We describe the influence of ancestry on gene expression levels within and between these diverse human populations and uncover a non-negligible impact on global patterns of gene expression. We further dissect the specific functional pathways differentiated between populations. We also identify 5,691 expression quantitative trait loci (eQTLs) after controlling for both non-genetic factors and population admixture and observe that half of the cis-eQTLs are replicated in one or more of the populations. We highlight patterns of eQTL-sharing between populations, which are partially determined by population genetic relatedness, and discover significant sharing of eQTL effects between Asians, European-admixed, and African subpopulations. Specifically, we observe that both the effect size and the direction of effect for eQTLs are highly conserved across populations. We observe an increasing proximity of eQTLs toward the transcription start site as sharing of eQTLs among populations increases, highlighting that variants close to TSS have stronger effects and therefore are more likely to be detected across a wider panel of populations. Together these results offer a unique picture and resource of the degree of differentiation among human populations in functional regulatory variation and provide an estimate for the transferability of complex trait variants across populations.The genetic basis of gene expression variation has long been studied with the aim to understand the landscape of regulatory variants, but also more recently to assist in the interpretation and elucidation of disease signals. To date, many studies have looked in specific tissues and population-based samples, but there has been limited assessment of the degree of inter-population variability in regulatory variation. We analyzed genome-wide gene expression in lymphoblastoid cell lines from a total of 726 individuals from 8 global populations from the HapMap3 project and correlated gene expression levels with HapMap3 SNPs located in  Variation among individuals in the degree to which genes are expressed (i.e. turned on or off) is a characteristic exhibited by all species, and studies have identified regions of the genome harboring genetic variation affecting gene expression levels. To assess the degree of human inter-population variability in regulatory variation, we describe mapping of regions of the genome that have functional effects on gene expression levels. We analyzed genome-wide gene expression in human cell lines derived from 726 unrelated individuals representing 8 global populations that have been genetically well-characterized by the International HapMap Project. We describe the influence of ancestry on gene expression levels within and between these diverse human populations and uncover a non-negligible impact on global patterns of gene expression. We identify ∼5,700 genes whose expression levels are associated with genetic variation located physically close to the gene, and we observe significant sharing of associations that is partially dependent on population genetic relatedness, among Asians, European-admixed, and African subpopulations. We identify biological functions affected by regulatory variation and describe common and unique characteristics of population-specific and population-shared associations. These results offer a unique picture and resource of the degree of differentiation among human populations in functional regulatory variation. This deficit of knowledge needs to be addressed given that it is likely that: (i) a large number of high-frequency eQTLs exist in human populations; (ii) cis-regulatory variation contributes to both population-selective effects One of the fundamental questions of human population genetics is the extent to which human populations from around the world differ from one another. Population differentiation can be seen from the perspective of history, where neutral DNA sequence variation is used to reconstruct the relationships between populations given models of demography, migration, and genetic drift. The recent revolution of experimental approaches that address genome function has allowed the characterization of population differentiation with respect to variants that alter genome function. To date, two types of functional variants have attracted the most attention (i) variants that alter protein coding sequence (non-synonymous variants), and (ii) variants that are associated with levels of gene expression, i.e., regulatory variants that are also referred to as eQTLs (expression Quantitative Trait Loci). While there have been extensive studies of human population differentiation with respect to protein coding variants cis-regulatory effects An extensive number of studies have characterized the level and patterns of regulatory variation and eQTLs over the last decade. eQTLs have been studied in lymphoblastoid cell lines (LCLs) from the HapMap populations in vitro transcription (IVT) reactions were performed as one-quarter scale Message Amp II reactions  for each RNA extraction using 200 ng of total RNA as previously described Total RNA was extracted from lymphoblastoid cell lines of the 726 individuals of 8 HapMap populations. The numbers of individuals of each population includes: CEU: 109 Caucasians living in Utah USA, of northern and western European ancestry, CHB: 80 Han Chinese from Beijing, China, GIH: 82 Gujarati Indians in Houston, TX, USA, JPT: 82 Japanese in Tokyo, Japan, LWK: 82 Luhya in Webuye, Kenya, MEX: 45 Mexican ancestry in Los Angeles, CA, USA, MKK: 138 Maasai in Kinyawa, Kenya, and YRI: 108 Yoruba in Ibadan, Nigeria . Two To assay transcript levels in the cell lines, we used Illumina's commercial whole genome expression array, Sentrix Human-6 Expression BeadChip version 2, et al. (2005). Samples were processed in an order randomized with respect to population of origin and IVT batch.On a single BeadChip, six arrays were run in parallel as described in 2 scale using a quantile normalization method With the Illumina bead technology, a single hybridization of RNA from one cell line to an array produces on average approximately 30 intensity values for each of 47,294 bead types. These background-corrected values for a single bead type are subsequently summarized by Illumina software and output to the user as a set of 47,294 intensity values for each individual hybridization. In our experiment, each cell line was hybridized to two arrays, thus resulting in two reported intensity values  for each of the 47,294 bead types. Hybridization intensity values were normalized on a logThe expression data for GIH, LWK, MEX and MKK populations were normalized for admixture using a customized version of EIGENSTRAT which generates principal components on the basis of genetic data We employed a latent variable analysis separately for each population to correct the expression data for known and unknown factors that may influence gene expression in this dataset, with the aim to characterize and compare the properties of these results to those obtained without the correction. This dimension reduction differs from the PCA for admixture (Population stratification correction of expression data) in that it is possible to account for effects of unknown covariates, such as complex batch effects or subtle environmental influences, which can then be factored out of the expression data. The reduced expression data sets were learned using the probabilistic estimation of expression residuals (PEER) framework We used the PEER Bayesian regression and factor analysis modules for each of the 8 populations separately to learn the global effects of known and hidden factors on gene expression. Population and gender indicators were modeled as known global factors, essentially using Bayesian regression. Jointly with modeling these known factors, 32 hidden factors were estimated using Bayesian factor analysis. The prior on the weight precisions that acts as a regularization parameter was set to  for both models. These regularization parameter influences the effective number of factors retained after training. Specific settings are the standard ARD from cis-eQTLs with probes to those cis-eQTLs without probes.Of the 47,294 probes for which we collected expression data, we selected a set of 21,800 probes for analysis. We included in our analyses each probe that mapped to an Ensembl gene, but not to more than one Ensembl gene (Ensembl 49 NCBI Build 36), and we excluded probes mapping to the X or Y chromosome. The final set of 21,800 probes considered for association mapping corresponds to 18,226 unique autosomal Ensembl genes. We mapped known 1000 genomes common SNPs (MAF>5%) from CEU, CHB, JPT, YRI (August 2010) to all probes. We found that of the 21,800 probes we used in our analysis, 1401 (6.4% of tested probes) overlapped a known common SNP. There is the risk of a SNP-in-probe effect for these overlapping variants, inducing false positive eQTLs. We decided to not simply exclude these probes in an overly-conservative manner, but instead tested for possible enrichment among statistically significant eQTLs and compared the degree of replication across populations for those Single nucleotide polymorphisms (SNPs) for the same 726 HapMap version 3 individuals of CEU, CHB, GIH, JPT, LWK, MEX, MKK, and YRI, were selected (Release version 2) for use in the association analyses. Any SNP with MAF>5% in a population and with less than 20% missing data was included. This corresponds to between 1.1 million and 1.3 million SNPs per population.ST for each of the 21,800 probes for each pairwise combination of populations. VST is a measure of the proportion of expression level variance explained by between-population divergence, and is analogous to the population genetics parameter FST, but for a quantitative trait ST is calculated as: (VT−VS)/VT, where VT is equal to the total variance across all individuals of the pair of populations and VS is the average within-population variance weighted by each population sample size. VS = (V1*n1+V2*n2)/(n1+n2), where V1 is the within-population variance of population 1, V2 is the within population variance of population 2, and n1 and n2 are the numbers of individuals sampled from population 1 and 2, respectively. VST values range from 0 to 1, with values near 1 signifying that the majority of gene expression variance for a probe segregates between populations rather than within populations.To quantify population differentiation with respect to gene expression levels, we calculated the statistic VST statistic as a determinant of expression differentiation and selected the top 5% of the probes which were significantly differentiated between any two populations. Using this cutoff, we computed a one-sided Fisher's exact probability to determine enrichment of Gene Ontology (GO) terms. The GO p-values were for all pairwise comparisons were combined using Fishers combined probability, to identify those functional categories that across all pairs of populations are consistently among the most diverged between pairs of populations. To address the question of whether genes of specific functions exhibit significant population-specific expression differentiation, we used the VST score and selected the top 5% of the probes which were significantly differentiated between any two populations. Using this cutoff, we computed a one-sided Fisher's exact probability to determine enrichment of GO terms in the top 5% of probes. For a single population, such as CEU, all GO term p-values from pairwise population comparisons with CEU were combined using the Fisher combined