Acer grosseri, an economically and ecologically important maple species, is mainly distributed in North China. Based on Sequence Related Amplified Polymorphism (SRAP) markers and morphological characters, A. grosseri shows rich genetic diversity. Less genetic differentiation occurred between than within natural populations. All studied populations of A. grosseri formed two main clusters. There was no significant correlation between genetic and geographical distances among populations. The biological characters, mating system, gene exchange, and selective pressure from environmental heterogeneity are the main factors affecting the genetic population structure of A. grosseri. Acer grosseri Pax., an economically and ecologically important maple species, is mainly distributed in North China. In this study, the genetic diversity and population differentiation of 24 natural populations of this species were evaluated using sequence-related amplified polymorphism markers and morphological characters. The results show that highly significant differences occurred in 32 morphological traits. The coefficient of variation of 34 characters was 18.19 %. Principal component analysis indicated that 18 of 34 traits explained 60.20 % of the total variance. The phenotypic differentiation coefficient (VST) was 36.06 % for all morphological traits. The Shannon–Wiener index of 34 morphological characters was 6.09, while at the population level, it was 1.77. The percentage of polymorphic bands of all studied A. grosseri populations was 82.14 %. Nei's gene diversity (He) and Shannon's information index (I) were 0.35 and 0.50, respectively. Less genetic differentiation was detected among the natural populations . Twenty-four populations of A. grosseri formed two main clusters, which is consistent with morphological cluster analysis. Principal coordinates analysis and STRUCTURE analysis supported the UPGMA-cluster dendrogram. There was no significant correlation between genetic and geographical distances among populations. Both molecular and morphological data suggested that A. grosseri is rich in genetic diversity. The high level of genetic variation within populations could be affected by the biological characters, mating system and lifespan of A. grosseri, whereas the lower genetic diversity among populations could be caused by effective gene exchange, selective pressure from environmental heterogeneity and the species' geographical range.Knowledge of the genetic diversity and structure of tree species across their geographic ranges is essential for sustainable use and management of forest ecosystems.  Genetic diversity, adaptation and evolution of a species . InvestiEstimates of genetic diversity and genetic variation can be indirectly carried out based on morphological information . MorpholAcer grosseri belongs to the Aceraceae and is an important ornamental perennial tree both economically and medicinally  markers and morphological characters to (i) evaluate the morphological variability and diversity of 24 natural populations, (ii) investigate the genetic diversity and structure of A. grosseri populations and (iii) identify the factors that affect the current genetic diversity and differentiation of this natural genetic resource.We, therefore, conducted a genetic analysis of A. grosseri, covering almost its entire distribution range in North China  per sample. Dimensions (length and width) for leaf, fruit and seed were measured by digital caliper with 0.1 cm precision. Small dimensions were measured by a digital Vernier calliper  with 0.02 mm precision. Angles were measured using a protractor with 1° precision. Leaf area was measured using a leaf area metre with 0.01 cmThe morphological traits data were standardized. One-way analysis of variance (ANOVA) was performed using the Statistical Package for Social Sciences program . Coefficients of variation (CV %) were determined as indicators of morphological variability. The simple correlation coefficient was calculated to determine the relationships between the studied morphological variables using the Pearson correlation coefficient.A. grosseri, PCA was investigated using SPSS software.Factor analysis was based on principal components to provide a reduced dimension model indicating differences measured among groups. This analysis has been widely used as a data reduction method to analyse multiple data on morphological characteristics and it has proven to be a valuable tool to understand relationships between characteristics and between populations . Based oVST) was assessed using the formula The phenotypic differentiation coefficient (Hsw) of each morphological trait and each population was evaluated using BIO-Dap software.The phenotype diversity  and 0.6 mM of both forward and reverse primers. The PCR amplification programme was as follows: 5 min of pre-denaturation at 94 °C; 1 min of denaturation at 94 °C; five cycles of 1 min of denaturation at 94 °C, 1 min of annealing at 35 °C and 1 min of elongation at 72 °C; then 35 cycles of denaturation for 1 min at 94 °C, annealing for 1 min at 50 °C, elongation for 1 min at 72 °C and a final elongation step of 5 min at 72 °C. Sequence-related amplified polymorphism products were analysed on 3 % non-denatured polyacrylamide gels in 1× TBE buffer running at 120 V constant voltage for 1 h and then silver stained according to previously reported procedures . The SRAP reaction mixtures  contained 50 ng DNA, 2× MasterMix  or absence (0), and the matrix of SRAPs data was assembled. Only reproducible and well-defined bands were scored.Na), effective number of alleles (Ne), Nei's gene diversity (He), Shannon's information index (I) and genetic differentiation between populations (GST). In addition, pair-wise Nm values (gene flow), i.e. the average number of migrants exchanged among populations per generation, were calculated using Wright's method (Nm = (1 − GST)/4GST. Subsequently, the pair-wise Nei's unbiased genetic distance  model (FST) was determined through permutation tests against a null distribution generated by the data.Population genetic parameters were analysed using POPGENE v3.2  model , and theFST/(1 − FST)) and geographic (ln (geographic distance)) matrices using GENEPOP v4.0  was set from 2 to 13. Five independent runs were conducted for each K value. Other parameters were set to default values, as suggested by K statistic, based on the rate of change of log-likelihood of data [l(K)] between successive K values, was used to select the optimal K, following Population structure was analysed using Bayesian clustering analysis as implemented in STRUCTURE v2.2  or fruit length/width (FLW)  are important characters that may result in the phenotypic variation of A. grosseri.Simple correlation coefficient analysis showed the existence of significant positive or negative correlations among morphological characteristics (data not shown). Sixteen morphological traits  (CV = 6.84 %), while it was the highest for leaf apex width/height (LAWH) CV = 37.83 %). The CV of leaf, fruit and seed traits was 21.23, 14.79 and 13.11 %, respectively  accounted for 13.60 % of the total variation and featured LL, LML, LW, LL and LSW, while the third component (PC3) accounted for 13.11 % of the variation, featuring LA, γ, AS and FW.For each factor of PCA, a principal component loading of >0.58 was considered as being significant , Fig. 2.VST) of all morphological traits was 36.06 %, indicating that differentiation mainly occurred within populations (Table The phenotypic differentiation coefficient (ns Table .HSW), and the mean of the Shannon–Wiener index for 34 morphological characters was 6.10, range 4.12–7.13 (Table HSW = 1.86), while the lowest was in the MS population (HSW = 1.71)  (Na), effective number of alleles per locus (Ne) and the Shannon's information index (I) at the species level were 1.78, 1.61 and 0.50, respectively (Table I) ranged from 0.35 to 0.62. Nei's gene diversity (H) showed similar trends, ranging from 0.25 to 0.45. The observed number of alleles (Na) ranged from 1.60 to 1.92. The effective number of alleles (Ne) ranged from 1.43 to 1.87. The highest and lowest genetic diversities occurred in populations TTZ  and TBD , respectively (Table The average gene diversity (He)  was estily Table . Within P< 0.001). Of the total genetic diversity, there were 1.74 variance components among populations and 16.08 within populations. Ten percent of the total variation occurred among populations, while 90 % occurred within populations (Table P< 0.001). When all 24 populations were considered, the coefficient of genetic differentiation among populations (GST) was 0.20, representing 19.6 % genetic variability among populations and 80.4 % within populations. Furthermore, the population pair-wise Nm was 3.42 at the species level.Analysis of molecular variance revealed that high genetic differentiation occurred within populations .To further determine the genetic relationships among the 24 populations, UPGMA clustering was carried out using Nei's unbiased genetic distance matrix. The dendrogram , Ne , H , I , PPB  and longitude, respectively.Correlation analysis revealed that a significant negative relationship existed among r = 0.72, P = 0.05).There was a significant correlation between the Euclidean distances matrix of morphological traits and the genetic distance matrix of SRAP data according to the Mantel test  was higher than that of A. ginnala (Hsw = 1.60) (A. mono (Hsw = 2.68)  and the fixation index (ΦST) signify a genetic structure at this hierarchical level. The results show the patterns of genetic structure, i.e. weak genetic differentiation    Table  occurredA. grosseri showed less genetic differentiation among populations than within populations.In general, genetic differentiation mainly exists within populations of species with a wide geographical distribution . GrowingNm < 1) is generally regarded as the threshold quantity, below which significant population differentiation may occur . However, population decline could occur owing to isolation and artificial destruction of A. grosseri populations. Random genetic drift in relatively small populations would result in differentiation between populations. This random factor may be an important reason for the lack of significant correlation between geographic and genetic distances.According to ay occur . In thisy fruits , indicatA. grosseri can grow in various habitats and different soil types  and the undergraduate innovative experiment program of China (201310118004).This work was supported by the Q.-d.Z. conducted the fieldwork and analysed data. R.-Z.J. performed the experiments and analysed data. C.M. performed the experiments, analysed data and wrote the manuscript. C.-W.T. joined the fieldwork and performed the experiments. Y.-L.W. conceived, designed the experiments and wrote the manuscript.None declared.


