Sitodiplosis mosellana, is an important pest in Northern China. We tested the hypothesis that the population structure of this species arises during a range expansion over the past 30 years. This study used microsatellite and mitochondrial loci to conduct population genetic analysis of S. mosellana across its distribution range in China. We found strong genetic structure among the 16 studied populations, including two genetically distinct groups (the eastern and western groups), broadly consistent with the geography and habitat fragmentation. These results underline the importance of natural barriers in impeding dispersal and gene flow of S. mosellana populations. Low to moderate genetic diversity among the populations and moderate genetic differentiation (FST = 0.117) between the two groups were also found. The populations in the western group had lower genetic diversity, higher genetic differentiation and lower gene flow  than those in the eastern group . Genetic distance between populations was positively and significantly correlated with geographic distance . The population history of this species provided no evidence for population expansion or bottlenecks in any of these populations. Our data suggest that the distribution of genetic diversity, genetic differentiation and population structure of S. mosellana have resulted from a historical event, reflecting its adaptation to diverse habitats and forming two different gene pools. These results may be the outcome of a combination of restricted gene flow due to geographical and environmental factors, population history, random processes of genetic drift and individual dispersal patterns. Given the current risk status of this species in China, this study can offer useful information for forecasting outbreaks and designing effective pest management programs.The wheat midge,  Sitodiplosis mosellana (Diptera: Cecidomyiidae) is one of the most destructive pests of wheat, and is distributed in most wheat-producing regions of the world, including Europe, Asia, and North America S. mosellana was first detected in China in the early 1310s. This species has one generation per year. Females live for 3–7 days and lay 60–80 eggs. The larvae hatch after 4–7 days, crawl into the floret and feed on the surface of developing wheat kernels for 2–3 weeks. Once moist conditions are detected, the mature larvae drop to the ground, burrow into the soil and overwinter as diapausing cocooned larvae. Most overwintering larvae may remain in diapause for 1–2 years, though a few can maintain diapause for up to12 years The wheat midge (Géhin) S. mosellana. The geographical distribution of S. mosellana over the past 30 years has shifted to the northeast of about 400 km S. mosellana outbreaks have continued to affect certain wheat fields S. mosellana has been effectively controlled, it still remains a serious pest in some regions of China Northern China is the major wheat-producing area in China, and is a region with complex topography  and variable climate. This region is also the main distribution area of Genetic diversity and population structure are important aspects of the population genetics of agricultural insects. Comparative studies of these aspects can therefore help to elucidate the factors affecting their population levels. The results of previous studies have shown that the genetic diversity and population structure of a species may be affected by several factors, such as climate change, environmental and ecological factors, natural barriers, human activities, migration and gene flow, and that these factors often act in combination S. mosellana. The results of such an analysis will provide essential information for understanding possible local adaptation and dispersal patterns, and for further clarifying the relationship between genetic variation and outbreaks of wheat midge in China. However, the limited number of markers available for analyzing geographic populations and individuals means that few population genetic studies of S. mosellana have been conducted Molecular genetic techniques, such as simple sequence repeat and mtDNA analyses, can be used to conduct a genetic analysis of S. mosellana across a broad geographic area in northern China. This is the first study to investigate the population genetics of S. mosellana comprehensively, and the results may provide more useful data for forecasting outbreaks and managing this species in China (e.g. by breeding resistant wheat varieties). These findings may also have significant implications for other regions where this species occurs.Based on background knowledge, we used two molecular markers (microsatellites and mtDNA) that have been widely used in many insect population genetic studies Sitodiplosis mosellana is a pest insect of wheat. The study of this pest is welcomed by farmers because understanding the behavior of this pest may be helpful to protect their wheat from pest damage. Thus, no specific permits were required for the described field studies.This study was carried out on private land, and we had got permission from the owners of these sites to conduct this study. Additionally, the field studies did not involve endangered or protected species.S. mosellana were collected from 16 geographic sites in northern China from May to Sep. in 2009–2011  and then mixed together. Larvae (still in the soil) were maintained at 22±1°C, 70–75% relative humidity and a photoperiod of 14-h light∶10-h dark through pupation and adult emergence stages. Adults from each site were collected daily and stored individually in 75% ethanol at −20°C until DNA extraction was performed according to Collins et al. Soil samples containing larvae of 009–2011 , rangingGAGTGGCAGGAAACAAGAGC, EW353 -R: TCATTGATGGAAGACTCACTT; EW548-F: ROX-TGCGAATCGATACCATAGGC, EW548-R: ATTGCCTGGAATTTTCCCTC; EW892-F: ROX-CCTCTCATTGATGCGTGTCT, EW892R: TTGAGTACCAGATTGCATTTCA; Tig99-F: FAM-GTGGAAATACGGTGCCATTT, Tig99-R: TCTTTCTCTCTCTCTGGCGG, respectively. The PCR reactions were carried out in a 20-µL reaction mixture containing 20–40 ng total DNA, 2.0 µL of 10× Taq DNA polymerase reaction buffer (Mg2+ free), 1.8 µL of 25 mmol/L Mg2+, 2 µL of 0.5 mmol/L dNTPs, 1.0 µL of 10 pmol/µL each primer, 11 µL ddH2O, 0.2 µL of Taq E (5 U/µL)  and 2 µL of DNA template. Reactions were carried out using a SensoQuest LabCycler 2.2  thermocycler for 35 cycles. After initial denaturation for 3 min at 95°C, each cycle comprised denaturation at 94°C for 1 min, 45 s at the annealing temperature of each primer, 50 s extension at 72°C, with a final extension at 72°C for 10 min. Annealing temperatures varied from 55°C for EW353, 56°C for EW548 and Tig99 to 57°C for EW892. Following amplification, the products were visualized at Sangon Biotech Co., Ltd.  using an ABI 3730XL automated sequencer . Microsatellite alleles were analyzed using GeneMapper4.0 software (Applied Biosystems). Microsatellite data were checked for errors and null alleles with MICROCHECKER V2.2.3 All individuals were genotyped at four microsatellite loci: EW353, EW548, EW892 and Tig99 ND4 and COX3 mtDNA using the following primers developed in this study: ND4-F (5′- GAAATAGGAG-AAGATATATT-3′), ND4-R (5′-TTGAAATAAGATTAATTCCTAC-3′); COX3-F (5′-ACGA-GATGTAACTCGAGAAAG-3′), COX3-R (5′-ATCAAGCTGCAGCTTCAAATC-3′). Annealing temperatures were 45°C for ND4 and 52°C for COX3. Following amplification, the products were sequenced by Sangon Biotech Co., Ltd. using the ABI-PRISM 3730 genetic analyzer (Applied Biosystems) using the same primers. The obtained sequence chromatograms were read with Chromas 2.33 . All haplotypes have been submitted to GenBank (Accession numbers: KF030063–KF030131).Polymerase chain reaction (PCR) was used to amplify the target sequences from Midges collected from each sampling site were assumed to represent local populations for the purposes of statistical analyses. To investigate the hypothesis that ecological, geographic and climatic factors may affect genetic variation, gene flow and population structure in this species, samples were divided into two groups throughout the region: the eastern group, including 10 populations ; and the western group including six populations .Ne), observed heterozygosity (Ho) and expected heterozygosity (He) for each population, calculated using PopGen 32 (version 1.31) For microsatellites, linkage disequilibrium was tested among all pairs of loci across all populations using GenePop 4.0 DH) and nucleotide diversity (π) as defined by Nei Sequence data for mtDNA were assembled and aligned using Clustalx2 (version 2.0.12) FST and Nm based on allele frequencies were calculated to estimate the degree of genetic differentiation over all populations using PopGen32. Pairwise FST values were used to estimate and assess the magnitude of differentiation among geographic populations using Arlequin v 3.5.1.2 estD values estD across loci. For mtDNA ND4, pairwise FST values based on haplotype frequencies were calculated using the program Arlequin v 3.5.1.2.For microsatellites, DH), intrapopulation diversity (SH), total genetic diversity (TH), population differentiation (GST) and gene flow (Nm) were also compared in DnaSP between the eastern and western groups of S. mosellana.Haplotype diversity  with their coordinates. For testing of statistical significance, 10,000 permutations in Mantel tests were used to test the null hypothesis that genetic distance and geographical distance were independent. These results were plotted in SPSS 12.0 for Windows .To determine if genetic and geographic distances between populations were significantly correlated, isolation by distance (IBD) was examined by testing the correlation between pairwise S. mosellana populations using multilocus genotype data. This program uses a coalescent genetic approach to cluster similar multilocus genotypes into K clusters, regardless of an individual's geographical origin. We conducted eight independent runs for each value of K ranging from 1–12 using the admixture model and correlated allele frequencies. To detect the true K present in microsatellite data, an ad-hoc measure ΔKK1–K12 was used across all runs. Each run consisted of a burn-in of 10,000 steps, followed by 20,000 Markov chain Monte Carlo repetitions.The Bayesian approach implemented in STRUCTURE version 2.2.3 S. mosellana populations identified by pairwise FST and STRUCTURE, hierarchical analysis of molecular variance (AMOVA) FST (using mtDNA ND4 haplotype frequencies) was carried out using Arlequin. The AMOVA program allows the hierarchical partitioning of the variance components into three components: within populations, among populations within groups and among groups. Significance of fixation indices was also tested using a nonparametric permutation approach with 2,000 permutations using the same software.To apportion variance between the eastern and western groups of 16 K = 2), previously inferred by STRUCTURE software using the Bayesian approach. Individuals were assigned to a group if the proportion ancestry ≥0.7; when no group was ≥0.7, the individual was unassigned and considered to be of mixed ancestry. Population assignment tests were also performed across all sites in this software (K = 5). Due to generally high levels of admixture, a threshold value of 70% was used when assigning membership of the sampling sites in the determined groups.Each individual was assigned to a group  .Compared with conventional phylogenetic trees, haplotype networks