Salmo trutta have been described in terms of five major mtDNA lineages, four of which correspond to major ocean basins, and one, according to some authors, to a distinct taxon, marbled trout Salmo marmoratus. The Atlantic and Danubian lineages of brown trout meet in a poorly documented contact zone in Central Europe. The natural versus human mediated origin of the Atlantic lineage in the upper Danube is a question of both theoretical and practical importance with respect to conservation management. We provide a comprehensive population genetic analysis of brown trout in the region with the aim of evaluating the geographic distribution and genetic integrity of these two lineages in and around their contact zone.Brown trout 1 hybrids were found implying that admixture has been established over time.Genetic screening of 114 populations of brown trout across the Danube/Rhine/Elbe catchments revealed a counter-intuitive phylogeographic structure with near fixation of the Atlantic lineage in the sampled portions of the Bavarian Danube. Along the Austrian Danube, phylogeographic informative markers revealed increasing percentages of Danube-specific alleles with downstream distance. Pure Danube lineage populations were restricted to peri-alpine isolates within previously glaciated regions. Both empirical data and simulated hybrid comparisons support that trout in non-glaciated regions north and northeast of the Alps have an admixed origin largely based on natural colonization. In contrast, the presence of Atlantic basin alleles south and southeast of the Alps stems from hatchery introductions and subsequent introgression. Despite extensive stocking of the Atlantic lineage, little evidence of first generation stocked fish or FSalmo in Central Europe. The distribution pattern of the Atlantic and Danube lineages is extremely difficult to explain without invoking very strong biological mechanisms.A purely phylogeographic paradigm fails to describe the distribution of genetic lineages of The peri-alpine distribution of relict populations of pure Danubian lineage brown trout implies that they colonized headwater river courses post-glacially ahead of the expansion of the Atlantic lineage. The recognition of natural as opposed to anthropogenic introgression of the Atlantic lineage into Danubian gene pools is of fundamental importance to management strategies. To the extent that studies support these expectations, the evolutionary significance of this non-biological source of genetic structure remains controversial [Telestes souffia[Thymallus thymallus[Cottus gobio[Perca fluviatilis[Leuciscus cephalus[Barbus carpathicus[An overwhelming majority of species in nature exhibit some level of phylogeographic structure and this structure is very often shown to correspond to major landscape features born out of paleo-environmental processes. The phylogeographic revolution  has promoversial . Moreoves souffia and Eurothymallus, but a ctus gobio. In contuviatilis and Euro cephalus and betwrpathicus. The prerpathicus. While mThe brown trout was one of the first non-model vertebrates to attract the attention of population geneticists in Europe -12 and sSalmo labrax[In Central Europe, the notion of a Danube lineage of brown trout has been well-established and unquestioned within management and conservation circles. The lineage, however, exhibits extensive life-history diversity and stretches across the entire Ponto-Caspian basin, exhibiting its deepest split across the Tigris-Euphrates catchment , leavingmo labrax, althougmo labrax reportedmo labrax. A reviemo labrax concludemo labrax. NonetheIn this paper we characterize the population genetic structure in the upper Danube in the Alpine and sub-Alpine regions of Austria and Bavaria including comparison to samples from adjacent areas of the Rhine and Elbe drainages Figure . This stN = 11) fixed for Danubian mtDNA (Table P < 0.001) between the frequencies of Atlantic mtDNA and the LDH-C1 90* allele across all populations. Correcting for multiple testing, there was no deviation from HWE at the population level for the LDH-C1 locus. For some comparisons in the text we will refer to populations fixed for Danube mtDNA as “pure Danubian”.Atlantic lineage mtDNA was fixed in the Rhine and Elbe drainages and there was a general decreasing trend in its mean occurrence from west to east (i.e. downstream) within the Danube basin ranging from a high of 93.5% in the Bavarian Danube to a low of 32.1% in the Austrian Drau, south of the Alps (Table P = 0.018) among drainages with the highest values found in the Austrian Danube (6.4) and the lowest in the Austrian Drau (5.1). There was a highly significant difference  in mean allelic richness between populations fixed for Danubian mtDNA (3.8) and the remaining Danubian populations of the Mur and Drau drainages (6.2). HE likewise ranged widely across populations (0.374 to 0.836) and showed wholly analogous patterns of statistical significance within and among major basins (data not shown). There was a significant positive correlation between HE and the percent occurrence of Atlantic basin mtDNA across populations in the Austrian Mur  and the Austrian Drau  drainages supporting the influence of recent admixture; in contrast, no such correlation was found across populations in the Bavarian or the Austrian Danube.The mean allelic richness across all loci at the population level ranged from 2.5  to 7.9  showed no deviation from HWE, not considering table-wide corrections for multiple testing. The remaining samples that showed significantly negative FIS-values stem either from hatcheries or small headwater streams. Samples that showed significantly positive FIS-values are known to be either moderately or heavily managed. After correcting for multiple testing only a single heavily managed population  deviated significantly from HWE, with a positive FIS-value, presumably reflecting the presence of both wild and hatchery-origin fish.Most populations  differentiation was considerably lower (FST = 0.031) while within drainage differentiation varied widely with the lowest values revealed among populations within the Bavarian Rhine (FST = 0.044) and Elbe (FST = 0.068), and the highest values found among populations within the Mur (FST =0.1465) and Drau (FST =0.188) where pure Danubian populations were found. A maximum FST value of 0.228 was observed among pure Danubian populations, presumably reflecting long periods of isolation relative to other among population comparisons within the global data set.The global F-statistics (Φ), the AMOVA drainage model  revealed 2.6% of the genetic variance distributed among drainages (ΦCT), 10% among populations within drainages (ΦSC), and 87.4% within populations (ΦST), all of which were highly significant (P < 0.0001). The portion of among drainage variance (ΦCT) rose to 4.8% when using R-statistics reflecting the influence of mutation on the among drainage variance. A higher (ΦCT) value (13.8%) was seen based on a reduced model for differentiation between native Danube and remaining Danubian populations reflecting the relatively high divergence of pure Danubian populations within the global data set.Using analog The allele size permutation test further supported the influence of mutation on phylogeographic structure (and thus longer periods of isolation) for global comparisons  as well as those involving among population differentiation of the native Danube populations Figure . In contThe principal component analysis of populations based on microsatellites revealed one axis PC-1, 28.2%) generally reflecting population differentiation corresponding to the two mtDNA (Atlantic and Danubian) lineages Figure . Populat8.2% geneTwo of the ten hatcheries (B &C) have an intermediate position. The first is known to be supplemented with locally caught fish, while the second is of Czech origin and presumed to be founded with fish from the Elbe drainage. A few Austrian Danube populations, all north of the Danube , are located intermediate along the X-axis, suggesting some admixture with pure Danube-lineage fish. A large number of Austrian Danube populations are found around the center of both axes potentially reflecting admixture between one or more lineages.Structure analysis revealed three main clusters primarily corresponding to: (1) Bavarian populations irrespective of drainage; 2) the so-called pure Danubian populations from the Mur and Drau; and 3) remaining populations primarily from the Danube catchment (data not shown). However, only the pure Danubian populations showed a high mean proportion of self-assignment  , the Austrian Danube  and pure Danubian populations  as well as the Drau drainage alone , suggesting that natural as opposed to anthropogenic mechanisms are still operative, if not dominant, in determining among population differentiation. The population tree highly supported both the distinction of Bavaria relative to Danube populations (including hatcheries), and the two members of a south alpine group in the Danube drainages (Mur and Drau). In addition, it provided moderate support for a group containing the Rhine and Elbe catchments , as well as the Rhine and Elbe basins combined (P = 0.04) using the within-locus k test. This test is noted for being more sensitive to recent as opposed to ancient expansion events compared to the inter-locus g test, which did not reveal any statistically significant signal.Statistically significant but weak isolation-by-distance signals were seen for Bavaria : 1) Hatcheries, 2) pure Danubian, 3) Bavarian, 4) Northeast Austrian granitic group . There were three presumably admixed population groups of interest: 1) the Austrian Danube, 2) the Mur, and 3) the Drau. For each of these three groups, we applied Bayesian clustering tests to each of the simulated hybrid crosses, resulting in 18 tests. Across all 18 tests, the posterior probably of individual assignment to an F1 hybrid was negligible (<1%) Figures  &7. HoweSalvelinus and Coregonus[Multiple marker systems  strongly support the natural occurrence of the Atlantic lineage of brown trout throughout large areas of the upper Danube catchment, whereas there is no evidence of the Danube lineage in the sampled populations of the Bavarian Rhine and Elbe catchments and very little trace (< 7% mtDNA) of the Danube-lineage in the sampled portion of the Bavarian Danube. The cause of this large-scale pattern is natural, reflecting the admixed faunal character of the upper Danube established over both geological and glacial time scales . These rCoregonus have arrCoregonus.While a relatively clear gradient of increasing Danube-specific alleles is found with increasing distance downstream (west-to-east) in the Danube catchment, the source of admixture displays a geographic as well as glacial pattern. Hatchery Atlantic strains appear to be the source of admixture in glaciated regions, especially south and southeast of the Alps, whereas natural sources of Atlantic lineage colonization from the upper Bavarian Danube appear to be the primary source of admixture north and northeast of the Alps, especially in unglaciated regions. Nonetheless, the influence of stocking in the region can be evaluated at a population level, as hatchery and wild Atlantic genotypes can be distinguished, but the overall presence and dominance of Atlantic genotypes is based on natural colonization.Regardless of the orientation of the Alps, pure Danube lineage populations are exceedingly rare and appear limited to isolated