Integrated analysis of long noncoding RNA‐associated competing endogenous RNA network in periodontitis
Background and Objectives Long noncoding RNAs (lncRNAs) play critical and complex roles in regulating various biological processes of periodontitis. This bioinformatic study aims to construct a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression, based...
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| Veröffentlicht in: | Journal of periodontal research 2018-08, Vol.53 (4), p.495-505 |
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| creator | Li, S. Liu, X. Li, H. Pan, H. Acharya, A. Deng, Y. Yu, Y. Haak, R. Schmidt, J. Schmalz, G. Ziebolz, D. |
| description | Background and Objectives
Long noncoding RNAs (lncRNAs) play critical and complex roles in regulating various biological processes of periodontitis. This bioinformatic study aims to construct a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression, based on high‐throughput RNA sequencing and microarray data about periodontitis.
Material and Methods
Data from 1 miRNA and 3 mRNA expression profiles were obtained to construct the lncRNA‐associated ceRNA network. Gene Ontology enrichment analysis and pathway analysis were performed using the Gene Ontology website and Kyoto Encyclopedia of Genes and Genomes. A protein‐protein interaction network was constructed based on the Search Tool for the retrieval of Interacting Genes/Proteins. Transcription factors (TFs) of differentially expressed genes were identified based on TRANSFAC database and then a regulatory network was constructed.
Results
Through constructing the dysregulated ceRNA network, 6 genes (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL) and 3 miRNAs (miR‐125a‐3p, miR‐200a, miR‐142‐3p) were detected. Three lncRNAs (MALAT1, TUG1, FGD5‐AS1) were found to target both miR‐125a‐3p and miR‐142‐3p in this ceRNA network. Protein‐protein interaction network analysis identified several hub genes, including VCAM1, ITGA4, UBC, LYN and SSX2IP. Three pathways (cytokine‐cytokine receptor, cell adhesion molecules, chemokine signaling pathway) were identified to be overlapping results with the previous bioinformatics studies in periodontitis. Moreover, 2 TFs including FOS and EGR were identified to be involved in the regulatory network of the differentially expressed genes‐TFs in periodontitis.
Conclusion
These findings suggest that 6 mRNAs (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL), 3 miRNAs (hsa‐miR‐125a‐3p, hsa‐miR‐200a, hsa‐miR‐142‐3p) and 3 lncRNAs (MALAT1, TUG1, FGD5‐AS1) might be involved in the lncRNA‐associated ceRNA network of periodontitis. This study sought to illuminate further the genetic and epigenetic mechanisms of periodontitis through constructing an lncRNA‐associated ceRNA network. |
| doi_str_mv | 10.1111/jre.12539 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2012115871</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2012115871</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4199-e4e38b813315e50895ecd305f17c0be4302c7c66340a625f4b56e5a6ca5f71443</originalsourceid><addsrcrecordid>eNp10M9OGzEQBnALFTUBeuAF0Epc4LAws_6zu0eEUpoKUQmV88rxzganGzu1N0K59RF4xj5JHZL2gFRfxpZ_-jT6GDtFuMJ0rheBrrCQvD5gY1QAOZRKfmBjgKLIuajEiB3FuID0VmX9kY2KWqKSCGP2PHUDzYMeqM200_0m2pj5Luu9m2fOO-Nbm26PDze_f73qGL2xb9b45YqG7Re51s_J-XXcqszR8OLDj8y6bEXB-ta7wQ42nrDDTveRPu3nMXv6PPl--yW__3Y3vb25z43Aus5JEK9mFXKOkiRUtSTTcpAdlgZmJDgUpjRKcQFaFbITM6lIamW07EoUgh-zi13uKvifa4pDs7TRUN9rR2nHpgAsEGVVYqLn7-jCr0MqYatUKTkClEld7pQJPsZAXbMKdqnDpkFotvU3qf7mrf5kz_aJ69mS2n_yb98JXO_Ai-1p8_-k5uvjZBf5BziKj0Y</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2067531007</pqid></control><display><type>article</type><title>Integrated analysis of long noncoding RNA‐associated competing endogenous RNA network in periodontitis</title><source>Wiley Online Library - AutoHoldings Journals</source><source>MEDLINE</source><creator>Li, S. ; Liu, X. ; Li, H. ; Pan, H. ; Acharya, A. ; Deng, Y. ; Yu, Y. ; Haak, R. ; Schmidt, J. ; Schmalz, G. ; Ziebolz, D.</creator><creatorcontrib>Li, S. ; Liu, X. ; Li, H. ; Pan, H. ; Acharya, A. ; Deng, Y. ; Yu, Y. ; Haak, R. ; Schmidt, J. ; Schmalz, G. ; Ziebolz, D.</creatorcontrib><description>Background and Objectives
Long noncoding RNAs (lncRNAs) play critical and complex roles in regulating various biological processes of periodontitis. This bioinformatic study aims to construct a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression, based on high‐throughput RNA sequencing and microarray data about periodontitis.
