Understanding the effects of intraspecific genetic diversity on the structure and functioning of ecological communities is a fundamentally important part of evolutionary ecology and may also have conservation relevance in identifying the situations in which genetic diversity coincides with species-level diversity.Early studies within this field documented positive relationships between genetic diversity and ecological structure, but recent studies have challenged these findings. Conceptual synthesis has been hampered because studies have used different measures of intraspecific variation  and have considered different measures of ecological structure in different ecological and spatial contexts. The aim of this study is to strengthen conceptual understanding by providing an empirical synthesis quantifying the relationship between genetic diversity and ecological structure.Here, I present a meta-analysis of the relationship between genetic diversity within plant populations and the structure and functioning of associated ecological communities (including 423 effect sizes from 70 studies). I used Bayesian meta-analyses to examine (i) the strength and direction of this relationship, (ii) the extent to which phenotypically adaptive and neutral (molecular) measures of diversity differ in their association with ecological structure and (iii) variation in outcomes among different measures of ecological structure and in different ecological contexts.Effect sizes measuring the relationship between adaptive diversity (genotypic richness) and both community- and ecosystem-level ecological responses were small, but significantly positive. These associations were supported by genetic effects on species richness and productivity, respectively.There was no overall association between neutral genetic diversity and measures of ecological structure, but a positive correlation was observed under a limited set of demographic conditions. These results suggest that adaptive and neutral genetic diversity should not be treated as ecologically equivalent measures of intraspecific variation.Synthesis. This study advances the debate over whether relationships between genetic diversity and ecological structure are either simply positive or negative, by showing how the strength and direction of these relationships changes with different measures of diversity and in different ecological contexts. The results provide a solid foundation for assessing when and where an expanded synthesis between ecology and genetics will be most fruitful. A growing number of studies provide evidence that intraspecific genetic diversity can influence the diversity, structure and functioning of plant and animal communities and ecosystems  have focussed on ecological effects stemming from two levels of genetic organization. One set of studies has documented ecological responses to or associations with genetic diversity itself . In this paper, I will treat all intraspecific phenotypic differentiation that has a demonstrable genetic component as ‘adaptive’ . Thus, neutral genetic variants are defined as being both selectively neutral for the individuals that carry them and ecologically neutral in their effects on other coexisting individuals, species and on ecological processes. Under these definitions, only adaptive genetic diversity can drive selection among coexisting species or respond to selection imposed by the ecological context, and thus, only adaptive genetic diversity has ecological consequences. Neutral diversity, on the other hand, can become associated with ecological structure indirectly, through the location-specific action of genetic drift and migration . In these cases, community- or ecosystem-level responses in genetically diverse mixtures can be predicted from information on the monoculture ‘performance’ of the component genotypes and their population frequencies  of individual populations could be reduced as more species compete over the total niche space . Data base-specific literature searches were merged in Endnote (version X4.0.2), and duplicate records were discarded to give a master data base containing 8670 articles. These articles were filtered to remove non-journal and irrelevant clinical and biomedical articles from the data base, leaving 6980 articles .This review synthesized results from experimental or field-based empirical studies. Theoretical papers were excluded from the review, as were simulation studies and other reviews. Reviews focusing on the relationship between genetic diversity and ecological structure were retained as relevant, and their bibliographies were checked against the Endnote data base to identify any further relevant articles from the primary literature.This review focussed on communities or ecosystems containing a population of at least one plant species whose genetic diversity had either been manipulated, or had been measured. Both natural and agricultural or farmed communities and ecosystems were valid subjects. As the aim of this review was to synthesize the effects of population-level genetic diversity, I excluded studies that dealt only with community- and ecosystem-level responses to genotypic or genetic identity. In other words, the plants whose genetic diversity were measured or manipulated must have comprised genuine ‘populations’ containing more than one individual.Arabidopsis thaliana) and agricultural cultivars were considered to meet this condition as well. Other studies not meeting this criterion were excluded. Studies focusing exclusively on community and ecosystem responses to intra-genomic diversity, for example, arising from interspecific hybridization, inter-population outcrossing or inbreeding were also excluded, because they investigate ecological responses to genetic identity rather than to genetic diversity measured at the population level.I refer to the species whose genetic diversity was observed as the ‘focal species’, and I define the spatial area within which a focal population resides and for which ecological outcome measures were recorded, as the sampling unit. The review included studies that manipulated genetic diversity experimentally and that observed non-manipulated genetic diversity of focal populations using molecular markers. Both neutral genetic diversity (measured with molecular markers) and adaptive phenotypic diversity were accepted as valid measures of genetic diversity . The repeatability of the title and abstract assessments were tested through independent assessment of a random subset of 517 articles (title assessment) and 100 articles . The level of concordance in assessment was measured using the Kappa coefficient of agreement . I did not check the objectivity of full-text assessment using Kappa analyses as I had done for title and abstract assessment. However, during full-text assessment, I was able to compare a complete description of the methods employed in each study with the review inclusion criteria given above, leading to robust decisions on study relevance. It should be noted that this review is not intended to be exhaustive in its scope. Although I have made every effort to identify and collate the relevant evidence, it is possible that some relevant papers are missing from this review.outcome level was recorded – whether outcomes were at the community level or the ecosystem level. Secondly, outcome type was recorded; this was a categorical description of the outcome variable nested within outcome level . My rationale for this was that larger effect sizes could be associated with greater differences in genetic diversity. For the studies that reported outcomes at the community level, I recorded a variable called trophic contrast that described whether focal species were at the same trophic level as the responding community (intra-trophic contrast) or at a different trophic level (inter-trophic contrast). Study sampling designs for the focal species (sampling strategy) were documented as either within-population, or between-population, or cultivar. The latter category was applied where the focal individuals were from agricultural cultivars or breeds that did not belong to any natural population. The sampling strategy variable for studies that manipulated focal species genetic diversity described whether the individuals of the focal species had been collected from different populations or from within the same population. The corresponding variable for observational studies described whether sampling units were focal species’ populations or were plots or stands within a single contiguous focal species’ population. I recorded the breadth of sampling units in metres, as a measure of their size . Where studies provided information on the area or volume of the sampling unit, I used the square- or cube-root of this value to approximate sample unit breadth; the median sample scale was used where the sample units within a study varied in area. The overall spatial extent of a study  was the Euclidian distance between the most widely separated sampling points for focal species’ individuals (for studies manipulating adaptive genetic diversity) or populations . To investigate whether the difference between study scale and sample unit scale could influence community-genetic effect sizes . This variable was extracted only for studies where genetic diversity had been manipulated. The final source of heterogeneity that I considered was intended to investigate the effects of locality characteristics on associations between neutral genetic diversity and ecological structure (Box area constraint). Secondly, I noted when sample units within studies were both variable in area and were isolated from other sample units, representing effective demographic islands (island effect).Potential sources of heterogeneity were extracted from relevant articles for use as explanatory variables in meta-analyses. Focal species identity and exposure type . When the relevant data were not presented in an extractable form, the article authors were approached in order to gain access to the necessary data summaries. Authors were also approached to gain missing information on the sources of heterogeneity. When relevant data were presented as a time series of repeated measures, I used data from the final time point to calculate effect sizes.Data were extracted from 69 articles (70 studies) to calculate effect sizes  relating within-population genetic diversity to measures of ecological structure. I extracted data from article text and from article figures using Iz-transformation to the raw correlation coefficients (these effect sizes are referred to as z(r) statistics). The measurement error variance (mev) of these effect sizes was calculated as 1/(n − 3), where n is the number of populations  was calculated as ((n1 + n2/n1 * n2) + d2/(2* (n1 + n2 − 2))) * ((n1 + n2)/(n1 + n2 − 2)). I used this measure of effect size for experimental studies because many of these studies presented effects for only two levels of genetic diversity; it would not have been possible to fit a correlation to these data. Studies manipulating focal species’ genetic diversity usually presented data for outcome variables (e.g. species richness) as means