Connecting perturbations of RNA binding proteins to their consequences

将 RNA 结合蛋白的扰动与其后果联系起来

• 批准号: 10388840
• 负责人: Michael P McGurk
• 金额: $ 6.76万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10388840
• 关键词: Affect; Alternative Splicing; Back; Binding Proteins; Biological; Biology; Characteristics; Communities; Complex; Data; Data Set; Defect; Degenerative Disorder; Development; Disease; Doctor of Philosophy; Environment; Event; Exclusion; Exons; Family; Fibrinogen; Future; Generations; Genes; Genome; Genomics; Goals; Human; Individual; Institutes; Large-Scale Sequencing; Lead; Length; Light; Linear Models; Logic; Malignant Neoplasms; Maps; Massachusetts; Mentorship; Methodology; Mutation; Outcome; Pathology; Pattern; Point Mutation; Protein Splicing; RNA; RNA Processing; RNA Splicing; RNA-Binding Proteins; Regulation; Regulatory Element; Research; Role; Shapes; Short Tandem Repeat; Site; Source; Statistical Models; Stretching; Structure; Tandem Repeat Sequences; Technical Expertise; Technology; Tissues; Training; Transcript; Variant; Work; career; experience; experimental study; field study; flexibility; gene product; genetic regulatory protein; human disease; knock-down; preference; skills; tool; transcriptome; transcriptomics

PROJECT SUMMARY/ABSTRACT Alternative splicing allows multiple gene products to be generated from a single gene, and contributes to transcriptomic diversity across tissues, development, and individuals. Given that most genes undergo alternative splicing, the disruption of splicing is a common contributor to disease. Pathology can result through mutations affecting the splicing of particular genes as well as broad splicing defects that affect many genes. Advances in sequencing technology have greatly simplified the problem of identifying the splicing products present in a given tissue and determining how splicing is perturbed in diseases states. But the problem remains to extract actionable interpretations from the hundreds or thousands of splicing changes that even a single sequencing experiment might reveal. The goal of this project is to understand how perturbations of splicing regulators connect to the resulting changes in splicing. I will consider both variation at RNA-binding protein target sites and disruption of the RBPs themselves. I will first consider the connection between short tandem repeat (STR) variation and splicing. Given that many of the most abundant STRs in the genome match the sequence preferences of important splicing factors, I will leverage sequencing data spanning hundreds of individuals to determine whether these highly mutable sequences represent a frequently ignored source of splicing variation. I will then consider the regulatory characteristics of RBPs themselves. I will first reframe the approach commonly used to integrate RBP binding and splicing data as a flexible linear model which can incorporate additional information and confounders. I will then apply this to recent ENCODE panel of RBP binding and knockdown data to infer the networks of splicing events regulated by a given RBP. I will then seek to use these networks to interpret patterns of altered splicing in disease states. I will carry out this work under the mentorship of Christopher Burge at the Massachusetts Institute of Technology (MIT), a leader in the field of alternative splicing. Given the Burge lab’s long track record of strong computational and experimental work, this will provide an ideal environment for both carrying out this research and developing the skills I will need for an independent career as a computational biologist. The proposed training will involve frequent interaction with experts in the study of RNA binding proteins and splicing, including the research groups that generated many of the datasets I will study, such as the Graveley and Yeo labs. Through this work I will develop further technical expertise in a number statistical and computational approaches and be immersed in the biology of splicing. I will have access to the experience and expertise I will need to transition from the evolutionary genomics of my PhD to the study of RNA processing and its regulation

项目摘要/摘要 选择性剪接允许从单个基因产生多个基因产物，并有助于 组织、发育和个体之间的转录多样性。鉴于大多数基因都经历了 选择性剪接，剪接的中断是导致疾病的常见因素。病理可以通过 影响特定基因剪接的突变以及影响许多基因的广泛剪接缺陷。 测序技术的进步极大地简化了识别剪接产物的问题 在给定的组织中存在，并决定剪接在疾病状态下如何受到干扰。但问题是 从成百上千的拼接变化中提取可操作的解释，即使是 单一的测序实验可能会揭示。 这个项目的目标是了解剪接调节器的扰动是如何连接到所产生的 拼接中的更改。我将同时考虑RNA结合蛋白靶点的变异和限制性商业惯例的破坏。 他们自己。我首先考虑短串联重复序列(STR)变异和剪接之间的联系。 鉴于基因组中许多最丰富的STR与重要的 拼接因素，我将利用跨越数百个个体的测序数据来确定这些 高度可变的序列是剪接变异的一个经常被忽视的来源。然后我会考虑 限制性商业惯例本身的监管特点。我将首先重新定义集成通常使用的方法 RBP将数据绑定和拼接为灵活的线性模型，该模型可以合并其他信息和 混血儿。然后，我将把它应用于最近的RBP结合和击倒数据的ENCODE小组，以推断 由给定RBP调控的剪接事件网络。然后我会试图利用这些网络来解释 疾病状态下的剪接改变模式。 我将在麻省理工学院克里斯托弗·伯奇的指导下开展这项工作 麻省理工学院(MIT)，替代剪接领域的领导者。鉴于Burge实验室长期记录的Strong 计算和实验工作，这将为开展这项研究提供一个理想的环境 并培养我作为计算生物学家独立职业所需的技能。建议数 培训将涉及与研究RNA结合蛋白和剪接的专家频繁互动，包括 产生了我将研究的许多数据集的研究小组，例如Graveley和Yeo实验室。 通过这项工作，我将进一步发展一些统计和计算方面的技术专长 并沉浸在剪接的生物学中。我将获得我将获得的经验和专业知识 需要从我博士的进化基因组学过渡到RNA加工及其调控的研究