109364 Grain Quality Improvement in Winter Wheat: GWAS and Genomic Selection.
Poster Number 106
Tuesday, October 24, 2017
Tampa Convention Center, East Exhibit Hall
Grain quality improvement in winter wheat: GWAS and Genomic Selection Jayfred Godoy1, Kendra L. Jernigan1, Craig F. Morris2, Kimberly A. Garland-Campbell3, Zhiwu Zhang1, Meng Huang1, Yao Zhou1, Arron H. Carter1 1 Washington State University, Department of Crop and Soil Sciences, Pullman, WA 99164-6420 2 Western Wheat Quality Laboratory, Agricultural Research Service, United States Department of Agriculture, Pullman, WA 99164-6394, USA 3 USDA-ARS, Wheat Health, Genetics, and Quality Research Unit, Pullman, WA 99164-6420 Abstract Soft white winter wheat is used in foreign markets for various end products requiring specific end-use quality profiles. Breeding for end-use quality traits can be destructive, costly, and time-consuming, hence, it is advantageous to use molecular markers for marker-assisted selection (MAS) and/or genomic selection. Our objectives were: 1) to identify genetic markers associated with end-use quality traits and, 2) assess the application of genomic prediction to select genotypes with superior end-use qualities. A panel of 480 elite lines from the Pacific Northwest regional breeding programs were genotyped with the 90K iSelect wheat single nucleotide polymorphism (SNP) chip. Best linear unbiased predictions (BLUPs) for 21 end-use quality traits were calculated from historical data and combined with genotype data for genome-wide association analysis (GWAS) and genomic prediction. A total of 90 marker-traits associations (MTAs) were identified by GWAS across 19 chromosomes. Significant markers for multiple end-use quality traits were found on chromosomes 1B, 1D, 5A, 5B, and 7A. Genomic prediction was conducted using gBLUP with jack-knife cross validation method implemented in GAPIT. Significant correlations were observed between the predicted phenotypic values and real phenotype. The highest correlation were that of break flour yield (75%), cookie diameter (78%), flour SDS (87%) and flour Lactic Acid SRC (88%). Genomic prediction and MAS can provide breeders more tools to effectively discard poor quality germplasm and increase the frequency superior end-use quality alleles in their breeding populations.