DocumentCode :
3239073
Title :
Characterization of conditions for competing endogenous RNA regulation in GBM
Author :
Yu-Chiao Chiu ; Chuang, Eric Y. ; Tzu-Hung Hsiao ; Yidong Chen
Author_Institution :
Grad. Inst. of Biomed. Electron. & Bioinf., Nat. Taiwan Univ., Taipei, Taiwan
fYear :
2013
fDate :
17-19 Nov. 2013
Firstpage :
23
Lastpage :
23
Abstract :
Summary form only given. MicroRNAs (miRNAs) are short non-coding RNAs with the average length of 22 nucleotides. They are known to induce mRNA degradation or suppression of translation by complementarily binding to 3´ untranslated regions (3´ UTRs) of target mRNA transcripts. Recently, an alternative mechanism through which miRNAs participate in gene regulation was postulated and experimentally validated, namely the competing endogenous RNAs (ceRNAs). By competing for a limited pool of common targeting miRNAs (miRNA programs; miRP), pairs of genes (ceRNAs) sharing, fully or partially, identical miRNAs binding sites can “talk” to each other: when one ceRNA is up-regulated (or down-regulated) in cells, it attracts (or releases) the targeting miRNAs away from (or toward) the other ceRNA, and in turn have protective (or harmful) effects on expression of the other ceRNA. Based on in silico and in vitro analysis, recent reports suggested the dynamic and condition-specific properties of ceRNA regulation. The essential factors involved in ceRNA regulation include size of miRP, number of miRP binding sites, expression level of miRP, and expression level of ceRNAs. For better characterizing the optimal conditions for ceRNA regulation, in the present study we aim to confer how essential factors determine strength of ceRNA regulation in vivo, by analyzing TCGA datasets of glioblastoma multiforme (GBM) patients with 491 tumor samples profiled with paired miRNA and gene expression. Based on the definition that two genes sharing any number of common targeting miRNAs as a putative ceRNA pair, and by utilizing TargetScan algorithm, we identified 47,451,423 putative ceRNA pairs, involving 10,872 ceRNAs (genes). Pairwise correlation coefficients of gene expression profiles were then computed for each of the putative ceRNA pairs, and then the CDF. Varying size of miRP, for example, generated multiple CDFs, and then the goodness-of-fit was performed for pinpointing th- essential factors and optimal conditions for intensified ceRNA activity. Our analysis results demonstrated that increased size of miRPs as well as the abundance of miRP binding sites stabilize ceRNA activity and strengthen coexpression of ceRNA pairs. Furthermore, the expression levels of both miRPs and ceRNAs affect ceRNA activity and lead to statistically significant differences in distributions of correlation coefficients. Taken together, the results indicated that ceRNA regulation depends on states of the essential factors and thus may involve complex and dynamic processes in vivo. Our findings bring biological insights into complex ceRNA crosstalk in glioblastoma multiforme and contribute to further unveiling complex mechanism governing ceRNA regulation.
Keywords :
RNA; bioinformatics; data analysis; genetics; genomics; molecular biophysics; statistical distributions; tumours; 3´ untranslated regions; TCGA dataset analysis; TargetScan algorithm; ceRNA expression level; competing endogenous RNA regulation; gene expression profiles; gene sharing; glioblastoma multiforme patients; miRNA binding sites; miRP binding sites; miRP expression level; microRNA degradation; microRNA suppression; nucleotides; pairwise correlation coefficients; short noncoding RNA; tumor samples; Bioinformatics; Biomedical electronics; Educational institutions; Gene expression; In vivo; Pediatrics; RNA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genomic Signal Processing and Statistics (GENSIPS), 2013 IEEE International Workshop on
Conference_Location :
Houston, TX
Print_ISBN :
978-1-4799-3461-4
Type :
conf
DOI :
10.1109/GENSIPS.2013.6735920
Filename :
6735920
Link To Document :
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