A robust method for testing association in genome-wide association studies

In genetic association studies, due to the varying underlying genetic models, no single statistical test can be the most powerful test under all situations. Current studies show that if the underlying genetic models are known, trend-based tests, which outperform the classical Pearson χ2 test, can be constructed. However, when the underlying genetic models are unknown, the χ2 test is usually more robust than trend-based tests. In this paper, we propose a new association test based on a generalized genetic model, namely the generalized order-restricted relative risks model. Through a Monte Carlo simulation study, we show that the proposed association test is generally more powerful than the χ2 test, and more robust than those trend-based tests. The proposed methodologies are also illustrated by some real SNP datasets.     

Residual pattern based test for interactions in two-way ANOVA

This article proposes a new test to detect interactions in replicated two-way ANOVA models, more powerful than the classical F -test and more general than the test of Terbeck and Davies (1998, Annals of Statistics 26, 1279-1305) developed for the case with unconditionally identifiable interaction pattern. We use the parameterization without the conventional restrictions on the interaction terms and base our test on the maximum of the standardized disturbance estimates. We show that our test is unbiased and consistent, and discuss how to estimate the p -value of the test. In a 3 x 3 case, which is our main focus in this article, the exact p -value can be computed by using four-dimensional integrations. For a general I x J case which requires an (I - 1) x (J - 1) dimensional integration for a numerical evaluation of the exact p -value, we propose to use an improved Bonferroni inequality to estimate an upperbound of the p -value and simulations indicate a reasonable accuracy of the upperbound. Via simulations, we show that our test is more powerful than the classical F -test and also that it can deal with both situations: unconditionally identifiable and non-unconditionally identifiable cases. An application to genetic data is presented in which the new test is significant, while the classical F -test failed to detect interactions.     

Landscape characteristics influencing the genetic structure of greater sage‐grouse within the stronghold of their range: a holistic modeling approach

Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high‐ and low‐quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage‐grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low‐quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33‐km‐diameter moving windows were preferred, suggesting small‐scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.     

A new association test based on disease allele selection for case–control genome-wide association studies

Background

Current robust association tests for case–control genome-wide association study (GWAS) data are mainly based on the assumption of some specific genetic models. Due to the richness of the genetic models, this assumption may not be appropriate. Therefore, robust but powerful association approaches are desirable.

Results

In this paper, we propose a new approach to testing for the association between the genotype and phenotype for case–control GWAS. This method assumes a generalized genetic model and is based on the selected disease allele to obtain a p-value from the more powerful one-sided test. Through a comprehensive simulation study we assess the performance of the new test by comparing it with existing methods. Some real data applications are also used to illustrate the use of the proposed test.

Conclusions

Based on the simulation results and real data application, the proposed test is powerful and robust.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-358) contains supplementary material, which is available to authorized users.     

Genetic differentiation of neutral markers and quantitative traits in predominantly selfing metapopulations: confronting theory and experiments with Arabidopsis thaliana

The comparison of the genetic differentiation of quantitative traits (QST) and molecular markers (FST) can inform on the strength and spatial heterogeneity of selection in natural populations, provided that markers behave neutrally. However, selection may influence the behaviour of markers in selfing species with strong linkage disequilibria among loci, therefore invalidating this test of detection of selection. We address this issue by monitoring the genetic differentiation of five microsatellite loci (FST) and nine quantitative traits (QST) in experimental metapopulations of the predominantly selfing species Arabidopsis thaliana, that evolved during eight generations. Metapopulations differed with respect to population size and selection heterogeneity. In large populations, the genetic differentiation of neutral microsatellites was much larger under heterogeneous selection than under uniform selection. Using simulations, we show that this influence of selection heterogeneity on FST can be attributable to initial linkage disequilibria among loci, creating stronger genetic differentiation of QTL than expected under a simple additive model with no initial linkage. We found no significant differences between FST and QST regardless of selection heterogeneity, despite a demonstrated effect of selection on QST values. Additional data are required to validate the role of mating system and linkage disequilibria in the joint evolution of neutral and selected genetic differentiation, but our results suggest that FST/QST comparisons can be conservative tests to detect selection in selfing species.     

