Literature DB >> 25835153

The advent of genome-wide association studies for bacteria.

Peter E Chen1, B Jesse Shapiro2.   

Abstract

Significant advances in sequencing technologies and genome-wide association studies (GWAS) have revealed substantial insight into the genetic architecture of human phenotypes. In recent years, the application of this approach in bacteria has begun to reveal the genetic basis of bacterial host preference, antibiotic resistance, and virulence. Here, we consider relevant differences between bacterial and human genome dynamics, apply GWAS to a global sample of Mycobacterium tuberculosis genomes to highlight the impacts of linkage disequilibrium, population stratification, and natural selection, and finally compare the traditional GWAS against phyC, a contrasting method of mapping genotype to phenotype based upon evolutionary convergence. We discuss strengths and weaknesses of both methods, and make suggestions for factors to be considered in future bacterial GWAS.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 25835153     DOI: 10.1016/j.mib.2015.03.002

Source DB:  PubMed          Journal:  Curr Opin Microbiol        ISSN: 1369-5274            Impact factor:   7.934


  58 in total

Review 1.  Microbial Speciation.

Authors:  B Jesse Shapiro; Martin F Polz
Journal:  Cold Spring Harb Perspect Biol       Date:  2015-09-09       Impact factor: 10.005

2.  Phylogenetic Methods for Genome-Wide Association Studies in Bacteria.

Authors:  Xavier Didelot
Journal:  Methods Mol Biol       Date:  2021

Review 3.  Microbial genome-wide association studies: lessons from human GWAS.

Authors:  Robert A Power; Julian Parkhill; Tulio de Oliveira
Journal:  Nat Rev Genet       Date:  2016-11-14       Impact factor: 53.242

4.  Bacterial genomics: Microbial GWAS coming of age.

Authors:  Daniel Falush
Journal:  Nat Microbiol       Date:  2016-04-26       Impact factor: 17.745

5.  MAGNAMWAR: an R package for genome-wide association studies of bacterial orthologs.

Authors:  Corinne E Sexton; Hayden Z Smith; Peter D Newell; Angela E Douglas; John M Chaston
Journal:  Bioinformatics       Date:  2018-06-01       Impact factor: 6.937

6.  Evolutionary genomic and bacteria GWAS analysis of Mycobacterium avium subsp. paratuberculosis and dairy cattle Johne's disease phenotypes.

Authors:  Vincent P Richards; Annette Nigsch; Paulina Pavinski Bitar; Qi Sun; Tod Stuber; Kristina Ceres; Rebecca L Smith; Suelee Robbe Austerman; Ynte Schukken; Yrjo T Grohn; Michael J Stanhope
Journal:  Appl Environ Microbiol       Date:  2021-02-05       Impact factor: 4.792

Review 7.  Population Biology and Comparative Genomics of Campylobacter Species.

Authors:  Lennard Epping; Esther-Maria Antão; Torsten Semmler
Journal:  Curr Top Microbiol Immunol       Date:  2021       Impact factor: 4.291

8.  Genome-wide epistasis and co-selection study using mutual information.

Authors:  Johan Pensar; Santeri Puranen; Brian Arnold; Neil MacAlasdair; Juri Kuronen; Gerry Tonkin-Hill; Maiju Pesonen; Yingying Xu; Aleksi Sipola; Leonor Sánchez-Busó; John A Lees; Claire Chewapreecha; Stephen D Bentley; Simon R Harris; Julian Parkhill; Nicholas J Croucher; Jukka Corander
Journal:  Nucleic Acids Res       Date:  2019-10-10       Impact factor: 16.971

Review 9.  The roles of environmental variation and parasite survival in virulence-transmission relationships.

Authors:  Wendy C Turner; Pauline L Kamath; Henriette van Heerden; Yen-Hua Huang; Zoe R Barandongo; Spencer A Bruce; Kyrre Kausrud
Journal:  R Soc Open Sci       Date:  2021-06-02       Impact factor: 2.963

10.  Identifying lineage effects when controlling for population structure improves power in bacterial association studies.

Authors:  Sarah G Earle; Chieh-Hsi Wu; Jane Charlesworth; Nicole Stoesser; N Claire Gordon; Timothy M Walker; Chris C A Spencer; Zamin Iqbal; David A Clifton; Katie L Hopkins; Neil Woodford; E Grace Smith; Nazir Ismail; Martin J Llewelyn; Tim E Peto; Derrick W Crook; Gil McVean; A Sarah Walker; Daniel J Wilson
Journal:  Nat Microbiol       Date:  2016-04-04       Impact factor: 17.745

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