Glossina fuscipes fuscipes is the major vector of human African trypanosomiasis, commonly referred to as sleeping sickness, in Uganda. In western and eastern Africa, the disease has distinct clinical manifestations and is caused by two different parasites: Trypanosoma brucei rhodesiense and T. b. gambiense. Uganda is exceptional in that it harbors both parasites, which are separated by a narrow 160-km belt. This separation is puzzling considering there are no restrictions on the movement of people and animals across this region.G. f. fuscipes vector populations can provide an explanation for this disjunct distribution of the Trypanosoma parasites. Therefore, we examined genetic structuring of G. f. fuscipes populations across Uganda using newly developed microsatellite markers, as well as mtDNA. Our data show that G. f. fuscipes populations are highly structured, with two clearly defined clusters that are separated by Lake Kyoga, located in central Uganda. Interestingly, we did not find a correlation between genetic heterogeneity and the type of Trypanosoma parasite transmitted.We investigated whether genetic heterogeneity of G. f. fuscipes populations and the distribution of T. b. gambiense and T. b. rhodesiense indicates that it is unlikely that genetic heterogeneity of G. f. fuscipes populations explains the disjunct distribution of the parasites. These results have important epidemiological implications, suggesting that a fusion of the two disease distributions is unlikely to be prevented by an incompatibility between vector populations and parasite.The lack of a correlation between genetic structuring of  Glossina fuscipes fuscipes. We therefore examined whether this tsetse subspecies is genetically uniform across Uganda. Our results indicate that G. f. fusicipes is not genetically different between the two disease zones, but there are clear genetic differences between northern and southern populations, which are separated by Lake Kyoga. Therefore, it is unlikely that variation in the tsetse fly determines the distribution of the two parasites. This implies that the two diseases may fuse in the near future, which would greatly complicate diagnosis and treatment of sleeping sickness in any potential area of overlap.The two types of sleeping sickness in West and East Africa are markedly distinct, require different treatments, and are caused by different parasites. The only country where both parasites are present is Uganda, where they are separated by a narrow 160 km disease-free belt. Because there is no restriction on the movement of humans and animals between the two disease zones, this separation is puzzling. We asked whether this disjunct distribution can be explained by variation within the tsetse fly that is largely responsible for transmitting both diseases in Uganda,  Trypanosoma brucei rhodesiense in East and Southern Africa and by T. b. gambiense in West and Central Africa, with the two diseases separated geographically more or less along the line of the Great Rift Valley T. b. rhodesiense has a rapid onset leading to a fatal condition within the first 6 months of infection, while infection with T. b. gambiense produces a chronic condition with long symptom-free periods, which may last several years T. b. brucei, T. congolense and T. vivax are responsible for a fatal disease (nagana) in cattle, domestic pigs, and other farm animals. Nagana has restricted agricultural development and nutrient availability and has had a profound economic effect on the continent Tsetse (Diptera: Glossinidae) are the sole vectors of pathogenic trypanosomes in tropical Africa, where they cause Human African trypanosomiasis (HAT), or sleeping sickness. HAT is a zoonosis caused by the flagellated protozoa T. b. gambiense present in the north-west and T. b. rhodesiense found in the south , and Angola. Isolated populations are also present in southwestern Ethiopia and southern Sudan In Uganda, where tsetse flies are estimated to infest approximately 2/3 of the total land area G. pallidipes and G. brevipalpis, the two other Ugandan tsetse species, are at low densities and have ranges that include the country's drier forest patches. In contrast, G. f. fuscipes, a riverine species, has poor waterproofing abilities and low water reserves. Therefore, the majority of G. pallidipes and G. brevipalpis habitat is unsuitable for G. f. fuscipes. Instead, G. f. fuscipes is confined to hydrophytic habitats, such as forested patches along rivers and lacustrine environments G. f. fuscipes habitat extends throughout much of Uganda, including the narrow belt separating the two diseases, whereas this area is unsuitable to G. pallidipes and G. brevipalpis. Importantly, the latter two species feed mostly on wild animals, whereas G. f. fuscipes feeds on the wild and domestic animals that serve as reservoirs for the parasites, as well as humans G. f. fuscipes to be the most important human disease vector species in Uganda G. morsitans, G. pallidipes, G. swynnertoni), forest , and riverine flies  indicate relatively high levels of genetic structuring G. swynnertoni, a savannah species from the highland of Tanzania, as well as G. p. gambiensis, a riverine species from West Africa, show the highest levels of gene flow. While estimates of gene flow among G. swynnertoni populations might be inflated because of a recent genetic expansion G. p. gambiensis populations are likely to be more accurate and reflect linear dispersal along water bodies bordering its patchy forest habitat Population genetic data on a variety of tsetse species, including savannah  and mitochondrial DNA (mtDNA) data to analyze levels and patterns of genetic differentiation between G. f. fuscipes specimens were collected from nine locations in Uganda and one location in southern Sudan between March 2004 and August 2005. Five of the Ugandan populations, i.e. Kamuli, Tororo, Lumino, Busia, and Iganga, are located south of Lake Kyoga; and four locations; i.e. Moyo, Soroti, Lira and Apac are located north of the lake  transformed with recombinant plasmid pUC 19. This library was constructed by the Genetic Identification Services, California, USA, using total genomic DNA extracted from the thoracic muscle of teneral flies from a G. f. fuscipes colony maintained at the International Atomic Energy Agency (IAEA) in Seibersdorf, Austria. The colony was established in Seibersdorf in 1986 and originated from flies collected in the Central African Republic. Primers for these loci were as follows: B03For 5′ GGAGGCTATGCTGATGAATG 3′, B03Rev 5′ TGATGCGAAAAAGAGAAACAG 3′, D05For 5′ TTTCCTTCCAGACGAACTG 3′, D05Rev 5′ CTTGGTATGGTCGTACATGG 3′, B05For 5′ CGCGCTTAGCTAGGAAACTC 3′, B05Rev 5′ AACGATTTGCTGTCCTCGAT 3′, D101For 5′ TGCCTTTACACTGCATACTACC 3′ , D101Rev 5′ AAAAAGAGGAGCAATGATGTG 3′, D12For 5′ GTTGATGGTCACACAACATAAG 3′, D12Rev 5′ TCAATGAGGAAAACTGAACTG 3′. Polymerase Chain Reaction (PCR) amplifications were performed using fluorescently labeled forward primers in 20 µl reactions containing 1 µl template DNA, 2 µl 10X PCR buffer, 1 mM of MgCl2, 0.5 µM dNTP's, 1 µM of each primer, and 1 unit of AmpliTaq Gold (Applied Biosystems). PCR reactions were performed using the following program: 10 min of denaturation at 94 °C, followed by 35 cycles of 30 sec at 94 °C, 30 sec at 55 °C, and 30 sec at 72 °C. All reactions were followed by a final extension step of 20 min at 72 °C. PCR products were diluted 1/10 and run on an ABI 3730 automated sequencer. Genotype scoring was performed using Genemapper version 3.7 (Applied Biosystems).Extraction of genomic DNA was performed following 2, 0.4 µM of each primer, 1 µl of BSA and 1 unit of AmpliTaq Gold (Applied Biosystems). Thermal cycler conditions consisted of an initial 10 min denaturation step at 94 °C, followed by 35 cycles of 1 min at 94 °C, 1 min at 48 °C, and 1 min at 72 °C. Reactions were terminated with a final extension time of 5 min at 72 °C. PCR products were purified with the Qiaquick PCR Purification Kit (Qiagen) and sequenced on an ABI 3730 automated sequencer (Applied Biosystems) following standard manufacturer protocols. Sequencing was performed in both the forward and reverse directions to minimize error.PCR amplification of 349 bp of the mtDNA COII gene and 433 bp of the CytB gene using universal invertebrate primer pairs mtD13/mtD15 and mtD26/mtD28 respectively T. b. gambiense, was considered a single group and the other three northern populations, Apac, Lira and Soroti, which transmit T. b. rhodesiense, were clustered. Fst values between populations were calculated using the ENA method implemented in FreeNA Fst values, these were also calculated using Arlequin . Fst values calculated with FreeNA were used to construct a neighbor-joining tree in PAUP version 4.0b10 k) within our dataset. These analyses were run for 350,000 generations with a burn-in of 100,000. Seven runs were performed for k = 1 to 8. This analysis was also performed including only the northern four populations to determine if populations transmitting different Trypanosoma parasites are differentiated.Average heterozygosity and allelic richness for the microsatellite loci were calculated using FSTAT Fst values for the mtDNA data set following Excoffier et al. Fst values were used to perform a Mantel test for Isolation-by-Distance using Isolation by Distance Web Service version 3.14  Sequence data from COII and CytB were edited with Sequencher 4.2.2. (Gene Codes Corporation) and the data from the two genes were combined for all subsequent analyses. Alignments were performed with Clustal W 2 test p-values based on a coalescent simulation algorithm . A significant p-value may be caused by violation of any of the assumptions in the null hypotheses; neutrality, constant population size, panmixia, or no recombination. Significant negative departures of these tests are caused by an excess of new mutations resulting from evolutionary forces such as selective sweeps or population expansion. Processes that maintain an excess of old mutations result in positive departures To detect departure from selective neutrality and demographic equilibrium, a Fs test G. f. fuscipes populations from the two disease belts were analyzed using five microsatellite loci. One population, Moyo, transmits T. b. gambiense, whereas the other seven populations transmit T. b. rhodesiense. Heterozygosity varied greatly between loci and between populations, with Kamuli fixed for a single allele at locus D12, and a heterozygosity of 0.80 for locus D05 in Apac , and these two loci also showed significant linkage disequilibrium in Tororo and Soroti before Bonferroni correction. This could indicate that these two loci may be linked and are not fully independent markers. However, in two other populations these two loci were completely unlinked (p = 1). Out of 40 tests of Hardy-Weinberg disequilibrium, only locus D05 in the Tororo population showed a significant excess of homozygotes after Bonferroni corrections. That is, we found no evidence for subdivision within populations.Fst values were calculated using the ENA algorithm Fst estimates .We also performed a separate clustering analysis including only the northern populations. This was done to examine whether any further sub-structuring was present within this group, in which populations differ in the Fst values A Mantel test of isolation-by-distance based on Slatkin's linearized G. f. fuscipes individuals belonging to nine populations. Two of these, Moyo and Tambura transmit T. b. gambiense, whereas the other seven populations transmit T. b. rhodesiense. We observed a total of 37 different haplotypes and haplotypic diversity within populations ranged from 0.552 to 0.830, with an overall haplotypic diversity of 0.931   see . No depa020) see  was deteG. f. fuscipes populations. Almost all pair-wise comparisons of Fst values were significant  lying in the T. b. rhodesiense belt, as those are from each other. That is, although populations within the northern and southern clusters are in most cases significantly differentiated, we found no evidence of genetic differentiation between tsetse transmitting T. b. gambiense vs. T. b. rhodesiense, other than would be expected based on their geographic separation.Both the microsatellite and mtDNA data analyses revealed high levels of differentiation between the studied nificant  and 4, iambiense . Our anaFst values using a method that does not take into account the presence of null alleles vs. the ENA method, indicates that no substantial bias was introduced. Additionally, the number of microsatellite loci included in the study was rather