PONE-D-23-29592Systematically mining genomic and proteomic variation linked to rare diseases: the example of monogenic diabetesPLOS ONE

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Additional Editor Comments:

Dear Authors,

Thank you very much for your submission to Plos One.

I think the manuscript is informative and describes some important points.

Sincerely,

Plos one editorial office

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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: Yes

Reviewer #3: Partly

Reviewer #4: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: N/A

Reviewer #3: N/A

Reviewer #4: N/A

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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

Reviewer #3: Yes

Reviewer #4: Yes

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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: Yes

Reviewer #3: Yes

Reviewer #4: Yes

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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: The study addresses the issue of pathogenic variation in monogenic diabetes. They developed an automated pipeline to mine the pathogenic variants in over 100 genes considering to be related with monogenic diabetes. By mining the variation data from both ClinVar and literatures and multiple processes, they identified the pathogenic variants in 36 genes, and further sorted out these causing translational changes. All the data from the study are available. The study is certainly a plus for further exploration in the subject.

Comments for improvement:

The definition of short deletions, short insertions, or other short fragment replacements needs to be given and justified. For example, how many bases deleted to be used as the cut off for short deletion?

The use of isoforms in the pipeline can cause mapping trouble as presented by the authors, as the number of isoforms in different genes can be substantial and lack of standardization and quality control. This is the reason to have RefSeq instead of isoforms in genomic annotation. The authors need to justify why use isoform instead of isoforms in their analysis.

“Note that not all these variants could be mapped automatically and those that did not map to Ensembl were formatted manually for input to Module 6. Detailed description needs to be given for formatted “manually”, and indicate the number of the variants under manually check.

ClinVar doesn’t have the classification of “unknown pathogenicity”. It should be the variants of unknown significance or VUS.

“For other types of consequence we focused on those presenting more than 80 % pathogenic and likely pathogenic variants”. Justification for 80% needs to be given, and the number at this cut-off needs to be given.

“We could map 2,701 of these variants to variants linked to monogenic diabetes according to

ClinVar or the literature”: should be “We mapped 2701 of….”

The version numbers for Ensembl, ClinVar and dbSNP need to be indicated. Different versions can be a reason for the inconsistence of the mapping results, such as “why the overlap of the variants taken from Rafique et al. and ClinVar seems limited in our analysis”.

The value of translation products has been repeatedly indicated to justify the development of translational products, as it “help predict the effect of genetic variation on the resulting protein structure and function”. However, there is no single example to justify their claim. I would suggest to present an example of coding changed protein with structural alteration as a proof of principle, considering they have generated rich coding-change pathogenic variants in multiple genes, like HNF1A.

The resolution is poor for all figures.

Reviewer #2: The authors present an interesting paper on the computational assessment of coding variants on protein sequences, categorizing these variants into different tiers depending on predicted pathogenicity.

Some minor comments to the authors

- The authors use the article by Rafique et al (2021). However, they should also mention the paper published by Bonnefond et al (2023) Nature Reviews particularly in their Discussion section (page 14) and how this compares to what they included in their study.

- Pg 4: Change port to import

- Page 3 “It is estimated that around 77 % of monogenic diabetes cases remain undiagnosed”. Specify why.

- Pg 3: Perhaps specify the total number of genes (to date) related to monogenic diabetes not just the 14 MODY genes

- I think it should be specified before (on page 5) which type of exonic variants were retained (listed on page 6)

- It would be good to specify the list of in silico tools used by Ensembl (VEP) to predict pathogenicity

- Did the authors consider cross checking some of the level 1/2 variants with ACMG/AMP predictions?

- Did the authors apply an alternative allele frequency cut-off? Perhaps some of the e.g. nonsense variants might be common.

- Page 8: Variants in BLK, KLF11 and PAX4 should be removed for dominant monogenic diabetes and it is still nonetheless considered controversial.

- Supp Table 5: would change to Yes/No in Rafique column

- Perhaps Links should be included as footnotes (rather than references in text)

Reviewer #3: This manuscript provides a modular Jupiter notebook approach for collecting information on monogenic diabetes variants across 108 genes. The authors compile their database from ClinVar and literature to generate a uniform list with annotations.

The work presented is thorough, though I was unable to personally validate the coding implementation. Additionally, the authors did not demonstrate this approach generalizes well to other diseases, making it difficult to assess wider utility.

Some of the approaches rely on circular logic - for example, the variants in Module 1 already include ClinVar data and use the Ensemble Variant Effect Predictor, which provides comprehensive annotations.

While this tool aims to fill a need, numerous established resources (DECIPHER, VEP etc.) and their continuous expansions already provide rich variant annotation and data integration. As more addons targeting monogenic diseases are actively developed and included in these tools actively the niche for this specific tool may diminish over time due to manual update needed for this work.

Overall, this manuscript describes a thoughtful effort to aggregate information on monogenic diabetes variants. However, given the breadth of existing tools, I am unable to clearly recognize the unmet need this resource fills in the community.

Reviewer #4: Authors developed automated and reproducible bioinformatics pipeline for mapping variants in genes related to MODY, and further collecting and harmonizing data about them. Their work addresses current challenges that geneticist face in the process of interpreting effect of rare/new genetic variants.

The pipeline has been described in detail and is made available for public use.

Additional value is that parts of this pipeline could be used to develop similar pipelines for other rare genetic disorders / groups of rare disorders. This is a needed tool in the rare disease ecosystem.

Therefore, I highly recommend publishing this manuscript in the current form.

Minor comment: I suggest including words “bioinformatics pipeline” in the title to facilitate bioinformaticians to find this valuable manuscript.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: Maja Stojiljkovic

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Bioinformatics pipeline for the systematic mining genomic and proteomic variation linked to rare diseases: the example of monogenic diabetes

PONE-D-23-29592R1

Dear Dr. Kuznetsova,

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.

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Kind regards,

Kazunori Nagasaka

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Dear Authors,

Thank you so much for submitting your manuscript to JOGR.

Now your manuscript is acceptable for publication in Plos One.

We look forward to your future submission.

Sincerely,

Kazunori Nagasaka

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: All comments have been addressed

Reviewer #4: All comments have been addressed

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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: Yes

Reviewer #4: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: Yes

Reviewer #4: N/A

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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

Reviewer #4: Yes

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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

Reviewer #4: Yes

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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: The revision has addressed my questions with satisfaction. The quality of revision is substantially improved over the original version.

Reviewer #2: (No Response)

Reviewer #4: The authors made changes in line with the first round of the review. I do not have any further comments.

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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: Yes: San Ming Wang

Reviewer #2: No

Reviewer #4: Yes: Maja Stojiljkovic

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