Digital gene expression analyses of mammary glands from meat ewes naturally infected with clinical mastitis

Clinical mastitis in sheep has gravely restrained production performance for a long time. Knowledge of mechanisms of its pathogenesis and resistance in meat sheep mammary gland with clinical mastitis are not yet understood, especially for clinical mastitis caused by natural infection. In this work, RNA-sequencing was firstly used to screen the differentially expressed genes (DEGs) in clinical mastitic mammary tissues (CMMTs) when compared with healthy mammary tissues (HMTs) from meat sheep flocks. We identified 420 DEGs including 316 upregulated and 104 downregulated genes in CMMTs. Gene ontology annotation revealed these DEGs were mainly engaged in immune response and inflammation response. Pathway enrichment showed they were primarily enriched in pathways relevant to inflammation, immune response and metabolism. Alternative splicing analysis showed most common differential splicing genes in CMMTs and HMTs were implicated in immune response. Immunostaining for three immune response-related proteins encoded by DEGs were mainly observed in mammary epithelium from both CMMTs and HMTs, and their positive signals were more intensive in CMMTs than those in HMTs. These findings provide experimental basis and reference for further researching the molecular genetic mechanisms, particularly immune defence mechanisms, of sheep mammary gland during clinical mastitis.


Material and Methods:
The authors talk about natural infection-clinical mastitis without clarifying which was the causing agent. Did they perform microbiological analysis to identify the responsible pathogen? Was the responsible pathogen the same for all three cases? Line 22: The current reference genome version is Ovis aries v3.1. The authors mention that they are using Oar_v4.0 genomic dataset. Could the authors give some more details on these? Line 36: I assume that the P <0.05 is the uncorrected P value and not the adjusted after FDR correction. I am wondering how many genes remain significantly differentially expressed after adjusting for multiple testing using FDR correction. A P <0.05 is a very mild threshold and the results could be false positive. This should be amended and the genes which are presented as differentially expressed should be the ones which remain significant after correcting for multiple testing. Did you find in the two groups any differentially spliced genes?

26-Mar-2019
Dear Dr Li, The editors assigned to your paper ("Digital gene expression analyses of mammary glands from meat ewes naturally infected with clinical mastitis") have now received comments from reviewers.
While one reviewer is positive about publication of your paper, the other reviewer raises some substantive comments on significance thresholds and the analysis of expression data. It will be important to address carefully these comments in your revision.
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• Authors' contributions All submissions, other than those with a single author, must include an Authors' Contributions section which individually lists the specific contribution of each author. The list of Authors should meet all of the following criteria; 1) substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data; 2) drafting the article or revising it critically for important intellectual content; and 3) final approval of the version to be published.
All contributors who do not meet all of these criteria should be included in the acknowledgements.
We suggest the following format: AB carried out the molecular lab work, participated in data analysis, carried out sequence alignments, participated in the design of the study and drafted the manuscript; CD carried out the statistical analyses; EF collected field data; GH conceived of the study, designed the study, coordinated the study and helped draft the manuscript. All authors gave final approval for publication.
• Acknowledgements Please acknowledge anyone who contributed to the study but did not meet the authorship criteria. Comments to the Author(s) The manuscript describes transcriptomic changes in mammary glands of sheep affected with clinical mastitis compared to healthy mammary tissues. The study resulted in the typical long list of DEGs, that were subsequently grouped into a meaningful functional categorization. Validation of RNA-seq results was done for a few genes with RT-qPCR and immunohistochemistry. The study was well-conducted and as transcriptome data of clinical mastitis in sheep are yet not available it represents an important addition to literature.

