Activated B-cell-like diffuse large B-cell lymphoma (ABC DLBCL) is characterized by increased expression and activator of signal transducer and activator of transcription 3 (STAT3). ABC DLBCL cells require STAT3 for growth in culture. In ABC DLBCL cells, eosinophils and perhaps all cells, four variant STAT3 mRNAs  are present as a result of two alternative splicing events, one that results in the inclusion of a 55-residue C-terminal transactivation domain (α) or a truncated C-terminal domain with 7 unique residues (β) and a second that includes (S) or excludes (ΔS) the codon for Ser-701 in the linker between the SH2 and C-terminal domains. A substantial literature indicates that both α and β variants are required for optimal STAT3 function, but nothing is known about functions of ΔS variants. We used a knockdown/re-expression strategy to explore whether survival of ABC DLBCL cells requires that the four variants be in an appropriate ratio. No single variant rescued survival as well as STAT3Sα-C, Sα with activating mutations (A661C and N663C) in the SH2 domain. Better rescue was achieved when all four variants were re-expressed or Sα and ΔSα or Sβ and ΔSβ were re-expressed in pairs. Rescue correlated with expression of STAT3-sensitive genes NFKBIA and NFKBIZ. We consider a variety of explanations why a mix of S and ΔS variants of STAT3 should enable survival of ABC DLBCL cells. Phosphorylation of Thr-714 and Ser-727 is also required for optimal transcriptional activity.16 STAT3 has two well-characterized splice variants, STAT3α and β, because of alternative splicing that results in a 55-residue transactivation domain (α) or truncation of the domain with 7 unique C-terminal residues (β).19 Consistent with the absence from STAT3β of most of the C-terminal transactivation domain and Ser-727, initial biochemical analyses suggested that STAT3β blocks the transcriptional function of the STAT3α protein in a dominant-negative manner.18 A gene-targeting mouse study, however, did not support this conclusion, demonstrating that STAT3β expression can rescue the embryonic lethality of a complete STAT3 deletion and activate specific STAT3 target genes.20 Despite functional overlap between the two variants, STAT3α also was shown to have non-redundant roles in modulation of cellular responses to IL-6 or IL-10.20STAT3 is activated by phosphorylation of Tyr-705, which can be catalyzed by JAKs working downstream of cytokine or growth factor receptors and by several non-receptor tyrosine kinases.21 We detected mRNAs of the ΔS variants in both eosinophils and ABC DLBCL cells and found comparable splice variant ratios  despite differences in total levels of STAT3 transcripts in the two types of cells.21 There was a tendency for the β splicing event to be paired with the ΔS splicing event, indicating that the two events are not completely independent. Analysis of publicly-available RNA-Seq data of 16 human tissues (GEO accession GSE30611) revealed that the ΔS variants account for 10–26% of the total,21 in accord with a prior investigation of tandem alternate donor splicing in which STAT3's ΔS proportion was consistently around 17% of total in human and mice leukocytes.22 Thus, although ΔS STAT3 variants are less abundant than S, the ΔS/S ratio remains relatively constant in tissues.21 Further, the ratio is conserved among species.22 These findings suggest that ΔS/S splicing is functionally indispensible, that is, function of STAT3 depends on having a mix of proteins that have or lack Ser-701.The existence of the α and β splice variants may not totally account for functional heterogeneity of STAT3. There are two other splice variants, STAT3ΔSα and ΔSβ, which are a result of a second splicing event that includes (S) or excludes (ΔS) the codon for Ser-701 in the linker between the SH2 and C-terminal domains.23 Better rescue was achieved when all four variants were re-expressed or Sα and ΔSα or Sβ and ΔSβ were re-expressed in pairs. Rescue correlated with expression of STAT3-sensitive genes NFKBIA and NFKBIZ. These results indicate that the mix of S/ΔS splicing is indeed required for optimal STAT3 function.Here, we performed functional analysis of the four STAT3 variants in STAT3-dependent ABC DLBCL cells. We used a knockdown/re-expression strategy to examine whether individual variants or their different combinations reversed the toxicity of shRNAs that selectively target endogenous STAT3. The results showed that no single variant rescued survival as well as STAT3Sα-C, an oncogenic Sα variant with activating mutations in the SH2 domain.24 The GCB cell line OCI-Ly19 with no constitutive STAT3 activation served as a control. To re-evaluate a survival role for STAT3, we generated two small hairpin (sh) RNAs against the common 3'UTR for all four splice variants and retrovirally transduced the shRNAs into these lymphoma cells along with the marker GFP; the percentage of GFP+ cells was calculated by flow-cytometric analysis during 12 days of observation  control  are present in OCI-Ly10 and HBL1 cells, with a similar expression pattern to eosinophils.l vector . The vec control . In HBL1 control .9 it should be possible to activate expressed variant STAT3 and thus replace activation of endogenous STAT3s. Both Sα and Sβ variants reacted with the D3A7 monoclonal anti-phospho-Tyr-705 antibody, with reactivity with Sβ being greater than with Sα  is unexplored. In this study, we used a knockdown/re-expression strategy to dissect the role of the STAT3 variants in the survival of STAT3-dependent ABC DLBCL cells; that is, whether expression of the individual STAT3 variants or different combinations rescues cell death caused by STAT3 shRNAs that target 3′UTR of endogenous STAT3. We found that any single variant was not sufficient to reverse STAT3 shRNA-mediated cell toxicity, the best being a moderate rescue by Sα, the most abundant variant (~80% in DLBCL). However, expression of a pair of Sα and ΔSα, a pair of Sβ and ΔSβ, or all four variants had a better rescue efficiency. These findings suggest that dimerization with a STAT3ΔS is required for optimal function of STAT3. The rescue mediated by these variants likely depends on their transcriptional activity given a positive correlation between rescue efficiency and expression of STAT3-sensitive genes NFKBIA and NFKBIZ.STAT3 is best known as forming a homo- or heterodimer for transcriptional activity and functionality.4 Phosphorylation of residue Tyr-705 (Tyr-704 in ΔS variants) accompanies canonical STAT3 activation. Ser-701 can be phosphorylated in the presence or absence of Tyr-705 phosphorylation.29 Furthermore, Tyr-704 of STAT3 ΔS splice variants can be phosphorylated,26 although as discussed in Results the anti-phospho-Tyr-705 monoclonal antibody we used may have been unable to detect the pTyr-704 epitope  and Thr-713/714.16 Further investigations will require methods to analyze phosphoform distribution, how the distribution is influenced by different signaling axes and the effects of the phosphoforms on STAT3-modulated transcription.The molecular mechanisms underlying functionalities of the variants with Ser-701 deletion are unknown. Recent large-scale proteomics studies may provide insight into the phosphostatus of STAT3 ΔS variants. The stability of phospho-Tyr-704/5 differs in α and β. epitope . Thus, fet al.31). STAT3 is able to form α-α, β-β and α-β dimers; and electrophoretic mobility shift assay (EMSA) competition assays suggest that α preferentially dimerizes with β rather than another α, leading to a factor with decreased transcription efficiency.18 The significance of STAT3 ΔS splice variants in dimerization has not been investigated. Our data may indicate that in Sα-Sβ combinations, the STAT3 heterodimer level is too high, decreasing transcription efficiency. In a pilot experiment, over-expression of any of the variants with the GFP retroviral vector on top of endogenous proteins was toxic to the lymphoma cells (loss of 30–50% of GFP+ cells from culture), which suggests that maintaining of a natural ratio of STAT3 variants is critical for cell fitness.The rescue efficiency was better upon transducing pairs of splice variants. The best pairs were Sα+Δα and Sβ+Δβ, whereas rescue by Sα+ΔSβ and ΔSα+Sβ was poor . Given tThe experimental system was limited by inability to control or measure endogenous STAT3 facilely after knockdown. The immunoblotting and qPCR were performed at day 5 post induction, while rescue was assessed at day 12 when STAT3 levels are more likely to be determined by the constructs. Further, we do not know the full panel of genes required for lymphoma cell viability. Expression of any single variant sustained expression of NFKBIA and NFKBIZ after knockdown of endogenous STAT3 . It is p17 STAT3 can dimerize with STAT5a/b32 and STAT1.33 In ABC DLBCL, the IFN-STAT1 pathway is lethal and thus basal STAT1 activity is low.34 Unphosphorylated STAT3 can bind to p65 of NF-κB.35 All of these proteins are expressed in ABC DLBCL.36 We cannot rule out the possibility of these interactions in DLBCL cells, but dimerization with non-STAT3 proteins seems unlikely to be functionally important, given little or no rescue by any of the single variants of STAT3.Adding to the complexity, STAT3 can dimerize with other members of the STAT family or even other proteins. STAT3Sβ increases its transcriptional activity by interacting with c-Jun.In summary, the data presented here indicate that a pair of S and ΔS variants are required for optimal STAT3 function in ABC DLBCL cells, including maintaining cell survival and activating the target genes NFKBIA and NFKBIZ. This functional analysis offers a starting point for the study of ΔS variants. Further research includes structural assessments of dimerization of the S and ΔS variants and genome-wide analysis of transcriptional activity of the ΔS variants.37 Doxycycline (20 ng/ml) was used for inducing the expression of genes of interest. The cell lines were grown in RPMI-1640 media  supplemented with 20% FBS , 100 U/ml penicillin, 100 μg/ml streptomycin , 2 mm GlutaGRO (Corning Cellgro), 1 × MEM-NEAA  and 1 mm Sodium Pyruvate Solution (Hyclone). All cultures were routinely tested for mycoplasma contamination. Human embryonic kidney cell line 293 T was cultured in DMEM  with 10% FBS. All cell lines were cultured at 37 °C in a 5% CO2 atmosphere.Doxycycline-inducible human diffuse large B-cell lymphoma cell lines  that express the bacterial tetracycline repressor were engineered as described previously.21 STAT3 variants, Sα, ΔSα, Sβ and ΔSβ were amplified by PCR and cloned into the HindIII and Xho1 restriction sites of pcDNA3.1+. A silent mutation, encoding for a Spe1 site, at Leu670 was added to aid in downstream sequence manipulation. The complete sequence of inserts was verified before transferring to pRetroCMV/TO vectors, which are inducible CMV/TO retroviral vectors (eGFP negative) with a selection marker hygromycin.38 Four full-length STAT3 variants were each subcloned into another inducible CMV/TO retroviral vector (eGFP+) with a selection marker hygromycin.38 