Seventeen population groups within the Russian Federation were characterized for the first time using a panel of 15 genetic markers that are used for DNA identification and in forensic medical examinations. The degree of polymorphism and population diversity of microsatellite loci within the Power Plex system (Promega) in Russian populations; the distribution of alleles and genotypes within the populations of six cities and 11 ethnic groups of the Russian Federation; the levels of intra- and interpopulation genetic differentiation of population; genetic relations between populations; and the identification and forensic medical characteristics of the system of markers under study were determined. Significant differences were revealed between the Russian populations and the U.S. reference base that was used recently in the forensic medical examination of the RF. A database of the allelic frequencies of 15 microsatellite loci that are used for DNA identification and forensic medical examination was created; the database has the potential of becoming the reference for performing forensic medical examinations in Russia. The spatial organization of genetic diversity over the panel of the STR markers that are used for DNA identification was revealed. It represents the general regularities of geographical clusterization of human populations over various types of genetic markers. The necessity to take into account a population’s genetic structure during forensic medical examinations and DNA identification of criminal suspects was substantiated. Molecular genetic analysis methods are now widely applied in the identification of the biological samples of individuals: victims of crimes, disasters, and acts of terrorism, criminals, and contingent of special divisions of armies or law enforcement. A genetic DNA analysis in forensic medical examinations has two stages. At the first stage, the DNA characteristics of the samples collected at the locus delicti are determined. At the second stage, they are matched with the DNA collected from the suspects or relatives of the victims. If there is no match of the genotypes, that points to the fact that the samples examined do not belong to the individual in question (taking into account the exclusion probability). When genotypes match, the probability of their random matching, i.e., the probability that other individuals may have the same genotypes, is also taken into account. The probability of a random match is calculated on the basis of data on the occurrence frequencies of the alleles (and genotypes) of the analyzed panel of genetic markers in reference populations. In order to create such reference databases, population samples collected with allowance for the population genetic structure of certain ethno-territorial groups are used. Allelic frequencies in various populations and groups have been published and presented in databases. These reference databases serve as a legally valid basis for forensic medical conclusions in interpreting the results of genotype comparisons.  The reliability and efficiency of DNA identification depends on two key factors: on the choice of the locus panel and the choice of the reference population. Selection of the loci panel. The genetic markers that are used for forensic medical expertise should be highly polymorphic and should possess a high resolution capacity. Multiallelic  unlinked microsatellite markers – STR (Short Tandem Repeats) loci are considered to be the most efficient ones. However, different panels of these STR markers are used in different regions. TH01, vWA, D18S51, D8S1179, D3S1358, FGA, D21S11, D1S1656, D2S441, D10S1248, D12S391  и  D22S1405 . In 2010, the standard was approved by the European Union.In Europe, Interpol uses two standards of loci sets – ENFSI (the European Network of Forensic Science Institutes) and EDNAP (the European DNA Profiling Group), consisting of seven STR loci each. In 2005, an agreement on the unification of the loci systems used in Europe was signed. The ENFSI proposed six more markers as candidates to be included into the European standard set (ESS) . In 2009D7S820, D13S317, CSF1PO, TPOX, D16S539, TH01, vWA,D5S818, D18S51, D8S1179, D3S1358, FGA, D21S1).  The CODIS and ENFSI systems have seven markers in common from the EDNAP/ENFSI primary standard.Starting in 1994, the CODIS (Сombined DNA Index System) system has been in use in the United States, its full format comprising 13 loci  another locus (amelogenin) is used, the size of its PCR fragments being different on the X and Y chromosomes, which allows for the determination of the sex of an individual by analyzing the DNA of a biological sample. PentaD and PentaE ) [When creating these systems, among the several tens of STR loci that had been tested, the most highly polymorphic ones within the majority of the examined populations were selected. For the convenience of genetic typing, the PowerPlex 16 system was designed, enabling the simultaneous amplification of 16 polymorphic loci in a single test tube, which considerably simplifies the analysis and reduces its cost. In addition to the amelogenin locus and the 13 loci from the CODIS system, this kit also comprises two highly polymorphic and easily readable pentanucleotide markers ( PentaE ) .On December 3, 2008, the Federal Law of the Russian Federation On State Genomic Registration in the Russian Federation was adopted. The law provides for the creation of the Federal database of genomic information under the Ministry of the Interior of the Russian Federation. Order of the Ministry of the Interior of the RF no. 70 dated February 10, 2006, is the official statutory act regulating the gene typing procedures for DNA identification; in the edition dated May 21, 2008, it establishes a set consisting of 12 STR markers and the amelogenin locus, which is totally identical to the American CODIS standard, as a mandatory set. Selection of the reference population. In order to reliably compare genotypes in each case, the choice of the reference population should depend on the group that the individual who has left biological marks belongs to. In actual practice, the reference population is usually selected among the populations represented in the criminal databases which were studied using this panel of STR markers. The less the reference population represents the gene pool of a tested group, the more individuals within this group have alleles that are not in the reference database, which results in a considerable decrease in the discrimination capacity of the method. There are correlations between the number (percentage) of individuals who have alleles that are not in the reference population and the genetic distance between the reference population and the population under analysis .F st) with respect to the loci used for each specific group within each specific territory. This correction permits the replacement of alleles and genotypes that are unknown for the reference population by their calculated frequencies, with allowance made for the differentiation degree F st [The use of an inadequate reference group may result in a decrease in the total identification probability by several orders of magnitude. The situation can be improved by introducing corrections based on the maximum degree of genetic differences between subpopulations within a reference population . In order to introduce such a correction, it is necessary to have information on the genetic differentiation between populations  and areIn the United States and Europe, a large massif of population has been characterized with respect to the loci used in forensic medical examinations. In other regions, several tens of population groups have been known to have been studied on the basis of panels of ENFSI, EDNAP, and CODIS genetic markers 7–.Data on the distribution of individual genetic markers from these panels in Russian populations has remained fragmentary 15–. In termIn this context, our work was aimed at determining the allelic frequencies of 15 autosomal STR loci from the PowerPlex 16 system in six urban population groups and 11 ethnic groups in the RF. A solution to this problem will allow to characterize the genetic variability of the Russian population using this system of markers and will lay the basis for the creation of our own reference population for DNA identification and forensic medical examinations in Russia. Populations Seventeen population groups with a total of 1,156 people representing different geographical regions of Russia  and belonging to different linguistic groups and different anthropological types were examined. N = 60), Belgorod ( N = 50), Orel ( N = 51), Orenburg ( N = 50), Yaroslavl ( N = 50), and Tomsk ( N = 185). Eleven samplings represent a wide range of the Russian population and neighboring countries: Komi ( N = 50), Mari ( N = 52), Khakas ( N = 92), Bashkir ( N = 70), Tatar ( N = 61), Chuvash ( N = 53), Dargins ( N = 48), Avars ( N = 50), Lezgins ( N = 50), Ukrainians ( N = 138), and Belorussians ( N = 46).Six samplings represent the Russian urban population: Moscow ( Molecular biology techniques The amplification of 15 STR loci and the sex marker (amelogenin gene) was carried out in the multiplex PCR format  on Applied Biosystems and Biometra gradient amplifiers under the conditions that were recommended by the manufacturer of the commercial PowerPlex system (Promega). Fluorescently labeled PCR fragments were separated by capillary gel electrophoresis on an ABIPrism 3130 and an ABIPrism 310 genetic analyzer (Applied Biosystems). The genotypes were read using Gene Mapper software (Applied Biosystems). The quality of gene typing was controlled using the standard set of alleles of all 16 microsatellites (“ladder”) supplied within the PowerPlex 16 system; the “ladder” were loaded in each gene typing cycle (in each run). Methods of statistical analysis of the results The data were analyzed using the modern statistical approaches employed in population genetics and forensic medicine. Correspondence of the observed genotype distributions to the Hardy–Weinberg equilibrium was estimated by the exact test of Guo and Thompson  implemenF st values and by an analysis of molecular variance (AMOVA), using the matrix of root-mean-square discrepancies in repeat numbers of R st. The dendrogram illustrating the genetic relationships between the populations was constructed using the unweighed pair group method with the arithmetic mean (UPGMA) in PHYLIP software.The genetic differentiation of the populations was analyzed by a calculation of pairwise D3S1358, TH01, D21S11, D18S51, D13S317, D7S820, D16S539, CSF1PO, vWA, D8S1179, TPOX, FGA, D5S818, PentaD, PentaE, D2S1338,  and  D19S433 ). However, since five markers   had not been studied in a number of populations, the remaining 12 loci were used in the analysis.The variability of the studied loci in the population of North Eurasia was analyzed using the database on the frequencies of microsatellite