Mekong Delta Development Research Institute, Can Tho Univ., Vietnam.
Research Faculty of Agriculture, Hokkaido Univ., Japan.
Plant Genome. 2019 Nov;12(3):1-11. doi: 10.3835/plantgenome2019.06.0042.
Single nucleotide polymorphism (SNP) analyses are a powerful tool to examine structure of local rice population. 3000 dataset of IRRI facilitates SNP profiling of Southeast Asian rice populations. Mekong Delta population is featured by comparisons with the other populations. The low π-value SNPs well-profile unique genetic regions in their genomes. Recent analyses using single nucleotide polymorphism (SNP) are a feasible mean for local collections which potentially possess useful, but not large, genetic variations. Genomic sequences of more than 3000 accessions released by the International Rice Research Institute (IRRI) can be used to characterize various local rice (Oryza sativa) populations. The aim of this study was to develop a method to facilitate genomic characterization of local rice populations. We mainly used 99 indica rice accessions (81 landraces and 18 improved varieties) from the Mekong Delta Development Research Institute (MDI). We obtained 2301 SNPs after a genomic sequencing analysis of the 99 rice accessions and subsequent filtering. Within the IRRI's dataset, the landraces fell into a cluster consisting of accessions from Southeast Asian countries (Ind3 cluster), and the MDI improved varieties were grouped in a cluster containing IRRI improved varieties (Ind1B cluster). A principal component analysis suggested that geographical location strongly affects phylogenetic relationships, and the MDI landraces were placed into a Vietnam+Cambodia group. To detect the nucleotide diversity within a population, π-value is commonly used. We think that whole genome distribution of π-values representing the nucleotide diversity of each population can be used to characterize local populations. Our simple profiling using low π-value genomic regions was able to reveal regional characteristics of rice genomes and should be useful for identifying local rice populations.
单核苷酸多态性（SNP）分析是研究当地水稻群体结构的有力工具。国际水稻研究所（IRRI）的 3000 个数据集促进了东南亚水稻群体的 SNP 分析。湄公河三角洲种群的特点是与其他种群进行比较。低π值 SNP 很好地描绘了其基因组中独特的遗传区域。最近使用单核苷酸多态性（SNP）的分析是对当地群体的可行手段，这些群体可能具有有用的遗传变异，但数量不大。国际水稻研究所（IRRI）发布的 3000 多个品种的基因组序列可用于描述各种当地水稻（Oryza sativa）群体。本研究旨在开发一种方法来促进当地水稻群体的基因组特征分析。我们主要使用了来自湄公河三角洲发展研究中心（MDI）的 99 个籼稻品种（81 个地方品种和 18 个改良品种）。在对 99 个水稻品种进行基因组测序分析和后续筛选后，我们获得了 2301 个 SNP。在 IRRI 的数据集内，地方品种分为一组，包括来自东南亚国家的品种（Ind3 组），MDI 改良品种分为一组，包括 IRRI 改良品种（Ind1B 组）。主成分分析表明地理位置强烈影响系统发育关系，MDI 地方品种被归入越南+柬埔寨组。为了检测群体内的核苷酸多样性，通常使用π值。我们认为代表每个群体核苷酸多样性的全基因组π值分布可以用来描述当地群体。我们使用低π值基因组区域的简单分析能够揭示水稻基因组的区域特征，应该有助于识别当地水稻群体。
