Date of Graduation

5-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Cell & Molecular Biology (PhD)

Degree Level

Graduate

Department

Cell & Molecular Biology

Advisor/Mentor

Lewis, Jeffrey A.

Committee Member

Evans, Timothy A.

Second Committee Member

Westerman, Erica L.

Third Committee Member

Bluhm, Burton H.

Keywords

Bioinformatics; Genomics; Parkinson; Transcriptomics; Yeast; α-Synuclein

Abstract

Parkinson’s Disease (PD) is a neurodegenerative disorder that causes countless suffering around the world. Both forms, familial and sporadic, have been associated with the misfolding and cytotoxicity of α-synuclein, an otherwise non-pathogenic protein suspected to have various roles in the normal maintenance of the central nervous system. Model organisms have emerged as great vessels to uncover the cellular and molecular mechanisms that shape α-syn biology, and great strides have been made to understand it. Yet, it is still unclear why some individuals are affected by α-syn toxicity, while others not so much. Since it’s extremely complicated to study and probe natural variation in human populations, we turn to the friendly yeast Saccharomyces cerevisiae to understand this phenomenon. We identify wild populations of yeast with increased resistance or susceptibility to α-syn cytotoxicity, and we leverage this natural variation to further understand α-syn resistance. By employing transcriptomic and genetic mapping via whole genome sequencing approaches, we are able to narrow down candidate genes for resistance. Moreover, some of these candidate genes have also been functionally validated as mediators of α-syn resistance in yeast and opened new avenues of research in other model organisms. Finally, we employ genetic engineering and genome modification techniques to create a new panel of strains that can be used in the future for further dissecting α-syn resistance or other similar phenotypes for these strains. Our results highlight the importance of using natural variation to dissect complex traits, as we are able to pinpoint genes that are only causal for a specific genetic background, underlining the real complexity behind any resistance phenotype. Beyond our findings relevant to the PD-research field, we showcase how similar methods could be used to leverage natural variation in model organisms for other human diseases or complex traits.

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