbers are not listed - how is this plasmid obtained?

The sequence was obtained from Millman et al[16], and ordered as gblock from IDT. The gblock was then cloned into a pET28a vector by Gibson assembly. We have now included this in the methods section.

Reviewer #2 (Recommendations For The Authors):

Page 2, line 40 - FLAPS should be FLAPs

We have corrected this typo in the revised version.

References

(1) Rousset, F. & Sorek, R. The evolutionary success of regulated cell death in bacterial immunity. Curr. Opin. Microbiol. 74, 102312; 10.1016/j.mib.2023.102312 (2023).

(2) Gao, L. et al. Diverse enzymatic activities mediate antiviral immunity in prokaryotes. Science 369, 1077–1084; 10.1126/science.aba0372 (2020).

(3) Carabias, A. et al. Retron-Eco1 assembles NAD+-hydrolyzing filaments that provide immunity against bacteriophages. Mol. Cell 84, 2185-2202.e12; 10.1016/j.molcel.2024.05.001 (2024).

(4) Wang, Y. et al. DNA methylation activates retron Ec86 filaments for antiphage defense. Cell Rep. 43, 114857; 10.1016/j.celrep.2024.114857 (2024).

(5) Wang, Y. et al. Cryo-EM structures of Escherichia coli Ec86 retron complexes reveal architecture and defence mechanism. Nat. Microbiol. 7, 1480–1489; 10.1038/s41564-022-01197-7 (2022).

(6) Milo, R. & Phillips, R. Cell biology by the numbers (Garland Science Taylor & Francis Group, New York NY, 2016).

(7) Sathiamoorthy, S. & Shin, J. A. Boundaries of the origin of replication: creation of a pET-28a-derived vector with p15A copy control allowing compatible coexistence with pET vectors. PLOS ONE 7, e47259; 10.1371/journal.pone.0047259 (2012).

(8) Sun, J. et al. Extensive diversity of branched-RNA-linked multicopy single-stranded DNAs in clinical strains of Escherichia coli. Proc. Natl. Acad. Sci. U. S. A. 86, 7208–7212; 10.1073/pnas.86.18.7208 (1989).

(9) Rice, S. A. & Lampson, B. C. Bacterial reverse transcriptase and msDNA. Virus Genes 11, 95–104; 10.1007/BF01728651 (1995).

(10) Simon, A. J., Ellington, A. D. & Finkelstein, I. J. Retrons and their applications in genome engineering. Nucleic Acids Res. 47, 11007–11019; 10.1093/nar/gkz865 (2019).

(11) Mirochnitchenko, O., Inouye, S. & Inouye, M. Production of single-stranded DNA in mammalian cells by means of a bacterial retron. J. Biol. Chem. 269, 2380–2383; 10.1016/S0021-9258(17)41956-9 (1994).

(12) Lopez, S. C., Crawford, K. D., Lear, S. K., Bhattarai-Kline, S. & Shipman, S. L. Precise genome editing across kingdoms of life using retron-derived DNA. Nat. Chem. Biol. 18, 199–206; 10.1038/s41589-021-00927-y (2022).

(13) Lampson, B. C. et al. Reverse transcriptase in a clinical strain of Escherichia coli: production of branched RNA-linked msDNA. Science 243, 1033–1038; 10.1126/science.2466332 (1989).

(14) Filonov, G. S., Moon, J. D., Svensen, N. & Jaffrey, S. R. Broccoli: rapid selection of an RNA mimic of green fluorescent protein by fluorescence-based selection and directed evolution. J. Am. Chem. Soc. 136, 16299–16308; 10.1021/ja508478x (2014).

(15) Renggli Sabine, Keck Wolfgang, Jenal Urs & Ritz Daniel. Role of Autofluorescence in Flow Cytometric Analysis of Escherichia coli Treated with Bactericidal Antibiotics. J. Bacteriol. 195, 4067–4073; 10.1128/jb.00393-13. (2013).

(16) Millman, A. et al. Bacterial Retrons Function In Anti-Phage Defense. Cell 183, 1551-1561.e12; 10.1016/j.cell.2020.09.065 (2020).

In so many ways this makes so little sense to me. I would assume it’s one of those cases where that functionality is an artifact of earlier versions. However, the fact this issue went unaddressed shows where priorities are.

My question is how were people supposed to find the studies to begin with? If they’re generally accessible and do not have demographic validations what was the actual plan for getting a significant outreach?

AI can be intelligent but there is times when it can be super wrong like the sentence states. It can be a 50/50 chance of trusting the program; it could be completely wrong at times so it would be better to try to do research on your own rather than relaying on the program.

How do we as data scientists balance not wasting our time attempting to connect irrelevant factors together and not letting our own assumptions influence our findings. It seems incredibly difficult to understand how our own perceptions is kind of a limiting factor.

This method being used was an interesting factor as it implies on each and one of us. For example whether if its the choice of stepping outside or staying inside, you may benefit from both but also miss an opportunity.

eLife Assessment

This study offers important insights into how entorhinal and hippocampal activity support human thinking in feature spaces. It replicates hexagonal symmetry in entorhinal cortex, reports a novel three-fold symmetry in both behavior and hippocampal signals, and links these findings with a computational model. The task and analyses are sophisticated, and the results appear convincing and of broad interest to neuroscientists.

Reviewer #1 (Public review):

Summary:

Zhang and colleagues examine neural representations underlying abstract navigation in entorhinal cortex (EC) and hippocampus (HC) using fMRI. This paper replicates a previously identified hexagonal modulation of abstract navigation vectors in abstract space in EC in a novel task involving navigating in a conceptual Greeble space. In HC, the authors identify a three-fold signal of the navigation angle. They also use a novel analysis technique (spectral analysis) to look at spatial patterns in these two areas and identify phase coupling between HC and EC. Interestingly, the three-fold pattern identified in the hippocampus explains quirks in participants' behavior where navigation performance follows a three-fold periodicity. Finally, the authors propose a EC-HPC PhaseSync Model to understand how the EC and HC construct cognitive maps. The wide array and creativity of the techniques used is impressive but because of their unique nature, the paper would benefit from more details on how some of these techniques were implemented.

Reviewer #2 (Public review):

The authors report results from behavioral data, fMRI recordings, and computer simulations during a conceptual navigation task. They report 3-fold symmetry in behavioral and simulated model performance, 3-fold symmetry in hippocampal activity, and 6-fold symmetry in entorhinal activity (all as a function of movement directions in conceptual space). The analyses seem thoroughly done, and the results and simulations are very interesting.

[Editors' note: this version was assessed by the editors without consulting the reviewers further.]

Author response:

The following is the authors’ response to the previous reviews

Public Reviews:

Reviewer #1 (Public review):

Summary:

Zhang and colleagues examine neural representations underlying abstract navigation in entorhinal cortex (EC) and hippocampus (HC) using fMRI. This paper replicates a previously identified hexagonal modulation of abstract navigation vectors in abstract space in EC in a novel task involving navigating in a conceptual Greeble space. In HC, the authors identify a three-fold signal of the navigation angle. They also use a novel analysis technique (spectral analysis) to look at spatial patterns in these two areas and identify phase coupling between HC and EC. Interestingly, the three-fold pattern identified in the hippocampus explains quirks in participants' behavior where navigation performance follows a three-fold periodicity. Finally, the authors propose a EC-HPC PhaseSync Model to understand how the EC and HC construct cognitive maps. The wide array and creativity of the techniques used is impressive but because of their unique nature, the paper would benefit from more details on how some of these techniques were implemented.

Comments on revisions:

Most of my concerns were adequately addressed, and I believe the paper is greatly improved. I have two more points. I noticed that the legend for Figure 4 still refers to some components of the previous figure version, this should be updated to reflect the current version of the figure. I also think the paper would benefit from more details regarding some of the analyses.

Specifically, the phase-amplitude coupling analysis should have a section in the methods which should be sure to clarify how the BOLD signals were reconstructed.

(1)“…I noticed that the legend for Figure 4 still refers to some components of the previous figure version, this should be updated to reflect the current version of the figure…”.

Thank you for pointing this out. We have revised the legend of Figure 4 by removing the significance notation “***: p < 0.001”, which referred to elements from a previous version of the figure.

(2)“…I also think the paper would benefit from more details regarding some of the analyses. Specifically, the phase-amplitude coupling analysis should have a section in the methods which should be sure to clarify how the BOLD signals were reconstructed”.

We agree and appreciate the reviewer’s helpful suggestion. We have added a dedicated subsection entitled “Phase–amplitude coupling” to the Materials and Methods, in which we provide a detailed description of how the EC and HPC BOLD signals were reconstructed and how the coupling analysis was implemented. Correspondingly, we refined the description of this analysis in the Results section under “Phase synchronization between the HPC and EC activity”. The revised sections have been included below for your convenience. 

