Measures Of Genetic Differentiation Research Articles

Genetic structure and taxonomic position of Pinus uliginosa Neumann population from Wielkie Torfowisko Batorowskie in Stołowe Mts. (locus classicus)

Genetic structure of <i>Pinus uliginosa</i> Neumann from Wielkie Tor-fowisko Batorowskie peat-bog (<i>locus classicus</i>) was studied by means of isoenzyme variability and compared with genetic structure of <i>P. mugo</i> Turra from Tatra Mts and <i>P. sylvestris</i> populations from Klodzka Valley and Czersk. The level of genetic variability in the population of <i>P. uliginosa</i> (heterozygosity, genotypic polymorphism) was similar to that in populations of <i>P. mugo</i>, with an excess of homozygosity in relation to Hardy-Weinberg equilibrium. An average number of alleles per locus in population of <i>P. uliginosa</i> is the same as in the studied <i>P. sylvestris</i> populations, but the average number of genotypes is slightly lower. However, populations of <i>P. mugo</i> from montaneus stands in Tatra Mts. are characterized by a higher number of alleles per locus than that in <i>P. uliginosa</i> population.In populations of <i>P. mugo</i> from peat-bogs, a lower number of alleles and genotypes is noted than in <i>P. uliginosa</i> population. The coefficients of genetic similarity (Nei and Hedrick) show the distinctly separate character of <i>P. uliginosa</i> as compared to <i>P. sylvestris</i> and loose relationship of this taxon to <i>P. mugo</i>. Also the measure of genetic differentiation of populations (G<sub>ST</sub>) confirms the specificity of this pine taxon.

High Dispersal and Generalist Habits of the BatArtibeus jamaicensison Cozumel Island, Mexico: An Assessment Using Molecular Genetics

Islands and insular biotas have been recognized as ideal models for studying adaptive radiations and evolutionary processes. In the present study we investigated the Jamaican fruit-eating bat, Artibeus jamaicensis from Cozumel Island, to evaluate the effect of ecological features on genetic diversity and structure across three different environments, semi-evergreen tropical forest, mangrove, and cenotes, using six microsatellite loci in 105 individuals. Genetic diversity was relatively high (forest HO = 0.693, HNei = 0.825; mangrove HO = 0.702, HNei = 0.710; cenotes HO = 0.695, HNei = 0.847). Pairwise genetic differentiation measures between localities were not significant and the overall level of differentiation was markedly low (FST = 0.009, G'ST = 0.088). Likewise, results showed that A. jamaicensis consists of one genetic group and relatedness among individuals was low. Results are concordant with our predictions that the island population will show high genetic diversity and null structure at the fin...

Optimizing the trade‐off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual‐based sampling scheme

Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, that is, the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic data sets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of interindividual measures of genotypic dissimilarity may efficiently replace interpopulation measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.

A range wide geographic pattern of genetic diversity and population structure of Castanea mollissima populations inferred from nuclear and chloroplast microsatellites

Understanding geographical pattern of genetic diversity and population structure is of great importance for formulating conservation and utilization strategies. In this study, we investigated the genetic diversity and population structure of 28 natural populations of Castanea mollissima in China using eight nuclear and six chloroplast microsatellite makers (nSSRs and cpSSRs). Populations from central China harbored the highest genetic diversity at both nSSR and cpSSR markers (nSSR: H E = 0.705; cpSSR: H = 0.461). The standardized measure of genetic differentiation estimated as G′ ST was 0.447 for nSSR and 0.803 for cpSSR, respectively. The G′ST-based pollen to seed flow ratio is 3.043, indicating that pollen flow is not extensive among C. mollissima populations. No obvious population genetic structure by geographical locations was found by STRUCTURE analysis based on nSSR data, and similarly, no signal of phylogeographic structure was detected for cpSSR analysis. Five boundaries defining zones of maximum genetic differences within the network of the C. mollissima populations were found, and the locations of those barriers were consistent with those of four mountains, i.e., Daloushan Mountain, Dabashan Mountain, Wushan Mountain, and Qingliangfeng Mountain, indicating that those mountains might act as genetic barriers obstructing the genetic exchange among natural C. mollissima populations. These results provide valuable baseline data for conservation and utilization of this species.

