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2018 ASHS Annual Conference

Genome-Wide Association Study and Genomic Selection for White Rust in Spinach

Thursday, August 2, 2018: 2:15 PM
Lincoln East (Washington Hilton)
Ainong Shi, University of Arkansas, Fayetteville, AR
Jun Qin, University of Arkansas, Fayetteville, AR
James Correll, University of Arkansas, Fayetteville, AR
Wei Zhou, University of Arkansas, Fayetteville, AR
Gehendra Bhattarai, University of Arkansas, Fayetteville, AR
Bazgha Zia, University of Arkansas, Fayetteville, AR
Waltram Ravelombola, University of Arkansas, Fayetteville, AR
Yuejin Weng, University of Arkansas, Fayetteville, AR
Chunda Feng, University of Arkansas, Fayetteville, AR
Bo Liu, University of Arkansas, Fayetteville, AR
Carlos A. A. Avila, Assistant Professor, Texas A&M AgriLife Research, Weslaco, TX
Beiquan Mou, USDA-ARS, Salinas, CA
White rust, caused by Albugo occidentalis, is a severe disease of economic importance that causes reduction in yield and quality in spinach (Spinacia oleracea L.). Because no major genes have been reported for resistance to white rust, quantitative resistance has been employed to manage white rust. Selecting for quantitative traits using classical breeding methods can be a challenge. However, the use of molecular markers linked to qualitative traits can be valuable. The objectives of this study are to evaluate and screen white rust resistance in a collection of world-wide spinach germplasm, to conduct genome-wide association study (GWAS) and identify SNP markers, and to do genomic selection (GS) for white rust resistance in spinach. A total of 910 spinach genotypes were evaluated in four seasons (the winter of 2014-15, 2015-16, 2016-17, and 2017-18) at the Del Monte White Rust Nursery in Crystal City, TX. Over 100 spinach genotypes have been identified with levels of quantitative resistance to white rust pathogen. SNPs identified from genotyping by sequencing (GBS) were used as genotypic data. Thus far, GWAS was conducted in 412 spinach genotypes using 648 SNPs and performed with compressed mixed linear model (cMLM) implemented in the GAPIT R package. Eight SNP markers were identified that were strongly associated with white rust resistance. Genomic estimated breeding values (GEBVs) were calculated using the best linear unbiased estimator (BLUE) plus best linear unbiased prediction (BLUP) in GAPIT with both genome-wide SNP set (648 SNPs) and the only associated SNP markers (8 SNPs). The GS was validated in the association panel with 250 spinach genotypes as s training set and 162 genotypes as validation set with high correlation coefficients (r) between the predicted breeding value and the phenotypic white rust resistant data: r=0.66 and 0.68 with 648 SNP set and 8 SNP set, respectively. The data from this study will provide breeders with a set of markers to select for white rust resistance in spinach breeding programs through marker-assisted selection (MAS) and GS.
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