Electronic Thesis and Dissertation Repository

Degree

Master of Science

Program

Computer Science

Supervisor

Dr. Peter K Rogan

Abstract

The Shannon Human Splicing Pipeline software has been developed to analyze variants on a genome-scale. Evidence is provided that this software predicts variants affecting mRNA splicing. Variants are examined through information-based analysis and the context of novel mutations as well as common and rare SNPs with splicing effects are displayed. Potential natural and cryptic mRNA splicing variants are identified, and inactivating mutations are distinguished from leaky mutations. Mutations and rare SNPs were predicted in genomes of three cancer cell lines (U2OS, U251 and A431), supported by expression analyses. After filtering, tractable numbers of potentially deleterious variants are predicted by the software, suitable for further laboratory investigation. In these cell lines, novel functional variants comprised 6–17 inactivating mutations, 1–5 leaky mutations and 6–13 cryptic splicing mutations. Predicted effects were validated by RNA-seq data of the three cell lines, and expression microarray analysis of SNPs in HapMap cell lines.


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