The genomic consequences of adaptive divergence and reproductive isolation between species of manakins

The processes of adaptation and speciation are expected to shape genomic variation within and between diverging species. Here we analyze genomic heterogeneity of genetic differentiation and introgression in a hybrid zone between two bird species (Manacus candei and M. vitellinus) using 59100 SNPs, a whole genome assembly, and Bayesian models. Measures of genetic differentiation (FST) and introgression (genomic cline center [α] and rate [β]) were highly heterogeneous among loci. We identified thousands of loci with elevated parameter estimates, some of which are likely to be associated with variation in fitness in Manacus populations. To analyze the genomic organization of differentiation and introgression, we mapped SNPs onto a draft assembly of the M. vitellinus genome. Estimates of FST, α, and β were autocorrelated at very short physical distances (<100 bp), but much less so beyond this. In addition, average statistical associations (linkage disequilibrium) between SNPs were generally low and were not higher in admixed populations than in populations of the parental species. Although they did not occur with a constant probability across the genome, loci with elevated FST, α, and β were not strongly co-localized in the genome. Contrary to verbal models that predict clustering of loci involved in adaptation and isolation in discrete genomic regions, these results are consistent with the hypothesis that genetic regions involved in adaptive divergence and reproductive isolation are scattered throughout the genome. We also found that many loci were characterized by both exceptional genetic differentiation and introgression, consistent with the hypothesis that loci involved in isolation are also often characterized by a history of divergent selection. However, the concordance between isolation and differentiation was only partial, indicating a complex architecture and history of loci involved in isolation.

GENOMIC REGIONS WITH A HISTORY OF DIVERGENT SELECTION AFFECT FITNESS OF HYBRIDS BETWEEN TWO BUTTERFLY SPECIES

Speciation is the process by which reproductively isolated lineages arise, and is one of the fundamental means by which the diversity of life increases. Whereas numerous studies have documented an association between ecological divergence and reproductive isolation, relatively little is known about the role of natural selection in genome divergence during the process of speciation. Here, we use genome-wide DNA sequences and Bayesian models to test the hypothesis that loci under divergent selection between two butterfly species (Lycaeides idas and L. melissa) also affect fitness in an admixed population. Locus-specific measures of genetic differentiation between L. idas and L. melissa and genomic introgression in hybrids varied across the genome. The most differentiated genetic regions were characterized by elevated L. idas ancestry in the admixed population, which occurs in L. idas-like habitat, consistent with the hypothesis that local adaptation contributes to speciation. Moreover, locus-specific measures of genetic differentiation (a metric of divergent selection) were positively associated with extreme genomic introgression (a metric of hybrid fitness). Interestingly, concordance of differentiation and introgression was only partial. We discuss multiple, complementary explanations for this partial concordance.

Genetically defining populations is of limited use for evaluating and managing human impacts on gene flow

Partitioning genetic variation into panmictic units is one of the most commonly used techniques in genetic studies of wild organisms. For conservation, the rationale is to identify units for management, most often referred to as populations. Describing these populations provides a measure of genetic differentiation, but they are only management units in relation to specific objectives. In situ conservation activities are mostly constrained to landscape (or ‘seascape’) units. With continuing habitat fragmentation, maintaining gene flow and genetic variation is an underlying objective for many conservation activities. Spatially explicit genetic approaches can describe how gene flow varies across a landscape, but the popular approach of identifying populations has limited and specific application. The statistical tests and sampling procedures used seldom allow for the spatial extent of genetic panmixia to be precisely defined. Gene flow, genetic variation and genetic detection of individual movements can be estimated without reference to populations. Furthermore, the term ‘population’ is used inconsistently in the literature and is often poorly defined. Formulating appropriate questions for management requires that the unit of study is clearly described, and often this could be organisms inhabiting defined areas of the landscape. Resources for conservation management are limited, so geneticists working on gene flow in wild organisms need to frame questions relevant to specific management needs and carefully consider the language and approaches employed.