These retroviral vectors of STAT3 variants were used for subsequent transfection into DLBCL cell lines. The STAT3Sα-C (constitutively active STAT3) plasmid was a gift from the Lou Staudt lab . STAT3 shRNAs were prepared in a doxycycline-inducible retroviral vector with a selection marker puromycin as described previously,37 with sequences of shSTAT3 #1 , shSTAT3 #2 . These STAT3 shRNAs only target total endogenous STAT3 expression, and have no effect on exogenous STAT3.STAT3 constructs were amplified from eosinophil RNA by RT–PCR and cloned into pcDNA3.1+ using standard molecular biology techniques. Briefly, eosinophil RNA was isolated, and cDNA was generated using random primers and SuperScript III first-strand synthesis system .The ABC DLBCL cell lines HBL1 and OCI-Ly10 and GCB DLBCL cell line OCI-Ly19 were infected by retroviral supernatants. The infected cells were selected with puromycin (1 μg/ml) or hygromycin (200–500 μg/ml) for 2 weeks to generate different stable cell lines or 1 week for selection of shRNA-expressing cells.Cell viability was measured with an automatic cell counter according to the manufacturer's instructions. Briefly, cells were harvested and suspended, and mixed with equal volume of 0.4% trypan blue. Ten microliters of the cell suspension was loaded onto TC20 system  counting slides, and the percentage of viable cells was quantified on a TC20 automated cell counter (Bio-Rad).For analysis of cell survival rate, cells were collected and washed twice with cold phosphate-buffered saline. GFP-positive cells were analyzed with BD AccuriTM C6 . Data were analyzed by the Flowjo software .m HEPES, 4 mm sodium pyrophosphate, 10 mm sodium fluoride, 2 mm orthovanadate, 100 mm NaCl, 10 mm EDTA, pH 7.5) with protease inhibitor cocktail . Protein concentrations were determined by BCA assay . Proteins were separated by SDS–PAGE and transferred onto nitrocellulose membranes. After blocking with non-fat milk, the membrane was probed with primary antibodies against proteins of interest. The primary antibodies included anti-STAT3pan , anti-STAT3α , anti-STAT3β,27 anti-phospho-STAT3 (Tyr-705) (D3A7) , anti-NFKBIA , anti-NFKBIZ , anti-α-tubulin , anti-β-actin  and anti-histone-H3 . After blotting with the HRP-conjugated secondary antibody, the membrane was developed using a chemiluminescence HRP substrate kit (Thermo Scientific). Specificities of the anti-STAT3α and anti-STAT3β antibodies for the respective ΔS variants were demonstrated by western blotting of mini-proteins expressed for each of the four variants and comprising the SH2 module through the C-terminal of the variant.Cells were lysed using MAPK lysis buffer  was used for relative qPCR, with GAPDH as a reference gene.39 By combining absolute and relative qPCR quantification data, mRNA levels were calculated: mRNA level=pan-STAT3 mRNA level (relative qPCR quantification) × STAT3 isoform percentage (absolute qPCR quantification).Total RNA was extracted using the RNeasy Plus Mini Kit  according to the manufacturer's protocol, and quantified with a Nanodrop lite spectrophotometer (Thermo Scientific). For each sample, 2 μg RNA was reverse transcribed with a first-strand cDNA synthesis kit . All quantification was performed using an ABI Stepone Plus Real-Time PCR System  in 96-well optical reaction plates. Primers were designed for absolute splice variant quantification, with reference to constructs of known concentration, as described previously.t-test and two-way ANOVA were performed to analyze statistical significance. P<0.05 and P<0.01 were used to show statistical significance throughout the article. Spearman's rank correlation coefficient was used to assess the correlation between rescue efficiency and expression of NFKBIA or NFKBIZ.In single and combination STAT3 experiment, the rescue efficiencies of different STAT3 variant stable cell lines on day 12 were calculated: Rescue efficiency=/. Two-tailed Student's


Centrocercus urophasianus) have a lek-based mating system and exhibit high site fidelity and skewed mating ratios. We quantified population structure by analyzing variation at 27,866 single-nucleotide polymorphisms in 140 males from ten leks (within five lek complexes) occurring in a small geographic region in central Nevada.Mating systems that reduce dispersal and lead to non-random mating might increase the potential for genetic structure to arise at fine geographic scales. Greater sage-grouse , suggesting that reproductive skew, where few males participate in most of the successful matings, could also potentially contribute to genetic differentiation. Models incorporating a habitat resistance surface as a proxy for potentially reduced movement due to landscape features indicated that both geographic distance and habitat suitability (i.e. preferred habitat) predicted genetic structure, with no significant effect of man-made barriers to movement (i.e. power lines and roads). Finally, we illustrate how data sets containing fewer loci (<4000) had less statistical precision and failed to detect the full degree of genetic structure.Our results suggest that habitat features and lek site geography of sage-grouse shape fine scale genetic structure, and highlight how larger data sets can have increased precision and accuracy for quantifying ecologically relevant genetic structure over small geographic scales.The online version of this article (doi:10.1186/s12862-016-0702-4) contains supplementary material, which is available to authorized users. Population genetic studies are essential for understanding how behavioral, ecological, and evolutionary processes shape the geographic distribution of genetic variation. Recent DNA sequencing advances now allow variation to be readily assayed at thousands of loci for large numbers of individuals and populations in non-model organisms , 2, poteNe) and increase genetic drift [Variation in behavioral and life history traits may have important consequences for the geographic structuring of genetic variation across populations e.g. –16). For. For16])ic drift , 22, 23.ic drift , 25, couic drift , 26–29.Centrocercus urophasianus; hereafter sage-grouse) are an iconic western North American bird species with a lek-based mating system [Artemesia spp.), where a subset of dominant males can account for a large proportion of the successful matings , 40CentrC. minimus), greater sage-grouse, and the Bi-state population of greater sage-grouse  [Previous studies utilizing small data sets of traditional molecular markers  have reported variable patterns of genetic structure across sage-grouse populations, leaving uncertainty about the scale of geographic genetic structure and obscuring the expected link between demographic and population genetic parameters across the range . The det border) –44. Howe border) , 46, lea border) , 47, 48. border) . AlthougHere we use a genotyping-by-sequencing (GBS) approach to quantify genetic variation at 27,866 single-nucleotide polymorphisms (SNPs) across 140 sage-grouse from ten leks located throughout a small geographic region in central Nevada , patterns of male movements documented across multiple years of monitoring, and potential habitat barriers [During the spring breeding season, we sampled ten leks separated by an average distance of 35.7 km in Eureka County, Nevada . We only included males in our study because we were unable to collect a sufficient number of female samples. Approximately 1.5 ml of blood was drawn from the basilic vein of each captured bird. Protocols for the capture and handling of sage-grouse were approved by the University of Nevada, Reno Institutional Animal Care and Use Committee .DNA was extracted from blood using Qiagen DNeasy Blood and Tissue kits  and quantified using a Nanodrop spectrophotometer . Reduced-representation libraries were constructed using a GBS approach , 53. GenE. coli) and low quality or aberrant reads. We used a Perl script to recognize barcodes assigned to each individual bird, to correct single-base errors in barcode sequences, and to remove sequences containing portions of the Illumina adaptors. After removing barcodes and cut site bases, retained sequences were 87, 88, or 89 bp in length. A reference of GBS sequenced regions was created with de novo assembly of a random subset of 25 million reads using the SeqMan ngen software . This used a minimum match percentage of 95, a gap penalty of 30, and only retained contigs containing a minimum of 10 reads . We generated the reference by removing contigs that were over-assembled or that were shorter than 84 or longer than 90 bases. Reads from each bird were subsequently aligned to the reference using the aln and samse algorithms in bwa .The number of reads representing alternative nucleotide states (i.e. SNPs) at each variant site was quantified using samtools and bcftools . We onlyWe used a hierarchical Bayesian model that incorporates uncertainty in sequencing coverage across loci and individuals to estimate allele frequencies and genotype probabilities simultaneously for all individuals based on estimated genotype likelihoods . This mopost hoc test of differentiation among leks and lek complexes based on Euclidean distances of the first two ordination axes.To summarize genotypic variation across individuals and to explore the relationship between geography and genetic structure, we utilized three complementary ordination methods . For allprcomp function in R. To quantify the relationship between individual genotypic variation and geography, we conducted Procrustes analyses on principal components (PCs) [We first conducted principal component analysis (PCA) on genotype probabilities using the ts (PCs) , 61 usinoptim.a.score function , following [a priori group assignments by inferring the most likely number of genetic clusters (K) using the find.clusters function in the adegenet package. This function utilizes K-means clustering to calculate a Bayesian information criterion (BIC) value for each potential value of K  and delineates individual group assignments for DAPC [a priori group assignments at both the lek (K = 10) and lek complex (K = 5) scales, which were based on patterns of male movement across multiple years of monitoring [We conducted Discriminant Analysis of PCs (DAPC)  using thollowing . We firsfor DAPC . Additionitoring .R), which is smaller than the maximum correlation of RDA predictor variables (|R| = 0.7) suggested by [We additionally used redundancy analysis (RDA)  to assesested by .FST [D; [To further summarize genetic differentiation among leks, we calculated pairwise FST  based onFST [D; ) and useFST [D;  in R.D) with the summed environmental resistance  between each pair of leks using a least-cost paths framework [To assess if environmental features contribute to observed differentiation among leks, we used a landscape genetic approach that compared genetic distance . For each dataset, we conducted PCA and Procrustes analysis as described above. Additionally, we employed DAPC on each subset to determine how data set size influenced the proportions of individuals correctly