and standard errors grouped by genetic diversity level . Means, standard errors and sample sizes were extracted for each outcome variable for each level of focal species’ genetic diversity. These were then used to calculate the standardized mean difference for each unique pairwise combination of genetic diversity levels. For example, a study that created experimental communities with one, three and six clones of the focal species would yield three effect sizes . I calculated d so that effect sizes would be positive when species diversity increased with genetic diversity, or when productivity, nutrient and elemental stocks increased with genetic diversity, or when fluxes or rates of change of the stocks decreased with increasing genetic diversity (I viewed nutrient or stock retention as a ‘positive’ outcome).Effect sizes were calculated in two ways, depending on whether studies focused on neutral genetic diversity within natural populations or whether they focused on experiments where the focal species’ adaptive genetic diversity had been manipulated. Thus, there were two effect-size data sets, one for each of these study designs. Effect sizes for neutral diversity were calculated from correlation coefficients that compared population-level genetic diversity with community structure or ecosystem functioning. Community-genetic effect sizes were calculated by applying Fisher's d) and effect sizes based on correlation coefficients (z(r)) were analysed separately. To take account of effect size precision, I fitted measurement error variance values (mev) about the effect sizes as a set of variance components. I assumed these to be known without error and they were fixed in the analysis, rather than estimated (Hadfield & Nakagawa z(r) (correlative) data set used molecular markers to infer numbers of clones within sampling units and therefore contributed putatively adaptive community-genetic effect sizes. Heterogeneity between putatively adaptive and neutral effect sizes in this data set was assessed, and then, the adaptive effect sizes were removed to allow analyses that focussed on neutral genetic diversity. Effect sizes z(r) for these adaptive measures of diversity did not differ significantly from the remaining correlative effect sizes based on neutral diversity (pMCMC = 0.952).Meta-analyses synthesizing the effect sizes were conducted using Bayesian mixed-effects meta-analytic models  effect sizes can also be biased. For example, in the community genetics literature, we might expect that studies would be more publishable if they reported positive relationships between genetic diversity and community-level diversity (assuming a ‘diversity begets diversity’ relationship). Non-significant negative effects observed in studies with small sample sizes would be more likely to be relegated to the file drawer. Such bias would result in asymmetry in the distribution of effect sizes around the pooled effect size, and this asymmetry can be detected visually using forest plots . The correlation between neutral genetic diversity and ecological structure was not consistently different from zero (z(r) = 0.139; 95% credible interval -0.024–0.311; pMCMC = 0.110).I reviewed 69 studies reporting relationships between genetic diversity and community diversity, structure and ecosystem function published between 1999 and 2013  community was at a different trophic level than the focal plant population  used Arabidopsis thaliana as the focal plant species. Adaptive community-genetic effect sizes were positive both for studies that sampled focal experimental individuals from within a single population or for studies that drew focal individuals from a number of different populations  = 0.232 and z(r) = 0.243, respectively; Fig. z(r) = 0.358; Fig. Neutral genetic diversity showed no overall consistent association with ecological structure at either the community or ecosystem levels, or for any component type of ecological response Fig. b. HoweveVariation in effect sizes among studies that manipulated adaptive variation accounted for between 29.2 and 37.0% of the total heterogeneity in effect sizes  on genotypic mixtures, relative to monocultures. Other studies focussing on Oenothera biennis have shown that both selective impacts of arthropods on the foundation plant population and corresponding selection flowing from the plant to the dependent arthropod community are able to occur through time  can lead to greater sustainability in populations and communities that are the focus of conservation efforts. Such management may lead to avoidance of the deleterious consequences of inbreeding , 0.631–0.721; Møller & Jennions et al. (d = 0.464 (following conversion from z(r) to d; Borenstein et al. d = 0.189 in this study  sampling design  and frequently used measures of genotypic or ecotypic richness, rather than measures of genetic variance. These two design biases could be addressed by the application of carefully designed experiments that incorporate different measures of adaptive genetic variation (as proposed by Hughes et al. The meta-analyses presented in this paper provide an objective and quantitative assessment of the relationship between population-level genetic diversity and community structure and ecological functioning. The results illustrate how this relationship varies between the two types of genetic diversity commonly used in community genetics studies among different ecological response measures and in different ecological and spatial contexts. In several instances, these findings bear out predictions and mechanistic interpretations that have been set out in previous narrative reviews (Vellend & Geber


Salvelinus alpinus and brown trout, Salmo trutta) and one introduced , from an alpine lake in sub-arctic Sweden, Lake Ånn. The genetic diversity of the three species was similar and sufficiently high from a conservation genetics perspective: corrected total heterozygosity, H’T = 0.54, 0.66, 0.60 and allelic richness, AR = 4.93, 5.53 and 5.26 for Arctic charr, brown trout and brook charr, respectively. There were indications of elevated inbreeding coefficients in brown trout (GIS = 0.144) and brook charr (GIS = 0.129) although sibling relationships were likely a confounding factor, as a high proportion of siblings were observed in all species within and among sampling locations. Overall genetic structure differed between species, Fst = 0.01, 0.02 and 0.04 in Arctic charr, brown trout and brook charr respectively, and there was differentiation at only a few specific locations. There was clear evidence of hybridisation between the native Arctic charr and the introduced brook charr, with 6% of individuals being hybrids, all of which were sampled in tributary streams. The ecological and evolutionary consequences of the observed hybridisation are priorities for further research and the conservation of the evolutionary potential of native salmonid species.Understanding the processes underlying diversification can aid in formulating appropriate conservation management plans that help maintain the evolutionary potential of taxa, particularly under human-induced activities and climate change. Here we assessed the microsatellite genetic diversity and structure of three salmonid species, two native (Arctic charr,  The conservation and maintenance of biodiversity is important for the stability and functioning of ecological communities and populations and also provides immeasurable benefits to human society such as ecosystem services and aesthetic value . BiodiveDiversification (or speciation) research has traditionally focused on the level of species and above, but diversification below this level is of equal importance and interest , 8. The Hybridisation is defined as the interbreeding of two different species and can have a variety of outcomes, including promoting speciation , introgrFreshwater fishes have one of the highest frequencies of both recent adaptive radiations and hybridisation among all animal taxa . The resSalvelinus and Salmo provide some classic cases of differential diets [Diversification in postglacial fishes, especially salmonids, is a widely recognised phenomenon, with variation occurring not only across a species range, but also within individual lakes. The salmonid family is composed of over 60 species, many of which include different ecotypes or spatially subdivided morphs . For exaal diets , 42, pheal diets , 44, as al diets , 46. Theal diets , 48. Theal diets –52.Salvelinus alpinus and brown trout, Salmo trutta) and one introduced , from an alpine lake in sub-arctic Sweden, Lake Ånn. The overall aims were to: 1) determine levels of genetic diversity and compare to previous studies of these species; 2) determine the extent of genetic diversification and structure in relation to geographic location, including recognised spawning locations; and 3) detect if any hybridisation is occurring, particularly between the native and introduced charr  species.However, due to their popularity as recreational fishing targets and their extensive and widespread translocation, it is important to consider processes of diversification and hybridisation in locations where both native and introduced salmonid species are present. This study assessed the genetic diversity and structure of three salmonid species, two native , and areas deeper than 10m being restricted to the south-western area [Salmo trutta, Arctic charr, Salvelinus alpinus, and Eurasian minnow, Phoxinus phoxinus; and one introduced species lake trout, Salvelinus namaycush, are known to inhabit the lake [Salvelinus fontinalis, is also present in the tributaries [Lake Ånn is situated in central Sweden  at an elevation of 526m . The lakern area . Barrierthe lake . The intbutaries . Lake trbutaries . Howeverbutaries  as a recbutaries . For exabutaries .2) tissue biopsy was taken from the caudal fin of each fish using sterile scissors. When possible fish were returned the water alive. Whilst electrofishing, individuals were identified to genus level only, i.e. Salmo or Salvelinus, as distinguishing between young (most fish were less than 50mm) Arctic and brook charr in the field was difficult. Tissue was frozen and transported to Uppsala University for analysis.Arctic charr, brown trout and brook charr were sampled by local licensed fisherman from Lake Ånn using gillnets from July to November 2012, and by the authors from the tributaries surrounding the lake by electrofishing in September 2012 . Each trTTCTCAACTAACCAYAAAGAYATYGG and COI R: TAGACTTCTGGGTGGCCRAARAAYCA [DNA was extracted from tissue samples using a modified salting out protocol . In ordeAARAAYCA  and PCR AARAAYCA . PCR proAARAAYCA  and blasO/HS/H’T), inbreeding coefficients (GIS), pairwise genetic differences , and AMOVA were calculated in Genodive [R) was calculated in FSTAT [Deviations from Hardy-Weinberg equilibrium and the presence of null alleles, stuttering and large allele dropout were assessed in Microchecker v2.2.3 . Visual Genodive . Allelicin FSTAT . A high 91 brown trout and 75 Arctic charr individuals were collected from Lake Ånn, and 49 brown trout, eight Arctic charr and 96 brook charr individuals were collected from tributaries. There