Recent advances in the inference of deep viral evolutionary history.

The rapid rate of virus evolution, while useful for outbreak investigations, poses a challenge for accurately estimating long-term viral evolutionary divergence and leaves us with little genomic traces at deep evolutionary timescales, complicating the reconstruction of deep virus evolutionary history. Recent advancements in protein structure prediction and computational biology have opened up new avenues and enabled us to peer back further in time and with greater clarity than ever before. Here, we review recent approaches to reconstructing the deep evolutionary history of viruses. In particular, we focus on how Bayesian models that account for evolutionary rates that are time-dependent may provide better estimates of the timescale of virus evolution. We then outline approaches to structural phylogenetics and their application to reconstructing the evolutionary history of viruses. Despite current limitations, including structural prediction uncertainty, conformational variation, and limited benchmarking, structural phylogenetics appears promising, particularly where sequence-level homology is eroded. The availability of and ease with which virus structures can now be predicted is likely to drive additional statistical and software developments in this area. Ultimately, answering fundamental questions of virus origins and early diversification, long-term host associations, virus classification, and the timescale of viral diseases will likely require unifying sequence and structural information into a temporally aware evolutionary inference framework.