Genomic prediction for sexual precocity and longevity traits using metafunders information through the blup genomic single step method of Nellore breed

• Grant number: 22/12134-0
• Support Opportunities: Scholarships in Brazil - Master
• Effective date (Start): March 01, 2023
• Effective date (End): January 29, 2025
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Fernando Sebastián Baldi Rey
• Grantee: Larissa Bordin Temp
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Associated scholarship(s): 23/08817-8 - Application of weighted genomic matrix in predicting reproductive performance in Nelore cattle, BE.EP.MS

Abstract

This research project aims to evaluate the effect of using one or many metafounders and missing pedigree in the estimates of (co) variance components, accuracy and bias of prediction for genomic values using the single step BLUP method for traits related to sexual precocity, fertility and longevity in cattle of Nellore breed. Phenotypic and genotypic information from Nellore Brazil breeding program will be used for the traits scrotal circumference at year (SC365), age at puberty of males (APM), probability of precocious calving at 24 (PPC24) and 30 months (PPC30) and stayability at 48 (STAY 48) and 72 months (STAY 72) with approximately 414.000, 25.000, 200.000 and 500.000 phenotypic observations, respectively. Single-trait BLUP-based, genomic analyses without metafounders (ssGBLUP) and genomic analyses using metafunders (ssGBLUP+MF) will be performed. The adopted metafounders will be related by a matrix of additive relations A() given by a positive definite matrix that can be inverted . Different numbers of metafounders will be tested. The methods used will be compared based on the accuracy and prediction bias of the genomic values for SC365, APM, PPC24, PPC30, STAY 48 and STAY 72 obtained by the LR method (linear regression). Through this project, it will be possible to determine how the inclusion of metafounders affects the prediction ability, accuracy and bias of genomic evaluations, as well as recommendations for its use in future work using genomic information in the Nellore breed.