lncrna相关的内源性竞争RNA (ceRNA)网络在肌腱病变中的作用分析

IF 1.4 4区 生物学 Q4 GENETICS & HEREDITY Genetics research Pub Date : 2022-05-12 DOI:10.1155/2022/9792913
Bing-Zhe Huang, Yang Jing-Jing, Xiao-Ming Dong, Zhuan Zhong, Xiao-Ning Liu
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The downregulated DEmRNAs were particularly associated with muscle contraction and muscle filament, while the upregulated ones were linked to extracellular matrix organization and cell adhesion. From the PPI network, 11 modules were extracted. Genes in MCODE 2 (such as TPM4) were significantly involved in cardiomyopathy, and genes in MCODE 4 (such as COL4A3 and COL4A4) were involved in focal adhesion, ECM-receptor interaction, and PI3K-Akt signaling pathway. The ceRNA network contained 7 lncRNAs (MIR133A1HG, LINC01405, PRKCQ-AS1, C10orf71-AS1, MBNL1-AS1, HOTAIRM1, and DNM3OS), 63 mRNAs, and 41 miRNAs. Downregulated lncRNA MIR133A1HG could competitively bind with hsa-miR-659-3p and hsa-miR-218-1-3p to regulate the TPM3. Meanwhile, MIR133A1HG could competitively bind with hsa-miR-1179 to regulate the COL4A3. Downregulated C10orf71-AS1 could competitively bind with hsa-miR-130a-5p to regulate the COL4A4. 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引用次数: 0

摘要

背景我们旨在构建lncRNA相关竞争内源性RNA(ceRNA)网络,并区分与腱病相关的特征lncRNA。方法从基因表达综合库(GEO)下载GSE26051基因图谱,包括23个正常肌腱和23个病变肌腱。鉴定了差异表达的mRNA(DEmRNA)和差异表达的lncRNA(DElncRNA),并进行了功能和途径富集分析。构建了蛋白质-蛋白质相互作用(PPI)网络,并通过模块挖掘进行了进一步分析。此外,基于已鉴定的lncRNA-mRNA共表达关系对和miRNA-mRNA调控对构建了ceRNA调控网络。结果我们从GEO数据中鉴定出1117个DEmRNA和57个DElncRNA。下调的DEmRNA与肌肉收缩和肌丝特别相关,而上调的DEmRNAs与细胞外基质组织和细胞粘附有关。从PPI网络中提取了11个模块。MCODE 2中的基因(如TPM4)显著参与心肌病,MCODE 4中的基因(例如COL4A3和COL4A4)参与局灶粘附、ECM受体相互作用和PI3K-Akt信号通路。ceRNA网络包含7个lncRNA(MIR133A1HG、LINC01405、PRKCQ-AS1、C10orf71-AS1、MBNL1-AS1、HOTAIRM1和DNM3OS)、63个mRNA和41个miRNA。下调的lncRNA MIR133A1HG可以与hsa-miR-659-3p和hsa-miR-218-1-3p竞争性结合以调节TPM3。同时,MIR133A1HG可以与hsa-miR-1179竞争性结合以调节COL4A3。下调的C10orf71-AS1可以与hsa-miR-130a-5p竞争性结合以调节COL4A4。结论根据lncRNA相关的ceRNA网络,发现7种重要的lncRNA,特别是MIR133A1HG和C10orf71-AS1与腱病相关。
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Analysis of the lncRNA-Associated Competing Endogenous RNA (ceRNA) Network for Tendinopathy
Background We aimed to construct the lncRNA-associated competing endogenous RNA (ceRNA) network and distinguish feature lncRNAs associated with tendinopathy. Methods We downloaded the gene profile of GSE26051 from the Gene Expression Omnibus (GEO), including 23 normal samples and 23 diseased tendons. Differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) were identified, and functional and pathway enrichment analyses were performed. Protein-protein interaction (PPI) network was constructed and further analyzed by module mining. Moreover, a ceRNA regulatory network was constructed based on the identified lncRNA–mRNA coexpression relationship pairs and miRNA–mRNA regulation pairs. Results We identified 1117 DEmRNAs and 57 DElncRNAs from the GEO data. The downregulated DEmRNAs were particularly associated with muscle contraction and muscle filament, while the upregulated ones were linked to extracellular matrix organization and cell adhesion. From the PPI network, 11 modules were extracted. Genes in MCODE 2 (such as TPM4) were significantly involved in cardiomyopathy, and genes in MCODE 4 (such as COL4A3 and COL4A4) were involved in focal adhesion, ECM-receptor interaction, and PI3K-Akt signaling pathway. The ceRNA network contained 7 lncRNAs (MIR133A1HG, LINC01405, PRKCQ-AS1, C10orf71-AS1, MBNL1-AS1, HOTAIRM1, and DNM3OS), 63 mRNAs, and 41 miRNAs. Downregulated lncRNA MIR133A1HG could competitively bind with hsa-miR-659-3p and hsa-miR-218-1-3p to regulate the TPM3. Meanwhile, MIR133A1HG could competitively bind with hsa-miR-1179 to regulate the COL4A3. Downregulated C10orf71-AS1 could competitively bind with hsa-miR-130a-5p to regulate the COL4A4. Conclusions Seven important lncRNAs, particularly MIR133A1HG and C10orf71-AS1, were found associated with tendinopathy according to the lncRNA-associated ceRNA network.
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来源期刊
Genetics research
Genetics research 生物-遗传学
自引率
6.70%
发文量
74
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.
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