small, and heterozygosity was low at locus D12. Therefore, the power of the microsatellite analysis was low, and finer scale patterns of population structuring probably could not be detected in this study. However, the fact that even with this low power we observe highly significant clustering of populations north and south of Lake Kyoga, combined with the observation that the mtDNA data set shows exactly the same pattern, clearly indicates that G. f. fuscipes in Uganda is subdivided into at least two distinct clusters with very limited gene flow between them. The forces that maintain the separation of these lineages seem to have been in place for some time since 10 fixed substitutions are present between northern and southern Ugandan populations.Our analyses indicated that the microsatellite data set included null alleles. This could have affected the data analysis and have lead to an overestimation of genetic differentiation. However, a comparison of G. f. fuscipes populations are comparable to those for other Glossina species and subspecies. Populations of savannah species, such as G. morsitans and G. pallidipes, tend to be substantially structured. This is consistent with the patchy distribution of most tsetse populations th century, as well as more recent HAT control measures th century, after episodes of the rinderpest epidemics ceased, tsetse populations have rebounded, and are expanding from highly scattered relict populations. Population recovery has also been assisted by reduced control efforts due to unstable political and economic conditions.The levels of genetic variation observed for both the mtDNA and the microsatellite markers between G. p. gambiensis in West Africa has low levels of genetic differentiation between populations G. palpalis, for which mark-release-recapture studies indicate that it can disperse up to 21 km in 5 days along gallery forests G. gambiensis populations seems to occur not only within single river systems, but also among populations distributed in the different river basins of Mali In contrast to the strong genetic structuring found in savannah and forest tsetse species, the riverine species G. p. gambiensis flies experience high levels of gene flow, suggesting that an isolation-by-distance (IBD) model may best explain their population structure, for a few savannah species the correlation between genetic differentiation and geographic distance was weak, suggesting that an island model, rather than IBD, may best describe the population structure of these tsetse species While G. f. fuscipes populations, the limited gene flow between populations within the northern and southern group suggests that the patchy distribution of G. f. fuscipes populations likewise plays a role in shaping the population structure of these vectors. In this regard, the riverine G. f. fuscipes is more similar to the savannah species G. morsitans and G. pallidipes, than it is to the other riverine species G. p. gambiensis. This observation is also supported by Krafsur et al G. f. fuscipes are either overestimated, or thwarted by unapparent environmental circumstances in the habitats interspersing the populations included in their study. Consequently, forces of genetic drift in East African G. f. fuscipes are much stronger than gene flow.While Lake Kyoga is the main factor in the genetic structuring of Ugandan It is worth noting that the presence of 10 fixed differences in the mtDNA, with the exception of a single Sudanese haplotype, implies an  complete absence of gene flow between the northern and southern populations. However, for the microsatellite makers, even though substantial differences in allele frequencies were observed between northern and southern populations, and each locus carried at least some alleles that were unique to either the north or south, no fixed differences were found. This discrepancy between the mtDNA and microsatellites could indicate a difference in dispersal between males and females. If dispersal is limited to males, fixed differences could accumulate in the maternally inherited mtDNA, whereas even a low number of migrating males would prevent the accumulation of fixed differences in the nuclear microsatellites. However, the lack of fixed differences in the microsatellite markers may also reflect a bias in the loci studied, as variability was one of the criteria for selecting the loci used for this study. Alternatively, the fast, step-wise mode of evolution of microsatellites with its tendency to create homoplasies could explain the lack of fixed microsatellite differences between the north and south.G. f. fuscipes population sizes in Uganda may be substantial.Within the nine Ugandan populations, both microsatellite and mtDNA data suggest that genetic diversity is relatively high with no evidence of genetic sub-structuring , S2. GivG. p. palpalis in western Africa G. f. fuscipes populations from the border region between Uganda and Kenya also indicates that single locations have genetically homogeneous G. f. fuscipes populations G. f. fuscipes populations based on the mtDNA diversity . These infections also have the propensity to influence population structure. Future studies on the identification of the Wolbachia strains present in the Northern and Southern G. f. fuscipes populations can provide additional information on the genetic differentiation between them.Various tsetse populations have been shown to carry infections of the endosymbiont Knowledge on the population structure of tsetse can provide specific guidance on the design of the most effective and economic vector control efforts, as well as on the sustainability of the control efforts. For example, the trapping systems are most effective if the genetic data shows the presence of highly structured populations in the target areas, indicating a minimal risk of re-invasion. Information on genetic differentiation also provides guidance to ongoing control projects as to where the most vulnerable populations reside, and where special effort needs to be given to incorporate physical barriers to prevent reinvasions. For example, our data indicate that tsetse control on either side of Lake Kyoga, is not likely to be affected by migration across or around the lake.G. f. fuscipes populations that can explain the existence of an historical break in the Trypanosoma distributions. This separation remains puzzling given unrestricted movement of animals and people across this region. Second, and of more immediate concern, given the narrow and progressively reducing corridor that separates the two diseases, our results imply that a fusion of the T. b. rhodesiense and T. b. gambiense ranges, currently less than 120 km apart, is unlikely to be prevented by genetic incompatibilities between vector and parasites. Our data suggest that the genetic structuring found among G. f. fuscipes Ugandan populations is more likely to reflect past geological and/or biogeographic events, and is not correlated with the subspecies of Trypanosoma parasite they transmit.These results also have at least two important epidemiological implications. First, from the vector point of view there is no genome-wide genetic discontinuity at putatively neutral loci across Table S1G. f. fuscipes populations from Uganda. H = Heterozygosity. A.R. = Allelic Richness.Heterozygosity and allelic richness for five microsatellite loci in eight (0.07 MB DOC)Click here for additional data file.Table S2G. f. fuscipes populations. n = mtDNA sample size, H = number of haplotypes, h = haplotypic diversity, π = nucleotide diversity (multiplied by 100).Measures of mtDNA diversity in (0.06 MB DOC)Click here for additional data file.Figure S1G. f. fuscipes based on the microsatellite data set. B: Geographic distance vs pairwise linearized Fst values for populations of G. f. fuscipes based on the mtDNA data set.A: Geographic distance vs pairwise linearized Fst values for populations of (2.41 MB TIF)Click here for additional data file.


Anopheles gambiae s.s. from the islands of Bioko and Annobón, and from continental Equatorial Guinea (EG) and Gabon.Patterns of genetic structure among mosquito vector populations in islands have received particular attention as these are considered potentially suitable sites for experimental trials on transgenic-based malaria control strategies. In this study, levels of genetic differentiation have been estimated between populations of Genotyping of 11 microsatellite loci located in chromosome 3 was performed in three island samples (two in Bioko and one in Annobón) and three mainland samples (two in EG and one in Gabon). Four samples belonged to the M molecular form and two to the S-form. Microsatellite data was used to estimate genetic diversity parameters, perform demographic equilibrium tests and analyse population differentiation.High levels of genetic differentiation were found between the more geographically remote island of Annobón and the continent, contrasting with the shallow differentiation between Bioko island, closest to mainland, and continental localities. In Bioko, differentiation between M and S forms was higher than that observed between island and mainland samples of the same molecular form.A. gambiae s.s. further supports the hypothesis of on-going incipient speciation within this species. The implications of these findings regarding vector control strategies are discussed.The observed patterns of population structure seem to be governed by the presence of both physical (the ocean) and biological (the M-S form discontinuity) barriers to gene flow. The significant degree of genetic isolation between M and S forms detected by microsatellite loci located outside the "genomic islands" of speciation identified in  Malaria is an infectious disease that causes between 300–500 million annual clinical cases and 1.5–3 million deaths per year, mainly in children under five years old in sub-Saharan Africa .Anopheles gambiae complex, that comprises seven sibling species. Within the complex, A. gambiae sensu stricto (s.s.) is the most synanthropic species and shows remarkable genetic heterogeneity .Within the M-form, the low levels of differentiation between the sample of Bioko and those from continental Equatorial Guinea suggest that gene flow between this island and the mainland is likely to occur. Reimer et al  detectedmainland . Conversmainland ,19,24,63A. gambiae s.s. from Equatorial Guinea. Patterns of genetic differentiation are most likely governed by the presence of both physical/geographic (the ocean) and biological (the M-S form discontinuity) barriers to gene flow. These findings have important practical implications for the management of vector control strategies. The biological partitioning between M and S-forms may influence the evolution of genes of interest such as insecticide resistance genes. An unusual frequency of knockdown resistance (kdr) mutations has been detected in the M-form population of Bioko, contrasting with the absence of these alleles in the S-form of this island [kdr mutations within each form would be desirable for a rational management of insecticides for malaria control. The closest proximity and lowest differentiation with mainland coupled with the genetic isolation found between sympatric M and S form populations in Bioko, could make this island inappropriate for initial experimental releases of genetically modified mosquitoes, as only part of the vector population might be affected. On the other hand, in Annobón the presence of a single molecular form coupled with its higher geographic and genetic isolation, might render this island comparatively more suitable for transgenic-based malaria control.In the present study, strong levels of population substructure were detected in s island . This imMM was involved in the design of the survey, microsatellite genotyping, data analysis and manuscript preparation. PS participated in data analysis and drafting the manuscript. JLV carried out microsatellite and data analysis. JC participated in field surveys and helped drafting the manuscript. PB and AL participated in molecular analyses and in the elaboration of the manuscript. FS and AC were involved in sample collections, molecular analyses and revised the manuscript. VER participated in the design of the study and revised the manuscript. JP conceived and co-supervised the study, assisted data analysis and coordinated the draft of the manuscript. AB participated in the conception and design of the study, revised the manuscript and provided overall supervision to the work. All authors read and approved the final manuscript.


