Showing papers in "Molecular Ecology in 2004"

The incomplete natural history of mitochondria

Abstract: Mitochondrial DNA (mtDNA) has been used to study molecular ecology and phylogeography for 25 years. Much important information has been gained in this way, but it is time to reflect on the biology of the mitochondrion itself and consider opportunities for evolutionary studies of the organelle itself and its ecology, biochemistry and physiology. This review has four sections. First, we review aspects of the natural history of mitochondria and their DNA to show that it is a unique molecule with specific characteristics that differ from nuclear DNA. We do not attempt to cover the plethora of differences between mitochondrial and nuclear DNA; rather we spotlight differences that can cause significant bias when inferring demographic properties of populations and/or the evolutionary history of species. We focus on recombination, effective population size and mutation rate. Second, we explore some of the difficulties in interpreting phylogeographical data from mtDNA data alone and suggest a broader use of multiple nuclear markers. We argue that mtDNA is not a sufficient marker for phylogeographical studies if the focus of the investigation is the species and not the organelle. We focus on the potential bias caused by introgression. Third, we show that it is not safe to assume a priori that mtDNA evolves as a strictly neutral marker because both direct and indirect selection influence mitochondria. We outline some of the statistical tests of neutrality that can, and should, be applied to mtDNA sequence data prior to making any global statements concerning the history of the organism. We conclude with a critical examination of the neglected biology of mitochondria and point out several surprising gaps in the state of our knowledge about this important organelle. Here we limelight mitochondrial ecology, sexually antagonistic selection, life-history evolution including ageing and disease, and the evolution of mitochondrial inheritance.

Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants.

Abstract: A compilation was made of 307 studies using nuclear DNA markers for evaluating among- and within-population diversity in wild angiosperms and gymnosperms. Estimates derived by the dominantly inherited markers (RAPD, AFLP, ISSR) are very similar and may be directly comparable. STMS analysis yields almost three times higher values for within-population diversity whereas among-population diversity estimates are similar to those derived by the dominantly inherited markers. Number of sampled plants per population and number of scored microsatellite DNA alleles are correlated with some of the population genetics parameters. In addition, maximum geographical distance between sampled populations has a strong positive effect on among-population diversity. As previously verified with allozyme data, RAPD- and STMS-based analyses show that long-lived, outcrossing, late successional taxa retain most of their genetic variability within populations. By contrast, annual, selfing and/or early successional taxa allocate most of the genetic variability among populations. Estimates for among- and within-population diversity, respectively, were negatively correlated. The only major discrepancy between allozymes and STMS on the one hand, and RAPD on the other hand, concerns geographical range; within-population diversity was strongly affected when the former methods were used but not so in the RAPD-based studies. Direct comparisons between the different methods, when applied to the same plant material, indicate large similarities between the dominant markers and somewhat lower similarity with the STMS-based data, presumably due to insufficient number of analysed microsatellite DNA loci in many studies.

Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power

Abstract: Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (DLR) appeared to be an effective way to predict whether F0 immigrants could be identified for a particular pair of populations using a given set of markers.

How to track and assess genotyping errors in population genetics studies.

Abstract: Genotyping errors occur when the genotype determined after molecular analysis does not correspond to the real genotype of the individual under consideration. Virtually every genetic data set includes some erroneous genotypes, but genotyping errors remain a taboo subject in population genetics, even though they might greatly bias the final conclusions, especially for studies based on individual identification. Here, we consider four case studies representing a large variety of population genetics investigations differing in their sampling strategies (noninvasive or traditional), in the type of organism studied (plant or animal) and the molecular markers used [microsatellites or amplified fragment length polymorphisms (AFLPs)]. In these data sets, the estimated genotyping error rate ranges from 0.8% for microsatellite loci from bear tissues to 2.6% for AFLP loci from dwarf birch leaves. Main sources of errors were allelic dropouts for microsatellites and differences in peak intensities for AFLPs, but in both cases human factors were non-negligible error generators. Therefore, tracking genotyping errors and identifying their causes are necessary to clean up the data sets and validate the final results according to the precision required. In addition, we propose the outline of a protocol designed to limit and quantify genotyping errors at each step of the genotyping process. In particular, we recommend (i) several efficient precautions to prevent contaminations and technical artefacts; (ii) systematic use of blind samples and automation; (iii) experience and rigor for laboratory work and scoring; and (iv) systematic reporting of the error rate in population genetics studies.

New insights from fine-scale spatial genetic structure analyses in plant populations.