Vulpes vulpes) have significantly impacted endangered ground‐nesting birds and native canids. These foxes derive primarily from captive‐reared animals associated with the fur‐farming industry. Over the past five decades, the cumulative area occupied by nonnative red fox increased to cover much of central and southern California. We used a landscape‐genetic approach involving mitochondrial DNA (mtDNA) sequences and 13 microsatellites of 402 nonnative red foxes removed in predator control programs to investigate source populations, contemporary connectivity, and metapopulation dynamics. Both markers indicated high population structuring consistent with origins from multiple introductions and low subsequent gene flow. Landscape‐genetic modeling indicated that population connectivity was especially low among coastal sampling sites surrounded by mountainous wildlands but somewhat higher through topographically flat, urban and agricultural landscapes. The genetic composition of populations tended to be stable for multiple generations, indicating a degree of demographic resilience to predator removal programs. However, in two sites where intensive predator control reduced fox abundance, we observed increases in immigration, suggesting potential for recolonization to counter eradication attempts. These findings, along with continued genetic monitoring, can help guide localized management of foxes by identifying points of introductions and routes of spread and evaluating the relative importance of reproduction and immigration in maintaining populations. More generally, the study illustrates the utility of a landscape‐genetic approach for understanding invasion dynamics and metapopulation structure of one of the world's most destructive invasive mammals, the red fox.Invasive mammalian carnivores contribute disproportionately to declines in global biodiversity. In California, nonnative red foxes ( Invasive species can have detrimental effects on native communities and threatened or endangered prey populations through competition or maladaptive hybridization with closely related taxa (Rhymer and Simberloff Vulpes vulpes) lists among the top‐2 species in terms of global impact , with no evidence of expansion until the 1970s Vail . BetweenFST) or isolation by distance. In contrast, if the contemporary range reflected many independent introductions of small numbers of individuals, we expected to observe substantial genetic structure with little relationship to proximity. Our second objective was to elucidate patterns of contemporary connectivity, which potentially affect the maintenance of particular populations or the entire metapopulation. To accomplish this, we applied a combination of population genetic statistics and ordination, tree‐based, and Bayesian clustering approaches to elucidating population structure free of spatially explicit models, and landscape resistance surface modeling approaches that tested explicit habitat‐based hypotheses about connectivity. We also investigated whether some populations were dependent on immigration (“sinks”) from other populations (“sources”) for persistence  of 402 nonnative red foxes collected from throughout lowland areas of California to investigate numbers of introductions, routes of spread, and contemporary connectivity among populations. The broader purpose of this study was to understand as completely as possible the “anatomy” of the red fox invasion of California both to assist in its management and to provide guidance to management of other nonnative red fox populations. Our first objective was to test hypotheses relating to the mechanics of the range increase. If the contemporary range reflected a sudden expansion from one or two locations, we expected to see a pattern of high genetic connectivity  were accessioned in the UC Berkeley Museum of Vertebrate Zoology or other collections (n = 16). Data for these and all unaccessioned  samples were deposited in the Dryad Digital Repository (DOI No.: doi: 10.5061/dryad.hj722). For the purposes of distribution modeling, we used an independent data set of 349 red fox occurrence records that were obtained by Lewis et al.  and bone (n = 4) specimens using the DNeasy® tissue kit , and from scats (n = 19) using the QIAamp® Stool Kit . Primers, PCR chemistry, and cycling conditions for the mtDNA D‐loop and cytochrome b loci were as previously reported  amplification, sequencing, and genotyping at the Mammalian Ecology and Conservation Unit of the Veterinary Genetics Laboratory of University of California, Davis. We extracted DNA from tissue . For comparison to other studies, we computed standard allele‐frequency‐based estimates of FST for both mtDNA haplotypes and microsatellites in Arlequin 3.1   and mtDNA (FST/[1 − FST]). First, to visualize barriers and corridors affecting gene flow based solely on genetic distances , we used an approach similar to that by Keis et al. . We therefore used program Structure (v. 2.0) to cluster samples on the basis of genotype frequencies and then examined the spatial distribution of cluster assignments , we performed a final run at each K consisting of 550,000 cycles . We tested increasing values of K until the ln P(D) either decreased or became notably more variable among replicate runs for 2 consecutive values of K. It is common to analyze patterns in “log probabilities of the data” associated with choices of K to infer the “correct” or “best” number of clusters describing structure of a population . Therefore, we developed an approach here that integrates multiple levels of K into “cluster profiles” characteristic of each sample, and then uses the most common cluster profiles among samples to assess hierarchical structure . To optimize our ability to infer migration among sites, we chose the highest K for which assignments nested within those at lower levels of K. To assess potential influences of uneven sample size on results, we ran analyses with a smaller random subsample from the more heavily sampled sites and found little difference from the complete data set .All Structure runs were conducted assuming admixture with correlated allele frequencies .We obtained mitochondrial sequences and/or microsatellite genotypes from 402 red foxes from 13 predefined sampling locations, including two 1920s foxes from the native–nonnative contact zone. We obtained 392 full cytochrome X¯ = 0.37, standard deviation [SD] = 0.23; Table FST = 0.49 , and all but three haplotypes were restricted to ≤3 sampling sites, indicating considerable population structure . The two most widespread haplotypes were G‐38 and N‐7, which also were found in two specimens  collected in the 1920s in southern Yolo County near an active fur farm  relative to gene diversities within sampling sites (FST (theta) was 0.086 (95% CI: 0.074–0.098). Pairwise FST estimates averaged 0.10 . Using the formula of Hedrick et al. , suggesting the presence of admixture. Genetic effective population size estimates ranged from 2 (95% CI: 1.6–2.5) in Morro Bay to 44.6 (28.9–73.0) in Monterey. All populations showed signatures of demographic bottlenecks, consistent with founder effects (Table DA indicated 3 sets of sites that clustered with moderate to high bootstrap support: (1) the SF Bay sampling sites; (2) Half Moon Bay and Monterey; and (3) Santa Barbara (SB) and SO  Bay Area sampling sites 0.51–0.52) and highest in the northern SJV (0.67), followed closely by Monterey and Half Moon Bay (0.64 each) sites  and both landscape resistance  and Euclidian distance , but the partial Mantel test was significant only for landscape resistance with Euclidian distance held constant , but not for Euclidian distance with landscape resistance held constant . The mtDNA‐based correlations were nonsignificant for landscape resistance and Euclidian distance in both simple and partial Mantel tests.Specifically, we used the inverse of this model as a resistance surface with which to project a hypothetical connectivity  map Fig. B. ConfroK corresponded to K = 2 , which grouped all of the 3 SF Bay sites into one cluster, consistent with the previous analyses showing the SF Bay area to be distinct. However, the posterior probability continued to increase approximately linearly with increasing levels of K, indicating additional structure nested within each of these K = 2 primary clusters . Clusters nested hierarchically up to K = 8, except for the Morro Bay sampling site, which did not consistently associate with any other particular sampling site . This exception could have stemmed from the very small genetic effective size (Ne = 2) of the Morro Bay population, which would be expected to result in rapid differentiation from the founding and other populations.To infer source–sink relationships between sampling sites and whether populations were extirpated and then replaced by colonists from other populations, we first conducted an admixture analysis to elucidate meaningful population units from sampling sites. In this analysis, the greatest increase in posterior probability per increase in K = 8, most sampling sites were characterized by at least one cluster representative of the home population  and were therefore most likely to expose first‐generation migrants  and, for samples spanning sufficient timeframes Table , with rents Fig. . Monterents Fig. , appearents Fig. , genotypThe SJV South site shared a cluster with SB and SO , suggesting it could have been founded by a single pair or possibly a single pregnant female.Nevertheless, the question remains as to the explanation for the relatively sudden appearance of red foxes over such a widespread region. We hypothesize that this population explosion was ignited by releases of foxes from defunct fur farms in multiple locations, a practice that apparently began in the 1960s in response to the economic downturn associated with the industry , FST averaged <0.05  could be considerably greater in the foothills, as has been suggested for other lowland fox species  among populations enabled us to investigate aspects of the landscape preventing or promoting connectivity as well as the directionality of gene flow between neighboring sites. The observed correspondence between model‐free genetic distance surfaces and topographic features for both mtDNA and microsatellite markers suggested a highly fragmented metapopulation. This pattern was corroborated by modeling the association of occurrence records – a completely independent data set – with landscape variables, which provided a more highly resolved map of the predicted distribution . The confrontation of this model with genetic data, which confirmed its utility for also representing dispersal habitat, indicated that human‐dominated valleys were the primary dispersal corridors and less human‐dense mountains, the primary barriers. The affinity of nonnative red foxes for human‐dominated valleys may stem partly from their feral nature and consequent ability to thrive in disturbed habitat . The observed genetic distinctiveness of the SF Bay area populations could relate to the original sources founding them, to the lack of gene flow after their establishment, or to both. One particular mechanism potentially constraining gene flow was natal habitat‐biased dispersal, that is, the tendency to disperse into familiar habitat  in Scotland  interpolations of residual genetic distances.Figure S2. Relationship between average log probability of the data and the number of clusters (K) in 10 replicate runs of Structure in all foxes.Figure S3. Cumulative frequency of genotypes relative to numbers of cluster profiles in all foxes.Figure S4. Hierarchy diagram of cluster profiles in all foxes.Figure S5. Relationship between average log probability of the data and the number of clusters (K) in 10 replicate runs of Structure in a subset of foxes.Figure S6. Cumulative frequency of genotypes relative to numbers of cluster profiles in a subset of foxes.Figure S7. Hierarchy diagram of cluster profiles in a subset of foxes.Figure S8. Bar graph indicating the ancestry fraction (q) apportioned to individual genotypes in a subset of foxes.Figure S9. Bar graphs indicating ancestry fraction (q) in red foxes in different sampling periods.Figure S10. Bar graphs indicating mtDNA haplotypes in red foxes in different sampling periods.Click here for additional data file.


