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Research Article | Host-Microbe Biology

Genome-Wide Association Analyses in the Model Rhizobium Ensifer meliloti

Brendan Epstein, Reda A. I. Abou-Shanab, Abdelaal Shamseldin, Margaret R. Taylor, Joseph Guhlin, Liana T. Burghardt, Matthew Nelson, Michael J. Sadowsky, Peter Tiffin
Julia Oh, Editor
Brendan Epstein
aDepartment of Plant and Microbial Biology, University of Minnesota, Saint Paul, Minnesota, USA
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Reda A. I. Abou-Shanab
bBiotechnology Institute, University of Minnesota, Saint Paul, Minnesota, USA
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Abdelaal Shamseldin
cEnvironmental Biotechnology Department, Genetic Engineering and Biotechnology Research Institute (GEBRI) at City of Scientific Research and Technology Applications (SRTA-City) New Borg El Arab, Alexandria, Egypt
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Margaret R. Taylor
bBiotechnology Institute, University of Minnesota, Saint Paul, Minnesota, USA
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Joseph Guhlin
aDepartment of Plant and Microbial Biology, University of Minnesota, Saint Paul, Minnesota, USA
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Liana T. Burghardt
aDepartment of Plant and Microbial Biology, University of Minnesota, Saint Paul, Minnesota, USA
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Matthew Nelson
aDepartment of Plant and Microbial Biology, University of Minnesota, Saint Paul, Minnesota, USA
bBiotechnology Institute, University of Minnesota, Saint Paul, Minnesota, USA
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Michael J. Sadowsky
aDepartment of Plant and Microbial Biology, University of Minnesota, Saint Paul, Minnesota, USA
bBiotechnology Institute, University of Minnesota, Saint Paul, Minnesota, USA
dDepartment of Soil, Water, and Climate, University of Minnesota, Saint Paul, Minnesota, USA
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Peter Tiffin
aDepartment of Plant and Microbial Biology, University of Minnesota, Saint Paul, Minnesota, USA
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Julia Oh
The Jackson Laboratory for Genomic Medicine
Roles: Editor
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DOI: 10.1128/mSphere.00386-18
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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.

  • Copyright © 2018 Epstein et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

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Genome-Wide Association Analyses in the Model Rhizobium Ensifer meliloti
Brendan Epstein, Reda A. I. Abou-Shanab, Abdelaal Shamseldin, Margaret R. Taylor, Joseph Guhlin, Liana T. Burghardt, Matthew Nelson, Michael J. Sadowsky, Peter Tiffin
mSphere Oct 2018, 3 (5) e00386-18; DOI: 10.1128/mSphere.00386-18

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Genome-Wide Association Analyses in the Model Rhizobium Ensifer meliloti
Brendan Epstein, Reda A. I. Abou-Shanab, Abdelaal Shamseldin, Margaret R. Taylor, Joseph Guhlin, Liana T. Burghardt, Matthew Nelson, Michael J. Sadowsky, Peter Tiffin
mSphere Oct 2018, 3 (5) e00386-18; DOI: 10.1128/mSphere.00386-18
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KEYWORDS

BSLMM
GWAS
Medicago
Rhizobium
Sinorhizobium
bacteria
chip heritability
genetic architecture
genomics
linkage disequilibrium
symbiosis

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