Dr. Vikas Vohra
ICAR-National Dairy Research Institute
India
Abstract Title: Buffalo Breeding 5.0: Harnessing Genomics, Transcriptomics and Beyond
Biography:
Dr. Vikas Vohra, a renowned buffalo breeder, is presently working as Head, Division of Animal Genetics & Breeding & Director, Centre for Advanced Faculty Training, ICAR-National Dairy Research Institute (NDRI), Karnal. Dr. Vohra completed his graduation from College of Veterinary and Animal Sciences, Mathura. He completed his M.V.Sc. in Animal Genetics and Breeding from Indian Veterinary Research Institute (IVRI), latter did his Doctorate from NDRI, India. He was trained at MSU, Michigan, USA. He has published more than 120 papers in reputed journals, authored/edited several books, and has been serving as an editorial board member in Journals of international repute.
Research Interest:
Buffaloes contribute significantly to India's dairy sector, accounting for over 45% of the national milk production (DAHD, 2024). Substantial progress has been made in buffalo genomics, including multi-trait selection indices integrating production, reproduction, and health traits have demonstrated improved prediction accuracy and genetic gain (Kumar et al., 2023). Whole genome resequencing and mitochondrial genome assembly efforts have further improved breed characterization and evolutionary understanding (Santhosh et al., 2024; 2025). SNP discovery, GWAS, ddRAD-based marker-trait associations, and transcriptome-wide association studies (TWAS) (George et al., 2023; Jaglan et al., 2023; Chhotaray et al., 2023). Transcriptomic and methylomic profiling have shed light on trait expression and epigenetic control in traits like milk yield, pigmentation, and disease resistance (Gurao et al., 2022; Singh et al., 2024). A sustainable genomic selection strategy, customized for Indian conditions and backed by large-scale female phenotypic datasets, is now feasible (Chhotaray & Vohra, 2022; Gowane & Vohra, 2022). Despite their importance, the pace of genetic improvement in buffalo remains slower compared to cattle, mainly due to long generation intervals, poor pedigree recording, and underutilization of advanced biotechnological tools. Buffalo Breeding 5.0 represents a transformative framework that leverages multi-omics approaches—genomics, transcriptomics, epigenomics, proteomics, and metabolomics—to enhance the genetic gain and precision of selection in buffalo populations. The adoption of Buffalo Breeding 5.0 is projected to reduce the generation interval and increase annual genetic gain. This integrated omics-based strategy ensures data-driven decision-making in selection, contributing to national goals of food security, climate resilience, and rural income enhancement.