were two COI haplotypes in Arctic charr, which varied by a single mutation, A/G, at site 386. Although only the G haplotype was detected in Bunnerån, there was no other strong phylogeographic distribution of the COI haplotypes across the lake and its tributaries . Only onP = 0.99), as were eight individuals from Stenbrottsbäcken (P = 0.95–0.99). There was also one individual from Stenbrottsbäcken that had equal probability (P = 0.50/0.50) of being a F2 hybrid or a backcross to Arctic charr. The individual from Kobbhuvudbäcken and two from Stenbrottsbäcken had Arctic charr mitochondrial haplotypes, i.e. their mother was Arctic charr. The remaining seven individuals had brook charr mitochondrial haplotypes and hence, mothers of brook charr origin.Principle components analysis of microsatellites from all three species combined revealed a clear separation of brown trout from the 2 charr species along the first PC-axis . AlthougSummary tables of the tests of Hardy-Weinberg equilibrium (HWE) and the presence of null alleles are shown in Tables B, C, D in T) of 0.54 (SD 0.08), AR of 4.93 (Nmin11) and GIS of -0.063 (SD 0.089). Brook charr were sampled from 4 tributaries and had an H’T of 0.60 (SD 0.10), AR of 5.26 (Nmin14) and GIS of 0.129 (SD 0.067). Finally, brown trout was sampled from 4 tributaries and 5 lake locations and had an H’T of 0.66 (SD 0.06), AR of 5.53 (Nmin10) and GIS of 0.144 (SD 0.06). Inbreeding coefficients (GIS) in brook charr and brown trout were relatively high, particularly in tributary locations such as Stenbrottsbäcken (GIS = 0.273), Herrån (GIS = 0.223) and Myckelbäcken (GIS = 0.174).Microsatellite genetic diversity measures for each species are shown in ST was low but significant  suggesting only weak genetic structure. The only significant pairwise FST value  was between Bunnerviken and Granön S, FST = 0.03. There was slightly higher genetic structure in brook charr among tributaries, with an overall FST = 0.04, P = 0.001. This was mainly driven by the differentiation among Klocka, Myckelbäcken and Stenbrottsbäcken. Overall FST in brown trout was also significant but low, FST = 0.02 (P = 0.001). Herrån was the most differentiated location with FST values from 0.04 to 0.11.In Arctic charr overall FA high number of sibling relationships were detected in all three species Tables , 3 and 4T = 0.66), followed by brook charr (H’T = 0.60) and Arctic charr (H’T = 0.54); the highest allelic richness values were also observed in brown trout (AR = 5.53), followed by brook charr (AR = 5.26) and Arctic charr (AR = 4.93). These levels of diversity are similar among the three species, despite differences in population demographic history, particularly for brook charr, which were presumably founded from a small number of introduced fish. Although there was only one mtDNA haplotype detected in brook charr, suggesting a population bottleneck upon introduction, microsatellite diversity levels were comparable to the two native species, and may indicate that gene flow, potentially via introgression with the native Arctic charr (see below) or ongoing unreported introductions, has been a stronger factor than genetic drift in Lake Ånn.The salmonid species of Lake Ånn had moderate levels of genetic diversity. Brown trout had the highest heterozygosity levels  were observed in both brook charr (GIS = 0.129) and brown trout (GIS = 0.144) particularly in the tributaries. However, these levels of inbreeding are generally within the range of those observed in previous studies of these species  and brown trout in Herrån (GIS = 0.223) and Årsön E (GIS = 0.374), and likely reflect the fact that brook charr and brown trout spawn in tributaries and display spawning site fidelity. This means that related individuals or family groups return to the same restricted geographical location to reproduce each year, resulting in tributary locations that experience inbreeding and have lower effective population sizes and/or carrying capacities compared to lake locations. Indeed a high number of sibling relationships were detected across the entire dataset, most notably in brook charr, which is restricted to tributaries. It is well recognised that fish populations residing and/or reproducing predominantly in lakes versus streams have contrasting demographic dynamics, e.g. spawning and dispersal behaviour, with consequences for effective population sizes and genetic diversity [ST = 0.01–0.04) indicated there is geneflow among spawning sites that is important for maintaining local genetic diversity. Although kinship associations may be responsible for elevating inbreeding coefficients and low effective population sizes, we recommend management measures to avoid the creation of even smaller and more isolated populations that in the long-term may pose genetic threats to overall population viability.Notably high levels of inbreeding , with tiversity . Indeed,iversity . Differeiversity , 80 as wiversity . Thus, oST analyses suggested that there is only weak spatial differentiation: in the southern part of Lake Ånn for Arctic charr; of one tributary, Herrån, in brown trout; and among most tributaries in brook charr. This could be due to the small spatial scale of the study area, the dispersal behaviour of each species, and/or disruption of spawning sites due to introduced species or environmental changes.Despite our expectation that genetic structure in Lake Ånn would be related to recognised spawning locations, there was evidence of only very low levels of genetic differentiation in all species across the study area. FST values observed in Lake Ånn, kinship analyses detected numerous sibling pairs within and among sampling locations, indicating that fish disperse freely around the lake, and to some extent the tributaries. Thus, even if fish display spawning site fidelity , outside of the spawning season adults utilise all areas of the lake for foraging. Indeed, kin groupings in a native population of brook charr have also been found to be quite weak between foraging and spawning periods due to natural mortality [Salmonids are renown for their high dispersal abilities, undergoing seasonal spawning migrations that may even require overcoming small waterfalls and weirs. In addition to the low Fortality . Previouortality , 69, 82)ortality , perhapsortality , 83. ThuSalvelinus namaycush, and brook trout, as well as climate change have altered the previously observed spawning behaviour and grounds (P. Jämting pers. comm.). This problem has also been observed in Lake Windermere in the UK, where only 7 out of 12 spawning grounds of Arctic charr are still in use, because of eutrophication and sedimentation due to climate change and introduced species [In addition, the roles of introduced species and environmental change in shaping genetic structure needs to be considered. In the 1960s local fisherman mapped the location of known spawning locations of Arctic charr in and around Lake Ånn . However species . Thus it species . FurtherHybridisation between Arctic charr and brook charr was first described in a natural situation, where there was a large difference in population size, brook charr being rarer, with the resulting hybrids displaying many overlapping characteristics of morphology and behaviour . This stSalvelinus leucomaenis, and although introgression has not yet been detected, the negative impacts due to wasted reproductive resources are a recognised problem [sensu [Salvelinus namaycush . Housh (see ), would S1 FileTable A Details of the primers and multiplexing used in this study. SA = Salvelinus alpinus, SF = Salvelinus fontinalis, ST = Salmo trutta. Tables B, C, D Results of the tests of Hardy-Weinberg equilibrium (HWE) and the presence of null alleles (NA) and stuttering (S) (Microchecker v2.2.3) in all three species. Locus and population combinations not in HWE (significant at P < 0.001 Bonferroni adjusted) are shown in bold. Tables E, F, G Pairwise FST tables for all three species. FST values in the lower triangle, P values in the upper triangle. Bonferroni corrected significant FST values shown in bold.(DOC)Click here for additional data file.S1 Tables(XLSX)Click here for additional data file.


Activated STAT3 plays an important role in oncogenesis by stimulating cell proliferation and resisting apoptosis. STAT3 therefore is an attractive target for cancer therapy. We have screened a traditional Chinese herb medicine compound library and found Eriocalyxin B (EB), a diterpenoid from Isodon eriocalyx, as a specific inhibitor of STAT3. EB selectively inhibited constitutive as well as IL-6-induced phosphorylation of STAT3 and induced apoptosis of STAT3-dependent tumor cells. EB did not affect the upstream protein tyrosine kinases or the phosphatase (PTPase) of STAT3, but rather interacted directly with STAT3. The effects of EB could be abolished by DTT or GSH, suggesting a thiol-mediated covalent linkage between EB and STAT3. Site mutagenesis of cysteine in and near the SH2 domain of STAT3 identified Cys712 to be the critical amino acid for the EB-induced inactivation of STAT3. Furthermore, LC/MS/MS analyses demonstrated that an α, β-unsaturated carbonyl of EB covalently interacted with the Cys712 of STAT3. Computational modeling analyses also supported a direct interaction between EB and the Cys712 of STAT3. These data strongly suggest that EB directly targets STAT3 through a covalent linkage to inhibit the phosphorylation and activation of STAT3 and induces apoptosis of STAT3-dependent tumor cells. Signal transducer and activator of transcription 3, known as STAT3, is a transcription factor as well as a signal transducer. In response to cytokines, such as IL-6, and growth factors, such as EGF and IGF, STAT3 is recruited from the cytosol to associate with the activated receptors through its phosphor-tyrosine recognition SH2 domain, and phosphorylated on its carboxy-terminal tyrosine Tyr705) and serine (Ser727) by the receptor-associated JAK kinases, Src, or other kinases. The tyrosine 705- phosphorylated STAT3 then dimerizes and translocates into the nucleus, where it binds to specific promoter sequences and regulates the expression of target genes, such as cyclin D1, bcl-XL, and c-myc, that are involved in cell growth and survival –6. Aberr05 and seBecause of the importance of STAT3 in regulating cell growth and survival, the STAT3 signaling pathway has been considered as a valid target for anti-cancer drugs ,12. A nuTo identify new STAT3 pathway inhibitors, we screened a traditional Chinese herb medicine compound library and found Eriocalyxin B (EB) as a potent and specific STAT3 pathway inhibitor. EB is a natural diterpenoid from Isodon eriocalyx var. laxiflora of the Labiatae family which has been reported to possess various bioactivities, especially anti-cancer, anti-inflammation, and anti-bacteria activities . EB has In the present report, we studied the molecular mechanisms of the selective inhibition of STAT3 by EB. We found that EB specifically inhibited STAT3 activation by covalently binding to the Cys712 near the SH2 domain of STAT3 through a Michael addition with its α, β-unsaturated carbonyl and prevented it to be phosphorylated and activated by