high elevation populations in previously glaciated areas. This inference is further supported by an earlier study reporting 72% Danube lineage mtDNA and nine populations (three reported herein) fixed for Danube-lineage mtDNA in the upper Inn, Lech, Salzach and Drau drainages in Austria . CuriousCottus gobio) in some river reaches found between 1 and 2,000 MASL today. We assume that this scenario was similar for many other glaciated river valleys of the Austrian Alps. Thus, pure Danubian lineage brown trout are primarily, if not exclusively found in headwater tributaries that were accessible in the early Holocene, but are now physically isolated from downstream colonization.Brown trout undoubtedly occupied large areas of Austria even during the height of the Würm glaciation, as glaciers did not reach the Danube from the south. No real glaciation occurred either north of the Danube or across large areas east and southeast of the Alps. In the mountainous region of Salzburg, for example, glaciers reached a maximum extension of about 5–600 MASL approximately 24–22,000 years ago . Based oSalmo trutta, but the Danubian linage brown trout stocks in the upper Danube as Salmo labrax admitting a hybrid zone in the upper Danube [For regions south and southeast of the Alps, Atlantic lineage trout apparently exist exclusively through human-mediated mechanisms. That the admixture in these regions is more recent than to the north is strongly supported by the elevated levels of allelic diversity in the presence of both mtDNA strains in the Mur and Drau compared to the lack of such a correlation in the north. However, elsewhere the existence of pure Danubian lineage brown trout in isolated headwater systems means that they colonized these systems in the early stages of the current interglacial in the absence of the Atlantic lineage. This is difficult to explain as the Atlantic lineage not only dominates brown trout stocks in the upper Danube in Bavaria, but also reveals no signal of recent  expansion and thus must have been available for post-glacial colonization of the Alps. There is also no indication of a breeding barrier between Danubian and Atlantic lineages. Thus, the post-glacial expansion into alpine rivers of only one of these two co-existing lineages strongly implies some level of pre-glacial physical separation within the upper Danube. Interestingly, some authors have considered the Atlantic lineage brown trout stocks in the region as r Danube . Regardlr Danube . Keller r Danube  investigRegardless of such experimental avenues, it is apparent that a phylogeographic paradigm for European brown trout is failing to provide both researchers and managers with the proper framework for providing biological insights. From a purely management standpoint, the identification of a “Danubian” or an “Atlantic” genetic lineage is useless if not misleading in many  areas of the Danube basin, because the so-called Atlantic lineage is the dominant native trout lineage in much if not all of the Bavarian Danube and overlaps extensively in many drainages of Austria as well. Moreover, a homogeneous view of the Danubian lineage for management purposes might very well be counter-productive if strong selective mechanisms are operative in higher elevation populations. Indeed, elevation as a proxy for specific environmental conditions may turn out to be an important functional characteristic at the population or meta-population level for conservation purposes. Discarding or lumping admixed populations might also be counter-productive if some regions have arrived at this admixture through human-mediated events, while others have been admixed for thousands of years, representing unique and well-adapted gene pools. Our results and baseline data allow us to distinguish not only between native and anthropogenic introgression within the Atlantic lineage, but also the relict status of peri-alpine Danubian populations providing a valuable resource for future conservation planning.The initial naming and description of five major mtDNA lineages in brown trout  was a brThe Atlantic lineage of brown trout is native to large areas of the upper Danube in Bavaria where it predominates, but also in numerous drainages of the Austrian Danube. The lineage has been a very successful post-glacial invader of river courses of the Austrian Danube, but to date there is no evidence of natural occurrence south and southeast of the Alps in the provinces of Styria and Carinthia. Pure Danubian lineage populations are found primarily in previously glaciated regions at higher elevations, in a peri-alpine distribution implying that the lineage colonized headwater river courses post-glacially ahead of the expansion of the Atlantic lineage. The distribution pattern of these two lineages is difficult if not impossible to describe without invoking strong biological mechanisms, meaning that a purely phylogeographic paradigm for these lineages fails to explain their distribution in the upper Danube basin. More recently, anthropogenic activities have aided the spread of the Atlantic lineage and there is no clear evidence of niche segregation or a breeding barrier where the two lineages are found in sympatry today.A total of 2568 brown trout were sampled from 97 populations (including 10 hatcheries) across Austrian and Bavarian reaches of the upper Danube basin, as well as Bavarian reaches of the upper Elbe and Rhine catchments  and 20–50 ng genomic DNA. The reaction consisted of 3 min denaturation at 94°C, 32 cycles of 45 s at 94°C, 15 s at 61°C, 30 s at 72°C, and a final extension step of 7 min at 72°C. The reactions were loaded on a 2% agarose gel.As both the Atlantic and Danubian mtDNA lineages of browns trout exist in the region ,14,25, w2, 0.8 U Taq polymerase (PeqLab) and 20–50 ng genomic DNA. The reaction consisted of 3 min denaturation at 94°C, 32 cycles of 45 s at 94°C, 10 s at 70°C, 30 s at 72°C, and a final extension step of 7 min at 72°C. The reactions were loaded on a 3.8% NuSieve GTG agarose gel (Cambrex Bio Science). Amplified fragments of 340 bp and 100 bp characterize the *90 and *100 alleles, respectively, while an additional 440 bp fragment spanning regions of exons 3 and 4, as described in [We developed an allele-specific duplex assay to replace the PCR-RFLP assay from  in orderribed in  is also HO) and expected (HE) heterozygosity and tests for deviations from Hardy-Weinberg expectations (HWE) were performed with FSTAT 2.9.3.2 [FST- and RST-statistics. The contribution of microsatellite allele sizes (i.e. a measure reflecting mutation) to the distribution of this variation was examined using the allele size permutation test [RST values from 10 000 permutations (pRST) was compared to the observed RST, which is analogous to FST when mutations are not contributing to genetic differentiation, and significantly greater than FST when they do. Such an evaluation should allow more temporal insight into the comparison of pairwise divergence estimates among groups of populations and whole basins. To gain perspective on the overall genetic relationships among the large number of populations screened we also carried out a Principal Component Analysis (PCA) on gene frequency data using the software PCAGEN 1.2 [The number of alleles per locus, allelic richness, observed ( 2.9.3.2 . The dis 2.9.3.2  using Ar 2.9.3.2  whereby ion test  implemenion test . The disAGEN 1.2 . PopulatAGEN 1.2 . PopulatAGEN 1.2 . Node cohttp://taylor0.biology.ucla.edu/struct_harvest). Structure analysis was repeated separately for a number of population groups defined by major drainages or sub-drainages .An a priori evaluation of genetic structure across the global data set was carried out with the program Structure v2.1  assumingFST) distances were examined using the Mantel test implemented in the GeneAlEx 6 software [Correlations between pairwise geographic (GGD) and genetic  against factors 3 through 6 (Y Axis), based on a PCA of microsatellite allele frequencies in all 97 newly typed populations. The additional factors further support several outlier populations as well as the uniqueness of several Pure Danubian populations (e.g. ANR and BIS) and the differentiation between these and Bavarian populations. Several of these populations defining the Y – axis are labeled with the population code for reference. There is however no general pattern or inference that can be drawn from these additional vectors of variation.Click here for fileQ-Values of Pure Danubian Populations. Percentage Self Assignment  of all pure Danubian populations found in this study. One known stock transport from Anrasersee to the Anlaufbach/Winbach drainage was made and is clearly evidenced here. Additionally, fish from these streams were released into Fuscher Ache by local authorities.Click here for fileComplete set of microsatellite data. Individual allelic data of all microsatellite loci across all populations analyzed in this study.Click here for file


Evolutionary molecular studies of island radiations may lead to insights in the role of vicariance, founder events, population size and drift in the processes of population differentiation. We evaluate the degree of population genetic differentiation and fixation of the Canary Islands blue tit subspecies complex using microsatellite markers and aim to get insights in the population history using coalescence based methods. The Canary Island populations were strongly genetically differentiated and had reduced diversity with pronounced fixation including many private alleles. In population structure models, the relationship between the central island populations  and El Hierro was difficult to disentangle whereas the two European populations showed consistent clustering, the two eastern islands (Fuerteventura and Lanzarote) and Morocco weak clustering, and La Palma a consistent unique lineage. Coalescence based models suggested that the European mainland forms an outgroup to the Afrocanarian population, a split between the western island group  and the central island group, and recent splits between the three central islands, and between the two eastern islands and Morocco, respectively. It is clear that strong genetic drift and low level of concurrent gene flow among populations have shaped complex allelic patterns of fixation and skewed frequencies over the archipelago. However, understanding the population history remains challenging; in particular, the pattern of extreme divergence with low genetic diversity and yet unique genetic material in the Canary Island system requires an explanation. A potential scenario is population contractions of a historically large and genetically variable Afrocanarian population, with vicariance and drift following in the wake. The suggestion from sequence-based analyses of a Pleistocene extinction of a substantial part of North Africa and a Pleistocene/Holocene eastward re-colonisation of western North Africa from the Canaries remains possible. Population divergence and speciation have fascinated evolutionary biologists ever since Darwin Cyanistes caeruleus) is found all over Europe, western Asia and northern Africa, including the Canary Islands caeruleus group) and the Afrocanarian blue tit complex (the teneriffae group) teneriffae group have dark blue or almost black cap, blue back and some populations lack the white wing pattern that is seen in the caeruleus group caeruleus and teneriffae full species status have been put forward The blue tit (C. c. ultramarinus) and the southern