Updated Bayesian ancestry analysis software

Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations.

BMC Bioinformatics. 2008 Dec 16;9(1):539

Authors: Corander J, Marttinen P, Siren J, Tang J

ABSTRACT: BACKGROUND: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions. RESULTS: We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software. CONCLUSIONS: The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at http://web.abo.fi/fak/mnf//mate/jc/software/baps.html.

PMID: 19087322 [PubMed - as supplied by publisher]

[link]

Sex, race, and selection for height

A few papers relating to a conversation I'm not particularly interested in. For the record, in the West:
Selection worked strongly in favor of very tall men, not just against short men. Since there were no hints of any evolutionary check on this selection, these findings suggest unconstrained directional selection for tallness in men. [Evidence of unconstrained directional selection for male tallness]
And:
Height was weakly but significantly related to reproductive success [among women]. The relationship was U-shaped, with deficits at the extremes of height. This pattern was largely due to poor health among extremely tall and extremely short women. However, the maximum reproductive success was found below the mean height for women. Thus, selection appears to be sexually disruptive in this population, favouring tall men and short women. Over evolutionary time, such a situation tends to maintain sexual dimorphism. Men do not use stature as a positive mate-choice criterion as women do. It is argued that there is good evolutionary reason for this, because men are orientated towards cues of fertility, and female height, being positively related to age of sexual maturity, is not such a cue. [Women's height, reproductive success and the evolution of sexual dimorphism in modern humans]
Whereas, in Africa:
In Western societies, height is positively correlated with reproductive success (RS) for men but negatively correlated with RS for women. These relationships have been attributed to sexual selection: women prefer tall men, and men prefer short women. It is this success in the marriage market which leads to higher RS for tall men and short women. We have already shown that the relationship between height and RS for women is quite different in a non-Western context. In a subsistence farming community in rural Gambia, height is positively correlated with reproductive success for women, largely owing to the higher survival of the children of tall women. Here, the relationship between height and reproductive success is analyzed for men in the same community. For these Gambian men, there is no significant relationship between height and the number of children they produce, although tall men do contract more marriages than shorter men. We conclude that environmental context needs to be taken into account when analyzing human reproductive behavior. [Height and reproductive success: How a Gambian population compares with the west]

Society for Nordish Physical Anthropology: new URL

The SNPA website is now located at:

http://www.theapricity.com/snpa/

The domain also hosts a new forum, from the people who used to run The Nordish Portal.

Geographic population structure in Britain

This 2007 genome-wide SNP study provides some information on geographic population structure in Britain.
 Thirteen genomic regions showing strong geographical variation are listed in Table 1, and Supplementary Fig. 7 shows the way in which their allele frequencies vary geographically. The predominant pattern is variation along a NW/SE axis. The most likely cause for these marked geographical differences is natural selection, most plausibly in populations ancestral to those now in the UK. Variation due to selection has previously been implicated at LCT (lactase) and major histocompatibility complex(MHC)7–9, and within-UK differentiation at 4p14 has been found independently10, but others seem to be new findings. All but three of the regions contain known genes. Aside from evolutionary interest, genes showing evidence of natural selection are particularly interesting for the biology of traits such as infectious diseases; possible targets for selection include NADSYN1 (NAD synthetase 1) at 11q13, which could have a role in prevention of pellagra, as well as TLR1 (toll-like receptor 1) at 4p14, for which a role in the biology of tuberculosis and leprosy has been suggested10.

There may be important population structure that is not well captured by current geographical region of residence. Present implementations of strongly model-based approaches such as STRUCTURE11,12 are impracticable for data sets of this size, and we reverted to the classical method of principal components13,14, using a subset of 197,175 SNPs chosen to reduce inter-locus linkage disequilibrium. Nevertheless, four of the first six principal components clearly picked up effects attributable to local linkage disequilibrium rather than genome-wide structure. The remaining two components show the same predominant geographical trend from NW to SE but, perhaps unsurprisingly, London is set somewhat apart (Supplementary Fig. 8).

[The Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661-678 (7 June 2007) | doi:10.1038/nature05911]
  
 
A later study ("Investigation of the fine structure of European populations with applications to disease association studies") finds 11 of these 13 SNPs are also "involved in East–West and North–South gradients covering all of Europe".
 
I'd prefer to see Scotland broken down by region -- I'd expect Lowlanders to be more similar to northern English. Ignoring London and Scotland, we see a continuum with East Anglia on one end and Wales on the other, consistent with the major trend detected here being varying proportions of continental Germanic and indigenous British ancestry.

Related: Genetic differentiation in the UK

Balls and brains

That's The Economist's headline:
The quality of a man’s sperm depends on how intelligent he is, and vice versa

THERE are few better ways of upsetting a certain sort of politically correct person than to suggest that intelligence (or, rather, the variation in intelligence between individuals) is under genetic control. That, however, is one implication of a paper about to be published in Intelligence by Rosalind Arden of King’s College, London, and her colleagues. Another is that brainy people are intrinsically healthier than those less intellectually endowed. And the third, a consequence of the second, is that intelligence is sexy. The most surprising thing of all, though, is that these results have emerged from an unrelated study of the quality of men’s sperm.

[. . .]

Ms Arden found 425 cases where samples had been collected and analysed from unvasectomised men who had managed to avoid spilling their seed during the collection process and had answered all the necessary questions for her to test her hypothesis, namely that their g values would correlate with all three measures of their sperm quality.

They did. Moreover, neither age nor any obvious confounding variable that might have been a consequence of intelligent decisions about health (obesity, smoking, drinking and drug use) had any effect on the result. Brainy men, it seems, do have better sperm.

By implication, therefore, they have fitter bodies over all, at least in the Darwinian sense of fitness, namely the ability to survive, to attract mates and to produce offspring. That is an important finding. Hitherto, biologists have tended to disaggregate the idea of fitness into a series of adaptations that are more or less independent of each other. This work adds to the idea of a general fitness factor, f, that is similar in concept to g—and of which g is one manifestation. To him that hath, in other words, shall be given. Unfortunately for the politically correct, Dr Miller’s hypothesis looks stronger by the day.

Dienekes links to the study. While the result has no direct bearing on Rushton's cross-racial claims (which stand or fall on their own merits), it seems to contradict the broader theoretical underpinning of Race, Evolution, and Behavior, proving that intelligence and reproductive potential need not be inversely related in humans (at least in men).

Related: Physical correlates of cognitive ability