Materials and Methods: Phase–amplitude coupling

To quantify the spatial peak relationship between EC and HPC BOLD activity, we implemented a cross-frequency amplitude–phase coupling analysis in the directional space (Canolty et al., 2006). Rather than analyzing raw BOLD signals, we reconstructed 6-fold EC activity and 3-fold HPC activity in each voxel using sinusoidal modulation weights (β_sine and β_cosine) estimated from the raw BOLD signals. Specifically, activity was modeled as β_cosinecos(kθ) + β_sinesin(kθ), where k denotes the rotational symmetry. This approach selectively captures the hypothesized spatial symmetries of neural activity (e.g., 6-fold or 3-fold periodicity) as a function of movement direction. For this coupling analysis, we used participants’ original movement directions (i.e., without applying orientation calibration). The reconstructed 6-fold EC and 3-fold HPC activity were then converted into analytic representations using the Hilbert transform, yielding the instantaneous phase of the HPC (ϕ_HPC) and the amplitude envelope of the EC (A_ERC). HPC phases were classified into nine bins. The composite analytic signal, defined as z = A_ERCe^iϕHPC, was used to compute the modulation index M (Canolty et al., 2006), defined as the absolute value of the mean of z values, quantifying the scalar coupling strength between EC amplitude and HPC phase within each bin. A surrogate dataset, a null distribution of the modulation indices (M^-), was generated by spatially offsetting the EC amplitude relative to the HPC phase across all possible spatial lags. The mean of this surrogate distribution was used as the baseline reference against which the observed coupling strength was compared.

Results: Phase synchronization between the HPC and EC activity

To examine whether the spatial phase structure in one region could predict that in another, we tested whether the orientations of the 6-fold EC and 3-fold HPC periodic activities, estimated from odd-numbered sessions using sinusoidal modulation with rotationally symmetric parameters, were correlated across participants. A cross-participant circular correlation was conducted between the spatial phases of the two areas to quantify the spatial correspondence of their activity patterns (EC: purple dots; HPC: green dots) (Jammalamadaka & Sengupta, 2001). The analysis revealed a significant circular correlation (Fig. 4a; r = 0.42, p < 0.001), as reflected by the continuous color progression across the participants (i.e., the colored lines connecting each pair of the EC and HPC dots in Fig. 4a), suggesting that participants with smaller hippocampal phases (green, outer ring) tended to have smaller entorhinal phases (purple, inner ring), and vice versa.

In addition to the across-participant phase correlation, we further examined the spatial alignment between the 6-fold EC and 3-fold HPC activity patterns. Given that the spatial phase of the HPC is hypothesized to depend on EC projections, particularly along the three primary axes of the hexagonal code, we examined whether the periodic activities of the EC and HPC were spatially peak-aligned. Notably, unlike previous studies that focused on temporal coherence of neural oscillations (Buzsaki, 2006; Maris et al., 2011; Friese et al., 2013), our analysis focused on periodic coupling between brain areas in the directional space. To test spatial peak alignment between EC and HPC, a cross-frequency spatial coupling analysis (adapted from the amplitude–phase coupling framework; Canolty et al., 2006) was employed to identify at which HPC phase the EC exhibited maximal amplitude modulation. If the activities of both areas were peak-aligned (i.e., no peak offset), a strong coupling at phase 0 of the HPC would be expected as shown by the one-cyclebased schema in Fig. 4b. In doing so, the instantaneous phase of the HPC and the amplitude envelope of the EC were extracted from the reconstructed activity using the Hilbert transform (see methods for details). HPC phases were classified into nine bins, and the modulation index (M), quantifying the scalar coupling strength between EC amplitude and HPC phase, was computed within each bin. As a result, significant coupling was observed in the bin centered at phase 0 of the HPC (Fig. 4c; t(32) = 2.57, p = 0.02, Bonferroni-corrected across tests; Cohen’s d = 0.45). In contrast, no significant coupling was found in other bins (p > 0.05). To rule out the possibility that the observed coupling was driven by a potential harmonic (integer multiple) relationship between the 3-fold and 6-fold periodicities, we additionally conducted control analyses using 9-fold and 12-fold EC components. However, no significant coupling was observed in these controls (Fig. 4c; p > 0.05). Together, these results confirmed selective alignments of spatial peaks between the 6fold EC and 3-fold HPC periodicity in the conceptual direction domain.

Reviewer #2 (Public review):

The authors report results from behavioral data, fMRI recordings, and computer simulations during a conceptual navigation task. They report 3-fold symmetry in behavioral and simulated model performance, 3-fold symmetry in hippocampal activity, and 6-fold symmetry in entorhinal activity (all as a function of movement directions in conceptual space). The analyses seem thoroughly done, and the results and simulations are very interesting.

We thank the reviewer for the positive assessment of our work.

We thank both reviewers again for their constructive and insightful feedback, which has substantially strengthened the manuscript.

DOI: 10.1016/j.celrep.2025.116896

Resource: RRID:IMSR_JAX:000664

Curator: @areedewitt04

SciCrunch record: RRID:IMSR_JAX:000664

What is this?

DOI: 10.1002/1878-0261.70205

Resource: The Cancer Genome Atlas (RRID:SCR_003193)

Curator: @scibot

SciCrunch record: RRID:SCR_003193

What is this?

I find this to be super cool, since I feel that seeing archives in person is actually amazing, since your seeing everything in real life.

I find Malala to be a huge inspiration to me, and I feel that she is strong for what she has done and I look up to her.

I feel that the setting gives the reader a better imagination of what's going on in my opinion.

I can agree with this, since I feel that people have their own preferences to characters.

This shows that anyone can share their story about learning literacy in the DALN. I like that it includes all kinds of people and experiences, making it a place to learn from others and see different ways people read, write, and communicate.

This part explains that every story has a problem that drives the action and a solution that finishes it. It helps me understand how to make my own stories interesting by showing challenges and how they get solved.

I like how this part shows that good storytelling uses our senses to make the story feel real. It helps us picture and experience what’s happening, not just read about it. I can see how adding these details can make my own writing more engaging.

For me this means we speak and write differently depending on where we are or who we are talking to. In school and work, we’ll learn the right way to use language in each situation. It shows that knowing when to use different styles is part of becoming a good speaker.

This part shows that literacy has changed over time. Now it means being able to communicate well in many ways, not just through books and writing. This connects to how we learn and share information today.

This perspective is incredibly telling for how disconnected these people are from the world around them. Their relationship with the internet is the exact same but with a nihilistic mindset.

This example seems more like harmless fun, because it isn't hurting anyone. The worst that can happen is that you mispronounce a word, and then I hope someone will tell you. This is where I feel like trolling should stay. I can see the argument in people being misled and being shamed for not knowing the word, especially if someone isn't educated (child), but it's not actually keeping someone out of a community, bullying or provoking outrage.

Comparing these two examples (RIP trolling and protest trolling) makes the stark differences between different kinds of trolling. Trolling, like many other things on the internet, isn’t necessarily good or bad, and it is driven by intention. It can be used for good and for bad.

are they really innate?

Some of my question is a tad rhetoric as I suspect that this current book is making an argument that there is a genetic basis for why/how it all works the way it does. It's also a question I know that Kelly has had buzzing around for a while.

Large swaths of these practices have been taught and handed down from one person to another and from one group to another for millennia as well, but the other question is if they've been independently re-discovered across time or if they've changed/evolved the way in which languages have shifted over these same time frames.

With behaviors like these being prevalent throughout all of human history is hard to imagine how we limit that harm. How do we design new systems that can account for seemingly ever present behaviors?

This way of trolling the mewbies seems like a power play or some sort of online bullying , that is excused by "trolling" I wonder if it's just an excuse to be mean, because if it happened in real life, I don't think people would find as amusing.

There’s lots of examples of widespread/mass trolling on 4chan changing entire communities or corners of the internet. When interacting with an individual troll, the consequences don’t go much further than mild annoyance, but when several people come together to collectively troll, they can cause real world consequences.

eLife Assessment

This valuable study introduces a model to help researchers understand how multivariate processes affect observed relationships in genetic data. The authors provide a tool to estimate model parameters. Overall, the authors provide solid evidence that their tool can obtain median-unbiased estimates of the true parameters when using simulated data under the model.

Reviewer #1 (Public review):

Summary:

The authors develop a multivariate extension of SEM models incorporating transmitted and non-transmitted polygenic scores to disentangle genetic and environmental intergenerational effects across multiple traits. Their goal is to enable unbiased estimation of cross-trait vertical transmission, genetic nurture, gene-environment covariance, and assortative mating within a single coherent framework. By formally deriving multivariate path-tracing rules and validating the model through simulation, they show that ignoring cross-trait structure can severely bias both cross- and within-trait estimates. The proposed method provides a principled tool for studying complex gene-environment interplay in family genomic data.

Strengths:

It has become apparent in recent years that multivariate processes play an important role in genetic effects that are studied (e.g., Border et al., 2022), and these processes can affect the interpretation of these studies. This paper develops a comprehensive framework for polygenic score studies using trio data. Their model allows for assortative mating, vertical transmission, gene-environment correlation, and genetic nurture. Their study makes it clear that within-trait and cross-trait influences are important considerations. While their exposition and simulation focus on a bivariate model, the authors point out that their approach can be easily extended to higher-dimensional applications.

Weaknesses:

(1) My primary concern is that the paper is very difficult to follow. Perhaps this is inevitable for a model as complicated as this one. Admittedly, I have limited experience working with SEMs, so that might be partly why I really struggled with this paper, but I ultimately still have many questions about how to interpret many aspects of the path diagram, even after spending a considerable amount of time with it. Below, I will try to point out the areas where I got confused (and some where I still am confused). If the authors choose to revise the paper, clarifying some of these points would substantially broaden the paper's accessibility and impact.