Iberian peninsula . Based on morphological data, Grant Studies of the blue tit radiation on the Canary Islands could potentially lead to new insights in the role of colonization, vicariance, populations size and drift in population divergence cf. . HoweverIn the present study, we evaluate the degree of population genetic variation, fixation, differentiation and structure of the Canary Islands and North African blue tit subspecies complex using microsatellite markers and aim to get insights in the population history using coalescence based methods. In blue tits, an extensive number of nuclear microsatellites have been developed et al.et al.et al.ombriosus on El Hierro, palmensis on La Palma, teneriffae on La Gomera and Tenerife, hedwigii on Gran Canaria, and ultramarinus on Fuerteventura and Lanzarote. The subspecies ultramarinus is also found in North Africa, whereas ogliastrae occurs in Spain and caeruleus in Sweden. In Kvist et al.degener, but the newer data indicate that this may not be the case et al.This study included samples from the seven Canary Islands populations, as well as from North Africa (Morocco and Ceuta), and the mainland of Spain and Sweden see Figure 1The birds were captured with mist-nets, measured and weighted, and a blood sample (≈30 µl) was taken by puncturing the brachial vein or with a syringe from the jugular vein. The blood samples were stored in a SET buffer containing 0.15 M NaCl, 0.05 M Tris and 0.001 M EDTA with a pH of 8.0, or in pure ethanol. The field work has been described elsewhere Table S1) Table S1. All birds were molecularly sexed by amplifying a Z- and W-linked locus, TGZ-002 , and this information was used for interpreting the genotypes of the Z-linked microsatellites.We selected a set of 21 microsatellite markers of which some were linked (located on the same chromosome) and some unlinked (situated on unique chromosomes) . Primer sequences and annealing temperatures for the microsatellites are given in ISstat ver. 2.9.3.2 ST between all pairs of populations and tested these statistically .To evaluate the genetic variability in each populations, we calculated number of alleles, allele richness, observed and expected heterozygosity ST, Jost’s Dest was used as a measure of genetic differentiation between populations est is a relative measure of differentiation, which ranges from zero (no differentiation) to one (complete differentiation), and simulations have shown that it is an unbiased estimator of differentiation, and outperforms FST, over a range of sample sizes and for markers with different numbers of alleles (including highly variable microsatellite loci) est across loci.In addition to Ftructuretructure algorithms search for clusters that maximize the likelihood that the observed individual genotypes belong to them. When there is strong population structure, the clusters that have the highest likelihood will coincide with a structure that minimizes deviations from Hardy–Weinberg equilibrium (single-locus measure) and linkage equilibrium (multi-locus measure) within the clusters. The most common and perhaps most biological meaningful way of running the Structure models is to use ‘admixture models’, which allow (but do not force) individuals to have a genetic origin from more than one genetic cluster tructuretructure ver. 2.3.3 Table S1) using a burn-in of 10,000 and a sampling period of 20,000 replicates. For each data set and model, we set the number of clusters (K) from 1 to 10, and used 20 iterations.We evaluated population structure with the Bayesian clustering processes and MCMC simulations implemented in the program SK was evaluated with the ΔK-method Ks, and the variation in probability within a K, are used instead of the K-specific probability per se to evaluate which K has the strongest support from the data. ΔK was calculated with Structure Harvester (http://taylor0.biology.ucla.edu/struct_harvest/). The posterior probability of the admixture proportions of each individual from Structure was visualised using Distruct  and ClumppThe most likely et al.et al.K was set to 7 (i.e. the number of subspecies). This procedure was used in order to evaluate whether the clustering process may be facilitated by such priors, and thus be able to support any of the suggested subspecies classifications.Finally, we analyzed our data using the mtDNA subspecies classification as a prior. We performed these analyses following the subspecies structure suggested by Kvist −4–10−31 and t2 in the past, 100–100,000 generations, depending on the population. We simulated 3,000,000 data sets, which were compared to the observed data to choose the scenario that best explains the data by estimating posterior probabilities for each scenario. The posterior probabilities were estimated using both, the logistic regression estimate and the direct estimate provided by the program. The logistic regression method was set to use from 30,000 to 60,000 first data sets  as dependent variables and differences between observed and simulated data set summary statistics as the independent variables to perform a polychotomic weighted logistic regression. The intercept is then used as a point estimate. The direct estimate is based on the relative proportion of each scenario found in the 500 closest data sets. The scenario that explained the data the best was used to estimate divergence times and effective population sizes for North Africa and Europe.We used the program DIYABC v. 1.0.4.45 Figure S1), (ii) central group and (iii) eastern group with Morocco . For eastern and central groups, we included also admixture into the scenarios. We simulated 4,000,000 data sets for scenario 1, 5,000,000 for scenario 2 and 6,000,000 for scenarios 3. Priors for effective population sizes were 100–10,000 individuals and for splitting times 100–1,000,000 generations, again depending on the population. The best scenarios from these runs (see below) included simultaneous splits within the eastern, central and western islands and the European population as an outgroup. These were included in the final run, where we built six scenarios differing in relation to when the splits occurred and from where the branch leading to eastern islands originate. All islands were treated as distinct populations and 6,000,000 simulations were run.Based on previous studies, we divided the Canary Island populations in three groups – western , central  and eastern  groups – in order to reduce the number of scenarios to be tested. We built separate scenarios including (i) western group with Europe and combined central group (Table S1). The reason for this is most likely that there are substantial primer site mutations leading to amplification failure in these populations. These two loci were excluded from further analyses, but we note that the pattern observed for Tgu09 supports a relationship between populations on the Canaries and North Africa.Two of the microsatellite loci included in the present study did not amplify in at least one population: Tgu09 did not amplify in samples from the Canary Islands and North Africa, and Pca8 did not amplify in the samples from La Palma . All FST-values were significantly different from zero (p<0.001).There was strong fixation and differentiation between most populations with FTenerife Table 2.tructure analyses supported the presence of strong population differentiation , whereas the two European populations showed highly consistent clustering, and La Palma a consistent unique lineage in the majority of iterations  = −26,148); the other 19 runs had a higher mean posterior probability (Ln(P) = −8,601) than the 20 iterations at K = 6 (Ln(P) = −8,950). However, also for the most likely K there was striking variation in how some of the populations clustered between different runs .The Set al. et al. K was set to 7 (i.e. the number of suggested subspecies) and 20 iterations were performed. These analyses were made because we were interested in evaluating whether detecting a structure corresponding to the subspecies categorisations would be facilitated by using such priors. However, the substructure groupings suggested by Kvist et al.et al.teneriffae on La Gomera and teneriffae on Tenerife did not cluster together more often than in runs without priors, teneriffae (hedwigii) on Gran Canaria did not cluster with teneriffae on Tenerife, and ultramarinus/degener in North Africa, Lanzarote and Fuerteventura did not cluster in these runs .We also performed admixture models using the subspecies classifications suggested by Kvist caeruleus population is an outgroup for the Canary Island and African populations. Both the logistic approach and the direct approach supported the scenario 3 in The first scenario  that we tested in DIYABC indicated that the European Figure S1; scenario 5 in Figure S2), with no admixture after the divergence (posterior probabilities 0.963–1.000). The direct approach, on the other hand, did not give strong support for any of the scenarios . Divergence times for a split between Fuerteventura, Lanzarote and Morocco were estimated to be only 120 generations ago , between La Gomera, Tenerife and Gran Canaria 100 generations ago (95% HPD 100–270 generations) and between La Palma, El Hierro and Central Islands 1,710 generations ago .In the runs of western, central and eastern island groups, respectively, the logistic regression method supported simultaneous splits of the island populations from their common ancestors within these groups  cyrenaicae in the teneriffae group) in the eastern part of the species’ Afrocanarian range, clustered the Libyan population as a basal lineage of C. teneriffae together with La Palma The pronounced divergence with low genetic diversity and yet unique genetic material in the Canary Island system requires an explanation. The population at La Palma is particularly intriguing since it shows highly divergent patterns on our sets of markers as well as on mtDNA and nDNA sequence data teneriffae complex is the presence of a historically much larger Afrocanarian population in which genetic variation was generated and maintained , Pop 2 = La Palma, Pop 3 = El Hierro, Pop 4 = Central Islands .(TIFF)Click here for additional data file.Figure S2Graphical illustration of six historical events tested with DIYABC. Test of the eastern Islands and North Africa: Pop 1 = Fuerteventura, Pop 2 = Lanzarote, and Pop 3 = North Africa (Morocco). Test of the Central Islands: Pop 1 = Tenerife, Pop 2 = Gran Canaria, and Pop 3 = La Gomera.(TIFF)Click here for additional data file.Figure S3Proportion of membership of individual blue tits of different populations to K = 7 clusters corresponding to the subspecies categorisation of (a) Kvist et al. (2005) and (b) Dietzen et al. (2008). All 20 iterations for K = 7 are shown (sorted according to declining posterior probability from top to bottom). Results are from admixture models using the full set of 19 loci. Populations are, from left to right: Sweden (Sw), Spain (Sp), El Hierro (Hi), La Palma (Pa), La Gomera (Go), Tenerife (Te), Gran Canaria (GC), Fuerteventura (Fu), Lanzarote (La) and Morocco (Mo).(EPS)Click here for additional data file.Table S1Genomic location of 21 microsatellite loci on the blue tit linkage map and the zebra finch genome assembly. Total number of alleles, and average observed heterozygosity (HO), expected heterozygosity (HE) and FIS, in the populations are given, followed by primer sequences and annealing temperatures .(PDF)Click here for additional data file.


