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  Detecting ancient positive selection in humans using extended lineage sorting

Peyrégne, S., Dannemann, M., & Prüfer, K. (2017). Detecting ancient positive selection in humans using extended lineage sorting. Genome Research, 27(9), 1563-1572. doi:10.1101/gr.219493.116.

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Peyregne_Detecting_GenRes_2017.pdf (Preprint), 3MB
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Peyregne_Detecting_GenRes_2017.pdf
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This manuscript is Open Access.This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International license), as described at http://creativecommons.org/licenses/by/4.0/.

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 Creators:
Peyrégne, Stéphane1, 2, 3, Author           
Dannemann, Michael2, 4, Author           
Prüfer, Kay2, 3, Author           
Affiliations:
1The Leipzig School of Human Origins (IMPRS), Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_1497688              
2Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_1497672              
3Genomes, Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_2074331              
4The Minerva Research Group for Bioinformatics, Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_2074303              

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 Abstract: Natural selection that affected modern humans early in their evolution has likely shaped some of the traits that set present-day humans apart from their closest extinct and living relatives. The ability to detect ancient natural selection in the human genome could provide insights into the molecular basis for these human-specific traits. Here, we introduce a method for detecting ancient selective sweeps by scanning for extended genomic regions where our closest extinct relatives, Neandertals and Denisovans, fall outside of the present-day human variation. Regions that are unusually long indicate the presence of lineages that reached fixation in the human population faster than expected under neutral evolution. Using simulations we show that the method is able to detect ancient events of positive selection and that it can differentiate those from background selection. Applying our method to the 1000 genomes dataset, we find evidence for ancient selective sweeps favoring regulatory changes in the brain and present a list of genomic regions that are predicted to underlie positively selected human specific traits.

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Language(s): eng - English
 Dates: 2017-07-182017-09
 Publication Status: Issued
 Pages: 11
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1101/gr.219493.116
 Degree: -

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Title: Genome Research
Source Genre: Journal
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Publ. Info: Cold Spring Harbor, N.Y. : Cold Spring Harbor Laboratory Press
Pages: - Volume / Issue: 27 (9) Sequence Number: - Start / End Page: 1563 - 1572 Identifier: ISSN: 1088-9051
CoNE: https://pure.mpg.de/cone/journals/resource/954926997202