Technological advancements have sparked discovery in biology, enabling important questions to be addressed experimentally at unprecedented depth and scale. One such advance, the development of large-scale approaches to study gene expression, has transformed the way we view the transcriptome. In recent years, these approaches have been applied to studies of alternative RNA splicing, a process where multiple distinct messenger RNAs can be generated from precursor transcripts to produce extensive transcriptomic diversity from a limited repertoire of genes. Global analyses have not only reinforced models initially based on single gene studies, they have also led to numerous insights into general principles governing the regulation and evolution of alternative splicing. In this thesis, I describe how I have combined both large-scale and focused approaches to study alternative splicing regulation during development and in an evolutionary context. Using microarray profiling and comparative genomics approaches, I describe the first large-scale comparative analysis of alternative splicing patterns between humans and chimpanzees. Next, I describe the discovery of a novel neural-specific RS domain splicing factor and the network of alternative exons it regulates to promote nervous system development in vertebrates. Finally, I describe the profiling of alternative splicing patterns during C. elegans development using splicing microarrays and high-throughput sequencing. In this latter study, I also describe two resources that facilitate the analysis of tissue- or cell type-specific splicing events, and enable the function of isoforms to be assessed in vivo. Collectively, these studies have shed light on how differential regulation of alternative splicing has contributed to the evolution of complexity and diversity in biological systems.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/31705 |
| Date | 05 January 2012 |
| Creators | Calarco, John Anthony |
| Contributors | Blencowe, Benjamin, Zhen, Mei |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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