Statistical inference of virus evolution using ancestral recombination graphs

Abstract

Ancestral recombination graphs (ARGs) represent the coalescent history at every locus in the genome, subject to mutation and recombination. Modelling viruses using the coalescent with recombination remains less explored, due to the potential for complex, multi-scale dynamics. Using perturbative methods, we establish mathematical bounds that describe the balance between inter-host and within-host coalescence, and demonstrate that the highly-recombinant Epstein-Barr Virus (EBV) coalesces predominantly at the inter-host level. We then modify SINGER, a tool from diploid genetics, for haploid ARG inference with fine-grained variable recombination rates. We provide insight into the paradox of high recombination rates and slow linkage disequilibrium decay, as ARG-based methods potentially allow us to disentangle epistatic effects from shared ancestry, and illustrate this using the coalescent topologies of EBV’s host cell-entry glycoproteins. Our findings demonstrate that ARG-based methods recover gene-level selective structure, and provide a general method for analysing virus phylodynamics in the limit of small quantities.