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Bioinformatics analysis to predict and identification target genes for up-regulated microRNAsas promising biomarkers in allergic rhinitis

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Year: 2016
COI code: IPMCMED01_067
Paper Language: English

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Authors Bioinformatics analysis to predict and identification target genes for up-regulated microRNAsas promising biomarkers in allergic rhinitis

Maryam Hosseini - B.Sc genetic student, Department of Genetics, Faculty of Basic Sciences, University of Shahrekord, Shahrekord, Iran
Somayeh Reiisi - Assistant professor, Department of Genetics, Faculty of Basic Sciences, University of Shahrekord, Shahrekord, Iran

Abstract:

Introduction: MicroRNAs (miRNAs) are a group of small noncoding RNA that can play important roles as regulators in biological processes comprising the development, inflammation and immune response. Because of the numerous of possible interactions between a single mir and target genes, bioinformatics prediction are very valuable to simplify the procedure for selecting putative target genes.Allergic rhinitis (AR) is a usual disorder in airway. The pathogenesis of AR is unknown but immune deregulation is involved in AR. Evidence displayed that miRNAs are important in regulatory inflammatory processes and they are considered satisfactory biomarkers. Nevertheless, whether miRNAs were involved in chronic allergic airway disease remains largely unknown. Therefore this study aims to investigate putative target genes and interaction networks where they are involved in AR.Methods:The original data set GSE51392 was received from the Gene Expression Omnibus, and then thedifferentially expressed miRNAsbetweenpatients with seasonal allergic rhinitisin two levels of baseline and allergen challenge were identified using the FlexArraysoftware. Their target genes were selected from four (Tagetscan, miRWalk, miRDB, DIANAmt) miRNA databases. Then, functional analysis was accomplished for the target genes using by construction of a miRNAs target gene network. Results:In this study, described four miRs (miR-425, miR-146a, miR-133a, and miR-135) whichindicated to be differentially expressed in patients with seasonal allergic rhinitis. The miRs were exposed to the most used predictions software and 26 predicted target genes were recognized. Then, enrichment analysis was performed revealing substantialgroups, comprising role in regulation of receptor protein in interleukin (IL-1RA, IL-13RA, IL-18 and IL-33) signaling pathwayand regulation of TGF-beta signaling pathway. A network construction was generated and links between the selected miRs and the predicted targets. Conclusions: In this study, we merged miRNA expression analysis with a bioinformatics-based workflow. Some genes, pathways and interactions, putatively involved in ARdevelopment, were identified.

Keywords:

MicroRNA, allergic rhinitis, target prediction, biomarker

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COI code: IPMCMED01_067

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Hosseini, Maryam & Somayeh Reiisi, 2016, Bioinformatics analysis to predict and identification target genes for up-regulated microRNAsas promising biomarkers in allergic rhinitis, First Personal Medical Congress, تهران, دانشگاه علوم پزشكي ايران - پژوهشكده ملي مهندسي ژنتيك و زيست فناوري ايران، مركز همكاري هاي فناوري و نوآوري هاي رياست جمهوري, https://www.civilica.com/Paper-IPMCMED01-IPMCMED01_067.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
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