| Grant number: | 17/23633-0 |
| Support Opportunities: | Regular Research Grants |
| Start date: | March 01, 2020 |
| End date: | February 28, 2022 |
| Field of knowledge: | Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals |
| Principal Investigator: | Josineudson Augusto Ii de Vasconcelos Silva |
| Grantee: | Josineudson Augusto Ii de Vasconcelos Silva |
| Host Institution: | Faculdade de Medicina Veterinária e Zootecnia (FMVZ). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil |
| Associated researchers: | Anibal Eugênio Vercesi Filho ; Maria Eugênia Zerlotti Mercadante ; Mário Luiz Santana Júnior ; Rogério Abdallah Curi |
Abstract
The Gyr breed and its crosses are unquestionably a consolidated genetic material, being the base along with the other zebu breeds, for the support of the cattle raising of tropical and subtropical countries like Brazil, Colombia, Mexico, Peru, Venezuela. The productive and reproductive potentials of the animals are expressed only to the extent that their environmental conditions allow. This effect is called genotype-environment interaction, that is the expression of genotypes in two different environments, and can be quantified using genomic data to be included in sire breeding programs. The objective of this project is to evaluate the importance of genotype-environment interaction in linear reaction norm models, based on genomic values, aiming at the genomic selection for the Gyr milk production of animals from Brazil and Colombia, as well as the study of genomic regions of greater variance in the environmental gradient. For this study the only animals with phenotypic records (dairy control) and pedigree information from Brazil and Colombia will be genotyped. To achieve the objectives, analyzes of data imputation by the FImpute program, genetic-quantitative analyzes reaction norms models for interaction genotype-environment of milk production, random regression analyzes using Bayesian estimation of the variance components using genomic relationship matrices, and association analysis (GWAS) by the Mizstal genomic program will be performed. (AU)
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