Identification of atrial fibrillation-related circular RNAs and constructing the integrative regulatory network of circular RNAs, microRNAs and mRNAs by bioinformatics analysis

Abstract

Atrial fibrillation (AF) is the most common cardiac arrhythmia with a high incidence of stroke. Many circular RNAs (circRNAs) have been demonstrated they are elated to various heart diseases and may play important roles in diagnostics or many pathophysiological processes. Nevertheless, there is Few studies on circRNAs functions in persistent AF. To identify AF-related circRNAs and construct the integrative regulatory network of circular RNAs, miRNAs, and mRNAs, we collected human right atrial appendage tissues from 5 patients suffering persistent AF (AF group) and 5 patients with normal sinus rhythm (NSR group) and characterized the global changes in circRNA expression with high-throughput sequencing technology. The differential expression of circRNAs and the interactions between circRNAs and microRNAs were analyzed. The microRNA expression file GSE68475 dataset was downloaded from the Gene Expression Omnibus (GEO) database to explore the differentially expressed microRNAs. The target genes of overlapped miRNAs were predicted by using DIANA-TarBase v8. We constructed the circRNA- miRNA-mRNA network using Cytoscape (version 3.4.0) and the network topology was analyzed by utilizing CentiScaPe app. Results showed that all of 600 differentially expressed circRNAs related to AF were screened, including 340 up-regulated and 260 down-regulated circRNAs. An integrative regulatory network was constructed, which included 30 circRNAs, 9 miRNAs and 130 target mRNAs of these miRNAs. It was concluded that that 30 circRNAs, including 8 upregulated circRNAs and 22 downregulated circRNAs, were predicted to highly possibly function as sponges of 9 miRNAs to regulate gene expression by using bioinformatics analysis. Moreover, the interactions of hsa-miR-339-5p with its related circRNAs and target mRNAs constructed the hub regulatory network in persistent AF by utilizing topology analysis. Our proposed regulatory network of circRNAs-miRNAs-mRNAs may provide new insight into the potential mechanism underlying persistent AF. Additionally, these important molecular may become novel biomarkers providing a new strategy in diagnosis and therapy of AF.