title: miRNA-target prediction based on transcriptional regulation.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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 cis-elements between promoters of a miRNA and its target genes. That is, our proposed method first identifies putative cis-elements in a promoter of a given miRNA, and then identifies genes that contain common putative cis-elements in their promoters. In this paper, we show that a significant number of common cis-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 cis-elements, their consensus sequences, and the advantages and disadvantages of our method.
  
  
  CONCLUSIONS
  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.
authors: INTEC Inc., 1-3-3 Shinsuna, Koto-ku, Tokyo 136-8637, Japan.
authors: Toyofumi
authors: T
authors: Fujiwara
authors: Tetsushi
authors: T
authors: Yada
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D016384:Consensus Sequence; D030561:Databases, Nucleic Acid; D005786:Gene Expression Regulation; D006801:Humans; D035683:MicroRNAs / Q000145:classification / Q000235:genetics*; D011401:Promoter Regions, Genetic / Q000235:genetics*; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D035683:MicroRNAs; D014157:Transcription Factors