Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The Univ. of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
Research Center for Agricultural Information Technology, National Agriculture and Food Research Organization, 3-1-1 Kannondai, Tsukuba, Ibaraki, 305-8517, Japan.
Plant Genome. 2020 Mar;13(1):e20005. doi: 10.1002/tpg2.20005. Epub 2020 Mar 19.
A genome-wide association study (GWAS) needs to have a suitable population. The factors that affect a GWAS (e.g. population structure, sample size, and sequence analysis and field testing costs) need to be considered. Mixed populations containing subpopulations of different genetic backgrounds may be suitable populations. We conducted simulation experiments to see if a population with high genetic diversity, such as a diversity panel, should be added to a target population, especially when the target population harbors small genetic diversity. The target population was 112 accessions of Oryza sativa L. subsp. japonica, mainly developed in Japan. We combined the target population with three populations that had higher genetic diversity. These were 100 indica accessions, 100 japonica accessions, and 100 accessions with various genetic backgrounds. The results showed that the GWAS's power with a mixed population was generally higher than with a separate population. Also, the optimal GWAS populations varied depending on the fixation index (F ) of the quantitative trait nucleotides (QTNs) and the polymorphism of QTNs in each population. When a QTN was polymorphic in a target population, a target population combined with a higher diversity population improved the QTN's detection power. By investigating F and the expected heterozygosity (H ) as factors influencing the detection power, we showed that single nucleotide polymorphisms with high F or low H are less likely to be detected by GWAS with mixed populations. Sequenced or genotyped germplasm collections can improve the GWAS's detection power by using a subset of the collections with a target population.
全基因组关联研究（GWAS）需要有合适的群体。需要考虑影响 GWAS 的因素（例如人口结构、样本量、序列分析和现场测试成本）。混合群体包含不同遗传背景的亚群可能是合适的群体。我们进行了模拟实验，以确定是否应该将具有高遗传多样性的群体（例如多样性面板）添加到目标群体中，尤其是当目标群体遗传多样性较小时。目标群体是 112 个日本粳稻亚种的亚种。我们将目标群体与具有更高遗传多样性的三个群体相结合。这三个群体分别是 100 个籼稻品种、100 个粳稻品种和 100 个具有各种遗传背景的品种。结果表明，混合群体的 GWAS 能力通常高于单独群体。此外，最佳 GWAS 群体取决于数量性状核苷酸（QTN）的固定指数（F）和每个群体中 QTN 的多态性。当 QTN 在目标群体中多态时，将目标群体与更高多样性的群体相结合可以提高 QTN 的检测能力。通过调查 F 和预期杂合度（H）作为影响检测能力的因素，我们表明，具有高 F 或低 H 的单核苷酸多态性不太可能通过混合群体的 GWAS 检测到。通过使用目标群体的子集中的一部分对测序或基因分型的种质资源进行收集，可以提高 GWAS 的检测能力。