probability and compared to the combination of GO term p-values for the other populations . We then filtered from the primary population those GO enrichment terms which were also found significantly differentiated among other populations. From this filtered list, we then selected the top ten GO terms for each population. These top ten values were used as indicative of functions which are significantly differentiated between the primary population and other populations and not between any other populations.To address the question of whether genes of specific functional classes tend to be among those exhibiting highest expression differentiation between populations (any pair of populations), we used the VWe addressed the question of whether those functions which are significantly differentiated in one population inform differentiation in a closely-related population . For example, differentiation might be similar for each of CHB and JPT when individually compared to all the other six populations (or for LWK and MKK and YRI). To address this, we assessed the enrichment in the p-value distribution for GO terms predicted in one population to be significant in another population (for each comparison both populations being compared are excluded). For example, we identify the GO terms that are significantly differentiated between CHB and all other populations (excluding JPT) and compare their p-values to the p-value distribution for terms with JPT and all other populations (excluding CHB).2 quantitative gene expression measurements for the 21,800 probes  from 726 unrelated individuals of each HapMap population assayed on the Illumina Sentrix Human-6 Expression BeadChip, 2) SNP genotypes for the unrelated individuals of each HapMap population with minor allele frequency above 5%.The eQTL association analysis employed: 1) Normalized logcis-eQTL analysis as follows: We limited the analysis to those probes and SNPs (MAF>5%) where the distance from the genomic location of the transcription start site (TSS) to SNP genomic location was less than or equal to 1 Mb. An association to a gene expression phenotype was considered significant if the p-value from the analysis of the observed data  was lower than the threshold of the 0.01 tail of the distribution of the minimal p-values  from 10,000 permutations of the expression phenotypes For each of the selected probes interrogating expression and for each SNP, we fit a Spearman Rank Correlation (SRC) model as previously described cis- regulatory signals exist for a given gene, we applied a stepwise association model as follows: For each probe that had a significant cis-eQTL at the 0.01 significance threshold, we regressed out of the expression levels the effect of the most-significant SNP, re-ran the SRC analysis on the rest of the significant cis-eQTL SNPs using the resulting expression residuals, and stored those SNPs with p-values more significant than the gene's permutation threshold. This was repeated separately for each probe until there were no SNPs from the initial significant eQTL list left to test (i.e. until none pass the permutation threshold after removing the effect of the most significant SNP at that step). At each iteration step, the most-significant SNP passing the permutation threshold is stored as an independent eQTL. We compared results obtained using the permutation thresholds based on the PCA corrected expression data to those obtained using permutation thresholds based on the residuals determined at each step of the stepwise model. We observed that there was no difference in the number of detected effects (not shown), so we used the thresholds based on the PCA residuals to evaluate p-values across steps.To determine whether independent We assessed the global landscape of expression using principal components analysis (PCA) . Unlike ST for each of 21,800 probes, corresponding to 18,226 unique autosomal Ensembl genes  terms, including nucleus, protein binding, RNA binding, nucleotide binding, RNA splicing  and regulation of immune response , indicating strong structure of expression variation for genes of these categories in CEU versus other populations, and that this structure is not seen between any other populations. We also addressed the question of whether those functions which are significantly differentiated in one population inform differentiation in a closely-related population . For example, differentiation might be similar for each of CHB and JPT when individually compared to all the other six populations . In general, GO terms corresponding to genes which are significantly diverged in expression in one population relative to the others are also diverged in expression in the other, closely-related populations  model (See cis association in at least one population. At higher stringency (permutation threshold 0.001), the per-population FDR ranged from 4%–11%; with a total of 1,132 genes exhibiting a significant cis association in at least one population.For each of the 21,800 probes  selected for analysis, we performed a odel See . The mododel See . Similarodel See  where FDcis-eQTLs associated with probes overlaying SNPs need to be interpreted with caution, we examined our significant associations for potential artifacts. At the 0.01 permutation threshold, of the 3,292 probes with significant associations , 249 probes (245 genes), overlaid a SNP. This means that 7.5% of the probes with a significant cis-eQTL overlaid a common SNP , which did not represent a significant enrichment of these probes among our significant associations. We did, however, consider the effect of these associations on across-population sharing of associations, and report levels of sharing both with and without these probes. At the 0.01 permutation threshold, of the 3,130 genes exhibiting a significant cis association, 1,074 genes had a significant association in at least two populations, and 63 in all eight populations. This indicates that 34% of genes with a significant cis-association had an association in at least two of the populations, and 2% of genes in all eight populations. If we conservatively exclude those probes known to overlap common SNPs, we reduce the number of non-redundant genes exhibiting a cis-association to 2,900, but observe that 957 (33%) of the remaining genes had a significant cis-association in at least two of the populations, and 54 (2%) in all eight populations. Thus, probes with underlying SNPs are not contributing significantly to our estimates of across-population sharing  of eQTLs. At higher stringency (permutation threshold 0.001), we note that none of the significant associations involve probes with underlying SNPs, and 48% of genes with a significant cis-association had an association in at least two of the populations, and 2% of genes in all eight populations . Together, these results demonstrate that by applying dimension reduction to the expression data, we do not introduce bias, rather we increase power and replication.To increase the power of our analysis we ran the data see  and the data see . In totated data . As expeted data . There ited data . Of the analysis . The addysis see . Of the cis-associated SNPs comprising a given cis-eQTL represent multiple, independent effects, we applied a stepwise regression framework to each probe that had at least two significant cis-eQTL SNPs at the 0.01 permutation threshold. We identified a total of 33 genes with multiple eQTLs , corresponding to 1.1% of genes with significant cis-eQTLs, or 1.7% of genes overall that had more than two significant cis-eQTL SNPs in at least one population. In CEU, fourteen genes exhibited multiple independent cis-effects (corresponding to 1.8% of genes with significant cis-eQTLs). In total, 10 genes (1.2%), 1 (0.14%), 7 (0.83%), 1 (0.12%), 0 (0%), 7 (0.71%), and 13 (1.5%) with multiple cis-eQTLs were detected for CHB, GIH, JPT, LWK, MEX, MKK and YRI respectively , translational activator of mitchondrially encoded cytochrome c oxidase subunit I, a gene with a role in Leigh Syndrome, was independently associated with five SNPs in LWK.To quantify the degree to which multiple ectively . Taken tcis- association, 1,074 (34%) of which had a significant cis-eQTL in at least two populations. We evaluated whether the extent to which pairs of populations shared significant cis- associations was related to their distance as defined by SNPs, with the goal of assessing the degree of sharing of functional variation across populations of varying ancestry. Qualitatively, we observed that more closely-related populations tend to share more cis- associated genes than more distantly-related populations  are similar among populations, suggests that the driving force behind the discovery of an eQTL in one population but not another is mainly due to allele frequency differences and not due to differences in absolute effect size.To quantify the degree of concordance of effect size across populations, for those SNP-probe associations significant in multiple populations, we asked whether the SNP exerts the same effect size in each of the populations, as quantified by expression level fold-change differences between homozygote genotype categories in each of the populations. We observe that the effect size (fold difference between homozygotes of the two different genotypic states of a SNP) is shared between any two populations when the association is also shared , and furcis- associations relative to the transcription start site (TSS) shows that the majority of association signals are approximately symmetrically centered on the TSS  in at least two populations and the distance to TSS of such eQTL-SNPs was larger relative to all other eQTL-SNPs for single genes. This signal suggests the presence of regulatory domains that influence multiple genes in a coordinated fashion and these tend to do so from long distances. Such coordinated regulation from distance is well known in the HOX cluster cis-eQTL results to the National Institute of Health's catalog of genome-wide association studies cis-eQTL in at least one population . These 62 SNPs associate with expression of 57 Ensembl genes, and 51 traits, including Alcohol dependence, Crohn's disease, Coronary Heart Disease, HDL cholesterol, Prostate Cancer, Trigylcerides, and many others . Of the 62 SNPs that were the most significant cis-eQTL for a given gene as well as associated to a trait in the GWAS catalog, we observed that 15 (∼24%) were the most significant SNP of the same gene in at least one additional population, a proportion which is likely an underestimate of the true value, given that the same SNPs weren't necessarily tested in all populations. We asked whether across-population replication of the most significant SNP per gene differed depending on whether that SNP was a GWAS SNP, and observed no difference . The eQTLs identified through our analyses contribute significantly to the available functional regulatory data that could be used to fine-map and elucidate the function of genetic variants contributing to complex phenotypes.The integration of eQTL results with GWAS has been proposed as a way to move toward biological and mechanistic understanding of complex trait etiology y others . The majcis- regulatory variation in a single cell type of individuals comprising a diverse set of eight human populations. The analysis of the genetics of nearly 20,000 gene expression phenotypes in such a number of human population samples allows us to identify large numbers of functionally variable regulatory regions in the human genome, as well as to estimate the degree of an aspect of functional