Genetic inferences about the population dynamics of codling moth females at a local scale.

Estimation of demographic parameters is important for understanding the functioning of natural populations and the underlying ecological and evolutionary processes that may impact their dynamics. Here, we used sibship assignment methods to shed light on the local dynamics of codling moth females in eight orchards in a 90-ha domain near Valence, France. Based on full-sib inference among 1,063 genotyped moths, we estimated (1) the effective number of females that had offspring, (2) their fertility and (3) the distribution of their oviposition sites within and among orchards. The average number of females in all the orchards increased between the first (~130) and the second (~235) annual generations. The average fertilities of the females were similar at each generation according to the host plant considered (apple, pear, or walnut), but differed between commercial (~10) and non-treated (~25) apple orchards. Females mainly clustered their eggs on contiguous trees along orchard borders, but they also occasionally dispersed their eggs among different orchards independently of the cultivated host plants or the inter-orchard distances (up to 698 m) during the second annual generation. The mean distance between two oviposition sites was 30 m. Sibship estimates of both the effective number of females and the inter-orchard migration rates (~5%) were in agreement with the observed genetic differentiation among the eight orchards (0.006 < F ( st ) < 0.013). These results confirm and extend previous field and laboratory observations in Cydia pomonella, and they demonstrate that sibship assignments based on genetic data are an interesting alternative to mark-release-recapture methods for inferring insect population dynamics.

Inferring introduction routes of invasive species using approximate Bayesian computation on microsatellite data.

Determining the routes of introduction provides not only information about the history of an invasion process, but also information about the origin and construction of the genetic composition of the invading population. It remains difficult, however, to infer introduction routes from molecular data because of a lack of appropriate methods. We evaluate here the use of an approximate Bayesian computation (ABC) method for estimating the probabilities of introduction routes of invasive populations based on microsatellite data. We considered the crucial case of a single source population from which two invasive populations originated either serially from a single introduction event or from two independent introduction events. Using simulated datasets, we found that the method gave correct inferences and was robust to many erroneous beliefs. The method was also more efficient than traditional methods based on raw values of statistics such as assignment likelihood or pairwise F(ST). We illustrate some of the features of our ABC method, using real microsatellite datasets obtained for invasive populations of the western corn rootworm, Diabrotica virgifera virgifera. Most computations were performed with the DIYABC program (http://www1.montpellier.inra.fr/CBGP/diyabc/).

A note on the accuracy of PAC-likelihood inference with microsatellite data.

Stephens and Donnelly have introduced a simple yet powerful importance sampling scheme for computing the likelihood in population genetic models. Fundamental to the method is an approximation to the conditional probability of the allelic type of an additional gene, given those currently in the sample. As noted by Li and Stephens, the product of these conditional probabilities for a sequence of draws that gives the frequency of allelic types in a sample is an approximation to the likelihood, and can be used directly in inference. The aim of this note is to demonstrate the high level of accuracy of "product of approximate conditionals" (PAC) likelihood when used with microsatellite data. Results obtained on simulated microsatellite data show that this strategy leads to a negligible bias over a wide range of the scaled mutation parameter theta. Furthermore, the sampling variance of likelihood estimates as well as the computation time are lower than that obtained with importance sampling on the whole range of theta. It follows that this approach represents an efficient substitute to IS algorithms in computer intensive (e.g. MCMC) inference methods in population genetics.

Inference on microsatellite mutation processes in the invasive mite, Varroa destructor, using reversible jump Markov chain Monte Carlo.