Alticus arnoldorum), where marine larval dispersal is the only probable means of connectivity among populations. We then compared these estimates to simulations of a range of marine dispersal scenarios and to collated FST and distance data from the literature for marine fish across diverse spatial scales. We found genetic connectivity at sea was extensive among marine populations and in the case of A. arnoldorum, apparently little affected by the presence of ecological barriers. We estimated that ~5000 km  was the spatial scale at which evolutionarily meaningful barriers to gene flow start to occur at sea, although substantially shorter distances are also possible for some taxa. In general, however, such a large estimate of connectivity has important implications for the evolutionary and conservation potential of many marine fish communities.Quantifying the spatial scale of population connectivity is important for understanding the evolutionary potential of ecologically divergent populations and for designing conservation strategies to preserve those populations. For marine organisms like fish, the spatial scale of connectivity is generally set by a pelagic larval phase. This has complicated past estimates of connectivity because detailed information on larval movements are difficult to obtain. Genetic approaches provide a tractable alternative and have the added benefit of estimating directly the reproductive isolation of populations. In this study, we leveraged empirical estimates of genetic differentiation among populations with simulations and a meta-analysis to provide a general estimate of the spatial scale of genetic connectivity in marine environments. We used neutral genetic markers to first quantify the genetic differentiation of ecologically-isolated adult populations of a land dwelling fish, the Pacific leaping blenny ( Genetic exchange among individuals and between populations—i.e. genetic connectivity—is important for the evolutionary dynamics of species across all spatial and temporal scales, from a local to regional level and from thousands to millions of years. Indeed, there has been enormous interest in estimating gene flow across space and time and this information has been used to understand biological and evolutionary processes like adaptation, biogeographic history and speciation . In addiFST  among populations will be positively correlated with geographic distance , has hice (e.g. ). As a rce . Whi. WhiFST Alticus arnoldorum) found on the Micronesian island of Guam , and are the most likely means by which individuals might be exchanged among populations. Because of this, A. arnoldorum provides a good opportunity to quantify the geographic extent of connectivity among populations that results primarily from the movement of marine larvae. This can be extremely difficult to achieve in genetic studies of population structure in the marine environment that sum the results of larval and adult dispersal .A. arnoldorum on Guam to genetic differentiation data from simulations that assumed a range of realistic marine dispersal scenarios for this species. The simulation used a spatial matrix of the inter-tidal zone around Guam and used various density-dependent models of dispersal. Thus, we were able to evaluate the extent to which a primarily larval-dispersed marine fish exhibited predictable or unexpected levels of population genetic differentiation.We compared our estimates of population genetic differentiation of A. arnoldorum into its broadest context by obtaining a general estimate of connectivity among marine fishes  using a meta-analysis of FST and distance data from published literature. Estimates of gene flow using FST have been documented by hundreds of studies for an equally vast number of spatial scales and different organisms including fishes. We took advantage of this enormous resource to estimate the rate at which gene flow is curbed by distance in marine fish across all environments and spatial scales. In doing so, we generalised the extent to which FST increases with distance and the magnitude of connectivity in marine fish globally.Second, we placed these findings from the larval-dispersing By integrating an empirical study, simulations and a meta-analysis , our oveA. arnoldorum, with little to no adult dispersal, populations should exhibit higher global FST than the simulated data  and low connectivity between populations that are geographically close . This outcome would indicate a more terrestrial mode of dispersal. Indeed, terrestrial animals such as mammals that cannot disperse in their earliest developmental stage generally have higher global FST than larval dispersers like fish [A. arnoldorum should be much higher than the median rate for marine fish collated in our meta-analysis if combined larval and adult dispersal results in high genetic connectivity in the marine environment . Given nt i.e. –12)..A. arnolA. arnoldorum might result from passive larval dispersal driven by ocean eddies and currents around Guam, followed by a sedentary adult phase . In this scenario, a Lagrangian larval dispersal model [A. arnoldorum predicts dispersal distances of up to 300km (~10km/day). As the circumference of Guam falls within this distance (~150 km), there should be no significant population structure among populations of A. arnoldorum. Instead, the global FST of A. arnoldorum should be similar to simulations that assume high dispersal scenarios  with a rate of IBD in A. arnoldorum being equal to, or less than, the median rate for marine fish estimated by our meta-analysis.Alternatively, connectivity among populations of al model  that assA. arnoldorum might be a combination of passive and active larval dispersal, followed by a sedentary adult phase (see scenario 2 above). Such a pattern could occur if natural selection is acting on a local level either before or after settlement due to ecological differences between sites , and the rate of IBD in A. arnoldorum should be equal to, or greater than, the median rate of FST and distance for marine fish from our meta-analysis.Finally, connectivity among populations of .g., see ). In thi.g., see , 46, whiThis study was carried out following procedures set by the University of New South Wales Animal Care and Ethics Committee in protocol #11/36b, initially approved on the 10th March 2011 and most recently reviewed on the 28th February 2013. Specimens were euthanized by first anaesthetizing fish using clove oil and then storing them under ice. No permits or approvals were required to collect specimens on Guam, and no work was conducted on private or protected land. All data from this publication have been archived in the Dryad Digital Repository (doi:10.5061/dryad.v63g0) and Genbank (KU922092-KU922117).Alticus arnoldorum fish  were collected each from six field locations around Guam  and data were obtained from both the mitochondrial (mtDNA) and nuclear genomes. The mtDNA adenosine triphosphate subunits 6 and 8  were amplified via polymerase chain reaction (PCR) for 20 samples per site using primers ATP8.2 and CO3.2 [Exosapit (Affymetrix), and sequenced by Macrogen on a 3730XL DNA sequencer. For the nuclear data set (number (n) = 204) we developed 17 novel microsatellite loci for A. arnoldorum using 454 next generation sequencing technology following Gardner et al [th of a PicoTiter plate at the Australian Genome Research Facility  on a Roche GL FLX (454) system. QDD was then used to detect microsatellites in the 454 output and to design primers. 1724 sequences containing putative microsatellite motifs with a minimum number of five repeats were identified. Of these, we selected 20 of the best loci for PCR trials, resulting in 17 polymorphic loci } with an initial denaturing at 95°C for 60 s, followed by a 65–53°C touch-down, ending with 30 cycles of 95°C for 15 s, 53°C for 15s and 72°C for 30 s with a final extension of 70°C for 5 min. Multiplexed PCR products using labelled primers (GeneMapper version 4.1 (Applied Biosystems).Thirty-four individual nd CO3.2  with PCRnd CO3.2 . PCR proer et al . A minimprimers: . PCR amp primers  were runGeneious v.5.6.  and genealogical relationships among individuals were investigated using the coalescent-based approach in TCS [Arlequin 3.5.1.2 [The 120 mitochondrial ATPase 6 and 8 sequences were aligned using h in TCS , 51. Seqh in TCS  per popu 3.5.1.2 .Arlequin. Mismatch analysis tests for the agreement of the data with a model of demographic expansion [FS values are generally observed. We also assessed the demographic history of the A. arnoldorum on Guam with a Bayesian Skyline Plot  modelleT v1.7.2  using thT v1.7.2  and a GTT v1.7.2  was thenST [Arlequin [ST) and geographic distance, either direct (Euclidian) or coastal distance in Arlequin [For the mitochondrial data set, pairwise population genetic structure was calculated as ΦST  and the Arlequin . IsolatiArlequin ) was invArlequin  of the aArlequin .Arlequin and linkage disequilibrium was assessed using Genepop [Microchecker [INEst [FIS) in the presence of null alleles at proportions (pn). We estimated genetic diversity at each locality as number of alleles per locus, allelic richness, and Wright’s inbreeding coefficient (FIS), using the software FSTAT [Arlequin [For the microsatellite dataset, the 17 microsatellite loci were tested for departures from Hardy-Weinberg equilibrium (HW) in  Genepop , 61. Micochecker  was thenr [INEst . This mere FSTAT  and expeArlequin .FST) of microsatellites among populations was estimated and tested for significance with 10,000 permutations using Arlequin [ST_est [est [FST was tested using a linear regression [SHUA) which is thought to provide another robust estimation of genetic exchange in addition to FST [, for pairwise population comparisons in Genalex [Pairwise genetic differentiation  probability of the data versus K over multiple runs and change in K (∆K) following Evanno et al. [FST) and direct and coastal distance  was calculated for individuals sampled in the same locality (distance class 0) and among individuals separated across a range of distances from 0 to 100 km evaluated at 5 km increments. Our data was tested against the null hypothesis of randomly distributed genotypes, with 999 permutations and 999 bootstrap replicates.o et al.  with 1,0o et al.  were alsce  in ArleArlequin . Spatial[Genalex  was thenIBDSim v.2 [IBDSim is based on a backward-in-time coalescent method that enables the generation of large data sets using complex demographic scenarios. For our simulations, we constructed a 100 km × 0.5 km matrix that was representative of the entire intertidal area between the two most distant sample sites on Guam . Our simulations therefore provide an assessment of genetic differentiation across a reasonable range of population densities .Next, we simulated genetic differentiation under a range of dispersal scenarios and compared these results with our microsatellite data. To do this, we used DSim v.2  to simuler study  conducteIBDSim Manual as ‘0’, ‘2’, ‘3’, ‘6’, ‘7’, and ‘9’; [2). For our simulated matrices representing a range of dispersal scenarios, the default values defined by IBDSim for dispersal distributions correspond to mean squared parent-offspring dispersal distances of 10 m, 40 m, 100 m 200 m, 1000 m. These distances can be interpreted as the average squared axial distance that offspring of a common ancestor will become separated per generation [M and n that control the maximum dispersal rate per generation and kurtosis (a measure of shape) of the dispersal distribution per generation respectively  to provide a “99% percentile” for FST values at each density.For each simulated population density, we used input parameters that closely matched those of our empirical dataset. These included 17 microsatellite loci under a strict stepwise mutation model  using aand ‘9’; ) to modeneration , 73. The Manual; ). For ea Manual;  and a on Manual; ) that al Manual; , 76. ThiFST over geographic distance in marine fish from published studies. This enabled us to estimate the rate at which genetic differentiation accumulates as a function of geographic distance. To collect these data, a systematic literature search