Anopheles gambiae is the main vector of human malaria in Sub-Saharan Africa. Given the extraordinary burden this disease imposes, the mosquito became a choice target for genetic control approaches with the purpose of reducing malaria transmission. In this study, we investigated the abundance and distribution of Herves TE in An. gambiae s.s. from Cameroon and four islands in the Gulf of Guinea, in order to determine their genetic structure. We have detected a population subdivision between Equatorial Guinea islands and the islands of São Tomé, Príncipe and mainland. This partitioning associates more with political rather than geographic boundaries, possibly reflecting different mainland source populations colonizing the islands.Transposable elements (TEs) are mobile portions of DNA that are able to replicate and spread in the genome of many organisms. TEs can be used as a means to insert transgenes in insects, being stably inherited throughout generations.  Anopheles mosquitoes by delivering and spreading transmission-blocking transgenes (e.g. refractoriness to Plasmodium infection) Over the past recent years, transgenic technologies have been proposed for malaria vector control Anopheles gambiae sensu stricto several TEs have been catalogued Herves element is a transpositionally active Class II TE isolated from An. gambiae s.s. and found in the sibling species Anopheles arabiensis and Anopheles merusHerves was inferred to be transpositionally active in natural populations of An. gambiae based on the high frequency of intact, transposase-encoding Herves elements observed and highly polymorphic insertion sites Transposons or TEs are mobile genetic sequences that can replicate and change their relative position within the genome An. gambiaeThe dynamics of TEs within populations is determined by the transpositional activity of the element, the strength of self- and host-regulatory mechanisms and the genetic structure of host populations An. gambiae s.s.An. gambiae s.s.Islands have been considered as candidate sites for experimental releases of transgenic mosquitoes for vector control An. gambiae s.s. on Bioko island were found to be genetically differentiated from mainland populations, using microsatellite DNA markers An. gambiae s.s. from the islands of São Tomé and Príncipe are genetically isolated from continental populations An. gambiae s.s. into these islands, coincident with episodes of intense human migration Populations of An. gambiae is critical for developing predictive tools to be used in planning and managing release of transgenic mosquitoes.In the islands of the Gulf of Guinea, malaria remains a major cause of morbidity and child mortality. However, in recent years the situation has progressively changed. In São Tomé and Príncipe, a malaria control program has reduced the number of cases by half over the past decade Herves transposon in An. gambiae s.s. from Cameroon and the four islands in the Gulf of Guinea, in order to determine the genetic structure of this TE among physically isolated populations and relate with the potential applicability of transposons as gene drive systems for island vector populations.In this study, we measured the abundance and site-occupancy frequency distribution of the Mosquito specimens were collected from one continental population of Cameroon, and four island populations of the Gulf of Guinea: Bioko, Príncipe, São Tomé and Annobón . DetailsNo specific permits were required for the described field studies. Mosquito collections were performed in villages either inside houses or outdoors. Informed verbal consent was obtained from household owners to perform the indoor sampling. This type of consent was chosen to avoid potential conflicts due to mistrust in signing official forms by the community. No specific ethics clearance was requested, since all mosquito collections were performed as part of routine mosquito surveillance implemented by the Malaria Control Programs of the regions sampled. The field studies did not involve endangered or protected species.An. gambiae s.s. of the M molecular form were analyzed in this study. Sample sizes for each locality are shown in Extraction of DNA from single mosquitoes was performed by a phenol-chloroform protocol PCR-based transposable element display was performed as described by Subramanian et al. Site occupancy frequency distributions were estimated using the TE display data. To obtain estimates of element frequencies and copy numbers per haploid genome we assumed Hardy–Weinberg equilibrium and followed Wright et al. hs, mean within-population expected heterozygosity Hs and their 95% credibility values, were calculated using a Bayesian approach with 250.000 generations after a burn-in of 50.000 generations implemented in HICKORY 1.1 Expected heterozygosity We calculated pairwise Fst estimates as a measure of genetic differentiation based on For a visual representation of genetic differentiation patterns, we performed a factorial correspondence analysis (FCA) on the multilocus genotype of each individual, using the option that takes into account the population of origin (FCA over populations), as implemented in GENETIX v. 4.05.2 Herves elements in all specimens analyzed by TE display (N = 81). A total of 35 sites were detected. Within each sample, element copy number (dcn) ranged from 4.5 to 7.5 per diploid genome  and Hv130 (6–14 occurrences per sample) (The TEs with the highest site-occupancy frequency were:  sample) . The two sample) .The analysis with Dfdist showed no evidence of sites under selection and all subsequent analyses were thus performed using the 35 detected sites. The estimates of genetic diversity (hs) within each sample ranged from 0.273 in Cameroon to 0.315 in S. Tomé 2004 . These vvs. S. Tomé 1997) to 0.574 (Cameroon and S. Tomé 1997 vs. Annobón). Comparisons between Annobón and the other samples showed the highest and the only significant Fst estimates (P = 0.541).Pairwise Fst-values ranged from −0.080 (Príncipe stimates . The onlP<0.001).Herves genetic structure. These results only partially agree with previous microsatellite-based studies conducted in the same geographic region. Reimer et al. We have detected a genetic partitioning between Equatorial Guinea islands (Annobón and Bioko) from the populations of São Tomé and Príncipe and mainland. This was evidenced by both FCA and AMOVA and also by pairwise Fst estimates. Geographic distance was not correlated with genetic differentiation and thus isolation by distance does not seem to influence Herves TE seem to reflect more political rather than geographic relations among islands. Bioko and Annobón, which belong to the same country, appear more closely related to each other and highly differentiated from mainland or São Tomé and Príncipe, in spite of being the nearest and farthest islands from mainland, respectively. A possible explanation could be a higher passive mosquito dispersal promoted by the movement of Equatorial Guinean nationals between islands. This hypothesis would imply a higher degree of human-mediated dispersal between islands of the same nationality  rather than between islands in closer geographic proximity (e.g. Bioko-Príncipe). However, the differences in mosquito biodiversity between the islands do not support this hypothesis and rather suggest that human-mediated mosquito dispersal between islands is likely to be rare. In São Tomé and Príncipe, the anopheline fauna is represented by only two species: An. gambiae s.s. M-form and Anopheles coustaniAnopheles melas, Anopheles funestus, Anopheles smithii and both M and S forms of An. gambiae s.s. have been recorded in Bioko island The patterns of population structure disclosed by the Herves elements have been introduced into São Tomé and Príncipe and Equatorial Guinea islands, respectively. Indeed, both historical and human mtDNA data suggest distinct origins and timings for the arrival of humans in Bioko  and São Tomé island (during the 15th century) An. gambiae s.s. it is likely that this mosquito also colonized the islands along with the human peopling An. gambiae s.s. in São Tomé and Príncipe An. gambiae M-form from Cameroon as a source population of Herves TEs in São Tomé and Príncipe. These results reinforce the notion of multiple, yet sporadic, colonizations of this vector into these islands. Given these considerations, it is therefore likely that the strong differentiation revealed by Herves TE when comparing Bioko and Annobón with São Tomé, Príncipe and Cameroon is the result of different continental origins of these populations. In this context, the analysis of additional mainland samples would be required in order to further clarify the source populations of An. gambiae s.s. from Annobón and Bioko.Another possibility is that the patterns of population structure reflect different historical mainland source populations from which Herves TE and by previous microsatellite based analyses. However, little is known about the mechanisms of regulation of Herves TE activity, which poses difficulties for comparing these markers.Finally, we cannot exclude the possibility that differences in the mode of evolution and inheritance may also contribute for the apparent discrepancy between patterns of population structure obtained by the Herves transposition during this period. This result is consistent with the large estimates of current effective population size obtained for An. gambiae M-form in São Tomé island An. gambiae complex An. gambiae suggested by this and previous studies in São Tomé and Príncipe is based on the analysis of samples for which collections pre-date the recent implementation of vector control measures that resulted in a significant malaria decrease on the islands Herves TE in samples collected post-intervention as a means to assess the usefulness of TE in determining the impact of vector control in the genetic structure of An. gambiae.The low differentiation observed between the two temporal samples from S. Tomé provides no evidence for significant demographic changes in the mosquito population between 1997 and 2004 or for high rates of Herves-occupied sites were rare and sites occupied in only a few individuals were very common in the sampled populations. This suggests that Herves remains active within these island mosquito populations, as was also observed in previous analyses of other mainland African An. gambiae populations Herves TE suggests Annobón as probably the most adequate of the four islands of the Gulf of Guinea for experimental release of transgenic vectors: it is the most remote island with An. gambiae displaying the highest degree of genetic isolation and the highest amount of Herves insertion site polymorphism. However, the patterns of population structure on the islands of the Guinean Gulf disclosed in this study by Herves TE are more likely to reflect different origins of mosquito colonization rather than levels of contemporary gene flow. These results should therefore be interpreted with caution. Further analyses involving comparisons with more mainland samples and combining different genetic markers are required to clarify the degree of isolation of these islands.In this study, locally fixed Table S1Distribution of Herves sites detected over the six sampled populations.(DOCX)Click here for additional data file.