can enhance the relationships among haplotypes and are preferable for intraspecific analyses. Unrooted networks of haplotype of S. mosellana using two neutrality tests (Tajima's DSFP<0.05 for D and SF). According to coalescent theory, a population usually exhibits a unimodal mismatch distribution following a recent population demographic or range expansion Demographic history changes were analyzed for The program BOTTLENECK v1.2.02 P>0.002 for all after Bonferroni corrections). Most populations deviated significantly from HWE (P<0.01) . Microchecker confirmed the presence of null alleles in three out of four loci . Single locus deviations from HWE (after Bonferroni corrections with P<0.001) were attributed to heterozygote deficiency in 21 out of 64 tests. However, these loci did not show consistent deviations across all populations. We therefore assumed that processes causing this nonequilibrium were specific to those populations, and we thus continued to include those loci in subsequent analyses.The four microsatellites were amplified in 374 individuals. Considerable variation was observed at all microsatellite loci. All four loci investigated were polymorphic both within and among populations. There was no evidence for linkage disequilibrium within any of the four loci  values across microsatellite loci ranged from 3.50 in WW to 7.00 in HuaX, with a mean value of 5.75. Observed heterozygosity (Ho) values and expected heterozygosity (He) values across loci ranged from 0.32–0.79 and 0.45–0.72, respectively. Excluding four populations of ZZ, LF, WW and YC, observed heterozygosity (Ho) values were lower than expected heterozygosity (He) values. Allelic richness (Ar) per population ranged from 3.09–6.64. The mean gene diversity across loci was 0.64 with the lowest in WW (0.44) and the highest in ZZ (0.72), indicating a high level of information of the chosen microsatellite. The inbreeding coefficient (Fis) ranged from 0.02–0.61. Combining ND4 and COX3, 15 out of 16 populations exhibited comparatively high haplotype diversity (excluding WW). The haplotype diversity and nucleotide diversity of these populations ranged from 0.28±0.016 to 0.82±0.025 and 0.0013±0.0005 to 0.0058±0.0004, respectively. Reduced levels of mtDNA genetic diversity were observed in three populations of LT, WW and YC compared with the other 13 populations.Basic summary statistics of genetic diversity are presented in P<0.001). More generally, the eastern populations showed higher genetic diversity  compared with the western populations . This phenomenon was supported by mtDNA analysis.The present microsatellite data indicated that many populations (12 out of 16 populations) had a deficiency of heterozygotes with significantly positive F values  and positively correlated with longitude . Altitudinal trends were usually stronger than longitudinal ones, especially in terms of allelic richness measures. There were no remarkable correlations (P>0.05) between latitude and several diversity parameters in this study.Analysis of correlations between geographic variables and diversity parameters indicated that allelic richness, expected heterozygosity and genetic diversity were all negatively correlated with altitude (FST and estD) based on microsatellite data , and pairwise estD values ranged from 0.000–0.431 (mean 0.157). The pairwise estD values showed an overall similar pattern to the pairwise FST values, though the estD values were on average slightly higher. An overall randomization test of population differentiation was significant for all loci combined (P<0.001).Genetic differentiation of all populations was measured using two different statistics  among the western populations compared with the eastern populations . The mean FST value between the eastern and western groups was 0.117. All the investigated loci contributed to this population differentiation .Pairwise FST values ranging from 0.22–0.45 and highly significant differentiation for exact tests across all populations, suggesting that the differentiation signal among all populations in mtDNA was stronger than that in microsatellites. DnaSP analysis indicated GST = 0.212, Nm = 0.39 for all populations; GST = 0.059, Nm = 3.96 for the eastern group; and GST = 0.078, Nm = 2.64 for the western group. Based on mtDNA ND4 and COX3, the total haplotype diversity was 0.852, and the within-population diversity was 0.5065. HST of the total population was 0.237, indicating a strong differentiation among populations (P<0.001), among the eastern populations  and among the western populations . Although comparison of gene flow between the eastern and western groups was significant (Nm>1), there was insufficient evidence to prevent genetic differentiation.mtDNA analysis using Arlequin software showed similar results to the microsatellite data  with FSS. mosellana populations  , suggesting that the genetic population differentiation (gene flow) of this species may follow an IBD pattern. However, there was no evidence to indicate a correlation between genetic and geographic distances within the eastern group of 10 populations    and withP<0.001)  (FST vs= 0.389) .S. mosellana populations, we used an admixture model implemented in STRUCTURE software to explore different numbers of populations K to the population structure based on microsatellite data. Considerable population structure was detected with LY+JN+FN+XS+XT+TJ+BJ+NY+HX+LC and HuaX+ZZ+LF+LT+WW+YC as two independent groups at K = 2, which was consistent with the hypothesis that these populations could be divided into two groups (the eastern and western groups), broadly corresponding to the two geographical areas  among groups and within populations , while variation among populations within groups was 6.13%  (P<0.0001).Assuming that the genetic groups inferred from the Bayesian analysis represented two gene pools, we performed AMOVA for these populations. Similar results were also obtained when AMOVA was carried out considering the eastern and western groups based on mtDNA analysis, showing significant variation  . OverallK = 2), with 176 individuals assigned to the eastern group and 123 individuals retained in the western group. Twenty-eight individuals were identified as migrants and 47 individuals as of mixed ancestry. Compared to the western populations (mean 81.3%), the eastern populations (mean 74.5%) tended to have lower assignment accuracy on average. The assignment test was successful for some populations (e.g. 100% assigned for WW and YC populations). Furthermore, with membership probabilities of ≥70%, the LC population was a mixture of insects from two groups, and may represent an intermediate type between the eastern and western populations.Individual assignment by STRUCTURE analysis indicated that 65–100% of the individuals from 15 populations (excluding LC) were assigned with membership probabilities of ≥70% . A totalP<0.01), with 18 out of 134 (13.4%) from the western populations as present-generation migrants, while only six out of 216 (2.7%) from the eastern populations (excluding LC) were identified as migrants. No migrants originating from the WW and YC populations were detected in other populations.The detection of migrants using GENECLASS produced very similar results to that using STRUCTURE. Twenty-four individuals were identified as migrants (S. mosellana were clearly segregated into two discrete groups (the eastern and western groups), which was consistent with the results analyzed by STRUCTURE. LC was separated from other nine populations in the eastern group with 78% bootstrap support, and significant clustering was observed among the western populations.The unrooted NJ dendrogram obtained from Nei's genetic distance  showed tND4 (ND4 and COX3 (K = 5) (The unrooted NJ tree of 42 haplotypes of ND4  and hapl (K = 5) , showed S. mosellana populations using mtDNA ND4. Tajima's D and Fu's SF tests were not significant (P>0.05) for all populations (SF tests (P<0.05) for the eastern and western groups, and when all populations were combined. The mismatch distribution analysis of overall populations of S. mosellana tended to be unimodal    using WiS. mosellana is widely distributed in Northern China, which includes many different geographic and biogeographic areas and can be divided into eastern and western regions according to geographic position. The results of the present study indicated that S. mosellana populations across its geographic distribution could also be divided into eastern and western groups in terms of their adaptations to different geographical and ecological environments in northern China. Significant differences in geographical and environmental factors between the two regions have led to great differences in genetic diversity, genetic differentiation and population structure of S. mosellana, which has been demonstrated at several scales.Recent advances in statistics and population genetics make it possible to investigate how geographical  and environmental (e.g. temperature and precipitation) factors affect the genetic diversity and population structure of a species S. mosellana populations S. mosellana (excluding WW) harbor moderate to high genetic diversity, indicating their ability to adapt to varying environmental conditions. The eastern populations exhibit a higher degree of genetic diversity than the western populations, suggesting that fragmented habitats, migration (decreased or eliminated) between populations and genetic drift have probably contributed to the loss of diversity of the populations in the western region . S. mosellana has recently undergone a substantial northeastern range expansion in China, including recent establishments in Tianjing and Beijing, which may be a cause of the low levels of genetic variation among the eastern populations. Analyses of the relationships between geographic variables  and genetic diversity  showed that the former are important factors leading to differences in genetic diversity among S. mosellana populations.Genetic diversity is the basis of an organism's ability to adapt to changes in its environment, and can be affected by many factors S. mosellana populations S. mosellana populations exhibit significant genetic differentiation, with FST values ranging from low to high among these populations. IBD tests identified a positive correlation between genetic and geographic distances in the populations, especially among the western group, suggesting that these populations are differentiated by a process of IBD, and that genetic drift is a much stronger force than gene flow. The present findings are partly consistent with those of prior studies Previous studies found obvious genetic differentiation between spring wheat-region and winter wheat-region groups among FST (estD) values also revealed significant genetic differentiation between the eastern and western groups (FST = 0.11), indicating that they are in two different gene pools and have evolved independently for several hundreds of thousands of years. AMOVA analysis based on mtDNA data indicated high genetic differentiation among populations, with about 50% of the genetic diversity that existed among groups.The FST, implying that drift may play a much larger role in determining allele frequencies in these populations than in other populations.Compared to the eastern populations, higher genetic differentiation and lower gene flow were detected among the western populations, which may be the result of