(1a) Figure 1 contains a large number of paths and variable names, and it is not always apparent which variables correspond to which paths. For example, at a first glance, the "k + g_c" term next to the "T_m" box could arguably correspond to any of the four paths near it. Disentangling this requires finding other, more reasonable variables for the other lines and sifting through the 3 pages of tables describing the elements of the figure.

(1b) More hand-holding, describing the different parameters in the model, would help readers who don't have experience with SEMs. For example, many parameters show up several times (e.g., delta, a, g_c, i_c, w) and describing what these parameters are and why they show up several times would help. Some of this information is found in the tables (e.g., "Note: [N]T denotes either NT or T, as both share the same matrix content"), though I don't believe it is explained what it means to "share the same matrix content."

(1c) Relatedly, descriptions of the path tracing were very confusing to me. I was relieved to see the example on the bottom of page 10 and top of page 11, but then as I tried to follow the example, I was again confused. Because multiple paths have the same labels, I was not able to follow along which exact path from Figure 1 corresponded to the elements of the sum that made up Theta_{Tm}. Also, based on my understanding of the path-tracing rules described, some paths seemed to be missing. After a while, I think I decided that these paths were captured by the (1/2)*w term since that term didn't seem to be represented by any particular path in the figure, but I'm still not confident I'm right. In this example, rather than referring to things like "four paths through the increased genetic covariance from AM", it might be useful to identify the exact paths represented by indicating the nodes those paths go through. If there aren't space constraints, the authors might even consider adding a figure which just contains the relevant paths for the example

(1d) The paper has many acronyms and variable names that are defined early in the paper and used throughout. Generally, I would limit acronyms wherever possible in a setting like this, where readers are not necessarily specialists. For the variables, while the definitions are technically found in the paper, it would be useful to readers if they were reminded what the variables stood for when they are referred to later, especially if that particular variable hasn't been mentioned for a while. As I read, I found myself constantly having to scroll back up to the several pages of figures and tables to remind myself of what certain variables meant. Then I would have to find where I was again. It really made a dense paper even harder to follow.

(1e) Relatedly, on page 13, the authors make reference to a parameter eta, and I don't see it in Figure 1 or any of the tables. What is that parameter?

(2) This point may be related to me misunderstanding the model, but if LT_p represent the actual genetic factors for the two traits for variants that are transmitted to the child, and T_p represents the PGS of for transmitted variants, shouldn't their be a unidirectional arrow from LT_p to T_p (since the genetic factor affects the PGS and not the other way around) and shouldn't there be no arrow from T_p to Y_0 (since the entire effect of the transmitted SNPs is represented by the arrow from LT_p to Y_0)? If I'm mistaken here, it would be useful to explain why these arrows are necessary.

(3) Some explanation of how the interpretation of the coefficients differs in a univariate model versus a bivariate model would be useful. For example, in a univariate model, the delta parameter represents the "direct effect" of the PGI on the offspring's outcome (roughly corresponding to a regression of the offspring's outcome onto the offspring's PGI and each parent's PGI). Does it have the same interpretation in the bivariate case, or is it more closely related to a regression of one of the outcomes onto the PGIs for both traits?

(4) It appears from the model that the authors are assuming away population stratification since the path coefficient between T_m and T_m is delta (the same as the path coefficient between T_m and Y_0). Similarly, I believe the effect of NT_m on Y_0 only has a genetic nurture interpretation if there is no population stratification. Some discussion of this would be valuable.

References:

Border, R., Athanasiadis, G., Buil, A., Schork, AJ, Cai, N., Young, AI, ... & Zaitlen, N.A. (2022). Cross-trait assortative mating is widespread and inflates genetic correlation estimates. Science , 378 (6621), 754-761.

Reviewer #2 (Public review):

(1) Summary and overall comments:

This is an impressive and carefully executed methodological paper developing an SEM framework with substantial potential. The manuscript is generally very well written, and I particularly appreciated the pedagogical approach: the authors guide the reader step by step through a highly complex model, with detailed explanations of the structure and the use of path tracing rules. While this comes at the cost of length, I think the effort is largely justified given the technical audience and the novelty of the contribution.

The proposed SEM aims to estimate cross-trait indirect genetic effects and assortative mating, using genotype and phenotype data from both parents and one offspring, and builds on the framework introduced by Balbona et al. While I see the potential interest of the model, it is still a bit unclear in which conditions I could use it in practice. However, this paper made a clear argument for the need for cross-traits models, which changed my mind on the topic (I would have accommodated myself with univariate models and only interpreted in the light of likely pleiotropy, but I am now excited by the potential to actually disentangle cross-traits effects).

The paper is written in a way that makes me trust the authors' thoroughness and care, even when I do not fully understand every step of the model. I want to stress that I am probably not well-positioned to identify technical errors in the implementation. My comments should therefore be interpreted primarily from the perspective of a potential user of the method: I focus on what I understand, what I do not, and where I see (or fail to see) the practical benefits.

For transparency, here is some context on my background. I have strong familiarity with the theoretical concepts involved (e.g., genetic nurture, gene-environment covariance, dynastic effects), and I have worked on those with PGS regressions and family-based comparison designs. My experience with SEM is limited to relatively simple models, and I have never used OpenMx. Reading this paper was therefore quite demanding for me, although still a better experience than many similarly technical papers, precisely because of the authors' clear effort to explain the model in detail. That said, keeping track of all moving parts in such a complex framework was difficult, and some components remain obscure to me.

(2) Length, structure, and clarity:

I do not object in principle to the length of the paper. This is specialized work, aimed at a relatively narrow audience, and the pedagogical effort is valuable. However, I think the manuscript would benefit from a clearer and earlier high-level overview of the model and its requirements. I doubt that most readers can realistically "just skim" the paper, and without an early hook clearly stating what is estimated and what data are required, some readers may disengage.

In particular, I would suggest clarifying early on:

• What exactly is estimated?

For example, in the Discussion, the first two paragraphs seem to suggest slightly different sets of estimands: "estimate the effects of both within- and cross-trait AM, genetic nurture, VT, G-E covariance, and direct genetic effects." versus "model provides unbiased estimates of direct genetic effects (a and δ), VT effects (f), genetic nurture effects (ϕ and ρ), G-E covariance w and v, AM effects (μ), and other parameters when its assumptions are met." A concise and consistent summary of parameters would be helpful.

• What data are strictly required?

At several points, I thought that phenotypes for both parents were required, but later in the Discussion, the authors consider scenarios where parental phenotypes are unavailable. I found this confusing and would appreciate a clearer statement of what is required, what is optional, and what changes when data are missing.

• Which parameters must be fixed by assumption, rather than estimated from the data?

Relatedly, in the Discussion, the authors mention the possibility of adding an additional latent shared environmental factor across generations. It would help to clearly distinguish: - the baseline model, - the model actually tested in the paper, and - possible extensions.

Making these distinctions explicit would improve accessibility.

This connects to a broader concern I had when reading Balbona et al. (2021): at first glance, the model seemed readily applicable to commonly available data, but in practice, this was not the case. I wondered whether something similar applies here. A clear statement of what data structures realistically allow the model to be fitted would be very useful.

I found the "Suggested approach for fitting the multivariate SEM-PGS model" in the Supplementary Information particularly helpful and interesting. I strongly encourage highlighting this more explicitly in the main manuscript. If the authors want the method to be widely used, a tutorial or at least a detailed README in the GitHub repository would greatly improve accessibility.

Finally, while the pedagogical repetition can be helpful, there were moments where it felt counterproductive. Some concepts are reintroduced several times with slightly different terminology, which occasionally made me question whether I had misunderstood something earlier. Streamlining some explanations and moving more material to the SI could improve clarity without sacrificing rigor.

(3) Latent genetic score (LGS) and the a parameter

I struggled to understand the role of the latent genetic score (LGS), and I think this aspect could be explained more clearly. In particular, why is this latent genetic factor necessary? Is it possible to run the model without it?

My initial intuition was that the LGS represents the "true" underlying genetic liability, with the PGS being a noisy proxy. Under that interpretation, I expected the i matrix to function as an attenuation factor. However, i is interpreted as assortative-mating-induced correlation, which suggests that my intuition is incorrect. Or should the parameter be interpreted as an attenuation factor?

Relatedly, in the simulation section, the authors mention simulating both PGS and LGS, which confused me because the LGS is not a measured variable. I did not fully understand the logic behind this simulation setup.

Finally, I was unsure whether the values simulated for parameter a in Figures 8-9 are higher than what would typically be expected given the current literature, though this uncertainty may reflect my incomplete understanding of a itself. I appreciated the Model assumptions section of the discussion, and I wonder if this should not be discussed earlier.

(4) Vertical transmission versus genetic nurture

I am not sure I fully understand the distinction between vertical transmission (VT) and genetic nurture as defined in this paper. From the Introduction, I initially had the impression that these concepts were used almost interchangeably, but Table 3 suggests they are distinct.

Relatedly:

• Why are ϕ and ρ not represented in the path diagram?

• Are these parameters estimated in the model?

The authors also mention that these parameters target different estimands compared to other approaches. It would be helpful to elaborate on this point. Relatedly, where would the authors expect dynastic effects to appear in this framework?

(5) Univariate model and misspecification

In the simulations where a univariate model is fitted to data generated under a true bivariate scenario, I have a few clarification questions.

What is the univariate model used (e.g., Table 5)? Is it the same as the model described in Balbona et al. (2025)? Does it include an LGS?

