Connecting perturbations of RNA binding proteins to their consequences

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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