Applications of Genome Wide Analyses to Improve Wheat (Triticum aestivum L.) Yield

Hexaploid wheat (Triticum aestivum L. em. Thell) is one of the world’s most important cereal crops. Yield is the most important trait for wheat breeding. Our objectives are to assess the relative efficiency of genomic selection (GS) for yield and yield stability; to assess the genotype by environment patterns and its effects; and to identify marker-trait associations. The population consists of 280 lines from seven different winter wheat breeding programs in the Northeastern U.S. Phenotypic data for yield and yield stability has been collected in 2012 and 2013. Genotyping has been conducted utilizing a 90K SNP chip panel. Preliminary analysis estimated yield heritability to be 0.71 in year 2012. Also, many markers were shown in high linkage disequilibrium with the translocation site on chromosome 2B. We will identify a subset of markers more evenly distributed throughout the genome for future analysis. Ridge regression best linear unbiased prediction for GS, genome wide association analysis, and principal component analysis will be conducted in R. Analyses of heterogeneity of genotype regressions, as well as additive main effects and multiplicative interaction models will be conducted in SAS. Any significant markers responsible for yield will be detected. Our results would also identify individuals with the highest breeding values to use for variety advancement. The findings of this research should directly benefit wheat breeding programs in the Northeastern U.S.