MBE Advance Access published online on November 11, 2008
Molecular Biology and Evolution, doi:10.1093/molbev/msn256
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Letter |
Accommodating the effect of ancient DNA damage on inferences of demographic histories
1 Institute of Evolutionary Biology, University of Edinburgh, King's Buildings, Edinburgh, EH9 3JT, UK
2 Centre for Macroevolution and Macroecology, School of Botany and Zoology, Australian National University, Canberra ACT 0200, Australia
3 Department of Computer Science, University of Auckland, Auckland, NZ
4 Department of Biology, The Pennsylvania State University, University Park, PA, 16802, USA
Corresponding Author: Andrew Rambaut, Institute of Evolutionary Biology, University of Edinburgh, King's Buildings, Edinburgh, EH9 3JT, UK., Tel.: +44 131 6508624, Email: a.rambaut{at}ed.ac.uk
Accepted for publication September 30, 2008.
DNA sequences extracted from ancient remains are increasingly used to generate large population data sets, often spanning tens of thousands of years of population history. Bayesian coalescent methods such as those implemented in the software package BEAST can be used to estimate the demographic history of these populations, sometimes resulting in complex scenarios of fluctuations in population size, which can be correlated with the timing of environmental events, such as glaciations. Recently, however, Axelsson et al. (2008) claimed that many of these complex demographic trends are likely to be the result of post-mortem DNA damage, a problem that they investigate by removing all sites involving transitions from ancient sequences prior to analysis. When this solution is applied to a previously published data set of Pleistocene bison, they show that the demographic signal of population expansion and decline disappears. While some apparently segregating mutations in ancient sequences may be due to post-mortem damage, we argue that discarding the data will result in loss of power to detect patterns of population change. Instead, to accommodate this problem, we implement a model in which sequences are the result of a joint process of molecular evolution and post-mortem DNA damage within a probabilistic inference framework. Through simulation, we demonstrate the ability of this model to accurately recover evolutionary parameters, demographic history and DNA damage rates. When this model is applied to the bison data set, we find that the rate of DNA damage is significant but low, and that the reconstruction of population size history is nearly identical to previously published estimates.
Key Words: ancient DNA • demographic history • coalescent • Bayesian MCMC