Combinatorial RNA Structural Features That Control RNA-Protein Binding

项目总结/摘要 RNA-蛋白质结合对基因调控至关重要，控制基本过程，包括 RNA剪接、翻译、定位和稳定性。RNA-蛋白质相互作用在广泛的 各种疾病，包括肌肉萎缩症，脆性X综合征，精神发育迟滞， Prader-Willi综合征、色素性视网膜炎、脊髓性肌萎缩症和癌症。进展 对理解RNA-蛋白质相互作用的潜在机制具有重要价值 来改善人类健康。虽然大多数基因调控的研究都集中在DNA上， 蛋白质相互作用，RNA结合蛋白（RBP）的作用机制仍然存在 神秘莫测然而，新的高通量测量将很快产生大量的RNA- 蛋白质相互作用数据。这些可以极大地阐明RNA调控，但也需要新的 分析方法。为了迎接这一挑战，我们提出了新的计算方法， 确定RNA-蛋白质结合的关键序列和结构，基于数百个 目前正在为人类ENCODE项目生成CLIP-seq和SELEX数据集。电流 用于建模RNA-蛋白质相互作用的方法具有较低的预测能力， 假设主要是由于两个不同的问题：（a）他们忽略了 每个RNA内的多个元件与蛋白质结合，以及（B）它们仅解释a 肤浅的方式。我们将通过开发创新方法来解决这些问题， 互补CLIP-seq和SELEX数据，以确定RNA元件的不同类别 绑定每个RBP;学习类之间的组合逻辑;以及学习序列， 定义每个类的结构。我们还将针对至少两种RBP验证我们的方法 使用RNA-蛋白质凝胶移位实验。我们预计，这项探索性研究将产生 功能强大、经过实验验证的软件工具， 从高通量测序数据的RNA-蛋白质结合方面。 !

PROJECT SUMMARY/ABSTRACT RNA-protein binding is critical to gene regulation, controlling fundamental processes including RNA splicing, translation, localization and stability. RNA-protein interactions play a role in a wide variety of diseases including muscular dystrophy, fragile X syndrome, mental retardation, Prader-Willi syndrome, retinitis pigmentosa, spinal muscular atrophy, and cancer. Advances towards understanding the underlying mechanisms of RNA-protein interaction have great value for improvement of human health. While most studies of gene regulation have focused on DNA- protein interactions, the mechanisms by which RNA-binding proteins (RBPs) act remain enigmatic. However, new high-throughput measurements will soon yield vast amounts of RNA- protein interaction data. These could dramatically clarify RNA regulation, but also demand novel analytical approaches. To meet this challenge, we propose novel computational methods to determine sequences and structures critical to RNA-protein binding, based on hundreds of CLIP-seq and SELEX datasets now being generated for the human ENCODE project. Current methods for modeling RNA-protein interactions have low predictive power, which we hypothesize is due, mainly, to two different issues: (a) they ignore combinatorial binding of multiple elements within each RNA to the protein, and (b) they only account for structure in a superficial manner. We will solve these problems by developing innovative methods that use complementary CLIP-seq and SELEX data to: determine the different classes of RNA elements binding each RBP; learn the combinatorial logic among classes; and learn the sequences and structures that define each class. We will additionally validate our methods for at least two RBPs using RNA-protein gel shift experiments. We expect that this exploratory study will yield powerful, experimentally validated software tools to determine combinatorial and structural aspects of RNA-protein binding from high-throughput sequencing data. !