Thelazia callipaeda is the causative agent of thelaziasis in canids, felids and humans. However, the population genetic structure regarding this parasite remains unclear.T. callipaeda clinical isolates using the following multi-molecular markers: cox1, cytb, 12S rDNA, ITS1 and 18S rDNA. The isolates were collected from 13 patients from 11 geographical locations in China. Next, the population structure of T. callipaeda from Europe and other Asian countries was analyzed using the cox1 sequences collected during this study and from the GenBank database. In general, the Chinese clinical isolates of T. callipaeda expressed high genetic diversity. Based on the cox1 gene, a total of 21 haplotypes were identified. One only circulated in European countries (Hap1), while the other 20 haplotypes were dispersed in Korea, Japan and China. There were five nucleotide positions in the cox1 sequences that were confirmed as invariable among individuals from Europe and Asia, but the sequences were distinct between these two regions. Population differences between Europe and Asian countries were greater than those among China, Korea and Japan. The T. callipaeda populations from Europe and Asia should be divided into two separate sub-populations. These two groups started to diverge during the middle Pleistocene. Neutrality tests, mismatch distribution and Bayesian skyline plot (BSP) analysis all rejected possible population expansion of T. callipaeda.In this study, we first explored the genetic variation of 32 T. callipaeda has a high level of genetic diversity, but further studies should be performed to explore the biology, ecology and epidemiology of T. callipaeda.The Asian population of  Thelazia callipaeda is the causative agent of thelaziasis canids, felids and humans. Despite the existing threat of thelaziosis in China, the genetic diversity of T. callipaeda has not been investigated across its wide geographical distribution in China, yet such information may provide insight into the disease epidemiology and the development of specific control measures. In this study, the genetic variation of 32 T. callipaeda clinical isolates collected from 13 patients from 11 geographical locations in China were explored using the following multi-molecular markers: cox1, cytb, 12S rDNA, ITS1 and 18S rDNA. In addition, the population structure of T. callipaeda from Europe and other Asian countries was analyzed using the cox1 sequences collected during this study and from the GenBank database. In general, the Chinese clinical isolates of T. callipaeda demonstrated high genetic diversity. Based on the cox1 gene, a total of 21 haplotypes were identified, one circulated in European countries (Hap1), while the other 20 haplotypes were dispersed in Korea, Japan and China. There were five nucleotide positions in the cox1 that were confirmed as invariable among individuals from Europe and Asia, but the sequences were distinct between these two regions. Population differences between Europe and Asian countries were greater than those among China, Korea and Japan, such that the T. callipaeda population from Europe and Asia should be divided into two separate sub-populations. These two groups started to diverge during the middle Pleistocene. Thelazia callipaeda (Spirurida: Thelaziidae) is the major etiological agent of ocular thelaziosis [Phortica , that feeds on the lachrymal secretions of mammals [T. callipaeda was previously known as the oriental eyeworm because of its original description in eastern Asia countries [T. callipaeda infections has been reported in animals and humans living in European countries and in China [The spirurid nematode laziosis . This wolaziosis ,3. The p mammals ,5. T. caountries . Since tountries . A broadountries . The firountries . Althougountries . China iountries . Recentlin China ,11.T. callipaeda poses a serious threat to public health and thelaziosis has even been termed as an emerging enzootic disease [T. callipaeda have been carried out. One possible reason is that as a neglected pathogen, T. callipaeda does not draw enough attention from most parasitologists. This may also be attributed to the difficulty in collecting T. callipaeda isolates from different hosts and distinct geographical locations.Consequently,  disease ,6,9. Und disease . HoweverThelazia species by using the first internal transcribed spacer (ITS1) ribosomal DNA sequence, and concluded that the ITS1 sequence was a useful genetic marker for the molecular identification of Thelazia spp. In 2005, Otranto et al. [T. callipaeda from Europe and Asia based on the mitochondrial cytochrome c oxidase subunit 1 gene (cox1). Recently, although various publications of the T. callipaeda infections in animals and humans have been reported [T. callipaeda isolates collected from different geographical locations in China by using three mitochondrial genes and two nuclear ribosomal DNA sequences as follows: mitochondrial cytochrome b (cytb), the small subunit of ribosomal DNA gene (12S rDNA) and cox1; ITS1 and the small subunit of nuclear ribosomal DNA (18S rDNA). These molecular markers were selected because they are suitable for inferring population differences and conducting phylogenetic analysis at different taxonomic levels [cox1, we also performed a genetic variability comparative analysis on clinical T. callipaeda isolates collected in China and from previous publications. Additionally, the presumed transmission pattern of T. callipaeda investigated here relied on phylogeny and molecular dating methods.More than 10 years ago, Otranto and Traversa  performeo et al.  investigreported ,14–18, nDNA gene S rDNA anc levels ,19–21. UThis study was approved by the Life Science Ethics Committee of Zhengzhou