A new bioinformatics pipeline to reveal the correlates of molecular evolutionary rates in ray-finned fishes
This thesis entails a multivariable investigation of molecular rate correlates in ray-finned fishes through development of a bioinformatics pipeline. The pipeline first matches data for 32 ecological traits with evolutionary rate measurements of the mitochondrial cytochrome c oxidase subunit I (COI) barcode region for over 6000 fish species. Linear regression analyses are then performed to identify those traits that contribute most to molecular rate variation, accounting for phylogenetic non-independence. The utility of the pipeline for other researchers and the potential for further molecular rate applications are then discussed. The results indicate that biological traits such as age at maturity, longevity, and body size are more general predictors of fish COI evolution rates than environmental factors such as temperature. This thesis showcases the use of bioinformatics tools to analyze different types of biological data and emphasizes the usage of multi-parameter studies to identify the most important sources of molecular rate variation.