Dataset Information

Crosstalk between miRNAs and their regulated genes network in stroke.

ABSTRACT: In recent years, more and more studies focus on the roles of genes or miRNAs in stroke. However, the molecular mechanism connecting miRNAs and their targetgenes remains unclear. The aim of this study was to determine the differential regulation and correlations between miRNAs and their targetgenes in human stroke. Stroke-related miRNAs were obtained from the Human MicroRNA Disease Database (HMDD) and their targetgenes were generated from three independent sources. Kappa score was used to create the network and the functional modules. A total of 11 stroke-related miRNAs were identified from the HMDD and 441 overlapping targetgenes were extracted from the three databases. By network construction and GO analysis, 13 functional modules, 186 biological processes, and 21 pathways were found in the network, of which functional module 8 was the largest module, cellular-related process and phosphate-related process were the most important biological processes, and MAPK signaling pathway was the most significant pathway. In our study, all miRNAs regulate the stroke modular network by their targetgenes. After the validation of miRNAs, we found that miR-605 and miR-181d were highly expressed in the blood of stroke patients which never reported before may supply novel target for treatment.

SUBMITTER: Yuan Y

PROVIDER: S-EPMC4735861 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Crosstalk between miRNAs and their regulated genes network in stroke.

Yuan Ye Y Kang Ruixia R Yu YaNan Y Liu Jun J Zhang YingYing Y Shen ChunFeng C Wang Jie J Wu Ping P Shen ChunTi C Wang Zhong Z

Scientific reports 20160202

In recent years, more and more studies focus on the roles of genes or miRNAs in stroke. However, the molecular mechanism connecting miRNAs and their targetgenes remains unclear. The aim of this study was to determine the differential regulation and correlations between miRNAs and their targetgenes in human stroke. Stroke-related miRNAs were obtained from the Human MicroRNA Disease Database (HMDD) and their targetgenes were generated from three independent sources. Kappa score was used to create ...[more]

PMID: 26830013

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Project description:MicroRNAs (miRNAs/miRs) are small non‑coding RNAs (ncRNAs) that regulate gene expression. Emerging knowledge has suggested that miRNAs have a role in the pathogenesis of metabolic disorders, supporting the hypothesis that miRNAs may represent potential biomarkers or targets for this set of diseases. However, the current evidence is often controversial. Therefore, the aim of the present study was to determine the associations between miRNAs‑target genes, miRNA‑long ncRNAs (lncRNAs), and miRNAs‑small molecules in human metabolic diseases, including obesity, type 2 diabetes and non‑alcoholic fatty liver disease. The metabolic disease‑related miRNAs were obtained from the Human MicroRNA Disease Database (HMDD) and miR2Disease database. A search on the databases Matrix Decomposition and Heterogeneous Graph Inference (MDHGI) and DisGeNET were also performed. miRNAs target genes were obtained from three independent sources: Microcosm, TargetScan and miRTarBase. The interactions between miRNAs‑lncRNA and miRNA‑small molecules were performed using the miRNet web tool. The network analyses were performed using Cytoscape software. As a result, a total of 20 miRNAs were revealed to be associated with metabolic disorders in the present study. Notably, 6 miRNAs (miR‑17‑5p, miR‑29c‑3p, miR‑34a‑5p, miR‑103a‑3p, miR‑107 and miR‑132‑3p) were found in the four resources (HMDD, miR2Disease, MDHGI, and DisGeNET) used for these analyses, presenting a stronger association with the diseases. Furthermore, the target genes of these miRNAs participate in several pathways previously associated with metabolic diseases. In addition, interactions between miRNA‑lncRNA and miRNA‑small molecules were also found, suggesting that some molecules can modulate gene expression via such an indirect way. Thus, the results of this data mining and integration analysis provide further information on the possible molecular basis of the metabolic disease pathogenesis as well as provide a path to search for potential biomarkers and therapeutic targets concerning metabolic diseases.

Dataset Information

Crosstalk between miRNAs and their regulated genes network in stroke.

Publications

Crosstalk between miRNAs and their regulated genes network in stroke.

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