GENOME WIDE ASSOCIATION STUDY AND DETECTION OF SELECTION SIGNALS IN THE GENOME OF NELORE CATTLE USING SEQUENCE DATA

• Grant number: 19/15397-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Effective date (Start): October 01, 2019
• Effective date (End): September 22, 2021
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Henrique Nunes de Oliveira
• Grantee: Amanda Marchi Maiorano
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Associated research grant: 17/10630-2 - Genetic aspects of meat production quality, efficiency and sustainability in Nelore breed animals, AP.TEM

Abstract

The adaptation process to tropical environment conditions and selection history in Brazilian Nelore herd make this breed an interesting instrument of study to detect signals of selection. The aim of this study will be to use genome sequence data of Nelore cattle to investigate signatures of selection using runs of homozygosity (ROH) islands and hapFLK statistic, and to perform single-step GWAS (ssGWAS) to study the genetic architecture of the adaptative trait individual´s annual fitness (pij). The proposed analyzes will allow the identification of genes and QTL on the genome of Nelore cattle. A total of 150 Nelore sires will be sequenced with Illumina HiSeq 4000 sequencing, which allows an average genomic coverage of 10X by sample. The criteria to choose sires to be sequenced will be their greater contribution in terms of genetic diversity in the current population. The ROH islands across the genome will be identified with the Plink v1.90 program. Homozygosity segments shared by more than 50% of the animals will be used as indicators of ROH islands, which will be used to indicate signatures of selection. The hapFLK statistic will be computed by chromosome using hapFLK v.1.4 and fastPhase programs. A genetic animal model will be proposed to estimate covariance components in the analysis of pij. Genomic regions identified as significant by the three method will be investigated to verify if they overlap with previous regions of genes and QTL described in bovine. Functional analyses of mapped genes and pathways will be performed considering DAVID v6.7 database.