Abstract: Many empirical studies have assessed fine-scale spatial genetic structure (SGS), i.e. the nonrandom spatial distribution of genotypes, within plant populations using genetic markers and spatial autocorrelation techniques. These studies mostly provided qualitative descriptions of SGS, rendering quantitative comparisons among studies difficult. The theory of isolation by distance can predict the pattern of SGS under limited gene dispersal, suggesting new approaches, based on the relationship between pairwise relatedness coefficients and the spatial distance between individuals, to quantify SGS and infer gene dispersal parameters. Here we review the theory underlying such methods and discuss issues about their application to plant populations, such as the choice of the relatedness statistics, the sampling scheme to adopt, the procedure to test SGS, and the interpretation of spatial autocorrelograms. We propose to quantify SGS by an ‘ Sp ’ statistic primarily dependent upon the rate of decrease of pairwise kinship coefficients between individuals with the logarithm of the distance in two dimensions. Under certain conditions, this statistic estimates the reciprocal of the neighbourhood size. Reanalysing data from, mostly, published studies, the Sp statistic was assessed for 47 plant species. It was found to be significantly related to the mating system (higher in selfing species) and to the life form (higher in herbs than trees), as well as to the population density (higher under low density). We discuss the necessity for comparing SGS with direct estimates of gene dispersal distances, and show how the approach presented can be extended to assess (i) the level of biparental inbreeding, and (ii) the kurtosis of the gene dispersal distribution.

Integrating QTL mapping and genome scans towards the characterization of candidate loci under parallel selection in the lake whitefish (Coregonus clupeaformis).

Abstract: As natural selection must act on underlying genetic variation, discovering the number and location of loci under the influence of selection is imperative towards understanding adaptive divergence in evolving populations. Studies employing genome scans have hypothesized that the action of divergent selection should reduce gene flow at the genomic locations implicated in adaptation and speciation among natural populations, yet once ‘outlier’ patterns of variation have been identified the function and role of such loci needs to be confirmed. We integrated adaptive QTL mapping and genomic scans among diverging sympatric pairs of the lake whitefish (Coregonus clupeaformis) species complex in order to test the hypothesis that differentiation between dwarf and normal ecotypes at growth-associated QTL was maintained by directional selection. We found evidence of significantly high levels of molecular divergence among eight growth QTL where two of the strongest candidate loci under the influence of directional selection exhibited parallel reductions of gene flow over multiple populations.

Identifying adaptive genetic divergence among populations from genome scans

Abstract: 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.

Comparative organization of chloroplast, mitochondrial and nuclear diversity in plant populations.

Abstract: Plants offer excellent models to investigate how gene flow shapes the organization of genetic diversity. Their three genomes can have different modes of transmission and will hence experience varying levels of gene flow. We have compiled studies of genetic structure based on chloroplast DNA (cpDNA), mitochondrial DNA (mtDNA) and nuclear markers in seed plants. Based on a data set of 183 species belonging to 103 genera and 52 families, we show that the precision of estimates of genetic differentiation ( G ST ) used to infer gene flow is mostly constrained by the sampling of populations. Mode of inheritance appears to have a major effect on G ST . Maternally inherited genomes experience considerably more subdivision (median value of 0.67) than paternally or biparentally inherited genomes ( ∼ 0.10). G ST at cpDNA and mtDNA markers covary narrowly when both genomes are maternally inherited, whereas G ST at paternally and biparentally inherited markers also covary positively but more loosely and G ST at maternally inherited markers are largely independent of values based on nuclear markers. A model-based gross estimate suggests that, at the rangewide scale, historical levels of pollen flow are generally at least an order of magnitude larger than levels of seed flow (median of the pollen-to-seed migration ratio: 17) and that pollen and seed gene flow vary independently across species. Finally, we show that measures of subdivision that take into account the degree of similarity between haplotypes ( N ST or R ST ) make better use of the information inherent in haplotype data than standard measures based on allele frequencies only.

Statistical phylogeography: methods of evaluating and minimizing inference errors.

Abstract: Nested clade phylogeographical analysis (NCPA) has become a common tool in intraspecific phylogeography. To evaluate the validity of its inferences, NCPA was applied to actual data sets with 150 strong a priori expectations, the majority of which had not been analysed previously by NCPA. NCPA did well overall, but it sometimes failed to detect an expected event and less commonly resulted in a false positive. An examination of these errors suggested some alterations in the NCPA inference key, and these modifications reduce the incidence of false positives at the cost of a slight reduction in power. Moreover, NCPA does equally well in inferring events regardless of the presence or absence of other, unrelated events. A reanalysis of some recent computer simulations that are seemingly discordant with these results revealed that NCPA performed appropriately in these simulated samples and was not prone to a high rate of false positives under sampling assumptions that typify real data sets. NCPA makes a posteriori use of an explicit inference key for biological interpretation after statistical hypothesis testing. Alternatives to NCPA that claim that biological inference emerges directly from statistical testing are shown in fact to use an a priori inference key, albeit implicitly. It is argued that the a priori and a posteriori approaches to intraspecific phylogeography are complementary, not contradictory. Finally, cross-validation using multiple DNA regions is shown to be a powerful method of minimizing inference errors. A likelihood ratio hypothesis testing framework has been developed that allows testing of phylogeographical hypotheses, extends NCPA to testing specific hypotheses not within the formal inference key (such as the out-of-Africa replacement hypothesis of recent human evolution) and integrates intra- and interspecific phylogeographical inference.