assigned to lek and lek complex.FST  on genetic structure parameter estimates by generating genotype sets with highly differentiated loci removed. We generated locus-specific pairwise FST estimates [FST estimates above the 98th and 97th quantiles of the genome-wide FST distribution for any pairwise analysis at the lek and lek complex levels, and conducted PCA and Procrustes analyses on each of the four trimmed data sets.We also evaluated the possible influence of loci with exceptionally high stimates  for all de novo assembly placed 22,175,595 reads into a set of 218,483 high-coverage contigs; the consensus sequences of these contigs were then used as a reference for the genomic regions represented by our GBS data. The final assembly contained 14 × 107 reads  with an average of 838,715 reads assembled per individual. After identifying variant sites where >90 % of individuals had at least one read, we retained 27,866 SNPs with minor allele frequencies >5 % and with an average coverage of 5.7X per locus per individual (sd = 1.7). Analyses below are based on genotype probabilities estimated with the hierarchical Bayesian model of [After quality screening, we retained 169,622,388 DNA sequences from 140 individuals. The initial model of .R2 = 0.675; F9,130 = 30.06; P < 0.001) and lek complexes . There was a hierarchical pattern of genetic structure, where lek complexes exhibited stronger and more consistent differentiation, while neighboring leks exhibited subtle if any differentiation. Additionally, the mean genetic distance among individuals sharing the same lek complex was significantly smaller than a null distribution of genetic distances . The K = 2 model fit the data best; BIC steadily increased from K = 2 to K = 40  and 11 PCs were retained for the lek complex DAPC . The lek complex DAPC  and lek complexes . DAPC assigned only 48.6 % of individuals to the correct lek, but 80.0 % of individuals were assigned to the correct lek complex  and lek complex  designations.The first two RDA axes (constrained by latitude and longitude) explained 1.94 and 1.15 % of the variance in total genotypic variation, respectively  from more southern complexes  , althouFST outlier loci removed. This indicates that the overall patterns in our results were not strongly influenced by loci with exceptional patterns of differentiation or residing in particular genomic locations. Our results are consistent with many recent studies that illustrate how the information content of population genetic analyses can depend on the extent of genomic sampling . For. ForFST ng (e.g. .Along with other recent studies detecting previously unrecognized structure, our results demonstrate the promise of population genomic data sets for quantifying fine-scale, ecologically relevant population genetic variation , 93. TheBIC, bayesian information criterion; DAPC, discriminant analysis of principal components; DF, discriminant function; GBS, genotyping-by-sequencing; PC, principal component; PCA, principal component analysis; PERMANOVA, permutational multivariate analysis of variance; RDA, redundancy analysis; SNP, single nucleotide polymorphism


Quercus oleoides Cham. and Schlect., tropical live oak, is a species of conservation importance in its southern range limit of northwestern Costa Rica. It occurs in high-density stands across a fragmented landscape spanning a contrasting elevation and precipitation gradient. We examined genetic diversity and spatial genetic structure in this geographically isolated and genetically distinct population. We characterized population genetic diversity at 11 nuclear microsatellite loci in 260 individuals from 13 sites. We monitored flowering time at 10 sites, and characterized the local environment in order to compare observed spatial genetic structure to hypotheses of isolation-by-distance and isolation-by-environment. Finally, we quantified pollen dispersal distances and tested for local adaptation through a reciprocal transplant experiment in order to experimentally address these hypotheses.High genetic diversity is maintained in the population and the genetic variation is significantly structured among sampled sites. We identified 5 distinct genetic clusters and average pollen dispersal predominately occurred over short distances. Differences among sites in flowering phenology and environmental factors, however, were not strictly associated with genetic differentiation. Growth and survival of upland and lowland progeny in their native and foreign environments was expected to exhibit evidence of local adaptation due to the more extreme dry season in the lowlands. Seedlings planted in the lowland garden experienced much higher mortality than seedlings in the upland garden, but we did not identify evidence for local adaptation.Q. oleoides population has a rich population genetic history. Despite environmental heterogeneity and habitat fragmentation, isolation-by-distance and isolation-by-environment alone do not explain spatial genetic structure. These results add to studies of genetic structure by examining a common, tropical tree over multiple habitats and provide information for managers of a successional forest in a protected area.Overall, this study indicates that the Costa Rican  Genetic diversity and structure have long been recognized as critical to the maintenance of viable and resilient populations  and as tThe factors that drive spatially structured genetic diversity are the subject of long-standing inquiries in population and landscape genetics –10. GeneHighly polymorphic neutral genetic markers are widely used to assess associations between environmental variation and population genetic structure , 24 and Quercus oleoides. The large population size until recent land-use change likely resulted in high genetic diversity within the population [Dasyprocta punctata  [Q. oleoides displays considerable variability in flowering phenology [Three conditions are thought to be necessary for local adaptation to occur: 1) high genetic variation exists within the population; 2) individuals within a population are distributed over varying environmental conditions; and 3) gene flow is extremely limited or absent among areas of the range , 36. Inipulation . Considepulation . Gene flpulation . Seed mo Agouti) . Therefohenology . The disQuercus oleoides, tropical live oak, is an important study system in terms of conservation. It provides important ecosystem services and is considered to be critical to restoration of Central American tropical dry forests [Quercus oleoides is the dominant primary producer in the seasonally dry tropical forest (SDTF) of Costa Rica, a highly threatened tropical ecosystem heavily cleared and fragmented for cattle and crops over the last century [Q. oleoides. Its range extends primarily along the Atlantic coast to northern Mexico, but the genetically distinct Costa Rican population is separated from the rest of the range by the Nicaraguan Depression and is on the Pacific slope [ forests . Quercus century , 43. The century , 45. The century , 41. Divic slope , 47.The purpose of this study is to examine the genetic diversity and structure of this important tropical tree species by 1) identifying how much standing genetic variability exists in this population; 2) characterizing population genetic structure; and 3) examining possible drivers of landscape scale genetic structure by quantifying pollen dispersal distances and testing for locally adapted genotypes. Specifically, we test three possible mechanisms that could contribute to landscape scale genetic structure, including isolation by distance, isolation by time (via asynchronous flowering) and isolation by environment. Finally, using a reciprocal transplant experiment, we tested the hypothesis that progeny from opposite ends of the primary climatic and elevation gradient within the population would be locally adapted.This study was conducted in the tropical dry forests of the 120,000-hectare Área de Conservación Guanacaste (ACG) in northwestern Costa Rica . Prior tQ. oleoides in Costa Rica . Duplicate sampling of vegetative clones was avoided by sampling non-neighboring trees separated by at least 25 meters. Each sampled tree was marked and its location was recorded , 5.0 μl Qiagen Master Mix, 1 μl (~10 ng) DNA, and sterilized water. The thermal cycles for this reaction were: 94°C for 15 min, followed by 35 cycles of 30 s at 94°C, 30 s at 50°C and 60 s at 72°C. A final extension step of 10 min at 72°C was added after the last cycle. An ABI 377 Automated Sequencer at the University of Minnesota’s Advanced Genetics Analysis Center was used to measure the length of the fluorescently labeled PCR product. We used the program GenoProfiler to characterize alleles by the length of the amplified fragments [Nine of the eleven microsatellites employed  were developed for r et al.  The othe [et al.  for Q. rragments .ST and analysis of molecular variance (AMOVA) [ST using a stepwise-mutation model. Differences between FST and RST can indicate the relative importance of drift and mutation in causing the observed differentiation [We calculated the percentage of polymorphic loci, average number of alleles per locus, observed and expected heterozygosities , and a f (AMOVA) . Among pntiation . The degntiation .et al. [The number of genetically distinct clusters was estimated using a Bayesian approach in which a Markov Chain Monte Carlo method clustered individuals to minimize Hardy-Weinberg disequilibrium and linkage disequilibrium (STRUCTURE ). This met al.  detectedSTRUCTURE results were compared to a similar clustering analysis performed by the program InStruct  where HaWe described the environment of each site using elevation, the Holdridge life zone classification system, and a climate classification specific to Costa Rica. The Holdridge system defines life zones based on annual precipitation and biotemperature (∑ mean monthly temperature >0°C /12) . BecauseAt three low elevation and three high elevation sites we collected detailed soil moisture, daily photon flux density, (PFD) temperature (T) and relative humidity (Rh) data which show the large environmental gradient in a more quantitative manner At 10 of the 13 sites we made phenological observations on one focal tree and its ten nearest neighbors. We recorded the presence of male and female flowers once per month for two years. It was not possible to visit the other three sites  every month due to poor accessibility.Quercus by Kampfer (ZAG 30 in Q. robur) and Steinkeller  [et al. [Pollen dispersal distances were estimated through molecular characterization of individuals using eight microsatellite loci developed for other species in the genus petraea) , 62. We petraea) –67 and 2 [et al. . In the  [et al. .FT  using the spatial heterogeneity in male gametes. ϕFT is inversely proportional to mean pollination distance and provides an estimate of effective pollination neighborhood size [ep) can also be derived from ϕFT in TwoGener [For the TwoGener analysis, we genotyped leaf tissue from 22 germinated acorns from