Abstract
Common wheat is one of the most important crops in China, which is the largest producer in the world. A set of 230 cultivars was used to identify yield-related loci by association mapping. This set was tested for seven yield-related traits, viz. plant height (PH), spike length (SL), spikelet number per spike (SNPS), kernel number per spike (KNPS), thousand-kernel weight (TKW), kernel weight per spike (KWPS), and sterile spikelet number (SSN) per plant in four environments. A total of 106 simple sequence repeat (SSR) markers distributed on all 21 chromosomes were used to screen the set. Twenty-one and 19 of them were associated with KNPS and TKW, respectively. Association mapping detected 73 significant associations across 50 SSRs, and the phenotypic variation explained (R2) by the associations ranged from 1.54 to 23.93%. The associated loci were distributed on all chromosomes except 4A, 7A, and 7D. Significant and potentially new alleles were present on 8 chromosomes, namely1A, 1D, 2A, 2D, 3D, 4B, 5B, and 6B. Further analysis showed that genetic effects of associated loci were greatly influenced by association panels, and the R2 of crucial loci were lower in modern cultivars than in the mini core collection, probably caused by strong selection in wheat breeding. In order to confirm the results of association analysis, yield-related favorable alleles Xgwm135-1A138, Xgwm337-1D186, Xgwm102-2D144, and Xgwm132-6B128 were evaluated in a double haploid (DH) population derived from Hanxuan10 xLumai14.These favorable alleles that were validated in various populations might be valuable in breeding for high-yield.
Highlights
Wheat is one the most important crops in the world with a total production of about 713 million tonnes in 2013 [1]
The CV of phenotypic traits in each environment were higher than 10% with the exception of spikelet number per spike (SNPS), indicating that trait values differed between cultivars
We found that the R2 for thousand-kernel weight (TKW) at nine loci were lower
Summary
Wheat is one the most important crops in the world with a total production of about 713 million tonnes in 2013 [1]. Many yield-related QTLs were identified in studies of using bi-parental populations segregating for traits such as plant height [3,4,5,6,7,8], spike length [9, 10], spikelet number per spike [10,11,12], kernel number per spike [10, 13, 14, 15], thousand-kernel weight [10, 16, 17, 18], kernel weight per spike [10, 19] and sterile spikelet number per spike [7, 10, 20, 21]. There has been progress in identification of yield-related QTL mapping based on bi-parental populations, only a relatively small part of the total phenotypic variation within a crop species is identified in a single cross [22]
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