Division of Biological Sciences, University of Missouri, Columbia, USA.
USDA-ARS, Columbia, MO, USA.
BMC Plant Biol. 2019 Oct 8;19(1):412. doi: 10.1186/s12870-019-2000-y.
Genome wide association studies (GWAS) are a powerful tool for identifying quantitative trait loci (QTL) and causal single nucleotide polymorphisms (SNPs)/genes associated with various important traits in crop species. Typically, GWAS in crops are performed using a panel of inbred lines, where multiple replicates of the same inbred are measured and the average phenotype is taken as the response variable. Here we describe and evaluate single plant GWAS (sp-GWAS) for performing a GWAS on individual plants, which does not require an association panel of inbreds. Instead sp-GWAS relies on the phenotypes and genotypes from individual plants sampled from a randomly mating population. Importantly, we demonstrate how sp-GWAS can be efficiently combined with a bulk segregant analysis (BSA) experiment to rapidly corroborate evidence for significant SNPs.
In this study we used the Shoepeg maize landrace, collected as an open pollinating variety from a farm in Southern Missouri in the 1960's, to evaluate whether sp-GWAS coupled with BSA can efficiently and powerfully used to detect significant association of SNPs for plant height (PH). Plant were grown in 8 locations across two years and in total 768 individuals were genotyped and phenotyped for sp-GWAS. A total of 306 k polymorphic markers in 768 individuals evaluated via association analysis detected 25 significant SNPs (P ≤ 0.00001) for PH. The results from our single-plant GWAS were further validated by bulk segregant analysis (BSA) for PH. BSA sequencing was performed on the same population by selecting tall and short plants as separate bulks. This approach identified 37 genomic regions for plant height. Of the 25 significant SNPs from GWAS, the three most significant SNPs co-localize with regions identified by BSA.
Overall, this study demonstrates that sp-GWAS coupled with BSA can be a useful tool for detecting significant SNPs and identifying candidate genes. This result is particularly useful for species/populations where association panels are not readily available.
全基因组关联研究（GWAS）是一种强大的工具，可用于鉴定与作物物种各种重要性状相关的数量性状基因座（QTL）和因果单核苷酸多态性（SNP）/基因。通常，作物中的 GWAS 使用一组自交系进行，其中对同一自交系进行多次重复测量，并取平均值作为响应变量。在这里，我们描述并评估了单株 GWAS（sp-GWAS），用于对单个植物进行 GWAS，而不需要自交系的关联面板。相反，sp-GWAS 依赖于从随机交配群体中采样的单个植物的表型和基因型。重要的是，我们展示了如何有效地将 sp-GWAS 与 bulk segregant analysis（BSA）实验相结合，快速证实显著 SNP 的证据。
在这项研究中，我们使用了 Shoepeg 玉米地方品种，该品种于 20 世纪 60 年代从密苏里州南部的一个农场作为开放授粉品种收集，以评估 sp-GWAS 与 BSA 的结合是否能够有效地用于检测植物高度（PH）的 SNP 显著关联。在两年内的 8 个地点种植了这些植物，总共对 768 个个体进行了 sp-GWAS 的基因型和表型分析。通过关联分析评估的 768 个个体中的 306k 个多态性标记共检测到 25 个与 PH 显著相关的 SNP（P≤0.00001）。我们的单株 GWAS 结果进一步通过 PH 的 bulk segregant analysis（BSA）验证。通过选择高矮植物作为单独的块体，对同一群体进行 BSA 测序。这种方法确定了 37 个与植物高度相关的基因组区域。在 GWAS 中的 25 个显著 SNP 中，三个最显著的 SNP 与 BSA 鉴定的区域共定位。
总的来说，这项研究表明，sp-GWAS 与 BSA 的结合可以成为检测显著 SNP 和鉴定候选基因的有用工具。对于那些不易获得关联面板的物种/群体来说，这一结果尤为有用。