each of ten variably spaced mother trees  Maternalood size , 67. Theood size . The numTwoGener . We alsoTwoGener .For the paternity exclusion method 63 adult trees (over 20cm DBH) within a 50-meter radius of one central mother tree were genotyped. Leaf tissue from the mother tree and 29 progeny were also genotyped. We used the program FaMoz to calculate exclusion probabilities using likelihood methods to estimate the number of likely pollen donors from within the 50m radius . The metWe used Mantel tests to quantify the correlation between Nei’s genetic distance and the geographic distance among sites . SpatialNormalized Euclidean distances among the sites were calculated from elevation, life zone, and climate type to make a matrix of environmental dissimilarity using the program Primer . Correlaet al. [Similarity of flowering time among sampling sites was calculated according to Schoener’s index of similarity  to descret al. .Partial Mantel tests, where the correlation between two matrices is tested while removing the effect of a third matrix, were calculated in the program ZT to compare matrices while excluding spatial distance . We compReciprocal transplant experiments are powerful means to detect local adaptation , 81 and We collected at least 50 acorns from 26 trees; thirteen maternal families from low elevation sites and thirteen maternal families from high elevation sites. Acorns were germinated and seedlings were grown in plastic nursery bags with a 1:1 mix of sand and peat. Acorn diameter and length were measured on a sample of seeds from a subset of the families to estimate acorn volume, which was then converted to mass based on a calibration curve derived from sampled measurements. The seedling nursery was covered with 70% shade cloth. Seedlings were well watered and grew for 2–3 months prior to transplantation. Two weeks before transplantation, we removed the shade cloth and reduced watering to allow for acclimation.Q. oleoides stands. Existing pasture vegetation was cleared, fenced, and covered with plastic sheeting in order to prevent competition of other vegetation with the seedlings. The lowland garden (280 meters above sea level) was located near the seedling nursery in sector Santa Elena , and the upland garden (800 meters above sea level) was located near the entrance to Parque Nacional Rincón de la Vieja (Two gardens were established in old pastures adjacent to current  site SC). The see1668 seedlings were planted through the plastic sheet in October 2006 and censused at least twice per year over the next three years. After six months, the plastic sheeting was removed and the growth of pasture vegetation was maintained by periodic mowing. To evaluate the effects of source population, location and their interactions on overall fitness, we used the maximum-likelihood approach called Aster Models , 85 in tQuercus virginiana . We fite, for all sites was 0.628.A total of 257 individuals were successfully assayed at 11 microsatellite loci. Allelic diversity was high with each locus containing between 6 and 17 alleles . Each siST = 0.102, p = 0.01 & RST = 0.15, p<0.001, Genetic variation was significantly partitioned among the 13 sampled sites based on an AMOVA  and our own density measurement (81 trees per hectare) to obtain an estimate of eight meters for the average effective pollen dispersal distance. In the paternity exclusion, 8 microsatellite markers were sufficient to exclude potential fathers with high probability (cumulative exclusion probability over 8 loci = 0.997), and there was very little chance any two individuals drawn at random from the population could not be differentiated (Probability of identity <0.001). The likelihood approach of FaMoz successfully excluded all but one potential father for 24 of the 29 genotyped offspring. Fathers for five of the 29 offspring were likely found outside of the 50-meter radius of the study stand, yielding an inflow rate of approximately 17%.Genotyping of the individuals in both the TwoGener analysis and the paternity exclusion analysis yielded high diversity and 100% polymorphic loci. The number of alleles per locus ranged from 6 (ZAG ½) to 20 (ZAG 102). For the TwoGener analysis, we successfully genotyped and average of 20 offspring from 10 mothers. The inter-mother distances varied from less than one kilometer to over 60 km. The majority of the total variation in male gametes (87%) was found within mothers, but a statistically significant 13% of the total variation in male gametes occurred among mothers  suggesting that potential adaptive capacity to future environmental change has not been lost. The 13 sites had a statistically significant level of among-site genetic variation . The large difference in estimated pollen dispersal distance between Q. lobata and Q oleoides (65m and 8m) can be explained by the higher density of Q. oleoides (1.19/hectare and 81/hectare). Other wind dispersed species have been shown to similarly derive paternity from nearby individuals . In all[Populus . The 17%a = 0.57 .We found no evidence that progeny from contrasting climatic and elevation sites were locally adapted. Given limits to gene flow across this gradient, we hypothesized that differences in the abiotic conditions of the lowland and upland environments might select against seedlings from the opposite environment. The results of our Aster analysis of the fitness of reciprocally transplanted progeny did not support this hypothesis, but the common garden results do corroborate results from the Mantel tests indicating little evidence for the hypothesis of isolation by environment. The model that included a source x garden interaction did not fit the data significantly better than a model without that interaction . There we) in the lowland population. Another possible interpretation for the consistently higher fitness of the lowland population is that unaccounted factors, such as greater allocation to below ground growth or the presence of maternal effects that caused lowland populations to have larger seed sizes. If families from the lowland population had larger overall seed sizes, then the higher leaf number in lowland individuals would not be a result of increased seedling performance [Quercus suber and Quercus douglasii, it has been shown that acorn size is larger in populations from drier habitats [The fitness of families from the lowland population was higher in the lowland environment . That reformance . In at lhabitats , 108. HoThe higher mean fitness of the lowland population relative to the upland population in both environments decreased as time progressed and was no longer significant by the third year. The advantage by the lowland population may thus be ephemeral or dependent on momentary environmental conditions, disappearing by the time these long-lived trees reach reproductive maturity. Our lack of evidence for local adaptation may be dependent on the life stage we examined. We chose to focus on achieving the desired amount of replication by planting seedlings into the gardens. However, it is possible that by not planting seeds directly in the gardens we missed an important life history stage that could have revealed a signal of local adaptation .Maternal family was a significant factor in the model, and there was a significant family x garden interaction. This suggests heritability of the fitness trait and therefore the potential to respond to natural selection. Our fitness trait is a composite of survival and leaf number and we observed wide variability among mean family survival . We alsoQuercus oleoides. Our results indicate that isolation by distance may be the dominant force shaping population genetic structure among some sites and at small distances, but environmental variation likely plays a role as well. Our methods did not allow us to precisely attribute proportions of total genetic variation to IBD or IBE, but other studies have found a dominant role of IBE in certain cases with IBD still playing a role [Patterns of spatial genetic variation, and the role that landscape heterogeneity plays in shaping those patterns, continues to grow as an area of research interest . We charg a role , 34, 92.g a role ). We intQuercus species where morphology remains consistent despite high variation in molecular markers [The fact that we do not see local adaptation given that conditions were met for it to be present is surprising; and although detecting local adaptation in early seedling stages of long-lived trees is challenging, the significant family x garden interaction suggests the potential for future adaptation . Despite markers . Our molDifferential gene exchange due to asymmetrical pollen or seed dispersal, chance associations caused by genetic drift or founder effects, selection on genomic regions near the surveyed microsatellite markers  and compe = 0.63) nearly matches that of the entirety of it’s range (He = 0.77) while also being significantly subdivided geographically such that it should more correctly be thought of as 5 distinct populations. The Costa Rican Q. oleoides have already been shown to be genetically unique from the rest of the range [Similar to other studies attempting to uncover the processes that create population genetic structure, our data do not support just one explanation. Because nearly the entire extent of this population now occurs within a conservation region, however, we have shown that the remnant oak stands are likely to harbor the diversity necessary for the recovery of part of the tropical dry forest ecosystem. The genetic diversity of this relatively small population .Temp, Rh, light, and soil moisture collected from three upland sites  and three lowland sites . Arrows illustrate eigenvectors for the variables. PCA axis 1 is significantly correlated with elevation (R(PDF)Click here for additional data file.S2 FigA) Map of TwoGener mother trees, paternity analysis tree, and phenology monitoring sites. B) Map of common garden locations and areas where maternal family seed sources were collected.(PDF)Click here for additional data file.S3 FigA) Log likelihood probability (Ln PD) estimates. B) delta K values for the number of distinct ancestral admixture groups. C) Mean likelihood estimates for K values from InStruct. D) Deviance information criterion (DIC) scores for K values from InStruct.(PDF)Click here for additional data file.S4 FigK = 5 was supported by the Evanno et al. (2005) delta K method for Structure results. K = 11 was considered the “optimal K” from Instruct(PDF)Click here for additional data file.S5 FigComparison of mean seed mass from a subsample of upland and lowland maternal families.(PDF)Click here for additional data file.S1 File(CSV)Click here for additional data file.S2 File(CSV)Click here for additional data file.S3 File(CSV)Click here for additional data file.S4 File(CSV)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 TableA) Genetic distance matrix. B) Spatial distance matrix. C) Environmental distance matrix. D) Flowering time similarity matrix.(PDF)Click here for additional data file.


