普通小麦籽粒过氧化物酶活性全基因组关联分析

doi:10.3864/j.issn.0578-1752.2017.21.016

摘要/Abstract

摘要： 【目的】小麦籽粒过氧化物酶（peroxidase，POD）活性对面制品加工品质有重要影响，发掘控制籽粒POD活性重要位点，并筛选其候选基因，为小麦品质的改良奠定基础。【方法】以151份黄淮冬麦区和82份北部冬麦区品种（系）为材料，分别利用来自于小麦90 K SNP芯片的18 189和18 417个高质量SNP标记，对POD活性进行全基因组关联分析（genome-wide association study，GWAS）。【结果】供试材料中POD活性表现出广泛的表型变异和多样性，黄淮麦区材料的POD活性变异系数为15.4%—21.8%，遗传力为0.79，北部麦区材料的POD活性变异系数为15.0%—19.9%，遗传力为0.82。相关性分析表明，不同环境之间材料的POD活性表现出显著的相关性，黄淮麦区相关系数为0.46—0.89（P＜0.0001），北部麦区相关系数为0.50—0.87（P＜0.0001）。多态性信息含量PIC值为0.09—0.38，最小等位基因频率MAF值为0.05—0.5。群体结构分析表明，黄淮麦区与北部麦区2个自然群体结构简单，均可分为3个亚群。GWAS分析结果表明，在黄淮冬麦区材料中共检测到20个与POD活性显著关联的位点（P＜0.001），分布在1A、2A、2B、2D、3A、3B、3D、4A、4B、5A、5B、6A、6D和7A染色体上，单个位点可解释7.8%—13.3%的表型变异。在北部冬麦区材料中共检测到20个与POD活性显著关联（P＜0.001）的位点，分布在1A、1B、1D、2A、2B、2D、3A、3B、4B、6A、6B、7A、7B和7D染色体上，单个位点可解释14.4%—23.2%的表型变异。加性回归分析表明，随着优异等位基因数量的增多，小麦籽粒POD活性越高。在发现的所有POD活性相关位点中，2个位点在黄淮麦区和北部麦区材料中均能检测到且稳定遗传，可将其转换为STARP（semi-thermal asymmetric reverse PCR）或CAPS标记，以应用于分子标记辅助育种。获得3个与POD活性有关的候选基因，分别编码磷酸甘露糖变位酶（PMM-D1）、辣根过氧化物酶（PER40）和烷基氢过氧化物还原酶（F775_31640）。【结论】黄淮麦区与北部冬麦区2个自然群体遗传多样性丰富，群体结构简单，适用于全基因组关联分析。在2个自然群体中分别发现20个POD活性位点，并在显著相关的位点区域内筛选到3个候选基因。含有越多优异等位变异的材料其POD活性越高。

关键词: 普通小麦, POD活性, 90 K SNP芯片, 群体结构

Abstract: 【Objective】 Peroxidase (POD) activity has browning and bleaching effects on the color of flour and flour-based products during processing and storage. Identification of associated loci and candidate genes for grain POD activity is important for molecular marker-assisted selection (MAS) in wheat quality breeding. 【Method】 In the present study, the POD activities were surveyed with 151 and 82 Chinese bread wheat cultivars from Yellow & Huai Winter Wheat Region (YHRVWWR) and Northern China Plain Winter Wheat Region (NWWR), respectively, and each set of cultivars was planted in four environments. A genome-wide association study (GWAS) was performed using the mixed linear model (MLM) based on 18 189 and 18 417 high-quality SNP markers from 90K SNP array for two sets of cultivars, respectively. 【Result】The POD activity of the tested materials showed extensive phenotypic variation and diversity. The variation coefficient of YHRVWWR was 15.4%-21.8%, the heritability was 0.79, and the variation coefficient of NWWR was 15.0%-19.9%, the heritability was 0.82. The POD activity of the materials in different environments showed a significant correlation, and the correlation coefficients were 0.46-0.89 (P＜0.0001) and 0.50-0.87 (P＜0.0001) in YHRVWWR and NWWR, respectively. The polymorphic information content of value was between 0.09-0.38, and the minimum allele frequency was between 0.05-0.5. The population structure analysis showed that the two natural populations in YHRVWWR and NWWR were simple and could be divided into three subgroups. In the YHRVWWR cultivars, 20 loci were found to be associated with POD activity (P＜0.001), which were located on chromosomes 1A, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 5A, 5B, 6A, 6D and 7A, and each explained 7.8%-13.3% of phenotypic variation. In the NWWR cultivars, 20 loci showed significant association with POD activity (P＜0.001), which were located on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4B, 6A, 6B, 7A, 7B and 7D, explaining 14.4%-23.2% of phenotypic variation. Two loci were detected in both the YHRVWWR and NWWR cultivars, and the associated SNPs could be used to develop STARP (Semi-thermal asymmetric reverse PCR) or CAPS markers. The regression analysis showed that the POD activity of wheat grain was higher with the increasing number of favorable alleles. Meanwhile, three candidate genes PMM-D1, PER40,and F775_31640 were scanned, encoding phosphomannomutase, horseradish peroxidasesand alkyl hydro peroxide reductase, respectively. 【Conclusion】The genetic diversity of the two natural populations in YHRVWWR and NWWR are rich in genetic structure and were suitable for genome-wide association analysis. Twenty POD activity loci were found in 2 natural populations, respectively, and three candidate genes were detected. Regression analysis showed that the more favorable alleles variation, the higher the POD activity.

时佳，翟胜男，刘金栋，魏景欣，白璐，高文伟，闻伟锷，何中虎，夏先春，耿洪伟. 普通小麦籽粒过氧化物酶活性全基因组关联分析[J]. 中国农业科学, 2017, 50(21): 4212-4227.

SHI Jia, ZHAI ShengNan, LIU JinDong, WEI JingXin, BAI Lu, GAO WenWei, WEN WeiE, HE ZhongHu, XIA XianChun, GENG HongWei. Genome-Wide Association Study of Grain Peroxidase Activity in Common Wheat[J]. Scientia Agricultura Sinica, 2017, 50(21): 4212-4227.

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