Date of Award

12-11-2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Bioinformatics

First Advisor

Stephanie Byrum

Second Advisor

Michael Robeson II

Abstract

Multi-omics experimental approaches are becoming a mainstream practice in systems biology underlining the need to design new integrative techniques and applications to enable the multi-scale characterization of different types of diseases for targeted therapy. Proteogenomics, a sub-field within the broad field of multi-omics incorporates techniques to integrate genomics, transcriptomics and proteomics data for efficient identification of novel proteoforms or protein isoforms. There are multitude of challenges when applying proteogenomics analyses, such as improper integration of each omics data type, missing structural annotations, inefficient identification of splice-junctions, novel genes, etc. This dissertation will outline a novel and integrative proteogenomics pipeline that can be easily adapted to the users' specific experimental design. It does this by generating sample-specific sequence databases from the users' own genomic and transcriptomic sequencing data. This information is subsequently mapped to the users' proteomics data to aid in the discovery of novel proteoforms, and their associated RNA isoforms. This integration allows the user to expand upon, existing pre-curated reference databases. The following work will also present a holistic guide, with an example case study of proteogenomics data integration strategies, which highlights the benefits and challenges proteogenomic integration strategies. The efficacy of the pipeline will be shown through its ability to robustly identify potential therapeutic vulnerabilities, of MAPK inhibitor resistance, within a patient derived xenograft (PDXs) model.

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