If the genetic correlation in the founder generation is set to zero, does this imply that all pleiotropy arises through assortative mating? If so, is this a realistic mechanism, and does it meaningfully affect the interpretation of the results?

(6) Simulations

Overall, I found the simulations satisfying to read; they largely test exactly the kinds of issues I would want them to test, and the rationale for these tests is clear.

That said, I was confused by the notation Σ and did not fully understand what it represents.

In the Discussion, the authors mention testing the misspecification of social versus genetic homogamy, but I do not recall this being explicitly described in the simulation section. They also mention this issue in the SI ("Suggested approach for fitting..."). I think it would be very helpful to include an example illustrating this form of misspecification.

(7) Cross-trait specific limitations

I am wondering - and I don't think this is addressed - what is the impact of the difference in the noisiness and the heritability of the traits used for this multivariate analysis?

Using the example, the authors mention of BMI and EA, one could think that these two traits have different levels of noise (maybe BMI is self-reported and EA comes from a registry), and similarly for the GWAS of these traits, let's say one GWAS is less powered than the other ones. Does it matter? Should I select the traits I look at carefully in function of these criteria? Should I interpret the estimates differently if one GWAS is more powered than the other one?

This creates an event due to the change in emotions. For example in the beginning, Nathaniel talked to Malcolm like he knew something that Malcolm didn't know and it created a sense of connection with Malcolm for us not knowing what Nathaniel is doing. With Nathaniel pouring his heart out to Malcolm and Malcolm switching up it up with Nathaniel by stabbing him, it created a shift in a connection with the characters. From going from feeling bad that Malcolm doesn't know whats going on to feeling bad that Nathaniel got stabbed after pouring his emotions out, it creates an event within the play.

eLife Assessment

This manuscript provides valuable insight into how genome organization changes as cells progress through the cell cycle after mitotic exit. The conclusions are supported by solid, rigorous data, and the use of sorted unsynchronized cells rather than cells treated with drugs is a particular strength. Two sharp genome remodeling events are identified at G1-S and to a lesser extent, at S-G2 transitions. A discussion on the limitations of Hi-C and a broader interpretation of results in the context of other mechanistic models would strengthen the overall rigor.

Reviewer #1 (Public review):

This work convincingly shows that, rather than gradually "evolving" throughout interphase, global chromatin architecture undergoes unexpectedly sharp remodeling at G1-S (and to a lesser extent, S-G2) transitions. By applying "standard" Hi-C analyses on carefully sorted cells, the authors provide an excellent temporal view of how global chromatin architecture is changed throughout the cell cycle. They show a surprisingly abrupt increase in compartmentation strength (particularly interactions between the "active" A compartments) at G1-S transition, which is slightly weakened at S-G2 transition. Follow-up experiments show convincingly that the compartment "maturation" does not require the DNA synthesis accompanying S phase per se, but the authors have not identified the responsible factors (work for future publications). The possible biological ramifications of these architectural changes (setting up potential replication "factories", and/or facilitating transcription-replication conflict resolution, both more pertinent for the active A compartments, which are most affected) have been well discussed in the article, but still remain speculative at this stage.

My major criticism of this article is aimed more at the state of the field in general, rather than this specific article, but it should be discussed to give a more balanced view: what actually is a chromatin compartment? Chromosomal tracing and live tracking experiments have shown that the majority of "structures" identified from Hi-C experiments are statistical phenomena, with even "strong" interactions only being infrequent and transient. A-B compartments are "built up" from multiple very low-frequency "interactions", so ascribing causal effects for genome functions is even tougher. As a result, I have very little confidence in the results of the authors' polymer simulations and their inferred "peninsula" A compartment structures without any other supporting experimental data.

Specific minor points:

(1) A better explanation for how Figure 1E was generated is required, because this figure could be very misleading. Figure 1F and all other cis-decay plots (and the Hi-C maps themselves) show that the strongest interactions are always at smaller genomic separations, so why should there be more "heat" at the megabase ranges in Figure 1E?

(2) An ultra-high-resolution Hi-C study (Harris et al., Nat Commun, 2023) identified very small A and B compartments, including distinctions between gene promoters and gene bodies, raising further questions as to what the nature of a compartment really is beyond a statistical phenomenon. It is unreasonable to expect the authors to generate maps as deep as this prior study, but how much do their conclusions change according to the resolution of their compartment calling? The authors should include a balanced discussion on the "meaning" of A/B compartments.

Reviewer #2 (Public review):

Summary:

This manuscript by Choubani et al presents a technically strong analysis of A/B compartment dynamics across interphase using cell-cycle-resolved Hi-C. By combining the elegant Fucci-based staging system with in situ Hi-C, the authors achieve unusually fine temporal resolution across G1, S, and G2, particularly within the short G1 phase of mESCs. The central finding that A/B compartment strength increases abruptly at the G1/S transition, stabilizes during S phase, and subsequently weakens toward G2 challenges the prevailing view that compartmentalization strengthens monotonically throughout interphase. The authors further propose that this "compartment maturation" is triggered by S-phase entry but occurs independently of active DNA synthesis, and that it involves a consolidation and large-scale reorganization of A-compartment domains.

Strengths:

Overall, this is a thoughtfully executed study that will be of broad interest to the 3D genome community. The data are of high quality, and the analyses are extensive, albeit not completely novel. In particular, previous work (Nagano et al 2017 and Zhang et al 2019) has shown that compartments are re-established after mitosis and strengthened during early interphase, and single-cell Hi-C studies have reported changes in compartment association across S phase. In particular, Nagano et al show that DNA replication correlates with a build-up of compartments, similar to what is presented here, with the authors' conclusion that compartment strength peaks in early S. The idea that it weakens toward G2, rather than continuing to strengthen, appears to be novel and differs from the prevailing framing in the literature.

Weaknesses:

That said, several aspects of the conceptual framing and interpretation would also benefit from further clarification, and the mechanistic interpretation of the reported compartment dynamics requires more careful positioning relative to established models of genome organization. Specific concerns are outlined below:

(1) One of the major conclusions of the study is that compartment maturation does not require ongoing DNA replication. However, the interpretation would benefit from more precise wording. Thymidine arrest still permits licensing, replisome assembly, and other S-phase-associated chromatin changes upstream of bulk DNA synthesis. Therefore, their data, as presented, demonstrate independence from DNA synthesis per se, but not necessarily from the broader replication program. Please clarify this distinction in the text and interpretations throughout the manuscript.

(2) A major conceptual issue that is not addressed at all is the well-established anti-correlation between cohesin-mediated loop extrusion and A/B compartmentalization. Numerous studies have shown that loss of cohesin or reduced loop extrusion leads to stronger compartment signals, whereas increased cohesin residence or enhanced extrusion weakens compartmentalization. Given this framework, an obvious alternative explanation for the authors' observations is that the abrupt increase in compartment strength at G1/S, and its decline toward G2, could reflect cell-cycle-dependent modulation of cohesin activity rather than a compartment-intrinsic "maturation" program.

The manuscript does not explicitly consider this possibility, nor does it examine loop extrusion-related features (such as loop strength, insulation, or stripe patterns) across the same cell-cycle stages. Without discussing or analyzing this widely accepted model, it is difficult to distinguish whether the reported compartment dynamics represent a novel architectural mechanism or an indirect consequence of known changes in extrusion behavior during the cell cycle. I strongly encourage the authors to analyze their data to determine if they observe anti-correlated loop changes at the same time they observe compartment changes. Ideally, the authors would remove loop extrusion during interphase using well-established cohesin degrons available in mESCs and determine if the relative differences in compartment dynamics persist.

(3) The proposed "peninsula-like" A-domain structures are inferred from ensemble Hi-C data and polymer modeling, rather than directly observed physical conformations. That is, single-cell imaging data clearly have shown that Hi-C (especially ensemble Hi-C) cannot uniquely specify physical conformations and that different underlying structures can produce similar contact patterns. The "peninsula" language, as written, risks being interpreted as a literal structural model rather than a conceptual visualization. Instead of risking this as just another nuanced Hi-C feature in the field, the authors could strengthen the manuscript by either (i) explicitly framing the peninsula model as a heuristic description of contact redistribution rather than a definitive physical architecture, or (ii) discussing alternative structural scenarios that could give rise to similar Hi-C patterns. Clarifying this distinction would improve the rigor and help readers better understand what aspects of A-compartment consolidation are directly supported by the data versus model-based extrapolations. For example, it would be useful to clarify whether the observed increase in long-range A-A contacts reflects spatial extension of internal A regions, changes in loop extrusion dynamics, increased compartment mixing within the A state, or population-averaged heterogeneity across alleles.

(4) The extension of the analysis to additional cell types using HiRES single-cell data is a valuable addition and supports the idea that compartment maturation is not unique to mESCs. However, the limitations of these data, in particular, the limited phase resolution, in addition to the pseudo-bulk aggregation and variable coverage, should be emphasized more clearly in the main text. Framing these results as evidence for conservation in principle, rather than definitive proof of identical dynamics across tissues, would be a more appropriate framing.