broken topography with numerous mountains and small plateaus characterized by very diverse climates in this area, leading to predominantly small-scale wheat growing. The populations of YC and WW had substantially higher levels of S. mosellana represented by the Taihang mountains may reflect this organism's dispersal ability and its adaptation to climatic variables. Mountains have also been shown to act as geographic barriers shaping the population structure of the other terrestrial species Locusta migratoriaPaeonia rockiiThe geographical structuring of haplotypes was significantly different between the eastern and western groups, which could be divided into two groups. The results suggest that mountains  have been a major geographic barrier limiting gene flow between the eastern and western groups in this species, with significant isolation between the populations on either side of the Taihang mountains. The geographic barrier to gene flow in S. mosellana arises during range shift in Northern China. A previous study found that S. mosellana could be divided into three groups: a spring wheat-region group, a winter wheat-region group and a mixed winter and spring wheat-region group S. mosellana was mainly characterized by geographic isolation. The Bayesian clustering method revealed the presence of two distinct (eastern and western) lineages of S. mosellana, corresponding largely to patterns of habitat fragmentation and geographic origin.We tested the hypothesis that the population structure of S. mosellana populations is not static. Compared with the eastern populations, the western S. mosellana populations are significantly differentiated from each other and more substructured. This study indicates that the complex and diverse topographic configuration in northern China  might have played an important role in shaping the genetic divergence and population structure of S. mosellana. The mountains in particular have played a more significant role in the genetic substructuring of S. mosellana populations than linear distance, and the current results suggest that the Taihang and Qinling mountains may be considered as isolated management units in terms of control efforts.The weak signal for division into five groups, combined with the high frequency of accurate assignments, suggests that fragmentation of the S. mosellana. Notably, the present study identified the presence of admixed individuals in most of these populations, suggesting that migration of S. mosellana occurred historically, and that this species is not only able to move between localities on occasion, but is also able to reproduce in the new area, thereby contributing to the genetic diversity of subpopulations.Migration analyses detected a high number of potential migrants mainly among the western populations (excluding the populations of WW and YC), indicating asymmetric migration from the western populations to the eastern populations. However, this is apparently not sufficient to overwhelm the effect of drift in the isolated areas and to maintain genetic similarity across the western range of S. mosellana may be affected by topography, wind, water and human activities. Our data also showed that the Qinling mountains could be considered as an important dispersal corridor allowing genetic exchange, as well as identifying isolated areas. The relatively strong global population structure and low degree of genetic variation within populations suggest that S. mosellana has a low capacity for active dispersal, but can disperse passively over long distances by wind, water and human-mediated transport This study indicates that the migration of S. mosellana make it necessary to understand its population structure and population dynamics in a mixed landscape in China. However, this aspect has been poorly studied to date. The results of the current genetic analyses of S. mosellana have important implications for the development of more effective and preventive pest management strategies in China, and for predicting population responses to climate change. To the best of our knowledge, this study is the most comprehensive report on the population genetics of S. mosellana at multiple scales across a broad geographic area in China. However, S. mosellana has a broad geographic distribution, and the diverse topography within its native range means that it shows strong regional subdivision in China. More detailed inferences about its phylogenetic and phylogeographic patterns are likely to be studied in the future, and require further sampling throughout China.The widespread agricultural impact and rapid range expansions of Figure S1ND4 based on genetic distances. Bootstrap support above 50%  is indicated by gray branches.Neighbor-joining tree of haplotypes of (TIF)Click here for additional data file.Figure S2Mismatch distributions of pairwise nucleotide differences for total populations of S. mosellana using gene sequences of ND4 (A) and COX3 (B). Solid lines show the observed frequency distributions and dashed lines show the distribution expected under the sudden-expansion model.(TIF)Click here for additional data file.Table S1Pairwise genetic distances across all populations of S. mosellana based on mtDNA ND4 using Arlequin v3.5.1.2.(DOC)Click here for additional data file.Table S2Analysis of molecular variance of S. mosellana based on mtDNA ND4 (K = 2).(DOC)Click here for additional data file.Table S3Analyses of natural tests of Tajima's D and Fu's sF and bottlenecks in 16 populations of S. mosellana.(DOC)Click here for additional data file.


Quercus variabilis) is one of the most widely distributed species in eastern Asia. In this study, leaf material of 528 Q. variabilis trees from 50 populations across the whole distribution  was collected, and three cpDNA intergenic spacer fragments were sequenced using universal primers. A total of 26 haplotypes were detected, and it showed a weak phylogeographical structure in eastern Asia populations at species level, however, in the central-eastern region of Mainland China, the populations had more haplotypes than those in other regions, with a significant phylogeographical structure . Q. variabilis displayed high interpopulation and low intrapopulation genetic diversity across the distribution range. Both unimodal mismatch distribution and significant negative Fu’s SF indicated a demographic expansion of Q. variabilis populations in East Asia. A fossil calibrated phylogenetic tree showed a rapid speciation during Pleistocene, with a population augment occurred in Middle Pleistocene. Both diversity patterns and ecological niche modelling indicated there could be multiple glacial refugia and possible bottleneck or founder effects occurred in the southern Japan. We dated major spatial expansion of Q. variabilis population in eastern Asia to the last glacial cycle(s), a period with sea-level fluctuations and land bridges in East China Sea as possible dispersal corridors. This study showed that geographical heterogeneity combined with climate and sea-level changes have shaped the genetic structure of this wide-ranging tree species in East Asia.The biogeographical relationships between far-separated populations, in particular, those in the mainland and islands, remain unclear for widespread species in eastern Asia where the current distribution of plants was greatly influenced by the Quaternary climate. Deciduous Oriental oak ( Quercus spp.) retreated to several refugia in the Iberian Peninsula, Italy and the Balkans during the Last Glacial Maximum  period. During the inter-glacial periods, they recolonized the northern areas from these refugia The climatic changes of the Quaternary  have exerted a profound influence on the patterns of modern plant distribution and evolution at the global scale Similarly, East Asia experienced strong climate oscillations during the glacial and interglacial periods although no massive glaciers occurred since the Quaternary Relative to European and North American continents, eastern Asia showed a higher diversity of plant species due to unique topography and climate of the eastern Asia region since Quaternary Ostryopsis davidiana Decne in north China Ginkgo biloba in south China Juniperus przewalskii in northeast Qinghai-Tibetan Plateau Cyclobalanopsis glauca in Taiwan Island Aucuba japonicaAristolochia kaempferiKirengeshoma species distributing in eastern China, southern Korea and Japan. However, the distribution ranges of these species do not cover the large part of eastern Asia, and it would be an advantage to examine how Quaternary climate impacted the retreat, migration, and re-colonization of a plant species distributed across the eastern Asia.With molecular data coupled with coalescent theory, distributional and demographic change through evolutionary time and the identification of glacial refugia have been conducted for Quercus variabilis) is one of the most widely distributed deciduous species in eastern Asia (latitude from 24° to 42° N and longitude from 96° to 140°E), and it covers Mainland China, Zhoushan Archipelago, Taiwan Island, Japanese Archipelago, and Korean Penninsula  and is an ideal species to study possible climate impact on the species distribution. There have been some small-scale investigations of population diversity by using nuclear gene or plasma gene marker for the species. For example, population genetic diversity of Q. variabilis has been investigated within Shaanxi and Henan provinces using isozyme Q. variabilis distribution Oriental oak  how the identified haplotypes are distributed within and among populations of Q. variabilis; 2) how genetic variation is distributed between and within populations; 3) is there a phylogeographic relationship among the populations, in particular, between the populations growing in the Mainland China and the peripheral populations in the Archipelagoes and Island populations in Zhoushan, Japan and Tawain, and 4) what is possible paleodistribution and population demographic history of Q. variabilis in pan-eastern Asia. With information above, we could deduce the possible glacial refugia status in the eastern Asia during LGM period and explore the possible roles of land bridges in influencing geographic distribution of the species during the glacial period.In 2008, we collected the samples of 50 Q. variabilis populations were selected across the entire natural distribution area of Q. variabilis in East Asia in 2008. Thirty-four populations were from Mainland China, three from Zhoushan Archipelago which located in East China Seas, four from Taiwan Island, three from Korea Peninsula and the remained six from Japanese Archipelago  primes  were selected according to sequencing performance and variation results , 50 mM KCl, 0.2 µM of each primer, 200 µM of each dNTP, 1.25 U of Taq polymerase (TaKaRa) in a total volume of 50 µl. PCR was conducted on a Mastercycler pro Thermal Cycler , and performed with initial denaturing of 5 min at 94°C followed by 35 cycles of 30 s at 94°C, 30s of annealing at 55°C, 90 s of elongation at 72°C, ending with a 10-min extension at 72°C. The products were checked on a 1% agarose gel, and then the products with a single band were directly sequenced in both directions by standard methods using a Taq dye deoxy terminator cycle sequencing kit on an Applied Biosystems Model 3730xl automated sequencer .Approximately 50 mg silica gel-dried leaves were grounded using Precellys 24 tissue homogenizer . Genomic