AD and CD measures and performed a principal component analysis, as well as a clustering analysis by structure. Results showed that we successfully recovered the genetic structure of analyzed populations formed by historical migrations. Aggregation patterns of these populations accord well with their linguistic affiliations, suggesting that deciphering of genetic relationships does in fact offer clues for study of ethnic differentiation.Population migrations in Southwest and South China have played an important role in the formation of East Asian populations and led to a high degree of cultural diversity among ethnic minorities living in these areas. To explore the genetic relationships of these ethnic minorities, we systematically surveyed the variation of 10 autosomal STR markers of 1,538 individuals from 30 populations of 25 ethnic minorities, of which the majority were chosen from Southwest China, especially Yunnan Province. With genotyped data of the markers, we constructed phylogenies of these populations with both  Other than the majority Han Chinese, there are 55 ethnic minorities living in China, composing 9.44% of the Chinese national population . Most of these minorities inhabit peripheral regions of China, especially border provinces such as Yunnan, Guangxi, and Tibet, where special landforms like the Hengduan Mountains vastly influenced their lives and history Recent researches on East Asian populations have benefited from STR markers In addition, close relationship between language and nationality has long been observed Microsatellite markers have been broadly used for analyzing relationships between human populations In this study, we surveyed the variation of 10 STR markers dispersed on Chromosome 3 for a total of 1,538 individuals in 30 populations, most of which come from southwestern provinces of China. Through analysis of the variations, we assessed the genetic diversity and interrelationships of these populations and tried to evaluate the reciprocal influences of languages and genetic structure among populations mostly living in contiguous regions.30 populations of 25 ethnic minorities from 9 provinces of China were surveyed in this study . Among tAll 1,538 DNA samples used in this study were obtained from 30 ethnic panels of immortalized cell lines created by the Chinese Human Genome Diversity Project (CHGDP) Ten microsatellite markers on Chromosome 3 included in ABI Prism Linkage Mapping Set (v2.5) were selected to be genotyped. They are D3S1297, D3S1304, D3S1263, D3S1266, D3S1285, D3S1278, D3S1292, D3S1279, D3S1614, and D3S1580 See  document2, 1 µL primer, 1520 ng DNA, and 0.25U Taq DNA polymerase  was adopted to perform polymerase chain reactions (PCR). Thermal cycling on the GeneAmp PCR System 9700 (Applied Biosystems) included a 5 min denaturation at 94°C, followed by 10 cycles of 30 s at 94°C, 30 s annealing at 55°C, and 30 s extension at 72°C as well as another 25 modified cycles with a denaturation temperature of 89°C, and a final extension at 72°C for 10 min.Dye-labelled primers from the aforementioned mapping set were 1∶10 diluted to 1pM for subsequent amplification reactions. After optimization, a 5-µL final volume with 0.5 µL PCR buffer , 1.25nmole dNTPs, 12.5nmole MgClElectrophoresis of amplified products was conducted on an ABI 3730 XL DNA Analyzer (Applied Biosystems). For each marker, a size-call panel was trained using the software GeneMarker (SoftGenetics), with data from a random successfully typed 96-well plate. Fragment sizes of each reaction were automatically determined with established panels and then manually checked and adjusted. Output data were then readied for further analysis. Unsuccessful reactions were retried until either success or three failures.EH) were calculated using Arlequin version 3.11 EH to present because it is considered a superior estimator of populational genetic variability Allele frequencies and expected heterozygosities  and the stepwise mutation model (SMM), with or without a bottleneck effect Previous comparison of different distance measures had shown that Nei et al's AD distances averaged over all loci were deployed to reconstruct a neighbor-joining (N-J) tree CD distance matrices by MICROSAT To investigate the genetic relationships of populations in a phylogenetic way, Z-score process is similar to the one advocated by Cavalli-Sforza A principal component analysis (PCA) based on allele frequencies was performed in MATLAB 2007a (MathWorks Inc.) to explore the extent of correlation between genetic relationships and geographical distribution of the populations. Ahead of the analysis, frequency data were normalized for each allele by dividing the offset from mean with standard deviation. This structure program K for the studied populations; clustering results were then visualized by the program CLUMPP K = 2 to 7 were carried out with both a burn-in and a run length of 50 000. The most likely K was then determined by comparing posterior probabilities of data under different K settings.In addition, the AD), geographic and linguistic distance matrices and assessed for significance by 2-way and 3-way Mantel tests vegan. In addition, contributions to correlation by different linguistic groups were assessed by running Mantel tests on the data that excluded relevant populations. To assess the correlation between the distributions of populations on the PCA plot and on the Earth surface, we also ran a Mantel test for the PCA distances against the geographical distance matrix.Lastly, the correlations between genetic relationship and linguistic affiliations as well as geographical distribution were assessed in a quantitative way. Linguistic distances of populations were determined according to the ‘least controversial phylogeny’ proposed by Sagart on the basis of literature As previously mentioned, some PCR reactions might fail 3 times and introduce missing data. Over 90% of loci for all populations have a success rate above 80%, and most of them are greater than 90% . HoweverEH) for the loci of all populations (EH of 0.883 (±0.021). D3S1266 is the least polymorphic, with a mean EH of 0.702 (±0.040). The 10th and 90th percentiles of EH for all markers are 0.677 and 0.886, respectively, with the highest being 0.913 (D3S1263 of Kirgiz) and the lowest being 0.598 (D3S1266 of Dai). Mean heterozygosities of D3S1297, D3S1278, D3S1279, and D3S1614 are much lower than expected when compared to that of CEPH individuals contained in the panel guide of ABI Prism Linkage Mapping Set v2.5. Such differences are not unexpected; though, EH values indicate that selected markers are highly diversified.To examine the diversity of selected markers, we calculated allele frequencies and expected heterozygosities (ulations . D3S1263Exact tests of Hardy-Weinberg Equilibrium (HWE) were applied to all markers to evaluate the extent of inbreeding within each population, given that sampling of ethnic individuals was restricted to typical habitats of corresponding populations and thus unlikely to introduce complex inner-population stratifications. Test results are summarized in P values of each AD matrix test with the full-loci dataset are shown in P values are all less than 0.05, suggesting distance measurements by different markers are overall positively correlated. For the 4 coefficients that are below 0.20, P values of 3 pairs with the marker D3S1266 are around 0.10, and that for D3S1263 with D3S1266 is as high as 0.215. Altogether, these results indicate that the performance of different marker distances is well in consistency. Therefore, it is reasonable to combine all the data for further distance-based analysis despite the existence of slight departures from HWE in our data.As a few marker-population pairs departed from HWE, Mantel tests on marker distance matrices were performed to ensure the legitimacy of joint loci analysis. Correlation coefficients and respective AD matrices reveals the relationships of populations in the full-loci dataset. The populations of Tajik, Uyghur, and Kirgiz from Northwest China, together with those of Dongxiang, Salar, and Mongolian from North China compose a solid branch bearing a high bootstrap value of 77%. Within these populations, Uyghur, Kirgiz, and Salar belong to the Turkic language family, while Dongxiang, Mongolian, and Tu belong to the Mongolian language family. These two language families are all branches of the Altaic languages. Maonan, a population of the Tai-Kadai language family, also appears in this northern cluster instead of clustering with other southern populations. Repeated genotyping and examination of individual genotypes were performed for samples of the Maonan and Mongolian populations and ruled out the possibility of sample mix-up during experiment stages. Although Mongolian also appears in Yunnan as the result of military migrations and war affairs in Yuan Dynasty Genetic relationships of the studied populations were firstly depicted by phylogenetic reconstructions. In , and Lisu, represents the regions of West Yunnan; the other, including Li, Mulam, Zhuang, and HanGuangdong, stands for Southeast China. Bootstrap values for the clusters of West Yunnan and Southeast China are 74% and 86%, respectively. Drung and Mulam are the innermost populations of each cluster. Similar to northern populations, southern ones also have agglomerative linguistic affiliations. The West Yunnan populations belong to the Tibeto-Burman language family of the Sino-Tibetan languages; as for the other cluster, Deang and Blang belong to the Mon-Khmer languages, whereas Li, Mulam, Zhuang, and Dai are members of the Tai-Kadai languages . Only the Maonan population, which also falls within the Tai-Kadai languages, appears at a position outside of its linguistic affiliation.With several populations situated at intermediate places, the remaining ones form two distinct parts. One, including Drung, NuThe three Han Chinese populations included in this study possess distinct positions in constructed phylogeny. HanGanshu and HanShangdong reside at the interface of the north and south clusters, as suggested by their branching sites and bootstrap values. On the contrary, HanGuangdong shows significantly close relationships to Tai-Kadai populations such as Zhuang and Dai., and Tibetan populations, another phylogenetic reconstruction was carried out using the full-population dataset, which has information of only 8 markers. As shown in CD matrices for both the full-loci and the full-population datasets (data not shown).In order to determine the positions for the WaCangyuan, WaXimeng, Jinuo. Positions of Drung and Mulam populations in the plot show evidence of extreme geographic isolations. The Altaic populations take up the upper part, and populations of the Tai-Kadai languages (except Maonan) appear in the lower right quadrant, while populations of the Tibeto-Burman language family occupy the lower left region. All these clusters of populations and linguistic affiliations resemble those in previous