Aedes aegypti. We analyzed mitochondrial and nuclear genomewide single nucleotide polymorphism markers generated via Restriction-site Associated DNA sequencing, as well as traditional microsatellite markers in Ae. aegypti from Rio. We found four divergent mitochondrial lineages and a strong spatial structuring of mitochondrial variation, in contrast to the overall nuclear homogeneity across Rio. Despite a low overall differentiation in the nuclear genome, we detected strong spatial structure for variation in over 20 genes that have a significantly altered expression in response to insecticides, xenobiotics, and pathogens, including the novel biocontrol agent Wolbachia. Our results indicate that high genetic diversity, spatially unconstrained admixing likely mediated by male dispersal, along with locally heterogeneous genetic variation that could affect insecticide resistance and mosquito vectorial capacity, set limits to the effectiveness of measures to control dengue fever in Rio.Dengue is the most prevalent global arboviral disease that affects over 300 million people every year. Brazil has the highest number of dengue cases in the world, with the most severe epidemics in the city of Rio de Janeiro (Rio). The effective control of dengue is critically dependent on the knowledge of population genetic structuring in the primary dengue vector, the mosquito  Aedes aegypti (Linnaeus 1762), that prefers to bite humans in densely populated areas and lay eggs in man-made water containers  revealed co-occurrence of two divergent lineages . Rio is considered a primary entry point for dengue viruses in Brazil from which they spread rapidly throughout the country  , as well as traditional microsatellite markers. Analyses of multiple marker systems allowed us to compare genetic diversity and structure with different spatio-temporal resolution, because different markers have distinct rates of evolution, levels of variability, and modes of inheritance  for SNP typing and the CTAB protocol . We used a customized double-digest RAD-seq method . One hundred picomolar P1 and 300 pm P2 Illumina adapters with customized barcode sequences were ligated to the genomic fragments using 100 units of T4 ligase at 16°C overnight (New England Biolabs). Following the sample pooling and purification, size selection of fragments 300–450 bp in length was completed with the Pippin Prep protocol . We used 12 PCR cycles with standard Illumina primers for the final library enrichment: 98°C for 30 s, 12 cycles of 98°C for 10 s, 60°C for 30 s, 72°C for 90 s, and the final elongation at 72°C for 5 min. The libraries were sequenced with HiSeq2000 using the 100-bp paired-end chemistry.Seventy six individuals collected in Tubiacanga, Urca, and Paquetá island during the wet season in 2011 were screened for nuclear and mitochondrial genomewide SNP variation (Tablehttp://hannonlab.cshl.edu/fastx_toolkit/index.html by Hannon Lab) to trim all raw FASTQ reads to the same length of 80 bp and retained those with a phred score ≥20 over the entire sequence length. High-quality reads were aligned to the Ae. aegypti reference nuclear genome AaegL1  for allele scoring. In total, 613 individuals were genotyped and used for subsequent analyses  , nucleotide diversity (mtπ), haplotype diversity (mtHd), and theta based on the number of segregating sites (mtθ) was calculated in r package pegas , nucleotide diversity (nπ), and theta (nθ) using the program stacks v.1.09  and allelic richness (NA) using the rarefaction method in r package gstudio (http://cran.rproject.org/web/packages/gstudio/index.html).The number of mitochondrial haplotypes  phylogenetic analysis using (i) the rapid bootstrap heuristic algorithm followed by a thorough ML search implemented in the program RAxML  as folded because information on ancestral polymorphisms is not available for Ae. aegypti. To generate the distribution of population parameters expected under drift-mutation equilibrium, we performed coalescent simulations using the programs msms  discriminant analysis of principal components (DAPC) implemented in the a-score as the criterion for determining the optimal number of PCs to be retained in a discriminant analysis. Strength of discrimination was measured using the reassignment of supplemental individuals into the clusters that were predefined with the subset of 10–15 individuals from each sampling location, where higher percentage of correct reassignment indicates stronger discrimination (i.e. higher structure). The optimal number of genetic clusters was calculated using the successive k-means procedure, where different clustering solutions were compared with the Bayesian information criterion (BIC). The lowest BIC value indicates the optimal number of genetic clusters . For the mitochondrial dataset, we calculated the genetic structuring parameter PhiST  for different effective population sizes and number of generations under isolation, while assuming the empirical number of samples, sample sizes, number of loci and alleles, and allele frequencies. Power to detect a given level of structuring and type I error were estimated using 1000 simulations.Due to a modest number of microsatellite loci (eight) and low sample sizes in the second and third sampling season that were available for this study Table, we asseAe. aegypti has abundant mitochondrial pseudogenes in the nuclear genome (Black and Bernhardt Because Stacks v.1.09 pipeline contained on average 6620 polymorphic RAD tags (SD = 2792) and 9369 SNPs (SD = 3924) per individual (File S3); 5123 RAD tags were present in ≥80% of individuals. After removing biallelic variants with the minor allele frequency lower than 0.05, we retained a subset of 1496 SNPs. For this subset, mean depth of coverage per site per individual was 8.3×. Overall FIS was 0.114 in the pooled dataset and theta (nθ) was 5.52, but these values varied among the three locations . Samples from Vietnam and Australia also had highly divergent co-occurring mitochondrial genomes, while those from Indonesia fell into one clade . The distribution of different mitochondrial haplotypes within the three localities in Rio is portrayed in the haplotype network analysis  for both nuclear SNPs and microsatellite datasets, as indicated by the lowest BIC value in the successive k-means procedure . Mosquitoes from Paquetá island did show greater genetic isolation and were more separated from mosquitoes in Tubiacanga and Urca based on their nuclear SNPs but not microsatellites  set in the analysis and . We also detected significant but weak isolation-by-distance between individuals across the city . However, after removing individuals from Paquetá island, no isolation-by-distance was evident .In contrast, nuclear variation exhibited a low level of spatial structuring and this was observed in both individual- and group-based analyses. In DAPC, the optimal number of genetic clusters was one  and GST for microsatellites was 0.008 (P = 0.002). Sample from Paquetá island showed the highest pairwise GST values, but only one of 105 pairwise comparisons in the entire 2011 microsatellite dataset remained statistically significant after Bonferroni correction (Table S3). Power analysis indicated that our microsatellite marker set had an acceptable type I error rate (а = 0.051) and a 100% power to detect GST ≥ 0.008 based on sample sizes from our 2011 collection. Sample sizes of the 2012 and 2013 collections . In the 2011 dataset, GST estimates (P ≪ 0.001) that ranged between 0.065 and 0.261 (TableWolbachia (wMel and wMelPop), as well as after exposure to insecticides and xenobiotics  had highly significant 0/1496 haAe. aegypti from Rio de Janeiro as revealed by multiple marker systems: RAD-seq generated SNPs in the mitochondrial and nuclear genomes, and microsatellites. We found several divergent mitochondrial lineages and strong spatial structure for mitochondrial variation, in contrast to the overall homogeneity in nuclear markers across Rio. Despite a low overall differentiation for the nuclear markers, we detected strong spatial structuring for variation in over 20 genes that have a significantly altered expression under the exposure to insecticides, xenobiotics, and pathogens, including the novel biocontrol agent Wolbachia.We report novel insights into the complex pattern of genetic diversity and spatial genetic structuring in GST comparisons all indicated very weak spatial structuring of nuclear variation despite the highly heterogeneous landscape of the Rio de Janeiro city . One exception was the geographically isolated Paquetá Island  influence the population dynamics of mitochondria  and parameters of demographic change  for the mitochondrial genome but not for the nuclear genome  is much greater than four if dispersal is sex-biased such that males show higher dispersal propensity, and much smaller than four if females are the dispersing sex , suggesting that Ae. aegypti males in Rio may have higher dispersal than females.Ae. aegypti has not been detected in mark–release–recapture (MRR) studies conducted in Rio or elsewhere  parameters. Perhaps Ae. aegypti females that disperse far have a lower reproductive output than females that remain local, while this is not the case in males. Some evidence in support of this hypothesis comes from the MRR experiments that recorded lower daily survival of females in parts of Rio where they showed higher dispersal propensity  and microsatellite markers. These studies pointed to two divergent mitochondrial clades . This suggests that the large ‘gaps’ between clades found in Rio are unlikely to represent missing haplotypes due to insufficient sampling.Human-assisted introductions are another mechanism contributing to mito-nuclear discordance in animals . In a long-term survey of Ae. aegypti abundance in Rio, there was no major decrease in mosquito numbers , suggesting that bottlenecks are not strong. Furthermore, a dramatic decline in effective population size was not detected in our microsatellite bottleneck tests (Table S4). The pattern of genomewide SNP diversity observed in Ae. aegypti from Rio therefore appears most consistent with complex re-introductions combined with high subsequent gene flow.We also found an overall deficit of rare SNPs across the nuclear genome of e Tajima . A stronAe. aegypti across Rio, we detected local genetic structure for variation in 25 genes with a putative role in the mosquito immune response and insecticide resistance , have been replacing organophosphates in Rio de Janeiro states since 2001  in Ae. aegypti from different parts of Rio (Vega-Rúa et al. Ae. aegypti's vectorial capacity for dengue viruses in Rio may be worthwhile.We also found spatial heterogeneity for variation in genes showing differential expression under the infection with bacteria and dengue viruses, or after a blood meal Table, and theWolbachia-infected Ae. aegypti for population replacement or suppression (Hoffmann et al. Wolbachia infection outside the release zone may be restricted because emigrant individuals are more likely to be males that do not transmit this maternally inherited endosymbiont. However, with male-biased dispersal, the release of Wolbachia-infected males for population suppression may be worth considering (Hancock et al. Wolbachia infection (TableOur study also provides useful information for the implementation of novel biocontrol strategies like those that use ion Table, it woulAe. aegypti in Rio de Janeiro, reflecting underlying processes that limit the effectiveness of local measures to control the mosquito populations. These factors need to be considered in future Wolbachia releases, and they contrast with patterns found in other parts of the world. The data we have collected also point to some intriguing patterns of differentiation in genes that may influence the local success of release programs.In conclusion, using multiple marker systems we uncovered a complex genetic structure of