This part creates an event due to the addition of a new character. Although it is early in the play the introduction of a character gives the change of an event. With the introduction being solely from Jess's point of view we are also stuck in this point of view with her during the introduction of Malcom. Due to Malcolm saying that if Jess wants to beat The Devils, she has to be able to beat him firsts, makes everyone ask about what is so special about Malcom that makes him on par with The Devils. It creates a tension between Jess and Lucky, and Malcom about the background of Malcom.

eLife Assessment

This important work demonstrates the role of physically linking the core and CTD kinase modules of TFIIH via separate domains of subunit Tfb3 in confining RNA Polymerase II Serine 5 CTD phosphorylation to promoter regions of transcribed genes in budding yeast. The main findings, resulting from analyses of viable Tfb3 mutants in which the linkage between TFIIH core and kinase modules has been severed, are supported by solid evidence from in vitro and in vivo experiments. There is an intriguing possibility that the Tfb3-mediated connection between core and kinase modules of TFIIH is an evolutionary addition to an ancestral state of physically unconnected enzymes, which could be examined more rigorously with additional evolutionary analyses.

Reviewer #1 (Public review):

Giordano et al. demonstrate that yeast cells expressing separated N- and C-terminal regions of Tfb3 are viable and grow well. Using this creative and powerful tool, the authors effectively uncouple CTD Ser5 phosphorylation at promoters and assess its impact on transcription. This strategy is complementary to previous approaches, such as Kin28 depletion or the use of CDK7 inhibitors. The results are largely consistent with earlier studies, reinforcing the importance of the Tfb3 linkage in mediating CTD Ser5 phosphorylation at promoters and subsequent transcription.

Notably, the authors also observe effects attributable to the Tfb3 linker itself, beyond its role as a simple physical connection between the N- and C-terminal domains. These findings provide functional insight into the Tfb3 linker, which had previously been observed in structural studies but lacked clear functional relevance. Overall, I am very positive about this manuscript and offer a few minor comments below that may help to further strengthen the study.

(1) Page 4

PIC structures show the linker emerging from the N-terminal domain as a long alpha-helix running along the interface between the two ATPase subunits, followed by a turn and a short stretch of helix just N-terminal to a disordered region that connects to the C-terminal region (see schematic in Figure 1A).

The linker helix was only observed in the poised PIC (Abril-Garrido et al., 2023), not in other fully-engaged PIC structures.

(2) Page 8

Recent structures (reviewed in (Yu et al., 2023)) show that the Kinase Module would block interactions between the Core Module and other NER factors. Therefore, TFIIH either enters into the NER complex as the free Core Module, or the Kinase Module must dissociate soon after.

To my knowledge, this is still controversial in the NER field. I note the potential function of the kinase module is likely attributed to the N-terminal region of Tfb3 through its binding to Rad3. Because the yeast strains used in Figure 6 retain the N-terminal region of Tfb3, the UV sensitivity assay presented here is unlikely to directly address the contribution of the kinase module to NER.

(3) Page 11

Notably, release of the Tfb3 Linker contact also results in the long alpha-helix becoming disordered (Abril-Garrido et al., 2023), which could allow the kinase access to a far larger radius of area. This flexibility could help the kinase reach both proximal and distal repeats within the CTD, which can theoretically extend quite far from the RNApII body.

Although the kinase module was resolved at low resolution in all PIC-Mediator structures, these structural studies consistently reveal the same overall positioning of the kinase module on Mediator, indicating that its localization is constrained rather than variable. This observation suggests that the linker region may help position the kinase module at this specific site, likely through direct interactions with the PIC or Mediator. This idea is further supported by numerous cross-links between the linker region and Mediator (Robinson et al., 2016).

Reviewer #2 (Public review):

Summary:

This work advances our understanding of how TFIIH coordinates DNA melting and CTD phosphorylation during transcription initiation. The finding that untethered kinase activity becomes "unfocused," phosphorylating the CTD at ser5 throughout the coding sequence rather than being promoter-restricted, suggests that the TFIIH Core-Kinase linkage not only targets the kinase to promoters but also constrains its activity in a spatial and temporal manner.

Strengths:

The experiments presented are straightforward, and the models for coupling initiation and CTD phosphorylation and for the evolution of these linked processes are interesting and novel. The results have important implications for the regulation of initiation and CTD phosphorylation.

Weaknesses:

Additional data that should be easily obtainable and analysis of existing data would enable an additional test of the models presented and extract additional mechanistic insights.

Reviewer #3 (Public review):

Summary:

Eukaryotic gene transcription requires a large assemblage of protein complexes that govern the molecular events required for RNA Polymerase II to produce mRNAs. One of these complexes, TFIIH, comprises two modules, one of which promotes DNA unwinding at promoters, while the other contains a kinase (Kin28 in yeast) that phosphorylates the repeated motif at the C-terminal domain (CTD) of the largest subunit of Pol II. Kin28 phosphorylation of Ser5 in the YSPTSPS motif of the CTD is normally highly localized at promoter regions, and marks the beginning of a cycle of phosphorylation events and accompanying protein association with the CTD during the transition from initiation to elongation.

The two modules of TFIIH are linked by Tfb3. Tfb3 consists of two globular regions, an N-terminal domain that contacts the Core module of TFIIH and a C-terminal domain that contacts the kinase module, connected by a linker. In this paper, Giordano et al. test the role of Tfb3 as a connector between the two modules of TFIIH in yeast. They show that while no or very slow growth occurs if only the C-terminal or N-terminal region of Tfb3 is present, near normal growth is observed when the two unlinked regions are expressed. Consistent with this result, the separate domains are shown to interact with the two distinct TFIIH modules. ChIP experiments show that the Core module of TFIIH maintains its localization at gene promoters when the Tfb3 domains are separated, while localization of the kinase module and of Ser5 phosphorylation on the CTD of Pol II is disrupted. Finally, the authors examine the effect of separating the Tfb3 domains on another function of TFIIH, namely nucleotide excision repair, and find little or no effect when only the N-terminal region of Tfb3 or the two unlinked domains are present.

Strengths:

Experiments involving expression of Tfb3 domains in yeast are well-controlled, and the data regarding viability, interaction of the separate Tfb3 domains with TFIIH modules, genome-wide localization of the TFIIH modules and of phosphorylated Ser5 CTDs, and of effects on NER, are convincing. The experiments are consistent with current models of TFIIH structure and function and support a model in which Tfb3 tethers the kinase module of TFIIH close to initiation sites to prevent its promiscuous action on elongating Pol II.

Weaknesses:

(1) The work is limited in scope and does not provide any major insights into the mechanism of transcription. One indication of this limitation is that in the Discussion, published structural and functional results on transcription are used to support the interpretations of the results here more than current results inform previous models or findings.

(2) The first described experiment, which purports to show that three kinases cannot function in place of Kin28 when tethered (by fusion) to Tfb3, is missing the crucial control of showing that Kin28 can support viability in the same context. This result also does not connect with the rest of the manuscript.

(3) Finally, the authors present the interesting and reasonable speculation that the TFIIH complex and connecting Tfb3 found in mammals and yeast may have evolved from an earlier state in which the two TFIIH subdomains were present as unconnected, distinct enzymes. This idea is supported by a single example from the literature (T. brucei). A more thorough evolutionary analysis could have tested this idea more rigorously.

The relationship between tits and caterpillars is beneficial since the birds rely on the caterpillars to feed their chicks, and we know this timing is shaped by environmental cues. But over time, could this tendency to match egg laying with caterpillar peaks become genetically encoded in the population?

Phenotypic plasticity is when a trait in an individual changes in response to the environment. In this case, only some females adjust their laying dates, which is plasticity. But if these differences in plasticity are heritable, natural selection could act on them, and over time this variation could drive evolution.

This variation leads to evolution since it has high heritability. The plastic responses, when the same genotype produces different phenotypes depending on environmental conditions, don’t equal evolution on their own if they are not heritable. But genetic differences in plasticity can be acted on by natural selection, which does drive evolutionary change.

Without a functioning system as complicated as our digestive system we would not be able to absorb and produce nutrients into our bloodstream to be used as energy.

The stomach breaks down the food we eat into nutrients or nourishment or energy which we use throughout the day

Reflection: The idea relates to my interests since it demonstrates that environmental management must evolve with the change in conditions. I can say that in my practice that a lot of issues occur because everyone is guided by some rigid rules and does not consider the impact that nature and society have on one another. SES approach can make us view people and the environment as a single system and utilize resources in a manner that can be sustained over a long period.

Defination: The SES environmental management approach implies treating the people and the nature as a single system. It is not comparable to the traditional frameworks since it involves the human behavior, social institutions and feedbacks with ecosystems and promotes adaptive and flexible management to be in a better place of coping with change and the uncertainty.

connection to concept: This concept is related to course material about adaptive management and resilience thinking, which focuses on connecting theory with the actual decision making. The watershed management in the U.S. is a good real life example, as the scientists, local communities, and government agencies collaborate to manage water resources in the terms of the ecological processes and social needs. With the help of an SES framework, it is more feasible, inclusive, and resilient to have the managers to understand better feedbacks between human activities and ecosystems, thus making the environmental management more practical.

comment on key idea: One major concept of social ecological systems (SES) science is the concept of resilience which adds investment to the capacity of the interconnected social and ecological systems to absorb disruptions, adapt to them and still survive. Such a view enhances the environmental management through transdisciplinary, adaptive approaches that appreciate complexity, uncertainty, and flexibility of governance as opposed to full control.

Question for the discussion: What are the practical applications of ideas of SES science by managers and communities that can work across disciplines and create resilience in actual environmental management scenarios?

Defination : Transdisciplinary approach is the method in which specialists in other fields and non-academic people such as communities, policymakers, non governmental organization and industries collaborate in developing practical solutions to complex problems.

