Dataset Information

Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis.

ABSTRACT: The present study integrated microRNA (miRNA) and mRNA expression data obtained from atrial fibrillation (AF) tissues and healthy tissues, in order to identify miRNAs and target genes that may be important in the development of AF. The GSE28954 miRNA expression profile and GSE2240 mRNA gene expression profile were downloaded from the Gene Expression Omnibus. Differentially expressed miRNAs and genes (DEGs) in AF tissues, compared with in control samples, were identified and hierarchically clustered. Subsequently, differentially expressed miRNAs and DEGs were searched for in the miRecords database and TarBase, and were used to construct a regulatory network using Cytoscape. Finally, functional analysis of the miRNA?targeted genes was conducted. After data processing, 71 differentially expressed miRNAs and 390 DEGs were identified between AF and normal tissues. A total of 3,506 miRNA?mRNA pairs were selected, of which 372 were simultaneously predicted by both miRecords and TarBase, and were therefore used to construct the miRNA?mRNA regulatory network. Furthermore, 10 miRNAs and 12 targeted mRNAs were detected, which formed 14 interactive pairs. The miRNA?targeted genes were significantly enriched into 14 Gene Ontology (GO) categories, of which the most significant was gene expression regulation (GO 10468), which was associated with 7 miRNAs and 8 target genes. These results suggest that the screened miRNAs and target genes may be target molecules in AF development, and may be beneficial for the early diagnosis and future treatment of AF.

SUBMITTER: Wang T

PROVIDER: S-EPMC4878535 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis.

Wang Tao T Wang Bin B

Molecular medicine reports 20160412 6

The present study integrated microRNA (miRNA) and mRNA expression data obtained from atrial fibrillation (AF) tissues and healthy tissues, in order to identify miRNAs and target genes that may be important in the development of AF. The GSE28954 miRNA expression profile and GSE2240 mRNA gene expression profile were downloaded from the Gene Expression Omnibus. Differentially expressed miRNAs and genes (DEGs) in AF tissues, compared with in control samples, were identified and hierarchically cluste ...[more]

PMID: 27082053

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Project description:PurposeTo investigate the expression profiles of long noncoding RNAs (lncRNAs) in patients with atrial fibrillation (AF).MethodsThe peripheral blood monocytes of a total of 20 patients with AF and 20 healthy subjects were collected for gene chip technology to detect differentially expressed lncRNAs from 2017.01 to 2017.08. Reverse transcription polymerase chain reaction (RT-PCR) was applied for further verification. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify the functions of differentially expressed genes and related pathways.ResultsThere were 19 lncRNAs differentially expressed (FC ≥ 2, P < 0.05), of which 6 were upregulated and 13 were downregulated. Two of three upregulated lncRNAs (P = 0.014 and 0.006 for HNRNPU-AS1 and LINC00861, respectively) and two of three downregulated lncRNAs (P = 0.028 and 0.032 for RP11-443B7.3 and CTD-2616J11.14, respectively) were randomly confirmed by RT-PCR and showed a significantly different expression with the RNA-seq results. GO analysis showed that differentially expressed genes enriched in differentially expressed transcripts in biological process were mainly involved in metabolic process, catabolic process, and biosynthetic process. Differentially expressed transcripts in cellular component were mainly involved in nuclear lumen, organelle lumen, and cytoplasm. Differentially expressed transcripts in molecular function were mainly involved in protein binding, RNA binding, and molecular function. KEGG enrichment pathway analysis showed that some of the enrichment pathways associated with differentially expressed lncRNAs include calcium signaling pathway, NF-kappa B signaling pathway, cytokine-cytokine receptor interaction, and Toll-like receptor signaling pathway. HNRNPU-AS1 was the highest positive correlated lncRNA in the networks.ConclusionsThe expression of lncRNA in peripheral blood of AF patients is different from that of normal people. The physiological functions of these differentially expressed lncRNAs may be related to the pathogenesis of AF, which provide experimental basis and new therapeutic target for prognosis and treatment of patients with AF. HNRNPU-AS1 may play an important role in the pathophysiology and mechanisms of AF.

Project description:Atrial fibrillation (AF) is a chronic and progressive disease, with advancing age, the morbidity of which will increase exponentially. Circular ribonucleic acids (RNAs; circRNAs) have gained a growing attention in the development of AF in recent years. The purpose of this study is to explore the mechanism of circRNA regulation in AF, in particular, the intricate interactions among circRNA, microRNA (miRNA), and messenger RNA (mRNA). Three datasets (GSE129409, GSE68475, and GSE79768) were obtained from the Gene Expression Omnibus database to screen differentially expressed (DE) circRNAs, DE miRNAs, and DE mRNAs in AF, respectively. Based on circRNA-miRNA pairs and miRNA-mRNA pairs, a competing endogenous RNAs (ceRNAs) network was built. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis of DE mRNAs in the network were performed and protein-protein interaction (PPI) networks were established to identify hub genes. Finally, a circRNA-miRNA-hub gene subnetwork was constructed. A total of 103 DE circRNAs, 16 DE miRNAs, and 110 DE mRNAs were screened in AF. Next, ceRNAs network in AF was constructed with 3 upregulated circRNAs, 2 downregulated circRNAs, 2 upregulated miRNAs, 2 downregulated miRNAs, 17 upregulated mRNAs, and 24 downregulated mRNAs. Thirty GO terms and 6 KEGG pathways were obtained. Besides, 6 hub genes (C-X-C chemokine receptor type 4 [CXCR4], C-X-C chemokine receptor type 2 [CXCR2], C-X-C motif chemokine 11 [CXCL11], neuromedin-U, B1 bradykinin receptor, and complement C3) were screened from constructing a PPI network. Finally, a circRNA-miRNA-hub gene subnetwork with 10 regulatory axes was constructed to describe the interactions among the differential circRNAs, miRNA, and hub genes. We speculated that hsa_circRNA_0056281/hsa_circRNA_0006665 -hsa-miR-613-CXCR4/CXCR2/CXCL11 regulatory axes and hsa_circRNA_0003638-hsa-miR-1207-3p-CXCR4 regulatory axis may be associated with the pathogenesis of AF.

Dataset Information

Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis.

Publications

Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis.

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