From global to local genetic structuring in the red gorgonian Paramuricea clavata: the interplay between oceanographic conditions and limited larval dispersal

Defining the scale of connectivity among marine populations and identifying the barriers to gene flow are tasks of fundamental importance for understanding the genetic structure of populations and for the design of marine reserves. Here, we investigated the population genetic structure at three spatial scales of the red gorgonian Paramuricea clavata (Cnidaria, Octocorallia), a key species dwelling in the coralligenous assemblages of the Mediterranean Sea. Colonies of P.clavata were collected from 39 locations across the Mediterranean Sea from Morocco to Turkey and analysed using microsatellite loci. Within three regions (Medes, Marseille and North Corsica), sampling was obtained from multiple locations and at different depths. Three different approaches (measures of genetic differentiation, Bayesian clustering and spatially explicit maximum-difference algorithm) were used to determine the pattern of genetic structure. We identified genetic breaks in the spatial distribution of genetic diversity, which were concordant with oceanographic conditions in the Mediterranean Sea. We revealed a high level of genetic differentiation among populations and a pattern of isolation by distance across the studied area and within the three regions, underlining short effective larval dispersal in this species. We observed genetic differentiation among populations in the same locality dwelling at different depths, which may be explained by local oceanographic conditions and which may allow a process of local adaptation of the populations to their environment. We discuss the implications of our results for the conservation of the species, which is exposed to various threats.

Predictions of single-nucleotide polymorphism differentiation between two populations in terms of mutual information

Mutual information (I) provides a robust measure of genetic differentiation for the purposes of estimating dispersal between populations. At present, however, there is little predictive theory for I. The growing importance in population biology of analyses of single-nucleotide and other single-feature polymorphisms (SFPs) is a potent reason for developing an analytic theory for I with respect to a single locus. This study represents a first step towards such a theory. We present theoretical predictions of I between two populations with respect to a single haploid biallelic locus. Dynamical and steady-state forecasts of I are derived from a Wright-Fisher model with symmetrical mutation between alleles and symmetrical dispersal between populations. Analytical predictions of a simple Taylor approximation to I are in good agreement with numerical simulations of I and with data on I from SFP analyses of dispersal experiments on Drosophila fly populations. The theory presented here also provides a basis for the future inclusion of selection effects and extension to multiallelic loci.

Population biology of sugar pine ( Pinus lambertiana Dougl.) with reference to historical disturbances in the Lake Tahoe Basin: Implications for restoration

Historical logging, fire suppression, and an invasive pathogen, Cronartium ribicola, the cause of white pine blister rust (WPBR), are assumed to have dramatically affected sugar pine ( Pinus lambertiana) populations in the Lake Tahoe Basin. We examined population- and genetic-level consequences of these disturbances within 10 sugar pine populations by assessing current population structure and trends for 1129 individuals, genetic diversity for 250 individuals, and frequency of WPBR-resistance for 102 families. Logging had occurred in 9 of 10 sites and fire suppression was evident in all stands. High density of white fir ( Abies concolor) is often an indicator of fire suppression and we found a negative relationship between sugar pine survivorship and white fir basal area ( r 2 = 0.31). C. ribicola was present in 90% of stands (incidence range: 0–48%) and we found a significant relationship between mean host survivorship and disease incidence ( r 2 = 0.46). We estimated population growth rates ( λ) from size-based transition matrices. For six of 10 sugar pine populations λ was ⩾1.0, indicating that these populations appear to be stable; for four populations, λ was <1.0, indicating populations that may be in decline. A population specific drift parameter, c i , which is a measure of genetic differentiation in allele frequencies relative to an ancestral population, ranged from 0.009 to 0.048. Higher values of c i indicate greater genetic drift, possibly due to a bottleneck caused by historical logging, other agents of mortality or much older events affecting population sizes. Effects of drift are known to be greater in small populations and we found a negative relationship between sugar pine density and c i ( r 2 = 0.36). Allele frequency of the Cr1 gene, responsible for WPBR-resistance in sugar pine, averaged 0.068 for all populations sampled; no WPBR infection was found in one population in which the Cr1 frequency was 0.112. Historical disturbances and their interactions have likely influenced the population biology of sugar pine in the Tahoe Basin; for some populations this has meant reduced population size, higher genetic drift, and poor survival of small- and intermediate-sized individuals. Possible management strategies include restoring population numbers, deploying WPBR-resistance, treating stands to promote natural sugar pine regeneration, and enhancing genetic diversity.