DNA was extracted from leaf powder using modified hexadecetyltrimethyl ammonium bromide (CTAB) procedure based on Doyle’s  results . PolymerHd) were calculated using DnaSP v5 Multiple alignments of the sequences were obtained using the program CLUSTALW Q. variabilis populations was divided into seven regions (marked from 1 to 7 in HS), total gene diversity (HT) and two parameters of population differentiation, GST  NST (coefficient of genetic variation influenced by both haplotype frequencies and genetic distances between haplotypes), were estimated by the program PERMUT (available at www.pierroton.inra.fr/genetics/labo/Software/) NST than GST. A higher NST than GST usually indicates the presence of phylogeographic structure with similar (closely related) haplotypes, being found more often in the same area than less similar haplotypes FST between mainland and islands populations and among islands populations.In order to estimate genetic differentiation among the populations from different geographic regions, the distribution range of FST/(1−FST) was calculated in ARLEQUIN and geographical distances were estimated with the program FOSSIL, and implemented in R language.Isolation by distance (IBD) Quercus7 generations, with sampling every 2000th generation, following a burn-in of the initial 10% cycles. The phylogenetic evolutionary tree was edited in FigTree v1.3.1 software (http://tree.bio.ed.ac.uk/software/figtree).Phylogenetic evolutionary tree of haplotypes was created by BEAST 1.7.3 which is a Bayesian statistical framework DSFD and F can be expected in cases of population expansion. Based on phylogeographical structure results, the demographic history of both populations in Central-Eastern China and East Asia was investigated using mismatch distribution analysis (MDA) in ARLEQUIN, to assess whether intraspecific lineages experienced past population expansions. The sum of square deviations between the observed and expected distributions and the raggedness index of the observed distribution were used as test statistics to validate fit of the models Tajima’s Q. variabilis population demographic expansion. First, the expansion time was estimated directly from the mismatch distribution with the statistic τ (tau) and translated into absolute time in years (t), using the equation T = τ/2u u is the neutral mutation rate for the entire sequence per generation and is calculated as u = µkg, where µ is the substitution rate in substitutions per site yr−1 (s/s/y), k is the average sequence length of the cpDNA region under study , and g is the generation time in yr . The mean substitution rate of the three combined cpDNA-IGS regions was obtained from the corresponding clock-calibrated BEAST tree of Q. variabilis. Second, we employed coalescence-based skyline-plot method to date population size changes over time (Bayesian skyline plot: BSP) using the BEAST program and Tracer v1.5 software (http://tree.bio.ed.ac.uk/software/tracer/).In addition, we used two methods to estimate the time of Q. variabilis via MAXENT (version 3.3.3 k) Q. variabilis was based on 325 presence records in the Chinese mainland sourced from Chinese Virtual Herbarium (http://www.cvh.org.cn/cms/) and 150 occurrence records in Taiwan, Japan, and Korea obtained from Global Biodiversity Information Facility (http://data.gbif.org/welcome.htm), after the removal of duplicate and inexistent records according to field surveys within each pixel . Bioclimatic variables were downloaded from the WorldClim database Maximum entropy modelling technique was employed to construct pontential palaeodistribution of Q. variabilis were aligned along a total length of 1670 bp with 23 variable nucleotide sites observed  of haplotypes  while population XY located in Dabie Mountains, Henan province and HZ in Zhejiang province had four haplotypes  . The popH6 existed only in Liaotung Peninsular and Korea Peninsular whereas H10 was only found in Zhejiang province, and H1 occurred only in populations from Anhui province . The Bayesian phylogenetic tree was shown in mv) in the network frame can be recognized in the network that mv1 connects H2, H16, H19 and H21, mv2 connects H9, H19 and H21, and mv3 connects H3, H10 and H17. These median vectors might be an indication that the three genotypes were missing in the sample collection during the sampling process, or were ancestor genotypes which had been extinct A phylogenetic network was established among 26 haplotypes . The netQ. variabilis populations with more haplotypes and higher nucleotide diversity  and nucleotide diversity  or haplotype diversity . Population PG, from Beijing in Northern China  and YB, from Yunnan province in Southwestern China  had the highest haplotype diversity and nucleotide diversity, population TN  and DM  had the second highest diversities, while all other populations  had low or zero diversity  was high  was essentially zero in populations from Southeastern China and 0.294±0.09 for populations from Central-Eastern China. By contrast, inter-population differentiation was the lowest in populations from Central-Eastern China (GST = 0.690±0.095) relative to populations from other regions .The total genetic diversity for all populations (P = 0.012) between GST (0.690) and NST (0.751) in Central-Eastern. This implied that there would be a significant phylogeographical structure in the Central-Eastern China region.There was a significant difference in genetic diversity (P<0.001)  indicated that 79.5% variation was partitioned among populations and only 17.51% of the variation within populations  . HoweverFCT = 0.817–0.832). In contrast, genetic differentiation among populations within Zhoushan and Japanese Archipelagoes and Taiwan Islands was low . This may indicate that isolation by distance effect was minimal in Q. variabilis populations in eastern Asia.Results from divergence test are presented in trnL-trnF, atpB-rbcL, trnH-psbA) chronogram of Q. variabilis (Q. variabilis (PP = 1) as 4.88 Ma , and obtained a point estimate for the coalescent time  of ‘Island’ clade and ‘Inland’ clade, suggesting a Quaternary split in haplotypes between Islands and Mainland in eastern Asia. H11, widespread in Taiwan and Japan Islands, was given a divergence time after 0.42 Ma .The BEAST-derived cpDNA  and the slowest reported cpDNA substitution rates for angiosperms (1.1×10−9 s/s/y), but consistent with the notion that woody taxa and/or phylogenetic relicts should have slower rates of molecular evolution Based on the cpDNA-IGS chronogram of HRag values. For Central-Eastern China populations, demographic expansions supported by significant SSD, spatial expansions supported by nonsignificant SSD and HRag values  . East Asia populations show spatial and demographic expansions supported by uniformly significant SSD and g values . Tajima’The Bayesian skyline plot (BSP) simulated the fluctuation of populations over time. Recent population size increases were observed in Middle Pleistocene (0.78 Ma - 0.13 Ma BP) from 0.5 Ma before present . The resThe test area under curve (AUC) for the ecological niche modelling (ENM), averaged across all 10 runs, was moderately high . The predicted distribution based on the model was similar to the species actual distribution  a, with Pinus tabulaeformisOstryopsis davidianaKirengeshomaDysosma versipellisTaxus wallichianaQ. variabilis had 26 haplotypes detected, with possible 114 missing ones and three un-sampled or extinct ancestral ones, with a complicated phylogenetic network and a lacking of distinct geographic structure . One important distribution characteristic is that many chloroplast haplotypes are discontinuous, such as H4 occurred in two locations which are more than 2,655 km apart, H5 is wide spread in eastern Asia but missing in most of populations in Central-Eastern China, H11 was found in coastal areas and islands but not in the inland regions except for Louguan Tai in Northwestern China. Another two cases of disjunct occurrence were found in H2 and H8. These disjunctions may be due to long-term fragmentation of Q. variabilis forests in the past. There was massive deforestation in East Asia, particularly in Central-Eastern and Northern China started around 1360s (start of the Ming Dynasty). There was also large scale clearing of forest areas for large agricultural expansion due to population expansion. This deforestation event resulted in large fragmentation of native forests and produced many isolated small plant populations Q. variabilis, as similar distribution characteristic also could be found in other species in the Chinese mainland Haplotype variation has been studied for several plant species in East Asia and China including tructure , 2. PopuDifferent haplotypes were detected in the adjacent populations from the same region. For example, H1 and H8 occurred in the North and South of Yangtze River respectively, where Yangtze River acted as a geographic barrier. In Laotung Peninsula, H6 and H8 were found in two close populations which might be derived from separate refugia.HT = 0.888) across the 50 populations of Q. variabilis in East Asia. The long evolutionary history of the species may have accumulated such genetic diversity. The wide geographical range of this species across a geologically dynamic region may help to provide ample opportunity for isolation, drift and conservation of the mutated alleles Q. variabilis was higher among populations within regions (HT = 0.667–1.00) and across the entire distribution, but lower within population (0–0.249) in these sampled regions  indicated large population differences. There was higher genetic differentiation between the populations in Mainland China and populations in Zhoushan and Japanese Archipelagoes, Taiwan Islands, and Korea Peninsula. This observed large differentiation could be readily attributed to isolation by seas. The abundance diversity among populations could also due to increased genetic drift in smaller populations, broad ecological niches, besides isolation by distance or barrier by local mountains. As an example, Oriental oak produce big-sized oak acorns which are dispersed mainly by rodents such as Apodemus peninsulae, Niviventor confucianus and A. agrarius over limited distances Q. variabilis is also a monoecious, autophilous plants, pollinated by wind and insects. Previous molecular studies have suggested that no species-specific nucleotide differences in several chloroplast DNA intergenic spacers in Japanese oak species owing to hybridization and (or) shared ancient polymorphism Q. variabilis Japanese populations. One possible explanation is that these populations might have gone through a bottleneck effect or founder effect when the population from mainland migrated to the Japan Archipelago. Similar phenomenon could also occur in Taiwan Island and Korea Peninsula. The similarity among Japan Archipelago, Taiwan Island and Korea Peninsula populations could be supported by the affinitive and shared haplotypes between Islands, simulated palaeodistribution and population expansion analysis.We detected a high level of total genetic diversity  could represent a remnant of an ancient centre of diversity for the species in North China region is an interesting observation. Previous investigations on conifer species preferred refugia in northern China during Pleistocene glaciations Q. variabilis with the range extended above 30°N and below 40°N, a finding that is somewhat inconsistent to the inference by