Helosciadium repens (Jacq.) W.D.J. Koch is threatened by genetic erosion. It is a Crop Wild Relative (CWR) of celery and celeriac and a potentially valuable genetic resource for plant breeding. The objective of this study was the analysis of distribution of genetic diversity with a set of selected populations in Germany. The results of the genetic analysis and data obtained during the site visits were used to identify a subset which was chosen to best represent the genetic diversity of H. repens in Germany. The chance of long‐term conservation by securing the identified populations in genetic reserves is distinctly possible.j was calculated to designate a subset of populations chosen to best represent the overall genetic diversity. Entry 18R (Δ18R = 0.2498) represented its pooled remainder the best, while entry 22R (Δ22R = 0.4902) differed the most from its complement.Seven hundred and fifteen individuals from 27 sites were assessed using six simple sequence repeat markers. Discriminant analysis of principal components was used to identify six clusters of genetically similar individuals. The complementary compositional genetic differentiation ΔBased on the results of the genetic analysis and information regarding the current conservation status, 14 most appropriate wild populations for potential genetic reserve were identified. The used markers display a low level of genetic variation between the analyzed populations, and a split between Northern and Southern populations was observed.H. repens.CWR species are essential genetic resources for plant breeding and food security. However, 11.5% of the European CWRs are threatened. Therefore, it is of utmost importance to determine their genetic compositions. These insights will provide the fundamental basis for making crucial decisions concerning future conservation strategies for  Fourteen most appropriate wild populations were successfully identified with SSRs, low level of genetic variation was estimated, and a split between Northern and Southern German populations was observed. They often contain valuable resistance genes and other useful genetic traits and are thus essential resources for plant breeding  als Bestandteil eines Bundesweiten Netzwerkes genetischer Erhaltungsgebiete in Deutschland‐ GE‐Sell” (Genetic Nature Reserves for Wild Celery (Apium and Helosciadium) as Part of a National Network in Germany) is one of the few projects, attempting to establish genetic reserves in practice  W.D.J. Koch, Helosciadium inundatum (Jacq.) W.D.J. Koch and Helosciadium nodiflorum (Jacq.) W.D.J. Koch. Pink et al.  as candidates for genetic reserves of one of the CWR of H. repens in Germany with microsatellites (SSR). To understand the contribution of each population to the overall diversity within the entire set, we analyzed the genetic diversity and composition of 27 occurrences. Finally, MAWPs were chosen, using criteria based on the quality standards proposed by Iriondo et al.  and data from local botanical institutes. The heterogeneous data set was homogenized in order to make the records comparable. The inventory contained 1,040 entries, of which 78 populations were selected for a preliminary assessment. Populations were selected based on the following criteria. (a) The selection must include all kinds of habitats where the species was found. Therefore, populations were chosen from different eco‐geographic units of the second‐order (EGUs) according to Meynen and Schmithüsen (A list of distribution data of mithüsen  to captumithüsen .(b) In some cases, the data from the agencies included possible immediate threats in the comments field of the database excerpts. Those populations were not taken into account, as the risk of these becoming extinct in the near future was too high. (c) The populations should have at least a population size of 30 individuals. (d) Also, if possible, populations existing in nature reserves (NRs) were selected. These sites already provide the infrastructure that can be used to improve the conservation of the CWR target taxon. In comparison to areas without a conservation status, NRs can sustain a genetic reserve for a more extended period.http://vm323.rz.uos.de/mapportal/pages/auswahl_gesell.php.Permission from authorities and property owners was obtained. The sites were visited in the year 2015 in order to assess the suitability of the location and the conservation status of the occurrence. In some cases, in Bavaria and Mecklenburg‐West Pomerania, current monitoring data already existed and was used for further assessment. The collected data were stored in the GE‐Sell database available online at The comparison of the first assessment with the date from the EAs indicated annual variations in population sizes. Locations with high population sizes were preferred to avoid traveling to sites with temporarily small population sizes. If the preliminary assessment in 2015, or the second visit in 2016 revealed immediate threats, the populations were not taken into account. Out of the confirmed occurrences, 27 populations were selected for sampling and genetic analysis in 2016 . The supernatant was then used in all further stages according to the instructions of the manufacturer. Sorbent is activated carbon with a high adsorption capacity. As it does not bind the DNA, it is therefore ideal for removing metabolites which potentially inhibit PCR reactions . Isolated DNA was diluted 1:20 and then used directly for PCR amplification.Leaves from up to 30 individuals of 27 ns Table  were colns Table . If a po2.3H. repens. All microsatellites were repeats of dinucleotides of various lengths. Forward primers of all sets were labeled with fluorescence dyes HEX or FAM , 0.4 dNTP mix (10 mM), 0.6 µl of each primer (0.3 µM), 1 µl DNA, and 0.1 µl FIREPol Taq‐polymerase (Solis BioDyne). PCRs were carried out under the following touchdown PCR conditions for all loci: 94°5′30″, 56°45″, 72°1′ 6  31 72°10′, 12°5′. Samples which failed in the first run were rerun using the 10 µl Biozym red HS Taq master mix (Biozym Scientific GmbH), 0.6 µl of each primer (0.3 µM), 1 µl DNA in a final volume of 20 µl. PCR products were checked on an agarose gel before being sent to TraitGenics for fragment analysis. The primer test revealed that eleven out of 49 SSR primer sets produce suitable products for further analysis. However, only six of these amplified regions across all populations successfully and were used in the further analysis. Individuals which failed to amplify in one or more primer sets were excluded.A test sample set was designed based on three populations . From each population, ten individuals were used. Microsatellite amplification was carried out for all 49 primer sets in a final volume of 20 µl, containing 1 µl DMSO, 2 µl 10× reaction buffer B (Solis BioDyne), 1.6 µl MgClThe software Genemapper v5.0  was used to evaluate the chromatograms by identifying all microsatellite alleles and their respective sizes. Each call was checked manually and corrected if necessary. Primer sets which successfully amplified polymorphic products in all test populations were used to analyze all 27 populations.2.5Ho), and expected heterozygosity (He) using 104 permutations and 5,000 bootstraps pseudo‐replicates. The SSR data was converted manually into a genepop format and loaded in R using the package adegenet for further analyses  was calculated with the software Fstat2.9.3.2 . A population with Δj = 0 population represents exactly its complement, while the genetic composition of a population with Δj = 1 is entirely different from its complement. ΔSD quantifies the average degree to which all populations differ from their complements .The measure Δ is free of model assumptions such as the presence of large, random mating populations in the Hardy–Weinberg equilibrium  and the function optim.a.score to find the optimal number of principal components. Additionally, another independent nonmodel approach was used to confirm the result. This method was based on the replicated nonhierarchical K‐means clustering  for each of the assumed groups between two and 30. The intergroup inertia was recorded as a proxy of clustering accuracy, and the delta K values were calculated  implemented in the R package http://www.naturalearthdata.com) provided the free vector and raster map data.Maps were drawn with QGIS‐2.8.1‐Wien  In every EGU represented in the set of 27 sites, at least one genetic reserve should be established to maximize the chance of capturing adaptive trait variation. To this end, one population was selected from each EGU. (b) Large population size was preferred over smaller population size. (c) As genetic reserve management relies on the support of local nature conservation agencies, other institutional stakeholders and volunteers, organizational and social aspects were also taken into account. (d) If the collectors found an immediate threat during the collection phase in 2016, the population in question was not considered as a MAWP. (e) Populations with an existing management plan, regardless of their conservation status, were given priority.The results from DifferInt were used to guide the selection of populations for genetic reserves. As means for conservation are always limited, the procedure was started with the population which had the lowest and highest Δ33.1H. repens populations. The largest population in MV was 3R with a distribution area exceeding 12,000 m2. Helosciadium repens is often found in patches rather than in continuous populations. Considering this, 12R with 400 m2 of a populated area was the largest population in the whole Northern area. In BY, the largest population was 22R with a population area of 350 m2, distributed over an area of 89,000 m2.Of the 78 preliminary assessed sites, 59 contained 3.2o and the He of each locus ranged from 0.1748 to 0.2755 (AXM0087 and AXM0105) and 0.2756 to 0.6389 (AXM0087 and AXM090), respectively. Twenty‐two populations were not in the HWE  to 0.667 . According to the FIS Index, population 23R showed panmixia (Table F varied between −0.505 (25R) and 0.656 (5R). Out of the 27 populations, 16 exhibited inbreeding .The numbers of alleles per locus ranged from four to nine , and the numbers of alleles per population ranged from six to 21 . The PIC ranged between 0.3646 (AXM0105) and 0.5802 (AXM0090). Out of the 38 distinct alleles, 12 alleles were private and three were rare (Table 3.3The numbers of SLG spanned from eight to 16 per locus (ANM0079 and AXM0105 with the lowest and AXM0090 with the highest count) and ranged from six to 36  in populations. The MLG spanned from one to 29 (13R and 23R with the lowest and 26R with the highest count). Within the whole data set , 68 SLG and 235 MLG were identified. Within populations, some MLGs were found to be duplicated ranging from two to 30 times. Population 13R was composed of only one MLG . In the ∆K versus numbers of groups (K) plot, the value with the highest ∆K was at K = 2. However, a K between two and six was also considered possible  versus number‐of‐clusters plot showed no clear indication of the “true e Figure . TherefoK = 2 the DAPC showed a division of N and S populations (data not shown). Only one population (16R from BY) did not coincide with its geographical distribution . Three populations  also had some individuals (<14%) affiliated with the Southern cluster. In the Southern cluster, there were eight populations with individuals associated with the Northern cluster (between 3% and 48%). For K = 4 and K = 6, the DAPC revealed similar, but more detailed clustering, compared with K = 2 (data for K = 4 not shown). However, with K = 6, only one population did not coincide with its geographical distribution (16R). Therefore, K = 6 was regarded to be the optimal number of clusters  and Western BB (12R) were allocated explicitly to cluster three. The rest of the North German populations were mostly linked to cluster five. Some individuals in a population were not assigned to the same cluster as the rest of the population (7% on average). When they are compared to the N populations, the S populations are more heterogeneous. Nevertheless, some populations from a specific region were allocated to a particular cluster  the regions which were affiliated to specific clusters were mostly overlapping (28% on average). Populations 15R, 18R, 20R, 22R, 26R, 27R, and 28R retrieved relatively high affiliation with more than one cluster. The BY populations can be organized into three groups according to the cluster assignment: East BY with 15R, 26R 27R, central BY with 18R, 21R, 22R, 23R, 25R, and West‐BY with 19R, 20R, 24R, 28R. Occurrences 16R and 20R had a high affiliation to cluster five, and 17R to cluster six. There was no correlation between the clusters and EGUs.3.5Besides the two selected populations based on the results from DifferInt 22R and 18R), populations 1R, 3R, and 5R from MV, 8R from east Muensterland region, 9R from Lower Saxony (NI), 12R and 13R from Brandenburg (BB), and 24R, 26R, and 27R from BY were also selected as MAWPs  the analyzed markers show a low level of genetic variation between populations in Germany. (b) The populations are divided into Northern and Southern populations. (c) MAWPs suited to establish genetic reserves were identified and recommended.Our study presents an analysis of genetic diversity and genetic differentiation based on a set of populations of 4.1SD‐values of the integration level SLG and MLG would be within the 95% confidence interval of all ∆SD‐values generated by the first permutation analysis . Schossau . Spalik, Banasiak, Feist, and Downie  resembles the genetic diversity of all remaining 26 populations better than any other . In Germany, the genetic reserve has no legal status. Long‐term success is highly dependent on the support and active collaboration of local people. Helosciadium repens patchy population structure should be considered when collecting seeds for storage in gene banks. Seeds from every MAWP should be collected for ex situ preservation of genetic diversity in gene banks. We recommend making the samples available for plant breeders and conservationists, as the sustainable use of wild populations is an argument toward investing in further conservation activities. The seeds can be stored in the WEL Gene Bank (National Gene Bank for German Crop Wild Relative Species, Botanical Garden of Osnabrueck, Germany; see Table Our study showed that the eight‐step process proposed by Frese, Bönisch, Herden, et al.  for an  is well None to declare.N.F. and T.H. conceived the ideas. T.H. homogenized the data excerpts did the laboratory work and led the writing of the manuscript. M.B. organized the data excerpts, managed the first and second assessment of the sites, and together with T.H. was involved in the decision process of the MAWPs. All authors contributed critically to the draft.https://doi.org/10.5061/dryad.rr4xgxd5c.This article has been awarded Open Data Badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at  Click here for additional data file. Click here for additional data file. Click here for additional data file.


