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普通小麦主要农艺性状的全基因组关联分析
引用本文:翟俊鹏,李海霞,毕惠惠,周思远,罗肖艳,陈树林,程西永,许海霞.普通小麦主要农艺性状的全基因组关联分析[J].作物学报,2019,45(10):1488-1502.
作者姓名:翟俊鹏  李海霞  毕惠惠  周思远  罗肖艳  陈树林  程西永  许海霞
作者单位:河南农业大学/省部共建小麦玉米作物学国家重点实验室/河南省粮食作物协同创新中心
基金项目:This study was supported by the National Key Research and Development Program of China(2017YFD0100706);the National Major Project for Developing New GM Crops(2016ZX08002003-004);the National Key Basic Research Program (973 Program)(2014CB138105)
摘    要:为解析小麦复杂农艺性状的遗传机制,本研究以150份小麦品种(系)为自然群体,在4个环境条件下测定了9个主要农艺性状,利用小麦35K SNP芯片,结合5种关联模型(Q、PCA、K、PCA+K、Q+K),进行全基因组关联分析。结果表明,全基因组多态性信息量PIC的范围为0.0950~0.5000,最小等位基因频率MAF值为0.0500~0.5000;群体结构分析和PCA分析均表明参试材料可分为两个亚群;连锁不平衡分析发现A基因组、B基因组、D基因组和全基因组的LD衰减距离分别为4.7、8、11和6 Mb。9个性状共检测到652个显著的关联位点(P≤0.001),其中21个SNP在2个或2个以上的环境中被重复检测到,分布在1A(1)、1B(4)、2A(3)、2D(2)、3A(1)、5A(1)、5B(5)、6A(1)、6B(2)和7D(3)染色体上; 1个SNP标记的物理位置未知, 3个SNP标记同时与2个性状显著关联;单个SNP的表型贡献率为7.67%~18.79%。8个优势等位变异在供试群体中所占比例较低,筛选出14个可能与小麦农艺性状相关的候选基因,其中TraesCS5B02G237200、TraesCS7D02G129700和TraesCS1B02G426300可能在植物抵御生物与非生物胁迫中起作用,TraesCS5B02G010800和TraesCS7D02G436800可能与植物激素的合成和响应有关,TraesCS2A02G092200可能与植物细胞壁的增强有关, TraesCS5A02G438800可能参与叶绿体发育,另外7个候选基因的功能未知。

收稿时间:2019-01-06

Genome-wide association study for main agronomic traits in common wheat
ZHAI Jun-Peng,LI Hai-Xia,BI Hui-Hui,ZHOU Si-Yuan,LUO Xiao-Yan,CHEN Shu-Lin,CHENG Xi-Yong,XU Hai-Xia.Genome-wide association study for main agronomic traits in common wheat[J].Acta Agronomica Sinica,2019,45(10):1488-1502.
Authors:ZHAI Jun-Peng  LI Hai-Xia  BI Hui-Hui  ZHOU Si-Yuan  LUO Xiao-Yan  CHEN Shu-Lin  CHENG Xi-Yong  XU Hai-Xia
Institution:Henan Agricultural University / National Key Laboratory of Wheat and Maize Crop Science / Collaborative Innovation Center of Henan Grain Crops, Zhengzhou 450046, Henan, China
Abstract:To illustrate the genetic mechanism of complex agronomic traits in wheat, we investigated nine agronomic traits using 150 wheat cultivars (lines) from China across four environments. Genome-wide association analysis was performed using wheat 35K genotyping assay with five association models (Q, PCA, K, PCA+K, Q+K). The results revealed that the polymorphic information content (PIC) of values was between 0.0950 and 0.5000, and the minimum allele frequency (MAF) was between 0.0500 and 0.5000. Both the population structure analysis and the PCA analysis showed that the tested materials could be divided into two sub-populations. Linkage disequilibrium analysis found that the LD decay distances of the A, B, D, and the whole genome were approximately 4.7, 8, 11, and 6 Mb, respectively. A total of 652 significant (P ≤ 0.001) marker-trait associations (MTAs) were detected, thereinto, 21 SNPs could be detected on chromosomes 1A(1), 1B(4), 2A(3), 2D(2), 3A(1), 5A(1), 5B(5), 6A(1), 6B(2), and 7D(3) in two or more environments. Three SNPs were significantly associated with two traits and the physical position of one SNP was unknown. Single SNPs could explain 7.67 % to 18.79 % phenotypic variation. It was found that eight favorable allelic variations accounted for a low proportion in the tested population. Fourteen candidate genes that may be related to agronomic traits of wheat were identified. Among them, TraesCS5B02G237200, TraesCS7D02G129700, and TraesCS1B02G426300 may play important roles in plants resistance to biotic and abiotic stress. TraesCS5B02G010800 and TraesCS7D02G436800 may be related to the hormones synthesis and response in plants. TraesCS2A02G092200 may enhance the cell wall formation of plants. TraesCS5A02G438800 may be involved in chloroplast development. The function of the other seven candidate genes is unknown.
Keywords:wheat  agronomic trait  linkage disequilibrium  genome-wide association study  candidate gene  
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