its upstream kinases. This study uncovered a new strategy to specifically inhibit the STAT3-mediated signaling and provided a novel STAT3 inhibitor for potential cancer treatment.The Chinese medicinal herb compound library was a collection of 182 natural compounds isolated from 69 traditional Chinese medicinal herbs (unpublished results). The compounds were dissolved in DMSO at a concentration of 10 mM. The final concentration of a compound in the screening assay was 10 μM. The library screening was performed using a cellular luciferase gene reporter assay as described below. EB (>98% purity) was purchased from Shanghai Boylechem Co.ltD. Stattic was purchased from Selleck Chemicals. Sodium orthovanadate and DAPI (Diamidino-phenyl-indole) were purchased from SIGMA. Antibodies against STAT3, p-STAT3 Tyr705, p-STAT3 Ser727, STAT1, p-STAT1 Tyr701, STAT5, p-STAT5 Tyr694, JAK2, p-JAK2 Tyr1007/1008, JAK1, p-JAK1 Tyr1022/1023, Tyk2, p-Tyk2 Tyr1054/1055, PARP and actin were purchased from CST . Antibodies against tubulin were purchased from Santa Cruz Biotechnology. Secondary HRP-conjugated antibody was purchased from MultiSciences Biotech. Alexa Fluor 488 donkey anti-mouse IgG antibody was purchased from Invitrogen.The HepG2/STAT3 luciferase gene reporter cell line was a gift from Prof. Xinyuan Fu , and was cultured in Minimal Essential Medium with 10% FBS. The cell line was generated by stably transfecting the HepG2 cells with a STAT3-responsive firefly luciferase reporter plasmid and was authenticated using the IL-6-induced STAT3 responsive luciferase reporter assay within 6 months. MDA-MB-231, MDA-MB-468, and MDA-MB-453 cells, which were cultured in DMEM with 10% FBS, and A549 cells, which were cultured in RPMI 1640 with 10% FBS, were all obtained from American Type Culture Collection (ATCC). They were passaged for less than 6 months and maintained as recommended by the provider. ATCC performed cell line authentication using DNA fingerprinting by short tandem repeat (STR) analysis.5 per well) were seeded into 12 well cell culture plates (Corning) and allowed to grow for 24 h and then treated with EB for 2 h followed by stimulation with IL-6 (50 ng/mL) for 5 h. Luciferase activity was determined using the Promega luciferase kits according to the manufacturer’s instruction. The cell number was counted at seeding and equal number of cells was seeded. All luciferase assay experiments were performed in triplicates to minimize the difference caused by cell number.The HepG2/STAT3 luciferase reporter cells (3.0*10Cells were lysed in 1X Laemmli sample buffer (Sigma-Adrich). The extracts were heated at 100°C for 5 minutes and proteins were separated by 8% SDS-PAGE, transferred to a nitrocellulose membrane (Whatman) and probed first with specific primary antibodies, then with horseradish peroxidase-conjugated secondary antibodies. The membranes were developed with enhanced chemiluminescence (ECL) detection system (Thermo).A549 cells were cultured in serum-free medium for 12 h, and then stimulated with IL-6 (20 ng/ml) for 40 min. The nuclear lysates were prepared essentially as described by Chaturvedi MM et al . To testA549 cells were cultured on coverslips in serum-free 1640 medium for 24 h. After incubation with or without 10μM EB for 2 h, cells were stimulated with 50 ng/ml IL-6 for 30 min. Cells were fixed with 4% paraformaldehyde for 10 min and permeabilized for 10 min with 1% Triton X-100 in PBS. After blocking with 1% donkey serum, the coverslips were incubated with a primary antibody against STAT3 for 1 h, followed by incubation with a fluorescence-labeled secondary antibody for 1 h. Cells were counterstained with DAPI. The samples were imaged by confocal microscopy at 20× magnification.http://www.eurofins.com/pharma-services/pharma-discovery-services/services/in-vitro-pharmacology/kinases/biochemical.aspx).Human JAK2, cSRC, EGFR, IKKβ, MAPK1 and PI3K in vitro kinase assays were performed by Eurofins' KinaseProfiler service  were seeded into 96-well plates. Twenty-four hours later, cells were treated with vehicle control (DMSO) or EB  for 48 h. 3--2, 5-diphenyltetrazolium bromide solution was then added to each well. After 5 h of incubation at 37°C, extraction buffer  was added. The cells were incubated overnight at 37°C, and the absorbance was measured at 595 nm using Tecan Infinite 200 Pro microplate reader (Tecan).Myc-tagged STAT3 plasmid was a gift from Eugene Chin’s lab . Cys to Ser mutations of C418S, C426S, C468S, C542S, C550S, C687S, C712S, C718S STAT3 mutants were generated by Fast Mutagenesis System (TransGen Biotech) and verified by DNA sequencing (Invitrogen). Transient transfection of A549 cells was performed using Lipofect 2000 (Invitrogen) according to the manufacturer’s instructions.EB was incubated with GSH, FT-8 (FICVTPTT) or QP-10 (QFTKCCPPKP) peptides at 37°C for 2 h. Then the samples were injected in the liquid chromatography-mass spectrometry (LC-MS) system using methanol/water (1:1) as the mobile phase. HPLC analysis was performed using an Angilent HP 1100 series HPLC system (Angilent Technologies). Mass spectrometry was recorded using a LCQ Deca ion trap mass spectrometer (ThermoFinnigan).−1. The eluted peptides were ionized and introduced into an LTQ Orbitrap Elite mass spectrometer using a nanospray source. Survey full-scan MS spectra  were acquired in the Orbitrap with resolution R = 24,000 at m/z 400. The 20 most intense ions were sequentially isolated in the linear ion trap and subjected to collisionally induced dissociation (CID) with a normalized energy of 35%. The exclusion duration for the data-dependant scan was 60 sec and the repeat count was 2.EB was incubated with the FT-8 (FICVTPTT) peptide at 37°C for 2 h, then vacuum-dried. The dried peptide samples were dissolved in 4-μl HPLC buffer A  and delivered onto the capillary RPLC trap column . After loading and washing, the peptides were transferred to analytical column (10 cm length with 75 μm ID) and were eluted with a 10min gradient of 2% to 80% HPLC buffer B  in buffer A at a flow rate of 300 nl min−1. The eluted samples were ionized and introduced into an LTQ Orbitrap Elite mass spectrometer using a nanospray source. Survey full-scan MS spectra  were acquired in the Orbitrap with resolution R = 24,000 at m/z 400. The 15 most intense ions were sequentially isolated in the linear ion trap and subjected to collisionally induced dissociation (CID) with a normalized energy of 35%. The exclusion duration for the data-dependant scan was 30 sec and the repeat count was 2.Bacteria-expressed STAT3 protein (0.2 mg/ml)  was treated with EB (20 μM) at 37°C for 2 h, and the sample was then separated by SDS-PAGE and stained with Coomassie blue. Coomassie-stained band was excised from the gel and cleaned by dH2O water, and then was digested by trypsin at 37°C overnight. After being vacuum-dried, The samples were dissolved in 4-μl HPLC buffer A  and delivered onto the capillary RPLC trap column . After loading and washing, the samples were transferred to analytical column (10 cm length with 75 μm ID) packed with C18resin  connected to an EASY-nLC 1000 HPLC system and were eluted with a 110 min gradient of 5% to 80% HPLC buffer B  in buffer A at a flow rate of 200 nl minhttp://www.rcsb.org/pdb/home/home.do), which was then imported to Maestro and processed using Protein Prepare Wizard. Water was removed and global energy was minimized until RMSD value was below 0.3 angstrom using OPLS-AA force field. The grid box centered at Cys712 near the SH2 domain of STAT3 was generated using Glide, and the standard precision mode was utilized during the docking simulation. The top scored pose was extracted and visualized using Pymol.The structure of Eriocalyxin B was drawn using Maestro 9.0 and prepared using LigPrep. Epik option was employed to predict the putative ionization states at physiological condition, and conformers were generated using the MMFF force field. The crystallographic structure of STAT3 (PDB entry:1BG1) was downloaded from RCSB Protein Data Bank (Cell proliferation was measured using the RTCA system (Roche). Initially, 50 μL of cell free growth medium (10% FBS) was added to the wells. After leaving the devices at room temperature for 30 min, the background impedance for each well was measured. Then 50 μL of the A549 cell suspension was seeded into the 16 well E-Plate (3000/well). After leaving the plates at room temperature for 30 min to allow cell attachment, they were locked in the RTCA DP device in the incubator for 24 h. After 24 h of RTCA profiling, the assay was paused, and the E-Plate were removed from the RTCA system. The existing media was carefully removed and replaced with the media containing IFN-γ (10000 U), EB (1 μM), or their mixture. The E-Plate 16 was placed back into the RTCA system and the cell growth was monitored for 48 h. CI (Cell index) was monitored every 5 min during the experiment. Results were plotted using the RTCA software.To identify novel and specific inhibitors of STAT3, we screened a traditional Chinese medicinal herb compound library using a STAT3 responsive luciferase reporter assay system . We idenTo verify whether EB inhibited STAT3 activation, we examined the phosphorylation of STAT3 in lung adenocarcinoma A549 cells using Western Blot analysis. We found that EB inhibited the IL-6-induced STAT3 Tyr705 phosphorylation in a dose and time-dependent fashion . EB alsoPhosphorylation of STAT3 on Tyr705 results in homo- or hetero-dimerization of STAT3, enabling its nuclear translocation and DNA binding . To furtTo understand the nature of the inhibition of STAT3 signaling by EB, we analyzed the effects of EB on the signaling of its close family members STAT1 and STAT5, which are structurally similar to STAT3, but have different functions in regulating cell growth ,26. SimiBinding of IL-6 to its receptor initiates cellular events including activation of STAT3 upstream kinases, which then phosphorylate and activate STAT3 . We examJAK family kinases, particularly JAK1, are the upstream kinases of STAT3 . To inveTo further verify our observation, we analyzed the effects of EB on JAK2 and other kinases in the in vitro kinase assays. EB did not inhibit the activities of any of the STAT3 kinases, such as JAK2, EGFR, cSrc , or the Because protein tyrosine phosphatases (PTPs) are also involved in the regulation of STAT3 phosphorylation , we inveEB contains two α, β-unsaturated carbonyl groups which have potential to react with thiols of cysteine and are critical for its biological activities . To inveTo further demonstrate a possible covalent interaction of EB with a thiol, EB was incubated with GSH and the products were examined by LC-MS. The LC-MS analysis detected two major products at m/z 652 [EB+GSH+H] and 959 [EB+2GSH+H], indicating the addition of one and two molecules of GSH to one EB respectively . The posThe above results suggested that EB may interact directly with one or more of the cysteines of STAT3 to form a covalent linkage to inhibit STAT3 activity. The STAT3 protein is composed of 6 functional domains –34, amonTo demonstrate a direct interaction of EB with the Cys712 of STAT3, we incubated EB with a bacteria-expressed STAT3 