Gene co-expression networks associated with carcass traits reveal new pathways for muscle and fat deposition in Nelore cattle

Autor(es)

Silva-Vignato, Barbara ^[1] ; Coutinho, Luiz L. ^[1] ; Poleti, Mirele D. ^[2] ; Cesar, Aline S. M. ^[1] ; Moncau, Cristina T. ^[3] ; Regitano, Luciana C. A. ^[4] ; Balieiro, Julio C. C. ^[5]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Coll Agr Luiz de Queiroz, BR-13418900 Piracicaba, SP - Brazil

^[2] Univ Sao Paulo, Coll Anim Sci & Food Engn, BR-13635900 Pirassununga, SP - Brazil

^[3] Univ Fed Lavras, BR-37200000 Lavras, MG - Brazil

^[4] Embrapa Pecuaria Sudeste, BR-13560970 Sao Carlos, SP - Brazil

^[5] Univ Sao Paulo, Coll Vet Med & Anim Sci, BR-13635900 Pirassununga, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: BMC Genomics; v. 20, JAN 10 2019.
• Citações Web of Science: 0

Resumo

BackgroundPositively correlated with carcass weight and animal growth, the ribeye area (REA) and the backfat thickness (BFT) are economic important carcass traits, which impact directly on producer's payment. The selection of these traits has not been satisfactory since they are expressed later in the animal's life and multigene regulated. So, next-generation technologies have been applied in this area to improve animal's selection and better understand the molecular mechanisms involved in the development of these traits. Correlation network analysis, performed by tools like WGCNA (Weighted Correlation Network Analysis), has been used to explore gene-gene interactions and gene-phenotype correlations. Thus, this study aimed to identify putative candidate genes and metabolic pathways that regulate REA and BFT by constructing a gene co-expression network using WGCNA and RNA sequencing data, to better understand genetic and molecular variations behind these complex traits in Nelore cattle.ResultsThe gene co-expression network analysis, using WGCNA, were built using RNA-sequencing data normalized by transcript per million (TPM) from 43 Nelore steers. Forty-six gene clusters were constructed, between them, three were positively correlated (p-value<0.1) to the BFT (Green Yellow, Ivory, and Light Yellow modules) and, one cluster was negatively correlated (p-value<0.1) with REA (Salmon module). The enrichment analysis performed by DAVID and WebGestalt (FDR 5%) identified eight Gene Ontology (GO) terms and three KEGG pathways in the Green Yellow module, mostly associated with immune response and inflammatory mechanisms. The enrichment of the Salmon module demonstrated 19 GO terms and 21 KEGG pathways, related to muscle energy metabolism, lipid metabolism, muscle degradation, and oxidative stress diseases. The Ivory and Light yellow modules have not shown significant results in the enrichment analysis.ConclusionWith this study, we verified that inflammation and immune response pathways modulate the BFT trait. Energy and lipid metabolism pathways, highlighting fatty acid metabolism, were the central pathways associated with REA. Some genes, as RSAD2, EIF2AK2, ACAT1, and ACSL1 were considered as putative candidate related to these traits. Altogether these results allow us to a better comprehension of the molecular mechanisms that lead to muscle and fat deposition in bovine. (AU)

• Processo FAPESP: 12/23638-8 - Bases moleculares da qualidade da carne em bovinos da raça Nelore
• Beneficiário: Luciana Correia de Almeida Regitano
• Modalidade de apoio: Auxílio à Pesquisa - Temático