ArticleFrontiers in veterinary science2022
Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Central Genes Associated With Bovine Subcutaneous Adipose Tissue.
Article in Frontiers in veterinary science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 10 citations in OpenAlex.
- Identification of diagnostic biomarkers of and immune cell infiltration analysis in bovine respiratory disease.Frontiers in veterinary science · 2025Article
- Evaluation of enzymatic protocols to optimize efficiency of bovine adipose tissue-derived mesenchymal stromal cell isolation.NPJ science of food · 2024Article
- Integrated analysis of muscle lncRNA and mRNA of Chinese indigenous breed Ningxiang pig in four developmental stages.Frontiers in veterinary science · 2024Article
- Article
- Identification of crucial modules and genes associated with backfat tissue development by WGCNA in Ningxiang pigs.Frontiers in genetics · 2023Article
- Expression Profile of Housekeeping Genes and Tissue-Specific Genes in Multiple Tissues of Pigs.Animals : an open access journal from MDPI · 2022Article
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13 authors at 2 institutions in 1 country.
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Abstract
Background: Fat deposition is an important economic trait in livestock and poultry production. However, the relationship between various genes and signal pathways of fat deposition is still unclear to a large extent. The purpose of this study is to analyze the potential molecular targets and related molecular pathways in bovine subcutaneous adipose tissue. Results: We downloaded the GSE116775 microarray dataset from Gene Expression Omnibus (GEO). The weighted gene co-expression network (WGCNA) was used to analyze the gene expression profile, and the key gene modules with the highest correlation with subcutaneous adipose tissue were identified, and the functional enrichment of the key modules was analyzed. Then, the "real" Hub gene was screened by in-module analysis and protein-protein interaction network (PPI), and its expression level in tissue samples and adipocytes was verified. The study showed that a total of nine co-expression modules were identified, and the number of genes in these modules ranged from 101 to 1,509. Among them, the blue module is most closely related to subcutaneous adipose tissue, containing 1,387 genes. These genes were significantly enriched in 10 gene ontologies including extracellular matrix organization, biological adhesion, and collagen metabolic process, and were mainly involved in pathways including ECM-receptor interaction, focal adhesion, cAMP signaling pathway, PI3K-AKT signaling pathway, and regulation of lipolysis in adipocytes. In the PPI network and coexpression network, five genes (CAV1, ITGA5, COL5A1, ABL1, and HSPG2) were identified as "real" Hub genes. Analysis of Hub gene expression by dataset revealed that the expression of these Hub genes was significantly higher in subcutaneous adipose tissue than in other tissues. In addition, real-time fluorescence quantitative PCR (qRT-PCR) analysis based on tissue samples and adipocytes also confirmed the above results. Conclusion: In this study, five key genes related to subcutaneous adipose tissue were discovered, which laid a foundation for further study of the molecular regulation mechanism of subcutaneous adipose tissue development and adipose deposition.
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