variation that has not been assessed before. We find that at least 20% of the genes tested in our analysis have a common cis-eQTL in at least one population, and we detect extensive sharing of eQTLs across human populations even with fluctuations in allele frequencies, while there is also substantial non-genetic variance in gene expression levels. Overall, our data show that across all populations, there is an enrichment among population differentiated genes for those genes involved in regulatory function, while each population has unique sets of sets of genes, and categories of gene function, whose expression levels differentiate that population.We have performed a comprehensive study of cis-eQTL associations detected using the residual gene expression profiles (‘REDUCED’ data) have very similar characteristics to those detected using the straightforward normalized and PCA-corrected data, however the degree of across-population replication was higher for the ‘REDUCED’ data, which provides confidence that the method is not simply adding false positive associations. Indeed, this demonstrates that by applying dimension reduction, we do not introduce bias, rather we increase power and replication. For associations detected in more than one population, we find nearly perfect concordance of allelic direction across populations, and find that the absolute allelic effect size, as estimated by the fold-change between the two homozygote classes, remains the same across populations, suggesting little in the way of modification of eQTL effects across populations. The last two results support the idea that while eQTLs may explain different degrees of population variance depending on their frequency in each population cis-eQTLs.In accordance with previous eQTL studies, we observe a symmetric distribution of eQTLs around the transcription start site (TSS), with the strongest, most highly replicated, signals directly at the TSS. The simplest explanation for the relationship between distance to TSS and replication across populations is one of statistical power, as the long-distance smaller effects are less likely to be replicated. However we cannot exclude the possibility that these patterns, at least in part, reflect true biology such as the nature of long-distance enhancers. We applied factor analysis to the gene expression data to account for global non-genetic effects on the expression profiles and increased our power to detect eQTLs, especially those of smaller effect. The additional cis-regulation of gene expression in a single cell type. Taken together, our results suggest extensive cis- regulatory variation in humans, much of which will be uncovered as additional cell types are analyzed under a variety different cellular and developmental conditions, in larger numbers of individuals representing an even wider representation of human genetic diversity. Already these analyses contribute to the functional annotation of the human genome, and as a resource we have provided a list of variants that are associated with complex traits and are also the most significant SNP for an eQTL in this cell type. Given the genome-wide scale of these data and the diversity of populations surveyed, these eQTLs may assist in fine-mapping causal variants for complex traits and provide testable hypotheses for the mechanism underlying significant GWAS associations. Finally, our results reveal substantial diversity in frequency of regulatory variants among populations, with future work to understand how that spectrum has been shaped by selective and demographic processes, and how these functional variants contribute to higher order phenotypes, including those of health and disease.Our study represents the most genetically diverse eQTL study undertaken in humans to date, and has revealed extensive http://www.ebi.ac.uk/arrayexpress/) database (Series Accession Number E-MTAB-264). Furthermore, all eQTL results have been stored in the searchable online GENEVAR eQTL database The expression data reported in this paper have been deposited in the Array Express  of gene expression data. Gene expression data for each of the 21800 probes was analyzed using PCA. Here we plot PC1 versus PC2-9. Subtle separation due to ancestry is apparent but is not a dominating feature of expression differences suggesting that environmental or experimental effects are having a non-negligible effect in shaping gene expression differences among all individuals.(TIF)Click here for additional data file.Figure S2cis-eQTLs, and as expected, these probes are enriched sooner for correlation with their expression PCs against marker-based PC1. This supports the conclusion that population differentiation affects individual genes in different ways.Identifying the population component of total expression variability. To determine at which point ancestry affects the landscape of gene expression, we plotted the correlation of all obtainable expression principal components against SNP marker-based PCA component 1 (which separates African versus non-African populations). In the plot below, one can see that correlation is enriched for stronger components (the first 50 components) and maximized at components 2 and 7. We further assessed this for only those probes with significant (TIF)Click here for additional data file.Figure S3ST distribution for 21,800 probes compared between a) CEU and CHB , and b) CEU and MKK .V(TIF)Click here for additional data file.Figure S4ST genes between CEU and 6 other populations . We then look at the p-value distribution in YRI for GO terms that are significantly enriched in high VST genes between YRI and the 6 other populations (excluding CEU). This example is shown in bold green in the top left panel. Interestingly, the admixed populations  appear to not be well correlated with any other population suggesting that the differentiation of gene expression is unique in these populations.The degree to which significantly diverged gene expression in one population is also divergent in another population. We sought to determine the degree to which significantly diverged gene expression in one population is also divergent in another population. To assess this we calculated the p-value enrichment for GO terms which are significantly associated with expression differentiation in one population in another population (for each comparison both populations are excluded). In general, GO terms corresponding to genes which are significantly diverged in expression in a reference population relative to the others are also diversified in expression within the other populations (excluding the reference population). As an example, we consider the GO terms that are significantly enriched in high V(TIF)Click here for additional data file.Figure S5ST greater than two versus median FST across all SNPs.For each pairwise population comparison, the number of genes with V(TIF)Click here for additional data file.Figure S6−log10  for SNP-probe pair representing the most significant SNP per Ensembl gene (significant at 0.01 permutation threshold) in the REDUCED analysis and the corresponding the −log10  for the same SNP-probe pair in the analysis of the normalized and PCA-adjusted data. Panels correspond to a) CEU, b) CHB, c) GIH, d) JPT, e) LWK, f) MEX, g) MKK, h) YRI.(TIF)Click here for additional data file.Figure S7cis- associations significant in pairs of populations. Analysis of associations significant at the 0.01 permutation threshold are shown above the diagonal. Analysis utilized normalized and PCA-corrected expression data.Counts of Ensembl genes with (TIF)Click here for additional data file.Figure S8Cis-eQTL sharing across populations using parsimony. Average FST estimates were determined every 10000 SNPs across all pairwise combination of populations and used to create a distance matrix which was assembled into a tree using Neighbour Joining and Matrix Representation with Parsimony. eQTLs were assigned to the tree based on their discovery in at least one population at the 0.01 permutation threshold and then at the 0.1 permutation significance in any additional population. Only one association was selected for each gene; this was done at random. We then created 100 random trees based on reassigning at random the populations at the leaves. Compared to these random trees, the extent of eQTL sharing was increased for some nodes within the observed tree  . Since this permutation strategy may be overly conservative due to the fact that it does not randomize sharing between populations we also investigated using a different randomization strategy where we randomly assigned the shared populations for each association. Here, we observed not only the previously observed pattern but also observed that the extent of eQTL sharing was increased for nodes within the African subtree . These results highlight enrichment of eQTL sharing that are consistent with population structure.(TIF)Click here for additional data file.Figure S9Distribution of effect sizes conditioned on population sharing. We stratified fold change between heterozygotes for 0.1 eQTLs by the number of populations that the eQTL was discovered in at the same threshold. We observed that larger effects are more frequently discovered in multiple populations .(TIF)Click here for additional data file.Figure S10cis-association p-values in each of the other seven populations. Left panels display the distribution of all corresponding SNP-probe pair p-values that were significant in CEU, and the right panel shows the distribution of SNP-probe pair p-values after removing those associations that were significant in both CEU and the test population. When the analysis was performed with each other population as the reference, the results remain the same.Distribution of corresponding CEU significant (0.01 permutation threshold) (TIF)Click here for additional data file.Figure S11cis- associations relative to the transcription start site (TSS) and in relation to population sharing , two populations (2 pops), etc. Shown is −log10 of the p-value plotted against distance from SNP to TSS for each population. Each dot represents the most significant SNP for a significant gene (permutation threshold 0.01) in a populationDistribution of (TIF)Click here for additional data file.Table S1Summary of the distribution of VST values per probe for all pairwise populationcomparisons, including the number of genes with VST greater than 0.2.(PDF)Click here for additional data file.Table S2The top 20 most differentiated Gene Ontology functions between all populations.(PDF)Click here for additional data file.Table S3For each population, the top 10 most differentiated Gene Ontology functions betweenthe primary population and other populations (and not between any other populations).(PDF)Click here for additional data file.Table S4Range of Spearman's rho for a) cis- associations detected using ‘REDUCED’ data,and b) Spearman's rho for cis- associations detected using normalized and PCA-corrected data.(PDF)Click here for additional data file.Table S5Overlap of cis- associated genes that were detected using: 1) normalized andPCA-corrected gene expression data, and 2) ‘REDUCED’ data.(PDF)Click here for additional data file.Table S6Number of Ensembl genes with independent cis-eQTLs at the 0.01 permutationthreshold, as determined by stepwise association model.(PDF)Click here for additional data file.Table S7Overlap of the most significant cis -eQTL SNP per gene per population (‘REDUCED’ permutation threshold 0.01) with GWAS SNPs from NHGRI GWAS Catalog (Accessed 8/4/2011).(PDF)Click here for additional data file.


