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Comprehensive Analysis of lncRNA and circRNA Mediated ceRNA network in Psoriasis
University of Skövde, School of Bioscience.
2022 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Evidence is accumulating that noncoding RNAs and circRNA are involved in psoriasis; however, the competing endogenous RNA (ceRNA) mediated regulatory mechanisms in psoriasis are rarely reported. The research study aimed to comprehensively investigate the differences in the expression levels of circular RNA (circRNA), long non-coding RNA (lncRNA), microRNA (miRNA/miR), and mRNA in psoriasis. In addition, key lncRNA/circRNA-miRNA-mRNA-ceRNA interactions were screened using the GSE145305 microarray dataset from the Gene Expression Omnibus database. After data preprocessing, differentially expressed circRNAs (DECs), lncRNAs (DELs), miRNAs (DEMs), or genes (DEGs) were identified, and normal controls using the linear models for the microarray data method. A protein-protein interaction (PPI) network was constructed for DEGs based on protein databases, followed by a module analysis. The ceRNA network was constructed based on the interaction between miRNAs and mRNAs and lncRNAs/circRNAs and miRNAs. The present study identified that in the case of mRNA 10 genes are significantly down-regulated, 86 genes are significantly up-regulated and in the case of miRNA 48 are significantly down-regulated and 75 genes are significantly up-regulated between patients with psoriasis and controls. miRNA, mRNA, lncRNA, and circRNA target predictionswere made. Then combined construction of a ceRNA network using mRNA-miRNA-lncRNA and mRNAmiRNA-circRNA. The current research has employed the knowledge of bioinformatics tools and software to determine the hub module and PPI network. Taken together, these identified ceRNA interactions may be crucial targets for the treatment of psoriasis.

Place, publisher, year, edition, pages
2022. , p. 53
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:his:diva-21555OAI: oai:DiVA.org:his-21555DiVA, id: diva2:1680579
Subject / course
Bioinformatics
Educational program
Bioinformatics - Master’s Programme
Supervisors
Examiners
Available from: 2022-07-04 Created: 2022-07-04 Last updated: 2022-07-04Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • modern-language-association-8th-edition
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