Weighted gene co-expression network analysis identifies functional modules related to bovine respiratory disease

Nooshin Ghahramani; Ali Hashemi; Bahman Panahi

doi:10.1371/journal.pone.0334688

Peer Review History

Original SubmissionFebruary 15, 2025
9 Jun 2025 Decision Letter - Angel Abuelo, Editor PONE-D-25-08222Weighted gene co-expression network analysis identifies functional modules related to bovine respiratory diseasePLOS ONE Dear Dr. Hashemi, 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. Both reviewers have raised important concerns regarding the manuscript that require extensive revisions for we to consider it further. Please address all the reviewers' comments when/if revising the manuscript. Note the attached file with comments from one of the reviewers. Also, the English language of the manuscript is not at a stage where it would be considered suitable for publication. Please work to revise the language throughout the manuscript for grammar and syntax correctness. Please submit your revised manuscript by Jul 24 2025 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: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . 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 . We look forward to receiving your revised manuscript. Kind regards, Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM 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. We noticed you have some minor occurrence of overlapping text with the following previous publication(s), which needs to be addressed: https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0307248 In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the methods section. 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Please include a separate caption for each figure in your manuscript. [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: Yes Reviewer #2: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: I Don't Know ****** 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 Reviewer #2: 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: Yes Reviewer #2: 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: Thank you for the opportunity to review the manuscript "Weighted gene co-expression network analysis identifies functional modules related to bovine respiratory disease" by Hashemi and colleagues. The investigators of this work sought to perform a meta-analysis of previously published RNA-Seq data specifically focused on bovine respiratory disease. I commend the investigators on their use of previously published literature/data and more novel bioinformatic analysis methods in an effort to corroborate and identify molecular features associated with BRD outcomes. I believe the paper to be technically sound and the results impactful, however a few areas require additional clarity and elaboration prior to publication. Below are my suggestions and questions which may improve the work prior to publication. Line 12 (abstract): The authors highlight their use of a "P-value combination approach" regarding a brief summarization of their methods for the abstract. This is somewhat ambiguous, as their methodology in a combinational approach of WCGNA, machine learning workflows, and statistical methods (ex: DESeq2). The lack of specificity in this sentence may distract future readers finding their abstract in literature searches; they may consider removing this part of the sentence and instead emphasize the aspect of the meta-analysis approach (including the number of studies included). Line 39-42 (and throughout): minor typographical errors and run-on sentences were identified. For example, it is believed that "through" should be "thorough". Additionally, it is unclear how the "identification of key genes" would prevent and control BRD; it is believed that the authors are eluding to how these identifications would lead to the development/employment of early disease detection systems. Line 78-79: it is unclear why the investigators specifically elected to use these five studies. There are additional published studies that have used whole blood as the tissue sample of evaluation (assumed as the connecting theme of these works), but the authors should expand upon the rationale behind these studies. The utility and approach behind performing a meta-analysis-like study in bioinformatics remains a highly contested subject, so it is assumed there are no strict criteria as to how to perform a study of this type. However, the authors should provide context and rationale when possible as this work may be evaluated in the future as a way of performing this type of study (outside of BRD or animal health research). Table 1, citation 20: this citation should be revised; DOI: 10.1016/j.ygeno.2020.07.014 Lines 95-118, methods: the authors utilized previously published RNA-Seq data for their statistical and combinational (p-value) analyses. However, I would express concern regarding the possibility of batch effects/technical bias across these five studies, as the laboratory techniques and bioinformatic processing, including alignment tools and reference assembly, are different across these projects (ex. Sun et al., 2020 utilized TopHat2 and the UMD3.1 genome, Johnston et al., 2021 utilized STAR and the UMD3.1 genome, and the work from the Jiminez, O’Donoghuem and Li publications utilized STAR and the UCD1.2 genome). The way this section is currently written, it is assumed the investigators acquired and combined the raw gene counts from each of these publications (not explicitly stated). The authors are recommend to comment and elaborate on their approach, as without the re-processing of combined raw data nor the use of a batch effect adjustment of raw gene counts (see DOI: 10.1093/nargab/lqaa078), this project risks presenting confounded results. Lines 100-102: which testing procedure was used with DESeq2 (i.e., Wald testing, likelihood ratio testing, etc.)