Taraxacum officinale (Asteraceae) is widely distributed weedy plant used as a traditional medicinal herb. The population genetics and historical biogeography of this plant have remained relatively unexplored. This study explores phylogeny, population genetics and ancestral reconstructions adopting multi locus sequence typing (MLST) approach. MLST sequences dataset was generated from genomics and chloroplast DNA sequences obtained from 31 T. officinale haplotypes located in 16 different countries. Phylogenetic analysis distributed these haplotypes in well differentiated geographic clades. The study suggested a close relationship between Europe and adjacent Asian countries. Populations of these regions predominantly formed common haplogroups, showed considerable level of gene flow and evidence for recombination events across European and Asian population. Biogeographical inferences obtained by applying statistical dispersal-vicariance analysis (S-DIVA) and Bayesian binary MCMC (BBM) analysis showed that T. officinale was putatively originated in Europe. Molecular clock analysis based on ITS dataset suggested that the divergence between Europe and East Asian populations can be dated to 1.07 Mya with subsequent dispersal and vicariance events. Among different spatial process long distance seed dispersal mediated by wind had potentially assisted the population expansion of T. officinale. Taraxacum officinale; Compositae-Lactuceae) is a group of highly invasive wild plants with worldwide distribution. Taraxacum species dominate in towns, along roadsides, shores of conduits and in many other rural sites. The representative species of this genus are Taraxacum officinale and T. erythrospermum. T. officinale has been documented particularly in North America, Asia, and Europe [T. officinale is found abundantly in cold regions. This indicates that it is basically acquainted with America through Alaska [T. officinale was contributed by the early European pilgrims who introduced different species of dandelion as a fancy [T. officinale is derived from relatively minor morphological modifications, leaving a seemingly limited set of morphological characters for phylogenetic studies. Multiple hybridization events in the evolution process of Taraxacum impair great difficulties in the interpretation of specific variation in Taraxacum phylogeny and biogeography [Dandelion  alone is not suitable for phylogenetic analysis of ividuals . Congrueividuals . TherefoTaraxacum is the most popular example for a wind-dispersed species with a hairy structure aiding aerial transport. The vast majority (99%) of wind-dispersed seeds are predicted to travel up to two meters [Spatial processes are crucial for determining the structure and dynamics of population and communities . Seed dio meters . TogetheT. officinae were collected from 16 different countries of the world and molecular data from nrDNA and cpDNA barcode loci combined. We constructed topologies based upon combined datasets of barcode loci and performed haplotype and recombination analysis to uncover the phylogeny, evolution process and current geographical distribution patterns in the level of species.In this study, samples of T. officinale was constructed by applying statistical dispersal-vicariance analysis (S-DIVA) and Bayesian binary MCMC (BBM) analysis implemented in RASP  and linking outcomes of this model with spatial process. It is proposed that wind-mediated seed dispersal could have played an important role in the diversification of T. officinale. Congruence of T. officinale population history with some climatic events illustrate the relevance of spatial process for determining the dynamics of population and historical biogeography of T. officinale. Previous studies have mostly focused on phylogeny of T. officinale [T. officinale by using MLST approach and spatial processes.Furthermore, a historical biogeography model of ficinale , 13, 20.T. officinale were collected from various locations of China or donated by researchers in the respective countries. Taraxacum plants are highly invasive and can be found abundantly on roads sides, gardens and rural areas. No special permissions were required for collection of plant samples. All samples were totally dried to null the propagation capability before shipment. Therefore, no special permissions were required for shipment and transportation process. This study did not involve endangered or protected species. Foreign samples were donated by samplers themselves or by the researchers from Department of Agriculture, Azad University of Gorgan, Iran; Institute of Agricultural Sciences, University of the Punjab, Pakistan. Details of sampling localities are shown in supplemental table A in Leaf samples of For fresh leaf samples, 50–100 mg of leaf material was crushed in liquid nitrogen. Genomic DNA was then extracted using the Sangon Biotech Plant DNA extraction kit  following manufacturer’s instructions. For dried leaf samples, leaf material was superficial cleaned through moderate friction using absorbent paper. DNA was extracted by adopting a modified CTAB method . The quaA pilot study was performed to select DNA barcode loci showing more than 90% PCR amplification efficacy. Afterwards, 4 candidate DNA barcode loci were amplified and sequenced from the extracted DNA of the leaf samples. These included two coding cpDNA loci ‘matK and rbcL’, one non-coding cpDNA intergenic spacer loci ‘psbA-trnH’ and a nuclear DNA locus ‘ITS2’ . PreviouDNA sequences were aligned using Clustal X2  and convTaraxacum population belonging to different geographical regions with PopArt (http://popart.otago.ac.nz). Networks were constructed under 95% parsimonious branch connections. Fu’s Fs and Tajima’s D approaches were used to collect information regarding demographic history of Taraxacum population [Haplotype networks were generated to depict relationship among pulation , 28.T. officinale haplotypes were analyzed by RDP version 4 [Potential recombinants along with parental analysis and approximation of possible recombination breakpoint positions in ersion 4 . Recombiersion 4 , Maximumersion 4  Chimaeraersion 4 , 33 and ersion 4  methods To support our biogeographical model, we estimated pairwise population differentiation using Slatkin’s linearized FST  and the http://www.topali.org/) and the model parameter values were used to construct ML tree. Clade support was estimated using 1000 bootstrap pseudo replicates [Phylogenetic inferences between haplotypes were generated using Maximum Likehood (ML) method in MEGA 7 . Every hplicates .-1 based on Eupatorium spp. [http://beast.bio.ed.ac.uk/Tracer) was used to check for convergence of the Markov chains and adequate effective sample size. A maximum clade credibility tree was obtained using Tree-Annotator software.Divergence time was estimated using a Bayesian approach with BEAST software version 1.6.1  using ITium spp. . The bes6 generations in all analyses. The data were sampled every 1000 generations, and the temperature for heating the chains was 0.1.The statistical dispersal-vicariance analysis (S-DIVA) and Bayesian binary MCMC (BBM) were implemented to infer ancestral distribution using RASP 3.2 . The trees previously constructed by BEAST analysis were used as the input data. Four regions were defined according to the sampling and distribution range of Taraxacum; Eur = Europe, WA = West Asia (Iran and Iraq), SA = South Asia (Pakistan), EA = East Asia . The MCMC chains were run for 5 × 10T. officinale samples were collected globally from 33 different sites across two continents. Four DNA barcoding loci were selected after performing pilot studies. These loci were successfully amplified for all plant samples. In accordance with the previous knowledge, all four loci used in this study are considered highly polymorphic in nature [T. officinale samples. This alignment was used for detection of recombination, construction of phylogenetic trees and haplotype networks. All the loci were amplified three times to get the best close match. Details of PCR amplifications are provided in n nature . Here 13T. officinale. The intra-specific distance ranged between 0.08 to 0.94% with an average value of 0.46%  to provide an accurate phylogeny for the construction of phylogenetic trees. Haplotypes of different geographical origin fell into clearly separated clades (We used the maximum likehood (ML) approach to obtain a consistent phylogeny based on nrDNA and cpDNA datasets. d clades . Tree brd clades .All the clades on ML tree can be clearly divided into two main groups “1 and 2”. Group 1 contained haplotypes of East and South Asian countries . Group 2T. officinale samples, 31 haplotypes were identified with some singletons and the remaining contained more than one  was seen between population of Europe and Asian regions with some non-significant indices (Taraxacum populations of Europe and Asian regions. The number of migrants (gene flow) among these populations ranged from 0.18 to 3.75 . Some potential haplotypes were detected with major and minor parents from Europe and Asia. Furthermore, higher gene flow was observed among population of Europe and Asia. These facts support as Europe is likely ancestral area of T. officinale. This west-to-east scenario of dispersion across Europe and Asia is also supported by tree topologies inferred from sequences of all four loci. Members of Europe and Asian population were sharing common linages in phylogenetic tress in case of T. officinale  are the plants that have been the topic of scientific and medicinal research for more than a century. In this study, plant samples were collected from 16 different countries of the world. We generated sequence datasets of four different barcode loci and used the data for the construction of species relationship, evaluation of divergence and historical biogeography.Dandelions  to construct le sizes , 46, 47.le sizes . Unlike T. officinale. Phylogeny resolution is often effected by discordant gene events [T. officinale. This can be the likely reason for this incourgence along with the hybridization process. All haplotypes of T. officinale were divided into two main groups; Group A and B  was seen at some branches in phylogenetic analysis of e events . The pose events . Some re A and B . The groT. officinale population, haplotype analysis was performed based on dataset of all barcode loci. In most of the cases there was considerable levels of population connectivity across different geographical regions  toward West Asia and from the west toward the East Asian region (ST) between European and Asian population of T. officinale further supports this model. The recombination and gene flow analysis indicate that population currently occurring in east and west Asian countries received a gene flow from Europe. Some potential recombinants of T. officinale were detected in the East Asian regions with major and minor parents from Europe and Asia  in current study and constructed historical biogeography of n region . This stand Asia . Such diT. officinale. This suggests East Asian population evolved from Europe parental populations nearly 1.05 million years ago from European parental population  successfully dispersed via seed in the Netherlands causing substantial levels of gene flow and population expansion [Taraxacum population from its putative origin towards East Asian countries. In the same way, the bidirectional wind patterns of Monsoon over Middle East and Asia favor the spatial pattern of seed dispersal between both regions.Spatial processes are important for determining the dynamics of population and biogeography. Seed dispersal is a leading spatial demographic process among sessile organisms setting the spatial template for population expansion , 69. Recr plants , 71. Prexpansion . Seasonaxpansion . WesterlT. officinale prevails complex phylogeny and single molecular barcode loci has little power to reveal deep phylogeny. There was considerable incongruence in every gene tree based on individual barcode loci. Use of multi locus sequence typing approach based on datasets of different barcode loci are more efficient in resolving complex T. officinale phylogeny and evolutionary events. The results of this study indicate evidence for ongoing gene flow and recombination between European and Asian population of T. officinale. Finally, the intra- and intercontinental expansion of T. officinale was driven by both biological dispersals and vicariance from Europe to Asian regions. This enigma suggests that environmental factors and evolutionary changes may have been favorable for distribution of T. officinale.In conclusion, our findings suggest that the genus S1 Tables(A) = Details of samples collection sites, sample collector’s name and height from the sea. (B) = Details of PCR primers used in this study. (C) = Genetic distance percentage generated using Kimura 2-parameter model analysis for the candidate barcode loci and their combinations. (D) = Details of NCBI Accessions. (E) = A detailed overview of recombination analysis performed by RDP V4 software.(DOCX)Click here for additional data file.


