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pmid:32982206
Construction of Potential miRNA-mRNA Regulatory Network in COPD Plasma by Bioinformatics Analysis.
Mengchan Zhu · Maosong Ye · Jian Wang · Ling Ye · Meiling Jin
International journal of chronic obstructive pulmonary disease · 2020 doi:10.2147/COPD.S255262
Paper
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Experiment
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Analysis
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Execution
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Complete file
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Increasing evidence indicates that aberrantly expressed microRNAs (miRNAs) are involved in the pathogenesis of COPD. However, an integrative exploration of miRNA-mRNA regulatory network in COPD plasma remains lacking.\nMethods: The microarray datasets GSE24709, GSE61741, and GSE31568 were downloaded from the GEO database and analyzed using GEO2R tool to identify differentially expressed miRNAs (DEMs) between COPD and normal plasma. The consistently changing miRNAs in the three datasets were screened out as candidate DEMs. Potential upstream transcription factors and downstream target genes of candidate DEMs were predicted by FunRich and miRNet, respectively. Next, GO annotation and KEGG pathway enrichment analysis for target genes were performed using DAVID. Then, PPI and DEM-hub gene network were constructed using the STRING database and Cytoscape software. Finally, GSE56768 was used to evaluate the hub gene expressions.\nResults: A total of nine (six upregulated and three downregulated) DEMs were screened out in the above three datasets. SP1 was predicted to potentially regulate most of the downregulated DEMs, while YY1 and E2F1 could regulate both upregulated and downregulated DEMs. 1139 target genes were then predicted, including 596 upregulated DEM target genes and 543 downregulated DEM target genes. Target genes of DEMs were mainly enriched in PI3K/Akt signaling pathway, mTOR signaling pathway, and autophagy. Through the DEM-hub gene network construction, most of the hub genes were found to be potentially modulated by miR-497-5p, miR-130b-5p, and miR-126-5p. Among the top 12 hub genes, MYC and FOXO1 expressions were consistent with that in the GSE56768 dataset.\nConclusion: In the study, potential miRNA-mRNA regulatory network was firstly constructed in COPD plasma, which may provide a new insight into the pathogenesis and treatment of COPD.", "claims": [{"id": "claim-method", "statement": "Student’s t-test was used to identify the differentially expressed genes (DEGs) between COPD and normal plasma.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32982206", "locator": "sections[9] \"Expression Analysis of Hub Genes by GSE56768 Dataset\" paragraph 2", "quote": "Student’s t-test was used to identify the differentially expressed genes (DEGs) between COPD and normal plasma."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The microarray datasets GSE24709, GSE61741, and GSE31568 were downloaded from the GEO database and analyzed using GEO2R tool to identify differentially expressed miRNAs (DEMs) between COPD and normal plasma.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32982206", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The microarray datasets GSE24709, GSE61741, and GSE31568 were downloaded from the GEO database and analyzed using GEO2R tool to identify differentially expressed miRNAs (DEMs) between COPD and normal plasma."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:32982206"], "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. 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"column_count": 4, "numeric_cells": 20, "header_rows": 1, "locator": "section[13]/table-wrap[1]#t0002"}}, {"id": "asset:table:pmid:32982206:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:0eb85fafe4fe64be5e10449684c00443438e8f1c195eb1693a199bedd98b49a3", "bytes": 786, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#t0003", "version": null, "note": "Top 10 Hub Genes of the Significantly Upregulated and Downregulated DEMs in the PPI Network Ranked by MCC", "structure": {"pmcid": "PMC7490070", "section_index": 15, "section_title": "Construction of PPI and DEM-Hub Gene Network", "row_count": 12, "column_count": 4}, "table": {"label": "Table 3", "caption": "Top 10 Hub Genes of the Significantly Upregulated and Downregulated DEMs in the PPI Network Ranked by MCC", "rows": [["Upregulated DEMs", "Downregulated DEMs"], ["Gene Symbol", "Score", "Gene Symbol", "Score"], ["MYC", "22,916", "FBXW7", "87,178,818,926"], ["VEGFA", "22,125", "CUL3", "87,178,299,448"], ["MAPK8", "18,605", "BTRC", "87,178,293,375"], ["STAT5A", "15,337", "ZBTB16", "87,178,292,663"], ["FOXO3", "14,769", "ANAPC13", "87,178,292,097"], ["FOXO1", "14,200", "CDC34", "87,178,292,085"], ["IGF1", "13,828", "FBXL18", "87,178,291,926"], ["NR3C1", "12,845", "FBXL20", "87,178,291,922"], ["HSPA8", "11,147", "SMURF1", "87,178,291,408"], ["EP300", "8381", "UBE2V1", "87,178,291,229"]], "row_count": 12, "column_count": 4, "numeric_cells": 26, "header_rows": 1, "locator": "section[15]/table-wrap[1]#t0003"}}], "gaps": ["asset:data:geo:GSE24709 not downloaded", "asset:data:geo:GSE24709 licence not read", "asset:data:geo:GSE31568 not downloaded", "asset:data:geo:GSE31568 licence not read", "asset:data:geo:GSE56768 not downloaded", "asset:data:geo:GSE56768 licence not read", "asset:data:geo:GSE61741 not downloaded", "asset:data:geo:GSE61741 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "PPI"}}, {"id": "method-2", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "pathway enrichment"}}, {"id": "method-3", "family": null, "specific": null, "label": "Student’s t-test", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Student’s t-test was used to identify the differentially expressed genes (DEGs) between COPD and normal plasma."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: ppi_network."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE24709", "GSE61741", "GSE31568", "GSE56768"], "resolved_accessions": ["GSE24709", "GSE61741", "GSE31568", "GSE56768"], "statements": ["The microarray datasets GSE24709, GSE61741, and GSE31568 were downloaded from the GEO database and analyzed using GEO2R tool to identify differentially expressed miRNAs (DEMs) between COPD and normal plasma."], "basis": "The paper names GSE24709, GSE61741, GSE31568, GSE56768 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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