Association Mapping of Agronomic QTLs in U.S. Spring Barley Breeding Germplasm

The use of genome-wide association studies (GWAS) to detect quantitative trait loci (QTL) controlling complex traits has become a popular approach for studying key traits in crop plants. The goal of this study was to identify the genomic regions of barley (Hordeum vulgare L.) that impact five agronomic and one quality trait in U.S. elite barley breeding lines, as well as to identify markers tightly linked with these loci for further use in barley improvement. Advanced recombinant inbred lines submitted to the U.S. Barley Coordinated Agricultural Project (CAP) were genotyped using a platform of 3072 single nucleotide polymorphism (SNP) markers from the barley oligonucleotide pool assays (BOPAs) 1 and 2. In each of 4 yr, approximately 770 lines were evaluated in a replicated, randomized complete block design under both irrigated and dryland conditions. This gave an overall population size of >3000 lines, which we analyzed in a hierarchical fashion, including analyzing the lines in aggregate using a mixed model to account for population structure and relatedness among the lines. We identified 41 significant marker–trait associations, of which 31 had been previously reported as QTL using biparental mapping techniques; 10 novel marker-trait associations were identified. The results of this work show that genes with major effects are still segregating in U.S. barley germplasm and demonstrate the utility of GWAS in barley breeding populations. The aim of QTL mapping in agronomically important crops is to find associations between genomic regions and traits that are of importance to the value of that crop. Once a significant association is found, the markers delimiting wthat genomic region can be used for selection in a breeding program, with the aim of increasing gain per unit time (Lande and Thompson, 1990). By identifying regions of the genome that impact traits of interest, we also gain insight into the overall genetic architecture of traits, which may subsequently influence breeding methods used to improve the trait. The traditional approach to identify genomic regions of interest has been biparental mapping. In biparental mapping, a population segregating for the trait of interest is created by intermating two parents that differ for the respective trait. This technique has proven extremely useful, as indicated by the plethora of published studies using the approach (Bernardo, 2008). However, biparental mapping is not without its limitations, including: only a small fraction of species-wide allelic diversity is sampled by using two parents; the estimation of the allelic effects are Published in The Plant Genome 7 doi: 10.3835/plantgenome2013.11.0037 © Crop Science Society of America 5585 Guilford Rd., Madison, WI 53711 USA An open-access publication All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. D. Pauli and T.K. Blake, Plant Sciences and Plant Pathology Dep., Montana State Univ., 119 Plant Bioscience Building, Bozeman 59717; G.J. Muehlbauer and K.P. Smith, Dep. of Agronomy and Plant Genetics, Univ. of Minnesota, 411 Borlaug Hall, 1991 Upper Buford Cir., St. Paul 55108; B. Cooper, Limagrain Cereal Seeds, 2040 SE Frontage Rd., Fort Collins, CO 80525; D. Hole, Plants, Soils, and Climate Dep., Utah State Univ., 2325 Old Main Hill RGH 112A, Logan, UT 84322; D.E. Obert, Limagrain Cereal Seeds, 4846 E. 450 N., Lafayette, IN 47905; S.E. Ullrich, Dep. of Crop and Soil Science, Washington State Univ., Pullman 99164. Received 15 Nov. 2013. *Corresponding author ([email protected]). Abbreviations: BOPA, barley oligonucleotide pool assay; CAP, U.S. Barley Coordinated Agricultural Project; FDR, false discovery rate; GWAS, genome-wide association studies; LD, linkage disequilibrium; MAF, minor allele frequency; P3D, population parameters previously determined; PC, principal component; PCA, principal component analysis; QTL, quantitative trait loci; SNP, single nucleotide polymorphism. Published October 31, 2014