PCOMPBIOL-D-25-02697

Panorama: a robust pangenome-based method for predicting and comparing biological systems across species

PLOS Computational Biology

Dear Dr. David Vallenet,

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Sreekanth Thota, Ph.D

Academic Editor

PLOS Computational Biology

Ilya Ioshikhes

Section Editor

PLOS Computational Biology

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: Arnoux et al. present a cutting edge tool for functional annotation and comparison of bacterial pangenomes, incorporating detection of important gene clusters such as secretion systems, defense systems, and genes encoding key metabolic pathways - PANORAMA. The manuscript is a detailed and impressive study.

Discussion of how to create models would be useful. It is not clear how much of this is implemented within PANORAMA itself.

Other tools which may be relevant to cite include:

- Hamburger: https://www.nature.com/articles/s41467-022-32929-2 https://github.com/djw533/hamburger

- spacedust: https://www.nature.com/articles/s41592-025-02816-x https://github.com/soedinglab/spacedust

It may be relevant to note gene-gene co-occurrence detection methods such as Coinfinder or Goldfinder

https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000338

https://www.biorxiv.org/content/10.1101/2024.04.29.591652v1.abstract

Line 615, S1 legend - appears to be an error “Analy[s]es were performed on the , RAM 615

disponible, type de machine”

Fig S2 labels are not legible and interpretation is not clear.

Reviewer #2: The manuscript by Arnoux et al deals with Panorama, a new and efficient method for comparing pangene adjacency graphs in bacteria. The paper is well written, methods clearly described and the examples used well organized and relevant. I have a very few comments on the paper and on the results, thus, recommend it for Minor Revisions

Introduction:

- The pangenome is not only the whole gene set, but can be considered also as the whole genomic sequence set, including IS, reg regions, etc...

- The type of pangenome graph that Panorama deals with are gene adjacency graphs produced by Ppanggolin, but other types of pangenome graphs exists: k-mers, DeBrujin, vg... Authors should restrict their type of graph.

Results

- What are the risks (present all along the analyses) that using a representative sequence for HMM annotation ? Is it possible that such representative in a very large family lacks some specific subfunctions present in other copies ?

- How do you deal with not-recorded in HMM sequences ? Let's say you have a very new type of bacteria, with very new functions, will the new genes be annotated ?

- For the benchmarking compared to Padloc and DefenseFinder, can you add also the CPU cost for computing the graph ? Your initial data is always the single genomes, not the graph, so it will be fairer to include the graph building in the comparison.

-Panorama is faster at the cost of more memory. is there a limit for that memory use ?

- The efficiency of Panorama is for me in the comparison of pangenomes. The method is very nice, however in the results themselves, the much higher number of E. coli (and thus the almost completion of the pangenome for it) will impair the comparison with much less numerous genomes, no ?

Discussion

- What about small SV and SNP within genes ? Can they be taken into account for evolutionary studies ?

M&M

-Why using Cecill2.1 licence and not Apache or LGPL ?

- In the figure 9, there is no (4) part

- Page 20, when clustering the gene families, it is possible that two clusters from the same family did not recognize between two highly divergent species. Can you test it ?

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes: Zachary Ardern

Reviewer #2: Yes: Francois Sabot

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Dear David Vallenet,

We are pleased to inform you that your manuscript 'Panorama: a robust pangenome-based method for predicting and comparing biological systems across species' has been provisionally accepted for publication in PLOS Computational Biology.

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

Best regards,

Sreekanth Thota, Ph.D

Academic Editor

PLOS Computational Biology

Ilya Ioshikhes

Section Editor

PLOS Computational Biology

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Dear Dr David Vallenet,

I am pleased to inform you that your manuscript has been accepted for publication in the current form.