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Mol Biol Evol. 2012 Feb;29(2):617-30. doi: 10.1093/molbev/msr212. Epub 2011 Sep 1.

An early divergence of KhoeSan ancestors from those of other modern humans is supported by an ABC-based analysis of autosomal resequencing data.

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Arizona Research Laboratories Division of Biotechnology, University of Arizona, Arizona, USA.


Sub-Saharan Africa has consistently been shown to be the most genetically diverse region in the world. Despite the fact that a substantial portion of this variation is partitioned between groups practicing a variety of subsistence strategies and speaking diverse languages, there is currently no consensus on the genetic relationships of sub-Saharan African populations. San (a subgroup of KhoeSan) and many Pygmy groups maintain hunter-gatherer lifestyles and cluster together in autosomal-based analysis, whereas non-Pygmy Niger-Kordofanian speakers (non-Pygmy NKs) predominantly practice agriculture and show substantial genetic homogeneity despite their wide geographic range throughout sub-Saharan Africa. However, KhoeSan, who speak a set of relatively unique click-based languages, have long been thought to be an early branch of anatomically modern humans based on phylogenetic analysis. To formally test models of divergence among the ancestors of modern African populations, we resequenced a sample of San, Eastern, and Western Pygmies and non-Pygmy NKs individuals at 40 nongenic (∼2 kb) regions and then analyzed these data within an Approximate Bayesian Computation (ABC) framework. We find substantial support for a model of an early divergence of KhoeSan ancestors from a proto-Pygmy-non-Pygmy NKs group ∼110 thousand years ago over a model incorporating a proto-KhoeSan-Pygmy hunter-gatherer divergence from the ancestors of non-Pygmy NKs. The results of our analyses are consistent with previously identified signals of a strong bottleneck in Mbuti Pygmies and a relatively recent expansion of non-Pygmy NKs. We also develop a number of methodologies that utilize "pseudo-observed" data sets to optimize our ABC-based inference. This approach is likely to prove to be an invaluable tool for demographic inference using genome-wide resequencing data.

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