Redes de coexpressão gênica e variantes de regiões regulatórias do tecido hepático associadas a fenótipos de qualidade de carne e carcaça em bovinos nellore

• Processo: 23/15881-4
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Mestrado
• Data de Início da vigência: 01 de fevereiro de 2024
• Data de Término da vigência: 31 de julho de 2024
• Área de conhecimento: Ciências Agrárias - Zootecnia - Genética e Melhoramento dos Animais Domésticos
• Pesquisador responsável: Luiz Lehmann Coutinho
• Beneficiário: Thaís Ribeiro da Silva
• Supervisor: James e Koltes
• Instituição Sede: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brasil
• Instituição Anfitriã: Iowa State University, Estados Unidos
• Vinculado à bolsa: 23/08402-2 - Redes de co-expressão gênica do tecido hepático associadas a fenótipos de qualidade da carne e carcaça em bovinos da raça nelore, BP.MS
• Assunto(s): Transcriptoma Biotecnologia
• Palavra(s)-Chave do Pesquisador: eQTL | Transcriptoma | Wgcna | Biotecnologia

Resumo

A new frontier in animal breeding is understanding how genetic variants influence phenotypes of economic interest. Transcriptome analysis, in combination with co-expression analysis, is instrumental in constructing gene expression networks associated with phenotypic traits. Understanding how genetic variants control gene expression should help us unravel some mechanisms that control phenotypic variance. This proposal aims to identify hepatic regulatory regions associated with gene expression and carcass and meat quality traits. To achieve this objective, we will use RNA-seq data from 90 animals that were also phenotyped for meat and carcass quality traits. We will employ Weighted Gene Co-expression Network Analysis (WGCNA), eQTL analysis, ATAC-Seq data, and the analysis of Transcription Factor Binding Sites (TFBS). The WGCNA analysis has already been completed, resulting in the identification of 10 significant gene network modules (p < 0.1) correlated with the meat and carcass phenotypes. Within these modules, our goal is to identify hub genes (highly connected genes) and transcription factors, highlighting the importance of the expression of these key regulators in modulating the studied phenotypes. The eQTL analysis will be used to identify the SNPs that regulate the expression of these regulatory genes. In addition, our project includes ATAC-seq data, allowing us to identify TFBS in regions of open chromatin and providing novel insights into the control of gene expression. Subsequent to these analyses, we will conduct a functional enrichment analysis of the co-expressed genes to elucidate the biological mechanisms that regulate these phenotypes. The integrated analysis will provide a comprehensive view of the regulatory mechanisms controlling important economic phenotypes. In addition, while at Iowa State University, the student will participate in graduate courses and lab meetings.