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Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls
Author(s) -
James Emmanuel San,
Shakuntala Baichoo,
Aquillah M. Kanzi,
Yumna Moosa,
Richard Lessells,
Vagner Fonseca,
John Mogaka,
Robert A. Power,
Túlio de Oliveira
Publication year - 2020
Publication title -
frontiers in microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.701
H-Index - 135
ISSN - 1664-302X
DOI - 10.3389/fmicb.2019.03119
Subject(s) - computational biology , genome wide association study , pipeline (software) , identification (biology) , data science , computer science , biology , genome , presentation (obstetrics) , genetics , gene , ecology , single nucleotide polymorphism , genotype , programming language , medicine , radiology
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.

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