Harrison et al., but consistent with Qian and Ricklefs’ hypothesis Q. variabilis.Whether population PG which had the second highest nucleotide diversity  to less than 35°N (Anhui Province) comparing population distribution at present and during LGM, inferred from our ENM construction. With pollen record in the sediment profiles collected in Taihu Lake , Xu et al. showed that in Taihu Lake, before 11000–9000 BP, deciduous broadleaf species  predominated while conifer species  co-existed SF indicated a demographic expansion of Oriental oak populations in East Asia. The results were consistent with Bayesian skyline plot that the ascent curve indicated an increased population size in Middle Pleistocene, a period that saw the advance and retreat of glaciers numerous times. Based on our fossil-calibrated cpDNA phylogenies, a rapid speciation event occurred at late Quaternary and we traced the spatial expansion of Q. variabilis populations in East Asia to the last glacial cycle(s).Typical responses of plants to climate changes were adaptive evolution through migration, resulting in the alteration of geographical distribution range Q. variabilis may have distributed across the temperate area in East Asia, with the northern range to Liaoning province at 40°N at least and the south range to the northern subtropical area at about 30°N. With the climate cooling at the beginning of the Quaternary, the north range of Oriental oak distribution retracted southwards (reaching to about 30°N) while some populations  might remained in certain special geographical locations between 30 and 40°N as possible refugia. The populations in the southern tip of the distribution colonized southwards (reaching about 20°N), forming a deciduous broadleaf forests in the areas where current evergreen broadleaf forests grew. As the starting point of diversification is given at the Pleistocene with 1.45 Ma, this distribution changing was very likely to cause the divergence between ‘Island’ clades and ‘Inland’ clades.Before the LGM, Q. variabilisQ. variabilis as a common tree species at the time. Across the East China Sea, the continental shelf areas as the land-bridge connected the Mainland China and Taiwan Islands, Oriental oak could distributed across the continental shelf areas and Islands.At the peak of the LGM, the MAT was about 15°C in the south range of the distribution, and about 7°C in the central part (southern Henan and northern Hubei) of the current distribution area of Although there have been a lot of literature showing a close relationship in flora distribution between Taiwan and Mainland China Q. variabilis populations migrated northwards from Central-Eastern China, re-colonized these lost distribution range, and finally, reached the Liaoning area as the north edge of the current distribution. There is possibility that some populations in Liaotung Peninsular could be the descendant from southern Korea Peninsula refugia. While the sea level rose, the land-bridge disappeared and the sea water separated populations remaining in Japanese and Zhoushan Archipelagoes and Taiwan Island from Mainland China. The lower level of population differentiation could be explained by a strong bottleneck or founder effects during the separation of Mainland and Islands. Meanwhile, in southern part of subtropical areas, other evergreen trees became dominant species in the new forests and Oriental oak retreated and only become a companion tree in the current evergreen forests.With increasing temperature after the LGM, Q. variabilis had a different evolutionary history relative to Q. robur in Europe that Q. robur only survived in several refugia in Mediterranean areas at the LGM Q. variabilis would more likely have been preserved in more places in East Asia at the LGM. We conclude that Oriental oak might have colonized current distribution by northward recolonization and possible expansion of many refugia after the LGM. Deciduous Oriental oak, one of the most widely distributed plant in Asia, providing an ideal species for investigating the biogeography of plants across the Mainland China, Korea Peninsular, Zhoushan and Japanese Archipelagoes and the Taiwan Islands in relation to Quaternary climate using phylogeographical approaches. Oriental oak haplotypes constituted one of the most complicated phylogenetic network among the plants studied so far in the eastern Asia, with possible two distinct clades. The first clade of ‘Island’ is mainly consisted by populations in isolated Taiwan Islands, Zhoushan and Japanese Archipelagoes, and Central-Eastern coastal region of Mainland China. Populations in the second clade were mainly from Central and Western Mainland China. Our results showed that the Central-Eastern China had populations with more haplotypes, the highest nucleotide diversity and significant phylogeographical structure and was the main glacial refugia at last glacier ages. Q. variabilis was distributed as dominant tree in the areas of current evergreen forests in the Mainland China, and the continental shelf areas as the land-bridge between the Mainland and Islands of East China Sea at the LGM while its offshore refugia probably existed in southernmost Korea. Restricted seed dispersal mechanisms, geographical obstacles and human-induced fragmentation resulted in higher interpopulation differentiation across the current distribution range, and in particular, between the populations in the Mainland China and Archipelagoes and Taiwan Islands. Our findings supported the hypothesis that Q. variabilis had survived in scattered multiple glacial refugia in East Asia and experienced a range expansion and rapid speciation in response to climatic fluctuations during Quaternary.This might indicate that Information S13tables.(DOCX)Click here for additional data file.


Several studies examined the fine-scale structure of human genetic variation in Europe. However, the European sets analyzed represent mainly northern, western, central, and southern Europe. Here, we report an analysis of approximately 166,000 single nucleotide polymorphisms in populations from eastern (northeastern) Europe: four Russian populations from European Russia, and three populations from the northernmost Finno-Ugric ethnicities (Veps and two contrast groups of Komi people). These were compared with several reference European samples, including Finns, Estonians, Latvians, Poles, Czechs, Germans, and Italians. The results obtained demonstrated genetic heterogeneity of populations living in the region studied. Russians from the central part of European Russia  exhibited similarities with populations from central–eastern Europe, and were distant from Russian sample from the northern Russia . Komi samples, especially Izhemski Komi, were significantly different from all other populations studied. These can be considered as a second pole of genetic diversity in northern Europe , as they had a distinct ancestry component. Russians from Mezen and the Finnic-speaking Veps were positioned between the two poles, but differed from each other in the proportions of Komi and Finnic ancestries. In general, our data provides a more complete genetic map of Europe accounting for the diversity in its most eastern (northeastern) populations. Identifying and understanding patterns of genetic variation within and between populations has long been the major focus of studies in human population genetics. Over the last decade, our ability to investigate population structure has been significantly enhanced by the advances in high-throughput genotyping technologies, as these allow simultaneous genotyping of hundreds of thousands of polymorphic markers. Compared with the previous methodology used in human population genetics, they enabled a new level of accuracy and power without the constraint of having to use only a few loci as a proxy for the entire genome To date, there is a number of studies in which the fine-scale structure of human genetic variation have been examined at a global, continental, geographic region, single country, or even a subpopulation level Russians are the largest ethnic group among the European populations: more than 80 million individuals live in an area that covers more than a third of continental Europe th century th–19th centuries In order to study genetic structure of the European Russians in greater detail, we combined genome-wide SNP data from the Tver sample mentioned above with the genotypes of three new Russian samples from southern (Kursk), eastern (Murom), and northern (Mezen) regions of European Russia . Taking The used research protocols and forms of informed consent have been approved by the Ethic Commission of the Medico-Genetic Scientific Centre of the Russian Academy of Medical Sciences . Written informed consent for participation was obtained from all subjects included in the study.Blood samples were collected in EDTA-coated vacutainers after recording genealogical information and obtaining informed consent from each individual. Inclusion in the study required that all individuals belong to the native ethnic group of the region studied , were healthy and unrelated. DNA was isolated from peripheral leukocytes according to standard techniques using proteinase K treatment and phenol–chloroform extraction P>0.00001, and with genotyping success rate >95% were accepted. Cryptic relatedness was tested with the same software and from the detected relative pairs (PI >0.2), only one was chosen for the subsequent analyses at random. These steps resulted in the retention of 165,872 autosomal SNPs in 603 individuals. To investigate population genetic structure, we also included genotypes of several populations described by Nelis et al. r2>0.2) using a window of 200 SNPs (sliding the window by 25 SNPs at a time), which yielded 59,318 and 52,808 SNPs, respectively.DNA samples were genotyped using different versions of Illumina BeadChips: Human370CNV-Duo (Tver and Murom), Human660W-Quad (Kursk), and HumanOmniExpress , according to the manufacturer’s protocol . All samples were subjected to the same quality control procedures using SNP and Variation Suite v.7.4.0 software package . Only SNPs from the 22 autosomal chromosomes with minor allele frequency >1%, at Hardy–Weinberg equilibrium In order to explore the genetic structure of the populations from European Russia, several forms of analyses were performed. We started with principal component analysis (PCA), a widely used method for identifying and visualizing patterns of population structure ST) using the SMARTPCA program in the EIGENSOFT software package (v.4.2). Allele frequency differences in pairs of populations were evaluated using trend tests. The resulting P values were subjected to Bonferroni correction and the significance threshold was set at P = 0.05 .Genetic differentiation among the populations was quantified by estimating pairwise Wright’s fixation indices , which, in contrast to PCA, implements a model-based clustering algorithm for estimating individual ancestry proportions 2) between marker pairs located less than 100 kb apart using the PLINK v. 1.07.29 software 2 values according to intermarker distances  and a mean r2 was calculated for each category.Finally, to assess the potential effect of population demographics on the population structure, the runs of homozygosity (ROH) and the extent of pairwise linkage disequilibrium (LD) were examined in the populations studied. ROH in the individuals were identified