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Empirical calibrated radiocarbon sampler: a tool for incorporating radiocarbon-date and calibration error into Bayesian phylogenetic analyses of ancient DNA

Authors

  • Martyna Molak,

    Corresponding author
    1. School of Biological Sciences, University of Sydney, Sydney, NSW, Australia
    2. Museum and Institute of Zoology, Polish Academy of Sciences, Warsaw, Poland
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  • Marc A. Suchard,

    1. Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA
    2. Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
    3. Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA
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  • Simon Y. W. Ho,

    1. School of Biological Sciences, University of Sydney, Sydney, NSW, Australia
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  • David W. Beilman,

    1. Department of Geography, University of Hawaii, Honolulu, HI, USA
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  • Beth Shapiro

    1. Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA, USA
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Abstract

Studies of DNA from ancient samples provide a valuable opportunity to gain insight into past evolutionary and demographic processes. Bayesian phylogenetic methods can estimate evolutionary rates and timescales from ancient DNA sequences, with the ages of the samples acting as calibrations for the molecular clock. Sample ages are often estimated using radiocarbon dating, but the associated measurement error is rarely taken into account. In addition, the total uncertainty quantified by converting radiocarbon dates to calendar dates is typically ignored. Here, we present a tool for incorporating both of these sources of uncertainty into Bayesian phylogenetic analyses of ancient DNA. This empirical calibrated radiocarbon sampler (ECRS) integrates the age uncertainty for each ancient sequence over the calibrated probability density function estimated for its radiocarbon date and associated error. We use the ECRS to analyse three ancient DNA data sets. Accounting for radiocarbon-dating and calibration error appeared to have little impact on estimates of evolutionary rates and related parameters for these data sets. However, analyses of other data sets, particularly those with few or only very old radiocarbon dates, might be more sensitive to using artificially precise sample ages and should benefit from use of the ECRS.

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