Genetic quality and sexual selection: an integrated framework for good genes and compatible genes.

Abstract: Why are females so choosy when it comes to mating? This question has puzzled and marveled evolutionary and behavioral ecologists for decades. In mating systems in which males provide direct benefits to the female or her offspring, such as food or shelter, the answer seems straightforward — females should prefer to mate with males that are able to provide more resources. The answer is less clear in other mating systems in which males provide no resources (other than sperm) to females. Theoretical models that account for the evolution of mate choice in such nonresource-based mating systems require that females obtain a genetic benefit through increased offspring fitness from their choice. Empirical studies of nonresourcebased mating systems that are characterized by strong female choice for males with elaborate sexual traits (like the large tail of peacocks) suggest that additive genetic benefits can explain only a small percentage of the variation in fitness. Other research on genetic benefits has examined nonadditive effects as another source of genetic variation in fitness and a potential benefit to female mate choice. In this paper, we review the sexual selection literature on genetic quality to address five objectives. First, we attempt to provide an integrated framework for discussing genetic quality. We propose that the term ‘good gene’ be used exclusively to refer to additive genetic variation in fitness, ‘compatible gene’ be used to refer to nonadditive genetic variation in fitness, and ‘genetic quality’ be defined as the sum of the two effects. Second, we review empirical approaches used to calculate the effect size of genetic quality and discuss these approaches in the context of measuring benefits from good genes, compatible genes and both types of genes. Third, we discuss biological mechanisms for acquiring and promoting offspring genetic quality and categorize these into three stages during breeding: (i) precopulatory (mate choice); (ii) postcopulatory, prefertilization (sperm utilization); and (iii) postcopulatory, postfertilization (differential investment). Fourth, we present a verbal model of the effect of good genes sexual selection and compatible genes sexual selection on population genetic variation in fitness, and discuss the potential trade-offs that might exist between mate choice for good genes and mate choice for compatible genes. Fifth, we discuss some future directions for research on genetic quality and sexual selection.

Patterns of DNA sequence diversity and genetic structure after a range expansion: lessons from the infinite-island model

Abstract: It has been long recognized that population demographic expansions lead to distinctive features in the molecular diversity of populations. However, recent simulation results have suggested that a distinction could be made between a pure demographic expansion in an unsubdivided population, and a range expansion in a subdivided population, both leading to a large increase in the total number of the individuals. In order to better characterize the effect of a range expansion, I introduce a simple model of instantaneous expansion under an infinite-island model, under which I derive the distribution of the number of mutation differences between pairs of genes (the mismatch distribution), the heterozygosity, the average number of pairwise difference, and the fixation index F(ST). These derivations are checked against simulations, and are shown to lead to results qualitatively similar to those one would obtain after a range expansion in a 2-dimensional stepping-stone model. I then apply these results to estimate immigration rates in hunter-gather and post-Neolithic human populations from patterns of mitochondrial (mtDNA) diversity. Potential problems with this estimation procedure are also discussed.

Microsatellite genotyping errors : detection approaches, common sources and consequences for paternal exclusion

Abstract: Microsatellite genotyping errors will be present in all but the smallest data sets and have the potential to undermine the conclusions of most downstream analyses. Despite this, little rigorous effort has been made to quantify the size of the problem and to identify the commonest sources of error. Here, we use a large data set comprising almost 2000 Antarctic fur seals Arctocephalus gazella genotyped at nine hypervariable microsatellite loci to explore error detection methods, common sources of error and the consequences of errors on paternal exclusion. We found good concordance among a range of contrasting approaches to error-rate estimation, our range being 0.0013 to 0.0074 per single locus PCR (polymerase chain reaction). The best approach probably involves blind repeat-genotyping, but this is also the most labour-intensive. We show that several other approaches are also effective at detecting errors, although the most convenient alternative, namely mother-offspring comparisons, yielded the lowest estimate of the error rate. In total, we found 75 errors, emphasizing their ubiquitous presence. The most common errors involved the misinterpretation of allele banding patterns (n = 60, 80%) and of these, over a third (n = 22, 36.7%) were due to confusion between homozygote and adjacent allele heterozygote genotypes. A specific test for whether a data set contains the expected number of adjacent allele heterozygotes could provide a useful tool with which workers can assess the likely size of the problem. Error rates are also positively correlated with both locus polymorphism and product size, again indicating aspects where extra effort at error reduction should be directed. Finally, we conducted simulations to explore the potential impact of genotyping errors on paternity exclusion. Error rates as low as 0.01 per allele resulted in a rate of false paternity exclusion exceeding 20%. Errors also led to reduced estimates of male reproductive skew and increases in the numbers of pups that matched more than one candidate male. Because even modest error rates can be strongly influential, we recommend that error rates should be routinely published and that researchers make an attempt to calculate how robust their analyses are to errors.