Geographical and Ecological Drivers of Mitonuclear Genetic Divergence in a Mediterranean Grasshopper

The study of the neutral and/or selective processes driving genetic variation in natural populations is central to determine the evolutionary history of species and lineages and understand how they interact with different historical and contemporary components of landscape heterogeneity. Here, we combine nuclear and mitochondrial data to study the processes shaping genetic divergence in the Mediterranean esparto grasshopper (Ramburiella hispanica). Our analyses revealed the presence of three main lineages, two in Europe that split in the Early-Middle Pleistocene and one in North Africa that diverged from the two European ones after the Messinian. Lineage-specific potential distribution models and tests of environmental niche differentiation suggest that the phylogeographic structure of the species was driven by allopatric divergence due to the re-opening of the Gibraltar strait at the end of the Messinian (Europe–Africa split) and population fragmentation in geographically isolated Pleistocene climatic refugia (European split). Although we found no evidence for environment as an important driver of genetic divergence at the onset of lineage formation, our analyses considering the spatial distribution of populations and different aspects of landscape composition suggest that genetic differentiation at mitochondrial loci was largely explained by environmental dissimilarity, whereas resistance-based estimates of geographical distance were the only predictors of genetic differentiation at nuclear markers. Overall, our study shows that although historical factors have largely shaped concordant range-wide patterns of mitonuclear genetic structure in the esparto grasshopper, different contemporary processes (neutral gene flow vs. environmental-based selection) seem to be governing the spatial distribution of genetic variation in the two genomes.     

Drivers of genetic differentiation in a generalist insect‐pollinated herb across spatial scales

The isolation‐by‐distance model (IBD) predicts that genetic differentiation among populations increases with geographic distance. Yet, empirical studies show that a variety of ecological, topographic and historical factors may override the effect of geographic distance on genetic variation. This may particularly apply to species with narrow but highly heterogeneous distribution ranges, such as those occurring along elevational gradients. Using nine SSR markers, we study the genetic differentiation of the montane pollination‐generalist herb, Erysimum mediohispanicum. Because the effects of any given factor may depend on the geographic scale considered, we investigate the contribution of different environmental and historical factors at three different spatial scales. We evaluate five competing models that put forward the role of geographic distance, local environmental factors [biotic interactions (IBEb) and climatic variables (IBEa)], landscape resistance (IBR) and phylogeographic patterns (IBP), respectively. We find significant IBD regardless of the spatial scale and the genetic distance estimator considered. However, IBEa and IBP also play a prominent role in shaping genetic differentiation patterns at the larger spatial scales, and IBR is significant at the fine spatial scale. Overall, our results highlight the importance of combining different estimators, statistical approaches and spatial scales to disentangle the relative importance of the various ecological factors contributing to the shaping of genetic divergence patterns in natural populations.     

A genetic association test through combining two independent tests

Gene- and pathway-based variant association tests are important tools in finding genetic variants that are associated with phenotypes of interest. Although some methods have been proposed in the literature, powerful and robust statistical tests are still desirable in this area. In this study, we propose a statistical test based on decomposing the genotype data into orthogonal parts from which powerful and robust independent p-value combination approaches can be utilized. Through a comprehensive simulation study, we compare the proposed test with some existing popular ones. Our simulation results show that the new test has great performance in terms of controlling type I error rate and statistical power. Real data applications are also conducted to illustrate the performance and usefulness of the proposed test.     

Genetic and morphological divergence reveals local subdivision of perch (Perca fluviatilis L.)

