Pectinatella magnifica , the freshwater magnificent bryozoan, is non-native in Europe and Asia. This study was designed to determine the genetic diversity and population structure of P. magnifica colonies collected from the Protected Landscape Area (PLA) and UNESCO Biosphere Reserve Třeboňsko (the Czech Republic) in the 2009 and 2011–2014 periods using Amplified Fragment Length Polymorphism (AFLP).Non-native species have aroused scientific interest because of their ability to successfully colonise areas to which they have been introduced, despite their sometimes limited genetic variation compared to their native range. These species establish themselves with the aid of some pre-existing features favouring them in the new environment. The vast majority of the examined non-native colonies, except three colonies sampled in 2012, expressed very low levels of genetic variation, not differentiating from the USA native colony. The Bayesian clustering approach grouped the 28 accessions into two genetically different populations.P. magnifica in the Czech Republic.The data suggest relatively low gene diversity within all colonies, which might reflect the recent expansion of The online version of this article (10.1186/s40709-017-0069-8) contains supplementary material, which is available to authorized users. Pectinatella magnifica , a freshwater bryozoan species that naturally inhabits lakes and rivers in eastern North America  for each K value. Also, in order to determine the most appropriate number of K, ΔK was calculated as described by Evanno et al. [Cluster and principal component analysis (PCA) were performed. These analyses were calculated by using R software . Analysis of the genetic structure of the population was carried out assigning samples to re 2.3.4 . The proo et al. .AFLP analysis with four primer combinations amplified 496 bands, ranging in size of 36–480 bp, from which 79.4% were polymorphic (394 bands). The number of polymorphic fragments for primer combination ranged from 72 to 132  to define genetic distance within accessions. First and second principal component of PCA analysis explained 15.2 and 9.8% variation, respectively Fig. . The higK = 2) with no consistent trend differentiating individual localities or years of collection by using these groups , and the colonization of new water streams, dams and ponds. In spite of its geographic distance, the sample from the native origin has shown no particular AFLP band pattern.In conclusion, our results showed the presence of a single metapopulation in all recently known localities across the Czech Republic with low or slight differentiation of Additional file 1: Table S1. Detailed description of the samples location including GPS.Additional file 2: Table S2. Detecting the number of clusters of individuals by using delta K.


Signal transducer and activator of transcription 3 (STAT3) is a key regulator of numerous physiological functions, including the immune response. As pathogens elicit an acute phase response with concerted activation of STAT3, they are confronted with two evolutionary options: either curtail it or employ it. This has important consequences for the host, since abnormal STAT3 function is associated with cancer development and other diseases. This review provides a comprehensive outline of how human viruses cope with STAT3-mediated inflammation and how this affects the host. Finally, we discuss STAT3 as a potential target for antiviral therapy. Signal transducer and activator of transcription 3 (STAT3) was first described in 1994 as a central transcription factor in acute inflammation . Upon cySTAT3 activity is additionally regulated by several post-translational modifications. First, phosphorylation at serine 727 (pS727) by a variety of serine/threonine kinases, such as the mitogen-activated protein (MAP) kinases, mechanistic target of rapamycin (mTOR), and protein kinase C delta type (PKCδ), increases transcriptional activity even further . In mitoSTAT3 mRNA, including Let-7a [HNF4A mRNA silencing [PTPRD and SOCS3 [Additional negative feedback regulators include the protein phosphatases receptor-type tyrosine-protein phosphatase C (PTPRC), receptor-type tyrosine-protein phosphatase D (PTPRD), receptor-type tyrosine-protein phosphatase T (PTPRT), and dual specificity protein phosphatase 2 (DUSP2) that hydrolyze p-STAT3 or upstream pathway members , 14, 15.g Let-7a , miR-17-g Let-7a , miR-29bg Let-7a , miR-124g Let-7a , and miRg Let-7a . STAT3-ailencing . Similarnd SOCS3 ,28.Although STAT3 phosphorylation is often considered a prerequisite for its transcriptional activity, unphosphorylated STAT3 (u-STAT3) can promote the expression of genes related to cell cycle progression ,30. FinaIn mammalian organisms, tissue injuries inflicted by pathogens are met by the release of inflammatory mediators and local infiltration of white blood cells. This eliminates foreign material, removes damaged tissue components, and clears the way for repair. STAT3 plays an essential role in these processes by enabling the expression of a variety of genes in response to specific external signals sensed by cell-surface receptors . Not alltrans-signaling pathway [Interleukin 6 (IL-6) is a classic proinflammatory cytokine that signals through STAT3 as part of the acute phase response (APR), a nonspecific reaction of the innate immune system to pathogen infection. During acute inflammation, IL-6 is produced in the lesion site to attract neutrophils and increase granulopoiesis . Upon ex pathway , which s pathway ,36. Upon pathway . Pathoge+ T cells into Th17 cells [+ T cells (Treg cells) [FH cells) via STAT3 [Apart from the lesion site, the IL-6/STAT3 proinflammatory signaling axis functions in many other cellular and tissue compartments. In secondary lymphoid tissues, where the adaptive immune response takes place, IL-6-mediated STAT3 activation promotes the proliferation and survival of T and B cell populations ,39. In a17 cells ,41, limig cells) . Moreoveia STAT3 ,44, effeia STAT3 .+ and CD8+ T cells, B cells, dendritic cells (DCs), and mast cells [Interleukin 10 (IL-10) also activates STAT3, but unlike IL-6 the IL-10/STAT3 axis has powerful anti-inflammatory properties. Its function is essential to restrain unwanted immune responses and prevent autoimmune pathologies . IL-10 ost cells . Until rst cells . As an est cells .H1) cell responses [regs out of naïve CD4+ T cells [IL-10 exerts its anti-inflammatory effect by suppressing T helper 1  initiate a canonical antiviral transcriptional program through STAT1 and STAT2, which results in an inflammatory, proapoptotic, and antiproliferative state . At the In this context, an initial proinflammatory response to IFNs is mediated by STAT1, which expression is far more abundant, while STAT3-mediated gene induction is prevented by the SIN3 transcription regulator family member A complex (SIN3A). This multimolecular complex, containing histone deacetylases 1 (HDAC1) and 2 (HDAC2), inactivates STAT3 by deacetylation . It has A potential regulatory layer that remains poorly understood is the role of STAT1 and STAT3 heterodimers induced by IFNs. On one hand, STAT1 and STAT3 heterodimers have been described to bind regulatory elements present in promoters of interferon-stimulated genes (ISGs) such as γ-activated sequence (GAS), supporting a potential antiviral role of STAT1 and STAT3 heterodimers . On the The suggested temporal dynamics of STAT biology may explain the serious consequences of persistent viral infections, as in the case of hepatitis C virus (HCV) . Here, sUpon infection, inflammatory cytokines trigger cell signaling in local stem cells or differentiated cells. Among other transcription factors, this eventually leads to the activation of STAT3 that mediates regenerative gene-expression programs. These genes include growth factors, cell-cycle stimulators, cell death inhibitors, and genes promoting dedifferentiation and cell motility and migration . The tasGiven the extensive role of STAT3 in many physiological processes, it is only logical that its perturbation entails a wide variety of pathological consequences. This is exemplified by loss-of-function mutations in the STAT3 gene that lead to the autosomal dominant hyper-immunoglobulin E (IgE) syndrome (AD-HIES) . These pSTAT3 mRNA [SOCS3 mRNA via up-regulation of snail family transcriptional repressor 1 (SNAIL1) [As STAT3 activation is a pivotal event in the APR elicited by pathogen invasion, many viruses have evolved to thrive in a STAT3-driven microenvironment and have developed strategies to stimulate STAT3 signaling , Table 1AT3 mRNA . Additio(SNAIL1) . HCV req(SNAIL1) . HCV sti(SNAIL1)  and indi(SNAIL1) . Further(SNAIL1) . Further(SNAIL1) . Similar(SNAIL1) . STAT3 a(SNAIL1) . In hepa(SNAIL1) . Kaposi’(SNAIL1) . In huma(SNAIL1) . Though (SNAIL1) . STAT3 a(SNAIL1) . VZV ind(SNAIL1) . Resvera(SNAIL1) . Similar(SNAIL1)  and favo(SNAIL1) .SOCS3 expression [In the acute phase, viral suppression of STAT3 reduces the host cell's ability to respond to inflammatory cytokines. On the other hand, inhibiting STAT3 also removes negative feedback on the antiviral response. To understand the beneficial effect of blocking STAT3 for viruses, it thus requires a temporal dissection of each individual virus/STAT3 interaction. Most viruses that suppress STAT3, however, do this to avoid the antiviral pressure exerted by STAT3 responsive genes in the acute phase of infection , Table 1pression . Other vpression . Likewispression . Human mpression . Contrarpression ,79, HCMVpression . Apart fpression . WhetherBIRC5) expression, a VZV host factor belonging to the family of inhibitors of apoptosis (IAP) [PCBP2) expression, limiting susceptibility of latently infected cells to lytic signals and fostering persistence [FOS), proto-oncogene c-Jun (JUN), and nuclear receptor subfamily 4 group A member 2 (NR4A2) [Apoptosis is perhaps the most primordial response of a host cell to infection, designed to thwart the virus spread. Generally, viruses need to prevent host cell apoptosis to maintain a compartment of infected cells . Howeveris (IAP) . During sistence . This gosistence . MuV is sistence . Finally (NR4A2) .The benefit for a virus to dampen STAT3 signaling lies in controlling antiviral innate immunity responses such as the APR . Many ofCXCL10, ISG15, IFITM1, IRF1, OAS2, and MX1 [+, and CD8+ T cells [reg cells [In contrast to HEV, the KSHV-mediated activation of STAT3 is associated with increased expression of C-C motif chemokine ligand 5 (CCL5) , a poten and MX1 . The vIL and MX1 ,111. vIL and MX1 . Chronic T cells . Analysieg cells ,114. MDSeg cells . Thus, bTGF-β1, TIMP-1) [STAT3 also plays a role in cell morphology, which viruses exploit to promote viral persistence, with grave consequences for host cell physiology . HCV-ind TIMP-1) , eventua TIMP-1) . IAV tri TIMP-1) . EBV is  TIMP-1) . EBV-med TIMP-1) . In acco TIMP-1) .In the cases where STAT3 activity has a proviral or pathogenic effect, blocking STAT3 represents an interesting therapeutic strategy. Unfortunately, no molecule directly targeting STAT3 has received Food and Drug Administration (FDA) approval for any pathology so far , and canIn addition, several natural products such as resveratrol or curcumin have been described to exhibit STAT3 inhibitory properties . ResveraThe multikinase inhibitor sorafenib exhibits an antiviral effect against various HCMV strains by inhibiting the expression of immediate