Evolution@Vanderbilt

Joshua joined the CoEvoD program as the inaugural second-year trainee supported by the NIH / NIGMS T32 Training Grant in 2025.

Joshua uses machine learning and other computational tools to reverse-engineer the molecular mechanisms by which birds evolved their long lifespans. Preliminary data shows extensive variations in metabolic genes that are unique to the avian clade. Joshua will infer the evolutionary timing of avian-specific mutations at key phylogenetic nodes (e.g. the evolution of flight), searching for coevolving mutations in deep time that may be compensatory, followed by ‘fine-tuned’ adaptive variation in derived lineages hypothesized to diverge between clades due to ecological and physiological variables. Additionally, incorporating machine learning to connect genotype with phenotype will provide new mechanistic insights into prolonged avian lifespans that could form new candidates for investigation in cellular models of human aging and metabolism.

Publications

Felgines, L., Rymen, B., Martins, L.M., Xu, G., Matteoli, C., Himber, C., Zhou, M., Eis, J., Coruh, C., Böhrer, M. and Kuhn, L., 2024. CLSY docking to Pol IV requires a conserved domain critical for small RNA biogenesis and transposon silencing. Nature Communications, 15(1), p.10298.