Tag: Prehistory

The great Eurasian explosion

By Razib Khan | September 17, 2012 9:38 pm

Dr. Joseph Pickrell has updated his preprint, The genetic prehistory of southern Africa, with some more material on the Sandawe. I’ve explored the genetics of the Sandawe a bit using ADMIXTURE, so I jumped straight to the section on ROLLOFF:

…To further examine this, we turned to ROLLOFF. We used Dinka and French as representatives of the mixing populations (since date estimates are robust to improperly specified reference populations). The results are shown in Supplementary Figure S22. Both populations show a detectable curve, though the signal is much stronger in the Sandawe than in the Hadza. The implied dates are 89 generations (2500 years) ago for the Hadza and 66 generations (2000 years) ago for the Sandawe. These are qualitatively similar signals to those seen by Pagani et al. [65] in Ethiopian populations. There are two possible historical scenarios that could lead to these signals: either the Hadza and Sandawe both directly admixed with a western Eurasian population about 2,000 years ago, or they admixed with an east African population that was itself admixed with a western Eurasian population. The latter possibility would be consistent with known east African admixture into the Sandawe [16] .

 

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CATEGORIZED UNDER: Genetics, Genomics

Live not by visualization alone

By Razib Khan | December 13, 2010 1:54 am

pc1
Synthetic map

In the age of 500,000 SNP studies of genetic variation across dozens of populations obviously we’re a bit beyond lists of ABO blood frequencies. There’s no real way that a conventional human is going to be able to discern patterns of correlated allele frequency variations which point to between population genetic differences on this scale of marker density. So you rely on techniques which extract the general patterns out of the data, and present them to you in a human-comprehensible format. But, there’s an unfortunate tendency for humans to imbue the products of technique with a particular authority which they always should not have.

ResearchBlogging.orgThe History and Geography of Human Genes is arguably the most important historical genetics work of the past generation. It has surely influenced many within the field of genetics, and because of its voluminous elegant visual displays of genetic data it is also a primary source for those outside of genetics to make sense of phylogenetic relations between human populations. And yet one aspect of this great work which never caught on was the utilization of “synthetic maps” to visualize components of genetic variation between populations. This may have been fortuitous, a few years ago a paper was published, Interpreting principal components analyses of spatial population genetic variation, which suggested that the gradients you see on the map above may be artifacts:

Nearly 30 years ago, Cavalli-Sforza et al. pioneered the use of principal component analysis (PCA) in population genetics and used PCA to produce maps summarizing human genetic variation across continental regions. They interpreted gradient and wave patterns in these maps as signatures of specific migration events. These interpretations have been controversial, but influential, and the use of PCA has become widespread in analysis of population genetics data. However, the behavior of PCA for genetic data showing continuous spatial variation, such as might exist within human continental groups, has been less well characterized. Here, we find that gradients and waves observed in Cavalli-Sforza et al.’s maps resemble sinusoidal mathematical artifacts that arise generally when PCA is applied to spatial data, implying that the patterns do not necessarily reflect specific migration events. Our findings aid interpretation of PCA results and suggest how PCA can help correct for continuous population structure in association studies.

A paper earlier this year took the earlier work further and used a series of simulations to show how the nature of the gradients varied. In light of recent preoccupations the results are of interest. Principal Component Analysis under Population Genetic Models of Range Expansion and Admixture:

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CATEGORIZED UNDER: Genetics, Genomics, History
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