Asymmetric Phylogenetic costs and their application in coevolutionary analysis

Coevolutionary studies aim to characterize symbiotic interactions by using phylogenetic distances to evaluate the topological discordance between the phylogenies of interacting taxa. However, traditional phylogenetic distances are not ideal for capturing asymmetrical relationships that can arise from biological factors, such as differences in evolutionary rates, or systematic factors, such as variations in sampling. To address these limitations, we introduced the Asymmetric Cluster Affinity (ACA) and Asymmetric Cluster Support (ACS) costs to quantify and represent asymmetrical phylogenetic relationships.

In our research, we provide exact solutions for calculating the diameter of the ACA and ACS costs and discuss the differences in direction when comparing two trees. Additionally, we explore the ACA Supertree problem and develop efficient local search algorithms leveraging tree-edit operations. We further apply these costs to biological data to detect coevolutionary signals between viruses and their hosts, as well as within virus genomes. Finally, we discuss potential future applications and theoretical extensions of these costs based on our findings.

Committee: Oliver Eulenstein (major professor), Tavis Anderson (major professor), Xiaoqiu Huang, Samik Basu (Substitute for Pavan Aduri) and Karin Dorman