Culicoides spp.). Australian BTV serotypes have origins in Asia and are distributed across the continent into two distinct episystems, one in the north and another in the east. Culicoides brevitarsis is the major vector of BTV in Australia and is distributed across the entire geographic range of the virus. Here, we describe the isolation and use of DNA microsatellites and gauge their ability to determine population genetic connectivity of C. brevitarsis within Australia and with countries to the north. Eleven DNA microsatellite markers were isolated using a novel genomic enrichment method and identified as useful for genetic analyses of sampled populations in Australia, northern Papua New Guinea (PNG) and Timor-Leste. Significant (P < 0.05) population genetic subdivision was observed between all paired regions, though the highest levels of genetic sub-division involved pair-wise tests with PNG  and PNG vs. Timor-Leste (FST = 0.095)). Analysis of multi-locus allelic distributions using STRUCTURE identified a most probable two-cluster population model, which separated PNG specimens from a cluster containing specimens from Timor-Leste and Australia. The source of incursions of this species in Australia is more likely to be Timor-Leste than PNG. Future incursions of BTV positive C. brevitarsis into Australia may be genetically identified to their source populations using these microsatellite loci. The vector’s panmictic genetic structure within Australia cannot explain the differential geographic distribution of BTV serotypes.Bluetongue virus (BTV) is a major pathogen of ruminants that is transmitted by biting midges (The online version of this article (doi:10.1186/s13567-015-0250-8) contains supplementary material, which is available to authorized users. Culicoides spp.) are vectors of bluetongue virus (BTV). In Australia, C. actoni Smith, C. brevitarsis Kieffer, C. fulvus Sen and Das Gupta are proven vectors of BTV and several others including C. brevipalpis Delfinado, C. dumdumi Sen and Das Gupta C. oxystoma Kieffer, C. peregrinus Kieffer and C. wadai Kitaoka are regarded as potential vectors [C. brevitarsis is the most widely distributed throughout northern and eastern parts of the continent [Bluetongue (BT) is an economically important viral disease throughout tropical and temperate regions of the world, posing a threat to the livestock industries, through production losses and negative impacts on trade . The dis vectors ,4. Of thontinent ,6, and iontinent .C. brevitarsis to non-sheep breeding regions, primarily in the south of the continent and the relatively low pathogenicity of Australian BTV serotypes. Surveillance has indicated that the distribution of BTV serotypes in Australia is asymmetric with all 10 serotypes detected in the far northern region and only two serotypes (BTV-1 and BTV-21) enzootic in the southern portions of the eastern states. The factors influencing the distribution of serotypes are unknown and there is concern that introductions of exotic BTV strains from Southeast Asia via windborne Culicoides could destabilize the current situation [Culicoides midges using an aerial migration model, indicated that migration of Culicoides into northern Australia from Timor-Leste (TL) and Papua New Guinea (PNG) is possible with Timor considered the most likely source of incursions [C. brevitarsis likely entered Australia and PNG separately from independent southeast Asian sources, in recent historical times [BTV appears to have been introduced to Australia from Southeast Asia on multiple occasions by infected wind-borne vectors ,9. Indeecursions . Recent cursions ,13 general times ,15. Addide novo from small organisms such as Culicoides from which limited quantities of genomic DNA can be extracted. The second aim was to identify and compare allelic diversity of microsatellite loci among C. brevitarsis in Australia and neighbouring countries (PNG and TL) that are suspected sources of Culicoides spp. entering Australia. In this latter aim, we also sought to determine the levels of population genetic connectivity among the regions and infer the likely source(s) of midges in Australia during historical and current times.The first aim of this study was to develop a technical workflow for identifying DNA microsatellite markers Culicoides were not included in analyses. After species identification, total genomic DNA was extracted from single specimens of C. brevitarsis using the DNeasy blood and tissue kit (Qiagen) according to the manufacturer’s protocol and by a non-destructive genomic DNA extraction method [A total of 141 samples were collected using light trap or sweep net, preserved in 70% ethanol and identified from sites in the Northern Territory (NT), Queensland (QLD), New South Wales (NSW), PNG and TL Figure  as descrn method . The genCulicoides for downstream manipulations, multiple displacement amplification-based (MDA) whole genome amplification (WGA) using Repli-g ultrafast mini kit (QIAGEN) was conducted on specimen DNA according to the manufacturers’ protocol. To assess the differences in yield of amplification from a range of starting amounts of genomic DNA and according to two different denaturing procedures, 10.7 ng and 0.215 ng of DNA were denatured either by heat (95 °C for 3 min) and or by adding denaturing solution  and then amplified using the REPLI-g ultrafast mini kit at 30 °C for 1.5 h followed by polymerase inactivation at 65 °C for 3 min. Water was used as a negative control. The resulting DNA was quantified using a Qubit fluorometer and qualitatively assessed by electrophoresis (1% agarose gel (Invitrogen) at 7.40 V/cm) in the presence of 1 kb DNA ladder and staining/UV visualisation.To improve the amount of genomic DNA yield from singleton To evaluate the quality of the whole genome amplified DNA, the products of the previous amplification (together with the negative control) were used as templates to PCR amplify a 600 bp housekeeper gene (actin). Each 20 μL reaction included 1 μL template DNA (approximately 20 ng), BSA (400 ng/μL), 5 μm each forward and reverse primer (Act-2 F and Act-8R)  and 15 μn = 7 New South Wales, n = 8 Northern Territory) was whole genome-amplified. The amplified whole genomic DNA was sequenced on 1/8 plate Roche 454 Genome Sequencer FLX plus by an external contractor . The raw sequence reads of amplified whole genomic DNA were screened directly for di-, tri- and tetranucleotides using MSATCOMMANDER v0.8.2 [C. brevitarsis raw reads. The primer pairs that were predicted to anneal to more than one read were aligned to those reads after reverse-complementing the reverse primer.To isolate DNA microsatellite markers, 1 μL of a pooled specimen DNA  at individual loci within populations. Microchecker [Genepop  was usedochecker  was usedDeviations from the Hardy-Weinberg equilibrium was estimated by using Arlequin v3.0 . The obsst) [To infer population structure from the microsatellite data, multilocus genetic distance  and fixast)  estimatest) ,23,26. PA Bayesian clustering approach implemented in STRUCTURE v2.3.4  was usedTo generate a matrix of individual membership co-efficient and population ancestry components, the following parameter set was applied: burnin period of 100 000, Markov chain Monte Carlo (MCMC) repeats of 100 000, ancestry model of admixture of LOCPRIOR model and a K value range from 1–10 with an iteration of 22.STRUCTURE HARVESTER v0.6.94  was usedThe DNA yield from WGA DNA of both heat-denatured and denaturing solution (buffer D1) denatured DNA was compared. The D1 buffer-denatured DNA yielded more WGA product than the heat-denatured DNA (data not shown). This suggests the superiority of the D1 buffer over heat as a denaturing agent in WGA. Tests using low concentration DNA sample template (0.215 ng) resulted in higher yield of WGA products compared to yield using higher concentration DNA template (10.7 ng). The size of WGA DNA smears was from >10 kb with a smear extended down to ~1 kb. The negative control reaction did not amplify. Positive controls based on actin gene amplification were successful in both the whole genome amplified heat and D1 buffer-denatured DNA. The negative control reaction from the same WGA reaction did not amplify.Culicoides genome [A total of 120 005 reads of 414 average read length was obtained after sequencing the amplified whole genomic DNA. The maximum theoretical genome coverage obtained in this study was ~0.25 X (no. of reads X average read length/size of genome) of the approximately 200 MB s genome . A totalA total of 526 primers were designed to the flanking regions of the microsatellite repeats. From these, 420 primers were either found to be similar to each other or homologous to sequences from other organisms in the database, while 106 primers were unique and were not homologous to anything in the NCBI database. After comparing the 106 unique primers against the sequenced reads, 93 primer pairs  varied from 0.01–0.89 and in 96% of comparisons was higher than the observed heterozygosity (Ho) with a range of 0–0.88. The inbreeding coefficient (FIS) was significantly different from zero in an average of eight loci per population. Estimates of FIS differed between populations such that NT and NSW had a higher frequency of loci showing significant inbreeding compared to the other populations. Locus HBCQD was monomorphic in TL, PNG and QLD but polymorphic in NT and NSW. Global tests by locus revealed departure from Hardy-Weinberg equilibrium for most loci among all the populations. While putative null alleles were identified at some loci in some populations using Microchecker, the null alleles were not locus specific . Paired region FST estimates indicated the highest levels of sub-division between PNG and Australia (FST = 0.12) and between PNG and Timor-Leste (FST = 0.095). In contrast, FST between Australia and Timor-Leste (0.03) was lower  using recombinant approaches as described by Glenn et al. [C. brevitarsis by initially increasing the amount of genomic DNA by whole genome amplification (MDA technique) and subsequently sequencing the whole genome amplified DNA on an eighth of a lane of a 454 GS FLX sequencer. To the best of our knowledge, this is the first study that has isolated microsatellite markers de novo from WGA DNA for any organism. The MDA-based whole genome amplification procedure provides an ideal method of isolating microsatellite markers from limited amounts of genomic DNA. This gave rise to 120 005 raw reads from which 93 primer pairs that are unique to a single read (and not the products of contamination) were isolated. The abundance of microsatellite repeats may be skewed due to a potential unbalanced representation of the genome during whole genome sequencing. A selected number of markers flanking the repeats were successfully validated and utilized to study Australasian populations of