Does heterozygosity estimate inbreeding in real populations

Abstract: Many recent studies report that individual heterozygosity at a handful of apparently neutral microsatellite markers is correlated with key components of fitness, with most studies invoking inbreeding depression as the likely underlying mechanism. The implicit assumption is that an individual's inbreeding coefficient can be estimated reliably using only 10 or so markers, but the validity of this assumption is unclear. Consequently, we have used individual-based simulations to examine the conditions under which heterozygosity and inbreeding are likely to be correlated. Our results indicate that the parameter space in which this occurs is surprisingly narrow, requiring that inbreeding events are both frequent and severe, for example, through selfing, strong population structure and/or high levels of polygyny. Even then, the correlations are strong only when large numbers of loci (~200) can be deployed to estimate heterozygosity. With the handful of markers used in most studies, correlations only become likely under the most extreme scenario we looked at, namely 20 demes of 20 individuals coupled with strong polygyny. This finding is supported by the observation that heterozygosity is only weakly correlated among markers within an individual, even in a dataset comprising 400 markers typed in diverse human populations, some of which favour consanguineous marriages. If heterozygosity and inbreeding coefficient are generally uncorrelated, then heterozygosity-fitness correlations probably have little to do with inbreeding depression. Instead, one would need to invoke chance linkage between the markers used and one or more gene(s) experiencing balancing selection. Unfortunately, both explanations sit somewhat uncomfortably with current understanding. If inbreeding is the dominant mechanism, then our simulations indicate that consanguineous mating would have to be vastly more common than is predicted for most realistic populations. Conversely, if heterosis provides the answer, there need to be many more polymorphisms with major fitness effects and higher levels of linkage disequilibrium than are generally assumed.

A simple method for the calculation of microsatellite genotype distances irrespective of ploidy level.

Abstract: Microsatellites are powerful molecular markers, used commonly to estimate intraspecific genetic distances. With the exception of band sharing similarity index, available distance measures were developed specifically for diploid organisms and are unsuited for comparisons of polyploids. Here, we present a simple method for calculation of microsatellite genotype distances, which takes into account mutation processes and permits comparison of individuals with different ploidy levels. This method should provide a valuable tool for intraspecific analyses of polyploid organisms, which are widespread among plants and some animal taxa. An illustration is given using data from the planarian flatworm Schmidtea polychroa (Platyhelminthes).

How species evolve collectively: implications of gene flow and selection for the spread of advantageous alleles

Abstract: The traditional view that species are held together through gene flow has been challenged by observations that migration is too restricted among populations of many species to prevent local divergence. However, only very low levels of gene flow are necessary to permit the spread of highly advantageous alleles, providing an alternative means by which low-migration species might be held together. We re-evaluate these arguments given the recent and wide availability of indirect estimates of gene flow. Our literature review of F(ST) values for a broad range of taxa suggests that gene flow in many taxa is considerably greater than suspected from earlier studies and often is sufficiently high to homogenize even neutral alleles. However, there are numerous species from essentially all organismal groups that lack sufficient gene flow to prevent divergence. Crude estimates on the strength of selection on phenotypic traits and effect sizes of quantitative trait loci (QTL) suggest that selection coefficients for leading QTL underlying phenotypic traits may be high enough to permit their rapid spread across populations. Thus, species may evolve collectively at major loci through the spread of favourable alleles, while simultaneously differentiating at other loci due to drift and local selection.

Landscape connectivity influences gene flow in a roe deer population inhabiting a fragmented landscape: an individual-based approach.

Abstract: Changes in agricultural practices and forest fragmentation can have a dramatic effect on landscape connectivity and the dispersal of animals, potentially reducing gene flow within populations. In this study, we assessed the influence of woodland connectivity on gene flow in a traditionally forest-dwelling species--the European roe deer--in a fragmented landscape. From a sample of 648 roe deer spatially referenced within a study area of 55 x 40 km, interindividual genetic distances were calculated from genotypes at 12 polymorphic microsatellite loci. We calculated two geographical distances between each pair of individuals: the Euclidean distance (straight line) and the 'least cost distance' (the trajectory that maximizes the use of wooded corridors). We tested the correlation between genetic pairwise distances and the two types of geographical pairwise distance using Mantel tests. The correlation was better using the least cost distance, which takes into account the distribution of wooded patches, especially for females (the correlation was stronger but not significant for males). These results suggest that in a fragmented woodland area roe deer dispersal is strongly linked to wooded structures and hence that gene flow within the roe deer population is influenced by the connectivity of the landscape.

