Abstract
Key messageThis study compares five models of GWAS, to show the added value of non-additive modeling of allelic effects to identify genomic regions controlling flowering time of sunflower hybrids.Genome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.
Highlights
Several tools are available to geneticists and breeders to identify the genetic control of traits of interest and to improve the performance of animals and plants
This study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids
We propose new Genome-wide association studies (GWAS) models including non-additive effects
Summary
Several tools are available to geneticists and breeders to identify the genetic control of traits of interest and to improve the performance of animals and plants. Its evolution has been crucial for the domestication of many crop species and their dissemination into new climatic regions (Colledge and Conolly 2007; Izawa 2007; Blümel et al 2015). It is highly heritable, and the gene regulatory network controlling flowering time is very well described, making it an excellent trait to combine quantitative genetics
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