protein in vitro. We however could not detect the Cys712-containing peptide of STAT3 in LC-MS analysis. It is possible that the Cys712 of STAT3 may form disulfide bond in vitro to prevent it to be modified by EB and to be detected by mass spectral analysis . TherefoTo examine the selectivity of EB, we synthesized another cysteine-containing peptide (QP-10: QFTKCCPPKP) and incubated it with EB. The LC-MS analysis showed that its reactivity with EB was 10 times lower than that of FT-8 , demonstWe also performed a computational modeling analysis on the interaction of EB with STAT3. The results of this modeling calculation predicted an interaction between the α, β-unsaturated carbonyl group in the A ring of EB and the Cys712 near the SH2 domain of STAT3 . The molTaken together, these data provided strong evidences to support the possibility that EB directly interact with STAT3 with a covalent binding to the Cys712 of STAT3 to prevent STAT3 to be phosphorylated.STAT3 is constitutively activated and/or overexpressed in many tumor cells including non-small cell carcinoma, breast carcinoma, melanoma, and leukemia cells –39, and To understand the nature of the EB-induced cell growth inhibition, we examined the effects of EB on the induction of apoptosis, as indicated by PARP cleavage, in the A549 cells. We found that EB induced PARP cleavage in A549 cells in a dose and time-dependent fashion , indicatIFN-γ inhibits cell growth by activating STAT1 and its downstream growth inhibitory genes . At the STAT3 is an important signal transducer and transcription factor in regulating genes critical for cell growth and is often activated in tumor cells. Identification of small molecules directly targeting STAT3 has been a well-recognized strategy for treating cancer, particularly the cancer cells with constitutively activated STAT3 ,43. DiteWe presented several lines of evidences to demonstrate that EB covalently bind to the Cys712 of STAT3. First, EB contains two α, β-unsaturated carbonyl groups which are thiol reactive and may form adducts with the thiols of the cysteine in the STAT3 proteins. Second, the inhibition of STAT3 phosphorylation by EB was abolished by DTT or GSH which formed a covalent linkage with EB, possibly through a Michael addition reaction. Third, site mutagenesis of the cysteine in and near the SH2 domain of STAT3 identified the Cys712 to be the critical amino acid for the EB inhibition of STAT3 phosphorylation. Fourth, a Cys712-containing peptide of STAT3 formed a covalent complex with EB. Last but not least, computational modeling analysis indicated that the α, β-unsaturated carbonyl group in the A ring of EB was in close contact with the Cys712 of STAT3 to allow EB to attack the residue to formed a covalent linkage. Taking together, these results strongly support that a Michael addition reaction may have occurred between the α, β-unsaturated carbonyl group of EB and the thiol of Cys712 of STAT3. The covalent modification of STAT3 by EB prevented STAT3 to be phosphorylated and activated, and therefore inhibited STAT3 signaling.The interaction between EB and STAT3 appeared to be quite specific. EB only inhibited the STAT3 signaling pathway, but not the STAT1 and STAT5 signaling pathways. A sequence analysis and comparison between different STATs indicate that only STAT3 contains the Cys712 . TherefoIt was previously reported that EB induced apoptosis of tumor cells and differentiation of TH1 and TH17 cells through multiple cellular signaling pathways such as NFκB and MAPK by inducing ROS ,20,47. WThere have been several reports demonstrated the in vivo anti-tumor activities of EB ,48. The A number of small molecule inhibitors of STAT3 have been reported, including Stattic , cryptotIn summary, our study discovered a natural small molecule inhibitor of STAT3, EB, which specifically and covalently binds to Cys712 of STAT3 to inhibit its phosphorylation and activation and induces apoptosis of tumor cells, especially those whose survival and growth are dependent on STAT3. Our study not only uncovered a new compound and a new method to treat cancer, but also introduced a new tool to study the function of STAT3 and a new strategy to inactivate proteins in general.S1 Fig(A) A549 cells were pretreated with EB at indicated concentrations for 2 h before stimulation by IL-6 (10 ng/ml) for 15 min. Whole cell lysates were processed for western blot analysis with the indicated antibodies.(TIF)Click here for additional data file.S2 Fig(A) MDA-MB-231 and MDA-MB-468 cells were treated with EB at indicated concentrations for 2 h. Whole cell lysates were processed for western blot analysis using indicated antibodies.(TIF)Click here for additional data file.S3 Fig(A) EB (20 μM) was incubated with bacteria-expressed STAT3 protein (0.2 mg/ml) at 37°C for 2 h, and the products were separated by SDS-PAGE and digested by trypsin. Tryptic peptides were analyzed by mass spectrometry. The experiment was repeated three times and matched peptides were shown in bold red. (B) MS/MS analysis of Cys712 containing peptide (FIC*VTPTTCSNTIDLPMSPR). y3, y5, y6, y7, y8, y9, y10 and y11 are well matched, y12~y18 (between Cys712 and Cys718) are poorly matched, demonstrating a possible disulfide bond between two cysteines. C* represents Cys712.(TIF)Click here for additional data file.


Coherent ecological networks (EN) composed of core areas linked by ecological corridors are being developed worldwide with the goal of promoting landscape connectivity and biodiversity conservation. However, empirical assessment of the performance of EN designs is critical to evaluate the utility of these networks to mitigate effects of habitat loss and fragmentation. Landscape genetics provides a particularly valuable framework to address the question of functional connectivity by providing a direct means to investigate the effects of landscape structure on gene flow. The goals of this study are (1) to evaluate the landscape features that drive gene flow of an EN target species (European pine marten), and (2) evaluate the optimality of a regional EN design in providing connectivity for this species within the Basque Country (North Spain). Using partial Mantel tests in a reciprocal causal modeling framework we competed 59 alternative models, including isolation by distance and the regional EN. Our analysis indicated that the regional EN was among the most supported resistance models for the pine marten, but was not the best supported model. Gene flow of pine marten in northern Spain is facilitated by natural vegetation, and is resisted by anthropogenic landcover types and roads. Our results suggest that the regional EN design being implemented in the Basque Country will effectively facilitate gene flow of forest dwelling species at regional scale. Long-term biodiversity conservation requires the preservation of ecological and evolutionary processes, such as gene flow, dispersal movements and population range shifts Ecological networks have been promoted as coherent systems composed of core areas linked by ecological corridors capable of facilitating the dispersal, migration and gene flow of wild species in landscapes and regions In the design of ecological networks there is a need to predict regional ecological corridors and to quantify the degree of expected landscape connectivity between specific areas Accurate identification of the potential factors that drive gene flow in heterogenous landscapes and the scales at which they are acting is a foundation of reliable mapping of corridors Landscape genetics has shifted towards individual-based sampling and analysis, especially when organisms are continuously distributed In 2005 a regional ecological network was established in the Basque Country (North Spain) by delimiting the ecological corridors linking forest protected areas Martes martes) is the most forest dependent species 2) Among the set of functional forest mammals used in the design of the coherent regional ecological network, the European pine marten  different binary landscape resistance maps which cover a gradient from greater to lesser preference of the pine marten for forest environments in order to identify which land uses favour or impede genetic interchange in the study area; and secondly (2) whether or not the resistance map with which the regional ecological network was originally designed in the Basque Country was correctly parametrized to reflect European pine marten gene flow.If there is no effect of landscape structure on dispersal and gene flow in martens, then we expected either: (a) panmixia, where there is no genetic pattern, or (b) isolation-by-distance, where genetic differences increase with geographic distance 2 and has an average human population density of 298 inhabitants per square kilometer. Forests cover 28%, forestry plantations 29%, non-wooded mountains 24%, cultivated land 14%, and urban land and infrastructures 5.7% of the land area, respectively.The region of the Basque Country is located in the northern Iberian Peninsula  within tLand use information was obtained in vector format from the most recent forest map of Spain Martes sp. (Martes martes and Martes foina) in the study area between 2004 and 2010. Thus, no specific permissions were required for faecal sampling purposes, as the sampling was carried out without needing to intervene directly in the species in focus. We conducted a multi-stage sampling scheme, in which samples from a pilot study were used to assess the appropriateness of the sampling with respect to the research questions. Thus, two scat-based surveys were conducted between 2004 and 2010 across the sympatric range of both species in the study area. The first survey, conducted in 2004–2005, was used to initially estimate the distribution range of the two sympatric species of the genus Martes in the study area and isolate genetic samples of the focal species (M. martes). The second, conducted in 2006–2010, was used to refine species distribution information and to obtain a higher number of M. martes samples for microsatellite genotyping after a genetic species identification process M. foina), which is widespread in the study area, and can also be easily confused with those of other carnivores We used non-invasive scat sampling to collect genetic samples from the Identification of individual pine martens used nuclear DNA following methods in Ruiz-González et al. Only samples showing> 50% positive PCRs were further amplified four times at the remaining 11 loci. Samples with ambiguous results after four amplifications per locus or with <50% successful amplifications across loci were removed from further analysis as they were not considered reliable genotypes. Multiplex PCR products were run on an ABI  3130XL automated sequencer (Applied Biosystems), with the internal size standard GS500 LIZ (Applied Biosystems). Fragment analyses were conducted using the ABI software Genemapper 4.0.R = 0.95) were discarded from the analysis. GIMLET software v 1.3.4 RELIOTYPE software The raw microsatellite data and geographic coordinates of the 101 pine marten individuals are included in r inter-individual genetic distance We summarized genetic variation