Selection signatures in sheep

• Grant number: 22/13986-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: March 01, 2023
• End date: December 31, 2023
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Danísio Prado Munari
• Grantee: Julia Lisboa Rodrigues
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Associated scholarship(s): 23/04627-0 - Advances in selection signature analyses between sheep populations, BE.EP.MS

Abstract

The formation of terminal breeds of domestic sheep occurred through natural selection, domestication, and artificial selection. These processes generated conserved marks in the genome of individuals, called selection signatures. These allow the identification of alleles associated with traits of economic interest, within and between sheep breeds, even if they are phenotypically distinct. In addition, they make it possible to identify genes and mutations that exert or have exerted a selective advantage over a given population. This study aims to identify genetic patterns within sheep breeds to understand the process of evolution, formation, and genetic selection. Records of 7,085 animals from three sheep breeds (Belclare, Suffolk, and Texel), genotyped with the Illumina OvineSNP50 panel, will be used. The statistical methodologies used to detect selection signatures within populations will be the Extended Haplotype Homozygosity - EHH and Haplotype Integration Score - iHS. The application of these methodologies in the study of genomic marks may provide a better understanding of the gene flow of the selection process and genetic evolution within sheep breeds and complementary information to the genes associated with the traits of economic interest. This information can be used in breeding programs and contribute to increase the accuracy of the prediction of genetic parameters and accelerate selection responses.