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Use of the additive main effects and multiplicative interaction model in QTL mapping for adaptation in barley
Authors:Ignacio Romagosa  Steven E Ullrich  Feng Han  Patrick M Hayes
Institution:(1) Present address: Centre UdL-IRTA, A Rovira Roure 177, 25196 Lleida, Spain;(2) Department of Crop and Soil Sciences, Washington State University, 99164-6420 Pullman, WA, USA;(3) Department of Crop and Soil Science, Oregon State University, 97331 Corvallis, OR, USA
Abstract:The additive main effects and multiplicative interaction (AMMI) model has emerged as a powerful analytical tool for genotype x environment studies. The objective of the present study was to assess its value in quantitative trait locus (QTL) mapping. This was done through the analysis of a large two-way table of genotype-by-environment data of barley (Hordeum vulgare L.) grain yields, where the genotypes constituted a genetic population suitable for mapping studies. Grain yield data of 150 doubled haploid lines derived from the lsquoSteptoersquo x lsquoMorexrsquo cross, and the two parental lines, were taken by the North American Barley Genome Mapping Project (NABGMP) at 16 environments throughout the barley production areas of the USA and Canada. Four regions of the genome were responsible for most of the differential genotypic expression across environments. They accounted for approximately 50% of the genotypic main effect and 30% of the genotype x environment interaction (GE) sums of squares. The magnitude and sign of AMMI scores for genotypes and sites facilitate inferences about specific interactions. The parallel use of classification (cluster analysis of environments) and ordination (principal component analysis of GE matrix) techniques allowed most of the variation present in the genotype x environment matrix to be summarized in just a few dimensions, specifically four QTLs showing differential adaptation to four clusters of environments. Thus, AMMI genotypic scores, when the genotypes constituted a population suitable for QTL mapping, could provide an adequate way of resolving the magnitude and nature of QTL x environment interactions.Ignacio Romagosa was on sabbatical leave from the University of Lleida and the Institut de Recerca i Tecnologia Agroalimentàries, Lleida, Spain, when this study was conducted
Keywords:Hordeum vulgare  Quantitative trait loci  Genotype x environment interaction  Pattern analysis  Molecular marker-assisted selection
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