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Extremely Rare Interbreeding Events Can Explain Neanderthal DNA in Living Humans

Overview of attention for article published in PLOS ONE, October 2012
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Title
Extremely Rare Interbreeding Events Can Explain Neanderthal DNA in Living Humans
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0047076
Pubmed ID
Authors

Armando G. M. Neves, Maurizio Serva

Abstract

Considering the recent experimental discovery of Green et al that present-day non-Africans have 1 to [Formula: see text] of their nuclear DNA of Neanderthal origin, we propose here a model which is able to quantify the genetic interbreeding between two subpopulations with equal fitness, living in the same geographic region. The model consists of a solvable system of deterministic ordinary differential equations containing as a stochastic ingredient a realization of the neutral Wright-Fisher process. By simulating the stochastic part of the model we are able to apply it to the interbreeding of the African ancestors of Eurasians and Middle Eastern Neanderthal subpopulations and estimate the only parameter of the model, which is the number of individuals per generation exchanged between subpopulations. Our results indicate that the amount of Neanderthal DNA in living non-Africans can be explained with maximum probability by the exchange of a single pair of individuals between the subpopulations at each 77 generations, but larger exchange frequencies are also allowed with sizeable probability. The results are compatible with a long coexistence time of 130,000 years, a total interbreeding population of order [Formula: see text] individuals, and with all living humans being descendants of Africans both for mitochondrial DNA and Y chromosome.

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Geographical breakdown

Country Count As %
United States 4 3%
United Kingdom 3 2%
Germany 2 1%
Netherlands 1 <1%
France 1 <1%
Brazil 1 <1%
Portugal 1 <1%
Canada 1 <1%
Switzerland 1 <1%
Other 2 1%
Unknown 117 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 26%
Student > Bachelor 24 18%
Student > Ph. D. Student 23 17%
Student > Master 10 7%
Professor > Associate Professor 9 7%
Other 23 17%
Unknown 10 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 36%
Arts and Humanities 30 22%
Social Sciences 14 10%
Biochemistry, Genetics and Molecular Biology 11 8%
Psychology 3 2%
Other 13 10%
Unknown 15 11%