基于SNP标记的小麦籽粒性状全基因组关联分析

【目的】籽粒性状是影响小麦产量的重要因素,通过对小麦籽粒性状进行全基因组关联分析,发掘控制小麦籽粒性状显著位点,为小麦籽粒性状的遗传改良研究提供理论参考。【方法】以在新疆种植的121份小麦为材料,利用小麦50K SNP芯片,对粒长、粒宽、籽粒长宽比、籽粒面积、籽粒周长和千粒重6个性状进行基于混合线性模型MLM（Q+K）的全基因组关联分析。【结果】在不同环境间6个籽粒性状均表现出广泛的表型变异,其中千粒重变异系数最大为13.91%—17.79%,各籽粒性状遗传力为0.85—0.90。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—0.50。群体结构分析表明,试验所用自然群体可分为4个亚群。GWAS结果表明,共检测到592个与6个性状显著关联位点（P<0.001）,其中,涉及6个性状的29个SNP在2个及以上的环境中被重复检测到,分布于1A（5）、1B（2）、1D、2A（5）、3B、5A、5D、6B（4）、6D、7B和7D（7）染色体上,解释9.3%—22.7%的表型变异。检测到6个与粒长稳定的关联位点,分布在1A、2A和7D染色体上,解释9.9%—22.7%的表型变异;检测到2个与粒宽稳定的关联位点,分布在3B和5D染色体上,解释9.6%—12.2%的表型变异;检测到6个与籽粒长宽比稳定的关联位点,分布在2A（2）、5A、7B和7D（2）染色体上,解释10.1%—19.4%的表型变异;检测到3个与籽粒面积稳定的关联位点,分布在1A、1B和1D染色体上,解释9.9%—18.2%的表型变异;检测到6个与籽粒周长稳定的关联位点,分布在1A（2）、2A、6D和7D（2）染色体上,解释9.3%—22.6%的表型变异;检测到6个与千粒重稳定的关联位点,分布在1B、2A和6B染色体上,解释9.7%—12.9%的表型变异。挖掘到5个控制小麦籽粒性状一因多效显著关联位点,分布在1A、2A（2）和7D（2）染色体上,解释9.9%—22.7%的表型变异。【结论】本研究材料遗传多样性丰富,在自然群体中共发现29个与6个籽粒性状在2个及以上环境中稳定显著的关联位点。

Genome-wide Association Analysis of Wheat Grain Size Related Traits Based on SNP Markers

【Objective】Grain traits are important factors affecting wheat yield. the significant locus of controlling wheat grain traits was explored by genome-wide association analysis of wheat grain traits, which provided a theoretical reference for the study of genetic improvement of wheat grain traits. 【Method】The genome-wide association analysis (GWAS) based on mixed linear model MLM (Q+K) was performed on 121 wheat grown in Xinjiang using wheat 50 K SNP chips for 6 traits which including grain length, grain width, grain length-width ratio, grain area, grain perimeter and 1000-grain weight.【Result】Six grain traits showed wide phenotypic variation in different environments, in which the maximum coefficient of variation of 1000-grain weight was 13.91-17.79 and the heritability of each grain trait was between 0.85-0.90. The polymorphism information content PIC value was 0.09-0.38, and the minimum allele frequency MAF value was 0.05-0.50. Group structure analysis shows that the natural groups used in the experiment can be divided into 4 subgroups. GWAS results showed that a total of 592 significant association sites (P<0.001) were detected in 6 traits, of which 29 SNPs were repeatedly detected in 2 or more environments, distributed in 1A(5), 1B(2), 1D, 2A(5), 3B, 5A, 5D, 6B(4), 6D, 7B and 7D(7) chromosomes, can explain 9.3% to 22.7% of the phenotypic variation. Six markers associated with stable grain length were detected, which distributed on 1A, 2A, and 7D chromosomes to explain the phenotypic variation of 9.9%-22.7%. Two markers associated with stable grain width were detected, which distributed on 3 B and 5 D chromosomes to explain the phenotypic variation of 9.6%-12.2%. Six markers associated with stable grain length-width ratio were detected, which distributed on 2A(2), 5A, 7B, and 7D(2) chromosomes to explain the phenotypic variation of 10.1%-19.4%. Three markers associated with stable grain area were detected, which distributed on 1A, 1B and 1D chromosome to explain the phenotypic variation of 9.9%-18.2%. Six markers with stable correlation with grain perimeter were detected, which distributed on 1A(2), 2A, 6D and 7D(2) chromosomes to explain the phenotypic variation of 9.3%-22.6%. Six markers associated with stable 1000-grain weight were detected, which distributed on 1B, 2A and 6B chromosomes to explain the phenotypic variation 9.7%-12.9%. Five dominant loci of pleiotropism with were found to control wheat grain traits, which distributed 1A, 2A(2) and 7D(2) chromosomes, explaining the phenotypic variation of 9.9%-22.7%.【Conclusion】In this study, the genetic diversity of the materials was abundant, a total of 29 multi-environment stability loci were found in natural population with 2 or more environmental associated with 6 grain traits.