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.
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We thank B. Carvalho for his advice on how to modify the OLIGO package. This work was primarily supported by US National Science Foundation (NSF) grant DEB-0519961 (J.B., M.N.), US National Institutes of Health (NIH) grant GM073822 (J.O.B.), and NSF grant DEB-0723935 (M.N.). Additional support was provided by the Dropkin Foundation, NIH grant GM057994 and NSF grant MCB-0603515 (J.B.), the Max Planck Society (D.W., M.T.), the Austrian Academy of Sciences (M.N.), the University of Lille 1 (F.R.), NIH grant GM078536 and NIH grant P42ES007373 (D.E.S.), NIH grant GM62932 (J.C., D.W.), the Howard Hughes Medical Institute (J.C.), the Deutsche Forschungsgemeinschaft (DFG) SFB 680 (J.d.M.), a Marie Curie International Outgoing Fellowship ‘ANAVACO’ (project number 220833; G.W.), and a Gottfried Wilhelm Leibniz Award of the DFG (D.W.). The project would not have been possible without the existence of The Arabidopsis Information Resource (http://arabidopsis.org).
This file contains Supplementary Information which comprises: 1 Genotyping; 2 Association Mapping Methods; 3 Enrichment for a priori candidates, Supplementary Figures 1-152 with legends, Supplementary References and Supplementary Tables 1-7.
About this article
Journal of Experimental Botany (2019)