Atractoscion aequidens, across the Benguela region. The geographical distributions of the two populations, on either side of the perennial upwelling cell, suggest a strong correlation between the oceanographic features of the system and the breakdown of gene flow within this species. Genetic divergence , absence of migrants (less than 1% per generation) between populations and coalescent estimates of time since most recent common ancestor suggest that the establishment of the main oceanographic features of the system (2 million years ago), particularly the strengthening and position of the perennial upwelling cell, is the most likely mechanism behind the observed isolation. Concordance between mitochondrial and nuclear genetic markers indicates that isolation and divergence of the northern and southern Benguela populations of A. aequidens occurred deep in the past and has continued to the present day. These findings suggest that the Benguela Current system may constitute an ancient and impermeable barrier to gene flow for warm-temperate fish species.Contemporary patterns of genetic diversity and population connectivity within species can be influenced by both historical and contemporary barriers to gene flow. In the marine environment, present day oceanographic features such as currents, fronts and upwelling systems can influence dispersal of eggs/larvae and/juveniles/adults, shaping population substructuring. The Benguela Current system in the southeastern Atlantic is one of the oldest upwelling systems in the world, and provides a unique opportunity to investigate the relative influence of contemporary and historical mechanisms shaping the evolutionary history of warm-temperate fish species. Using the genetic variation in the mitochondrial DNA Control Region and eight nuclear microsatellite DNA loci, we identified the presence of two highly divergent populations in a vagile and warm-temperate fish species,  Contemporary patterns of genetic diversity and population connectivity within species are known to be influenced both by historical population processes, and by historical and present barriers to gene flow The Benguela Current, in the southeastern Atlantic, is characterized by cold sea surface temperatures, high productivity levels, and the presence of a perennial upwelling cell that physically divides the system into two contrasting subsystems Atractoscion aequidens (Cuvier 1830) is a migratory, benthopelagic sciaenid fish inhabiting coastal environments (15–200 m depth) along the western coast of Africa, from Mauritania to South Africa, and the eastern coast of Australia A. aequidens an ideal candidate to investigate the influence of oceanographic features on population connectivity. Because demographic changes cannot be inferred from climatic or fossil records, genetic data can provide a valuable source of information in this context. To uncouple the influence of contemporary versus historical processes, we analyzed both mitochondrial DNA (mtDNA) and nuclear microsatellite DNA variation in A. aequidens to investigate: i) present patterns of genetic diversity; and ii) the influence of Pleistocene climatic events on genetic connectivity, phylogeography and demographic history across the Benguela Current system. The data presented here provides the first comprehensive study of the influence of the Benguela Current oceanographic features in the genetic substructuring of coastal marine fish species in the region.Due to the nature of the sampling effort, fin clipping from commercial fishing catches, no ethics approval was considered necessary. Permissions for collecting samples were obtained when necessary .n = 382 – sampling sites LUA, BEN, LUC, NBE, PIN), northern Namibia (n = 7 – HEN) and South Africa   see . All indGenetic variation was screened at one mitochondrial DNA (mtDNA) region and eight nuclear microsatellite loci . The mtDA. aequidensp<0.05 A total of 395 individuals from six different localities  were scrH), private haplotypes (PH), haplotype diversity (h) and nucleotide diversity (π) were calculated for mtDNA CR sequences for each sample location using Arlequin v.3.5.1 φST values between samples were estimated using Arlequin v.3.5.1 A. aequidens.Number of haplotypes (aN), allelic richness (AR), observed and expected heterozygosity (OH and EH), and Wright's inbreeding coefficient (ISF), as implemented in FSTAT v.2.9.3 FST levels of 0.005, 0.02 and 0.05 using two effective population sizes (eN = 500 and eN = 2000), and varying the number of generations (t) accordingly. As the software only supports up to 50 alleles per locus, locus Geelb32 was removed , and all simulations performed for seven loci and six populations (n = 50 to n = 70). Each simulation was run for 1,000 replicates, and power was estimated as the proportion of the 1,000 tests that indicated significant genetic differentiation. After assessing power of the microsatellite dataset, pairwise population genetic differentiation was estimated using Weir & Cockerham's STF estimator STF can be low Dest, which is independent of heterozygosity, in SMOGD v.1.2.5 K, from K = 1–6, using burn-in lengths of 20,000 and run lengths of 80,000 Monte Carlo Markov Chain (MCMC) steps. In each analysis, five independent runs were performed for each value of K to ensure convergence of parameters during the runs. Estimation of the most likely K was performed based on the obtained posterior probabilities of the data From the microsatellite dataset, intraspecific and within-population nuclear genetic diversity was estimated as number of alleles  algorithm implemented in Network v.4.6 DFS0θ = 2N0μ), size after expansion (1θ = 2N1μ) and number of generations elapsed since expansion  were estimated assuming a sudden expansion model, and applying a general CR sequence divergence rate of 3.6% per My for marine teleosts A. aequidens undertakes large-scale migrations eN) using DNA sequence variation, when the nucleotide substitution model and rate are known D and FS tests, in order to date the fluctuation of female effective population size (efN) through time, a strict molecular clock was enforced, using a CR sequence divergence rate of 3.6% per My.Assessment of past population expansion was conducted on the mtDNA dataset using Tajima's m), as well as eN and efN were estimated using the coalescent-based method in Migrate v.3.4.2 m were obtained from M (M = mμ), and estimates of eN and efN were obtained from θ . Inference of immigration rate per generation was obtained by multiplying M and θ (xNem) m were obtained by applying a range of mutation rates: the commonly used 0.1% per generation, but also 0.05% and 0.2% per generation. In addition, in order to estimate recent migration rates (1–2 generations) between the two populations, the coalescent approach implemented in BAYESASS th iteration. Convergence of runs was assessed in Tracer v.1.5 Patterns of average, historical and contemporary connectivity between the northern and southern subsystem populations  from the mtDNA dataset. Two independent runs , using the HKY nucleotide substitution model and establishing the tree prior as the coalescent with constant size, were conducted in BEAST v.1.7.4 A. aequidens individuals (GenBank accession number JX192142-286) were amplified and sequenced for 583 bp of CR. The 144 sequences yielded 51 haplotypes, defined by 60 variable nucleotide sites, 51 of which sites were parsimony informative and 29 representing fixed differences between samples from Angola/Namibia and South Africa (A. aequidens exhibited high levels of haplotype diversity (h = 0.853) and moderate levels of nucleotide diversity (π = 0.005), with consistent levels across samples . Despite a smaller sample size, the southern haplogroup exhibited slightly higher genetic diversity values   .A. aequidens individuals (doi:10.5061/dryad.5gf80), and did not exhibit evidence of amplification errors, conforming to Hardy-Weinberg and linkage equilibrium expectation for the majority of loci and samples  below the level accepted to have no substantial impact on differentiation statistics aN), allelic richness (AR) and expected heterozygosity (EH), were similarly high across all samples  and microsatellite  datasets. For mtDNA, pairwise tests . No significant differentiation was observed among Angolan and Namibian samples  or among South African samples .There was significant genetic differentiation between se tests  indicateFST = 0.055, p<0.05; pairwise FST = 0.006–0.05, all p<0.001), but no significant differentiation within each area  – see Dest , and ranged from Dest = 0  to Dest = 0.268 .A similar pattern of genetic substructuring was observed in the microsatellite dataset, with all samples from Angola being significantly different from all samples from South Africa  and microsatellites , but non-significant variation among populations within groups when the hypothesis of a northern versus southern Benguela subsystem population structure was tested.Hierarchical analyses of the distribution of genetic variance (AMOVA) corroborated the pairwise sample tests, in finding significant variation distributed among groups for both mtDNA  and individuals sampled in the southern Benguela region (ARN and PAL) with no haplotypes shared between regions  to the northern (Angola) population, and 2m = 0.0006 individuals in the opposite direction. Using microsatellite data, both MIGRATE and BAYESASS retrieved very similar results: 1m = 0.0003 and 2m = 0.0002 with a mutation rate of 1×10−4 per generation, and 1m = 0.0019 and 2m = 0.0074, respectively. These findings further support the results from STRUCTURE where no admixed individuals were identified between clusters (eN) and female effective population size (efN) were high and of similar magnitude across the two populations .Estimates of average, long-term and recent migration rates among the two putative populations of clusters . CoalescSimilar likelihoods were obtained for estimates of time since the most recent common ancestor (tmrca) between the two putative populations , using tA. aequidens around southern Africa is composed of two distinct and non-interbreeding populations, the distributions of which appear to coincide with contemporary oceanographic features of the Benguela Current system. There was no evidence of genetic population substructuring