Dear Dr. Mariani,

Thank you very much for submitting your manuscript "A systems genomics approach uncovers molecular associates of RSV severity" 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.

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.

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

[1] A letter containing a detailed list of your responses to the 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.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. 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,

Anders Wallqvist

Associate Editor

PLOS Computational Biology

Florian Markowetz

Deputy Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: 1. METHODS: RNA PROCESSING: Pearson correlation testing of gene expression and GRSS: please specify what kind of normalization and transformation methods are used for correlation. RNA-seq data is not normally distributed.

2. METHODS: PATHWAY ANALYSIS: Combined feature weights used for pathway analysis were compared to the results without those weights – where is this data?

3. RESULTS: 139 infants were enrolled, but supplemental figure 2 represents only 134 subjects

4. RESULTS: Table S1. Subsets of CD4, CD8 and CD19 were sorted from PBMC, what is the range of cell numbers for each population? Why only some lymphocyte RNA-seq data was available for certain infants? Is this because low cell number count for some patients?

5. RESULTS: Figure 2. It would be nice to explain different colors in figure legend.

6. RESULTS: Do you have flow cytometry data of the nasal epithelial cells to show similar cell number/type for each subject? Just to make sure the gene expression difference is not due to the difference in cells present in different cell population.

7. RESULTS: INTEGRATED METHOD DEVELOPMENT: Supplementary Tables 2&3 don’t actually show the comparison between the PCA/elastic net model and other methods for GRSS prediction? Where is the prediction accuracy of method 1 and other methods?

8. RESULTS: Figure 4: what do the colors in the plot for the TFs mean? Please provide color scale key.

9. SUPPLEMENTAL INFO: FEATURE WEIGHT CALCULATION: 2ND PARAGRAPH: Methods 3 and 5 use a secondary PCA, not method 4.

Reviewer #2: Integrative analyses of gene expression data from airway epithelial cells and immune cells with the airway microbiome with the objective to understand host response associated with infant RSV infection severity. The investigators used elastic net regularized regression method, which is a reasonable approach. The findings are interesting and many support prior published literature on the involvement of specific immune pathways and airway microbiome associations. The application of methods to support the integration of high dimensional multi-omics data to understand infant RSV infection severity is novel.

MAJOR COMMENTS:

- Many of the findings support prior individual associations, which while perhaps arguing it decreases novelty, it supports the approach taken.

- A major recognized limitation is the small sample size, but not discussed is the possibly non-random missing data.

- There is no description of cohort participants used in this analysis, specifically age of infants, time from symptom onset to collection of specimens, infant sex, antibiotic administration, and how these covariates were included in the analyses. The infant age, sex, RSV strain and time from symptom onset to collection of biospecimens could well be different based on disease severity and impact the measured host responses. Only a small subset of subjects have all data types, and there is no description of the group of 23 infants with all data types, nor the groups of 61 and 35 subjects, nor the distribution by heathcare or GRSS. It isn’t clear how or if the associations between key covariates and outcomes were included. This is particularly important for sex, infant age at time of infection, RSV strain, and time from symptom onset to sample collection.

- It is also unclear if the described 3 week follow-up biospecimens were used or could be used in these analyses to represent baseline or resolution, or if they were or could be compared with data from acute infection to assess change.

- There should be a discussion of study limitations, as well as a more robust discussion of what supports confidently knowing that L1L1 or L2L2 is the true model.

Minor comments:

- Review articles are cited to support prior findings, and the primary source should be cited in support of specific prior findings

- A number of the individually described findings have been previously published, and these should both be recognized and those manuscripts cited

- Looking at the demographics of the study population in the referenced published methods manuscript, these aren’t “full-term”, but rather “term” infants.

- Methods/”Weight assignment and transcription factor analysis” sub-section. The second to last sentence in this section seems to be missing a key word describing the methods.

Reviewer #3: The manuscript looks original and well organized. Sometimes the reading results not fluent due to the technical details.

Major revisions:

1. The total number of the infant whose RT-PCR confirmed RSV illness is 139. And also, 61 subjects are in the first set and 35 in the second. Do the authors suspect that the number of patients too small? Can this small number of patients be enough to conduct an integrative analysis and deduce general results?

2. The authors used some "preliminary exploratory analyses" to drive the research. Please, can the authors specify which kind of preliminary analyses have been conducted?

3. In the same section ("Results", lines 14-17 ), the authors used some generic words as, "relatively weak", "strong correlation", "weak features". Please, try to support with numerical evidence (tables, percentage, graphs) your assertions.

4. In the same section (Results, line 16), the authors refer to the use of an "appropriate dimension reduction". Please, can you specify which kind of dimension reduction and support your choice?

5. In the same section (Results, line 21), the authors refer to a "shared variation between data types". Please, can you document it?

5. In the section "Model application and interpretation" (line 11-24 and so on), the authors used some generic words as "clearly", "evident", "highest weighted", "unweighted", "high degree", "majority", "significantly activated", etc. Please, can the author try to support these sentences with numerical evidence?

Minor revisions:

1. Supplementary figure 2. It could be better to use a different color for the column with a value of 23

2. Section "Model application and interpretation" (line 20). Please, can the authors better specify which figure they are referring to? It is easy to be lost.

3. Section "Model application and interpretation" (line 28). Please, the authors should insert the reference for the "Ingenuity" application

4. Section "Model application and interpretation" (line 28). The authors mention "Ingenuity suggested that ...": where are the results? In which figure?

5. Section "Model application and interpretation" (line 35). The authors mention "upper right/Panel D": In which figure?

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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: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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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.

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Reviewer #1: Yes: Zhaohui Xu

Reviewer #2: No

Reviewer #3: Yes: Emilio Mastriani, PhD

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

Dear Dr. Mariani,

Thank you very much for submitting your manuscript "A systems genomics approach uncovers molecular associates of RSV severity" 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.

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,

Anders Wallqvist

Associate Editor

PLOS Computational Biology

Florian Markowetz

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]

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: it looks good to me

Reviewer #2: The authors have been responsive to the reviewer comments and the manuscript is improved and addresses and intersting question taking a novel and challenging approach. There remains the significant limitation of the sample size and multiple testing. It would be preferable to include a statement to the methods section and the limitations section of the discussion to explain that the findings may be due to type I error due to multiple testing, this may not be obvious to all readers and would be preferable to state.

Suggest adding to the methods and limitations something along the lines of:

We applied a significance threshold for association using a a 2-sided p<0.05 without adjustment for multiple testing, such that findings should be considered exploratory.

Reviewer #3: I wish to thank the authors for their professionality. The article appears to be ready for publication and relevant to the scientific community.

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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: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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

Reviewer #3: Yes: Emilio Mastriani

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.

Dear Dr. Mariani,

We are pleased to inform you that your manuscript 'A systems genomics approach uncovers molecular associates of RSV severity' 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.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

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,

Anders Wallqvist

Associate Editor

PLOS Computational Biology

Florian Markowetz

Deputy Editor

PLOS Computational Biology

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