Mark A. Beaumont

Evaluating loci for use in the genetic analysis of population structure

Loci that show unusually low or high levels of genetic differentiation are often assumed to be subject to natural selection. We propose a method for the identification of loci showing such disparities. The differentiation can be quantified using the statistic FST. For a range of population structures and demographic histories, the distribution of FST is strongly related to the heterozygosity at a locus. Outlying values of FST can be identified in a plot of FST vs. heterozygosity using a null distribution generated by a simple genetic model. We use published data-sets to illustrate the importance of the relationship with heterozygosity. We investigate a number of models of population structure, and demonstrate that the null distribution is robust to a wide range of conditions. In particular, the distribution is robust to differing mutation rates, and therefore different molecular markers, such as allozymes, restriction fragment length polymorphisms (RFLPS) and single strand conformation polymorphisms (SSCPS) can be compared together. We suggest that genetic variation at a discrepant locus, Identified under these conditions, is likely to have been influenced by natural selection, either acting on the locus itself or at a closely linked locus.

Identifying adaptive genetic divergence among populations from genome scans

The identification of signatures of natural selection in genomic surveys has become an area of intense research, stimulated by the increasing ease with which genetic markers can be typed. Loci identified as subject to selection may be functionally important, and hence (weak) candidates for involvement in disease causation. They can also be useful in determining the adaptive differentiation of populations, and exploring hypotheses about speciation. Adaptive differentiation has traditionally been identified from differences in allele frequencies among different populations, summarised by an estimate of FST. Low outliers relative to an appropriate neutral population‐genetics model indicate loci subject to balancing selection, whereas high outliers suggest adaptive (directional) selection. However, the problem of identifying statistically significant departures from neutrality is complicated by confounding effects on the distribution of FST estimates, and current methods have not yet been tested in large‐scale simulation experiments. Here, we simulate data from a structured population at many unlinked, diallelic loci that are predominantly neutral but with some loci subject to adaptive or balancing selection. We develop a hierarchical‐Bayesian method, implemented via Markov chain Monte Carlo (MCMC), and assess its performance in distinguishing the loci simulated under selection from the neutral loci. We also compare this performance with that of a frequentist method, based on moment‐based estimates of FST. We find that both methods can identify loci subject to adaptive selection when the selection coefficient is at least five times the migration rate. Neither method could reliably distinguish loci under balancing selection in our simulations, even when the selection coefficient is twenty times the migration rate.

Inferring population history with DIY ABC

Summary: Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. Availability: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc. Contact: j.cornuet@imperial.ac.uk Supplementary information: Supplementary data are also available at http://www.montpellier.inra.fr/CBGP/diyabc

Statistical evaluation of alternative models of human evolution

An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species ≈141 thousand years ago (Kya), an exit out-of-Africa ≈51 Kya, and a recent colonization of the Americas ≈10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.

The Bayesian revolution in genetics

Bayesian statistics allow scientists to easily incorporate prior knowledge into their data analysis. Nonetheless, the sheer amount of computational power that is required for Bayesian statistical analyses has previously limited their use in genetics. These computational constraints have now largely been overcome and the underlying advantages of Bayesian approaches are putting them at the forefront of genetic data analysis in an increasing number of areas.

ONeSAMP: a program to estimate effective population size using approximate Bayesian computation

The estimation of effective population size from one sample of genotypes has been problematic because most estimators have been proven imprecise or biased. We developed a web‐based program, onesamp that uses approximate Bayesian computation to estimate effective population size from a sample of microsatellite genotypes. onesamp requires an input file of sampled individuals’ microsatellite genotypes along with information about several sampling and biological parameters. onesamp provides an estimate of effective population size, along with 95% credible limits. We illustrate the use of onesamp with an example data set from a re‐introduced population of ibex Capra ibex.

The origins of lactase persistence in Europe.

