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Description
I studied the evolution and cell biology of Paramecium tetraurelia—a model ciliate with over 40,000 distinct protein-coding genes resulting from as many as three ancient whole-genome duplication events. I was interested in the functional diversification of these gene duplicates at the level of protein localization, but the commonly used tools to study this were tedious. I instead applied a protein-correlation profiling approach to this system by way of generating a dozen sub-cellular fractions with different protein constituents due to the density of their resident organelle and then assayed these fractions using quantitative mass spectrometry. Each protein’s unique abundance profile provided evidence for its subcellular localization, and I used both supervised and unsupervised classification algorithms to cluster proteins together based on the similarity of these profiles to several hundred “marker proteins” which I manually curated. After expanding the protein inventory for numerous organelles by as many as a thousand proteins, I determined many features not previously understood or appreciated such as mosaic biochemical pathways, evidence for differential sorting mechanisms, and the abnormal evolutionary patterns of the mitochondrial proteome of ciliates. I developed a simple bioinformatic tool to probe spatial proteomics datasets more easily for proteins of interest. I demonstrate its applicability using a handful of well-characterized proteins in the budding yeast Saccharomyces cerevisiae as well as interesting proteins in less well-studied model systems like P. tetraurelia and the apicomplexan Toxoplasma gondii to both recapitulate known interactions and discover new ones. Finally, I look for large-scale evidence of gene duplicates relocalizing to new cellular compartments in P. tetraurelia and S. cerevisiae using this new dataset and a previously generated one, respectively. I find thousands of pairs of duplicates which are differentially identified and display evidence for subcellular divergence, and this seems to be largely decoupled from large changes in protein sequence but are instead associated with indels in their N-terminal peptide. These findings support the use of high-throughput proteomic techniques to determine evidence of functional divergence of gene duplicates. Taken together, this works provides a deep characterization of one of the largest unicellular proteomes in nature.
ContributorsLicknack, Timothy James (Author) / Lynch, Michael (Thesis advisor) / Wideman, Jeremy (Committee member) / Chen, Julian (Committee member) / Taylor, Jay (Committee member) / Arizona State University (Publisher)
Created2022
Description
Regulation of transcription initiation is a critical factor in the emergence of diverse biological phenotypes, including the development of multiple cell types from a single genotype, the ability of organisms to respond to environmental cues, and the rise of heritable diseases. Transcription initiation is regulated in large part by promoter regions of DNA. The identification and characterization of cis-regulatory regions, and understanding how these sequences differ across species, is a question of interest in evolution. To address this topic, I used the model organism Daphnia pulex, a well-characterized microcrustacean with an annotated genome sequence and selected a distribution of well-defined populations geographically located throughout the Midwestern US, Oregon, and Canada. Using isolated total RNA from adult, female Daphnia originating from the selected populations as well as a related taxon, Daphnia pulicaria (200,000 years diverged from D. pulex), I identified an average of over 14,000 (n=14,471) promoter regions using a novel transcription start site (TSS) profiling method, STRIPE-seq. Through the identification of sequence architecture, promoter class, conservation, and transcription start region (TSR) width, of cis-regulatory regions across the aforementioned Daphnia populations, I constructed a system for the study of promoter evolution, enabling a robust interpretation of promoter evolution in the context of the population-genetic environment. The methodology presented, coupled with the generated dataset, provides a foundation for the study of the evolution of promoters across both species and populations.
ContributorsSnyder, Shannon (Author) / Lynch, Michael (Thesis advisor) / Harris, Robin (Committee member) / Raborn, Randolph T (Committee member) / Wideman, Jeremy (Committee member) / Arizona State University (Publisher)
Created2020