Functional and computational analysis of RNA-binding proteins and their roles in cancer

Abstract

This work is concerned with mRNA processing in mammalian cells and proceeds in two parts. In the first part, I introduce a computational framework for inferring the abundances of mRNA isoforms using high-throughput RNA sequencing data. This framework was applied to study the targets of the ubiquitous splicing factor hnRNP H in human cells. In the second part, I describe an experimental study of the Musashi (hnRNP-like) family of RNA-binding proteins in stem cells and cancer cells, which incorporates computational analyses that rely heavily on the framework developed in part one. In sum, this work provides a computational framework of general use in global analyses of RNA processing and its protein regulators, as well as functional insights into a family of poorly understood RNA-binding proteins. Several related analyses and techniques developed as part of the thesis are described in Appendix A-C. Appendix A describes a study of activity-dependent gene expression and mRNA processing in the mouse olfactory bulb. It uses computational techniques developed in part one of the thesis. Appendix B describes a technique for quantitative visualization of alternative splicing from RNA sequencing data and its integration into a genome browser. Appendix C describes a method for clonal analysis of neural stem cell growth and differentiation in culture using live imaging and `microdot' plates, developed as part of the work presented in part one of the thesis.