Evolutionary patterns and processes: lessons from ancient DNA

Michela Leonardi; Pablo Librado Sanz; Clio Der Sarkissian; Mikkel Schubert; Ahmed H. Alfarhan; Saleh A. Alquraishi; Khaled A. S. Al-Rasheid; Cristina Gamba; Eske Willerslev; Ludovic Antoine Alexandre Orlando

doi:10.1093/sysbio/syw059

Evolutionary patterns and processes: lessons from ancient DNA

Michela Leonardi, Pablo Librado Sanz, Clio Der Sarkissian, Mikkel Schubert, Ahmed H. Alfarhan, Saleh A. Alquraishi, Khaled A. S. Al-Rasheid, Cristina Gamba, Eske Willerslev, Ludovic Antoine Alexandre Orlando

Research output: Contribution to journal › Journal article › Research › peer-review

70 Citations (Scopus)

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Abstract

Ever since its emergence in 1984, the field of ancient DNA has struggled to overcome the challenges related to the decay of DNA molecules in the fossil record. With the recent development of high-throughput DNA sequencing technologies and molecular techniques tailored to ultra-damaged templates, it has now come of age, merging together approaches in phylogenomics, population genomics, epigenomics, and metagenomics. Leveraging on complete temporal sample series, ancient DNA provides direct access to the most important dimension in evolution-time, allowing a wealth of fundamental evolutionary processes to be addressed at unprecedented resolution. This review taps into the most recent findings in ancient DNA research to present analyses of ancient genomic and metagenomic data. [Ancient DNA; metagenomics; palaeogenomics; population genomics; temporal sampling.].

Original language	English
Article number	syw059
Journal	Systematic Biology
Volume	66
Issue number	1
Pages (from-to)	e1-e29
Number of pages	29
ISSN	1063-5157
DOIs	https://doi.org/10.1093/sysbio/syw059
Publication status	Published - 2017

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10.1093/sysbio/syw059Licence: CC BY-NC

Leonardi_2017_Evolutionary_patternsFinal published version, 1.08 MBLicence: CC BY-NC

Cite this

Evolutionary patterns and processes : lessons from ancient DNA. / Leonardi, Michela; Sanz, Pablo Librado; Der Sarkissian, Clio; Schubert, Mikkel; Alfarhan, Ahmed H.; Alquraishi, Saleh A.; Al-Rasheid, Khaled A. S.; Gamba, Cristina; Willerslev, Eske; Orlando, Ludovic Antoine Alexandre.

In: Systematic Biology, Vol. 66, No. 1, syw059, 2017, p. e1-e29.

Research output: Contribution to journal › Journal article › Research › peer-review

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abstract = "Ever since its emergence in 1984, the field of ancient DNA has struggled to overcome the challenges related to the decay of DNA molecules in the fossil record. With the recent development of high-throughput DNA sequencing technologies and molecular techniques tailored to ultra-damaged templates, it has now come of age, merging together approaches in phylogenomics, population genomics, epigenomics, and metagenomics. Leveraging on complete temporal sample series, ancient DNA provides direct access to the most important dimension in evolution-time, allowing a wealth of fundamental evolutionary processes to be addressed at unprecedented resolution. This review taps into the most recent findings in ancient DNA research to present analyses of ancient genomic and metagenomic data. [Ancient DNA; metagenomics; palaeogenomics; population genomics; temporal sampling.].",

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AU - Alquraishi, Saleh A.

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AU - Orlando, Ludovic Antoine Alexandre

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AB - Ever since its emergence in 1984, the field of ancient DNA has struggled to overcome the challenges related to the decay of DNA molecules in the fossil record. With the recent development of high-throughput DNA sequencing technologies and molecular techniques tailored to ultra-damaged templates, it has now come of age, merging together approaches in phylogenomics, population genomics, epigenomics, and metagenomics. Leveraging on complete temporal sample series, ancient DNA provides direct access to the most important dimension in evolution-time, allowing a wealth of fundamental evolutionary processes to be addressed at unprecedented resolution. This review taps into the most recent findings in ancient DNA research to present analyses of ancient genomic and metagenomic data. [Ancient DNA; metagenomics; palaeogenomics; population genomics; temporal sampling.].

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