was conducted in Web of Science®. Titles, abstracts and keywords of all articles published between 2006 and 2011were searched for using the terms: ‘phylogeography*’, ‘population genetic structure*’, ‘population genetic*’ and ‘landscape genetics*’. Of the 612 articles pertaining to fish, 66 focused on marine fish, employed microsatellite markers, compared more than three populations, provided usable geographic information and measured pairwise FST  and our analysis also relies on this assumption. We calculated the average number of individuals per population sampled per study to provide an approximate measure of precision that was then used to obtain a weighted average β for each species. Unweighted averages were also assessed but these gave very similar results and did not change any of the conclusions. Additionally, we recorded for each study whether or not spatial population structure was present , and where tested by the authors, whether or not there was IBD  or panmixia. This enabled us to test for any association between our measure of β and IBD (or lack there of) identified by the authors. For these analyses, species averages were not used to allow for comparison across studies.Where ΔFST. This was used instead of simply comparing “raw” FST values by distance because the magnitude of individual FST values will differ depending on the number of alleles within each sub-population examined by a study [FST values estimated for the furthest and nearest population reported by a study helps control for this potential bias among studies since we are comparing the rate at which FST accumulates with distance across studies rather than raw FST values. Moreover, the geographic distance at which the maximum pairwise FST occurs has been documented to be highly variable , and thA. arnoldorum was calculated with a Mantel test on microsatellite data. Due to the non-independence of pairwise comparisons and sample size (six populations), no confidence intervals for the A. arnoldorum estimate were calculated.Where data were collected for the same species over multiple studies, the average slope between studies, weighted by the average number of individuals per populations in each sample, was calculated. This reduced our sample size from 66 studies to 58 distinct species. The confidence interval for the slope was then estimated using a bootstrapping percentile procedure in R version 2.15.0 . Bootstrapping was weighted by average sample size (NB: unweighted bootstrapping gave very similar results). The slope for FST between the closest and furthest pairwise populations on a plot of distance (x-axis) by FST (y-axis) was calculated  was calculated as:We also used our meta-analysis data to estimate the geographic distances necessary to achieve a range of genetic differentiation values for marine fish more generally. For each species, the linear line connecting α is the intercept of the extrapolated line, and β is the slope of this line  of ATPase 6 and 8 for 120 individuals including the start and stop codons for each gene. These were composed of 29 unique haplotypes, defined by 25 variable characters of which seven were parsimony-informative. Summary statistics for the mitochondrial data are shown in A. arnoldorum on Guam suggest a recent population size increase that may have occurred during the late Pleistocene. While analyses based on a single molecular clock must be interpreted with caution, BSP analysis indicated that A. arnoldorum population size increased on Guam approximately 20 thousand years ago  a result also indicative of demographic expansion or directional selection. For the mismatch analysis however, our data deviated significantly from the model expected under demographic expansion . However, the distribution of the observed number of pairwise differences was unimodal in distribution, which is expected of populations experiencing demographic expansion [Analyses of demographic trends in ears ago . Consistxpansion .O ranged from 0.645 (TS) to 0.703 (AP). Observed and expected HWE values and their associated P- values for each locus within each sampling location are shown in Microchecker found that there does not appear to be any scoring error or allele dropout, but at approximately half the loci, null alleles may account for the homozygosity excess observed in our data. Further, the multilocus “null free” average inbreeding coefficient (FIS) as calculated by INEst ranged from 0.004 to 0.006 and was much lower than FIS derived using 1-HO/HE . Within each sampling location, the average H 1-HO/HE . This suA. arnoldorum on Guam. For the microsatellite dataset, overall genetic differentiation (FST) was very low (0.0043) and changed little with the removal of the loci with null alleles (0.0053). Analysis of pair-wise population structure based on mtDNA ΦST was very low and non-significant for all population comparisons . Pair-wise population structure based on FST was very low (ranging from 0.0008–0.0095) yet a statistical effect was discernible after Bonferroni correction in five of the 21 pairwise comparisons (SHUA) was also very low and ranged from 0.021–0.032 and had no statistically distinguishable effects in any pairwise comparison. In a similar manner to mtDNA, there was no relationship between geographic distance  and FST. Generally, the same pattern of significant pairwise population structure (FST) was observed across the matrix following the removal of the loci that had putatively null alleles, with the exception of two pairwise comparisons   indicating possible greater than random genetic similarity. However, given the large increase in variance around r within this distance class, this result should be interpreted with caution.From microsatellite spatial autocorrelation analysis, there was a small, but statistically distinguishable effect of positive spatial structure (greater than random genetic similarity) is present between pairs of individuals from the same sampling site, regardless of whether or not the putative null alleles were excluded or included in the analysis  . Howeverpt 20 km . At 20 kFST was more dependent on grid population density than dispersal scenario , our simulations suggest a population density just below one individual m-2  the density of larval fish was lower than settled adult populations; or (iii) that the distribution of individuals was fragmented around the circumference of Guam.In each of our computer simulations, scenario : global dual m-2 . The aveuals m-2 , which wow 0.001 . This coFST slope over geographic distance (β) not surprisingly we found considerable variation across the published studies: slopes ranged as low as -0.0049 km-1  to as high as 0.0017 km-1 . However, the majority of β values were clustered close to zero with the interquartile range lying between -6.0 x 10-7km-1 and 2.1 x 10-5km-1 , 15% reported little to no spatial genetic structure (few significant pairwise FST comparisons), while 65% reported spatial genetic structure (the majority of pairwise FST comparisons were significant)  compared to studies that found no evidence of IBD . However, the median β in studies that identified IBD was significantly different from zero  . The mos zero , we predicted the geographic distance at which a given FST is likely to be observed  would result in our overall estimate of FST slope with distance presented in the article to be greater than it should be. This would mean that FST accumulates even more slowly across vast oceanic distances already supporting our conclusion .By extrapolating the complete meta-analysis data set and assuming that the relationship between observed . This shT = 0.15 , the datAlticus arnoldorum) to biologically informed simulations and a large meta-analysis of published literature, we provide a broad estimate of the patterns and spatial scale of genetic connectivity at sea. Our comparison was framed around three alternative scenarios of how the behaviour of pelagic larvae might impact genetic connectivity among marine populations. Our results suggest that a scenario involving both passive and active larval dispersal explains the extensive connectivity among populations of A. arnoldorum  for a pair of populations to reach 50% of the drift-dispersal equilibrium FST using the following equation [While our results clearly showed an absence of spatial genetic structuring and IBD in both microsatellite and mitochondrial DNA among sampled sites of und Guam  Tables, und Guam . The ratine fish . Given tequation :T=ln(0.A. arnoldorum of five larvae m-2 (e.g. [m) is 1% per generation and that the effective population size (Ne) is 10% of the maximum population density [T is approximately 23 generations. This would be well within the timescale predicted using Bayesian Skyline Plot analysis , that danalysis . It seem-1 [-1, it is possible for a passively drifting particle to travel ~242 km during the time of the average pelagic larval phase of an A. arnoldorum . This distance is less than the 300 km estimated under a Lagrangian dispersal model for the same time frame [A. arnoldorum despite adult populations being ecologically isolated from one another. This is common in coral reef fish [The patterns of ocean circulation around Guam are generally both spatially and temporally variable with an overall flow that fluctuates from westward to northward at speeds of 0.1–0.2 ms-1 . At the me frame  yet stileef fish , 86, 87,eef fish , 88–92.A. arnoldorum populations  have been shown to reflect direct estimates of dispersal in mammals (e.g. ), reptilβ  is consβ was calculated separately for studies exhibiting IBD compared to those that did not , not surprisingly, we found that the β was considerably higher and significantly different to zero in studies that found IBD compared to those that did not  actually identified IBD . In the  did not . This reβ in our meta-analysis  presumably underlies the considerable variance in analysis ; Table 2distance . Indeed, = 0.15; ), and po = 0.15; ). HoweveFST values are generally expected for highly heterozygous markers such as microsatellites [FST comparison. In addition, frequently used measures of genetic connectivity including FST may also over-estimate population connectivity . This is because it takes only a few migrants between populations per generation to prevent the accumulation of appreciable genetic differentiation as presumed by FST [It is also important to recognise that low tellites , which ctellites . This pad by FST . Indeed,d by FST , 106 andd by FST , 25. TakWith this in mind, the degree to which populations are connected based on our meta-data still has some potentially important ramifications for understanding how species respond to selection and adapt to environmental change . Even raFST Click here for additional data file.S2 Fig10 of the effective population size, and the thin grey lines are the 95% higher posterior density.The thick black line is the median estimate of the log(TIF)Click here for additional data file.S3 FigIndividuals are grouped by sampling location and each individual is represented by one vertical line broken into K coloured segments, with the lengths being proportional to the K inferred cluster.(TIF)Click here for additional data file.S1 TableA, number of alleles.Types of fluorescence used to label forward primers are indicated with the primer sequence . N(DOCX)Click here for additional data file.S2 TableNa, number of alleles per locus; Ar, allelic richness; FIS, Wrights inbreeding coefficient; HW Obs, Hardy-Weinberg observed heterozygosity; HW Exp. Hardy-Weinberg expected heterozygosity; and HW p-value, Hardy-Weinberg P-value; *, significant after sequential Bonferonni correction.(DOCX)Click here for additional data file.S3 TableNo comparisons were significantly different.(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 TableN, correlation, r, upper U and lower L bounds for a 95% confidence interval (H0: r = 0), the upper Ur and lower Lr bounds determined by bootstrap resampling, the probability P of a one-tailed test for positive autocorrelation, and the x-intercept are shown across all distance classes.The number of pairwise comparisons, (DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.


