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Genomewide analysis of epistatic effects for quantitative traits in barley
Authors:Xu Shizhong  Jia Zhenyu
Institution:Department of Botany and Plant Sciences, University of California, Riverside, California 92521, USA. xu@genetics.ucr.edu
Abstract:The doubled-haploid (DH) barley population (Harrington x TR306) developed by the North American Barley Genome Mapping Project (NABGMP) for QTL mapping consisted of 145 lines and 127 markers covering a total genome length of 1270 cM. These DH lines were evaluated in approximately 25 environments for seven quantitative traits: heading, height, kernel weight, lodging, maturity, test weight, and yield. We applied an empirical Bayes method that simultaneously estimates 127 main effects for all markers and 127(127-1)/2=8001 interaction effects for all marker pairs in a single model. We found that the largest main-effect QTL (single marker) and the largest epistatic effect (single pair of markers) explained approximately 18 and 2.6% of the phenotypic variance, respectively. On average, the sum of all significant main effects and the sum of all significant epistatic effects contributed 35 and 6% of the total phenotypic variance, respectively. Epistasis seems to be negligible for all the seven traits. We also found that whether two loci interact does not depend on whether or not the loci have individual main effects. This invalidates the common practice of epistatic analysis in which epistatic effects are estimated only for pairs of loci of which both have main effects.
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