Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis

Purpose. The competing endogenous RNA (ceRNA) network regulatory has been investigated in the occurrence and development of many diseases. This research aimed at identifying the key RNAs of ceRNA network in pterygium and exploring the underlying molecular mechanism. Methods. Differentially expressed...

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Main Authors: Yuting Xu, Chen Qiao, Siying He, Chen Lu, Shiqi Dong, Xiying Wu, Ming Yan, Fang Zheng
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:BioMed Research International
Online Access:http://dx.doi.org/10.1155/2020/2383516
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spelling doaj-6973af01cc904ca5a874604fde7fef502020-12-07T09:08:22ZengHindawi LimitedBioMed Research International2314-61332314-61412020-01-01202010.1155/2020/23835162383516Identification of Functional Genes in Pterygium Based on Bioinformatics AnalysisYuting Xu0Chen Qiao1Siying He2Chen Lu3Shiqi Dong4Xiying Wu5Ming Yan6Fang Zheng7Department of Ophthamology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, ChinaDepartment of Corneal, Hankou Aier Eye Hospital, Wuhan, Hubei 430024, ChinaCenter for Gene Diagnosis & Core Lab, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, ChinaDepartment of General Surgery, Second Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu 210000, ChinaDepartment of Ophthamology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, ChinaDepartment of Ophthamology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, ChinaDepartment of Ophthamology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, ChinaDepartment of Corneal, Hankou Aier Eye Hospital, Wuhan, Hubei 430024, ChinaPurpose. The competing endogenous RNA (ceRNA) network regulatory has been investigated in the occurrence and development of many diseases. This research aimed at identifying the key RNAs of ceRNA network in pterygium and exploring the underlying molecular mechanism. Methods. Differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs were obtained from the Gene Expression Omnibus (GEO) database and analyzed with the R programming language. LncRNA and miRNA expressions were extracted and pooled by the GEO database and compared with those in published literature. The lncRNA-miRNA-mRNA network was constructed of selected lncRNAs, miRNAs, and mRNAs. Metascape was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on mRNAs of the ceRNA network and to perform Protein-Protein Interaction (PPI) Network analysis on the String website to find candidate hub genes. The Comparative Toxicogenomic Database (CTD) was used to find hub genes closely related to pterygium. The differential expressions of hub genes were verified using the reverse transcription-real-time fluorescent quantitative PCR (RT-qPCR). Result. There were 8 lncRNAs, 12 miRNAs, and 94 mRNAs filtered to construct the primary ceRNA network. A key lncRNA LIN00472 ranking the top 1 node degree was selected to reconstruct the LIN00472 network. The GO and KEGG pathway enrichment showed the mRNAs in ceRNA networks mainly involved in homophilic cell adhesion via plasma membrane adhesion molecules, developmental growth, regulation of neuron projection development, cell maturation, synapse assembly, central nervous system neuron differentiation, and PID FOXM1 PATHWAY. According to the Protein-Protein Interaction Network (PPI) analysis on mRNAs in LINC00472 network, 10 candidate hub genes were identified according to node degree ranking. Using the CTD database, we identified 8 hub genes closely related to pterygium; RT-qPCR verified 6 of them were highly expressed in pterygium. Conclusion. Our research found LINC00472 might regulate 8 hub miRNAs (miR-29b-3p, miR-183-5p, miR-138-5p, miR-211-5p, miR-221-3p, miR-218-5p, miR-642a-5p, miR-5000-3p) and 6 hub genes (CDH2, MYC, CCNB1, RELN, ERBB4, RB1) in the ceRNA network through mainly PID FOXM1 PATHWAY and play an important role in the development of pterygium.http://dx.doi.org/10.1155/2020/2383516
collection DOAJ
language English
format Article
sources DOAJ
author Yuting Xu
Chen Qiao
Siying He
Chen Lu
Shiqi Dong
Xiying Wu
Ming Yan
Fang Zheng
spellingShingle Yuting Xu
Chen Qiao
Siying He
Chen Lu
Shiqi Dong
Xiying Wu
Ming Yan
Fang Zheng
Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis
BioMed Research International
author_facet Yuting Xu
Chen Qiao
Siying He
Chen Lu
Shiqi Dong
Xiying Wu
Ming Yan
Fang Zheng
author_sort Yuting Xu
title Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis
title_short Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis
title_full Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis
title_fullStr Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis
title_full_unstemmed Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis
title_sort identification of functional genes in pterygium based on bioinformatics analysis
publisher Hindawi Limited
series BioMed Research International
issn 2314-6133
2314-6141
publishDate 2020-01-01
description Purpose. The competing endogenous RNA (ceRNA) network regulatory has been investigated in the occurrence and development of many diseases. This research aimed at identifying the key RNAs of ceRNA network in pterygium and exploring the underlying molecular mechanism. Methods. Differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs were obtained from the Gene Expression Omnibus (GEO) database and analyzed with the R programming language. LncRNA and miRNA expressions were extracted and pooled by the GEO database and compared with those in published literature. The lncRNA-miRNA-mRNA network was constructed of selected lncRNAs, miRNAs, and mRNAs. Metascape was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on mRNAs of the ceRNA network and to perform Protein-Protein Interaction (PPI) Network analysis on the String website to find candidate hub genes. The Comparative Toxicogenomic Database (CTD) was used to find hub genes closely related to pterygium. The differential expressions of hub genes were verified using the reverse transcription-real-time fluorescent quantitative PCR (RT-qPCR). Result. There were 8 lncRNAs, 12 miRNAs, and 94 mRNAs filtered to construct the primary ceRNA network. A key lncRNA LIN00472 ranking the top 1 node degree was selected to reconstruct the LIN00472 network. The GO and KEGG pathway enrichment showed the mRNAs in ceRNA networks mainly involved in homophilic cell adhesion via plasma membrane adhesion molecules, developmental growth, regulation of neuron projection development, cell maturation, synapse assembly, central nervous system neuron differentiation, and PID FOXM1 PATHWAY. According to the Protein-Protein Interaction Network (PPI) analysis on mRNAs in LINC00472 network, 10 candidate hub genes were identified according to node degree ranking. Using the CTD database, we identified 8 hub genes closely related to pterygium; RT-qPCR verified 6 of them were highly expressed in pterygium. Conclusion. Our research found LINC00472 might regulate 8 hub miRNAs (miR-29b-3p, miR-183-5p, miR-138-5p, miR-211-5p, miR-221-3p, miR-218-5p, miR-642a-5p, miR-5000-3p) and 6 hub genes (CDH2, MYC, CCNB1, RELN, ERBB4, RB1) in the ceRNA network through mainly PID FOXM1 PATHWAY and play an important role in the development of pterygium.
url http://dx.doi.org/10.1155/2020/2383516
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