Abstract
The detection of selection signatures assists in understanding domestication, evolution, and the identification of genomic regions related to adaptation and production traits in buffaloes. The emergence of high-throughput technologies like Next Generation Sequencing and SNP genotyping had expanded our ability to detect these signatures of selection. In this study, we sought to identify signatures of selection in five buffalo populations (Brazilian Murrah, Bulgarian Murrah, Indian Murrah, Nili-Ravi, and Kundi) using Axiom Buffalo 90 K Genotyping Array data. Using seven different methodologies (Tajima’s D, CLR, ROH, iHS, FST, FLK and hapFLK), we identified selection signatures in 374 genomic regions, spanning a total of 381 genes and 350 quantitative trait loci (QTLs). Among these, several candidate genes were associated with QTLs for milk production, reproduction, growth and carcass traits. The genes and QTLs reported in this study provide insight into selection signals shaping the genome of buffalo breeds. Our findings can aid in further genomic association studies, genomic prediction, and the implementation of breeding programmes in Indian buffaloes.
Acknowledgements
All the authors of the manuscript wish to thank the Director and Joint Director (Research), ICAR-Indian Veterinary Research Institute (IVRI) for providing all the requisite facilities.
CRediT authorship contribution statement
K.A. Saravanan: Methodology, Formal analysis, Writing – original draft. Divya Rajawat: Methodology, Formal analysis, Writing – original draft. Harshit Kumar: Writing – review and editing. Sonali Sonejita Nayak: Writing – review and editing. Bharat Bhushan: Resources, Supervision. Triveni Dutt: Resources, Supervision. Manjit Panigrahi: Conceptualization, Writing – review and editing.
Disclosure statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data availability statement
The Axiom buffalo SNP array data used in this study are available at the Dryad data repository (https://doi.org/10.5061/dryad.h0cc7).
Funding
The author(s) reported there is no funding associated with the work featured in this article.