University (No. 2017–0006). The protocol and written informed consent form were approved by the Human Ethics Committees of the Zhengzhou University. All subjects older than eighteen years old provided written informed consent; in the case of children, they provided written informed assent, and their parents/guardians provided written consent for them. All worms were collected from patients to treat their thelaziasis and not expressly for the purpose of the present study.T. callipaeda according to the morphological characteristics  described in Otranto et al. [A total of 32 worms were harvested from 13 patients from 11 distinct geographical locations in China from September 2007 to July 2016 . All nemo et al. .cytb, cox1, 12S rDNA, ITS1 and 18S rDNA, were amplified to explore the genetic diversity of T. callipaeda. For 12S, ITS1 and cox1, the amplifications were obtained using primer combinations described in Casiraghi et al. (2004) [cytb and 18S markers were designed as follows: cobF 5′-TGATTGGTGGTTTTGGTAA-3′; and cobR 5′- ATAAGTACGAGTATCAATATC-3′; and 18SF 5′- CTCATAAAATAATTGG TGAATCTGAATAGC-3′ and 18SR 5′-ATAACTTTTCAGCAATGGTTACAG-3′, respectively. PCR products were purified using the EasyPure PCR Purification Kit  and sequenced in both directions at the Genwiz Company . All sequences were deposited in the GenBank database  following the manufacturer’s protocol. Five molecular markers, viz. . (2004) , Otranto. (2004) , and Otrdatabase . The seqp = 0.05) to detect the partitions of genetic diversity within and among populations. Pairwise FST values between populations were performed for all datasets in Arlequin to explore levels of genetic differentiation among the populations. The significance of FST values evaluated was based on 1000 random permutations. Demographic changes were also estimated using mismatch distributions in Arlequin with 1000 simulations, under a scenario of no recombination. The validity of the expansion model was tested by using the sum of squared deviations (SSD) and raggedness index (RI) between observed and expected mismatches. The neutrality tests using Tajima’s D [FS [The program DnaSP v5.10  was empljima’s D  and Fu’s’s D [FS  were alsT. callipaeda, all available sequences of cox1 in the GenBank database were included  according to the substitution rate for nematode mtDNA [To make a worldwide genetic variability comparative analysis of included . In addide mtDNA . Tracer de mtDNA  was usedcox1 haplotypes was estimated through maximum parsimony (MP) and Bayesian inference (BI). MP analysis was performed in MEGA v.6.06. Confidence in each node was assessed by boot-strapping (1000 pseudo-replicates). Bayesian inference was performed in MrBayes v.3.2 [8 steps.The phylogenetic pattern of all es v.3.2 , after des v.3.2 . The anacytb, cox1, 12S, ITS1 and 18S were 1035 bp, 660 bp, 453 bp, 772 bp and 1201 bp, respectively. In 32 isolates from eleven localities, the genetic markers of cox1, 12S, ITS1 and 18S were used to identify 9, 8, 8 and 7 new haplotypes (Haps),. For cytb, 8 Haps were identified in only 25 isolates because the sequences of isolates from Hefei (HF) and Liuan (LA) of Anhui province were not amplified . Clinical eyeworms from Dandong (DD) and Tongchuan (TC) shared geographical specific Haps using each of the selected markers. Isolates from Huanggang (HG) and Wuhan (WH) also revealed specific Haps when using cytb, cox1, 12S and ITS1; however, these samples shared a single haplotype using 18S. Using cytb, 12S and ITS1, a single geographical specific haplotype was identified in T. callipaeda from Shangluo (SL). Interestingly, using cox1 (Hap3) and 18S (Hap5), these isolates from SL shared the same haplotype with all samples from Luoyang (LY), 4 samples from Pingdingshan (PDS) and one from Zhengzhou (ZZ). The remaining isolates from PDS and ZZ shared the same haplotype using 12S, ITS1 and 18S. However, when using cytb and cox1, the remaining isolates possessed two distinct Haps. Using cytb, 12S, ITS1 and 18S, worms from Jiaozuo (JZ) shared the same haplotype with the second sample from ZZ. Only with cox1, did the JZ isolates identify as a distinct haplotype. The results from the analysis of molecular variance (AMOVA) showed that much more genetic variance lay among the populations than within the populations for all datasets, more specifically, cytb: 69.77% vs. 30.23%; cox1: 91.32% vs. 8.68%; 12S: 94.26% vs. 5.74%; ITS1: 91.69% vs. 8.31%; 18S: 83.71% vs. 16.29% (FST) values between specified geographical regions were estimated for all molecular markers used to measure the population differentiation , using the 18S gene . The remaining haplotypes were shared by samples from Eastern Asia countries . Haps2–8 and haps10–12 were shared by samples isolated from domestic dogs (Canis familiaris). Hap9 and haps13–21 were identified in eyeworms collected from humans (Homo sapiens). The alignment of 21 haplotypes revealed nucleotide variations (36 transitions and 1 transversion) at 37 alignment positions  were 0.961 for Europe vs. Korea, 0.866 for Europe vs. Japan, 0.827 for Europe vs. China, 0.444 for Korea vs. Japan, 0.275 for Korea vs. China, and 0.430 for Japan vs. China  suggested that the HKY+G model was most suitable for pologies . Among tpologies . The timxpansion . Mismatcxpansion . In addixpansion . The resxpansion .Thelazia can cause veterinary or medical problems in many parts of the world [T. callipaeda affects humans in China, causing mild to severe clinical symptom [T. callipaeda in China. In this study, we collected 32 eye worms from 13 patients from 11 distinct geographical locations in China over a period of 10 years, and performed a genetic variation analysis of these isolates using a multi-gene approach to