Cicer species (94 genotypes) from the primary, secondary and tertiary gene pool, we analysed 5,257 DArT markers and 651 KASPar SNP markers. Based on successful allele calling in the tertiary gene pool, 2,763 DArT and 624 SNP markers that are polymorphic between genotypes from the gene pools were analyzed further. STRUCTURE analyses were consistent with 3 cultivated populations, representing kabuli, desi and pea-shaped seed types, with substantial admixture among these groups, while two wild populations were observed using DArT markers. AMOVA was used to partition variance among hierarchical sets of landraces and wild species at both the geographical and species level, with 61% of the variation found between species, and 39% within species. Molecular variance among the wild species was high (39%) compared to the variation present in cultivated material (10%). Observed heterozygosity was higher in wild species than the cultivated species for each linkage group. Our results support the Fertile Crescent both as the center of domestication and diversification of chickpea. The collection used in the present study covers all the three regions of historical chickpea cultivation, with the highest diversity in the Fertile Crescent region. Shared alleles between different gene pools suggest the possibility of gene flow among these species or incomplete lineage sorting and could indicate complicated patterns of divergence and fusion of wild chickpea taxa in the past.To estimate genetic diversity within and between 10 interfertile  Cicer arietinum). During the past few decades, our understanding of the importance of plant genetic resources and the need to conserve them has grown Many crops that are grown across multiple regions have limited genetic diversity due to bottlenecks from domestication, selective breeding and in some taxa, natural processes In order to make more efficient use of wild relatives, we need improved classifications of their relationship to crop material and to other wild species Phaseolus) Ascochyta blight and Fusarium wilt, pod borer insects, and tolerance to abiotic stresses like terminal drought, high and low temperatures C. reticulatum, and its interfertile sister species C. echinospermum, is the main source of new variation, although introgression is possible from the more distantly related gene pools with greater effort Chickpea is an important crop in semi-arid tropical regions such as South Asia and Eastern & Southern Africa, Mediterranean regions, and cool temperate areas C. reticulatum and C. echinospermum) of chickpea are restricted to southeastern Turkey C. reticulatum and C. echinospermum) that have a narrow geographic distribution compared to other crops domesticated in the Fertile Crescent. The shift in phenology may have accompanied the introduction of other crops such as sesame and sorghum that are summer annuals Cultivated chickpea first appears in the archaeological record some 6.6–7.2 thousand years ago in Syria KBioscience Competitive Allele-Specific Polymerase chain reaction (KASPar) assays, and GoldenGate assays from Illumina Inc. Single nucleotide polymorphism (SNP) markers have become the markers of choice for various genome wide analyses because they are widespread across genomes, accurate and reproducible, and well suited to automated detection The present study is focused on the assessment of relationships in a diversity panel of chickpea which includes breeding material from the three seed types  and wild species from the primary, secondary, and tertiary gene pools using KASPar technology and hybridization based DArT arrays for high-throughput SNP genotyping. We examined the level of genetic differentiation among these groups of genotypes and assessed how segregating variation is spread across the genome of chickpea.A diverse set of 94 chickpea genotypes  includinTotal genomic DNA was isolated from 10–12 leaves of two week old plants following a modified CTAB protocol as described in Cuc et al. SNPs were identified using four different approaches: Solexa/Illumina sequencing, mining of Sanger Expressed Sequence Tags (ESTs), allele-specific sequencing of candidate genes, and allele-specific sequencing of tentative orthologous genes (TOGs) as described by Hiremath et al. The germplasm was divided into three different clusters based on geographical origin, namely the Fertile Crescent, Central and South Asia, and Ethiopian Highlands . Additiovs cultivated with the DArT markers and seed type with the SNP markers) was calculated. The polymorphism information content (PIC) values for SNP and DArT markers across 94 diverse genotypes were calculated by using PowerMarker software A separate AMOVA was performed on the SNP data to assess variation within and among desi, kabuli, and pea-shaped seed types. In both AMOVAs, we assessed genetic variation within groups (Fct), within populations (Fst), between populations within a group (Fsc), population polymorphism, and Nei’s genetic distance and gene flow (Nm) using GenAlEx v.6.41 STRUCTURE 2.3 http://www.geneious.com). A cladogram was produced using unweighted pair-group method with arithmetic mean (UPGMA) cluster analysis under the Jukes-Cantor genetic distance model with 100 bootstrap replications. The consensus tree was then rooted with the clade of individuals from the tertiary gene pool.A complementary approach to assessing relationships among taxa is a phylogenetic analysis. Distance-based phylogenetic analysis of SNP data was performed using the software package Geneious v. 7.0.6 (Biomatters) . DArT data was used to understand the diversity and genetic architecture of the germplasm. As expected, wild species genotypes had higher levels of polymorphic markers (99.60%) compared to cultivated genotypes (35.79%)  and cultivated species ((35.79%) . A UPGMA(35.79%) . Two maj(35.79%) . HoweverC. microphyllum, appears admixed with the primary gene pool. However, this could be due to its closer phylogenetic relationship to C. reticulatum or accidental gene flow in the germplasm collection. The secondary gene pool, with the closely related and interfertile species of C. pinnatifidum, C. bijugum and C. judaicum formed one tight cluster. The immediate ancestors of the crop, C. reticulatum and C. echinospermum, show up as a group with substantial admixture with the cultivated individuals. This could represent the derivation of the crop, and could also represent introgression from the crop to the wild species (or artefacts of maintenance in germplasm facilities). The cultivated accessions of C. arietinum showed little admixture with the wild material in this analysis.In parallel, STRUCTURE was also used to understand the clustering between cultivated and wild species genotypes. With the DArT data, STRUCTURE resolved four clusters using the Evanno method . This grC. reticulatum, the likely progenitor of cultivated chickpea  was calculated based on Nei’s genetic distance. As expected, higher similarity was observed between the primary and secondary gene pools (Nei’s genetic distance 0.15), while greater distance was observed between primary and tertiary gene pools (Nei’s genetic distance 0.69). Furthermore, a greater distance was observed between the secondary and tertiary gene pools than between the primary and secondary gene pools, which suggests that genotypes from the primary and secondary gene pools are more closely related to each other than to the tertiary gene pool. Across all wild material, numbers of effective alleles and values of heterozygosity were much higher than in the crop material. Within the wild material, the secondary gene pool had the greatest diversity, with highest effective allele estimates and highest heterozygosity  were observed, with most individuals demonstrating substantial admixture  provides flexibility in use and have been proven successful for molecular breeding applications involving only few markers for genotyping a large number of segregating lines Cicer material where it lacks the information needed to separate patterns of relationships and complemented our analysis with the inclusion of independent DArT data that lacks such bias. In particular, focusing our analysis of the wild material on the DArT data should avoid the skew that SNP data can introduce.Understanding the available genetic diversity in the germplasm collection is a pre-requisite to adopt effective conservation and management strategies to use these genetic resources in crop improvement. Understanding patterns of genetic diversity can complement efforts to match collections from differing climatic regions to planting zones differing in climate C. reticulatum, the immediate progenitor of cultivated chickpea, but genotypes of this species were less diverse than other Cicer species. Our results will allow the most genetically distinct of the existing accessions of these species to be used in breeding to maximize the diversity introgression into cultivated forms. However, as international germplasm collections contain only 18 unique C. reticulatum accessions C. reticulatum, particularly beyond the Mardin region of southeastern Anatolia where most existing collections were made, would be greatly beneficial. Relatively higher levels of genetic variation were present in the wild species of the secondary and tertiary gene pools, which span a far greater ecological range than C. reticulatum, which is restricted to oak savannas and disturbed pastures in southeastern Anatolia. However, the levels of genetic variation were still not all that high, consistent with the high probabilities on the assignment tests and the primarily selfing reproductive system of most Cicer species. Traits of wild species that are beneficial in a Mediterranean climate, such as vernalization, can hinder efforts to breed chickpea for cultivation in subtropical climates. Therefore, wild species from different regions, such as the African highlands or Central Asia could provide climatically adaptive traits for chickpea production in non-Mediterranean climates. For instance, species from outside the Fertile Crescent, such as C. cuneatum from Ethiopia and C. microphyllum from Central Asia (Pakistan and Afghanistan) could be exploited as sources of adaptive variation for those regions. Furthermore, wild species from more arid environments, such as C. judaicum and C. pinnatifidum, could be useful in expanding the resistance of cultivated chickpea to important biotic stresses like Ascochyta, Helicoverpa, Fusarium and Botrytis Gray Mold In many crops that are deficient in genetic variation, wild relatives remain a critical resource. As is the case in other crops C. reticulatum and C. echinospermum, which have seed and flower colours similar to desi seed types.Based on seed type, chickpea has been subdivided in to three groups: desi, kabuli and pea-shaped. Significant differentiation among desi and kabuli seed type cultivars was observed, although far less than exists between wild species. The distinction could be due to a relatively recent evolution of kabuli seed type from a desi seed type ancestor that closely resembled the wild species, as previously speculated Cicer species spanning ecologically meaningful gradients in abiotic or biotic factors such as moisture, soil fertility or pathogen distribution would be extremely useful. Analysis of variation across these gradients in wild relatives could show how natural selection has adapted populations of wild relatives to these localized conditions, giving us natural targets for breeding.Germplasm collections contain relatively low numbers of wild relatives of crops Figure S1a. Principal coordinates analysis of wild species of chickpea based on primary, secondary and tertiary gene pool. b. Population structure analysis across wild chickpea accessions to understand the distribution of primary, secondary and tertiary gene pool species.(TIF)Click here for additional data file.Figure S2a. Population structure analysis across cultivated chickpea accessions based on seed type. b. Analysis of molecular variance within and among cultivated population based on seed type.(TIF)Click here for additional data file.Table S1Details about the Cicer accessions used in the study.(XLS)Click here for additional data file.Table S2Summary of the genotyping data generated using 651 CKAM markers on 94 Cicer accessions.(XLS)Click here for additional data file.Table S3Summary of the genotyping data generated using DArT markers.(XLS)Click here for additional data file.


