Semi-parametric statistical models for complex traits analysis using genomic data from Nelore cattle

• Grant number: 14/00779-0
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: June 01, 2014
• End date: February 28, 2017
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal Investigator: Lucia Galvão de Albuquerque
• Grantee: Rafael Espigolan
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Associated research grant: 09/16118-5 - Genomic tools to genetic improvement of direct economic important traits in Nelore cattle, AP.TEM
• Associated scholarship(s): 15/13084-3 - Application of kernel regressions in single step model (ssGBLUP) to predict genomic values using productive important traits in Nellore cattle, BE.EP.DR

Abstract

A large amount of genomic data is now available for identification and selection of genetically superior individuals, with potential to increase the accuracy of prediction of breeding values and, thus, the efficiency of animal breeding programs. Several statistical methods have been proposed for use in genomic data. Although several studies are being conducted, is still very limited number of studies determining the ability of prediction with statistical parametric and semi- parametric models with a set of real genomic data. Thus, in the proposed project, the prediction ability of genomic values with parametric models BLUP (Best Linear Unbiased Predictor), ssGBLUP (Single Step Genomic Best Linear Unbiased Predictor), BayesianLasso and the semi-parametric model RKHS (Reproducing Kernel Hilbert Spaces regression) will be studied using a set of simulated and real genomic data for growth characteristics, reproductive and carcass and meat in Nellore cattle. With the results, we hope to obtain important and relevant information in the genetic evaluation of commercial cattle populations. (AU)

Academic Publications

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

ESPIGOLAN, Rafael. Parametric and semi-parametric models for predicting genomic breeding values of complex traits in Nelore cattle. 2017. Doctoral Thesis - Universidade Estadual Paulista (Unesp). Faculdade de Ciências Agrárias e Veterinárias. Jaboticabal Jaboticabal.