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  Ancient biomolecules and evolutionary inference

Cappellini, E., Prohaska, A., Racimo, F., Welker, F., Pedersen, M. W., Allentoft, M. E., et al. (2018). Ancient biomolecules and evolutionary inference. Annual Review of Biochemistry, 87, 1029-1060. doi:10.1146/annurev-biochem-062917-012002.

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annurev-biochem-062917-012002.pdf (Publisher version), 2MB
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© 2018 Enrico Cappellini et al.

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 Creators:
Cappellini, Enrico, Author
Prohaska, Ana, Author
Racimo, Fernando, Author
Welker, Frido, Author
Pedersen, Mikkel Winther, Author
Allentoft, Morten E., Author
Damgaard, Peter de Barros, Author
Gutenbrunner, Petra1, Author              
Dunne, Julie, Author
Hammann, Simon, Author
Roffet-Salque, Melanie, Author
Ilardo, Melissa, Author
Moreno-Mayar, J. Victor, Author
Wang, Yucheng, Author
Sikora, Martin, Author
Vinner, Lasse, Author
Cox, Jürgen1, Author              
Evershed, Richard P., Author
Willerslev, Eske, Author
Affiliations:
1Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_2063284              

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Free keywords: ancient DNA; ancient genomics; paleogenomics; ancient proteins; ancient lipids; paleoproteomics
 Abstract: Over the past three decades, studies of ancient biomolecules—particularly ancient DNA, proteins, and lipids—have revolutionized our understand- ing of evolutionary history. Though initially fraught with many challenges, today the field stands on firm foundations. Researchers now successfully retrieve nucleotide and amino acid sequences, as well as lipid signatures, from progressively older samples, originating from geographic areas and depositional environments that, until recently, were regarded as hostile to long-term preservation of biomolecules. Sampling frequencies and the spa- tial and temporal scope of studies have also increased markedly, and with them the size and quality of the data sets generated. This progress has been made possible by continuous technical innovations in analytical methods, enhanced criteria for the selection of ancient samples, integrated experimental methods, and advanced computational approaches. Here, we discuss the history and current state of ancient biomolecule research, its applications to evolutionary inference, and future directions for this young and exciting field.

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Language(s): eng - English
 Dates: 2018-04-252018-06
 Publication Status: Published in print
 Pages: 36
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Degree: -

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Title: Annual Review of Biochemistry
Source Genre: Journal
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Publ. Info: Palo Alto, Calif. : Stanford University Press
Pages: - Volume / Issue: 87 Sequence Number: - Start / End Page: 1029 - 1060 Identifier: ISSN: 0066-4154
CoNE: https://pure.mpg.de/cone/journals/resource/954925458038