Evidence for an apartheid-like social structure in early Anglo-Saxon England

The role of migration in the Anglo-Saxon transition in England remains controversial. Archaeological and historical evidence is inconclusive, but current estimates of the contribution of migrants to the English population range from less than 10 000 to as many as 200 000. In contrast, recent studies based on Y-chromosome variation posit a considerably higher contribution to the modern English gene pool (50-100%). Historical evidence suggests that following the Anglo-Saxon transition, people of indigenous ethnicity were at an economic and legal disadvantage compared to those having Anglo-Saxon ethnicity. It is likely that such a disadvantage would lead to differential reproductive success. We examine the effect of differential reproductive success, coupled with limited intermarriage between distinct ethnic groups, on the spread of genetic variants. Computer simulations indicate that a social structure limiting intermarriage between indigenous Britons and an initially small Anglo-Saxon immigrant population provide a plausible explanation of the high degree of Continental male-line ancestry in England.

Gene conversion and evolution of Xq28 duplicons involved in recurring inversions causing severe hemophilia A

Inversions breaking the 1041 bp int1h-1 or the 9.5-kb int22h-1 sequence of the F8 gene cause hemophilia A in 1/30,000 males. These inversions are due to homologous recombination between the above sequences and their inverted copies on the same DNA molecule, respectively, int1h-2 and int22h-2 or int22h-3. We find that (1) int1h and int22h duplicated more than 25 million years ago; (2) the identity of the copies (>99%) of these sequences in humans and other primates is due to gene conversion; (3) gene conversion is most frequent in the internal regions of int22h; (4) breakpoints of int22h-related inversions also tend to involve the internal regions of int22h; (5) sequence variations in a sample of human X chromosomes defined eight haplotypes of int22h-1 and 27 of int22h-2 plus int22h-3; (6) the latter two sequences, which lie, respectively, 500 and 600 kb telomeric to int22h-1 are five-fold more identical when in cis than when in trans, thus suggesting that gene conversion may be predominantly intrachromosomal; (7) int1h, int22h, and flanking sequences evolved at a rate of about 0.1% substitutions per million years during the divergence between humans and other primates, except for int1h during the human-chimpanzee divergence, when its rate of evolution was significantly lower. This is reminiscent of the slower evolution of palindrome arms in the male specific regions of the Y chromosome and we propose, as an explanation, that intrachromosomal gene conversion and cosegregation of the duplicated regions favors retention of the ancestral sequence and thus reduces the evolution rate.

Likelihood-based estimation of microsatellite mutation rates

Microsatellites are widely used in genetic analyses, many of which require reliable estimates of microsatellite mutation rates, yet the factors determining mutation rates are uncertain. The most straightforward and conclusive method by which to study mutation is direct observation of allele transmissions in parent-child pairs, and studies of this type suggest a positive, possibly exponential, relationship between mutation rate and allele size, together with a bias toward length increase. Except for microsatellites on the Y chromosome, however, previous analyses have not made full use of available data and may have introduced bias: mutations have been identified only where child genotypes could not be generated by transmission from parents' genotypes, so that the probability that a mutation is detected depends on the distribution of allele lengths and varies with allele length. We introduce a likelihood-based approach that has two key advantages over existing methods. First, we can make formal comparisons between competing models of microsatellite evolution; second, we obtain asymptotically unbiased and efficient parameter estimates. Application to data composed of 118,866 parent-offspring transmissions of AC microsatellites supports the hypothesis that mutation rate increases exponentially with microsatellite length, with a suggestion that contractions become more likely than expansions as length increases. This would lead to a stationary distribution for allele length maintained by mutational balance. There is no evidence that contractions and expansions differ in their step size distributions.

Why are autism spectrum conditions more prevalent in males?

Autism Spectrum Conditions (ASC) are much more common in males, a bias that may offer clues to the etiology of this condition. Although the cause of this bias remains a mystery, we argue that it occurs because ASC is an extreme manifestation of the male brain. The extreme male brain (EMB) theory, first proposed in 1997, is an extension of the Empathizing-Systemizing (E-S) theory of typical sex differences that proposes that females on average have a stronger drive to empathize while males on average have a stronger drive to systemize. In this first major update since 2005, we describe some of the evidence relating to the EMB theory of ASC and consider how typical sex differences in brain structure may be relevant to ASC. One possible biological mechanism to account for the male bias is the effect of fetal testosterone (fT). We also consider alternative biological theories, the X and Y chromosome theories, and the reduced autosomal penetrance theory. None of these theories has yet been fully confirmed or refuted, though the weight of evidence in favor of the fT theory is growing from converging sources (longitudinal amniocentesis studies from pregnancy to age 10 years old, current hormone studies, and genetic association studies of SNPs in the sex steroid pathways). Ultimately, as these theories are not mutually exclusive and ASC is multi-factorial, they may help explain the male prevalence of ASC.

Likelihood-free estimation of model evidence

Statistical methods of inference typically require the likelihood function to be computable in a reasonable amount of time. The class of “likelihood-free” methods termed Approximate Bayesian Computation (ABC) is able to eliminate this requirement, replacing the evaluation of the likelihood with simulation from it. Likelihood-free methods have gained in efficiency and popularity in the past few years, following their integration with Markov Chain Monte Carlo (MCMC) and Sequential Monte Carlo (SMC) in order to better explore the parameter space. They have been applied primarily to estimating the parameters of a given model, but can also be used to compare models. Here we present novel likelihood-free approaches to model comparison, based upon the independent estimation of the evidence of each model under study. Key advantages of these approaches over previous techniques are that they allow the exploitation of MCMC or SMC algorithms for exploring the parameter space, and that they do not require a sampler able to mix between models. We validate the proposed methods using a simple exponential family problem before providing a realistic problem from human population genetics: the comparison of different demographic models based upon genetic data from the Y chromosome.