C. brevitarsis.Microsatellite loci are regarded as powerful molecular markers because of their high mutability, co-dominance, abundance in the genome and relative ease of scoring ,32 and hn et al.  and utilCulicoides species have entered northern Australia from both Timor-Leste and PNG [C. brevitarsis to northern Australia are less certain. Based on their study of COI haplotypes, Gopurenko et al. [Aerial arthropod dispersal modeling studies have assessed the possible routes of introduction of BTV vectors into Australia from neighboring countries including Timor-Leste and PNG. The models predict stronger pathways of dispersal from Timor-Leste to Australia, than from PNG ,11,39. M and PNG . More reo et al.  found evC. brevitarsis in Timor-Leste, Australia and northern PNG.So far, no genetic studies have used multi locus markers to examine population structure of this species. The current study applied 11 newly isolated microsatellite markers to determine the population genetic structure of C. brevitarsis in Australia are more similar to those in Timor-Leste than in northern PNG. This is particularly evident in STRUCTURE analyses, which have assigned Australia and Timor-Leste specimens to a population cluster separate from a single PNG cluster. Pairwise FST tests indicate significant structure exist between Australia and its northern neighbors, but the level of FST structure evidenced between these two regions is less than that in pair-wise comparisons with PNG. The results demonstrate that C. brevitarsis in Australia was potentially introduced into NT from Timor-Leste or from neighboring islands in Indonesia (less likely from PNG) consistent with previous spatial modeling studies that indicated the islands of Timor and Sumba in the Indonesian Archipelago were the likely principal sources of Culicoides dispersal into northern Australia [Culicoides on land [The results here indicate populations of ustralia ,11,39. Tustralia . The hig on land . In cont on land .C. brevitarsis from northeastern Australia and southern PNG was not conducted in this study and future genetic work is required to examine levels of population connectivity between the two regions and to test the possibility of separate entry of BTV infected midges into northeastern Australia from the southern PNG region. The movement of other species of Culicoides from southern PNG into northern QLD has been documented [C. brevitarsis appears likely. Our starting working hypothesis was to highlight the potential larger genetic difference between the most distant NT and NSW regions and we placed more emphasis in the sampling of these two regions rather than the intermediate Queensland area. This has lead to a weaker significance of these last samples over the rest of the individuals.Genetic sampling of cumented  so movemST estimates of population subdivision indicate C. brevitarsis populations are genetically panmictic in Australia and display no evidence of genetic separation or structure between northern and eastern sampled populations. This result suggests that the presence of the two BTV episystems in Australia (northern and eastern) as demonstrated by the distribution of BTV serotypes is not as a result of genetic structuring of this vector and is due to other factors for example, the presence of other vector species in northern Australia that are absent from southeastern Australia.Furthermore, both STRUCTURE analysis and conventional FC. brevitarsis populations in the same regions examined in the present study and further their modeled estimates of effective maternal population size in contemporary populations was in the order of hundreds of thousands of individuals. Alternatively, null allele presence, caused by mutations at locus specific primer annealing sites which retard PCR amplification efficiency of particular alleles, can result in excesses of homozygotes scored at loci and hence significant deviation from Hardy-Weinberg Equilibrium in populations [The 11 loci isolated and validated in this study were polymorphic with number of alleles ranging from 3 to 13. Departure from Hardy-Weinberg equilibrium resulting from excessive homozygote presence in one or more sampled populations was evident at all 11 loci. Severe inbreeding can cause an excess of homozygotes across loci, however, this would involve substantial and or ongoing bottlenecking of populations down to few breeding adults . Substanulations . Alleliculations .To validate the levels of potential allelic and genotypic miss-scores caused by a variety of PCR processes including PCR dropout and primer redundancy, a total of 86 DNA samples initially identified either as homozygous at one or more loci or had failed to amplify were re-amplified at one or more of the 11 markers using a touchdown PCR program. Three percent of samples initially identified as homozygous were scored as heterozygotes in the repeat PCRs, 17% of samples that failed to amplify previously were successfully re-amplified, 7% of samples that had been amplified before failed to amplify during this re-amplification experiment and 73% were unchanged.ST and also population assignment testing (as employed in STRUCTURE) and they identified significant but small upwards biases to FST (FST increased between 0.003 and 0.004) and slight reduction in the power of STRUCTURE to correctly assign individuals to populations (0.2 and 1.0% units). With these caveats, we argue the likely slight upward biases to our pairwise estimates of FST as well as some effects on specimen cluster assignment using STRUCTURE, which would not drastically change the results of our study.The effects of null allele on test for HWE have been reported earlier . The effde novo isolation of microsatellite markers from C. brevitarsis. These microsatellite markers are likely to be very useful for genetically typing population origins of C. brevitarsis detected in the future. They can also be applied to carry out a broader analysis of gene flow in Australasian and Southeast Asian populations of C. brevitarsis.We have demonstrated that whole genome amplification of the genomic DNA and subsequent whole genome sequencing resulted in a successful


Anguilla anguilla) is a highly migratory fish species with declining population due to a steep recruitment collapse in the beginning of the 1980s. Despite punctual observations of genetic structure, the population is viewed as a single panmictic reproductive unit. To understand the possible origin of the detected structure in this species, we used a combination of mitochondrial and nuclear loci to indirectly evaluate the possible existence of cryptic demes. For that, 403 glass eels from three successive cohorts arriving at a single location were screened for phenotypic and genetic diversity, while controlling for possible geographic variation. Over the 3 years of sampling, we consistently identified three major matrilines which we hypothesized to represent demes. Interestingly, not only we found that population genetic models support the existence of those matriline‐driven demes over a completely panmictic mode of reproduction, but also we found evidence for asymmetric gene flow amongst those demes. We uphold the suggestion that the detection of demes related to those matrilines reflect a fragmented spawning ground, a conceptually plausible consequence of the low abundance that the European eel has been experiencing for three decades. Furthermore, we suggest that this cryptic organization may contribute to the maintenance of the adaptive potential of the species.Using evolutionary theory to predict the dynamics of populations is one of the aims of evolutionary conservation. In endangered species, with geographic range extending over continuous areas, the predictive capacity of evolutionary‐based conservation measures greatly depends on the accurate identification of reproductive units. The endangered European eel ( Born in the Sargasso Sea, eels are passively transported towards the European coasts with the main ocean currents. This connection is facilitated by the North Atlantic gyre , 2011 (n = 127) and 2012 (n = 121). Specimens were dried with absorbing tissue, weighed , measured with an electronic caliper , and a piece of tissue was clipped for DNA extraction.We sampled 403 glass eels from three distinct cohorts captured in the mouth of the river Adour in France (GPS coordinates: 43°31′48″N. 1°31′28″W). Individuals were captured within the fourth week of December of 2010  – log(W) regression, and b is the slope of this regression. To investigate whether we could fit a regression line common to all the cohorts (and therefore consider a species‐specific growth), we first performed an analyses of covariance with log(W) as the dependent variable and log(L) as an independent variable and “cohort” as a fixed effect. Since all our fish were captured at the glass eel stage in the mouth of the Adour River, we expected Kn to provide an estimate of individual condition after the transatlantic migration. This estimate is referred to as “condition index at arrival”.We first calculated the relative condition index (Kn) Le Cren  followinND5) gene following , the sister species of the European eel, were added from a previous study  were calculated for each cohort in DnaSP v5 , the sister species of the European eel were used to provide a visual calibration of intraspecific diversity  , in line with estimates of most recent common ancestor (TMRCA) of both species reported by  >200 and distribution of posterior's marginal likelihood was inspected in Tracer v1.6 .With the substitution model, mutation rate and respective clock model, as well as the initial tree height, we proceeded with the construction of the BSP. BSP were constructed independently for each matriline. The tree prior for these analyses was set to “coalescent: Bayesian skyline”  PCR kit's recommendations. Genotyping was performed on an ABI© 3100 Genetic Analyzer. Alleles were called in GENEMARKER© v. 1.91 . We controlled the quality of microsatellite data by estimating the frequency of null alleles through maximum likelihood estimates of gene frequency .Table S6. Estimates for the modes and respective 95% confidence interval for mutation‐scaled effective population size (θ) and Nem in model II, where 4 Nem = Mj→i*θ for 2010.Table S7. Estimates for the modes and respective 95% confidence interval for mutation‐scaled effective population size (θ) and Nem in model II, where 4 Nem = Mj→i*θ for 2011.Table S8. Estimates for the modes and respective 95% confidence interval for mutation‐scaled effective population size (θ) and Nem in model II, where 4 Nem = Mj→i*θ for 2012.Click here for additional data file.Appendix S1. Mitochondrial DNA sequences (ND5).Click here for additional data file.Appendix S2. Microsatellite allelic frequencies.Click here for additional data file. Click here for additional data file.