phylogenetic analysis. It is noteworthy that the distribution of populations in this plot well approximates their geographical locations in r = 0.418, p = 0.0054) of the Mantel test between PCA distances by the first two components and the geographical distance matrix can be found. Patterns revealed by PCA of the full-population dataset do not alter much; the Wa populations and the Tibetan population show affinity to the clusters of Southeast China and West Yunnan, respectively (data not shown).Besides phylogenetic reconstructions, we applied a principal component analysis (PCA) to allele frequency data of typed markers. structure program was utilized to study relationships of the populations from a different point of view. The results under different K settings for the full-loci dataset are shown in X|K)) from different batches suggested K = 3 as the most appropriate configuration according to the rules set out in the structure manual  than the remaining ones. This suggests that they are ordered at the innermost and the outermost locations in the regional phylogeny, which is not surprising since migrations of these Muslim populations like Tajik and Uyghur into their nowadays areas between Central Asia and East Asia happened much later than the contribution of Central Asians' ancestors to the formation of East Asian populations K = 3, the three previously identified cores, Northwest China (light purple), Southeast China (green), and West Yunnan (orange), constitute individual clusters, leaving populations like Pumi, Bai, HanShandong, HanGansu, and Tu to fall between distinct clusters. When K is equal or greater than 4, no new evident cluster can be introduced and proportions of this newly added part don't vary as much across most populations as those of the other three sources. Complexity of membership coefficients of populations like HanGanshu, HanShandong, Aini, Bai, and Pumi can be best illustrated by their undefined affiliations to any distinct clusters.A clustering analysis by the e manual . When K structure analysis was applied to populations of the three cores separately to examine any additional decomposable stratification. For all three of the cores, structure clustering didn't yield any separation of populations within each of them (data not shown). This result was expected, as previous overall clustering had suggested that with only 10 markers employed in this study, certain level of differentiation among these populations cannot be resolved by the structure program. Increased number of markers might help to produce finer separation for populations of these three cores.As a next step, r = 0.239) for the full-loci dataset is slightly weaker than that between genetics and geography (r = 0.287). Permutation shows that the two correlations are both significant ; though, the significance is greater for the former pair no matter geographical distances were controlled (in 3-way tests) or not (for 2-way tests), which is possibly because the quantification of geographical distances with arch lengths for populations in Yunnan could not take into account the effects of special landforms in that area, thus making the distances among these populations shorter than they would otherwise be. The correlation between linguistic affiliations and geography is both the highest (r = 0.346) and the most significant (p = 0.0002) among all the three pairs. Tests for the full-population dataset gave similar conclusions to the above comparisons (data not shown).As has been seen in previous phylogenetic, factor decomposition, and clustering analyses, the genetic relationships of populations shows a strong correlation with their linguistic affiliations. To explore such a correlation in a quantitative way, we statistically compared genetic, geographic and linguistic distance matrices for our population datasets  level when Tajiks (speakers of Iranian languages) were excluded, which reminds us the special role of this population as revealed in previous PCA analysis (p = 0.017) and its coefficient is even slightly increased (r = 0.165) under 3-way Mantel test. Such a contrast suggests that even though the geographical dispersion may not significantly resemble the genetic relationship when Tajik was excluded, there still be a certain correlation between genetic and linguistic affiliations for these populations.When populations of a specific language were excluded from the full-loci dataset, changes in coefficients and analysis . Howeverp<0.05) correlation for all partial datasets. However, when Mongolian or Turkic populations were excluded, the coefficients between genetics and linguistics of 3-way tests for respective partial datasets reduced to an insignificant level , while it is not the case for other partial datasets that excludes populations of a language like Tai-Kadai and Tibeto-Burman. This change relative to the full-loci dataset is because the exclusion of Mongolian or Turkic populations results in a reduction of averaged genetic distances among the remaining populations, and thus the correlation between genetics and linguistics with geographical distances controlled in 3-way tests is more easily confounded by regional migration events as well as the quantification method of geographical distances for closely distributed populations.2-way Mantel tests yielded significant Click here for additional data file.Figure S2Contributions by PCA components in real and random datasets. The barplot as well as the labelled numbers stands for the contributions by the first 10 components in PCA of our real dataset. Solid line stands for the mean contributions in 10,000 random datasets and dashed lines are corresponding 95% upper bound and 5% lower bound. Contributions by the first two components, though only 24.33% in total, are much higher than that by the first component in random datasets.(0.01 MB EPS)Click here for additional data file.Figure S3structure clusterings. Plotting follows conventions, where the central mark is the median, the edges of the box are the 25th and 75th percentiles, the whiskers extend to the most extreme data points not considered outliers, and outliers are plotted individually.Boxplot of posterior probabilities of the (0.01 MB PDF)Click here for additional data file.Table S1Information of 30 sampled populations. Lat and Long stand for latitude (north) and longitude (east), respectively.(0.07 MB DOC)Click here for additional data file.Table S2EH) for all markers of each population. Values are crossed out for the 5 loci where missing rates within respective population are higher than 40%.Expected heterozygosities ((0.02 MB XLS)Click here for additional data file.Table S3Detailed frequency data of 10 loci for studied populations. Numbers in header line represent fragment sizes called in the GeneMarker environment. Contained in the last column of each table are the allele numbers that were successfully called for each population.(0.09 MB XLS)Click here for additional data file.Table S4P values of exact tests for Hardy-Weinberg equilibrium. Values<0.05 mean significant departure from equilibrium and are labeled as bold face. Values are crossed out for the 5 loci whose missing rates within respective population are higher than 40%.(0.02 MB XLS)Click here for additional data file.Table S5AD distance; linguistic distances were constructed according to the ‘least controversial phylogeny’ proposed by Sagart Matrices of genetic, linguistic and geographical distances used for Mantel tests. Genetic distances used here is the (0.10 MB XLS)Click here for additional data file.


Rare species have seldom been studied in marine habitats, mainly because it is difficult to formally assess the status of rare species, especially in patchy benthic organisms, for which samplings are often assumed to be incomplete and, thus, inappropriate for establishing the real abundance of the species. However, many marine benthic invertebrates can be considered rare, due to the fragmentation and rarity of suitable habitats. Consequently, studies on the genetic connectivity of rare species in fragmented habitats are basic for assessing their risk of extinction, especially in the context of increased habitat fragmentation by human activities. Sponges are suitable models for studying the intra- and inter-population genetic variation of rare invertebrates, as they produce lecitotrophic larvae and are often found in fragmented habitats.Scopalina lophyropoda (Schmidt), using the allelic size variation of seven specific microsatellite loci. The species can be classified as "rare" because of its strict habitat requirements, the low number of individuals per population, and the relatively small size of its distribution range. It also presents a strong patchy distribution, philopatric larval dispersal, and both sexual and asexual reproduction. Classical genetic-variance-based methods (AMOVA) and differentiation statistics revealed that the genetic diversity of S. lophyropoda was structured at the three spatial scales studied: within populations, between populations of a geographic region, and between isolated geographic regions, although some stochastic gene flow might occur among populations within a region. The genetic structure followed an isolation-by-distance pattern according to the Mantel test. However, despite philopatric larval dispersal and fission events in the species, no single population showed inbreeding, and the contribution of clonality to the population makeup was minor (only ca. 4%).We investigated the genetic structure of a Mediterranean sponge, S. lophyropoda populations at all spatial scales examined confirms the philopatric larval dispersal that has been reported. Asexual reproduction does not seem to play a relevant role in the populations. The heterozygote excess and the lack of inbreeding could be interpreted as a hitherto unknown outcrossing strategy of the species. The envisaged causes for this strategy are sperm dispersal, a strong selection against the mating of genetically related individuals to avoid inbreeding depression or high longevity of genets combined with stochastic recruitment events by larvae from other populations. It should be investigated whether this strategy could also explain the genetic diversity of many other patchy marine invertebrates whose populations remain healthy over time, despite their apparent rarity.The structure of the  Many marine invertebrates are sessile as adults, have limited dispersal abilities, and their populations are in general well-structured e.g., -8), desp, desp8])The particular rocky habitats of most marine sessile invertebrates  are often fragmented in space. Habitat fragmentation has been reported to account for population isolation in invertebrates with poor dispersal capabilities through the hampering of genetic exchange among populations . MoreoveRare species are considered to be strongly vulnerable in fragmented habitats , especiaSponges are key, widespread elements in benthic ecosystems e.g., ,19). Thu. Thu19])Scopalina