Identification of important genomic footprints using eight different selection signature statistics in domestic cattle breeds

Divya Rajawat; Manjit Panigrahi; Harshit Kumar; Sonali Sonejita Nayak; Subhashree Parida; Bharat Bhushan; G K Gaur; Triveni Dutt; B P Mishra

doi:10.1016/j.gene.2021.146165

Identification of important genomic footprints using eight different selection signature statistics in domestic cattle breeds

Gene. 2022 Mar 30:816:146165. doi: 10.1016/j.gene.2021.146165. Epub 2022 Jan 11.

Authors

Divya Rajawat¹, Manjit Panigrahi², Harshit Kumar¹, Sonali Sonejita Nayak¹, Subhashree Parida³, Bharat Bhushan¹, G K Gaur¹, Triveni Dutt⁴, B P Mishra⁵

Affiliations

¹ Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
² Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India. Electronic address: manjit707@gmail.com.
³ Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
⁴ Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
⁵ Division of Animal Biotechnology, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.

PMID: 35026292
DOI: 10.1016/j.gene.2021.146165

Abstract

In the present study, the population genomic data of different cattle breeds were explored to decipher the genomic regions affected due to selective events and reflected in the productive, reproductive, thermo-tolerance, and health-related traits. To find out these genomic deviations due to selective sweeps, we used eight different statistical tools (Tajima's D, Fu & Li's D*, CLR, ROH, iHS, F_ST, FLK, and hapFLK) on seven indigenous and five exotic cattle breeds. We further performed composite analysis by comparing their covariance matrix. Several candidate genes were found to be related to milk production (ADARB, WDR70, and CA8), reproductive (PARN, FAM134B2, and ZBTB20), and health-related traits (SP110, CXCL2, CLXCL3, CXCL5, IRF8, and MYOM1). The outcome of this investigation provides a basis for detecting selective sweeps that explain the genetic variation of traits. They may possess functional importance for multiple cattle breeds in different subcontinents. However, further studies are required to improve the findings using high-density arrays or whole-genome sequencing with higher resolution and greater sample sizes.

Keywords: Candidate genes; Genome; Genomic footprints; Phenotype and QTL; SNP; Selective sweep.

MeSH terms

Animals
Cattle / genetics*
DNA Footprinting / veterinary*
Data Interpretation, Statistical*
Datasets as Topic
Genetics, Population
Selective Breeding*
Species Specificity