Approximate Bayesian computation with deep learning supports a third archaic introgression in Asia and Oceania

Bibliographic Collection: 
Publication Type: Journal Article
Authors: Mondal, Mayukh; Bertranpetit, Jaume; Lao, Oscar
Year of Publication: 2019
Journal: Nature Communications
Volume: 10
Issue: 1
Pagination: 246
Date Published: 2019/01/16
Publication Language: eng
ISBN Number: 2041-1723

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.

Short Title: Nature Communications