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Choosing the optimal population for a genome‐wide association study: A simulation of whole‐genome sequences from rice
The Plant Genome ( IF 3.9 ) Pub Date : 2020-03-19 , DOI: 10.1002/tpg2.20005
Kosuke Hamazaki 1 , Hiromi Kajiya‐Kanegae 1, 2 , Masanori Yamasaki 3 , Kaworu Ebana 4 , Shiori Yabe 5 , Hiroshi Nakagawa 6 , Hiroyoshi Iwata 1
Affiliation  

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 (FST) 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 FST and the expected heterozygosity (He) as factors influencing the detection power, we showed that single nucleotide polymorphisms with high FST or low He 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.

中文翻译:

为全基因组关联研究选择最佳种群:水稻全基因组序列的模拟

全基因组关联研究(GWAS)需要合适的人群。需要考虑影响GWAS的因素(例如种群结构,样本量以及序列分析和现场测试成本)。包含不同遗传背景亚群的混合种群可能是合适的种群。我们进行了模拟实验,以查看是否应将具有较高遗传多样性的种群(例如多样性面板)添加到目标种群,尤其是当目标种群具有较小的遗传多样性时。目标人群是稻的112个种。粳稻,主要在日本开发。我们将目标人群与具有更高遗传多样性的三个人群结合在一起。这些是100 d种,100种粳稻和100种具有不同遗传背景的种。结果表明,混合人群的GWAS的能力通常高于单独人群。此外,最佳GWAS种群根据每个种群中的数量性状核苷酸(QTN)的固定指数(F ST)和QTN的多态性而变化。当QTN在目标人群中具有多态性时,目标人群与更高多样性的人群相结合会提高QTN的检测能力。通过调查F ST和预期的杂合度(H e)作为影响检测能力的因素,我们发现单核苷酸多态性具有很高的混合人群的GWAS不太可能检测到F ST或低H e。测序或基因分型种质收藏可以通过使用具有目标种群的部分收藏来提高GWAS的检测能力。
更新日期:2020-03-19
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