Factors affecting the amount of genomic DNA extracted from ape faeces and the identification of an improved sample storage method.

Abstract: Genetic analysis using noninvasively collected samples such as faeces continues to pose a formidable challenge because of unpredictable variation in the extent to which usable DNA is obtained. We investigated the influence of multiple variables on the quantity of DNA extracted from faecal samples from wild mountain gorillas and chimpanzees. There was a small negative correlation between temperature at time of collection and the amount of DNA obtained. Storage of samples either in RNAlater solution or dried using silica gel beads produced similar results, but significantly higher amounts of DNA were obtained using a novel protocol that combines a short period of storage in ethanol with subsequent desiccation using silica.

Distribution of the bacterial symbiont Cardinium in arthropods.

Abstract: 'Candidatus Cardinium', a recently described bacterium from the Bacteroidetes group, is involved in diverse reproduction alterations of its arthropod hosts, including cytoplasmic incompatibility, parthenogenesis and feminization. To estimate the incidence rate of Cardinium and explore the limits of its host range, 99 insect and mite species were screened, using primers designed to amplify a portion of Cardinium 16S ribosomal DNA (rDNA). These arthropods were also screened for the presence of the better-known reproductive manipulator, Wolbachia. Six per cent of the species screened tested positive for Cardinium, compared with 24% positive for Wolbachia. Of the 85 insects screened, Cardinium was found in four parasitic wasp species and one armoured scale insect. Of the 14 mite species examined, one predatory mite was found to carry the symbiont. A phylogenetic analysis of all known Cardinium 16S rDNA sequences shows that distantly related arthropods can harbour closely related symbionts, a pattern typical of horizontal transmission. However, closely related Cardinium were found to cluster among closely related hosts, suggesting host specialization and horizontal transmission among closely related hosts. Finally, the primers used revealed the presence of a second lineage of Bacteroidetes symbionts, not related to Cardinium, in two insect species. This second symbiont lineage is closely allied with other arthropod symbionts, such as Blattabacterium, the primary symbionts of cockroaches, and male-killing symbionts of ladybird beetles. The combined data suggest the presence of a diverse assemblage of arthropod-associated Bacteroidetes bacteria that are likely to strongly influence their hosts' biology.

Quantifying genotyping errors in noninvasive population genetics

Abstract: The use of noninvasively collected samples greatly expands the range of ecological issues that may be investigated through population genetics. Furthermore, the difficulty of obtaining reliable genotypes with samples containing low quantities of amplifiable DNA may be overcome by designing optimal genotyping schemes. Such protocols are mainly determined by the rates of genotyping errors caused by false alleles and allelic dropouts. These errors may not be avoided through laboratory procedure and hence must be quantified. However, the definition of genotyping error rates remains elusive and various estimation methods have been reported in the literature. In this paper we proposed accurate codification for the frequencies of false alleles and allelic dropouts. We then reviewed other estimation methods employed in hair- or faeces-based population genetics studies and modelled the bias associated with erroneous methods. It is emphasized that error rates may be substantially underestimated when using an erroneous approach. Genotyping error rates may be important determinants of the outcome of noninvasive studies and hence should be carefully computed and reported.

Can assignment tests measure dispersal

Abstract: Individual-based assignment tests are now standard tools in molecular ecology and have several applications, including the study of dispersal. The measurement of natal dispersal is vital to understanding the ecology of many species, yet the accuracy of assignment tests in situations where natal dispersal is common remains untested in the field. We studied a metapopulation of the grand skink, Oligosoma grande , a large territorial lizard from southern New Zealand. Skink populations occur on isolated, regularly spaced rock outcrops and are characterized by frequent interpopulation dispersal. We examined the accuracy of assignment tests at four replicate sites by comparing long-term mark-and-recapture records of natal dispersal with the results of assignment tests based on microsatellite DNA data. Assignment tests correctly identified the natal population of most individuals (65–100%, depending on the method of assignment), even when interpopulation dispersal was common (5–20% dispersers). They also provided similar estimates of the proportions of skinks dispersing to those estimated by the long-term mark-and-recapture data. Fully and partially Bayesian assignment methods were equally accurate but their accuracy depended on the stringency applied, the degree of genetic differentiation between populations, and the number of loci used. In addition, when assignments required high confidence, the method of assignment (fully or partially Bayesian) had a large bearing on the number of individuals that could be assigned. Because assignment tests require significantly less fieldwork than traditional mark-and-recapture approaches (in this study 7 years), they will provide useful dispersal data in many applied and theoretical situations.

