Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering

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.

Fig 1. Diagram of admixed lines production from hybrids obtained by mating dent and flint lines according to a sparse factorial design.

Fig 2. PCoA on genetic distances with coloration of individuals depending on their genetic background: dent, flint or admixed.

Fig 3. Schematic of allele effects when divergent SNP effects are observed between groups, depending on the biological hypothesis: (a) local genomic difference between groups (LD or mutation) and (b) allele effects interacting with the genetic background.

The denomination of the allelic states on the x-axis include the SNP allele (0/1), its ancestry (D/F) and the genetic background in which it is observed (D/A/F), as presented in Table 2.

Fig 4. Position of QTLs detected with (a) M₁, (b) M₂ and (c) M₃ for MF using a FDR of 20%.

The size of the grey dots is proportional to the -log₁₀(pval) of the test at the most significant SNP of the region. Red vertical lines correspond to the location of the QTLs presented in section “Highlighted QTLs”. Note that major QTLs detected by a model may be discarded with another model because of filtering on allele frequencies.

Fig 5. Boxplots of phenotypes adjusted for polygenic background variation using relatedness (MF K corrected) for the different alleles of the six highlighted QTLs: (a) Vgt1, (b) Vgt2, (c) Vgt3, (d) QTL4.1, (e) QTL2.1 and (f) QTL7.2 using M₃.

The denomination of the allelic states on the x-axis includes the SNP allele (0/1), its ancestry (D/F) and the genetic background in which it was observed (D/A/F), as presented in Table 2.