Genome-Wide SNP Discovery and Population Structure Analysis of 244 Indonesian Local Rice Accessions

Single Nucleotide Polymorphism (SNP) markers are essential tools for the genetic management and breeding of rice, enabling precise characterization of genetic diversity. However, SNP datasets specifically developed for analyzing the population structure of Indonesian local rice remain limited. This study aimed to identify polymorphic SNP markers and analyze the lineage and population structure of 244 Indonesian local rice accessions. BAM files of these accessions were obtained from the 3K Rice Genome Project via the International Rice Informatics Consortium. High-quality SNPs were generated through variant calling and stringent filtering, followed by annotation and population analyses using IR64, DJ123, and Nipponbare as references. A total of 3,839,961 high-quality SNP loci were identified across the 12 rice chromosomes. Hierarchical clustering and principal coordinate analysis consistently grouped the accessions into three major clusters, corresponding to Indica, Japonica, and admixed groups. Population structure analysis confirmed two main subpopulations: Indica and Japonica, with Japonica further divided into Temperate and Tropical subgroups. Eleven accessions showed admixed ancestry. This study provides essential insights into the genetic diversity and population structure of Indonesian local rice, supporting genetic resource conservation, trait discovery, and breeding efforts.

Authors

Institutions

Publication Details

Journal
HAYATI Journal of Biosciences
Published
2025-10-13
DOI
https://doi.org/10.4308/hjb.33.1.142-152
Primary Topic
Plant Disease Resistance and Genetics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genome-Wide SNP Discovery and Population Structure Analysis of 244 Indonesian Local Rice Accessions

Rizky Dwi Satrio, Miftahul Huda Fendiyanto, Miftahudin Miftahudin, Satya Nugroho et al.
HAYATI Journal of Biosciences
Plant Disease Resistance and Genetics
article

Genome-Wide SNP Discovery and Population Structure Analysis of 244 Indonesian Local Rice Accessions

Rizky Dwi Satrio, Miftahul Huda Fendiyanto, Miftahudin Miftahudin, Satya Nugroho, Aris Hairmansis
article en

Abstract

Single Nucleotide Polymorphism (SNP) markers are essential tools for the genetic management and breeding of rice, enabling precise characterization of genetic diversity. However, SNP datasets specifically developed for analyzing the population structure of Indonesian local rice remain limited. This study aimed to identify polymorphic SNP markers and analyze the lineage and population structure of 244 Indonesian local rice accessions. BAM files of these accessions were obtained from the 3K Rice Genome Project via the International Rice Informatics Consortium. High-quality SNPs were generated through variant calling and stringent filtering, followed by annotation and population analyses using IR64, DJ123, and Nipponbare as references. A total of 3,839,961 high-quality SNP loci were identified across the 12 rice chromosomes. Hierarchical clustering and principal coordinate analysis consistently grouped the accessions into three major clusters, corresponding to Indica, Japonica, and admixed groups. Population structure analysis confirmed two main subpopulations: Indica and Japonica, with Japonica further divided into Temperate and Tropical subgroups. Eleven accessions showed admixed ancestry. This study provides essential insights into the genetic diversity and population structure of Indonesian local rice, supporting genetic resource conservation, trait discovery, and breeding efforts.

HAYATI Journal of BiosciencesVol. 33(1)
National Agriculture and Food Research Organization (JP), IPB University (ID), Indonesia Defense University (ID), Indonesian Agency for Agricultural Research and Development (ID), Ministry of Environment (KR)
Badan Riset dan Inovasi Nasional, Lembaga Pengelola Dana Pendidikan
Openalex Percentile: Top 79%
Plant Disease Resistance and Genetics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.