early genes of HCMV at clinically relevant concentrations . HoweverSTAT3 is a key regulator in inflammation and tissue regeneration triggered by almost every pathogenic infection. Therefore, viruses must deal with STAT3 activity by either curtailing it or employing it. STAT3 dependencies of viruses put a spotlight on the diverse role of signal transduction during viral infections and represent a target for potential antiviral strategies. Deregulated STAT3 signaling is an oncogenic driver and is associated with virus-induced complications, including cancers. However, targeting STAT3 during viral infection and cancer is currently an untapped reservoir, and the question still remains as to why it has not yet resulted in a broad range of clinical applications.Currently, unspecific tyrosine kinase inhibitors  and monoclonal antibodies  that block upstream components in the STAT3 pathway are readily administered to patients as cancer chemotherapeutics ,132. SimSeveral natural products targeting STAT3 are currently being explored and seem promising; however, many (including curcumin and resveratrol) have been described as pan-assay interference compounds (PAINs). In other words, it currently cannot be ruled out that the observed effects of these natural compounds are due to an interference with the experimental readout rather than an interaction with their specific targets .STAT3 mRNA that is in early phase I and II studies for advanced solid and hematological cancers [Due to multiple and redundant pathways that converge in STAT3 activation, direct STAT3-targeting agents would be a gold standard to assess the potential benefit of this approach. One reason why we have not observed a breakthrough in STAT3-targeting drugs so far may be that transcription factors are notoriously difficult to target and that many of the STAT3 inhibitors evaluated to date have shown to be problematic regarding their potency, bioavailability, and specificity . Neverth cancers –137, and cancers . The eva


Delphinus delphis). This species is highly social, and exhibits weak spatial genetic structure in the Northeast Atlantic and Mediterranean Sea, thought to result from fluid social structure and low levels of site fidelity. We found that although sampled groups were not composed of closely related individuals, close kin were frequently found in the same geographic location over several years. Our results suggest that common dolphin exhibits some level of site fidelity, which could be explained by foraging for temporally varying prey resource in areas familiar to individuals. Dispersal from natal area likely involves long-distance movements of females, as males are found more frequently than females in the same locations as their close kin. Long-distance dispersal may explain the near panmixia observed in this species. By analysing individuals sampled in the same geographic location over multiple years, we avoid caveats associated with divergence-based methods of inferring sex-biased dispersal. We thus provide a unique perspective on this species’ social structure and dispersal behaviour, and how it relates to the observed low levels of population genetic structure in European waters.Social structure plays a crucial role in determining a species’ dispersal patterns and genetic structure. Cetaceans show a diversity of social and mating systems, but their effects on dispersal and genetic structure are not well known, in part because of technical difficulties in obtaining robust observational data. Here, we combine genetic profiling and GIS analysis to identify patterns of kin distribution over time and space, to infer mating structure and dispersal patterns in short-beaked common dolphins  contains supplementary material, which is available to authorized users. In social animals, patterns of social interactions and kin association are determined by a combination of intrinsic and extrinsic factors, such as intra-specific competition, dispersal behaviour, predator avoidance and food availability. Social structure and dispersal patterns can also be linked with specific mating strategies, often resulting in sex-biased dispersal (Clutton-Brock and Lukas Canis lupus) populations revealed that dispersal of individuals is biased towards habitats similar to their natal habitats , bonobos (Pan paniscus) and hamadryas baboons (Papio hamadryas), where dispersal is female-biased  and killer whales (Orcinus orca), this knowledge has been obtained mostly from population genetic studies  is a well-documented example of this type of social structure. This genus is characterised by a fission-fusion structure, where factors such as age, sex and reproductive status likely influence the social strategies of each individual dolphin  are highly social and are often seen in groups ranging from less than 30 to thousands of individuals  showed no evidence for kinship structure within a group  based on free-ranging animals along the Portuguese coast, which are part of the larger Atlantic population where no studies on social structure have been carried out. Biopsy samples were obtained from multiple groups found in the same locations during multiple years, and kinship patterns were identified using individual multilocus genotypes. Kinship patterns were then analysed in the context of group composition, geographic location and year of sampling. We specifically assessed whether (1) groups of interacting common dolphin individuals are composed of related individuals, (2) individuals are found in the same locations as their close kin over multiple years and (3) kinship level between individuals increases with geographic proximity of locations where they are observed.In this study, we provide an assessment of social structure in short-beaked common dolphin  in five separate locations along the Portuguese coast, separated by approximately 20 to 100 nautical miles. Samples were collected throughout three separate field seasons (2007–2009), although not all locations were sampled in all of the seasons . Simulations also assumed that 80% of parents of both sexes remain unsampled. We considered two confidence levels—strict (95%) and relaxed (80%).In some cases, the parent-offspring pair was identified twice with individual parent-offspring assignment reversed. Because we did not know the age of individuals, it was impossible to know which of these assignments was correct, but for our purposes, it was not necessary to know which individual was a parent and which was an offspring. When such reverse parent-offspring assignments occurred, only one of the results was kept and the match noted. If no parentage was assigned to an individual at either strict or relaxed confidence level, then it was concluded that no parents or offspring of a given individual were sampled.KINGROUP was used as a complementary method of identifying groups of close kin. We used this program to identify the most likely partition of all individuals into groups of kin related at a given level . The full sibship reconstruction (FSR) method was implemented, which partitions the analysed sample set into groups of kin sharing a common relationship. This allows for single-individual groups, which represent those individuals that do not have any relatives at the particular level (e.g. full-siblings), within the dataset. The most likely partition into kin groups is determined by calculating the likelihood that individuals in a group share a hypothesised kinship relationship (the primary hypothesis). Simulations are then used to test if that relationship level is significantly more likely than an alternative relationship (the null hypothesis). Because multiple alternative relationships are often possible, complex null hypotheses were tested. The primary hypothesis that the group consists of full-siblings was tested against the null hypothesis of the relationship at the level of half-siblings to unrelated. The primary hypothesis that the group consists of half-siblings was tested against the null hypothesis of the relationship at the level of cousins to unrelated.Using this method, we reconstructed the partition of the analysed dataset into three kinship classes—full-siblings, half-siblings and cousins. KINGROUP has a limited ability of distinguishing between parent-offspring and full-siblings, so CERVUS parent-offspring pairs were accepted if KINGROUP found them to be related at either a parent-offspring or a full-sibling level.Because KINGROUP identifies groups of individuals at a particular level of relatedness, full-sibling groups may also include parent-offspring pairs , and half-sibling groups may include, e.g. grandparent-offspring pairs . Parent-offspring pairs were distinguished from full-sibling pairs by including an additional condition that they have to share at least one allele at each locus .When comparing the two parents-offspring trio matches to establish the likelihood of an assigned parent being correct, the number of mismatching loci and pair confidence were considered. The putative parent with the least mismatching loci and an assigned confidence level was predicted to be the most likely parent.Kin relationships were then integrated with information regarding sampling group, time of sampling and location of sampling. Specifically, we were interested in determining which of those factors maximised the grouping of related individuals. It should be noted that because of how groups were defined (see earlier), individual groups might have been sampled multiple times in the same day, if found at discrete times of the day.FST between locations, mean FIS and mean pairwise relatedness. If sex-biased dispersal is occurring, then the dispersing sex is expected to have lower mAIc, FST, FIS and mean pairwise relatedness, but higher vAIc.We determined the number of kin groups including individuals sampled in the same day, month and year for each of the three different kinship relationships independently, and compared them to groups containing individuals sampled across different years. The number of kin groups containing individuals sampled exclusively in the same location, was also compared to the number of kin groups containing individuals sampled in different locations. When a group was found to be sampled only in two different locations, we discriminated whether these locations were geographically next to each other or not. Correlation between the number of kin groups and the location was assessed through contingency table analyses, using a Pearson chi-squared test and a Fisher exact test  using the software PAST  geographic information system. This was done only for cousin groups, which reflect wider family relationships and therefore are more appropriate to assess the population level extent of natal dispersal. Furthermore, kin groups of closer relationships were usually composed of too few individuals to allow robust interpolation.