within the northern Benguela subsystem (Angola and northern Namibia) population or within the southern Benguela subsystem (South Africa) population, but high genetic divergence was found between the two populations in both mitochondrial and nuclear genomes.Our results present evidence that A. aequidens within each region, so effective long-term passive dispersal by eggs/larvae and/or active dispersal by adults must be occurring. The impact of oceanographic features in population substructuring is dependent on species life history features A. aequidens may contribute to the observed panmixia. Both regional populations have pelagic eggs and an extended larval phase, likely to promote gene flow, but the two populations display divergent adult reproductive migration behavior that appears to be matched to different oceanographic regimes in the two subsystems . Based on adult catch information and the small size at maturity, there is no evidence of a spawning migration in the northern population . With a continuous distribution throughout the northern Benguela boundary region , it appears that this population has evolved an extended spawning season (seven months) to ensure that eggs are widely distributed by the bi-directional currents in the region The northern and southern Benguela boundary regions are characterized by multiple oceanographic features such as fronts , freshwater outflows , and multiple upwelling cells A. aequidens must be linked to a major impermeable barrier to gene flow located between the two putative populations. In the case of southern African A. aequidens, the complete isolation of the two populations, indicated by high levels of population divergence for both mtDNA and nuclear markers, combined with an absence of shared haplotypes or identifiable migrants (migration rates less than 1% per generation), suggest not only that the Benguela Current prevents dispersion in all life stages, but also that this is a long term and on-going effect. The genetic break between northern and southern populations coincides with the main upwelling features associated with the Benguela system, with several upwelling cells along southern Namibian and western South African coasts A. aequidens across the Benguela system.Given the effectively homogenized population structure within each region, the substantial genetic divergence between northern and southern populations of φST = 0.902, microsatellite FST = 0.055: probability of genetic homogeneity for both = p<0.001) were very high for a marine teleost. Marine fish typically have widespread distributions, historically large effective population sizes, high dispersal potential and high fecundity, all of which features promote low average genetic differentiation A. aequidens in the Benguela Current region is linked to the presence of an ancient and impermeable barrier to gene flow.Population genetic divergence values for the pairwise comparisons between samples from the northern and southern populations  around 25 Ka. As estimates of time since expansion based solely on mismatch distribution parameters have severe drawbacks as the only source of information regarding a species' demographic history, as they may be influence by early branching in the gene tree A. aequidens population. Severe declines in many marine fishes are associated with the LGM, with the majority of populations showing recovery after the end of the last glacial period ∼10 Ka A. aequidens does not appear to have been as rapid, but occurred earlier than reported for other fishes. In particular, studies conducted on other species in the southern Benguela region suggest that population growth occurred quite recently, during the Holocene (8-6 Ka) A. aequidens populations than those reported for other species in the Benguela Current region. The timing and rate of A. aequidens population expansion suggests that both populations may have survived the LGM in warm refugia that allowed range and population expansion from early in the interglacial period. Early population expansions pre-dating the end of the LGM have been described in warm-temperate fish species in the northern hemisphere, commonly associated with suitable refugia A. aequidens. Furthermore, a warming period between 40-18 Ky has been reported for the region, which may have contributed to an earlier population expansion of warm-temperate species in the Benguela Current system The mtDNA data  indicated strong support for past population growth, suggesting that both A. aequidens occurred deep in the past and has continued to the present day.The concordance between mitochondrial and nuclear genetic markers showing substantial differentiation, and the lack of indication of any contemporary gene flow, indicates that isolation and divergence of the northern and southern Benguela populations of A. aequidens populations in the Benguela Current region dates from the Pliocene-Pleistocene transition approximately 2 Ma. This transition was characterized by a generalized cooling of world oceans and major changes to circulation patterns, which have been linked to population isolation and vicariant speciation events for many fishes A. aequidens populations.The coalescent simulations indicated that the isolation of


Saxifraga oppositifolia in the isolated Arctic Svalbard archipelago. Purple saxifrage is a circumpolar, ecologically and morphologically variable species with a wide range of habitats. Population genetic structures showed that both genetic variation and differentiation levels are modest, outcrossing is the main mating system, and dispersal and gene flow are important, likely accountable to strong winds and human and animal vectors. Different growth habits  did not possess distinct genetic composition.Using DNA markers and sequencing we investigated patterns of genetic variability in purple saxifrage,  Saxifraga oppositifolia in the isolated Arctic Svalbard archipelago. The genetic analysis included genotyping using nine polymorphic microsatellite markers and sequencing of the nuclear internal transcribed spacer region. Among populations, mean allele numbers per microsatellite locus ranged from 2.0 to 2.6, and 9 % of alleles were unique. Observed (HO) and expected (HE) heterozygosities averaged 0.522 and 0.445, respectively. Typically negative but non-significant FIS values (mean −0.173) were found in S. oppositifolia populations. FST values were relatively low (mean 0.123). The Bayesian structure analysis provided additional information on population genetic structures. Seven out of 11 studied populations, including populations located both near each other and far apart (distances 5–210 km), showed relatively homogeneous clustering patterns, while one population located on a slope in the main settlement of Longyearbyen possessed a unique genetic structure. The Mantel test proved that there is no significant correlation between genetic and geographical distances. Different growth habits  did not possess distinct genetic compositions based on microsatellite variation. Internal transcribed spacer sequencing revealed 12 polymorphic sites. Among 24 sequenced Svalbard samples, eight haplotypes were detected, none shared by the mainland samples. Population genetic structures of S. oppositifolia in Svalbard show that both genetic variation and differentiation levels are modest, outcrossing is the main mating system, and dispersal and gene flow are important, probably attributable to strong winds and human and animal vectors.We investigated patterns of genetic variability in  In natural environments, organisms are typically exposed to several stress factors simultaneously, and the stresses are often most pronounced in extreme habitats, such as those at high latitudes and altitudes. For instance, Arctic plants may encounter many unique environmental factors, such as drought, permafrost, nutrient leaching, cryoturbation, extreme temperatures and short growing seasons . The ext, Saxifraga oppositifolia, is an Arctic–Alpine early flowering perennial herb. It is a circumpolar, ecologically and morphologically variable species with a wide range of habitats. It probably has the widest global distribution in the family Saxifragaceae  (Purple saxifrageragaceae . Saxifraant life . It is aant life . Saxifrae future . It is sbus sp.) . HoweverS. oppositifolia include random amplification of polymorphic DNA studies by S. oppositifolia  populations possess low levels of genetic variation and are genetically differentiated due to the colonization history and small population sizes and consequent effects of genetic drift, (ii) inbreeding and heterozygote deficiency are negligible due to supposedly prevalent outcrossing, and (iii) founder dynamics combined with gene flow from various sources has generated an admixed genetic structure in populations exposed to considerable human interference when compared with pristine populations. Since S. oppositifolia is morphologically variable and presents different growth habits  in the Arctic Svalbard archipelago in locations between latitudes 78 and 80°N , 0.15 µL of DyNAzyme II DNA polymerase (Finnzymes) (2 U µL−1) and 0.5 µl of both primers (5 pmol µL−1). The polymerase chain reactions (PCR) were carried out as follows: DNA denaturation at 94 °C for 4 min followed by 30 cycles of denaturation at 94 °C for 45 s, annealing at 46–60 °C (depending on the primer pair) for 45 s, and elongation at 72 °C for 1 min, with a final elongation at 72 °C for 10 min. For genotyping, PCR products were first diluted with ddH2O. Following this, 2 µL of each sample were pipetted into a 96-well plate, and 8 µL of standard  diluted with ddH2O (1/45) were added. The plates were then run with the MegaBACE 1000 DNA Analysis System (Amersham Biosciences). Genotyping results were then analysed with the MegaBACE Fragment Profiler 1.2 (Amersham Biosciences).We determined the population genetic characteristics of the populations using the following nine polymorphic microsatellite markers developed for itifolia : SaxJC, 2O, 2 μL of 10× buffer, 0.4 μL of dNTP mix (10 mM), 0.6 μL of Dynazyme II DNA polymerase (2 U μL−1) and 1 μL of both primers (5 pmol μL−1). The PCR cycle was similar to that in microsatellite genotyping, but the annealing temperature was 50 °C. Amplification products were run on a 1 % agarose gel, and the DNA