Divergence dates for Malagasy lemurs estimated from multiple gene loci: geological and evolutionary context

Abstract: The lemurs of Madagascar are a unique radiation of primates that show an extraordinary diversity of lifestyles, morphologies and behaviours. However, very little is known about the relative antiquity of lemuriform clades due to the lack of terrestrial fossils for the Tertiary of Madagascar. Here, we employ a Bayesian method to estimate divergence dates within the lemuriform radiation using several unlinked gene loci and multiple fossil calibrations outside the lemuriform clade. Two mitochondrial genes (cytochrome oxidase II and cytochrome b ), two nuclear introns (transthyretin intron 1 and von Willebrand factor gene intron 11) and one nuclear exon (interphotoreceptor retinoid binding protein, exon 1) are used in separate and combined analyses. The genes differ in taxon sampling and evolutionary characteristics but produce congruent date estimates. Credibility intervals narrow considerably in combined analyses relative to separate analyses due to the increased amount of data. We also test the relative effects of multiple vs. single calibration points, finding that, when only single calibration points are employed, divergence dates are systematically underestimated. For the mitochondrial DNA data set, we investigate the effects of sampling density within the mouse lemur radiation (genus Microcebus ). When only two representative species are included, estimated dates throughout the phylogeny are more recent than with the complete-species sample, with basal nodes less affected than recent nodes. The difference appears to be due to the manner in which priors on node ages are constructed in the two analyses. In nearly all analyses, the age of the lemuriform clade is estimated to be approximately 62–65 Ma, with initial radiation of mouse lemurs and true lemurs (genus Eulemur ) occurring approximately 8–12 Ma. The antiquity of the mouse lemur radiation is surprising given the near uniform morphology among species. Moreover, the observation that mouse lemurs and true lemurs are of similar ages suggests discrepancies in rates of morphological, behavioural and physiological evolution in the two clades, particularly with regard to characteristics of sexual signalling. These differences appear to correlate with the nocturnal vs. diurnal lifestyles, respectively, of these two primate groups.

Population Graphs: the graph theoretic shape of genetic structure

Abstract: Patterns of intraspecific genetic variation result from interactions among both historical and contemporary evolutionary processes. Traditionally, population geneticists have used methods such as F-statistics, pairwise isolation by distance models, spatial autocorrelation and coalescent models to analyse this variation and to gain insight about causal evolutionary processes. Here we introduce a novel approach (Population Graphs) that focuses on the analysis of marker-based population genetic data within a graph theoretic framework. This method can be used to estimate traditional population genetic summary statistics, but its primary focus is on characterizing the complex topology resulting from historical and contemporary genetic interactions among populations. We introduce the application of Population Graphs by examining the range-wide population genetic structure of a Sonoran Desert cactus (Lophocereus schottii). With this data set, we evaluate hypotheses regarding historical vicariance, isolation by distance, population-level assignment and the importance of specific populations to species-wide genetic connectivity. We close by discussing the applicability of Population Graphs for addressing a wide range of population genetic and phylogeographical problems.

Using genetic markers to estimate the pollen dispersal curve

Abstract: Pollen dispersal is a critical process that shapes genetic diversity in natural populations of plants. Estimating the pollen dispersal curve can provide insight into the evolutionary dynamics of populations and is essential background for making predictions about changes induced by perturbations. Specifically, we would like to know whether the dispersal curve is exponential, thin-tailed (decreasing faster than exponential), or fat-tailed (decreasing slower than the exponential). In the latter case, rare events of long-distance dispersal will be much more likely. Here we generalize the previously developed TWOGENER method, assuming that the pollen dispersal curve belongs to particular one- or two-parameter families of dispersal curves and estimating simultaneously the parameters of the dispersal curve and the effective density of reproducing individuals in the population. We tested this method on simulated data, using an exponential power distribution, under thin-tailed, exponential and fat-tailed conditions. We find that even if our estimates show some bias and large mean squared error (MSE), we are able to estimate correctly the general trend of the curve - thin-tailed or fat-tailed - and the effective density. Moreover, the mean distance of dispersal can be correctly estimated with low bias and MSE, even if another family of dispersal curve is used for the estimation. Finally, we consider three case studies based on forest tree species. We find that dispersal is fat-tailed in all cases, and that the effective density estimated by our model is below the measured density in two of the cases. This latter result may reflect the difficulty of estimating two parameters, or it may be a biological consequence of variance in reproductive success of males in the population. Both the simulated and empirical findings demonstrate the strong potential of TWOGENER for evaluating the shape of the dispersal curve and the effective density of the population (d(e)).

North Atlantic phylogeography and large‐scale population differentiation of the seagrass Zostera marina L.