markers in 51 populations that we compiled . The database comprised both our own results presented in this paper and the data from earlier studies 25–, includiThe analysis of this vast massif was carried out using both statistical and cartographic gene-geographic. The statistical analysis consisted of the calculation of genetic distances according to Nei  using thHeterozygosity with respect to each locus was calculated, and the averaged (over 12 loci) values of heterozygosity were obtained in each population. These values were mapped using GeneGeo software that was developed by a number of authors for several years. The calculation of interpolated heterozygosity values was performed on the basis of the data in reference points (immediately in the populations under study) to a uniform grid consisting of 335,661 nodes (881× 381); the 301,681 nodes remaining after the water area were eliminated. Interpolation was performed using the generalized Shepard’s method. The cube of the weighting function was employed; i.e., the contribution of each point into the calculated value in a certain node was in reverse proportion to the cube of the distance between the reference point and the node; the reference points at a distance of more than 3,000 km were not taken into account. The discrimination potential of the system, which consisted of 15 microsatellites, was estimated using standard medical forensic indices that included the matching probability (MP), power of discrimination (PD), power of exclusion (PE), and paternity index (PI) .Genetic variability of 15 STR PowerPlex 16 Fig. 1 shows an example of the multiplex gene typing of amelogenin and 15 satellites from the PowerPlex 16 system in one of the samples. Only the panel of microsatellite markers (15 STR) was used to perform the analysis in this study.In addition to 15 unlinked autosomal STR markers, the PowerPlex 16 system, which is intended for determining an individual’s genetic profile, comprises the marker of the amelogenin gene, which is located on X and Y chromosomes and is required for sex determination. Table 1 . The average level of intra-population genetic diversity  of 15 STR in the populations under study was 0.796; the most variable loci (He > 0.85) – D21S11, D18S51, PentaE , and FGA  – have more than 15 alleles. The highest number of alleles was found in loci FGA (20), PentaE (18), and D18S51  (18).The results of a study of the genetic variability of these 15 STR in Russia and neighboring countries are listed in PentaE  are characterized by the highest dispersion of the repeat number  and PentaD  (17-repear dispersion). The least polymorphic marker (He = 0.612), TPOX ,has eight alleles. The expected heterozygosity of the remaining 10 microsatellites of the PowerPlex 16 system varies within the range 0.74 < He < 0.82, the number of alleles detected varying from 8 to 12.Pentanucleotide microsatellites Distribution of alleles and genotypes over populations p  < 0.05) was detected only in 21 of them. The accumulation of deviations from the Hardy–Weinberg equilibrium was detected only in the Tomsk population (five loci out of 15). However, when introducing the Bonferroni correction for comparison multiplicity, the actual significance level for the kit consisting of 15 tests per population is equal to 0.0035; therefore, with allowance for the Bonferroni correction, only one deviation from the Hardy–Weinberg equilibrium ( FGA locus in the Tomsk population) turned out to be statistically significant.In the populations consisting of 255 genotype distributions (15 loci in 17 samplings) that were studied, the deviation from the Hardy–Weinberg equilibrium (HWE) ( D7S820  locus in six Russian cities) is shown in Fig. 2 . The genetic variability indices of 17 populations over 15 microsatellites are summarized in Table 2 . All 17 populations have close degrees of genetic diversity (the average heterozygosity fluctuating within 0.771–0.803). The highest degree of genetic variability was revealed in the populations of Lezgins, Ukrainians, and Tomsk residents; the lowest degree was revealed in the Mari, Khakas, and Orel residents.An example of allele distribution in populations   was calculated in 51 populations of Russia and neighboring countries using both our data and the results obtained by other authors represented in the database compiled by us . Although all the markers contained in the PowerPlex 16 panel were selected on the basis of the maximum intra-population variability (including heterozygosity), the populations in different Russian regions differ in terms of their heterozygosity level. The map demonstrates that the maximum heterozygosity (above 79%) is observed in the populations of Western and Central Europe and in the neighboring western regions of NIS countries. The heterozygosity level decreases gradually when moving eastwards. Thus, in the European part of Russia and the Trans-Urals, it is equal to 78%; in Central Asia and Altai, approximately 77%; in the Baikal region, less than 77%. This regularity of gradual decrease in heterozygosity across the entire Eurasian continent (from the Atlantic to the Pacific coast) can be clearly traced to an appreciable degree, although separate populations may fall out of the general trend . In the deep south, an increase in heterozygosity to maximum values exemplified by the Pakistani population was observed.The heterozygosity of 12 loci ( The longitude tendency towards decreasing geterozygosity (from the west to the east of North Eurasia) that was first described in the markers of the “criminal panel” has been well-known on the basis of the conventional gene-geographic studies of the population of the USSR. Heterozygosity maps of the conventional  markers are given in , which aGenetic differentiation of populations F st values compared pairwise are not higher than 0.25%). Meanwhile, the group of Slavic populations significantly differs from most of the other populations. Populations of the Volga-Ural region (the Tatars and Chuvash), as well as the Mari, have no significant genetic difference between each other; however, they differ from other ethnic groups. Two other groups that are characterized by significant differences from all the other groups are the populations from the North Caucasus , the Bashkirs, and the Khakas.The analysis of the genetic differences between populations was performed by the molecular variance method (AMOVA) with account for the variation in allelic frequencies, and the dispersion of tandem repeat numbers revealed significant genetic variations between the groups of populations studied. All Russian populations, the Ukrainians, Belorussians, and Komis are characterized by a community of the gene pool with respect to the studied markers and the absence of a significant inter-population differentiation  and highly significant ( p  > 0.00001).The total level of genetic differentiation of the pool consisting of 17 populations turned out to be relatively high .Meanwhile, the analysis inside the massif consisting of six Russian urban populations, in spite of the considerable territorial sparseness of the cities that represent the center of the European section of Russia (Moscow), its south , north (Yaroslavl), the Urals (Orenburg), and Siberia (Tomsk) revealed the total absence of inter-population differences between 15 microsatellites in these populations in terms of frequencies and molecular dispersion. The Within the context of using and studying 15 STR to perform DNA identification, these data point to the possibility of using the sum frequencies over Russian megapolises when carrying out a medical forensic expertise of the urban (predominantly Russian) population. In addition, these data indicate the necessity for accounting for data on the frequencies of the “identification” markers in other ethnic groups of the Russian Federation to perform calculations in these populations. Table 3 ).The comparison of the frequencies of 15 STR in an aggregate sampling of the populations of Russian cities with the frequencies in Caucasian Americans supplied by Promega company  as the rGenetic relationships between populations: phylogenetic analysis Fig. 4 .The tree of genetic inter-population relationships was constructed based on the matrix of pairwise genetic distances between populations with respect to the combination of the 15 STR loci obtained by AMOVA and with account for the differences in allelic frequencies and the dispersion of the tandem repeat number. The dendrogram constructed by the unweighed pair-group method with an arithmetic mean (UPGMA) in PHYLIP software is shown in The arrangement of populations on the dendrogram completely coincides with the revealed pattern of genetic differentiation in the Russian population over the DNA markers that are used for medical forensic expertise. The populations studied are grouped into four clusters, each of these clusters being characterized by a community of the gene pool of populations inside the cluster and significant differences (and large genetic distances) from the populations belonging to other clusters. The most distant cluster is formed by the Khakas and Bashkir populations, the ones with the highest proportion of the mongoloid race component. The rest of the populations are much closer to each other than they are to the Bashkirs or Khakas; however, they can also be clearly divided into three separate groups – Slavic populations  and Komis; populations of the Volga-Ural region ; and North Caucasus populations (Dargins and Avars). The location of the Lezgin population in a cluster with the Turk-lingual and the Uralian-lingual populations of the Volga-Ural region is a surprise. This is likely associated with random effects due to the small number of samplings. Genetic relationships between populations: multidimensional scaling Fig. 5 . The spatial distribution of a population represents the degree of similarity between the individual gene pools in the best way. It can be seen that all European populations are concentrated in the left-hand side of the plot. The proximity of populations in the European cluster points to the unity of the gene pool of the populations studied . Two more clusters are located in direct proximity: the population of the Volga-Ural region and the North Caucasus population. It is noteworthy that, as opposed to a phylogenetic analysis, the multidimensional scaling places the Lezgins into a cluster together with the Dargins and Avars. The Asian populations are located in the right-hand side of the plot. Here, the largest and vastest  cluster was formed by the South Siberian and Central Asian populations. The populations of the extreme northwest of Siberia (the Koryak and Chukchi) stand apart and form their own cluster. Finally, the East Asian populations (the Chinese and Koreans) also form a separate cluster. It is interesting that the population of Russians who have been living in China for several generations [The location of the