Genetic parameters estimation for novel traits

• Ano de defesa: 2025
• Autor(a) principal: Garcia, Arielly Oliveira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa; Zootecnia
• Palavras-chave em Português: Bovinos de corte - Melhoramento genético; Bovinos de leite - Melhoramento genético; Suínos - Melhoramento genético; Análise de variância; Suínos - Doenças; Padrões de herança; CIENCIAS AGRARIAS::ZOOTECNIA::GENETICA E MELHORAMENTO DOS ANIMAIS DOMESTICOS
• Link de acesso: https://locus.ufv.br/handle/123456789/34618; https://doi.org/10.47328/ufvbbt.2025.519

Genetic improvement is a cornerstone of animal production systems, potentially enhancing productivity, health, and welfare across livestock species. The success of breeding programs relies on the accurate estimation of genetic parameters, which guide selection decisions and enable the prediction of breeding values. The parameters, heritability, genetic correlation, and repeatability, are informative, as they quantify the extent to which phenotypic variation is attributable to genetic causes and help to define the expected response to selection. Genetic parameters are derived from the decomposition of phenotypic variance into its underlying components, including additive genetic, maternal, environmental, and permanent environmental variances. Estimating these components typically involves linear mixed models and relies on appropriately structured data sets. Understanding the magnitude and structure of these components is essential for the design and implementation of effective breeding strategies. Different categories of traits tend to exhibit distinct patterns of genetic variability. Production traits, such as milk yield and composition, are typically characterized by moderate to high heritability and repeatability. Reproductive traits, in contrast, often show low heritabilities due to their complex physiological nature and strong environmental influence. Welfare-related traits and health indicators usually present low to intermediate values, reflecting both genetic and environmental contributions to their expression. These expected ranges provide important context when interpreting estimated genetic parameters and inform selection strategies across trait types. This thesis aimed to estimate variance components and genetic parameters across different countries, animal populations, and trait categories, providing a comprehensive evaluation of the genetic architecture of production, reproductive, and welfare traits. Despite the biological and species- specific differences, a unified analytical approach was applied, with each study focusing on genetic (direct and maternal) variances and covariances and repeatability when applicable. The first study focused on dairy Gir cattle in Brazil, aiming to estimate heritability, genetic correlations, and repeatability for milk quality traits, namely fat percentage, protein percentage, and somatic cell count. The second study evaluated calving ease in a beef-on-dairy system in the United States, involving Jersey and Holstein cows inseminated with Angus, Charolais, and Simmental bulls,intending to estimate direct and maternal heritabilities for this reproductive trait. The third study, conducted in the Netherlands, involved a pig population and focused on the estimation of genetic parameters for two welfare-related traits: swine inflammation and necrosis syndrome and skin damage. The analysis included direct and maternal heritability estimates, genetic correlations between the traits, and repeatability estimates for skin damage. Across studies, the results aligned with established expectations for the trait categories: reproductive traits exhibited the lowest heritabilities, welfare traits also showed low estimations, and production traits demonstrated higher heritabilities and repeatabilities. These findings reinforce the importance of tailoring breeding strategies to the genetic characteristics of each trait and contribute to the broader understanding of trait-specific genetic variability across livestock species. Keywords: Beef-on-Dairy. Gir cattle. Livestock. Pigs. Variance components. SINS.