The level of gene flow is an important factor influencing genetic differentiation between populations. Typically, geographic distance is considered to be the major factor limiting dispersal and should thus only influence the degree of genetic divergence at larger spatial scales. However, recent studies have revealed the possibility for small-scale genetic differentiation, suggesting that the spatial scale considered is pivotal for finding patterns of isolation by distance. To address this question, genetic and morphological differentiation were studied at two spatial scales (range 2–13 km and range 300 m to 2 km) in the perch ( Perca fluviatilis L.) from the east coast archipelago of Sweden, using seven microsatellite loci and geometric morphometrics. We found highly significant genetic differentiation between sampled locations at both scales. At the larger spatial scale, the distance per se was not affecting the level of divergence. At the small scale, however, we found subtle patterns of isolation by distance. In addition, we also found morphological divergence between locations, congruent with a spatial separation at a microgeographic scale, most likely due to phenotypic plasticity. The present study highlights the importance of geographical scale and indicates that there might be a disparity between the dispersal capacity of a species and the actual movement of genes. Thus, how we view the environment and possible barriers to dispersal might have great implications for our ability to fully understand the evolution of genetic differentiation, local adaptation, and, in the end, speciation.  © 2009 The Linnean Society of London, Biological Journal of the Linnean Society , 2009, 96 , 746–758.     

Population structure of North American beluga whales (Delphinapterus leucas) based on nuclear DNA microsatellite variation and contrasted with the population structure revealed by mitochondrial DNA variation

Beluga whales ( Delphinapterus leucas ) in North American waters migrate seasonally between wintering areas in broken pack ice and summering locations in estuaries and other open water areas in the Arctic and sub-Arctic. Results from our previous investigation of beluga whale mitochondrial DNA (mtDNA) revealed genetic heterogeneity among beluga from different summering locations that was interpreted as representing a high degree of summering site philopatry. However, mtDNA is maternally inherited and does not reflect mating that may occur among beluga from different summering locations in wintering areas or during annual migrations. To test the possibility that breeding occurs among beluga from different summering locations, genetic variability at five nuclear DNA (nDNA) microsatellite loci was examined in the same animals tested in the mtDNA study. Beluga samples ( n = 640) were collected between 1984 and 1994 from 24 sites across North America, mostly during the summer. Whales from the various sites were categorized into eight summering locations as identified by mtDNA analysis, as well as four hypothesized wintering areas: Bering Sea, Hudson Strait (Hudson Strait, Labrador Sea, southwest Davis Strait), Baffin Bay (North Water, east Davis Strait), and St Lawrence River. Microsatellite allele frequencies indicated genetic homogeneity among animals from summering sites believed to winter together but differentiation among whales from some of the wintering areas. In particular, beluga from western North America (Bering Sea) were clearly distinguished from beluga from eastern North America (Hudson Strait, Baffin Bay, and St Lawrence River). Based upon the combined data set, the population of North American beluga whales was divided into two evolutionarily significant units. However, the population may be further subdivided into management units to reflect distinct groups of beluga at summering locations.     

Population structure of North American beluga whales (Delphinapterus leucas) based on nuclear DNA microsatellite variation and contrasted with the population structure revealed by mitochondrial DNA variation

Beluga whales ( Delphinapterus leucas ) in North American waters migrate seasonally between wintering areas in broken pack ice and summering locations in estuaries and other open water areas in the Arctic and sub-Arctic. Results from our previous investigation of beluga whale mitochondrial DNA (mtDNA) revealed genetic heterogeneity among beluga from different summering locations that was interpreted as representing a high degree of summering site philopatry. However, mtDNA is maternally inherited and does not reflect mating that may occur among beluga from different summering locations in wintering areas or during annual migrations. To test the possibility that breeding occurs among beluga from different summering locations, genetic variability at five nuclear DNA (nDNA) microsatellite loci was examined in the same animals tested in the mtDNA study. Beluga samples ( n = 640) were collected between 1984 and 1994 from 24 sites across North America, mostly during the summer. Whales from the various sites were categorized into eight summering locations as identified by mtDNA analysis, as well as four hypothesized wintering areas: Bering Sea, Hudson Strait (Hudson Strait, Labrador Sea, southwest Davis Strait), Baffin Bay (North Water, east Davis Strait), and St Lawrence River. Microsatellite allele frequencies indicated genetic homogeneity among animals from summering sites believed to winter together but differentiation among whales from some of the wintering areas. In particular, beluga from western North America (Bering Sea) were clearly distinguished from beluga from eastern North America (Hudson Strait, Baffin Bay, and St Lawrence River). Based upon the combined data set, the population of North American beluga whales was divided into two evolutionarily significant units. However, the population may be further subdivided into management units to reflect distinct groups of beluga at summering locations.     