populations in the space within the first two dimensions of multidimensional scaling is shown in erations  cannot bFig. 3 ), since both features typically result from genetic drift, its intensity being higher in small and isolated Siberian populations. Another significant conclusion consists in the contrast between the homogeneity of European populations  and heterogeneity of the other regions studied. The populations of the Caucasus, Volga-Ural region, Southern Siberia, Northeastern Siberia, and East Asia have drastically different allelic frequencies. In addition, Siberian populations differ considerably between each other.A conclusion can be reasonably drawn that the panel consisting of the 12 autosomal microsatellite loci that are used in the practical activity of medical forensic experts also happens to be highly informative for fundamental studies into the gene pool. Firstly, this fact is attested to by the consistency between the genetic clusterization of populations with respect to the markers set and the geographic (and linguistic) grouping of the same populations. Secondly, the distribution of populations within the plot space repeats their spatial distribution on the geographical map . Thirdly, the relative dimensions of the clusters correlate well with the concepts that were earlier formulated in science . Let us specify that high interpopulation variability in Siberia agrees well with the low interpopulation variability (heterozygosity) of these populations , the power of discrimination (PD), the power of exclusion (PE), and the paternity index (PI). The MP and PD indices are used in the DNA identification of a person, whereas the PE and PI indices are calculated when determining paternity. The values of these indices in certain populations, as well as those in Caucasian Americans, are listed in In general, all the populations studied had very high values of the discrimination potential of the PowerPlex 16 system. The matching probability of genotypes with respect to 15 STR markers for a total sampling of the Russian urban population was equal to 1 out of 281 000 000 000 000 000 (1 out of 281 quadrillion) individuals. In other populations, this index is slightly lower, but it still considerably exceeds all reasonable thresholds for DNA identification. It should also be noted that the paternity indices in all populations are higher than the values set by the statutory acts prevailing on the territory of the Russian Federation by several orders of magnitude. Thus, the following levels of evidence of the expert investigation was ascertained in Section 7 of the Instruction for Organization and Production of Expert Investigations in the Bureau of Medical Forensic Expertise approved by Order of the Ministry of Healthcare of the Russian Federation no. 161 dated March 24, 2003: The Bayesian probability of paternity is at least 0.9990, and the paternity index (PI) is at least 1,000 for a case of complete trio mother–child–putative father; and the Bayesian probability is at least 0.9975, and the PI is at least 400 for a duet child–putative father. The resulting indices of informativeness of the15 STR for DNA identification in a medical forensic expertise for the Russian and Ukrainian populations either exceed those of U.S. Caucasian Americans or are very close to them (the reference data provided by Promega company). In other ethnic groups of Russia, these indices are somewhat lower either due to the smaller volume of the samplings or due to the features of their population-genetic structure, but in any case they remain very highly informative. RusDNAid DNA Identification Database Primary data on the allelic frequencies of 15 microsatellite loci from the PowerPlex 16 system in 17 populations within Russia and neighboring countries are represented in the RusDNAid database designed by us. The database is hosted online on the websites of the Institute of Medical Genetics, Siberian Branch of the Russian Academy of Medical Sciences (http://www.medgenetics.ru/web-resources/pp16-rus/) and the Vavilov Institute of General Genetics, Russian Academy of Sciences (www.vigg.ru/info/data_bases/human/DNAid). The frequencies mentioned can be used as reference frequencies (for the corresponding population or ethnic group) in order to calculate identification probabilities for a genetic expertise, including the identification of a person, establishment of paternity, etc. Moreover, these data can be used in comparative population genetic studies. Estimates of the genetic variability of microsatellite loci, which are used for DNA identifications that comply with the international standards for such studies, were obtained for the first time in this study for the population of Russia and neighboring countries. The informativeness and resolution capacity of the full panel of STR loci was first estimated, and the reference allelic frequencies for Russian urban populations, certain ethnic groups of the Russian Federation, and neighboring countries were obtained. The identification indices of the systems used for DNA identification based on the CODIS international standard comprising 13 STR loci, or its extended version consisting of 15 STR, that make up the PowerPlex 16 system  were estimated for most of the populations of European countries, the USA, Japan, and a number of other countries. These reference databases underlie the performance of the national services of medical forensic expertise. In Russia, until recently, there was no reference database on the locus contained in the standard identification panels. The results of the present study allow to fill this gap and offer a possibility to align the standards of personality typing with international practice. The spatial organization of genetic diversity, which was revealed by a gene-geographic method, phylogenetic analysis and multidimensional scaling on the basis of the panel of STR markers used for DNA identification, demonstrates the general regularity of the geographic clusterization of human populations on the basis of different types of genetic markers, from the conventional protein polymorphism to full-genomic SNP sets ; it sho


Based on AFLP analyses of 134 individuals from 28 populations, 10 populations were identified that possessed hybrid individuals. Overall estimates of FST values revealed strong support for population structure in the Cytb data set; however, analyses of the SmcY gene and the AFLP data indicated ongoing gene flow between species. Pairwise FST comparisons of populations were not significant for the SmcY gene; although they were significant for the Cytb gene, indicating that these populations were structured and that gene flow was minimal. Therefore, gene flow between I. parvidens and I. tridecemlineatus appeared to be restricted to populations that exhibited hybridization. In addition, the fragmented nature of the geographic landscape suggested limited gene flow between populations. As a result, the distributional pattern of interspersed parental and hybrid populations were compatible with a mosaic hybrid zone model. Because ground squirrels display female philopatry and male-biased dispersal, the ecology of these species is compatible with this hypothesis.DNA sequence data from mitochondrial cytochrome- Hybrid zones are the result of the interaction of genetically distinct groups that produce offspring of mixed ancestry  have been examined on multiple geographic scales  is a prime example of this type of effect. These species hybridize  gene indicated a common mitochondrial genome with similar haplotypes among individuals of both species across the putative zone of sympatry. Haplotypes of individuals from this region were similar to haplotypes of I. tridecemlineatus outside of the putative zone of sympatry . The identification of hybrids was confirmed based on the incongruence of haplotypes of the SmcY gene and morphological identifications . Only fragments (50–400 bp in length) that could be scored unambiguously as present or absent with the program GeneMapper, version 3.7 (Applied Biosystems) were used. The fragments were converted to a binary matrix consisting of zeros and ones using GenAlEx, version 6.5  for each population and for pairwise comparisons between localities.Statistical parsimony networks were generated from the program TCS 1.21  was estimated with STRUCTURE 2.3.1  was set to two to represent both species without imposing any a priori knowledge of species identification  from binary genetic distances and an AMOVA in the program GenAlEx, version 6.5 . Genotype frequencies of each hybrid class were checked for sufficient loci differentiation to ensure reliable hybrid class assignment by the program . The significance of the FST values was tested against a null distribution determined by 50,000 random permutations of individuals among samples following the method of Lynch and Milligan (FIS) were estimated using the approximate Bayesian computation (ABC) approach in the program ABC4F  of the FIS distribution was used to detect any departure from HWE with a threshold value of 0.001 for acceptance . The genetic variation among populations was 78.56%, whereas genetic variation within populations was 21.44%.The parsimony network analysis of the data set  and resues Table ; howeveres Table . ResultsSmcY data set , as a result of the presence of SmcY haplotypes of both species (Table P < 0.05). The variation within populations accounted for 65.04% of the total variation, and the variation among populations accounted for 34.96% of the total variation.The parsimony network analysis of the 39 sequences of the data set  identifiI. parvidens but were absent in reference populations of I. tridecemlineatus.A total of 478 AFLP fragments were scored, and 300 fragments were polymorphic (62.2%). Of the polymorphic fragments, 10 fragments were determined to be fixed through species-level comparisons of reference populations and diagnostic in distinguishing each species. The majority of these markers (8 of 10) were present in reference populations of I. parvidens, I. tridecemlineatus, or hybrid) as designated in Thompson et al. The individuals examined for the PCoA analysis were placed in one of three groups (P = 0.001). The percentage of molecular variation among populations was 19%, whereas the percentage of molecular variation within populations was 81%. The majority of the molecular variation occurred between the I. parvidens group and I. tridecemlineatus group . The molecular variation between the hybrids group and the I. parvidens  and I. tridecemlineatus  groups was lower.Because of small sample size at some localities, the AMOVA was performed treating each species and hybrids as populations as in the PCoA. This approach revealed significant genetic variation among and between populations (q) estimated from the program STRUCTURE indicated that 73.2% of individuals sampled clustered with I. parvidens, whereas 26.8% of individuals sampled clustered with