using SNP and Variation Suite v.7.4.0. ROH was defined as a sequence of at least 25 consecutive homozygous SNPs spanning at least 1500 kb, with a maximum gap of 100 kb between adjacent SNPs and a minimum density of 1 SNP per 50 kb To probe population structure, we first analyzed our data sets using a model-free ancestry PCA. In ST statistics, in which FST values were not greater than 0.001  differences in allele frequencies between populations from the Kursk, Murom, and Tver regions, but 144 to 172 SNPs in each of these populations differed from those of Russians from the Mezen region. The highest number of SNPs with large differences in allele frequencies was found between Izhemski Komi and populations from the Kursk, Murom, and Tver regions   .To further explore the population structure, a model-based structure-like analysis using the ADMIXTURE software was performed To explore the potential effect of population demographics on the population structures identified, ROH were compared across populations. ROH may indicate prolonged isolation and a reduced population size In this study, we used genome-wide SNP data to analyze the population genetic structure of Russians, Veps, and Komi. The samples under investigation covered territories in the northeastern Europe, not been included in previous analyses.The results obtained revealed no substantial genetic stratification within Russians from central–southern regions of European Russia . These three populations were clustered in close proximity to other populations from central–eastern Europe. In contrast, a sample from the northern Archangelsk region of Russia, Mezen Russians, was clearly distant from those of Kursk, Murom, and Tver. These data are in good agreement with earlier data obtained for polymorphisms of the Y-chromosome th–14th centuries, when Komi lived westward of their current territory and were the neighbors of Veps The Veps were another population that exhibited an increased percentage of both Komi and Finnic ancestries. The high level of Finnic ancestry is evidently characteristic of this population, as they belong to the same linguistic community, the Finnic-speaking community, as Finns do. The higher level of Komi ancestry in this population compared with that of Finns and Estonians could be from admixture of Veps (Ves) with Komi (ancient Permians) in the 11th–14th centuries th century and that Izhma was founded mainly by a group of Vimski Komi. Later, some Russian and Nenets families joined them ST values, which were the same between Izhemski Komi and both Priluzski Komi, who shared the same ethnic territory, and the geographically distant Finns from Helsinki, and from their higher parameters of ROH estimated.As for the Komi themselves, it has been proposed Both nROH and cROH have been shown to be higher in northern Europeans compared to their southern counterparts, which is consistent with the smaller effective population size and lower population density in northern Europe In summary, we reported results of the first genome-wide autosomal SNP-based study of the population structure of European Russia, in which samples of Russians, Veps, and Komi were analyzed. The data obtained strongly supports the results of earlier genetic studies, based either on Y-chromosome polymorphisms or on a limited number of autosomal markers, and suggested a genetic distinction of the northern Russian populations. Here, we were able to show clearly that this distinction was attributed to admixture with Finno-Ugric populations. The second important finding of our work was the context of that admixture. Our data on Komi population structure led us to consider this group as the second pole of genetic diversity in northern Europe (in addition to the pole occupied by Finns). Although we understand that the picture of the genetic structure of populations from European Russia obtained is still sparse, we propose that populations (ethnic groups) located between those two poles will have different proportions of Komi and Finnic ancestries .Figure S1Scree plots for eigenvalues of components 1 to 25 from the principal component analysis: (A) individuals from Russia, (B) individuals from Russia and selected samples from seven European countries.(TIF)Click here for additional data file.Figure S2Principal component analysis of the autosomal genotypic data of individuals from European Russia. PC3 and PC4 are shown. Population designations are the same as in (TIF)Click here for additional data file.Figure S3ST among 16 European populations.Multidimensional scaling analysis (two dimensions) of pairwise F The FST matrix from (TIF)Click here for additional data file.Figure S4Results of ADMIXTURE clustering at K = 6 to 8. The number of populations and their order are the same as at (TIF)Click here for additional data file.Figure S5Cross-validation plot for 16 populations from the ADMIXTURE analysis. The plot displays the cross-validation error versus K. The results of eight runs with different random seeds are presented.(TIF)Click here for additional data file.Figure S6The decay of LD across the genomes of the populations from Russia and the European reference samples. The samples of Poles and Russians from the HGDP were not included because of their smaller sample size. The Italian sample was also excluded (its merging with other samples resulted in a significant decrease in the number of SNPs).(TIF)Click here for additional data file.Table S1ST statistics calculated in pairs of all European populations analyzed.F(DOC)Click here for additional data file.


Prunus sibirica L. populations were investigated using 10 ISSR, SSR, and SRAP markers. The results suggest that the entire population has a relatively high level of genetic diversity, with populations HR and MY showing very high diversity. A low level of inter-population genetic differentiation and a high level of intra-population genetic differentiation was found, which is supported by a moderate level of gene flow, and largely attributable to the cross-pollination and self-incompatibility reproductive system. A STRUCTURE (model-based program) analysis revealed that the 21 populations can be divided into two main groups, mainly based on geographic differences and genetic exchanges. The entire wild Siberia apricot population in China could be divided into two subgroups, including 107 accessions in subgroup (SG) 1 and 147 accessions in SG 2. A Mantel test revealed a significant positive correlation between genetic and geographic distance matrices, and there was a very significant positive correlation among three marker datasets. Overall, we recommend a combination of conservation measures, with ex situ and in situ conservation that includes the construction of a core germplasm repository and the implement of in situ conservation for populations HR, MY, and ZY.The genetic diversity and population genetic structure of 252 accessions from 21  Indeed,Siberian apricot (Prunus sibirica L.) in China. Siberian apricot, a member of the genus Prunus belonging to the family Rosaceae, is an important ecological and economic tree species endemic to Asia. P. sibirica is distributed in regions of eastern Siberia, including the maritime territory of Russia, eastern regions of Mongolia, and northern regions of China [Siberian apricot is distributed throughout a total area of approximately 2 million hectare, with an annual seed production of nearly 1 million tons. It is able to grow in environments with a low temperature, strong wind, low rainfall, and poor soil. Considering its ecological benefits, such as water and soil conservation, windbreak, sand fixation, and environmental protection and greening, Siberian apricot is often used for afforestation in north China [P. sibirica also have important economic values: the seed shell can be pyrolyzed to activated carbon and pyroligneous liquor [In this work, we present a case study of of China . In Chinth China . The sees liquor ; the sees liquor ; the sees liquor ,10. Trads liquor .Siberian apricot is an important breeding resource for apricot production. According to molecular studies, many apricot cultivars grown for fruit, particularly in China, belong to the species P. armeniaca obtained through introgression with P. sibirica [P. sibirica or obtained by grafting with P. sibirica [P. sibirica have been important for introgressing resistance to Plum pox virus (PPV) in North American germplasm [Siberian apricot in recent years has highlighted the often low fruit set and tree productivity due to late-season frosts and a lack of variety breeding, with an insufficient fruit supply for industrial development. Therefore, the use of diverse wild resources to broaden the genetic base and increase the potential for the ecological adaptation of Siberian apricot cultivars allows important objectives to be pursued in breeding. Unfortunately, due to human interference, the area originally covered by wild resources has been greatly reduced, with the remaining area mostly found on mountains and cliffs. Thus, the genetic diversity and population structure of Siberian apricot in China should be immediately investigated for resource conservation and breeding.Furthermore, sibirica . For adasibirica . In addiermplasm . The incDNA markers allow the direct assessment of relatedness at the DNA level by estimating the proportion of alleles in individuals and populations. Different molecular markers can be used for genomic analysis, and simple sequence repeats (SSR), inter-simple sequence repeats (ISSR), and sequence-related amplified polymorphism (SRAP) markers have been recognized as useful molecular markers for diversity studies, population genetic analysis, and other purposes in various species –16. SSR Siberian apricot in China. Thus, the objectives of this study were to (i) characterize the genetic diversity and genetic differentiation of 21 Siberian apricot populations using SSR, ISSR, and SRAP markers; (ii) characterize the genetic structure in the populations; (iii) assess the correspondence among the three markers; and (iv) offer an effective conservation strategy for wild Siberian apricot.To our knowledge, there is no research to date focusing on the genetic diversity and population structure of 2.2.1.h), Shannon’s information index (I), and the percentage of polymorphic bands (PPB) were used to assess the genetic diversity , followed by populations HR and AS, with a high level of diversity at the species level . According to the SRAP markers, population HR had the highest genetic diversity , followed by populations ZY and MY, with a weaker level of diversity at the species level  than the ISSR markers. Based on the SSR markers, the highest genetic diversity was present in population AS , followed by populations MY and HC, with a high level of diversity at the species level . Populations KK and LX showed the lowest genetic diversity index using these three markers.Ten respective primers for SSR, ISSR, and SRAP markers amplified 45, 103, and 120 putative genetic loci, with a total of 268 loci detected. For the SSR markers, we detected 4.50 observed number of alleles and 3.77 effective number of alleles; for the ISSR and SRAP markers, 91.3% and 82.5% bands, respectively, were polymorphic  and S2. iversity . The ISSSiberia apricot in China showed a relatively high level of genetic diversity, higher than cultivated apricot (P. armeniaca) in Turkey revealed by ISSR markers (PPB = 88%) but lower than wild