Dear Prof. Robinson-Rechavi,

Thank you very much for submitting your manuscript "Rhythmicity is linked to expression cost at the protein level but to expression precision at the mRNA level" for consideration at PLOS Computational Biology.

As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

Generally I think this topic is interesting and very important to the circadian field. However, there are some substantial concerns that need to be addressed before its publication.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

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[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

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Sincerely,

Guang-Zhong Wang

Guest Editor

PLOS Computational Biology

Ville Mustonen

Deputy Editor

PLOS Computational Biology

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Generally I think this topic is interesting and very important to the circadian field. However, there are some substantial concerns that need to be addressed before its publication.

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: Please see the attached.

Reviewer #2: The author compared the expression levels of rhythmic and non-rhythmic proteins, and concluded that the abundance of rhythmic proteins in arabidopsis, mouse and ostreococcus was higher than that of non-rhythmic proteins, and further calculated the energy consumption of proteins according to the protein abundance, and found that the cost of rhythmic proteins was higher than that of non-rhythmic proteins.

Major comments

1) I am not an expert in proteomics, but according to my knowledge, the proteomics data of mouse liver and cyanobateria used by the authors used SILAC and TMT for protein quantitation respectively, both of which are relatively quantitative methods. Because of the different ionization efficiencies of different peptides, it is not possible to directly compare MS signals of different peptides to determine their abundance in samples, but peaks with the same peptide can be compared in different samples (PMID: 30609196). I checked the data and code using to calculate mouse liver data from Mauvoisin et al., which was used by the author. Although the calculation code was provided, the annotation was not very clear. I think the author used Ratio H/L as the expression of protein abundance. However, Ratio H/L refers to the intensity of each peptide relative to the ratio of the same peptide in the MIX group, which cannot be used for comparison between different proteins. The current relative quantitative method that can be used for comparing proteins can be quantified by label free, processed by MaxQuant, and compared with the IBAQ value therein.

2) The authors calculated the energy expended in protein translation, but not in RNA transcription. The authors assume that the energy cost of RNA transcription is negligible compared to that of protein translation. This is possible in terms of calculating the total energy of transcription and translation, but on the other hand, transcription takes place in the nucleus, and its energy use might be thought of as being in a relatively closed system. Is it possible to calculate the energy of RNA transcription alone? Do the authors think such calculations have biological significance? If agree, I suggest that this work be supplemented.

3) In the absence of other data, the authors have to assume that this noise calculated at the transcriptional level is representative of noise at the protein level, or in any case functionally relevant. I don't think this is a reasonable estimate because the error is too large to make the protein noise calculated using this assumption meaningful. Perhaps the authors should have used other methods to estimate the amount of protein and protein noise from single cell data, for example, ribosome profiling. Or the author can discuss the error of the estimation.

Minor comments

1) To test the hypothesis that genes tend to be rhythmic in the tissues in which they are highly expressed, the authors used a mouse circadian dataset with 11 tissues (transcriptomics from Zhang et al. (2014), Supplementary Table S2). As far as I know, that dataset includes a total of 12 mouse tissues. What about the other tissues? If a selection was made, perhaps the author should state the criteria in the data section.

2) In this paper, gene expression noise is a very important concept. Although the author directly uses the calculation method by Barroso et al. (2018) when quantifying noise expression, I think it is still necessary to explain the quantification process of noise and the biological significance of noise in more detail in the method section.

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

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Reviewer #1: No

Reviewer #2: No

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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. 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 us at figures@plos.org.

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To enhance the reproducibility of your results, we recommend that 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 to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Attachments

Attachment

Submitted filename: LaloumPlosCompBioReview.pdf

Attachment

Submitted filename: comments.docx

Dear Prof. Robinson-Rechavi,

Thank you very much for submitting your manuscript "Rhythmicity is linked to expression cost at the protein level but to expression precision at the mRNA level" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

The second reviewer still has some points need to be carefully addressed.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Guang-Zhong Wang

Guest Editor

PLOS Computational Biology

Ville Mustonen

Deputy Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

The second reviewer still has some points need to be carefully addressed.

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: Please see attached.

Reviewer #2: I am glad that the authors have given detailed replies to my previous comments.

In my last review, I mentioned that the abundance of different proteins obtained by previous quantitative methods cannot be compared with each other. The authors reanalyzed it in this revision. It's nice to see that the new results are slightly different from the previous results that there is no change in the conclusions. However, the authors’ reply is not very clear about how to improve the method. I think the authors have moved from analyzing the abundance at the protein level to the peptide level. Is my understanding correct?

As for the second question I mentioned earlier, “whether it is necessary to calculate mRNA-related expression energy”, the authors calculated that the energy required to produce protein was more than 160 times that of mRNA, and the energy cost of protein was much higher than that of mRNA. Therefore, it makes sense to consider just the protein without needing to be very elaborate. I think the explanation given by the author is reasonable.

As for another comment, that transcriptional noise is not representative of translation noise, I would like to thank the authors for providing relevant article on the fact that transcriptional noise is a major source of noise in bacteria. This substitution makes sense in bacteria and yeast. Unfortunately, there is no data on multicellular species, which would make this paper more rigorous.

The author has answered the reasons why the hypothalamus was not included in the analysis. I think the reasons given are reasonable.

In addition, I have a new suggestion for the author to consider.

Major comments

1)As briefly mentioned in the manuscript, other factors such as ‪protein-protein misinteractions, undesirable enzyme activities or antagonistic pleiotropy may also explain the rhythmicity of gene transcription. The authors should provide strong evidences to exclude the possibility that those factors can lead to noise reduction in ‪rhythmic mRNAs.

And no more other comments.

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code 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 and code 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 or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: None

Reviewer #2: None

**********

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

Reviewer #2: No

Figure 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. 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 us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, we recommend that 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 to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

References:

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.

Attachments

Attachment

Submitted filename: LaloumPlosCompBioReviewRevision.pdf

Attachment

Submitted filename: comments.docx

Dear Prof. Robinson-Rechavi,

We are pleased to inform you that your manuscript 'Rhythmicity is linked to expression cost at the protein level but to expression precision at the mRNA level' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted 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.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

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Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology. 

Best regards,

Guang-Zhong Wang

Guest Editor

PLOS Computational Biology

Ville Mustonen

Deputy Editor

PLOS Computational Biology

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