A Hierarchical Bayesian Model for Next-Generation Population Genomics

The demography of populations and natural selection shape genetic variation across the genome and understanding the genomic consequences of these evolutionary processes is a fundamental aim of population genetics. We have developed a hierarchical Bayesian model to quantify genome-wide population structure and identify candidate genetic regions affected by selection. This model improves on existing methods by accounting for stochastic sampling of sequences inherent in next-generation sequencing (with pooled or indexed individual samples) and by incorporating genetic distances among haplotypes in measures of genetic differentiation. Using simulations we demonstrate that this model has a low false-positive rate for classifying neutral genetic regions as selected genes (i.e., Φ(ST) outliers), but can detect recent selective sweeps, particularly when genetic regions in multiple populations are affected by selection. Nonetheless, selection affecting just a single population was difficult to detect and resulted in a high false-negative rate under certain conditions. We applied the Bayesian model to two large sets of human population genetic data. We found evidence of widespread positive and balancing selection among worldwide human populations, including many genetic regions previously thought to be under selection. Additionally, we identified novel candidate genes for selection, several of which have been linked to human diseases. This model will facilitate the population genetic analysis of a wide range of organisms on the basis of next-generation sequence data.

Genetic variation of wild litchi (Litchi chinensis Sonn. subsp. chinensis) revealed by microsatellites

Understanding the amount and distribution of genetic diversity in natural populations can inform the conservation strategy for the species in question. In this study, genetic variation at eight nuclear microsatellite loci was used to investigate genetic diversity and population structure of wild litchi (Litchi chinensis Sonn. subsp. chinensis). Totally 215 individuals were sampled, representing nine populations of wild litchi. All eight loci were polymorphic, with a total of 51 alleles. The expected heterozygosity in the nine populations ranged from 0.367 to 0.638 with an average value of 0.526. Inbreeding within wild litchi populations was indicated by a strong heterozygote defect. Significant bottleneck events were detected in the populations from Yunnan and Vietnam, which could be responsible for lower levels of genetic diversity in these populations. Measures of genetic differentiation (F ST = 0.269) indicated strong differentiation among wild litchi populations. Significant correlation was found between genetic differentiation and geographical distance (r = 0.655, P = 0.002), indicating a strong isolation by distance in these populations. Bayesian clustering suggested genetic separation among three regional groups, namely, the western group, the central group and the eastern group. Some conservation strategies for wild litchi populations were also proposed based on our results.

Microsatellites behaving badly: empirical evaluation of genotyping errors and subsequent impacts on population studies

Microsatellites are useful tools for ecological studies because they can be used to discern population structure, dispersal patterns and genetic relationships among individuals. However, they can also yield inaccurate genotypes that, in turn, bias results, promote biological misinterpretations, and create repercussions for population management and conservation programs. We used empirical data from a large-scale microsatellite DNA study of white-tailed deer (Odocoileus virginianus) to identify sources of genotyping error, evaluate corrective measures, and provide recommendations to prevent bias in population studies. We detected unreported mutations that led to erroneous genotypes in five of 13 previously evaluated microsatellites. Of the five problematic markers, two contained mutations that resulted in null alleles, and three contained mutations that resulted in imperfect repeats. These five microsatellites had error rates that were four times greater on average than those observed in the remaining eight. Methodological corrections, such as primer redesign, reduced errors up to 5-fold in two problematic loci, although analytical corrections (computational adjustment for errors) were unable to fully prevent bias and, consequently, measures of genetic differentiation and kinship were negatively impacted. Our results demonstrate the importance of error evaluation during all stages of population studies, and emphasize the need to standardize procedures for microsatellite analyses. This study facilitates the application of microsatellite technology in population studies by examining common sources of genotyping error, identifying unreported problems with microsatellites, and offering solutions to prevent error and bias in population studies.

Population Genetic Diversity and Structure inGoodyera rosulacea(Orchidaceae), Endemic in Korea, and Implications for Conservation

We assessed genetic diversity and structure in the outcrossing orchid Goodyera rosulacea, endemic to limestone regions in Korea. Using allozymes as genetic markers, standard genetic diversity measures within and among populations as well as genetic structure were estimated. In addition, a regression analysis between pairwise genetic and geographical distances and correlation analyses between population sizes and estimates of genetic variation within populations were conducted to gain insights into the past evolutionary processes. Moderate levels of genetic variation were found in the species (%P s = 31.6%, A s = 1.37, H es = 0.126); at the population level, slightly lower levels were estimated (%P p = 27.8%, A p = 1.31, H ep = 0.100). Overall fixation index was not significantly different from zero (F IS = 0.160). As compared with that in most terrestrial orchids, the measure of genetic differentiation among populations was also moderate (F ST = 0.150). At the regional scale, a weak linear regression between pairwise genetic and geographical distances was found, suggesting that populations are not at equilibrium between gene flow and genetic drift (i.e., little evidence of isolation-by-distance effect). A significant correlation between population size and mean number of alleles per locus was detected (p = 0.006). These results suggest that genetic drift, coupled with limited seed dispersal, has played an increasing role in the genetic dynamics of small populations, though outcrossing breeding system might have in part counterbalanced against these negative effects. Threats to the species are considered to be anthropogenic. In situ and ex situ conservation strategies are suggested to preserve the genetic variation in the rare G. rosulacea.

