Bayesian methods applied to genomic breeding value predictions for average daily weight gain in Nellore cattle

• Grant number: 13/21644-3
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: January 01, 2014
• End date: December 31, 2014
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Danísio Prado Munari
• Grantee: Adriana Luiza Somavilla
• Supervisor: Guilherme J. M. Rosa
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Institution abroad: University of Wisconsin-Madison (UW-Madison), United States
• Associated to the scholarship: 12/23702-8 - Prediction of genomic-enabled breeding values and Genome-Wide Association Study for feedlot average daily weight gain in Nelore cattle, BP.DR

Abstract

The Nellore cattle is the most economically important breed reared in Brazil, because of their adaptation to the tropical environment, heat tolerance, parasite resistance and good reproductive performance, which are all factors that contribute to higher productivity. Most breeding programs have been based on body weight and weight gain traits, by using performance information for all related individuals in the population, giving greater genetic gain and increased inbreeding rates. In addition, genomic selection can reduce inbreeding rates, generation interval and maintenance of genetic variability, because of more accurate genomic estimated breeding values of young animals. Thus, appropriate methods can enable genomic selection and contribute to genetic improvement of Nellore cattle. Bayesian methods allow us to predict genomic breeding values by using different assumptions for marker effects and their variances. The aim of this study is to test different Bayesian methods to estimate marker effects and equations for predicting GEBVs. (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)

SOMAVILLA, ADRIANA L.; REGITANO, LUCIANA C. A.; ROSA, GUILHERME J. M.; MOKRY, FABIANA B.; MUDADU, MAURICIO A.; TIZIOTO, POLYANA C.; OLIVEIRA, PRISCILA S. N.; SOUZA, MARCELA M.; COUTINHO, LUIZ L.; MUNARI, DANISIO P.. Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle. G3-GENES, GENOMES, GENETICS, v. 7, n. 6, p. 1855-1859, JUN 2017. (13/21644-3, 12/23638-8, 12/23702-8)