? Line 125: the use of Pearson correlation coefficients with WGCNA (and generally within statistics) are often considered to be limited in interpretation due to the sensitivity to outlier data and risk of estimator bias, especially when applied to data with limited sample size. While the authors of WGCNA have often recommended to have a minimum of 15 samples (well surpassed by this study), they also recommend a more robust coefficient (such as the biweight midcorrelation) and signed networking for adjacency matrix construction. While this technique has been used and published previously, the investigators may comment on the rationale of this aspect of their methods. Lines 130-142: which platform/software/toolkit was used to perform functional enrichment analyses? The authors explain the databases used, but not the specific toolkit (ex. DAVID, WebGestalt, gProfiler, etc.). Lines 154-163: similar to the previous comment, it is unclear what program was utilized here. Additionally, the techniques described are supervised algorithms which require training and cross-validation. Therefore, a confusion matrix should be produced from these algorithms which would have demonstrated the classification statistics (i.e., F1 scores, AUCs, balanced accuracies, recall, precision, etc.). It is assumed that the authors utilized the balanced accuracies as their determination for model selection, but this should be explicitly stated and the full statistics of all models should be provided as a table or supplemental file. Line 231: the values used in the decision tree are not described. Are these adjusted gene count values or do they represent something else? Figures: it may be the formatting within the PDF file, but please ensure that the figures are of high quality/resolution. Specifically, Figure 3 is blurred and the "Fishercomb" header is clipped from the image. Reviewer #2: • The authors should consult a native English speaker to improve the readability of this article. • The authors have a well-organized methods section but should be sure to include sufficient detail for the methods being described. The authors should describe how they searched for datasets to include in their meta-analysis and what inclusion/exclusion criteria were applied. Additionally, the authors should justify their methodological choices (e.g., line 178: removing samples with a standard connectivity score less than -2.5). • The overall structure/organization of the discussion had logical flow. Within each paragraph of the discussion, I encourage the authors to condense and summarize the information rather than discussing each point individually. Coalescing the relevant information into a single overarching statement with better contextualizing the relevance of each outcome on BRD would improve the readability of the discussion. • In general the authors should familiarize themselves with current research on biomarkers in animal health and BRD to be able to more appropriately interpret their findings. ****** 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: Yes: Matthew A. Scott Reviewer #2: 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. Attachments Attachment Submitted filename: Review_Report_PONE-D-25-08222.docx https://doi.org/10.1371/journal.pone.0334688.r001
Revision 1
26 Jul 2025 Author Response Reviewer #1: • 1- Line 12 (abstract): The authors highlight their use of a "P-value combination approach" regarding a brief summarization of their methods for the abstract. This is somewhat ambiguous, as their methodology in a combinational approach of WCGNA, machine learning workflows, and statistical methods (ex: DESeq2). The lack of specificity in this sentence may distract future readers finding their abstract in literature searches; they may consider removing this part of the sentence and instead emphasize the aspect of the meta-analysis approach (including the number of studies included). Dear reviewer, Thank you for your insightful consideration of our manuscript. in current study, comprehensive meta-analysis was performed using P-value combination approach, in the next step, the identified meta genes were subjected the systems biology analysis using weighted gene co-expression network method. Then, the most functionally importance modules and genes were further validated using machine-learning approach. Finally, the critical regulatory network associated with BRD were constructed. 2- Line 39-42 (and throughout): minor typographical errors and run-on sentences were identified. For example, it is believed that "through" should be "thorough". Additionally, it is unclear how the "identification of key genes" would prevent and control BRD; it is believed that the authors are eluding to how these identifications would lead to the development/employment of early disease detection systems. Dear reviewer, Thank you for your insightful consideration of our manuscript. has been extensively investigated (3, 4). Detecting key genes involved in BRD, enables a better understanding of the biological pathways that contribute to disease resistance, particularly those related to immune response and inflammation (5, 6). 