fragments were excised and purified prior to sequencing using the E.Z.N.A. Gel Extraction Kit (Omega Bio-Tek). Purified DNA samples were sequenced at Macrogen Inc. using PCR primers. Internal transcribed spacer sequences were aligned with CLUSTAL W , F-statistics estimators FST and inbreeding coefficients FIS, and conducted Hardy–Weinberg equilibrium (HWE) testing for all loci with χ2 tests, and performed a Mantel test to discover possible relationships between genetic and geographical distances, all using Arlequin v3.5.1.2  to discover the value with the highest estimate of log-likelihood probability (ln Pr(X|K)) of the data. For each value of K, 10 independent runs were conducted with a burn-in length of 100 000 iterations, followed by a data collection period of 106 iterations. Furthermore, to identify the correct number of clusters (K) that best explains the data, ΔK values were calculated according to Based on microsatellite data, we calculated mean numbers of alleles per locus, mean observed and expected heterozygosities  in each population to distinguish plants with a common clonal ancestry from plants sharing the same microsatellite-based multilocus genotype (MLG) by chance. When MLGs were found more than once in a population, the software MLGsim  and to simulate the corresponding critical values for the significance level P < 0.05. To obtain the critical values for the test statistic, PSEX, the number of simulations was increased until stable critical values were reached.Since vegetative propagation is a potential mode of reproduction in We constructed haplotype networks for the ITS sequence data, including all our own data and comparable sequences of the same species available in GenBank, using the network building software TCS 1.2.1 . Therefore, no further adjustments due to MLGs were made for the data set.Identical MLGs were found in all populations, except in BIS and FLO. The total percentage of MLGs was 21 % of all genotyped individuals. In most cases the number of plants sharing the same MLG was two. However, according to the simulated critical values of HO) and expected (HE) heterozygosities varied between 0.367–0.695 and 0.375–0.525, and averaged 0.522 and 0.445, respectively. Hardy–Weinberg equilibrium testing conducted for populations indicated significant heterozygote deficiencies and excesses at 5 and 23 % of loci, respectively. Inbreeding coefficients (FIS) were commonly negative (mean −0.173), indicating slight heterozygote excesses, but the values were statistically non-significant in all populations.Among populations, mean allele numbers per locus were relatively even, ranging from 2.0 (NYB and FLO) to 2.6 (BOH) . The Mantel test revealed that there is no significant association between genetic and geographic distances. Population structures were also assessed using the Bayesian structure analysis by determining the log-likelihood probability of the data (ln Pr(X|K)) as well as the rate of change values (ΔK). The highest ΔK value was detected at K = 5 , while LYR possessed a more unique clustering pattern . No evident genetic difference was detected between different growth habits  within populations  were included in the network analysis. In all, nine single-nucleotide polymorphisms and three 1-bp indels were detected. The 24 Svalbard sequences resulted in eight haplotypes, among which one haplotype with 11 samples was dominant  and five samples from mainland Norway (accession numbers EF687807–EF687811). The clear, recorded region included most of the ITS1 region, complete 5.8S rRNA and most of ITS2. Additionally, 11 ITS sequences previously available for S. oppositifolia may benefit from this. S. oppositifolia is a plant that can rapidly colonize new deglaciated areas without losing genetic diversity. In addition, Genetic characteristics of species impact their capacity to maintain their populations and colonize new areas. The presence of genetic diversity is especially important for plant populations in highly stochastic environments like the Arctic. The Arctic climate has been warming and the surface air temperature has increased, especially in the Atlantic region around the Svalbard archipelago . More neP > 0.05) based on the testing of the PSEX values obtained. However, potential smaller clones were excluded on the grounds of the random sampling strategy. Among populations, mean allele numbers per locus ranged from 2.0 to 2.6, and only 3 out of 32 alleles (9 %) were unique. Observed (HO) and expected (HE) heterozygosities averaged 0.522 and 0.445, respectively. The expected heterozygosities and allele numbers indicate a modest and relatively even level of genetic variation. In a previous AFLP-based study on S. oppositifolia in the Alps and Pyrenees and Sierra Nevada, HE values varying regionally between 0.110 and 0.163, but such low values may be attributable to the different types of markers used. Also based on AFLP markers, S. oppositifolia between the present and previous studies are difficult, as the present study is the only one utilizing microsatellites.In the present study, although 21 % of the genotyped samples possessed MLGs that were identical to another MLG in the same population, none of the MLGs were likely to represent clones  found in S. oppositifolia populations indicate that outcrossing is the main mating system despite the species being self-compatible and dependent on its pollinators. At individual loci, significant heterozygote deficiencies were rare (5 %) but excesses were more common (23 %). The typical pollinators of Saxifraga, bumblebees (Bombus sp.), do not occur in Svalbard, where it needs to rely on other available pollinators, such as insects of the order Diptera  indicated a fair level of gene flow between populations occurring in different parts of Svalbard. Relatively low levels of differentiation have also been found in S. oppositifolia by Saxifraga species utilizing AFLP markers has revealed high levels of differentiation. Saxifraga callosa was studied in the Alps and showed extensive differentiation (GST = 0.899) , including populations located both near each other and far apart (distance variation 5–210 km), showed relatively homogeneous clustering patterns. Another set of three populations  resembled each other, while population LYR, located on a slope next to a new housing area and building sites in the main settlement of Longyearbyen, possessed a unique genetic structure. It is likely that the human-mediated colonization history and dispersal have been extensive, and that is reflected in the present genetic composition of S. oppositifolia in Longyearbyen. As expected from the Bayesian structure results, the Mantel test results proved that there is no significant correlation between genetic and geographical distances.Besides S. oppositifolia did not possess distinct genetic compositions based on microsatellite variation. For instance, population BOH containing mainly compact individuals and population BRE containing only trailing plants were genetically quite similar (FST = 0.070). Yet, earlier research on growth and reproduction patterns in S. oppositifolia has indicated that morphological variability is adaptive  of S. oppositifolia was also found in mainland Norway, Greenland, Slovakia and Switzerland.Sequencing of the nuclear ITS region revealed 12 polymorphic sites. Among 24 sequenced Svalbard samples, a total of eight haplotypes were detected, none shared by the mainland samples. One major Svalbard haplotype (46 % of samples) was found in seven populations , which are located at distances 9–198 km from each other. Among the five samples sequenced for LYR, four haplotypes were found, two of which were unique among the study material. Based on the network analysis conducted, one of the unique ITS sequences of LYR appeared to descend from a haplotype discovered among samples from mainland Norway. These observations also support the view of the distinct colonization history of the LYR population. Among the nine mainland haplotypes, the Norwegian ones were related to each other or Svalbard haplotypes, except for a sample from Hordaland in southern Norway, which was identical to a haplotype also found in mountainous areas of Italy and Spain. Otherwise, the haplotypes from Austria, Italy and Spain were relatively closely related, while the haplotype revealed for the two samples from the USA was distinct. An increased sample size in mainland Europe, especially in Norway, could have provided a more precise insight into the relationship between Svalbard and other populations. Recently Saxifraga paniculata, S. oppositifolia indicates a fair level of haplotype diversity in the Arctic Svalbard populations. The ITS region as such is not supposed to be especially useful when studying larger-scale phylogeography of S. oppositifolia because of its largely unresolved topology with low statistical support .In a related species,  support . Yet, thS. oppositifolia. Small seeds are dispersed by the winds across the glaciers and whole plants have been known to float great distances on ice (S. oppositifolia, particularly on its nutritious reproductive shoots (S. oppositifolia has occurred repeatedly and from several source regions, probably by wind and drifting sea ice. Evidently, establishment limits distribution more than dispersal.Strong winds in the open landscape, sea currents, drift ice and dispersal by vectors, such as humans and birds, may explain the present phylogeographic and population genetic patterns of s on ice . It has e shoots , especiae shoots . AlthougS. oppositifolia in Svalbard revealed that differentiation levels are modest, and that dispersal and gene flow are important phenomena within Svalbard, probably attributable to strong winds and human and animal vectors. The nine polymorphic microsatellite markers used and ITS sequencing are useful tools when examining population genetics and phylogeography of S. oppositifolia on different geographic scales.Population genetic structures detected in Kuopion Luonnon Ystäväin Yhdistys Foundation and NordForsk.Financial support was obtained from M.P. collected most samples, conducted all laboratory work and part of the data analysis and manuscript preparation. H.K. collected some samples and conducted part of the data analysis and manuscript preparation.None declared.


