Genome-wide association mapping of agronomic traits and carbon isotope discrimination in a worldwide germplasm collection of spring wheat using SNP markers

Association mapping has been proposed to identify polymorphisms involved in phenotypic variations and may prove useful in identifying interesting alleles for breeding purposes. Using this approach, a total of 382 cultivars and advanced lines of spring wheat obtained from three breeding programs (Chile, Uruguay and CIMMYT) were evaluated for plant height (PH), kernels per spike (KS), 1,000 kernel weight (TKW), grain yield and carbon isotope discrimination (Δ13C) and tested for genotyping-by-sequencing-derived SNP markers across the hexaploid wheat genome. A Bayesian clustering approach via Markov chain Monte Carlo was performed to examine the genetic differentiation (FST) among different genetic groups. The results indicated the existence of two distinct and strongly differentiated genetic groups. Cluster I contained 215 genotypes (56.3 %), over 60 % (137/215) of which were collected from CIMMYT. Cluster II showed the highest FST value, according to 95 % credible interval. Linkage disequilibrium (LD) among SNPs was calculated for the A, B and D genomes and at the whole-genome level. LD decayed over a longer genetic distance for the D genome than for the A and B genomes. In the A and B genomes, LD declined to 50 % of its initial value at about 2 cM. In the D genome, LD was much more extensive, declining to 50 % of its initial value only at 22 cM. In the whole genome, LD declined to 50 % of its initial value at an average of 4 cM. Important genomic regions associated with complex traits in spring wheat were identified. Selection on these regions may increase the efficiency of the current breeding programs. Although most of the associations were environment specific, some stable associations were detected for Δ13C, KS, PH and TKW. Chromosomes 1A, 3A, 4A and 5A were the most important chromosomes, as they comprised quantitative trait loci (QTL) for Δ13C, a trait that can be used as an indirect tool for increased water-use efficiency in wheat. Environment-specific genomic regions were detected, indicating the presence of QTL-by-environment interaction. To produce suitable genotypes under contrasting water availability conditions, QTL × E interactions (and genotype-by-environment interaction) should be considered in the current spring wheat breeding program.