Varroa destructor is a parasitic mite of the Eastern honeybee Apis cerana. Fifty years ago, two distinct evolutionary lineages (Korean and Japanese) invaded the Western honeybee Apis mellifera. This haplo-diploid parasite species reproduces mainly through brother-sister matings, a system which largely favors the fixation of new mutations. In a worldwide sample of 225 individuals from 21 locations collected on Western honeybees and analyzed at 19 microsatellite loci, a series of de novo mutations was observed. Using historical data concerning the invasion, this original biological system has been exploited to compare three mutation models with allele size constraints for microsatellite markers: stepwise (SMM) and generalized (GSM) mutation models, and a model with mutation rate increasing exponentially with microsatellite length (ESM). Posterior probabilities of the three models have been estimated for each locus individually using reversible jump Markov Chain Monte Carlo. The relative support of each model varies widely among loci, but the GSM is the only model that always receives at least 9% support, whatever the locus. The analysis also provides robust estimates of mutation parameters for each locus and of the divergence time of the two invasive lineages (67,000 generations with a 90% credibility interval of 35,000-174,000). With an average of 10 generations per year, this divergence time fits with the last post-glacial Korea-Japan land separation.

GENECLASS2: a software for genetic assignment and first-generation migrant detection.

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.

Analytical bayesian approach for assigning individuals to populations.

We propose a general formulation of the Bayesian method for assigning individuals to a population among a predetermined set of reference populations using molecular marker information. Compared to previously published methods, ours allows us to consider different types of prior information about allele frequencies by using a Dirichlet prior probability distribution. It also makes it possible to assign a set of individuals assumed to belong to the same population with increased accuracy using their pooled genotype data. The efficiency of the method is illustrated by application to a group of closely related coconut populations. An interesting feature of the Bayesian procedure is the way it handles imprecise information. With a poor or even incomplete dataset, assignment is still be possible and gives valid results: poor data quality is reflected in an ambiguous result rather than in a false conclusion.

Estimating admixture proportions with microsatellites: comparison of methods based on simulated data.

Several methods have been developed to estimate the parental contributions in the genetic pool of an admixed population. Some pair-comparisons have been performed on real data but, to date, no systematic comparison of a large number of methods has been attempted. In this study, we performed a simulated data-based comparison of six of the most cited methods in the literature of the last 20 years. Five of these methods use allele frequencies and differ in the statistical treatment of the data. The last one also considers the degree of molecular divergence by estimating the coalescence times. Comparisons are based on the frequency at which the method can be applied, the bias and the mean square error of the estimation, and the frequency at which the true value is within the confidence interval. Eventually, each method was applied to a real data set of variously introgressed honeybee populations. In optimal conditions (highly differentiated parental populations, recent hybridization event), all methods perform equally well. When conditions are not optimal, the methods perform differently, but no method is always better or worse than all others. Some guidelines are given for the choice of the method.

Genetic structure of a greenhouse population of the spider mite Tetranychus urticae: spatio-temporal analysis with microsatellite markers.

The genetic structure of a greenhouse population of the mite Tetranychus urticae was studied by the analysis of five microsatellite loci. Genetic variation was compared during a crop season between periods of population foundation and rapid population increase and was investigated in two consecutive years. The population displayed significant heterozygote deficiency at all the sampling periods. However, inbreeding tended to decrease with increasing density (FIS coefficient between 0.13 and 0.25). No significant genetic differentiation between samples was found either at a spatial scale within the greenhouse or at a temporal scale between two growing seasons (FST between 0.008 and 0.09). Estimations of the genetic relatedness between pairs of individuals indicated that the distances between pairs of sisters and unrelated mites in the greenhouse were not significantly different, suggesting that mites do not tend to form patches that reside close to the point of birth.

Genetic diversity of the honeybee in Africa: microsatellite and mitochondrial data.

