Avaliação da seleção genômica em bovinos: percepções de simulações computacionais usando dados reais de SNP
DOI:
https://doi.org/10.57201/ieuna2424208Palavras-chave:
precisão preditiva, seleção de marcadores, cruzamentoResumo
A seleção genômica (GS) é um método que usa dados genômicos para estimar os valores de reprodução e classificar os candidatos à seleção. Apesar de suas muitas vantagens, sua aplicação em programas de criação de gado ainda é incipiente em muitos sistemas pecuários desenvolvidos em ambientes tropicais e subtropicais, como os do Paraguai. As simulações computacionais são ferramentas poderosas que melhoram nossa compreensão das aplicações da SG em diferentes cenários e são valiosas como uma etapa inicial antes da implementação dessa técnica em programas de melhoramento "reais". Neste estudo, dados reais sobre polimorfismos de nucleotídeo único (SNPs) das raças Indicus e Taurus foram usados para simular três esquemas de cruzamento: cruzamentos F1, cruzamentos absorventes e rotacionais. Os fenótipos foram selecionados para características relacionadas à força de cisalhamento, crescimento e tolerância. Comparamos a precisão preditiva de três chips SNP de 50k que diferiam nas metodologias de seleção: seleção aleatória, seleção baseada em diferenças mínimas de frequência alélica entre raças e seleção baseada em diferenças mínimas de frequência alélica entre raças com um limite de 0,09 em Taurus. Os resultados indicam que o cruzamento rotacional demonstra uma precisão preditiva ideal (0,38), enquanto a seleção de marcadores com base nas diferenças de frequência alélica entre as raças (0,18 e 0,17, respectivamente) não beneficia significativamente as previsões.
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Copyright (c) 2024 Lino César Ramírez Ayala, Jordi Leno-Colorado, Laura M. Zingaretti, Elies Ramón Gurrea, Yuliaxis Ramayo-Caldas, Miguel Pérez-Enciso
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