Identification of key LncRNAs and mRNAs associated with intramuscular fat in pig via WGCNA.

Abstract

Background: Intramuscular fat (IMF) not only directly affects the tenderness, juiciness, and overall flavour of meat but also plays a significant role in influencing consumer preferences for pork. Therefore, exploring key biomarkers that influence IMF deposition is highly important for breeding high-quality pork. IMF is a typical quantitative trait that is regulated by the interaction of multiple coding and noncoding RNAs. Traditional differential analysis methods typically focus on individual genes, making it difficult to identify key genes and their underlying mechanisms accurately. Weighted gene coexpression network analysis (WGCNA) is an efficient and accurate method for identifying and characterizing key pathways and genes associated with complex traits. Therefore, the aim of this study was to construct an mRNA‒lncRNA coexpression network related to IMF using WGCNA to explore and identify potential candidate genes that influence IMF in pigs.

Results: Full-length transcriptome sequencing was performed on 31 220-day-old Jiangquan black pigs raised in the same environment, and a gene expression matrix comprising 25,609 genes was constructed. Nine coexpression modules were identified through WGCNA, with the number of genes in these modules ranging from 33 to 3648. The magenta module (corr = 0.7, P < 0.01) and the turquoise module (corr = -0.77, P < 0.01) were significantly associated with IMF deposition. Hub genes in each module were identified on the basis of the screening criteria of GS > 0.4 and MM > 0.8. Combined with enrichment analysis and protein‒protein interaction (PPI) analysis, 18 key mRNAs potentially related to IMF were selected: CRKL, CBL, PDGFRB, DOCK1, YWHAH, HSP90AB1, LOC100524873, NDUFA1, NDUFA11, NDUFA12, NDUFA2, NDUFAB1, NDUFB10, NDUFB3, NDUFB7, NDUFS5, NDUFS6, and UQCR10. To explore the regulatory role of lncRNAs in the process of IMF deposition, we constructed an lncRNA‒mRNA‒pathway network on the basis of the relationships between lncRNAs and key mRNAs, as well as the results of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. This network includes four key lncRNAs (TGOLN2, LOC100521518, LOC100524915, and LOC100622481) and predicts the potential mechanisms by which lncRNAs regulate IMF deposition.

Conclusions: Through WGCNA, enrichment analysis, and PPI analysis, 18 mRNAs and four lncRNAs potentially involved in IMF deposition were identified, and the lncRNA regulatory pathways were preliminarily explored. Our findings provide new insights into the regulatory mechanisms of pig IMF deposition and lay the foundation for further exploration of the molecular mechanisms underlying pig fat deposition.