investigate the population structure of T. callipaeda.Although more than 10 species of the spirurid genus he world , only T. symptom . It is sT. callipaeda population identified by each molecular marker were generally consistent. Of all the geographic populations, only PDS and ZZ isolates revealed two different haplotypes. Worms from ZZ were harvested in two different patients. However, interestingly, all PDS isolates that were collected from a single child also had two haplotypes, indicating the patient probably experienced two or more infections of drosophilid flies. Each geographic population and the total population demonstrated high haplotype diversity (Hd) values (nearly 1.0) by all markers, however, the nucleotide diversity (Pi) values of each gene were below 0.01, indicating that multiple haplotypes were differentiated by few nucleotide mutations. Correspondingly, the AMOVA results also showed that much more genetic variance exists among the populations than within the populations [FST) was used to measure the population differentiation. Most of the FST values between specified geographical regions were far more than 0.25, indicating very high genetic differentiation and a long-term interruption of gene flow among the geographical populations [Haplotypes of the Chinese ulations . The paiulations .cox1 sequence, Otranto et al. [T. callipaeda population in 2005. Since then, sequences of T. callipaeda from different geographical locations and different hosts have been published [T. callipaeda population. Some interesting discoveries were made: (1) Thirteen novel genotypes of T. callipaeda were identified; four from Japan (Haps9–12), and another nine from Chinese clinical isolates (Haps13–21); within the 4 Japanese genotypes, one was from a human, and the other 3 were from Canis familiaris. (2) In cox1, Otranto et al. [T. callipaeda population from Europe and Asia should be divided into the following two subgroups: one group (clade I) comprising worms from European countries (Hap1) and a sample isolated from a dog in Anhui of China (Hap4); the other group (clade II) comprising T. callipaeda from Korea, Japan and China. Individuals in clade II diverged earlier than those in clade I. Within the Asian haplotypes, Hap13  was the ancestral haplotype; then, it was transmitted to Japan, Korea and other regions of China. (5) All of the neutrality tests, mismatch distribution and BSP analyses rejected possible population expansion of T. callipaeda, indicating this nematode population was in the stable phase [Based on the partial o et al.  performeublished , 16–18. ublished , we addean Haps9–, and anoo et al. , and posle phase .T. callipaeda from distinct hosts  was inconspicuous, suggesting a lack of connection between eyeworms and host species [T. callipaeda populations are tightly linked to the intermediate host (vector). The drosophilid fly Phortica variegata was the vector of T. callipaeda in Europe, whereas the T. callipaeda in Anhui of China was transmitted by P. okadai [T. callipaeda in Korea, Japan and China, it is very likely that some novel species or genotypes of Phortica flies exist in these areas. Hence, further studies should be launched to explore the biology, population genetics, ecology and epidemiology of T. callipaeda in the future.Generally, the population structures of parasites are associated with large genetic differentiation among populations from different geographical regions and/or hosts and low intra-population genetic variability ,40. In t species . That be. okadai ,12. AlthT. callipaeda expressed a high level of genetic diversity. Using the cox1 gene, thirteen new genotypes were identified, four from Japan (Haps9–12), and nine from China (Haps13–21). There were five positions in the cox1 sequences  that were confirmed invariable among individuals from Europe and Asia, but the sequences were distinct between these two regions. Population differences between Europe and Asian countries were greater than those among China, Korea and Japan, and the T. callipaeda populations from Europe and Asia should be divided into two separate sub-populations. These two groups started to diverge during the middle Pleistocene.In summary, the Chinese clinical isolates of S1 Table(DOC)Click here for additional data file.S2 Table(DOC)Click here for additional data file.S3 Table(DOC)Click here for additional data file.S4 Table(DOC)Click here for additional data file.S5 Table(DOC)Click here for additional data file.S1 Fig(DOC)Click here for additional data file.S2 Fig(DOC)Click here for additional data file.S3 Fig(DOC)Click here for additional data file.


Linum flavum and interpret the Quaternary history of its peripheral populations, especially those at the westernmost isolated range edge, discussing their migrations and possible relict status. We defined our peripheral transect across three study regions from Central Hungary, eastern Austria to southwestern Germany. Using AFLP fingerprinting and cpDNA sequence variation , we analyzed 267 and 95 individuals, respectively, representing each study region by four populations. Hierarchical AMOVA (AFLPs) indicated significant variation among study regions  and moderate differentiation between populations (10%). Population differentiation was high at the westernmost range edge , but also in the east , compared to the Austrian study region (8.6%). Correspondingly, AFLP diversity was highest in the center of the study transect in eastern Austria. CpDNA haplotypes support a pattern of regional structuring with the strongest separation of the westernmost range edge, and some haplotype sharing among Austrian and Hungarian individuals. Equilibrating nucleotide versus haplotype diversity patterns, the highly diverse