And it could also be used as a complementary tool for forensic parentage testing when combined with standard STR genetic markers. Furthermore, calculation of the AD distance and stF values of pairwise populations, phylogenetic reconstruction, multidimensional scaling analysis, structure clustering analysis were also conducted to probe the genetic relationships between Dongxiang group and the other 30 reference populations. Results demonstrated that Dongxiang ethnic group might be genetically closer related with most Chinese populations involved in our study, especially Tibet groups, Xibe group, and several Han populations.In comparison with the most preferred genetic marker utilized in forensic science (STR), insertion/deletion analysis possesses further benefits, like absence of stutter peak, low mutation rate, and enabling mixed stain analysis. At present, a total of 169 unrelated healthy Dongxiang individuals dwelling in Dongxiang Autonomous county of Gansu province were recruited in our study to appraise the forensic usefulness of the panel including 30 autosomal diallelic genetic markers. The insertion allele frequencies were in the range of 0.1598 at HLD 111 to 0.8550 at HLD 118. The cumulative match of probability and the combined probability of exclusion were estimated based on independence of pairwise loci, with the values of 3.96 × 10 Insertion/deletion (InDel) polymorphic genetic marker characterized by abundance in the genome, relative low mutation rate, small amplicon size, and compatibility with current genotyping platform  is gradustF), and AD values of pairwise populations were constructed based on these 30 InDels to explore the interpopulation genetic relationships between Dongxiang and 30 reference populations.As a country with a long-civilized history, China is also universally accepted to be one big oriental country composed of 56 ethnics and full of modern vitality. Diversities of ethnics and cultures make China a tremendous treasure to conduct genetic-related analysis. Dongxiang group is one of the Muslin ethnic groups mainly distributed in Gansu province and Xinjiang Uyghur Autonomous Region, China. According to the 2010 census, the population of Dongxiang reach 515,000 . Making 10.6084/m9.figshare.6743057).A total of 169 healthy unrelated Dongxiang individuals were recruited in our study from Dongxiang Autonomous county of Gansu province. All the individuals declared on kinships among them within at least three generations and no immigration events happened in their family history. Not until the written informed consents were acquired from each of them did we further continue our research. Five milliliters peripheral blood was collected and the genomic DNA was extracted by paramagnetic particle method according to the manufacturer’s recommendation. Procedures involved in our experiment were in good agreement with the human and ethical research principles of Southern Medical University and Xi’an Jiaotong University, China. Genotypic data of the 30-InDel loci for 169 Dongxiang individuals could be found in the public database named “figshare” . Positive control as well as negative control was also included to ensure precise results of InDel genotyping.Thirty InDel loci were co-amplified in a single PCR system with the necessary reagents and reaction conditions strictly set following the manufacturer’s protocol of Investigator DIPplex commercial kit  in GeneAmp PCR 9700 Thermal Cycler . Subsequent genotyping of PCR products was performed in an ABI 3500XL Genetic Analyzer  according to the manufacturer’s recommendation and alleles allocation were operated by GeneMapper P-values for interpopulation differentiation comparisons were conducted in Arlequin version 3.5.1.2 software , discrimination power (DP), probability of exclusion (PE), polymorphism information content (PIC), and observed heterozygosity (Ho) of the 30 InDels were implemented by modified PowerState version 1.2 spreadsheet. Linkage disequilibrium (LD) analysis was carried out by SNPAnalyzer version 2.0  software . Locus-bsoftware . Expect software , respectP = 0.05/30) after Bonferroni’s correction  and cumulative probability of exclusion (CPE).With significance level for probability values set at 0.00167  with the Bonferroni’s correction applied, and no significant differences were observed between Dongxiang and Yi group in Sichuan at all the 30 loci, one locus differentiation with Tibet Tibetan, Qinghai Tibetan, Beijing Han, and Chengdu Han populations, three loci difference with Uyghur, Xibe, Miao, and Tujia, Zhuang groups, four loci differentiation with Hui, Kazak, She groups, and Henan Han population, five loci differentiation with Guangdong Han population, and six loci difference with Shanghai Han population. By contrast, significant differentiation was observed between Dongxiang group and six Mexican populations  at 6, 7, 8, 11, 12, and 12 loci, as well as four European populations [Central Spanish  exhibited relative small deletion allele frequencies in most Chinese populations in exception of Kazak and Uyghur groups while a small branch of cluster 3  showed larger deletion allele frequencies in these populations. Hence, we speculated these above-mentioned loci might be potential for biogeographic ancestry inferences for Chinese populations involved in our study. On the part of distributions of deletion allele frequencies for the 30 loci, Dongxiang group was discovered to share analogical deletion allele frequency distributions with several Chinese populations  while distinct deletion allele frequencies distributions with most non-Chinese populations, which meant a similar genetic structure among Dongxiang and these Chinese populations. Furthermore, observations showed the deletion allele frequencies of the 30 loci were approximately identical among the only four European populations included in our study, which indicated the 30-InDel panel could be suitable for personal identification cases in these populations.Additionally, a heatmap of deletion allele frequencies for the 30 loci was also performed. As shown in AD distance is one of the most commonly used genetic distances to measure the genetic divergence between species or between populations within the same species and it was developed under the assumption that genetic differences originated from genetic drift and mutation events , several Han populations in Henan, Shanghai, Beijing, and Chengdu , Xibe group (AD = 0.0024) and Tibetan group in Tibet (AD = 0.0028), and far related with the above-mentioned non-Chinese populations with the least AD distance values found between Dongxiang and Cape Colored population (AD = 0.0159).Nei’ n events . PresentstF is generally considered as a measure of population differentiation on account of genetic structure  positioned in the middle of the plot and the left part of the plot was occupied by six Mexican groups, four European groups, and three African groups. Apparently, the studied Dongxiang group closely assembled with most Chinese populations , relatively far distant from two Central Asian populations , six Mexican populations, and four European populations, most far distant from three African populations. So, MDS plot also verified that Dongxiang group was in close genetic relation to most Chinese populations, especially Tibet groups, Xibe group, and several Han populations.Multidimensional scaling analysis is a generally employed method with the capability to visualize the similarity level of individual cases of a dataset. An MDS algorithm aims at placing each object in a N-dimensional space and the distances between two different objects can be preserved as well as possible . PresentK) defined at 2–7. And a burn-in period of 10,000 was also taken into account to acquire representative estimations of the parameters. As shown in Figure 6, population names as well as their corresponding language families were labeled on the bottom and the top of the figure. The width of each bar was proportional with the population sample size. When K at 2 and 3, East Asian groups and non-East Asian groups could be differentiated by distinct discrepancy of color compositions. And when K at 4, two African indigenous populations (Xhosa and Zulu), six Mexican groups  and Cape Colored population, a subset of European groups , and two Central Asian groups (Uyghur and Kazak) could be further distinguished. Similar clustering results could be generated at K = 5, 6. And when K = 7, Cape Colored population differed from Mexican groups with less brown components and more pink components. We surprisingly discovered the population substructure traits of Dongxiang group exerted similar hypothetical ancestry components with additional East Asian populations involved in our study at K = 3, 4, 5, 6, 7, which meant Dongxiang group was genetically closer with the most of Chinese populations involved in our study rather than other non-Chinese populations.STRUCTURE analysis is commonly recognized to be capable of inferring population structure and assigning individuals to populations using multi-locus genotypic data . In presAD values among Dongxiang and the 30 reference populations and displayed in Figure 7. The color of each population was labeled according to their corresponding language families. And four distinct branches were easily distinguished, with the first, second, third, and fourth branch composed of eighteen Asian populations, four European populations, six American populations, and three African populations, respectively. And we found clustering of the 31 populations roughly complied with their geographic locations and language families. The studied Dongxiang group was found to cluster with Tibet groups in Tibet and Qinghai, Xibe group, Hui group, and Han populations of diverse regions , indicating that relative close genetic relationships could be detectable among these populations. In exception of Cape Colored group, the only two African indigenous groups were discovered to be far related with most of the populations, which was in good accordance with previous studies. Furthermore, an unrooted tree  was also constructed based on allele frequencies of the 30 loci by Phylip version 3.69 software, and the population distribution was quite similar with the above-mentioned mega tree, so we further validated our results.With neighbor-joining method applied, a phylogenetic tree was conducted based on Recently, the development of DNA genotyping technology provides a promising approach to explore the genetic backgrounds for Dongxiang group and fascinated the progress of origin exploration for Dongxiang group to a certain extent. -11) and CPE (0.9886) certified the usefulness of these 30-InDel loci for forensic personal identification. Besides, to further clarify the genetic origin of Dongxiang ethnic group, we firstly applied the 30 insertion-deletion polymorphic genetic markers to explore the genetic relationships between the studied Dongxiang group and additional 30 reference populations. And observations indicated that Dongxiang was close related with Xibe group, Tibet groups in Tibet and Qinghai, and Han populations of several different regions . We believe our data presented here can be meaningful for further enriching the genetic background researches for Dongxiang group.At present, the forensic efficiency of the 30-InDel panel was assessed in Chinese Dongxiang ethnic group with the enrollment of 169 unrelated healthy individuals. And the results of CMP (3.96 × 10This study was carried out according to the recommendations of “Human and Ethical Committee of Southern Medical University and Xi’an Jiaotong University, China” with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the “Human and Ethical Committee of Southern Medical University”.BZ and XL designed this study. QL wrote the manuscript. YG, TX, YF, XJ, and WC collected the samples and extracted DNA. CC and YZ helped to conduct the statistical analysis. BZ also revised the manuscript. All authors agreed to the submission of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