I. tridecemlineatus. However, values of q ranged from 0.0–0.1 (I. parvidens) to 0.9–1.0 (I. tridecemlineatus) for 81 individuals, likely representing nonadmixed individuals  analyzed were identified as hybrids with NewHybrids. No individuals were assigned as multigenerational backcrosses. When considering along with the admixture values from STRUCTURE, 53 of the 134 individuals  were classified as hybrids based on the AFLP data , these two individuals have SmcY haplotypes incongruent with their nuclear genome, and they are from localities (20 and 23) documented for potential hybridization . In general, pairwise FST estimates were high (−0.57143 to 1.0000), and many pairwise comparisons were statistically significant (86 of 375). In contrast, the estimates of FST values for the SmcY data set were lower than those for the Cytb data set, suggesting a high level of outbreeding. The overall FST estimate was 0.03519 (P < 0.05). Although pairwise comparisons varied from −1.00000 to 1.00000, only two of the 210 comparisons were statistically significant, indicating a paucity of haplotypes at each locality.Overall, estimates of FST value for the AFLP data set was low (FST = −0.0632), indicating a higher than expected number of heterozygotes because of outbreeding. In contrast, the permutation test implemented in the program AFLP-SURV (Vekemans P < 0.05), contradicting the result of the overall estimate. However, the pairwise FST comparisons between populations were low (0.0051–0.1988) and statistically significant reflecting a high level of interbreeding between populations, confirming the results of the overall FST estimate for the AFLP data set.The overall estimated Vekemans  rejectedFIS values were estimated for 15 of the 28 populations  to 0.865 . All reliable FIS values had 95% HDPI that incorporated the 0.001 threshold; therefore, HWE was accepted. Tests for linkage disequilibrium confirmed this result. An analysis of the entire AFLP data set yielded a statistically significant probability of linkage disequilibrium (P < 0.00001), supporting the acceptance of HWE by the FIS estimates. Estimates of linkage disequilibrium were calculated for 14 localities  indicated that I. parvidens and I. tridecemlineatus have unique genomes; therefore, any gene flow is limited to a few populations. This pattern is aligned closely to the distribution of SmcY haplotypes examined in this study and that of Thompson et al. The analyses of the AFLP data confirm gene flow between populations of I. parvidens and I. tridecemlineatus. Therefore, it appears that ground squirrel populations in the study area are structured genetically. The Cytb data set supports this hypothesis, which might be exaggerated due to the maternal inheritance of the mitochondrial genome and the intense female philopatry in ground squirrels  all were classified as hybrids. In fact, all major hybrid classes  are represented at this locality. Although this may be indicative of a hybrid swarm  throughout the city. The majority of hybrids at this locality were collected at a golf course near the northern edge of the city; however, remaining populations were nearly all I. parvidens and I. tridecemlineatus, the limited geographic extent of hybridizing populations provides an interesting caveat to the stage of the speciation process. Without the addition of the AFLP data set to the uniparentally inherited sequence data, a complete interpretation of the parental contribution to contemporary hybridization could not be inferred, nor could an accurate assessment of spatial structure of parental populations and their hybrids be determined. Because contemporary hybridization is likely the result of secondary contact (Cothran I. tridecemlineatus genome (Flicek et al. This study provides the groundwork for future studies of evolutionary mechanisms underlying the speciation process in ground squirrels. Although contemporary hybridization occurs between  Cothran , the cur Cothran . The anc Cothran , selecti Cothran , allowin Cothran . However Cothran , as the  Cothran . With th


Naja atra genomic libraries, which were enriched for AC-motif microsatellites. The thirteen loci were screened on a group of 48 individuals from two populations, one in Yong’an and the other in Ganzhou. These markers revealed a relatively high degree of genetic diversity  and heterozygosity (Ho ranged from 0.213–0.854 and He ranged from 0.301–0.838). Tests for departure from Hardy-Weinberg equilibrium and for linkage disequilibrium were conducted for each of the two populations separately. After sequential Bonferroni correction, none of the 13 loci showed significant departures from Hardy-Weinberg equilibrium. Hierarchical analysis of molecular variance indicated that a small but significant (P < 0.001) proportion (16.0%) of the total variation in the microsatellite DNA data were attributable to differences among populations, indicating geographical structuring and restricted gene flow. It could be attributable to the Wuyi mountains in the area having a sufficiently isolating effect to significantly reduce gene flow. Our microsatellite data also showed a low Nm (1.31) value in the two populations from mainland China. Thus, the Yong’an and Ganzhou populations could be treated as distinct evolutionarily significant units (ESUs). The high level of polymorphism revealed by these microsatellite markers will be useful for the study of gene flow, population structure and evolutionary history of N. atra.We characterize thirteen polymorphic microsatellite loci isolated from  Naja atra) is an oviparous elapid snake with a distribution covering southeastern China  and northern Vietnam  used in this study were collected from two populations, one in Yong’an (Fujian Province) and the other in Ganzhou (Jiangxi Province). Fresh tissue (tail muscle) samples were used to extract total genomic DNA using EasyPure Genomic DNA Extraction Kit (TransGen Biotech). DNA was resuspended in TE buffer . Genomic DNA was used to construct a library enriched for AC-motif microsatellite sequences. The enrichment protocol essentially followed the FIASCO (Fast Isolation by AFLP of sequences COtaning repeats) [Mse I and ligated to Mse I AFLP adaptor. The digestion-ligation mixture was diluted (1:10), and directly amplified in a total volume of 20 μL with primer Mse I-N. The product from this step was mixed 1 μL (about 20 pmol) of a 5′-biotinylated (AC)10 oligonucleotide probe in a total volume of 40 μL  at 68 °C for 1 h. The DNA fragment (AC)10 complex were obtained by adsorption of streptavidin and separated by a magnetic field from the hybridization buffer. The complex fragments were ligated into PMD19-T vector and transformed into competent cells (DH5α). Cells were plated on “blue-white” of Luria-Bertani plates. In total, 384 positive colonies were selected by polymerase chain reaction using nonbiotinylated (AC)10 probe primer and universal M13 primers. Those that produced a two-band pattern in agarose electrophoresis were considered to contain a microsatellite repeat.Forty-eight individuals  along with Rox GS350 size standard, and analyzed with GENEMARKER .For the microsatellites sequences containing adequate flanking regions, PCR primers were designed using CID software . From thThe number of alleles at each polymorphic locus, their size range and observed and expected heterozygosities were calculated using CERVUS 3.0 software . DeviatiDetails of the microsatellite loci and variability measures across 48 individuals of the Chinese cobra are summarized in Tests for departure from HWE and for LD were conducted for each of the two populations separately. After sequential Bonferroni correction , none ofP < 0.001) proportion (16.0%) of the total variation in the microsatellite DNA data were attributable to differences among populations, indicating geographical structuring and restricted gene flow. It could be attributable to the Wuyi mountains in the area having a sufficiently isolating effect to significantly reduce gene flow (see P < 0.001) proportion of variation also occurred within populations (84.0%). Previous work based on data with the mitochondrial control region sequences of the Chinese cobra in Taiwan showed low Nm values (0.31–2.00) between populations, indicating low levels of gene flow [Nm (1.31) value between the two populations from mainland China. The results of AMOVA and the low Nm value between the two populations indicated that the Yong’an and Ganzhou populations should be treated as distinct ESUs. Given the existence of distinct ESUs, reintroducing confiscated cobras from the illegal trade back into the wild should be conducted with caution to prevent artificial gene flow.AMOVA indicated that a small but significant (flow see . A signiene flow . Accordiene flow . Our micN. atra especially directed toward a finer-scaled understanding of gene flow, population structure and dispersal dynamics within and between population groups.In conclusion, the microsatellite loci presented in this study will be useful for genetic studies in


Juniperus morrisonicola, a dominant alpine species in Taiwan, and inferred historical, demographic dynamics based on multilocus analyses. Lower levels of genetic diversity in north indicated that populations at higher latitudes were vulnerable to climate change, possibly related to historical alpine glaciers. Neither organellar DNA nor nuclear genes displayed geographical subdivisions, indicating that populations were likely interconnected before migrating upward to isolated mountain peaks, providing low possibilities of seed/pollen dispersal across mountain ranges. Bayesian skyline plots suggested steady population growth of J. morrisonicola followed by recent demographic contraction. In contrast, most lower-elevation plants experienced recent demographic expansion as a result of global warming. The endemic alpine conifer may have experienced dramatic climate changes over the alternation of glacial and interglacial periods, as indicated by a trend showing decreasing genetic diversity with the altitudinal gradient, plus a fact of upward migration.Postglacial climate changes alter geographical distributions and diversity of species. Such ongoing changes often force species to migrate along the latitude/altitude. Altitudinal gradients represent assemblage of environmental, especially climatic, variable factors that influence the plant distributions. Global warming that triggered upward migrations has therefore impacted the alpine plants on an island. In this study, we examined the genetic structure of  As planet Earth faces rising temperatures linking to escalating anthropogenic greenhouse gas emissions, global changes in its climate are greatly influencing the abundance and distribution of species. In contrast to recent global warming, geological evidence shows that ice ages recurred at regular intervals of 100,000 years followed by a 20,000-year warm period (Milankovitch cycles) during the late Pleistocene . In the