Profiling SNP and Nucleotide Diversity to Characterize Mekong Delta Rice Landraces in Southeast Asian Populations. Issue 3 (1st November 2019) - Tam, Nguyen Thanh; Dwiyanti, Maria Stefanie; Koide, Yohei; Nagano, Atsushi J.; Ky, Huynh; Tin, Huynh Quang; Hien, Nguyen Loc; Dung, Le Viet; Kishima, Yuji
Abstract : Core Ideas: 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.