populations at the Pannonian range edge (Austria) indicate long‐term persistence, while Central Pannonian populations are obviously effected by recent bottlenecks. Intermediate nucleotide, but high haplotype diversity within the westernmost exclave (Swabian Alb), is indicative of a founder bottleneck during its pre‐LGM or early postglacial migration history, followed by sufficient time to accumulate cpDNA variation. The not obviously reduced genetic diversity and distinctiveness of L. flavum at the westernmost range edge suggest a long‐term persistence (relict status) of populations in this region, where the species has survived probably even the Würm glaciation in extra‐Mediterranean refugia. This genetic relict variation represents an important part of the overall genetic diversity found in the western periphery of this steppe plant and highlights the high conservation priority of respective gene pools.We investigate patterns of genetic variation along an east–west transect of Central European populations of  Utilizing a Central European peripheral study transect, we include the Central Hungarian region  and chloroplast DNA sequence analyses. Consequently, we will answer the question whether the specific biogeographical history of this species at the (westernmost) range edge covers basically expected patterns regarding peripheral populations .Based on these considerations, we are aiming at (1) the evaluation of the distribution of genetic variation and diversity along our peripheral study transect, and (2) testing our hypotheses on the relict status of the Swabian Alb populations and reconstructing the Quaternary history of 22.1Linum flavum L. belongs to the evidently monophyletic and predominantly yellow‐flowering group, sect. Syllinum Griseb., which is widespread in the northern hemisphere and evolved about 19–17 mya ago  in Austria and generally “endangered” in Germany  in combination with low precipitation rates (<600 mm per year), for example, the Hungarian Plains in Central Hungary  where it only occurs in few, mostly scattered and isolated populations.Our Central European study transect, where only We randomly collected leaf material from four populations per study region and 24 individuals per population Table . The minIsolation of total genomic DNA from silica dried leaf material (ca. 20 mg) was carried out using sterilized glass pellets for grinding and the DNeasy™ Plant Mini Extraction Kit  according to the manufacturer's protocol.2.3AFLP profiles of 288 individuals Table  were genMseI and EcoRI. Preselective amplifications were performed with primer pairs containing each one selective nucleotide. For selective amplifications, three primer combinations  were included during lab work . For the amplification step a 10 μl reaction mix (containing 5 μl Multiplex PCR Master Mix (QIAGEN), 2.2 μl H2O , 0.4 μl forward primer , 0.4 μl reverse primer (Eurofins) and 2 μl of diluted DNA) run under the following conditions: initial 15 min at 95°C, followed by 35 cycles each of 45 s at 95°C, 45 s at 55°C, and 1 min at 72°C, then finally 10 min at 72°C. 12 μl of diluted PCR products were then sent to LGC Genomics  for cycle sequencing using the same forward primers. Sequences obtained were manually aligned with BioEdit . The visualization of the distance matrix resulted in an unrooted neighbor‐net phenogram using SplitsTree4 .A genetic structure, we used Bayesian clustering running BAPS  to reveal the optimal number of clusters (K) by the means of stochastic optimization. Clustering of individuals was carried out with a maximal number of 2–200 groups (K) and performing ten replicates. A Bayesian admixture analysis  were calculated with ARLEQUIN . With different hierarchical approaches the differentiation among and within study regions or groups of populations was investigated using significance tests on the basis of 1,000 permutations. For testing isolation‐by‐distance (IBD) patterns  using the statistical software “R” : Nei's gene diversity . Genetic diversity was tested for correlation with peripheral location  and population size categories using Spearman's rank correlation coefficient in SPSS .Different measures of AFLP outlier analysis was originally performed using the software DFDIST, adapted for dominant markers . Outlier analyses are based on the assumption that genetic differentiation between populations at certain loci under divergent or balancing selection should be higher or lower than that at neutral loci, respectively. Utilizing a Bayesian approach estimating allelic frequencies for dominant markers, previously developed by Zhivotovsky  validating the reliability of the detected outliers. BAYESCAN is based on the multinomial Dirichlet model and assumes that allele frequencies within populations follow such a distribution. To directly deduce the posterior probability of each locus being under selective pressure, this approach defines and compares two alternative models . Model selection is then based on posterior odds (PO), which represent the ratio of posterior probabilities of the models and are used as a threshold for considering a locus to be under selection , a program to create statistical parsimony haplotype networks, the alignment of cpDNA sequences was analyzed. For this analysis, insertions/deletions longer than one base pair as well as inversions were coded as single‐step mutations, and sequence gaps were treated as a fifth character state. Genetic diversity indices  based on cpDNA variation were again calculated using ARLEQUIN , respectively. From 558 AFLP fragments, one was monomorphic (0.2%) and therefore excluded from further statistical analyses.Initially, 288 individuals representing four populations per study region