3- Line 78-79: it is unclear why the investigators specifically elected to use these five studies. There are additional published studies that have used whole blood as the tissue sample of evaluation (assumed as the connecting theme of these works), but the authors should expand upon the rationale behind these studies. The utility and approach behind performing a meta-analysis-like study in bioinformatics remains a highly contested subject, so it is assumed there are no strict criteria as to how to perform a study of this type. However, the authors should provide context and rationale when possible as this work may be evaluated in the future as a way of performing this type of study (outside of BRD or animal health research). Dear reviewer, Thank you for your insightful consideration of our manuscript. these studies were selected based on several key criteria to ensure the reliability and reproducibility of the results. Only studies that utilized whole blood as the biological sample were included, as this provides consistency in tissue-specific gene expression profiles and minimizes variability introduced by different tissue types. This allows for independent verification, re-analysis, and integration with other datasets as part of meta-analytical approaches. Table 1, citation 20: this citation should be revised; DOI: 10.1016/j.ygeno.2020.07.014. It was revised, please see the citations in the Table 1 4- Lines 95-118, methods: the authors utilized previously published RNA-Seq data for their statistical and combinational (p-value) analyses. However, I would express concern regarding the possibility of batch effects/technical bias across these five studies, as the laboratory techniques and bioinformatic processing, including alignment tools and reference assembly, are different across these projects (ex. Sun et al., 2020 utilized TopHat2 and the UMD3.1 genome, Johnston et al., 2021 utilized STAR and the UMD3.1 genome, and the work from the Jiminez, O’Donoghuem and Li publications utilized STAR and the UCD1.2 genome). The way this section is currently written, it is assumed the investigators acquired and combined the raw gene counts from each of these publications (not explicitly stated). The authors are recommending to comment and elaborate on their approach, as without the re-processing of combined raw data nor the use of a batch effect adjustment of raw gene counts (see DOI: 10.1093/nargab/lqaa078), this project risks presenting confounded results. Dear reviewer, Thank you for your insightful consideration of our manuscript. to minimize the impact of batch effects resulting from variations in experimental protocols, sequencing platforms, alignment tools, and reference genome annotations, we first used a normalization approach implemented in the DESeq2 software. This method effectively reduces unwanted sources of variation commonly encountered in high-throughput sequencing experiments, thereby enhancing the accuracy and comparability of gene expression measurements. Lines 100-102: which testing procedure was used with DESeq2 (i.e., Wald testing, likelihood ratio testing, etc.)? Dear reviewer, Thank you for your insightful consideration of our manuscript. The Wald test was calculated using DESeq2 to assess the statistical significance of DEGs between conditions. 5- Line 125: the use of Pearson correlation coefficients with WGCNA (and generally within statistics) are often considered to be limited in interpretation due to the sensitivity to outlier data and risk of estimator bias, especially when applied to data with limited sample size. While the authors of WGCNA have often recommended to have a minimum of 15 samples (well surpassed by this study), they also recommend a more robust coefficient (such as the biweight midcorrelation) and signed networking for adjacency matrix construction. While this technique has been used and published previously, the investigators may comment on the rationale of this aspect of their methods. Dear reviewer, thank you for your critical reviewing of our manuscript. As you mentioned to increase the reliability of constructed co expression network, we performed the outlier detection step to remove the outliers from the study, moreover, after the removing the outliers the applied samples we higher than 15 samples, which increase the reliability of our study, furthermore, the applied approach were signed method for network construction. 6- Lines 130-142: which platform/software/toolkit was used to perform functional enrichment analyses? The authors explain the databases used, but not the specific toolkit (ex. DAVID, WebGestalt, gProfiler, etc.). Dear reviewer, Thank you for your insightful consideration of our manuscript. To investigate the functional significance of the identified modules, enrichment analysis was carried out based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) using the STRING and DAVID databases (39). This procedure detects biological-processes, molecular-functions, and cellular-components that are crucially over-represented. Detecting over-represented biological and molecular pathways donates valued comprehension of biological mechanisms in BRD. 7- Lines 154-163: similar to the previous comment, it is unclear what program was utilized here. Additionally, the techniques described are supervised algorithms which require training and