During the interglacial periods like today, in a subtropical island that were isolated from the adjacent mainland by oceans, with the impacts of increasing temperatures, species previously growing at the mid-elevation habitats were forced to migrate upward and dwell at mountain peaks, resulting in isolated, island-like populations. In contrast, when alpine glaciers grew during glacial periods, previously isolated populations of the alpine species would shift down and connect to each other, forming a meta-population and thus lowering the genetic heterogeneity. Apparently, in contrast to the continental species that experienced north-south migrations over the glacial cycles, the migration of island species, especially those dwelling in alpine regions and hindered by mid-elevation forests, was much more constrained due to oceanic isolation. Accordingly, over glacial-interglacial cycles, the demography of most alpine species on islands periodically fluctuated. Fates of those alpine species were more complicated than expected, given geologically young age of the island with high levels of species diversity/endemism that was originally derived from the adjacent mainland.According to the geological evidence, the island of Taiwan, part of the island-arc system along the western edge of the Pacific Ocean, first emerged from the water when the Eurasian and Pacific plates collided about 9 million years ago (Ma), but it attained its modern shape only 5–6 Ma . Taiwan’Juniperus morrisonicola Hayata , a conifer in the high mountains of Taiwan  was thereby estimated between different mountain ranges.To determine the demographic history that followed the divergence of gram IMa . In thisJ. morrisonicola. The length of the aligned sequences for each locus ranged from 403 to 900 bp .In total, 96 individuals were collected from the Sheishan, Central, and Yushan Mountains of Taiwan, which span 3,200 to 3,952 m above the sea level (a.s.l.) . Sequenco 900 bp . Haplotyonicola.  For orgaL spacer . NH popuJ. morrisonicola  displayed the greatest value of FCT and maximal variance, although nonsignificant . The groups for K = 2 did not match the geographical distributions, with the TK population forming one group and the remaining forming the other group. The SAMOVA of mtDNA sequences also revealed the greatest FCT value and a statistically maximal variance between groups at K = 2 , whereas without matching any geographical distribution. The pattern for the SAMOVA of nuclear sequences also suggested K = 2, with the SS population differentiated from all others. In contrast, the microsatellites revealed a pattern different from the sequence data. In total, 8 groups were identified, with low correspondence to the geographical distribution  and K = 6 (ΔK = 2.0916), we assigned the proportion of each individual in each population among 3 and 6 clusters, respectively  and the effective number of migrants per generation (m) for the comparisons between mountains were indicated  was larger than that of the Sheishan and the Yushan Mountains. For the historical gene flow, Yushan Mountains to Central Mountains (4.05) was highest, followed by from Yushan to Sheishan (3.64), from Central to Sheishan (3.54), and from Sheishan to Central (1.27)  . ResultsD statistic yielded negative values for all loci, except for Pgi. Nevertheless, only Chs, Maldehy, and Myb loci showed significant results. At the population level, values for most populations were negative but nonsignificant, with an exception in populations of the CMR at the Chs and Maldehy loci , corresponding to the alpine glacier development in Taiwan [J. morrisonicola, we divided the conifer into two groups, i.e., the northern group with populations northern to SC, where the southern limit of alpine glacier occurred, vs. southern group with the remaining populations of TK and KS. Interestingly, demographic analyses revealed that the northern populations may have experienced demographic shrinkage after 1 Ma, whereas southern population expanded simultaneously, implying that the southern populations might have originated from some retreated populations as the extremely global cooling occurred during late Pleistocene (Juniperus populations.The Bayesian skyline plots (BSP) were used to uncover the demographic histories of sonicola . Till 3 n Taiwan –11  [P. luchuensis complex in East Asia  [J. morrisonicola based on organellar and nuclear markers  than J. thurifera, an endemic tree in the western Mediterranean basin (Ho = 0.773–0.822) [J. morrisonicola  , as well6–0.033) , much lo markers . We alsoPgi loci . Neverthis study –57. Besi3–0.822) . In addisonicola , suggest studies –60. The J. morrisonicola showed population expansion before the onset of MPT, and then quickly shrunk especially during 0.55–0.24 Ma, with a statistical support across the 95% confidence interval. This result suggested that alpine glaciers in Taiwan might have been developed as the climate change during MPT. In Taiwan, glacial remains could be observed at several high mountains some 10,000 years ago, corresponding to the Younger Dryas period [J. morrisonicola with lower levels of genetic polymorphisms, especially those inhabiting mountaintops, faced a higher risk of extinction. For other alpine R. pseudochrysanthum complex in Taiwan, the northern populations had lower level of genetic variations than southern ones [J. morrisonicola showed lower fecundity of seedling in the field [C. glauca, a species distributed on lowland mountain peaks  at 0.9 Ma led to ice ages with 100,000-year cycles . MPT inis period . At thats period . As Kuanern ones . Comparehe field , suggestin peaks . Interesevations . AccordiJ. morrisonicola might be threatened by the historical alpine glaciers. The surviving populations might have been shaped by local adaptation, range shifts, and other stochastic factors [-1 during the last century, in parallel with rising temperatures in the region. Responding to the increasing temperatures, migration of alpine species at local peaks would be largely constrained, inevitably resulting in high rates of extinction [R. pseudochrysanthum complex, and that higher-elevation populations had lower effective population sizes than lower-elevation ones, and northern populations also had lower level of genetic diversity than southern ones [J. morrisonicola was long enough, low levels of genetic diversity and high levels of genetic differentiation among mountain ranges would be expected, due to small, isolated and fragmented patches of J. morrisonicola.Here, we showed that  factors –69. Of t factors , which i factors , elevati factors –74. In T factors  found thtinction . A previern ones . If the J. morrisonicola, valleys and high mountain ridges could demarcate the plants’ habitats and might consequently impede gene flow among plant populations and opportunities to colonize new habitats [J. morrisonicola, only about 200 generations have been completed. Given such a short time for isolation between populations, incomplete lineage sorting would lead to maintenance of ancestral polymorphisms within populations [Rapid climate change may also act as a potent agent of natural selection within populations, which in combination with habitat fragmentation alters population genetic structure . For alphabitats . Unexpeculations , explainJ. communis [J. excelsa [J. morrisonicola in different mountain ranges grow in isolated and fragmented patches. These results suggested that frequent gene flow might have occurred during the glacial maxima, as the alpine populations shifted downward/southward and connected to each other. As recent gene flow was likely hindered among island-like populations, the trend showing decreasing nucleotide diversity along with increasing altitudes implied population shrinkage in this alpine species. A similar scenario was also found for Rhododendron pseudochrysanthum, another alpine plant in Taiwan [On the other hand, the IMa analyses revealed non-zero, historical migration among mountain ranges . Here, ccommunis  and J. e excelsa . Today, n Taiwan .J. morrisonicola decreases with increasing altitudinal gradients. The northern populations at high latitudes were less genetically polymorphic at nuclear and organellar markers than southern ones, suggesting that the development of alpine glaciers had likely led to the loss of genetic polymorphisms. In addition to the effects of incomplete lineage sorting, high rates of historical gene flow via pollen and seeds could also have resulted in the low levels of genetic differentiation among Juniperus populations. In contrast, microsatellites supported some levels of genetic differentiation across mountain ranges. Our analyses revealed a scenario of the initial colonization during the early Pleistocene, followed by steady population growth until the approaching of the ice age, which brought the alternation of glacial and interglacial periods and turned the populations into a rapid demographic contraction. In contrast, most other species at lower elevations of Taiwan experienced recent demographic expansion. Apparently, these climate changes had significant impacts on the demography of J. morrisonicola, as well as other alpine conifers, such as Abies, on this island. Nevertheless, these populations should not be considered as a dead-end destined for deterministic extinction and perhaps as a focus of conservation efforts.In this study, we found that genetic diversity of populations in S1 FigtrnS-trnG; (B) trnT-trnL; (C) coxI; (D) coxIII; (E) Chs; (F) Maldehy; (G) Myb; (H) Needly; (I) Pgi.The phylogeny based on haplotype sequences were reconstructed with MEGA 5. Bootstrap values are indicated at nodes. (A) (PDF)Click here for additional data file.S2 FigtrnS-trnG; (B) trnT-trnL; (C) coxI; (D) coxIII; (E) Chs; (F) Maldehy; (G) Myb; (H) Needly; (I) Pgi.(A) (PDF)Click here for additional data file.S3 Figm) for the comparison between mountains. (C) Diagram of migration numbers and effective population sizes for Juniperus morrisonicola. The thickness of the lines corresponds to the fraction of migrating individuals per generation (M), and the area of the circle corresponds to the effective population sizes.(A) effective population sizes (θ), and (B) the effective number of migrants per generation ((PDF)Click here for additional data file.S4 FigThe bold line represents the mean estimation, while the area between dashed lines represents the 95% confidence interval. (A) All populations, (B) northern populations, and (C) southern populations.(PDF)Click here for additional data file.S5 FigX-axis presents number of simulated datasets. Y-axis presents the proportion of supported scenarios. Scenarios are denoted by different colors. (A) Sequence data, (B) microsatellite data.(PDF)Click here for additional data file.S6 FigThe fluctuation in effective population size over time for 14 plant species (a–n) based on previously published DNA sequences . Black l(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.


