Abstract
When handling a structured population in association mapping, group-specific allele effects may be observed at quantitative trait loci (QTLs) for several reasons: (i) a different linkage disequilibrium (LD) between SNPs and QTLs across groups, (ii) group-specific genetic mutations in QTL regions, and/or (iii) epistatic interactions between QTLs and other loci that have differentiated allele frequencies between groups. We present here a new genome-wide association (GWAS) approach to identify QTLs exhibiting such group-specific allele effects. We developed genetic materials including admixed progeny from different genetic groups with known genome-wide ancestries (local admixture). A dedicated statistical methodology was developed to analyze pure and admixed individuals jointly, allowing one to disentangle the factors causing the heterogeneity of allele effects across groups. This approach was applied to maize by developing an inbred “Flint-Dent” panel including admixed individuals that was evaluated for flowering time. Several associations were detected revealing a wide range of configurations of allele effects, both at known flowering QTLs (Vgt1, Vgt2 and Vgt3) and new loci. We found several QTLs whose effect depended on the group ancestry of alleles while others interacted with the genetic background. Our GWAS approach provides useful information on the stability of QTL effects across genetic groups and can be applied to a wide range of species.
Highlights
Quantitative traits are genetically determined by numerous regions of the genome, known as quantitative trait loci (QTLs)
The objectives were (i) to demonstrate the interest of multi-group analyses to identify new QTLs, (ii) to highlight the interest of applying multi-group genome-wide association studies (GWAS) models to identify group-specific allele effects at QTLs and (iii) to show how admixed individuals can help to disentangle the factors causing the heterogeneity of allele effects across groups: local genomic differences or epistatic interactions between QTLs and the genetic background
Genotype x Environment (GxE) variances were limited and the broad sense heritabilities were high for each genetic background, ranging from 0.88 in the admixed lines to 0.96 in the dent and flint lines for both male flowering (MF) and female flowering (FF)
Summary
Quantitative traits are genetically determined by numerous regions of the genome, known as quantitative trait loci (QTLs). The advent of high density genotyping of single nucleotide polymorphisms (SNPs) has opened the way to the identification of QTLs in diversity panels. These studies, referred to as genome-wide association studies (GWAS), use the linkage disequilibrium (LD) between the SNPs and causal variants at QTLs underlying the traits of interest. An efficient control of these spurious associations can be done by taking structure and kinship into account in the statistical model [1, 3] This procedure will limit the statistical power at differentiated SNPs, making them difficult to detect in multi-group GWAS, especially in case of rare alleles [4]
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call