Aplicação de modelos funcionais na seleção genômica ampla

• Ano de defesa: 2017
• Autor(a) principal: Moura, Ernandes Guedes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Lavras; Programa de Pós-Graduação em Estatística e Experimentação Agropecuária; UFLA; brasil; Departamento de Ciências Exatas
• Palavras-chave em Português: Genomas – Seleção – Métodos estatísticos; Marcadores genéticos; Regressão (Estatística); Teoria bayesiana de decisão estatística; Genomes – Selection – Statistical methods; Genetic markers; Regression (Statistics); Bayesian statistical decision theory; Estatística; Genética
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/12270

Upon the emergence of high-density SNP markers, along with great advancements related to the increase in the predictive ability of models, there have been problems of multicolinearity and high dimensionality of models in genomic selections, causing many statistic and computational challenges. This work aimed at proposing a method and checking its efficiency in genomic selections with functional models. Thus, we suggest that the effects of a genetic locum is a function of its respective genomic position. To verify the suitability of such models, we simulated 300 individuals in three populations F2, according to three heritabilities (0.2; 0.5 and 0.8) in a total of 12150 SNP markers distributed into ten bond groups. The model proposed in this study was successful with oligogenic and polygenic scenarios, therefore, further research with real data and several genetic frames is recommended for more consistent conclusions.