Metafounders for genomic prediction in Montana breed

• Grant number: 19/05516-1
• Support type: Scholarships abroad - Research Internship - Doctorate
• Effective date (Start): June 10, 2019
• Effective date (End): March 09, 2020
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Fernando Sebastián Baldi Rey
• Grantee: Sabrina Kluska
• Supervisor abroad: Daniela Andressa Lino Lourenco
• Home Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Local de pesquisa : University of Georgia (UGA), United States
• Associated to the scholarship: 17/21573-0 - Genomic evaluation in composite cattle of the Montana breed using real and simulated data applying the BLUP genomic single-step method, BP.DR

Abstract

The seeking for methodologies capable of increase accuracy of genetic evaluation is constant. However for multi-breed populations few are the studies using ssGBLUP and specific approaches for these populations. The aim of this research project is to evaluate the impact of metafounders use in the genetic parameters estimation, genomicestimation breeding values (GEBV), bias and accuracy of GEBV for multi-breed population on ssGBLUP method. The data base is composed by phenotypic information of 514,165 pure-breed, crosses and composite animals (Montana). The traits of birth weight (BF), weaning weight (WW), postweaning weight gain (PWG) and scrotal circumference at 12 months of age (SC12) will be used. A total of 1,899 animals were genotyped using three different panels with 30, 35 or 770 thousand of SNPs. Subsequently, all these genotypes were imputed to a Illumina GeneSeek® Genomic Profiler (GGP) commercial panel with containing approximately 30,000 SNPs markers.Single-traits analysis for all traits described above will be performed. The methods BLUP, ssGBLUP (single-step BLUP) and ssGBLUP+MFS (single-step BLUP+ metafounders) will be performed, and then these models will be compared each other. The results of this study should show the advantages of metafounders use as well as ssGBLUP implementation in a multi-breed evaluation in order to increase the accuracy of genetic evaluations.