Genomic fossils calibrate the long-term evolution of hepadnaviruses.

Because most extant viruses mutate rapidly and lack a true fossil record, their deep evolution and long-term substitution rates remain poorly understood. In addition to retroviruses, which rely on chromosomal integration for their replication, many other viruses replicate in the nucleus of their host's cells and are therefore prone to endogenization, a process that involves integration of viral DNA into the host's germline genome followed by long-term vertical inheritance. Such endogenous viruses are highly valuable as they provide a molecular fossil record of past viral invasions, which may be used to decipher the origins and long-term evolutionary characteristics of modern pathogenic viruses. Hepadnaviruses (Hepadnaviridae) are a family of small, partially double-stranded DNA viruses that include hepatitis B viruses. Here we report the discovery of endogenous hepadnaviruses in the genome of the zebra finch. We used a combination of cross-species analysis of orthologous insertions, molecular dating, and phylogenetic analyses to demonstrate that hepadnaviruses infiltrated repeatedly the germline genome of passerine birds. We provide evidence that some of the avian hepadnavirus integration events are at least 19 My old, which reveals a much deeper ancestry of Hepadnaviridae than could be inferred based on the coalescence times of modern hepadnaviruses. Furthermore, the remarkable sequence similarity between endogenous and extant avian hepadnaviruses (up to 75% identity) suggests that long-term substitution rates for these viruses are on the order of 10(-8) substitutions per site per year, which is a 1,000-fold slower than short-term rates estimated based on the sequences of circulating hepadnaviruses. Together, these results imply a drastic shift in our understanding of the time scale of hepadnavirus evolution, and suggest that the rapid evolutionary dynamics characterizing modern avian hepadnaviruses do not reflect their mode of evolution on a deep time scale.