Statistical evaluation of alternative models of human evolution

Fagundes, Nelson; Ray, Nicolas; Beaumont, Mark; Neuenschwander, Samuel; Salzano, Francisco; Bonatto, Sandro; Excoffier, Laurent (2007). Statistical evaluation of alternative models of human evolution. Proceedings of the National Academy of Sciences of the United States of America - PNAS, 104(45), pp. 17614-17619. Washington, D.C.: National Academy of Sciences NAS 10.1073/pnas.0708280104

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An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species approximately 141 thousand years ago (Kya), an exit out-of-Africa approximately 51 Kya, and a recent colonization of the Americas approximately 10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Biology > Institute of Ecology and Evolution (IEE) > Population Genetics

UniBE Contributor:

Excoffier, Laurent

ISSN:

0027-8424

Publisher:

National Academy of Sciences NAS

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:58

Last Modified:

05 Dec 2022 14:17

Publisher DOI:

10.1073/pnas.0708280104

Web of Science ID:

000250897600015

URI:

https://boris.unibe.ch/id/eprint/24782 (FactScience: 52943)

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