ST = 0.147) was less than that of the Gobi and Pakistan (FST = 0.308) suggesting more recent male-mediated nuclear gene flow between Gobi and Altai than between Gobi and the Pakistan bears. Our results provide valuable information for conservation and management of bears in this understudied region of Central Asia and highlight the need for special protection and additional research on Gobi brown bears.Knowledge of genetic diversity and population structure is critical for conservation and management planning at the population level within a species’ range. Many brown bear populations in Central Asia are small and geographically isolated, yet their phylogeographic relationships, genetic diversity, and contemporary connectivity are poorly understood. To address this knowledge gap, we collected brown bear samples from the Gobi Desert (n = 2360), Altai, Sayan, Khentii, and Ikh Khyangan mountains of Mongolia (n = 79), and Deosai National Park in the Himalayan Mountain Range of Pakistan (n = 5) and generated 927 base pairs of mitochondrial DNA (mtDNA) sequence data and genotypes at 13 nuclear DNA microsatellite loci. We documented high levels of mtDNA and nDNA diversity in the brown bear populations of northern Mongolia , but substantially lower diversity in brown bear populations in the Gobi Desert and Himalayas of Pakistan. We detected 3 brown bear mtDNA phylogeographic groups among bears of the region, with clade 3a1 in Sayan, Khentii, and Buteeliin nuruu mountains, clade 3b in Altai, Sayan, Buteeliin nuruu, Khentii, and Ikh Khyangan, and clade 6 in Gobi and Pakistan. Our results also clarified the phylogenetic relationships and divergence times with other brown bear mtDNA clades around the world. The nDNA genetic structure analyses revealed distinctiveness of Gobi bears and different population subdivisions compared to mtDNA results. For example, genetic distance for nDNA microsatellite loci between the bears in Gobi and Altai (F Understanding the phylogeographic patterns and current genetic connectivity of a species provides a greater understanding of evolutionary history and is important for conservation and management decisions . NaturalUrsus arctos) was historically distributed across most of the Northern Hemisphere, but many populations, particularly in the southern portions of their distribution, are now isolated and of conservation concern [U. a. collaris) [U. a. jeniseensis) [U. a. arctos) [The brown bear   or as Moseensis) . Brown bseensis) , 13 or E arctos) , 15. The arctos) .Only a few studies have investigated the phylogeny of brown bears in Central Asia –19. ThesIn brown bears, as in most mammals, males are generally the dispersing sex and they can disperse over very large distances, whereas females generally have short dispersal distances and often overlap with their maternal home range . In this2 skin) were collected from local museums, field biologists, and locals from the Khovd (n = 1), Altai (n = 12), Sayan (n = 7), Khentii (n = 29), Buteeliin nuruu (n = 19) and Ikh Khyangan mountains (n = 6) between June 2005 and December 2016. The 5 hair samples from the Himalaya were collected in 1996 [We collected brown bear samples from 8 geographic locations, including the Great Gobi “A” Strictly Protected Area (hereinafter Gobi) , the Altai , Sayan , Buteeliin nuruu , Khentii , Bogd Khan , and Ikh Khyangan mountains  in Mongolia, and Deosai National Park in Pakistan   . We coll in 1996 . All tisTotal genomic DNA from scats, hair, and skin was extracted using the QIAamp DNA Stool kit and Qiagen DNeasy tissue kit . We extracted DNA from hair in a room dedicated to low-quality and -quantity genetic samples and included 5–10 guard hair roots in each extraction, if available. We extracted DNA from scat in a biosafety hood in a room dedicated to low-quality and- quantity genetic samples to avoid any cross-contaminations. A negative control was included to test for contamination in each batch of extractions.Extracted DNA was first screened with 3 mitochondrial DNA species ID primers  to ensure the sample was from a bear and to evaluate the sample quality . We chos(ID)sibs [Based on the probability of identity among siblings statistic P(ID)sibs , we dete(ID)sibs  to match(ID)sibs . Relioty(ID)sibs  was usedST [The genetic diversity within each population was calculated using Arlequin  and MicrST  and G”stST  and betwST . To furtST  from eacST . We applST  using STST .Taq DNA polymerase. The PCR thermal cycle profiles were as follows: an initial-denaturing step of 94°C for 10 minutes; denaturing step of 95°C for 30 seconds, annealing at 55°C for 30 seconds, and extension at 72°C for 1 minute (35–54 cycles); plus a final extension at 72°C for 10 minutes. The PCR products were stored at 4°C. To remove primers and unincorporated nucleotides, amplified products were purified using the QIAquick PCR purification kit . Contaminants were checked during DNA extraction, PCR, and sequencing processes using negative controls (one negative control for each 15–20 samples). The laboratory processes in DNA extraction, PCR, and sequencing were performed in separate rooms to avoid the cross-contamination. Sequences were determined with an Applied Biosystems 3130xl sequencer . Sequences were edited by hand using Sequencher version 5.3  and aligned using MAFFT.v7 [http://www.fluxus-engineering.com) using sequences collected during this study as well as Genbank data. Most samples from Genbank were from extant brown bear populations but also included 3 cave bear samples and 6 fossil brown bear samples  gene (671bp) and control region (CR) (256 bp). A partial COXII gene was amplified with primers BCOX2F 5'-CTTTGTCAGGGTTAAATTATAGGT-3' and BCOX2R 5'-GGAGAAGTCTGCATTCTCAGT-3' . The CR MAFFT.v7 . The numMAFFT.v7 . The hyp samples .Ursus spelaeus, FN390870) [Melursus ursinus, EF196662), were retrieved from Genbank for phylogenetic analysis. Sequence availability was greater in the control region , compared to the COXII region, which had fewer available samples . We performed independent analyses of both datasets, as well as a fully concatenated matrix of CR and COXII gene sequences, with all available sequence data. Because many samples had identical sequences , we pruned all datasets by randomly removing duplicate samples from the same geographic region. This allowed us to reduce the number of identical haplotypes, while retaining geographic representation. Sequences were aligned separately using Muscle v.3.8.31 [Due to the extensive amount of research on bear phylogeny based on mtDNA, an additional 115 brown bear haplotypes from populations in mainland Russia, the Middle East, and from the hypothesized sister species, the extinct cave bear (N390870)  and the v.3.8.31 . Models v.3.8.31 , where psumtrees function of the dendropy package v.4.0 [sump and sumt commands in MrBayes. A majority-rule consensus tree showing all compatible partitions from the resulting posterior distribution of topologies was used to recover the posterior probabilities of nodes. Each analysis described above was performed independently on both the full and pruned datasets of the CR and the COXII genes, as well as the full and pruned concatenated dataset of all CR and COXII sequences.To infer evolutionary relationships, we performed a phylogenetic analysis using both maximum likelihood and Bayesian criteria. Maximum likelihood trees were estimated using Garli . Each ange v.4.0  was usedge v.4.0 . Each ange v.4.0 . StationU. maritimus) + brown bear lineage, and the node corresponding to our entire ingroup + sloth bear, to estimate times of divergence across the tree. Calibration priors were centered around the median age reported from previous studies of the fossil record , or der Ursinae –54). ForCombiner  and a maCombiner .We obtained 773 consensus genotypes (≥10 loci) and identified 138 individual bears, including 68 from Gobi (including 1 sample from Khovd), 23 from Khentii, 15 from Buteeliin nuruu, 7 from Sayan, 5 from Bogd Khan, 10 from Altai, 5 from Ikh Khyangan, and 5 from Himalaya using 13 microsatellite loci .For genetic distance and genetic diversity calculations, individuals from Khentii, Buteeliin nuruu, and Bogd Khan were included as 1 population, due to the short geographic distance between the areas (50–200 km) and results from PCoA and Bayesian clustering analyses. Subsequently, we successfully sequenced 79 samples for the mtDNA CR fragment (256 bp) and 65 samples for the mtDNA COXII fragment (671 bp) .E = 0.48) and the Himalaya  to the highest values in Khentii+Buteeliin nuruu+Bogd Khan  and Altai  and Khyangan   in 7 of 8 brown bear populations, except 3 microsatellite loci that were monomorphic in the Himalayan sample (n = 5). A total of 85 alleles were generated by 13 microsatellite loci with a range of 77–246 bp. Genetic diversity levels were highly variable among populations in Central Asia, ranging from the lowest values in the Gobi  .The brown bear populations in Central Asia showed a comparatively high genetic diversity, based on CR (π = 0.03 and Hd = 0.89) and COXII (π = 0.01 and Hd = 0.87), especially the populations in the Altai, Khentii+Buteeliin nuruu+Bogd Khan, and Ikh Khyangan mountains . HoweverBased on CR data, we identified 22 previously undocumented haplotypes. Three haplotypes were reported previously as Gobi-I: Genbank accession number AB010728 from GGSPA ; PA136: Phylogenetic inference identified 6 primary clades of bears, with varying levels of support, that corresponded to hypothesized lineages from previous work  tree, summarized during the divergence dating analysis. This topology was inferred from the concatenated dataset (927 bp) and provides divergence times summarized at nodes of interest. Phylogenetic inference of the full dataset (both Maximum Likelihood and Bayesian topologies) is provided in the supplemental material .The brown bear sequences from Central Asia were clustered in clades 3a, 3b, and 6 . The beaThe median-joining haplotype network also showed 3 divergent groups in Central Asia . For claBased on the divergence time estimate, the clade 3b2 bears in the Sayan-Khentii-Ikh Khyangan-Russian Siberia and clade 3b3 bears in eastern Hokkaido diverged around 0.24 mya (0.13–0.38 kya) from clade 3b1 in Altai. The Maximum Likelihood and Bayesian phylogenetic tree, along with the divergence estimate, indicated that the Himalayan brown bears diverged from Gobi bears 0.69 mya (0.32–1.21 mya) years ago .ST = 0.339, G''ST = 0.282) than all other pairwise comparisons. Overall, brown bears in both the Gobi and Himalaya had higher pairwise differentiation values  with the Altai, Sayan, and Khentii (included Buteeliin nuruu and Bogd