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Use of simulation and modelling as a tool to identify animals to be genotyped

Grant number: 18/26465-3
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): April 01, 2019
Effective date (End): February 28, 2022
Field of knowledge:Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
Principal researcher:Júlio Cesar de Carvalho Balieiro
Grantee:Fernando de Oliveira Bussiman
Home Institution: Faculdade de Medicina Veterinária e Zootecnia (FMVZ). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated scholarship(s):19/25801-2 - Understanding how population structure, genotyping strategy, and selection affects genomic predictions, BE.EP.DR

Abstract

The cost of genotyping still being the main obstacle for research and implementation of genomic selection in several animal species in Brazil. Studies of genome-wide association are also dependent on government or private funding, and often have the number of animals reduced according to the cost of each genotyped animal in the experiments. This work aims to use the simulation technique to propose methodologies of previously study who and how many animals to be genotyped, but also to validate different strategies of statistical modeling for discrete quantitative variables. Genotypes and phenotypes will be simulated for a real population according to their pedigree. The distribution of the simulated traits will be based on real distribution of important phenotypes to the population under study. Different genotyping strategies will be tested: Top-down EBV (50%> predicted genetic values - EBVs and 50% phenotypes and 50% EBvs); Top Pheno (> phenotypes); Random (random); Progeny (animals with higher progeny) and Graph Therory (animals sampled within communities). Parametric and non-parametric modelling will be tested in order to determine the best of analysis strategy. The following strategies will be evaluated: (a) random regression; (b) best linear unbiased prediction, by single-step; (c) ridge regression; (d) Reproducing Kernel Hilbert Spaces Regression (RKHS); (e) generalized linear mixed model, and finally; (f) linear threshold model. Given the advantages of multitrait models, the rank reduction technique will be implemented to enable complex models in the practical field, aiming possible implementation of breeding programs. It is expected that this work will implement simulation routines based on real pedigree and determine the most appropriate strategy for analysis to select the best set of animals to be genotyped in domestic populations, as well as, to indicate the advantages and disadvantages of each modeling implemented for genetic evaluations, reducing spending few informative animal genotyping to characterize the population. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BUSSIMAN, FERNANDO DE OLIVEIRA; FONSECA E SILVA, FABYANO; BUENO CARVALHO, RACHEL SANTOS; VENTURA, RICARDO VIEIRA; MATTOS, ELISANGELA CHICARONI; STERMAN FERRAZ, JOSE BENTO; ELER, JOANIR PEREIRA; DE CARVALHO BALIEIRO, JULIO CESAR. Confirmatory factor analysis and structural equation models to dissect the relationship between gait and morphology in Campolina horses. LIVESTOCK SCIENCE, v. 255, JAN 2022. Web of Science Citations: 0.
BUSSIMAN, FERNANDO DE OLIVEIRA; BUENO CARVALHO, RACHEL SANTOS; E SILVA, FABYANO FONSECA; VENTURA, RICARDO VIEIRA; STERMAN FERRAZ, JOSE BENTO; MATTOS, ELISANGELA CHICARONI; ELER, JOANIR PEREIRA; DE CARVALHO BALIEIRO, JULIO CESAR. Reduced rank analysis of morphometric and functional traits in Campolina horses. JOURNAL OF ANIMAL BREEDING AND GENETICS, NOV 2021. Web of Science Citations: 0.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.