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Genome-wide association study of principal components of growth traits and visual scores in Nellore cattle

Grant number: 17/03331-9
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): July 01, 2017
Effective date (End): June 30, 2018
Field of knowledge:Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
Principal Investigator:Roberto Carvalheiro
Grantee:Giovana Vargas
Supervisor abroad: Flavio Schramm Schenkel
Home Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
Local de pesquisa : University of Guelph, Canada  
Associated to the scholarship:15/25449-6 - Genomic association and prediction of principal components of growth traits and visual scores in Nelore cattle, BP.DR

Abstract

Principal component analysis (PCA) is used to extract important information from multivariate data which is expressed as a set of new variables called principal components (PCs). The PCs can show associations with a biological meaning among the traits, usually not observed in the original data. Genome-wide association studies (GWAS) can be used as an important tool to identify genomic regions possibly associated with these PCs with biological meaning. The objective of this study is to use genome-wide association analysis to identify genomic regions associated with principal components of growth traits and visual scores in Nellore cattle. Besides the genome-wide association analysis, functional enrichment analyses will be performed to characterize the genomic regions, and the candidate genes will be analyzed for all categories, biological processes, molecular functions, and cellular components. Records from Aliança Nellore dataset will be used with information of, approximately, 600,000 animals at birth, 500,000 at weaning and 330,000 at yearling, from 246 farms located in different regions of Brazil and Paraguay. Principal component analysis will be performed by reparameterization of multivariate mixed model equation. GWAS will be conducted considering the weighted single step GBLUP (wssGBLUP) and Bayes C methods using as "phenotype" predicted breeding values for the principal components, provided by quantitative analysis. It is expected that the results contribute to investigate important genomic regions associated to the principal components with biological meaning, which could assist the selection process. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
VARGAS, GIOVANA; SCHENKEL, FLAVIO SCHRAMM; BRITO, LUIZ FERNANDO; DE REZENDE NEVES, HAROLDO HENRIQUE; MUNARI, DANISIO PRADO; DE ALBUQUERQUE, LUCIA GALVAO; CARVALHEIRO, ROBERTO. Genomic regions associated with principal components for growth, visual score and reproductive traits in Nellore cattle. LIVESTOCK SCIENCE, v. 233, MAR 2020. Web of Science Citations: 0.
VARGAS, GIOVANA; SCHENKEL, FLAVIO SCHRAMM; BRITO, LUIZ FERNANDO; DE REZENDE NEVES, HAROLDO HENRIQUE; MUNARI, DANISIO PRADO; BOLIGON, ARIONE AUGUSTI; CARVALHEIRO, ROBERTO. Unravelling biological biotypes for growth, visual score and reproductive traits in Nellore cattle via principal component analysis. LIVESTOCK SCIENCE, v. 217, p. 37-43, NOV 2018. Web of Science Citations: 0.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.