Grant: Doctoral: Vanier Canada Graduate Scholarships

Alternative splicing (AS) plays a major role in amplifying the complexity encoded by the genome by producing proteins with distinct structures and functions from the same gene locus. In this project we aim to study the scope of AS in cancer and associate alterations to disease phenotypes. By regulating the inclusion of coding sequences in a context specific manner, different proteins can be produced for each type of tissue at specific developmental stages. The splicing machinery is complex, composed of DNA sequence signals and many proteins that coordinate in the regulation of alternative expression. Cancers are known for their genomic instability which can greatly affect this machinery. Mutations which alter splicing signals or related factors may have an effect on alternative splicing, some changes may be damaging the cell and others could be beneficial for a tumor. Although specific patterns of AS have been detected for some cancers, the extent to which this is central to the disease is not fully known. In the past few years, technological advances have allowed us to obtain a sample representation of the transcriptome, the set of expressed genes in their active configuration. RNA-Seq is the application of next-generation sequencing to the analysis of transcriptomes. By taking advantage of large cohorts of cancer samples for which we already have RNA-Seq data, we can conduct large-scale analysis to find patterns specific to cancer. Novel bioinformatic methods will need to be developed when existing ones do not provide us with enough information. We will then use this data to analyze AS patterns on 50 breast cancer samples, and use genomic DNA data to try to determine the genomic causes for thiese changes. This project has the potential of discovering markers for cancer detection and treatment response prediction. Information generated by our project will also help subsequent studies with data analysis by eliminating artifacts and highlighting significant results.