Plant Genomics and Breeding Center, Crop Science Department, Eliseu Maciel College of Agronomy, Universidade Federal de Pelotas, Campus Universitário do Capão do Leão, PO Box 354, Pelotas, Rio Grande do Sul, 96010-900, Brazil.
Embrapa Temperate Climate Center, Rodovia BR 392, Km 78, PO Box 403, Pelotas, Rio Grande do Sul, 96010-971, Brazil.
J Appl Genet. 2019 Feb;60(1):27-31. doi: 10.1007/s13353-018-0475-0. Epub 2018 Oct 23.
Narrowing of genetic diversity and the quantitative nature of most agronomic traits is a challenge for rice breeding. Genome-wide association studies have a great potential to identify important variation in loci underlying quantitative and complex traits; however, before performing the analysis, it is important to assess parameters of the genotypic data and population under study, to improve the accuracy of the genotype-phenotype associations. The aim of this study was to access the genetic diversity, linkage disequilibrium, and population structure of a working panel of Brazilian and several introduced rice accessions, which are currently being phenotyped for a vast number of traits to undergo association mapping. Ninety-four accessions were genotyped with 7098 SNPs, and after filtering for higher call rates and removing rare variants, 93 accessions and 4973 high-quality SNPs remained for subsequent analyses and association studies. The overall mean of the polymorphic information content, heterozygosity, and gene diversity of the SNPs was comparable to other rice panels. The r measure of linkage disequilibrium decayed to 0.25 in approximately 150 kb, a slow decay, explained by the autogamous nature of rice and the small size of the panel. Regarding population structure, eight groups were formed according to Bayesian clustering. Principle components and neighbor-joining analyses were able to distinguish part of the groups formed, mainly regarding the sub-species indica and japonica. Our results demonstrate that the population and SNPs are of high quality for association mapping.
遗传多样性的缩小和大多数农艺性状的数量性质是水稻育种的一个挑战。全基因组关联研究有很大的潜力来识别数量和复杂性状下的重要变异；然而，在进行分析之前，评估研究中基因型数据和群体的参数对于提高基因型与表型关联的准确性非常重要。本研究旨在评估巴西和一些引入的水稻品系工作群体的遗传多样性、连锁不平衡和群体结构，这些品系目前正在对大量性状进行表型分析，以进行关联作图。94 个品系用 7098 个 SNPs 进行了基因型分析，经过更高的呼叫率过滤和稀有变异去除后，93 个品系和 4973 个高质量 SNPs 保留用于后续分析和关联研究。SNP 的多态信息含量、杂合度和基因多样性的总体平均值与其他水稻群体相当。连锁不平衡的 r 测量值在大约 150 kb 处衰减到 0.25，衰减缓慢，这是由水稻的自交性质和群体的小尺寸解释的。关于群体结构，根据贝叶斯聚类形成了 8 个组。主成分和邻接分析能够区分部分形成的组，主要是关于亚种籼稻和粳稻。我们的结果表明，群体和 SNP 非常适合关联作图。
