Evolution of default genetic control mechanisms

William Bains; Enrico Borriello; Dirk Schulze-Makuch

doi:10.1371/journal.pone.0251568

Peer Review History

Original SubmissionJanuary 6, 2021
18 Feb 2021 Decision Letter - Ernesto Perez-Rueda, Editor PONE-D-21-00488 Evolution of default genetic control mechanisms PLOS ONE Dear Dr. Bains, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Apr 04 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols We look forward to receiving your revised manuscript. Kind regards, Ernesto Perez-Rueda Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: In this manuscript, motivated by the switch from “default on” to “default off” logic during the eukaryogenesis, the authors built a model to simulate the evolution of the default mode of gene expression and test the correlation between the mode and various model parameters. While I appreciate the authors’ efforts, I have several doubts on different components of the simulation, which makes me question how much the simulation can tell us on the biological questions. First of all, there is probably a problem in the fundamental definition of “default off” logic. In Line 115, the authors stated, “We argue that this ‘Default off’ logic is more efficient if the majority of the genome is silent.” Is this tautology? I think “the majority of the genome is silent“ is just synonymous with the “default off” logic. Second, the assumptions about “environments” is not very clear. And the underlying biological reasoning is not clear as well. In Fig 3A-B, the authors demonstrated a simple case under a certain environment. Then suddenly in Fig 3C, there are three environments. Both the purpose of increasing the number of environments and the biological scenarios to depict by the increase are not very clear. Especially, the author attempted to test the hypothesis on the environmental complexity and the evolution of the default mode. Presumably, the optimal goal of gene control is to express different certain sets of genes at different time or at different habitats. That could be modeled by fluctuations with these “environments.” But in this study, it seems that the environmental complexity only represents the number of possible environments existed for matching instead of frequent alternations among possible environments with time. I am really curious if using the fluctuating environments would lead to different conclusions. Also, I have doubts on the measurements for “default off” and “default on” logic. While I understand why the shorter elements have a higher likelihood to be active in the model, that does not seem to reflect the real biology of gene regulation/control. The activity of elements is usually determined by the matching specificity between the sequence of regulatory elements and the regulatory molecules in the environments. It is not easy to rationale the biological meaning on the role of length in the simulation here. After all, I feel the evolution of "default off" logic results from the gains of negative elements with strong specificity instead of the decreasing specificity of negative elements for spurious interactions. Of course, whether this is true requires more empirical data. Finally, the author stated they found a “striking” correlation between the fraction of expressed genes and the tendency of “default on” logic. But if the “default on” logic suggests that more positive elements are active, isn’t the higher fraction of expressed genes just a natural outcome of that? Minor comments: In Fig 2a, why the arrow of transcription is from the phenotype to genotype? It should be opposite. In Fig 2b, what “ve” means should be explained in more details in the text around page 6. There is an error on reference format in Line 193. I appreciate the authors have considered the percentage to full adaptation and illustrated cases of adaptation very clearly. But I would further encourage the authors to also run the simulation without any fitness differences in the model at all and see if non-adaptation parameters in the models (e.g. mutation rates and choice of measurements) are sufficient to create the correlations (a negative control of the methodology). ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0251568.r001
Revision 1
29 Mar 2021 Author Response [Auth] We are grateful to the reviewer for their detailed comments. We provide a formatted version of our response uploaded with the MSS. In that, the reviewer's comments are in bold, our responses are in plain test. Here we flag our responses with [Auth]. Line numbers refer to the Track Changes version of the revised paper. First of all, there is probably a problem in the fundamental definition of “default off” logic. In Line 115, the authors stated, “We argue that this ‘Default off’ logic is more efficient if the majority of the genome is silent.” Is this tautology? I think “the majority of the genome is silent“ is just synonymous with the “default off” logic. [Auth] We apologise for not making this clearer. The concept of a ‘default off’ logic is that the genome controls are structured such that it is ‘easier’ for a gene to be inactive than to be active. Specifically, more metabolic energy needs to be expended to turn a gene on in a ‘default off’ genome. This does not mean that genes are inactive. The entire genome could be active at the same time in a ‘default off’ genome – that would just take a lot more metabolic energy to achieve than in a ‘default on’ genome. [Auth] To use an analogy, it requires less energy for a human to be sitting down than running. Our ‘default’ state is sitting down and (relatively) inactive. That is not to say that marathons, where everyone is running, cannot happen, just that they take energy to make happen. [Auth] We have made this point explicitly in lines 118 – 124., and added some additional text to line 97 – 99 and 396 Second, the assumptions about “environments” is not very clear. And the underlying biological reasoning is not clear as well. In Fig 3A-B, the authors demonstrated a simple case under a certain environment. Then suddenly in Fig 3C, there are three environments. Both the purpose of increasing the number of environments and the biological scenarios to depict by the increase are not very clear. [Auth] We have revised the text around this substantially, adding new explanation in lines 204 - 215. In essence, the complexity of the environment to which a genotype adapts could be a single complex environment (say, a rainforest) or several simpler environments which alternate (say, a tidal pool at high and low tide). We have tried to make the rationale for including both in our model clearer. [Auth] Figure 3C was included to illustrate that the model does adapt when presented with multiple alternating environments, but if the reviewer thinks this is confusing and does not help understanding, we can remove this illustration. Especially, the author attempted to test the hypothesis on the environmental complexity and the evolution of the default mode. Presumably, the optimal goal of gene control is to express different certain sets of genes at different time or at different habitats. [Auth] This is our expectation, yes, and the model is built around this idea That could be modeled by fluctuations with these “environments.” But in this study, it seems that the environmental complexity only represents the number of possible environments existed for matching instead of frequent alternations among possible environments with time. I am really curious if using the fluctuating environments would lead to different conclusions. [Auth] We also were interested in this! We have expanded our discussion of the environmental parameters in lines 202 – 213 and 375 - 380. We have also addressed this with some additional analysis, which shows that whether the environment fluctuates or not does affect the correlation of environment with default genetic mode. However it suggests that fluctuating environments are weakly correlated with ‘default on’ genetics, which is not what we would expect. We discuss this briefly (lines 369 – 373). We have not explored enough of the parameter space to see if the rate of fluctuation or the number of different environments has an effect. Also, I have doubts on the measurements for “default off” and “default on” logic. While I understand why the shorter elements have a higher likelihood to be active in the model, that does not seem to reflect the real biology of gene regulation/control. The activity of elements is usually determined by the matching specificity between the sequence of regulatory elements and the regulatory molecules in the environments. It is not easy to rationale the biological meaning on the role of length in the simulation here. After all, I feel the evolution of "default off" logic results from the gains of negative elements with strong specificity instead of the decreasing specificity of negative elements for spurious interactions. Of course, whether this is true requires more empirical data. [Auth] The reviewer brings up a very good point. In Eukaryotes controls with very little sequence specificity (analogous to short sequences in our model) are common in the folding and compaction of chromatin, e.g. the binding of H2A/H2B histone pair to nucleosomes, which require energy to remove but are essentially sequence-agnostic. This is accurately captured by our model. However other controls are likely to be sequence specific. [Auth] We have therefore re-analysed the model runs to ask whether negative elements that interact with ‘coding’ sequences present in the same cell also show correlations with genome or environmental factors (lines 309 – 312, 336 – 350 and new columns in Table 1). This explicitly probes the regulatory sequence + regulator pair that the reviewer mentions. We have added this analysis to Table 1. The result show very similar correlations to the existing model. Finally, the author stated they found a “striking” correlation between the fraction of expressed genes and the tendency of “default on” logic. But if the “default on” logic suggests that more positive elements are active, isn’t the higher fraction of expressed genes just a natural outcome of that? [Auth] As above, ‘default on’ means that it is ‘easier’ to turn a gene on, not that it necessarily is on under any selective regime. We agree that the result is ‘obvious’, but to our knowledge it has not been pointed out before that the nature of the gene control architecture of eukaryotes is best suited to a genome that is mostly not expressed at any one time. Minor comments: In Fig 2a, why the arrow of transcription is from the phenotype to genotype? It should be opposite. [Auth] Correct – our apologies! We have corrected this. In Fig 2b, what “ve” means should be explained in more details in the text around page 6. [Auth] We have added some text on this, in lines 156 - 157 There is an error on reference format in Line 193. [Auth] We have corrected this I appreciate the authors have considered the percentage to full adaptation and illustrated cases of adaptation very clearly. But I would further encourage the authors to also run the simulation without any fitness differences in the model at all and see if non-adaptation parameters in the models (e.g. mutation rates and choice of measurements) are sufficient to create the correlations (a negative control of the methodology). [Auth] This is a good idea, and we thank the reviewer for it. We have now carried out a set of ‘control’ model run where replication was uncoupled from fitness, and have included details of these in the revised paper, in a new section 3. (lines 423 - 441). This exercise did uncover a bias in one measure, which explains why this measure was more poorly correlated with outcomes. Attachments Attachment Submitted filename: Response to reviewers V 3.0.docx https://doi.org/10.1371/journal.pone.0251568.r002
