GENOMIC ASSOCIATION AND PREDICTION OF PRINCIPAL COMPONENTS OF GROWTH TRAITS AND VISUAL SCORES IN NELORE CATTLE

• Grant number: 15/25449-6
• Support Opportunities: Scholarships in Brazil - Doctorate
• Effective date (Start): December 01, 2016
• Effective date (End): December 31, 2018
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Roberto Carvalheiro
• Grantee: Giovana Vargas
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Associated scholarship(s): 17/03331-9 - Genome-wide association study of principal components of growth traits and visual scores in Nellore cattle, BE.EP.DR

Abstract

Principal component analysis is a multivariate statistical technique that allows to evaluate the magnitude of variability and inter-relationships between traits of interest. The aim of this study was to evaluate genetic principal components of growth traits and visual score at weaning and yearling in Nelore cattle, in order to identify the inter-relationship between these traits and possibly identify different biotypes of animals, determined by the principal components. Besides the quantitative genetic approach, genotypic information will be used to conduct association studies of principal components, aiming to identify genomic regions to differentiate the animals according to the components. Finally, genomic predictions will be conducted to evaluate the ability of genotypic information to discriminate the animals according to the principal components and, eventually, to the differentiate biotypes (if they are identified in the quantitative analysis). Data from Aliança Nelore database 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 the multivariate mixed model equation. Association studies and genomic prediction will be conducted considering the single weighted step GBLUP and BayesC methodologies, using as "pseudo-phenotype" the predicted breeding values for the principal components, provided by the quantitative analysis. The predictive ability of genomic selection will be evaluated using cross-validation.

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; 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. (09/16118-5, 17/03331-9, 15/25449-6)

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. (09/16118-5, 17/03331-9, 15/25449-6)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

VARGAS, Giovana. A genomic association and prediction of principal components of growth traits and visual scores in Nellore cattle. 2018. Doctoral Thesis - Universidade Estadual Paulista (Unesp). Faculdade de Ciências Agrárias e Veterinárias. Jaboticabal Jaboticabal.