were investigated. Final analyses were then based on 267 individuals , as for 21 individuals the generation of reliable AFLP fragment patterns was not possible. The three primer combinations resulted in 219, 170, and 169 AFLP fragments  across all populations, but not within each of the three study regions  was detected.The individual‐based Bayesian clustering analyses of population structure revealed an optimal number of K = 3 groups. All populations from the Swabian Alb region were assigned to one group  while the Austrian and Hungarian populations showed a varying allocation to the remaining two groups: (2) A1, A2, A3, H1, H2; and (3) A4, H3, H4. Moreover, an admixture analysis , leading to a slightly lower regional differentiation of 11.5%; in both cases, the populational differentiation within groups reached about 10%. Population differentiation within each of the three study regions was calculated separately and resulted in the highest differentiation among Hungarian populations (13.4%) and the lowest between Austrian populations  and the proportion of polymorphic markers (PLP) revealed similar results for all populations  of regional genetic diversity, while for the Swabian Alb  and the Hungarian region  analyses indicated lower, but similar genetic diversity. Frequency down‐weighed marker values (from sums) ranged from 51.13 in the population Klingenstein  to 151.67 in the population Bisamberg . On regional scale, the pattern again revealed highest values in Austria  and lower genetic diversity in the Swabian Alb  and the Hungarian region . None of the genetic diversity estimates was correlated with neither population size nor geographical longitude .As estimators of 3.2L. flavum samples, 95 could be finally used for further analyses (others removed due to incomplete sequence information). Therefore, number of individual sequence information range between six and nine samples per population  differentiating all Swabian Alb samples from the rest (including the latter two Eichkogel samples). In the Pannonian group , consisting of 36 haplotypes, no further obvious regional substructuring was found. Within this Pannonian haplotype group three haplotypes  included both, Hungarian and Austrian individuals of two to three different populations  in a westward direction. The highest differentiation among populations within a study region was found in Hungary while the differentiation among the Swabian Alb populations was only slightly lower. Moreover, no clear evidence for reduced genetic diversity within the absolute westernmost exclave could be observed in both, the mainly nuclear AFLP and the chloroplast DNA data. Actually, the estimated diversity values were more similar for the Swabian Alb and the Hungarian populations although the latter ones represent the more continuous part of the distribution range. This result corresponds well with findings by Kajtoch et al. (Pinus nigra) and a recent population decline, there. In summary, although most assumptions of the abundance center distribution hypothesis  in the Austrian and highest in the Swabian Alb region, that is., not following the so‐called abundant center distribution  rather than a postglacial arrival  are currently the only documented populations in this region  distinctiveness of these populations. In this respect, we have to note that genetic markers analyzed here are mainly not suitable for the indication of selective processes. However, at least our AFLP outlier analyses  populations is controversially assessed . As regionally proportions of intraspecific genetic diversity are only rarely quantitatively analyzed . Nevertheless, other investigations covering the intraspecific genetic constitution of steppe plants indicate contrary to our L. flavum study mainly reduced genetic diversity in Central Europe, that is, also reduced uniqueness  and atpI‐H (LT827070‐103).European Nucleotide Archive (ENA) accession numbers for DNA sequences: M.K. and K.P. conceived the idea, interpreted the data, and wrote most of the manuscript; K.P., K.B., and M.K. analyzed the data, and K.B. wrote part of the manuscript and prepared the map. K.P. and K.B. performed the molecular work, and M.K., K.B., M.H., and M.T. collected the plant material. M.H., M.T., and K.B. critically revised the manuscript mainly drafted by K.P. and M.K. All authors finally approved the manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Apis cerana) are an endemic population, which is well adapted to the local agricultural and ecological environment. In this study, the genetic structure of seven eastern honey bees (A. cerana) populations from Mount Huang in China were analyzed by SSR (simple sequence repeat) markers.The Mount Huang eastern honey bees  contains supplementary material, which is available to authorized users. A. cerana) are an endemic population, which is well adapted to the local agricultural and ecological environment. They have a particularly strong foraging instinct and resistance to parasitic mites as well as American foulbrood. This endemic population was listed in the first directory of potential breeding stock for conservation in 2001. The A. cerana conservation document Wannan (Wan D/XM01-19-87) was published according to ecological standards in Anhui province. However, since then, a massive replacement of the endemic honey bees has occurred, especially after the importation of Apis mellifera [A. cerana populations with imported stocks.Mount Huang lies in the southern end of the Anhui province of China (Wannan), between 117°02′–118°55′ east longitude and 29°24′–30°24′ north latitude. It has a typical humid subtropical monsoon climate, luxuriantly diverse flora and fauna, including honey bees. The Mount Huang