When a population experiences a reduction of its effective size, it generally develops a heterozygosity excess at selectively neutral loci, i.e., the heterozygosity computed from a sample of genes is larger than the heterozygosity expected from the number of alleles found in the sample if the population were at mutation drift equilibrium. The heterozygosity excess persists only a certain number of generations until a new equilibrium is established. Two statistical tests for detecting a heterozygosity excess are described. They require measurements of the number of alleles and heterozygosity at each of several loci from a population sample. The first test determines if the proportion of loci with heterozygosity excess is significantly larger than expected at equilibrium. The second test establishes if the average of standardized differences between observed and expected heterozygosities is significantly different from zero. Type I and II errors have been evaluated by computer simulations, varying sample size, number of loci, bottleneck size, time elapsed since the beginning of the bottleneck and level of variability of loci. These analyses show that the most useful markers for bottleneck detection are those evolving under the infinite allele model (IAM) and they provide guidelines for selecting sample sizes of individuals and loci. The usefulness of these tests for conservation biology is discussed.

https://www.genetics.org/content/genetics/144/4/2001.full.pdf

Description and Power Analysis of Two Tests for Detecting Recent Population Bottlenecks from Allele Frequency Data

The Quaternary cold periods in Europe are thought to have heavily influenced the amount and distribution of intraspecific genetic variation in both animals and plants. The phylogeographies of 10 taxa, including mammals (Ursus arctos, Sorex spp., Crocidura suaveolens, Arvicola spp.), amphibians (Triturus spp.), arthropods (Chorthippus parallelus), and plants (Abies alba, Picea abies, Fagus sylvatica, Quercus spp.), were analysed to elucidate general trends across Europe. Only a small degree of congruence was found amongst the phylogeographies of the 10 taxa, but the likely postglacial colonization routes exhibit some similarities. A Brooks parsimony analysis produced an unrooted area phylogram, showing that: (i) the northern regions were colonized generally from the Iberic and Balkanic refugia; and (ii) the Italian lineages were often isolated due to the presence of the Alpine barrier. The comparison of colonization routes highlighted four main suture-zones where lineages from the different refugia meet. Some of the intraspecific genetic distances among lineages indicated a prequaternary divergence that cannot be connected to any particular cold period, but are probably related mainly to the date of arrival of each taxon in the European continent. As a consequence, molecular genetics so far appears to be of limited use in dating Quaternary events.

Comparative phylogeography and postglacial colonization routes in Europe

We propose a new method for approximate Bayesian statistical inference on the basis of summary statistics. The method is suited to complex problems that arise in population genetics, extending ideas developed in this setting by earlier authors. Properties of the posterior distribution of a parameter, such as its mean or density curve, are approximated without explicit likelihood calculations. This is achieved by fitting a local-linear regression of simulated parameter values on simulated summary statistics, and then substituting the observed summary statistics into the regression equation. The method combines many of the advantages of Bayesian statistical inference with the computational efficiency of methods based on summary statistics. A key advantage of the method is that the nuisance parameters are automatically integrated out in the simulation step, so that the large numbers of nuisance parameters that arise in population genetics problems can be handled without difficulty. Simulation results indicate computational and statistical efficiency that compares favorably with those of alternative methods previously proposed in the literature. We also compare the relative efficiency of inferences obtained using methods based on summary statistics with those obtained directly from the data using MCMC.

https://www.genetics.org/content/genetics/162/4/2025.full.pdf

Approximate Bayesian computation in population genetics.

Microsatellite null alleles are commonly encountered in population genetics studies, yet little is known about their impact on the estimation of population differentiation. Computer simulations based on the coalescent were used to investigate the evolutionary dynamics of null alleles, their impact on F(ST) and genetic distances, and the efficiency of estimators of null allele frequency. Further, we explored how the existing method for correcting genotype data for null alleles performed in estimating F(ST) and genetic distances, and we compared this method with a new method proposed here (for F(ST) only). Null alleles were likely to be encountered in populations with a large effective size, with an unusually high mutation rate in the flanking regions, and that have diverged from the population from which the cloned allele state was drawn and the primers designed. When populations were significantly differentiated, F(ST) and genetic distances were overestimated in the presence of null alleles. Frequency of null alleles was estimated precisely with the algorithm presented in Dempster et al. (1977). The conventional method for correcting genotype data for null alleles did not provide an accurate estimate of F(ST) and genetic distances. However, the use of the genetic distance of Cavalli-Sforza and Edwards (1967) corrected by the conventional method gave better estimates than those obtained without correction. F(ST) estimation from corrected genotype frequencies performed well when restricted to visible allele sizes. Both the proposed method and the traditional correction method have been implemented in a program that is available free of charge at http://www.montpellier.inra.fr/URLB/. We used 2 published microsatellite data sets based on original and redesigned pairs of primers to empirically confirm our simulation results.

Microsatellite Null Alleles and Estimation of Population Differentiation

GENECLASS2 is a software that computes various genetic assignment criteria to assign or exclude reference populations as the origin of diploid or haploid individuals, as well as of groups of individuals, on the basis of multilocus genotype data. In addition to traditional assignment aims, the program allows the specific task of first-generation migrant detection. It includes several Monte Carlo resampling algorithms that compute for each individual its probability of belonging to each reference population or to be a resident (i.e., not a first-generation migrant) in the population where it was sampled. A user-friendly interface facilitates the treatment of large datasets.

GENECLASS2: A Software for Genetic Assignment and First-Generation Migrant Detection

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Computer note. BOTTLENECK: a computer program for detecting recent reductions in the effective size using allele frequency data

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

/pdf/inferring-population-history-with-diy-abc-h93xb0eqtl.pdf

Inferring population history with DIY ABC

Sequential techniques can enhance the efficiency of the approximate Bayesian computation algorithm, as in Sisson et al.'s (2007) partial rejection control version. While this method is based upon the theoretical works of Del Moral et al. (2006), the application to approximate Bayesian computation results in a bias in the approximation to the posterior. An alternative version based on genuine importance sampling arguments bypasses this difficulty, in connection with the population Monte Carlo method of Cappe et al. (2004), and it includes an automatic scaling of the forward kernel. When applied to a population genetics example, it compares favourably with two other versions of the approximate algorithm.

Adaptive approximate Bayesian computation

Sociobiologists have long sought to estimate precisely the relatedness among members of social insect colonies because of the central significance of kinship in evolutionary and behavioural studies. By using microsatellites, we directly identified the 7-20 subfamilies (patrilines) present in five honeybee colonies belonging to three different subspecies ( Apis mellifera mellifera, A. m. carnica and A. m. ligustica ). By focusing further investigations on one A. m. mellifera colony, we showed that the genetic structure remained largely unchanged over time as long as the colony is headed by the same queen. The genetic diversity within the colony also provided a good estimate of the genetic diversity of the local honeybee population. The distribution of patrilines was significantly different in swarming workers compared with contemporaneous pupae of the original colony, probably due to unequal propensities for swarming among patrilines. Conversely, no bias in the relative proportions between worker and queen brood could be detected.

Jean-Marie Cornuet

Papers

Computer note. BOTTLENECK: a computer program for detecting recent reductions in the effective size using allele frequency data

GENECLASS2: A Software for Genetic Assignment and First-Generation Migrant Detection

Inferring population history with DIY ABC

Adaptive approximate Bayesian computation

Precise assessment of the number of patrilines and of genetic relatedness in honeybee colonies