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PLoS Genet. 2018 Nov 12;14(11):e1007758. doi: 10.1371/journal.pgen.1007758. eCollection 2018 Nov.

A fast and agnostic method for bacterial genome-wide association studies: Bridging the gap between k-mers and genetic events.

Author information

1
bioMérieux, Marcy l'Étoile, France.
2
Univ Lyon, Université Lyon 1, CNRS, Laboratoire de Biométrie et Biologie Evolutive UMR5558 F-69622 Villeurbanne, France.
3
EPI ERABLE - Inria Grenoble, Rhône-Alpes, France.

Abstract

Genome-wide association study (GWAS) methods applied to bacterial genomes have shown promising results for genetic marker discovery or detailed assessment of marker effect. Recently, alignment-free methods based on k-mer composition have proven their ability to explore the accessory genome. However, they lead to redundant descriptions and results which are sometimes hard to interpret. Here we introduce DBGWAS, an extended k-mer-based GWAS method producing interpretable genetic variants associated with distinct phenotypes. Relying on compacted De Bruijn graphs (cDBG), our method gathers cDBG nodes, identified by the association model, into subgraphs defined from their neighbourhood in the initial cDBG. DBGWAS is alignment-free and only requires a set of contigs and phenotypes. In particular, it does not require prior annotation or reference genomes. It produces subgraphs representing phenotype-associated genetic variants such as local polymorphisms and mobile genetic elements (MGE). It offers a graphical framework which helps interpret GWAS results. Importantly it is also computationally efficient-experiments took one hour and a half on average. We validated our method using antibiotic resistance phenotypes for three bacterial species. DBGWAS recovered known resistance determinants such as mutations in core genes in Mycobacterium tuberculosis, and genes acquired by horizontal transfer in Staphylococcus aureus and Pseudomonas aeruginosa-along with their MGE context. It also enabled us to formulate new hypotheses involving genetic variants not yet described in the antibiotic resistance literature. An open-source tool implementing DBGWAS is available at https://gitlab.com/leoisl/dbgwas.

PMID:
30419019
PMCID:
PMC6258240
DOI:
10.1371/journal.pgen.1007758
[Indexed for MEDLINE]
Free PMC Article

Conflict of interest statement

I have read the journal’s policy and the authors of this manuscript have the following competing interests: MJ, MT, PM and AvB are employees of bioMérieux, a company that develops and sells diagnostic tests in the field of infectious diseases. However, the study was designed and executed in an open manner and the presented method as well as all data generated have been deposited in the public domain, also resulting in the current publication.

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