Japan has often been viewed as an Asian country that possesses a genetically homogenous community. The basis for partitioning the country into prefectures has largely been geographical, although cultural and linguistic differences still exist between some of the districts/prefectures, especially between Okinawa and the mainland prefectures. The Major Histocompatibility Complex (MHC) region has consistently emerged as the most polymorphic region in the human genome, harbouring numerous biologically important variants; nevertheless the presence of population-specific long haplotypes hinders the imputation of SNPs and classical HLA alleles. Here, we examined the extent of genetic variation at the MHC between eight Japanese populations sampled from Okinawa, and six other prefectures located in or close to the mainland of Japan, specifically focusing at the haplotypes observed within each population, and what the impact of any variation has on imputation. Our results indicated that Okinawa was genetically farther to the mainland Japanese than were Gujarati Indians from Tamil Indians, while the mainland Japanese from six prefectures were more homogeneous than between northern and southern Han Chinese. The distribution of haplotypes across Japan was similar, although imputation was most accurate for Okinawa and several mainland prefectures when population-specific panels were used as reference. The advent of high-throughput genotyping technology has considerably advanced our understanding of human genetic variation globally. Landmark studies such as the Human Genome Diversity Project2368910111214151618192021Studies have reported considerable genetic differences at the MHC between global populations18Although the classical serotyping, and the subsequent conversion to the HLA allele nomenclature, provides the most biologically relevant information, the availability of this information for global populations lags considerably as compared to the availability of SNP data1827In this study, we investigate the extent of haplotype diversity in HLA Class I and Class II genes across eight Japanese populations, comprising Ryukyu samples from the Okinawa prefecture and seven groups of samples from six prefectures, located in or close to the mainland of Japan. To benchmark the extent of genetic diversity seen in these eight populations, we performed the same analyses between: (i) East Asian samples with ancestries originating from North and South China; and (ii) South Asian samples with ancestries originating from the Gujarat state in North India and from the Tamil-Nadu state in South India . In ordeThis study considered 1,400 Japanese individuals which is a subset of the 3,933 subjects in Asian Diversity Project (ADP), comprising 200 subjects each from seven regions (prefectures or cities): Amagasaki (in Hyogo Prefecture), Ehime, Fukuoka, Kita-nagoya (in Aichi Prefecture), Okinawa, Shimane and Tokyo. We additionally considered 85 unrelated Japanese samples from Tokyo in Phase 3 of the International HapMap Project (HapMap)PHWE > 0.05) were retained in our analysis, while all samples were used as these data have been already subject to prior quality control in previous publications5293031323334Four of the seven Japanese populations from the ADP  were genotyped on the Illumina Omni 2.5 M array, while samples from Shimane and Tokyo were genotyped on the Illumina HumanHap550, and samples from Okinawa were genotyped on the Illumina OmniExpress. The HapMap and SGVP samples were genotyped on both the Affymetrix SNP6.0 and the Illumina Human1M. Only SNPs with call rates greater than 95% and with no departure from Hardy-Weinberg equilibrium  in Japan: Amagasaki (in Hyogo Prefecture), Ehime, Fukuoka, Kita-Nagoya (in Aichi Prefecture), Okinawa, Shimane and Tokyo, apart from 85 unrelated Japanese subjects from Tokyo in Phase 3 of the International HapMap Project, abbreviated as HapMap JPT. Blood samples were collected in the individual regions for anthropology and/or genetic epidemiology study. All participants from the different studies provided written informed consent, and the local ethics committees approved the protocols30313233343031323334The Amagasaki Study is an ongoing population-based cohort study of 5,743 individuals , aged >18 years and recruited for a baseline examination between September 2002 to August 2003Participants in the Anti-aging study cohort (AASC) are middle-aged to elderly persons who were consecutive participants in the medical check-up program at Ehime University Hospital Anti-aging CenterThe Kyushu University Fukuoka Cohort Study is a community-based prospective epidemiologic cohort of 12,959 subjects, who participated in the baseline survey during the period from February 2004 to August 2007The Kita-Nagoya Genomic Epidemiology (KING) study  is an ongoing community-based prospective observational study of the genetic basis of cardiovascular disease and its risk factorIn the study of the Ryukyu population, only individuals, whose four grandparents were originated from the Ryukyu Islands, were includedThe Cardio-metabolic Genome Epidemiology (CAGE) Network is an ongoing collaborative effort to investigate genetic and environmental factors, and their interactions affecting cardiometabolic traits/disorders among Asian populations, including the Japanese, Vietnamese and Sri LankanThe genotype data for all the Japanese populations were phased with BEAGLE version 3.3.2ST defined as the following by Rosenberg and colleagues1To investigate the extent of allele frequency differences at each SNP between two populations, we calculated the SNP-level Fp1 and p2 denote the frequency of a particular allele in the two populations respectively. This was calculated between every pair of populations in the collection of eight Japanese and four benchmarking populations.where HLA-A, HLA-B, HLA-C, HLA-DR, HLA-DQ and HLA-DP for the purpose of measuring the extent of diversity in the observed haplotypes in the MHC region. For each of the six HLA genes, a buffer region of 100 kb up- and downstream is appended and the distinct haplotypes that are formed by the SNPs located within this extended gene region is considered. The multi-allelic version of FST in ARLEQUIN version 3.1ST for each gene locus between every pair of populations. Since the samples were characterized with SNP arrays alone in the present study, the HLA haplotype data were not converted to the HLA allele nomenclature but arbitrarily numbered in the individual HLA genes.Our analyses considered six HLA genes: smartPCA in the EIGENSOFT packageK × K distance matrix, where the  element in the matrix is given by the average SNP-level FST between population i and population j, averaged across 1,607 common SNPs present in the interval between 25 Mb and 35 Mb on chromosome 6. The second set of three PCAs considered the same population set as the first set of three PCAs, between 12 (K = 12), eight (K = 8) and seven (K = 7) populations respectively. The third set of three PCAs was similar in construct to the second set, except that the analysis considered the haplotype-based FST at each of the six HLA genes.A series of PCAs were performed with different input. The first set of three PCAs were performed with r2) between the observed genotype and the imputed allele dosage was calculated for the 400 masked SNPs across the 19 samples, and for the purpose of benchmarking imputation performance, we defined the discordance rate as 1 – r2. For benchmarking, the Han Chinese and Indian samples were similarly included in the imputation analyses, as both reference panels for the Japanese and as target data to be imputed, although the accuracy of the imputation for these samples with population-specific panels was not meaningful due to overfitting. All imputation was performed with IMPUTE version 2.3.0We performed a series of SNP imputation in the different Japanese populations to evaluate the performance of the different population-specific and combined reference panels at the MHC. The target data to perform the imputation comprised 19 new subjects from each of the seven Japanese populations which similarly possessed the same 1,607 SNPs, although we masked 400 random SNPs and used the remaining 1,207 SNPs as input for imputation. Each population was imputed nine times, against the eight single-population reference panels and the combined East Asian reference panel which was derived from a combination of the CHB, CHS, JPT and Southeast Asian Malay samples from the SGVP or HapMap. Each of the seven population-specific panels consisted of 200 individuals, while the combined East Asian panel consisted of a modestly larger size with 350 individuals. The squared Pearson correlation coefficient  were significantly distinct from the East Asian populations , although it was also clear that there were three genetic sub-clusters that corresponded to the Okinawa samples, Han Chinese and mainland Japanese respectively . The OkiK × K distance matrices (K represents the number of populations) constructed from the 1,607 SNPs in the 10 Mb region on chromosome 6 . This effectively represented the genetic distance using the FST metric to quantify the extent of allele frequency differences between pairs of populations. These analyses similarly distinguished the South Asians and Han Chinese from the Japanese samples  and Shimane . The distinction between Ehime and Shimane and the rest of the mainland Japanese samples was similarly observed in the haplotype-based PCAs at the six HLA genes , while H8 was not found in any of the eight Japanese populations  were used as the target data for imputation.We observed that the use of either the HapMap JPT panel or the combined East Asian panel yielded marginally higher discordance rates, when compared to the use of most of the single-population panels , providiThree other Japanese populations  similarly produced the lowest discordance rates when the respective population-specific reference panels were used, although this was not unique to the population-specific reference panels; there were at least one other single-population panel that yielded an equivalent level of discordance rates. For example, the lowest discordance rate of 2% was seen in Shimane when either the Shimane panel or the Amagasaki panel was used as reference. It was also evident that the use of reference panels constructed from Han Chinese or Indians yielded comparatively poorer imputation performance for the Japanese samples.Our study has examined the genetic diversity between eight Japanese populations, comprising samples from Okinawa Prefecture and seven other populations samples from six prefectures, located in or close to the mainland of Japan. Our analyses focused on evaluating the genetic variation seen in the HLA Class I and Class II genes at the MHC, especially on how haplotypes differed between these populations as a surrogate to infer imputation performance for recovering the classical HLA alleles with SNP-level data. We used two pairs of populations from South Asia  and East Asia  to benchmark the extent of genetic differences observed in the Japanese