A total of 738 colonies from 64 localities along the African continent have been analysed using the DraI RFLP of the COI-COII mitochondrial region. Mitochondrial DNA of African honeybees appears to be composed of three highly divergent lineages. The African lineage previously reported (named A) is present in almost all the localities except those from north-eastern Africa. In this area, two newly described lineages (called O and Y), putatively originating from the Near East, are observed in high proportion. This suggests an important differentiation of Ethiopian and Egyptian honeybees from those of other African areas. The A lineage is also present in high proportion in populations from the Iberian Peninsula and Sicily. Furthermore, eight populations from Morocco, Guinea, Malawi and South Africa have been assayed with six microsatellite loci and compared to a set of eight additional populations from Europe and the Middle East. The African populations display higher genetic variability than European populations at all microsatellite loci studied thus far. This suggests that African populations have larger effective sizes than European ones. According to their microsatellite allele frequencies, the eight African populations cluster together, but are divided in two subgroups. These are the populations from Morocco and those from the other African countries. The populations from southern Europe show very low levels of 'Africanization' at nuclear microsatellite loci. Because nuclear and mitochondrial DNA often display discordant patterns of differentiation in the honeybee, the use of both kinds of markers is preferable when assessing the phylogeography of Apis mellifera and to determine the taxonomic status of the subspecies.

Inferring population history from microsatellite and enzyme data in serially introduced cane toads, Bufo marinus.

Much progress has been made on inferring population history from molecular data. However, complex demographic scenarios have been considered rarely or have proved intractable. The serial introduction of the South-Central American cane toad Bufo marinus in various Caribbean and Pacific islands involves four major phases: a possible genetic admixture during the first introduction, a bottleneck associated with founding, a transitory population boom, and finally, a demographic stabilization. A large amount of historical and demographic information is available for those introductions and can be combined profitably with molecular data. We used a Bayesian approach to combine this information with microsatellite (10 loci) and enzyme (22 loci) data and used a rejection algorithm to simultaneously estimate the demographic parameters describing the four major phases of the introduction history. The general historical trends supported by microsatellites and enzymes were similar. However, there was a stronger support for a larger bottleneck at introductions for microsatellites than enzymes and for a more balanced genetic admixture for enzymes than for microsatellites. Very little information was obtained from either marker about the transitory population boom observed after each introduction. Possible explanations for differences in resolution of demographic events and discrepancies between results obtained with microsatellites and enzymes were explored. Limits of our model and method for the analysis of nonequilibrium populations were discussed.

Juxtaposed microsatellite systems as diagnostic markers for admixture: an empirical evaluation with brown trout (Salmo trutta) as model organism.

A juxtaposed microsatellite system (JMS) is composed of two microsatellite repeat arrays separated by a sequence of less than 200 bp and more than 20 bp. This paper presents the first empirical evaluation of JMSs for the study of genetic admixture induced by man, with brown trout (Salmo trutta) as model organism. Two distinct admixture situations were studied: native populations from streams of the Atlantic basin and of the Mediterranean basin, respectively, all stocked with domestic strains originating from the Atlantic basin. For these two situations, we first evaluated by simulation the ability of JMSs to differentiate between alien alleles and naturally shared homoplasious or ancestral alleles, and thus to behave as diagnostic markers for admixture. Simulations indicated that JMSs are expected to be reliable diagnostic markers in most divergent (i.e. Mediterranean) populations and nonreliable diagnostic markers in most closely related (i.e. Atlantic) populations. Three JMSs were genotyped in domestic strains as well as in nonstocked and stocked populations of brown trout sampled in different rivers of the Mediterranean and Atlantic basins. The observed distributions of JMS haplotypes were consistent with simulation predictions confirming that JMSs were reliable diagnostic markers only over a given proportion of the species range, i.e. in substantially divergent populations. JMSs also reinforced the diagnostic character of three microsatellite sites for the studied Mediterranean populations. This last result is consistent with our simulation results which showed that, although much less frequently than at JMSs, diagnostic markers are likely to be found at single site microsatellites provided that the native Mediterranean population has a sufficiently small effective population size. For each population of the Mediterranean basin admixture coefficients did not differ significantly across JMSs and mean admixture coefficients sometimes differ among populations. The interpretation of the origin of JMS haplotypes based on the allele length variants was supported by nucleotide sequence analysis.