Material and Methods
Data from 1 miRNA and 3 mRNA expression profiles were obtained to construct the lncRNA‐associated ceRNA network. Gene Ontology enrichment analysis and pathway analysis were performed using the Gene Ontology website and Kyoto Encyclopedia of Genes and Genomes. A protein‐protein interaction network was constructed based on the Search Tool for the retrieval of Interacting Genes/Proteins. Transcription factors (TFs) of differentially expressed genes were identified based on TRANSFAC database and then a regulatory network was constructed.
Results
Through constructing the dysregulated ceRNA network, 6 genes (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL) and 3 miRNAs (miR‐125a‐3p, miR‐200a, miR‐142‐3p) were detected. Three lncRNAs (MALAT1, TUG1, FGD5‐AS1) were found to target both miR‐125a‐3p and miR‐142‐3p in this ceRNA network. Protein‐protein interaction network analysis identified several hub genes, including VCAM1, ITGA4, UBC, LYN and SSX2IP. Three pathways (cytokine‐cytokine receptor, cell adhesion molecules, chemokine signaling pathway) were identified to be overlapping results with the previous bioinformatics studies in periodontitis. Moreover, 2 TFs including FOS and EGR were identified to be involved in the regulatory network of the differentially expressed genes‐TFs in periodontitis.
Conclusion
These findings suggest that 6 mRNAs (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL), 3 miRNAs (hsa‐miR‐125a‐3p, hsa‐miR‐200a, hsa‐miR‐142‐3p) and 3 lncRNAs (MALAT1, TUG1, FGD5‐AS1) might be involved in the lncRNA‐associated ceRNA network of periodontitis. This study sought to illuminate further the genetic and epigenetic mechanisms of periodontitis through constructing an lncRNA‐associated ceRNA network.</description><identifier>ISSN: 0022-3484</identifier><identifier>EISSN: 1600-0765</identifier><identifier>DOI: 10.1111/jre.12539</identifier><identifier>PMID: 29516510</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Bioinformatics ; Cell adhesion & migration ; Cell adhesion molecules ; ceRNA ; Computational Biology ; Cytokines ; Dentistry ; DNA microarrays ; Gene expression ; gene expression data ; Gene Expression Profiling ; Gene Ontology ; Gene Regulatory Networks - genetics ; Genes ; Genomes ; Gum disease ; Humans ; Intracellular Signaling Peptides and Proteins - genetics ; lncRNA ; Microarray Analysis ; MicroRNAs - genetics ; miRNA ; mRNA ; Ontology ; Periodontitis ; Periodontitis - genetics ; Proteins ; regulatory network ; RNA, Long Noncoding - genetics ; RNA, Messenger - genetics ; Sequence Analysis, RNA ; Signal transduction ; Transcription factors</subject><ispartof>Journal of periodontal research, 2018-08, Vol.53 (4), p.495-505</ispartof><rights>2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd</rights><rights>2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.</rights><rights>Copyright © 2018 John Wiley & Sons A/S</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4199-e4e38b813315e50895ecd305f17c0be4302c7c66340a625f4b56e5a6ca5f71443</citedby><cites>FETCH-LOGICAL-c4199-e4e38b813315e50895ecd305f17c0be4302c7c66340a625f4b56e5a6ca5f71443</cites><orcidid>0000-0002-9810-2368 ; 0000-0002-9319-6780</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fjre.12539$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fjre.12539$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29516510$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, S.</creatorcontrib><creatorcontrib>Liu, X.</creatorcontrib><creatorcontrib>Li, H.</creatorcontrib><creatorcontrib>Pan, H.</creatorcontrib><creatorcontrib>Acharya, A.</creatorcontrib><creatorcontrib>Deng, Y.</creatorcontrib><creatorcontrib>Yu, Y.</creatorcontrib><creatorcontrib>Haak, R.</creatorcontrib><creatorcontrib>Schmidt, J.</creatorcontrib><creatorcontrib>Schmalz, G.</creatorcontrib><creatorcontrib>Ziebolz, D.</creatorcontrib><title>Integrated analysis of long noncoding RNA‐associated competing endogenous RNA network in periodontitis</title><title>Journal of periodontal research</title><addtitle>J Periodontal Res</addtitle><description>Background and Objectives