Metrioptera roeselii) far beyond its natural distribution with levels found in their respective founder populations and coupled the data with timing since establishment. This allowed us to analyze if the introduced populations showed signs of temporal changes in genetic variation and have made it possible to evaluate underlying mechanisms. For this, we used neutral genetic markers, seven microsatellite loci and a 676–bp-long sequence of the mtDNA COI gene. All tested indices  except inbreeding coefficient had significantly higher values in populations within the founding populations inside the continuous area of the species distribution compared with the introduced populations. A logarithmic model showed a significant correlation of both allelic richness and unbiased expected heterozygosity with age of the isolated populations. Considering the species' inferred colonization history and likely introduction pathways, we suggest that multiple introductions are the main mechanism behind the temporal pattern observed. However, we argue that influences of assortative mating, directional selection, and effects of an exceptional high intrapopulation mutation rate may have impacts. The ability to regain genetic diversity at this level may be one of the main reasons why M. roeselii successfully continue to colonize northern Europe.Newly founded isolated populations need to overcome detrimental effects of low genetic diversity. The establishment success of a population may therefore depend on various mechanisms such as assortative mating, purging of deleterious alleles, creation of new mutations and/or repeated inflow of new genotypes to reduce the effects of inbreeding and further loss of genetic variation. We compared the level of genetic variation in introduced populations of an insect species ( With increasing human activities, particularly in agriculture, trade, and transport, the numbers of introductions of non-native species have increased dramatically during the second half of the 20th century  is not possible, intrapopulation mutations are the only mechanism that can increase genetic diversity (Pannell and Charlesworth es Lynch . If new es Lynch . It has es Lynch . As an ees Lynch . Such coMetrioptera roeselii (Orthoptera: Tettigoniidae) from long-term and detailed studies. The species has extended its natural range by several long-distance introduction events far beyond the main distribution range during the last 130 years. This has resulted in new populations of M. roeselii being recorded in Sweden, Denmark, and England  and establishment success, knowledge about founder history, colonization pathways, and propagule pressure of species is needed  compared the level of variation in nuclear and mitochondrial markers as a proxy for overall variation in the introduced populations with the levels in the founder populations and (2) analyzed the temporal changes of genetic variation in the introduced populations. Our expectations were that the isolated populations would have a reduced genetic diversity, that the youngest populations would exhibit signs of previous bottlenecks, and finally, that the level of diversity would be related to the age of colonized populations. We expected that the patterns found can serve as an indicator of what mechanism(s) is involved. These data provide a unique and useful base for continued analyses and testing of the suggested processes.This insect is a small (body length of 14–18 mm) and common omnivorous bush-cricket species that inhabits a wide range of grassland habitats . We genotyped 24 individuals in every isolated and continuous population  for seven nuclear microsatellites  averaged over loci in the software HP-Rare 1.1 , we used the approach of individual inbreeding model (IIM) in the software INEst (Chybicki and Burczyk π) were calculated from the mitochondrial COI sequences for each population using the software DnaSP 5  divided by overall range in allele size (R) produces ratio (M), which is expected to be smaller in recently reduced populations than in populations in mutation-drift equilibrium as it is supposed that k decreases faster than R when the population size is reduced  derived from 10,000 such simulations. Ancestral theta (θ) was set at three different values  to account for a wide range of mutation rates and possible Ne values prior to population bottleneck.To test for bottleneck effects in the isolated populations, if a population was affected by a recent reduction in effective size, we firstly performed Sign and Wilcoxon tests with the null hypothesis being the presence of a mutation-drift equilibrium under the two-phased mutation model (TMM). This was carried out in the software Bottleneck 1.2.02 . The estimate of a population's minimum age was based on the earliest date of observations from published reports and databases  and the genetic diversity of isolated populations was tested by single linear regressions for all six above-mentioned indices . Contrary, when M-ratio values were compared, they were below the Mc for all three levels of ancestral θ . We can therefore not conclude if isolated populations are being in mutation-drift equilibrium or not.All genetic indices, except the inbreeding coefficient, had significantly higher values in sites within the area where the species is abundant and occurs as a continuous population  or close to significant  correlation with the age of the isolated population ; Ne = 12.39 + 5.77 × ln(age)]. The youngest of the isolated populations (<20 years) showed the lowest values of genetic diversity, with diversity increasing rapidly in populations of intermediate ages and leveling off toward the oldest populations (>120 years)  Fig. . The othM. roeselii established far beyond the species main distribution were most likely introduced via long-distance passive transport of individuals and/or eggs, probably with hay or other plant material from cargo ships. In the present study, we show that these events have resulted in significantly reduced genetic diversity in the introduced populations compared with their inferred sources. This is frequently observed when isolated populations lack gene flow  and expected heterozygosity (R2 = 0.61) on the time scale from 4 to 126 years. One could argue that our logarithmic relationship is strongly influenced by the low genetic diversity of LUL at the northern periphery and that this population inhabits an unrepresentatively unfavorable climatic cold area which resulted in very low effective size. However, rapid current expansion at the northern species range within the continuous area , has previously been observed in Orthoptera, although the mechanism behind this is generally unknown (Chapuis et al. −5 bp per generation. As it seems that mutations can occur more frequently in marginal or isolated populations (Agrawal and Wang M. roeselii is beyond the upper limit of expected average for invertebrates (Lynch Although we are missing empirical data on this, we suggest also another possible mechanism causing the rapid increase in genetic variation in the isolated populations of es Lynch .FIS as the old populations (Table M. roeselii so successfully currently colonizes northern Europe. The species appears to be highly adaptable (Cassel-Lundhagen et al. M. roeselii are probably not subjected to a loss of fitness (cf. Falconer and Mackay M. roeselii successfully thrived and colonized uninhabited areas even when founded by very small propagule sizes (Berggren Association between genetic diversity and population dynamics is considered fundamental for species survival (Allendorf and Lundquist ns Table , Fig. 1,Berggren .


