Modeling And Partitioning The Nucleotide Evolutionary Process For Phylogenetic And Comparative Genomic Inference

The transformation of genomic data into functionally relevant information about the composition of biological systems hinges critically on the field of computational genome biology, at the core of which lies comparative genomics. The aim of comparative genomics is to extract meaningful functional information from the differences and similarities observed across genomes of different organisms. We develop and test a novel framework for applying complex models of nucleotide evolution to solve phylogenetic and comparative genomic problems, and demonstrate that these techniques are crucial for accurate comparative evolutionary inferences. Additionally, we conduct an exploratory study using vertebrate mitochondrial genomes as a model to identify the reciprocal influences that genome structure, nucleotide evolution, and multi-level molecular function may have on one another. Collectively this work represents a significant and novel contribution to accurately modeling and characterizing patterns of nucleotide evolution, a contribution that enables the enhanced detection of patterns of genealogical relationships, selection, and function in comparative genomic datasets. Our work with entire mitochondrial genomes highlights a coordinated evolutionary shift that simultaneously altered genome architecture, replication, nucleotide evolution and molecular function (of proteins, RNAs, and the genome itself). Current research in computational biology, including the advances included in this dissertation, continue to close the gap that impedes the transformation of genomic data into powerful tools for the analysis and understanding of biological systems function