| Grant number: | 21/14641-4 |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate |
| Start date: | May 01, 2022 |
| End date: | April 30, 2023 |
| Field of knowledge: | Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals |
| Principal Investigator: | José Bento Sterman Ferraz |
| Grantee: | Felipe Eguti de Carvalho |
| Supervisor: | Luiz Fernando Brito |
| Host Institution: | Faculdade de Zootecnia e Engenharia de Alimentos (FZEA). Universidade de São Paulo (USP). Pirassununga , SP, Brazil |
| Institution abroad: | Purdue University, United States |
| Associated to the scholarship: | 19/25266-0 - Genomic prediction for sex-dependent traits in Nellore cattle, BP.DR |
Abstract This study will evaluate the inclusion of genomic information in the prediction of genetic values, with or without the inclusion of the X chromosome markers, as well as explore our knowledge of the mechanisms that modulate the genetic architecture of andrology traits and semen quality in males and precocity in females in Nellore cattle. The dataset consists of pedigree information containing 660,608 animals, with approximately eight equivalent generations. Phenotypic data of Nellore heifers, cows, and bulls, ranging from approximately 10,000 to 100,000 in number, aged between 14 to 48 months and born between 1998 and 2020. Information on 7,303 genotyped animals for 44,135 SNPs (single nucleotide polymorphisms) using the GeneSeek SNP Beadchips Bovine GGP-HDi chip. The choice of appropriate animal models for the analyses will be made as part of the development of this study, and the analysis will be performed based on the single-step genomic BLUP method. GWAS analyses will be performed using the single-step GWAS methodology considering the same linear animal model used to estimate the variance components and will be performed in two scenarios: first, without the inclusion of markers located on the X chromosome, and second, with the inclusion of markers on the X chromosome. Based on the estimates of the means of (co)variance components obtained with the model that included the X chromosome + autosomes and the model that included only autosomes, we will obtain two breeding values for the animals, calculated by the proposed single-step method and the predictive performance will be calculated using the dataset that has been divided into training and validation subsets. We must obtain reliable information and create tools for improving the reproductive performance of Nellore animals. (AU) | |
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