populations. There were multiple lines of evidence to support that Okinawa (Ryukyu) samples from Okinawa Prefecture were distinct from the mainland Japanese individuals, even more distinct than the case for genetic differences between North and South Indians. While mainland Japanese were comparatively more homogenous than Han Chinese, samples from Ehime Prefecture appeared to be marginally different from the remaining mainland Japanese individuals. The genetic differences observed between the eight Japanese populations can be partially explained by diversity at the haplotype level; the distribution of major haplotypes in each of the HLA genes has been found to vary between the populations, particularly between Okinawa and mainland Japanese populations. The haplotype variations at the MHC appear to be manifested by the discernible differences in imputation accuracy, where population-specific panels can yield marginally better performance than even a combined East Asian panel, despite the substantial homogeneity observed between the Japanese populations.While the first phase of our imputation analysis contrasted the accuracy with the HapMap JPT reference panel against the accuracy with the population-specific and East Asian combined panels, it should be highlighted that the conventional approach to SNP imputation is to use the largest possible cosmopolitan panel, which is generally formed by a combination of samples from all available reference populations. Our intent of current genetic comparison analysis was to highlight the point that, even within the homogenous mainland Japanese populations where the predominant genetic differences were seen for the inter-population frequencies of the major haplotypes but not for the haplotype classes, there were some gains by using well-matched samples from the same populations as reference. This is important from the perspective of HLA imputation, as it has previously been shown that the use of cosmopolitan panels does not always yield superior performance to a smaller but population-specific panel27While numerous studies have thus far reported the presence of complex linkage disequilibrium (LD) patterns at the MHC4142435One may ask whether the population differentiation observed at the MHC extends to the rest of the genome, especially because in a study by Yamaguchi-Kabata and colleaguesBy virtue that the MHC is significantly more polymorphic than the rest of the genome, harbours one of the most biologically important regions in the genome and at the same time possesses long stretches of high LD, there is a need to acknowledge that broad metrics of imputation performance often calculated with input from across the genome may potentially mask important limitations with regard to imputation of SNPs in the HLA regions. Several studies4748How to cite this article: Saw, W.-Y. et al. Mapping the genetic diversity of HLA haplotypes in the Japanese populations. Sci. Rep.5, 17855; doi: 10.1038/srep17855 (2015).


Mycteroperca microlepis, an important fishery species, are genetically connected across the Gulf of Mexico and if so, whether that connectivity is attributable to either contemporary or historical processes. Populations of Gag on the Campeche Bank and the West Florida Shelf show significant, but low magnitude, differentiation. Time since divergence/expansion estimates associated with historical population dynamics indicate that any population or spatial expansions indicated by population genetics would have likely occurred in the late Pleistocene. Using coalescent-based approaches, we find that the best model for explaining observed spatial patterns of contemporary genetic variation is one of asymmetric gene flow, with movement from Campeche Bank to the West Florida Shelf. Both estimated migration rates and ecological data support the hypothesis that Gag populations throughout the Gulf of Mexico are connected via present day larval dispersal. Demonstrating this greatly expanded scale of connectivity for Gag highlights the influence of “ghost” populations (sensu Beerli) on genetic patterns and presents a critical consideration for both fisheries management and conservation of this and other species with similar genetic patterns.Describing patterns of connectivity among populations of species with widespread distributions is particularly important in understanding the ecology and evolution of marine species. In this study, we examined patterns of population differentiation, migration, and historical population dynamics using microsatellite and mitochondrial loci to test whether populations of the epinephelid fish, Gag,  Understanding the genetic structure of populations requires distinguishing the signature of historical influence from the consequences of contemporary patterns of migration and population size , 2. DescWide-ranging taxa that display little or no spatial differentiation in genetic variation present a different interpretive challenge. Many reef-associated marine species found in the southeastern United States (including in the Gulf of Mexico (GOM) and along the Atlantic coast) show this particular pattern of having an extended range with low levels of present day population differentiation –15. In tThunnus obesus) revealed sizeable and asymmetrical migration patterns between Atlantic and Pacific populations, inconsistent with population genetics determined solely by historical factors [Fundulus heteroclitus, reveal the complexity that the intersection of historical and contemporary processes can generate. In each of these cases, we have gained a greater understanding of factors affecting population genetics and their relationship to understanding current species biology.Developments in population genetic methods –22 have  factors , while,  factors . Even mo factors  assessmeMycteroperca microlepis, an epinephelid fish common in the Gulf of Mexico and Western Atlantic and target for important regional fisheries, illustrates these issues related to the population genetics of wide-ranging marine species. Gag possess a complex life cycle and a set of distinct life history that are broadly representative of many reef fishes in this region. This includes ontogenetic migrations among diverse habitats over the course of their life time, from an open ocean pelagic larval stage lasting about 40 days, to seagrass associated juvenile stage for 7–9 months [Gag, 9 months –28, and 9 months –28. In a9 months . Individ9 months  or among9 months , 31.Studies on other species from the GOM provide little insight as to whether this lack of spatial structure in Gag is because of historical or contemporary processes. Fluctuation in sea level and large oscillations in the size of the GOM over evolutionary time have been suggested as mechanisms for homogenizing genetic variation among different reef fish populations, while also explaining why population genetics reflect recently expanded rather than historically isolated populations , 33. AltIn this study, we examined genetic variation in Gag populations on Campeche Bank and the West Florida Shelf to evaluate hypotheses about emerged patterns that appear to be explained by contemporary gene flow. By using a variety of genetic data and implementing traditional and coalescent-based methods, we distinguish the signature of history from the pattern produced by ongoing migration, providing evidence for regional population connectivity previously underappreciated in contemporary population genetic assessments.Genetic samples (fin clips and heart tissue) for adult Gag were collected in conjunction with collaborative research efforts with commercial fishermen along the West Florida Shelf (WFS)  and fishMycteroperca bonaci [Epinephelus morio [Epinephelus quernus [Genomic DNA was extracted using magnetic beads methodology . Microsatellite primers for 10 loci, developed in other studies for Gag , black ga bonaci , red grous morio , and Haw quernus , were aset al., 1990). The high-fidelity Invitrogen Pfx50 Taq was used to minimize sequencing errors. PCR products were direct sequenced using PCR primers. All samples were sequenced with both forward and reverse primers and no sequence was included in the data set where contigs of those two sequences could have yielded ambiguous results (any repetitive regions required both flanking regions to be sequenced appropriately). All sequence ambiguities were examined, edited manually, and aligned using Sequencher v.4.5 software. Two perfect-repeat indels were found in this region . All raw genotypic and sequence data can be found in a priori, to be experiencing high migration rates (those in close proximity to one another on the WFS) and regions that may be experiencing much lower migration rates (Campeche Bank and the West Florida shelf). The rationale for the second scheme is based on previous studies that demonstrated (1) spatial differences in growth patterns of a related species, the Red Grouper Epinephelus morio along the WFS, suggesting possible population structure [Patterns of genetic differentiation across the GOM were examined using both traditional F-statistic-based  and coaltructure ; (2) spatructure , and (3)tructure . Loci wetructure  as well tructure . Controltructure  and Fu’structure . Calculatructure , with mtGenetic differentiation among comparison groups was assessed across all loci. Microsatellite data were tested for differentiation among “populations” using Chi-squared tests  and Fish4, respectively.We explored the role of historical events on the present distribution of genetic diversity in several ways. Patterns in microsatellite gene diversity relative to equilibrium expectation were assessed using the program Bottleneck v.1.2.02 , implemeeμ) and mutation-scaled migration rates M (= m/μ) among groups. Finally, number of migrants (Nm) was calculated by using the generated estimates for θ and M (Nm = (θ*M)/4).Patterns of genetic connectivity for Gag in the GOM were examined using Bayesian coalescent approaches , 61. Migst scheme), and the 3-population model breaking up the WFS into NWFS and SWFS samples (2nd scheme).MIGRATE can accurately differentiate among migration models to find the one that is best supported by the data . It provST analyses) and specific models based on other regional Gag migration studies. These specific cases included the following 3-population examples: Scenario 1: CB as a genetic source population and WFS sub-populations as sinks (i.e. one-way migration from CB to both WFS populations and free migration within the WFS); Scenario 2: a migration model allowing connectivity among all population except for no migration from SWFS to CB; and Scenario 3: WFS as genetic source populations and CB as a sink (i.e. one-way migration from the WFS to CB and free migration within the WFS). Scenario 1 summarizes a connectivity hypothesis describing either historical dispersal from CB or on-going connectivity via larval dispersal [Scenario 2 reflects the combination of ecological hypotheses on connectivity from various ecological studies of Gag dispersal in the GOM [Scenario 3 models either historical secondary contact due to