Multivariate and genome-wide SNP-based characterization of genetic diversity and population structure in a subset of the 3 K rice (Oryza sativa L.) genome panel of germplasm accessions
TL;DR
The combined phenotypic and genotypic analyses revealed substantial genetic diversity and identified elite accessions for the development of high-yielding and zinc-biofortified rice cultivars.
Abstract
The narrow genetic base of cultivated rice necessitates the identification of diverse germplasm accessions possessing superior agronomic performance and enhanced nutritional quality. The present study aimed to assess the phenotypic and genetic diversity among a subset of 300 rice germplasm accessions and identify elite accessions for rice biofortification and yield improvement programmes. The germplasms were evaluated during Kharif 2023 for nine quantitative traits using an alpha lattice design at Mandya and Gangavathi. Analysis of variance revealed significant differences among the accessions for all traits, indicating substantial phenotypic diversity. Principal Component Analysis identified the major contributors to phenotypic variation, with the first four principal components explaining 69% of the total variation. Based on phenotypic performance, 50 representative accessions were selected for K-means clustering and Multi-Trait Genotype–Ideotype Distance Index (MGIDI) analysis. The accessions were grouped into three distinct clusters with contrasting grain yield and grain zinc concentration. MGIDI identified IRGC 349 as the accession closest to the ideotype, combining high grain yield (6.10 t/ha) with favourable grain zinc concentration (24.59 ppm) and desirable agronomic traits. Based on mean performance across locations, IRGC 647 exhibited the highest grain zinc concentration (34.97 ppm) and was identified as a promising donor for rice biofortification programmes. Genetic diversity and population structure were assessed using 102,580 genome-wide single nucleotide polymorphism (SNP) markers. STRUCTURE analysis, SNP-based principal component analysis (PCA) and phylogenetic-based clustering consistently identified two major genetic subpopulations. The combined phenotypic and genotypic analyses revealed substantial genetic diversity and identified elite accessions for the development of high-yielding and zinc-biofortified rice cultivars.