Numerous studies assess the correlation between genetic and species diversities, but the processes underlying the observed patterns have only received limited attention. For instance, varying levels of habitat disturbance across a region may locally reduce both diversities due to extinctions, and increased genetic drift during population bottlenecks and founder events. We investigated the regional distribution of genetic and species diversities of a coastal sand dune plant community along 240 kilometers of coastline with the aim to test for a correlation between the two diversity levels. We further quantify and tease apart the respective contributions of natural and anthropogenic disturbance factors to the observed patterns. We detected significant positive correlation between both variables. We further revealed a negative impact of urbanization: Sites with a high amount of recreational infrastructure within 10 km coastline had significantly lowered genetic and species diversities. On the other hand, a measure of natural habitat disturbance had no effect. This study shows that parallel variation of genetic and species diversities across a region can be traced back to human landscape alteration, provides arguments for a more resolute dune protection, and may help to design priority conservation areas. The analogy between the processes determining genetic diversity (GD) within species and species diversity (SD) within communities has long been recognized . By promoting founder effects and driving local resampling of alleles and species, habitat disturbance decreases both genetic and community diversity (panel B) and ultimately creates SGDCs (panel C). This mechanism, coupled with migration among patches, promotes SD–GD correlations in various phylogeographic contexts, provided that there is sufficient time to allow the system to reach a migration–drift equilibrium. In our example simulation, it takes only 200 generations to wipe out any initial phylogeographic background and generate a consistent SGDC pattern (panel C). These results are robust to interspecies variations in key life‐history traits such as sensitivity to disturbance events, mating systems, migration abilities, and effective population sizes. The interested readers are referred to the recent works of Laroche et al.  for a coMetapopulation model simulating how habitat disturbance jointly impacts genetic and community diversity. We consider an 11 × 11 landscape of interconnected patches . This disturbed landscape is then used to simulate the evolution of 100 independent species for 500 generations until the system reaches a migration–drift equilibrium and the initial conditions have no further effect. Diversity statistics represented as dots of varying diameter are collected in each patch over time by measuring (i) the average genetic diversity  and (ii) the number of species occupying each patch . The collected diversity estimates are then related to local extinction probabilities, and their pairwise correlation is tracked through generations. B Diversity estimates related to local extinction probabilities, as observed when the system is at equilibrium (500 generation). C Correlation between genetic and community diversity (SD–GD correlation as a function of time). The median straight line and 75 % and 95 % confidence interval envelopes are displayed. These results are robust to interspecies variations in life‐history traits . B and C are based on 100 replicates. Migration events are allowed only among adjacent patches. Extinction probabilities are constant through time. All simulations were performed using QuantiNemo  a detailed ecological survey of sand dune habitats to assess species diversity, (ii) a genetic analysis of seven representative plant species, and (iii) a detailed ecological survey to assess the drivers of SGDCs . These three datasets were initially collected at distinct spatial resolutions and were all averaged over the same 5‐km‐resolution grid prior to statistical analysis.2 each) arranged along 94 geo‐referenced transects  that spanned the beach inland gradient. Plant species composition and a comprehensive set of habitat characteristics  were recorded within each plot, allowing a detailed characterization of the community diversity at each surveyed site.The study area was surveyed during June 2003 by the French National Forest Office (ONF) over 773 circular plots  unspecific to the sand dune plant community Favennec  were excH) to reflect regional variations in natural disturbance.Natural disturbance was quantified using a principal component analysis computed at the ONF sampling plot scale and based on eight representative environmental descriptors : (i) dune facies  and two widespread species (Cakile maritima – Brassicaceae and Eryngium maritimum – Apiaceae)  to be used in further analyses.Regional genetic diversity was assessed using a ‘moving window’ approach . It is highly variable along the coastline, ranging from 29.01 to 3278.75 hectares (Table S3). As above, St was averaged over the same 5‐km‐resolution grid.Anthropogenic disturbance was estimated from publicly available data  describing the amount (in hectares) of urbanized area within 10 km of the coastline in our study region (Table S3). This descriptor is very highly correlated with the resident population census, the number of houses, and tourist accommodation capacity (Table S3) and was used here as a surrogate of anthropogenic habitat disturbance .S, E, Sh, R) against the latitudinal coordinates of each grid cell and (ii) extracting residuals for measuring pairwise correlations among diversity estimates. Significance levels were then evaluated using 50 000 randomized permutations. The procedure was performed using custom R scripts (available upon request).The association between SD and GD was assessed using pairwise Pearson's correlations. First, we corrected diversity indexes for spatial autocorrelation, to improve the statistical independence of our 19 data points and enhance the accuracy of our statistical tests, by (i) regressing each variable  accounts for local variations in species and genetic diversity  while removing the effects of spatial autocorrelation by considering the latitudinal coordinates of each grid cell as a covariate. The analysis was performed on standardized data, and significance levels were assessed using 50 000 random permutations.The respective effects of natural and anthropogenic disturbance on diversity levels were assessed using a correlation decomposition procedure . Within all seven species, GD estimated by the Shannon information content and the rarity index varied markedly among grid cells , with estimates of S, E, Sh, and R being significantly correlated with each other  was homogeneous throughout the study area, when averaged at the regional scale. In contrast, a clear hotspot of anthropogenic disturbance (St) was detected in the upper half of the study area and corresponded to grid cells with decreased GD–SD levels. Accordingly, the correlation decomposition analysis revealed that habitat disturbance accounted for 33–64% of the quantified SGDCs  accounted for 34% of the variance shaping the joint GD–SD datasets (Table St) accounted alone for 21% of the variance (Table H) and its interaction with anthropogenic disturbance (St × H) accounted, respectively, for 5% and 8% of variance  that reduces available dune habitats  and fragments the formerly continuous sand belt, and second, via habitat degradation around developed areas through trampling, littering, and eutrophication. Specifically, habitat destruction and degradation may reduce SD due to local extirpations of species and may reduce GD through increased genetic drift during population bottlenecks and founder events during recolonization. Additionally, within a fragmented and extremely narrow landscape such as a sandy coast, migration among habitat patches may be exacerbated, especially for plants that do not disperse via water currents, which may delay the restoration of GD and SD.Studies of SGDC patterns in habitats disturbed by humans have yielded contrasting results. For instance, Wei and Jiang  did not The human impact on GD and SD is most pronounced in the center of the study region (between 44.2° and 44.8° north). Municipalities with the largest tourist accommodation capacities, resident population sizes, and amount of urbanized coastal landscape are located in this area . Favennec  and ForeAlyssum loiseleurii, Astragalus baionensis, and Hieracium eriophorum during the 19th century until the first half of the 20th century, when increased waterside development started (e.g., Loiseleur–Deslongchamps Habitat disturbance may have particularly affected species endemic to the French Atlantic coast. Historical data suggest a larger and a more continuous distribution of endemics such as In this study, we show that GD and SD within a coastal sand dune plant community can covary at the regional scale, and this pattern is at least in part driven by varying levels of human landscape alteration. Our study nevertheless suggests that evaluating additional drivers of the landscape diversity, notably those affecting the metapopulation and community dynamics (e.g., local connectivity, Lamy et al. Table S1. Species included in the genetic diversity survey.Table S2. AFLP datasets.Table S3. Proxy data for human disturbance of the coastal sand dunes.Table S4. Correlation decomposition, including non‐native and weedy species.Table S5. RDA analysis, including non‐native and weedy species.Figure S1. Principal Component Analysis of vegetation plots.Figure S2. Genetic diversity estimated by the Shannon index and rarity index along the coastal gradient.Data S1. R script implementing the correlation decomposition analysis.Click here for additional data file.


