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Optimized Bone Sampling Protocols for the Retrieval of Ancient DNA from Archaeological Remains
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Ancient Biomolecules and Evolutionary Inference.

Enrico Cappellini1, Ana Prohaska2, Fernando Racimo1

  • 1Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen, Denmark; email: ecappellini@snm.ku.dk , ewillerslev@snm.ku.dk.

Annual Review of Biochemistry
|May 1, 2018
PubMed
Summary
This summary is machine-generated.

Ancient biomolecule research, including DNA, proteins, and lipids, has advanced significantly over 30 years. Modern techniques enable retrieval from challenging environments, revolutionizing evolutionary history studies.

Keywords:
ancient DNAancient genomicsancient lipidsancient proteinspaleogenomicspaleoproteomics

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Area of Science:

  • Paleogenomics
  • Paleoproteomics
  • Paleolipidomics

Background:

  • Ancient biomolecule studies, including DNA, proteins, and lipids, have overcome initial challenges.
  • The field has expanded in sampling scope, data quality, and geographic reach.
  • Progress relies on technical innovations, improved sample selection, and computational methods.

Purpose of the Study:

  • To review the history and current status of ancient biomolecule research.
  • To highlight applications in evolutionary inference.
  • To discuss future directions in the field.

Main Methods:

  • Retrieval of ancient DNA, protein sequences, and lipid signatures.
  • Analysis of samples from diverse and challenging depositional environments.
  • Integration of advanced analytical and computational approaches.

Main Results:

  • Successful retrieval of biomolecules from progressively older and more challenging samples.
  • Increased sampling frequencies and spatial/temporal scope of studies.
  • Generation of larger and higher-quality datasets for evolutionary research.

Conclusions:

  • Ancient biomolecule research is now a robust field.
  • Technological advancements have enabled significant progress in understanding evolutionary history.
  • The field holds exciting future potential for evolutionary inference.