events such as historical range contractions typical to glaciation events or on-going adult migration from the WFS around the GOM to CB. Bayes Factors were calculated for all comparisons and values greater than 150 are considered very strong support for a particular model.While population size varied freely, migration type and directionality was strictly defined for various hypothetical “scenarios” (i.e. models) in order to examine hypotheses about what types of connectivity best describes the data. These migration “scenarios” included default models of migration among populations allowing for either unfettered asymmetric or symmetric migration among all populations  showed little evidence for significant deviations from equilibrium expectations for microsatellites. Only three tests of the ten loci within population supported significant deviations after Bonferroni correction, but no consistent pattern of bias could be determined for any one locus across all populations. No significant evidence for null alleles or large allele drop-out was observed. Loci exhibited variable levels of linkage disequilibrium among populations ; howevernd scheme comparisons). While the NWFS and SWFS appeared to be significantly different from each other, those differences disappeared after the application of Bonferroni corrections. Two-“population” comparisons of WFS and CB (1st scheme comparisons) also revealed significant differentiation using both Fisher’s Exact Test  and a Chi-squared Test . Tests possess sufficient power of detectability as POWSIM runs, using the allele frequencies determined from the empirical data, yielded false positive rates less than 5%. While we found some evidence of differentiation, the magnitude of this difference was quite small . This includes standardized measures of microsatellite FST-values (φ’ST), which compensate for high-heterozygosity bias, and, thus, low-magnitude values, associated with these loci. In fact, significant differentiation was often found where pairwise comparisons showed a negative value  for φ’ST. These results indicate that while significant genetic differentiation may exist between regions (particularly between CB and WFS populations), the effect size of such differences was small.We found statistically significant population structure across the GOM, but at a very low magnitude . Both NWWe found a similar low magnitude of population differentiation  in the mGenetic data suggested that patterns of genetic diversity were influenced by either demographic or spatial expansion. Mismatch distributions of mtDNA fit both pure demographic and spatial expansion models; however, different models were diagnosed as “best fit” when different subsets of the data were used. For sequence-only data, spatial expansion models could not be rejected from any level of examination i.e. ; howeverTime-since-expansion (τ) estimates indicated that any expansion predates the Holocene. All estimates were nested within the Pleistocene and were generally similar for both demographic and spatial expansion models. Times-since-expansion for spatial expansion models in the entire GOM were 109,740 ) years ago (ya), 140,627 ) ya, and 85,702 ) ya for sequence, RFLP, and combined data, respectively. Interestingly, GOM and CB showed similar value for τ in both models for sequence data. WFS, SWFS, and NWFS all showed lower values for τ than CB . Thus, wScenario 1), the 3-population migration model which mimicked available ecological data (Scenario 2), full 3-population migration model, full 3-population symmetric migration model, one-way migration from CB to WFS, one-way migration from WFS to CB, full 2-population model, full 2-population symmetric model, one-population model, one-way migration from NWFS and SWFS to CB (Scenario 3). Except the poorly fitted Scenario 3 model, CB showed consistently higher estimates for θ than the other populations (Scenario 1), patterns of migration, based on the estimated number of migrants (Nm), showed substantial migration from CB to both NWFS and SWFS (Nm > 20) that was on the same scale as that between NWFS and SWFS , five converged on estimated values , while one (θWFS = 1837.06) appeared to be indeterminately large when examining posterior parameter estimation distributions. This result indicates that the IMa-model, which is a very robust means of simultaneously assessing the effects of both migration and population growth on patterns in population genetics data [CB to WFS = > 2000; Nm WFS to CB = 1.5) and estimates of time of divergence are within the confidence intervals of those estimated from mismatch distributions (see Runs of the program MIGRATE v3.1.2 on the microsatellite data described genetic migration patterns dominated by asymmetric gene flow. The ranking of migration models based on Bayes Factor (BF) scores resulted in the following hierarchy ): one-way migration from CB to NWFS and SWFS  to adult migration.Overall, a pattern of high, asymmetric connectivity across the Gulf of Mexico was supported by multiple lines of evidence, demonstrating Campeche Bank as a genetic source for a mixed population of Gag on the West Florida Shelf. Significant, yet small φ’neration ) that woST-values (~0.5), which are not presented in the observed data. Additionally, simulation of the same process with the number of generation approximating time since last glacial maxima (~1300 generations) also show larger FST-values than observed here . Thus, this “historical” population dynamic would appear to be dampened by some other homogenizing force (i.e. migration among sub-populations) and the CB population may have served as a refuge source for migrants during population expansion after range retractions.Estimates of time since expansion also suggest that asymmetric, on-going migration accounts for the continued low differentiation between populations. The timing  of population divergence of Gag populations predates the most recent glacial maximum  when sea-levels were 130 m lower than present day . This clGiven the distances among populations, the biological proclivities of the species, and the apparent barriers to migration, larval dispersal would appear to be the most parsimonious explanation for persistent connectivity among sub-populations. Adult dispersal from CB to WFS is highly unlikely given that this demersal fish, typically associated with depths of 10–100 m, would have to cross a body of water over 2800 m deep. The only plausible route for adult migration between CB to the WFS would be to circumnavigate the entire Gulf, remaining on the shelf edge throughout the migration. While there is evidence for similar migrations from the Western Atlantic to the northeastern Gulf , no suchet al [With regard to larval dispersal, Fitzhugh et al  describeet al ) and oceet al , 72) eviPhylogeography within the southeastern United States environments typically has focused on patterns of vicariance across the Florida Peninsula; however, this genetic “barrier” has proved largely ineffective in differentiating populations for a suite of regional marine species, leaving the actual spatial scale of many populations sometimes underappreciated. These regional patterns of genetic homogenization in other co-occurring reef fish such as red snapper and red grouper are attributed to either population expansion and retraction events , 32 or tBrachidontes exustus, across the Caribbean [Many studies in this region are a reflection of their spatial scale. A study by Lee and Foighil  that geoaribbean  providedaribbean  in phyloaribbean . While mWith Gag, ignorance of the populations on CB misleads our ideas on both historical and contemporary population genetic patterns. These considerations are not only important for our understanding of regional phylogeography, but for conservation and management. Gag is one of the most sought after fisheries species in the southeastern United States. In addition to dramatic environmental incidences, Gag face many anthropogenic stresses. For example, as a result of intensive fishing pressure, its demography has been seriously altered  andWide-spread marine species present difficult situations for ecologists and evolutionary biologists trying to explain patterns of migration given their often large effective population size, their natural variability in recruitment process, and their sometimes perturbed population status from human exploitation. Numerous studies have focused on describing patterns of differentiation in these species across a variety of spatial scales , 76, 85 S1 FigWhite region indicates typical sequence, while shaded areas represent indel regions that adhere to a step-wise mutational model. Grey highlights where there is a 9-base repeat indel; black highlights where there is a 40-base repeat indel. Primers were nested within neighboring coding genes for t-RNA protein (thin black lines at the end of the sequence).(PDF)Click here for additional data file.S1 FilePop1: South West Florida Shelf; Pop2: North West Florida Shelf; Pop3: Campeche Bank(TXT)Click here for additional data file.S2 File(FASTA)Click here for additional data file.S1 Tablen is allele richness of locus; FIS is inbreeding coefficient for sample; He is heterozygosity; n is the total number of alleles per locus. Symbols denote significant deviations from Hardy-Weinberg equilibrium (◊); heterozygote excess (*), and heterozygote deficiency (†).A(XLSX)Click here for additional data file.S2 Tablee). π is nucleotide diversity for All and Sequence Only data and average gene diversity for Indels. Significance for Tajima’s D tests and Fu’s Fs indicated by asterisks: * is p-value < 0.05; ** is p-value < 0.01; *** is p-value < 0.001.N is sample size. L is length of sequence. h is number of haplotypes. H is haplotype diversity. S is number of segregating sites. n is number of substitutions. Θ is Watterson’s (1975) estimate of the population parameter theta (= μN(XLSX)Click here for additional data file.S3 TableA less conservative Bonferroni correction of the p-value significance threshold  showed only two significant incidences of LD in the North West Florida Shelf population, one significant incident of LD between loci in the South West Florida Shelf population, and 4 significant incidences of LD between loci on Campeche Bank. After a Bonferroni correction considering all comparisons, no specific loci pair demonstrated significant LD in multiple populations.(XLSX)Click here for additional data file.S4 TableRegions are abbreviated as follows: Campeche Bank is CB; West Florida Shelf is WFS; South West Florida Shelf is SWFS; North West Florida Shelf is NWFS. Parameter estimates shown for each model indicate the different type of connections allowed between different populations. For example, the model describing Asymmetric Migration CB to WFS show only migration from CB to WFS allowed in this migration model. Mode, median, and 97.5% credible intervals shown for all parameters. Shade region of table indicates the model that was shown to be most supported by the data after Bayes Factor analyses (>>150—very strong support).(XLSX)Click here for additional data file.