Abstract: As the most widespread seagrass in temperate waters of the Northern Hemisphere, Zostera marina provides a unique opportunity to investigate the extent to which the historical legacy of the last glacial maximum (LGM18 000–10 000 years BP ) is detectable in modern population genetic structure. We used sequences from the nuclear rDNA–internal transcribed spacer (ITS) and chloroplast mat K-intron, and nine microsatellite loci to survey 49 populations (> 2000 individuals) from throughout the species’ range. Minimal sequence variation between Pacific and Atlantic populations combined with biogeographical groupings derived from the microsatellite data, suggest that the trans -Arctic connection is currently open. The east Pacific and west Atlantic are more connected than either is to the east Atlantic. Allelic richness was almost two-fold higher in the Pacific. Populations from putative Atlantic refugia now represent the southern edges of the distribution and are not genetically diverse. Unexpectedly, the highest allelic diversity was observed in the North Sea–Wadden Sea–southwest Baltic region. Except for the Mediterranean and Black Seas, significant isolation-by-distance was found from ~150 to 5000 km. A transition from weak to strong isolation-by-distance occurred at ~150 km among northern European populations suggesting this scale as the natural limit for dispersal within the metapopulation. Links between historical and contemporary processes are discussed in terms of the projected effects of climate change on coastal marine plants. The identification of a high genetic diversity hotspot in Northern Europe provides a basis for restoration decisions.

Effect of unsampled populations on the estimation of population sizes and migration rates between sampled populations

Abstract: Current estimators of gene flow come in two methods; those that estimate parameters assuming that the populations investigated are a small random sample of a large number of populations and those that assume that all populations were sampled. Maximum likelihood or Bayesian approaches that estimate the migration rates and population sizes directly using coalescent theory can easily accommodate datasets that contain a population that has no data, a so-called ‘ghost’ population. This manipulation allows us to explore the effects of missing populations on the estimation of population sizes and migration rates between two specific populations. The biases of the inferred population parameters depend on the magnitude of the migration rate from the unknown populations. The effects on the population sizes are larger than the effects on the migration rates. The more immigrants from the unknown populations that are arriving in the sample populations the larger the estimated population sizes. Taking into account a ghost population improves or at least does not harm the estimation of population sizes. Estimates of the scaled migration rate M (migration rate per generation divided by the mutation rate per generation) are fairly robust as long as migration rates from the unknown populations are not huge. The inclusion of a ghost population does not improve the estimation of the migration rate M; when the migration rates are estimated as the number of immigrants Nm then a ghost population improves the estimates because of its effect on population size estimation. It seems that for ‘real world’ analyses one should carefully choose which populations to sample, but there is no need to sample every population in the neighbourhood of a population of interest.

Chloroplast DNA variation and postglacial recolonization of common ash (Fraxinus excelsior L.) in Europe.

Abstract: We used chloroplast polymerase chain reaction-restriction-fragment length polymorphism (PCR-RFLP) and chloroplast microsatellites to assess the structure of genetic variation and postglacial history across the entire natural range of the common ash (Fraxinus excelsior L.), a broad-leaved wind-pollinated and wind-dispersed European forest tree. A low level of polymorphism was observed, with only 12 haplotypes at four polymorphic microsatellites in 201 populations, and two PCR-RFLP haplotypes in a subset of 62 populations. The clear geographical pattern displayed by the five most common haplotypes was in agreement with glacial refugia for ash being located in Iberia, Italy, the eastern Alps and the Balkan Peninsula, as had been suggested from fossil pollen data. A low chloroplast DNA mutation rate, a low effective population size in glacial refugia related to ash’s life history traits, as well as features of postglacial expansion were put forward to explain the low level of polymorphism. Differentiation among populations was high (G ST = 0.89), reflecting poor mixing among recolonizing lineages. Therefore, the responsible factor for the highly homogeneous genetic pattern previously identified at nuclear microsatellites throughout western and central Europe (Heuertz et al. 2004) must have been efficient postglacial pollen flow. Further comparison of variation patterns at both marker systems revealed that nuclear microsatellites identified complex differentiation patterns in south-eastern Europe which remained undetected with chloroplast microsatellites. The results suggest that data from different markers should be combined in order to capture the most important genetic patterns in a species.

‘What's larvae got to do with it?’ Disparate patterns of post‐glacial population structure in two benthic marine gastropods with identical dispersal potential

Abstract: In marine environments, many species have apparently colonized high latitude regions following the last glacial maximum (LGM) yet lack a life-history stage, such as a free-living larva, that is clearly capable of long-distance dispersal. Two hypotheses can explain the modern high latitude distributions of these marine taxa: (1) survival in northern refugia during the LGM or (2) rapid post-glacial dispersal by nonlarval stages. To distinguish these two scenarios, I characterized the genetic structure of two closely related northeastern Pacific gastropods that lack planktonic larvae but which have distributions extending more than 1000 km north of the southern limit of glaciers at the LGM. Despite having identical larval dispersal potential, these closely related species exhibit fundamentally different patterns of genetic structure. In Nucella ostrina, haplotype diversity among northern populations (British Columbia and Alaska) is low, no pattern of isolation by distance exists and a coalescent-based model of population growth indicates that during the LGM population size was reduced to less than 35% of its current size. In the congeneric and often sympatric N. lamellosa, northern populations harbour a diversity of ancient private haplotypes, significant evidence of isolation by distance exists and regional subdivision was found between northern (Alaska) and southern (southern British Columbia, Washington and Oregon) populations. Estimates of coalescent parameters indicate only a modest reduction in population size during the LGM and that northern and southern populations of N. lamellosa split approximately 50 Kyr before the LGM. The patterns are consistent with the hypothesis that N. ostrina recently reinvaded the northeastern Pacific but N. lamellosa survived the LGM in a northern refuge. A comparison of similar studies in this region indicates that depleted levels of genetic variation at high latitudes--evidence suggestive of recent colonization from a southern refuge--is more common among intertidal species that live relatively high on the shore, where exposure times to cold stress in air are longer than for species living lower on the shore. These data suggest that for some faunas, ecological differences between taxa may be more important than larval dispersal potential in determining species' long-term biogeographical responses to climate change.