lophyropoda  has only been recorded from a few Western Mediterranean localities [S. lophyropoda can be classed as a "rare species" according to the definition of Chapman [calities -24. Rececalities ,26 need calities ,27. The calities ,28. The  Chapman , owing t Chapman .S. lophyropoda allowed us to predict some aspects of its population genetics. First, the larvae do not move far away from the release point, but remain close to their parents in a vertical posture, suggesting philopatry [Several known reproduction traits of ilopatry ,28,29. Silopatry  indicateilopatry  may reprilopatry .S. lophyropoda) in order to better understand the maintenance and growth of its populations, which have been monitored for the last 20 years. The study was performed at three spatial-scales: within populations, between populations of a geographic region, and between isolated regions. We also assessed the relative extent of sexual and asexual reproduction in the populations.The main objective of this study was to gain knowledge on the genetic connectivity among populations of a marine rare sponge species inhabiting fragmented habitats  for locus Scol_d, three individuals ca. 1%) for Scol_n and one (ca. 0.5%) for both, Scol_p and Scol_c. These unsized alleles were not included in the analyses, but cannot be considered null alleles. All microsatellite loci were polymorphic  ranging from 0.322 (GA) to 0.469 (SA). Single locus exact tests for the Hardy-Weinberg equilibrium indicated significant deviations (P < 0.05) in 9 out of 42 comparisons. In the MU population there was heterozygote deficit, whereas in all other populations the departures were due to heterozygote excesses  to -0.099 in SA, and both were in the Blanes region. Multi-locus FIS values for all populations, but that in MU, were negative, although only values for CG, SA and GA were significantly different from 0 (P < 0.05), revealing outcrossing.All the "a priori" defined populations of se Table , with meST and RST, over all populations, were significantly (P < 0.05) different from 0 (FST = 0.122 and RST = 0.076). Multi-locus pairwise FST indicated significant differences among all the population pairs (Table ST/(1-FST) values against the logarithm of the geographic distances revealed significant isolation by distance according to the Mantel test , but were slightly lower for Port Cros (0.344). Multi-locus pairwise FST indicated significant differences among the geographical regions  revealed the presence of significant genetic structure (P < 0.05).As for the geographical regions Table , Cabo dens Table . The gloOverall, the hierarchical AMOVA revealed significant genetic structuring of the analyzed samples at the three geographical levels , as shown by the highest peak in the ΔK for K = 3 .Bayesian clustering analyses detected the highest likelihood for the model with three genetically homogeneous groups of individuals , under the Stepwise Mutation Model (SMM). The tests performed, assuming the Two Phase model (TPM) and the Infinite Allele model (IAM), rendered non-significant results. With respect to the geographical regions, the Wilcoxon test again detected recent bottlenecks in each of the three regions  using the SMM model  but not using the TPM and IAM models.The number of multi locus genotypes (MLGs) occurring more than once was variable in the populations studied Table . IndividThe probabilities of finding identical MLGs by random mating were significantly small P < 0.05) for the ramets from CG, for the groups of three and four ramets sharing MLGs in BA, and for two groups of two ramets presenting identical MLGs in GA . Most diversity was found within the populations, but differentiation among populations and among geographic regions was also significant. The Bayesian clustering method (STRUCTURE), however, turned out to be more conservative and only detected three genetically independent groups, which correspond to the three geographical regions. However, when the polymorphism shown by the selected markers is limited, as it occurs in sponge microsatellites, or there is a strong isolation by distance pattern, the STRUCTURE algorithm is limited to resolve population clusters [ST values, and the presence of private alleles), we can conclude that the sampled populations are genetically well structured, though some gene flow may take place within regions.Microsatellites have proven their use as powerful markers for population and clonality studies in the sponge clusters , and hasclusters -36. ThusS. lophyropoda larvae [Scopalina species in the distribution area of S. lophyropoda [The positive regression between genetic differentiation and geographic distance between populations of this species revealed distance isolation and short-range effective dispersal. This pattern agrees with the philopatric behavior reported for a larvae ,29, whica larvae , could ca larvae , and it a larvae . The lata larvae  and leadhyropoda  could beS. lophyropoda, the contribution of clonality to the populations was minor. Only 4% (9 out of 222) of the ramets analyzed can be assumed to be the result of asexual reproduction. A plausible explanation is that fissions are balanced with fusions between clone-mates [Gene flow can be maintained by dispersal of sexual and/or asexual propagules. In ne-mates , since cS. lophyropoda sperm in particular but the reported short-range dispersal [S. lophyropoda larvae, fully agrees with the strong genetic structure in the species. The strong genetic structuring  indicates that there is a current absence of connectivity among the regions but STRUCTURE results point to some, although restricted, gene flow among the populations within a region, which may occur through sporadic stochastic dispersal events. A combined sexual-asexual dispersal mechanism consisting in asexual fragments of ripe individuals containing larvae has been speculated [Since asexual dispersal appears to be unimportant in the species and the few clones identified use to be found at smaller distances than 0.5 m , gene flispersal ,28,29,32eculated , which, S. lophyropoda microsatellites, some studies in other taxa  reported that microsatellites fit the mixed TPM or the IAM, but not the SMM [Bottleneck tests under IAM and TPM did not reveal any recent reduction in size of the populations, which is in agreement with the growth detected during the last 20 years in the several populations studied (authors' obs.). Only under the less probable mutation model for the microsatellites (SMM) -42, the  the SMM -42. ThusCrambe crambe; [S. lophyropoda are shared with those reported for C. crambe, whereas other aspects are contrasting. The populations are genetically structured in both species, despite their respective patchy vs. continuous distributions and the differences in larval behavior [S. lophyropoda (4% on average) while it reached 23% in C. crambe [C. crambe, several individuals did not amplify for each locus, which may contribute to a failure in differentiation of some individuals that were not real clones. On the other hand, fusion rates between ramets  are more balanced in the former with fission rates and thus could account for the low extent of clonality in our "snapshot" sampling.Most marine invertebrates with non-feeding and short dispersed larvae present genetically structured populations and inbreeding, whatever the Phylum they belong to ,43-45. A crambe; ). Some pbehavior . Restric. crambe . There aC. crambe populations showed inbreeding [S. lophyropoda has no inbreeding depression and exhibits heterozygote excess for most of the loci studied. In fact, our results contrast with theory and experimental evidences, which suggest that the effective size of small populations, and its response to selection, decreases with time [S. lophyropoda populations, however, support studies that predict that inbreeding should not be that common in marine invertebrates, despite their restricted dispersal, strong population structure, and consanguinity . Our. OurC. cScopalina lophyropoda, as other sessile marine invertebrates, a priori considered rare, lives without apparent constrains in fragmented populations with natural low abundances and restricted dispersal abilities. Mechanisms that are as yet poorly understood may be acting in those populations to maintain the necessary genetic diversity for the species to adapt to changing environments. This study has shown the results of these potential strategies, which would act in S. lophyropoda to avoid inbreeding, despite the species biological features. Efforts should be concentrated on the study of these mechanisms, which are responsible for the persistence of most marine sessile invertebrates with small, scattered populations and which have restricted dispersal, for their implications in the maintenance of marine biodiversity. Results on these mechanisms should be considered in the implementation of conservation directives, as rare species inhabiting fragmented habitats may require particular protection rules.Scopalina lophyropoda populations were sampled by SCUBA diving from several localities in the Northwestern Mediterranean. The species identity was confirmed through amplification of a fragment of mtDNA cytochrome c oxidase gen, given the presence of several cryptic species [ species ,27. Due S. lophyropoda [The samples were cleaned from foreign tissues. The DNA was extracted using the DNeasy Tissue Kit (Qiagen) and screened for the seven microsatellite loci that had been previously isolated from hyropoda , under tIndividuals sharing multi-locus genotypes (MLGs) could have resulted either from sampling individuals resulting from asexual reproduction (ramets), or from sampling two or more individuals resulting from sexual reproduction (genets). The probability of the latter depends on the allele frequencies in the population and the observed heterozygosities. To test this probability, we used the program MLGsim . This pIS, as in [The TRANSFORMER-3 program  was usedS, as in  and depaS, as in . Ewens-WS, as in  and GENES, as in , respectST values  values and the logarithm of the geographical distances between the populations , using a Mantel test. The analysis of molecular variance (AMOVA) is a testing procedure based on permutation analysis for studying molecular variation within species. It was performed using ARLEQUIN software [ad hoc statistic ΔK as in Evanno et al. [Differentiation statistics based on microsatellite allele data are widely used for studying moderately-structured populations . Wright's (as in ) were ess (as in  and Slats (as in  global Re (as in  Michalake (as in . Isolatisoftware . The numsoftware . K was io et al. . The proo et al. . This prAB conceived the study, performed the samplings, carried out the DNA genotyping, performed the statistical analyses, and drafted the manuscript. MJU also conceived the study and performed the samplings, supervised the genetic studies, and contributed to the writing of the manuscript. Both authors read and approved the final manuscript.