Stenocereus thurberi, a xenogamous columnar cactus of northwestern Mexico and a good model to illustrate spatial dynamics of gene flow in long-lived species. Previous studies in this cactus showed differences among populations in the type and abundance of pollinators, and in the timing of flowering and fruiting. In this study we analyzed genetic variability and population differentiation among populations. We used three primers of ISSR to analyze within and among populations genetic variation from eight widely separated populations of S. thurberi in Sonora, Mexico. Sixty-six out of 99 of the ISSR bands (P = 66.7%) were polymorphic. Total heterozygosity for all populations sampled revealed high genetic diversity . The AMOVA showed that most of the genetic variation was within populations (80.5%). At the species level, estimates of population differentiation, θ = 0.175 and θB = 0.194, indicated moderate gene flow among populations. The absence of a significant correlation between genetic and geographic distances indicated little isolation by geographic distance. The large genetic variation and diversity found in S. thurberi is consistent with its open reproductive system and the high mobility of bats, a major pollinator. However, small changes in number or kind of pollinators and seed dispersal agents, in the directionality of migratory routes, and/or in the timing of flowering and fruiting among populations, can critically affect gene flow dynamics.Bats are the main pollinators and seed dispersers of  Genetic diversity and its spatial distribution is the result of mutation, genetic drift, gene flow and natural selection acting within and among populations of a species , 2. The Lophocereus schottii (Engelm.) Hunt, a columnar cactus of the Sonoran Desert, has been attributed to the limited dispersal abilities of its pollinator moth Upiga virescens  and 850 [(GT) 8YC] where R is equivalent to Adenine (A) or Guanine (G) and Y to Cytosine (C) or Thymine (T).A total of 20 random ISSR primers  were screened. The random amplified ISSR best products were tested again by adjusting PCR conditions including amount and concentration of Mg, dNTP's, primer and DNA, as well as the times and temperatures of alignment and extension. Three ISSR random primers were selected to search for genetic variation that were present in all studied populations, were not monomorphic, and showed a clear and reproducible pattern of bands (loci): 835 -1 and Var(x) = x(1-x)/N, where N is the number of individuals in the sample . Each run was performed using 25000 burn-in periods and 25000 MCMC repetitions after burn-in. We used a model allowing admixture with correlated allele frequencies without any prior information. We determined the most probable K value using the maximum value of ΔK according to Evanno et al. [Population structure for the total data set was further investigated with a Bayesian clustering analysis conducted in STRUCTURE ver. 2.3.2 ,66. In tc groups . The opto et al. .To assess genetic similarities between all pairs of populations, we estimated the linear function Fst/(1-Fst)  using thP < 0.05).From the amplifications generated with the three ISSR primers, we obtained 99 bands (“loci”): 36 with primer 835, 27 with primer 846 and 36 with primer 850. We found significant differences in allelic frequencies among populations for 88 of 99 loci examined . At the population level, the northern population of Sonoyta showed the maximum value of genetic variation , while the minimum was found in the southern population of Las Guásimas , nor for any correlation between values of expected heterozygosity of each population with its latitude, longitude or altitude (P>0.1). The highest correlation  was found between expected heterozygosity and latitude , with a general trend to increased heterozygosity at higher latitudes , and the lowest in the Las Guásimas population  that ranged from θ = 0.137–0.212 with a confidence level of 95%. The average value of θ for all loci was 0.175, indicating moderate genetic differentiation. The AMOVA revealed that most of the genetic variation was found within populations (80.49%), resulting in a value of ФST = 0.195, analogous to FST  and are within the 95% CrI  derived from STRUCTURE analysis was four, however, other groupings were less likely. The four groups suggested: 1) three groups with a predominantly SE-NW direction including in the southeast, Masiaca-Tayopa; in central Sonora, Las Guásimas-Magdalena; and in the northwest, Carbó-Sonoyta, and 2) one group in central Sonora linking the Sierra Madre foothills and the coast of the Gulf of California, Tecoripa-Bahía de Kino, overlapping the other three groups with a predominant E-W trend . A hieraStenocereus thurberi did not follow a pattern of isolation by distance .Genetic distances expressed as the linear regression Fst/(1-Fst)  between S. thurberi is not an exception . Our results are consistent with those of Hamrick et al. [et al. [S. thurberi, i.e. all are long-lived woody species with wide geographical distributions, high population densities, predominantly outcrossing mating systems, and animal dispersal of pollen and seeds over long distances. All these features have been associated with high levels of genetic diversity of vascular plants in general [Columnar cacti are characterized by relatively high levels of genetic variability, and k et al.  using is [et al.  assessed general ,72,73 an general ,17,22.S. thurberi populations, higher genetic variation in northern populations was surprising as these populations were more recently established (between 5.2 and 3.5 ka B. P.) than more southerly populations [In ulations . A possiS. thurberi, bats, birds and insects have been associated with the movement of pollen and/or seeds [S. thurberi populations show relatively higher genetic differentiation than most species of chiropterophilous cacti , and hu= 0.189; ), and arthurberi . Their ethurberi , and thethurberi  may explthurberi , and thethurberi . In contthurberi ). HawkmoL. yerbabuenae, is one of the main pollinators of S. thurberi [Melanerpes uropygialis) and house finches (Carpodacus mexicanus), is likely to represent a significant, albeit small, fraction of gene flow. However, other organisms are known to be involved in seed dispersal. For example, it has been documented that humans are likely responsible for long-distance dispersal of Pachycereus pringlei, and probably for other columnar cacti [S. thurberi through gene flow by seed dispersal. As in the case of bats, certain routes determined by water, food, and shelter availability could provide corridors for preferential gene flow that might obscure isolation-by-distance patterns [Moderate values of gene flow can be explained in part because the long nosed bat, thurberi ,37. Thisthurberi . It alsothurberi ,77, and ar cacti . Indigenpatterns ,79. BatsIn the absence of isolation by distance , moderatCeiba aesculifolia and Bombax palmeri. The complexity of this pattern was confirmed by Bustamante et al. [S. thurberi would be far more intricate than simple geographical distance. The results from STRUCTURE suggest there are links among populations along a S-N axis, as well as an E-W axis, suggesting 1) complex patterns of gene flow, most likely related to bat local and global migration, and 2) different groups of pollen and seed vectors that could overlap in time and space. In the first case, local and regional migration patterns depend on the availability of resources and adequate sites for giving birth and tending the young bats [Pachycereus pecten-aboriginum. During spring, some chiropterophilous species  bloom in the foothills of southern Sonora. Then, near the onset of summer, the northern species of columnar cacti initiate flowering in the desert plains. At a local level, migration becomes diffuse and complex because several species of bat pollinated cacti flower almost synchronically: first Pachycereus pringlei (cardón-sagüeso) in coastal Sonora and the Baja California peninsula, and Carnegiea gigantea (saguaro) in Sonora and Arizona, and later Stenocereus thurberi throughout Sonora and Baja California Sur. Results from STRUCTURE analyses hinted that there could be several groups of bats following corridors northwards, or coming from the Sierra Madre Occidental outposts towards the rich coastal forests of cardón, saguaro, and organ pipe cactus. The patterns from STRUCTURE are strongly supported by the genetic distance analysis (UPGMA and neighbour-joining) that show high correspondence in population groups. The migrating bats most likely go across the Gulf of California via the midriff islands as shown by Ramírez [As Cockrum  demonstre et al. , who shoung bats . The resung bats  that sho Ramírez  in her sS. thurberi are mainly the products of the activity of their pollinators and dispersers, as well as the complex history and particular ecological settings of each population. The life history traits of S. thurberi  can contribute to the maintenance of high levels of genetic diversity. These results support previous observations that columnar cacti have moderate levels of genetic variability.Levels of genetic variability and genetic structure of The movement of pollinators and dispersal agents highlight the role of gene flow as an evolutionary force . The lacS. thurberi are repositories of most of the species’ genetic variation. Therefore, we might be tempted to think that keeping a few populations should be sufficient to maintain the current genetic diversity. However, this approach does not consider the need to maintain pollination corridors that allow migration of bats, its main pollinators and dispersal agents. These corridors are complex and seem to depend on the local community dynamics. Even though S. thurberi has relatively high levels of genetic diversity, the persistence of this species depends on the activities of migratory organisms for their pollination and dispersal, and is threatened by deforestation and fragmentation of the landscape along its distribution range [Levels of genetic diversity suggest that populations of on range .Stenocereus thurberi is present in both sides of the Gulf of California. In this study, we only examined the populations in the continental distribution range. Future research needs to include peninsular and island populations to better understand bat migration patterns, and to elucidate the phylogeographic structure and origin of these disjunct populations which offer the chance to explore the contrast between dispersal and vicariance associated with the formation of the Gulf of California.S1 Dataset(XLS)Click here for additional data file.S1 FigAt each node is the value of bootstrap (based in 1000 replicates) that supports it.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.