Reconciling fast Hepatitis B evolutionary rates with ancient co-divergence

Abstract

Estimating evolutionary rates and divergence times for hepatitis B virus (HBV) has long been complicated by conflicting calibration approaches and extensive rate variation. To unlock the full potential of ancient and modern HBV genomic data, we develop a Bayesian mixed-effects molecular clock model that accounts for various sources of rate variation including time-dependent rate decay. Our analyses reveal a pronounced decline in evolutionary rates over time, reconciling HBV divergence estimates with human migration events across both deep and more recent timescales. We show that HBV spread into Europe through both Neolithic farming expansions and later steppe migrations, paralleling patterns proposed for Indo-European language origins. Phylogeographic reconstructions suggest that the Neolithic-associated lineage dispersed at approximately 1 km/year, consistent with archaeological estimates, while genotype D expanded during the Bronze Age at an almost threefold higher rate, plausibly driven by technological innovations underlying steppe expansions. Historical overlap between these lineages facilitated recombination, giving rise to genotype E, which has become a dominant HBV genotype in Africa. These findings demonstrate that ancient viral genomes, when analyzed with models capturing complex rate dynamics, provide a powerful lens on human prehistory and the processes shaping pathogen diversity.

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Cite

BibTeX RIS

BibTeX

@misc{lemey2026reconciling,
  title = {{Reconciling fast Hepatitis B evolutionary rates with ancient co-divergence}},
  author = {Philippe Lemey and Xiang Ji and Bram Vrancken and Magdalini Bletsa and Pratyusa Datta and Liana Eleni Kafetzopoulou and Jonathon Mifsud and Guy Baele and Mahmoud Reza Pourkarim and Livia Patrono and Sebastien Calvignac-Spencer and Ludovic Orlando and Paul Bastide and Stephane Guindon and Darren Martin and Marc Suchard},
  howpublished = {HAL},
  year = {2026},
  month = jun,
  doi = {10.64898/2026.06.05.730483},
  url = {https://hal.science/hal-05774295v1},
  note = {CC BY-NC-ND},
}

RIS

TY  - UNPB
TI  - Reconciling fast Hepatitis B evolutionary rates with ancient co-divergence
AU  - Philippe Lemey
AU  - Xiang Ji
AU  - Bram Vrancken
AU  - Magdalini Bletsa
AU  - Pratyusa Datta
AU  - Liana Eleni Kafetzopoulou
AU  - Jonathon Mifsud
AU  - Guy Baele
AU  - Mahmoud Reza Pourkarim
AU  - Livia Patrono
AU  - Sebastien Calvignac-Spencer
AU  - Ludovic Orlando
AU  - Paul Bastide
AU  - Stephane Guindon
AU  - Darren Martin
AU  - Marc Suchard
PY  - 2026
DA  - 2026/06/08
PB  - HAL
DO  - 10.64898/2026.06.05.730483
UR  - https://hal.science/hal-05774295v1
AB  - Estimating evolutionary rates and divergence times for hepatitis B virus (HBV) has long been complicated by conflicting calibration approaches and extensive rate variation. To unlock the full potential of ancient and modern HBV genomic data, we develop a Bayesian mixed-effects molecular clock model that accounts for various sources of rate variation including time-dependent rate decay. Our analyses reveal a pronounced decline in evolutionary rates over time, reconciling HBV divergence estimates with human migration events across both deep and more recent timescales. We show that HBV spread into Europe through both Neolithic farming expansions and later steppe migrations, paralleling patterns proposed for Indo-European language origins. Phylogeographic reconstructions suggest that the Neolithic-associated lineage dispersed at approximately 1 km/year, consistent with archaeological estimates, while genotype D expanded during the Bronze Age at an almost threefold higher rate, plausibly driven by technological innovations underlying steppe expansions. Historical overlap between these lineages facilitated recombination, giving rise to genotype E, which has become a dominant HBV genotype in Africa. These findings demonstrate that ancient viral genomes, when analyzed with models capturing complex rate dynamics, provide a powerful lens on human prehistory and the processes shaping pathogen diversity.
ER  -

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