Khan) mountains than these 3 areas had among themselves   .ST = 0.26–0.330, GST'' = 0.14–0.18) than those between Gobi and Altai, Sayan, Khentii   . The bea12–0.14) .The Bayesian clustering also strongly supported the split between Gobi and other brown bear populations in the Himalaya, Altai, Sayan, Khentii, Buteeliin nuruu, and Bogd Khan. The population split at K = 2 received the highest likelihood value, based on the Evanno method  S3 Fig)S3 Fig) aPrincipal Coordinate Analysis (PCoA) revealed that all Gobi bears clustered together, separately from the rest of the Central Asian brown bears. Himalayan brown bears were distinct from the brown bears in the Altai-Sayan and Khentii mountain ranges . TherefoAs an additional result, we found an 8 bp deletion in the X chromosome microsatellite locus (SE47-48) in all Gobi bear samples. Also, only a few females (n = 4) from Altai and Ikh Khyangan had allele 232 in 1 of the X chromosomes, but the rest of the sampled brown bear populations had a 240 allele at this locus.Collecting genetic data and samples from wildlife in remote regions is a difficult task but can provide valuable information about evolutionary history, taxonomy, population connectivity and genetic health of populations. Using mitochondrial and nuclear DNA data collected from previously unsampled brown bear populations in Central Asia, first, we documented high levels of mtDNA and nDNA diversity in the Altai, Sayan, Buteeliin nuruu and Khentii populations, but substantially lower diversity in the brown bear populations in Gobi and Himalaya. Second, our data revealed 3 brown bear mtDNA phylogeographic groups among the bears of the region, with clade 3a1 in Sayan, Khentii, and Buteeliin nuruu mountains, clade 3b in Altai, Sayan, Buteeliin nuruu, Khentii, and Ikh Khyangan, and clade 6 in Gobi and Himalaya. Our results also clarified the phylogenetic relationships with other brown bear mtDNA clades around the world. Third, nDNA clustering analyses revealed different population subdivisions compared to mtDNA results, especially for the brown bear populations in Gobi, Himalaya and Altai.E = 0.78), Sayan , Khentii , and Ikh Khyangan  mountain ranges , and Ikh Khyangan were hypothesized to be contiguous within Mongolia and with the large bear populations in Russia, China, and Kazakhstan , 61; ourn ranges . Becausen ranges  Figs, esn ranges .The previously undescribed haplotypes found in this study are unique to Central Asian brown bears. Brown bears in the Altai Mountains had 5 novel mtDNA haplotypes (Hap3-Hap7 in CR). Both the Gobi (Hap1_CR and Hap2_CR) and Himalayan populations (Hap26 in CR and Hap13 in COXII) had 2 novel haplotypes , which wWe found that the genetic diversity of both Himalayan and Gobi bears was very low. We chose a set of markers that were polymorphic in Gobi bears to facilitate individual identification of samples collected from hair snares, but 3 of them  were monomorphic for Himalayan bears. Previous studies , 67 presOur analysis of genetic variation of CR and COXII mtDNA sequences revealed that brown bears from Central Asia included 3 divergent haplogroups that clustered into clades 3a1, 3b, and 6. The phylogeographic history of each mitochondrial lineage is examined below.The brown bears in Clade 3a have been divided into 2 main divergent groups , 9: 1) sWe found several haplotypes on both CR  and the COXII  in Khentii and Buteeliin nuruu that fit within the 3a1 subclade . AdditioOur results were consistent with the previous divergence time estimates using the complete mitochondrial genome, i.e., that subclades 3a1 and 3a2 diverged in the Eurasian continent about 53 kya (95 CI: 21–95 kya) and then 3a2 moved earlier than 3a1 to Hokkaido Island through Sakhalin .We found brown bears in clade 3b throughout most sampling locations, including the Altai, Sayan, Buteeliin nuruu, Khentii, and Ikh Khyangan mountains. Previously brown bears of this clade have been found in Eastern Hokkaido, the Russian Far East, eastern Alaska, and northern Canada , 17, 58.Although these two geographically distant populations are in the same clade, their haplotypes differed by 4 bp in COXII (671bp) in the protein coding region and 1–2 bp in the control region (256 bp). The first phylogenetic paper on Gobi bears  found thST and G”ST between bears from the Gobi and Himalaya  was greater than between the Gobi and Altai, Sayan, Khentii, and Ikh Khyangan , suggesting more recent male-mediated nuclear gene flow between the Gobi and the northern sampling areas than between the Gobi and the Himalayan bears. Both the STRUCTURE and PCoA analyses indicated that Gobi bears are genetically distinct and divergent from the bears in Himalaya, the Altai-Sayan region, and Khentii  was closer than that of the Gobi and Deosai National Park in the Himalayan Mountain Range (FST = 0.308). Bipaternal microsatellite markers reveal more recent gene flow history than mtDNA analyses as well as male-mediated gene flow and may therefore be more relevant for discerning current relationships important for management and conservation. This discordant pattern has also been observed in the ABC Islands in Alaska and in Scandinavia, where male brown bear gene flow has been documented using nuclear microsatellite markers [In contrast to the mtDNA (clade 6) results, the genetic distance for nDNA microsatellite loci between the bears in Gobi and the Altai  from Khovd showed admixed ancestry in the STRUCTURE and PCoA analyses, which suggests relatively recent gene flow between the bears in the Gobi and Altai. Previously (before 1940), the distribution of Gobi bears was larger than their current distribution , 83. SigSTRUCTURE and PCoA analyses indicated that the Gobi brown bear population was the most divergent of all groups sampled. However, there was also additional informative population structure revealed in these analyses. STRUCTURE at K = 3 and the PCoA results revealed that the Himalaya population (mtDNA clade 6a) is the next most divergent followed by the Altai Mountain population . The historical corridors between those two populations could have been the ridges of the Ugam, Pskem, Kirgiz, Talaz Alatau, Zailiy Alatau, Kungey Alatau, Ter Alatau, Ketmen, Dzhungar Alatau, Saure, Tarbagataye, and Southern Latay regions in Kyrgystan, Kazakstan, China, and the Zhunghar Gobi in southwestern Mongolia .ST = 0.051 to FST = 0.014 during 20 years [ST (0.23) between brown bear populations in the South Selkirk Mountains in North America, which has been isolated for several decades from the neighboring populations across a 5-km wide valley filled containing a town and rural farms. Due to this restriction of gene flow for the small population (≤100) in the area [The degree of genetic differentiation observed among the Gobi and Himalayan populations is larger than the average Fst between distinctive subpopulations in northwestern Europe (0.051) . Interes20 years , because20 years , 90. In 20 years  found a the area , geneticST values (0.026), STRUCTURE, and PCoA analyses. The Sayan, Buteeliin nuruu, and Khentii bears currently have haplotypes belonging to both clades 3a1 and 3b. Therefore, there is still potential gene flow between the populations in the Altai and Sayan mountains through the Siilkhem Mountains, although our study detected that the bears in the Altai have novel mtDNA haplotypes of the 3b clade only in this region, as well as indications of divergence in both STRUCTURE and PCoA analyses using microsatellite loci. Anthropogenic factors, such as human land use, grazing, farming, and new settlements in Mongolia and Russia, may now restrict movements between populations in Altai and Sayan.For bears in the Sayan, Buteeliin nuruu and Khentii, and Ikh Khyangan mountain ranges, our results indicate substantial gene flow, according to the results in a pairwise FInterestingly, the Altai and Ikh Khyangan populations have genetic similarities, including 3b haplotypes, and small degree of shared ancestry based on STRUCTURE analyses. Also in support of the genetic link between these separated bear populations was a unique sex-specific X chromosome loci (SE47-48) loci, allele 232 that we found in all Gobi bears and in 2 females from each Altai and Ikh Khyangan. These 4 bears were heterozygous containing a 232 allele, as found in the Gobi, and a 240 allele, as found in other brown bear populations. Given that that the geographic distance between the Altai and Ikh Khyangan sampling areas (> 2000 km) is the furthest among the populations we sampled, these genetic similarities may be explained through shared historical ancestry and connectivity. For instance, the coastal bears in Alaska  and Kodiak bears  which crossed the Bering Strait were eventually cut off with no gene flow, but still shared similar haplotypes with clade 3 bears in Eurasia.Brown bear populations are classified as threatened or endangered across most of Central Asia, due to anthropogenic effects combined with climate change , 15. ForS1 TableAncient DNA sequences from brown bears and extinct cave bear were retrieved from Genbank database with their corresponding accession number, species name, sample ID, references and sampling location. The age estimates were based on uncalibrated radiocarbon years  as well as BEAST posterior estimates .(DOCX)Click here for additional data file.S2 TableThe concatenated sequencing dataset includes 671 bp COXII and 261bp Control Region. Twenty-two new haplotypes for control region sequences and 12 new haplotypes from COXII were identified in this study. Concatenated column gives the sample ID used in the phylogenetic and divergence time analyses. The previously reported haplotypes are indicated with the symbol (§) and the Genbank ID is in parentheses in the sample ID column.(DOCX)Click here for additional data file.S3 TableDescription: n, number of individuals; S, variable sites; Haplotype (gene) diversity, Hd; Nucleotide diversity, π; Average number of nucleotide differences, K.(DOCX)Click here for additional data file.S4 TableDescription: Gaps are excluded and the total sites 243 bp out of 261 bp. n, number of individuals; S, variable sites; Haplotype (gene) diversity, Hd; Nucleotide diversity, π; Average number of nucleotide differences, K.(DOCX)Click here for additional data file.S1 FigThe concatenated sequencing dataset (927 bp) includes 671 bp COXII and 256 bp Control Region. a) Bayesian and b) Likelihood analyses. The samples with green dots are from our study.(TIF)Click here for additional data file.S2 FigThe concatenated sequencing dataset (927 bp) includes 671 bp COXII and 256 bp Control Region. Colors in each node indicate the geographic sampling locations; the size of the node indicate frequency of the haplotype. The hatches represent mutational differences in the sequences. The names of the new haplotypes discovered in this study are given in the underlined text on the nodes.(TIF)Click here for additional data file.S3 FigThe results are based on 13 loci microsatellite dataset of Asian brown bears. A) The DeltaK results support K = 2 as the most basic level of subdivision , which s(TIF)Click here for additional data file.S4 FigColors and pie charts represent proportions of the ancestry belonging to each K. Pie charts and names (with sample size) are in the general locations. The current brown bear distribution  is highl(TIF)Click here for additional data file.