Strong genetic clines and geographical variation in gene flow in the rocky intertidal barnacle Balanus glandula

Abstract: A long-standing issue in marine biology is identifying spatial scales at which populations of sessile adults are connected by planktonic offspring. We examined the genetic continuity of the acorn barnacle Balanus glandula, an abundant member of rocky intertidal communities of the northeastern Pacific Ocean, and compared these genetic patterns to the nearshore oceanography described by trajectories of surface drifters. Consistent with its broad dispersal potential, barnacle populations are genetically similar at both mitochondrial (cytochrome oxidase I) and nuclear (elongation factor 1-alpha) loci across broad swaths of the species' range. In central California, however, there is a striking genetic cline across 475 km of coastline between northern and southern populations. These patterns indicate that gene flow within central California is far more restricted spatially than among other populations. Possible reasons for the steep cline include the slow secondary introgression of historically separated populations, a balance between diversifying selection and dispersal, or some mix of both. Geographic trajectories of oceanic drifters closely parallel geographical patterns of gene flow. Drifters placed to the north (Oregon; approximately 44 degrees N) and south (Santa Barbara, California; approximately 34 degrees N) of the cline disperse hundreds of kilometers within 40 days, yet over the long-term their trajectories never overlapped. The lack of communication between waters originating in Oregon and southern California probably helps to maintain strong genetic differentiation between these regions. More broadly, the geographical variation in gene flow implies that focusing on species-level averages of gene flow can mask biologically important variance within species which reflects local environmental conditions and historical events.

Climate and habitat barriers to dispersal in the highly mobile grey wolf

Abstract: We reanalysed published data to evaluate whether climate and habitat are barriers to dispersal in one of the most mobile and widely distributed mammals, the grey wolf ( Canis lupus ) Distance-based redundancy analysis (dbRDA) was used to examine the amount of variation in genetic distances that could be explained by an array of environmental factors, including geographical distance Patterns in genetic variation were also examined using MDS plots among populations and relationships between genetic structure and individual environmental variables were further explored using the BIOENV procedure We found that, contrary to a previous report, a pattern of isolation with distance is evident on a continental scale in the North American wolf population This pattern is apparently related to climate and habitat Specifically, vegetation types appear to play a role in the genetic dissimilarities among populations When we controlled for the effect of spatial variation, climate was still associated with genetic distance Further, partitioning of geographical distances into latitudinal and longitudinal axes revealed that the east–west gradient had the strongest relationship with genetic distance We suggest two possible mechanisms by which environmental conditions may influence the dispersal decisions made by wolves

Unreliable mtDNA data due to nuclear insertions: a cautionary tale from analysis of humans and other great apes

Abstract: Analysis of mitochondrial DNA sequence variation has been used extensively to study the evolutionary relationships of individuals and populations, both within and across species. So ubiquitous and easily acquired are mtDNA data that it has been suggested that such data could serve as a taxonomic 'barcode' for an objective species classification scheme. However, there are technical pitfalls associated with the acquisition of mtDNA data. One problem is the presence of translocated pieces of mtDNA in the nuclear genome of many taxa that may be mistaken for authentic organellar mtDNA. We assessed the extent to which such 'numt' sequences may pose an overlooked problem in analyses of mtDNA from humans and apes. Using long-range polymerase chain reaction (PCR), we generated necessarily authentic mtDNA sequences for comparison with sequences obtained using typical methods for a segment of the mtDNA control region in humans, chimpanzees, bonobos, gorillas and orangutans. Results revealed that gorillas are notable for having such a variety of numt sequences bearing high similarity to authentic mtDNA that any analysis of mtDNA using standard approaches is rendered impossible. Studies on humans, chimpanzees, bonobos or orangutans are apparently less problematic. One implication is that explicit measures need to be taken to authenticate mtDNA sequences in newly studied taxa or when any irregularities arise. Furthermore, some taxa may not be amenable to analysis of mtDNA variation at all.