Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Central Genes Associated With Bovine Subcutaneous Adipose Tissue.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35812879", "kind": "science-record", "revision": 4, "content_hash": "sha256:3cf77fedd1436c5b2fe44f35029be398b4293a72f8dbbc09214961a0d77c5c26", "created_at": "2026-11-01T18:14:52Z", "updated_at": "2026-11-01T22:06:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Weighted Gene Co-Expression Network Analysis Identifies Key Modules and Central Genes Associated With Bovine Subcutaneous Adipose Tissue.", "doi": "10.3389/fvets.2022.914848", "pmid": "35812879", "authors": ["Hui Sheng", "Cuili Pan", "Shuzhe Wang", "Chaoyun Yang", "Junxing Zhang", "Chunli Hu", "Honghong Hu", "Xue Feng", "Mengli Yang", "Zhaoxiong Lei", "Yuhong Gao", "Zhong Wang", "Yun Ma"], "journal": "Frontiers in veterinary science", "year": 2022, "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.\nResults: 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.\nConclusion: 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.", "claims": [{"id": "claim-method", "statement": "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.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35812879", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "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."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35812879", "locator": "sections[20] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "WGCNA analysis of GSE116775 identified the blue module as the module most highly correlated with bovine subcutaneous adipose tissue.", "kind": "quantitative", "target": {"value": 0.88, "unit": "correlation coefficient", "tolerance": null, "source": "According to the aim of the study, we found the highest correlation between the blue module and bovine subcutaneous adipose tissue (r = 0.88, p = 3e-61)."}, "evidence": [{"asset": "source:pmid:35812879", "locator": "sections[14] \"Identification of Key Modules\" paragraph 2", "quote": "According to the aim of the study, we found the highest correlation between the blue module and bovine subcutaneous adipose tissue (r = 0.88, p = 3e-61)."}, {"asset": "source:pmid:35812879", "locator": "sections[14] \"Identification of Key Modules\" paragraph 2", "quote": "Figure 3C shows that the expression level of genes related to subcutaneous adipose tissue in the blue module is significantly higher than that in other tissues, so the blue module is selected for further analysis."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "WGCNA analysis of GSE116775 identified the blue module as the module most highly correlated with bovine subcutaneous adipose tissue.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35812879"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE116775"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE116775"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35812879", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fvets.2022.914848", "sha256": 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