Regulatory networks involved in modulating fat deposition in pigs identified by gene co-expression analysis.

The regulatory mechanisms underlying the interaction between fatty acid (FA) profiles and gene expression are highly complex, involving signaling pathways and transcription factors that control lipid metabolism. Using the gene co-expression approach, we can identify key gene regulators and gain a better understanding of gene interactions that may play an important role in regulatory mechanisms. Therefore, this study aims to identify gene-expression regulatory mechanisms associated with FA deposition profiles in skeletal muscle across different diets. We used basal diets with different levels of soybean oil (1.5% soybean oil [SOY1.5], reference diet; or 3% soybean oil [SOY3.0], enriched diet) added during the growth and finishing phases in a 98-day study. Total RNA was extracted, and mRNA was sequenced (Illumina). Bioinformatics analysis was performed with quality control, preprocessing, and alignment using Sus scrofa11.1. Gene abundance was normalized to transcripts per million. To identify co-expressed modules, we used weighted gene co-expression network analysis (WGCNA) with RNA-Seq data and the deposited FA profile. After filtering, data from 33 immunocastrated male pigs were used in this study. To identify pathways and Gene Ontology (GO) terms affected by the enriched diet (with 3% soybean oil), DAVID and REVIGO were used. Diets with varying levels of soybean oil affect metabolic processes differently. In general, we identified co-expression networks mainly involved in lipid metabolism, diseases and general response involved in inflammatory processes, glucose homeostasis. We constructed co-expression networks and identified the hub genes, including TPM1 and SLC38A10, as well as CSRNP1, TRIP10, ZFP30, and MYBPH. Co-expression analysis using WGCNA provides new insights into fatty acid deposition by identifying candidate genes potentially involved in lipid regulation and influenced by dietary differences.