The two paragraphs prior to this almost seem to juxtapose this statement; after all, the overarching rule of the Qing Dynasty officials in the region, specifically in areas of different cultures, seemed to be very considerate of the ways of other cultures and how their rule over the region might negatively impact these cultures. This is the same for the Russian empire, as specifically the conquest of Siberia was noted to not be as violent as other countries would have been, albeit not as respectful as the Qing Dynasty. However, the chosen statement unfortunately does make sense; these were both still conquests, after all, and combating such different and distinct ways of rule and culture against one another in such close proximity could only ever serve to harm those who were conquered.

The phrasing of this paragraph alludes to this conquest, or the absorption of Siberia into the Russian Empire, as not necessarily being violent; nonetheless, the consequences of this on the native culture and land appears to be no different than that of a violent conquest. As this section later states, the treatment of the native people was not anywhere near as harsh as conquests done by the Americas, and yet the religion and way of life of these natives was lost all the same.

While this is common to hear in cases of women from colonized countries and / or societies, it is still difficult to read about. Something that stands out about this case, however, is the hypocrisy of the Spaniards in this case; as noted in the previous paragraph, they were obsessed with their women being “pure of blood,” which by that definition, the indigenous women were not. Similarly, indigenous women being put in this position, i.e. the position of being forced to bear the children of the male Spaniards, ironically put them in a relatively similar social position to that of the Spanish women, aside from the racial privileges that the Spanish women had.

Both of these regions experienced weather conditions almost like mass extinction events, occurring at the same time, both technically within the same continent. However, both events in themselves were antithetical to each other, despite both having the same outcome of excessive death counts. As the following section states, this Great Dying paved the way for European and African people to settle into these regions and “replace the varied cultures” that had survived there for so long; perhaps, considering this, the Great Dying of the central Mexico and Caribbean regions was a small-scale mass extinction event for the indigenous people of those regions after all.

About a year cycle - takes longer to grow

About a 6 month cycle

I wonder nowadays kids feel about youtubers and other online entertainers. Now that such a dynamic is more widely available how is this affecting kids?

Very interesting! I've never heard of this model before.

One of my favourite methods! Much easier to create connections and phrases that help me remember the information.

I agree with this. If someone is reading outload and they are monotoned, they have a blank face and no pep to keep attention, nope sleep time! You have to keep someone's attention. If you want to know if you are a good storyteller, volunteer to do a story reading day at a Pree school or the library but ask for kids under the age of 6. That is the real test. My daughter can keep kids' attention all day. I can for a little bit. My husband stands no chance! so yes being entertaining while you're telling a story is a MUST!!!

A story can have several different reasons on why it was made. Some help people learn things from educational and some as cultural knowledge. Some stories can tell someone's personal history like a memoir. I used to tell stories to help my kids understand things (made up stories), potty training, friends, school time things like this. My grandfather would tell me stories about the factories. I would tell stories to friends about where i have been growing up. I've learned a lot of fun facts- Like taking a quarter to help push a thumb tack into a wall. that came from a contractor who walked into my CPR class as I was struggling with a thumb tack. My go to hack. There are so many reason for stories.

"world of story" caught my eye because i think about the native paintings that show stories of hunts and battles that took place and even though you cant listen to it you'll be able to take yourself there in imagination and relive the tale.

i agree because when your reading a story you try to make the most sense of it by putting yourself in to the story which can easily misinterpret the story vs. when you listen to a story the teller will make you feel as if its your own.

the connection that stories bring is incredible because they make you feel as if you experienced it yourself.

Explaining how making the food become overwhelming and uncomfortable with the strong and some harsh words reflect how Amy sees her culture through as an outsider rather than as something familiar.

If I am understanding this rating scale correctly, the interval scale is significant to me because it is one that I personally experience and had to participate in when I experienced short term memory loss during an illness. The Wechsler Memory Scale task is when a person is asked to remember a number while listening to a story and then recall the number later. This is measured on an interval scale because the score goes up in equal steps based on how many numbers are remembered but the score of zero does not mean the person has no memory at all. Simply it is meant to access the severity of memory loss if any is being experienced by the subject.

Ratio scale = most informative/detailed measurement Its measurement explains its exact value and category (Is all of the measurements in one)

Ordinal scale = measurement within a scale Ex.) Rating from 1-10

An independent variable is a variable/subject that has its own individual, observable value to a study.

Definition of variable. A factor of interest in a study.

This text explains that statistics are not only used in science but also help us in everyday life. This shows that understanding statistics helps us tell the difference between good and bad information so that we can make informed decisions. Without this we can be easily influenced and misled in our everyday lives. Learning and using statistics help us make better more informed decisions that are in our best interest. An example of this that I often experience as a mom on a fixed income is the constant credit cards or loan ads, and mailings that I am exposed to promising low monthly payments, low rates, and even credit improvment. However, by using a combination of common sense, statistics that include my personal income, past and present rates, fees, and total cost over time, I am able to make informed decisions and avoid being misled by "words" and making a choice of what is truly beneficial to myself and my income affordability.

Doing this is the first line of defense when strengthening your analytical statistic skills.

Statistics is the way science shows and organizes the relationship between variables, and without it we would not be able to tell reality and fantasy.

If you wanted to test the effects of a certain fertilizer on soybean growth, you would want to randomize the experiment plots so that all the controls didn't receive more sun/water (or anything else) than the treated plants.

The number of experimental units

great conclusion -- it's important to recongnize then business tries to sell you something, showcasing it as a product - magic that you never had in your life before...

That's actually connect to the points of large data that might bring more problems from the previous lecture

The tool is just trained on the human artworks to replicate them :)

It helps to know the basics on how LLM models answers on the questions where it analyses each word as a token, let's image some set of number, and try to find the most related words. That's why LLM models claim something as factual data, but you tell that they are wrong, they admit it and deeply apologize as a part of their polite training

which kills creativity and uniqueness

From a parenting and educational perspective, daughter would write an awesome and authentic letter to the Olympic Athlete. However, the real problem isn't that the letter needs to be perfect, but that the father is prioritizing efficiency over dedicating time to help her learn and express herself.

Q: standing

A: 1) Based on this page:<br /> “standing” means being upright on its feet in one place (not sitting or lying down). Here it describes the tabby cat upright on the corner of Privet Drive.

2) General knowledge (not from this page):<br /> “standing” can also mean having a particular status or reputation (e.g., “in good standing”), but that is not the meaning in this passage.

1）基于本页内容：<br /> “standing” 的意思是“站着、直立地待在原地”（不是坐着或躺着）。这里用来描述那只虎斑猫直立地站在女贞路的街角。

2）常识补充（非本页内容）：<br /> “standing” 也可以表示“地位/声望/名誉”（例如 “in good standing”），但这不是本段文字里的用法。

TLDR 1) Glutamate is released and binds to both AMPA and NMDA receptor 2) AMPA receptor opens to allow entry of sodium. NMDA cannot open due to magnesium blockage. 3)Influx of sodium via AMPA receptor causes depolarisation which removes magnesium blockage 4)NMDA channel opens and sodium and calcium can enter 5)Influx of calcium results in activation of kinases that travel to nucleus, leading to upregulation of AMPA receptor in the post synaptic cell or increased glutamate released.

Contains word "Icon" or the full word of iconography. Derived from sight

Contains the word "Echo" which is derived from a sound. Hence it is sound memory

Like a haptic vest used in virtual reality games. It means touch or the sensation of touch

Đây là một repository được tạo bởi Vercel Labs, chuyên về các quy tắc tốt nhất khi viết React, được tối ưu hóa để AI agents và LLMs có thể hiểu và áp dụng. Mục đích: Tạo ra một bộ hướng dẫn có cấu trúc, dễ đọc cho AI về cách viết React code hiệu quả, tập trung vào performance optimization.

Cấu trúc thư mục ├── rules/ # Các file quy tắc riêng lẻ │ ├── _sections.md # Metadata của các phần │ ├── _template.md # Template tạo quy tắc mới │ └── area-description.md # Các file quy tắc cụ thể ├── src/ # Scripts build ├── metadata.json # Thông tin document ├── AGENTS.md # File output tổng hợp (tự động tạo) └── test-cases.json # Test cases cho LLM (tự động tạo)

This is why we examine patterns in medical records and study them to better understand the causes based on commonalities of lifestyle.

This was brought up I believe in chapter one. It highlights the idea that we have to use the sociological imagination to analyze this rather than simply blaming the person for not getting vaccinated, we would have to examine why the individual did not want to get vaccinated and what patterns followed as a result.

This is vital to the spread of COVID-19, especially consider that they implemented little travel during the time and the doctors ask about travel during screenings when you are ill.

This explains how different groups are affected by certain conditions or are at greater risk than others due to factors that aren't just physiological. These are also patterns that we are observing and studying.

I wonder if this will shift again because of weight loss medications and being able to acknowledge, educate, and address the problem faster than we used to.

This hits on the facts that disease and illness can be a result and or influenced by social factors.

I believe these are components of illness that we don't follow because they are minuscule compared to spreading germs, I think we focus less on the smaller but important ideals and how they effect different communities differently.

This makes me think about growing up as a product of your environment, if “one’s position in social structure impacts the chances of leading a long and healthy life” your only going to be as healthy as your social structure is

This shows that spending more money on health care does not automatically lead to better health outcomes. Even though the United States invests heavily in health care, factors like inequality, access to care, and social conditions still affect life expectancy. This suggests that improving population health requires addressing broader social and economic issues, not just increasing health care spending.