Sclerotinia sclerotiorum is an important pathogen of numerous crops in the North Central region of the United States. The objective of this study was to examine the genetic diversity of 145 isolates of the pathogen from multiple hosts in the region. Mycelial compatibility groups (MCG) and microsatellite haplotypes were determined and analyzed for standard estimates of population genetic diversity and the importance of host and distance for genetic variation was examined. MCG tests indicated there were 49 different MCGs in the population and 52 unique microsatellite haplotypes were identified. There was an association between MCG and haplotype such that isolates belonging to the same MCG either shared identical haplotypes or differed at no more than 2 of the 12 polymorphic loci. For the majority of isolates, there was a one-to-one correspondence between MCG and haplotype. Eleven MCGs shared haplotypes. A single haplotype was found to be prevalent throughout the region. The majority of genetic variation in the isolate collection was found within rather than among host crops, suggesting little genetic divergence of S. sclerotiorum among hosts. There was only weak evidence of isolation by distance. Pairwise population comparisons among isolates from canola, dry bean, soybean and sunflower suggested that gene flow between host-populations is more common for some crops than others. Analysis of linkage disequilibrium in the isolates from the four major crops indicated primarily clonal reproduction, but also evidence of genetic recombination for isolates from canola and sunflower. Accordingly, genetic diversity was highest for populations from canola and sunflower. Distribution of microsatellite haplotypes across the study region strongly suggest that specific haplotypes of S. sclerotiorum are often found on multiple crops, movement of individual haplotypes among crops is common and host identity is not a barrier to gene flow for S. sclerotiorum in the north central United States. Sclerotinia sclerotiorum (Lib.) de Bary has been the focus of research since it was first described over a hundred years ago in part because this fungus is capable of infecting many different crops ). Each PCR was conducted in a volume of 20 μl with 1× PCR buffer, 2 mM MgCl2, 0.2 mM dNTPs, 0.025 μM forward primer, 0.25 μM reverse primer, 0.25 μM universal M13 primer 5’-CAGTCGGGCGTCATCA-3’ labeled with PET, VIC, or 6FAM fluorophores , 1 U Platinum® Taq DNA polymerase , and 40 ng genomic DNA. A single fluorophore was assigned to each locus to avoid errors in allele size estimate caused by differences between fluorophores. Hot start touchdown PCR was performed on an Eppendorf Mastercycler  for 36 cycles . Lengths of PCR products were determined by capillary gel electrophoresis on a 3730 DNA analyzer  at the Plant Microbe Genomics Facility, Ohio State University. Genemarker 4.0  was used to assign alleles by the Plant Microbe Genomics Facility. PCR products that differed by ≤ 1 bp were scored as identical in length. Lengths of the PCR products were determined by the Plant Microbe Genomics Facility and verified by the authors through direct examination of the output from the DNA analyzer.Twelve microsatellite primer pairs  developeS. sclerotiorum from each of four hosts  [Rst values between samples on the four hosts to examine differentiation between S. sclerotiorum populations from different hosts. Arlequin was also used to conduct an analysis of molecular variance (AMOVA) in order to partition the degree of genetic variability into among- and within-population components, in which a population of S. sclerotiorum was considered to be all the isolates from a given crop. Isolates from the remaining hosts were not included in the analysis, because there were insufficient isolates (1–2 per host species).Standard estimates of population genetic diversity were calculated with allelic frequencies per locus per host population using the software Arlequin v. 3.1 and Genodive v. 2.0 , 23, 24.nflower) . BecauseA) across loci for each of the populations. The index of association developed by Brown, Feldman and Nevo [d which accounts for the number of loci and is thus less biased. Both of these indices give an indication of the extent to which populations of haploid fungi reproduce clonally which leads to linkages among alleles at different loci rather than recombination. The indices were calculated for the full data set and for a clonally-corrected data set in which clonal genotypes were removed if they were exact repeats within the population. We implemented the analysis using the R package “poppr” developed by Kamvar, Tabima and Grunwald [In order to assess the presence or absence of linkage disequilibrium in the four host populations we calculated an index of association  included only one isolate .There was little evidence for genetic isolation of st crops . Ninety-vely low . Howevervely low  indicateS. sclerotiorum, but most have reported data about the pathogen collected from only one or two crops [S. sclerotiorum across multiple crops over a large geographic area. Studies of this nature have been conducted recently in the U.S., U.K., Iran, Brazil and India [S. sclerotiorum was conducted by Clarkson et al. [S. sclerotiorum had multiclonal populations in the UK. One microsatellite haplotype was widely distributed across hosts and areas.Numerous studies have examined genetic diversity of wo crops , 33, 34.nd India , 35, 36.n et al.  in the US. sclerotiorum examined 178 isolates from seven hosts from eight states in the eastern half of the U. S. They found 34 haplotypes in that population and multiple haplotypes were recovered from some crops. Attanayake et al. [Studies on genetic diversity in the U.S. have focused on diversity of the pathogen on individual crops , 37, 38 e et al.  examinedS. sclerotiorum in the U.S. have used a variety of methods to characterize diversity, therefore comparing results between different studies, especially for haplotypes, to obtain a more complete overview of the population structure in the U.S. is rarely possible. This is especially true if one wishes to know the geographic distribution of haplotypes and which are most dominant in the population. For example, Cubeta et al. [Past studies on genetic diversity of a et al.  used soua et al.  used thea et al.  used thea et al.  and Attaa et al.  on the oa et al.  to charaS. sclerotiorum at global scales, since various methods of characterizing haplotypes have been implemented [It is also difficult to compare genetic variability of lemented , 32, 36.lemented , 33, 35.lemented , 14. BecS. sclerotiorum are found on multiple crops, movement of individual haplotypes among crops occurs and that host identity is not a barrier to gene flow for this pathogen [S. sclerotiorum across more than one crop [The patterns of microsatellite marker allele frequencies within our study population strongly suggest that specific haplotypes of pathogen . There wone crop , 18 .S. sclerotiorum from the North Central region, especially for isolates from soybean and dry bean. However, when the isolates from canola and sunflower were analyzed using a correction for clonality, there was evidence of genetic recombination within the isolates from these crops. The reasons for the differences among isolates from these host crops are not clearly understood. The extent of genetic recombination within isolates from the North Central region is being examined in greater detail in a companion study by sequencing part of the genome and analyzing allele distribution [The analysis of linkage disequilibrium indicated a strong prevalence of clonal reproduction in the population of ribution .S. sclerotiorum did vary across hosts. Nei’s index of genetic diversity was highest for isolates from canola and sunflower and lowest for those from soybean. We expected to observe the greatest diversity in soybean, since isolates from this crop were obtained throughout the North Central region while canola and sunflower are primarily grown in North Dakota and northern Minnesota and more isolates were obtained from soybean than other crops. However, isolates from soybean had the lowest relative measures of genetic diversity Click here for additional data file.


N = 298) obtained after the population recovery in the mid-1990s, were used as a reference.Many western European carnivore populations became almost or completely eradicated during the last ~200 years, but are now recovering. Extirpation of wolves started in Finland in the 19th century, and for more than 150 years the population size of wolves has remained small. To investigate historical patterns of genetic variation, we extracted DNA from 114 wolf samples collected in zoological museums over the last ~150 years. Fifteen microsatellite loci were used to look at genotypic variation in this historical sample. Additionally, we amplified a 430 bp sequence of mtDNA control region from the same samples. Contemporary wolf samples  suggesting population fragmentation. Evidence of a genetic population bottleneck was also detected.Our analyses of mtDNA revealed reduced variation in the mtDNA control region through the loss of historical haplotypes observed prior to wolf declines. Heterozygosity at autosomal microsatellite loci did not decrease significantly. However, almost 20% of microsatellite alleles were unique to wolves collected before the 1960s. The genetic composition of the population changed gradually with the largest changes occurring prior to 1920. Half of the oldest historical samples formed a distinguishable genetic cluster not detected in the modern-day Finnish or Russian samples, and might therefore represent northern genetic variation lost from today’s gene pool. Point estimates of Our genetic analyses confirm changes in the genetic composition of the Finnish wolf population through time, despite the geographic interconnectivity to a much larger population in Russia. Our results emphasize the need for restoration of the historical connectivity between the present wolf populations to secure long-term viability. This might be challenging, however, because the management policies between Western and Eastern Europe often differ greatly. Additionally, wolf conservation is still a rather controversial issue, and anthropogenic pressure towards wolves remains strong. Ne). Increase of inbreeding in small populations can ultimately lead to lower evolutionary potential and elevated extinction risk [The direct and indirect influences of human activities has caused drastic changes in the genetic composition of many wild populations. Decline and fragmentation of formerly continuous populations into isolated local populations raise several genetic concerns, such as the loss of genetic variation and its associated effects on local effective population sizes . Consion risk .Canis lupus) is one of the most controversial animals, and has been an object of intense eradication campaigns throughout Western Europe [The grey wolf  associated with population decline.In the present study, we used DNA extracted from wolf samples obtained from zoological museums to examine historical patterns of genetic variability and structure in the Finnish wolf population, which experienced a dramatic population decline over a ~150 year period. We were further interested to see the possible stabilizing effect of