A Beta-Mixture Model for Assessing Genetic Population Structure

An important fraction of recently generated molecular data is dominant markers. They contain substantial information about genetic variation but dominance makes it impossible to apply standard techniques to calculate measures of genetic differentiation, such as F-statistics. In this article, we propose a new Bayesian beta-mixture model that more accurately describes the genetic structure from dominant markers and estimates multiple F(ST) s from the sample. The model also has important application for codominant markers and single-nucleotide polymorphism (SNP) data. The number of F(ST) is assumed unknown beforehand and follows a random distribution. The reversible jump algorithm is used to estimate the unknown number of multiple F(ST) s. We evaluate the performance of three split proposals and the overall performance of the proposed model based on simulated dominant marker data. The model could reliably identify and estimate a spectrum of degrees of genetic differentiation present in multiple loci. The estimates of F(ST) s also incorporate uncertainty about the magnitude of within-population inbreeding coefficient. We illustrate the method with two examples, one using dominant marker data from a rare orchid and the other using codominant marker data from human populations.

Isolation by distance across the Hawaiian Archipelago in the reef‐building coralPorites lobata

There is an ongoing debate on the scale of pelagic larval dispersal in promoting connectivity among populations of shallow, benthic marine organisms. The linearly arranged Hawaiian Islands are uniquely suited to study scales of population connectivity and have been used extensively as a natural laboratory in terrestrial systems. Here, we focus on Hawaiian populations of the lobe coral Porites lobata, an ecosystem engineer of shallow reefs throughout the Pacific. Patterns of recent gene flow and population structure in P. lobata samples (n = 318) from two regions, the Hawaiian Islands (n = 10 sites) and from their nearest neighbour Johnston Atoll, were analysed with nine microsatellite loci. Despite its massive growth form, ∼ 6% of the samples from both regions were the product of asexual reproduction via fragmentation. Cluster analysis and measures of genetic differentiation indicated that P. lobata from the Hawaiian Islands are strongly isolated from those on Johnston Atoll (F(ST) = 0.311; P < 0.001), with the descendants of recent migrants (n = 6) being clearly identifiable. Within the Hawaiian Islands, P. lobata conforms to a pattern of isolation by distance. Here, over 37% (P = 0.001) of the variation in genetic distance was explained by geographical distance. This pattern indicates that while the majority of ongoing gene flow in Hawaiian P. lobata occurs among geographically proximate reefs, inter-island distances are insufficient to generate strong population structure across the archipelago.

Influence of mutation rate on estimators of genetic differentiation--lessons from Arabidopsis thaliana.

BackgroundThe analysis of molecular variation within and between populations is crucial to establish strategies for conservation as well as to detect the footprint of spatially heterogeneous selection. The traditional estimator of genetic differentiation (FST) has been shown to be misleading if genetic diversity is high. Alternative estimators of FST have been proposed, but their robustness to variation in mutation rate is not clearly established. We first investigated the effect of mutation and migration rate using computer simulations and examined their joint influence on QST, a measure of genetic differentiation for quantitative traits. We further used experimental data in natural populations of Arabidopsis thaliana to characterize the effect of mutation rate on various estimates of population differentiation. Since natural species exhibit various degrees of self-fertilisation, we also investigated the effect of mating system on the different estimators.ResultsIf mutation rate is high and migration rate low, classical measures of genetic differentiation are misleading. Only ΦST, an estimator that takes the mutational distances between alleles into account, is independent of mutation rate, for all migration rates. However, the performance of ΦST depends on the underlying mutation model and departures from this model cause its performance to degrade. We further show that QST has the same bias. We provide evidence that, in A. thaliana, microsatellite variation correlates with mutation rate. We thereby demonstrate that our results on estimators of genetic differentiation have important implications, even for species that are well established models in population genetics and molecular biology.ConclusionsWe find that alternative measures of differentiation like F'ST and D are not suitable for estimating effective migration rate and should not be used in studies of local adaptation. Genetic differentiation should instead be measured using an estimator that takes mutation rate into account, such as ΦST. Furthermore, in systems where migration between populations is low, such as A. thaliana, QST < FST cannot be taken as evidence for homogenising selection as has been traditionally thought.

