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首页> 美国卫生研究院文献>other >Detecting the QTL-Allele System of Seed Oil Traits Using Multi-Locus Genome-Wide Association Analysis for Population Characterization and Optimal Cross Prediction in Soybean
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Detecting the QTL-Allele System of Seed Oil Traits Using Multi-Locus Genome-Wide Association Analysis for Population Characterization and Optimal Cross Prediction in Soybean

机译：利用多基因座全基因组关联分析检测种子油性状的QTL-等位基因系统用于大豆的群体特征和最佳交叉预测

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摘要

Soybean is one of the world's major vegetative oil sources, while oleic acid and linolenic acid content are the major quality traits of soybean oil. The restricted two-stage multi-locus genome-wide association analysis (RTM-GWAS), characterized with error and false-positive control, has provided a potential approach for a relatively thorough detection of whole-genome QTL-alleles. The Chinese soybean landrace population (CSLRP) composed of 366 accessions was tested under four environments to identify the QTL-allele constitution of seed oil, oleic acid and linolenic acid content (SOC, OAC, and LAC). Using RTM-GWAS with 29,119 SNPLDBs (SNP linkage disequilibrium blocks) as genomic markers, 50, 98, and 50 QTLs with 136, 283, and 154 alleles (2–9 per locus) were detected, with their contribution 82.52, 90.31, and 83.86% to phenotypic variance, corresponding to their heritability 91.29, 90.97, and 90.24% for SOC, OAC, and LAC, respectively. The RTM-GWAS was shown to be more powerful and efficient than previous single-locus model GWAS procedures. For each trait, the detected QTL-alleles were organized into a QTL-allele matrix as the population genetic constitution. From which the genetic differentiation among 6 eco-populations was characterized as significant allele frequency differentiation on 28, 56, and 30 loci for the three traits, respectively. The QTL-allele matrices were also used for genomic selection for optimal crosses, which predicted transgressive potential up to 24.76, 40.30, and 2.37% for the respective traits, respectively. From the detected major QTLs, 38, 27, and 25 candidate genes were annotated for the respective traits, and two common QTL covering eight genes were identified for further study.
机译：大豆是世界上主要的植物油来源之一，而油酸和亚麻酸含量是大豆油的主要品质特征。受限制的两阶段多基因座全基因组关联分析（RTM-GWAS），具有错误和假阳性控制的特征，为相对彻底地检测全基因组QTL等位基因提供了一种潜在的方法。在四个环境下测试了由366个种质组成的中国大豆地方品种种群（CSLRP），以确定种子油的QTL等位基因组成，油酸和亚麻酸含量（SOC，OAC和LAC）。使用具有29,119个SNPLDB（SNP连锁不平衡模块）的RTM-GWAS作为基因组标记，检测到50个，98个和50个QTL，分别具有136、283和154个等位基因（每个位点2–9个），其贡献分别为82.52、90.31和表型差异为83.86％，分别对应于SOC，OAC和LAC的遗传力91.29、90.97和90.24％。事实证明，RTM-GWAS比以前的单场所模型GWAS过程更强大，更高效。对于每个性状，将检测到的QTL等位基因组织成QTL等位基因矩阵作为种群遗传构成。从中，六个生态种群之间的遗传分化被表征为三个性状分别在28、56和30个基因座上的显着等位基因频率分化。 QTL-等位基因矩阵也用于最佳杂交的基因组选择，其预测各自性状的侵害潜力分别高达24.76、40.30和2.37％。从检测到的主要QTL中，对38、27和25个候选基因的各自性状进行注释，并确定了覆盖8个基因的两个常见QTL，以供进一步研究。

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