Proclossiana eunomia was investigated in two mountainous areas of southern Europe  and in two areas of intermediate elevation .The main components of the spatial genetic structure of the populations are neighbourhood size and isolation by distance. These may be inferred from the allele frequencies across a series of populations within a region. Here, the spatial population structure of A total of eight polymorphic loci were scored by allozyme electrophoresis, revealing a higher polymorphism in the populations of southern Europe than in those of central Europe.Isolation by distance effect was much stronger in the two mountain ranges (Pyrenees and Asturias) than in the two areas of lower elevation (Ardennes and Morvan). By contrast, the neighbourhood size estimates were smaller in the Ardennes and in the Morvan than in the two high mountain areas, indicating more common movements between neighbouring patches in the mountains than in plains.Short and long dispersal events are two phenomena with distinct consequences in the population genetics of natural populations. The differences in level of population differentiation within each the four regions may be explained by change in dispersal in lowland recently fragmented landscapes: on average, butterflies disperse to a shorter distance but the few ones which disperse long distance do so more efficiently. Habitat fragmentation has evolutionary consequences exceeding by far the selection of dispersal related traits: the balance between local specialisation and gene flow would be perturbed, which would modify the extent to which populations are adapted to heterogeneous environments. Spatial models of genetic population structure generally refer either (i) to populations isolated in space, and connected by immigration and emigration , or to  from the resulting data compare the dispersal ability of the species in the respective parts of its range. We infer both neighbourhood size and isolation by distance effect from estimates of FST and geographic distances between populations in two mainly natural (mountain) and two mainly man-shaped (fragmented) landscapes.In this paper we would like (i) to compare neighbourhood size and isolation by distance effect in the butterfly P. eunomia populations varied between the studied regions (Table P. eunomia shows the lowest number of polymorphic loci (three); this is due to the fact that the populations there originated from introduction performed in 1970 and 1974 from individuals coming from the Ardennes where only four polymorphic loci could be found [The genetic polymorphism of be found -20. PopuFST values per region showed that the differentiation between populations within each of the regions are moderate (sensu [distance), showed marked differences between the regions , rangins Figure . In the s Figure , indicats Figure . The IsoFST = a+b/(4x+1), for x being the geographical distances between populations, provided the same ranking of regions , the highest for the Morvan (27.58), with the Ardennes (0.01035) and the Pyrenees (14.09) being intermediate.The approach advocated by Porter & Geiger , the intns Table . The strThe percentage of correctly assigned individuals to their population, varied between the four regions, from 8.3% in the Ardennes to 40.4% in the Asturias Table . In the P. eunomia varied strongly among the four studied regions. The FST values per region all fall above the median value of FST for European butterfly populations . The cof origin ,24, and  Slatkin ), even i Slatkin . The sloP. eunomia populations in the lowlands of central Europe corresponds to (i) a lower dispersal rate leading to a lower neighbourhood size, and (ii) for the individuals which do disperse to a more efficient dispersal power preventing thus isolation by distance in lowland areas of relative high connectivity. The relation between dispersal ability and population genetic structure was firmly established on the basis of intrageneric but interspecific comparison [Parnassius smintheus [Compared to high mountains, the genetic structure of mparison . At the mintheus . Howevermintheus . Indeed,mintheus , which gmintheus . This lomintheus . This bemintheus ,29. The mintheus .Melitatea cinxia butterflies. Genotypes with this allele had elevated metabolic rate, which suggests selection on PGI or a closely related locus for better dispersal performance [The latter point suggests that habitat fragmentation might have selected some phenotypic traits conferring better performances to dispersing individuals. Admittedly, a recent study elegantly showed that the frequency of a PGI allele was higher in more mobile formance . Howeverformance .In lowland areas, long distance dispersal may lead to successful gene flow, as in the Ardennes the frequency of distance between populations is relatively high until 90 km. In contrast, in the Pyrenees and the Asturias, frequencies of pairwise distances drops dramatically at 30 km Figure , leavingm) than for the "Hill" region (nh). The individuals which move away from the neighbourhood area may move very far; however, their probability of leading to long distance dispersal, say of distance d, is smaller in the "Mountain" region than in the "Hill" region. Such a result may analytically be viewed as the sum of two negative exponential kernels, one for small distances, up to the range of the neighbourhood size, and another one for long distance dispersal.The opposite trend of neighbourhood size and isolation by distance effect seems paradoxical. As individuals tend to move more, one would expect that the neighbourhood size will increase and the isolation by distance effect will get weaker. In which conditions would such opposite trends occur? Dispersal kernels do not usually follow a simple inverse exponential equation , the popP. eunomia varied according to the level of habitat fragmentation [Our study shows that dispersal behaviour by individuals may hardly be modelled using a single one-parameter function, however convenient this may be. For free flying insects, the factors affecting dispersal at small distances, such as mate-locating or mate-avoidance behaviour  or feedientation . Our genProclossiana eunomia were sampled using butterfly nets [Between 1990 and 1995, a total of 53 populations of fly nets ,38 in fofly nets ), the Mofly nets ,40. Genofly nets , adaptedfly nets .Dij the geographic distances between population i and population j. A value of 4 for α was found to be realistic for the Ardennes populations [Within the Ardennes and the Morvan, the populations were closer to each other than in the mountain areas of the Pyrenees and the Asturias, where each population was more isolated Figure . If we m945;Ajξim, with Ajulations . For eacF statistics were calculated with the GENEPOP software [FST between populations and geographic distances between the same locations. The strength of the effect was estimated as the slope of the regression of the log-log relationship between these variables [FST were input into a 2-dimensional model, using R's mds procedure [software . Isolatiariables . A compaariables . The fitrocedure . The resNm) may be estimated by the relationship Neighbourhood size could be estimated by two methods. (i) Slatkin  suggeste4(1FST−1).FST = a+b/(4x+1), where x is the geographical distance between populations, and a and b the fitted parameter values [Neighbourhood area may then be estimated by the intercept of the function of the pairwise r values .This approach on dispersal was complemented by tests of assignments. GeneClass2  was usedDij: geographical distance between populations i and j. N: number of individuals in one or a set of populations, m: proportion of migrants. Studied alleles: PGI phosphoglocose isomerase E.C.5.3.1.9, PGM phosphoglucomutase E.C.2.5.7.1, 6PGD 6-phosphoclodonate dehydrogenase E.C.1.1.1.44, G6PDH glucose 6-phosphate dehydrogenase E.C.1.1.1.49, HBDH β-hydroxybutirate dehydrogenase E.C.1.1.1.30, AAT aspartate aminotransferase E.C.2.6.1.1, MPI mannose-phosphate isomerase E.C.5.3.1.8, AK adenilate kinase E.C.2.7.4.3.GN and BB carried out the allozyme electrophoreses. HD, now officially retired from his professorship at the University of Provence, and MB conceived the study. All authors contributed to the field work. GN carried out the data analysis and drafted the manuscript. All authors commented the manuscript and approved the final version.List of sampled localities, with allele frequencies and sample size. For each locality, the coordinates are given in latitude and longitude (Greenwich coordinates) and xy coordinates in m within each region.Click here for file


Amblyrhynchus cristatus) inhabit the coastlines of large and small islands throughout the Galápagos archipelago, providing a rich system to study the spatial and temporal factors influencing the phylogeographic distribution and population structure of a species. Here, we analyze the microevolution of marine iguanas using the complete mitochondrial control region (CR) as well as 13 microsatellite loci representing more than 1200 individuals from 13 islands.Marine iguanas  gene flow due to male-biased dispersal, the results of our sex-biased dispersal tests and the finding of strong genetic differentiation between islands do not support this view. Therefore, our study is a nice example of how recently developed analytical tools such as Bayesian clustering analysis and DNA sequence-based demographic analyses can overcome potential biases introduced by simply relying on FST estimates from markers with different inheritance patterns.While a past genetic study based on pure  The legacy of the Galápagos archipelago may be forever attached to the development of Darwin's theory. Yet, the unique character of these islands have continued to make them an ideal model for evolutionary study ,2. The GAmblyrhynchus cristatus). This species is endemic to the archipelago and is frequently found along the coasts of all the major islands as well as many smaller ones. Marine iguanas exhibit a unique natural history among lizards, feeding almost exclusively on specific algae species in the intertidal or subtidal zones, while breeding and nesting completely on land [Among the organisms that inhabit the Galápagos, one of the most amenable to evolutionary study is the marine iguana  data as well as nuclear-coded loci (three microsatellite and three minisatellite loci), traced back the microevolution of 22 population/subpopulations of marine iguanas from 15 islands in the archipelago [b data, marine iguana populations were grouped into three major lineages: one occupying the older eastern and central islands, another found mostly in the geographically distant northern islands, and a third distributed across the northern and younger western islands. However, this genetic structuring was not supported by nuclear markers, which did not show any clear sign of population differentiation among islands. Based on these results, nuclear gene flow was supposed to be high across the archipelago and is mainly the result of male-biased dispersal as males have been observed to swim to different islands during the breeding season [A comprehensive genetic study based on both mitochondrial cytochrome b (cythipelago . Despitehipelago . While tg season . This wag season ).In this study, we revisit the population genetic structure of marine iguanas in order to lend insight into the patterns of gene flow, genetic diversity, and demographic history of this species. Data is presented from over 1200 individuals from 23 populations sampled at two different time points using an increased number of nuclear markers (thirteen microsatellite loci) as well as the typically fast-evolving mtDNA control region (CR). We use this information to unravel patterns of past and current dispersal in marine iguanas, and discuss results within the context of the island progression hypothesis and sex-biased dispersal.Marine iguanas were sampled during two different time periods, 1991/1993 and 2004. Samples from 1991/93 were a subset of those collected and