SLCO1B3 (rs4149117) and CYP3A4 (rs2242480) genes differentiated at the highest level the African group of populations, while NAT2 gene loci  and VKORC1 (rs9923231) differentiated East Asian populations. The VKORC1 rs9923231 was among the investigated loci the one with the largest global minor allele frequency (MAF) range; its MAF ranged from 0.027 in Nigeria to 0.924 in Han Chinese. The distribution of the investigated gene loci positions Roma population within the joined European and South Asian clusters, suggesting that their ADME gene pool is a combination of ancestral (Indian) and more recent (European) surrounding, as it was already implied by other genetic markers. However, when compared to the populations worldwide, the Croatian Roma have extreme MAF values in 10 out of the 95 investigated ADME core gene loci. Among loci which have extraordinary MAFs in Roma population two have strong proof of clinical importance: rs1799853 (CYP2C9) for warfarin dosage, and rs12248560 (CYP2C19) for clopidogrel dosage, efficacy and toxicity. This finding confirms the importance of taking the Roma as well as the other isolated populations`genetic profiles into account in pharmaco-therapeutic practice.The products of the polymorphic ADME genes are involved in Absorption, Distribution, Metabolism, and Excretion of drugs. The pharmacogenetic data have been studied extensively due to their clinical importance in the appropriate drug prescription, but such data from the isolated populations are rather scarce. We analyzed the distribution of 95 polymorphisms in 31 core ADME genes in 20 populations worldwide and in newly genotyped samples from the Roma (Gypsy) population living in Croatia. Global distribution of ADME core gene loci differentiated three major clusters; (1) African, (2) East Asian, and (3) joint European, South Asian and South American cluster. The  Medication efficacy and adverse drug reactions are associated with specific genes’ variants  that areNumerous studies have been published on ADME-related genes' polymorphisms and their clinical importance. Some of them used large panels of genes and/or big samples from large population groups , 4–10, wAlthough today’s state-of-art methodology in personalized medicine is individual genotyping prior to medications, unfortunately this approach has not been routinely applied at points of care and usually follows after an adverse drug effect. Therefore, population ADME genes profiling is useful for clinical practice especially in cases when the population consists of different ancestry groups.It has been estimated that about 15 million of Roma people live worldwide today from whom 10 million reside in Europe. About 40 thousand Roma live in Croatia . HoweverAnthropologically, the Roma are the transnational minority population marked by common Indian ancestry. Various social and economic pressures caused gradual population fragmentation and formation of a complex network of numerous and often endogamous subgroups with specific languages , religions, and socio-cultural characteristics , 20. LasTheir pronounced genetic differences from the majority Croatian population and traces of their ancestral origins have been detected in mitochondrial DNA , Y chromSince isolated populations usually have a unique genetic profile it is important to determine their ADME genes pattern in the context of broader global diversity , 29. TheThe minor allele frequencies (MAFs) and sample sizes as well as the references in addition to the 1000 Genomes for all 95 SNPs used in the this study are presented in the Genetic distance analyses were carried out to quantify genetic differentiation across 21 populations in this study and the dendrogram is reported in The relationship between genetic variation and geographic distance was analyzed using correlation between matrices of genetic and geographic distances. The correlation is positive and significant  indicating isolation by spatial distance at the global scale. Focusing on the Croatian Roma population, their genetic distances from the other 20 populations in this study were plotted against the geographic distances . Roma clThe Principal Component Analysis (PCA) was performed using MAF data for 95 ADME core genes’ loci for 21 populations from various part of the world, including Croatian Roma. PCA revealed six PCs  reflecting the genetic relationships among the populations showing a pattern that is very similar to that obtained by genetic distance dendrogram. PC1  separates four African countries from the rest of the world while PC2  separates four East Asian countries. PC3  separates South Asians from the remaining European-American cluster with the Croatian Roma being intermediate to Europeans and South Asians. The PC4 axis  separates Americans from the European-Roma group and places the Roma population at the top of the positive pole of the axis (while negative pole is represented by Peru). PC5  differentiates European countries (placing at the opposite poles Finland and UK) while PC6  differentiates East Asian populations (opposing Han from Dai Chinese populations).In order to elucidate the most characteristic continental single nucleotide polymorphisms (SNPs) among the core ADME genes’ loci, we performed the gene-oriented Principal Component Analysis (gPCA). The gPCA revealed three significant components: gPC1  was defined by the global range in MAF values (i.e. it contains not population-specific but locus-specific information). However, gPC2 (9.3%) and gPC3  were population-specific.Combining population- and gene-oriented approaches, SLCO1B3) and rs2242480 (CYP3A4) that have the highest factor scores at the positive pole and  rs4124874 (UGT1A1), rs9923231 (VKORC1), and rs1128503 (ABCB1) at the negative pole. In the combination with the results (factor loadings) from the population-oriented PCA (data not here presented), we consider rs4149117 (SLCO1B3) and rs2242480 (CYP3A4) as the most distinctive African loci.As shown in VKORC1), rs1143671, rs2257212, rs1143672, rs2293616 , and rs4149117 (SLCO1B3). At the negative pole of gPC3 there are three SNPs  all of them placed within NAT2 gene. In the combination with the results of the population-based PCA (data not here presented), those results indicate that distinctive SNPs for the East Asians are the three NAT2 gene SNPs and a VKORC1 (rs9923231) SNP.The East Asian (EAS) gPC3 has 6 loci on the positive pole (factor scores higher than 2): rs9923231 , rs2242480 in CYP3A4 gene  and rs1048943 in CYP1A1*2C gene .The largest global MAF differences (delta) between maximal and minimal MAF values for 95 SNPs are presented graphically in decreasing order  and the ABCB1), rs1902023 (UGT2B15), rs12248560 (CYP2C19*17), rs1799853 (CYP2C9), rs3758581 (CYP2C19), rs10509681 (CYP2C8*3), rs1138272 (GSTP1), rs8192709 (CYP2B6), and rs34059508 (SLC22A1) (and next to the highest MAF for rs28371725 (CYP2D6)). On the other side, Roma have the lowest MAF for rs4149117 (SLCO1B3) ).Focusing on the Croatian Roma, they have the extreme MAF values for 10 SNPs . Their hThe findings of numerous studies suggest that population differences in ADME genes show marked geographic and ethnic variation. However, most of the studies investigating these variations generally lack pharmacogenetic data on isolated populations. The same is true for the Roma, one of the worlds’ largest transnational minority populations. Roma are an example of isolated population with specific migrational history whose gene pool is highly influenced by the genetic drift due to unique social and cultural features.Therefore, in this paper we investigated the position that the Croatian Roma take within the world-wide variation in 95 ADME core genes’ loci. The ADME genes’ MAF information from twenty 1000 Genomes’ populations is here enriched by the data found through systematic literature search.VKORC1 (rs9923231), SLCO1B3 (rs4149117), CYP3A4 (rs2242480), and NAT2 .The results of this study confirm the previous findings that distinguish three world’s populational clusters: African, East Asian and joint European, South Asian and Native American . AdditioAmong all the studied loci, locus rs9923231 in VKORC1 gene takes a special position. It is the one characterized by the largest MAF differences among the populations worldwide (delta = 0.897) and is among few SNPs that define both African and East Asian continental clusters. Those findings are even more important having in mind that among the ADME genes VKORC1 is the one with the most vital implications for medical decisions considering appropriate pharmacotherapy.VKORC1 gene encodes vitamin K 2,3-epoxide reductase complex 1, which is responsible for the conversion of vitamin K-epoxide to vitamin K [VKORC1 genotype seems to be the most important predictor of adequate warfarin dose [Striking differences in worldwide allele frequency distribution noticed in rs9923231 is mostly explained as a result of selection [rin dose , 34. TheCYP3A4 gene. This