−18), as were all probabilities of non-exclusion of parents/siblings . The heterozygosity levels across all loci were high , consistent with the heterozygosity levels described in other studies for common dolphin in the eastern North Atlantic . After excluding those two loci, mean HE and HO were both 0.81. Both values (0.72 and 0.81) are within the ranges identified as giving low rates of kinship misclassification (~5%) in earlier simulation studies , whilst 25 fathers and 21 mothers were assigned with relaxed confidence level (80%). Of all parent-pair assignments, two pairs were assigned with strict confidence, and eight pairs were assigned with relaxed confidence. Although pairs assigned with relaxed confidence are more likely to be false positives, they are likely to represent close kin relationship other than parent-offspring pairs, such as full-siblings.KINGROUP inferred a total of 22 full-sibling groups, 65 half-sibling groups and 25 cousin groups. Comparison with CERVUS results allowed six out of the 22 full-sibling pairs to be identified as parent-offspring matches Table . Full-siOverall, our study sampled 46 different groups of interacting individuals, with an average of 3.9 sampled individuals per group see Fig. . On the Overall, 16 parent-offspring pairs (as identified in CERVUS) were sampled in the same location Table . The remGenerally, kin groups that were composed of more individuals tended to have a larger geographical area where members of the kin group were sampled Table . Only thχ2 = 18.233, p = 0.019), with most kin groups at a level higher than half-siblings (53%) found in the same or neighbouring locations relative to separate locations  were found in two or less locations ; these could be either two neighbouring locations or two separate locations (i.e. locations that were not situated next to each other). Correlation between the number of kin groups and sampling location was significant  but not for female offspring . Fewer mothers were found in the same region as their offspring compared to fathers and their offspring . Consistently, less female offspring were found in the same location as one of their parents than male offspring . For male offspring, most individuals were found in the same or neighbouring locations as their fathers, but in separate locations to their mothers ; however, the geographical distribution of these groups shows that even in such cases, most individuals will be concentrated in only one or two areas Fig. , which wThe results of this study show that common dolphin social groups do not consist of closely related individuals, which is consistent with a previous study on mass strandings , but female kin were mostly found in non-neighbouring, geographically distant locations, indicating that females disperse over longer distances than males on average. This result is consistent with those found in Zanardo et al. , where kF statistics and assignment values, have low power in systems where the sex dispersal asymmetry is low and overall dispersal rates are high  large-scale panmixia in Europe


SNPs) have emerged as a tool for detection of fine‐scale structure. In Hudson Bay, Canada, three polar bear (Ursus maritimus) subpopulations (Foxe Basin (FB), Southern Hudson Bay (SH), and Western Hudson Bay (WH)) have been delineated based on mark–recapture studies, radiotelemetry and satellite telemetry, return of marked animals in the subsistence harvest, and population genetics using microsatellites. We used SNPs to detect fine‐scale population structure in polar bears from the Hudson Bay region and compared our results to the current designations using 414 individuals genotyped at 2,603 SNPs. Analyses based on discriminant analysis of principal components (DAPC) and STRUCTURE support the presence of four genetic clusters: (i) Western—including individuals sampled in WH, SH (excluding Akimiski Island in James Bay), and southern FB (south of Southampton Island); (ii) Northern—individuals sampled in northern FB (Baffin Island) and Davis Strait (DS) (Labrador coast); (iii) Southeast—individuals from SH (Akimiski Island in James Bay); and (iv) Northeast—individuals from DS (Baffin Island). Population structure differed from microsatellite studies and current management designations demonstrating the value of using SNPs for fine‐scale population delineation in polar bears.Defining subpopulations using genetics has traditionally used data from microsatellite markers to investigate population structure; however, single‐nucleotide polymorphisms ( The basis for these subpopulations was inferred by: (i) mark–recapture movement studies, which compared the distance between capture and recapture locations of bears during the onshore period  and used small panels of microsatellite markers and mitochondrial DNA sequence data  and WH (n = 120) from capture–recapture studies conducted by the Ontario Ministry of Natural Resources and Forestry and Environment and Climate Change Canada, respectively. FB (n = 119) and DS (n = 63) samples were provided by the Governments of Nunavut (Department of Environment) and Newfoundland and Labrador (Department of Environment and Conservation) from capture–recapture studies, defense of life and property kills, and subsistence harvest. Capture and handling protocols were consistent with the guidelines of the Canadian Council on Animal Care and approved annually by Animal Care Committees of the Ontario Ministry of Natural Resources and Forestry, Environment and Climate Change Canada, and Quebec Wildlife Department for Animal Care .We used blood and skin samples from FB, SH, and WH polar bears as well as from the adjacent Davis Strait subpopulation (DS) because of its intermediate genetic relationship to the Hudson Bay region and the Canadian Archipelago  following the manufacturers recommended protocol. SNP genotypes were obtained using a custom‐designed , 9K Ill & Davis , Purcell & Davis . There w & Davis ), SH, or2.3To investigate the pattern of population structure, we used discriminant analysis of principal components  and used the diffNgroup option to identify the sharp changes in fit of models (measured using the Bayesian information criterion (BIC)) with different number of clusters   repetitions . STRUCTURE output was analyzed using STRUCTURE HARVESTER version 0.693  plots from STRUCTURE HARVESTER, optimal number of genetic clusters (K) was determined as the smallest value of K that captured the major structure of the dataset while maintaining small differences in likelihoods .For our analyses, an ancestry (Q) cutoff was applied to identify strongly assigned and admixed individuals. Based on the five independent runs of STRUCTURE, individuals were identified as strongly assigned to a cluster if their mean Q was equal to or greater than 0.80. Sampling locations of strongly assigned individuals were plotted to visually assess similarity in geographic sampling location and genetic cluster assignment, and to examine how assignment relates to the site fidelity associated with capture location. These geographic plots were created with ArcMap version 10.1 , and pie graphs depicting the proportion of individuals sampled in each subpopulation that were strongly assigned/unassigned to each of K = 1–10 . Using the cross‐entropy criterion with 5% of genotypes masked, the optimal K‐value was selected based on identification of the single run with the lowest cross‐entropy across 50 total runs.We also examined population structure using the spatial method of TESS3 version 1.0 , expected heterozygosity (HEXP), inbreeding coefficients (FIS), and FST were calculated for capture location  using GenoDive 2.0b27  sampled across the four current subpopulations .K, the BIC plot displayed the lowest value at K = 2. However, the diffNgroups option supported the presence of four genetic clusters in 16 of 20 runs. At K = 4, the first two discriminant functions clearly separated one cluster from the remaining groups . However, K = 4 represented the smallest value of K that captured the majority of the structure in the dataset while maintaining small differences in likelihoods . Examination of the replicated runs of K = 4 showed two nearly equally likely solutions. However, only one solution was well supported when strongly assigned individuals were mapped by capture location .Using STRUCTURE, we observed that the mean likelihood curve had nearly equal, yet increasing, likelihoods from  Figure S. HoweverWe named the four genetic clusters identified by DAPC and STRUCTURE as: (i) Western—including individuals sampled in WH, SH (excluding Akimiski Island in James Bay), and southern FB (south of Southampton Island); (ii) Northern—individuals sampled in northern FB (Baffin Island) and DS (Labrador coast); (iii) Southeast—individuals from SH (Akimiski Island in James Bay); and iv) Northeast—individuals from DS (Baffin Island).K‐value of three , which corresponds to the identified Western, Northern, and Southeast genetic clusters. Samples from the Akimiski Island of James Bay region showed isolation from the other two genetic clusters .The cross‐entropy criterion implemented in TESS3 does not differentiate between DAPC identified Northern and Northeastern clusters. However, the TESS analysis did support a distinction between north of Southampton Island to the east and DS. Findings indicate FIS estimates and tests were not performed for genetic clusters as the removal of admixed individuals results in an unequal sample size for comparison to values calculated using capture locations. In addition, STRUCTURE derived clusters that include strongly assigned individuals will by definition have lower inbreeding coefficients. We found more inbreeding than expected in SH, FB, and DS and the opposite to be true in WH. Each showed significant departures from Hardy–Weinberg equilibrium . Allelic richness was high in each of the genetic clusters, whereas the private allelic richness was low across genetic clusters , STRUCTURE, and geographic concordance of individual genetic assignments in relation to capture locations . However, implementation of the diffNgroup option, which automates cluster identification by considering sudden rates of change in BIC values between a different number of clusters, found four groups. This method has been used previously to define groups in extant Mimulus species . These groups correspond to the Western and Southeast clusters and then a single group combining the Northern and Northeast clusters. The analysis indicates spatially a division north of Southampton Island. It is important to note that TESS directly incorporates spatial information when determining the number of genetic clusters in a dataset. Therefore, given that the er Table  and thater Table  hypothes4.2Our conclusions regarding the number of genetic clusters and their geographic locations differ from previous studies. These differences may be attributed to the larger number of markers, greater sample sizes, and more even distribution of sampling across the landscape used in our study. In particular, our sampling was continuous and evenly distributed within SH, a subpopulation that was not included in Paetkau et al.  and was K = 2  and spatially by TESS3  demonstrates this first degree of differentiation, grouping WH, SH, and southern FB in one cluster and northern FB, and DS in a second. Thus, suggesting the Canadian Archipelago ancestry is the strongest signal within the region.However, although different from previous studies our results are in line with the structure they highlighted. The initial research by Paetkau et al.  suggesteK = 4 in the Hudson Bay region.Previous evidence of fine‐scale structure in the Hudson Bay region was found by Crompton et al. , 2014, P4.3The presence of genetic structure in polar bears could be a result of geographic features such as polynyas or landmasses that can act as barriers to gene flow  Slatkin, , and canFST estimates SNP data are available on Dryad (doi:  Click here for additional data file.