Most Powerful Permutation Invariant Tests for Relatedness Hypotheses Using Genotypic Data

The problem of inferring kinship structure among a sample of individuals using genetic markers is considered with the objective of developing hypothesis tests for genetic relatedness with nearly optimal properties. The class of tests considered are those that are constrained to be permutation invariant, which in this context defines tests whose properties do not depend on the labeling of the individuals. This is appropriate when all individuals are to be treated identically from a statistical point of view. The approach taken is to derive tests that are probably most powerful for a permutation invariant alternative hypothesis that is, in some sense, close to a null hypothesis of mutual independence. This is analagous to the locally most powerful test commonly used in parametric inference. Although the resulting test statistic is a U-statistic, normal approximation theory is found to be inapplicable because of high skewness. As an alternative it is found that a conditional procedure based on the most powerful test statistic can calculate accurate significance levels without much loss in power. Examples are given in which this type of test proves to be more powerful than a number of alternatives considered in the literature, including Queller and Goodknight's (1989) estimate of genetic relatedness, the average number of shared alleles (Blouin, 1996), and the number of feasible sibling triples (Almudevar and Field, 1999).     

Colonization genetics of an animal-dispersed plant (Vaccinium membranaceum) at Mount St Helens, Washington

Population founding and spatial spread may profoundly influence later population genetic structure, but their effects are difficult to quantify when population history is unknown. We examined the genetic effects of founder group formation in a recently founded population of the animal-dispersed Vaccinium membranaceum (black huckleberry) on new volcanic deposits at Mount St Helens (Washington, USA) 24 years post-eruption. Using amplified fragment length polymorphisms and assignment tests, we determined sources of the newly founded population and characterized genetic variation within new and source populations. Our analyses indicate that while founders were derived from many sources, about half originated from a small number of plants that survived the 1980 eruption in pockets of remnant soil embedded within primary successional areas. We found no evidence of a strong founder effect in the new population; indeed genetic diversity in the newly founded population tended to be higher than in some of the source regions. Similarly, formation of the new population did not increase among-population genetic variance, and there was no evidence of kin-structured dispersal in the new population. These results indicate that high gene flow among sources and long-distance dispersal were important processes shaping the genetic diversity in this young V. membranaceum population. Other species with similar dispersal abilities may also be able to colonize new habitats without significant reduction in genetic diversity or increase in differentiation among populations.     

Effect of anthropogenic landscape features on population genetic differentiation of Przewalski's gazelle: main role of human settlement

Anthropogenic landscapes influence evolutionary processes such as population genetic differentiation, however, not every type of landscape features exert the same effect on a species, hence it is necessary to estimate their relative effect for species management and conservation. Przewalski's gazelle (Procapra przewalskii), which inhabits a human-altered area on Qinghai-Tibet Plateau, is one of the most endangered antelope species in the world. Here, we report a landscape genetic study on Przewalski's gazelle. We used skin and fecal samples of 169 wild gazelles collected from nine populations and thirteen microsatellite markers to assess the genetic effect of anthropogenic landscape features on this species. For comparison, the genetic effect of geographical distance and topography were also evaluated. We found significant genetic differentiation, six genetic groups and restricted dispersal pattern in Przewalski's gazelle. Topography, human settlement and road appear to be responsible for observed genetic differentiation as they were significantly correlated with both genetic distance measures [F(ST)/(1-F(ST)) and F'(ST)/(1-F'(ST))] in Mantel tests. IBD (isolation by distance) was also inferred as a significant factor in Mantel tests when genetic distance was measured as F(ST)/(1-F(ST)). However, using partial Mantel tests, AIC(c) calculations, causal modeling and AMOVA analysis, we found that human settlement was the main factor shaping current genetic differentiation among those tested. Altogether, our results reveal the relative influence of geographical distance, topography and three anthropogenic landscape-type on population genetic differentiation of Przewalski's gazelle and provide useful information for conservation measures on this endangered species.     

