miRNA-target prediction based on transcriptional regulation.
miRNA-target prediction based on transcriptional regulation.
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DOI：
10.1186/1471-2164-14-s2-s3
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发表时间：
2013
期刊：
影响因子：
4.4
通讯作者：
Yada T
中科院分区：
文献类型：
--
作者：
Fujiwara T;Yada T
microRNA（miRNAs）是在动植物中发现的一类微小的内源性RNA，通过与3'UTR和编码外显子的结合，在转录后调控靶mRNA的降解或翻译抑制。为了深入了解miRNA的生物学作用，必须确定mRNA靶点（靶基因）的完整库。已经开发了许多用于miRNA靶点预测的计算机程序。这些程序主要集中在3'UTR中的潜在结合位点，这些位点根据特定的碱基配对规则被miRNA识别。在这里，我们介绍了一种新的方法，miRNA的目标预测，是完全独立于现有的方法。该方法基于这样的假设，即miRNA及其靶基因的转录倾向于由共同的转录因子共同调节。这一假说预测了miRNA启动子与其靶基因之间常见的顺式元件的频繁出现。也就是说，我们提出的方法首先确定一个给定的miRNA的启动子中的推定顺式元件，然后确定在其启动子中包含共同的推定顺式元件的基因。在这篇论文中，我们发现了大量的常见顺式元件出现在约28%的实验支持的人类miRNA靶数据中。此外，我们表明，基于我们的方法的人类miRNA靶点的预测是统计学上显着的。此外，我们讨论了常见的顺式元件，其共识序列的随机发病率，我们的方法的优点和缺点。这是第一个报告表明普遍的转录调控的miRNA和它的靶基因的共同转录因子和预测能力的miRNA的目标的基础上，这一属性。
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. 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. 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.