analyzed from the Rassmann et al. study . The totTotal genomic DNA was extracted from blood samples in a 96-well format using the QIAamp 96 DNA Blood Kit (QIAGEN Inc.) following the manufacturer's instructions. Complete mtDNA CR sequences (1183 bp) were generated for 1203 marine iguana specimens using PCR protocols that are described elsewhere ,30. We g6 generations where the first 10% of parameter samples were discarded as burn-in.CR sequences were edited in the program SEQUENCHER v4.2.2  and alig6 generations each, and the first 10% of parameter values were discarded as burn-in. Adequate mixing was determined by examining the effective sample size and parameter trace values as visualized in the program TRACER v1.4 [Since the point of branch connection between marine iguana mtDNA phylogroups and Galápagos land iguanas has previously been shown to be unclear due to the large divergence between the two species , the rooCER v1.4  and the h), haplotype diversity (Hd), nucleotide diversity (π), and the average number of nucleotide differences between sequences (K) were calculated for each population using DNASP. Data were generated separately for the two temporal samples (1993 and 2004) from Marchena island, as a previous study showed that a bottleneck occurred in between samplings [ST calculations based on Wright's FST [The number of haplotypes . GenotyURE v2.1  and the URE v2.1 .FST = -ln using t-ln we used the same approach as described for the D-loop sequences (see above). The correlation between possible dispersal distance of marine iguanas vs genetic distance (FST) was tested with a Mantel test as implemented in the program ARLEQUIN v3.11 [In order to determine the correlation between island age IN v3.11 . The sigFs test [D statistic [Tests of recent population expansion were conducted on the combined population samples  FST values should be lower for the dispersing sex because allele frequencies of the dispersing sex should be more similar across populations; iii) Immigrants tend to have a lower Assignment Index  is provided by Table S2 [see Additional file Complete mtDNA CR sequences were obtained for 1203 marine iguanas and contained 1183 bp, or 1179 bp when positions with insertions/deletions (indels) were removed as they did not provide significant information and would have extremly limited important applications within the program DNASP (the dataset with gaps can be obtained from SS or SG upon request). D-loop haplotypes have been deposited in GeneBank under accession numbers h = 7) and was widely distributed across the archipelago; clade B (PPV = 1) contained 30 haplotypes that were found mostly on the central and eastern islands, but also on southern Isabela (IBA and IWE); clade C (PPV = 0.96) accounted for the majority of haplotypes (h = 69) and occurred on the northern  and western (Fernandina and Isabela) islands as well as on the two central islands of Floreana and Rábida at low frequency. The average pairwise divergence within each of the three clades was low  were removed from the statistical parsimony analysis to simplify the general phylogeographic patterns. The majority of clade C haplotypes were limited to the far western (Fernandina and western Isabela) and northern  regions of the archipelago, although two clade C haplotypes, H60 and H106, were also found on two central islands, Floreana and Rábida.Hd > 0.900; Table Many populations from the west (i.e. Fernandina and western Isabela) showed high levels of genetic diversity (FST= 0.74) and west (FST= 0.70). There was also significant structure between northern and western islands, but to a lesser degree (FST= 0.42). Within regions, genetic distinctiveness among populations was much greater in the eastern/central archipelago (FST= 0.55) than in the north (FST= 0.18) or west (FST= 0.09). However, some eastern/central islands  contained many individuals that shared haplotypes with populations from other islands ; a result of the fact that haplotypes from these populations are from two different clades  and could explain 20% of the observed variation.The analysis of genetic structure Table  showed t FST= 0.4. Within Table We found different patterns of genetic differentiation across the archipelago. Individuals sampled at different time points (i.e. 1991/93 and 2004) from the northern , central  and one of the eastern (Española) islands each form a single island-specific genetic cluster with a low degree of intermixing with genetic clusters from other islands. On the other easternmost island of San Cristóbal, two highly distinct genetic clusters were found corresponding to the western (SRL) and eastern (SRP) populations. The strong genetic differentiation among these islands  was further supported by the results of the individual-based self-assignment test. Proportions of individuals correctly assigned to these island populations ranged from 96-100% indicating low levels of gene flow between islands . Within-island FST differentiation ranged from 0 (on Fernandina) to 0.11  and FST between islands from the same region ranged from 0.01 (west) to 0.13 (north). Differentiation between geographic regions was low, ranging from 0.1  to 0.14  (see Table p = 0.25). A slight (r = 0.26), but highly significantly (p = 0.001) correlation between possible dispersal distances and genetic distance was found that could explain 7% of the observed variation between matrices . However, only the west showed a clear unimodal mismatch pattern which is suggestive of recent population expansion  were obtained for two sites on Fernandina (FPE and FPM) and for one site on western Isabela (ICB), indicating an excess of recent mutations in these populations due to population growth , but with a much weaker signal than for the FS test. In addition, when all the western populations were combined, FS values were negative and significant , but D values were not .For the mtDNA dataset, both the western and northern populations conformed to the model of sudden-expansion  site on Santiago.Intra-locus Table Genetic studies have revealed that many species in the Galápagos follow the progression hypothesis, where islands are colonized in order of their emergence (reviewed in ). This pGalápagos marine iguanas feed exclusively on aquatic algae and are closely tied to the coastal environment throughout their lives ,68,69. Lb study [7 generations. This outcome is likely due to the large divergence between marine and land iguana CR sequences (approximately 10%) compared to the low divergence within marine iguanas (max. 1.6%), reflecting the long timeframe in which the two species have independently evolved on both existing and submerged islands.On a broad scale, the current study provides evidence that the progression hypothesis appears to hold true for marine iguanas. Our CR analyses, as well as the previously published cytb study , suggestFST-values between regions  was also found on the far-western island of Fernandina, demonstrating the potential for rare long-distance dispersal from the east. Similarly, haplotypes from clade C, which were previously shown to be restricted to the north and west, were also identified on two of the central islands, Floreana and Rábida. A unique clade A haplotype was also identified on northern Isabela, showing that this lineage extends across the entire northern archipelago. The ancestral haplotype in this clade (H5) was widely distributed, existing on San Cristóbal to the east, and Santiago and Marchena in the north-central archipelago. Since San Cristóbal is one of the two oldest islands in the Galápagos, clade A likely radiated from there to the north and west, all the way to the northern tip of Isabela. This fits well with the patterns of island age as well as the path of the prevailing Humboldt current which approaches the archipelago from a southeasterly direction  and is t3 was alsWhile the progression hypothesis generally explains the overall east/west division of marine iguanas, dispersal patterns have produced a more complicated history within regions. Unlike tortoises and other Galápagos organisms that exhibit complete genetic structuring among older populations, many marine iguana CR haplotypes are shared between different islands in the eastern/central region Figure . For exaMicrolophus [Bayesian cluster analysis of microsatellite loci genotypes shows that most marine iguanas belong to highly distinct genetic island clusters Figure . This rerolophus .FSTanalyses of nuclear genetic data, high levels of gene flow between islands and populations were reported [FST was approximately 0.1 for the 22 marine iguana populations examined. Although the average FST differentiation found in our study was in the same range , the high level of genetic differentiation between islands indicated by Bayesian cluster analyses suggests that recent gene flow has been limited, and consequently that FST values may provide little information about fine scale population structure . Anoiewed in ). As an -2650 km . In anot-2650 km  indicatiSince the study of Rassmann et al. found significant differentiation between islands and regions based on maternally inherited mtDNA markers but not on bi-parentally inherited nuclear microsatellite and minisatellite loci, they concluded that male-mediated dispersal and gene flow was likely responsible for this discrepancy . SupportFST-based test statistics between the two studies. In the former study [FST-value (FST= 0.09) than females (FST= 0.12) suggesting that males disperse more than females. Conversely, FST  estimates for the same set of males and females, which were genotyped at thirteen microsatellite loci, were not significantly different  than for females (FST= 0.106), but also non-significant (p = 0.82). These findings suggest that the results of the Rassman et al. study [In our study none of the four tests conducted showed significant evidence for sex-biased dispersal in marine iguanas Table . Since ter study  males dil. study , which wl. study , we cannversus the rest of the Isabela; see Figure Beyond the results of the sex-biased dispersal tests, the observed genetic patterns make high dispersal rates in marine iguanas unlikely. Bayesian-based population structure analysis Figure  indicateSpheniscus mendiculus) population [Marine iguana populations on the westernmost islands of Isabela and Fernandina are among the largest in the Galápagos, with Fernandina alone numbering in the hundreds of thousands . Individpulation .The western marine iguana populations also possess a high level of genetic diversity for both mitochondrial and microsatellite data, even though they occur on the two most recently emerged islands. The emergence age of the oldest volcano on Isabela is less than 535,000 years, while the emergence age of Fernandina is estimated to be only 35,000 years . In contFS values for Punta Espinosa and Punta Mangle on Fernandina  indicatThis comprehensive analysis of the population structure of Galápagos marine iguanas both supports and transforms our previous knowledge about the microevolution of this unique species. The detailed mtDNA analyses trace back migration routes in the evolutionary past and suggest that colonization of islands progressed from geologically older to younger islands in the archipelago. The existence of highly differentiated genetic clusters among islands as well as no specific support for sex-biased dispersal conflict with the previously held view of high male gene flow among islands. More generally, our study demonstrates how the development of recent analytical tools such as Bayesian clustering analysis and DNA sequence-based demographic analyses allow us to tease apart the role of past and present gene flow in shaping current patterns of population differentiation.Project conception and design: SS SG AC HLS. Performed laboratory work: SS SG DL TCH. Data analysis: SS SG DL TCH. Wrote the paper: SS SG AC MR. Figure design: DL SG SS. Field sampling: SS SG AC MR CM SR HMS GG GO AMP. All authors read and approved the final manuscript.Table S1: Possible dispersal distances of marine iguanas.Click here for fileSupporting information on mitochondrial CR analyses [analyses -93.Click here for fileTable S2: Detailed infromation on D-loop haplotypes.Click here for fileTable S3: General characteristics of the three mitochondrial clades of Galápagos marine iguanas.Click here for fileFigure S1: Estimation of genetic clusters according to Evanno et al.Click here for fileTable S4: Best found partitions according to BAPS v3.2.Click here for fileFST(based on microsatellite loci) versus possible dispersal distance.Figure S2: Scatter plot Click here for fileFigure S3: Mismatch distribution of Galápagos marine iguana D-loop haplotypes.Click here for fileTable S5: Intra locus specific k-values of thirteen microsatellite loci of Galápagos marine iguana populations.Click here for filevs genetic diversity valuesFigure S4: Scatter plot with regression analysis of island perimeter as measured by NOAA GIS resource (World Vector Coastline) .Click here for file


