An integrated analysis of mRNAs, lncRNAs, and miRNAs based on weighted gene co-expression network analysis involved in bovine endometritis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34508138", "kind": "science-record", "revision": 5, "content_hash": "sha256:fc2cf0d1a46a97d09a811ad1ef7acf52521c7679a303624a51a61d2e7e14432c", "created_at": "2026-11-01T15:41:51Z", "updated_at": "2026-11-01T21:26:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An integrated analysis of mRNAs, lncRNAs, and miRNAs based on weighted gene co-expression network analysis involved in bovine endometritis.", "doi": "10.1038/s41598-021-97319-y", "pmid": "34508138", "authors": ["Negin Sheybani", "Mohammad Reza Bakhtiarizadeh", "Abdolreza Salehi"], "journal": "Scientific reports", "year": 2021, "abstract": "In dairy cattle, endometritis is a severe infectious disease that occurs following parturition. It is clear that genetic factors are involved in the etiology of endometritis, however, the molecular pathogenesis of endometritis is not entirely understood. In this study, a system biology approach was used to better understand the molecular mechanisms underlying the development of endometritis. Forty transcriptomic datasets comprising of 20 RNA-Seq (GSE66825) and 20 miRNA-Seq (GSE66826) were obtained from the GEO database. Next, the co-expressed modules were constructed based on RNA-Seq (Rb-modules) and miRNA-Seq (mb-modules) data, separately, using a weighted gene co-expression network analysis (WGCNA) approach. Preservation analysis was used to find the non-preserved Rb-modules in endometritis samples. Afterward, the non-preserved Rb-modules were assigned to the mb-modules to construct the integrated regulatory networks. Just highly connected genes (hubs) in the networks were considered and functional enrichment analysis was used to identify the biological pathways associated with the development of the disease. Furthermore, additional bioinformatic analysis including protein-protein interactions network and miRNA target prediction were applied to enhance the reliability of the results. Thirty-five Rb-modules and 10 mb-modules were identified and 19 and 10 modules were non-preserved, respectively, which were enriched in biological pathways related to endometritis like inflammation and ciliogenesis. Two non-preserved Rb-modules were significantly assigned to three mb-modules and three and two important sub-networks in the Rb-modules were identified, respectively, including important mRNAs, lncRNAs and miRNAs genes like IRAK1, CASP3, CCDC40, CCDC39, ZMYND10, FOXJ1, TLR4, IL10, STAT3, FN1, AKT1, CD68, ENSBTAG00000049936, ENSBTAG00000050527, ENSBTAG00000051242, ENSBTAG00000049287, bta-miR-449, bta-miR-484, bta-miR-149, bta-miR-30b and bta-miR-423. The potential roles of these genes have been previously demonstrated in endometritis or related pathways, which reinforced putative functions of the suggested integrated regulatory networks in the endometritis pathogenesis. These findings may help further elucidate the underlying mechanisms of bovine endometritis.", "claims": [{"id": "claim-method", "statement": "To assign the mb-modules to Rb-modules, spearman correlations were calculated between the MEs of Rb-modules and mb-modules.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34508138", "locator": "sections[9] \"Assign the mb-modules to the Rb-modules and target prediction\" paragraph 2", "quote": "To assign the mb-modules to Rb-modules, spearman correlations were calculated between the MEs of Rb-modules and mb-modules."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Raw RNA-Seq and miRNA-Seq data were obtained from the Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (NCBI) under the accession number GSE66827. The data contained endometrial samples related to nine healthy and six endometritis cows at 7 and 21 days post-partum6.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34508138", "locator": "sections[3] \"Dataset\" paragraph 2", "quote": "Raw RNA-Seq and miRNA-Seq data were obtained from the Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (NCBI) under the accession number GSE66827. 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