Bactrocera dorsalis, the Oriental fruit fly, is one of the world's most destructive agricultural insect pests and a major impediment to international fresh commodity trade. The genetic structuring of the species across its entire geographic range has never been undertaken, because under a former taxonomy B. dorsalis was divided into four distinct taxonomic entities, each with their own, largely non‐overlapping, distributions. Based on the extensive sampling of six a priori groups from 63 locations, genetic and geometric morphometric datasets were generated to detect macrogeographic population structure, and to determine prior and current invasion pathways of this species. Weak population structure and high genetic diversity were detected among Asian populations. Invasive populations in Africa and Hawaii are inferred to be the result of separate, single invasions from South Asia, while South Asia is also the likely source of other Asian populations. The current northward invasion of B. dorsalis into Central China is the result of multiple, repeated dispersal events, most likely related to fruit trade. Results are discussed in the context of global quarantine, trade, and management of this pest. The recent expansion of the fly into temperate China, with very few associated genetic changes, clearly demonstrates the threat posed by this pest to ecologically similar areas in Europe and North America. Global fruit and vegetable production was estimated at 676.9 and 879.2 million tonnes, respectively, in 2013, with global fruit exports in the same year valued at USD 97.02 billion , and the focus of this paper, the Oriental fruit fly, Bactrocera dorsalis (Hendel).One of the major biological impediments to horticultural production and export in tropical and subtropical regions of the world is the frugivorous tephritid fruit flies (Diptera: Tephritidae)  and molecular markers (cox1 and nad6 genes and microsatellite loci) to determine global population structuring in this species. Three independent markers were used in an integrative framework  what is the likely region of origin for the species and its associated global invasive pathways; and (c) what variation occurs in invasive Central China populations. The results are discussed with respect to the management of this pest.Taken together, we address the following specific research questions with these comprehensive data: (a) whether macrogeographic population structure is detectable in 22.1B. dorsalis adults were collected from 63 locations and assigned into six a priori groups , Southern China and far northern South‐East Asia (SCNA), Southern South‐East Asia (SSA), South Asia (SA), Africa (AF) and Hawaii (HI)) based on biogeographical factors. Thirty‐five locations were sampled within China, belonging to 16 provinces. Details of the sampling sites and sampling sizes are given in Supporting Information Table Two‐thousand eight‐hundred and sixty‐seven 2.2Usually, the right wing was dissected from each fly for slide mounting, image capture and analysis, the left was used instead if the right wing was damaged. Wings were slide mounted using DPX mounting agent and air‐dried prior to image capture using an AnMo Dino‐Eye microscope eyepiece camera (model # AM423B) mounted on a Leica MZ6 stereomicroscope. Fifteen wing landmarks were selected following Schutze, Jessup, & Clarke, Raw landmark coordinate data were imported into the computer program MORPHOJ v1.04a  was calculated in MORPHOJ v1.04a. Centroid size is an isometric estimator of size calculated as the square root of the summed distances of each landmark from the center of the landmark configuration. ANOVA with post hoc Tukey's test was used to assess for significant differences among sample sites.Samples were a priori assigned to the above six groups  and 16 provinces within China, from which subsequent canonical variates analysis (CVA) was applied to determine relative differences in wing shape among groups  for animal tissue, and slight modifications were made to increase DNA concentration  and nad6 sequences from each individual were reviewed using Chromas (version 2.33) and assembled using DNAMAN 5.2 . To delete low‐quality sections, all sequences were aligned with the standard sequences of B. dorsalis from NCBI using MEGA 7.0 , number of effective alleles (NE), observed heterozygosity (HO), and expected heterozygosity (HE) were calculated using POPGENE 1.32 , haplotype diversity (Hd), and the number of haplotypes were estimated using DnaSP 6  from 1 to 10 and conducted 10 independent runs for each value of K. Each run consisted of a burn‐in period of 50,000 steps, followed by 100,000 Markov chain Monte Carlo (MCMC) repetitions with a model allowing admixture. ΔK values  method in NETWORK 5.0.0.3 , effective population size after expansion (Ɵ1), time of populations expansion (T), Tajima's D, Fu's Fs and sum of square deviation (SSD) between expected and observed mismatch distribution.Neutrality tests and mismatch distribution of the sequences were calculated in Arlequin 3.5 with 1,000 bootstrap replicates, six parameters were calculated: effective population size before expansion , with significant variation found between populations from Central China (largest wings) compared with South Asia and southern South‐East Asia : The three remaining population groups were intermediate between, and not significantly different from, the two extremes   was detected between geographic distances and Mahalanobis distances  was found in all Asian groups , whereas invasive populations in Africa (HS = 0.547) and Hawaii (HS = 0.413) had lower genetic diversity  and nad6 (525 bp) were sequenced from 2,442  and 2,426 (609 haplotypes) individuals, respectively. Both mitochondrial genes exhibited greater haplotype and nucleotide diversity in the Asian groups than Africa and Hawaii  which formed a unique cluster; Burundi (BI), South Africa , and most of Kenya (KE) formed another cluster. K = 9 showed a complex structure for 51 Asian populations; K = 4 and K = 6 were found for the 35 Chinese populations and the other 16 Asian populations, respectively. Zhenjiang (ZJ) from Central China alone was separated from the other three clusters within China; while Myanmar (MM), the Philippines , and Papua New Guinea (PNG) were differentiated from the other Asian populations.Bayesian clustering analysis of microsatellite genotypes implemented in STRUCTURE suggested that the maximum value for the estimated likelihood of cox1 (249 haplotypes) and nad6 (219 haplotypes) without the third base of codons, and only the torso was displayed  and effective population size before expansion (Ɵ0), which can serve as an estimate of the extent of population growth, indicated that B. dorsalis exhibited a certain degree of population growth in all the groups (Supporting Information Table pSSD > 0.05).Neutrality tests performed on the 4B. dorsalis populations and encompasses both the accepted native range and recent (<70 years) invasive locations. This extensive sampling provides higher resolution of population relationships and more rigorous tests regarding invasive history and region of origin of this highly invasive and pestiferous fruit fly than previously available.This study represents the largest‐ever sampling of 4.1B. dorsalis into two genetic units, an Asian group and a non‐Asian group, while the network of mitochondrial haplotypes did not suggest any subdivision in the data. The non‐Asian group inferred in the microsatellite data corresponded to known recent invasive populations in Africa and Hawaii. Interpretation of this pattern would normally imply recent common ancestry between these locations; however, it is much more likely in this case that the pattern shows the effect of separate founder events in each location , but there was very limited integration of that data with non‐Indian populations , another tropical fruit fly species which has demonstrated the capacity to survive temperate winters (Meats, B. dorsalis invasion is progressing, whether there is ongoing gene flow with the source population/s, and whether there are morphological or molecular characteristics associated with the invasion front, can help inform management and prevention of novel invasions into Europe and North America.Within China, the ongoing northward spread of s Meats, . UnderstB. tryoni into temperate Australia (Sultana, Baumgartner, Dominiak, Royer, & Beaumont, B. dorsalis into regions that were considered climatically unsuitable poses a threat not only to northern China, but also to ecologically similar areas in Europe and North America should it establish on either continent.From the extensive sampling within China conducted here, our data suggest that there are only subtle signatures associated with the invasion front. Central Chinese flies possessed the largest wings of any sampled group and were significantly different to South and South‐East Asian populations; however, they were not significantly different to southern Chinese populations. Larger body size in northern populations may be an adaptation to cooler temperatures, following a Bergmann cline type model (Blackburn, Gaston, & Loder, 4.3B. dorsalis's entire geographic range, no macrogeographic population structuring was observed: a result fully consistent with prior studies which have covered individual components of the range (Choudhary et al., B. dorsalis, no significant differences have been detected between populations (Hallman, Myers, Jessup, & Islam, Despite our extensive sampling across B. dorsalis into Central China, without any apparent strong selective pressure, must pose a deep concern for other temperate regions of the world, especially Europe and North America. The invasion and spread in the last decade of spotted‐wing drosophila, Drosophila suzukii Matsumura, across both Europe and North America, has demonstrated just how susceptible the fruit growing industries in those continents are to polyphagous fruit feeders (Lee et al., B. dorsalis attacks fruits from well over 20 plant families and is generally regarded as one of global agriculture's most damaging insects (Clarke et al., The current movement of The authors declare no conflict of interest.https://doi.org/10.5061/dryad.kh0f141; DNA sequences: Genbank accessions MG687532‐MG692399.Wing shape data and microsatellite genotypes data for this study are available at Dryad Digital Repository:  Click here for additional data file.