locus exhibits significant difference between Africans and non-Africans [Another locus, which shows large differences in allele frequencies among the investigated populations, is rs2242480, the intron variant in Africans  which isAfricans  identifiAfricans , 34. AltAfricans , clopidoAfricans  and pharAfricans  carbamazAfricans .SLCO1B3 gene also separates African cluster from the other populations. The G allele of the rs4149771 locus was found even two times more frequently in non-Africans  than in Africans, in approximately 80% vs. 40% of subjects [SLCO1B3 gene encodes for solute carrier organic anion transporter family member 1B3 normally expressed in the liver and involved in transporter functions to uptake large, non-polar drugs and hormones. The rs4149771, like the previous one, is suspected to be connected with carboplatin and paclitaxel toxicity [Locus rs4149117 in subjects . Roma potoxicity  and withtoxicity .NAT2, one of the most polymorphic ADME genes, encodes for a NAT2 protein, which is expressed mostly in the liver, small intestine and colon tissues as a typical xenobiotic metabolizing enzyme . NAT2 geCYP1A1 gene. CYP1A1 is a member of the CYP1 family and participates in the metabolism of numerous xenobiotics, as well as endogenous substrates [CYP1A1*2C. The highest frequency of the mutated allele is noticed in the South American population from Peru while the absence of mutated allele is noticed in most of the African populations. Such distribution implies its introduction after the Out of Africa migrational event and therefore its current distribution probably results from genetic drift. Roma population has the frequency of minor allele within the European range which is substantially lower than in the ancestral South Asian populations.Among loci with the most pronounced population differences as revealed by MAF delta values is rs1048943 missense  mutation within bstrates . CYP1A1 Although there is evidence of selection for some of the above mentioned genes, the overall large allele variations between populations more often result from genetic drift, migrations and other demographic events .As it can be seen from our results, ADME core loci separate African and East Asian clusters from other Euro-Asian and American populations. This pattern is also confirmed by clustering of genetic distances. The Roma population is positioned within the European cluster and is close to the South Asian populations. Such results suggest that Roma ADME gene pool is a combination of two main layers: ancestral (Indian) and more recent (European). This is also evident from the analyses of the uniparental genetic markers , 23. SimCYP2C and CYP2D subfamily regions was also found in previous research of isolated populations in Europe  [CYP2B6 gene, Spikey et al. [SLCO1B3 gene and all of them confirmed that the Roma differ considerably from geographically close majority populations, as well as from Indian populations in those particular loci. Such results are not surprising knowing Roma genetic history which is influenced by strict rules of group endogamy, reproductive isolation and specific mating practice and isolation over the past several centuries.Although Roma population is found to be a member of the closely related European and South Asian clusters, it has the extreme MAF values in 10 out of 95 analyzed SNPs. Significant genetic differentiation from general Europeans in SNPs in the cadians) . Among tcadians)  particuly et al.  studied y et al.  analyzedCYP2C9) for warfarin dosage, and rs12248560 (CYP2C19) for clopidogrel dosage, efficacy and toxicity, while the second locus has been also clinically annotated as level 2A (very important pharmacogene) for citalpram or escitalopram pharmacokinetics. Additionally, rs10509681 (CYP2C8) has been annotated as level 2A for rosiglitazone pharmacokinetics and rs1902023 (UGT2B15) as level 2B  for lorazepam or oxazepam (www.pharmagkb.org). The identification of high risk allele at loci whose genotypes have a direct influence on quality of drug intake in this population, shows the necessity of the assessment of unique genetic profile of Roma in order to achieve the most in the modulation of pharmacotherapy in this population.Our population genetics findings contribute to the knowledge of interpopulation differences in high-risk pharmacogenomics allele distribution. The Pharmacogenomics Knowledgebase (PharmGKB) is a source of clinically relevant information, including dosing guidelines, annotated drug labels, and potentially actionable gene–drug associations and genotype–phenotype relationships . SeveralOur data confirm that isolated populations take specific positions within the global ADME genetic landscape. This pinpoints that the pharmacogenetics guidelines of the well-defined majority populations cannot be used in pharmaco-therapeutic practice in population isolates, and confirms the necessity for defining their specific genetic profile.Biological material used in this study was collected in multiple field studies, which were part of the on-going multidisciplinary anthropological, molecular-genetic and epidemiological research of Roma populations in Croatia. The fieldwork was carried out in several regions of Croatia with the highest number of Roma minority inhabitants according to the census data . The parwww.pharmaadme.org, 137 single nucleotide polymorphisms (SNPs) were selected for genotyping using the KASP and 127 of them were genotyped successfully. Allele and genotype frequencies were calculated by direct counting method.Genotyping of 439 DNA samples was done using KASP method. The KASP genotyping assay is a form of competitive allele-specific PCR combined with homogeneous fluorescent SNP genotyping system, which determines the alleles at a specific locus within genomic DNA . This teThe present investigation of genetic diversity was based on SNPs from the ADME core list which were genotyped in both the Croatian Roma and in 20 populations with different genetic ancestry from the 1000 Genomes Project Phase 3 list. This limitation and the finding that four ADME SNPs genotyped were monomorphic, led to further reduction of the total number of SNPs so in the end a total of 95 SNPs located in 31 ADME genes were used for the analyses.The 20 populations from the 1000 Genomes project belong to the five large continental regions, and each region is represented by four populations: (1) European (EUR): Finland, Italy, Spain, UK, (2) South Asian (SAS): Bangladesh, India, Pakistan, Sri Lanka, (3) African (AFR): Gambia, Kenya, Nigeria, Sierra Leone, (4) Central and South American (AMR): Colombia, Mexico, Peru, Puerto Rico, and (5) Eastern Asian (EAS): Dai Chinese, Han Chinese, Japan, Vietnam (only China is represented by two distinct populations—Han and Dai—since Han is a majority population while Dai represent here non-Han China populations).e!Ensembl browser for the each SNP, were: (1) clearly stated study geographical population and, where relevant, participants' ethnicity, (2) alleles frequencies and sample sizes, (3) samples come from the general population or control groups in case-control studies. These additional genotyping data enlarged the size of the 11 following 1000 Genomes populations: Italy, Spain, UK, India, Sri Lanka, Gambia, Kenya, Colombia, Mexico, Han Chinese and Japan. Allele frequencies for these populations were calculated by weighting samples for each population.In our analyses, we enriched the 1000 Genomes’ data with those found in the publications citing any of the 95 investigated SNPs in the above mentioned populations. Selection criteria for using data from these publications, listed at the http://evolution.gs.washington.edu/phylip.html).The genetic distance matrix, computed according to the method of Nei (1972), was subjected to hierarchic clustering routine using UPGMA (unweighted pair-group method using arithmetic averages) available in free software Phylip v3.697 (IBD: Isolation by distance v1.52 (available at http://www.bio.sdsu.edu/pub/andy/IBD.html). Geographic distances between the analyzed populations were calculated using two free online softwares: iTouchMap and Movable Type Scripts. iTouchMap calculates latitude and longitude of a point, and Movable Type Scripts calculated distance between latitude/longitude points (available at http://itouchmap.com/latlong.html and http://www.movable-type.co.uk/scripts/latlong.html).The Mantel test of correlation between genetic and geographic distances was performed using non-commercial software Principal component analysis (PCA) is a multivariate method that systematically identifies underlying variables, or principal components (PCs), that best differentiate a set of data . Two anaS1 TableThe references are provided in cases when data from the literature are used in addition to the 1000 Genomes data.(XLSX)Click here for additional data file.S2 TableThe list is ordered by decreasing delta values .(DOCX)Click here for additional data file.