Lygaeus equestris (Heteroptera) in southwestern Finland and in eastern Sweden. We tested whether genetic differentiation of the L. equestris populations was related to the similarity of vegetation, and whether there was more within-population genetic variation in habitats with a high number of plant species or in those with a large population of the primary food plant, Vincetoxicum hirundinaria. We also tested whether genetic differentiation of the populations was related to the geographic distance, and whether location of the populations on islands or on mainland, island size, or population size affected within-population genetic variation. Pairwise FST ranged from 0 to 0.1 indicating low to moderate genetic differentiation of populations. Differentiation increased with geographic distance between the populations, but was not related to the similarity of vegetation between the habitats. Genetic variation within the L. equestris populations did not increase with the population size of the primary food plant. However, the more diverse the plant community the higher was the level of genetic variation within the L. equestris population. Furthermore, the level of genetic variation did not vary significantly between island and mainland populations. The effect of the population size on within-population genetic variation was related to island size. Usually small populations are susceptible to loss of genetic variation, but small L. equestris populations on large islands seemed to maintain a relatively high level of within-population genetic variation. Our findings suggest that, in addition to geographic and species-specific ecological factors, the plant community affects population genetic structure of oligophagous herbivores.Several characteristics of habitats of herbivores and their food-plant communities, such as plant-species composition and plant quality, influence population genetics of both herbivores and their host plants. We investigated how different ecological and geographic factors affect genetic variation in and differentiation of 23 populations of the oligophagous seed predator  Herbivores have to adapt to geographically and temporally varying communities of their host plants as well as to genetically determined plant defenses and the nutritive content of their food-plant species. Plant-species composition and plant quality exert selection on herbivores and may affect their population genetics e.g. . On the The occurrence and nutritive quality of a single food-plant species determine the survival and performance of specialist herbivores e.g. . AccordiIn addition to food-plant quality and diversity, several other, more general, biological and geographic characteristics of the habitat and population may influence the genetic structure of herbivore populations. Small and isolated populations are in general more susceptible to the loss of within-population genetic variation that affects the viability of populations and species Lygaeus equestris (Heteroptera) in southwestern Finland and in eastern Sweden. We used amplified fragment length polymorphisms (AFLP) to assess genetic variability. We specifically tested whether genetic variation of L. equestris was higher in populations that occurred with large populations of the primary food plant, Vincetoxicum hirundinariaV. hirundinaria populations may sustain larger and more stable L. equestris populations than smaller V. hirundinaria populations. Furthermore, while L. equestris may use other plant species than V. hirundinaria as alternative food L. equestris populations occurring in habitats with a high total number of vascular plant species. Since L. equestris may feed on a large number of alternative food-plant species when the seeds of V. hirundinaria are not available  is a seed-eating true bug that is specialised to feed on Vincetoxicum hirundinaria Med. ( =  Cynanchum vincetoxicum (L.) Pers.) (Apocynaceae), a highly poisonous long-lived perennial herb L. equestris may occasionally also feed on several other plant species than V. hirundinaria, in Scandinavia it is found merely in V. hirundinaria populations Lygaeus equestris is locally common in the distribution area of V. hirundinaria in Scandinavia, but its population sizes vary considerably among years and populations  granted a licence to collect L. equestris was extracted with NucleoSpin Tissue kit  according to the manufacturer's standard protocol. All laboratory work and genotyping were performed by the Center of Evolutionary Applications . The genotyping was based on amplified fragment length polymorphism (AFLP) profiles that were generated using a protocol modified from Vos et al.DNA of Marker reproducibility and genotyping-error rate were estimated using replicates in different phases of the AFLP protocol . It is ret al.Allele frequencies were calculated with the square-root method L. equestris using the AFLP-SURV 1.0 program e) as measures of within-population genetic variation for each of the 23 populations e, we first calculated the expected heterozygosity per locus, hj, by subtracting the expected frequencies of homozygotes from 1 . This was repeated for all loci and the average was calculated to obtain expected heterozygosity over all loci, He. We also estimated the average genetic variation within populations by calculating the average PLP and mean expected heterozygosity, HS, and standard errors for these values.We estimated the levels of genetic differentiation and within-population genetic variation of ST, to estimate genetic differentiation among populations in terms of allele frequencies L. equestris populations, we also calculated pairwise genetic differentiation as pairwise FST for all population pairs.In addition to estimating the level of within-population genetic variation, we calculated average Wright's fixation index, FV. hirundinaria populations varies in our study area. Thus, the number of mature V. hirundinaria individuals was counted in all those study sites, where population size was lower than 100 individuals . On these two islands, the L. equestris samples were collected only from one site, and V. hirundinaria population size was estimated based on observations from this site The size of ividuals . In popuL. equestris was related to the diversity of the plant community we estimated plant-species diversity in the communities where the V. hirundinaria and L. equestris populations occurred. We conducted the vegetation survey twice during the summer 2009  in all study sites, and all the plant species present at least once were regarded as present. Poaceae and Carex were excluded from the vegetation survey because of limited resources and the fact that these groups are not among the most important alternative food sources of L. equestrisL. equestris feeding on these plants in our study area . Poaceae was abundant in all populations, but Carex species were present only in some of the populations. First, we investigated whether the genetic differentiation between the L. equestris populations was related to the similarity of vegetation between the study sites. For this analysis, we calculated the Sørensen's species similarity coefficients for each population pair using presence/absence data on the plant species L. equestris correlated positively with the number of vascular plant species .To test whether genetic differentiation between populations or within-population genetic variation of L. equestris in the same area where the V. hirundinaria population size was estimated. The population size of L. equestris was estimated by calculating the average number of individuals observed on 14–20 randomly chosen V. hirundinaria plants in the ten Finnish populations and multiplying the average by the estimated number of V. hirundinaria individuals in a population. The V. hirundinaria individuals from which L. equestris was counted varied in size and were chosen haphazardly from the entire area where V. hirundinaria occurred. The L. equestris individuals were counted in August – September to insure that all individuals represented the same generation. We then tested whether large L. equestris populations had more within-population genetic variation compared to smaller populations .In August – September 2007 we estimated the population size of L. equestris populations was related to the geographic distance between populations we determined the distances for all population pairs using the geographic coordinate data registered with GPS (Garmin eTrex). The distances between the populations vary from one to 598 kilometres. We also examined whether the island populations had less within-population genetic variation than mainland populations, as water may restrict migration between populations http://www.paikkatietoikkuna.fi/web/fi/kartta and http://www.gis.lst.se/lanskartor).To investigate whether the genetic differentiation between the ST values were computed after each permutation consisting of randomly permuting individuals among existing populations. The real observed FST was then tested against the distribution obtained by permutation. The permutation tests for genetic differentiation were done using AFLP-SURV 1.0 program We tested the significance of the overall genetic differentiation among populations with permutation tests. The resampling statistics was based on 100 000 random permutations. FL. equestris populations (pairwise FST) was related to the similarity of vegetation between the sites. We first tested whether the geographically closely located populations were more similar in vegetation by comparing the geographic distance with the Sørensen's similarity coefficients by simple Mantel test between the two matrices. Because geographically close populations were more similar in vegetation , we tested whether the genetic differentiation of L. equestris was associated with the similarity of vegetation by conducting partial Mantel test correcting for the geographic distances between the populations. We also tested whether the genetic differentiation between the L. equestris populations correlated with the geographic distance between populations with simple Mantel test between the two matrices. The tests of significance were based on 100 000 random permutations We tested whether the genetic differentiation of L. equestris was associated with geographic and ecological characteristics of the study sites. We used the percentage of polymorphic loci (PLP) and expected heterozygosity (He) as estimates of within-population genetic variation e as the dependent variables. The location of population on an island or on mainland was included as a fixed factor and V. hirundinaria population size and the number of vascular plant species were included as continuous factors in the analyses of the 23 L. equestris populations from Finland and Sweden. Because we had some additional data collected exclusively from the ten Finnish island populations, we conducted separate analyses using the data from these populations , L. equestris population size, and the interactions between these variables were included as continuous variables in the analyses. The continuous explanatory variables were not correlated (data not shown) except for V. hirundinaria population size and L. equestris population size . This is due to the fact that V. hirundinaria population size was used to count L. equestris population size. The population sizes of V. hirundinaria and L. equestris were not included in same models. Because the assumptions of general linear model were not fulfilled for PLP in the analysis with the 10 L. equestris populations from Finland, these data were analysed using ranked values. We used the AIC values to select the best-fitting models in all analyses We tested whether the within-population genetic variation of ST values ranged from 0 to 0.100. This level of among-population differentiation can be considered low or moderate ST values of 45 population pairs  indicated moderate differentiation (FST between 0.05 and 0.15). The average FST indicating overall genetic differentiation among all populations was 0.034±0.001 . This value suggests rather low genetic differentiation among the L. equestris populations. However, the permutation test indicated that populations were genetically more differentiated than random assemblages of individuals (p<0.05).The pairwise FL. equestris populations was not related to the similarity of vegetation between the study sites . Genetic differentiation of the L. equestris populations increased with increasing geographic distance between the populations  ranged from 74.6% to 94.9% in the individual populations (e) ranged from 0.265 to 0.316 (S) was 0.294±0.003 (mean ± se).We found significant level of genetic variation within the ulations . The aveto 0.316 . The meaV. hirundinaria nor the number of vascular plant species affected the percentage of polymorphic loci, PLP . PLP did not vary significantly between island and mainland populations . Furthermore, the effect of the population size of V. hirundinaria on PLP of L. equestris did not differ between island and mainland populations . Moreover, the effect of the number of plant species on PLP did not differ between island and mainland populations .When all 23 populations from Finland and Sweden were included in the analysis, neither the population size of L. equestris was related to island size  of L. equestris . In contrast, the effect of the number of vascular plant species on He was significant .When all 23 populations from Finland and Sweden were included in the analysis, the population size of ncreased . He did e, was significant . As in the model with all 23 populations, the more plant species in the plant community, the higher was the level of genetic variation within L. equestris population in terms of He. Neither island size, nor the population size of L. equestris affected He .When the ten island populations from Finland were analysed separately, the effect of the number of vascular plant species on expected heterozygosity, He) genetic variation within the populations increased with the diversity of the plant community. However, the effect of plant-species diversity on the percentage of polymorphic loci depended on island size. The diverse set of alternative food-plant species together with other resources (i.e. more diverse habitats for oviposition and hibernation) occurring on large islands may enable the existence of highly viable and stable L. equestris populations with high level of within-population genetic variation. On large islands with high plant-species diversity and high within-population genetic variation L. equestris may be able to feed on several alternative species simultaneously. These populations may then survive through periods with no V. hirundinaria seeds available. Agrawal et al. et al.In line with our predictions, our results demonstrate that in terms of expected heterozygosity , affects the abundance of V. hirundinaria seeds. Consequently, the potential competitive effect of E. connexa on L. equestris is likely to vary among populations (L. equestris populations was not influenced by the population size of V. hirundinaria is the impact of contemporary migration (see below).In addition to the availability of a diverse set of alternative food-plant species, the availability of the primary food, L. equestris finds its food plants. However, another Lygaeid species, Oncopeltus fasciatus, finds its food plant  mainly by olfactory cues and prefers dense patches of food plants L. equestris.We used plant-species diversity and the abundance of the primary food plant as features of the plant community to explain genetic variation of an oligophagous herbivore. In nature, in addition to the number of the plant species, their spatial distribution, densities, and relative abundances contribute to the ability of herbivores to find and use the different food plants L. equestris populations studied here have a high level of within-population genetic variation .Compared to other sexually reproducing insects, the ion e.g. . MigratiL. equestris populations on small islands had low percentage of polymorphic loci on average, but small populations on larger islands harboured a higher level of within-population genetic variation. In our study area, L. equestris populations on large islands may be less susceptible to population bottlenecks and extinction-recolonisation processes that both can alter allele frequencies in populations and reduce within-population genetic variation L. equestris populations on large islands are likely to be older than those on smaller islands. The small but older L. equestris populations on larger islands are likely to have had a longer history of inbreeding suggesting that deleterious recessive alleles have been purged in these populations. However, if the small and young populations on small islands still harbour deleterious alleles that are expressed due to inbreeding, these populations may be more prone to extinction In general, small populations often have less within-population genetic variation compared to large populations due to loss of alleles caused by inbreeding and genetic drift L. equestris increased with increased geographic distance among the populations , seems to suggest that the number of potential alternative food-plant species present in a habitat might be more important for survival of L. equestris than the identity of species per se. Indeed, most plant species have been shown to be quite poor quality food for L. equestris, and lead to reduced growth and lower reproduction L. equestris has previously been studied in Sweden using allozyme electrophoresis L. equestris between her two study areas (225 km distance), but not among the seven populations within one area . In our study, the pairwise FST values of L. equestris population pairs with less than 10 km distance indicated low level of differentiation .Wang Our findings provide valuable information about the role of ecological and geographic factors as modifiers of the population genetic structure of an oligophagous seed-eating herbivore. Several studies have shown that herbivore-species diversity increases with plant-species diversity and plant genetic diversity e.g. . To our Supporting Information S1Description of DNA extraction and genetic analysis.(DOC)Click here for additional data file.Supporting information S2Results from mixed model ANOVAs and general linear models. Complete models without model simplification.(DOCX)Click here for additional data file.