apricot (P. armeniaca) in the Ili Valley (PPB = 94.84%) [P. armeniaca) in the Maghreb region (0.593), but similar to the core collection apricot germplasm in China (0.731) [Siberia apricot has a slightly weaker genetic diversity index than wild apricot in the Ili Valley (PPB = 91.3% vs. 94.84%) but a larger population size and distribution area. As wild apricot in the Ili Valley has been accepted as the oldest and most diverse natural population, we suggest that the natural Siberia apricot populations in China retain a relatively high level of genetic diversity [Compared to previous research in apricot species, the  94.84%) ,26. The  (0.731) ,28. As tiversity .Siberia apricot growing region. Because of their economic value, the Siberia apricot seeds are widely collected by villagers in north China, and most populations will be affected by human disturbance [Siberia apricot growth and overlaps with the P. armeniaca distribution. In recent years, apricots grown for the kernels have been cultivated in this region, including hybrid varieties of P. armeniaca and P. sibirica [P. armeniaca occurred with P. sibirica in this region, affecting the genetic diversity of P. sibirica.The HR and MY populations showed much higher diversity parameters and are close in geographical distance. The two populations are located at the western end of the Yanshan Mountains, a traditional turbance ,30. The sibirica . We beli2.2.GST) was 0.18. An AMOVA analysis showed that 25.01% of the total gene diversity was found among the natural populations, whereas the remaining 74.99% of the total variation occurred within the populations  was 0.15, indicating that 83.35% of the total variance occurred within the populations. The three markers all indicated a low level of inter-population genetic differentiation and high level of intra-population genetic differentiation in wild Siberia apricot. This result was further confirmed by the moderate level of gene flow (Nm) between the populations .Assuming Hardy-Weinberg equilibrium, the genetic differentiation coefficient was calculated from the allele frequencies estimated according to the square root method using POPGENE. As revealed by the ISSR markers, the relative magnitude of genetic differentiation among the populations (ulations . The SRAFst (0.15) and Gst (0.18 and 0.28), a large amount of genetic variation in Siberia apricot was found within the populations, equivalent to the differentiation among the natural populations observed in wild apricot of the Ili valley  but lower than the North Africa apricot populations (Fst = 0.04) according to SSR markers [Siberia apricot in China is an outcrossing species. A value of Nm > 1 indicates no significant genetic differentiation among populations [Siberia apricot can be spread over a long distance by the combination of insects and wind, the large distribution area and largely discontinuous distribution negate this possibility. As a long-lived perennial woody plant, P. sibirica is widely distributed in regions of eastern Siberia, with large population sizes. To adapt to ecologically diverse habitats, it has probably accumulated considerable genetic variation within species. The populations in China may be characterized by shared ancestral polymorphisms, and have maintained large effective population sizes so that the shared variation has not been lost by drift. Considering the partly overlapping distribution with P. armeniaca and P. mandshurica, the variation found among the P. sibirica populations was possibly due to drift or crossing with other Prunus species. In addition, P. sibirica uses an animal-ingested seed dispersal system; its efficiency largely depends on the migration habits and activity of animals. Obligate fruit-eaters that feed mainly or solely on the fruit of P. sibirica during the maturation period, when fruit-ripening asynchrony occurs, may confine their activities within the areas where ripe fruits are available. As a result, the seed exchange among P. sibirica populations will be minimal. In addition, factors such as the low seed germination rate and breeding system may also partly contribute to the present population genetic differentiation in P. sibirica.Based on the values  markers ,29. Due ulations . In the 2.3.http://pritchardlab.stanford.edu/structure.html) [K values were plotted against the K numbers of the sub-groups. The maximum ΔK occurred at K = 2 for the three markers  . Followire.html) , the ΔK  markers . We diviK = 2, the populations were split into two groups: populations LY, ZD, AS, HC, HX, ZY, YG, GL, and HY in group I and the remaining populations in group II.Considering the ISSR markers, the dendrogram divided the 21 populations into two main clusters, a large cluster with 13 populations and a small with 8 populations . The STRr = 0.7379; SRAP, r = 0.6160; SSR, r = 0.5490; p ≤ 0.001). Most of the area of group I is located in the warm-temperate zone in northwest China, and group II is located in the mid-temperate zone in northeast and north China, and there is a large difference in light, temperature, and other climate conditions in these two regions [Siberia apricot [Siberia apricot trees was approximately 3–6 m in group I and 1.5–5 m in group II; thus, we hypothesized that environmental differences would affected the genetic structure of P. sibirica populations in the long term. In northern China, the distribution of P. sibirica overlaps with wild P. armeniaca and P. mandshurica [P. mandshurica is completely distributed in northeastern China, the region in which most of the group II populations are found. We hypothesized that genetic exchange of group I and group II with different species of Prunus would also affect the difference in genetic structure between the groups. In general, geographic difference and genetic exchange should be mainly responsible for the current genetic structure of populations.The population genetic structure reflects interactions among species with regard to their long-term evolutionary history, mutation and recombination, genetic drift, reproductive system, gene flow, and natural selection ,36. Thus apricot . Plant g apricot . In our dshurica ; The P. 2.4.r = 0.766, ISSR with SSR r = 0.694, SRAP with SSR r = 0.631, p < 0.01). The results showed some differences with a report by Budak using ISSR, SSR, RAPD, and SRAP markers in buffalo grass (Buchloe dactyloides) [r = 0.66, p < 0.01), but non-significant correlation between SRAP and the other markers.The three markers resulted in similar dendrogram and sub-group division results, revealing a possible correlation and uniformity among them. To obtain a more robust comparison, a Mantel matrix correspondence test was used in matrices of the genetic distance values of 252 accessions generated using the three markers. The test revealed a very significant positive correlation among them (ISSR with SRAP yloides) , which iDespite the great and similar discriminating power of each marker system used, there were some differences detected. For instance, the number of total polymorphic and discriminant fragments was higher for the ISSR markers (94 polymorphic fragments), showing a higher capacity to reveal polymorphisms than SRAP. Previous research supports a higher capacity of ISSRs to reveal polymorphisms and to demonstrate a great potential to determine the intra- and inter-genomic diversity as compared to other arbitrary primers . In this2.5.vs. combined molecular marker datasets for the purpose of genetic diversity analysis [Siberia apricot populations. The SSR data were converted into a dominance data matrix to generate a dendrogram with combined ISSR and SRAP data. The software NTSYS 2.11 was applied to construct the neighbor-joining tree on the basis of the Jaccard similarity coefficient [K occurred at K = 2  , and 13 and 17 accessions assigned to SG 1b and SG 2b (0.50≤ membership probabilities of <0.80) [Few studies have compared the results obtained from individual analysis ,43. In tfficient . Followifficient , the obvat K = 2 , which ind SG 2) . With mef <0.80) . SG 1b aK = 2 and K = 4 were considered to best depict the genetic structure, reflecting a slight difference with our results [K value as 5 or 7, rather different from our results [The Cluster analysis or STRUCTURE analysis revealed that most accessions from the same population aggregated together. In population HY, 9 accessions were in placed into SG 1b, with the other 3 accessions being placed into SG 2b. The STRUCTURE analysis of some graft- and seed-propagated apricots in North African showing  results . Researc results . Differe2.6.Siberia apricot distribution. Seed collection might represent the highest threat for wild Siberia apricot at present and in the future due to the development of the Siberia apricot seed industry [The main objective in any plant genetic resource conservation program should be to maintain the highest possible level of genetic variability . Accordiindustry ,10,28. TSiberia apricot genetic resources and considering the large distribution area and dispersal situation, we recommend a combination of conservation measures that include ex situ and in situ conservation. Firstly, we recommend the construction of a core germplasm repository and the collection of germplasm resources in greater breadth and depth. This will allow seeds to be collected and exchanged between populations, increasing the genetic diversity in each area and conserving the scarce germplasm resources through natural regeneration. In fact, more attention should be given to ex situ efforts because it would be difficult to implement in situ conservation for all the populations due to the large distribution area and dispersal. Secondly, in situ conservation should be implemented immediately. Given their high level of genetic diversity and desirable growth patterns in their original habitat, populations HR and MY should be assigned a high priority. Additionally, the genetic diversity of the two subgroups should be protected, and a priority conservation measure should be instituted for population ZY. These measures should include the establishment of nature reserves and forest reservation and the banning of grazing. Thirdly, seed collection activity using wild resources should be controlled, and the development of cultivated Siberia apricot resources should be encouraged. For the sake of industrial development and local economies, the commercial planting of Siberia apricot should be established in suitable areas.To preserve the valuable wild 3.3.1.Siberian apricot in July and August 2012  were collected from north China, a region with a continuous distribution of ust 2012 . The col3.2.The maternal tissues forming the testa were separated from the rest of the seed (embryo), and genomic DNA was extracted using the modified DNA extraction protocol of Martin and Li ,47. The 3.3.2, 0.4 mM dNTPs, and 1 U Taq DNA Polymerase. The ISSR reactions were performed with an initial step of 3 min at 95 °C, followed by 35 cycles of denaturation at 94 °C for 60 s, annealing for 60 s, and extension at 72 °C for 120 s; a final extension was performed for 5 min at 72 °C. The SRAP cycling parameters included 3 min at 95 °C, 5 cycles of three steps of denaturing at 94 °C for 60 s, annealing at 35 °C for 60 s and extension at 72 °C for 60 s. In the following 35 cycles, the annealing temperature was increased to 50 °C, and one cycle of 5 min at 72 °C was used for extension. The ISSR and SRAP amplification