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. 2018 Sep 6;10(9):2266-2283.
doi: 10.18632/aging.101541.

Comprehensive analysis of circRNA expression pattern and circRNA-miRNA-mRNA network in the pathogenesis of atherosclerosis in rabbits

Feng Zhang #  1 , Ruyou Zhang #  2 , Xiaoyu Zhang  3 , Yingnan Wu  1 , Xiaoying Li  1 , Shuang Zhang  1 , Wenying Hou  1 , Yu Ding  4 , Jiawei Tian  1 , Litao Sun  1 , Xianchao Kong  5
Affiliations

Comprehensive analysis of circRNA expression pattern and circRNA-miRNA-mRNA network in the pathogenesis of atherosclerosis in rabbits

Feng Zhang et al. Aging (Albany NY). .

Abstract

Atherosclerosis is a chronic and multifactorial inflammatory disease and is closely associated with cardiovascular and cerebrovascular diseases. circRNAs can act as competing endogenous RNAs to mRNAs and function in various diseases. However, there is little known about the function of circRNAs in atherosclerosis. In this study, three rabbits in the case group were fed a high-fat diet to induce atherosclerosis and another three rabbits were fed a normal diet. To explore the biological functions of circRNAs in atherosclerosis, we analyzed the circRNA, miRNA and mRNA expression profiles using RNA-seq. Many miRNAs, mRNAs and circRNAs were identified as significantly changed in atherosclerosis. We next predicted miRNA-target interactions with the miRanda tool and constructed a differentially expressed circRNA-miRNA-mRNA triple network. A gene ontology enrichment analysis showed that genes in the network were involved in cell adhesion, cell activation and the immune response. Furthermore, we generated a dysregulated circRNA-related ceRNAs network and found seven circRNAs (ocu-cirR-novel-18038, -18298, -15993, -17934, -17879, -18036 and -14389) were related to atherosclerosis. We found these circRNAs also functioned in cell adhesion, cell activation and the immune response. These results show that the crosstalk between circRNAs and their competing mRNAs might play crucial roles in the development of atherosclerosis.

Keywords: RNA-seq; atherosclerosis; ceRNA network; circular RNA; competing endogenous RNAs.

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Conflict of interest statement

CONFLICTS OF INTEREST: The authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
Two-dimensional ultrasound of right common carotid arteries at eighth week. (A-C) Two-dimensional ultrasound images show that the right common carotid arteries in the case group formed obvious atherosclerotic plaques indicated by the arrows. (D-F) Two-dimensional ultrasound images clearly show that the intimas of the right common carotid arteries in the control group remain smooth (white triangle).
Figure 2
Figure 2
Hematoxylin and eosin staining of right common carotid arteries. (A-C) Hematoxylin and eosin stained vessels reveal plaques of different severities in the carotid arteries of the case group, ×40 (arrows). (D-F) Hematoxylin and eosin stained vessels show that the carotid arteries in the control group without obvious abnormalities, ×40.
Figure 3
Figure 3
The circRNAs in rabbit carotid arteries. (A) Circos plot showing circRNAs on rabbit chromosome. The outmost layer of ring is chromosome map of the rabbit genome. The larger inner green ring represents all circRNAs detected by RNA-seq. The smaller inner ring indicates the differentially expressed circRNAs with fold change > 2 and p-Value < 0.05, the up and down regulation circRNAs have been marked in red and blue bars. (B) Among detected circRNAs, 4,879 common circRNAs and 1,442 specific circRNAs in AS group and 3,097 specific circRNAs in control group. (C) The TPM distributions of circRNAs.
Figure 4
Figure 4
Features of circRNAs. Distribution of the sequence length (A) and exon number (B) of circRNAs.
Figure 5
Figure 5
Heatmap showing expression profiles of different RNAs. (A-C) Hierarchical cluster analysis was used to assess the significantly different expressed mRNA, circRNA and miRNAs, respectively (FoldChange > 2 and PValue < 0.05). Red and green denoted high and low relative expression, respectively. Each RNA was represented by a single row of colored boxes and each sample was presently by a single column.
Figure 6
Figure 6
The view of DEcircRNA-DEmiRNA-DEmRNA triple network. The network includes 81 miRNAs, 115 circRNAs, 399 mRNAs and 3007 edges. The blue nodes represented mRNA, the red nodes represented miRNAs, and the orange nodes represented circRNAs.
Figure 7
Figure 7
Gene Ontology (GO) analysis of dysregulated mRNAs in the DEcircRNA-DEmiRNA-DEmRNA triple network. (A) Top 20 enrichment terms of biological processes. (B) The enrichment map of GO annotation. Node size represents the number of mRNAs in specific GO term. The edge thickness represents the number of mRNAs shared by two GO term linked by the edge.
Figure 8
Figure 8
The layout of dysregulated circRNA related ceRNA network (DCCN) and its structural characteristics. (A) The view of DCCN. The DCCN was comprised of 1452 edges between 365 mRNAs and 112 circRNAs. The blue nodes represented mRNA, the red nodes represented miRNAs, and the orange nodes represented circRNAs. (B) Degree distribution of DCCN. (C-D) Boxplot of degree and betweenness centrality of mRNAs and circRNAs.
Figure 9
Figure 9
The key module of DCCN. (A) The ceRNA module network of 7 circRNAs with largest degree, betweenness and closeness in DCCN. The blue nodes represented mRNA and the orange nodes represented circRNAs. (B) The gene ontology (GO) enrichment analysis of the module. The enriched GO terms ranked by gene count.
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