Daktulosphaira vitifoliae) is one of the world’s most important viticultural pests. However, the reproductive mode, genetic structure and host adaptation of phylloxera in various viticultural environments remains unclear. We examined reproductive mode and genetic structure of phylloxera by analyzing microsatellite makers across the samples from four vineyard-sites in California.Grape phylloxera  were observed among different repeated genotypes within each vineyard. Moreover, high variation of FIS was observed among different loci in each vineyard-site. Genetic structure analysis (UPGMA) and various measures of population differentiations  consistently separated AXR#1  associated populations from the populations associated with other different rootstocks.The phylloxera populations in California are believed to have predominantly parthenogenetic reproduction. Therefore, genetic diversity of phylloxera is expected to be limited. However, this study showed relatively high levels of diversity in Napa and Yolo county populations with a large number of unique genotypes, average number of alleles (2.1 to 2.9) and observed heterozygosities (0.330 to 0.388) per vineyard-sites. Reproduction diversity index (G: N—unique genotypes versus number of samples) ranged from 0.500 to 0.656 among vineyard-sites. Both significant and non-significant Psex and FIS consistently suggested the occurrence of both parthenogenetic and sexual reproduction in California populations. This study clearly identified two major groups of phylloxera obtained from various rootstocks, with one group exclusively associated with only AXR#1 rootstock, defined as “biotype B”, and another group associated with vinifera-based rootstocks, known as “biotype A”.Genetic diversity, G: N ratio,  Daktulosphaira vitifoliae) Fitch (Hemiptera: Phylloxeridae) is an economically important pest that specializes in feeding on grapevine (Vitis spp.). It is an aphid-like pest that forms pocket like galls on leaves and hooked galls (nodosities) on the young root tips. This pest has destroyed vineyards around the world for the past 150 years and is regarded as one of the world’s most important viticultural pests and one site at Yolo County (Woodland). Detailed sample information and population IDs are presented in Table  Collins-V. vinifera x V. rupestris) rootstock. The south end of the Collins site  was still planted with the original AXR#1 at the time of sampling. However, the adjoining 4 hectares of the Collins site (Col-2) were replanted with the rootstock 5C (V. berlandieri x V. riparia) after the AXR#1 failed to phylloxera. Samples from the University of California, Davis Oakville Experimental Station (UCD-OKV) were collected from about a 1 hectare block planted with the rootstocks 5C, 1103P and 101-14Mgt. This site was also replanted over an AXR#1 block that failed to phylloxera. The Woodland samples were collected from leaf galls that had formed at a rootstock nursery block containing 110R and 101-14Mgt.The Collins site is a 6 hectare vineyard in Oakville, Napa County, CA that was originally planted with AXR#1  for DNA extraction as described by. DNA con2, 1U Taq polymerase (Applied Biosystems) 0.2 mM dNTP (Applied Biosystems), 0.25 pM of the labeled primer, 0.25 pM of the unlabeled primer and 20 ng DNA. A PTC-100  was used to run the reactions with the following program: 95°C for 5 min followed by a 40 cycles of 95°C for 30 sec, 58°C for 30 sec and 72°C for 1 min, and a final extension at 72°C for 10 min.Eight microsatellite markers from phylloxera were employed in the present study. Five of these markers  were described in and threThen 1 μl of PCR product was added to 10 μl deionized formamide and 0.15 μl of molecular size standard (GENESCAN 500 ROX). The mixed PCR products were then loaded on to an ABI PRISM 3100 Genetic Analyser (Applied Biosystems) with 36-cm capillaries filled with polymer POP-6 module. The data were analyzed by GeneMap 4.0 (Applied Biosystems).n times a multilocus genotype in a population and the likelihood of them having resulted from clonal reproduction was tested using MLGsim software[Psex values were calculated for every set of repeated genotypes at each population as suggested by Halkett et al.[Psex values, identifying repeated copy multilocus genotypes that did not occur by chance from sexual reproduction (true clones). Calculations were done for each population, taking into account sample size and allele frequencies. The significance level was set to 0.05.Allelic data obtained from multilocus microsatellite markers were combined and genotypes were identified. Several sets of repeated genotypes were identified within the population at each study site. The probability of observing software. Based ot et al.. Using aTo estimate reproduction diversity, a diversity index was calculated for each population using the G: N ratio, where G is the total number of unique genotypes found across all samples and N is total number of samples. The G:N ratio ranges from 0– all individuals share the same genotype, in case of strict clonality to 1– all individuals have distinct genotypes, under sexual reproduction.F-statistics due to the presence of identical copies of clonal genotypes in the populations tested, a clonal-corrected  data set was built, and applied to the analyses.Under the very likely condition that repeated  ‘amplification’ is not equal over all genotypes, unwitting inclusion of clonal copies in population genetic analyses has the potential to mislead. TherefoHO), Nei’s unbiased expected heterozygosity (HE)[FIS)[FIS from zero within population was determined using the FSTAT randomization test. Hardy–Weinberg equilibria over all loci and populations were tested using GENEPOP web version 4.0.10[GenAlEx Version 6.3 was usedity (HE) per micrity (HE) was usedE)[FIS) within en 4.0.10. A Markon 4.0.10. GENEPOPFST as a basic matrix of population genetic structure and differentiation. A significance test of FST was performed using FSTAT ver. 2.9.3.2[http://bioinformatics.org/~tryphon/populations) and graphically displayed with MEGA4 software[GENEPOP web version 4.0.10 was used 2.9.3.2, where t 2.9.3.2 between software. ConfideFinally, to evaluate the overall patterns of population variation within a multivariate data set (multiple loci and multiple samples), a principal coordinate analysis (PCA) was performed using GenAlEx Version 6.3 on a covm, where m is the proportion of each population having immigrant ancestry and where first-generation immigrants or offspring of two immigrant parents will be considered as having full immigrant ancestry and offspring of one immigrant and one native parent will be considered as having half immigrant ancestry. It also calculates a confidence interval for results that would be returned from uninformative data, typically those that do not contain sufficient variation to estimate dispersal with high confidence[To obtain an estimate of the magnitude and direction of contemporary gene flow among populations, a genetic assignment method was used with BayesAss.ver.1.3. This panfidence,48. A ruHL, GJ, and MAW coordinated the study. TLR and GJ collected samples and prepared DNA samples for genetic analyses. TLR, HL, MSI carried out genotyping of phylloxera samples. MSI, MAW and HL analyzed results and wrote the paper. All authors read and approved the final manuscript.Distributions of multilocus genotypes of grape phylloxera among the populations from four vineyard-sites in Napa (Oakville) and Yolo (Woodland) counties, California.Click here for file