Reviewer: 2
Comments to the Author(s) This is an interesting manuscript studying the transcriptome signature of clinical mastitis in sheep. Although the manuscript is well written, the sample size is small and the authors used very mild significant thresholds. Stricter significant thresholds-at least adjusting for multiple testing-should be performed for the Differential Expression analysis. All the analysis related to co-expression, pathway and network analysis etc should be repeated using only the DE results after adjusting for multiple testing using for example FDR correction. Moreover, the whole discussion should be re-written in a more focused way with in depth comparisons among the present studies and previous studies on the topic. The authors also miss recent publications on the topic for example https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3982-1 Material and Methods: The authors talk about natural infection-clinical mastitis without clarifying which was the causing agent. Did they perform microbiological analysis to identify the responsible pathogen? Was the responsible pathogen the same for all three cases? Line 22: The current reference genome version is Ovis aries v3.1. The authors mention that they are using Oar_v4.0 genomic dataset. Could the authors give some more details on these? Line 36: I assume that the P <0.05 is the uncorrected P value and not the adjusted after FDR correction. I am wondering how many genes remain significantly differentially expressed after adjusting for multiple testing using FDR correction.
A P <0.05 is a very mild threshold and the results could be false positive. This should be amended and the genes which are presented as differentially expressed should be the ones which remain significant after correcting for multiple testing. Did you find in the two groups any differentially spliced genes?
Author's Response to Decision Letter for (RSOS-181604.R0) See Appendix A.

Do you have any ethical concerns with this paper? No
Have you any concerns about statistical analyses in this paper? No

Recommendation?
Accept with minor revision (please list in comments)

Comments to the Author(s)
The authors have done a good job addressing previous comments and revising the manuscript accordingly. I am happy with the current version of the manuscript. My only concern is the English writing of the manuscript which needs some further improvement.
Minor comments below: Line 15 page 2 Introduction: is this indigenous sheep breed meat or dairy? Line 52 page 2 M&M: change the "is both caused" with "were both caused" Page 8 line 48 discussion: change "compare with" to "compare to" Page 8 line 57 discussion: change "in accord" with "in accordance" Page 9 lines 53-55: the sentence should be re-written to make better sense.

30-May-2019
Dear Dr Li: On behalf of the Editors, I am pleased to inform you that your Manuscript RSOS-181604.R1 entitled "Digital gene expression analyses of mammary glands from meat ewes naturally infected with clinical mastitis" has been accepted for publication in Royal Society Open Science subject to minor revision in accordance with the referee suggestions. Please find the referees' comments at the end of this email.
The reviewers and Subject Editor have recommended publication, but also suggest some minor revisions to your manuscript. Therefore, I invite you to respond to the comments and revise your manuscript.
• Ethics statement If your study uses humans or animals please include details of the ethical approval received, including the name of the committee that granted approval. For human studies please also detail whether informed consent was obtained. For field studies on animals please include details of all permissions, licences and/or approvals granted to carry out the fieldwork.
• Data accessibility It is a condition of publication that all supporting data are made available either as supplementary information or preferably in a suitable permanent repository. The data accessibility section should state where the article's supporting data can be accessed. This section should also include details, where possible of where to access other relevant research materials such as statistical tools, protocols, software etc can be accessed. If the data has been deposited in an external repository this section should list the database, accession number and link to the DOI for all data from the article that has been made publicly available. Data sets that have been deposited in an external repository and have a DOI should also be appropriately cited in the manuscript and included in the reference list.
If you wish to submit your supporting data or code to Dryad (http://datadryad.org/), or modify your current submission to dryad, please use the following link: http://datadryad.org/submit?journalID=RSOS&manu=RSOS-181604.R1 • Competing interests Please declare any financial or non-financial competing interests, or state that you have no competing interests.
• Authors' contributions All submissions, other than those with a single author, must include an Authors' Contributions section which individually lists the specific contribution of each author. The list of Authors should meet all of the following criteria; 1) substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data; 2) drafting the article or revising it critically for important intellectual content; and 3) final approval of the version to be published.
All contributors who do not meet all of these criteria should be included in the acknowledgements.
We suggest the following format: AB carried out the molecular lab work, participated in data analysis, carried out sequence alignments, participated in the design of the study and drafted the manuscript; CD carried out the statistical analyses; EF collected field data; GH conceived of the study, designed the study, coordinated the study and helped draft the manuscript. All authors gave final approval for publication.
• Acknowledgements Please acknowledge anyone who contributed to the study but did not meet the authorship criteria.
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Once again, thank you for submitting your manuscript to Royal Society Open Science and I look forward to receiving your revision. If you have any questions at all, please do not hesitate to get in touch. Comments to the Author(s) The authors have done a good job addressing previous comments and revising the manuscript accordingly. I am happy with the current version of the manuscript. My only concern is the English writing of the manuscript which needs some further improvement.
Minor comments below: Line 15 page 2 Introduction: is this indigenous sheep breed meat or dairy? Line 52 page 2 M&M: change the "is both caused" with "were both caused" Page 8 line 48 discussion: change "compare with" to "compare to" Page 8 line 57 discussion: change "in accord" with "in accordance" Page 9 lines 53-55: the sentence should be re-written to make better sense.

