miRNA-target prediction based on transcriptional regulation

<p>Abstract</p> <p>Background</p> <p>microRNAs (miRNAs) are tiny endogenous RNAs that have been discovered in animals and plants, and direct the post-transcriptional regulation of target mRNAs for degradation or translational repression via binding to the 3'UTRs an...

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Main Authors: Fujiwara Toyofumi, Yada Tetsushi
Format: Article
Language:English
Published: BMC 2013-02-01
Series:BMC Genomics
Online Access:http://seq.cbrc.jp/ISCB-Asia2012/
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spelling doaj-0c6d2e87f4fd49dd9cf36ea703bae6f82020-11-25T01:41:05ZengBMCBMC Genomics1471-21642013-02-0114Suppl 2S310.1186/1471-2164-14-S2-S3miRNA-target prediction based on transcriptional regulationFujiwara ToyofumiYada Tetsushi<p>Abstract</p> <p>Background</p> <p>microRNAs (miRNAs) are tiny endogenous RNAs that have been discovered in animals and plants, and direct the post-transcriptional regulation of target mRNAs for degradation or translational repression via binding to the 3'UTRs and the coding exons. To gain insight into the biological role of miRNAs, it is essential to identify the full repertoire of mRNA targets (target genes). A number of computer programs have been developed for miRNA-target prediction. These programs essentially focus on potential binding sites in 3'UTRs, which are recognized by miRNAs according to specific base-pairing rules.</p> <p>Results</p> <p>Here, we introduce a novel method for miRNA-target prediction that is entirely independent of existing approaches. The method is based on the hypothesis that transcription of a miRNA and its target genes tend to be co-regulated by common transcription factors. This hypothesis predicts the frequent occurrence of common <it>cis</it>-elements between promoters of a miRNA and its target genes. That is, our proposed method first identifies putative <it>cis</it>-elements in a promoter of a given miRNA, and then identifies genes that contain common putative <it>cis</it>-elements in their promoters. In this paper, we show that a significant number of common <it>cis</it>-elements occur in ~28% of experimentally supported human miRNA-target data. Moreover, we show that the prediction of human miRNA-targets based on our method is statistically significant. Further, we discuss the random incidence of common <it>cis</it>-elements, their consensus sequences, and the advantages and disadvantages of our method.</p> <p>Conclusions</p> <p>This is the first report indicating prevalence of transcriptional regulation of a miRNA and its target genes by common transcription factors and the predictive ability of miRNA-targets based on this property.</p> http://seq.cbrc.jp/ISCB-Asia2012/
collection DOAJ
language English
format Article
sources DOAJ
author Fujiwara Toyofumi
Yada Tetsushi
spellingShingle Fujiwara Toyofumi
Yada Tetsushi
miRNA-target prediction based on transcriptional regulation
BMC Genomics
author_facet Fujiwara Toyofumi
Yada Tetsushi
author_sort Fujiwara Toyofumi
title miRNA-target prediction based on transcriptional regulation
title_short miRNA-target prediction based on transcriptional regulation
title_full miRNA-target prediction based on transcriptional regulation
title_fullStr miRNA-target prediction based on transcriptional regulation
title_full_unstemmed miRNA-target prediction based on transcriptional regulation
title_sort mirna-target prediction based on transcriptional regulation
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2013-02-01
description <p>Abstract</p> <p>Background</p> <p>microRNAs (miRNAs) are tiny endogenous RNAs that have been discovered in animals and plants, and direct the post-transcriptional regulation of target mRNAs for degradation or translational repression via binding to the 3'UTRs and the coding exons. To gain insight into the biological role of miRNAs, it is essential to identify the full repertoire of mRNA targets (target genes). A number of computer programs have been developed for miRNA-target prediction. These programs essentially focus on potential binding sites in 3'UTRs, which are recognized by miRNAs according to specific base-pairing rules.</p> <p>Results</p> <p>Here, we introduce a novel method for miRNA-target prediction that is entirely independent of existing approaches. The method is based on the hypothesis that transcription of a miRNA and its target genes tend to be co-regulated by common transcription factors. This hypothesis predicts the frequent occurrence of common <it>cis</it>-elements between promoters of a miRNA and its target genes. That is, our proposed method first identifies putative <it>cis</it>-elements in a promoter of a given miRNA, and then identifies genes that contain common putative <it>cis</it>-elements in their promoters. In this paper, we show that a significant number of common <it>cis</it>-elements occur in ~28% of experimentally supported human miRNA-target data. Moreover, we show that the prediction of human miRNA-targets based on our method is statistically significant. Further, we discuss the random incidence of common <it>cis</it>-elements, their consensus sequences, and the advantages and disadvantages of our method.</p> <p>Conclusions</p> <p>This is the first report indicating prevalence of transcriptional regulation of a miRNA and its target genes by common transcription factors and the predictive ability of miRNA-targets based on this property.</p>
url http://seq.cbrc.jp/ISCB-Asia2012/
work_keys_str_mv AT fujiwaratoyofumi mirnatargetpredictionbasedontranscriptionalregulation
AT yadatetsushi mirnatargetpredictionbasedontranscriptionalregulation
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