Health problems are not only caused by individual behaviors, but by the social conditions that shape those behaviors in the first place. Instead of blaming people for choices like smoking or poor diet, it encourages us to look at factors like income, stress, and access to resources. Understanding these “causes of the causes” helps explain why some groups experience worse health outcomes than others.

This explains that people are not avoiding chronic diseases altogether, but are getting them at older ages. Advances in medicine and healthier behaviors have helped delay these illnesses, which is why life expectancy has increased. However, this also means healthcare systems need to be prepared to care for more older adults living with chronic conditions.

If I were to challenge any of the aspects, it would be this one. Using carbon dating and fossil samples may be the easiest way to determine if speciation occurred simultaneously or if we can find proof of timeline-based speciation.

It feels like this is a valid reason to criticize a theory, considering current species distribution is complex to link to former species distribution.

This makes a lot of sense as the explanation for the high biodiversity found in the area, I can understand why people are interested in researching it further.

I appreciate how the importance of both fast and slow thinking is mentioned. Fast thinking is important in busy environments and setting require you to have commonsense or knowledge on the top of your head. While slow thing is needed when you encounter a situation that has high risk, give you time to thing, and require research.

Slower thinking forces you to analyze , access the gravity of , and improve a situation. For example when creating an essay instead of jumping into writing, slow thinking may cause you to pause and survey that material, and essay prompt. You may also come up with a format or plan first .

When a conclusions or thesis is made without evidence it cause the entire book or paper to lose credibility. This forces the author to question its legitimacy. When there is evidence against the thesis however with no evidence to support, then the argument is proven wrong altogether. This shows that proper research is important.

I am aware that I have cognitive bias when familiar or shady situations occur. This action may be due to personal experience or assumptions made without proof and may lead me to act irrational.

I would be very much interested in better understanding what is meant by information privilege and what its effects are on those who cannot access said information. Does it result in lower/uncredible work due to the inability to access information, etc?

It was interesting to get to know about non-profit LLM models that are accessible to anyone. Never heard of them

A great connection to the LIAON - 5 statement, that data isn't filtered, and it might take over 100 years (forgive me if im wrong) to filter all of the data that is getting scrapped while training the models

Love this idea of equity in the research communities however editing and work wtih time consuming tasks might be used by everyone. I mean that there is no specific 'marginalized' or group who in need for this. All of the researchers no matter of the language, level of expertise, and gender use LLM for tedious and time-consuming editing

I think this might due to a simple reason that most of the researchers nowadays just non-white and non native English speakers. However, can't reason why they perceive higher benefits and lower risks? Maybe simply because they have more experience with LLM models and prompting?

Figure to remind the phase change words.

I think that knowing the five common steps in the writing process, will help you organize your ideas.

I think this is the most important because I tend to free write in a conversational and simple style, which takes some of the nerves and pressure off of writing

reading can give you a basis to refer to, look back on, and use for the overall writing process. you can borrow or take inspiration from other author's tones and diction

Statistics are not always 100% accurate, because all variables are not available to take into account for the study.

It's natural for people to see two numbers and assume they are related without looking at the bigger picture and realizing there is another factor that connects the two initial factors, which is known as the third-variable.

History effect is a flaw in statistical studies that leads people to think an outcome is affected by one factor when really it is another, in this case it is time.

This is close to a definition of stats.

I agree and also believe that college has that ability to train the mind of a student when it comes to English since you are taught techniques and proper writing formats that improve your writing overtime due to progressively harder classes. In these class you master what skill were introduce to you and then taught more.

Writing at a high level is important for many professions since they all require the use of rhetoric in some form. The purpose of this could be to analyze data, get a point across, persuade, or simply inform.

It’s a warning, not just rhetoric. It signals lawmakers may pursue: Laws to limit judicial review Changes to court jurisdiction Alterations to judicial election rules Increased use of constitutional amendments to override court interpretations

Reinforcing the 3 focuses of the information sciences: people, techonology and information

It is a big help for data novice people because a lot of the time these details arent provided

Just today I watched a video lecture by professor Wickes on her research about STEM education for non-stem people. Basically, she raised the same problem about Kaggle - it's place with all of the perfect datasets that and rarely you can see in real work, fr example in the company. The process of learning by using Kaggle omits the essential parts of the computing and data education - data cleaning and preparation.

It is important that when emailing our instructor we are professional and specific with our writing. Thank you for letting us know how we should email you.

I like knowing that this course will help me in the future as a healthcare professional, specifically a Registered Nurse. I look forward to understanding all of the material in this class, and apply it to my future career in the healthcare field.

This sentence is important to be aware of because it lists different responsibilities for us to follow as students. We must ensure to be openminded towards our peers and treat others with respect and kindness.

I found it very informative that you want assignments to be submitted strictly through Word documents. Now I know what should be submitted in the drop box and what is expected of me.

It is important to know where your assignments are and what to look forward to. This allows for accommodations to be made to my schedule and be prepared to complete work on time.

I think this part of the syllabus is very important, it explains the consequences of a late assignment submission. It is very clear and very forward in terms of the late policy for this course.

I'm intrigued with the grading percentages of the class. Now I can actively visualize how much each part of the course is weighed and how it can affect my grade.

This is denied by Freud (he says they anticipated psychoanalysis not influenced it), which becomes really relevant as analyzed by Derrida. Freud wants to be forgotten and for psychoanalysis to evolve and for this to happen it cannot be philosophy, it must have legitimacy of science.

It shocks me that social status on the birth and what qualities people have.

1.- Use the SQL Type.

2.- Copy a message and annote its metadata.

When African Americans where enslaved they were told if they fight for our country, they will have more rights and be freed but almost/ if not all were never freed and had to come back and go back to work for their families.

When this was overruled, I wonder what was going through their minds when the overruled this policy, and how they felt when freed people lost their right to the land. Because I feel like if something like that happened now, we would have war/ riot.

This description fascinates me as I took an intro to ecology course and completed an honors research paper that looked at ecosystem interactions with human involvement. I am interested in examining these interactions on the microbial level and finding out any relevant medicinal insights. - Grant Pareja

This is good practice because it this site is accessible and consistent on many devices such as a laptop, desktop, tablet, and phone with the layout changing accordingly to each medium. This makes it easy for users to access this website no matter what device they are using.

This is a good practice because it states important information about the place which leaves the users with no questions. This shows more pictures of the place, a short paragraph of details such as the type of neighbourhood (quiet and mature), places nearby (Ottawa General Hospital, downtown, grocery stores), number of guests and pets allowed (2 people and 1 pet). Later on the more offerings are showed (free parking, washer and dryer and 50+ more). Ratings are also showed further down the page. This helps users understand what to expect when making their decision.

I think we should say "against competitors" or "versus similar companies you're aware of," etc. Otherwise I worry they'll think we're just asking which one stands out from the others on this list, or something like that.

I don't really care, but it's interesting that we're not using "Somewhat agree" and "Strongly agree" here, etc. I'm curious whether there's a reason for the change in word order (and "Extremely" for "Strongly"). Fine to leave it, just curious.

This text is very interesting and brought my attention because it shows how psychology shapes the way our personalities are and how everyone is different in their individual ways.

Psychology is what shapes our actions, thoughts, and the way we think.

From my understanding of the text, Landons father Hosea talks about his son Landon going to different schools and figuring out what he wants to study . Hosea is concerned because he fears that his son will have anxiety or fear maybe without guidance of his father.

RR\ID Summary of Reviews: This preprint assesses ultra-deep, untargeted metagenomic sequencing of wastewater as a viral surveillance strategy, showing broad detection of common and seasonal viruses and strong potential for public health use. At the same time, reviewers identify several important limitations. These include the high cost and uncertain scalability of ultra-deep sequencing, as well as insufficient validation and poorly defined detection limits for rare or low-abundance viruses. Reviewers also note the imprecise use of terms such as “unbiased,” “scalable,” and “novel.” In addition, they highlight potential biases introduced by library preparation and bioinformatic filtering that may influence viral representation. Further concerns include challenges in interpreting seasonal trends and the need for clearer normalization strategies, assembly metrics, and data presentation to strengthen epidemiological inferences.

Read directly in RR\ID: https://rrid.mitpress.mit.edu/pub/oxvdp4fv/release/2

Reviewer #1: Evidentiary Rating: Potentially Informative

Written Review: The manuscript presents an ultradeep, untargeted wastewater metagenomic survey and makes several key claims about pathogen detection, viral seasonality, and the discovery of emerging viruses. Below, we evaluate these claims and the evidence provided. 1. Highly pathogenic viruses, including H5N1, are present in Missouri wastewater

The authors claim that highly pathogenic viruses like the H5N1 are escaping ordinary surveillance and being picked up by the authors’ ultradeep metagenomic surveillance, requires further scrutiny. In order to be sure that these viruses are really present in the sewage, it is not sufficient to present read counts or BLAST-based classifications alone. Notably, influenza H5N1 was detected only by the less conservative BLAST-based NVD pipeline, while the more stringent GOTTCHA2 method does not find it. 2. Ultradeep Untargeted approach can reveal many remerging and novel viruses

In order to show that it is the “ultra-deepness” that allows us to see new viruses, the authors should present rarefaction curves. However it is of course not a very controversial claim. One can point to other papers and to the general understanding of microbial and viral community sampling, where increased sequencing depth greatly improves the detection of low-abundance taxa.