P. ginseng is currently found only in the Russian Primorye and the populations are extremely exhausted and require restoration. Analysis of the genetic diversity and population structure of an endangered species is a prerequisite for conservation. The present study aims to investigate the patterns and levels of genetic polymorphism and population structures of wild P. ginseng with the AFLP method to (1) estimate the level of genetic diversity in the P. ginseng populations in the Russian Primorsky Krai, (2) calculate the distribution of variability within a population and among populations and (3) examine the genetic relationship between the populations.The natural habitat of wild P. ginseng populations were investigated with Amplified Fragment Length Polymorphism (AFLP) markers. The genetic relationships among P. ginseng plants and populations were delineated.Genetic variability and population structure of ten P. ginseng. The partition of genetic diversity with AMOVA suggested that the majority of the genetic variation (64.5%) was within populations of P. ginseng. The inter-population variability was approximately 36% of the total variability. The genetic relationships among P. ginseng plants and populations were reconstructed by Minimum Spanning tree (MS-tree) on the basis of Euclidean distances with ARLEQUIN and NTSYS, respectively. The MS-trees suggest that the southern Uss, Part and Nad populations may have promoted P. ginseng distribution throughout the Russian Primorye.The mean genetic variability within populations was high. The mean level of polymorphisms was 55.68% at the population level and 99.65% at the species level. The Shannon's index ranged between 0.1602 and 0.3222 with an average of 0.2626 at the population level and 0.3967 at the species level. The analysis of molecular variances (AMOVA) showed a significant population structure in P. ginseng populations in the Russian Primorye are significant in genetic diversity. The high variability demonstrates that the current genetic resources of P. ginseng populations have not been exposed to depletion.The  Panax ginseng C.A. Meyer  is a representative species of the Panax L. genus which is a relic of the Araliacea family [P. ginseng spread over a vast territory including the Russian Primorsky Krai, Korea and China. Currently, wild P. ginseng can only be found in Russia; however, its populations are extremely exhausted and restoration is needed [P. ginseng is listed in the Red Book of Primorsky Krai as an endangered species [a family . Their na family . At the s needed . P. gins species .Analysis of the genetic diversity and population structure of an endangered species is a prerequisite for conservation . GeneticP. ginseng [Panax quinquefolius  [P. quinquefolius in the United States [P. quinquefolius population from Ontario, Canada, has a polymorphism level of about 46% estimated with RAPD analysis [A high level of polymorphism of a marker is a basic condition that must be assessed population genetics studies . A study ginseng . Allozymginseng) -16. Theranalysis .Miscanthus, three fluorescently labeled AFLP primer pairs generated 998 polymorphic markers, as opposed to only 26 polymorphic markers produced by two ISSR [As a reproducible and robust technique, AFLP  generatetwo ISSR .P. ginseng with the AFLP method to (1) estimate the level of genetic diversity in the P. ginseng populations in the Russian Primorsky Krai, (2) calculate the distribution of variability within a population and among populations and (3) examine the genetic relationship between the populations.The present study aims to investigate the patterns and levels of genetic polymorphism and population structures of wild P. ginseng individuals were collected from the ten administrative areas of Primorsky Krai , 19 from the Spassk area (Spa), 16 from the Ussuriisk area (Uss), 13 from the Dalnerechensk area (Drech), 16 from the Dalnegorsk area (Dgor), 15 from the Olginsk area (Olg), 15 from the Pozharsk area (Pozh), 24 from the Nadezhdinsk area (Nad), 19 from the Partizansk area (Part) and 10 from the Yakovlevsk area (Yak).One hundred and sixty-seven 167) 67 P. ginet al. [Total genomic DNA was extracted from fresh leaf tissue according to Echt et al. . The extet al. .et al. [EcoRI and MseI restriction enzymes. Pre-amplification reactions utilized AFLP primers with two selective nucleotides. EcoRI and MseI selective amplification primers contained three and four selective nucleotides, respectively (Table EcoRI-NNN selective primers were labeled with fluorescent 6-carboxy fluorescein (6-FAM) at the 5' end. The AFLP fragments were analyzed on an ABI Prism 3100 automated capillarity system with GeneScan Analysis Software . All unambiguous peaks including monomorphic peaks between 50-500 base pairs (bp) were analyzed and the scoring results were exported as a presence/absence matrix.AFLP genotyping was performed according to Vos et al.  using Ecly Table . AFLP adIS) [FST) between pairs of populations  were calculated. Gene flow between pairs of populations (Nm = (1-FST)/4FST) was calculated from FST values [P. ginseng and populations from a matrix of squared Euclidean distances using ARLEQUIN  and NTSYS  respectively.Parameters of genetic variability and genetic mutual relations of populations were calculated with the POPGEN32   and ARLEIS)  was usedIS)  was condT values . We recoEco(ACG)/Mse(CCTC), Eco(ACG)/Mse(CCTT), Eco(ACA)/Mse(CCTG), Eco(ACA)/Mse(CCGG), Eco(ACA)/Mse(CCAC), Eco(ACT)/Mse(CCGA), Eco(ACT)/Mse(CCTA), Eco(ACC)/Mse(CCAG), and Eco(ACC)/Mse(CCGC). Using two of the primer pairs Eco (ACA)/Mse(CCTG) and Eco(ACA)/Mse(CCGG)  were found in the Uss and Dgor populations. The mean level of polymorphisms was 55.68% at the population level and 99.65% at the species level. The Shannon's index ranged between 0.1602 and 0.3222 with an average of 0.2626 at the population level and 0.3967 at the species level. The intra-population genetic polymorphisms ranged from 38.65% (Uss) to 69.15% (Chu) with an average of 55.68% (Table Nine (9) AFLP primer pairs were tested, namely G) Table , we deteFST between populations, obtained with AMOVA, were significant (P = 0.0000) and varied from 0.09180 (Pozh-Nad) to 0.60506 (Drech-Uss) (Table Nm) between populations based on AMOVA (FST = 0.355) was 0.45.All pair wise s) Table . The nons) Table . The aveP. ginseng plants , whereas the Olg population was characterized by the highest value (36.5 units). The average value of Euclidean genetic distances between the plants of different populations (28.78 units) was higher than that of intra-population genetic distances (26.35 units)  by allozyme and RAPD [and RAPD ,27-29 whP. ginseng was revealed by the AFLP method. While genetic diversity is theoretically higher in large populations, the Uss population was small in size but appeared to have suffered from the loss of a genetic diversity more than other populations. Several populations  were distinguished by having higher levels of variability. For these populations, the average value of polymorphisms was 65.39%. At the species level, the percentage of polymorphisms was 99.65%. The high level of variability may be due to cross-pollination; however, P. ginseng's capability for cross-pollination is yet to be established [P. ginseng inflorescences are potential pollinators [Panax notoginseng, four pairs of fluorescently labeled AFLP primers produced 312 fragments, of which 240 (76.9%) were polymorphic [Panax stipuleanatus, the same primers revealed 346 loci, of which 334 (96.5%) were polymorphic [High genetic variability in ablished . A largelinators . In PanaP. ginseng. FST, estimates of inter-population variability, varied from 0.09180 to 0.60506  was 0.45; therefore, wild P. ginseng has a relatively high genetic differentiation value among populations and a relatively low level of gene flow. In cultivated P. ginseng, inter-population RAPD variability ranged from 1.77% to 42.01% [P. stipuleanatus was among the populations [P. ginseng' FST values are consistent with estimates of inter-population variability, which were obtained with AMOVA and AFLP markers for plant species with mixed type of propagation (FST = 0.35) [P. ginseng is a species with mixed type of propagation. The ability of P. ginseng to produce seeds via autogamy, out-crossing or agamospermy without pollination was demonstrated earlier [P. ginseng suggest that human activities  are the major contributor that threatens the survival of the wild P. ginseng populations.Analysis of molecular variance (AMOVA) of the AFLP data showed a significant population pattern of the wild Russian 06 Table , indicatty Table . The valo 42.01%  and was o 42.01% . The fluulations . P. gins = 0.35) . Accordi = 0.35) , P. gins earlier . The higUss, Part, Olg, Yak, Dgor and Drech) clustered together and four populations  were partially mixed with other populations , suggesting the ancestral status of the Uss population. The Part population, also at the central position on the MS-tree, may have the same ancestral status as the Uss population  that belongs to the n Figure ; Nad andl Figure . The abse Figure  may be eUss, Part and Nad populations may have promoted P. ginseng distribution throughout the Russian Primorye. This result supports the assumption that Sikhote-Alin was re-colonized by P. ginseng when thermophilic plants spread from the south to the north during the early Holocene warm period [The MS-trees suggest that the southern m period .P. ginseng and whether P. ginseng is adapted for heterogeneous conditions; (2) whether a positive correlation between genetic and geographical distances among P. ginseng populations may be established; and (3) using the multi-locus mating system program (MLTR) to estimate the level of inbreeding and cross-pollination in wild P. ginseng populations.Future studies may focus on (1) using AMOVA to investigate whether genetically differentiated regions exists for P. ginseng populations in the Russian Primorye contain a significant level of genetic diversity and are essentially differentiated. The gene flow of the populations was less than one (Nm = 0.45) which indicates continued divergence among populations [P. ginseng populations have not been exposed to depletion.The ulations . The curChu: Chuguevsk area; Spa: Spassk area; Uss: Ussuriisk area; Drech: Dalnerechensk area; Dgor: Dalnegorsk area; Olg: Olginsk area; Pozh: Pozharsk area; Nad: Nadezhdinsk area; Part: Partizansk area; Yak: Yakovlevsk area; bp: base pairs; AMOVA: Analysis of molecular variance; MS-tree: Minimum Spanning tree; 6-FAM: 6-carboxy fluoresceinAFLP: Amplified Fragment Length Polymorphism; ISSR: Inter Simple Sequence Repeat; AFLP: Amplified Fragment Length Polymorphism; The authors declare that they have no competing interests.YNZ and GDR designed the research. GDR and ILK performed the research and analyzed the data. TIM collected the plants. GDR wrote the manuscript. AAB contributed to the data acquisition. YNZ helped in writing the manuscript and coordinating the study. All authors read and approved the final version of the manuscript.