Domesticated cattle were then introduced into Europe during the Neolithic transition. However, the scarcity of palaeogenetic data from the first European domesticated cattle still inhibits the accurate reconstruction of their early demography. In this study, mitochondrial DNA from 193 ancient and 597 modern domesticated cattle (Bos taurus) from sites across Europe, Western Anatolia and Iran were analysed to provide insight into the Neolithic dispersal process and the role of the local European aurochs population during cattle domestication.Cattle domestication started in the 9Using descriptive summary statistics and serial coalescent simulations paired with approximate Bayesian computation we find: (i) decreasing genetic diversity in a southeast to northwest direction, (ii) strong correlation of genetic and geographical distances, iii) an estimated effective size of the Near Eastern female founder population of 81, iv) that the expansion of cattle from the Near East and Anatolia into Europe does not appear to constitute a significant bottleneck, and that v) there is evidence for gene-flow between the Near Eastern/Anatolian and European cattle populations in the early phases of the European Neolithic, but that it is restricted after 5,000 BCE.The most plausible scenario to explain these results is a single and regionally restricted domestication process of cattle in the Near East with subsequent migration into Europe during the Neolithic transition without significant maternal interbreeding with the endogenous wild stock. Evidence for gene-flow between cattle populations from Southwestern Asia and Europe during the earlier phases of the European Neolithic points towards intercontinental trade connections between Neolithic farmers.The online version of this article (doi:10.1186/s12863-015-0203-2) contains supplementary material, which is available to authorized users. The process of Neolithisation started in a region spanning from the Zagros Mountains to Central Anatolia and from Palestine to the plains beyond the East Taurus Mountains ,2. It walennium) ,4. Elemellennium -7, whilellennium . The subllennium . The extllennium -17. An ellennium , a view llennium ,20.Bos taurus), a recent coalescent-based analysis using ancient Iranian samples suggested a severe Near Eastern domestication bottleneck, with an estimated effective size of just 80 female founders [et al. [Bos taurus has so far been hindered by the lack of data from the key bridging areas of the Neolithic, namely Anatolia, the Balkans, and the Western Mediterranean.As animal husbandry was an important part of the foundation of the new agricultural lifestyle, remains of domesticated animals can serve as a good proxy for the Neolithic spatial expansion and the presence and activity of farmers in newly populated areas . In recefounders . However [et al. . Thus, dn = 193, including the Iranian samples) and modern (n = 597) mtDNA dataset that widely covers the area of the Neolithic westwards expansion from the 7th millennium BCE onwards. The focus of the study is on the time period when cattle were first introduced to Europe, thereby allowing us to address the following questions: i) Is the scenario of a single and severe domestication bottleneck in the Near East still supported when adding the much larger dataset from western Anatolia and Europe? ii) Did cattle reach Europe in a single dispersal process or is there evidence for multiple introductions or continuous gene-flow between regions? iii) How much of the genetic diversity from the Near East was introduced to the European continent? iv) Did the spread of cattle coincide with the spread of the Neolithic culture? and v) Are there any signs of admixture with female aurochs along the expansion route of domestic cattle?In this study we greatly extend a previous coalescent-based demographic model, based on 15 ancient Iranian and 27 modern Near Eastern and Anatolian cattle mitochondrial DNA (mtDNA) sequences, in terms of sample size, and geographic and temporal range . To be a150 samples of prehistoric domestic cattle from 24 archaeological sites were taken to analyse a 434 bp long mitochondrial d-loop fragment , Northern and Western France (11) and Syria (1), plus 80 previously published sequences mainly from Central and Western Europe and Iran were used for population genetic analyses , under strict rules for contamination prevention as described in Bramanti et al. . Those iet al. [Amplification of 434 bp of the HVSI (positions 15914–9 according to reference sequence V00654) was generally conducted using a PCR primer set consisting of 6 primer pairs as in Bollongino et al.  (BosU1/L2 (Applied Biosystems), 0.2 mM dNTP’s (Quiagen), 0.4 μg/μl BSA (Roche), and 0.2 μM primer (Biospring) and HPLC-H20 (Acros Organics). Initial activation at 90°C for 6 min was followed by 50 cycles of denaturation (40 sec at 94°C), annealing (40 sec at 52-60°C), and elongation (40 sec at 72°C) in a Mastercycler gradient (Eppendorf). Blank controls were processed during each PCR. At least three independent PCRs from two different extracts were performed. Samples were sequenced on an ABI PRISM™ 3130 Genetic Analyzer (Applied Biosystems) using POP-6™ polymer (Applied Biosystems).PCR reactions were usually performed with 2.5 U AmpliTaq Gold® (Applied Biosystems), 1x PCR Gold Buffer (Applied Biosystems), 2 mM MgClSequences were analysed using the programs SeqMan™ and MegAlign™ (DNASTAR Lasergene® 7.1 and 8). At least three sequences obtained from independent PCRs from two independent DNA extractions per sample per primer pair were usually used to create a majority rule consensus sequence. For further details on ancient DNA work and sequencing including deviations from the general laboratory procedure described see Additional file All new and previously published ancient DNA sequences were subdivided into the following geographical groups: Iran/Syria, Western Anatolia, Southeastern Europe, Southeastern Central Europe, Italy, Southern France, Central/Western Europe, and Spain. These groups were further subdivided into chronological subgroups reflecting up to four different Neolithic and post-Neolithic periods per region . Haplotype diversity, mean number of pairwise differences, Tajima’s D, Fu’s Fs and population pairwise FST values calculated using Reynolds’ genetic distances and running 10,000 permutations in Arlequin 3.5.1.2. The MDS plot was created in R 2.14.2 R [The MDS  plot is based on F2.14.2 R  using th2.14.2 R , plotrix2.14.2 R  and shap2.14.2 R .ST values calculated using Reynolds’ genetic distances and running 10,000 permutations in Arlequin 3.5.1.2. Geographical coordinates were determined by eye as the centre of appropriate countries per group for the modern samples and the centre of all archaeological sites per group for the ancient samples.Correlation between genetic and geographical distances among defined populations/groups was assessed by a Mantel test  under 9,et al. [ND at time 8,500 years BCE . Following the domestication bottleneck, this Near Eastern population grows exponentially to a modern Near Eastern and Anatolian effective population size NNE of 1,007,170 , after which it is changed to rate ML (‘late migration’). Prior values for ND are drawn uniformly from the range 1 – 1,000, P uniformly from the range 0 – 1, and both migration parameters uniformly from the range 0 – 0.01. The mutation rate is fixed at 45% per million years, the posterior modal value previously estimated by Bollongino et al. [Coalescent simulations were performed using Bayes Serial SimCoal , by exteet al. . Similaret al.  and, agao et al. ). At 6,4o et al. .n = 24), ancient European (n = 169), modern Near Eastern and Anatolian (n = 100) and modern European (n = 497). We calculated 5 within- and 2 between-sample summary statistics  and cut the ancient sequences accordingly. The resulting 790 sequences were grouped into 4 sample groups: ancient Near Eastern and Anatolian . None of the blank controls contained amplifiable amounts of bovine DNA . It is There are 35 different mitochondrial lineages in the 193 prehistoric individuals, eight of which occur more than once in the dataset. Non-unique haplotypes (H) were named according to their haplogroup and numbered consecutively (H1-H8). Additional files The MDS plot Figure  reveals ST values between the resulting eight groups. The greatest genetic distances can be observed between Iran 7,000-5,000 BCE and the groups from Central/Western Europe 5,400-4,400 BCE and Southern France 5,500-4,500 BCE with values of 0.47 and 0.40, respectively. These groups also show the greatest geographical distances. The second highest FST values occur between Southeastern Europe 6,200-5,500 BCE and Central/Western Europe 5,400-4,400 BCE and between Southeastern Europe 6,200-5,500 BCE and Southern France 5,500-4,500 BCE (0.27 and 0.29 respectively). In comparison, the genetic distance between Iran 7,000-5,000 BCE and Southeastern Central Europe 5,100-4,000 BCE is – despite greater geographical distance - slightly lower (0.23). The FST between Iran 7,000-5,000 BCE and Southeastern Europe 6,200-5,500 BCE is even smaller (0.17). The geographically adjacent groups of Southeastern Europe 6,200-5,500 BCE and 5,500-5,000 BCE and Southeastern Central Europe 5,100-4,000 BCE reveal a distance as high as 0.16 and 0.10, respectively.Subgroups comprising only the earliest Neolithic cattle of each geographical group were used to further evaluate the influence of sample age and geographical location on genetic distances. Figure ST resulted in a strong positive correlation  between geographical and genetic distance among the eight groups. Approximately 56% of the variation can be explained by geographical distance (R2 = 0.56). There is a weaker correlation of genetic and geographical distances in modern samples . Here, only 29% of the variation can be explained by geographical distance (R2 = 0.29). Complete population pairwise FST matrices can be found in Additional file A Mantel Test on the basis of Reynolds’ FThe estimates of haplotype diversity (Ĥ), the mean number of pairwise differences (π), Tajima’s D, and Fu’s Fs are given in Table Haplotype diversity clearly decreases in a southeast to northwest direction with Iran 7,000-5,000 BCE (0.96) at the high end, and Southern France 5,500-4,500 BCE (0.00) and Central/Western Europe 5,400-4,400 BCE (0.22) at the low end. The haplotype diversity of the earliest domesticated cattle on the European continent in Southeastern Europe 6,200-5,500 BCE (0.62) is much lower than in Iran, and comparable to Western Anatolia 6,400-5,700 BCE (0.64), but higher than in the geographically close European group of Southeastern Central Europe 5,100-4,000 