CAREER: Uncovering the regulation of low fidelity mRNA splicing

University Of Massachusetts Medical School, Worcester MA

Investigators

Abstract

The central dogma of molecular biology involves the synthesis of ribonucleic acid (RNA) from the genes defined in deoxyribonucleic acid (DNA) molecules. Some of these RNA molecules then act as messengers that shuttle instructional blueprints to enable proper cellular function. The informational content encoded by RNA is amplified by the process of splicing, which enables the creation of dozens of different RNA molecules from a single gene sequence. The process of splicing is very complex, with one of the largest molecular complexes and many auxiliary factors working together to coordinate the precise levels and compositions of messenger RNAs. This intricacy opens the door for noise and errors in splicing that may comprise a substantial fraction of RNA output in a cell. While quality control mechanisms to check for and correct such errors have been identified over the last decade, less is known about how often these errors occur and why certain erroneous RNAs escape detection and removal. This project will use novel genomics and computational tools to identify directly and quantify erroneously spliced RNAs, gaining a better understanding of the regulation of proper RNA synthesis for cellular function. More broadly, the project aims to teach the cross-cutting skills of biological data analysis to up and coming researchers and educators by (1) hosting Worcester area undergraduates for a combined summer research and outreach experience in computational biology and (2) facilitating an enrichment program at UMass Chan Medical School for Worcester Public School science teachers. For decades, the process of mRNA splicing was thought to be highly efficient, with little opportunity for deviation outside of regulated alternative splicing decisions. This idea led to a widespread perspective that all alternative mRNA isoforms must be regulated and, potentially, have biological function. Recently, however, researchers have identified pervasive, non-canonical splice site choice, including those at low-fidelity spliceosome binding sequences. These discoveries suggest that there is widespread error and cryptic splice site usage by mRNA splicing mechanisms, with unexplored roles for stochastic, biological noise in shaping metazoan transcriptome diversity. This project will use high-throughput sequencing of nascent RNA to track splicing intermediates through cellular compartments, creating a catalog of cryptic splice sites and examining genetic and biochemical features associated with these events. These studies will provide insight into how and when undesirable splicing products escape or are pruned by mRNA quality control mechanisms. Leveraging this catalog, a statistical model will be built to enable a predictive understanding of cryptic splice site usage and employ gene editing tools to test predictions from this model. The long-term research goal of this project is to define what constitutes noise in mRNA splicing and use these studies to redefine the mRNA splicing code. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.