DOI: 10.5061/dryad.tn6652t
title: Data from: Genome-wide association analyses in the model rhizobium Ensifer meliloti

description: Genome-wide association studies (GWAS) can identify genetic variants
 responsible for naturally occurring and quantitative phenotypic variation
 and 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 non-independence 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 stains of Ensifer meliloti. For 10
 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 known to be 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.
description: Master
 READMELists location of most
 important data and results and describes the analysis
 workflow.NCBI accession
 numbersncbi.zipStrain InformationMetadata for the strains included in the study.strain_info.zipPopgen AnalysesResults and code for population genetic summaries.popgen.zipFigure & Table codefigs_tables.zipPhenotype DataAll phenotype data, both raw and processed.pheno_data.zipReference GenomeCopy of reference genome sequence and annotation.reference_genome.zipLD Grouping AnalysisCode for and results from LD grouping.ld_groups.zipPAVsPresence-absence variant calling results and code.pav_calls.zipSingle-variant Association AnalysesCode for and results from the single-variant association analyses with GEMMA.gwas.zipModel SelectionCode to run forward model selection and results for real and permuted data.model_selection.zipGenome-wide PVE analysesCode that used GEMMA to get BSLMM and LMM chip-heritability estimates and summaries of results.bslmm.zipDe novo AssembliesDe novo assemblies and annotation used for identifying PAVs.assembly.zipRaw SNP and Indel CallsRaw variant calls from FreeBayes based on alignment of reads to USDA1106.snp_calls.zipVariant Calls For AnalysisSNP and PAV calls combined and filtered on missingness. Starting point for association and LD grouping analyses.variant_filtering_for_analysis.zip