Prediction of clustered RNA-binding protein motif sites in the mammalian genome.

Prediction of clustered RNA-binding protein motif sites in the mammalian genome.

Sequence-specific interactions of RNA-binding proteins (RBPs) with their target transcripts are essential for post-transcriptional gene expression regulation in mammals. However, accurate prediction of RBP motif sites has been difficult because many RBPs recognize short and degenerate sequences. Here we describe a hidden Markov model (HMM)-based algorithm mCarts to predict clustered functional RBP-binding sites by effectively integrating the number and spacing of individual motif sites, their accessibility in local RNA secondary structures and cross-species conservation. This algorithm learns and quantifies rules of these features, taking advantage of a large number of in vivo RBP-binding sites obtained from cross-linking and immunoprecipitation data. We applied this algorithm to study two representative RBP families, Nova and Mbnl, which regulate tissue-specific alternative splicing through interacting with clustered YCAY and YGCY elements, respectively, and predicted their binding sites in the mouse transcriptome. Despite the low information content in individual motif elements, our algorithm made specific predictions for successful experimental validation. Analysis of predicted sites also revealed cases of extensive and distal RBP-binding sites important for splicing regulation. This algorithm can be readily applied to other RBPs to infer their RNA-regulatory networks. The software is freely available at http://zhanglab.c2b2.columbia.edu/index.php/MCarts.

RNA结合蛋白（RBP）与其靶转录本的序列特异性相互作用对哺乳动物转录后基因表达调控至关重要。然而，由于许多RBP识别短且简并的序列，准确预测RBP基序位点一直很困难。在此我们描述了一种基于隐马尔可夫模型（HMM）的算法mCarts，它通过有效整合单个基序位点的数量和间距、它们在局部RNA二级结构中的可及性以及跨物种保守性来预测成簇的功能性RBP结合位点。该算法学习并量化这些特征的规则，利用了从交联和免疫沉淀数据中获得的大量体内RBP结合位点。我们应用该算法研究了两个具有代表性的RBP家族，Nova和Mbnl，它们分别通过与成簇的YCAY和YGCY元件相互作用来调控组织特异性可变剪接，并预测了它们在小鼠转录组中的结合位点。尽管单个基序元件的信息含量较低，但我们的算法做出了具体预测，并成功通过实验验证。对预测位点的分析还揭示了对剪接调控很重要的广泛且远端的RBP结合位点的情况。该算法可很容易地应用于其他RBP以推断其RNA调控网络。该软件可在http://zhanglab.c2b2.columbia.edu/index.php/MCarts免费获取。