eastern honey bees  of populations from most of regions in Fujian was 0.5171 . In another study, a significant difference in genetic structures was found among honey bees from six regions in Wuyi Mountain located in Fujian province, the mean He of the six different region population was range from 0.4525–0.5613 [Apis cerana as well as in Apis mellifera (western European honey bee) populations in Jiangsu province, they found the mean He of A. cerana population in this province was 0.4424. Cao et al. [A. cerana populations from different regions in Zhejiang province, their results showed that the genetic diversity of A. cerana in Zhejiang was relatively low, with the mean He was 0.3179. Guo et al. [A. cerana populations in Qinling-Data mountain areas has rich genetic polymorphism, with the mean He, number of alleles, polymorphism information content (PIC) were 0.6877, 7.71, 3.7488 respectively. Ji et al. [A. cerana populations from geographically different regions in China using 21 microsatellite loci. 502 alleles were found, and the average value of He of 21 microsatellites was 0.8689. Additionally, the mean He of the populations from Wuding (Yunnan province), Hainan, Bomi Tibet was 0.695, 0.6641 and 0.562 respectively, revealing their relatively high genetic diversity. Genetic diversity of A. cerana populations from Lushui in Yunnan province was evaluated with 21 microsatellite markers. 121 alleles were found, and the mean number of effective alleles was 5.76, the average He and PIC of all loci were 0.6752 and 0.6192, respectively, these results indicated the high level of genetic diversity in Lushui [A. cerana populations distributed in different geographic areas in the south west Yunnan province were also surveyed using 21 microsatellite loci. All populations showed high levels of heterozygosity except the population from Diqing, the average He of the total populations was 0.739, and a significant genetic differentiation was found among all six populations [A. cerana populations is overall higher in the southwest of China than in the middle east of China.Microsatellites are suitable nuclear markers used in population genetic studies in various taxonomic groups , 3. Thiso et al.  analyzedi et al.  found sin Lushui . Six A. A. cerana in Mount Huang of Anhui province, in south east China, is presently not available. Therefore, the objectives of this study were to examine the genetic structure of Mount Huang honey bee populations using microsatellite analyses. Our findings provide important information that can be used for effective management and conservation of A. cerana in Wannan.However, information about genetic variation of Adult workers from 190 colonies were collected from seven locations covering the main bee keeping areas in Huangshan , south o2 are listed in Table Total DNA was extracted from the thorax of each bee, following the method of Smith and Hagen , and theHo and He) of each microsatellite locus were computed with Microsatellite-Toolkit software [The number of alleles, allele frequencies, observed and expected heterozygosity  algorithms and unweighted pair group method with arithmetic mean (UPGMA) using PHYLIP software package (version 3.69) .Ho and He are listed in Additional file He) varied between 0.597 ± 0.109 in the HSD population and 0.71 ± 0.056 in the SC population, and mean observed heterozygosities between 0.398 ± 0.186 in HSD population and 0.495 ± 0.235 in JC population. The observed heterozygosity (Ho) was relatively high in all populations except that of JC at loci A035, and HSD population at loci A107. The mean number of alleles for each population ranged from 2.936 ± 0.853 in HSD to 6.438 ± 1.632 in SC population.The locations where honey bee samples were collected were mentioned in Yu et al. . The numP < 0.05) from Hardy-Weinberg equilibrium in 86 out of 112 population-locus combination and all deviations were in favor of homozygotes (Table P < 0.0001) differentiation among all populations. Multilocus FIS values varied between 0.181 (A029) and 0.618 (A088), while the FIT values varied from 0.314 (A028) to 0.701 (AP297). A high heterozygote deficiency within populations and the total population were revealed by positive FIS and FIT .We detected significant deviations . The seven A. cerana populations in this study could then be genetically divided into three different groups, which included one group with JC, HSD, YC, and QMC populations, another with JXC and HZD populations, while the SC population was a separate group (Fig. A. cerana and other populations.Large genetic distances were observed among all populations, especially those between oup Fig. . YC was A. cerana on a larger geographic scale should be carried out to fully elucidate the patterns of conspecific and intraspecific population structure in Wannan A. cerana.Microsatellite data obtained in this study demonstrated that the Mount Huanghoney bee populations still have a natural genome worth being protected for conservation. However, further screening of