Hybrid origins of honeybees from italy (Apis mellifera ligustica) and sicily (A. m. sicula).

The genetic variability of honeybee populations Apis mellifera ligustica, in continental Italy, and of A. m. sicula, in Sicily, was investigated using nuclear (microsatellite) and mitochondrial markers. Six populations (236 individual bees) and 17 populations (664 colonies) were, respectively, analysed using eight microsatellite loci and DraI restriction fragment length polymorphism (RFLP) of the cytochrome oxidase I (COI)-cytochrome oxidase II (COII) region. Microsatellite loci globally confirmed the southeastern European heritage of both subspecies (evolutionary branch C). However, A. m. ligustica mitochondrial DNA (mtDNA) appeared to be a composite of the two European (M and C) lineages over most of the Italian peninsula, and only mitotypes from the African (A) lineage were found in A. m. sicula samples. This demonstrates a hybrid origin for both subspecies. For A. m. ligustica, the most widely exported subspecies, this hybrid origin has long been obscured by the fact that in the main area of queen production (from which most of the previous ligustica bee samples originated) the M mitochondrial lineage is absent, whereas it is present almost everywhere else in Italy. This presents a new view of the evolutionary history of European honeybees. For instance, the Iberian peninsula was considered as the unique refuge for the M branch during the quaternary ice periods. Our results show that the Apennine peninsula played a similar role. The differential distribution of nuclear and mitochondrial markers observed in Italy seems to be a general feature of introgressed honeybee populations. Presumably, it stems from the social nature of the species in which both genome compartments are differentially affected by the two (individual and colonial) reproduction levels.

New methods employing multilocus genotypes to select or exclude populations as origins of individuals.

A new method for assigning individuals of unknown origin to populations, based on the genetic distance between individuals and populations, was compared to two existing methods based on the likelihood of multilocus genotypes. The distribution of the assignment criterion (genetic distance or genotype likelihood) for individuals of a given population was used to define the probability that an individual belongs to the population. Using this definition, it becomes possible to exclude a population as the origin of an individual, a useful extension of the currently available assignment methods. Using simulated data based on the coalescent process, the different methods were evaluated, varying the time of divergence of populations, the mutation model, the sample size, and the number of loci. Likelihood-based methods (especially the Bayesian method) always performed better than distance methods. Other things being equal, genetic markers were always more efficient when evolving under the infinite allele model than under the stepwise mutation model, even for equal values of the differentiation parameter F(st). Using the Bayesian method, a 100% correct assignment rate can be achieved by scoring ca. 10 microsatellite loci (H approximately 0.6) on 30-50 individuals from each of 10 populations when the F(st) is near 0.1.

Microsatellite analysis of sperm admixture in honeybee.

Sperm usage was investigated in an instrumentally inseminated honeybee queen. Her progeny were examined in the first 3 months of the egg-laying period using a microsatellite marker. Frequencies of different subfamilies differed significantly from one month to another. However, there was no evidence for sperm displacement or sperm precedence of a specific male in the worker progeny. The variance of subfamily proportions decreased over time suggesting that sperm admixture in the spermatheca was incomplete at the beginning of the egg-laying period of the queen and improved progressively during the first months after mating.

Estimating the effective number of breeders from heterozygote excess in progeny.

The heterozygote-excess method is a recently published method for estimating the effective population size (Ne). It is based on the following principle: When the effective number of breeders (Neb) in a population is small, the allele frequencies will (by chance) be different in males and females, which causes an excess of heterozygotes in the progeny with respect to Hardy-Weinberg equilibrium expectations. We evaluate the accuracy and precision of the heterozygote-excess method using empirical and simulated data sets from polygamous, polygynous, and monogamous mating systems and by using realistic sample sizes of individuals (15-120) and loci (5-30) with varying levels of polymorphism. The method gave nearly unbiased estimates of Neb under all three mating systems. However, the confidence intervals on the point estimates of Neb were sufficiently small (and hence the heterozygote-excess method useful) only in polygamous and polygynous populations that were produced by <10 effective breeders, unless samples included > approximately 60 individuals and 20 multiallelic loci.

