花生重要农艺及产量性状的全基因组关联分析

Genome-wide Association Study of Agronomic and Yield Traits in a Worldwide Collection of Peanut(Arachis hypogaea) Germplasm

通过关联分析法发掘与花生(Arachis hypogaea)产量性状显著关联、同时又在花生基因组上随机分布的SSR位点及优异等位变异,可了解产量相关基因区域的分布特点,有助于利用分子标记辅助选择方法选育高产花生新品种。选用64个SSR标记,采用MLM(Q+K)方法对166份花生资源进行全基因组关联分析。结果表明,通过聚类分析和结构划分,供试群体受其综合性状遗传特点和来源地域的影响可被划分成7个亚群,聚类结果与群体结构基本一致,同时群体特点与材料来源地的生态划分符合同类聚集的规律。通过对6个产量相关性状的3年数值的关联分析,分别发掘出SSR位点有20个、33个和26个,2年以上重复检出的SSR位点有13个(P<0.05),各SSR位点的表型变异解释率范围为0.011–0.348 1,平均为0.067 3;共检出590个等位变异,平均每个标记位点12.29个,表型变异解释率值最高的是与单株果数呈显著关联的位点TC1A02(P<0.001),含21个等位变异;与产量构成主要因子紧密关联的位点中,百果重的TC1A02-C470(+41.588 5)、TC1A02-C560(+40.926 1)和p PGPseq2E6-B473(+63.953 4),单株果数的TC1A02-C500(+7.374 4),单株饱果数的GM1843-E157(+4.316 6),可用于产量性状的分子辅助育种。

Association analysis of yield-related traits and simple sequence repeat （SSR） loci distributed randomly in the peanut genome could contribute to marker-assisted selection breeding by the detection of elite alleles and the interaction of the gene region associated with high yield traits. We performed genome-wide association analysis with the mixed linear model （Q＋K） by scanning 166 peanut germplasm with selected 64 SSR markers. In all, 166 peanut germplasm could be assigned to 7 subpopulations by population structure and cluster analysis, with results from both methods similar. The morphological characteristics and geographic origin of germplasm were consistent within model-based clusters. From 2011 to 2013, the number of detected SSR markers significantly associated with 6 yield-related traits was 20, 33 and 26 respectively; 13 markers （P〈0.05） were detected repeatedly over 2 years. The mean rate of phenotypic explanation of SSR loci associated with traits was 0.067 3 （range 0.011-0.348 1）. In total, 590 alleles were detected, with a mean of 12.29 alleles per SSR loci. Among all the trait-related markers, TC1A02 （P〈0.001） had the highest rate of phenotypic explanation and contained 21 alleles, which was associated with the trait of pod number per plant. Among the SSR loci associated with the main effective factors of yield, the elite alleles with a high positive effect that could be used in marker-assisted selection of yield improvement were TC1A02-C560 （＋40.926 1）, TC1A02-C470 （＋41.588 5）, pPGPseq2E6-B473 （＋63.953 4） associated with 100-pod weight, TC1A02-C500 （＋7.374 4） associated with pod number per plant and GM1843-E157 （＋4.316 6） associated with full pod number per plant.