Zostera marina) populations occupying coastal waters of Alaska are separated by a peninsula and island archipelago into two Large Marine Ecosystems (LMEs). From populations in both LMEs, we characterize genetic diversity, population structure, and polarity in gene flow using nuclear microsatellite fragment and chloroplast and nuclear sequence data. An inverse relationship between genetic diversity and latitude was observed , as was significant genetic partitioning across most sampling sites . Variance in allele frequency was significantly partitioned by region only in cases when a population geographically in the Gulf of Alaska LME (Kinzarof Lagoon) was instead included with populations in the Eastern Bering Sea LME , suggesting gene flow between the two LMEs in this region. Gene flow among locales was rarely symmetrical, with notable exceptions generally following net coastal ocean current direction. Genetic data failed to support recent proposals that multiple Zostera species (i.e. Z. japonica and Z. angustifolia) are codistributed with Z. marina in Alaska. Comparative analyses also failed to support the hypothesis that eelgrass populations in the North Atlantic derived from eelgrass retained in northeastern Pacific Last Glacial Maximum refugia. These data suggest northeastern Pacific populations are derived from populations expanding northward from temperate populations following climate amelioration at the terminus of the last Pleistocene glaciation.Eelgrass ( Zostera marina Linnaeus, SP.PL.2: 968. 1753), a marine angiosperm adapted to the cold waters of the North Atlantic and North Pacific, is the most widely distributed of the 60+ seagrass species. Zostera marina provides valuable habitat for diverse animal assemblages, functioning as an important primary producer and erosion stabilizer in coastal ecosystems. Dramatic declines in seagrasses are documented worldwide over the past three decades [Eelgrass  occurs in Alaskan waters [Z. marina occurs in geographically isolated coastal lagoons in two Large Marine Ecosystems (LMEs) [Coastal Alaska, on the Pacific coast of North America, represents both the northern- and western-most limits of c region , and eelc region ,13. Desp locales , and tha species  occurs i species  suggestsn waters . Along ts (LMEs) , the Eass (LMEs) ,13,19. Ds (LMEs)   , Califors (LMEs) ,21), ands (LMEs) . Howevers (LMEs) ) will cos (LMEs)  and oil s (LMEs) ) as wells (LMEs) ,26, are Z. marina collected from Atka, its presence there could signal a phylogeographic connection with eelgrass populations in Eurasia.Eelgrass populations along the Alaska Peninsula  and the Z. marina along the southern (Pacific coast) of the Alaska Peninsula (part of the GoA-LME) are separated geographically from populations along the northern coast of the peninsula (part of the EBS-LME), and exposed to different current regimes and environmental conditions. Differences in gene flow polarity among populations of marine organisms in the different LMEs may reflect the different ocean current circulation patterns. On the Pacific side of the peninsula, the Alaska Stream, flows westward along the southern portion of the Alaska Peninsula and represents the northern boundary current of the anticyclonic Pacific subarctic gyre  in the Bering Sea basin ; the AleZ. marina populations elsewhere [Z. marina’s range when compared to temperate populations, northern latitude populations along the North Pacific coast of North America flower less frequently than at southern latitudes [Ocean currents, oceanographic mixing patterns, geographic barriers, and distance all influence eelgrass distribution and apparently play a role in the differentiation of lsewhere ,21,36–39lsewhere  suggest lsewhere ,41, displsewhere  and seedlsewhere  is typicatitudes . Thus, latitudes   and the nuclear 5.8S rRNA gene and associated internal transcribed spacers, ITS-1 and ITS-2, we: (i) validate species, given plasticity in morphology within Zostera can confound species determinations [Z. marina along the North Pacific and Bering Sea coasts of Alaska, which are geographically separated by the Alaska Peninsula; (iii) test for association between genetic and geographical distances among populations within the two regions, and (iv) test for polarity of gene flow among populations within the EBS- and GoA-LMEs. Because the population genetic structure of marine angiosperms, as in other species, has been influenced by Pleistocene environmental events [The central aim of this study is to characterize genetic structure in largely undisturbed native populations of inations ,51 leadil events , and becl events , we alsoAll eelgrass samples collected in United States waters were obtained on public access lands, and all researchers sampling in United States waters, including California, received permission for sampling eelgrass from the appropriate state regulatory agencies where required . Eelgrass samples from Yaquina Bay were obtained on public access lands and no permission was required because the plant species is not endangered or protected in the area sampled. In Alaska, permission was also obtained from the specific U. S. Fish and Wildlife Service Refuges for sampling on Refuge lands. Samples in Mexico were collected with permission from SEMARNAT , the federal agency responsible for promoting the protection of natural resources in Mexico and the regulatory authority for collecting in Mexico’s intertidal areas. The species is not considered endangered or protected in areas where the sampling occurred in waters of either the United States, or Mexico.Eelgrass meadows from 12 sites along the mid-to-northern Pacific Coast of North America were sampled during summer months between 2000–2006 . EelgrasZ. marina separated by 20–200 m were randomly collected during low tides. For KS, > 250 samples were retrieved from an outboard engine propeller at various sampling sites along a general transect of 2.5 km. Plants were scraped clean of visible epiphytes and invertebrates, blotted dry with paper towels and stored in powdered silica gel until DNA was extracted from leaf tissue. All individuals in each population were sampled within an area smaller than 750,000 m2. This area is much larger than the genetic neighborhood area (500–1600 m2) for eelgrass suggested by Ruckelshaus [At all but one study site (KS), eight to sixty individuals of kelshaus ,55 and Rkelshaus  but is nkelshaus .Zostera chloroplast maturase K (matK) gene and 488 bp of the 5.8S rRNA gene and associated internal transcribed spacers, ITS-1 and ITS-2 (ITS) were collected following methods presented in the literature [matK and ITS from 3–13 individuals per population (except Morro Bay for ITS) in the other two Pacific Coast LMEs of North America: 1) the California Current LME (CC-LME), including Puget Sound, Washington (PS), Monterey (MON), Humboldt (HUM), and Morro bays, California, and four lagoons along the coast of Baja California Peninsula . All maresearch  and sequresearch ,57) fromresearch ,58. For research ) were alMatK and ITS sequences were collapsed into haplotypes using DNACollapser [Zostera occurs in Alaska and to verify that our analyses were from populations of Zostera marina, we used the BLASTN algorithm [matK and ITS haplotypes to data from different Zostera species deposited on NCBI ; and UAM Herb:40475, collected from Cowpack Lagoon on the Seward Peninsula (EBS-LME). We note that UAM Herb:40475, previously determined to be Z. marina, was annotated and ascribed in 2006 to Z. angustifolia. Unfortunately, no sequence data for ITS or matK attributed to Z. angustifolia are archived in GenBank. Nevertheless, we assumed that if two different Zostera species occupied habitats within the two high latitude LMEs, and Z. angustifolia was indeed a discrete lineage and one of those species, we would observe 1) diagnostic differences between UAM Herb: 40475 (cf. Z. angustifolia) and UAM Herb: 43460 (Z. marina) at the ITS and matK genes, and 2) among sequences assayed from individuals representing our target populations. Further, 3) if sampled ‘populations’ actually comprised individuals from different species, we should observe significant linkage disequilibrium (and likely deviations from Hardy Weinberg proportions) across most or all microsatellite loci collected across individuals sampled from within the mixed ‘population’ [ollapser . To addrlgorithm  to compaCBI see ,61,62). ,62. MatKCBI . HomoloB125358; ) were inID and PIDsib; [Details of analyses to assess levels of genetic diversity at microsatellite loci are provided in  PIDsib; ), using  PIDsib; , and to  PIDsib; ,71. In a PIDsib; .