Integrative approach revealed contrasting pattern of spatial structuring within urban and rural biotypes of Culex pipiens

Population structure of pests is an important issue when designing management strategies to optimize control measures. In this study, we investigated a spatial pattern of genetic and phenotypic variation within seven urban and within six rural populations of Culex pipiens from Vojvodina Province (Serbia) incorporating landscape genetic methods (using allozyme data) and wing size and shape (using geometric morphometric approach). Comparing rural samples, no strong genetic groupings of individuals were detected. Nevertheless, traditional approaches where individuals are pre‐assigned to populations, including F statistics and amova (analysis of molecular variance), revealed low, but significant genetic differentiation among samples. Similarly, phenotypic data (wing size and shape) indicated some level of heterogeneity among rural samples. Contrary to genetic homogeneity found within rural biotype, the individual‐based structuring characterized urban biotype. Geneland revealed the presence of two genetic clusters within urban group which is in concordance with F_ST and amova results. These results showed that sample from Novi Sad (NS) is a distinct genetic unit, which has been likely resulted in intensive insecticide use over several decades. Furthermore, phenotypic differentiation supported the existence of spatial structuring. Therefore, complementary use of molecular markers and phenotypic traits may be a powerful tool for revealing hidden spatial diversity within Cx. pipiens.     

Genetic spatial autocorrelation can readily detect sex-biased dispersal

Sex-biased dispersal is expected to generate differences in the fine-scale genetic structure of males and females. Therefore, spatial analyses of multilocus genotypes may offer a powerful approach for detecting sex-biased dispersal in natural populations. However, the effects of sex-biased dispersal on fine-scale genetic structure have not been explored. We used simulations and multilocus spatial autocorrelation analysis to investigate how sex-biased dispersal influences fine-scale genetic structure. We evaluated three statistical tests for detecting sex-biased dispersal: bootstrap confidence intervals about autocorrelation r values and recently developed heterogeneity tests at the distance class and whole correlogram levels. Even modest sex bias in dispersal resulted in significantly different fine-scale spatial autocorrelation patterns between the sexes. This was particularly evident when dispersal was strongly restricted in the less-dispersing sex (mean distance <200 m), when differences between the sexes were readily detected over short distances. All tests had high power to detect sex-biased dispersal with large sample sizes (n ≥ 250). However, there was variation in type I error rates among the tests, for which we offer specific recommendations. We found congruence between simulation predictions and empirical data from the agile antechinus, a species that exhibits male-biased dispersal, confirming the power of individual-based genetic analysis to provide insights into asymmetries in male and female dispersal. Our key recommendations for using multilocus spatial autocorrelation analyses to test for sex-biased dispersal are: (i) maximize sample size, not locus number; (ii) concentrate sampling within the scale of positive structure; (iii) evaluate several distance class sizes; (iv) use appropriate methods when combining data from multiple populations; (v) compare the appropriate groups of individuals.     

Seascape genomics provides evidence for thermal adaptation and current‐mediated population structure in American lobster (Homarus americanus)

Investigating how environmental features shape the genetic structure of populations is crucial for understanding how they are potentially adapted to their habitats, as well as for sound management. In this study, we assessed the relative importance of spatial distribution, ocean currents and sea surface temperature (SST) on patterns of putatively neutral and adaptive genetic variation among American lobster from 19 locations using population differentiation (PD) approaches combined with environmental association (EA) analyses. First, PD approaches (using bayescan , arlequin and outflank ) found 28 outlier SNPs putatively under divergent selection and 9770 neutral SNPs in common. Redundancy analysis revealed that spatial distribution, ocean current‐mediated larval connectivity and SST explained 31.7% of the neutral genetic differentiation, with ocean currents driving the majority of this relationship (21.0%). After removing the influence of spatial distribution, no SST were significant for putatively neutral genetic variation whereas minimum annual SST still had a significant impact and explained 8.1% of the putatively adaptive genetic variation. Second, EA analyses (using Pearson correlation tests, bayescenv and lfmm ) jointly identified seven SNPs as candidates for thermal adaptation. Covariation at these SNPs was assessed with a spatial multivariate analysis that highlighted a significant temperature association, after accounting for the influence of spatial distribution. Among the 505 candidate SNPs detected by at least one of the three approaches, we discovered three polymorphisms located in genes previously shown to play a role in thermal adaptation. Our results have implications for the management of the American lobster and provide a foundation on which to predict how this species will cope with climate change.     