Previous studies have demonstrated variations in volatile compound content during fruit spoilage. Infrared spectroscopy was proposed as an alternative method to discriminate the various states of decayed fruit through the makeup of their volatile compounds. Based on the infrared spectra of volatile compounds obtained from decayed grapes, this study simplified the extraction of their feature spectra and visualized their gas plumes by using a commercial infrared thermal camera equipped with a custom-made wavelength filter. As a function of volatilization gradients, accumulated gray value and imaging area were proposed as indicators for semi-quantitative analysis in a volatilization range similar to that of ethanol solutions ranging from 10% to 70%. Fresh, seriously decayed, and slightly or moderately decayed grapes were rapidly discriminated through their alcoholic volatiles by thermal images with correct classification ratings of 100%, 93.3%, and 90%, respectively. Table grapes deteriorate rapidly during postharvest storage. Loss of quality accompanied with berry decay of table grapes during storage reduces their shelf-life and compromises food safety in marketing . Thus, aIn general, fruits contain specific volatile compounds, and the types or ratios of the compounds vary during berry development and deterioration –4. Thus,In recent years, gas plume visualization has been achieved by using an imager paired with a filter based on the specific wavelength band of the gas of interest –17. This-1. A series of nine ethanol solutions (10–90% v/v) were prepared by dilution of 75% or 95% ethanol solution with deionized water. A 100-ml portion of each diluted ethanol solution was transferred into a 150-ml transparent plastic container for measurements.Jufeng grape cultivar. It is commercially available and was obtained from a fruit chain store (Guo Xiang Si Ye) located close to the Beijing Academy of Agriculture and Forestry Sciences (BAAFS), Beijing, China. Fresh grape berries (108.6±6.0 g) with short stems (about 0.5 cm) were stored in 150-ml plastic containers (as used for ethanol solutions) at 18°C for days to reach different spoilage stages classified as: 1) fresh (FR), stored for 1–3 days; 2) slightly decayed (SL), stored for 4–6 days, visually intact except for stem browning; 3) moderately decayed (MO), stored for 7–9 days, visually softened, some with mildew stains at stem joints; 4) seriously decayed (SR), stored for 10–12 days, berries were visually juicy and some were cracked. Normally, grapes without any treatment will be seriously decayed within 7 days at room temperature [Experiments in this study used the  berries 8.6±6.0 gImages of the grape samples at different spoilage stages are shown in Vapors from ethanol solutions were monitored by an IR camera as a feasibility analysis prior to the measurements of table grapes. Sample containers containing ethanol solutions or grape berries were placed in front of the blackbody to obtain thermal images before and after the container caps were removed. Prior to the recording of images, samples were shaken (caps on) to improve gas diffusion. The measurement of each spoilage stage of grapes used 15 replicates, while each concentration of ethanol solutions used 5 replicates. During the measurements, the air temperature was 19.8 ± 1.8°C and the humidity was 39 ± 5%.Thermal images taken before and after the container caps were removed (cap-on and cap-off) were adjusted to the same background in a temperature span of 2°C by FLIR QuickReport (version 1.2) software. Because of the absorption of cold gases, radiation from the blackbody was expected to be attenuated when the caps were removed . Thus, vT-test were used for statistical analysis by the Matlab software (version 7.0). Classification of grapes in different spoilage stages was performed by Euler Clustering using Unscrambler software (version 9.7). Error bars in this study represent the standard errors.Considering the central 160 × 190 region in the gas plume images, the accumulated gray value (AGV) and the actual imaging area (AIA) in the region were defined and calculated for data analyzing. AGV was defined as the sum of the gray value in each pixel before image amplification. AIA was defined as the total number of pixels with a gray value over zero. Based on AGV and AIA in the gas plume images, analysis of variance (ANOVA) and Alcohols make up a large proportion in the volatile compounds released from decayed grapes , 19 and False color images of the ethanol vapors released from the different solutions are shown in P < 0.05).P < 0.05). This indicates that the effective detection range of thermal imaging used in this study may cover the volatilization range of ethanol solutions from 30% to 70%.According to Raoult's law , 21, a hCurve fitting of averaged AIA in gas plume images is shown in In summary, alcohol vapors, particularly that of the ethanol, can be effectively monitored and semi-quantitatively analyzed by thermal imaging. Base on AGVs and AIAs in the images of gas plumes, the upper and lower detecting limitations were similar to the volatilization of ethanol solutions ranging from 70% down to 10%.After acquiring gas plume images from ethanol solution, volatile compounds from grapes at different spoilage stages were monitored by the same experimental set-up. Data obtained from the gas plumes of ethanol solutions provided crucial criteria for monitoring and analyzing the volatiles from grapes by thermal imaging.P < 0.05), which was less than 1.0 × 103 . When compared with slightly or moderately decayed grapes, seriously decayed grapes had a much higher AGV (P < 0.05). The averaged AGV for seriously decayed grapes was 4.9 × 104, which is close to that observed for 30% and 40% ethanol solution Click here for additional data file.S2 Table(DOC)Click here for additional data file.S3 TableFR, SL, MO and SR in the table represent fresh grapes, slightly decayed grapes, moderately decayed grapes and seriously decayed grapes, respectively.(DOC)Click here for additional data file.


Pecten maximus) from nine populations around Northern Ireland at 13 microsatellites and 10 539 SNPs. The shells were then subjected to morphometric and colour analysis in order to compare patterns of phenotypic and genetic variation. We found that RAD sequencing was superior at resolving population structure, yielding higher Fst values and support for two distinct genetic clusters, whereas only one cluster could be detected in a Bayesian analysis of the microsatellite dataset. Furthermore, appreciable phenotypic variation was observed in size-independent shell shape and coloration, including among localities that could not be distinguished from one another genetically, providing support for the notion that these traits are phenotypically plastic. Taken together, our results suggest that RAD sequencing is a powerful approach for studying population structure and phenotypic plasticity in natural populations.The field of molecular ecology is transitioning from the use of small panels of classical genetic markers such as microsatellites to much larger panels of single nucleotide polymorphisms (SNPs) generated by approaches like RAD sequencing. However, few empirical studies have directly compared the ability of these methods to resolve population structure. This could have implications for understanding phenotypic plasticity, as many previous studies of natural populations may have lacked the power to detect genetic differences, especially over micro-geographic scales. We therefore compared the ability of microsatellites and RAD sequencing to resolve fine-scale population structure in a commercially important benthic invertebrate by genotyping great scallops ( For exaet al. )Although the latter studies are suggestive of phenotypic plasticity, the inability to reject the hypothesis of population differentiation is strictly speaking not proof that there are no genetic differences between populations. We attempted to overcome this issue by increasing the genetic resolution from the 10 or so microsatellites typical of most studies to over 10 000 SNPs and by using a modern morphometric approach capable of providing highly detailed size-independent characterization of shape variability. Having done so, we still found no clear evidence for genetic structure after having excluded Mulroy Bay , which lends stronger than usual support to the hypothesis that shell shape and colour have a plastic component. Nevertheless, phenotypic differences need not necessarily reflect genome-wide divergence, because local adaptation can still potentially occur even under high levels of gene flow . Thus, i5.We compared the ability of microsatellites and RAD sequencing to resolve fine-scale population genetic structure in a benthic invertebrate, the great scallop. Our results lend support to previous simulation and empirical studies by showing that even with as few as five individuals per population, RAD sequencing is capable of detecting population genetic structure where a standard panel of microsatellites struggles. Furthermore, a number of populations that exhibited significant phenotypic differences could not be distinguished from one another genetically, suggesting that shell shape and coloration are likely to be phenotypically plastic.


Dioscorea sp.) are staple food crops for millions of people in tropical and subtropical regions. Dioscorea alata, also known as greater yam, is one of the major cultivated species and most widely distributed throughout the tropics. Despite its economic and cultural importance, very little is known about its origin, diversity and genetics. As a consequence, breeding efforts for resistance to its main disease, anthracnose, have been fairly limited. The objective of this study was to contribute to the understanding of D. alata genetic diversity by genotyping 384 accessions from different geographical regions , using 24 microsatellite markers. Diversity structuration was assessed via Principal Coordinate Analysis, UPGMA analysis and the Bayesian approach implemented in STRUCTURE. Our results revealed the existence of a wide genetic diversity and a significant structuring associated with geographic origin, ploidy levels and morpho-agronomic characteristics. Seventeen major groups of genetically close cultivars have been identified, including eleven groups of diploid cultivars, four groups of triploids and two groups of tetraploids. STRUCTURE revealed the existence of six populations in the diploid genetic pool and a few admixed cultivars. These results will be very useful for rationalizing D. alata genetic resources in breeding programs across different regions and for improving germplasm conservation methods.Yams ( Dioscorea sp.) are important food security crops for millions of small-scale farmers in the tropical and subtropical regions of Africa, Asia, the Pacific, the Caribbean and Latin America [Dioscorea alata (known as the "greater yam" or the "winged yam") is one of the major cultivated species with wide geographical distribution [D. rotundata in production volumes. Several traits of D. alata make it particularly valuable for commercial cultivation. These include high yield potential, ease of propagation, early growth vigour for weed suppression, and long storability of tubers [Yams  with 431 accessions. In addition, several international collections have been assembled, including those of the CRB-PT  and the IITA , with 181 and 772 accessions of D. alata, respectively.A wide diversity also exists in India , 29 wherD. alata from different regions  using enzymatic markers. However, the weak polymorphism of the four enzymatic systems did not reveal correlations between the groups of zymotypes and the geographic origins, ploidy levels and/or the phenotypic characteristics of the accessions.Lebot et al.  evaluateD. alata collections, including RAPDs [D. alata involved a limited number of cultivars, and none was conducted at the global scale.Various molecular markers have been used to characterize the genetic diversity of the ng RAPDs , AFLPs [ng RAPDs  and SSRsng RAPDs , 33, 34.ng RAPDs , 36. NevDioscorea alata accessions from different regions, including the South Pacific, Asia, Africa and the Caribbean using a common set of 24 microsatellite markers.The aim of the present study was to analyze the genetic diversity and population structure of 384 D. alata accessions originating from four collections were evaluated . Overall, the germplasm was composed of 298 diploids, 51 triploids and 35 tetraploids. Ploidy levels of most accessions were determined in previous studies [Overall, 384 valuated . These i studies , 11, 31  studies .Genomic DNA of the accessions was isolated in each institute using the DNeasy Plant Mini Kit  or the modified CTAB method as described by Sharma et al. .D. abyssinica, D. praehensilis, D. japonica and D. alata, were selected to analyze the accessions. Eleven primers were chosen based on their capacity to reveal high polymorphism and easy-to-score profiles (not stuttering) from a previous study . The remaining thirteen were newly identified SSRs from D. alata [Twenty-four SSR primer pairs  developeD. alata . Microsa-Ferrand). Each locus was fluorescently labeled by M13 tail as described by Vallunen [TM, VICR, NEDTM and PETR). The PCR amplifications were performed in a 10 μL final volume containing final concentrations of 1X AmpliTaq Gold 360 Master Mix (AB-life