θ, [ρ, [Details of analyses to assess levels of population and regional structure are provided in θ, ; ρ, [74,θ, [ρ, ), employθ, [ρ, –78. Signθ, [ρ, , using Gθ, [ρ,  and judgadegenet [To further investigate the pattern of population structuring, we also applied a Bayesian clustering approach . Data weadegenet ,83. Optiadegenet .We employed hierarchical analyses of molecular variance (AMOVA) to test the hypothesized regional relationship between the GoA-LME and EBS-LME populations relative to a suite of alternative hypotheses, quantifying variance at four hierarchical levels: 1) between regions (EBS-LME and GoA-LME), 2) among populations within regions, 3) among individuals within populations, and 4) within individuals. Statistical significance of variance measures was assessed via non-parametric permutation .CE), evaluating confidence of the tree topology via bootstrapping over loci (1000 replicates) using POPULATIONS 1.2.30 [We examined genetic relationships among populations by creating a neighbor-joining tree , inferreS 1.2.30  and visuS 1.2.30 . We usedS 1.2.30  to compaS 1.2.30 , testingS 1.2.30  for popuE) data and standardized allelic richness (AR [http://dx.doi.org/10.5066/F7GQ6VTK), and all HE values were derived from genets.To determine whether there is an inverse relationship between genetic diversity and latitude, as expected if contemporary populations of eelgrass in the North Pacific colonized from temperate or southern refugia following climate amelioration at the Pleistocene/Holocene boundary, we performed a linear regression analysis fitting two commonly-used measures of genetic diversity: expected heterozygosity , to , to E) dness . Data fm) among populations, assuming a constant per-locus mutation rate (μ). To test whether net current direction can predict localized direction of gene flow, we performed MIGRATE analyses separately for Bering Sea and Pacific coast populations, estimating full models, Θ = 4Neμ  demonstrated we sampled and extracted genomic DNA from Z. marina and not the invasive Z. japonica, which may occur in Alaskan coastal waters . We observed two ITS haplotypes  assayed, as well as in Japan , which differed at up to two segregating sites across four variant nucleotide sites , were observed across the species’ North American Pacific coast distribution (Z. angustifolia), were characterized by a single matK variant .There were 61 pairwise instances in which we found that more than one sample yielded an identical 10-locus genotypes . In no instance were identical genotypes observed in samples from across two or more populations. Genotypic richness was lowest in UNGA and PWS . We dropP < 1.0) for at least one locus; only KIL, PWS and YAB were polymorphic at all loci  than EBS-LME populations (0.29). Overall HO was 0.33; again, average HO was higher in GoA-LME (0.35) than EBS-LME (0.26) populations.Number of alleles detected per locus ranged from four  to 43 (CT-17) and the mean number of alleles per locus per population  ranged from 2.2 to 7.6 . All EBSall loci . Allelicall loci ; allelicall loci . Overall0 at YAB . OverallP = 0.003) due to significant heterozygote deficit at one locus , and TOG (P < 0.0001) due to significant heterozygote deficit at two loci . No significant inbreeding values were observed across loci overall, after correction for multiple tests . Exact tests among the 382 possible pairwise comparisons demonstrated significant linkage disequilibrium (P < 0.005) in 15 cases . This is lower than the number of spurious results expected for 382 pairwise comparisons (19.1), although more significant pairwise comparisons were observed (4) than expected spuriously (2.25) within YAB. The global test across populations, for all 45 pairings of loci, was not significant (P > 0.087). Given the general adherence to HWE expectations and lack of significant linkage disequilibrium, coupled with the results of the sequence analysis of chloroplast and nuclear loci, we conclude that our populations are comprised of Z. marina and do not represent either Z. japonica, or Z. angustifolia. All data from genets and across loci were retained for analysis of population structure.The global test revealed significant departures from HWE in 2 of the 12 populations: SCC ; values of ρ were higher . Pairwise population differentiation estimated by θST among all pairs of populations ranged from 0.043 to 0.592 (θST) was significantly different from zero among all North Pacific coast population pairwise comparisons (excluding YAB) except one: NAK–AKSI  and North Pacific , but overall ρ was higher in the EBS-LME populations ρEBS = 0.359; ρNPacific = 0.322). In 37 pairwise comparisons, ρST values were greater than θST values; there were 29 instances of the reciprocal (θST (0.592) value among all North Pacific Alaskan populations occurred between WB and KS; the greatest ρST value (0.795) was between KS and SCC  and for all pairwise population comparisons , except AKSI and UNGA .Results of the hierarchical AMOVA  of the total genetic variation could be attributed to variation between the two biogeographical regions (GoA-LME vs. EBS-LME), while 25.2%  of the variance could be explained by differences among populations within the two regions , ρp was not significant for any between-region test . Bayesian clustering confirmed trends of significant population structuring observed with pairwise θST comparisons: when analyses were not constrained to number of clusters, the highest posterior probability was obtained for K = 9 (Ln(X/K) = -7670.6, LnP = 1.0; We observed significant differentiation based on variance of allele frequency overall , however this model did not perform significantly better than the null model of 12 populations , and in fact indicated 9–13, 17, and 20 cluster models did not perform significantly worse than the optimal model. Using 15 inferred clusters, YAB and WB were largely recovered as inferred populations 7 and 15, while other populations were divided among many inferred groupings with shared original sample populations, including SCC in 2, 4–6, and 8–10, KIL in 1, 4–6, 8–10, and 12 and IZL in 2, 4–6, and 8–10  occurred between populations in the EBS-LME (IZL–SCC: DCE = 0.172); the largest occurred between a GoA-LME and EBS-LME population . The neighbor-joining(DCE) tree revealed two main clusters , or among populations within regions . However, significant correlations were observed between log-transformed genetic distances and geographic distances when all populations were pooled overall  and for populations within the EBS-LME .We found no significant correlation between Rousset’s genetic  and geogE and AR correlated inversely with latitude, explaining 73.8% (HE) and 32.7% (AR) of the variance in percentage  = -inf; LnL(full) = -1153.68; LRT = inf, df = 4, P < 0.00001). Maximum likelihood estimates based on Markov Chain Monte Carlo simulations suggest that the direction of gene flow among populations on the Pacific coast is predominantly westward , and a 7-population geographic model for GoA-LME populations , and based on our inference of partial genetic partitioning between regions and to test for polarity associated with LME-specific current patterns. 24–1.074  Tables. westward . Howeverwestward  showed ewestward . Similarwestward , Fig 6.Z. marina in the extreme high latitude portion of its Northeast Pacific distribution. As such, it provides a foundational assessment of genetic diversity of eelgrass in the region. Fundamental to assessing genetic structure of Z. marina populations, however, is ensuring the samples representing locales within the Northeast Pacific are indeed Z. marina, particularly given the proposal that Alaska hosts more than one species of Zostera [Z. marina, which demonstrates large phenotypic plasticity [Zostera species include variation in leaf morphology, particularly leaf width. As width of leaves are influenced by both genetic and environmental factors [This study represents the first characterization of macrogeographic population genetic parameters among undisturbed meadows of  Zostera . The abi Zostera , for cla Zostera , and robasticity ,100, con factors , they ea factors ,51.matK genes has clarified species relationships within Zostera [Z. marina and Z. japonica [Z. japonica nuclear ITS and chloroplast matK sequences among the samples from Nakwasina and Crab Bay in the Alexander Archipelago  that occurs in areas with strong fluctuations in environmental conditions such as salinity, temperature, pH, and oxygen concentration at low tide. Similar to Becheler et al. [Z. angustifolia’ from Z. marina in Brittany, we observed no genetic signatures in samples collected in Alaska that were consistent with the presence a ‘Z. angustifolia’ taxon that differed from Z. marinaFurther, based on variation in leaf morphology among a, Elven  considera. Elven  suggestsof fruit –104), cibspecies  or a disbspecies ,106, oth. marina –109. Rec. marina  demonstrr et al. , who wasmatK sequences assayed from among our Alaskan samples were identical to previous assays of Z. marina [matK sequences attributed to the disputed taxon Z. angustifolia are archived in public databases, so inference using data from those loci was not possible. Nevertheless, we failed to find any differences in ITS or matK sequences between vouchered specimens determined to be Z. marina, and the specimen annotated in UAM as Z. angustifolia (UAM Herb:40475) or among individuals representing Alaskan populations within the distributional ranges proposed by Elven [Z. angustifolia and Z. marina. In future situations in which leaf size is a determining factor in Zostera species determination, we recommend the use of molecular data in tandem with morphological data to ensure accurate taxonomic classification of specimens; this is particularly important in cases that expand the distribution of a species.The nuclear ITS and chloroplast . marina . Unfortuby Elven  for Z. aMicrosatellite markers are of limited use for determining species –112, dueZ. angustifolia’ represents an ecotype that manifests ‘above a perturbation threshold’ (p. 2402) in extreme expression of phenotypic plasticity and