Identifying species-specific k-mers for fast and accurate metagenotyping with Maast and GT-Pro

Zhou Jason Shi; Stephen Nayfach; Katherine S Pollard

doi:10.1016/j.xpro.2022.101964

Identifying species-specific k-mers for fast and accurate metagenotyping with Maast and GT-Pro

STAR Protoc. 2023 Mar 17;4(1):101964. doi: 10.1016/j.xpro.2022.101964. Epub 2023 Jan 20.

Authors

Zhou Jason Shi¹, Stephen Nayfach², Katherine S Pollard³

Affiliations

¹ Chan Zuckerberg Biohub, San Francisco, CA, USA; Gladstone Institutes, Data Science and Biotechnology, San Francisco, CA, USA.
² Department of Energy, Joint Genome Institute, Walnut Creek, CA, USA; Lawrence Berkeley National Laboratory, Environmental Genomics and Systems Biology Division, Berkeley, CA, USA.
³ Chan Zuckerberg Biohub, San Francisco, CA, USA; Gladstone Institutes, Data Science and Biotechnology, San Francisco, CA, USA; University of California San Francisco, Department of Epidemiology and Biostatistics, San Francisco, CA, USA. Electronic address: katherine.pollard@gladstone.ucsf.edu.

Abstract

Genotyping single-nucleotide polymorphisms (SNPs) in microbiomes enables strain-level quantification. In this protocol, we describe a computational pipeline that performs fast and accurate SNP genotyping using metagenomic data. We first demonstrate how to use Maast to catalog SNPs from microbial genomes. Then we use GT-Pro to extract unique SNP-covering k-mers, optimize a data structure for storing these k-mers, and finally perform metagenotyping. For proof of concept, the protocol leverages public whole-genome sequences to metagenotype a synthetic community. For complete details on the use and execution of this protocol, please refer to Shi et al. (2022a)¹ and Shi et al. (2022b).².

Keywords: Bioinformatics; Evolutionary biology; Genetics; Genomics; Microbiology; Sequence analysis.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Genome*
Microbiota* / genetics
Polymorphism, Single Nucleotide / genetics

Grants and funding

R01 HL160862/HL/NHLBI NIH HHS/United States