technologies), 0.05 μM labeled forward primer, 0.5 μM reverse primer and 25 ng of template DNA. For all loci the same PCR program was used, consisting of an initial denaturation at 95°C for 10 min followed by a touchdown PCR consisting of 45 cycles with denaturation at 95°C for 30 s; annealing for 30 s with temperature decreasing 1°C every cycle from 62°C to 56°C (7 cycles), then 30 cycles at 55°C and 8 cycles at 56°C; and a final extension at 72°C for 5 min. Two to four individual PCR products labeled with different fluorochroms were multiplexed and visualized using capillary gel electrophoresis on an ABI PRISM 3100 DNA sequencer .PCR amplifications and gel electrophoresis were carried out on the GENTYANE genotyping platform  or absence (0) of alleles for each microsatellite locus per accession. The following genetic parameters were estimated: number of alleles per locus, number of rare alleles with a frequency lower than 1% , highestIn order to compare accessions and their relationships, we calculated genetic distances between each pair of accessions with Dice dissimilarity coefficients , using tD.alata accessions. We used the Darwin software [Indeed, since our study sample includes cultivars with three different ploidy levels (from diploids to tetraploids) whose parental contributions are unknown, we performed a Principal coordinate analysis (PCoA) to explore the diversity structure of all software . This mesoftware .We also carried out a cluster analysis for diploid accessions only using the UPGMA algorithm and the Dice similarity coefficient, using the NTSYSpc software version 2.1 . Reliabiq) derived from the different clusters. So, individuals which may have mixed ancestry could be identified. In order to identify the number of populations (K) capturing the major structure in the data, we used the admixture model with a burn-in period of 30,000 steps and 106 MCMC (Markov Chain Monte Carlo) replicates. The number of clusters (K) evaluated ranged from 1 to 10. The analysis was performed using three independent runs for each simulated value of K. We then calculated ΔK [Population structure of diploids was also examined using a Bayesian approach using the software STRUCTURE V.2.3 . This molated ΔK , an ad-hlated ΔK .Seventeen accessions presenting more than 25% of the missing data were removed from the analyses. The total number of accessions analyzed was 367, including 77 from India, 67 from Vanuatu, 89 from Caribbean, 87 from Africa, 13 from New Caledonia and 7 from French Guyana.The analysis of 24 SSRs across 367 accessions allowed the identification of 256 alleles , with thD. alata. Nine loci showed a significant heterozygote deficit while two loci presented significant excess. Overall, a slight heterozygote deficit was observed across all accessions .Genetic diversity (expected heterozygosity) values ranged from 0.20 to 0.86 and the observed heterozygosity from 0.16 to 0.90. The mean genetic diversity of 0.66 indicated moderate to high levels of polymorphism in The Dice dissimilarity coefficients between all possible pairs of genotypes ranged from 0 and 0.86. Individuals with a distance of zero had the same alleles over the set of 24 loci and may be considered as possible duplicates. Several duplicates were detected  in each The population structure was first inferred by Principal coordinate analysis (PCoA) on all 376 accessions based on 256 alleles. The first two axes explained 57% of the genetic variability .P < 0.0001).Results showed that the accessions originating from India are primarily distributed in the lower part of the graph, whereas the accessions from Vanuatu are mainly distributed on the upper right-hand side  revealinThe accessions of the international collections (IITA and CRB-PT) are distributed almost everywhere on the PCoA, showing that the diversity observed in India and in Vanuatu is well represented in CRB-PT and partially represented in IITA . PCoA alThe 83 polyploid cultivars from the four collections  represented identical profiles across all 24 SSR loci  and can be considered as duplicates. This group included the Florido variety selected by Martin and Rhodes  in MayagGroup X assembled 15 cultivars including 9 from Africa, five from India and one from Caribbean. Group III included 12 cultivars, eight of which are from Vanuatu, one from New Caledonia and three from Caribbean. This group represents accessions known and cultivated in the Caribbean under the names of Kabusa and Lupias. The eight cultivars from Vanuatu were classified by Malapa .Groups V and VI presented each 12 cultivars belonging to one collection. Group V is composed exclusively of cultivars from India and Group VI of cultivars from Vanuatu. Cultivars of group VI were classified in the morphotype convar M7 by Malapa . They arGroup II contained 9 cultivars five of which were from Africa and four from the Caribbean region. This group is composed of cultivars known and cultivated in the Caribbean under the names of Kinabayo and Oriental that produce female flowers. Cultivar Oriental was resistant to anthracnose in Guadeloupe  and was Group IX also assembled nine accessions of which eight are from India and one from Caribbean. Group XI assembled six cultivars from Vanuatu that were classified in the morphotype group, Convars M4 . They arThe remaining 82 diploids (61 cultivars and the 21 breeding lines) were either not grouped or clustered in small groups containing two to four cultivars.A total of four triploid groups were identified based on PCoA and genetic distances analysis . The larGroup XIII included six cultivars of which three are from New Caledonia, two from Africa and one from Vanuatu. This group includes accessions known in the Caribbean under the name of Goana. All cultivars belonging to this group have a characteristic allelic profile with three alleles at loci L31 (257 bp-261bp-265bp) and L30 (224bp-230bp-234bp), which is specific to this group. Group XV and XIV were the smallest and contained four and three accessions, respectively.Two tetraploid groups were identified based on PCoA and genetic distances analysis . The larGroup XVII included six cultivars of which one was from New Caledonia and five from Vanuatu. These cultivars were classified by Malapa  in the mΔk for K = 6 supporting the presence of six genetically distinct populations (K = 6), here denoted as P1, P2, P3, P4, P5 and P6, respectively . The Evanno’s method showed a peak of ectively . Overallectively . The resD. alata using microsatellite markers. Several other studies on genetic diversity have been conducted on this species using different types of molecular markers including random amplified polymorphism DNAs [D. alata originating from the South Pacific, Asia and the Caribbean using isozymes. However, due to low polymorphism of these markers, no relationships could be established between these accessions.This study represents the first approach that comprehensively investigates the genetic diversity within different large collections of ism DNAs , 55, ampism DNAs , 56, 57 ism DNAs , 58. Howism DNAs  evaluateD. alata cultivars (H’ = 0.41). The diversity level detected in this species is also higher than what is reported in 146 D. rotundata cultivars (H’ = 0.50) [Microsatellite markers were effective for identifying polymorphism and for evaluating the genetic relationships between the 367 accessions analyzed. Regarding all 24 SSRs loci investigated, the estimated diversity index (H’ = 0.66) was found to be high. Genetic diversity detected in this study is much higher than the one reported by Siqueira et al.  for 89 B = 0.50) .D. rotundata, whose center of origin is known and domestication is well documented [D. alata is actually not known yet. This species is supposed to have been domesticated in Southeast Asia [Our results revealed the existence of two divergent genepools in India and Vanuatu. In contrast to African species cumented , 62, 63,ast Asia  about 60ast Asia .D. alata in Africa and in New World takes place later in the 15th and 16th century. According to Prain and Burkill [th century. Degras [th century with the slave trade.The introduction of  Burkill  this spe. Degras  argued tPCoA and UPGMA analysis revealed a clear separation of the accessions into 17 major groups of genetically close cultivars, including eleven groups of diploids, four groups of triploids and two groups of tetraploids.Two of the diploid groups assembled only cultivars from Vanuatu (VI and XI) and one group exclusively from India (V). The other diploid groups included cultivars from several geographic regions. Among these two included cultivars from India (I and X) and two from South Pacific (III and VII). One group (IV) assembled accessions from all geographic origins analyzed . It included six cultivars from three different geographic origins  which are genetically identical across 24 loci. The results indicate that farmers adopt good yam cultivars with superior attributes readily and these eventually get widely distributed.The four triploid groups included cultivars from several geographic regions. Three groups consisted of cultivars from Vanuatu and one had cultivars from India. The biggest group (XII) included cultivars that have been largely diffused . One group (XIV) included only cultivars from South Pacific . Group XIV assembled cultivars from Africa and South Pacific , while group XV included cultivars from Caribbean and Vanuatu.Both tetraploid groups contained cultivars from several geographic regions, except from India. Group XVI included cultivars from Africa and South Pacific  and Group XVII assembled cultivars only from South Pacific .D. alata cultivars originating from Africa and from the New World (Caribbean and South America) are genetically very similar to Asian and/or South Pacific cultivars.Our results demonstrated a high degree of differentiation within this highly heterozygous species, probably due to limited gene flow, primarily restricted by the mating system of this species. This work showed also that Dioscorea alata cultivars are exclusively vegetatively-propagated and present a low fertility. Two different hypotheses could explain this structuration in several groups of genetically close cultivars:The reproductive system is one of the important life-history characteristics that strongly influence genetic variability . DioscorAccessions belonging to the same group are the outcome of former sexual events with the same parents or genetically related parents.Accessions belonging to the same group are the outcome of the same initial clone that evolved via somatic mutations fixed by vegetative propagation.−3 and 10−6, depending on the species and on their position in the genome [D. alata. The low number of allelic differences between cultivars assembled in group III, suggests the most likely hypothesis that this group was created from a single initial clone that evolved through mutations. Indeed, the number of allelic differences within this group corresponds to a total of 1 to 7 mutations, which is consistent with this hypothesis, on the basis of a mutation level of 10−3–10−4.Given the mutational rate of SSR markers (between 10e genome ) and theIn contrast, the number of alleles differentiating the cultivars reassembled in other groups (ex: groups IV and VI) is higher to explain their origin from only an initial genotype. So, the most likely hypothesis is that these groups were created from several genetically related clones, which evolved through somatic mutations over time.D. alata cultivars in Vanuatu [D. alata appears to be rare in farmers’ fields and makes the diversification of local cultivars by selecting spontaneous seedlings difficult. However, farmers can detect somaclonal variants and propagate them. The high genetic variability observed between D. alata cultivars in Vanuatu is thought to be the results of multiple introductions of genetically distant individuals. The role of sexual reproduction and mutation in shaping the diversity has also been well documented for D. rotundata species [Our results are congruent with those obtained with DArTs to study the origin of  Vanuatu . The low Vanuatu . However species .Varietal diversity can be increased by controlled pollinations and breeding new cultivars and this has proven to be an effective way of genetic improvement , 23, 68.D. alata genetic resources existing in Asian and South Pacific countries are still necessary in order to apprehend the genetic diversity available in these regions and allow their preservation and valorization in breeding programs.Much larger evaluations of Microsatellite markers and a worldwide sample material proved to be effective for identifying polymorphism and for evaluating genetic relationships between yam varieties, clarifying relationships between genetic diversity, geographic origins, and ploidy levels.We did not identify any center of origin for this crop, but we demonstrated in our study the existence of two diversification pools, one from Vanuatu, and the other from India. High diversity levels were found in international germplasm collections, with CRB collection spanning throughout worldwide genetic diversity, while IITA collection was spanning a lesser extent but targeted more specific diversity component of variation for this species, possibly reflecting a finer sampling scheme.S1 TableIdentified groups based on PcoA and UPGMA analysis are also indicated.(XLSX)Click here for additional data file.