Distortion of allele frequency distributions provides a test for recent population bottlenecks.

We use population genetics theory and computer simulations to demonstrate that population bottlenecks cause a characteristic mode-shift distortion in the distribution of allele frequencies at selectively neutral loci. Bottlenecks cause alleles at low frequency (< 0.1) to become less abundant than alleles in one or more intermediate allele frequency class (e.g., 0.1-0.2). This distortion is transient and likely to be detectable for only a few dozen generations. Consequently only recent bottlenecks are likely to be detected by tests for distortions in distributions of allele frequencies. We illustrate and evaluate a qualitative graphical method for detecting a bottleneck-induced distortion of allele frequency distributions. The simple novel method requires no information on historical population sizes or levels of genetic variation; it requires only samples of 5 to 20 polymorphic loci and approximately 30 individuals. The graphical method often differentiates between empirical datasets from bottlenecked and nonbottlenecked natural populations. Computer simulations show that the graphical method is likely (P > .80) to detect an allele frequency distortion after a bottleneck of < or = 20 breeding individuals when 8 to 10 polymorphic microsatellite loci are analyzed.

Comparative analysis of microsatellite and allozyme markers: a case study investigating microgeographic differentiation in brown trout (Salmo trutta).

A comparative study between microsatellite and allozyme markers was conducted on natural populations of resident brown trout (Salmo trutta) sampled over a reduced geographical scale and on hatchery strains. The higher level of polymorphism observed at microsatellite loci resulted in higher power of statistical tests for differentiation among population samples and for genotypic linkage disequilibrium. Genetic distances of Cavalli-Sforza and Edwards were on average two times larger for microsatellites than for allozymes but multilocus FST estimates computed over the entire set of populations were not significantly different for both categories of markers. Assignment tests of individual fish to the set of sampled populations demonstrated a much higher efficiency of microsatellites compared to allozymes. Pairwise multilocus FST estimates were significantly correlated to waterway distances and there was a significant tendency for the incorrectly classified individuals to be assigned to one of the nearest populations, indicating that isolation-by-distance acted significantly on brown trout populations. This increase of differentiation with distance was higher for allozymes than for microsatellites. Traditional measures of genetic differentiation (Cavalli-Sforza and Edwards' chord distance and FST) were compared for microsatellites to recently proposed statistics taking into account allele size differences (Goldstein's distance and PST). Using Goldstein's distance for neighbour-joining analysis did not improve the tree structure resolution. Multilocus estimates of PST and FST were not significantly different when computed over the entire set of populations but no significant correlation was detected between matrices of pairwise multilocus PST estimates and waterway distances.

Classifying individuals among infra-specific taxa using microsatellite data and neural networks.

The method of neural networks was tested for its ability to assign individuals on the basis of their multilocus genotypes, using a data collection of 430 honeybees and 8 microsatellite loci. This data set includes various taxonomical levels (populations within the same subspecies, various subspecies belonging to the same evolutionary lineage, and the 3 lineages of the species). Qualitative genotypic data have been submitted to 2 types of transformation (simple coding and coding plus factorial correspondence analysis), and they have been partitioned in 2 sets, a training set of 300 individuals and a testing set of 103 individuals. Two procedures ("leave one out" and "hold out") were applied to evaluate the quality of prediction. Compared to discriminant analysis, neural networks performed better in terms of correctly classified individuals at any taxonomical level. For instance, with the simple coding and the hold out procedure, the proportions of correctly assigned individuals from the testing set were 66.2%, 82.3% and 100% at the populations, subspecies and lineage level, respectively. The potential use of neural networks in populations genetics is discussed.

Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data.

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.