Genome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>

ABSTRACT Genome-wide association studies (GWAS) can identify genetic variants responsible for naturally occurring and quantitative phenotypic variation. Association studies therefore provide a powerful complement to approaches that rely on de novo mutations for characterizing gene function. Although...

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Autores principales:	Brendan Epstein, Reda A. I. Abou-Shanab, Abdelaal Shamseldin, Margaret R. Taylor, Joseph Guhlin, Liana T. Burghardt, Matthew Nelson, Michael J. Sadowsky, Peter Tiffin
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2018
Materias:	BSLMM GWAS Medicago rhizobium Sinorhizobium bacteria Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/a17bda2ae4904668946fb9ce49b25f50
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spelling	oai:doaj.org-article:a17bda2ae4904668946fb9ce49b25f502021-11-15T15:22:26ZGenome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>10.1128/mSphere.00386-182379-5042https://doaj.org/article/a17bda2ae4904668946fb9ce49b25f502018-10-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSphere.00386-18https://doaj.org/toc/2379-5042ABSTRACT Genome-wide association studies (GWAS) can identify genetic variants responsible for naturally occurring and quantitative phenotypic variation. Association studies therefore provide a powerful complement to approaches that rely on de novo mutations for characterizing gene function. Although bacteria should be amenable to GWAS, few GWAS have been conducted on bacteria, and the extent to which nonindependence among genomic variants (e.g., linkage disequilibrium [LD]) and the genetic architecture of phenotypic traits will affect GWAS performance is unclear. We apply association analyses to identify candidate genes underlying variation in 20 biochemical, growth, and symbiotic phenotypes among 153 strains of Ensifer meliloti. For 11 traits, we find genotype-phenotype associations that are stronger than expected by chance, with the candidates in relatively small linkage groups, indicating that LD does not preclude resolving association candidates to relatively small genomic regions. The significant candidates show an enrichment for nucleotide polymorphisms (SNPs) over gene presence-absence variation (PAV), and for five traits, candidates are enriched in large linkage groups, a possible signature of epistasis. Many of the variants most strongly associated with symbiosis phenotypes were in genes previously identified as being involved in nitrogen fixation or nodulation. For other traits, apparently strong associations were not stronger than the range of associations detected in permuted data. In sum, our data show that GWAS in bacteria may be a powerful tool for characterizing genetic architecture and identifying genes responsible for phenotypic variation. However, careful evaluation of candidates is necessary to avoid false signals of association. IMPORTANCE Genome-wide association analyses are a powerful approach for identifying gene function. These analyses are becoming commonplace in studies of humans, domesticated animals, and crop plants but have rarely been conducted in bacteria. We applied association analyses to 20 traits measured in Ensifer meliloti, an agriculturally and ecologically important bacterium because it fixes nitrogen when in symbiosis with leguminous plants. We identified candidate alleles and gene presence-absence variants underlying variation in symbiosis traits, antibiotic resistance, and use of various carbon sources; some of these candidates are in genes previously known to affect these traits whereas others were in genes that have not been well characterized. Our results point to the potential power of association analyses in bacteria, but also to the need to carefully evaluate the potential for false associations.Brendan EpsteinReda A. I. Abou-ShanabAbdelaal ShamseldinMargaret R. TaylorJoseph GuhlinLiana T. BurghardtMatthew NelsonMichael J. SadowskyPeter TiffinAmerican Society for MicrobiologyarticleBSLMMGWASMedicagorhizobiumSinorhizobiumbacteriaMicrobiologyQR1-502ENmSphere, Vol 3, Iss 5 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	BSLMM GWAS Medicago rhizobium Sinorhizobium bacteria Microbiology QR1-502
spellingShingle	BSLMM GWAS Medicago rhizobium Sinorhizobium bacteria Microbiology QR1-502 Brendan Epstein Reda A. I. Abou-Shanab Abdelaal Shamseldin Margaret R. Taylor Joseph Guhlin Liana T. Burghardt Matthew Nelson Michael J. Sadowsky Peter Tiffin Genome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>
description	ABSTRACT Genome-wide association studies (GWAS) can identify genetic variants responsible for naturally occurring and quantitative phenotypic variation. Association studies therefore provide a powerful complement to approaches that rely on de novo mutations for characterizing gene function. Although bacteria should be amenable to GWAS, few GWAS have been conducted on bacteria, and the extent to which nonindependence among genomic variants (e.g., linkage disequilibrium [LD]) and the genetic architecture of phenotypic traits will affect GWAS performance is unclear. We apply association analyses to identify candidate genes underlying variation in 20 biochemical, growth, and symbiotic phenotypes among 153 strains of Ensifer meliloti. For 11 traits, we find genotype-phenotype associations that are stronger than expected by chance, with the candidates in relatively small linkage groups, indicating that LD does not preclude resolving association candidates to relatively small genomic regions. The significant candidates show an enrichment for nucleotide polymorphisms (SNPs) over gene presence-absence variation (PAV), and for five traits, candidates are enriched in large linkage groups, a possible signature of epistasis. Many of the variants most strongly associated with symbiosis phenotypes were in genes previously identified as being involved in nitrogen fixation or nodulation. For other traits, apparently strong associations were not stronger than the range of associations detected in permuted data. In sum, our data show that GWAS in bacteria may be a powerful tool for characterizing genetic architecture and identifying genes responsible for phenotypic variation. However, careful evaluation of candidates is necessary to avoid false signals of association. IMPORTANCE Genome-wide association analyses are a powerful approach for identifying gene function. These analyses are becoming commonplace in studies of humans, domesticated animals, and crop plants but have rarely been conducted in bacteria. We applied association analyses to 20 traits measured in Ensifer meliloti, an agriculturally and ecologically important bacterium because it fixes nitrogen when in symbiosis with leguminous plants. We identified candidate alleles and gene presence-absence variants underlying variation in symbiosis traits, antibiotic resistance, and use of various carbon sources; some of these candidates are in genes previously known to affect these traits whereas others were in genes that have not been well characterized. Our results point to the potential power of association analyses in bacteria, but also to the need to carefully evaluate the potential for false associations.
format	article
author	Brendan Epstein Reda A. I. Abou-Shanab Abdelaal Shamseldin Margaret R. Taylor Joseph Guhlin Liana T. Burghardt Matthew Nelson Michael J. Sadowsky Peter Tiffin
author_facet	Brendan Epstein Reda A. I. Abou-Shanab Abdelaal Shamseldin Margaret R. Taylor Joseph Guhlin Liana T. Burghardt Matthew Nelson Michael J. Sadowsky Peter Tiffin
author_sort	Brendan Epstein
title	Genome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>
title_short	Genome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>
title_full	Genome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>
title_fullStr	Genome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>
title_full_unstemmed	Genome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>
title_sort	genome-wide association analyses in the model rhizobium <italic toggle="yes">ensifer meliloti</italic>
publisher	American Society for Microbiology
publishDate	2018
url	https://doaj.org/article/a17bda2ae4904668946fb9ce49b25f50
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Genome-Wide Association Analyses in the Model Rhizobium <italic toggle="yes">Ensifer meliloti</italic>

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