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Mining Metagenomic Data Sets for Ancient DNA: Recommended Protocols for Authentication

Key, Felix M., Posth, Cosimo, Krause, Johannes, Herbig, Alexander, Bos, Kirsten I.·2017·Trends in Genetics
DOI 10.1016/j.tig.2017.05.005
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Abstract

While a comparatively young area of research, investigations relying on ancient DNA data have been highly valuable in revealing snapshots of genetic variation in both the recent and the not-so-recent past. Born out of a tradition of single-locus PCR-based approaches that often target individual species, stringent criteria for both data acquisition and analysis were introduced early to establish high standards of data quality. Today, the immense volume of data made available through next-generation sequencing has significantly increased the analytical resolution offered by processing ancient tissues and permits parallel analyses of host and microbial communities. The adoption of this new approach to data acquisition, however, requires an accompanying update on methods of DNA authentication, especially given that ancient molecules are expected to exist in low proportions in archaeological material, where an environmental signal is likely to dominate. In this review, we provide a summary of recent data authentication approaches that have been successfully used to distinguish between endogenous and nonendogenous DNA sequences in metagenomic data sets. While our discussion mostly centers on the detection of ancient human and ancient bacterial pathogen DNA, their applicability is far wider.

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  • eDNA has provided insights into spatial and temporal distribution of animal species, including extinct hominins, and impact of global climatic change.

    “Environmental DNA has also provided insights into the spatial and temporal distribution of animal species, including extinct hominins 49 , and the impact of global climatic change 22,48,90,91,328 .”

    From Ancient DNA analysis (2021) · cites this paper as [328]

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Metadata

Authors
Key, F. M., Posth, C., Krause, J., Herbig, A., & Bos, K. I.
Venue
Trends in Genetics
Publisher
Elsevier BV
Published
2017-08
Volume
33
Issue
8
Pages
508-520
ISSN
0168-9525
DOI
10.1016/j.tig.2017.05.005
Cited by
118
References
28
Language
en
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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