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| 成骨不全环状RNA生物信息学分析 |
| Bioinformatics analysis of osteogenesis imperfecta related cyclic RNAs |
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| DOI：10.3969/j.issn.1006.7108.2017.04.003 |
| 中文关键词: 成骨不全 miRNA circRNA：靶基因 信号通路 生物信息学预测 |
| 英文关键词:Osteogenesis imperfecta MicroRNAs CircRNAs Target genes Signaling pathway Bioinformatics prediction |
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| 中文摘要: |
| 目的 对成骨不全血清中差异表达的 miR-21、miR-26a、miR-29a、miR-29b、miR-30e、miR-34c、miR-133a、miR-145、miR- 210、miR489与miR-1297等共11种miRNAs进行circRNAs及其靶基因的预测，同时分析其与circRNAs及靶基因间的相互作用。方法 采用starbase软件对11种差异性表达miRNAs相关circRNAs进行预测，将得到的miRNA-circRNA进行频数分布分析并通过cytoscape软件进行网络分析寻找核心分子。采用miRWALK软件对11种差异性表达miRNAs相关靶基因进行预测，将得到的miRWALK-靶基因进行频数分布分析并通过cytoscape,DAVID软件进行网络分析寻找核心分子。结果 Starbase软件对11种不同miRNAS所预测的靶circRNAs的总数量为222个，非重叠circRNAs为141个。其中MIBl_hsa_circ_000886, MIBl_hsa_circ_002013 ,CPNEl_hsa_circ_000657 ,CYP4F3_hsa_circ_001395 ,KIAA1586_hsa_circ_001439 与其中 4 种 miRNA 相互作用。另有14个circRNAs与3种miRNA相互作用。miRWALK软件对11种不同miRNAs所预测的靶基因中CNOT6、ELF2、NAV3等基因在不同数量级数据库中与相应不同种miRNAs作用密切。通过对11种miRNA相应circRNA以及靶基因生物学预测分析得到 YES1 基因与 miR-133a、miR-l45 以及 FATl_hsa_circ_000713 与 LMNB2_has_circ_001499 之间存在相互作用。PPP2CA 与 miR-29a、miR-29b、miR-133a 以及 KIAAl586_hsa_circ_001439 之间存在相互作用。NTN4 和 SRGAP1 与 miR-26a、miR-145以及RFCl_hsa_circ_001649之间存在相互作用。结论 本研究对成骨不全血清中差异表达的11种miRNAs及其相互作用的circRNAs、靶基因与相关信号通路进行了网络分析与预测，为进一步分析之间相互作用奠定了基础。 |
| 英文摘要: |
| Objective To predict circRNAs and target genes for 11 differentially expressed miRNAs including miR-21，miR-26a, miR-29a, miR-29b, miR-30e, miR-34c, miR-133a, miR-145, miR-210, miR489 and miR-1297 in the serum specimens of osteogenesis imperfecta (OI) patients. Methods The Starbase software was used to predict the related circRNAs of the eleven differentially expressed miRNAs, and the frequency distribution of miRNA-circRNA was analyzed and the network analysis was conducted by Cytoscape software to find the core elements. Using the miRWALK software, the target genes of the eleven differentially expressed miRNAs were predicted, the target genes of miRWALK were obtained by frequency distribution analysis and Cytoscape DAVID software to find the core molecule using network analysis. Results A total of 222 circRNAs were predicted by the Starbase software for these 11 miRNAs and 141 of them belonged to non-overlapping circRNAs. Among them, MIB1_has_circ_000886, MIBl_hsa_circ_002013,CPNE1_hsa_circ_000657 CYP4F3_hsa_circ_001395 and KIAA1586_hsa_circ_001439 were found to interact with four kinds of miRNAs. Another 14 circRNAs were found to interact with three kinds of miRNAs. MiRWALK software predicted that the target genes of CNOT6, ELF2 and NAV3 were closely interacted with corresponding differentially expressed miRNAs of OI. MiR-133a\ miR-145 was identified to interact with YES1 gene and circRNA FAT1 _hsa_circ_000713 and LMNB2_hsa_circ_001499.MiR-29a\miR-29b\miR-133a interacted with PPP2CA gene and KIAA1586_hsa_circ_001439 circRNA. MiR- 145\miR-26a interacted with NTN4 and SRGAPi genes and RFC1_hsa_circ_001649 circRNA. Conclusion In this study, we analyzed differentially expressed miRNAs of OI and their corresponding circRNAs and target genes. Meanwhile, the network interaction among miRNAs, circRNAs and target genes as well as signaling pathways were also analyzed. The study laid the foundation for the further interaction analysis of miRNAs, circRNAs and target genes. |
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