Bioinformatics-Based Identification of CircRNA-MicroRNA-mRNA Network for Calcific Aortic Valve Disease.

IF 1.4 4区生物学 Q4 GENETICS & HEREDITY

Genetics research Pub Date : 2023-01-01 DOI:10.1155/2023/8194338

Linghong Song, Yubing Wang, Yufei Feng, Hao Peng, Chengyan Wang, Juncang Duan, Kejian Liu, Xihua Shen, Wenyi Gu, Yan Qi, Shan Jin, Lijuan Pang

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引用次数: 0

Abstract

Background: Calcific aortic valve disease (CAVD) is the most common native valve disease. Valvular interstitial cell (VIC) osteogenic differentiation and valvular endothelial cell (VEC) dysfunction are key steps in CAVD progression. Circular RNA (circRNAs) is involved in regulating osteogenic differentiation with mesenchymal cells and is associated with multiple disease progression, but the function of circRNAs in CAVD remains unknown. Here, we aimed to investigate the effect and potential significance of circRNA-miRNA-mRNA networks in CAVD.

Methods: Two mRNA datasets, one miRNA dataset, and one circRNA dataset of CAVD downloaded from GEO were used to identify DE-circRNAs, DE-miRNAs, and DE-mRNAs. Based on the online website prediction function, the common mRNAs (FmRNAs) for constructing circRNA-miRNA-mRNA networks were identified. GO and KEGG enrichment analyses were performed on FmRNAs. In addition, hub genes were identified by PPI networks. Based on the expression of each data set, the circRNA-miRNA-hub gene network was constructed by Cytoscape (version 3.6.1).

Results: 32 DE-circRNAs, 206 DE-miRNAs, and 2170 DE-mRNAs were identified. Fifty-nine FmRNAs were obtained by intersection. The KEGG pathway analysis of FmRNAs was enriched in pathways in cancer, JAK-STAT signaling pathway, cell cycle, and MAPK signaling pathway. Meanwhile, transcription, nucleolus, and protein homodimerization activity were significantly enriched in GO analysis. Eight hub genes were identified based on the PPI network. Three possible regulatory networks in CAVD disease were obtained based on the biological functions of circRNAs including: hsa_circ_0026817-hsa-miR-211-5p-CACNA1C, hsa_circ_0007215-hsa-miR-1252-5p-MECP2, and hsa_circ_0007215-hsa-miR-1343-3p- RBL1.

Conclusion: The present bionformatics analysis suggests the functional effect for the circRNA-miRNA-mRNA network in CAVD pathogenesis and provides new targets for therapeutics.

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基于生物信息学的CircRNA-MicroRNA-mRNA网络在钙化主动脉瓣疾病中的鉴定

背景:主动脉瓣钙化病(CAVD)是最常见的先天性瓣膜疾病。瓣膜间质细胞(VIC)成骨分化和瓣膜内皮细胞(VEC)功能障碍是CAVD进展的关键步骤。环状RNA (circRNAs)参与调节间充质细胞的成骨分化，并与多种疾病进展相关，但环状RNA在CAVD中的功能尚不清楚。在这里，我们旨在研究circRNA-miRNA-mRNA网络在CAVD中的作用和潜在意义。方法:使用从GEO下载的两个mRNA数据集、一个miRNA数据集和一个CAVD circRNA数据集来鉴定de -circRNA、de -miRNA和de -mRNA。基于在线网站预测功能，确定了构建circRNA-miRNA-mRNA网络的常用mrna (fmrna)。对fmrna进行GO和KEGG富集分析。此外，还通过PPI网络鉴定了枢纽基因。根据各数据集的表达情况，利用Cytoscape软件(版本3.6.1)构建circRNA-miRNA-hub基因网络。结果:共鉴定出32个de - circrna、206个de - mirna和2170个de - mrna。交叉得到59个fmrna。fmrna的KEGG通路分析富集于肿瘤通路、JAK-STAT信号通路、细胞周期通路和MAPK信号通路。同时，在氧化石墨烯分析中，转录、核仁和蛋白同型二聚化活性显著增强。基于PPI网络鉴定出8个枢纽基因。基于circrna的生物学功能，我们获得了CAVD疾病中三个可能的调控网络，包括:hsa_circ_0026817-hsa-miR-211-5p-CACNA1C、hsa_circ_0007215-hsa-miR-1252-5p-MECP2和hsa_circ_0007215-hsa-miR-1343-3p- RBL1。结论:生物构象分析提示circRNA-miRNA-mRNA网络在CAVD发病机制中的功能作用，为治疗提供新的靶点。

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来源期刊

Genetics research 生物-遗传学

自引率

6.70%

发文量

审稿时长

>12 weeks

期刊介绍： Genetics Research is a key forum for original research on all aspects of human and animal genetics, reporting key findings on genomes, genes, mutations and molecular interactions, extending out to developmental, evolutionary, and population genetics as well as ethical, legal and social aspects. Our aim is to lead to a better understanding of genetic processes in health and disease. The journal focuses on the use of new technologies, such as next generation sequencing together with bioinformatics analysis, to produce increasingly detailed views of how genes function in tissues and how these genes perform, individually or collectively, in normal development and disease aetiology. The journal publishes original work, review articles, short papers, computational studies, and novel methods and techniques in research covering humans and well-established genetic organisms. Key subject areas include medical genetics, genomics, human evolutionary and population genetics, bioinformatics, genetics of complex traits, molecular and developmental genetics, Evo-Devo, quantitative and statistical genetics, behavioural genetics and environmental genetics. The breadth and quality of research make the journal an invaluable resource for medical geneticists, molecular biologists, bioinformaticians and researchers involved in genetic basis of diseases, evolutionary and developmental studies.