Decoding global RNP topologies in splicing regulation

选择性剪接(AS)是产生大量转录组和蛋白质组多样性的主要机制 从有限的基因组中。AS的时空调控对细胞分化和谱系的影响 决心。破坏剪接的突变会导致包括神经退化在内的一系列疾病， 肌肉营养不良和癌症。因此，理解和定位剪接对于未来的 精准医学。在过去的30年里，由于研究的重点是顺式元件及其相关的反式 因子，如RNA结合蛋白(RBPs)。热力学定律规定，RNA折叠成低游离态 然而，关于RNA-蛋白质复合体(RNP)的能量结构，人们知之甚少 大的RNP中的前-mRNA结构控制剪接，以及一般的各种RNA加工事件。我们的实验室 发明了几种基于化学交联连接的方法，使整个转录组的直接分析成为可能 体内不依赖蛋白质的RNA2D和3D结构(Paris和SHARC)。在本提案中，在目标1中，我们 开发高通量技术SHARCLIP并对其进行基准测试，以直接捕获所有RNA结构， RNA-RNA、RNA-蛋白质和蛋白质-蛋白质相互作用。SHARCLIP在概念上类似于 分析蛋白质介导的染色质构象的方法，例如chia-PET和hiChIP，并将带来 一维RNP相互作用研究向更高维度发展。在目标2中，将paris和SHARC应用于染色质 相关的RNA和新方法SHARCLIP到关键的剪接调控因子，我们将构建全转录组 2个Encode细胞系中RNA-结构和RNA-蛋白质相互作用模型及其去卷积动力学 HepG2和K562，以及来自人类iPS分化系统的6个脑细胞系。在目标3中，进一步 结合特定的细胞类型AS程序和剪接中涉及的疾病变体，我们将测试 突变通过改变结构来起作用。以结构模型为指导，我们将结合使用 CRISPR基因组编辑和结构扰动反义寡核苷酸以测试特定结构在 调节神经元分化中的剪接。总而言之，这项提议将产生一种新技术， 同时捕获体内多价RNA-蛋白质相互作用组和RNA结构，建立 基于结构剪接编码，提供了重要的资源来实现RNA加工的机制研究， 为将来的剪接靶向治疗铺平了道路。

Alternative splicing (AS) is a major mechanism that generates the vast transcriptome and proteome diversity from the limited genome. Spatial and temporal regulation of AS contributes to cell differentiation and lineage determination. Mutations that disrupt splicing cause a wide range of diseases including neurodegeneration, muscular dystrophies, and cancer. Therefore, understanding and targeting splicing is essential to the future of precision medicine. In the past 3 decades, AS studies have focused on cis elements and their associated trans factors, such as RNA binding proteins (RBPs). The laws of thermodynamics dictate that RNAs fold into low free energy structures in the context of RNA-protein complexes (RNPs), however, very little is known about how pre-mRNA structures in large RNPs control splicing, and various RNA processing events in general. Our lab invented several chemical crosslink-ligation based methods that enabled direct analysis of transcriptome-wide protein-independent RNA 2D and 3D structures in vivo (PARIS and SHARC). In this proposal, in Aim 1, we develop and benchmark a high throughput technology, SHARCLIP, to directly capture all RNA structures, RNA-RNA, RNA-protein, and protein-protein interactions together. SHARCLIP is conceptually similar to methods that analyze protein-mediated chromatin conformations, e.g., ChIA-PET and hiChIP, and will bring 1D RNP interaction studies to higher dimensions. In aim 2, applying PARIS and SHARC to chromatin associated RNAs, and the new method SHARCLIP to key splicing regulators, we will build transcriptome-wide RNA-structure and RNA-protein interaction models and deconvolve their dynamics in 2 ENCODE cell lines HepG2 and K562, as well as 6 brain cell lineages from a human iPS differentiation system. In aim 3, further integrating cell type specific AS programs and disease variants implicated in splicing, we will test whether mutations act by altering the structures. With the structure models as a guide, we will use a combination of CRISPR genome editing and structure-perturbing antisense oligos to test the roles of specific structures in regulating splicing in neuronal differentiation. Together, this proposal will produce a new technology that simultaneously capture multi-valent RNA-protein interactome and RNA structurome in vivo, establish a structure-based splicing code, provide an important resource to enable mechanistic studies of RNA processing, and pave the way for future therapeutic targeting of splicing.