gene flow from the neighbouring, large eastern population, i.e. could gene flow from Russian population have been large enough to prevent negative consequences  and error rates  indicatA total of 23 nucleotide positions were found to be polymorphic within the amplified 431 bp long mtDNA sequences yielding eight distinct haplotypes  was large (0.329–0.514) and highly significant (P < 0.001) between the first (before 1920) and all other temporal groups (Table N = 6), in which four individuals carried the haplotype OW63 and other two had unique haplotypes (OW17 and OW36). The large difference between the first and other groups was mostly due to the shift between the two dominating haplotypes; in the first group 12 of the 18 individuals (66.6%) had the OW40 haplotype and only one OW63 (5.6%), whereas among wolves collected after 1960 abundances were reversed. In 1960–1979 ten individuals of 29 (34.5%) had haplotype OW40 and 17 (56.6%) OW63, and in 1980–1993 the proportions (respectively) were 4/28 (14.3%) and 21/28 (75.0%).Mitochondrial diversity measured as number of haplotypes and number of polymorphic sites was highest Table  at the blarge 0.39–0.514 aD P = 0.0013 and for Fu’s FSP = 0.011), whereas for the group collected in 1980–1993, Fu’s test value FS was significant (P = 0.006), but Tajima’s D showed a decreasing trend (P = 0.059).Neutrality tests suggested significant demographic changes in the wolf population at the end of the historical sampling period Table . The twoThe overall dataset including our 81 historical samples consisted of 497 sequences with the mtDNA sequence length of 287 bp. In total, 21 different haplotypes among European wolves were detected , whereas the historical temporal groups 1920–1959, 1960–1979, and the modern reference sample (1995–2009) were in HW-equilibrium. None of the 15 loci showed a constant pattern of deviation (indicating e.g. amplification errors). Significant linkage disequilibrium (P < 0.001) between loci was detected in 7 of the 105 pairwise comparisons in samples collected prior to 1920, 2/105 in 1920–1959, 2/105 in 1960–1979, 3/105 in 1980–1993 and 1/105 in 1995–2009.The oldest (prior to 1920) and the latest (1980–1993) temporal groups deviated significantly from HW-equilibrium with several loci showing heterozygosity deficiency . Allelic richness estimates were also rather similar throughout the study period, whereas private allelic richness was clearly higher in samples collected prior to 1960  of samples collected before and after 1960 using the randomization test, no notable differences between the groups were found except for a slightly higher  allelic richness in the older group (3.947 vs 3.655).We found no significant differences in the amount of expected or observed heterozygosity among the temporal groups, and there was no evidence of inbreeding (Table N = 298), whereas only four (3.7%) alleles were unique to the present wolf population. Of these 21 historical alleles, nine (42.9%) were only found from samples prior to 1960 (N = 18) and four (19.0%) from samples collected in 1960–1993 (N = 40). Because the sampling of present-day wolf population is rather comprehensive , it is FST = 0.022–0.096; Table FST) between the temporal groups were significantly correlated with the elapsed time .The genetic composition of the Finnish wolf population clearly changed over time. Genetic differentiation between the temporal groups was small or moderate  than any of the estimates between the oldest and other temporal Finnish groups  and the oldest temporal group of the Finnish wolves (prior to 1920) was significant, but smaller , which was too small for reliable testing (N = 6). Even though alleles frequency distribution was L-shaped in all groups, the proportion of rare alleles (frequency ≤ 0.1) was lower in the first two temporal groups  than in following samples (F = 0.390/0.386/0.472), and as a consequence, the distribution more shallow.Bottleneck tests based on the heterozygosity excess method did not indicate severe preceding bottlenecks in any of the temporal groups or in the modern-day reference sample. L-shaped allelic frequency distribution typical to non-bottlenecked populations , the occurrence of a genetic bottleneck in the first temporal sample was supported. Under the evolutionary scenarios investigated, bottlenecks for other temporal groups are supported only if the mutation model follows a strict step-wise mutation model (SMM) or the proportion of larger than single-step mutations is at most ~10%.Ne estimates with single-sample methods for the wolves prior to 1920 were very small: LD-Ne = 20.5 (13.5–35.2) and 13.2 (10.8–19.6) with ONeSAMP method. ONeSAMP approach provided consistently lower Ne estimates compared to the method based on linkage disequilibrium for other temporal groups as well  suggested a Genetic analyses of DNA extracted from museum specimens allowed us to directly assess the patterns of genetic variation and structure in the historical Finnish wolf population. Demographic changes due to recent anthropogenic perturbations of wild population are often so large, that the use of present-day data solely to reconstruct the population history could be misleading ,23. ConsLoss of genetic diversity is assumed in conjunction with strong population size decline if gene flow is insufficient to prevent local genetic drift . Our resCompared to the Eastern European wolf populations, which were probably less affected during the historical wolf persecution than the western populations (see Background), the number of mitochondrial haplotypes was of the same order or even higher in our oldest temporal group: In the Finnish wolf samples collected prior to 1920, 5 haplotypes were found among 18 samples  and well above the often used critical value of 0.68 typical to putatively stable wild populations [M = 0.794) were much higher than this critical value in equilibrium under the most realistic evolutionary scenarios , n detail .Ne compared to autosomal markers and lack recombination. Thus they are more prone to genetic drift. Contrary to microsatellites showing a likely bottleneck in the earliest temporal period, changes in mitochondrial diversity were more gradual, and a significant signal of demographic change was detected only in temporal groups collected at or after the 1960′s  of Ne e.g. for large mammals, which have low fecundity and a Type I survivorship curve [Ne is biased high when immigration reduce the drift signal [Ne of the whole metapopulation and not solely the local Ne [Some assumptions of ip curve ,56. On tip curve ,56. The t signal . In thatlocal Ne ,54.Ne in the Finnish wolf population during the last ~150 years suggested a historical effective size ranging from 86 to 176.4 , 1920–1959 in the second (N = 10), 1960–1979 in the third (N = 33) and 1980–1993 in the fourth group (N = 36).One hundred and fourteen historical wolf samples from 1845–1993 were collected from zoological museums in Oulu, Helsinki and Kuopio in Finland. Collection year and location were known for most of the samples  was used for illustration and comparison of the distribution of genetic variation in different temporal groups, and for comparison of the amount of private alleles between historical and present-day wolves. Collection locations of the analysed historical samples together with the corresponding temporal grouping are presented in Figure N = 37; for sample information see [A random subset of contemporary Finnish wolf samples  wereGenetic analysis of DNA extracted from museum specimens or other old material is challenging and requires special precautions. Post mortem degradation and inhibiting substances often yield target DNA of low quality and/or quantity, and samples are prone to contamination with foreign DNA ,61. Low All work phases before polymerase chain reaction (PCR) were conducted in a laboratory where no DNA handling was previously conducted and where no physical connection to other laboratories existed. The ISO5 class laboratory is equipped with efficient filtering units and separate, positive air displacement. Special clean room clothing with a mask was used while working in the laboratory. Work phases were separated into two rooms: Sample preparation  was done in one room in a laminar flow hood equipped with extra suction fan and UV-light. Working equipment and work spaces were thoroughly cleaned between every sample preparation, and no more than six samples were handled simultaneously. In each extraction round two negative controls were added. The laminar hood and equipment used were UV illuminated overnight between extractions. The buffer preparation, DNA extraction and setup of PCR were done in a second room, which had a separate PCR preparation hood . Several blank controls were run in each PCR reaction. Clean room clothing was changed every working day and procedures were separated in a way that no walking from dust-producing bone preparation room to other room was required during the same day.Bone sample preparation and DNA extraction followed the protocol suggested by Rohland & Hofreiter . Before All historical samples were amplified for a ~450 bp long mitochondrial control region fragment using primers ClCRleft and ClCRright , 2.5 μM of each primer and 0.5-3 μl of DNA extract. PCR protocol included 4 min denaturation at 95°C followed by 11 cycles with 30 s at 95°C, 30 s at 65°C in the first round and thereafter decrease by 1°C for each cycle and 1 min at 72°C and 45 cycles 30 s at 95°C, 30 s at 52°C and 60 s at 72°C and a final extension at 72°C for 8 min. Negative extraction and PCR controls were run along the samples in each PCR reaction to detect possible contaminations. PCR products were purified using FastAP™ (Fermentas) –ExoI method as described in the manufacturer’s info sheet. After that they were sequenced with BigDye™ Terminator v3.1 kit (Applied Biosystems). Unincorporated dye was removed using Sephadex®  method. Sequencing was performed on an ABI 3730 DNA analyser (PerkinElmer Applied Biosystems) and gel runs visually checked with Sequencher .PCR amplifications were performed in 25 μl volume with 2.5 mM MgCl2, 0.2 mM each dNTP, 0.4 μM of forward and reverse amplification primer, 0.3 U AmpliTaq® 360 DNA Polymerase and 1 μl of template DNA. The forward primer of each primer pair was labelled with fluorescent dye. The PCR profile for primers C20.253, C09.173, CXX.225, CPH2, CPH4, CPH8, CPH12, C2001, C2088 and C2096 was set up with an initial denaturation phase of 5 min at 95°C followed by 11 cycles with 30 s at 95°C, 30 s at 58°C (then -0.5°C per cycle) and 1 min at 72°C and 38 cycles with 30 s at 95°C, 30 s at 50°C and 1 min at 72°C. Final extension at 72°C for 10 min concluded the reaction. Five other loci  had first 5 min at 95°C followed by 5 cycles with 30 s at 95°C and 45 s at 65°C (then -1°C for each cycle), 11 cycles with 30 s at 95°C and 30 s at 60°C (then -1°C for each cycle) and 1 min at 72°C, 28 cycles 30 s at 95°C, 30 s at 55°C and 1 min at 72°C, and a final extension of 10 min at 72°C.Extracted historical wolf DNA was amplified with 15 microsatellite loci -68; Dog The quality of extracted DNA was first tested with two microsatellite loci (C2096 and CPH2) with relatively short products (< 110 bp) and previously known to amplify well even with degraded DNA. Samples that gave products for these loci were amplified for all 15 