Association and Validation of Yield-Favored Alleles in Chinese Cultivars of Common Wheat (Triticumaestivum L.)

RESEARCH ARTICLE Association and Validation of Yield-Favored Alleles in Chinese Cultivars of Common Wheat (Triticumaestivum L.) Jie Guo1☯, Chenyang Hao3☯, Yong Zhang2☯, Boqiao Zhang2, Xiaoming Cheng2, Lin Qin1, Tian Li3, Weiping Shi2, Xiaoping Chang3, Ruilian Jing3, Wuyun Yang4, Wenjing Hu2, Xueyong Zhang3*, Shunhe Cheng1,2* a11111 1 National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu, China, 2 Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu Province, Yangzhou, Jiangsu, China, 3 Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture/Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China, 4 Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, Sichuan, China ☯ These authors contributed equally to this work. * (XZ); (SC) OPEN ACCESS Citation: Guo J, Hao C, Zhang Y, Zhang B, Cheng X, Qin L, et al. (2015) Association and Validation of Yield-Favored Alleles in Chinese Cultivars of Common Wheat (Triticumaestivum L.). PLoS ONE 10(6): e0130029. doi:10.1371/journal.pone.0130029 Academic Editor: Liuling Yan, Oklahoma State University, UNITED STATES Received: January 22, 2015 Accepted: May 15, 2015 Published: June 11, 2015 Copyright: © 2015 Guo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper and its Supporting Information files. Funding: This work was supported by grants from the Chinese Ministry of Science and Technology (2011CB100100; http://www.973.gov.cn/AreaAppl. aspx), the China Agricultural Research System (CARS-3-1-1; http://www.caaswheat.cn/), the National High-Tech R&D Program of China (2012AA101105; http://www.863.gov.cn/), the National Science and Technology Infrastructure Program (2011BAD35B03; http://www.nsfc.gov.cn/), and the National Natural Science Foundation of China (31301320; http://www. nsfc.gov.cn/). 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. PLOS ONE | DOI:10.1371/journal.pone.0130029 June 11, 2015 1 / 18 Association and Validation of Yield-Favored Alleles in Common Wheat Competing Interests: The authors have declared that no competing interests exist. Introduction Wheat is one the most important crops in the world with a total production of about 713 million tonnes in 2013 [1]. With an increasing world population it is necessary to continuously raise production mainly through higher yields. Identification of new yield-related lociis becoming increasingly important in all food crops. Wheat yield is determined by three key factors, viz. spikes per unit area, kernel number per spike and thousand-kernel weight. Most yield-related traits in wheat are controlled by genes with low heritability [2]. Many yield-related QTLs were identified in studies of using bi-parental populations segregating for traits such as plant height [3–8], spike length [9, 10], spikelet number per spike [10–12], 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]. For example, as a diagnostic marker, Xgwm261 closely linkedto Rht8 on 2D, plays an important role in wheat yield improvement in southern Europe [3, 4]. Although 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]. Association analysis identifies trait-marker relationships based on linkage disequilibrium [23]. This method has several advantages compared to bi-parental populations, such as (1) materials used in association analysis can be existing germplasm ranging from landraces to modern varieties and advanced lines; (2) novel and superior (favorable) alleles associated with the best phenotypes can be identified and ranked for use in breeding; (3) association mapping is more efficient and cheaper than other methods [24]; and (4) the results of association mapping apply to a wider range of genetic backgrounds. For example, Sajjad et al. [25] identified six SSR loci associated with yield-related traits on chromosome 3A, explaining 10.7 to 17.3% of the yield-related phenotypic variation in 94 wheat cultivars using 39 SSRs. Among them, Xgwm155 and Xwmc527, Xcfa2134 and Xgwm369, Xgwm155, and Xgwm369 were associated with grain yield per plant, fertile florets per spikelet, plant height, and spike length, respectively. Wang et al. [26] genotyped 531 SSR markers in the Chinese mini core wheat collection; 22 SSR loci were associated with TKW, each explaining phenotypic variation ranging from 1.56 to 21.99%. Six loci, Xcfa2234-3A, Xgwm156-3B, Xbarc56-5A, Xgwm234-5B, Xwmc17-7A and Xcfa2257-7A accounted for more than 10% of the variation. Using the same association panel Zhang et al. [27] identified 23 SSR loci significantly associated with KNPS, and reported that favorable alleles combined with additive effects. They also identified favorable alleles at the (...truncated)