Association mapping for yield, yield components and drought tolerance-related traits in spring wheat grown under rainfed and irrigated conditions.

摘要

Genome-wide association mapping shows promise for identifying quantitative trait loci (QTL) for many traits including drought stress tolerance. Candidate gene analysis also has been used to identify functional single nucleotide polymorphisms (SNPs) that can be associated with important traits. In 2010 and 2011, we evaluated an International maize and wheat improvement center ( CIMMYT) spring wheat association mapping panel under rainfed and full irrigation conditions in Greeley, CO, and Melkassa, Ethiopia (total of five environments) for grain yield and its components, canopy spectral reflectance, and several other phenological or drought-related traits. A total of 287 lines were genotyped with Diversity Array Technology (DArT) markers to identify associations with measured traits under different moisture regimes. Significant differences among lines were observed for most traits within each environment and across environments. Best linear unbiased predictors (BLUPs) of each line were used to calculate marker-trait associations using 1863 markers with a mixed linear model with population structure and a kinship-matrix included as covariates. Three drought responsive candidate genes (Dehydration-Responsive Element Binding 1A, DREB1A; Enhanced Response to abscisic acid (ABA), ERA1; and Fructan 1-exohydrolase, 1-FEH), were amplified using genome-specific primers and sequenced from 126 lines to identify single nucleotide polymorphisms (SNPs) within the candidate genes and determine their association with measured traits. For genome wide association mapping, the highest number of stable associations was obtained for kernel hardness followed by grain volume weight (test weight), an important trait under drought stress conditions. The most stable marker-trait association was obtained for grain yield on chromosome 2DS. All marker-trait associations for above-ground biomass were environment-specific. Multi-trait marker-trait association for grain yield and other traits such as harvest index, final biomass, thousand kernel weight, plant height and flag leaf length were detected on chromosome 5B. A grain yield QTL was again co-localized with harvest index QTL on chromosome 1BS. Normalized difference vegetation index (NDVI) shared QTL region with a harvest index QTL on chromosome 1AL, while green leaf area shared a QTL with harvest index on chromosomes 5A. For drought tolerance candidate genes, SNPs within DREB1A gene were associated with final biomass, spikelets per spike, days to heading and NDVI. The 1-FEH gene amplified from the A genome showed associations with grain yield, final biomass, NDVI, green leaf area, kernel number per spike and spike length. However, 1-FEH from the B genome was associated with traits such as days to heading, days to maturity, thousand kernel weight and test weight. The ERA1 gene from the B genome was associated with spike m-2, harvest index, grain filling duration, leaf senescence, flag leaf width, plant height and spike length, whereas ERA1 from the D genome was associated with kernel weight per spike, flag leaf width, leaf senescence, kernel number per spike and harvest index. In general, each candidate gene had effects on multiple traits under both rainfed and irrigated conditions. Both genome wide and candidate gene approaches showed that most of the measured traits are controlled by several QTL/genes with minor effects. QTL/genes with pleotropic effects were also detected. Therefore, the information generated by this study might be used in marker-assisted selection to improve drought tolerance of wheat.