Lactase persistence (LP) is common among people of European ancestry, but with the exception of some African, Middle Eastern and southern Asian groups, is rare or absent elsewhere in the world. Lactase gene haplotype conservation around a polymorphism strongly associated with LP in Europeans (−13,910 C/T) indicates that the derived allele is recent in origin and has been subject to strong positive selection. Furthermore, ancient DNA work has shown that the −13,910*T (derived) allele was very rare or absent in early Neolithic central Europeans. It is unlikely that LP would provide a selective advantage without a supply of fresh milk, and this has lead to a gene-culture coevolutionary model where lactase persistence is only favoured in cultures practicing dairying, and dairying is more favoured in lactase persistent populations. We have developed a flexible demic computer simulation model to explore the spread of lactase persistence, dairying, other subsistence practices and unlinked genetic markers in Europe and western Asias geographic space. Using data on −13,910*T allele frequency and farming arrival dates across Europe, and approximate Bayesian computation to estimate parameters of interest, we infer that the −13,910*T allele first underwent selection among dairying farmers around 7,500 years ago in a region between the central Balkans and central Europe, possibly in association with the dissemination of the Neolithic Linearbandkeramik culture over Central Europe. Furthermore, our results suggest that natural selection favouring a lactase persistence allele was not higher in northern latitudes through an increased requirement for dietary vitamin D. Our results provide a coherent and spatially explicit picture of the coevolution of lactase persistence and dairying in Europe.

COMPUTER PROGRAMS: onesamp: a program to estimate effective population size using approximate Bayesian computation

The estimation of effective population size from one sample of genotypes has been problematic because most estimators have been proven imprecise or biased. We developed a web‐based program, onesamp that uses approximate Bayesian computation to estimate effective population size from a sample of microsatellite genotypes. onesamp requires an input file of sampled individuals’ microsatellite genotypes along with information about several sampling and biological parameters. onesamp provides an estimate of effective population size, along with 95% credible limits. We illustrate the use of onesamp with an example data set from a re‐introduced population of ibex Capra ibex.

Y genetic data support the Neolithic demic diffusion model

There still is no general agreement on the origins of the European gene pool, even though Europe has been more thoroughly investigated than any other continent. In particular, there is continuing controversy about the relative contributions of European Palaeolithic hunter-gatherers and of migrant Near Eastern Neolithic farmers, who brought agriculture to Europe. Here, we apply a statistical framework that we have developed to obtain direct estimates of the contribution of these two groups at the time they met. We analyze a large dataset of 22 binary markers from the non-recombining region of the Y chromosome (NRY), by using a genealogical likelihood-based approach. The results reveal a significantly larger genetic contribution from Neolithic farmers than did previous indirect approaches based on the distribution of haplotypes selected by using post hoc criteria. We detect a significant decrease in admixture across the entire range between the Near East and Western Europe. We also argue that local hunter-gatherers contributed less than 30% in the original settlements. This finding leads us to reject a predominantly cultural transmission of agriculture. Instead, we argue that the demic diffusion model introduced by Ammerman and Cavalli-Sforza [Ammerman, A. J. & Cavalli-Sforza, L. L. (1984) The Neolithic Transition and the Genetics of Populations in Europe (Princeton Univ. Press, Princeton)] captures the major features of this dramatic episode in European prehistory.

Immigration and the ephemerality of a natural population bottleneck: evidence from molecular markers

Population bottlenecks are often invoked to explain low levels of genetic variation in natural populations, yet few studies have documented the direct genetic consequences of known bottlenecks in the wild. Empirical studies of natural population bottlenecks are therefore needed, because key assumptions of theoretical and laboratory studies of bottlenecks may not hold in the wild. Here we present microsatellite data from a severe bottleneck (95% mortality) in an insular population of song sparrows (Melospiza melodia). The major findings of our study are as follows: (i) The bottleneck reduced heterozygosity and allelic diversity nearly to neutral expectations, despite non–random survival of birds with respect to inbreeding and wing length. (ii) All measures of genetic diversity regained pre–bottleneck levels within two to three years of the crash. This rapid recovery was due to low levels of immigration. (iii) The rapid recovery occurred despite a coincident, strong increase in average inbreeding. These results show that immigration at levels that are hard to measure in most field studies can lead to qualitatively very different genetic outcomes from those expected from mutations only. We suggest that future theoretical and empirical work on bottlenecks and metapopulations should address the impact of immigration.