AbstractAphyocyprisnormalis (Teleostei: Cyprinidae) is an endemic species in South China, but little is known about its genetic structure. This study examined the population structure of A.normalis using sequences of the mitochondrial DNA control region and cytochrome b gene . In total, 107 specimens were collected from nine populations. All 105 mtDNA haplotypes were identified as belonging to two allopatric phylogroups. The results of a statistical dispersal-vicariance analysis (S-DIVA) suggested that the ancestral populations of A.normalis were distributed widely on Hainan Island and east of the Leizhou Peninsula. A comparison of the fixation indices NST (0.532) and GST (0.004) revealed that the phylogeny and geography had a significant relationship. Our study found that (1) the Wuzhishan and Yinggeling Mountain Range was an important barrier limiting gene exchange between populations on both sides; (2) cyclic climate changes may have shaped migrations and population differentiations; and (3) different colonization times caused different population diversities between codistributed species. In addition, the inter- and intraspecific diversities of the genus Aphyocypris were estimated. Glyptothoraxhainanensis and Opsariichthyshainanensis, are considered endemic to Hainan Island, but previous studies  e.g., . Based o studies  have fou studies . AccordiWY Range) rises steeply from the central and southern regions of Hainan Island and gives way to a broad plain in the north. WY Range was an important barrier based on the population structure of the Reeves’s butterfly lizard. However, WY Range did not act as a barrier to gene flow among populations of oriental garden lizards . In addition, the four largest rivers on the island, the Nandu, Changhua, Wanquan, and Linshui Rivers, originate from the WY Range and flow outwards into the Qiongzhou Strait, South China Sea, and Gulf of Tonkin, respectively  and northern Hainan (Nandu and Changhua Rivers). WY Range was an important phylogeographic break based on the population structures of the cyprinid fishes G.orientalis and Onychostomalepturum. However, WY Range did not act as a barrier to gene flow among populations of another cyprinid, O.hainanensis.The Wuzhishan and Yinggeling Mountain Range , and Pararasbra (P.moltrechti), Nicholsicypris , and Yaoshanicus (Y.arcus) are monotypic. Until now, there were eight species within the genus Aphyocypris  How did A.normalis colonize the rivers on the island and mainland? (3) Is there a phylogeographic break in freshwater fish on Hainan Island? To address the aforementioned questions, the mitochondrial DNA cytochrome b gene and control region sequences (hereafter mtDNA) were used to evaluate the phylogenetic relationships and population genetic structure  What are the taxonomic boundaries within re e.g., . These rA.normalis was collected from nine localities on Hainan Island and mainland China  using primers from PCR mixture contained 5 ng template DNA, 5 µl 10x reaction buffer, 5 µl dNTP mix (10 mM), 5 pmol of each primer and 2 U of Taq polymerase . PCR was performed on an MJ Thermal Cycler with the following program: one cycle of denaturation at 95 °C for 4 min, 30 cycles of denaturation at 94 °C for 45 s, annealing at 48 °C for 1 min 15 s and extension at 72 °C for 1 min 30 s, followed by 72 °C extension for 10 min and sample storage at 4 °C. The purified PCR products were sequenced using an ABI 377 automated sequencer . Chromatograms were checked with the Chromas software (Technelysium), and sequences were manually edited using BioEdit 6.0.7 .A total of 107 specimens of it 6.0.7 . Moreoveh) (π and θω)  provides insight into population dynamics over recent evolutionary history  partitioned were used to the observed variation among samples into within-population (FST), within-group (FSC) and among-group (FCT) components in Arlequin version 3.5 (CT) when the program was instructed to identify K = 2 to K = 8 partitions of the sampling area.Nucleotide sequences were aligned in Clustal X 1.81 . Levels h)  and nucl and θω)  in DnaSP and θω) . Compari history . The exision 3.5 . Arlequision 3.5  was usedMRCA) was also calculated with the software package BEAST. A molecular clock was calibrated using a divergence rate of 2% per million years (MRCA). We ran 106 generations. The output was visualized in Tracer v1.6 , a program that complements DIVA, was employed to determine statistical support for ancestral range reconstructions (7 Markov Chain Monte Carlo (MCMC) steps and the first 10% as burn-in. The analysis was performed using the ‘maxareas = 5’ option because the populations were divided into six groups  and 945 bp of the control region (MH909956-MH910020) sequences were analyzed. A total of 105 haplotypes  were obtained for 107 sequences from nine populations analyzed (Table π) in the region was the highest in northern Hainan Island (average = 1.20) and the lowest in the northern Yunkai Mountains . At the population level, the nucleotide diversity (θπ) was the highest in population QH  and the lowest in population HY . Estimates of the current (θπ) and historical (θω) genetic diversity per site for each sample indicated that all samples showed a pattern of decline  of cyt b . The pairwise FST values ranged from 0.144 (between populations HO and QH) to 0.820 (between populations HY and BT) (Table ST within the mainland region (mean FST = 0.493) was smaller than that within island regions (mean FST = 0.514) (Table ST between the mainland and island was similar to that within the island (Table ST (0.532) and GST (0.004) revealed that NST was much larger than GST. This result suggested a strong relationship between phylogeny and geography. These results indicated that the population differentiations were significant.All FST = 0.50. The paFST = 0.50. The paFST = 0.50. The paCT = 0.35, p < 0.001). All samples were divided into five units: (1) BS, (2) BT, (3) TH, (4) HY and (5) others. The results of AMOVA indicated significant genetic structures at several levels  TH,  HY and . The results of the S-DIVA analysis indicated that possible ancestral populations of A.normalis were distributed on Hainan Island and east of the Leizhou Peninsula. The rising of the WY Range on Hainan Island separated the populations into two groups, south and north of the WY Range. After a vicariance event, the populations in the north of the WY Range migrated to the west of the Leizhou Peninsula.The coalescence time of Pararasbora, Yaoshanicus, and Nicholsicypris are synonymous with the genus Aphyocypris. Our study considered that a genus should fulfill two criteria at least, monophyly and distinctness. In this study, the range of the p-distance among the genera Candidia, Nipponocypris and Opsariichthys was 12.39% to 16.17% (mean = 15.16%) (Table Aphyocypris and the other three genera ranged from 15.31% to 18.22% (mean = 16.52%) , Yaoshanicus (Y.arcus) and Nicholsicypris  with Aphyocypris  diverged by a vicariance event. At 0.458 mya, the WY Range arose on Hainan Island and isolated the population in the southern Hainan Island region as lineage II  and G.orientalis (G.orientalis showed moderate to high genetic differentiation, but those within A.normalis showed a high level of genetic differentiation (Table A.normalis. The haplotype and nucleotide diversities of A.normalis are higher than those of G.orientalis. Moreover, the genus Aphyocypris only includes ten species in East Asia, but the genus Garra contains 138 species in Asia and Africa (A.normalis and G.orientalis had different colonization times, with A.normalis in the early Pleistocene and G.orientalis in the late Pleistocene. Our study considered that the ancestral populations of these two species originated from different mainland populations. Thus, our future aim is to understand the comparative phylogeography and geological history in Hainan Island and its adjacent area.Our study found that ientalis  have simon Table . Althougd Africa . Our stu


Semnopithecus entellus), a colobine primate with a wide range of altitudinal distribution across the Nepalese Himalaya, using the mitochondrial DNA control region  and cytochrome B  sequences combined with paleodistribution modeling.Past climatological events and contemporary geophysical barriers shape the distribution, population genetic structure, and evolutionary history of many organisms. The Himalayan region, frequently referred to as the third pole of the Earth, has experienced large-scale climatic oscillations in the past and bears unique geographic, topographic, and climatic areas. The influences of the Pleistocene climatic fluctuations and present-day geographical barriers such as rivers in shaping the demographic history and population genetic structure of organisms in the Nepal Himalaya have not yet been documented. Hence, we examined the effects of late-Quaternary glacial-interglacial cycles and riverine barriers on the genetic composition of Hanuman langurs  sequences, with haplotype and nucleotide diversities of 0.958 ± 0.015 and 0.0237 ± 0.0008, respectively. The troops were clustered into six major clades corresponding to their river-isolated spatial distribution, with the significantly high genetic variation among these clades confirming the barrier effects of the snow-fed Himalayan rivers on genetic structuring. Analysis of demographic history projected a decrease in population size with the onset of the last glacial maximum (LGM); and, in accordance with the molecular analyses, paleodistribution modeling revealed a range shift in its suitable habitat downward/southward during the LGM. The complex genetic structure among the populations of central Nepal, and the stable optimal habitat through the last interglacial period to the present suggest that the central mid-hills of Nepal served as glacial refugia for the Hanuman langur.Hanuman langurs of the Nepal Himalaya region exhibit high genetic diversity, with their population genetic structure is strongly shaped by riverine barrier effects beyond isolation by distance; hence, this species demands detailed future phylogenetic study.The online version of this article (10.1186/s12862-018-1280-4) contains supplementary material, which is available to authorized users. The geographical separation of populations by barriers can alter ranging behavior, prevent dispersal, and restrict gene flow . BarrierRivers are major physical barriers, with Wallace  initiallRivers of the Nepal Himalaya originate at an elevation of 6000–8000 m and carry snow melt southwards to the plains at elevations lower than 100 m within a north-south distance of less than 200 km . The widSemnopithecus entellus), the only colobine primate from the Nepal Himalaya , occupy a wide elevational and latitudinal distribution and are likely a good model species to explore riverine barrier effects. Hanuman langurs are restricted to the Indian subcontinent and are distributed throughout most parts of India, Nepal and Sri Lanka, as well as parts of Pakistan and Bangladesh [Primate species have been used to assess the riverine barrier hypothesis as the taxonomic boundaries of many primates coincide with major river courses , 8, 19, ngladesh . Taxonomngladesh –27. Hanungladesh . Studiesngladesh , 30 and ngladesh , 32 and ngladesh , 34. Recngladesh  describeDue to the morphological variations among the isolated populations of Hanuman langurs living in complex and fragmented forest environments as well as the effects of riverine barriers, population genetic analysis was necessary. Thus, we explored i) the level of genetic diversity among Hanuman langur populations; ii) the strength and influence of riverine barriers on the population genetic structure of Hanuman langur; and, iii) the effect of Pleistocene climatic fluctuations on the demographic history of Hanuman langurs in Nepal. To investigate these issues, we collected fecal samples from wild Hanuman langur troops covering almost the entire range of the species in Nepal from < 200 m to 3800 m asl and analyzed genetic variation within the control region  and cytochrome B  fragments of the mitochondrial DNA. Coalescent-based molecular analyses and paleodistribution modeling can provide a robust picture of the distributional history of a species –37. TherNepal lies on the southern flank of the central Himalaya between China and India, ranging at latitudes of 26°22′ and 30°27′ N and longitudes of 80°40′ and 88°12′ E  . HanumanSchima-Castanopsis, Elaeocarpus-Macaranga forests in the mid-hills and mountains, and Quercus-Pinus-Rhododendron forests in the high mountains [Hanuman langurs are diurnal, arboreal, and primarily folivorous, relying mostly on young tender leaves, buds, fruits, coniferous needles, and cones, though are known to occasionally consume termites, insect larvae , and eveountains .From August 2016 to May 2017, surveys were conducted along the tributaries of the Koshi, Gandaki, and Karnali-Mahakali river systems . In eastern Nepal, the Tamor and Arun tributaries of KRS; in central Nepal, the Trishuli, Marshyangdi and Kaligandaki tributaries of GRS; and, in far-western Nepal, the Karnali and Mahakali rivers of KMRS were sampled  following the manufacturer’s protocols, with some modifications: the 2 ml sample tube with lysis buffer was centrifuged for 2 min at 14000 rpm and 600 μl of the supernatant was taken for further processing; final elution was performed using 75 μl of elution buffer considering the low concentration of DNA in fecal samples.2O, 0.5 μl of each forward and reverse primer, and 1.0 μl of template DNA. The PCR assays for loci were carried out with an initial denaturation at 94 °C for 5 min, followed by 35 cycles with denaturation at 94 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 60 s, and final extension at 72 °C for 10 min. Precautions were taken to avoid any contamination between the samples and from external sources. Only six samples were processed in one batch. Every PCR amplification was carried out with a negative control and the pre- and post-PCR work were performed independently using separate equipment.PCR amplification of mtDNA fragments encompassing the entire control region (CR) was performed using the primer pairs LCRF (5’-AATTGACGTTCTATCTAAACTAC-3′) and LCRR (5′- GGGGATGCTTGCATGTGTAA-3′); furthermore, the CYTB was amplified using the primer pairs LCYF (5’-CGAGATCTGAAAAACCATCGTTG-3′) and LCYR (5’-AACTGCAGTCATCTCCGGTTTACAAGA-3′). The 25 μl reaction solution contained 12.5 μl of 2× power Taq PCR Master Mix , 10.5 μl of ddHThe amplicons obtained were the intended loci and were confirmed not to be exogenous contaminants or nuclear insertions of mitochondrial DNA (numts) because: (i) colobine-specific primer pairs that successively failed to amplify high-quality vertebrate DNA were used for each locus; (ii) single PCR amplicon of the expected size was detected in all individual samples; (iii) no extreme variant sequences were detected; and iv) the coding region of CYTB had no abnormal stop codons. Moreover, as fecal samples are richer in mtDNA molecules due to their large copy numbers, small size, and lower vulnerability to degradation than the nuclear DNA, the natural degradation of DNA from fecal samples made nuclear copies even more scarce, reducing the likelihood of amplifying numts .After separation in 1.2% agarose gel, the amplicons were purified and sequenced using the BigDye Terminator Cycle Kit v.3.1  in both directions on an ABI 3730XL sequencer .The CR (1090 bp) and CYTB (1140 bp) sequences were assembled and edited using Seqman (DNASTAR Lasergene v.7.1) and aligned using the Clustal W  algorithst, CYTB_2nd; P2 = CYTB_3rd, CR) with the GTR + G evolutionary model and Bayesian Information Criterion (BIC) was determined using Partition Finder v.2.1.1 [The concatenated CR and CYTB sequences were used to assess the population genetic structure. A phylogenetic tree depicting the relationship among the haplotypes was constructed using the maximum likelihood (ML) algorithm in RaxML v.8.2.10 , and the v.2.1.1 . The geo v.2.1.1 .ST was calculated from pairwise nucleotide differences between populations and their statistical significance was checked using 10,000 permutations as implemented in Arlequin v.3.5.1.2 [ST, against the corresponding log10 transformed geographical distance  between the Euclidian distance and number of river tributaries separating the population pairs; therefore, the correlation results between genetic distance and number of major rivers isolating the population pairs were omitted. Further, the effect of altitudinal gradient on genetic variations was assessed by correlation between genetic distance and altitudinal gradient between the population pairs using the Mantel test in Arlequin v.3.5.1.2 [The six major clades defined by the phylogenetic tree and MJ haplotype network were considered as populations for downstream analyses. Population pairwise F.3.5.1.2 . The gen.3.5.1.2 . The reg.3.5.1.2 . Assessm.3.5.1.2  by group2-test) [Multiple complementary methods were employed to assess the demographic history of the Hanuman langurs in Nepal. Neutrality tests, Tajima’s D  and Fu’s2-test)  in DnaSP2-test)  were per2-test) .Demographic changes of Hanuman langurs through time were estimated on HVR I sequences by Bayesian skyline plot (BSP)  analysishttp://worldclim.org/). The spatial resolutions of LGM variables were harmonized with those of current and LIG periods by resampling in 30 arcsec. All bioclimatic variables were clipped to a region from 78.5°E to 92.5°E and from 24°N to 31°N using ArcGIS 10.3.1 and exported in ASCII format. Bioclimatic variables often show high collinearity, resulting in poor model performance and misleading interpretation [P < 0.05) with the threshold of r ≥ |0.8|, and from all pairs of correlated variables beyond the threshold, only ecologically meaningful variables for the species  were selected for further analyses  was performed with the MaxEnt algorithm using the geographic coordinates of 29 wild Hanuman langur troops  and bioretation . Therefohttp://www.cgiar-csi.org/data/srtm-90m-digital-elevation-database-v4-1). The elevation values of suitable habitat pixels were extracted, and their mean, maximum, and minimum were computed.The logistic outputs of habitat suitability for the present, LGM, and LIG were converted to binary outputs of unsuitable (0–0.377) and suitable (0.377–1) habitats using the threshold of maximum training specificity and sensitivity (maxTSS = 0.377), as explained for the model generated by presence-only data by Liu et al. . The potOf the 87 fecal samples analyzed, both CR (1090 bp) and CYTB (1140 bp) sequences were successfully obtained from 67 (77.01%) samples. From the CR sequences, we identified 108 polymorphic sites (S) and 35 haplotypes (H) (GenBank Accession Numbers: MH271130-MH271164) with a haplotype diversity (Hd) of 0.957 ± 0.015 and nucleotide diversity (π) of 0.02978 ± 0.0009. Most CR polymorphic sites were in the HVR I fragment (82/108), with the 67 HVR I (489 bp) sequences defining 34 haplotypes (H) with an overall Hd of 0.955 ± 0.015 and π of 0.0528 ± 0.0015. For the CYTB sequences, we identified 15 haplotypes (GenBank Accession Numbers: MH271115-MH271129)  and for the concatenated CR + CYTB (2230 bp) sequences we identified 37 haplotypes . Among the 37 haplotypes demarcated by the set of concatenated sequences, 89.19% (33/37) was troop specific, 8.11% (3/37) was shared between two troops, and 2.70% (1/37) was shared among three troops.The gene genealogy inferred by the ML, MP, and NJ analyses consistently deduced a six-clade structure Fig. . Clade Ir = − 0.061, P = 0.909 for number of polymorphic sites; r = 0.615, P = 0.193 for number of haplotypes; r = 0.200, P = 0.703 for haplotype diversity; and r = − 0.382, P = 0.454 for nucleotide diversity; no r-values were statistically significant at P < 0.05).Among the six clusters (Hap_17 was included in clade CB due to its geographic proximity and closeness in the MJ network with Hap_18 and Hap_19) defined by the phylogenetic tree and MJ network, haplotype diversity (for the 2230 bp fragment) was highest in CA, whereas the nucleotide diversity was highest in CB and lowest in EA  and the lowest was between the CA and CB populations (0.7246)  between the genetic and geographical distances among populations  between genetic distance and altitudinal gradient.Population pairwise F6) Table . The Mantions 0.908 and thAssessment of population genetic structure by AMOVA partitioned 48.00% of genetic variation among the populations within groups and 41.44% of variation among groups . The Ramos-Onsin and Rozas test also yielded a high R2 value , indicating a relatively stable population. The neutrality test results for the individual clades were also not sufficiently statistically informative to analyze their demographic patterns . Among the population groups, the Eastern group demonstrated a unimodal curve, which peaked close to the y-axis, whereas the Central and Western groups displayed multimodal curves. The Bayesian skyline plot revealed a relatively stable effective population size (Ne) over the last 250,000 years, though the population decreased with the onset of the LGM in the Himalayan region  is more extensive compared to that during the LGM (Max_prob = 0.940) and LIG (Max_prob = 0.895) Fig. . SuitablHanuman langurs are one of the most endangered and protected non-human primate species in Nepal. The species has a wide latitudinal and elevational distribution in forest patches that are fragmented by natural barriers such as rivers and human settlements. Hanuman langurs are vulnerable to alteration and loss of their natural habitat due to anthropogenic activities, as well as conflicts with local people due to their raiding of crops . One of Trachypithecus geei  from India [T. leucocephalus  [Rhinopithecus roxellana (Hd = 0.845 and π = 0.0331) [R. brelichi  from China [R. bieti  [The Hanuman langur populations of Nepal demonstrated higher haplotype and nucleotide diversity (Hd = 0.955 ± 0.015 and π = 0.0528 ± 0.0015 for HVR I fragment) compared to other colobines of limited distribution range, including om India , T. leuc0.00044) , Rhinopi 0.0331) , and R. ± 0.018) . Thus, tAmong the populations we examined, the highest haplotype diversity was found in clade CA, which might relate to the strong elevational gradient associated with the occurrence of troops in these populations , even inST between the populations was high. Population pairs in close geographical proximity had lower FST values, whereas the