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

2019/01/10 by Mayukh Mondal, Jaume Bertranpetit, Óscar Lao · 1 citation
Biochemistry, Genetics and Molecular Biology · Arts and Humanities · #Forensic and Genetic Research #Forensic Anthropology and Bioarchaeology Studies #Genetic diversity and population structure #Introgression #Neanderthal #Approximate Bayesian computation #Lineage (genetic) #Evolutionary biology #Clade #Biology #Population #Phylogenetic tree #Population genomics #Demographic history #Genome #Genomics #Geography #Genetic variation #Genetics #Gene #Demography #Archaeology

paper · pdf · doi:10.1038/s41467-018-08089-7

openalex publication_date 2019/01/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

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.

Citations

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Cited by

• Homo [wikipedia]