title: The utility of ancient human DNA for improving allele age estimates, with implications for demographic models and tests of natural selection.
abstract: The age of polymorphic alleles in humans is often estimated from population genetic patterns in extant human populations, such as allele frequencies, linkage disequilibrium, and rate of mutations. Ancient DNA can improve the accuracy of such estimates, as well as facilitate testing the validity of demographic models underlying many population genetic methods. Specifically, the presence of an allele in a genome derived from an ancient sample testifies that the allele is at least as old as that sample. In this study, we consider a common method for estimating allele age based on allele frequency as applied to variants from the US National Institutes of Health (NIH) Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project. We view these estimates in the context of the presence or absence of each allele in the genomes of the 5300 year old Tyrolean Iceman, Ötzi, and of the 50,000 year old Altai Neandertal. Our results illuminate the accuracy of these estimates and their sensitivity to demographic events that were not included in the model underlying age estimation. Specifically, allele presence in the Iceman genome provides a good fit of allele age estimates to the expectation based on the age of that specimen. The equivalent based on the Neandertal genome leads to a poorer fit. This is likely due in part to the older age of the Neandertal and the older time of the split between modern humans and Neandertals, but also due to gene flow from Neandertals to modern humans not being considered in the underlying demographic model. Thus, the incorporation of ancient DNA can improve allele age estimation, demographic modeling, and tests of natural selection. Our results also point to the importance of considering a more diverse set of ancient samples for understanding the geographic and temporal range of individual alleles.
authors.affiliation: Department of Anthropology, University of Wisconsin-Madison, Madison, WI, USA; Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, USA. Electronic address: as2847@cornell.edu.
authors.forename: Aaron J
authors.initials: AJ
authors.lastname: Sams
authors.affiliation: Department of Anthropology, University of Wisconsin-Madison, Madison, WI, USA.
authors.forename: John
authors.initials: J
authors.lastname: Hawks
authors.affiliation: Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, USA.
authors.forename: Alon
authors.initials: A
authors.lastname: Keinan
mesh_terms: D000818:Animals; D000885:Anthropology, Physical; D004247:DNA / Q000032:analysis / Q000235:genetics*; D005060:Europe; D019143:Evolution, Molecular; D005828:Genetics, Population / Q000379:methods*; D006801:Humans; D008297:Male; D059125:Neanderthals / Q000235:genetics*; D012641:Selection, Genetic
chemical_list: D004247:DNA
keywords: Europe; Neandertals; Ötzi