populations separated by distance and/or rivers had higher FST values. This FST distribution demonstrates the effectiveness of rivers as barriers as well as isolation by distance phenomenon. The genetic diversity pattern in Hanuman langurs fits the assumption of the central-abundance model that explains the reduced genetic diversity and higher genetic differentiation in peripheral populations than in central populations [The overall pairwise Fulations . The aveulations .The phylogenetic inference using ML, MP, and NJ algorithms consistently defined six major clades for the Hanuman langurs in Nepal; namely EA, CA, CB, CC, WA, and WB. Clade EA from eastern Nepal and clade CA from central Nepal are isolated by the Arun, Tamakoshi, and Sunkoshi tributaries of the Koshi River system, and the Trishuli River of the Gandaki River system Fig. . Clades r = 0.343, P < 0.001) between the inter-individual genetic distance FST and the respective geographic distance, but a lower correlation  between the altitudinal gradients and genetic distance. Isolation by distance can explain the increase in genetic differentiation at neutral loci with geographic distance [In addition to the riverine barrier effect on the population genetic structure of Hanuman langurs, isolation by distance also showed a profound effect. The nonparametric Mantel test demonstrated a statistically significant positive correlation  sequences. Table S3. Predictor variables used in the construction of the niche models. Table S4. Correlation matrix among the 19 bioclimatic variables retrieved from the Worldclim website (http://worldclim.org/) after clipping to a region from 78.5°E to 92.5°E and from 24°N to 31°N. Figure S5. Area under curve (AUC) of the receiving operating curve (ROC) for the single training/test split run. Figure S6. Average area under the curve (AUC) for 25 replicates of MaxEnt runs. The red line is average value and blue bars represent ±1 standard deviation. Figure S7. The individual response curve of major three predictive variables to the Maxent model prediction. Figure S8. Distribution of suitable habitat pixels along the elevational gradient. X-axis represents the elevation gradients and y-axis represents the pixel frequency. (PDF 572 kb)


Numerous archaeological cultures associated with early nomads have been discovered throughout the Eurasian steppe belt. The Tagar archaeological culture existed in the Minusinsk basin  in the northeastern periphery of the Eurasian steppe belt from the 8th to 1st century BC during the pre-Scythian, Scythian, and Early Xiongnu-Sarmatian periods. In this study, we evaluated mtDNA diversity in the Tagar population based on representative series (N = 79) belonging to all chronological stages of the culture. The Tagar population had a mixed mtDNA pool dominated by Western Eurasian haplogroups and subgroups  and, to a lesser degree, Eastern Eurasian haplogroups . The Tagar population showed a similar mtDNA pool structure to those of other Iron Age populations representing the “Scythian World.” We observed particularly high similarity between the Tagar and Classic Scythians from the North Pontic region. Our results support the assumption that genetic components introduced by Bronze Age migrants from Western Eurasia contributed to the formation of the genetic composition of Scythian period populations in Southern Siberia. Another important component of the Tagar mtDNA pool was autochthonous East Eurasian lineages, some of which (A8 and C4a2a) are potential markers of the westward genetic influence of the eastern populations of the Scythian period. Our results suggest a genetic continuity  between the Early, Middle, and Late Tagar populations.Early nomads in the Eurasian steppes since the beginning of the 1 Early nomadic groups were the driving force of large-scale demographic events in Eurasia during the Early Iron Age. The range of early nomads encompasses the Eurasian steppes from the North Pontic region in the west to Southern Siberia and Eastern Central Asia in the east. Several stages in the development of these early nomadic communities, such as pre-Scythian, Scythian, and Xiongnu-Sarmatian periods, are distinguished based on archaeological and historical data. A characteristic feature of these periods is the widespread distribution of common elements in material cultures within the steppe belt and adjacent territories, accompanied by the intensification of cultural and, apparently, genetic interactions among populations from geographically remote regions of Eurasia.In the 1Numerous local groups of early nomads have been studied using methods in archaeology and physical anthropology. These studies have elucidated the local features of the material culture of early nomads from different regions of the Eurasian steppe and have enabled the reconstruction of probable internal and external cultural vectors and, to some extent, genetic links. Large collections of skeletal remains have accumulated, many of which have been characterized by methods in physical anthropology . These paleoanthropological collections have been used for molecular genetic studies of the Early Iron Age nomads, from single samples and small local series –3 to comst millennium BC, that is, during the pre-Scythian, Scythian, and Early Xiongnu-Sarmatian periods. During this time, the Tagar culture progressed through several stages  in the northeastern periphery of the Eurasian steppe belt for almost the entire 1To date, several thousand burials and numerous other sites belonging to the Tagar culture have been excavated in the Minusinsk basin and adjacent territories . DesThere are uncertainties related to the formation of the Tagar population. The Minusinsk basin was not isolated from external migration flows, which were especially intense during the Bronze Age. The degree of influence of Bronze Age migrants and autochthonous genetic components in the initial formation of the Tagar population and external influences at different stages of the culture are subjects of discussion among archaeologists , 8, 9. CDespite large collections of Tagar paleoanthropological materials, paleogenetic studies are limited. The paleogenetic data published to date include small series of mtDNA and Y-chromosome samples without a specified chronology   and sevest millennium BC.In this study, we evaluated mtDNA diversity in the Tagar population using a representative series  from burials belonging to all major chronological stages of the Tagar culture. We discuss the results of genetic analyses in the context of the issues of the Tagar population origin, its relationship with other ancient populations in Southern Siberia and other regions, and the dynamics of its genetic structure during the 1The main area of the Tagar culture covers the steppe and forest-steppe zone in the basin of the middle Yenisei River and its tributaries . Paleoanthropological materials from 95 individuals from 13 burial grounds of the Tagar culture located on the territory of the Minusinsk basin in the central part of the Tagar culture area were obtained  ).All specimens analyzed in this study were obtained from Repository of Paleoanthropological Collections of the Institute of Archaeology and Ethnography, Siberian Branch, Russian Academy of Sciences . All materials are available for further studies according to the full description , number of burial ) given in Due to favorable climatic conditions of the Minusinsk basin, all the skeletal materials included in the study are characterized by a very high degree of macroscopic preservation. Fragments of long bones with a large layer of compact bone were included in the analysis.All the ancient DNA experiments were carried out in the Laboratory of molecular paleogenetics of the Institute of Cytology and Genetics SB RAS .DNA was extracted as previously described , 12. In www.sequest.niboch.nsc.ru).The mtDNA analysis consisted of two steps. In the first step, mtDNA hyper-variable region (HVR) I was analyzed using two PCR strategies: 1) four overlapping fragments of mtDNA HVRI were amplified  and 2) ahttp://www.phylotree.org) [http://haplogrep.uibk.ac.at/) [Sequences were aligned with the revised Cambridge Reference Sequence of human mtDNA (rCRS)  by usingree.org)  by using.ac.at/) .After the preliminary phylogenetic analysis of the HVRI data, informative positions in the mtDNA coding regions were analyzed, and haplogroups and sub-haplogroups were identified. Primer pairs from  were usewww.fluxus-enginering.com). Phylogeographic analysis was conducted by using a database of mtDNA variability in modern Eurasian populations .Interpopulation differences of the Tagar population with other ancient and modern populations of Eurasia were estimated by istances  using thistances . The sigHaplotype sharing analysis between Tagar population and other ancient groups was carry out as in the article .www.sequest.niboch.nsc.ru).Nine autosomal STRs and the sex-determining marker amelogenin were simultaneously co-amplified by using the AmpFlSTR Profiler Plus Kit  according to the manufacturer`s instructions. Results see  were anaExperimental work with the ancient material was carried out in specially equipped, isolated clean rooms using special clothes. All work surfaces and instruments were routinely cleaned with a 5% solution of bleach and irradiated by UV light. Blank controls were run in parallel with samples in all extraction and amplification procedures, to identify possible contamination. PCR with positive amplification in blanc control were discarded. MtDNA HVRI sequences were determined for all staff working in ancient DNA facility.Sequences of the mtDNA HVRI fragment (15997–16409) were obtained for 79 out of 95 ancient individuals included in the original sample set  and builWe compared our Tagar series with two previously published small Tagar series from other burial grounds  in terms of haplogroup composition and haplotype sharing . We dete) in termFST values, haplotype sharing analysis, and phylogeographic analysis) between the Tagar group and several ancient populations of Eurasia, including both earlier Neolithic and Bronze Age populations and the approximately synchronous Iron Age groups (using mtDNA HVRI sequences). Accounting for the substantial Western and Eastern Eurasian components in the Tagar gene pool, we used ancient groups from the western and eastern parts of the Eurasian steppe belt in addition to populations from Southern Siberia and adjacent regions for comparison , followed by Afanasievo population from the Minusimsk Basin and Middle Bronze Age population from the Mongolian Altai Mountains (the region adjacent to the Minusinsk basin) Figs  Tables , the TagFST and close positions on the MDS plot) between our overall Tagar series and Scythians from the North Pontic region [Among the Iron Age populations , the Tagar group showed a relatively close mtDNA sequence similarity with groups representing the “Scythian World”  Figs  Tables. c region , 4, 26, c region , 37, 38 c region , are higOur series (N = 79) included individuals representing all three main stages in the progression of the Tagar culture , Middle stage (N = 24), and Late stage (N = 9)); accordingly, we compared the mtDNA sequences of these chronologically