Genome-Wide Association to Identify the Genetic loci Associated with Various Agro-Economical Traits in Mungbean (Vigna radiata L. Wilczek)
P. B. Manjunatha *
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, 110012, India.
Revanth Ragul A.
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, 110012, India.
Manju Kohli
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, 110012, India.
Saikat Chowdhury
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, 110012, India.
K. M. Shivaprasad
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, 110012, India.
Shashidhar B. R.
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, 110012, India.
Madhusudan B. S.
Department of Agriculture Engineering, REVA University, Bengaluru-560064, India.
Harsh Kumar Dikshit
Division of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, 110012, India.
*Author to whom correspondence should be addressed.
Abstract
Mungbean (Vigna radiata L. Wilczek) is a significant food legume globally, particularly in Asia, contributing to nutritional security and environmental sustainability. However, understanding its genetic basis for agro-economic traits remains incomplete. To address this, 126 mungbean genotypes were studied for eleven agronomic traits in two environments, revealing significant phenotypic diversity. Using genotyping-by-sequencing (GBS), 55,634 genomic variations were identified, with 15,926 SNPs retained for genetic diversity and linkage disequilibrium analysis. Subgroups were identified, and LD decayed at 68 kilo base (kb). Genome-wide association studies (GWAS) using BLINK identified 50 significantly associated signals for agronomic traits. In-silico analysis identified candidate genes within 30 kb of each SNP, with 11 genes likely regulating traits such as flowering time, plant height, pod characteristics, nitrogen status, seed traits, and yield. For traits like days to maturity and primary branch, candidate genes were not identified. Understanding genetic control of these traits is crucial for mungbean breeding, especially for developing varieties adaptable to climate change. GWAS results can aid in integrating favorable alleles into elite germplasm through marker-assisted selection (MAS), enhancing mungbean breeding efforts.
Keywords: Mungbean, SNPs, diversity, association, agro-economic traits, candidate gene