Reference-free structural variant detection in microbiomes via long-read co-assembly graphs

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dc.citation.firstpagei58en_US
dc.citation.issueNumberSupplement_1en_US
dc.citation.journalTitleBioinformaticsen_US
dc.citation.lastpagei67en_US
dc.citation.volumeNumber40en_US
dc.contributor.authorCurry, Kristen Den_US
dc.contributor.authorYu, Feiqiao Brianen_US
dc.contributor.authorVance, Summer Een_US
dc.contributor.authorSegarra, Santiagoen_US
dc.contributor.authorBhaya, Devakien_US
dc.contributor.authorChikhi, Rayanen_US
dc.contributor.authorRocha, Eduardo P Cen_US
dc.contributor.authorTreangen, Todd Jen_US
dc.date.accessioned2024-09-10T19:29:02Zen_US
dc.date.available2024-09-10T19:29:02Zen_US
dc.date.issued2024en_US
dc.description.abstractMotivation: The study of bacterial genome dynamics is vital for understanding the mechanisms underlying microbial adaptation, growth, and their impact on host phenotype. Structural variants (SVs), genomic alterations of 50 base pairs or more, play a pivotal role in driving evolutionary processes and maintaining genomic heterogeneity within bacterial populations. While SV detection in isolate genomes is relatively straightforward, metagenomes present broader challenges due to the absence of clear reference genomes and the presence of mixed strains. In response, our proposed method rhea, forgoes reference genomes and metagenome-assembled genomes (MAGs) by encompassing all metagenomic samples in a series (time or other metric) into a single co-assembly graph. The log fold change in graph coverage between successive samples is then calculated to call SVs that are thriving or declining.Results: We show rhea to outperform existing methods for SV and horizontal gene transfer (HGT) detection in two simulated mock metagenomes, particularly as the simulated reads diverge from reference genomes and an increase in strain diversity is incorporated. We additionally demonstrate use cases for rhea on series metagenomic data of environmental and fermented food microbiomes to detect specific sequence alterations between successive time and temperature samples, suggesting host advantage. Our approach leverages previous work in assembly graph structural and coverage patterns to provide versatility in studying SVs across diverse and poorly characterized microbial communities for more comprehensive insights into microbial gene flux.Availability and implementation: rhea is open source and available at: https://github.com/treangenlab/rhea.en_US
dc.identifier.citationCurry, K. D., Yu, F. B., Vance, S. E., Segarra, S., Bhaya, D., Chikhi, R., Rocha, E. P. C., & Treangen, T. J. (2024). Reference-free structural variant detection in microbiomes via long-read co-assembly graphs. Bioinformatics, 40(Supplement_1), i58–i67. https://doi.org/10.1093/bioinformatics/btae224en_US
dc.identifier.digitalbtae224en_US
dc.identifier.doihttps://doi.org/10.1093/bioinformatics/btae224en_US
dc.identifier.urihttps://hdl.handle.net/1911/117862en_US
dc.language.isoengen_US
dc.publisherOxford University Pressen_US
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution (CC BY) license.  Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleReference-free structural variant detection in microbiomes via long-read co-assembly graphsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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