Adh2 sequence variation in a diverse sample of maize landraces from lowland middle South America, and performed a comprehensive integrative analysis of population structure and diversity including already published data of archaeological and extant specimens from the Americas. Geographic distribution models were used to explore the relationship between environmental factors and the observed genetic structure.Maize landraces from South America have traditionally been assigned to two main categories: Andean and Tropical Lowland germplasm. However, the genetic structure and affiliations of the lowland gene pools have been difficult to assess due to limited sampling and the lack of comparative analysis. Here, we examined SSR and Adh2 locus and the distinct spatial pattern inferred from geographic distribution models.Bayesian and multivariate analyses of population structure showed the existence of two previously overlooked lowland gene pools associated with Guaraní indigenous communities of middle South America. The singularity of this germplasm was also evidenced by the frequency distribution of microsatellite repeat motifs of the Our results challenge the prevailing view that lowland middle South America is just a contact zone between Andean and Tropical Lowland germplasm and highlight the occurrence of a unique, locally adapted gene pool. This information is relevant for the conservation and utilization of maize genetic resources, as well as for a better understanding of environment-genotype associations.The online version of this article (doi:10.1186/s12870-016-0874-5) contains supplementary material, which is available to authorized users. Zea mays L. ssp. mays) was domesticated from its wild relative, the teosinte Zea mays ssp. parviglumis Iltis & Doebley, in the lowlands of south-western Mexico during the early Holocene, whence it spread rapidly northwards and southwards across America [There is general consensus that maize ( America –4. In So America . In thisAdh2) in archaeological maize specimens, which revealed an east–west partitioning of allele frequencies. These studies provided evidence of two separate expansion events in South America; one occurring from the highlands of Central America into the Andean region, and the other from the alluvial regions of Panama into the lowlands and then along the northeast coast of the continent [Based on the cytogenetic analysis of South American landraces, McClintock et al.  suggesteontinent .More recently, Vigouroux et al.  inferredKnowledge of the structure of genetic variation in present-day maize landraces, and how it is related to their geographical distribution, provides valuable insights for reconstructing dispersal routes. Maize landraces from the highlands of South America  have emerged repeatedly as a distinct entity, as evidenced by morphological, cytogenetic and molecular data , 9, 10. Recent research concerning the population dynamics of maize landraces has also provided evidence for a highland-lowland genetic structuring pattern. Bracco et al.  conducteRegardless of what the most plausible hypothesis of maize dispersal may be, it is undisputed that its spreading was accompanied by a remarkable adaptation to heterogeneous environmental conditions , 16, 17.Adh2 microsatellite sequences were obtained from representative individuals of NWA and NEA to allow comparison with the archaeological and extant specimens from southern South America studied by Freitas et al. [Herein we provide a comparative framework to analyse maize diversity and clarify the relationships among lowland South American gene pools. For this purpose, the sampling conducted by Bracco et al.   were genotyped on 232 individuals from the Argentinean provinces of Chaco, Corrientes, Entre Ríos, Formosa and Misiones .To fully represent the racial diversity of maize in NEA and to complement the data presented by Bracco et al. , 10 SSR To put the SSR data in a continental context, our dataset was analysed in combination with those of Bracco et al. , Lia et Allele size equivalences between maize landraces from NWA and those of Matsuoka et al.  were det−14 and probability of identity among siblings of 4.7 × 10−5. Analyses were performed using K values from 1 to 10, 10 replicate runs per K value, a burn-in period length of 105 and a run length of 106. No prior information on the origin of individuals was used to define the clusters. All the analyses were run under the correlated allele frequency model [K value. A measure of the second order rate of change in the likelihood of K (ΔK) [density function of R 3.0.2 (R Core Team 2014).Genetic clusters were inferred using the Bayesian approach implemented in STRUCTURE 2.3.4 . Howevercy model . The runf K (ΔK)  was calcf K (ΔK) . An indif K (ΔK) . The modf K (ΔK)  was applf K (ΔK) . A graphdapc was executed by retaining 150 principal components, which accounted for 96 % of total genetic variation and five discriminant functions, and using the clusters identified by the K-means algorithm [find.clusters, with n.iter = 1000000 and n.start = 25, evaluating a range from 1 to 40.Population structure was also examined by the Discriminant Analysis of Principal Components (DAPC) , using tlgorithm . The numper locus (A), allelic richness (Rs) [He) [Diversity indices were calculated for the genetic clusters inferred by Bayesian analysis, using only individuals unequivocally assigned to their respective clusters (Q > 0.80). The mean number of alleles ess (Rs)  and geneRs) [He)  were estRs) [He) . The preRs) [He) . File coRs) [He) .Differentiation between STRUCTURE groups was assessed by the Allele frequency divergence estimate provided by the software. Cluster analysis was carried out applying the Neighbour-joining algorithm  implemenAdh2 microsatellite region  included part of the 5’ untranslated promoter region, the exons 1 and 2, and the intervening intron. PCR primers were designed with the Primer3 software 0.4.0 [Individuals of 16 landraces from Northern Argentina (NWA + NEA) were sequenced for the re 0.4.0 : upstreare 0.4.0 , and there 0.4.0 . To detere 0.4.0 . Bands fre 0.4.0 . Both stAdh2 microsatellite alleles derived from the archaeological landraces examined by Goloubinoff et al. [Adh2 sequences retrieved from GenBank corresponding to Brazilian and Bolivian landraces . The compiled data set (N = 497) was divided into three allele types following Freitas et al. [n, (GA)nTA and GAAA(GA)n.The data gathered were analysed together with f et al. , Freitasf et al.  and Grimf et al. , under tf et al.  and Grimf et al. , and froStatistical associations between allele types and geographic regions were evaluated with the likelihood ratio Chi-square test implemented in Infostat software 2013 .https://www.cs.princeton.edu/~schapire/maxent/). This program uses presence-only data in the form of geo-referenced occurrence records, and a set of environmental variables to produce a model of the distribution range of the species under study. The raw and logistic outputs of MaxEnt are monotonically related and can be interpreted as an estimate of habitat suitability [Geographic distributions were modelled using the Maximum Entropy method , implemetability , 46.http://www.worldclim.org/) [We modelled the geographic distribution of the genetic groups retrieved from Bayesian clustering, considering only individuals with Q > 80 %. Following the guidelines provided in Scheldeman & van Zonneveld , a minimim.org/)  at 2.5 aim.org/) . By defaim.org/) . In addiim.org/) . Becauseim.org/) ; thus, wim.org/) , 51.I statistic of Warren et al. [D [Model performance was assessed using the area under the receiver operating characteristic curve (AUC)  for bothn et al.  and Schot al. [D  as implet al. [D  includedhttp://www.diva-gis.org/Data.All the maps used in this study were freely available at K (LnP(D)) and the rate of change in the log likelihood of the data between successive K values (∆K) , and two of the main groups previously described for South America by Vigouroux et al. [Bayesian population structure analysis of the complete SSR data matrix  supported the existence of five distinct genetic clusters, as inferred from the joint assessment of the log-likelihood of the data conditional on Analysis of STRUCTURE outputs showed that membership coefficients (Q) in a given cluster were higher than 0.80 for 79 % of the individuals. Following this criterion, 145 individuals were assigned to HM-US, 275 to Andean, 157 to Tropical Lowland, 344 to NEA Flours, and 99 to NEA Popcorns, whereas 268 (21 %) were classified as admixed  and HM-US (mean F = 0.038) as the most similar to a common hypothetical ancestor, followed by the Andean (mean F = 0.087), whereas the NEA Flours (mean F = 0.172) and the NEA Popcorns (mean F = 0.539) appeared as the most divergent groups  to 0.236 (HM-US vs. NEA Popcorns) , Middle Southern South America , and Eastern South America . The MSSA region encompasses NEA and adjacent areas of Paraguay, Bolivia and western Brazil, whereas the ESA region encompasses northern, central and eastern Brazil.To assess whether the marked differentiation detected for the NEA groups in the SSR analyses was in agreement with the ancient structuring pattern reported by Freitas et al. , we examAdh2 microsatellite dataset (N = 497), with the most frequent being (GA)n, (GA)nTA, and GAAA(GA)n  and between the MSSA and ESA regions . Conversely, differences between MSSA and the Andean region were non-significant.Six microsatellite allele types were recognised in the compiled The bounded geographic distribution of the genetic clusters identified here prompted us to investigate whether the observed genetic structuring was accompanied by distinct environmental requirements, especially for lowland germplasm. Habitat suitability models were obtained for four of the genetic clusters inferred by STRUCTURE, using two feature settings. Occurrence locations are given in Additional file Geographic distribution models produced by averaging cross-validation replicates are presented in Fig. The variables with highest average relative contribution are summarised in Table Pairwise comparison of I and D indices applied to habitat suitability distributions revealed significantly different model predictions for each group Table .Table 3COur results reveal the occurrence of three clearly distinct gene pools in the lowlands of South America, namely: Tropical Lowland, NEA Flours and NEA Popcorns. Although Vigouroux et al.  recognisBoth the Bayesian and DAPC methods show a clear separation among the NEA Flours, NEA Popcorns and the remaining clusters. Although DAPC inferred a larger optimal cluster number, the groups obtained are compatible with those from STRUCTURE since they represent subdivisions within the latter. These findings are consistent with the higher sensitivity of DAPC for detecting substructure in hierarchical models . NotwithAs mentioned before, the composition of the Tropical Lowland cluster obtained in our analysis is similar to that reported by Vigouroux et al. , includiZea mays ssp. mexicana [The levels of diversity constitute an important factor in