20 Apr 2021 Decision Letter - Ernesto Perez-Rueda, Editor PONE-D-21-00488R1 Evolution of default genetic control mechanisms PLOS ONE Dear Dr. Bains, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. ============================== ACADEMIC EDITOR: I consider that the manuscript is adequate to be published in PLOS ONE previous to clarify the reviewer concerns associated the section of "Existing genome’ measures". Please, clarify the definition and its consistence witht eh R_a and R_m definitions, and their posterior discussion. ============================== Please submit your revised manuscript by Jun 04 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. 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Kind regards, Ernesto Perez-Rueda Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. 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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: All of my previous questions are well addressed. But I have new questions for the newly added section of ‘Existing genome’ measures. In Line 343~344, the statement suggests that larger E_g means a more likely "default-on" mode. This definition is not consistent with the definitions of R_a and R_m, whose larger values suggest a more likely "default-off" mode (Line 315~317 + Line 326~328). Then, with that inconsistency, in the table 1, why do they tend to show the same sign of correlation coefficients for various model parameters? I hope the authors can check the definitions of these measurements, make these measurements more consistent with each other if possible, and clarify whether these different measures lead to similar correlations in the modified manuscript. One typo in the manuscript: L316- two equal signs in the equation? ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0251568.r003
Revision 2
27 Apr 2021 Author Response Reviewer #1: All of my previous questions are well addressed. But I have new questions for the newly added section of ‘Existing genome’ measures. In Line 343~344, the statement suggests that larger E_g means a more likely "default-on" mode. This definition is not consistent with the definitions of R_a and R_m, whose larger values suggest a more likely "default-off" mode (Line 315~317 + Line 326~328). Then, with that inconsistency, in the table 1, why do they tend to show the same sign of correlation coefficients for various model parameters? I hope the authors can check the definitions of these measurements, make these measurements more consistent with each other if possible, and clarify whether these different measures lead to similar correlations in the modified manuscript. We understand the reviewer’s confusion, and apologise for not explaining this more clearly. In all measures, a value of <1 is associated with a ‘default off’ mode. In the ‘new gene’ modes, regulatory element length is inversely related to the probability that that element is active. So length(negative elements)/length(positive) elements is <1 if the length of the negative elements is shorter than the length of the positive elements, and hence the probability of the negative elements being active is larger than the probability of the positive elements being active. For the ‘existing genome’ measures we are measuring actual activity, not the chance of activity through matching to a random sequence. So if positive/negative <1, more negative elements are active than positive ones. This was not made clear in the text, and we have added some text to try to remedy this. We hope it is better explained now. The wording in lines 315-317 and 326-328 was also ambiguous, and suggested that high values of Ra and Rm meant ‘default off’. In Table 1 it was correctly stated that for all measures <1 implied ‘default off’. We have corrected this wording. One typo in the manuscript: L316- two equal signs in the equation? Thank you, yes this was an error, now corrected. We have also added a reference to the introduction to a recent Nature paper on proteins in chromatin structure in Yeast, which has some relevance. Attachments Attachment Submitted filename: PLoS reply to reviewer round 2.docx https://doi.org/10.1371/journal.pone.0251568.r004
29 Apr 2021 Decision Letter - Ernesto Perez-Rueda, Editor Evolution of default genetic control mechanisms PONE-D-21-00488R2 Dear Dr. Bains, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Ernesto Perez-Rueda Academic Editor PLOS ONE Additional Editor Comments (optional): I consider that the manuscript is scientifically suitable for publication. Reviewers' comments: https://doi.org/10.1371/journal.pone.0251568.r005
Formally Accepted
4 May 2021 Acceptance Letter - Ernesto Perez-Rueda, Editor PONE-D-21-00488R2 Evolution of default genetic control mechanisms Dear Dr. Bains: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Ernesto Perez-Rueda Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0251568.r006

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