Long noncoding RNAs (lncRNAs) play critical and complex roles in regulating various biological processes of periodontitis. This bioinformatic study aims to construct a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression, based on high‐throughput RNA sequencing and microarray data about periodontitis.
Material and Methods
Data from 1 miRNA and 3 mRNA expression profiles were obtained to construct the lncRNA‐associated ceRNA network. Gene Ontology enrichment analysis and pathway analysis were performed using the Gene Ontology website and Kyoto Encyclopedia of Genes and Genomes. A protein‐protein interaction network was constructed based on the Search Tool for the retrieval of Interacting Genes/Proteins. Transcription factors (TFs) of differentially expressed genes were identified based on TRANSFAC database and then a regulatory network was constructed.
Results
Through constructing the dysregulated ceRNA network, 6 genes (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL) and 3 miRNAs (miR‐125a‐3p, miR‐200a, miR‐142‐3p) were detected. Three lncRNAs (MALAT1, TUG1, FGD5‐AS1) were found to target both miR‐125a‐3p and miR‐142‐3p in this ceRNA network. Protein‐protein interaction network analysis identified several hub genes, including VCAM1, ITGA4, UBC, LYN and SSX2IP. Three pathways (cytokine‐cytokine receptor, cell adhesion molecules, chemokine signaling pathway) were identified to be overlapping results with the previous bioinformatics studies in periodontitis. Moreover, 2 TFs including FOS and EGR were identified to be involved in the regulatory network of the differentially expressed genes‐TFs in periodontitis.
Conclusion
These findings suggest that 6 mRNAs (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL), 3 miRNAs (hsa‐miR‐125a‐3p, hsa‐miR‐200a, hsa‐miR‐142‐3p) and 3 lncRNAs (MALAT1, TUG1, FGD5‐AS1) might be involved in the lncRNA‐associated ceRNA network of periodontitis. This study sought to illuminate further the genetic and epigenetic mechanisms of periodontitis through constructing an lncRNA‐associated ceRNA network.</description><subject>Bioinformatics</subject><subject>Cell adhesion & migration</subject><subject>Cell adhesion molecules</subject><subject>ceRNA</subject><subject>Computational Biology</subject><subject>Cytokines</subject><subject>Dentistry</subject><subject>DNA microarrays</subject><subject>Gene expression</subject><subject>gene expression data</subject><subject>Gene Expression Profiling</subject><subject>Gene Ontology</subject><subject>Gene Regulatory Networks - genetics</subject><subject>Genes</subject><subject>Genomes</subject><subject>Gum disease</subject><subject>Humans</subject><subject>Intracellular Signaling Peptides and Proteins - genetics</subject><subject>lncRNA</subject><subject>Microarray Analysis</subject><subject>MicroRNAs - genetics</subject><subject>miRNA</subject><subject>mRNA</subject><subject>Ontology</subject><subject>Periodontitis</subject><subject>Periodontitis - genetics</subject><subject>Proteins</subject><subject>regulatory network</subject><subject>RNA, Long