loci. All amplifications were repeated and results interpreted independently at least three times by two people. A heterozygote genotype was not validated unless each allele had been observed twice and a homozygote unless three amplifications were consistently homozygous. If these requirements were not met after five amplifications, half locus or missing data for a given locus was recorded. Target amplicon length affects the amplification success in samples with degraded DNA and therefore fragments < 200 bp should generally be used ,28. We rMitochondrial variation and population bottleneck tests Sequence variability in population was quantified as the number of polymorphic sites (S), the number of haplotypes (H), haplotype diversity (Hd) and nucleotide diversity (π) with the software ARLEQUIN  between the temporal groups based on pairwise differences. Additionally, Tajima’s D [FS [Ne, whereas nucleotide diversity is less affected [.5.1.3.; ). Becaus.5.1.3.; ,71. ARLEjima’s D  and Fu’s’s D [FS  tests imaffected ,73.Phylogenetic analysis of mtDNA sequences Temporal haplotype network for the historical mtDNA consensus sequences was constructed using the TempNet script [N = 656) from GenBank and aligned them with our historical wolf sequences using the CLUSTAL W function [N = 472) and 287 bp (N = 497) discarding shorter sequences. According to substitution model tests in MEGA, Kimura’s two parameter model K2P; [Canis indica and C. himalayensis), which are suggested to be among the most ancient wolf lineages [t script  in R [75function  implemenfunction . Only sedel K2P;  with gamdel K2P;  and usinlineages , were usThe software GENETIX  was useHardy-Weinberg equilibrium in each temporal group was tested with the exact test  using GENEPOP 4.0.10 . Global FST) between the temporal groups were estimated with the program ARLEQUIN. The significance tests for global AMOVA  results were based on 1023 permutations. Population pairwise FST-values were calculated with the distance method [FST matrix in TFPGA v1.3 [The distribution of genetic variation within and between the groups (AMOVA) and genetic differentiation , which generates axes that describe the maximum genetic variation among individuals and plots individuals along these axes according to their genotype. To see, if genetic variation patterns were significantly different between the temporal groups, we compared the means and variances of individual scores along the first and second FCA axis between the first and present-day samples. With a null hypothesis of equality, obtained means and variances of the two FC axes were tested with We conducted an assignment analysis to get further information on the differentiation of the temporal groups. We performed assignment runs for the samples using the Rannala and Mountain  BayesianN = 37; [FST) between these population samples was calculated and the distribution of genetic variation among individuals visualized with a FCA plot.Finally, we compared the oldest Finnish historical wolves with the present-day Russian Karelian reference population  to see K (the number of clusters), from K = 1 to K = 15. Each run consisted of 500 000 replicates of the MCMC after a burn-in of 100 000. We used the admixture model and allowed the allele frequencies to be correlated among temporal groups  to inveups (see ). All otups (see ) was useups (see  ad hoc mNe) preceding each study period. The test was performed for all temporal groups using the two-phase model (TPM) of microsatellite evolution and a probability of 95% for single-step mutations with variance of 12 as suggested by Piry et al. [He > Heq, see [We used the software BOTTLENECK  to invey et al. . The WilHeq, see ) was detμ) of 2 × 10-4 /locus/generation  of 0.04, 0.08, 0.2 and 0.4. As a proportion of other than one-step mutations (pg) five different values were used: 0.00, 0.05, 0.10, 0.20 and 0.30 and the mean size of multi-step mutations (δg) was set to 3.1  with fo3.1 (see ). CriticNe [Ne estimator, ONeSAMP [Ne:s in each temporal group. Samples collected 1920–1959 were excluded due to small sample size.We used two single-sample approaches to estimate effective population sizes in each temporal group separately. First, we used a linkage disequilibrium (LD) based effective population size estimator, LD-Ne . We used ONeSAMP , which iNe from genetic change between two or more sampling points . Next we ran our data sets with a maximum value of Ne set to 500 with MNE [m = 0) was chosen, and maximum likelihood followed that described in Wang [Ne values. We tested the Ne likelihoods from 2 to 500 in steps of two with 1000 MC repeats for each value.First we used the program TempoFS  to estimo plan I  with a cwith MNE , which u in Wang . Finally in Wang  was emplThe data set supporting the results of this article is included within the article and its additional files.The authors declare that they have no competing interests.This study was a part of the PhD research of EJ supervised by JA and MR. Samples used in this study were collected by JA and EJ, and prepared in clean facilities and molecular laboratory by EJ and JH. Genetic analyses were made by EJ with the help from JA and MR except for mtDNA phylogeny part, which was done by JH. EJ wrote the manuscript with help from all co-authors. Final manuscript was approved by co-authors except MR, who passed away shortly before it was finished.List of museum specimens.Click here for fileAmplification success for the museum samples.Click here for filemtDNA haplotype tree (390 bp) for European wolves including Finnish museum haplotypes from this study.Click here for fileLocus-specific microsatellite results for temporal museum groups and modern-day reference data.Click here for fileTemporal changes of allelic frequencies in the museum data.Click here for fileText S1. Statistical analyses for the distribution of genetic variation (FCA) among the temporal museum groups.Click here for fileDistribution of genetic variation: present-day Karelian wolves vs. Finnish wolves collected before 1920.Click here for fileResults from Structure runs for the museum samples.Click here for fileDistributions of allele frequencies among the museum groups and contemporary reference sample.Click here for fileData set.Click here for filePrimer sequences for mtDNA amplification.Click here for file


Lathyrus sativus L. and its relative species may yield fundamental insights into evolutionary history and provide options to meet the challenge of climate changes. 30 SSR loci were employed to assess the genetic diversity and population structure of 283 individuals from wild and domesticated populations from Africa, Europe, Asia and ICARDA. The allele number per loci ranged from 3 to 14. The average gene diversity index and average polymorphism information content (PIC) was 0.5340 and 0.4817, respectively. A model based population structure analysis divided the germplasm resources into three subgroups: the relative species, the grasspea from Asia, and the grasspea from Europe and Africa. The UPGMA dendrogram and PCA cluster also demonstrated that Asian group was convincingly separated from the other group. The AMOVA result showed that the cultivated species was quite distinct from its relative species, however a low level of differentiation was revealed among their geographic origins. In all, these results provided a molecular basis for understanding genetic diversity of L. sativus and its relatives.The study of genetic diversity between  Lathyrus L. includes as many as 187 species [Lathyrus sativus L.) is the only species widely cultivated as a food crop in the genus Lathyrus, whereas other species (Lathyrus cicera L. and Lathyrus ochrus L.) are cultivated to a lesser extent [The genus  species . These a species . Grassper extent . Moreover extent .Lathyrus sativus. PCR-based molecular markers utilized so far in L. sativus and its relative species include random amplification of polymorphic DNA (RAPD) [L. sylvestris L. and L. latifolius L., amplified fragment length polymorphism (AFLP) [L. sativus, L. cicera, and L. ochrus [There have been recent studies of genetic diversity in A (RAPD) ,7, restrA (RAPD)  which wam (AFLP)  clarifie. ochrus .Lathyrus sativus using simple repeat sequence (SSR) markers [L. sativus with the European Molecular Biology Laboratory (EMBL) nucleotide sequence database. Amplification was successful only in 10 out of 20 of the SSR primers, with only 6 of these exhibiting size polymorphism and subsequently used in genetic diversity analysis for 13 Italian landraces [L. sativus. EST-SSRs derived from Medicago truncatula L. to investigate the genetic diversity among 20 grasspea accessions from Ethiopia [Up to now, there was little study of genetic diversity in  markers –13  with the following cycle: 5 min initial denaturation at 95°C; 35 cycles of 30 s at 95°C, 30 s at the optimized annealing temperature (Polymerase chain reactions (PCR) were performed in 10 μl reaction volumes containing 5 μl 2 x TaqPCR MasterMix , 1 μl primer, 1.5 μl of genomic DNA (30 ng) and dd Hperature , 45 s of2)/n, where pi is the frequency of the ith allele, n is the total number of genotypes [The genetic diversity parameters and polymorphism information content (PIC) of each primer pair were calculated by Powermarker v3.25  using thenotypes . POPGENEenotypes  was usedenotypes . The proenotypes ,22 was uenotypes . The numenotypes . Analysienotypes .120 SSR markers were randomly selected to validate polymorphism at first. 25% of them were polymorphic . 30 SSR Lathyrus sativus and its relatives was inferred by using STRUCTURE V2.3.3 based on 30 SSR markers. At K = 2, all the germplasm were divided into L. sativus and its relatives. But, according to the method described by Evanno et al. [L. sativus also divided into 2 subgroups  was between African and European grasspea. Based on the origin of L. sativus accessions, the genetic distance between Africa and Asia (0.0141) was larger than it between Europe and Asia (0.0118). These result matched with structure analysis above.The n source , Fig. 4.distance  Lathyrus sativus species used in this study. Nei’s genetic distance of 0.7247 between L. sativus and L. cicera was the smallest in our study among L. sativus and its nine relative species  DC, L. pratensis L., L. sylvestris L. and L. latifolius L. In general, L. clymenum and L. ochrus were annual species, however, L. pratensis, L. sylvestris, and L. latifolius were perennial species.Clustering analysis based on Nei’s genetic distance divided all the 10 species under genus r groups . One groThe genetic relationship of individual accessions was analyzed using principal component analysis (PCA); all the cultivated accessions were labeled according to their geographical origin. Within cultivated species, accessions from Asia were somewhat associated with their geographical origin and were different from other accessions , especiaLathyrus sativus and its relatives by analysis of molecular variance (AMOVA). The results showed that the cultivated species was significantly distinct from its relatives at P-value of 0.0001 . The European accessions were widespread throughout Southern and partly Central Europe, penetrating to the northern coast of Africa . The result of structure demonstrated that pulation . One conpulation  also suppulation . Althoug sativus , our res sativus  which bagh et al .


