No abstract

Quantitative trait locus (QTL) analysis of kernel shape and weight in common wheat was conducted using a set of 131 recombinant inbred lines (RIL) derived from 'Chuan 35050' 9 'Shannong 483'. The RIL and their two parental genotypes were evaluated for kernel length (KL), kernel width (KW), thousand-kernel weight (TKW), and test weight (TW) in four different environments. Twenty QTL were located on 12 chromosomes, 1A, 1B, 1D, 2A, 2B, 3B, 4A, 4B, 5D, 6A, 6B, and 7B, with single QTL in different environments explaining 5.9-26.4% of the phenotypic variation. Six, three, four, and seven QTL were detected for KL, KW, TKW, and TW, respectively. The additive effects for 17 QTL were positive with Chuan 35050 increasing the QTL effects, whereas the remaining three QTL were negative with Shannong 483 increasing the effects. Eight QTL (40%) were detected in two or more environments. Two QTL clusters relating to KW, TKW, and TW were located on chromosomes 2A and 5D, and the co-located QTL on chromosome 6A involved a QTL for KW found in two environments and a QTL for TKW detected in four environments.

Wheat (Triticum aestivum) is a major staple food crop worldwide. Genetic dissection of important agronomic traits is essential for continuous improvement of wheat yield to meet the demand of the world's growing population. We conducted a large-scale genome-wide association study (GWAS) using a panel of 768 wheat cultivars that were genotyped with 327 609 single-nucleotide polymorphisms generated by genotyping-by-sequencing and detected 395 quantitative trait loci (QTLs) for 12 traits under 7 environments. Among them, 273 QTLs were delimited to %1.0-Mb intervals and 7 of them are either known genes (Rht-D, Vrn-B1, and Vrn-D1) that have been cloned or known QTLs (TaGA2ox8, APO1, TaSus1-7B, and Rht12) that were previously mapped. Eight putative candidate genes were identified for three QTLs that enhance spike seed setting and grain size using gene expression data and were validated in three biparental populations. Protein sequence analysis identified 33 putative wheat orthologs that have high identity with rice genes in QTLs affecting similar traits. Large r 2 values for additive effects observed among the QTLs for most traits indicated that the phenotypes of these identified QTLs were highly predictable. Results from this study demonstrated that significantly increasing GWAS population size and marker density greatly improves detection and identification of candidate genes underlying a QTL, solidifying the foundation for large-scale QTL fine mapping, candidate gene validation, and developing functional markers for genomics-based breeding in wheat.