Noncoding - genetics</subject><subject>RNA, Messenger - genetics</subject><subject>Sequence Analysis, RNA</subject><subject>Signal transduction</subject><subject>Transcription factors</subject><issn>0022-3484</issn><issn>1600-0765</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp10M9OGzEQBnALFTUBeuAF0Epc4LAws_6zu0eEUpoKUQmV88rxzganGzu1N0K59RF4xj5JHZL2gFRfxpZ_-jT6GDtFuMJ0rheBrrCQvD5gY1QAOZRKfmBjgKLIuajEiB3FuID0VmX9kY2KWqKSCGP2PHUDzYMeqM200_0m2pj5Luu9m2fOO-Nbm26PDze_f73qGL2xb9b45YqG7Re51s_J-XXcqszR8OLDj8y6bEXB-ta7wQ42nrDDTveRPu3nMXv6PPl--yW__3Y3vb25z43Aus5JEK9mFXKOkiRUtSTTcpAdlgZmJDgUpjRKcQFaFbITM6lIamW07EoUgh-zi13uKvifa4pDs7TRUN9rR2nHpgAsEGVVYqLn7-jCr0MqYatUKTkClEld7pQJPsZAXbMKdqnDpkFotvU3qf7mrf5kz_aJ69mS2n_yb98JXO_Ai-1p8_-k5uvjZBf5BziKj0Y</recordid><startdate>201808</startdate><enddate>201808</enddate><creator>Li, S.</creator><creator>Liu, X.</creator><creator>Li, H.</creator><creator>Pan, H.</creator><creator>Acharya, A.</creator><creator>Deng, Y.</creator><creator>Yu, Y.</creator><creator>Haak, R.</creator><creator>Schmidt, J.</creator><creator>Schmalz, G.</creator><creator>Ziebolz, D.</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-9810-2368</orcidid><orcidid>https://orcid.org/0000-0002-9319-6780</orcidid></search><sort><creationdate>201808</creationdate><title>Integrated analysis of long noncoding RNA‐associated competing endogenous RNA network in periodontitis</title><author>Li, S. ; Liu, X. ; Li, H. ; Pan, H. ; Acharya, A. ; Deng, Y. ; Yu, Y. ; Haak, R. ; Schmidt, J. ; Schmalz, G. ; Ziebolz, D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4199-e4e38b813315e50895ecd305f17c0be4302c7c66340a625f4b56e5a6ca5f71443</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Bioinformatics</topic><topic>Cell adhesion & migration</topic><topic>Cell adhesion molecules</topic><topic>ceRNA</topic><topic>Computational Biology</topic><topic>Cytokines</topic><topic>Dentistry</topic><topic>DNA microarrays</topic><topic>Gene expression</topic><topic>gene expression data</topic><topic>Gene Expression Profiling</topic><topic>Gene Ontology</topic><topic>Gene Regulatory Networks - genetics</topic><topic>Genes</topic><topic>Genomes</topic><topic>Gum disease</topic><topic>Humans</topic><topic>Intracellular Signaling Peptides and Proteins - genetics</topic><topic>lncRNA</topic><topic>Microarray Analysis</topic><topic>MicroRNAs - genetics</topic><topic>miRNA</topic><topic>mRNA</topic><topic>Ontology</topic><topic>Periodontitis</topic><topic>Periodontitis - genetics</topic><topic>Proteins</topic><topic>regulatory network</topic><topic>RNA, Long Noncoding - genetics</topic><topic>RNA, Messenger - genetics</topic><topic>Sequence Analysis, RNA</topic><topic>Signal transduction</topic><topic>Transcription factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, S.</creatorcontrib><creatorcontrib>Liu, X.</creatorcontrib><creatorcontrib>Li, H.</creatorcontrib><creatorcontrib>Pan, H.</creatorcontrib><creatorcontrib>Acharya, A.</creatorcontrib><creatorcontrib>Deng, Y.</creatorcontrib><creatorcontrib>Yu, Y.</creatorcontrib><creatorcontrib>Haak, R.</creatorcontrib><creatorcontrib>Schmidt, J.</creatorcontrib><creatorcontrib>Schmalz, G.</creatorcontrib><creatorcontrib>Ziebolz, D.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of periodontal research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, S.</au><au>Liu, X.</au><au>Li, H.</au><au>Pan, H.</au><au>Acharya, A.</au><au>Deng, Y.</au><au>Yu, Y.</au><au>Haak, R.</au><au>Schmidt, J.</au><au>Schmalz, G.</au><au>Ziebolz, D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrated analysis of long noncoding RNA‐associated competing endogenous RNA network in periodontitis</atitle><jtitle>Journal of periodontal research</jtitle><addtitle>J Periodontal Res</addtitle><date>2018-08</date><risdate>2018</risdate><volume>53</volume><issue>4</issue><spage>495</spage><epage>505</epage><pages>495-505</pages><issn>0022-3484</issn><eissn>1600-0765</eissn><abstract>Background and Objectives