interpreting the high differentiation of the NEA groups. If these would have derived from any of the major groups in relatively recent times and then subjected to isolation by cultural or environmental factors, one would expect the diversity levels to be low and the allelic variants to be a subset of the original gene pool. Our analysis of diversity indices revealed that the variability levels of the NEA Flours were similar to those of the Andean group, whereas the NEA Popcorns had the lowest estimates Table . Moreovemexicana . In summAdh2 microsatellite allele types considered here revealed that statistically significant differences were found between ESA and MSSA, and between ESA and Andean regions. Since most of the data were collected from the literature, we could not establish a direct link between the geographic origin of all the individuals included in the analysis and their membership to any of the genetic groups inferred from our SSR analysis. However, the differences in the distribution of Adh2 microsatellite motifs between ESA and MSSA provide additional evidence favouring the existence of two distinct genetic groups in the lowlands of South America, with NEA Flours and NEA Popcorns sampling localities being contained within the boundaries of the MSSA category. On the other hand, the homogeneity found between Andean and MSSA is in agreement with the view of previous authors that Andean germplasm had an influence on the landraces of middle South America [The frequency distribution analysis of the  America , 8, 10.Adh2 microsatellite variability, the inferred genetic groups from the lowlands of South America, i.e. Tropical Lowland and NEA Flours, also showed significantly different habitat suitability models, not only between each other but also with the other gene pools , though they seem to be affected differently by the rainfall regime, with a greater impact on NEA Flours. Altitude appears as a determinant factor for HM-US and Andean Table , but witLike in our study, Hufford et al.  found thIn addition to our results of genetic and distribution modelling, diverse sources of evidence support the existence of a particular maize group from lowland middle South America. Most of the landraces of NEA Flours and all of the landraces of NEA Popcorns were collected from the Guaraní indigenous communities settled in the province of Misiones, Argentina. In contrast, NEA landraces collected outside these communities and currently maintained in the Germplasm Bank of INTA Pergamino, appeared to be greatly influenced by the Tropical Lowland gene pool Fig. . In accoDifferent authors have proposed middle South America as a contact region where the Andean landraces interbred with those of the eastern coast of South America , 11. How


Pelophylax) in southern France, through a fine-scale genetic survey. We identified three different taxa over less than 200 km2: the autochthonous P. perezi, along with the alien P. ridibundus and P. kurtmuelleri, which have suddenly become invasive. As a consequence, the latter hybridizes and may now form a novel hybridogenetic complex with P. perezi, which could actively promote its replacement. This exceptional situation makes a textbook application of genetics to early-detect, monitor and understand the onset of biological invasions before they pose a continental-wide threat. It further emphasizes the alarming rate of amphibian translocations, both at global and local scales, as well as the outstanding invasive potential of Pelophylax aliens.The genetic era has revolutionized our perception of biological invasions. Yet, it is usually too late to understand their genesis for efficient management. Here, we take the rare opportunity to reconstruct the scenario of an uprising invasion of the famous water frogs ( The efficient management of invasive amphibians primarily requires their early detection, proper identification and the long-term monitoring of their expansions. However, these steps can be challenging if introduced species are undistinguishable from related autochthonous taxa, with which they even often hybridize . This group involves multiple taxa distributed throughout the Western Palearctic14, and are characterized by a special mode of reproduction: hybridogenesis (reviewed in refs kl in nomenclature), that reproduce hemiclonally by eliminating one of the two parental genomes from the germline18. For instance, hybridogenesis in P. kl. esculentus (of P. lessonae × P. ridibundus hybrid origin) triggers the elimination of the P. lessonae germline, and only the P. ridibundus genome is transmitted to their offspring19. Kleptons therefore act as genetic parasites20.These important issues are well-illustrated by European water frogs . Some are currently expanding  and are already present on a continental scale (P. ridibundus and P. bergeri), with catastrophic effects on local fauna such as predation, competition, as well as genetic introgression and/or hybridogenetic replacement of native water frogs27. Importantly, the ability of genome exclusion seems to vary geographically, depending on the hybridogenetic system from which the invaders is derived16, thus prompting for knowledge regarding the nature and origins of Pelophylax introductions. A major management issue is that morphological determination of these species is highly challenging30, and becomes even more confusing with the cryptic occurrence of exotic lineages throughout Western Europe.Water frogs are notorious invaders: many taxa have been introduced outward their natural ranges , despite widespread suitable breeding sites and close proximity from known lowland populations  determine the nature of expanding populations, (2) reconstruct the scenario of invasion, (3) get insights into the hybridization potential of the lineages involved and (4) assess the utility of morphological determination methods. We show that our study area is being invaded by three lineages simultaneously (undistinguishable by morphology), two of them potentially forming a new hybridogenetic complex. This exceptional pattern provides a textbook application of genetic methods for understanding the onset of biological invasions and guide their management, and further emphasizes the alarming rate and invasive potential of Pelophylax aliens.This situation provides a unique opportunity to characterize a new invasion of cyt-b sequences and nuclear microsatellite genotypes (see Methods). We could include a total of 84 mitochondrial cyt-b haplotypes from the study area and other European Pelophylax, over 975 bp aligned . Microsatellite diversity ranged from 5 to 21 alleles (average: 12.5). Null alleles were detected for some loci/populations  and was therefore not included in population-based analyses (which relies on estimation of heterozygosity).Our data combined mitochondrial Pelophylax monophyletic taxa , the marsh frog (P. ridibundus), and the Balkan frog (P. kurtmuelleri), with strong geographic association . Analyses with restricted sequence length (514 bp), but enabling comparisons with published sequences of P. ridibundus, P. kurtmuelleri and P. cf. bedriagae from all over their ranges allowed to fully confirm the identification of Larzac’s haplotypes . Second, some individuals had intermediate STRUCTURE admixture proportions consistent with hybridization .Although most individuals have matching nuclear and mitochondrial ancestries Fig. , we highP. ridibundus and P. kurtmuelleri populations (average Fst   = 0.26) than compared to P. perezi . Genetic structure within P. ridibundus populations was low (average Fst = 0.05), and more pronounced within P. perezi (Fst = 0.11) and P. kurtmuelleri (average Fst = 0.11) , in addition to the two P. perezi × P. kurtmuelleri hybrids. The PCA on morphometrics separated the three ratios relative to the length of the metatarsal tubercle  from the one relative to its height  , native from Greece and Albania; its sister species the Eurasian marsh frog (P. ridibundus), widely distributed throughout Eastern and Central Europe; and the Perez’s frog (P. perezi), which inhabits Spain, Portugal and southern France. Their presence is demonstrated by unequivocal mitochondrial evidence, further supported by reciprocal nuclear clustering of microsatellite genotypes. Importantly, whereas previous genetic analyses could not reliably discriminate between P. ridibundus and P. kurtmuelleri34, we show that the mitochondrial marker cyt-b is powerful enough to distinguish both taxa in monophyletic clades, even when accounting for their strong intraspecific diversity . Given previous records that showed no water frogs over Larzac in the 1970s31 , both species were probably first introduced between ten and forty years ago in Larzac, and expanded throughout the plateau in recent years (this study). The current geographic pattern suggests that several independent introduction events contributed to the presence of P. ridibundus in the west and of P. kurtmuelleri in the east of the study area. Releases were probably numerous and of various origins: several haplotypes were sampled for each species, and different mitochondrial/nuclear lineages co-occur in both areas. This is exacerbated in the west (loc. 1–12), where multiple introduction events have been reported by locals , resulting in a mixture of different taxa.Being naturally distributed in eastern parts of Europe, P. perezi, is unclear. It may either involve illegal releases from presumably native southern populations (e.g. loc. 27–28) and/or natural expansion northwards. Yet, from our samples, the presence of P. perezi seems to also predate the recent demographic explosion, so its historical, cryptic persistence in Larzac cannot be excluded. In contrast with the two other expanding lineages, the high mtDNA diversity argues for a long-term demographic stability of P. perezi populations, and thus their legitimate occurrence in the area. Microsatellite gives a somehow conflicting signal, i.e. lower diversity of P. perezi compared to P. ridibundus and P. kurtmuelleri. However, this might be because our loci were originally developed from the P. ridibundus species complex: microsatellite diversity is known to severally drop when reused in congeneric species, proportionally to their genetic distance35. In any case, the contemporary situation of P. perezi in Larzac rather seems precarious compared to the other expanding species, which may actually replace it in the area (see below).The origin of the third Larzac’ water frog, P. kurtmuelleri), and/or be a response to climate change. Temperature, evapotranspiration and aridity indices rapidly increased in the last three decades over southern France, leading to a northward extension of the Mediterranean climate . As ectotherms, amphibians are highly sensitive to thermal and hydric environmental modifications37. Detailed ecological surveys combined with niche modelling analyses, would help testing the role of climate change in these water frog invasions, and especially understand whether the natural range of P. perezi extended northward. In parallel, the numerous suitable waterbodies in the area38 along with