Genetic variation within plant species is determined by a number of factors such as reproductive mode, breeding system, life history traits and climatic events. In alpine regions, plants experience heterogenic abiotic conditions that influence the population's genetic structure. The aim of this study was to investigate the genetic structure and phylogeographic history of the subalpine shrub Rhododendron ferrugineum across the Pyrenees and the links between the populations in the Pyrenees, the Alps and Jura Mountains. We used 27 microsatellite markers to genotype 645 samples from 29 Pyrenean populations, three from the Alps and one from the Jura Mountains. These data were used to estimate population genetics statistics such as allelic richness, observed heterozygosity, expected heterozygosity, fixation index, inbreeding coefficient and number of migrants. Genetic diversity was found to be higher in the Alps than in the Pyrenees suggesting colonization waves from the Alps to the Pyrenees. Two separate genetic lineages were found in both the Alps and Pyrenees, with a substructure of five genetic clusters in the Pyrenees where a loss of genetic diversity was noted. The strong differentiation among clusters is maintained by low gene flow across populations. Moreover, some populations showed higher genetic diversity than others and presented rare alleles that may indicate the presence of alpine refugia. Two lineages of R. ferrugineum have colonized the Pyrenees from the Alps. Then, during glaciation events R. ferrugineum survived in the Pyrenees in different refugia such as lowland refugia at the eastern part of the chain and nunataks at high elevations leading to a clustered genetic pattern. The maintenance of genetic diversity within populations is essential for the conservation of species since it can enable adaptation to future environmental changes Genetic structure and genetic divergence within and among plant populations result from a number of contemporary and historical factors acting at various temporal and spatial scales. Alpine habitats are typically characterized by small spatial changes in environmental variables such as topography, temperature, snow cover, soil moisture or bedrock At large scales, species genetic patterns are often shaped by past climate-driven range dynamics The genetic pattern and phylogeography of many species Rhododendron ferrugineum (Ericaceae) in the Pyrenees. This species is insect pollinated and reproduces both sexually (mixed mating system) and vegetatively through layering. It is widely distributed at high elevation, on non-calcareous bedrock. The aim of the present study is to understand to what extent the phylogeographical history of the species has shaped its present genetic patterns. The Asian origin of the genus RhododendronR. ferrugineum before the Pyrenees, with the Pyrenean populations most likely derived from populations from the Alps. After the migration to the Pyrenees, the species had to survive successive glaciation events. Different hypotheses of glacial refugia and postglacial colonization and their consequences on the genetic patterns of R. ferrugineum may be proposed: 1. The species could have survived glaciation episodes in one or both of the two main refugia at the eastern and south central part of the Pyrenees .Rhododendron ferrugineum L. (Ericaceae) is an evergreen shrub with a mean height of 70 cm that dominates subalpine landscapes in the Alps and Pyrenees between 1500 to 2200 m a.s.l, on north-to-west facing slopes, sometimes reaching 90–100% of the vegetation cover. It is also found in the Jura Mountains, in the Northern Apennines and in the Apuan Alps Rhododendron ferrugineum is a clonal, self-compatible 2; vs. Alps, Pyrenees vs Jura Mountains and Alps vs. Jura Mountains was 900 km (ranging from 515 to 1430 km), 695 km (from 590 to 830 km) and 335 km (from 165 to 640 km) respectively. The distances between populations across the Pyrenees ranged from 3 to 370 km with an average of 126 km. In each of the 33 populations , young leaves of twenty individuals were sampled , separated by at least 5 m in order to avoid sampling clonal individuals, were dried in silica gel in the field and then stored at −20°C.We sampled 29 populations across the Pyrenees, the population in the Jura Mountains and three populations in the Alps , Table 1For each individual sampled, 20 mg of leaf tissue was ground with two tungsten beads (diameter 3 mm) in a sterile 2 ml Eppendorf tube at 30 Hz for 90 s using TissueLyser II (Qiagen). Then, the quality and amount of DNA obtained from the DNeasy-Plant Mini Kit  following the manufacturer's instructions was verified using a Nanodrop ND 1000 spectrophotometer .We used nuclear microsatellites as suitable molecular markers to reconstruct regional phylogeographical patterns Amplifications were carried out in a 10 μl mix containing 10 ng of template DNA, 0.7 × Qiagen Multiplex PCR Master Mix, 10 μM of each primer and RNase free water. Cycling conditions were 15 min at 95°C, 30 ×  and 30 min at 60°C. Each set of reactions included a negative (water) and a positive (known genotype) control. Fragment lengths were read on an ABI 3730 sequencer  and scored with Genemapper version 4.0 software with the GeneScan – 600 LIZ  as internal size standard.O) and expected heterozygosity (HE) and the inbreeding coefficient (FIS).All 645 individuals were tested for clonality with GenAlEx 6.5 software ST , as well as the ΔK method To analyze the genetic structure among populations, we used Structure software  or population size (according to the six population size groups in FST) and geographical (km) distances. Mantel test were also used to determine wheter elevational separation was related to genetic differentiation. Calculation of the gene flow on the basis of rare alleles was conducted m) was corrected for the number of samples.Mantel tests A total of 153 alleles at 27 microsatellite loci were detected across 645 individuals at all sites . No clonSignificant departures from HWE across loci were detected in 12 out of 33 (or 36%) sites. The RF87P2 marker was the only locus that showed no departures from HWE. Most of the loci showed significant departures from HWE in two to seven populations, except RF14P3, RF47P1 (11 populations each), RF56P1 (13 populations) and RF96P2 (31 populations). These instances likely reflect occasional departures from random mating rather than the presence of null alleles. Indeed, the probability of null alleles was low for all loci, according to Oosterhout's method O and HE were 4.6, 0.37 and 0.35 respectively in the Pyrenees, and 5.2, 0.5 and 0.45 in the Alps. Expected (HE) and observed heterozygosity (HO) ranged from 0.20 to 0.59 and from 0.29 to 0.56 respectively for all sites. HE was high in the Alps and Jura Mountains (ranging from 0.39 to 0.57), and in some Pyrenean populations  and the lowest in the easternmost  and westernmost  Pyrenean populations. These latter populations were small and isolated (<1 ha) except the large and central population EspI (>100 ha). Significant heterozygosity excesses (FIS coefficients ranging from −0.07 to −0.21) were detected in three eastern  and four central populations of the Pyrenees . In contrast, significant heterozygosity deficiency was found in four populations with particularly high values of FIS coefficients in SomI (0.16) and EspI (0.31). Because the frequencies of null alleles did not appear to be significant, the highest FIS values could be due to inbreeding.The number of alleles ranged from 2 to 15 (mean 6.25) alleles per locus. A total of 16 private alleles  and most of the highest values (>0.33) were found in the Pyrenees between eastern and western populations, reaching 0.45 for LecL/AraH. The population from the Jura Mountains showed a highly variable level of FST (from 0.25 to 0.42).The FT values  were sigTo infer the relationship between populations we used the clustering algorithm implemented in the program Structure. Comparing all 33 populations (K: 1 to 34), ΔK as a function of K reached a peak at K = 2 and then reached a second peak at K = 6 . At K = ST showed that as expected for polymorphic loci such as microsatellites, the within-population variance component was rather high . The among variation component (FST) ranged from 9% to 31% according to the grouping and was statistically significant in all combinations tested (P = 0.001). At a superior hierarchical level, the genetic clusters could explain a significant part of the total genetic variance  whereas it was not significant when grouping populations into altitudinal groups (P = 0.956) or population size (P = 0.222).The analysis of molecular variance AMOVA;  based onST values were all significantly different among clusters  and CL5 or CL6 . The FST values between CL1 and the Pyrenean clusters were quite low (ranging from 0.16 to 0.20).Allelic richness (Ar) was highest in CL1  and lowest in CL6  and ranged from 3.2 to 3.8 in the other clusters . FST valclusters . The higThere was a positive relationship (Mantel test) between genetic distance and geographical distance matrices across populations located in the Pyrenees . The increase of isolation with geographical distance was consistent with the previous results . When including populations from the Alps and Jura, the Mantel test was still positive (R = 0.26) but not significant (P = 0.383), confirming the lack of strong differentiation among the populations from the Alps and Pyrenees. At the Pyrenean scale, the correlation among elevational distances and FST was slightly positive but not significant .Gene flow among all studied populations  was low and reached a mean value of Nm = 0.72 migrants per generation. The values reached 2.88 for all Pyrenean populations but 2.10 in the eastern lineage (CL2) and 5.9 in the western lineage (CL3 to CL6).R. ferrugineum populations in the Pyrenees  but lower than in the Alps and the Apennine populations ; Quercus petraea: HE: 0.76–0.84, R. ferrugineum populations. Accordingly, most of the populations studied showed a FIS close to zero and a great proportion of the genetic variation was found within populations as observed in other R. ferrugineum populations Microsatellite analysis revealed a relatively high level of genetic variability in Rhododendron genus is known to originate from Asia E, HO) suggesting bottlenecks during the migration events R. ferrugineum either from the southwestern Alps The R. ferrugineum was not correlated to altitude or population size; instead there was a sharp longitudinal split between the two genetic lineages. Other studies in alpine ecosystems similarly found no changes in genetic diversity depending on population size or along altitudinal gradients We found that genetic diversity of Papaver alpinum,Trifolium alpinum, E, HO) and exhibited private alleles  despite relatively lower allelic richness likely due to the loss of rare alleles by genetic drift, common in such small populations Fagus sylvatica) or sometimes in the vicinity of Mediterranean Quercus ilex forests. These data suggested that they were more likely to be rear-edge remnant populations The longitudinal genetic pattern seemed to result from the migration of two Alpine lineages and from the establishment of populations in refugia along the Pyrenean chain due to glaciation events. The strong differentiation between the eastern and western Pyrenean lineages and the low level of gene flow observed between the two suggested that very few admixtures occurred since the two lineages had become established. This may result from topographical barriers , seed dispersion by gravity and short pollinator travels hampering gene flow among populations and genetic homogenization. An east-west genetic separation had also been observed in other Pyrenean species  R. ferrugineum heathlands must be locally preserved due to their high ecological and patrimonial value. We think that, henceforth, in aim to preserve genetic diversity of the species, the genetic pattern here revealed should be taken into consideration to choose sites that have to be protected. The eastern lowland isolated populations  grow in very specific habitat and present rare alleles. According to the “rear edge population hypothesis”, they harbor all together the bulk of species' genetic diversity R. ferrugineum, is high in the eastern Pyrenees, especially close to population EynH The longitudinal genetic structuration found in R. ferrugineum highlights a much more complex role of the Pyrenees in species genetic pattern and biogeography. The species showed two genetically isolated lineages, which have probably colonized the Pyrenees from the Alps and Jura Mountains. Our findings suggest that the eastern lineage most likely survived in large lowland refugia and that low-altitude small and isolated rear-edge populations have survived until now after the upward recolonization of highland areas agreeing with our HYP 3. Extensive gene flow may have occurred in lowland refugia as well as among populations growing in high altitude plateaus. The sub-structure of the central and western lineage suggests that the species mostly survived glaciations in isolated nunataks (HYP 2) but that some lowland refugia could also have played a role locally (HYP 1). Our study provides a useful genetic reference framework to select R. ferrugineum heathlands in management projects in the Pyrenees and points out priority populations for protection.In conclusion, the Pyrenees are usually considered to only be a latitudinal barrier to northward or southward species expansions. In agreement with previous findings Table S1Rhododendron ferrugineum.Characteristics of 27 polymorphic microsatellite markers in (DOCX)Click here for additional data file.Table S2Genetic parameters for the 27 microsatellite markers .(DOCX)Click here for additional data file.Table S3ST comparisons between all sampling sites above the diagonal as calculated by Genetix. Non-significant FST are in bold.Pairwise F(DOCX)Click here for additional data file.