Comments from the Editorial Office:
For information about language editing services endorsed by the Royal Society, please follow the link below: https://royalsociety.org/journals/authors/language-polishing/ Author's Response to Decision Letter for (RSOS-181604.R1)

04-Jun-2019
Dear Dr Li, I am pleased to inform you that your manuscript entitled "Digital gene expression analyses of mammary glands from meat ewes naturally infected with clinical mastitis" is now accepted for publication in Royal Society Open Science.
You can expect to receive a proof of your article in the near future. Please contact the editorial office (openscience_proofs@royalsociety.org and openscience@royalsociety.org) to let us know if you are likely to be away from e-mail contact. Due to rapid publication and an extremely tight schedule, if comments are not received, your paper may experience a delay in publication.
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The responds to the reviewer's comments and suggestions are as following.
Special thanks again to your reviews. Please do not hesitate to contact us if you have any questions regarding revised version of this paper or responses to reviewer's comments and suggestions.
With best regards,

Response to Reviewer 2 Comments
Point 1: This is an interesting manuscript studying the transcriptome signature of clinical mastitis in sheep. Although the manuscript is well written, the sample size is small and the authors used very mild significant thresholds. Stricter significant thresholds-at least adjusting for multiple testing-should be performed for the Differential Expression analysis. All the analysis related to co-expression, pathway and network analysis etc should be repeated using only the DE results after adjusting for multiple testing using for example FDR correction.
Response 1: Thank you very much for your comments. Admittedly, in the present study, the sample size is small, but it meets the minimum biological research requirement. In many relevant literatures published recently, the sample size is also n=3. In our ongoing study, we selected more sample size (n=5) to reveal the specific regulator mechanisms of key candidate genes and pathways in mastitic sheep mammary glands experimentally infected with single or mixed bacteria isolated from infected animals used in this study.
According to your comment, we re-screen the differentially expressed genes in healthy and mastitic groups based on thresholds of |log2(fold change)| > 1 and FDR < 0.05. All results related to clustering heatmap, GO annotation, pathway enrichment, co-expression network, protein-protein interaction network etc were also re-analyzed according to differential gene results after FDR correction.

Point 2:
The whole discussion should be re-written in a more focused way with in depth comparisons among the present studies and previous studies on the topic. The authors also miss recent publications on the topic for example https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3982-1 Response 2: Thank you very much for your comment and suggestion. We have re-written the whole "Discussion" in our revised version according to the comment. In revised manuscript, we also cited this recent reference in "Discussion" part. Response 4: Thank you very much for your comment. We are very sorry for our negligence. In our revised manuscript, we have provided the URL address on Oar_v4.0 genomic dataset used in this study. For details, please see "3.3. Quality control of raw data and mapping reads to the genome" section.
Point 5: Line 36: I assume that the P < 0.05 is the uncorrected P value and not the adjusted after FDR correction. I am wondering how many genes remain significantly differentially expressed after adjusting for multiple testing using FDR correction. A P < 0.05 is a very mild threshold and the results could be false positive. This should be amended and the genes which are presented as differentially expressed should be the ones which remain significant after correcting for multiple testing.