Potential regulation of lncRNAs in the hepatic lipid metabolism of pigs fed different levels and oil sources

• Grant number: 24/19019-8
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: May 01, 2025
• End date: April 30, 2026
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Aline Silva Mello Cesar
• Grantee: Bruna Pereira Martins da Silva
• Supervisor: Wellison Jarles da Silva Diniz
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Institution abroad: Auburn University, United States
• Associated to the scholarship: 22/10780-2 - Potential regulation of lncRNA in lipid metabolism of the muscle and liver of pigs fed different levels and oil sources, BP.DR

Abstract

Lipids act as signaling molecules, participate in several processes, and are essential for all cell types. The liver is one of the main tissues responsible for lipid metabolism, a complex and dynamic process involving various transcriptional regulators. lncRNAs play key roles in lipid metabolism and have been widely studied in animal models such as pigs. The objectives of this study are to identify pathways, networks, and co-expression modules associated with lncRNAs and lipid metabolism and to investigate the regulatory potential of these lncRNAs, using transcriptome data from the liver of pigs fed different levels and sources of oil. For this study, data from 72 male pigs from a 98-day experimental period will be used. The experimental treatments consisted of corn and soybean meal diets containing 1.5% soybean oil (SOY1.5), or 3.0% soybean oil (SOY3.0), or 3.0% canola oil (CO), or 3.0% fish oil (FO). The lncRNAs were identified, quantified, and annotated from the RNA-Seq data (n = 72). The results obtained were used for differential expression analysis using the DESeq2. The association with phenotypes of interest (fatty acid profile and animal energy efficiency) will be estimated through the construction of co-expression networks from the RNA-Seq data with the normalized transcripts per million (TPM), using the Weighted Correlation Network Analysis (WGCNA) R-package. Functional enrichment analysis and network and pathway analysis of genes from the co-expression modules containing lncRNA correlated with the fatty acid profile, and animal energy efficiency will be carried out using the ClueGO in the Cytoscape plug-in and ShinyGO. The expected results of this study have a technological and innovative profile since they can provide a deeper understanding of the processes that link lncRNA to lipid metabolism, using pigs as a relevant animal model.