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Genomic analysis for preweaning calf mortality in Nellore cattle /

Orientador: Ana Fabrícia Braga Magalhães / Resumo: ABSTRACT – Preweaning calf mortality is one of main causes of economic losses in beef cattle, since most of economic incomes are represented by the number of weaned calves available for sale. It is also detrimental for genetic progress due to the reduction of young candidates for selection. The inclusion of molecular markers in genetic analysis allows a better understanding of genetic mechanisms underlying calf mortality. The objectives of this study were: i) to estimate direct and maternal heritability of preweaning calf mortality in Nellore cattle and ii) to seek for genomic regions and candidate genes affecting direct and maternal effects of preweaning calf mortality in Nellore cattle. Variance components were estimated via Bayesian Inference using a threshold animal model, that included the systematic effects of contemporary group, birth weight as linear covariate, and age of dam at calving as linear and quadratic covariates. The direct and maternal genetics, and the residual were fitted as random effects. The final dataset used contained phenotypic records on 67,196 animals, offspring of 1,469 sires and 30,970 dams. The SNPs effects were estimated based on the weighted single-step GBLUP approach, using information of 8,443 genotyped animals with 410,936 SNPs. Direct and maternal heritability estimates were of 0.2143±0.0348 and 0.0137±0.0066, respectively. The top 10 genomic regions accounted for 13.61 and 14.23% of direct and maternal additive genetic variance and harbor... (Resumo completo, clicar acesso eletrônico abaixo) / Mestre

Identiferoai:union.ndltd.org:UNESP/oai:www.athena.biblioteca.unesp.br:UEP01-000925228
Date January 2019
CreatorsGarzón, Natalia Andrea Marín
ContributorsUniversidade Estadual Paulista "Júlio de Mesquita Filho" Faculdade de Ciências Agrárias e Veterinárias.
PublisherJaboticabal,
Source SetsUniversidade Estadual Paulista
LanguagePortuguese
Detected LanguageEnglish
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