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

Abstract

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 (D 13 C) and tested for genotyping-bysequencing-derived SNP markers across the hexaploid wheat genome. A Bayesian clustering approach via Markov chain Monte Carlo was performed to examine the genetic differentiation (F ST ) 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 CI-MMYT. Cluster II showed the highest F ST 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 Electronic supplementary material The online version of this article (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 D 13 C, KS, PH and TKW. Chromosomes 1A, 3A, 4A and 5A were the most important chromosomes, as they comprised quantitative trait loci (QTL) for D 13 C, 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 9 E interactions (and genotype-by-environment interaction) should be considered in the current spring wheat breeding program.

Identification and validation of QTL for grain yield and plant water status under contrasting water treatments in fall-sown spring wheats

“…In this study, LD extent varied across chromosomes, from 0.55 cM for chromosome 7A to 12.84 cM for chromosome 1D (Table S4). The whole genome average critical r 2 value was 0.21, which is similar to the values reported by Mora et al (2015) and Edae et al (2014) in their spring wheat mapping panels. In this study, r 2 values varied from 0.17 for chromosome 3D to 0.27 for chromosome 5D.…”

Phenotypic and metabolic variation among spring Brassica napus genotypes during heat stress

“…Genotypic differences for CID have been reported in numerous crop species including B. napus (Matus et al 1995;Chen et al 2011;Kottmann et al 2014;Dhanapal et al 2015;Mora et al 2015). Easlon et al (2013) demonstrated a relationship between CID and water-use efficiency in Arabidopsis; however, given the absence of any relationship between yield and CID in either the control or heat-stress treatment in this study, further exploration into the relationship of CID to heat stress appears unwarranted.…”

SSR-based genetic analysis of sweet corn inbred lines using artificial neural networks

“…(Felsenstein 1989). Principal coordinate analysis was based on standardized covariance of genetic distances calculated for codominant markers (option DISTANCE, sub-option GENETIC), according to Mora et al (2015). Nei's genetic distances between inbred lines were used to create the UPGMA dendrogram, and their reliability was assessed by bootstrapping.…”