cross-validation. Therefore, a confusion matrix should be produced from these algorithms which would have demonstrated the classification statistics (i.e., F1 scores, AUCs, balanced accuracies, recall, precision, etc.). It is assumed that the authors utilized the balanced accuracies as their determination for model selection, but this should be explicitly stated and the full statistics of all models should be provided as a table or supplemental file. Dear reviewer, Thank you for your insightful consideration of our manuscript. Supervised machine learning involve training a model on a dataset that includes both input features (genes) and known outputs (healthy or disease status). The process involved in machine learning can be broken down into several key stages: data pre-processing, data splitting, model selection, model training, and model evaluation (41). We employed machine learning algorithms to identify and validate the most significant meta-genes associated with BRD, ensuring precise gene prioritization with optimal accuracy. 9- Line 231: the values used in the decision tree are not described. Are these adjusted genes count values or do they represent something else? Dear reviewer, Thank you for your insightful consideration of our manuscript. the provided values are the normalized expression values of genes. 8- Figures: it may be the formatting within the PDF file, but please ensure that the figures are of high quality/resolution. Specifically, Figure 3 is blurred and the "Fishercomb" header is clipped from the image. Dear reviewer, Thank you for your insightful consideration of our manuscript. we revised and increased the quality of figure. Please see the revision format. Reviewer #2: • The authors should consult a native English speaker to improve the readability of this article. Dear reviewer, Thank you for your insightful consideration of our manuscript. we focused on improving the readability and logical flow of the article. • The authors have a well-organized methods section but should be sure to include sufficient detail for the methods being described. The authors should describe how they searched for datasets to include in their meta-analysis and what inclusion/exclusion criteria were applied. Additionally, the authors should justify their methodological choices (e.g., line 178: removing samples with a standard connectivity score less than -2.5). Dear reviewer, thanks you for your insightful comments, we utilized p-value combination approaches for meta-analysis. as described in methods and material section. To minimize the impact of batch effects arising from variations in experimental protocols, sequencing platforms, alignment tools, and reference genome annotations, normalization and batch effect reduction approach were performed. For WGCNA, Following the removal of outlier samples, the remaining high-quality data were subjected to weighted gene co-expression network analysis to explore the underlying gene expression patterns. The soft-thresholding power (β) was selected by systematically evaluating the scale-free topology fit index (R²) across a range of candidate powers. The optimal β was defined as the smallest power at which the network began to exhibit approximate scale-free properties (R² > 0.8). This selection process ensures that the constructed network reflects the expected biological architecture of gene co-expression, thereby improving the accuracy and interpretability of subsequent module detection and functional analysis. Moreover, the heat map illustrated the TOM values to visualize the degree of interconnectedness among genes within the network modules identified using the dynamic tree cutting algorithm (Fig 4C). Yellow and progressively red colors demonstrate the low and higher TOM values, respectively. The gene expression patterns within each module were condensed into a single representative vector, named the module eigengene, which corresponds to the first principal component derived from the module’s expression data matrix (Fig 4D). • The overall structure/organization of the discussion had logical flow. Within each paragraph of the discussion, I encourage the authors to condense and summarize the information rather than discussing each point individually. Coalescing the relevant information into a single overarching statement with better contextualizing the relevance of each outcome on BRD would improve the readability of the discussion. Dear reviewer, Thank you for your insightful consideration of our manuscript. It was revised. Please see the revision. • In general the authors should familiarize themselves with current research on biomarkers in animal health and BRD to be able to more appropriately interpret their findings. Dear reviewer, Thank you for your insightful consideration of our manuscript. the CFB gene, which regulates cellular senescence, was observed to be upregulated in this study, consistent with previous findings suggesting its role as an immune-related gene during BRD Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0334688.r002