P ≤ 1.56E-03) allelic frequencies and genotype distributions in many study markers in comparison with African, European, American and Asian populations. Based on FST values, the Amerindian population was also the most distinct (mean FST = 0.09917). These data highlight the unique genetic profile of the indigenous population from the Brazilian Amazon region, which is potentially important from a pharmacogenetic viewpoint. Understanding the diversity of ADME- related genetic markers is crucial to the implementation of individualized pharmacogenomic treatment protocols in Amerindian populations, as well as populations with a high degree of admixture with this ethnic group, such as the general Brazilian population.The variation in the allelic frequencies of polymorphic pharmacogenes among different ethnic groups may be responsible for severe adverse reactions to or altered efficacy of a wide variety of drugs. Amazonian Amerindian populations have a unique genetic profile that may have a fundamental on the efficacy and safety of certain drugs. The genetic characteristics of these populations are poorly known, which can negatively impact the systematic application of treatments guided by pharmacogenomic guidelines. We investigated the diversity of 32 polymorphisms in genes responsible for drug Absorption, Distribution, Metabolism and Excretion (ADME) in Amazonian Amerindians, and compared the findings with populations from other continents available in the 1000 Genomes database. We found significantly different ( Much of this inter-individual variability is related to polymorphisms in the genes involved in the Absorption, Distribution, Metabolism, and Excretion (the ADME process) of drugs or the mechanisms that determine their action in the body3.Inter-individual variability plays a fundamental role in the tolerance of and response to a number of different treatments that are widely used in clinical practice6. The principal determinant of this interethnic variability is the allelic frequencies of the polymorphisms found in pharmacogenes, which may vary considerably among different ethnic groups9.The discovery that the response to and tolerance of drugs may vary not only among individuals, but systematically among populations, in particular among different ethnic groups, had a fundamental impact on pharmacogenetic studies, leading to the development of the field of Pharmacoethnicity10, being formed by three principal ancestral groups: European settlers, African slaves, and Amerindians (Native Americans). Five centuries of miscegenation of these groups have resulted in an extremely heterogeneous genetic makeup, and a considerable challenge for pharmacogenetic studies in Brazil13.The Brazilian population is characterized by its high degree of ethnic admixture14 the Amerindian population of Brazil numbers 896 917, representing 0.47% of the country’s population. While this population is genetically distinct, few data are available on the incorporation of modern habits  into its traditional lifestyles. It nevertheless seems likely that distinct patterns of toxicity and response to pharmacological therapies will be found in this ethnic group in comparison with other populations16. However, genomic studies of pharmacogenetic biomarkers are extremely rare in Amazonian Amerindian populations.According to the most recent census (2010) of the Brazilian Institute of Geography and Statistics17.The general lack of pharmacogenomic data for these Amerindian populations represents a major obstacle to the incorporation of Pharmacogenomics (PGx) into the development of individualized treatment protocols designed to maximize the efficacy of therapies in this ethnic group. In this context, the identification of genetic polymorphisms and molecular markers of clinical significance in these populations will be essential for the development of effective treatment protocols not only for this ethnic group, but also for the populations that are admixed with this group, such as the Brazilian oneIn this context, the present study investigated a set of 32 molecular ADME markers in a combined Amazonian Amerindian population, and compared the results with populations representing five continents, obtained from the 1000 Genomes database.The study population was composed of 146 healthy individuals from three Amerindian groups located in the Amazon region of Brazil, selected from a sample database of an epidemiological study of indigenous populations of Pará State. This group included 61 individuals from the Asurini do Trocará group, 25 from the Asurini do Koatinemo group, and 60 from the Kayapó-Xicrin group. The study was approved by the National Committee for Ethics in Research (CONEP), with CAAE number 20654313.6.0000.5172. The informed consent was obtained from each study participant and all research methods in this study were performed in accordance with the approved guidelines.http://www.1000genomes.org), composed of 661 individuals from Africa (AFR), 503For the analyses, these three populations were combined in a single group, denominated IND. For comparison with populations from other continents, we used data obtained from the 1000 Genomes, phase 3 release (available at from Europe (EUR), 347 from the Americas (AMR), 504 from East Asia (EAS), and 489 from South Asia (SAS).www.pharmgkb.org), or it has been pointed in the specific literature as an important biomarker (www.ncbi.nlm.nih.gov/pubmed), and (3) it should also be among the PGx biomarkers recommended for drug dosage adjustment by global drug regulatory agencies.Thirty-two polymorphisms of 16 pharmacogenes were selected based on three main criteria: (1) the marker must be involved in any of the steps of the ADME process; (2) the PGx biomarker should also have high-level clinical annotations or related VIPs in the public database of the PharmGKB , according to the manufacture’s recommendations. The concentration and purity of the DNA were measured with a NanoDrop 1000 spectrophotometer .The polymorphisms of the ADME-related genes were genotyped by allelic discrimination using the TaqMan OpenArray Genotyping technology, with a set of 32 customized assays, which were run in a QuantStudio™ 12 K Flex Real-Time PCR system , according to the manufacturer’s protocol. The Taqman Genotyper software was used for data analysis and to verify the accuracy of the genotype readings, as well as the quality of the genotyping. The data were then filtered for SNPs that deviated from Hardy–Weinberg equilibrium (HWE).The allele frequencies of the Amerindian population were obtained directly by gene counting, and compared with the other study populations . The distribution of the genotypes among the six populations was analyzed using Fisher’s exact test. Pairwise comparisons between populations were also based on Fisher’s exact test, with the p-value being adjusted by the Bonferroni correction, with a critical p-value of 1.56E-03 being considered in all cases.ST). We ran a multidimensional scaling analysis of the FST values to provide a graphical representation of the genetic differentiation of the Amerindian population in comparison with each of the five study populations. The analyses were run in SPSS v.12.0  and Arlequin v.3.518.The inter-population variability of the ADME SNPs was assessed using Wright’s fixation index . The allele frequencies were determined for a total of 32 markers  for the comparisons of allele and genotype frequencies, and the FST values for each pairwise comparison revealed the similarities and differences in the 26 SNPs related to the ADME drug process  analysis of the Fess Fig. ; Table 2The 26 SNPs were also analyzed in pairwise comparisons between the IND population and the mean values for the five 1000 Genomes populations (ALL), as well as each of these populations individually, in order to characterize the unique aspects of the genetic profile of the Amerindian population, in comparison with those of the other populations Table .Table 3PABCB1, ABCC2, ABCC4, ABCG2, SLC22A7, and SLC29A1 genes. In the case of the phase I genes, there were two groups, the CYP2A6 and the DPYD genes with six significantly different polymorphisms. We also observed significantly different distributions in six polymorphisms in six other genes involved in the ADME processing of drug: the ITGB5, MTHFR, RRM1, TP53, TYMP and UMPS genes.In the comparison between the IND and the AFR populations, the distribution of 20 polymorphisms of 14 genes was significantly different between populations. Eight of the polymorphisms involved six transporter genes: the ABCG2, SLC22A7 and SLC29A1. Five polymorphisms were found in the phase I genes, CYP2A6 and DPYD. Four polymorphisms of four other ADME genes were also significantly different, that is, the ITGB5, MTHFR, RRM1 and UMPS genes.By contrast, we identified only 12 polymorphisms of nine genes that varied significantly between the IND and the AMR populations. These included one polymorphism in each of the three transporter genes: ABCC2, ABCG2, SLC22A7, and SLC29A1 genes. Significant differences were also found in the two phase I genes, CYP2A6 and DPYD. A significant level of variation was also found in a further five polymorphisms, of five genes, the FPGS, ITGB5, MTHFR, TP53 and UMPS.In the comparison between the IND and the EAS populations, 16 polymorphisms of 11 genes had a significantly different distribution. These included five polymorphisms of four transporter genes: the ABCC2, ABCC4, ABCG2, SLC22A7 and SLC29A1. In the phase I genes, significant differences were found in one polymorphism of the CYP2A6 gene and in four polymorphisms of the DPYD gene. The analysis also demonstrated significant differences in seven polymorphisms in five other genes related to the ADME: the ITGB5, MTHFR, RRM1, TYMP, and UMPS genes.Pairwise comparisons between the IND and the EUR populations revealed significant differences in 18 polymorphisms in 12 genes. Six of these polymorphisms involved five transporter genes: ABCB1, ABCG2, SLC22A7, and SLC29A1. Six of the variants were also found in the phase I genes, CYP2A6 and DPYD. The five other markers were identified in four other ADME-related genes, ITGB5, MTHFR, TP53 and UMPS.Finally, significant differences were identified between the IND and SAS populations in 16 polymorphisms present in 10 genes. Five of these polymorphisms were present in four transporter genes: 19. High rates of hospitalization due to ADRs are caused, in part, by the standardization of drug doses, which overlooks the variability among patients in factors such as the symptoms of the disease, environmental and genetic characteristics, and ethnicity21.Adverse Drug Reactions (ADRs) are one of the principal causes of morbidity in developed countries22. The main challenge to achieve maximum effectiveness of a drug is also the interindividual variability in drug response. Drug mechanisms focused on targets with genetic support would succeed twice as often as those without it, reducing the clinical trial’s phases due to lower rates of failure caused by lack of efficacy during clinical development23.Another important factor to be considered during treatment choice is drug efficacy, the ability of a drug to achieve the desired effect25. There have been relatively few studies of molecular biomarkers in Amerindian populations, highlighted by the fact that they are absent from the 1000 Genomes database, the largest available collection of data on human genetic variability.Most pharmacogenetic studies focus on Caucasian populations, which cannot necessarily be extrapolated reliably to the application of PGx in other ethnic groups, such as Amerindian, which may have a unique genetic profile resulting from prolonged geographic isolation and inbreedingThis emphasizes the need for the investigation in other ethnic