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LIVER TISSUE GENE COEXPRESSION NETWORKS ASSOCIATED WITH MEAT AND CARCASS QUALITY PHENOTYPES IN NELLORE CATTLE

Grant number: 23/08402-2
Support Opportunities:Scholarships in Brazil - Master
Effective date (Start): September 01, 2023
Status:Discontinued
Field of knowledge:Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
Principal Investigator:Luiz Lehmann Coutinho
Grantee:Thaís Ribeiro da Silva
Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:19/04089-2 - The Nelore hologenome: implications in beef quality and feed efficiency, AP.ESCIENCE.TEM
Associated scholarship(s):23/15881-4 - LIVER GENE CO-EXPRESSION NETWORKS AND REGULATORY REGION VARIANTS ASSOCIATED WITH MEAT AND CARCASS QUALITY PHENOTYPES IN NELLORE CATTLE, BE.EP.MS

Abstract

In Brazil, beef cattle are mainly based on pure and crossbred zebu animals, which makes the breed important in the global beef market. Transcriptome analysis and WGCNA (Weighted correlation network analysis) are important methods for the construction of gene expression networks associated with phenotypic characteristics to propose new genes of interest for further studies. In this way, it is easier to elucidate the shared biological pathways underlying these characteristics, as well as the main regulators involved. The objective of this study is to construct co-expression networks of genes expressed in the liver of Nellore cattle using Weighted Gene Correlation Network Analysis (WGCNA) and identify hub genes and metabolic pathways regulating the phenotypes of quality of meat and carcass: Shear force at 0, 7 and 14 days, Ribeye area, pH, Color at 0, 7 and 14 days, Cooking Loss at 0, 7 and 14 days, Backfat Thickness, Final Weight Gain, Renal, pelvic and inguinal fat expressed as % of hot carcass weight and Renal, pelvic and inguinal fat expressed in kg. Liver tissue samples were collected from 90 animals for RNA-seq. The sequencing data were aligned to the reference genome and the expression data were normalized to log2-CPM. The analysis will be performed using the R package WGCNA version 1.72-1. An enrichment analysis will be achieved, using the DAVID 2021 version, to verify the significantly enriched modules and thereby verify which metabolic pathways and processes these genes are involved in. Thus, identifying possible candidate genes associated with meat and carcass quality phenotypes.

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