products were analyzed by 1.8% agarose gel electrophoresis in 1× TBE buffer and stained with ethidium bromide; the products were photographed using a Gel Documentation System . The amplifications for the SSR analysis were performed with an initial step of 3 min at 95 °C, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 51 to 57 °C (depending on the primer) for 30 s, and extension at 72 °C for 60 s; a final extension was performed for 5 min at 72 °C. The PCR products were separated by electrophoresis through a 6% denaturing polyacrylamide gel, and the fragments were visualized by silver staining. The genotypes were assessed by eye on the fluorescent plate.The extracted apricot genomic DNA was separately amplified by PCR using 10 ISSR, SSR, and SRAP primers; the primers sequences and sources are listed in 3.4.The ISSR and SRAP amplification fragments were scored according to a binary matrix where 0 and 1 coded for the absence and presence of a band, respectively. For each SSR locus, the allelic composition and number of total alleles were determined for each accession.PPB), Nei’s gene diversity (h), and Shannon’s information index (I). The coefficient of gene differentiation  and gene flow (Nm) between the populations were also calculated using this program [The genetic diversity was assessed using the program POPGENE 1.32 , as meas program ,40,56. T program . Mantel  program . The SSR program ,59,60.K) capturing the major structure in the data, we used a burn-in period of 50,000 Markov Chain Monte Carlo iterations and 100,000 runs, with an admixture model following Hardy-Weinberg equilibrium, and correlated allele frequencies and independent loci for each run. Seven independent runs were performed for each simulated value of K, ranging from 2 to 20. The true K value was determined using both an estimate of the posterior probability of the data for a given K  and the Evanno ΔK [Genetic relationships among individuals were assessed by a multivariate principal component analysis (PCoA) performed with NTSYS 2.11  to identify the number of groups based on eigen vectors. Population structure was determined using the model-based program, STRUCTURE . To idenvanno ΔK ,34.4.Siberia apricot collections, information that is of critical importance for the design of genetic diversity and structure analyses. First, the results suggest that wild Siberia apricot in China has a relatively high level of genetic diversity; the populations HR and MY show very high diversity parameters, which was attributed to their being less affected by human disturbance. A low level of inter-population genetic differentiation and a high level of intra-population genetic differentiation were found, which was supported by a moderate level of gene flow. We believe that the predominant genetic variation found in wild Siberia apricot is attributable to the differences within populations, and is caused by the cross-pollination and self-incompatibility of this plant. Second, the STRUCTURE analysis indicated that the 21 populations can be divided into two main groups. The LY, ZD, AS, HC, HX, ZY, YG, GL, and HY populations were assigned to group I, and the other populations were assigned to group II. The geographic differences and genetic exchange should be mainly responsible for the observed genetic structure of the populations. The Mantel matrix correspondence test revealed a very significantly positive correlation among the datasets of the three markers. Third, the entire wild Siberia apricot population in Chian could be divided into two subgroups, with 107 accessions in SG 1 and 147 accessions in SG 2. Furthermore, the Mantel test revealed a significant positive correlation between the genetic and geographic distance matrices. Lastly, we recommend a combination of conservation measures, with ex situ and in situ conservation, such as the construction of a core germplasm repository, the collection of germplasm resources in greater breadth and depth, and the implementation of in situ conservation in populations HR, MY, and ZY. The information obtained from this collection of genotypes will be helpful for the development of good varieties for breeding programs and the conservation of the genetic resources of wild Siberia apricot in China.In conclusion, our data initially confirm that all sets of ISSR, SSR, and SRAP markers provide an accurate picture of the population structure within wild Figure S1.K values for different numbers of populations assumed (K) in the STRUCURE analysis.ΔFigure S2.Principal component analysis on combined three markers data sets of the entire population.


Salmo salar) populations. On the basis of the analysis of 11 microsatellite loci, we found that the overall genetic structure among populations dramatically decreased over the period studied. Admixture rates among populations were highly variable, ranging from a nearly undetectable contribution from donor stocks to total replacement of the native gene pool, suggesting extremely variable impacts of stocking. Depending on population, admixture rates either increased, remained stable, or decreased in samples collected between 1998 and 2006 compared to samples from 1965 to 1987, suggesting either rising, long-lasting or short-term impacts of stocking. We discuss the potential mechanisms contributing to this variability, including the reduced fitness of stocked fish and persistence of wild locally adapted individuals.While the stocking of captive-bred fish has been occurring for decades and has had substantial immediate genetic and evolutionary impacts on wild populations, its long-term consequences have only been weakly investigated. Here, we conducted a spatiotemporal analysis of 1428 Atlantic salmon sampled from 1965 to 2006 in 25 populations throughout France to investigate the influence of stocking on the neutral genetic structure in wild Atlantic salmon ( Anthropogenic pressures on natural populations have the potential to alter the distribution of genetic diversity within and among wild populations. By comparing historical and current genetic diversity we can test for changes in the genetic structure of populations as a result of such perturbations  populations in France and two Scottish populations. We tested whether stocking changed the genetic admixture rates within salmon populations and led to a reduction in genetic differentiation among donor and targeted populations. We also examined if such practices may have led to a decrease in the overall genetic structure among populations in France. We then investigated if such practices may have only short-term effects on the neutral genetic diversity of wild populations by comparing the level of genetic diversity in some populations at the time of stocking and several generations after the end of these operations. We hypothesized that stocking may have mixed effects on genetic diversity including (i) a global homogenization of genetic diversity among populations, (ii) variable admixture rates of stocked populations and a decrease in differentiation between donors and targets of stocking, and (iii) only short-term changes in genetic variation.In this study, we investigated the genetic effects of a variety of stocking strategies using Atlantic salmon populations from France as a case study. Some of these populations were stocked from 1950s to 1980s using nonlocal fish (mainly from Scotland) , but some rivers were stocked with fish from different French rivers  buffer and chelex, at 55°C 2 h and then at 100°C for 10 min  were analyzed at the SSAD486 locus in order to document if brown trout or hybrids between S. salar and S. trutta were misidentified as salmon .Genomic DNA was extracted from He, , was used to infer effective size of populations and their recent evolution. The function theta was used to obtain an overview of the current and ancestral average of θ (4 × Ne × μ) with Ne the effective size and μ the mutation rate. The function VarEff was then used to characterize effective population sizes. We used a stepwise mutation model for microsatellites with μ = 6 × 10−4  with n equal to the number of putative populations, and performed 15 replicates for each k. Each run started with a burn-in period of 50,000 steps followed by 300,000 MCMC replicates. For each individual, the 90% credible intervals of admixture values were estimated. We selected the k with the highest likelihood  genetic distances  were variable among samples  was higher than between historical samples of these same rivers, which were collected contemporary to stocking . The differentiation observed between Bresle and Shine  was slightly higher than between Bresle and Soey, but showed a similar increase over time.The neighbor-joining tree of Nei genetic distances illustrates the genetic structure among French populations Fig. , clearlyFst = 0.038, CI: 0.033–0.042) than historical samples . Analyses of molecular variance furthermore revealed a higher differentiation both among and within groups in historical samples  than in recent ones . In the Brittany region, Fst among the 13 populations was 0.006, CI: 0.004–0.008 and 0.020, CI: 0.015–0.026 for recent and historical samples, respectively.The genetic differentiation among populations was usually lower in recently collected samples than historical samples in the 20 populations that were sampled temporally Fig. . HoweverThis study constitutes one of the largest spatiotemporal assessments of the consequences of stocking practices on the genetic structure of wild populations. In the absence of extensive stocking practices, relatively low gene flow and high stability of the genetic structure among populations or subpopulations of Atlantic salmon have been documented . Despite high stocking pressures and a reduced effective population size, we did not detect any significant admixture in either Allier temporal samples. Maladaptation and low fitness of stocked fish have been widely demonstrated and could be one reason for the absence of admixture in this population  from 1960s to 1990s. A reduced effective population size is expected to further enhance the effects of stocking , within river Fsts among temporal samples from unstocked rivers were low, thus arguing against the possibility of strong genetic drift. Glover et al. , collected during stocking, than in the most recent sample (2%), collected several generations after the end of supplementation. Furthermore, we found a higher differentiation between Bresle and Scottish samples  in recently collected samples than in samples collected during stocking. These results strongly suggest that despite high immediate effects of stocking, these practices may only have short-term genetic influences and that a resilience of a “natural” population  genetic makeup to stocking is possible. While some authors proposed that temporal reproductive isolation . In the same way, catch and release of Atlantic salmon in healthy populations may also allow conciliating population conservation and game fishing without threatening the wild populations nor requiring compensative stocking  to limit detrimental introgressive hybridization. Moreover, neighboring Atlantic salmon populations and even sympatric brown trout populations might also be taken into account given possible intraspecific and interspecific gene flow. That being said, the management programs of already admixed wild populations can also benefit from ameliorations. In agreement with Hansen and Mensberg , this st