BCE (0.52). Again, diversity in Central/Western Europe 5,400-4,400 BCE is substantially lower (0.22). Following the northern Mediterranean coast, the values also drop sequentially from Western Anatolia 6,400-5,700 BCE (0.64) to Italy 6,000-5,500 BCE (0.40) to Southern France 5,500-4,500 BCE (0.00).Haplotype diversity estimates increase with time in the two regions where samples from two Neolithic periods are available: from 0.22 to 0.50 in Central/Western Europe and from 0.62 to 0.78 in Southeastern Europe. In Southeastern Europe, haplotype diversity remains the same in the subsequent Chalcolithic group 5,000-4,000 BCE (0.78), but increases again during the Bronze Age 2,700-2,200 BCE (0.81). Similar patterns are observed when considering the mean numbers of pairwise differences. The Neolithic subgroups also show a tendency of decreasing values with distance from Iran. Regionally, the values increase with time; in Central/Western Europe from 0.45 to 0.91 and in Southeastern Europe from 1.26 to 1.79 to 2.11. In the youngest Southeastern European group  the value drops again (0.54). In Central/Western Europe, where both diversity indices increase with time, Tajima’s D is also significantly negative (Fu’s Fs only in the younger group). This is not the case for Southeastern Europe. Diversity estimates of the 597 modern cattle sequences only show a slight tendency towards an east to west gradient for both haplotype diversity, and the mean number of pairwise differences. Tajima’s D and Fu’s Fs are mostly significantly negative. All diversity estimates and graphical visualisations of chronological and geographical diversity trends can be found in the Additional file ND and P , with the joint mode found at ND = 81 and P = 0.73. The marginal modal value for ND was 92 . Marginal densities for the two migration parameters ME and ML are given in Figure ME , we are able to say that migration between the Near East and Europe (ML) appears to have been greatly reduced, essentially to zero, in the period after 5,000 years BCE . Further simulations were performed in order to test the sensitivity of these parameter estimations to our assumed fixed values of NNE and NE. Increasing or decreasing both NNE and NE by an order of magnitude produced estimates that did not significantly differ from those given above  and modern mtDNA dataset (n = 597) of domesticated cattle from the Near East, Anatolia and Europe for coalescent simulation and approximate Bayesian computation, we inferred a (joint) posterior mode of 81 female founder individuals at the beginning of the domestication process. This result is consistent with the previous estimate based on 15 ancient Iranian and 27 modern Near Eastern and Anatolian cattle [th millennium BCE [Using an ancient . Smaller genetic distances are observed between more adjacent areas, such as between Iran and Western Anatolia and between Iran and Southeastern Europe . Other statistics are equally consistent with the serial dilution model: Neolithic cattle from Iran yield the highest value for haplotype diversity in the whole dataset (0.96). Haplotype diversity consistently decreases along the proposed two main Neolithisation routes, with the lowest values in remote areas, i.e. in Neolithic Central/Western Europe and Southern France , while intermediate values are observed in between.Subsequent to the first domestication phase, the ancient DNA data, together with archaeological evidence, point to an intermittent expansion scenario. Expanding from Southeastern Anatolia, cattle reached Western Anatolia and the Aegean not before 7,000 BCE. From here, they spread simultaneously across Southeastern Europe and along the Mediterranean coast into Central, Northern, Southwestern, and Western Europe. In essence, the observed strong correlation between genetic and geographical distances together with decreasing genetic diversity roughly in a southeast to northwest and southwest direction is consistent with the idea of serial dilution of diversity by a series of recurring founder events. The oldest (Neolithic) groups with the greatest geographical distance from each other, namely Iran and Central/Western Europe and Southern France, show the highest FAlternative scenarios of secondary domestications or traceable female gene-flow from wild aurochs in Europe have been discussed several times in the literature ,47-51. TThe strict separation of domestic cattle from their wild European relatives is very different to what can be observed in other animals. For example, pigs were imported to Europe in a similar way to cattle, but after a few centuries all their mitochondrial lineages were replaced through admixture with local wild boar ,53.The summary statistical patterns described here may be partly biased by the fact that the analysed data come from heterochronous and spatially diverse samples . TherefoOur model suggests that a high proportion 73%) of domesticated cattle in Anatolia and the Near East may have migrated into Europe. This indicates that the expansion into Europe was a far less severe bottleneck than assumed, and that much of the variation present in the original Anatolian/Near Eastern population survived in initial European cattle populations. Consistent with this, the Western Anatolian and Southeastern European sample groups constitute a cluster in the MDS plot Figure . However% of domeST values between Iran , Southeastern Europe  and Italy  are much lower  despite larger geographic distances. A good indicator for this massive demographic change is that the frequency of the mitochondrial Q-lineage drops from 50 % in Southeastern European  to 4% in Central/Western Europe . Haplotype diversity decreases drastically from 0.62 to 0.22. There are several additional lines of evidence that point to the region between Southeastern Europe and Central Europe as a kind of core area where the Neolithic idea was re-consolidated: i) From archaeology: The Linearbandkeramik culture  developed here and spread rapidly over Central Europe starting around 5,600 BCE [Tracing the spread of cattle through the European mainland, there are patterns in the data that point to significant demographic changes connected to the expansion of the Neolithic culture from Southeastern to Central/Western Europe. The genetic distance between Southeastern Europe  and Central/Western Europe  is unexpectedly high (0.27). To put this high value into context: the F,600 BCE ; ii) Fro,600 BCE ; iii) Fr,600 BCE . We therCattle herding becomes more and more important with the onset of the LBK. A few centuries later, cattle bones constitute up to 70% of all domesticated animal bones in faunal assemblages in Central Europe, a value that stays roughly the same for most of the subsequent millennia with some regional fluctuations ,57. AccoInterestingly, there is no indication for population growth in Southeastern Europe. The observed diachronic increase in haplotype diversity in the Southeastern European sample groups appears in tandem with new, previously absent mitochondrial haplotypes . However, it is clear that there is support at least for some level of migration during this early period as the estimated modal migration rate is clearly greater than 0.According to our demographic modelling, migration between Anatolia/the Near East and Europe was greatly reduced, essentially to zero, in the period after 5,000 BCE. We should expect that accurately estimating the level of early migration between 6,400 and 5,000 BCE to be difficult, as it is somewhat confounded by the proportion of cattle th millennium BCE [We therefore suggest that a probable underlying scenario for our observations is one of continuous gene-flow into Europe following the initial colonization at around 6,400 BCE. This scenario also fits in with archaeological evidence for accelerated westward acculturation occurring in the first half of the 6nium BCE . This eaIt is of note that this pattern has changed again in later periods. The pattern of decreasing diversity in the direction of the Neolithic expansion and the correlation of genetic and geographical distances is considerably weaker in modern-day cattle breeds than in the Neolithic. It is not clear yet to which extent human migrations from the East as postulated for the Bronze Age  influencth millennium BCE, with a small effective number of wild female aurochs . After 7,000 BCE, domestic cattle populations were transported from the Central Anatolian plateau to Western Anatolia and the Aegean. Much of the original Anatolian and Near Eastern variation (approximately 73%) survived in the first Neolithic cattle that were introduced to Europe around 6,400 BCE. Despite some evidence for subsequent gene-flow with Anatolia and the Near East between 6,400 and 5,000 BCE, most of the initial genetic diversity was lost as cattle spread through Europe along with the Neolithic transition: Via the Mediterranean trajectory, migrating farmers reached i.e. Southern Italy, Northern Africa, the Tyrrhenian Islands, Southern France and the Iberian Peninsula by boat. The low genetic diversity observed in the few genetic data available from these regions points to a significantly low effective population size of cattle arriving in the Western Mediterranean. Along the second trajectory across the European mainland and without major signs of introgression from wild aurochs, cattle finally reached Central, Western  and Northern Europe . Also here, much of the genetic diversity was lost during the move, particularly when cattle were brought to Central Europe by LBK farmers.Overall, palaeogenetic together with archaeological and archaeozoological data strongly support the following scenario: taurine cattle were domesticated in a region between Southeastern Anatolia and the Zagros Mountains, Syria and the Lebanon. The domestication process started in the mid-9Gene-flow between Europe and Anatolia and the Near East appears to have been reduced, essentially to 0, after around 5,000 BCE. In modern breeds however, the genetic effects of the inferred migratory patterns and geographical diversification become far less pronounced, probably due to selective breeding and trade of high performance cows in very recent times.In summary, the genetic prehistory of domestic cattle seems to consist of a small, localised domestication process, followed by a relatively straightforward series of spasmodic expansion episodes resulting in a serial dilution of genetic diversity from the Near East to Western and Northern Europe. Future genomic multi-locus studies of ancient DNA from prehistoric periods will hopefully add greater detail to this picture, particularly by incorporating the potentially divergent demography of male cattle.