Abstract
Microbial genome-wide association studies (mGWAS) are a new and exciting research field that is adapting human GWAS methods to understand how variations in microbial genomes affect host or pathogen phenotypes, such as drug resistance, virulence, host specificity and prognosis. Several computational tools and methods have been developed or adapted from human GWAS to facilitate the discovery of novel mutations and structural variations that are associated with the phenotypes of interest. However, no comprehensive, end-to-end, user-friendly tool is currently available. The development of a broadly applicable pipeline presents a real opportunity among computational biologists. Here, (i) we review the prominent and promising tools, (ii) discuss analytical pitfalls and bottlenecks in mGWAS, (iii) provide insights into the selection of appropriate tools, (iv) highlight the gaps that still need to be filled and how users and developers can work together to overcome these bottlenecks. Use of mGWAS research can inform drug repositioning decisions as well as accelerate the discovery and development of more effective vaccines and antimicrobials for pressing infectious diseases of global health significance, such as HIV, TB, influenza, and malaria.
Highlights
Microbial genome-wide association studies are a new area of research aimed at identifying genetic variants in microbial genomes that are associated with host variation in or microbe phenotypes, for example genetic variation affecting phenotypes such as carriage (Lees et al, 2017) in humans and virulence (Laabei, 2014) in microbes
Successful applications of Microbial genome-wide association studies (mGWAS) include identifying genetic determinants of pyomyositis in Staphylococcus aureus (Young et al, 2019) which revealed that the presence of Panton-Valentine leucocidin (PVL) locus increased the odds of pyomyositis
Of particular interest is antimicrobial drug resistance which poses a significant threat to public health, especially due to the emergence of several multidrug-resistant strains worldwide (Aun et al, 2018; Wozniak et al, 2014; Frost et al, 2019). mGWAS has been crucial in identifying novel genomic markers responsible for drug resistance
Summary
Microbial genome-wide association studies (mGWAS) are a new area of research aimed at identifying genetic variants in microbial genomes that are associated with host variation in or microbe phenotypes, for example genetic variation affecting phenotypes such as carriage (Lees et al, 2017) in humans and virulence (Laabei, 2014) in microbes. Microbial genomes vary widely both in terms of gene content and sequence diversity This plasticity hampers the use of traditional single nucleotide polymorphism (SNP)-based methods for identifying all genetic associations with phenotypic variation (Lees et al, 2016). The differential expression (presence-absence) of homologous genes is a common approach applied to determine genes responsible for a given phenotype in microbial GWAS In this approach, the core genome or genes shared by all closely related organisms, usually at the species level, are eliminated and the unique genes only present in a given species are tested for significant association to the phenotype of interest. CNVs and SIs, like gene presence-absence, can result from acquisition of additional copies of a gene from mobile genetic elements or large-scale deletions or duplications of sections of the genome
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