This review discusses the progress of ethnic genetics, the genetics of common diseases, and the concepts of personalized medicine. We show the relationship between the structure of genetic diversity in human populations and the varying frequencies of Mendelian and multifactor diseases. We also examine the population basis of pharmacogenetics and evaluate the effectiveness of pharmacotherapy, along with a review of new achievements and prospects in personalized genomics. The concept of personalized medicine, which puts the individual patient, with all of his specific peculiarities, into the center of attention, is not new. The 19th-century Russian physicians M.Y. Mudrov and N.I. Pirogov were well aware of this principle. “A doctor treats the patient, not the disease… Each patient needs special treatment depending on his physical constitution, even if the disease is the same,” wrote Mudrov. The great medical practitioners of the past also acknowledged the prophylactic value of personalized medicine – “Healthy people should be kept in hand… they should be advised on keeping to a healthy lifestyle” . A new aIn Russia, ideas related to personalized medicine based on the advances in molecular genetics are being actively pursued at several genetic schools. One school, headed by RAMS full member V.P. Puzyrev -11, is d The geographical region, ethnic group, and population largely determine the genetic traits of an individual. Setting aside the issues of the substance, the terminological and meaningful differences in the geographic, ethnic and population levels of gene-pool organization, we shall review these terms in the context of personalized medicine in which they are essentially synonymous – they reflect the individual traits of a human that are dependent on his genetic origins. It is agreed that a detailed understanding of genetic diversity in human populations is crucial for determining the genetic basis of most common diseases . Approac Currently, the most useful tools for describing genetic variability in various ethnic groups and populations are genome-wide sets of single nucleotide polymorphisms (SNPs), which are sometimes complemented by copy number variability (CNV) data . A promising method that is sure to be used in years to come is the re-sequencing of complete genomes in representative cohorts from different populations. Studies in ethnogenetics are among the most productive areas of genetic science in Russia, and such studies are being actively pursued in a number of research facilities 27–. The importance of population genetics for personalized medicine also derives from the fact that knowledge of the role of genetic variability in the pathogenesis of common diseases can only be obtained by a detailed analysis of the associations between genetic markers and diseases on large cohorts of patients and healthy people from various populations. Specifically, one of the most productive approaches for association analysis, the so-called Genome-wide Association Study (GWAS), requires the testing of hundreds, if not thousands, of individuals and replication of the discovered associations in other populations.  The cooperative development of ethnic genetics, the genetics of common diseases, and the concept of personalized medicine spawns a number of key questions. Answers to these questions will determine to what use and how quickly genetics will be adopted in predictive medicine:  - How marked are interethnic differences in disease incidence and disease susceptibility gene frequencies?  - What are the evolutional mechanisms behind the differences in disease gene frequencies?  - Do racial, ethnic or geographical origins influence the impact of distinct genetic variants on the course of a disease?  - To what degree does genetic diversity account for the differences in the spread and outcome of diseases between racial and ethnic groups?  - Is there any need for information on the racial/ethnic origin of patients for medical research?  Drawing up a picture of the current understanding of the answers to these questions is the main aim of this article. Fst ) is 0.10-0.15 when estimating the global level of genetic differentiation in human populations. This interval includes values obtained for most systems of genetic markers in classical and molecular population genetics of humans -- blood type, protein polymorphism, RFLP, Alu-repeats, hypervariable segments of mtDNA [Y -chromosome, whose variants differ (20-30%) between populations much more than other marker systems. These two types of markers are so distinctly different because of specific evolutional, population, and social mechanisms we will not discuss in this work  are responsible for 10–15% of the genetic variability in humans (Table 1). In other words, the Wright Fixation Index .et al . [A relatively low level of genetic subdivision in human populations can be observed in the most representative and complete sets of markers – on large and random datasets of autosomal polymorphisms, including genome-wide sets of hundreds of thousands of SNPs. Li et al .  analyzedet al . . Somewhaet al . , while tet al . .FST = 0.32) [FST = 0.38) [The low level of genetic differentiation in human populations as compared to related species (chimpanzees (  = 0.32)  and gori = 0.38) ), despitThe most general distribution pattern of human population diversity is its strict geographical structure, namely the clustering of geographically adjacent populations. On a worldwide scale, populations can be grouped into racial-continental groups for any set of markers. These groups are African Negroids, Caucasoids , Asian Mongoloids, Austronesians, and American Indians , 25, 36 Y -chromosomes, X -chromosomes, and autosomal markers, including complete genomic sets of SNPs.The population of Russia is not exempt from this pattern. Russian populations cluster into several large ethnogeographical groups: Slavs, Northern Caucasus populations, Finno-Ugric peoples of the North European and Volga-Ural regions, the populations of South Siberia and Central Asia, and the populations of Eastern Siberia and North Asia , 33. TheIt is probable that the only major exception to the “geographical pattern” is the Indian subcontinent, in which the genetic diversity is better correlated to the language group, rather than the geographical origin. This is due to the complex ethnic and social structure of the population, caste hierarchy of large ethnic groups, and the presence of numerous small clan/tribe groups , 39. How different are human populations in terms of disease incidence and disease gene frequency?  If we assume that the question of general interpopulation genetic diversity in humans has been answered, then the following questions arise: To what degree is genetic variation correlated with phenotypic variation, especially for clinical phenotypes (diseases)? To what degree are the differences in disease gene frequencies responsible for the interethnic and interpopulation differences in disease incidence? The first question can be answered using data on genetic epidemiology and medical statistics, while the second question needs special approaches.  Ethnic component of monogenic diseases Genetic epidemiology has collected a large set of data on the frequency of Mendelian (monogenic) diseases in various populations. The overall load of hereditary diseases (HD)  in stable populations is relatively low and varies in a narrow range from 1.5 to 3.5 cases per 1,000 . For instance, 10 Russian populations including Slav, Finno-Ugric, and North Caucasus populaces vary in their summed HD load from 1.59 per 1,000 in the cities of the Kirovsk region to 3.5 per 1,000 in rural Mari populations . A similIn the case of HD, differences in disease incidence are directly linked to differences in the allele frequencies in the population. The main factors behind population dynamics, which form the overall picture of interpopulation differences in an HD load, are genetic drift and the founder effect . Drift pHowever, there are several interesting exceptions to this rule. The most well-known is the high number of individuals that are heterozygous for sickle-cell anemia and β-thalassemia in subtropical and tropical regions, such as the Mediterranean. Regions where these erythrocyte diseases occur frequently are virtually identical to those where malaria incidence is high . HeterozAnother common hereditary disease, cystic fibrosis, occurs frequently among Europeans and is much less common in other geographical regions. The wide spread of the main mutation (ΔF508) across all of Europe and its rarity in other parts of the world indicate that this mutation appeared a long time ago, sometime after the migration of modern humans from Africa. Direct estimates of the mutation’s age using various methods suggest the opposite: namely that the mutation appeared relatively recently, about 10 thousand years ago , 59. The Local adaptation of populations to dietary products can also lead to differentiation for certain diseases. Thus, the high incidence of the celiac disease in Northern Europe, especially in Scandinavian countries, and low incidence in Southern Europe are likely connected to the longer history of agriculture, specifically cereal plant cultivation, in the south of Europe and the prevalence of game as the main source of food for the Scandinavian population, which would mean that there were virtually no cereals in their diet. The role of genetic drift and the founder effect in the spread of HD can be illustrated well by the accumulation of certain forms of hereditary pathologies in some populations. Well-known examples of such populations are the Finns, Ashkenazi Jews, French Canadians and the Amish peoples. More than 20 so-called “Finnish” diseases have been documented - these are HD , whose incidence among Finns is much higher than among other populations , 61. The 2 ). As many as 6 diseases can be termed “Yakut,” since the frequency of these diseases is above mean global frequencies by as much as several ten-fold. These diseases include two types of dwarfism which have been documented only recently [In Russian populations, the phenomenon of ethnospecific diseases is most often seen in Yakuts  into account during medico-genetic counseling, DNA-diagnostics, and screening programs. In this context, DNA-diagnostics of HD can be considered as the first real use of personalized genomic medicine.  Genetic diversity and complex diseases. GWAS Interpopulation comparisons of the frequencies of common multi-factor diseases (MFD), also known as complex diseases, are complicated by the absence of homogenous medical statistics for global populations and the considerable clinical and genetic heterogeneity of MFD. However, there is a considerable amount of data on the interpopulation differences in the occurrence of MFDs, such as cardio-vascular diseases , 69, diaThe U.S. population can act as a good model for comparing the incidence of complex diseases: it is a multiracial country with a highly developed healthcare system and thorough medical statistics.  To what extent can such differences be attributed to interethnic genetic differentiation? Important information on this subject can be obtained by analyzing the associations of genetic markers with complex diseases, including genome-wide association searches. et al . [Ioannides et al .  