Approximate Bayesian computation with deep learning supports a third archaic introgression in Asia and Oceania.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
16 01 2019
16 01 2019
Historique:
received:
13
07
2018
accepted:
12
12
2018
entrez:
18
1
2019
pubmed:
18
1
2019
medline:
18
1
2019
Statut:
epublish
Résumé
Since anatomically modern humans dispersed Out of Africa, the evolutionary history of Eurasian populations has been marked by introgressions from presently extinct hominins. Some of these introgressions have been identified using sequenced ancient genomes (Neanderthal and Denisova). Other introgressions have been proposed for still unidentified groups using the genetic diversity present in current human populations. We built a demographic model based on deep learning in an Approximate Bayesian Computation framework to infer the evolutionary history of Eurasian populations including past introgression events in Out of Africa populations fitting the current genetic evidence. In addition to the reported Neanderthal and Denisovan introgressions, our results support a third introgression in all Asian and Oceanian populations from an archaic population. This population is either related to the Neanderthal-Denisova clade or diverged early from the Denisova lineage. We propose the use of deep learning methods for clarifying situations with high complexity in evolutionary genomics.
Identifiants
pubmed: 30651539
doi: 10.1038/s41467-018-08089-7
pii: 10.1038/s41467-018-08089-7
pmc: PMC6335398
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Pagination
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