Computational Methods for Deep Sequencing Based RBP Binding Motif Characterizatio

描述（由申请人提供）：由于识别其结合位点的灵活性，RNA结合蛋白可以具有100至1000个靶mRNA。这些位点可以包含序列和结构元件，并且当比较不同RBP的结合基序时，即使在相同RBP家族的成员之间，也显示出巨大的变化。直到21世纪初，结合位点的表征主要限于涉及特定RBP和靶基因/结合基序的个体研究。只有在过去的十年中，体内结合基序的初步鉴定才成为可能;首先使用RIP芯片方法，然后使用CLIP和RIP-seq。这最后两种方法结合了深度测序的力量，不仅使我们能够识别更多的结合位点，而且还可以进行更精细的映射。一个值得关注的领域是发展计算方法，对这些技术产生的数据集进行全面分析。在这个项目中，我们将在两个结肠癌细胞系中用RIP-seq分析五个RBP的靶点。我们将设计和实现一个框架，用于表征RNA结合蛋白的结合特异性。我们将评估和改进从这些数据中识别RBP目标的方法。最后，我们将建立一个关于RNA结合蛋白、其靶基因、结合位点和结合特异性的信息数据库。

DESCRIPTION (provided by applicant): RNA binding proteins can have 100s to 1000s of target mRNAs thanks to flexibility in recognizing their binding sites. These sites can incorporate both sequence and structural elements and show tremendous variation when binding motifs of different RBPs are compared, even among members of the same RBP family. Until early 2000s, characterization of binding sites was mostly restricted to individual studies involving a particular RBP and a target gene/binding motif. Only in the last decade, en masse identification of in vivo binding motifs became possible; first with the RIP-chip approach and then with CLIP and RIP-seq. These last two methods incorporate the power of deep sequencing, allowing us not only to identify more binding sites but also to conduct a more refined mapping. One area that urges attention is the development of computational methods to perform comprehensive analyses of datasets generated by these techniques. In this project we will profile targets for five RBPs with RIP-seq in two colon cancer cell lines. We will design and implement a framework for characterizing the binding specificity of RNA binding proteins. We will evaluate and refine methodology for RBP target identification from such data. Finally, we will develop a database of information about RNA-binding proteins, their target genes, binding sites and binding specificities.