Colias eurytheme and Colias eriphyle, there has been historical debate over the extent of hybridization occurring and the identity of phenotypically intermediate individuals as genetic hybrids. This study assesses the population structure of these two species to measure the extent of hybridization and the genetic identity of phenotypic intermediates as hybrids. Amplified fragment length polymorphism (AFLP) marker analysis was performed on 378 specimens collected from northern California and Nevada. Population structure was inferred using a Bayesian/Markov chain Monte Carlo method, which probabilistically assigns individuals to genetic clusters. Three genetic clusters provided the best fit for the data. C. eurytheme individuals were primarily assigned to two closely related clusters, and C. eriphyle individuals were mostly assigned to a third, more distantly related cluster. There appeared to be significant hybridization between the two species. Individuals of intermediate phenotype (putative hybrids) were found to be genetically indistinguishable from C. eriphyle, indicating that previous work based on the assumption that these intermediate forms are hybrids may warrant reconsideration.Gene flow and hybridization among species dramatically affect our understanding of the species as a biological unit, species relationships, and species adaptations. In North American  Colias eurytheme , Colias philodice (clouded sulfur), and Colias eriphyle (yellow sulfur), has long been recognized  is the sister group to these two species , which includes  Gerould . The sta Gerould . C. euryHovanitz .Colias system, however, presents an unusual pattern. The observed frequencies of phenotypic intermediates suggest that the two species experience low but consistent levels of gene flow wherever they occur in sympatry, while the two parent species retain distinct identities  genetic incompatibility results in selection for characters that reduce interspecific crosses ultimately leading to complete reproductive isolation, or (2) lack of incompatibility and divergence leads to an increase in hybridization rates Taylor . The ColColias butterflies provide a convenient system in which to study hybridization. C. eurytheme and C. eriphyle are present at low and high elevations in the western United States and across the Sierra Nevada  markers have been used to measure hybridization and produce linkage maps of hybridizing butterfly species successfully  Is there genetic evidence that individuals of intermediate coloration are in fact of mixed parentage ? (3) Is there genetic evidence of higher levels of introgression at a site where high frequencies of phenotypic intermediates have been historically observed?Using AFLP marker techniques, this research addressed the following questions: (1) Is there genetic evidence for introgression between Colias eurytheme is extremely common and has a wide range across the United States, excepting the northernmost regions and peninsular Florida . Wang and Porter  might be polymorphic individuals of a single species ..C. euryt Gerould . Most pu Gerould , as Lepi Gerould . The put Edwards . As discColias system does not appear to maintain high hybrid abundance relative to parent species. In the eastern United States, C. eurytheme hybridizes naturally with C. philodice, which (as noted previously) has historically been considered the same species as C. eriphyle  introgression in the C. eurytheme population . AFLP analysis followed the methods of Vos et al. , which iAFLP amplicon data were collected on an ABI 3130XL Capillary Electrophoresis Genetic Analyzer  and compiled for each primer combination with ABI GeneMapper software version 3.7 . GeneScan 500 ROX was used as an internal size standard. To minimize scoring errors, the threshold detection settings were adjusted so that fragment sizes <50 bp, higher than 500 bp, and lower than 100 reflective fluorescent units were not scored during the automated scoring process. All samples were evaluated manually for quality control following the automated scoring process. Any sample runs showing questionable size standards or peak signals were either scored by hand or omitted from the study. Only two individuals did not produce any clear genetic signal, and those individuals were omitted from the study. To confirm repeatability, a random sample of twenty individuals were run through the restriction, ligation, preselective PCR, selective PCR, fragment analysis, and scoring process an additional time. Any alleles that could not be accurately scored in both replicates  were omitted. The final scored dataset consisted of 363 individuals from nine sites spanning six regions and 114 loci (TableK) is identified based on the presence/absence data of all AFLP loci of all the individuals. Two possible models can be used to infer populations: either assuming no admixture or assuming admixture. Under the model that assumes no admixture, each individual is assumed to come purely from one of a number of discrete populations, and the posterior probability of each individual originating from a particular population is estimated. Under the model that assumes admixture and allows individuals to be of mixed ancestry, each individual’s genotype is proportionally assigned to the inferred populations. Because AFLP data consist of presence or absence of particular gene fragments, the methods of Falush et al. . In this model, the results of the genetic clustering of individuals were visualized in three ways:Following the no-admixture species differentiation model run, the model assuming admixture was run using the genotypes of all individuals in order to address our first two research questions. Predesignated population information was included in the input file, but not incorporated into the model  and any morphological intermediates were segregated. This comparison allows both the detection of the extent of hybridization in presumed hybrids and any differences in hybridization among different geographic regions.Regional comparison, in which individuals were partitioned into one of the six collection regions and any individuals that unambiguously looked like hybrids were t-tests were used to determine whether Montague and Gazelle  each show significantly higher frequencies of intermediate phenotype individuals than Sierra Valley, CA. Unpaired t-tests incorporated annual mean hybrid frequencies from all sampling years we have on record; paired t-tests incorporated only mean hybrid frequencies from years where data exist for both sites in the comparison. The admixture model was then run in STRUCTURE to compare the extent of hybridization between C. eurytheme and C. eriphyle present at Montague, Standish, and Gardnerville/Minden. The population assignment probabilities were compared for intermediates collected at Montague vs. Standish and Gardnerville/Minden.Finally, we addressed our third research question by performing a comparison assuming admixture between sites only where phenotypic intermediates were caught . Montague and the nearby collection site Gazelle have historically shown higher frequencies of phenotypic intermediates than other collection sites . Using R software , where K is the number of potential population clusters. Longer runs of 1 000 000 generations did not significantly affect the assignment probabilities. The protocol of Evanno et al. (K) for the entire group of individuals. This method calculates ΔK based on the rate of change in the logarithm of the likelihood function of successive K values.In all STRUCTURE runs, the model simulated 100 000 generations following an initial burn-in of 20 000 generations with 10 independent replicates of each o et al.  was follFour unique primer pairs generated a total of 114 AFLP bands ranging in size from 58 to 377 bp, 95.6% of which were polymorphic. The different primer pairs produced between 19 and 39 AFLP bands.C. eurytheme and C. eriphyle, three clusters best explained the AFLP data. In this model, each individual’s assignment probability to a cluster estimates the proportion of the individual’s genome that originated from each cluster  than to cluster 3 (0.099 probability). As averaged over 55 individuals, C. eriphyle were more likely to be assigned to cluster 3 (0.732 probability) than to clusters 1 and 2 (0.134 probability for both). Even so, there was a wide range in the assignment probabilities to the three clusters among individuals within each species: in C. eurytheme, the probability of assignment to cluster 1 ranged between 0.159 and 0.644 and to cluster 2 ranged between 0.177 and 0.615; in C. eriphyle, the probabilities of assignment to cluster 3 ranged between 0.081 and 0.986. The unevenness in assignment probabilities between the two species  suggests that there is greater introgression in C. eriphyle than in C. eurytheme. The genetic distance  between clusters 1 and 2 is 0.0005, between clusters 1 and 3 is 0.0035, and between clusters 2 and 3 is 0.0028, indicating that cluster 3 is more genetically distant than clusters 1 and 2 are to each other  C. eurytheme from regions where C. eriphyle does not occur , (2) C. eurytheme from regions where C. eriphyle co-occurs (“C. eurytheme sympatric”), (3) C. eriphyle, and (4) unambiguous phenotypic intermediates. Three clusters (K = 3) provided the best fit for the AFLP data. Of the individuals morphologically identified as C. eurytheme, there was relatively higher assignment of individuals to clusters 1 and 2 ,  C. eurytC. eurytheme to avoid any erroneous categorization of mixed ancestry individuals, such that nine groups were predefined in this comparison: (1) Sacramento Valley C. eurytheme, (2) west Sierra C. eurytheme, (3) High Sierra C. eurytheme, (4) East Sierra C. eurytheme, (5) East Sierra C. eriphyle, (6) western Great Basin C. eurytheme + phenotypic intermediates, (7) western Great Basin C. eriphyle, (8) Shasta Valley C. eurytheme + phenotypic intermediates, and (9) Shasta Valley C. eriphyle. The proportions of assignment probability of each population to the three clusters reflect their geographic location  in the Shasta Valley region, cluster 3 of the three clusters had the highest probability of assignment . Similarly, the nearby town Gazelle (for which data were available from 1980 to 1998) showed significantly higher frequencies of phenotypic hybrids than Sierra Valley for both paired and unpaired t-tests . Montague and Gazelle did not significantly differ from one another in their frequencies of phenotypic hybrids, which was expected, as the two sites are approximately 24 kilometers apart and could be considered the same Colias population. Similar data do not exist for other sites of record, so we were limited in our comparison of Montague to other sites, but these results show that Montague has a consistently higher frequency of phenotypic intermediates than at least one other collection site.These results address our third research question of whether there is genetic evidence of higher levels of introgression at Montague, a site where high frequencies of phenotypic intermediates were historically observed. Analyses of historical data collected by one of us (from 1984 to 2000) revealed that Montague showed significantly higher annual frequencies of phenotypic hybrids than Sierra Valley for both paired and unpaired K = 3) again providing the best fit for the data. For all three sites, the genetic makeup of C. eurytheme individuals was largely assigned to a mixture of clusters 1 and 2  than C. eriphyle at western Great Basin sites Gardnerville/Minden and Standish . In phenotypic intermediates at all three sites, on average more than half of the genome is assigned to cluster 3, but there does not appear to be a regional trend. The genetic assignment proportions in intermediates from Standish and Montague are similar to proportions assigned in their C. eriphyle counterparts, but the proportions in intermediates from Gardnerville/Minden are quite different from C. eriphyle from Gardnerville/Minden  provide the best explanation for the data. C. eurytheme individuals appear to be assigned mostly to a combination of two clusters (represented as red and green in the bar plots) and C. eriphyle individuals appear to be assigned mostly to a third cluster (represented as blue in the bar plots). According to the neighbor-joining tree, clusters 1 and 2 are more genetically similar to one another than either are to cluster 3, which supports the current understanding of C. eriphyle as a distinct species from C. eurytheme, although the high variation in the proportions of cluster assignments within species indicates either very recent species divergence or significant interbreeding. Within C. eriphyle individuals, the average genome proportion assigned to cluster 2 is usually equal to or higher than the proportion assigned to cluster 1. Moreover, in C. eurytheme individuals from regions where both species are sympatric, the average genome proportion assigned to cluster 2 is consistently higher than cluster 1. As the two species are sympatric only east of the Sierran Crest and C. eurytheme occurs alone west of the Sierran Crest, this implies a geographic pattern to clusters 1 and 2, where cluster 1 is more prevalent west of the Sierran crest and cluster 2 is more prevalent east of the Sierran Crest. The two-cluster genetic makeup of C. eurytheme