COMPARATIVE BIOINFORMATIC AND MOLECULAR EVOLUTIONARY ANALYSIS OF CHORDATE GENES AND GENOMES

• Main Author: Unkn Unknown
• Format: Text
• Language: English
• Published: Temple University. Libraries 2020
• Subjects: Biology; Bioinformatics; FOS Computer and information sciences; Arctic
• Online Access: https://dx.doi.org/10.34944/dspace/4735; https://scholarshare.temple.edu/handle/20.500.12613/4753

As knowledge of evolutionary processes has expanded over the years, we havedeepened our understanding about how they drive organismal, cellular, and molecular biology and the factors beyond natural selection that are involved. Nevertheless, selection maintains a role in fixing and maintaining successful adaptations to new niches, whether from environmental change or organismal migration. Adaptation should not be considered solely on the level of individual genes and point substitutions as selection occurs on multiple levels. Examination on these multiple levels can further aid in understanding the constraints on evolution and how organisms can attain a phenotype. Here we present two packages of tools for the examination of selection on the levels of protein structure and genetic pathways as well as on the individual gene and sequence levels., followed by examples of potential applications. First, we present a package of Application Programming Interface (API) tools that simplifies use of The Adaptive Evolutionary Database. Second, we present a package of tools implemented in the Rust programming language for fast and reliable analysis of phylogenetic data. Then we describe the phenotypic data and methodology for use of these tools to analyze evolution on multiple levels, where genomic data is available. A broad scale analysis of the protein structural properties of evolutionary genetic changes in proteins is developed and described. We also present an organization of phenotypic data for mammals in the arctic biome, an ancestral reconstruction of the evolution of the phenotypic traits under study, and demonstrate a methodology to apply the tool packages to this cohort when sufficient genomic data is available.