Dear Deepa,

Thank you for submitting your revised manuscript entitled "Mutation bias alters the distribution of fitness effects of mutations" for consideration as a Research Article by PLOS Biology.

Your revisions have now been evaluated by the PLOS Biology editorial staff and the Academic Editor, and I'm writing to let you know that we would like to send your revised version out for re-review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

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Feel free to email us at plosbiology@plos.org if you have any queries relating to your submission.

Kind regards,

Roli

Roland Roberts, PhD

Senior Editor

PLOS Biology

rroberts@plos.org

Attachments

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Submitted filename: ResponseToReviewers.pdf

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Submitted filename: ResponseToReviewers_auresp_1.pdf

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Submitted filename: ReviewerResponse.docx

Dear Deepa,

Thank you for your patience while we considered your revised manuscript "Mutation bias alters the distribution of fitness effects of mutations" for publication as a Research Article at PLOS Biology. This revised version of your manuscript has been evaluated by the PLOS Biology editors, the Academic Editor and two of the original reviewers.

Based on the reviews, we are likely to accept this manuscript for publication, provided you satisfactorily address the remaining points raised by the reviewers. Please also make sure to address the following data and other policy-related requests.

IMPORTANT - please attend to the following:

a) Unfortunately reviewer #3 was unable to re-review; however, we have new comments from both of the others. Reviewer #1 signs off enthusiastically with no further requests. Reviewer #2 concedes that s/he was wrong on one of their previous concerns, but still wants further explanation on the second. S/he also wants you to address some significant presentational issues, and insists (with arguments why) that you include statistical results more prominently in the paper. Please address these remaining requests from reviewer #2.

b) Please address my Data Policy requests below; specifically, we need you to supply the numerical values underlying Figs 2, 3, 4, 5AB, 6ABCD, S1AB, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11ABCD, S12 ABCD, S13ABC, S14, S15ABCDEF, either as a supplementary data file or as a permanent DOI’d deposition. I note that you already supplied the raw data in the existing supplementary data files, but we do also need the values directly underlying each Fig panel.

c) Please cite the location of the data clearly in all relevant main and supplementary Figure legends, e.g. “The data underlying this Figure can be found in S1 Data” or “The data underlying this Figure can be found in https://zenodo.org/records/XXXXXXXX

d) I note that you mention the reviewers ["and three reviewers (including Thomas Bataillon)"] in the Acknowledgements. While we appreciate the sentiment, this is against PLOS policy, so please could you remove it?

e) Please make any custom code available, either as a supplementary file or as part of your data deposition.

As you address these items, please take this last chance to 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 cover letter that accompanies your revised manuscript.

In addition to these revisions, you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests shortly.

We expect to receive your revised manuscript within two weeks.

To submit your revision, please go to https://www.editorialmanager.com/pbiology/ and log in as an Author. Click the link labelled 'Submissions Needing Revision' to find your submission record. Your revised submission must include the following:

- a cover letter that should detail your responses to any editorial requests, if applicable, and whether changes have been made to the reference list

- a Response to Reviewers file that provides a detailed response to the reviewers' comments (if applicable, if not applicable please do not delete your existing 'Response to Reviewers' file.)

- a track-changes file indicating any changes that you have made to the manuscript.

NOTE: If Supporting Information files are included with your article, note that these are not copyedited and will be published as they are submitted. Please ensure that these files are legible and of high quality (at least 300 dpi) in an easily accessible file format. For this reason, please be aware that any references listed in an SI file will not be indexed. For more information, see our Supporting Information guidelines:

https://journals.plos.org/plosbiology/s/supporting-information

*Published Peer Review History*

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https://plos.org/published-peer-review-history/

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Should you, your institution's press office or the journal office choose to press release your paper, please ensure you have opted out of Early Article Posting on the submission form. We ask that you notify us as soon as possible if you or your institution is planning to press release the article.

*Protocols deposition*

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please do not hesitate to contact me should you have any questions.

Sincerely,

Roli

Roland Roberts, PhD

Senior Editor

rroberts@plos.org

PLOS Biology

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DATA POLICY:

You may be aware of the PLOS Data Policy, which requires that all data be made available without restriction: http://journals.plos.org/plosbiology/s/data-availability. For more information, please also see this editorial: http://dx.doi.org/10.1371/journal.pbio.1001797

Note that we do not require all raw data. Rather, we ask that all individual quantitative observations that underlie the data summarized in the figures and results of your paper be made available in one of the following forms:

1) Supplementary files (e.g., excel). Please ensure that all data files are uploaded as 'Supporting Information' and are invariably referred to (in the manuscript, figure legends, and the Description field when uploading your files) using the following format verbatim: S1 Data, S2 Data, etc. Multiple panels of a single or even several figures can be included as multiple sheets in one excel file that is saved using exactly the following convention: S1_Data.xlsx (using an underscore).

2) Deposition in a publicly available repository. Please also provide the accession code or a reviewer link so that we may view your data before publication.

Regardless of the method selected, please ensure that you provide the individual numerical values that underlie the summary data displayed in the following figure panels as they are essential for readers to assess your analysis and to reproduce it: Figs 2, 3, 4, 5AB, 6ABCD, S1AB, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11ABCD, S12 ABCD, S13ABC, S14, S15ABCDEF. NOTE: the numerical data provided should include all replicates AND the way in which the plotted mean and errors were derived (it should not present only the mean/average values).

