Yang, Yan (2018-05). Characterization of Yield and Yield Components Using Bi-Parental and Association Mapping of Texas Popular Cultivars and Synthetic Wheat. Doctoral Dissertation. Thesis uri icon


  • Defining genetic architecture of complex traits is a fundamental step towards marker-assisted selection (MAS) for wheat improvement. Quantitative trait loci (QTL) studies provide prime information on the action, number and effect of QTL/genes controlling quantitative traits. The objective of this study was to use a saturated genetic map, derived from 90K single nucleotide polymorphic (SNP) array and genotype-by-sequence (GBS) markers, to map QTL associated with stripe rust resistance, grain yield, yield components, and other agronomic traits including test weight, height, and heading date. A mapping population of 124 F6 recombinant inbred lines (RILs) developed from the cross 'TAM 112'/'TAM 111' was developed. A set of 9928 markers were used for QTL analyses. The largest and most consistent stripe rust resistance QTL was identified on the long arm of chromosome 2B. Five tightly linked SNP markers were converted to Kompetitive allele specific PCR (KASP) markers for high throughput screening. The corresponding diagnostic markers should be applied through marker-assisted breeding. The same mapping population was used to identify and characterize QTL for yield and yield components for which data was obtained from eight Texas environments. QTL analysis was performed using the three different software based on individual environment and three mega-environments. Four unique and consistent QTL regions with pleiotropic effects were identified after comparing different models, which were distributed on chromosome fragment 1D2, 2D1, 4D, and 7D1. Synthetic derived wheat (SDW) has been reported to produce more yield than conventional bread wheat. To understand the genetics of marker-trait associations underlying yield performance in SDW, field trials were conducted at nine locations over three years. Yield, yield components, and other agronomic traits were measured on a panel of 419 SDW lines. We employed GBS to identify the genetic loci for yield traits though genome wide association studies (GWAS). All accessions, which were derived from synthetic spring lines crossed with TAM 111 or TAM 112, clustered into two subgroups, which were highly consistent with their pedigrees. The results of this study uncovered 45 loci associated with yield, yield components, and agronomic traits in individual environment based on best linear unbiased predication values. Candidate genes co-localized with such QTL, thereby providing potential targets for selection.

publication date

  • August 2018