24 Sep 2025 Decision Letter - Angel Abuelo, Editor PONE-D-25-08222R1Weighted gene co-expression network analysis identifies functional modules related to bovine respiratory diseasePLOS ONE Dear Dr. Hashemi, 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 see below some minor change suggestions from the reviewers. Please submit your revised manuscript by Nov 08 2025 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: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . 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 . We look forward to receiving your revised manuscript. Kind regards, Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM Academic Editor PLOS ONE Journal Requirements: If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise. 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. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: (No Response) ******** 2. 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: Yes Reviewer #2: Partly ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: N/A ****** 4. 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 Reviewer #2: 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 Reviewer #2: 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: Thank you for the opportunity to review the revised manuscript. The author's have addressed all comments and made substantial revisions to the manuscript. Reviewer #2: Thank you for addressing the changes so thoroughly. The authors have done a great job improving the discussion by focusing on the results relevant to BRD and contextualizing within their model. Line 29: For consistency please remove the alpha from TNF Line 95-97: I appreciate that the authors have elaborated on their selection process, however i think the this description still needs to be expanded further. As written another researcher does not have sufficient detail to reproduce the article selection. Could the authors include the range of dates that they considered recent research, what was the sample size cut off required for inclusion or exclusion, as well as the keywords used to initially identify articles. Line 118: The description of table 1 still includes species, please remove as that has been removed from the table. Line 326: I caution the authors when discussing oxidative stress not to over interpret their gene expression data. The authors should avoid statements such as “effectively protecting cells against oxidative protein damage” as they did not assess if cells were protected against oxidative protein damage. ****** 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 Reviewer #2: 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.0334688.r003
Revision 2
30 Sep 2025 Author Response Editor, review your reference list to ensure that it is complete and correct. Dear editor, we carefully reviewed all the references from the beginning and re-imported them using EndNote. Some references were duplicates and were removed, while others contained errors, which we also eliminated. We also thoroughly reviewed the entire manuscript for grammar and syntax and applied the necessary corrections. Line 29: For consistency, please remove the alpha from TNF Dear reviewer, we removed the α from TNF Line 95-97: I appreciate that the authors have elaborated on their selection process, however i think this description still needs to be expanded further. As written another researcher does not have sufficient detail to reproduce the article selection. Could the authors include the range of dates that they considered recent research, what was the sample size cut off required for inclusion or exclusion, as well as the keywords used to initially identify articles. Dear reviewer, we restricted our search to studies published between 2020 and 2023, which we considered representative of recent research. To ensure statistical robustness, only studies meeting a predefined minimum sample size were included. Articles were initially identified using the following keywords: “whole blood RNA-seq,” “Bos taurus,” “BRD,” and “gene expression.”" We also reviewed the first part of the Materials and Methods section and applied the necessary corrections. Line 118: The description of table 1 still includes species, please remove as that has been removed from the table. Dear reviewer, we removed species from the text. Line 326: I caution the authors when discussing oxidative stress not to over interpret their gene expression data. The authors should avoid statements such as “effectively protecting cells against oxidative protein damage” as they did not assess if cells were protected against oxidative protein damage. Dear reviewer, oxidative stress removed from the text. Attachments Attachment Submitted filename: Response_to_Reviewers_auresp_2.docx https://doi.org/10.1371/journal.pone.0334688.r004
2 Oct 2025 Decision Letter - Angel Abuelo, Editor Weighted gene co-expression network analysis identifies functional modules related to bovine respiratory disease PONE-D-25-08222R2 Dear Dr. Hashemi, 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 will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. For questions related to billing, please contact billing support . 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, Angel Abuelo, DVM, MRes, MSc, PhD, DABVP (Dairy), DECBHM Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0334688.r005
Formally Accepted
Acceptance Letter - Angel Abuelo, Editor PONE-D-25-08222R2 PLOS ONE Dear Dr. Hashemi, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, 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. You will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing. If we can help with anything else, please email us at customercare@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. Angel Abuelo Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0334688.r006

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