through the number of alleles per locus (A), expected (HE) and observed (HO) heterozygosities using GENETIX v 4.05.2 2, We produced different resistance maps representing 59 different hypotheses about the resistance of different land use types using ARCGIS version 9.3 1) Isolation by distance: Our first hypothesis and null model was a test of isolation by distance across a uniform resistance landscape 2) Binary Landscape resistance maps: Our second set of hypotheses propose that some land uses promote genetic connectivity for forest dependant species, such as the pine marten, that specialize in such habitats vs non-habitat-model). As pine martens are believed to need a minimum woodland area to survive (ca. 2km2) vs. non-habitat and parameterized the models according to a range of plausible resistance values. As there is not a general rule for the assignment of resistance values to non-habitat, we explored 4 different resistance values  of non-habitat relative to habitat to verify if it could affect the detectability of landscape genetic relationships, as it has been previously shown in both empirical x to Land_Gx; With barrier effect: Land_Abx to Land_Gbx; where X corresponds to the 4 evaluated resistances values per model: 5, 25, 50, and 100) , highways, urban areas, reservoirs and quarries (resistance 1000)  .3) Ecological network resistance map: We evaluated the resistance map previously utilized in the design of ecological corridors linking forest Natura 2000 areas of the Basque Country The raw ascii file of the EN is included in The effective and Euclidean distances between each pair of individuals were calculated with PATHMATRIX 1.1 We proposed 59 alternative landscape models: 1) 56 binary landscape resistance maps; 2) two complex resistance maps based on the resistance surfaces used to develop the regional ecological network (EN and ENnb) , and 3) r) was correlated with different matrices of geographical and (cost) distances encompassing a total number of 5151 pairwise comparisons, including: i) Euclidean distance, to determine whether the patterns of differentiation follow an isolation by distance pattern (null hypothesis) and ii) the effective distances calculated for each of the 58 resistance maps, to infer landscape structure effects on gene flow. The correlation between distance matrixes was calculated by means of the Mantel test The pairwise genetic distances matrix  Mantel tests in a reciprocal causal modeling framework Martes sp. (M. martes and M. foina) based on genetic species identification results. Thus, unequivocal species identification was possible in 83.45% of the samples. We effectively identified 232 faecal samples as stone marten and 262 as pine marten. Additionally, we obtained 57 tissue samples from road-killed pine martens.Out of 733 faecal samples collected from the entire study area, 141 were discarded because they were not fresh or because they presumably belong to the same individual (samples separated by <1km). 494 out of 592 analyzed samples were classified as Out of 262 faecal samples identified as pine marten, 108 were not included to the microsatellite genotyping procedure. These samples correspond to the sampling period from 2004–2005, which was used for a first distribution assessment of sympatric martens in the study area and were not potentially fresh enough for microsatellite analysis. Thus, 213 pine marten samples  were used for microsatellite genotyping.The first quality-screening test, based on 4 replicates of four loci, was not passed by 73 non-invasive samples (47.40%), which were immediately discarded. The remaining 81 samples (52.59%) were amplified at the other 11 loci. After multiple-tubes genotyping, 27 samples from this sub-set  were then discarded because they showed <50% PCR success, or because of high failure rates. Full multilocus microsatellite genotypes were obtained for the remaining 54 samples  all showing reliability score> 0.95 −10, and with a probability of 4.45×10−5 for a full-sib, suggesting no “shadow effect”  and expected (HE) heterozygosity values were 0.53 and 0.58, respectively . All 15 We evaluated the unimodality of support across the 56 binary resistance maps for the log transformed and untransformed data to determine which form of the data should be used for subsequent analyses. After the effects of distance are partialled out, ranking the models by partial Mantel r value provides a means to determine which hypotheses have the greatest support and to identify the most related model to the genetic structure , Fig. 3.1) Isolation by distance: A significant positive correlation was obtained between the genetic distances and Euclidean distances , bearing clear witness to the existence of a pattern of isolation by distance (IBD) (ce (IBD) , Fig. 3.ce (IBD) , Fig. 4.2) Binary resistance maps: All of the simple Mantel tests were significant when analyzed in log-transformed form  Ecological network resistance map: The effective distances calculated on the basis of the EN map were positively correlated with genetic distances and explained a slightly higher proportion of the observed genetic variance than the Euclidean distances , as the relationship between genetic distance and effective distance was always significant when Euclidean distance was factored out of the relationship (p <0.05) .1) Binary landscape resistance maps: The correlation values after factoring out the effect of Euclidean distance showed the same pattern of increase of that obtained by means of a simple Mantel test, with Land_Fb50 showing the highest partial Mantel r correlation  Ecological network resistance map: Both EN and ENnb models appeared better supported than the null model of IBD as this latter retained a significant positive relationship with ar-based genetic distance after factoring out the effects of Euclidean distance, but less supported than the top resistance models  <Land_C(b) <Land_D(b) <Land_E(b)<Land_F(b)]. Original causal modeling identified the same pattern and suggested that Land_Eb and Land_Fb for resistance values of 50 and 100 are the most supported models. Likewise, novel reciprocal causal modeling highlighted similar results, identifying Land_Fb100 as the uniquely supported model, due to its greater discriminatory power These results are in consonance with recent ecological studies of European pine martens, based on radio tracking, which provide new data substantially differing from traditional descriptions in the scientific literature as strictly forest dependant species Additionally, models that increase the barrier effect of major roads and urban areas leads to a substantial improvement in the correlation between genetic distances and cost distances. The correlation with models Land_Ab-Land_Fb was greater than that obtained with models Land_A-Land_F, and the uniquely supported model in reciprocal causal modeling included the barrier effect (Land_Fb100). This suggests that the potential barrier effect of these land uses could have a synergic effect within a fragmented landscape, decreasing the gene flow due to road avoidance behaviour and/or road mortality Martes sp., providing contrasting results regarding landscape effects on gene flow Martes americana) dispersal in Ontario is impeded by the loss and fragmentation of suitable habitat. Wasserman et al. Similar landscape genetics studies have also been conducted on other forest dependant Even though no previous individual-based landscape genetics data was available for the pine marten, Mergey et al. Maps of ecological corridors are commonly used in land use planning, but unfortunately are more often the product of expert opinion rather than empirical data Thus, the resistance map with which the regional ecological network was originally designed in the Basque Country (EN), appears to have high congruence with one of its official target species at regional scale Since our ability to detect the effects of landscape structure on genetic differentiation depends on both the landscape features used and the relative costs of each feature, different resistance values could provide different results Some landscape genetic studies have found that the untransformed geographic distances perform better than logarithmic transformation e.g. , while mThis paper presents a comprehensive individual-based landscape genetic analysis of the European pine marten, and the first formal use of landscape genetics to evaluate the effectiveness of regional ecological networks. We compared results from several methods of model selection and found that ranking based on Mantel r or partial Mantel r, the unimodality of support in the hypothesis cube, causal modeling and reciprocal causal modeling all identified the same best models of landscape resistance for European pine marten in northern Spain. Reciprocal causal modeling appeared to provide the strongest differentiation among hypotheses and enabled the identification of a single, independently supported model. Gene flow of European pine marten is facilitated by natural land cover, such as forest, scrublands and pastures and meadows, and is resisted by anthropogenic land uses and linear barriers such as major roads. We confirm that the resistance map used to develop the regional ecological network in the Basque Country is a close surrogate to the empirically optimized resistance model for marten.Figure S1Mantel Correlation values for a) Land_A-Land_G and b) Land_Ab-Land_Gb models for the 4 different cost values evaluated on the log transformed cost distances.(TIF)Click here for additional data file.Figure S2Partial Mantel Correlation values for a) Land_A-Land_G and b) Land_Ab-Land_G models for the 4 different cost values evaluated on the log transformed cost distances.(TIF)Click here for additional data file.Figure S3Mantel Correlation values for a) Land_A-Land_G and b) Land_Ab-Land_G models for the 4 different cost values evaluated on the untransformed cost distances.(TIF)Click here for additional data file.Figure S4Partial Mantel Correlation values for a) Land_A-Land_G and b) Land_Ab-Land_G models for the 4 different cost values evaluated on the untransformed cost distances.(TIF)Click here for additional data file.Table S1Summary of the genetic variability. Genetic variability of the 15 microsatellite loci multiplexed used in this study. Number of alleles (NA), Observed (HO) and expected (HE) heterozygosities for each locus and for whole data set.. Loci marked with an asterisk deviated from Hardy-Weinberg proportions.(DOC)Click here for additional data file.Table S2Sample locations and microsatellite data. Complete genetic profiles (15 microsatellite loci) and the geographic coordinates for the 101 pine marten individuals(XLS)Click here for additional data file.Table S3Resultsof causal modeling of landscape resistance on genetic distance in European pine marten according to Mantel and partial mantel tests for the untransformed distances.(DOC)Click here for additional data file.File S1Ecological network resistance map. Raw '.asc' file of the EN resistance map from which all the resistance maps evaluated can be produced following the resistance values outlined in (ZIP)Click here for additional data file.


