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

Mondal, Mayukh, 1989-; Bertranpetit, Jaume, 1952-; Lao Grueso, Oscar, 1976-

doi:http://dx.doi.org/10.1038/s41467-018-08089-7

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

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Mondal M, Bertranpetit J, Lao O. Approximate Bayesian computation with deep learning supports a third archaic introgression in Asia and Oceania. Nat Commun. 2019;10(1):246. DOI 10.1038/s41467-018-08089-7

Abstract

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.