facilitates survival of Z. marina in stressful and fluctuating environments. Although many  of the locales assayed in our study arguably fall under the category of “stressful and fluctuating,” our research was not designed to specifically test their hypothesis. Nevertheless, our results are in accord with Becheler et al. [Z. marina and Z. angustifolia) were sampled from the same locale. Thus, it is possible that specimens recently attributed to Z. angustifolia in Alaska are, as in Brittany, an ecotype of Z. marina, rather than a discrete species. Combined, our data suggest that, currently, a single species of Zostera, Z. marina, occurs in Alaska, and as elsewhere is characterized by wide phenotypic plasticity even within the same sampling locale (i.e. Wide Bay). Certainly, however, given the importance of comprehensive sampling to uncover the presence of rare, cryptic species or recent invaders, further sampling and ongoing monitoring is warranted.We found no evidence from the microsatellite analyses suggesting more than one species occurred among our samples; we found no global or population-wide signature of linkage disequilibrium or deviations from HWE in microsatellite loci, expected if our population samples included individuals belonging to different species. Becheler et al.  suggester et al.  in that ST (ρ) values are larger than overall FST (θ) values, and for 54% of all pairwise comparisons, ρ values are larger, and typically substantially so, than θ values. This pattern is repeated within regions: ρST values were greater than θST values in 11 of 21 pairwise population comparisons within the GoA-LME, and in eight of the 10 pairwise population comparisons within the EBS-LME. Interestingly however, θST exceeded ρST values in a small majority of between-region comparisons (53%), involving mostly populations occurring near the tip of the Alaska Peninsula.Significant within-species structuring was evident among almost all locales studied, as demonstrated by the analyses of variance in allele frequencies using traditional F-statistics as well as Bayesian clustering analyses, with at least nine clusters among the 12 locales analyzed. Further, this divergence is in general not extremely recent ,116; RSTZ. marina along most of the north Pacific coast of North America, and the observation that movement of dislodged vegetative material is the main adaptation the fruits have for dispersal [Z. marina populations and the success of restoration programs. However, most of these studies have been conducted in areas already heavily impacted by anthropogenic activity, which can increase population isolation via fragmentation [Studies of eelgrass populations in the northwestern North Pacific , along tispersal ,107, a fentation , complicθp value was observed when populations were generally partitioned into three regional groupings, corresponding to 1) populations in the Bering Sea ; 2) populations along the southern portion of the Alaska Peninsula; and 3) populations farther east, along the Gulf of Alaska and the northernmost Pacific coast (Alexander Archipelago). However, given the close relationship of KIL with Bering Sea populations, this boundary appears to be semipermeable for eelgrass populations around the tip of the Alaska Peninsula, where currents flow from the GoA-LME to the EBS-LME. Nevertheless, under the SMM, these partitions were not identified as significant, suggesting observed differentiation among these three regions is an evolutionarily shallow phenomenon, with connectivity still maintained by low levels of gene flow [Although we observed significant genetic structure among the high latitude populations in both the EBS- and GoA-LMEs, regional (inter-LME) differentiation was only significant if we forced KIL, located along the Pacific coast of the western Alaska Peninsula and therefore within the GoA-LME, to group with populations in the EBS-LME , which feed exclusively on eelgrass prior to embarking on long-distance flights to wintering areas in Mexico [In distance , and gendistance . Gene fldistance , and as distance –129. Izen Mexico ,131, andn Mexico ,132. Thun Mexico ,132, andZ. marina along the northern Gulf and Bering Sea coasts of Alaska are lower relative to those observed at the same loci in eelgrass populations to the south. For example, average heterozygosity (HE) in eelgrass populations in Baja California was approximately 0.6, and mean number of alleles (A) approximately 5.5 [Z. marina in the north Atlantic and Europe [Z. marina and another proposed species, Z. pacifica. The genetic criterion used by Coyer et al. [Z. pacifica (and not based on any diagnostic differences in sequences from the nuclear and chloroplast genome). The potential presence of another species in that region cannot account for our observation of increased genetic diversity at lower latitudes; all genotypes from all individuals used in our comparative analyses, including those from California (MON), amplified a product at CT20. As well, we observed no global signal of linkage disequilibrium, expected in cases of recent introgression [http://dx.doi.org/10.5066/F7GQ6VTK).Other studies ,117,133 tely 5.5  and thosd Europe  and Japad Europe . Howeverd Europe  and Wylld Europe ; thus wed Europe  posit thr et al.  to distigression , within gression ; MON, htPosidonia oceanica L., an endemic Mediterranean seagrass [P. oceanica, Z. marina is characterized by a clonal reproduction habit, reproducing in two ways: sexually by means of flowers , and asneoecius . While bic coast , in Alasic coast .Z. marina demonstrate a remarkable level of morphological and physiological variability, and leaf width and length often correlates with habitat [Z. angustifolia (UAM Herb: 40475) based on morphological characters (discussed earlier) nevertheless possesses identical chloroplast and nuclear sequences with Z. marina from elsewhere in the North Pacific, suggesting the specimen is actually Z. marina. Here, we found no evidence of large genetic differences among individuals taken from the same site, but at different locations within the tidal zone. Results from our population genetics assessment–i.e. lower to moderate levels of genetic diversity, and relatively higher levels of clonality in northern when compared to southern populations  to from 700 to 15,000 m-2 at IZL [We have already pointed out that different populations of  habitat ,138,139.ulations . Thus seulations , reprodu Quintin  are lowe2 at IZL . Thus th2 at IZL .Phyllospadix and Zostera) species [Zostera species to between three and six million years ago (mya), based on an ITS clock for algae and other green plants [Z. marina originated in the Pacific between eight and 20 mya, during the Neogene epoch. Olsen et al. [Z. marina and observed higher levels of genetic diversity within the Pacific populations. Although eastern Pacific and western Atlantic populations appear to be connected, western Pacific and eastern Atlantic populations of eelgrass appear less so, prompting Olsen et al. [Z. marina via a trans-Arctic connection, as hypothesized for a number of marine taxa . Howeveaxa , includmatK and ITS genes in both high latitude LMEs . The first is suggested by the distribution of matK haplotypes that corresponds to a break, well-supported based on distribution of other marine species, near Cape Mendocino in northern California [Z. marina to these biogeographic breaks.Marko  posits ttudy and  fails tolifornia . The seclifornia , as welllifornia . ClearlymatK haplotype (matK2), which is fixed in Alaskan populations, to be present in the North Atlantic. To date, variant matK2 , but not in Alaska, are identical to those in samples collected from Atlantic and, at lower frequency, in Japanese waters [We suggest that extant populations in the Northeast Pacific likely reflect a leading edge northward Holocene expansion of populations held in temperate LGM refugial populations , that, to date, appear to have reached only as far north as 66.52° N , the northernmost documented occurrence of the species in the Northeast Pacific. Olsen et al.  cite theo et al. ) has note waters ,96. ThusS1 FigZ. marina samples collected from locales in the EBS-, GoA-, CC- and GoC-LMEs along the Pacific Coast of North America, and Japan. GenBank accession numbers containing sequence data from a representative of each haplotype are provided, selected from GenBank accession numbers KU704921-KU705084 (matK), and KU704817-KU704920 (ITS). Asterisks (*) indicate locales for which sequence data from Talbot et al. [t et al.  are incl(TIF)Click here for additional data file.S2 Fig(A) 9 genetic clusters estimated from the microsatellite data under admixture models for K = 1–20, and clusters when analyses were constrained to partition clusters when (B) K = 2, (C) K = 3, and (D) K = 4. Individual samples are represented by a single vertical line along the x-axis, according to sampling locale, which are delineated from other sampling locales by a black vertical line.(TIF)Click here for additional data file.S3 Figadegenet (k = 12) [(A) Comparison of sampled populations to the optimal number of clusters in these data. Inferred by k-means (k = 15). (B) Plot of membership probability of each individual to each sampled population using DAPC. Implemented in (k = 12) .(TIF)Click here for additional data file.S1 Methods(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.