might suggest that (1) this species is a mix of two closely related populations, which potentially were originally geographically separate, but which over time have become more mixed via continual gene flow, leading to the patterns we see today, or (2) this species is beginning to diverge into two distinct populations, potentially due to geographic isolation.In all analyses, three genetic clusters , it is worthwhile to consider the genetic patterns when phenotypic intermediates are lumped with C. eurytheme. This avoids ambiguity when assigning predetermined populations in the STRUCTURE analysis. However, considering the genetic makeup of the phenotypic intermediates (as discussed below), it is likely that phenotypic intermediates are indeed genetically distinct from C. eurytheme and thus they should be considered separate entities when considering the extent of hybridization between C. eurytheme and C. eriphyle.When phenotypic intermediates are lumped with C. eriphyle at Standish, CA. The individual genomes in this population are assigned on average 14.8% to cluster 1, 36.7% to cluster 2, and 48.5% to cluster 3. However, this pattern may be an artifact of a small sample size, as only ten C. eriphyle specimens were collected from Standish.At the site level, there appear to be unusually high levels of introgression in C. eriphyle, as the majority of individual genetic assignments in both of these groups are to genetic cluster 3. In the western Great Basin region, the intermediates have even higher probabilities of assignment to cluster 3 than do C. eriphyle individuals. These data suggest that what were assumed to be hybrids are instead color morphs of C. eriphyle.Surprisingly, it does not appear that individuals of intermediate coloration (which have long been assumed to be hybrids) are of mixed parentage. At every comparison level , phenotypic intermediates are genetically indistinguishable from C. eriphyle wherever C. eriphyle occurs, including in western Canada where C. eurytheme is very rare or absent . If phenotypic intermediates were true genetic hybrids, individuals with distinct orange coloration should not be observed in regions where C. eurytheme is rare or absent. Second, when C. eriphyle went temporarily extinct in Sierra Valley in 1994 due to drought and alfalfa senescence, intermediate phenotypes were also absent from that site until C. eriphyle’s re-colonization a year and a half later. If these intermediate phenotypes were true genetic hybrids, one would not expect all phenotypic hybrids and backcrosses to disappear along with C. eriphyle , it is possible that “orange” genes from C. eurytheme have repeatedly entered “yellow” populations via hybridization and, at least in the case of C. eriphyle, introgressed widely, becoming a functional color polymorphism even in allopatric populations, extending far beyond any obvious genomic signature of hybridization. Testing this hypothesis will require identification and sequencing of the genes determining orange coloration in both C. eurytheme and phenotypic intermediates.Further molecular work such as gene and genome sequence data analysis would strengthen these conclusions. Future research would benefit from sampling


Hucho hucho) from: Poland, Germany, Slovakia, and Ukraine were investigated using ten microsatellite DNA loci. Microsatellite DNA analysis was successfully applied for the first time in the Polish broodstock of this fish species. The genetic variation and genetic distance between these broodstocks were evaluated. In addition, we examined the potential effects of a genetic bottleneck on the genetic variation of the broodstocks. The European huchen broodstocks exhibited moderate genetic diversity (PIC = 0.405–0.496 and I = 0.831–1.047) with the exception of German broodstock which presented higher genetic diversity (PIC = 0.590 and I = 1.254). Observed (Ho) and expected (He) heterozygosity across the investigated loci in all broodstocks ranged from 0.434 to 0.686 and from 0.452 to 0.650, respectively. Overall, the studied broodstocks were in Hardy-Weinberg equilibrium (HWE); however, from 8 to 42 % of the loci deviated from HWE in each stock. The Garza-Williamson index (M = 0.146–0.279) and values of the heterozygosity excess revealed a reduction of genetic variation in all studied broodstocks because of the founder or bottleneck effect. The analysis of genetic differentiation (Fst) and Nei’s genetic distance between pairs of broodstocks revealed that Polish and Ukrainian broodstocks of European huchen were characterized by the closest genetic distance. In contrast, the highest genetic divergence parameters (Fst and Nei’s distance) were observed among German, Slovak, and Ukrainian broodstocks.Four broodstocks of European huchen ( Hucho hucho), also called Danube salmon, is the largest salmonid species and one of the most endangered members of the Salmonidae family (Holcik Hucho taimen) are exclusively freshwater residents. Furthermore, this fish species can live for more than 20 years, and adults are large piscivorous predators of up to 1.65 m standard length (SL) and with a maximum mass of 60 kg (Kottelat and Freyhof European huchen (y Holcik . It is ey Holcik . EuropeaBrachymystax lenok)   pelvic or pectoral fin clips were placed in Eppendorf tubes and kept in 96 % ethanol at a temperature of 4 °C until DNA extraction. DNA was isolated from collected fin clips using standard Chelex 100 procedure , Germany , Slovakia  and Ukraine  during the years 2011-2013  and 0.6 unit GoTaq flexi DNA polymerase . Re-distilled water was used to bring the reaction mixture to the desired final volume. Amplification was performed with a Mastercycler gradient thermocycler  under the following conditions: an initial denaturation at 94 °C for 3 min, followed by 34 cycles at 94 °C for 30 s, annealing at 53–61 °C  (Table Ar) were computed by GenePop software (version 4.2.1) (Rousset Ho) and expected heterozygosity (He), the exact Hardy-Weinberg (H-W) equilibrium test, as well as linkage disequilibrium (LD) were calculated using Arlequin software (version 3.5) (Excoffier and Lischer Fis) were calculated using Fstat software (version 2.9.3)  was also calculated employing PowerMarker software (version 3.25) (Liu and Muse Fst) and Nei’s genetic distance. Shannon’s index (I) for each loci within tested broodstocks was calculated using PopGene software (version 1.3.2) (Yeh and Boylet M), which was computed applying Arlequin software 3.5. A test for bottleneck assessment was also conducted using the Bottleneck software (version 1.9)  and infinite allele model (IAM) for four broodstocks of European huchen were tested. This method is based on the assumption that in non-bottlenecked broodstock (close to mutation drift equilibrium) the value of expected heterozygosity (He) is equal to Heq (heterozygosity expected in a mutation-drift equilibrium). The excess of He over Heq is the evidence of severe reduction in broodstock effective size that may occur because of a bottleneck event. In order to accommodate the obtained genotypic data to the requirements of employed software, every tetrasomic locus was examined as two disomic loci and as result the mean values was considered for estimation of genetic parameters.The Micro-Checker software (version 2.2.3) was used to check microsatellite null alleles, scoring errors due to stuttering and large allele drop-out in samples  Goudet . The polStr-12, Str-15, Str-60, Str-73, Str-543, Ssa-85, Ssa-171, BleTet-2, Sfo-292, Omm-1016, Omm-5017) were monomorphic in all broodstocks, one (Str-85) did not produce any PCR product and seven loci  produced non specified bands (stutter bands). Ten microsatellite loci  were selected for further analyses because they were characterized by good quality products and were polymorphic  and 467 bp. The number of amplified alleles per locus ranged from one (Sfo-262) to 26 (Omm-1077) with an average of 8.1 alleles per locus  of the four broodstocks of European huchen are shown in Tables PIC) in fish from Poland, Germany, Slovakia, and Ukraine were 0.430, 0.590, 0.496, and 0.405, respectively. The mean allelic richness varied from 3.944 to 5.200 in studied broodstocks of European huchen  in the investigated broodstocks ranged from 0.434 (Ukraine) to 0.686 (Germany) and were close to the mean values expected under H-W equilibrium (He) (Table Heq). In all broodstocks, under the infinite allele model (IAM) and stepwise mutation (SMM) models, heterozygosity excess were detected in most of analyzed loci; however, observed He>Heq differences were significant in only Polish  and Ukrainian  broodstocks. All investigated loci differed in terms of the Garza-Williamson index (M). In all samples M values were the lowest for the most polymorphic loci (such as BleTet-9 and Omm-1077) and the highest for the least polymorphic loci . The mean observed M values in the examined broodstocks varied from 0.146 to 0.279. The mean fixation index (Fis) in fish from Poland, Germany, Slovakia, and Ukraine were −0.071, −0.082, −0.047, and 0.053, respectively (Table The mean observed heterozygosity (Fst) of the four broodstocks of European huchen was 0.1139. Analysis of the genetic structure of the studied broodstocks with AMOVA method revealed that 13.20 % of the genetic diversity was distributed among broodstocks and 86.80 % occurred among individuals within the broodstocks. The Nei’s genetic distances among the four broodstocks and the Fst matrix are shown in Table Fst values, occurred between Ukraine and Slovakia (0.1731). The lowest genetic divergence and genetic distance were observed between Poland and Ukraine , while the highest genetic distances were observed among German, Slovak, and Ukrainian broodstocks  with the exception of German broodstock which presented high genetic diversity (the mean He and PIC were close to 0.6). Similar moderate indices of genetic diversity to those observed in the present study were reported for some populations of taimen from Heilongjiang River Basin (China)  consistently ranked the broodstocks in order of decreasing diversity (Germany > Slovakia > Poland > Ukraine). However, there were no significant differences between these parameters among the four studied broodstocks (P > 0.05).The comparison of the overall number of private alleles, allelic ranges and its frequency clearly demonstrates genetic differences between studied broodstocks of European huchen. This confirms the hypothesis that the broodstocks studied do not share a common gene pool at the population genetic level. Genetic diversity, which can be evaluated as the allele number by locus and the mean number across loci, differed among the studied groups of fish. Examined broodstocks of European huchen exhibited moderate genetic diversity  indicating a small overall deficiency of heterozygotes, while the rest of the analyzed broodstocks of European huchen were characterized by negative Fis indicators exhibiting small overall excess of heterozygotes against Hardy-Weinberg expectations. In contrast, in domesticated stocks of fish the observed heterozygosity (Ho) sometimes exceeds the expected heterozygosity (He). For example, this tendency was observed in Chinook salmon (Oncorhynchus tshawytscha) stocks   and stepwise mutation models (SMM) in Polish and Ukrainian broodstocks. The heterozygosity excess at observed loci in mentioned broodstocks might be indicative of a small founding population size or bottleneck events as was hypothesized in the case of the hatchery stocks of brook trout   from China ; however, the majority of diversity were observed between individuals within a broodstocks (86.80 %). Similar genetic diversity (13.10 %) was observed among two hatchery stocks of barfin flounder (A continuous genetic monitoring of hatchery stocks is an important tool for development of sustainable conservation management programs. Management based on supportive and captive breeding carries the risk of adverse modifications to a gene pool, resulting in loss of genetic diversity, decrease of heterozygosity, or inbreeding depression. The consequence of inbreeding depression in hatchery stocks can be the negative effects on: hatching rate, fry survival, growth rate, and spawning performance, as well as inefficiency of feed conversion, occurrence of deformations and presence of short-lived albino fish (Guo-Sheng et al. The potential for evolution and adaptation to new environments is limited by the genetic diversity of the population. Natural selection favors individuals that are better adapted to live in natural environment than in captivity, thus research programs aimed at retaining the evolutionary genetic adaptive potential of European huchen stocks are very important. Therefore the optimum degree of genetic differentiation and a high genetic diversity should be permanently controlled. Moreover, European huchen habitat continues to be threatened by further anthropogenic factors influence and particularly unfavorable conditions may adversely impact on the populations characterized by low genetic variation level. The lack of information on the genetic structure of European huchen broodstock in Poland essentially limits the sustainable conservation of this species. Therefore, baseline genetic data are crucial to guide future population specific conservation programs and research efforts on European huchen in Poland.