Most giant groupers in the market are derived from inbred stock. Inbreeding can cause trait depression, compromising the animals’ fitness and disease resistance, obligating farmers to apply increased amounts of drugs. In order to solve this problem, a pedigree classification method is needed. Here, microsatellite and mitochondrial DNA were used as genetic markers to analyze the genetic relationships among giant grouper broodstocks. The 776-bp fragment of high polymorphic mitochondrial D-loop sequence was selected for measuring sibling relatedness. In a sample of 118 giant groupers, 42 haplotypes were categorized, with nucleotide diversity (π) of 0.00773 and haplotype diversity (HD) of 0.983. Furthermore, microsatellites were used for investigation of parentage. Six out of 33 microsatellite loci were selected as markers based on having a high number of alleles and compliance with Hardy-Weinberg equilibrium. Microsatellite profiles based on these loci provide high variability with low combined non-exclusion probability, permitting practical use in aquaculture. The method described here could be used to improve grouper broodstock management and lower the chances of inbreeding. This approach is expected to lead to production of higher quality groupers with higher disease resistance, thereby reducing the need for drug application. The numbers of domesticated and farmed fish are increasing to facilitate feeding of the burgeoning human population . More thMicrosatellite and mitochondria markers have been used previously for tracking the genetic history of groupers ,20,21,22Within the 776-nt D-loop fragment examined here, 56 nucleotides exhibited variations, including insertion and deletion, among the 118 giant grouper broodstocks . Among tIn other developed systems, either of two distinct genetic markers  has been used to assess variation within populations and to identify individuals. Low variation in D-loop nucleotide sequences of this fish species from our investigation suggested that the broodstock inbreeding level in Taiwan is high.Examination of the results for microsatellite loci in giant grouper  revealedBy applying these six loci to a subset of 64 fish, the first parent non-exclusion probability is 0.01138738 (or 98.86% accurate) which we can identify the parentage relationship without knowing the genotypes of both parent fish. The non-exclusion probability (second parent) will lower (0.00089627 or 99.91% accurate) when one of the parent fish genotype is known . It is iKnowing the origin of the broodstock can help to preclude collection of genetically closely related fish. We collected the samples from farms known to constantly replenish the broodstock from wild-caught fish or by purchasing small numbers of giant groupers from each of multiple different fish farms. This approach is recommended, since it can increase genetic variation within the fish population.The observed large numbers of haplotypes  and high allele numbers  indicate that our samples were derived from different genetic pools. Nevertheless, the present study analyzed only a small number of giant groupers; the sample sizes of future studies will affect the determination of the number of D-loop haplotypes, number of microsatellite loci alleles, and their combined non-exclusive probabilities. Analysis of mitochondrial D-loop alone may have limitations. Offspring from a single female are expected to share a single mitochondrial haplotype . HoweverThe fin tissue samples from 118 individual broodstock animals were collected in three different locations (Linbian (44 fish), Jiadong (64 fish), and Fangliao (10 fish); −1 of proteinase K, then incubated at 55 °C in a water bath until the tissue was completely dissolved. After lysis was completed, 20 μL of RNaes A (10 μg/mL) was added to the tube, and then incubated at 37 °C for 1 h. DNA extraction was performed using the phenol-chloroform  method. Following precipitation in 99% ethanol, air dry and resuspension in TE buffer .A piece of fin tissue (100 mg) sampled from each grouper was subjected to the following DNA extraction procedure. The fin tissue was homogenized in 1 mL of extraction buffer  with 100 μg mLFull-length  giant grouper mitochondrial DNA, as sequenced by our laboratory (accession number: KJ451389), was used for primer design. The forward (ATCATCGGCCAAATCGCATC) and reverse (GAACTGTAGGGCATTCTCAC) primers were designed to amplify a 1259-bp fragment. We then focused on the 776-bp D-loop sequence. Genetic analysis, including nucleotide composition, mutation rate, nucleotide diversity (π) , haplotyEpinephelus lanceolatus [E. guttatus [E. fuscoguttatus [E. coioides [E. quernus [E. awoara [The selection of the potential microsatellite loci as genetic markers in our species was based on previous studies. Primer design focused on several loci described in previous studies for various species , includiceolatus , E. guttguttatus , E. fuscguttatus , E. coiocoioides , E. quer quernus  and E. a. awoara . The PCRThe number of alleles for each locus, distribution of alleles, observed heterozygosity (OH), expected heterozygosity (EH), and agreement with Hardy-Weinberg equilibrium was measured using MSA 4.05  softwareSo far, there are about 300 male giant grouper broodstocks in Taiwan. Collection the genetic information from microsatellite to develop markers for each broodstock will be crucial for addressing the problem of inbreeding. For the techniques described in the present work, the mitochondrial D-loop should be used first to determine the potential sibling relationships among fish; biogeographic analysis then can be used to identify the individual broodstock to reduce inbreeding. Furthermore, the marker can be used to preclude the offspring from parent fish which shared the same microsatellite pattern but different in mitochondrial DNA sequence. In fact, the numbers of male broodstock typically are much lower than those of female broodstock, so maintenance of a separate male broodstock  may constitute an effective way to manage the genetic variation of farmed giant grouper.


