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Article Open Access

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

  • Authors:
    • Tao Wang
    • Bin Wang
  • View Affiliations / Copyright

    Affiliations: Department of Cardiology, Shandong Jiaotong Hospital, Jinan, Shandong 250031, P.R. China, Department of Otorhinolaryngology, Hangzhou First People's Hospital, Hangzhou, Zhejiang 310006, P.R. China
    Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 4535-4540
    |
    Published online on: April 12, 2016
       https://doi.org/10.3892/mmr.2016.5106
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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.
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Copy and paste a formatted citation
Spandidos Publications style
Wang T and Wang B: Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis. Mol Med Rep 13: 4535-4540, 2016.
APA
Wang, T., & Wang, B. (2016). Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis. Molecular Medicine Reports, 13, 4535-4540. https://doi.org/10.3892/mmr.2016.5106
MLA
Wang, T., Wang, B."Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis". Molecular Medicine Reports 13.6 (2016): 4535-4540.
Chicago
Wang, T., Wang, B."Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis". Molecular Medicine Reports 13, no. 6 (2016): 4535-4540. https://doi.org/10.3892/mmr.2016.5106
Copy and paste a formatted citation
x
Spandidos Publications style
Wang T and Wang B: Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis. Mol Med Rep 13: 4535-4540, 2016.
APA
Wang, T., & Wang, B. (2016). Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis. Molecular Medicine Reports, 13, 4535-4540. https://doi.org/10.3892/mmr.2016.5106
MLA
Wang, T., Wang, B."Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis". Molecular Medicine Reports 13.6 (2016): 4535-4540.
Chicago
Wang, T., Wang, B."Identification of microRNA-mRNA interactions in atrial fibrillation using microarray expression profiles and bioinformatics analysis". Molecular Medicine Reports 13, no. 6 (2016): 4535-4540. https://doi.org/10.3892/mmr.2016.5106
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