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

基本信息

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
项目类别：
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

项目摘要

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

项目概要/摘要选择性剪接允许从单个基因产生多个基因产物，并有助于鉴于大多数基因都会经历跨组织、发育和个体的转录组多样性。选择性剪接，剪接的破坏是导致疾病的常见因素。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解决了拼接产物的识别问题存在于给定组织中并确定剪接在疾病状态下如何受到干扰。仍然需要从数百或数千个剪接变化中提取可操作的解释，即使是单个测序实验可能会揭示这一点。该项目的目标是了解剪接调节器的扰动如何与产生的结果联系起来我将考虑 RNA 结合蛋白靶位点的变化和 RBP 的破坏。我将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 与重要的序列偏好相匹配剪接因素，我将利用跨越数百个人的测序数据来确定这些是否高度可变的序列代表了经常被忽视的剪接变异来源。我将首先重新构建通常用于整合的方法。 RBP 结合和拼接数据作为灵活的线性模型，可以包含附加信息和然后我会将其应用到最近的 RBP 结合和敲低数据的 ENCODE 面板中以推断然后我将寻求使用这些网络来解释由给定 RBP 调节的剪接事件网络。疾病状态下的剪接模式。我将在麻省理工学院 Christopher Burge 的指导下开展这项工作鉴于 Burge 实验室长期以来的强大记录，麻省理工学院 (MIT) 是替代剪接领域的领导者。计算和实验工作，这将为开展这项研究提供理想的环境并培养我作为一名计算生物学家的独立职业所需的技能。培训将涉及与 RNA 结合蛋白和剪接研究专家的频繁互动，包括生成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业知识方法并沉浸在剪接生物学中，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转向RNA加工及其调控的研究