Ancient Biomolecules and Evolutionary Inference

Enrico Cappellini; Ana Prohaska; Fernando Racimo; Frido Welker; Mikkel Winther Pedersen; Morten Erik Allentoft; Peter de Barros Damgaard; Petra Gutenbrunner; Julie Dunne; Simon Hammann; Mélanie Roffet-Salque; Melissa Ilardo; José Victor  Moreno Mayar; Yucheng Wang; Martin Sikora; Lasse Vinner; Jürgen Cox; Richard P Evershed; Eske Willerslev

doi:10.1146/annurev-biochem-062917-012002

Ancient Biomolecules and Evolutionary Inference

Enrico Cappellini, Ana Prohaska, Fernando Racimo, Frido Welker, Mikkel Winther Pedersen, Morten Erik Allentoft, Peter de Barros Damgaard, Petra Gutenbrunner, Julie Dunne, Simon Hammann, Mélanie Roffet-Salque, Melissa Ilardo, José Victor Moreno Mayar, Yucheng Wang, Martin Sikora, Lasse Vinner, Jürgen Cox, Richard P Evershed, Eske Willerslev

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Abstract

Over the past three decades, studies of ancient biomolecules - particularly ancient DNA, proteins, and lipids - have revolutionized our understanding 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 spatial 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.

Original language	English
Article number	36
Journal	Annual Review of Biochemistry
Volume	87
Number of pages	32
ISSN	0066-4154
DOIs	https://doi.org/10.1146/annurev-biochem-062917-012002
Publication status	Published - 20 Jun 2018

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Ancient Biomolecules and Evolutionary InferenceFinal published version, 1.73 MBLicence: CC BY

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Cappellini, E., Prohaska, A., Racimo, F., Welker, F., Pedersen, M. W., Allentoft, M. E., Damgaard, P. D. B., Gutenbrunner, P., Dunne, J., Hammann, S., Roffet-Salque, M., Ilardo, M., Moreno Mayar, J. V., Wang, Y., Sikora, M., Vinner, L., Cox, J., Evershed, R. P., & Willerslev, E. (2018). Ancient Biomolecules and Evolutionary Inference. Annual Review of Biochemistry, 87, Article 36. https://doi.org/10.1146/annurev-biochem-062917-012002

Cappellini, E, Prohaska, A, Racimo, F , Welker, F , Pedersen, MW , Allentoft, ME, Damgaard, PDB, Gutenbrunner, P, Dunne, J, Hammann, S, Roffet-Salque, M, Ilardo, M, Moreno Mayar, JV , Wang, Y , Sikora, M , Vinner, L, Cox, J, Evershed, RP & Willerslev, E 2018, 'Ancient Biomolecules and Evolutionary Inference', Annual Review of Biochemistry, vol. 87, 36. https://doi.org/10.1146/annurev-biochem-062917-012002

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title = "Ancient Biomolecules and Evolutionary Inference",

abstract = "Over the past three decades, studies of ancient biomolecules - particularly ancient DNA, proteins, and lipids - have revolutionized our understanding 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 spatial 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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AU - Cappellini, Enrico

AU - Prohaska, Ana

AU - Racimo, Fernando

AU - Welker, Frido

AU - Pedersen, Mikkel Winther

AU - Allentoft, Morten Erik

AU - Damgaard, Peter de Barros

AU - Gutenbrunner, Petra

AU - Dunne, Julie

AU - Hammann, Simon

AU - Roffet-Salque, Mélanie

AU - Ilardo, Melissa

AU - Moreno Mayar, José Victor

AU - Wang, Yucheng

AU - Sikora, Martin

AU - Vinner, Lasse

AU - Cox, Jürgen

AU - Evershed, Richard P

AU - Willerslev, Eske

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AB - Over the past three decades, studies of ancient biomolecules - particularly ancient DNA, proteins, and lipids - have revolutionized our understanding 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 spatial 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.

U2 - 10.1146/annurev-biochem-062917-012002

DO - 10.1146/annurev-biochem-062917-012002

M3 - Journal article

C2 - 29709200

SN - 0066-4154

VL - 87

JO - Annual Review of Biochemistry

JF - Annual Review of Biochemistry

M1 - 36

ER -

Ancient Biomolecules and Evolutionary Inference

Abstract

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