the strong dispersal capability of water frogs39 likely triggered the rapid colonization. This high connectivity is also illustrated by low genetic differentiation among the populations of each taxon. Hence, we predict that P. ridibundus (expanding southeastward) will soon meet P. kurtmuelleri (expanding westward) in the center of our study area (between loc. 12 and 13). These two species being known for their distinctive advertisement calls28, future monitoring of the invasions should include bioacoustic protocols, providing a cheap and reliable alternative to genetic tools in this case.After years of scarce records, the sudden colonization of Larzac by water frogs is puzzling. These range expansions may testify that introduced lineages are more adapted to the dry conditions of Larzac . Hybridization mechanisms are crucial to consider in the context of biological invasions, as they may induce genetic pollution (through introgressive hybridization) or cause the elimination of parental germlines (through hybridogenesis), in both cases eventually leading to the complete replacement of local taxa , indicative of backcrossing. This indicates that the two marsh frog species P. ridibundus and P. kurtmuelleri are able to successfully mate, which is not surprising given their young evolutionary history (~1.8 My14). In amphibians, reproductive isolation in the wild is usually reached at Pleistocene divergences, although this depends on radiations  and the time since contact43. Introgressive hybridization was also reported between the invasive P. ridibundus and P. bedriagae in Belgium29, despite four million years of independent evolution14.We found evidence for hybridization with genetic introgression between the alien ers Fig. , while oP. perezi and P. kurtmuelleri, which would then form a new klepton. First, two individuals were identified as P. perezi × P. kurtmuelleri hybrids with F1-like admixture proportions, consistent with this new klepton . Such asymmetric cyto-nuclear discordance is a known echo of hybridogenetic dynamics44; in our case, it can only result from the backcrossing of female hybrids (from P. perezi mothers) by P. kurtmuelleri males, thus restoring two copies of the nuclear P. kurtmuelleri genome while maintaining the maternally-transmitted P. perezi mtDNA. The fact that we did not find the reverse pattern (P. perezi carrying P. kurtmuelleri mtDNA) is thus compatible with a hypothetical elimination of the P. perezi germline in hybrids, which would then only contribute gametes with the P. kurtmuelleri genome . It is thus legitimate to assume that P. kurtmuelleri could have the potential to form a similar hybridogenetic complex with P. perezi  might provide novel insights regarding their occurrence and evolution.ezi Fig. , which wP. kl grafi, i.e. the klepton between P. perezi and P. ridibundus, among our samples; this taxon usually coexists with P. perezi in southern France21. We see several potential reasons for this absence/misdetection. First, we included only one area where the natural occurrence of P. kl grafi was confirmed, i.e. Lake Salagou (loc. 27–28). Micro-differences in breeding periods and habitat choice , along with yearly fluctuations in relative frequencies may all have contributed to an involuntary bias towards P. perezi in our sampling of Salagou. Second, in areas where marsh frogs have become invasive, it is not excluded that P. kl grafi has been replaced ecologically or genetically, in the same way as P. perezi. Cyto-nuclear discordance in P. kurtmuelleri individuals (carrying P. ridibundus mtDNA) could in fact stem from past hybridization with P. kl grafi.It is surprising however, that we failed to detect Pelophylax invaders. First, we demonstrate the necessity of molecular tools to detect these invasions. No morphometric criteria allowed to reliably discriminate between the Pelophylax species identified in southern France, as shown for the P. kl. esculentus complex46. The significant morphological variations we reported between P. ridibundus and other lineages might be linked to heterogeneous environmental conditions rather than actual interspecific differences, given that this taxon is currently distributed over a separated part of the study area. This species is anyway known to be highly variable phenotypically47.Our results have direct implications for the management of Pelophylax aliens to conquer large areas, even in arid environments. Amphibian invaders are often detected too late, and in the meanwhile had already established wide invasive ranges, impeding their efficient eradication and compromising native species . In addition to involuntary releases linked to international trade, amphibians are increasingly introduced for ornamental and culinary purposes in private ponds, without concern regarding their taxonomic nature and the ecological consequences. We recommend immediate conservation measures to limit such translocations, notably through a more stringent legislative policy on the matter, along with actions to raise awareness to the general public.Third, we raise the flag on extremely frequent human translocations, both at the global and the regional scale, a central cause of the biological invasion problemPelophylax. Here, it could form a new, artificial, hybridogenetic complex between the Balkan’s and Perez’s frogs, eventually driving the local extinction of the latter. While this issue deserves further investigations, it can be paralleled with other hybridogenetic systems formed in invasive contexts . Importantly, it alarms on the risk posed by P. kurtmuelleri on native green frogs throughout Europe .Fourth, this situation demonstrates the outstanding hybridizing potential of Pelophylax to extend outside the plateau. Such measure seems conceivable due to the remote geographic situation of Larzac. However, it might be more complicated in the well-connected lowlands, where amphibian communities are already a mixture of native and exotic species32. The management of hybridizing, morphologically similar species like water frogs are particularly problematic in areas of long-term occurrence, since native populations may have been secretly replaced by invasive taxa without noticeable demographic changes.In respect to these points, we recommend the eradication of identified alien populations. Immediate actions should be taken to prevent the ongoing colonization of P. kurtmuelleri  and P. perezi  to be used as reference in phylogenetic analyses, complementing published data (see below). Supplementary Table A total of 139 water frogs from 28 localities were captured with dip-nets during several breeding seasons (spring-summer 2006–2015) throughout the study area, which encompasses the Larzac Plateau (loc. 1–22), the valley of the Hérault River in the southeast (loc. 23–26) and Lake Salagou in the southwest (loc. 27–28). In addition, we further included samples from the natural ranges of Most individuals were measured with a digital caliper and a ruler for snout-ventral length (SVL), tibia length (LTi), toe length (LTo), and for the metatarsal tubercle length (LMT) and height (HMT). Tissues samples for DNA analyses were obtained by toe clipping, and preserved in 96% ethanol at 4 °C. Procedures were approved by the local and national ethics committees for animal experiments  and performed in accordance with their guidelines and regulations.cytochrome-b (975 bp) in 102 individuals , using published primers (cytb_60 F and cytb_60 R from50) and methods12.DNA was extracted using the Qiagen Biospring robotic workstation. We sequenced the mitochondrial Rica5, Rica1b5, Rica1b6, Re1Caga10, ReGa1a23, Rrid013A, Rrid059A, and Res16). These loci have the power to distinguish species from the P. kl. esculentus complex as well as to discriminate other exotic taxa29. These were amplified in two multiplex PCRs, diluted, and ran to an ABI3130 Genetic Analyzer, strictly following the protocols described in ref. Rica18) used in ref. We genotyped all individuals from the study area for eight polymorphic microsatellites in water frogs  and tested branch support by 1 000 bootstrap replicates. Published sequences correspond to all European Pelophylax spp. cyt-b haplotypes available on GenBank with a similar coverage (975 bp), and include P. bedriagae, P. bergeri, P. cretensis, P. cypriensis, P. epeiroticus, P. kurtmuelleri, P. lessonae, P. perezi, P. ridibundus and P. shqipericus  and nucleotide diversity (п) in DNASP53. Moreover, to ascertain species identification, especially between closely-related marsh frogs (see Results), we analyzed a shorter portion of cyt-b (514 bp) to include published sequences from previous phylogeographic work14 that exhaustively covers the intraspecific diversity of these species.We combined our new sequences n = 102) with published ones to build a maximum-likelihood phylogenetic tree of mitochondrial 02 with p54. We then performed several analyses of genetic structure. First, we used STRUCTURE55 to cluster individuals into K groups, testing from K = 1 to 11. We computed ten replicate runs per K, each consisting of 100’000 iterations after 10’000 of burnin. The numbers of groups best-explaining the data were retained considering the average log-likelihood Pr(X│K) and the ΔK statistics56, computed in STRUCTURE HARVESTER57. Their replicate runs were combined with CLUMPP58 and graphically represented using DISTRUCT59. Second, we performed a Principal Component Analysis (PCA) on individual genotypes using the R packages adegenet and ade4. Third, we computed pairwise genetic distances (Fst) between populations with sufficient sample sites (n > 6) in Fstat60, pooling some proximate localities . We also estimated observed heterozygosity (Ho) for these populations, as well as for the identified taxa (see Results), considering only individuals confidently assigned to the corresponding nuclear cluster (STRUCTURE admixture proportion above 0.95). One marker (Rica5) was not considered in population-based analyses due to the high frequency of null alleles (see Results).Microsatellite genotypes were checked and corrected for null alleles using Micro-CheckerP. perezi × P. kurtmuelleri hybrids, which might represent a new hybridogenetic taxon (see Results and Discussion). We considered four ratios of measurements usually tested as discriminants between sympatric species of Pelophylax frogs46: toe length/metatarsal tubercle length (Lto/LMT), tibia length/metatarsal tubercle length (Lti/LMT), tibia length/metatarsal tubercle height (LTi/HMT), and snout-ventral length/metatarsal tubercle length (SVL/LMT).To test whether the identified taxa can be distinguished by morphometrics, we selected individuals with available measurements data that were confidently assigned to the corresponding nuclear cluster (see the end of last section), and at least 40 mm long (SVL). We also included the two individuals identified as ade4. In addition, we tested whether they significantly differ between taxa with Tuckey’s HSD tests.We performed a PCA on these four variables (log-transformed) for the selected individuals using the R package Supplementary Information