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Construction of competitive endogenous RNA network reveals regulatory role of long non-coding RNAs in type 2 diabetes mellitus.

ABSTRACT: Increasing epidemic of type 2 diabetes mellitus (T2DM) and its comorbidities makes it urgent to understand the pathogenesis and regulatory mechanism. However, little is known about the regulatory role of lncRNAs in diabetes. Here, we constructed a T2DM-related competitive endogenous RNA (ceRNA) network (DMCN) to explore biological function of lncRNAs during the development of diabetes mellitus. This network contained 351 nodes including 98 mRNAs, 86 microRNAs and 167 lncRNAs. Functional analysis showed that the mRNAs in DMCN were annotated into some diabetes-related pathways. Furthermore, mTOR-centred subnetwork was extracted and ncRNA-involved mTOR pathway was established. Finally, we validated that NEAT1 was potentially communicated with mTOR signalling target protein mLST8 via the association with miR-181b. These findings provide significant insight into lncRNA regulatory network in T2DM.

SUBMITTER: Lin Z

PROVIDER: S-EPMC5706502 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Construction of competitive endogenous RNA network reveals regulatory role of long non-coding RNAs in type 2 diabetes mellitus.

Lin Zijing Z Li Xinyu X Zhan Xiaorong X Sun Lijie L Gao Jie J Cao Yan Y Qiu Hui H

Journal of cellular and molecular medicine 20170623 12

Increasing epidemic of type 2 diabetes mellitus (T2DM) and its comorbidities makes it urgent to understand the pathogenesis and regulatory mechanism. However, little is known about the regulatory role of lncRNAs in diabetes. Here, we constructed a T2DM-related competitive endogenous RNA (ceRNA) network (DMCN) to explore biological function of lncRNAs during the development of diabetes mellitus. This network contained 351 nodes including 98 mRNAs, 86 microRNAs and 167 lncRNAs. Functional analysis ...[more]

PMID: 28643459

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Project description:BACKGROUND:Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. METHODS:Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. RESULTS:This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). CONCLUSIONS:The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma.

Project description:BackgroundIncreasing evidence has suggested that non-coding RNAs (ncRNAs) play critical roles in the pathogenesis of diabetic retinopathy (DR), but their underlying mechanisms remain unclear. The purpose of this study was to determine latent key genes and to structure a competing endogenous RNA (ceRNA) regulatory network to discover the potential molecular mechanisms governing the effects of high glucose on human retinal endothelial cells (HRECs).MethodsWe obtained microarray data for long non-coding RNA (lncRNA) and mRNA of high-glucose-induced HREC samples from NCBI GEO datasets. The ceRNA network was screened using intersecting prediction results from miRcode, TargetScan, miRTarBase and miRDB. The protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes and hub genes were obtained using the cytoHubba app. The ClusterProfiler package was applied for performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The expression of key RNAs was verified using the qRT-PCR method. A key ceRNA subnetwork was constructed based on the criticality of the genes and its binding sites were verified by luciferase reporter assay. The viability and apoptosis of HRECs were tested using the transfection of the miR-449c inhibitor.ResultsA total of 3,328 lncRNAs and 2,017 mRNAs were screened for differentially expressed (DE) profiles. The newly constructed ceRNA network was composed of 410 lncRNAs, 35 miRNAs and 122 mRNAs. The 10 hub genes were identified through the PPI network. GO and KEGG analysis revealed that DE mRNAs were mainly related to the positive regulation of the mRNA catabolic process, cell polarity, and the G1/S transition of mitotic and cell cycle signaling pathways. QRT-PCR was used to verify RNAs and the most important genes were screened out. A key ceRNA subnetwork OIP5-AS1/miR-449c/MYC was established. The binding site was verified by luciferase reporter assay. The expression levels of OIP5-AS1 and MYC increased after miR-449c inhibitor transfection, miR-449c decreased, HRECs activity increased, and apoptosis decreased, compared with the control group.ConclusionWe successfully built the key ceRNA subnetwork, OIP5-AS1/miR-449c/MYC, by applying the GEO database for data analysis and mining. The results from the ceRNA network allow us to better understand the effect of ncRNAs on HRECs under hyperglycemic conditions and the pathogenesis of DR.

Dataset Information

Construction of competitive endogenous RNA network reveals regulatory role of long non-coding RNAs in type 2 diabetes mellitus.

Publications

Construction of competitive endogenous RNA network reveals regulatory role of long non-coding RNAs in type 2 diabetes mellitus.

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