Multiple spatial scale patterns of genetic diversity in riparian populations of Ainsliaea faurieana (Asteraceae) on Yakushima Island, Japan

Habitat and geographical features of river systems strongly influence gene flow and spatial genetic patterning in riparian plant populations. We investigated the patterns of genetic diversity within and among populations of Ainsliaea faurieana relative to different spatial conditions (along a river, among rivers, and among regions on an island), based on nuclear and chloroplast microsatellite DNA variations. Within an individual river system, we found higher haplotype diversities in downstream populations, and in a Bayesian analysis of recent migration, we detected unidirectional gene movements from upstream to downstream, indicating water-mediated dispersal along the river. Mantel tests detected no isolation-by-distance in genetic variation, suggesting the maintenance of a metapopulation with wide-range seed dispersal by water. Moreover, the observed high level of genetic differentiation, especially in the cpDNA (F(ST) = 0.539), indicated a metapopulation structure with frequent extinction and colonization. On a larger scale, we found high population differentiation and clear genetic structuring among regions, suggesting that gene flow was restricted by geographical features (mountains separating river systems) for relatively long periods. Our findings of genetic structures based on different spatial conditions elucidated patterns and ranges of historical and contemporary gene movement in a plant species that is persistent in extremely disturbed riparian environments.     

Spatiotemporal segregation among summer stocks of beluga (Delphinapterus leucas) despite nuclear gene flow: implication for the endangered belugas in eastern Hudson Bay (Canada)

Migratory connectivity between areas frequented by wide-ranging animals provides crucial information for conservation and management. In and around Hudson Bay (Canada), three stocks of beluga whales (Delphinapterus leucas) are associated with distinct summering areas. We analyzed genetic variation at mtDNA and 13 microsatellite loci among individuals (N > 1400) harvested by 23 Inuit communities to identify mating units and assess temporal and spatial differences in the way stocks use common migratory pathways. Strong structure at mtDNA and a lack of convincing evidence for nuclear genetic differentiation indicate that both males and females adopt distinct migratory routes towards summering grounds while probably interbreeding on wintering grounds. Spatiotemporal variation in stock composition indicates that subsistence hunting targets all three stocks. While representing ca. 5% of belugas in Hudson Bay, the endangered Eastern Hudson Bay stock accounts for 17% of the overall subsistence harvest by Inuit communities of northern Nunavik (Quebec), and ca. 30% of the spring harvest along northeastern Hudson Bay. Despite interbreeding, cultural conservatism of maternally transmitted migration routes seems to prevent the re-establishment of stocks in previously frequented estuaries. This phenomenon supports the current use of demographic population models based on stock composition for developing behavior-based management strategies.     

Genetic structure and dispersal in a small South African rodent. Is dispersal female-biased?

Dispersal greatly determines genetic structure of populations, although it is influenced by landscape heterogeneity, quality of the matrix, resource distribution and local population densities and dynamics. To get insights into some of those processes we analysed the genetic structure of the hairy-footed gerbil Gerbillurus paeba (Rodentia, Murinae, Gerbillinae) in the southern Kalahari (South Africa). Samples were taken from 20 populations covering an area of about 2200 km². Genetic data were related to landscape characters and population dynamics. We used newly developed microsatellites and found at all loci some indication for the presence of null alleles. However, null alleles seem to have little influence on the general results of our analyses. Altogether we found even nearby populations of G. paeba to be significantly differentiated, although assignment tests revealed 24% of individuals as immigrants. Genetic structure was independent of landscape heterogeneities at all spatial scales. Autocorrelation analyses (range 50–90 km) revealed significant genetic structure within populations on distances <3 km. We found some indication for female-biased dispersal. Our study suggests that dispersing individuals have little influence on the long-term genetic structure and that drift is the major cause of genetic diversity. The observed genetic pattern likely derives from strong population fluctuations of G. paeba. The landscape structure has little influence on the genetic differentiation between populations.