compared These data indicate that the differences in susceptibility gene frequencies may be one of the causes behind the interethnic differences in MFD incidence. However, the biological effect of the associated alleles is unidirectional, irrespective of the racial/ethnic origins, even though the relative share of the marker in the disease or susceptibility can vary. This is most probably due to the genotype (haplotype) surroundings, as well as gene-gene and gene-environment interactions. In recent years, the main source of new data concerning MFD susceptibility genes has been genome-wide association studies (GWAS). GWAS requires high-throughput analysis, which is achieved by using large cohorts  representative of the population, and a large number (hundreds of thousands) of tested polymorphisms, which are representative of the genomic diversity. A catalog of published GWAS is supported by the U.S. National Institute of Genomic Research and includes GWAS which were performed under very strict criteria: no fewer than 100,000 SNP must be analyzed, and the level of significance of a SNP-trait association must be no lower than 0.00001 . As of tFst ) also varied considerably from marker to marker . The mean level of interpopulation difference was 10.5%; i.e., it did not significantly differ from the differentiation level observed for conditionally neutral or genome-wide datasets of markers.A major part of these GWAS have been conducted on European populations, and no reliable estimations of the interethnic differentiation of disease-associated genome regions can be made using GWAS data alone. Adeyemo and Rotimi  managed  These data suggest that the level of interpopulation and interethnic differences for genes associated with MFD does not differ from the general level of differentiation in the gene-pool, and that the risk of developing a disease associated with a genetic marker can vary significantly between population groups, depending on the frequencies of the associated marker and the modulating effects of other genes and environmental factors. APOE gene in Alzheimer’s disease (AD). Reliable association of this marker with AD has been observed for all of the tested race groups; however, the frequency of the allele differs considerably . Homozygozity for the ε4 allele increases the risk of AD 33-fold for Japanese, 15-fold for white Americans, and only 6-fold for African Americans. For heterozygous individuals these values are correspondingly 5.6–3–1.1.The role of gene-gene and gene-environment interactions is usually hard to differentiate; however, their overall effect in the modification of disease risk associated with a certain gene or marker can be very significant and has population specificity. As an example, we can examine data for the role of the ε4 allele of the  Thus, even if the risk of complex disease development is reliably associated with distinct genetic markers in all populations and these markers have unidirectional effects, the magnitude of the effect or the severity of the risk still greatly depends on ethnicity- and population-specific factors of genetic and probably non-genetic nature. So, data on ethnic origins can provide additional information in making personalized medical prognoses. One of the main advantages of personalized medicine is the individualization of drug therapy. Response to a drug, choice of the optimal drug class, dosage, and usage schedules can, at least partially, be determined using genetic factors. Information on individual genetic markers can help a clinician select the appropriate drug strategy. Based on these principles, pharmacogeneticists attempt to identify the genes and gene variants that influence the efficiency of drug therapy and lower the risk of side effects. It has been shown that the most widely used drugs are only effective in 25-60% of patients, and there have been 2 million cases of side effects per year in the U.S. alone, including more than a 100,000 deaths .Pharmocogenomics studies have collected considerable data on the association of genetic markers with the effectiveness of certain drugs. During the last 20 years there have been approximately 2,000 studies on this subject, and hundreds of genes associated with drug therapy efficiency have been identified . Most ofThe FDA (Food and Drug Administration) of the U.S. Ministry of Healthcare has approved the addition of genetic marker information into the annotations of about 30 drugs, including warfarin, abacavir, imatinib, atorvastatin, etc. . The lisMost of the relevant pharmacogenetic data has been collected on Caucasoids - more than 80% of the published research has been conducted on the European and U.S. populations . In someFst  = 0.021) in Russian populations; however, it is tightly correlated with the geographical layout, as are most other marker systems  , a as weProgress in sequencing technology has been colossal in terms of speed and cost reduction. The sequencing of Venter’s genome, which was conducted on first generation sequencers, cost his company about 2 million U.S. dollars. Genomes which are sequenced on second-generation machines  cost about 200–500,000, while the most recent studies involving the re-sequencing of complete genomes cost no more than 1,500 U.S. dollars. So, Francis Colins’  prognosiThe “1,000 genomes” project is aimed at obtaining complete and accurate genome sequences of 2,000 individuals from different populations of the main geographical regions of the world  . During  What new knowledge do personal genomes add to the understanding of human genetic variability and what is their use in personalized medicine? First of all, researchers discover new genetic variants – each genome has about 2.5–4 million SNPs, several thousands of insertions/deletions and several hundreds or thousands of CNVs (Table 2). Most of these variants are being described for the first time. Re-sequencing data from complete genomes confirms the level of individual variability observed for the genomes sequenced in the “Human Genome” project - on average 3 million SNP from a 3 billion base genome yield differences in 1 nucleotide in a thousand.  The genomes of two individuals overlap for about half of the SNPs (Table 5). The degree of relation between the genomes is correlated with the genetic differentiation between the populations to which these genomes belong. The Yoruba genome is the farthest removed from others (38–45% overlapping SNPs), while the most related genomes are those of а Chinese and Korean (60–67% overlapping SNPs).  “Overlaying” the variable positions in complete genomes onto the data obtained in large-scale population projects (such as HapMap) allows us to glimpse at the genetic origins of an individual. For instance, by comparing SNPs in the Venter, Watson, and YH Chinese genomes with four HapMap populations , based on the marker distributions in populations CEU, YRI, CHB, and JPT, researchers can estimate the level of cross-breeding between the main racial and ethnic components observed in these genomes. Thus, the shares of Caucasoid, Negroid, and Mongoloid components in Venter’s genome were estimated at 93.3, 5.1, and 1.6% respectively. The genome of the Nobel-prize winner Watson had a lower share of Caucasoid SNP (73.0%) due to the increased amount of Negroid markers (25.6%).  A personal genome sequence provides complete information on whether the individual carries any alleles associated with clinical phenotypes and is thus extremely valuable for individual health prognoses and for estimating MFD risks. The precision and relevance of the genetic health prognosis are thus unlimited by the technical possibilities of genome study but depend on the amount of knowledge on a phenome and its genetic determinants.  Data on complete genomes are insufficient at the moment in order to systematize the layout of interpopulation differences on a genome-wide scale; however, the existence of interindividual and interracial differences in the number of MFD-associated markers is obvious. Thus, Venter’s genome has about 50 SNPs which are associated with alcoholism. The sequenced Yoruba genome has 30, Watson - 25, and the Mongoloids  have less than 20. Venter is also a record-holder in terms of SNPs associated with tobacco addiction (about 40 SNPs). The Chinese and ancient Greenlander have about 20 of these markers, while Watson’s genome, as well as the Korean and Yoruba genomes, has none. et al . [The most complete approach to using genome-scale information for making individual health prognoses was demonstrated in the recent work of Ashley et al . . In ordeet al . . The DNA Humans display a relatively low level of genetic variability , which is set on a background of high phenotypic variability and strict geographical structure of the genetic variation, which is manifested in the clustering of geographically adjacent populations. The spatial nature of the genetic variability distribution of modern humans can be observed at different levels of population structure and in various groups of markers, including the genes associated with MFD development. Genetic differences between human populations are responsible for only 10-15% of the genetic variability in humans. However, these differences prove significant in the field of personalized medicine in terms of diagnosing monogenic diseases, estimating the susceptibility to common diseases, and making health prognoses, and the efficiency of drug therapy.  Returning to the issues stated in the introduction, let’s sum up our current knowledge. Genetic differentiation in populations for disease genes is as large as the overall level of interpopulation diversity on a genome-wide scale. Observed interethnic differences in the incidence of human diseases can be almost completely (for Mendelian diseases) or to a significant degree (for MFD) explained by the different frequencies of disease-associated genes. The general “geographical pattern” of genetic diversity took shape during the spread of modern humans through migrations, genetic drift, and sudden changes in the effective size of populations. However, natural selection could have played a significant role in the development of the variability of some regions of the genome both on a global scale (such as the immune response or skin pigmentation gene) or at the level of population adaptations to the local environment (such as genes for metabolizing compounds present in the diet). The biological effects of distinct genetic variants (mutations of polymorphisms) in relation to disease are usually stable and do not depend on the racial, ethnic, or geographic context. However, the magnitude of the effects (the relative role of the marker in the disease itself or in the risk of disease development) can exhibit strong variation at the population and individual levels due to the different genetic (haplotypic) environment and modifying gene-gene and gene-environment interactions. Undoubtedly, the “ethnic factor” must be taken into account during medical studies, especially those concerning personalized genomic medicine. The long history of discussions on this issue in medical and genetic literature continues . Howeve Integration of genomics and phenomics in the framework of system biology, novel powerful instruments for describing and analyzing genetic diversity - sequencing individual genomes and genome-wide analysis of SNP on microarrays, the HapMap and “1000 genomes” projects - all of these new happenings give hope as to fast progress in the categorization of genetic diversity associated with the risk of common diseases, the efficiency of drug therapy, and the establishment of a tight link between basic scientific results and proven recommendations for personalized medicine.