metaSNV v2: detection of SNVs and subspecies in prokaryotic metagenomes
Open accessAbstract
SUMMARY: Taxonomic analysis of microbial communities is well supported at the level of species and strains. However, species can contain significant phenotypic diversity and strains are rarely widely shared across global populations. Stratifying the diversity between species and strains can identify 'subspecies', which are a useful intermediary. High-throughput identification and profiling of subspecies is not yet supported in the microbiome field. Here, we use an operational definition of subspecies based on single nucleotide variant (SNV) patterns within species to identify and profile subspecies in metagenomes, along with their distinctive SNVs and genes. We incorporate this method into metaSNV v2, which extends existing SNV-calling software to support further SNV interpretation for population genetics. These new features support microbiome analyses to link SNV profiles with host phenotype or environment and niche-specificity. We demonstrate subspecies identification in marine and fecal metagenomes. In the latter, we analyze 70 species in 7524 adult and infant subjects, supporting a common subspecies population structure in the human gut microbiome and illustrating some limits in subspecies calling. AVAILABILITY AND IMPLEMENTATION: Source code, documentation, tutorials and test data are available at https://github.com/metasnv-tool/metaSNV and https://metasnv.embl.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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The advancement of computational tools for shotgun metagenomic sequencing has enabled profiling of microbes taxonomically and quantitatively and access to genetic information at subspecies and strain resolutions.
“The advancement of computational tools for the analysis of shotgun metagenomic sequencing has enabled researchers to not only profile microbes taxonomically and quantitatively but also to access their genetic information at subspecies and strain resolutions.”
From Global genetic diversity of human gut microbiome species is related to geographic location and host health (2025) · cites this paper as [11]
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- Authors
- Van Rossum, T., Costea, P. I., Paoli, L., Alves, R., Thielemann, R., Sunagawa, S., & Bork, P.
- Affiliations
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL) , 69117 Heidelberg, Germany
- European Molecular Biology Laboratory (DE)
- SIB Swiss Institute of Bioinformatics (CH)
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-11-17
- Volume
- 38
- Issue
- 4
- Pages
- 1162-1164
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC8796361
- OpenAlex
- W3212852449
- Cited by
- 23
- References
- 26
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 5 · 2023: 5 · 2022: 5
- FWCI
- 1.18
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Repository for Publications and Research Data (ETH Zurich) (publishedVersion, cc-by)
- ETH Zürich Research Collection (cc-by)
- Funders
- European Union’s Horizon 2020 Research and Innovation Programme (ERC-AdG-669830)
- Bundesministerium für Bildung und Forschung (01GL1746B)
- Swiss National Science Foundation (205321_184955)
- Eidgenössische Technische Hochschule (ETH) Zürich
- European Molecular Biology Laboratory
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- single nucleotide variants, subspecies identification, microbial population structure, strain diversity, human gut microbiome, marine metagenomes, fecal metagenome, niche specificity, infant gut microbiota
- MeSH terms
- Gastrointestinal Microbiome, Humans, Phenotype, Software, Metagenome, Microbiota
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