Long noncoding RNAs (lncRNAs) play critical and complex roles in regulating various biological processes of periodontitis. This bioinformatic study aims to construct a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression, based on high‐throughput RNA sequencing and microarray data about periodontitis.
Material and Methods
Data from 1 miRNA and 3 mRNA expression profiles were obtained to construct the lncRNA‐associated ceRNA network. Gene Ontology enrichment analysis and pathway analysis were performed using the Gene Ontology website and Kyoto Encyclopedia of Genes and Genomes. A protein‐protein interaction network was constructed based on the Search Tool for the retrieval of Interacting Genes/Proteins. Transcription factors (TFs) of differentially expressed genes were identified based on TRANSFAC database and then a regulatory network was constructed.
Results
Through constructing the dysregulated ceRNA network, 6 genes (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL) and 3 miRNAs (miR‐125a‐3p, miR‐200a, miR‐142‐3p) were detected. Three lncRNAs (MALAT1, TUG1, FGD5‐AS1) were found to target both miR‐125a‐3p and miR‐142‐3p in this ceRNA network. Protein‐protein interaction network analysis identified several hub genes, including VCAM1, ITGA4, UBC, LYN and SSX2IP. Three pathways (cytokine‐cytokine receptor, cell adhesion molecules, chemokine signaling pathway) were identified to be overlapping results with the previous bioinformatics studies in periodontitis. Moreover, 2 TFs including FOS and EGR were identified to be involved in the regulatory network of the differentially expressed genes‐TFs in periodontitis.
Conclusion
These findings suggest that 6 mRNAs (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL), 3 miRNAs (hsa‐miR‐125a‐3p, hsa‐miR‐200a, hsa‐miR‐142‐3p) and 3 lncRNAs (MALAT1, TUG1, FGD5‐AS1) might be involved in the lncRNA‐associated ceRNA network of periodontitis. This study sought to illuminate further the genetic and epigenetic mechanisms of periodontitis through constructing an lncRNA‐associated ceRNA network.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>29516510</pmid><doi>10.1111/jre.12539</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-9810-2368</orcidid><orcidid>https://orcid.org/0000-0002-9319-6780</orcidid></addata></record> |
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| source | Wiley Online Library - AutoHoldings Journals; MEDLINE |
| subjects | Bioinformatics Cell adhesion & migration Cell adhesion molecules ceRNA Computational Biology Cytokines Dentistry DNA microarrays Gene expression gene expression data Gene Expression Profiling Gene Ontology Gene Regulatory Networks - genetics Genes Genomes Gum disease Humans Intracellular Signaling Peptides and Proteins - genetics lncRNA Microarray Analysis MicroRNAs - genetics miRNA mRNA Ontology Periodontitis Periodontitis - genetics Proteins regulatory network RNA, Long Noncoding - genetics RNA, Messenger - genetics Sequence Analysis, RNA Signal transduction Transcription factors |
| title | Integrated analysis of long noncoding RNA‐associated competing endogenous RNA network in periodontitis |
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