IMPORTANT: Please also ensure that figure legends in your manuscript include information on where the underlying data can be found, and ensure your supplemental data file/s has a legend.

Please ensure that your Data Statement in the submission system accurately describes where your data can be found.

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CODE POLICY

Per journal policy, if you have generated any custom code during the course of this investigation, please make it available without restrictions. Please ensure that the code is sufficiently well documented and reusable, and that your Data Statement in the Editorial Manager submission system accurately describes where your code can be found.

Please note that we cannot accept sole deposition of code in GitHub, as this could be changed after publication. However, you can archive this version of your publicly available GitHub code to Zenodo. Once you do this, it will generate a DOI number, which you will need to provide in the Data Accessibility Statement (you are welcome to also provide the GitHub access information). See the process for doing this here: https://docs.github.com/en/repositories/archiving-a-github-repository/referencing-and-citing-content

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DATA NOT SHOWN?

- Please note that per journal policy, we do not allow the mention of "data not shown", "personal communication", "manuscript in preparation" or other references to data that is not publicly available or contained within this manuscript. Please either remove mention of these data or provide figures presenting the results and the data underlying the figure(s).

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REVIEWERS' COMMENTS:

Reviewer #1:

Firstly, I apologise for the late submission of this review. I continue to really like this paper and think it is an excellent contribution to the field - adding necessary experimental data to a largely theoretical area. The data are robust, and the experimental design is elegant and appropriate to the hypothesis. The authors have responded thoroughly to reviewer comments, and the manuscript is much improved as a result. I particularly appreciated the additional information provided on mutation calling and fitness estimation, which increased my confidence in the reliability of the results. The finding that bias reversal can increase the proportion of beneficial mutations is compelling and well supported. I congratulate the authors on a lovely piece of work.

Reviewer #2:

The authors have presented a revised submission, responding in a detailed way to 3 different reviews, each of which raised multiple points. I appreciate all of their effort to improve the presentation of this very interesting and important study.

My initial review included a critique that, upon consideration, was partly wrong. I argued that mutY should be excluded from any statistical test due to being used previously to argue the same kind of conclusion, and that the non-independence of mutants means that there are only 4 (or 3) data points, not 7. The first point remains valid and it is a simple matter to take this into account (by dropping the data from mutY but keeping mutT and the others). In careful statistical work, we do not purport to test a hypothesis that was proposed based on prior data in a way that includes the same prior data, because the hypothesis is not independent of that data.

However, the second point is not valid. I argued that mutT and mutY were not independent, and likewise that mut S, L and H were not independent, due to hitting the same pathway. This is why I said there were only 4 data points and not 7. But this isn't really correct for the dependent variable, the DFE. The mutations that hit the same pathway are non-independent for the ti/tv bias (and the mutation spectrum generally), but the DFEs they generate are presumably largely independent because (presumably) they are mostly not sharing the same mutations. It would be useful for the authors to explain this if it is, in fact, true.

I still find problems with the presentation. The scatter-plots and correlations in Fig S3, in my opinion, are best suited to convey the main results. I wish that the figures were not so confusing in their use of color. Figure 4 has 7 different color keys. Fig 1 has a colored gradient and also a separate 3-color scheme. Fig 1 needs to present the logic of a prediction (and perhaps the logic of the theory that drives it): when the independent variable (mutation bias) is shifted, this induces (by biased depletion due to the effect of arrival bias) a shift in the dependent variable (DFE). Having actual numbers for ti/tv bias is a distraction.

The authors repeatedly present results in the main text without providing a statistical finding, somethings doing this using words like "significant". They literally have a sentence that says our results support our predictions without specifying the precise substance of either the results or the predictions! In some cases they have done tests, and in other cases they have made a qualitative comparison, e.g., p. 22 line 9 they are using a qualitative analysis in reaching conclusions about Fig. 4 "In contrast, no other axis of variation in mutation spectrum matched the pattern of variation in fb across strains (compare Figure 4A with Figures 4C-F). "

I want to stress that this is a quantitative empirical paper. The statistical results should be front and center, not something that one has to dig to find. Saying "our results support out conclusions" without immediately backing that up with numbers is not satisfactory.

However, having said all that, the paper has been improved in response to the reviews and it does not need to be perfect. Ideally there will be other papers to follow from this group or from others. So, I would recommend the paper for publication without further revision.

Dear Deepa,

Thank you for the submission of your revised Research Article "Mutation bias alters the distribution of fitness effects of mutations" for publication in PLOS Biology. On behalf of my colleagues and the Academic Editor, Laurence Hurst, I'm pleased to say that we can in principle accept your manuscript for publication, provided you address any remaining formatting and reporting issues. These will be detailed in an email you should receive within 2-3 business days from our colleagues in the journal operations team; no action is required from you until then. Please note that we will not be able to formally accept your manuscript and schedule it for publication until you have completed any requested changes.

Please take a minute to log into Editorial Manager at http://www.editorialmanager.com/pbiology/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

PRESS: We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with biologypress@plos.org. If you have previously opted in to the early version process, we ask that you notify us immediately of any press plans so that we may opt out on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

Thank you again for choosing PLOS Biology for publication and supporting Open Access publishing. We look forward to publishing your study. 

Sincerely, 

Roli

Roland G Roberts, PhD, PhD

Senior Editor

PLOS Biology

rroberts@plos.org