successive Tagar groups with each other and with the sequences of other Iron Age nomadic populations to infer the dynamics of the mtDNA pool structure of Tagar populations and to detect potential external influences on their genetic composition at different cultural stages  were located within the genetic variability (in terms of mtDNA) of Scythian World nomadic groups Figs  Tables. In a comparison of our Tagar series with modern populations in Eurasia, we detected similarity between the Tagar group and some modern Turkic-speaking populations (with the exception of the Indo-Iranian Tajik population) . Among tA phylogeographic analysis revealed both geographically widespread and specifically distributed  mtDNA lineages in our Tagar series. We observed informative lineages among both the East Eurasian and West Eurasian parts of our Tagar series. Several lineages from the Tagar series belonged to East Eurasian mtDNA clusters, including A8, C4a2, F1b1b, and G2a, which are characteristic of modern populations in Southern Siberia and adjacent regions of Eastern Central Asia and Middle Asia.Several lineages and subclusters originated from western areas of Eurasia and were dominant in modern and ancient populations of various parts of Europe, Caucasus, and the Near East . Most of these West Eurasian clusters were present in Southern Siberia since the Bronze Age . Most ofThus, our analysis revealed the presence of distinct phylogeographical components in the Tagar mtDNA series and mixed origins of the Tagar mtDNA pool. However, several West Eurasian  and East Eurasian (lineages of haplogroups C and D) lineages from the Tagar series showed wide distributions in the territory of Western and Central Eurasia (for West Eurasian clusters) or Eastern and Central Eurasia (for East Eurasian clusters) and therefore were phylogenetically uninformative.st millennium BC and played a key role in the formation of the cultural and genetic landscape of populations of a large part of Eurasia from Eastern Europe to Eastern Central Asia during the so-called pre-Scythian, Scythian, and Xiongnu-Sarmatian times and in subsequent periods. A large number of archaeological cultures associated with early nomads have been discovered in both the west and east regions of the Eurasian steppe belt. Analyses of these archaeological materials by various methods make it possible to objectively reconstruct the important ethnogenetic processes involving early nomads. Paleogenetic study of the anthropological remains of early nomads is one of the most promising areas of research at the moment. Analyses of the genetic composition of both eastern [Early nomads originated in the Eurasian steppes in the beginning of the 1 eastern , 37, 38  eastern  groups o eastern  have beeth to 1st century BC, i.e., during the pre-Scythian, Scythian, and Early Xiongnu-Sarmatian periods. Only a small number of samples from the Tagar culture  from representatives of the Tagar culture from the Minusinsk basin . The Tagar culture existed in the Minusinsk basin for a long time, at least from the 8l period  or withol period ) have beOur work is a good example of the correlation between the number of mtDNA samples and the quality, generalizability and representativity of mtDNA diversity data for an ancient population. More than 74% of HVRI haplotypes and several haplogroups  found in our Tagar series were absent from previously published data (N = 16) .p with (1–p)N = 0.05. For N = 16 , p = 0.037. With a high probability, we identified all of the main clusters of mtDNA present in the gene pool of the Tagar culture population in the Minusinsk basin. Thus, we obtained substantially more representative mtDNA diversity data for the Tagar population than were previously available.For a mtDNA series including N samples, under a simple binomial approximation, we cannot rule out the possibility that some undetected mtDNA clusters existed in the population at a frequency ata from , 10), p According to our results, the Tagar populations show a similar mtDNA pool structure to those of other Iron Age populations representing the “Scythian World” Figs  Tables. rd millennium BC) [st half of the 2nd millennium BC (Middle Bronze Age) [It has been suggested that the genetic similarity between the western and eastern early nomadic Scythian-like groups reflects the multiregional  origin of these groups with similar genetic components . Accordinium BC) , and (2)nze Age) , 65.Our results are not inconsistent with the assumption of a probable role of gene flow due to the migration from Western Eurasia to the Minusinsk basin in the Bronze Age in the formation of the genetic composition of the Tagar population. Particularly, we detected many mtDNA lineages/clusters with probable West Eurasian origin that were dominant in modern populations of different parts of Europe, Caucasus, and the Near East (such as K and HV6) in our Tagar series based on a phylogeographic analysis.st half of the 2nd millennium BC—Andronovo culture population from the Minusinsk basin and Andronovo-time population from the adjacent Baraba forest-steppe region.To assess the potential influence of Bronze Age populations in the Minusinsk basin (and the related migration wave from west of the Eurasian steppe) on the formation of the genetic composition of the Tagar population we compared our Tagar series with several chronologically preceded ancient populations: 1) Early Bronze Age (pre-Andronovo) Afanasievo and Okunevo culture populations from Minusinsk basin and Ealy Bronze Age Yamnaya culture populations from Eastern Europe ; 2) Middle Bronze Age populations, related with Andronovo migration wave during the 1We detected relatively low genetic distances between our Tagar population and two Bronze Age populations from the Minusinsk basin—the Okunevo culture population (pre-Andronovo Bronze Age) and Andronovo culture population, followed by Afanasievo population from the Minusinsk Basin and Middle Bronze Age population from the Mongolian Altai Mountains (the region adjacent to the Minusinsk basin) Figs  Tables. However, based on our mtDNA data, we cannot exclude the possibility that some West Eurasian clusters of mtDNA were introduced (or reintrodused) to Southern Siberian Iron Age populations more recently, independent of the Bronze Age migration waves discussed above. In this regard, it is interesting to note some specific West Eurasian mtDNA lineages shared between eastern and western populations of the Scythian World. For example, a lineage with rCRS HVRI haplotype belonged to haplogroup U . Most of these components belong to the East Eurasian cluster of mtDNA haplogroups. Moreover, the role of each of these components in the formation of the genetic composition of subsequent (to the present) populations in South Siberia and Central Asia could be very different. In this regard, cluster C4a2a (and its subcluster C4a2a1), and haplogroup A8 are of particular interest.Lineages in the C4a2a (and C4a2a1) cluster represent a significant portion of the haplogroup C diversity in our Tagar series (three out of five lineages). Interestingly, in the Early Iron Age, the mtDNA cluster C4a2a (including C4a2a1) did not appear to be widely distributed in Southern Siberia and Central Asia: these lineages were not detected in other populations of Scythian and Xiongnu-Sarmatian times, both in the territory of the Altai-Sayan mountain system and beyond. Only a single mtDNA line belonging to the related cluster C4a2 was detected in the Mongolian Xiongnu . This diUnlike C4a2a, the role of A8 in the gene pool of the population of Southern Siberia has reduced substantially over the past ~2000 years. This cluster was widely represented in Scythian-Siberian groups, including the Tagar, Pazyryk and Aldy Bel culture populations (this study and ) Fig 8;. InteresThese components, e.g., haplogroups A8 and C4a2a (C4a2a1), in the gene pool of populations in the Early Iron Age and more recent periods in the western regions of the Eurasian steppe belt are potential markers of the influence of the eastern populations during the Scythian period on western populations. According to the results of Unterlander et al. .We compared successive Tagar groups  with each other and with other Iron Age nomadic populations to evaluate changes in the mtDNA pool structure. Despite the genetic similarity between the Early and Middle Tagar series and Scythian World nomadic groups Figs  Tables, We observed differences in the mtDNA pool structure between the Early and the Middle chronological stages of the Tagar culture population, as evidenced by the change in the ratio of Western to Eastern Eurasian mtDNA components. The contribution of Eastern Eurasian lineages increased from about one-third (34.8%) in the Early Tagar group to almost one-half (45.8%) in the Middle Tagar group.At the level of mtDNA haplogroups, we detected a decrease in the diversity of phylogenetic clusters during the transition from the Early Tagar to the Middle Tagar. This decline in diversity equally affected the West Eurasian and East Eurasian components of the Tagar mtDNA pool. It should be noted that this decrease can be partially explained by the smaller number of Middle Tagar than Early Tagar samples. Under a simple binomial approximation the mtDNA clusters, observed at frequencies of 6.3% and 11.7%, could be lost by chance in our Early (N = 46) and Middle (N = 24) Tagar samples, respectively. However, the simultaneous lack of several such clusters, with a total frequency in the gene pool of the Early group of 34.8%, is unlikely.Using a haplotype sharing analyses, we obtained similar results . ExactlyThus, our results confirm the genetic continuity between the Early and Middle Tagar groups. Additionally, we detected a reduction in mtDNA diversity in the Tagar gene pool at the level of haplogroups and haplotypes. We did not find evidence for a migration wave or a change in the direction of interpopulation genetic interactions during this period.The observed reduction in the genetic distance between the Middle Tagar population and other Scythian-like populations of Southern Siberia, in our Another important issue is the change in the genetic structure of the Tagar population during the transition from the Middle (Saragash) to the Late (Tes`) stage. The Late Tagar stage refers to the Xiongnu period. Many archaeologists suggest that the formation of the Tes`stage involved the direct cultural influence of the Xiongnu and/or related groups of nomads from more eastern regions of Central Asia , 73. SomIn this study, we only investigated a small series of Tes`mtDNA samples. We do not have a complete understanding of the genetic composition of the Tes`population. However, our results are of interest in the context of the possible influence of eastern nomads during this period. The Late Tagar group (Tes`stage) was most distantly related to Xiongnu and other eastern nomadic groups  human groups.S1 File(DOCX)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S3 File(DOCX)Click here for additional data file.S4 File(DOCX)Click here for additional data file.S5 File(DOCX)Click here for additional data file.S6 File(DOCX)Click here for additional data file.S7 File(DOCX)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.


