Parâmetros Genéticos, Análise Funcional de Genes Candidatos e Efeitos Pleiotrópicos para Características de Interesse Econômico em Bovinos Senepol

• Ano de defesa: 2024
• Autor(a) principal: Clélia Soares de Assis
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; Brasil; VETER - ESCOLA DE VETERINARIA; Programa de Pós-Graduação em Zootecnia; UFMG
• Palavras-chave em Português: Bovino; Veterinária
• Link de acesso: http://hdl.handle.net/1843/74490; https://orcid.org/0009-0006-5315-1170

Understanding the genetic architecture of feed efficiency traits and their relationship with other traits of economic interest, with carcass traits and meat quality, may promote sustainable benefits to beef cattle farming activities. Data from 42,251 Senepol cattle, females and males (castrated and non-castrated) were evaluated. The following characteristics were analyzed: residual food intake (RFI), dry matter intake (DMI), rib eye area (REA), subcutaneous fat thickness (SFT) and marbling (MAR). The components of (co)variance, heritabilities and genetic correlations were estimated using conventional BLUP and genomic ssGBLUP, validating the use of genomic information in the genetic prediction of the characteristics under study through linear regression analysis (RL). Genetic values and Single Nucleotide Polymorphism (SNP) solutions were obtained using the genomic ssGBLUP method. Of the 42,251 cattle, 4,419 genotyped cattle were used in genome-wide association studies to identify genomic windows that explain at least 1% of the genetic variance for the traits under study. The annotation of positional candidate genes was performed using the GALLO/R package. To identify functional candidate genes (FCG), a systems biology approach was adopted, using software such as GUILDify and ToppGene. The heritability estimates obtained by the BLUP and genomic ssGBLUP methods were consistent for most traits. The genetic correlations obtained by genomic ssGBLUP, in general, showed a decrease, however no difference was observed due to the overlap of high-density intervals. The prediction accuracies obtained using the genomic ssGBLUP method were, for the most part, higher than for BLUP, therefore the inclusion of genomic information provided an improvement in prediction accuracies. Eight FCGs were shared between at least two traits, suggesting possible simultaneous control of correlated traits. The identification of genomic regions and their respective genes can allow understanding the genetic architecture of RFI in Senepol cattle. These results are promising for beef cattle farming, as they can serve as guides to evaluate the genetic architecture of feed efficiency traits and their relationship with other traits of economic interest, evaluated in different environments.