groups, in particular Amerindians, of predictive molecular biomarkers known to play a role in specific treatments or other, as yet undiscovered markers, in order to understand the genetic variability of these populations and to use the knowledge to delineate personalized treatment protocols, in order to improve drug security in Amerindian populations from the Amazon region, as well as in other populations with a high degree of admixture with this ethnic group.ST indices indicate that the Amerindian and African populations were the most distinct genetically, which is consistent with the history of the world’s human populations, in which the Amerindian and African groups represent the extremes of the evolutionary process26.In the present study, we compared the genetic variability of Amerindian populations from the Amazon region with five populations from the 1000 Genomes Project, analyzing 26 genes responsible for the absorption, distribution, metabolization, and excretion of drugs. The FST analysis, the lower values of genetic differences with the Amazonian Amerindians is observed on the East Asian population , which is mainly composed of Chinese and Japanese individuals. This outcome corroborates with the “Bering Strait” hypothesis, which discusses that the settlement of the Americas and the formation of the first Native Americans are due the migrations of Asians populations that occurred less than 15,000 years ago through a land extension known as the Bering land bridge, which joined Northeast Asia and North America27.Still regarding the FST analysis concomitant with the pairwise comparisons analysis, the Amerindian population is genetically most similar to the American population, with significant differences being found in only 12 polymorphisms, and an FST value of 0.06042. The American samples from the 1000 Genomes database includes Colombian (CLM), Puerto Rican (PUR), Peruvian individuals (PEL), and Californian residents of Mexican descent (MXL), who are representative of the different populations of Latin America, which implies a certain degree of genetic similarity with the ancestral populations of South and Central America28.Relying up on the F29. This genetic admixture originated during the European colonization of the New World, when native Americans came into contact with European immigrants arriving on the continent from 1492 onward, and with African immigrants, from 1502 onward30.In fact, high levels of interethnic admixture have already been shown in populations from the Americas, and in particular, from Latin Americaet al. (2012) investigated the exome of the Colombian, Mexican and Puerto Rican populations from the 1000 Genomes database and estimated the contributions of African, European, and Native American ancestors to these populations. The findings of the study indicated that Amerindians contributed 12.8% of the PUR exome, 25.6% of that from CLM, and 47.6% from MXL31. There are still no studies that evaluate the ancestry of Peruvian samples in the 1000 Genomes database, however, Homburger et al. (2015) evaluated 119 individuals from Peru and determined that they had an Amerindian ancestry of 68.3%32.Gravel The profile of the genomic ancestry of Latin American countries thus indicates considerable heterogeneity in terms of the contribution of Amerindians, resulting from the varied history of the formation of these populations, and their degree of interethnic admixture. The study of ADME polymorphisms in native American populations is, therefore, fundamentally importance to ensure the optimal implementation of healthcare programs that include genomic information on both Latin and Amerindian populations.ABCB1, CYP2A6 and DPYD– whose profiles in the Amerindian population were significantly different from the other study populations. The impact on the enzyme activity caused by the allelic variants analysed is described at Supplementary Table 33.Here, we discuss specifically the data on three of the genes – ABCB1 gene (P-glycoprotein encoding [P-gp]) belongs to the ATP-binding cassete (ABC) superfamily of human carriers, and plays a key role in the absorption, distribution, and elimination of drugs within the organism, being considered one of the major determinants of drug resistance34. The rs1128503 and rs1045642 polymorphisms of the ABCB1 gene have been identified as have a potential role in the response to and toxicity of a number of different drugs, including imatinib, opioids and treatments for epilepsy37.The ABCB1 gene and Aliskiren (Rasilez HCT®), an antihypertensive drug. The EMA identifies ABCB1 as the principal efflux system involved in the intestinal absorption and biliary excretion of the drug and contraindicates the concomitant administration of Aliskiren and medications that may influence ABCB1 gene action38. The HCSC also refers to the role of the ABCB1 gene in the Aliskiren efflux system in its drug labelling, contraindicating the use of different glycoprotein inhibitors and other drugs during treatment with Aliskiren39. Polymorphisms on the ABCB1 gene also may cause a polymorphic enzyme of P-gp with diminished activity40, therefore, should also be considered as an influence factor of Aliskiren efficacy.The European and Canadian drug regulatory authorities require the inclusion of pharmacokinetic information on their drug labels on the interaction between the ABCB1 variants (of at least 40%) in the Amerindian populations from the Amazon Region. These variants may reduce glycoprotein activity and thus alter the metabolization of antihypertensive drugs, such as Aliskiren, affecting its efficacy in the treatment of Amerindian populations.In the present study, we found high allele frequencies of the CYP2 genes on chromossome 19 includes six families, one of which is the CYP2A family, with three genes, the CYP2A6, CYP2A7, and CYP2A13. The CYP2A6 gene is highly polymorphic, and its protein product represents one of the principal liver enzymes responsible for the metabolism of drugs and xenobiotics41.The cluster of CYP2A6 gene on its Letrozole label. Letrozole is a chemotherapeutic drug used to treat breast cancer. In vitro studies have shown that it is metabolized primarily in its inactive form in liver microsomes through the action of the CYP2A6 gene42.The Japanese Pharmaceutical Regulatory Agency (PMDA) includes pharmacogenetic information on the CYP2A6 polymorphisms, which modify enzyme activity, may suffer either an increased toxicity profile or treatment shortcomings. There is a wide range of functional activity data for the described variants of CYP2A6, leading to either differences in enzyme activity or mRNA expression and, consequently, protein levels43. Patients with specific polymorphic variants or a combination of CYP2A6 polymorphisms that define them as poor metabolizers may present a twofold increase in their plasmatic concentrations of Letrozole when compared with extensive metabolizers42.Patients identified as poor or normal metabolizers based on their CYP2A6*9 (rs28399433), which was extremely frequent (46%) in the Amerindian population, and much higher than in the other populations, in which the mean frequency is 13%. This indicates that the Amerindian population from the Amazon region has an abnormally high proportion of poor metabolizers, due to the frequency of the CYP2A6*9 variant, which may determine adverse toxic reactions during treatment with Letrozole, and other drugs that are metabolized by the CYP2A subfamily.One of the markers associated with the poor metabolizer profile is DPYD gene is composed of 23 exons at the 1p22 chromosomal locus. This gene encodes the enzyme dihydropyrimidine dehydrogenase (DPD), which accounts for about 85% of the hepatic catabolism of 5-fluorouracil to its inactive metabolic form, 5- fluoro-5,6-dihydrofluorouracil44. Because this is an essential enzyme in the metabolism of 5-fluorouracil, patients with low DPD enzyme activity have a higher risk of developing severe and even lethal toxicities during standard chemotherapeutic treatment with this drug45.The DPYD genotypes as the major non-functional variants of this gene: *2 A (rs3918290), *13 (rs55886062), and rs67376798. The CPIC guidelines characterize phenotypes based on each of these three variants, and strongly recommend the use of alternative drugs or the reduction of the standard 5-Fluorouracil dose by 50% for patients who are either homozygous or heterozygous for any of these three variants46.The guidelines of the Clinical Pharmacogenetics Implementation Consortium (CPIC) indicate three DPYD gene in their pharmacogenetic drug labels. Capecitabine is one of the major 5- Fluorouracil prodrugs used to treatment various types of solid neoplasias. The FDA includes a warning note in its label for this drug (XELODA®), advising patients who have genotypes associated with an absence or reduced activity of DPD that they are at a higher risk of developing severe or potentially lethal adverse reactions47.A number of national drug regulatory authorities include information on the 49.The FDA also includes pharmacogenetic information labels on the potential for severe toxicity in patients with DPD deficiency during treatment with Fluorouracil, describing the different types of adverse reaction presented by patients with homozygous or heterozygous mutations resulting from a partial or total deficiency of the DPD enzyme. The FDA recommends discontinuing permanently the use of Fluorouracil based on the severity of the toxicities observed in patients treated by the 5- FU regimeDPYD gene were identified in our Amerindian population. The allele frequencies of the rs17116806, rs1801159 and rs4970722 markers were all higher than 40%, contrasting with the much lower frequencies found in all other populations around the world. Two of three deleterious polymorphisms mentioned in the CPIC guidelines were identified in our Amerindian population. The frequency of the rs3918290 marker was 1%, similar to that of most other populations, in particular those from Asia. The rs55886062 marker had a frequency of 2%, however, which is relatively high in comparison with the other populations, in which it did not exceed 1%, when present.Nine polymorphic variants of the In our Amerindian population, the frequency of the rs1801133 mutation was consistent with that found in the other study populations (mean = 23%), whereas the rs1801131 polymorphism had a low frequency (9%) compared to the other populations (mean = 25%). This indicates a lower risk of developing serious adverse effects in Amerindian women, associated with the use of contraceptives based on norelgestromin and ethinylestradiol.Up until now, there has been no systematic assessment of the potential response of Amerindian ethnic groups from the Amazon basin to treatment with drugs known to be influenced by genetic polymorphisms. Our study evaluated the unique features in the genetic profile of 26 ADME-related genes in an Amazonian Amerindian population comparing with others continental populations, which may reflect a distinct therapeutic profile in relation to the efficacy and toxicity of drugs marketed widely for the treatment of a range of diseases. Given this, there is a clear need for the understanding of the individual genetic profiles of Amerindians, and the application of this knowledge to the design of specific pharmacogenomic-guided treatment protocols for indigenous Amazon ethnic groups. This approach would also be valid for populations, such as that of Brazil, which present a high degree of miscegenation with this indigenous group. As future perspectives of our research group regarding this study, data on other clinically better known ADME polymorphisms will further be reported in a separate paper.Table SI. Functional Activity of the allelic variants of ABCB1, CYP2A6 and DPYD gene.


