Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines

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Abstract
Large-scale genome-wide association (GWA) studies have become an important tool in human genomics, mostly focused on disease but also on adaptive variations such as skin colour. The technique is now shown to be similarly useful in plants. Atwell et al. report a GWA study of over a hundred phenotypes in naturally occurring inbred lines of Arabidopsis thaliana. The results range from significant associations, usually for single genes, to more difficult-to-interpret findings that indicate confounding by complex genetics and population structure. The accompanying paper by Todesco et al. demonstrates the ability of this technique to detect major-effect gene loci. Using forward genetics and GWA analyses, they show that variation at a single locus (ACD6) in Arabidopsis underlies phenotypic variation in vegetative growth as well as resistance to infection. The strong enhancement of resistance mediated by one of the alleles at this locus explains its persistence in natural populations throughout the world, despite it drastically reducing new leaf production. Here, large-scale genome-wide association studies were carried out with the naturally occurring inbred lines of Arabidopsis thaliana, which can be genotyped once and phenotyped repeatedly. The results range from significant associations, usually corresponding to single genes, to findings that are more difficult to interpret, because confounding by complex genetics and population structure makes it hard to distinguish true associations from false. Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases1,2, genome-wide association (GWA) studies have, owing to advances in genotyping and sequencing technology, become an obvious general approach for studying the genetics of natural variation and traits of agricultural importance. They are particularly useful when inbred lines are available, because once these lines have been genotyped they can be phenotyped multiple times, making it possible (as well as extremely cost effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we demonstrate the power of this approach by carrying out a GWA study of 107 phenotypes in Arabidopsis thaliana, a widely distributed, predominantly self-fertilizing model plant known to harbour considerable genetic variation for many adaptively important traits3. Our results are dramatically different from those of human GWA studies, in that we identify many common alleles of major effect, but they are also, in many cases, harder to interpret because confounding by complex genetics and population structure make it difficult to distinguish true associations from false. However, a-priori candidates are significantly over-represented among these associations as well, making many of them excellent candidates for follow-up experiments. Our study demonstrates the feasibility of GWA studies in A. thaliana and suggests that the approach will be appropriate for many other organisms.