Indian Journal of Genetics and Plant Breeding (The)
SCOPUSWeb of Science
  • Year: 2024
  • Volume: 84
  • Issue: 2

Study on submergence tolerance of rice (Oryza sativa L.) in a core panel of North-East India using GWAS

  • Author:
  • Munmi Phukon, Janardan Das, R. Sruthi, Rahul K. Verma1, Mahendra K. Modi2, Ashok Bhattacharyya3, Sanjay K. Chetia4,*
  • Total Page Count: 9
  • Page Number: 193 to 201

1DBT-North-East Centre for Agricultural Biotechnology, Assam Agricultural University, Assam, 785 013, India

2Assam Down Town University, Guwahati, 381 026, Assam, India

3Department of Plant Pathology, Assam Agricultural University, Assam, 785 013, India

4Directorate of Research (Agriculture), Assam Agricultural University, Assam, 785 013, India

Assam Rice Research Institute, Assam Agricultural University, Titabor, Assam, 785 630, India

*Corresponding Author: Sanjay K. Chetia, Directorate of Research (Agriculture), Assam Agricultural University, Assam, 785 013, India, E-Mail: sanjaykumarchetia@gmail.com

Online published on 2 July, 2025.

Abstract

Rice (Oryza sativa L.) being the major food crop of the north-eastern region, combating floods in rice fields for higher economic yield is a major challenge. A core panel, consisting of local rice landraces that have been cultivated in the flood-prone areas of this region for years, was used for this GWAS study to uncover possible genetic resistance sources to submergence. A study on GWAS was conducted to understand the mechanism of resistance of rice under water-submerged conditions through higher expression of genes. The GWAS analysis of a core panel of 400 rice landraces generated 38,723 filtered SNPs. The result showcased nine loci across the 12 rice chromosomes, one locus each in chromosome 2 and 4, five loci in chromosome 6, and two loci in chromosome 9. The two promising loci among these nine identified loci codes for zinc fingers, C3HC4 type domain-containing proteins, with FDR adjusted p-values of 0.04 each and allele effect of 4.60 and 4.57, respectively. These GWAS-identified association signals are a valuable source for allele mining and can be validated and introgressed into elite germplasms to decipher submergence tolerance in future breeding programs.

Keywords

GWAS, Submergence, SNPs identification, Rice landraces