Sebastiscus marmoratus. Based on 130 individuals sampled from 10 locations in the northwestern Pacific Ocean, we identified and genotyped 17 653 single-nucleotide polymorphisms. The patterns of genetic diversity and population differentiation suggested that the Okinawa Trough might be the ancestral centre of S. marmoratus after the Last Glacial Maximum. A shallow genetic structure was observed among sampled populations based on the implemented structuring approaches. Surprisingly, we detected genetic homogeneity in two population pairs (i.e. Xiamen–Niigata and Zhuhai–Iki Island), in which populations have large geographical and latitudinal intervals. Population structure and allele frequency distribution based on outlier loci also mirrored the observed genetic homogeneity in the above-mentioned population pairs. Integrated with biological, environmental and genomic data, our results provide possible genetic evidence for parallel evolution. Our study also provides new perspectives on the population structure of S. marmoratus, which could have important implications for sound management and conservation of this fishery species.Understanding patterns of population diversity and structuring among marine populations is of great importance for evolutionary biology, and can also directly inform fisheries management and conservation. In this study, genotyping-by-sequencing was used to assess population genetic diversity and connectivity of  GeneticGasterosteus aculeatus [Engraulis encrasicolus [Gadus morhua [Oncorhynchus mykiss [Clupea harengus [Parallel evolution provides valuable systems for studying the genetics of new adaptations , and ideculeatus –10, Euroasicolus , Atlantis morhua , steelhes mykiss  and Atlaharengus . HoweverSebastiscus marmoratus is probably an ideal candidate for the detection of parallel evolution. With low genetic background noise, the genetic homogeneity in this species [S. marmoratus are roughly identical between SEC and JPN regions [S. marmoratus populations, we applied a genotyping-by-sequencing (GBS) approach to investigate the population diversity and structuring of 10 populations (five Chinese populations and five Japanese populations) sampled from the NWP. The inclusion of S. marmoratus samples from SEC and JPN regions may provide possible evidence for parallel evolution of this species.In the northwestern Pacific Ocean (NWP), with the influence of the Kuroshio Current System (KCS), the ecological conditions between southeastern Chinese (SEC) coasts and Japanese (JPN) coasts are roughly homogeneous . It is t species  allows u species . Reporte regions ,17. It i regions . Therefo2.2.1.S. marmoratus were obtained from 10 locations along the NWP , and then the PCR products were purified. The sequencing was performed in three lanes of an Illumina HiSeq2500 platform, using 150-bp paired-end reads. The library preparation and sequencing processes were performed commercially at Novogene Co. Ltd in Beijing, China.DNA isolation was accomplished by a standard phenol–chloroform extraction protocol, followed by RNase A treatment. The GBS libraries were constructed following Elshire et al. . Briefly2.3.S. marmoratus assembled using SOAPdenovo2 software [p < 0.05 were excluded. The parameter scripts of BWA, SAMtools and VCFtools are shown in the electronic supplementary material. We also tested for departures from linkage disequilibrium (LD) expectations within each sample site and chose to exclude loci that exhibited strong LD . Testinr2 > 0.8 . All datr2 > 0.8 .2.4.fdist approach implemented in Lositan [Fst belonging to the neutral distribution is used to classify loci into one of three selection categories: neutral selection (0.1–0.9), balancing selection (less than 0.1) and divergent selection (greater than 0.995) [Fst, 0.95 confidence intervals and a false discovery rate of 0.1. Five independent runs were performed to further reduce false positives. Secondly, we used a Bayesian model-based approach in BayeScan 2.1 [To identify outlier loci putatively under selection, two different approaches were used. Firstly, we used the  Lositan . The pron 0.995) . OutlierScan 2.1 , which hScan 2.1 . Analyse2.5.π) and expected heterozygosity (He) of each population. Given that genetic diversity indexes are normally correlated to sample size [pheatmap to detect population homogeneity based on allele frequencies. The pairwise fixation index (Fst) for each of the two populations was estimated using Arlequin software and the significance of each pairwise Fst value was assessed by 10 000 bootstrap permutations [α = 0.01) correction [p.adjust in the package stats.The program Arlequin 3.5  was usedple size , rarefacutations . To corrrrection  using thK) was estimated using a cross-validation procedure in the Admixture software. The best value of the coancestry cluster exhibited the lowest cross-validation error (CVE) compared with the other cluster values. In order to further estimate the substructure of S. marmoratus populations, we increased the coancestry clusters spanning from 2 to 10 and ran the analysis with 10 000 iterations. Principal component analysis (PCA) was also implemented using the R package adegenet [cD) with 1000 bootstrap replications on individuals and visually displayed using SplitsTree 4.14.4 [Population structure was investigated by using the program Admixture 1.3.0 . The besadegenet  to deteradegenet  based one 4.14.4 .2.6.E-value 1 × 10−3) against the NR database at the National Center for Biotechnology Information (NCBI) website. In the case of multiple hits, the best match was chosen. Then, the functional annotations of these genes were obtained using Blast2GO [E-values <1 × 10−6, annotation cut-off values greater than 55 and a GO weight greater than 5.The contigs containing outlier loci were used as queries in nucleotide searches with BlastX (Blast2GO . This so3.S. marmoratus in this study (n = 20), Zhoushan , Xiamen , Zhuhai , Fangchenggang , Niigata , Kochi , Yokosuka , Tottori  and Iki Island .The 130 individual is study  were sam3.1.n = 180) were identified as outliers, 0.8% (n = 141) were under balancing selection, and the rest (n = 17 332) were considered as the non-outlier dataset.The GBS sequencing produced 212.8 million high-quality reads, with a mean of 1.64 million reads per individual . Quality-filtered reads were mapped against the assembled genome. A total of 563 880 putative SNPs were produced among our samples and 17 653 SNPs were retained following filtering steps. Of these loci, 1.0% . Consequently, inhibition or promotion of such protein expression could result in a broad spectrum of phenotypes. In addition, different geographical populations also need to adapt to a variety of other biotic and abiotic factors not considered in this study.3.3.π) of S. marmoratus was 0.136 ± 0.064 and ranged from 0.074 to 0.199 within each sample location. The global observed heterozygosity (Ho) and expected heterozygosity (He) were 0.130 ± 0.077 and 0.136 ± 0.066, respectively, and the estimates within each population ranged from 0.152 to 0.185 and from 0.158 to 0.202, respectively  except for the Niigata–Xiamen and Yokosuka–Kochi pairs, indicating a certain degree of population differentiation.The pairwise ntiation . HoweverK = 1), suggesting population panmixia. As the K value increased, the plots showed six genetic subpopulations when K ranged from 5 to 10: (1) RS, (2) ZS, (3) XM, NI, (4) KO, YO and TO, (5) IK, ZH and (6) FCG (a), showing genetic homogeneity among sampled populations. The NJ tree mirrored the results of the Admixture and PCA analyses, showing shallow genetic structuring across all populations (b).Different methods of determining population structure generally produced similar results. The most likely numbers of the coancestry cluster were one ( (6) FCG . The PCA (6) FCG a, showinulations b.FigureIt is worth noting that the substructure of the Admixture analyses revealed an unexpectedly close relationship in two population pairs (i.e. XM-NI and ZH-IK), where the populations within the pairs have large geographical and latitudinal distances . Given t4.S. marmoratus populations. S. marmoratus is a demersal rockfish with restricted migration during the juvenile and adult life history and thus is considered to disperse only during the larval stage. However, given a very short pelagic larval duration lasting about 10 days [S. marmoratus were almost exposed during the last glacial period [S. marmoratus, integrated with the highest genetic diversity of population ZS. Similar inferences were also derived in the population genetic studies of Lateolabrax maculatus [Synechogobius ommaturus [Thamnaconus hypargyreus [In the present study, using high-resolution genomic SNPs, weak but statistically significant levels of genetic differentiation were detected among  10 days , larval l period , so thisl period . Under saculatus , Synechommaturus  and Thamargyreus .S. marmoratus. A similar conclusion was also drawn in the Atlantic herring case [S. marmoratus populations. To our knowledge, this might be the first report of parallel evolution in the NWP.Understanding the capacity of natural populations to adapt to their local environment is a central topic in evolutionary biology . Geograping case , in whicing case –10 and Aing case , given sS. marmoratus. Further studies linking environment, genotype and biology are warranted to fully demonstrate the pattern of parallel evolution in this species.In spite of the large geographical and latitudinal interval, the habitats of SEC and JPN regions are generally homogeneous because of the influence of the KCS . Environ