Polistes nimpha belongs to primitively eusocial wasps for which no data are available on its population’s genetic structure and relatedness/relationships of individuals. The purpose of this research is to determine the amplification efficiency in P. nimpha of microsatellite primers developed for P. dominula and using these primers, to explore genetic diversity, population structure and relatedness/relationship of P. nimpha in the context of its reproductive options. Eight out of twelve microsatellite markers analyzed on 59 individuals (pupae and larvae) were polymorphic (mean PIC = 0.545) and mutated following the stepwise mutation model. The Bayesian clustering method gave the probability of >0.898 of there being 10 clusters within the pooled sample of 15 nests. In two or three nest clusters, full- and/or half-siblings and unrelated individuals occurred. A significant correlation between genetic and geographic distances was detected. There are three main possibilities that come into play to explain our genetic results and direct field observations: cooperative nest foundation, visitations, and/or usurpation events. So far there is no conclusive evidence to exclude or support any of these possibilities.The Eurasiatic The online version of this article (doi:10.1007/s00040-015-0421-7) contains supplementary material, which is available to authorized users. Polistes (Hymenoptera: Vespidae) comprises more than 200 wasp species representing a primitively eusocial group of insects  (Polistinae).There are a limited number of studies that have been devoted to identification and the analysis of microsatellite loci in Polistes nimpha is one of the three species of the genus that can be found in Poland  and P. carolina (L. 1767)  to determine the amplification efficiency and polymorphism of P. dominula microsatellites (Henshaw P. nimpha and (2) to explore genetic evidence for possible reproductive options in this species.This study represents the first attempt to understand genetic diversity and population structure and relatedness/relationship between individuals of  Henshaw  in P. ni2) where nest sites occur were selected in April 2014.The study area was located at the edges of a military training field near the city of Poznań, Poland Fig. . Three aP. nimpha. The initial nest searching began on May 12, 2014, and each recorded nest was revisited at approximately 7–10 (21)-day intervals. Nests were watched at forenoon hours 8:00 a.m. to 12:00 noon during the active hours of the inhabitants. One week after the nest identification, from May 19 to May 23, 2014, foundresses of P. nimpha were marked individually. Each nest was observed for 45 min per week during the following 5 weeks until days after the first workers’ appearances. Nest contents, a number of cells, and causes of nest failure were documented. Nests were considered as inactive if foundress was not present on the nest for two consecutive following checks. All nests have been marked with numbered tags. Moreover, the nest locations were measured at their latitude and longitude coordinates.Established plots were searched thoroughly for nests of For genetic analysis, fifty-nine individuals were collected on June 9, 2014 from 15 nests (two pupae and two larvae per nest), except one nest from which one pupa and two larvae were taken. The pupae and larvae were preserved in 95 % alcohol and stored at low temperature (4 °C). Vouchers are deposited in the Department of Systematic Zoology, Faculty of Biology, Adam Mickiewicz University in Poznań, Poland.Genomic DNA was extracted from the legs of each pupa (right leg of the second pair) or from ca. P. dominula  collected from 15 nests. To describe informativeness of genetic markers related to expected heterozygosity, the polymorphism information content (PIC) values were calculated using the program Cervus. The program Micro-Checker v. 2.2.3 , as implemented in the program GenPop v. 4.2 (Raymond and Rousset http://kimura.univ-montp2.fr/~rousset/Genepop.htm), using 1000 dememorization steps, 100 batches, and 1000 iterations per batch. To assess the Hardy–Weinberg equilibrium for each locus, the goodness-of-fit Chi-square tests , population stratification, and/or null alleles. The deviation from Hardy–Weinberg proportions caused by heterozygote excess was tested with a global test  was conducted using Nei’s unbiased distance pairwise matrix to test whether patterns in microsatellite data support the partitioning of the sample into BAPS clusters.To assign individuals to groups based on their multilocus genotypes, a Bayesian clustering algorithm was used, as implemented in the BAPS software version 6.0 at As suggested by Frantz et al. , it is ir) was calculated to measure associations between the relatedness estimators using Statistica v. 10.0 (Statsoft). A t test was performed with the same program to determine whether differences between means of relatedness are significant between distinguished groups.Kinship analysis, which relies on a model that assigns dyads to discrete relationship categories   Fig. . At the ks) Fig. . MateriaThe nest destruction was not witnessed, but trace evidence examinations allowed us to conclude that activities of large animals , invertebrates  and/or humans had destroyed the nests. In over 80 % of the cases, the mammals’ activity was the most important predictor of nest mortality. For a large proportion of nests, the reason for their failure is unknown. The degree of destruction varied substantially across sites; only stalks of nests remained (the comb had been damaged), or inhabitants had been eaten, but the nest (comb) had remained untouched Table .Table 1PP. nimpha on May 8, 2014 and May 14, 2014.Due to the considerable nest mortality Fig. , only 42Pdom 1, 2, 7, 20, 25, 93, 117, 121, 127, 139, 140) were polymorphic, and one locus (Pdom 151) was monomorphic (Table S1). Only eight polymorphic loci had a size variation consistent with the occurrence of strictly stepwise mutations in the repeat array. The remaining primers  showed more complex patterns of evolution (nonstepwise mutations). These three loci were excluded; thus the truncated set contains data for eight microsatellite loci collected from 59 individuals. Large allele dropout and stuttering were not detected. At the locus Pdom 7, missing data for four individuals probably appeared because of mutations in the primer binding sites.High rates of microsatellite amplification were observed. From a total of 13 primer pairs, 12 pairs that amplify without any problems were chosen for genetic analysis. Table S1 shows the characteristics of the pursued and nonamplifiable pair of primers. Eleven microsatellite loci  was equal to 0.545, ranging from 0.033 (Pdom 93) to above 0.5 . The latter four loci are highly polymorphic. The mean number of different alleles per locus was 6.875, ranging from 2 (Pdom 93) to 11 (Pdom 7). The mean expected heterozygosity was 0.5765 (unbiased expected heterozygosity UHe = 0.577), meaning that there is a >57 % chance of being a heterozygote under random mating conditions. The average value of the observed heterozygosity (Ho) was slightly higher than Hardy–Weinberg expectations, Ho = 0.588. However, no significant deviations from Hardy–Weinberg equilibrium were observed for the alternative hypothesis of heterozygote excess (H1), (P = 0.433 ± SE 0.020). Chi-square tests for individual loci showed a significant deviation (P < 0.05) for Pdom 20 , (Table S2).Standard measures of genetic diversity in To relate observable structure (nests) to the genetic structure of analyzed population, a model-based clustering was employed. Taking genetic information into account, the Bayesian clustering method, based on the individual-level clustering model for unlinked markers, gave the probability of >0.898 of being 10 genetic clusters within the pooled sample of 15 nests . The inferred six clusters  were coherent in terms of wasps’ nests . The remaining clusters 1–3, 5) were composed of all individuals originated from two nests  or three nests (cluster 3). The principal coordinate analysis (PCoA) results broadly confirmed the grouping based on BAPS analysis. In the PCoA, the individuals were grouped accordingly, but only 40.97 % of the variation in the input data has been captured by the first three axes (PCoA 1–3), ; thus, it can be concluded that genetic differences among individuals do increase linearly with geographic distance.In the case of organism’s limited dispersal ability, we expect an isolation-by-distance type of population structure, in which genetic similarity is contrarily related to geographical distance calculations . Based on the method-of-moments estimators, the BAPS clusters composed of individuals originated from two or three nests  expressed significantly lower levels of relatedness coefficients (P < 0.05) than did the second group composed of one-nest clusters   were based on the maximal likelihood. All pairwise comparisons between individuals classified to mixed cluster no. 1 , the method-of-moments estimators is commonly preferred  in which only some individuals that originated from different nests are full-sibs and the others are unrelated may indicate three main reproductive tactics in the population of this species: short visits of foundresses, cooperative (pleometrotic) nest foundations, and/or nest usurpation. These tactics in Polistes wasps are hypothesized to have different fitness payoffs over time, depending on environmental shifts   . As was hypothesized by Gamboa  nests. Nevertheless, this kind of cooperation cannot be fully excluded due to methodological reasons (marking of wasps was performed shortly after eggs were laid but before offspring emerged). So far, in P. nimpha, pleometrotic nest foundation was detected only at sites where the aggregation of sibling females was possible during the winter  (Turillazzi and Cervo 1985: 49). The winter destruction of plants and difficulties in the aggregation of females that build nests on this kind of substratum were hypothesized to be main factors for nest foundation by a single foundress (Turillazzi and Cervo 1985). Based on materials, we collected from the nests built on vegetation; the single-foundress colonies comprise only 50 % of detected BAPS clusters. Thus, the causes of pleometrotic nest foundation have yet to be investigated and determined.Pleometrotic nest foundation was described for y Gamboa  and Tibby Gamboa , multiplP. nimpha from our genetic data. The possibilities of laying eggs by visiting, nonaggressive wasps in the nests of sibling females or intraspecific usurpation cannot be excluded based on our direct field observations. It should be underlined, however, that in the case of unmarked wasps, there are always difficulties in differentiating a visitor, a joiner, a switcher, an adopter, or a usurper (Nonacs and Reeve 1985). The case of cluster no. 1 being composed of two nests in which full-siblings were found is a prime example of ambiguity because the interpretation could be twofold: eggs were laid by one queen who was fertilized by related males, or eggs were laid by a pair of full sisters. The former phenomenon was discovered for the first time by Seppä et al.  from the natal nest (Hirose and Yamasaki P. olivaceus (De Geer) was detected .However, the tendency of individuals originating from two or three different nests to cluster together can reflect close affinity of some individuals or be a result of stochastic error , usurping established colonies, or joining other queens (Nonacs and Reeve 1985). Based on our data, no nests rebuilding or joining has been observed Supplementary material 2 (PDF 195 kb)Supplementary material 3 (PDF 111 kb)Supplementary material 4 (PDF 191 kb)


Crocidura olivieri complex. We tested the respective role of forest retraction/expansion during the Pleistocene, rivers , ecological gradients (parapatric model) and anthropogenic factors in explaining the distribution and diversification within this species complex. We sequenced three mitochondrial and four nuclear markers from 565 specimens encompassing the known distribution of the complex, i.e. from Morocco to Egypt and south to Mozambique. We used Bayesian phylogenetic inference, genetic structure analyses and divergence time estimates to assess the phylogenetic relationships and evolutionary history of these animals.This study aims to reconstruct the evolutionary history of African shrews referred to the C. olivieri complex  can be segregated into eight principal geographical clades, most exhibiting parapatric distributions. A decrease in genetic diversity was observed between central and western African clades and a marked signal of population expansion was detected for a broadly distributed clade occurring across central and eastern Africa and portions of Egypt (clade IV). The main cladogenesis events occurred within the complex between 1.37 and 0.48 Ma. Crocidura olivieri sensu stricto appears polyphyletic and C. viaria and C. fulvastra were not found to be monophyletic.The C. olivieri complex.Climatic oscillations over the Pleistocene probably played a major role in shaping the genetic diversity within this species complex. Different factors can explain their diversification, including Pleistocene forest refuges, riverine barriers and differentiation along environmental gradients. The earliest postulated members of the complex originated in central/eastern Africa and the first radiations took place in rain forests of the Congo Basin. A dramatic shift in the ecological requirements in early members of the complex, in association with changing environments, took place sometime after 1.13 Ma. Some lineages then colonized a substantial portion of the African continent, including a variety of savannah and forest habitats. The low genetic divergence of certain populations, some in isolated localities, can be explained by their synanthropic habits. This study underlines the need to revise the taxonomy of the The online version of this article (doi:10.1186/s12862-015-0344-y) contains supplementary material, which is available to authorized users. Crocidura olivieri  complex . Accession numbers are provided in Additional file The sequence data supporting the results of this article are available in the GenBank repository [