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Codon substitution models can be used to quantify selective pressure on molecular sequences. The work contained within this dissertation represents my efforts to create, validate, and test codon models, and to apply them to biologically diverse data sets. Specifically, my objective is to determine the impact and consequences of instantaneous multi-nucleotide mutational events (MH) on the statistical inference of evolutionary rate parameters. In evolutionary terms, MH events represent rare phenomena which may have strong effects on protein-coding genes. Evidence for MH events directly impact the patterns and processes of protein-coding gene evolution across species and time. My central hypothesis is that accounting for multi-nucleotide mutational events alters the estimation of evolutionary rate parameters and represents an alternative path a gene may embark upon during their evolutionary history. This hypothesis is fundamentally based on a synthesis of my own work, and others within the field, on the relationship of the evolutionary properties of functional coding regions of the genome. My rationale is that completion of my dissertation will result in the generation of new statistical methodologies and readily available computational implementations designed to identify key targets of evolutionary mechanisms, genomic patterns, and biological processes important for the functional adaptation of the genome as it relates to MH. My long-term goal is to develop novel strategies to improve the biological realism of statistical models of molecular sequence evolution. I accomplish this goal by addressing gaps in conventional protein-coding gene model assumptions and with the inclusion of additional biological, statistical, physiological, and evolutionary information. In this effort, I have created a codon model to account for MH events, with details described in Chapter 2. We have also made the model easily available on and provided several useful visualizations to aide in the interpretations of results.
To better understand the evolution of protein-coding genes, I applied my methods and other existing methods in the field to explore potentially novel biological insights into a gene family, the heat shock proteins, which play an important role as a protein chaperone, and in another paper, Brain-Derived Neurotrophic Factor (BDNF), which plays an important role in brain development. I developed software pipelines, curated data, and provided visualizations for the interpretation of results. The publications associated with this work are highlighted in Chapters 3 and 4, respectively.
To enable the exploration of molecular virology and the analysis of viral pathogens I developed “Rapid Assessment of Selection in CLades (RASCL)”: a novel application for the rapid assessment of molecular sequence evolution viral clades. I used RASCL to study the emergence and ongoing evolution of SARS-CoV-2 lineage and to identify key sites subject to adaptive evolution and the development of new viral lineages. Near-real-time pathogen molecular surveillance is an important part of understanding the spread of disease. Our development of scalable tools to analyze big datasets of viral pathogen sequences is a critical step forward for global public health.
My methods and results can be used to translate existing molecular sequence data into novel insights, and to improve the understanding of important evolutionary systems, and all together constitute an accessible platform for quantifying selective pressure on molecular sequences. / Biology
Date January 2023
CreatorsLucaci, Alexander
ContributorsPond, Sergei, Kumar, Sudhir, Hey, Jody, Muse, Spencer V., 1966-
PublisherTemple University. Libraries
Source SetsTemple University
Detected LanguageEnglish
TypeThesis/Dissertation, Text
Format384 pages
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Relation, Theses and Dissertations

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