Long-term genetic stability and population dynamics of laboratory strains of Schistosoma mansoni.

Measures of genetic differentiation between populations are useful tools for understanding the long-term dynamics of parasite communities. We followed the allele frequencies of microsatellite markers in samples taken over a period of 16 yr from the Case Western Reserve University-Naval Medical Research Institute (CWRU-NMRI) laboratory strain of Schistosoma mansoni. DNA was isolated from pooled samples of adults, eggs, or cercariae collected at 46 time points and genotyped for 14 tri- or tetranucleotide microsatellite markers. For comparison, 2 S. mansoni reference strains (Biomedical Research Institute-NMRI, which has a common origin with the CWRU line, and PR-1) were analyzed over shorter periods of time. We observed that the long-term allele frequencies are generally stable in large laboratory populations of this parasite, and a high degree of similarity was observed between the allele frequencies of consecutive samples from different developmental stages. The CWRU strain, however, showed 2 periods of marked deviation from stability as demonstrated using genetic differentiation measures. The first period corresponds to an admixture event with the BRI strain in which a new equilibrium was established as the "migrants" became blended into the existing CWRU population, consistent with 23% admixture from BRI. The second corresponds to a period of genetic drift when the CWRU population size was greatly reduced with an accompanying loss in genetic diversity. Having demonstrated the utility of pooled samples for the genetic analysis of population dynamics in laboratory strains of schistosomes, this approach will be useful for analyzing field samples to determine the impact of schistosomiasis control programs on parasite population structure. Accounting only for the intensity or prevalence of parasite populations may fail to register significant changes in population structure that could have implications for resistance, morbidity, and the design of control measures.

Self‐recruitment and sweepstakes reproduction amid extensive gene flow in a coral‐reef fish

Identifying patterns of larval dispersal within marine metapopulations is vital for effective fisheries management, appropriate marine reserve design, and conservation efforts. We employed genetic markers (microsatellites) to determine dispersal patterns in bicolour damselfish (Pomacentridae: Stegastes partitus). Tissue samples of 751 fish were collected in 2004 and 2005 from 11 sites encompassing the Exuma Sound, Bahamas. Bayesian parentage analysis identified two parent-offspring pairs, which is remarkable given the large population sizes and 28 day pelagic larval duration of bicolour damselfish. The two parent-offspring pairs directly documented self-recruitment at the two northern-most sites, one of which is a long-established marine reserve. Principal coordinates analyses of pair-wise relatedness values further indicated that self-recruitment was common in all sampled populations. Nevertheless, measures of genetic differentiation (F(ST)) and results from assignment methods suggested high levels of gene flow among populations. Comparisons of heterozygosity and relatedness among samples of adults and recruits indicated spatially and temporally independent sweepstakes events, whereby only a subset of adults successfully contribute to subsequent generations. These results indicate that self-recruitment and sweepstakes reproduction are the predominant, ecologically-relevant processes that shape patterns of larval dispersal in this system.

Spatio-temporal population structuring and genetic diversity retention in depleted Atlantic bluefin tuna of the Mediterranean Sea.

Fishery genetics have greatly changed our understanding of population dynamics and structuring in marine fish. In this study, we show that the Atlantic Bluefin tuna (ABFT, Thunnus thynnus), an oceanic predatory species exhibiting highly migratory behavior, large population size, and high potential for dispersal during early life stages, displays significant genetic differences over space and time, both at the fine and large scales of variation. We compared microsatellite variation of contemporary (n = 256) and historical (n = 99) biological samples of ABFTs of the central-western Mediterranean Sea, the latter dating back to the early 20th century. Measures of genetic differentiation and a general heterozygote deficit suggest that differences exist among population samples, both now and 96-80 years ago. Thus, ABFTs do not represent a single panmictic population in the Mediterranean Sea. Statistics designed to infer changes in population size, both from current and past genetic variation, suggest that some Mediterranean ABFT populations, although still not severely reduced in their genetic potential, might have suffered from demographic declines. The short-term estimates of effective population size are straddled on the minimum threshold (effective population size = 500) indicated to maintain genetic diversity and evolutionary potential across several generations in natural populations.