We agree that the sequencing and wet lab procedure is indeed suited to finding novel viruses, but the bioinformatic workflow that the authors choose to implement, is not. Retaining only reads that share k-mers with known viruses in databases, will remove very novel viruses. Furthermore, we expect that the viral assemblies will be more fragmented, when all reads with unknown kmers are removed. 3. Many coronaviruses, rhino viruses and influenza show distinct and reproducible seasonality in the ultradeep metagenomes

The study analyses samples from a single site spanning a single year. In order to claim that the seasonality is “reproducible”, data from multiple years (several winters) or multiple cities would be useful. The different viruses do indeed seem to have different peaks and can thus be considered distinct from each other. We agree with the authors on this.

Additional comments: 1. It would be helpful if the authors presented their Kraken2 results in the supplementary material to see both classifiers side by side, as “unique in the GOTTCHA2 database” does not necessarily mean it is unique in the wastewater microbiome community, where many species can share sharing genomic regions. 2. We would recommend an alternative way of visualising the seasonal trends of the viruses as it is quite difficult to see it on the heatmaps. Lineplots for some specific genomes of interest could be helpful. 3. The comparison between metagenomic SARS-CoV-2 counts and PCR measurements shows only a modest correlation, which could also originate from the two workflows that process the samples in different ways. 4. The authors might consider treating the data compositionally (see CLR and ALR transformations), as recommended by Gloor et al1. If a lot of additional microbes are added to a sample, the relative abundance of everything else will go down. 1. Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V. & Egozcue, J. J. Microbiome Datasets Are Compositional: And This Is Not Optional. Front. Microbiol. 8, (2017).

Reviewer #2: Evidentiary Rating: Reliable

Written Review: The paper is well written and the use of a high number of samples is a key point to show representative results.

Some issues to revise:

Using RNA-seq means that DNA viruses are clearly at a disadvantage, which introduces a bias, yet the authors claim the study is unbiased. This study includes a bioinformatic filtering step that selects viruses matching specific known viral families. The supposed unbiased nature of the described method, should be discussed in greater depth.

It is also stated (in the introduction) that targeted methods are unable to detect highly divergent, novel viral sequences circulating in the population, but there are published papers showing that probe-capture–based methods can recover viruses beyond the targeted panel. In addition, targeted studies have been shown to detect viral sequences that were not previously identified by untargeted approaches. As said before, this study includes a bioinformatic filtering step that selects viruses matching specific known viral families, which would avoid identification of new families. These points should be also discussed.

It’s also not clear what criteria were used for taxonomic assignment. There is no explanation of minimum coverage, depth, or which typing/detection genes were required. As a result, this statement feels quite vague: "all reported human-infecting viruses were captured with sufficient coverage to assemble enough reads to confidently assign taxonomy".

The classification of picobirnavirus as human viruses should be reconsidered according to published information.

Reviewer #3: Evidentiary Rating: Strong

Written Review: The authors showcase an impressive ultra-deep sequencing effort and in the manuscript documenting their work address several central points and goals, such as to “test the feasibility of viral surveillance using unbiased metagenomic sequencing”; that their approach can detect novel viruses and is unbiased and scalable; the ability to detect low abundance viruses such as influenza A. Critical thoughts about these claims are developed in the following paragraphs.

In principle, the feasibility of the presented metagenomics approach is well demonstrated, but I think a clearer communication of what the authors’ notion of feasibility is exactly, and how well the experimental approach performs with regard to such feasibility goals would drive that point home even better. For example, most researchers don’t have resources for routine ultra-deep sequencing - could one sequence less deep and still achieve enough statistical power to detect low abundance viruses?

While the exact definition of terms like “scalable” in this manuscript remains vague, one might argue that the presented approach is, due to its cost, currently not scalable, and probably will not be so in the midterm, even if sequencing costs continue to drop. Whether the approach is scalable to more than one location or along other axes is not explicitly evaluated in the manuscript.

Similarly, the authors use “unbiased” but also use “minimally biased” throughout the manuscript. I would recommend a unified use and an explicit discussion of the mentioned minimal biases. Further, a RNA virus workflow is presented, without DNase treatment, implying that DNA viruses are equally represented - but the ability to capture different virus types is not addressed in the manuscript. Has the workflow been optimized to represent DNA and RNA viruses equally, or are DNA viruses in the library just a useful “side-effect”? This challenges the claim of being unbiased.

Similarly, the authors claim being able to detect “novel” viruses and list relying on a priori knowledge of genetic makeup as a disadvantage of probe-capture approaches, but clearly also rely on a priori knowledge by basing detection filters on public databases. Being more explicit about what “novel” means in their study would make the manuscript more comprehensive. Additionally, this also impacts the notion of “unbiased” (see above).

The authors validate SARS-CoV-2 detection with digital PCR. A similar validation approach for viruses which are “unexpected” and/or occur in low abundance would strengthen the claim of detecting epidemiological relevant virus surges. Especially the subtyping of influenza down to the genotype would benefit greatly from documenting how the authors came to that conclusion, for example with influenza virus segment coverage plots.

Viral detection is validated via digital PCR for SARS-CoV-2. I would appreciate more information about the capability of ultra-deep sequencing to detect viruses, by establishing e.g. a limit of detection. In that context, the absolute number of reads attributed to SARS-CoV-2 or other viruses (depicted in Fig 4 & 5) is unclear to me, since the denominator of the normalization is not explicitly stated, i.e. the number or fraction of reads mapped to viral contigs. This together with better documentation of assembly statistics would enhance the manuscript and provide a clearer picture about the method’s capability in detecting low abundance or unexpected viruses.

Overall, the manuscript is well written, explains methods in great detail and documents well this impressive approach of ultra-deep sequencing. I believe that an associated publication will greatly benefit the community. Publishing a negative finding such as rRNA removal not significantly improving viral detection is appreciated. Using SQL to query the large amounts of generated data is a great approach and shows the intention and ambition of building a routine surveillance pipeline.

An old friend of mine published their poetry and offered physical copies. I had asked about this because I still thought you had to order, for example, a thousand copies and then hope you would sell them all. It is wonderful that this technology has came to be for writers because now you don't have to worry about being left with an excessive amount of copies. This is especially good for people with small followings or who are new to self-publishing. I believe the more accessible things like this become, the more we can hear from voices who can't afford printing thousands of copies.

When I was a teen, a lot of people in my social circles wrote books on free websites. It was very nice, in my opinion. People would write books on their phone when they had free time, and would go home and edit them on a laptop or continue on their phone. During this time, I felt people's vocabulary got better. Although the popularization of this form of writing and publishing books might devalue physical books or purchasable e-books, this accessibility encouraged many to write. As a result of being able to write and access books without payment, people were reading and learning more.

Less than 5% seems like a really small number, but when put into comparison to just how many books have been written and released physically over time, it's actually really impressive that e-books have made a decent dent in the book market. Especially given the short amount of time e-books have been released.

I remember growing up when the tablet or iPad was released, the Kindle was completely forgotten. This might have just been in my community, but they were seen as foolish to buy since all they could do was read books. People would buy a tablet instead since it was able to do more than a Kindle. I do wonder if maybe a Kindle would encourage reading, because most people I knew who bought tablets were not reading on them.

This message will impact the receiver (my boss) by having them figure out how to get the meeting ready the next day. This message also impacts them by showing that I am not someone who is a no-show, and that I tried my best under the circumstances to maintain responsibility and reliability. The message would hopefully not harm our relationship quality, which at this point is new, slightly unstable, and mostly trustworthy.

My receiver needs to know why I won't be at work in the morning, how I can attempt to help (finding someone to complete my responsibilities?), and what my plan is moving forward.

This is a good practice because there are buttons on the listing such as guest favourite, the heart (like/save), and the listing itself. These buttons are clear and easy to interact with.

This is a good practice because it clearly shows and describes key information such as a photo, the type of room (guest suite in Ottawa), dates available (Jan. 30-Feb. 1), price ($304 CAD), and rating (4.89/5) which allows users to easily scan and compare listings without having to click individual listings for more information.

The GoFundMe examples are quietly horrifying. They show how privatization shifts responsibility downward while masquerading as generosity. When students are crowdfunding heat for schools, the social contract has clearly failed.

This is an intellectually honest moment. By invoking Labaree, Dr. Robin acknowledges that the public/private binary is messy. I appreciate this because it avoids moral absolutism while still insisting that mission matters as much as funding.

There are many types of social groupings in the world, but communities are a form of social grouping where people share a certain story or aspect that has been a part of their life or has become a part of their lives. Communities are a tight group of people with a strong sense of sharing a form of their identity

A community can bring people of like minds together, and it can make people feel happy and positive about what makes them a community. The thing is, though, if their isn't many people in the community, then it can make you feel like you are the only one.

I want to inform my boss that I have gotten sick and will not make it to work to set up the meeting.

noted

noted

the human experience> my experience

not about MY experience with suffering, but about THE human experience of suffering for example, or grief, or love, etc, using my experiences to inform the overall narrative

emotional engagement = impact

I express differently in different situations. In real life, I often listen to another's opinion, while online communication, such as commenting on RedNote were often more sharp and acute, because people will worry less of the relationships with strangers.

This part is really important because it shows us how documents can fail even though the information given is correct. Writing at the wrong level can make instructions not useable.