Micropterus dolomieu) populations. Analyses of a total of 572 M. dolomieu samples, representing the contemporary invasive South African range, contemporary and historical native USA range (dating back to the 1930s when these fish were first introduced into South Africa), revealed that the historical native range had higher genetic diversity levels when compared to both contemporary native and invasive ranges. These results suggest that both contemporary populations experienced a recent genetic bottleneck. Furthermore, the invasive range displayed significant population structure, whereas both historical and contemporary native US populations revealed higher levels of admixture. Comparison of contemporary and historical samples showed both a historic introduction of M. dolomieu and a more recent introduction, thereby demonstrating that undocumented introductions of this species have occurred. Although multiple introductions might have contributed to the high levels of genetic diversity in the invaded range, we discuss alternative factors that may have been responsible for the elevated levels of genetic diversity and highlight the importance of incorporating historic specimens into demographic analyses.Understanding the demographic history of introduced populations is essential for unravelling their invasive potential and adaptability to a novel environment. To this end, levels of genetic diversity within the native and invasive range of a species are often compared. Most studies, however, focus solely on contemporary samples, relying heavily on the premise that the historic population structure within the native range has been maintained over time. Here, we assess this assumption by conducting a three‐way comparison of the genetic diversity of native (historic and contemporary) and invasive (contemporary) smallmouth bass ( Invasive species are particularly suitable for demographic analyses, as they frequently experience rapid alternations in levels of genetic diversity following introduction  assess the genetic differentiation and diversity within M. dolomieu populations in South Africa, (b) investigate how genetic diversity changed over time in both native and invasive ranges, and (c) assess the introduction history of M. dolomieu into South Africa. Given the small M. dolomieu founding population, we predict that the invasive South African range will have a lower genetic diversity when compared to the native (historic and contemporary) North American range due to a loss of alleles, as suggested by Dlugosch and Parker  in a room previously unexposed to fish DNA using sterilized equipment. Prior to each extraction, all equipment and surfaces were treated with 10% bleach to remove any potential contaminants. Pikor, Enfield, Cameron, and Lam  showed t2.2n = 7; formalin fixed), representing the Detroit River, were obtained from the Royal Ontario Museum (ROM), Canada.Fresh tissue samples  were derived from specimens collected by angling in both the native United States of America (USA) and Canada and the invasive South African (SA) ranges during the summer months of 2014 and 2015 Figure . Nine lon = 63) were obtained from the South African Institute for Aquatic Biodiversity (SAIAB), Grahamstown, South Africa, rendering a total sample size of 306 specimens representing eight river systems  before sampling a piece of tissue. Tissue samples were stored in 70% ethanol for subsequent DNA extraction. Additional specimens (2.3n = 519). This was not possible for the historical samples due to the limited availability of tissue and the degraded nature of the DNA. A standard 25 μl mastermix was prepared for both mtDNA polymerase chain reactions (PCRs). The internal cytb primers, basscytbf1 (5′‐CAC CCC TAC TTC TCC TAC AAA GA‐3′) and basscytbr1 .To corroborate the morphological identification of the contemporary collected specimens and assess genetic diversity and demographic history of both native and invasive populations, two partial mitochondrial DNA (mtDNA) gene regions, namely cytochrome b (cytb) and control region (CR), were amplified for all the contemporary samples . To ensure accurate scoring, reference individuals previously scored were used as positive controls. Historical specimens were scored blindly  and repeated three times to ensure accuracy and consistency. Where scoring inconsistencies were observed  and more than three loci could not be scored , the entire specimen was removed from the data set and excluded from the study. Similarly, as one microsatellite locus, Mdo8, did not amplify for the majority of historical samples, it was removed from the historical data set entirely. Thus, nine microsatellite loci were analysed for the contemporary data set, but only eight microsatellite loci were analysed for the historical data set.The same nine microsatellite loci were amplified for the historic samples, following the amplification procedure used for the contemporary DNA, but due to the degraded nature of the DNA, this did not yield results. Thus, the resulting PCR products for each multiplex were diluted with distilled water to obtain a 1/10 PCR product which, in turn, served as template in the subsequent PCR. To ensure amplification and to avoid the overestimation of genetic diversity often associated with the amplification of ancient‐ and formalin‐fixed DNA , haplotype diversity (h) and nucleotide diversity (π) were calculated for each sample site. The population history for M. dolomieu in both ranges was examined using Fu's Fs  conducted to determine the amount of population subdivision among sampled localities. All analyses were conducted in ARLEQUIN 3.5.2.2  and invasive (SA—CI) ranges, the number of haplotypes  and expected heterozygosity (HE), and Wright's inbreeding coefficient (FIS), as implemented in FSTAT 2.9.3.2  in Genepop 4.2.1 Rousset, , with st Goudet, , Genepop Goudet, , HP‐Rare Goudet,  and ARLE Goudet, . Statist Goudet, . Allelic Goudet, , correctHO) between the three groups , an analysis of variance (ANOVA) was conducted in spss statistics 20.0.0 , with loci selected as random factors. Subsequently, a Bonferroni post hoc test was used to further assess the differences between groups. In addition, a stacked bar graph was constructed to visualize the variation among localities and loci. Second, Weir's  populations. As only eight loci were successfully amplified for the historical native (HN) specimens, all comparative analyses incorporating the historical samples only compared the eight loci, while contemporary SA–USA comparisons encompassed nine loci. First, to determine whether there was a difference in observed heterozygosity . Runs were conducted using an initial burn‐in of 75,000 Markov chain Monte Carlo (MCMC) generations, followed by 350,000 MCMC steps. STRUCTURE HARVESTER 0.6.94  using microsatellite allelic frequencies was conducted in the R package Adegenet 1.3.1  were more closely related to the historic native samples than to the remaining SA individuals (CI)  originated from (a) a single serial introduction from the source population (CN + HN), (b) two independent introduction events from the same source or (c) an unsampled source population  to the observed data  for each. Scenarios were subsequently compared through a logistic regression, which was conducted on the linear discriminant analysis components  on the microsatellite data set to determine whether the invasive South African n Figure . First, 33.1M. dolomieu specimens collected from eight river systems in the invasive SA range (CI) were successfully sequenced for 306 bp of cytb and 979 bp of CR, while the nine native USA (CN) localities yielded a total of 209 and 174 successfully sequenced M. dolomieu specimens for cytb and CR, respectively. Both cytb and CR rendered fewer haplotypes for the CN range when compared to the CI range, but similar haplotype and nucleotide diversity levels were observed  and invasive  populations, but differed between sampling localities and gene fragment  for cytb (DO—SAR and KO—VES) and FST = 0.013 to FST = 0.125 (both p < 0.05) for CR .A total of 292 3.2n = 306; eight localities) and native  ranges, were successfully genotyped for nine microsatellite loci, while 53 museum samples, representing 11 localities within the historical native range, were successfully genotyped for eight microsatellite loci. Neither of the three groups  displayed amplification errors , nor did any loci exhibit linkage disequilibrium. FreeNA  ranged from 0.39 (ONEI) to 0.59 (DET), while levels of expected heterozygosity (HE) ranged from 0.35 (MP) to 0.73 (MUS) across all loci.A total of 519 contemporary sampled specimens, representing both invasive (HO) among populations and loci, with reservoirs  consistently displaying lower levels of HO , with HO being higher for HN compared to both contemporary groups (Bonferroni post hoc test p < 0.001). A significant marker effect  was, however, observed. Overall, FST among HN samples was significantly low , but this was not so for the CI  and CN  populations. Likewise, pairwise FST values revealed significant population differentiation among CI populations, ranging from FST = 0.066–0.469 (DO—KO and BE—MP), with similar results being observed when comparing populations across all three groups, that is, CI, CN and HN , but this was not the case under the TPM model . Similarly, no significant excess of heterozygotes was detected for the HN population .There was substantial variation in observed heterozygosity  were obtained for the HN populations  shared a cluster with HN, but this was not the case for any of the CN populations, despite overlapping sampling localities , based on allelic frequencies, revealed two distinct groups along the first two axes: the first comprising both CN and CI populations and the second comprising the HN populations Figure . Limiteds Figure a. Both Cs Figure . The rems Figure a. The CNThe ABC analysis consistently supported the notion of a more recent introduction. The first set of scenarios tested , with individual admixture levels increasing with stocking intensity  range when compared to the contemporary native (CN) range, contradicting the general assumption that genetic diversity is lower in recently invaded ranges than in long‐established native populations. However, when comparing all three groups, the historical native (HN) range displayed the highest levels of heterozygosity, number of alleles (Na) and allelic richness (AR). Although this might have resulted from a statistical artefact due to the smaller sample size for the HN range, similar findings were previously reported for Atlantic salmon , Olifants (OL: n = 7), Doring (DO: n = 2), and Kouga (KO: n = 1) Rivers suggests shared ancestry with the HN samples, but the remainder of the invasive South African populations belong to four additional clusters, hinting at the idea of multiple introductions. The ABC results support this notion, as the best‐fit scenario suggested a second, more recent, introduction from North America (Scenario 2). Furthermore, when considering the invasive South African individuals associated with the HN STRUCTURE cluster as a separate South African population (CIS), the ABC analyses supported the STRUCTURE results and suggested at least two introductions: one coinciding with the recorded historic introduction and at least one more recent introduction. Indeed, the observed admixture between CI and CN suggests that the more recent introduction also originated from the USA. Unexpectedly, no support was obtained for either scenario examining single versus multiple introductions from a single source (Scenarios i and ii), nor any scenario postulating admixture . This may be due to several factors, such as the unequal sample sizes between HN and CI/CN range, the simplicity of the ABC models, or perhaps it could be ascribed to the fact that the HN population was not in HWE. Furthermore, the presence of a temporal Wahlund effect within the HN range, likely due to the pooling of multiple populations, may too have decreased the accuracy of the ABC results. Although our results support the notion of multiple introductions, this should be interpreted with caution as several factors may be responsible for this pattern, including an unsampled source population, postinvasion genetic drift, insufficient marker resolution and admixture in the source population  dispersal events are known to increase population mixing, ultimately increasing the species’ genetic diversity and hence, adaptability to the novel environment (Berthouly‐Salazar et al., Invasive species capable of harbouring large, genetically diverse source populations are thought to make better invaders (Gaither, Bowen, & Toonen, 4.3Micropterus salmoides, identified extremely low levels of neutral genetic diversity within invasive populations in lentic environments with limited connectivity (Hargrove, Weyl, & Austin, 2 catchment, was more diverse, suggesting multiple introduction events or hybridization between co‐occurring Micropterus species (Hargrove et al., Molecular techniques are indispensable tools in invasion biology (Blanchet, 4.4M. dolomieu, both within its native USA and invasive SA range. With regard to management in the native range, our data support the management recommendations by Brewer and Orth (M. dolomieu is no longer a feasible option due to the magnitude of the invasion, and the current management strategy is to prevent spread into previously uninvaded catchments by restricting stocking (see Woodford et al., M. dolomieu introductions into the country, it is imperative that South Africa strictly enforces its current legislation with regard to avoiding new introductions of this already invasive species. In addition, introductions even in river systems that have already been invaded may aid in increasing the genetic fitness of these already highly successful invaders and could facilitate further spread and exacerbate the already considerable impacts on native biota (Van Der Walt et al., Understanding the introduction history of an invasive species is crucial when wanting to decide on a management strategy for the species in question (Prentis et al., and Orth  that stoM. dolomieu, as study organism, our results corroborate the idea that genetic variation can indeed change over spatiotemporal scales. Both CI and CN range displayed high levels of admixture and limited population structuring. Although this pattern is not uncommon for invasive species that have been introduced multiple times, our results suggest that various factors may have played a role in shaping the genetic diversity of the CI range.In conclusion, while studies comparing contemporary genetic variation among native and invasive ranges are valuable (Lozier & Cameron, Our study highlights the importance of including historical DNA; however, caution should be taken when working with historical specimens as the degraded nature of the DNA not only hampers the successful amplification of the specimens (Sefc, Payne, & Sorenson, None declared.https://doi.org/10.5061/dryad.5jf41k5.Data available from the Dryad Digital Repository:  Click here for additional data file.