Falco naumanni), by genetically assigning feathers from individuals of unknown origin that concentrate in large roosts during the pre-migratory period. Our findings suggest that birds from multiple breeding populations in the Central and Eastern Mediterranean region move towards two pre-migratory sites in the Balkans, some of them detouring greatly from their expected flyways, travelling more than 500 km to reach these sites and prepare for the post-nuptial migration. By identifying the origin of individuals using the pre-migratory sites, not only we provide a better understanding of the possible impact of local threats at these sites on multiple breeding populations but also inform the design of effective conservation actions for the species.Identifying patterns of individual movements in spatial and temporal scales can provide valuable insight into the structure of populations and the dynamics of communities and ecosystems. Especially for migrating birds, that can face a variety of unfavorable conditions along their journey, resolving movements of individuals across their annual cycle is necessary in order to design better targeted conservation strategies. Here, we studied the movements of a small migratory falcon, the Lesser Kestrel ( Specifically for birds, extrinsic markers such as ringing and tracking devices have undoubtedly offered a great amount of information regarding routes, strategies, and mechanisms of migration as well as mortality and dispersal of individuals building towards more effective conservation strategies for migratory birds11. Despite this wealth of information, such methods do have limitations mainly due to the need of recovering the individuals to obtain the desired data as, typically, return rates are low12. Although satellite tracking does not require recapturing the individuals, it can however be applied only on relatively large birds due to weight restrictions, while it can come at great cost when information based on a large sample size is needed. On the other hand, intrinsic markers only require an initial capture, but in order to be informative, they need to differ at the population level while these differences have to be quantified a priori13. Stable isotope and genetic markers have been the most commonly used intrinsic markers which either used separately or combined, have contributed significantly to the study of bird movements during the last decades15.Identifying patterns of individual movements in spatial and temporal scales , can provide insights into the structure of populations and the dynamics of communities and ecosystems17. Such approach has proved to be useful in multiple issues such as wildlife poaching20, illegal translocations21 or even used to identify a fishing competition fraud22. Regarding bird migration, genetic markers have been used, mostly at larger spatial scales, in order to link species populations’ breeding and wintering grounds (i.e. migratory connectivity)23. However, only a few studies26 have addressed so far the origin of individuals gathering at staging areas or stopover sites during migration, as insufficient genetic differentiation among populations of migratory species can render the assignment efforts futile27. Since migrating birds are subject to a number of unfavorable conditions that could, in turn, have an effect at a breeding population-level28 resolving movements of individuals across their annual cycle is necessary in order to assess the impact of local threats to population dynamics29 as well as to design effective conservation strategies for migratory birds31.The use of genetic markers is based on the premise that populations show some levels of genetic structuring. Briefly, different areas of the genome can be targeted  and as long as these markers are either population-specific or the genetic variation shows a geographical structure on the breeding range, then any unknown sampled individual could theoretically be assigned back to their breeding populations with the use of assignment testsFalco naumanni) is a small migratory falcon which breeds from the Mediterranean across the Middle East and Central Asia up to Mongolia and China, while its wintering grounds are located in sub-Saharan Africa32. The species underwent rapid declines throughout its European range since the early 1960s, especially in Central and Eastern Europe. Local extinctions and range contraction led to a fragmented distribution of the species34. Currently, Italy and Greece host several thousand pairs accounting for the 36% of the species’ European population35 whereas some smaller populations exist in the Former Yugoslav Republic of Macedonia and the Turkish Thrace. A single colony located in Croatia is considered the northernmost population of the species in Europe36. Lesser Kestrels do not migrate directly to Africa but show a pronounced pre-migratory behaviour that can last for several weeks. That is, after the breeding period and before the post-nuptial migration, adults and juveniles move to specific areas where they form large gatherings and roost communally, mainly in trees. There they exploit the temporal abundance of food resources, mainly insects, so as to build up the appropriate fat reserves and replace – at least partially - their flight feathers (i.e. moult)39. It has also been suggested that such gatherings may facilitate the selection of future breeding habitats and aid spring navigation40. Therefore, the importance of pre-migratory areas has been discussed in previous studies42 for a number of different species46. Although data from tracking devices and ringing recoveries have revealed few specific movements of individuals towards known pre-migratory sites in the Iberian47, Apennine48 and the Balkan Peninsula49, detailed knowledge concerning the origin of individuals in pre-migratory sites is rather restricted.The Lesser Kestrel , 31 out of 146 unknown individuals (21.2%) to a reference population. The majority (19) of these 31 individuals were assigned to Central and Northern Greece (CNG), 6 individuals were assigned to Central Italy (APU), 4 were assigned to the local breeding population of Ioannina (GIA), whereas Agrinio (LES) and Komotini (KAL) had a single individual assigned to each one of them , where the assignment of 31 of them was in agreement with the previous methods. Nevertheless, the spatial smoothing method implemented by SCAT was able to make the distinction between Central (CGR) and a Northern Greek population (KIL) and further assigned five individuals  followed by Structure (89.6%) and GeneClass2 58.5%)  or different moulting strategies62 (i.e. some birds might not moult in the pre-migratory sites but rather perform a complete moult in their wintering grounds) could be further possible explanations.One of the most intriguing results of this study is the detection of putative areas of origin inferred by the continuous assignment method. The majority of putative areas coincide with already known breeding sites of the species such as northern Italy, F.Y.R.O.M., Turkish Thrace as well as smaller colonies in southern Greece. Although some variability in the geographic estimates is expected, the breeding status of the species is still rather precarious in Albania and Montenegro, so more intensive fieldwork in these areas could reveal breeding locations that are suggested by our results. Apart from the located populations of origin, we did not find any sign of birds originating from Croatia, Sicily or Limnos Island. A plausible explanation could be the existence of differences in the breeding phenology and/or variations in the pre-migratory and migratory strategy of these populations: Croatian Lesser Kestrels fledge in late July and move locally before migration63 and when the underlying structure of populations is shaped from isolation by distance processes. Unlike SCAT, most other standard assignment methods suffer from two serious drawbacks. Firstly, they can have a strong bias against the assignment of samples to reference populations of smaller sample sizes because reduced sample size can give inaccurate allele frequencies20. Secondly, they both assume that the true population of origin has been sampled54. The methods implemented in SCAT overcome these limitations of the standard assignment tests. However, our success rates were not high as SCAT was able to assign only 55 out of 146 unknown individuals (37.7%) whereas the other two methods performed less well (21.2%) although results were within the range of other spatial assignment studies63. Low assignment rates in assignment studies can be explained by the ecology and behaviour of the focal species, as patterns of genetic differentiation and gene flow are highly influenced by habitat characteristics and migratory behaviour64. Migratory populations of raptors have been found to generally have weaker genetic structure than non-migratory ones65, because for example some individuals might migrate through a different route upon their return on the breeding grounds, and consequently disperse and breed far from their natal site66. In fact the genetic structure among Lesser Kestrel populations is relatively weak34, therefore some genotypes can be relatively common in more than one potential source populations and unassigned individuals could possess shared common alleles and no rare alleles at some loci, thus showing probabilistic membership to multiple populations. However, the presence of private or rare alleles in the populations along with the spatially patterned distribution of their allele frequencies enabled the assignment of some individuals. Additionally, the number of samples genotyped and our marker of choice may be a limitation on our assignment inference. More training samples or the use of SNPs could improve the assignment accuracy63.Our results conform to the expected elevated performance of the spatial smoothing method in relation to other assignment methods, especially when applied at a regional level31. It has been reported for example that the mountainous areas adjacent to Ioannina city play a major role as foraging grounds for the Lesser Kestrel during the premigratory period39 thus any habitat degradation could compromise birds during this critical stage of their annual cycle. Resolving the pre-migratory movements in Central and Eastern Mediterranean region will help to understand the magnitude of local-threat impacts on the species and highlight the importance of these stopover sites for breeding populations that span across different countries.Despite that, our results are still relevant under a conservation perspective. Both pre-migratory sites should be considered as a single target area for the implementation of conservation actions for the species, since the distance between them is short (approximately 60 km “as the crow flies”) and they host individuals from the same breeding areas. Thus, individuals could easily move between the two sites. The pre-migration period could influence the survival of individuals since birds optimize their condition for migration. As Lesser Kestrels are highly gregarious during this period, even small scale threats can have a great impact on a large number of birdshttp://conventions.coe.int/Treaty/EN/Treaties/Html/123.htm.). Sampling was approved by every relevant national authority: University of Ioannina and the Hellenic Ministry of Environment and Energy (130551/1277) in Greece, University of Bari and Instituto Superiore per la Ricerca e la Protezione Ambientale-ISPRA (n. 0020267) in Italy, and the Croatian Ministry of Environment .Moulted feathers of Lesser Kestrels were collected from the pre-migratory roost of Ioannina city over a 3 year period 2013–2015) and the pre-migratory roost of Drino Valley in 2016 . In cases of feathers without or a barely visible blood clot, we performed a manual extraction following an improved method for moulted feathers68. DNA from blood samples was extracted using the NucleoSpin Tissue kit (Macherey-Nagel) following the manufacturers’ protocol. All individuals were genotyped at 16 microsatellite loci 72. Procedures on loci amplification and their properties are described in detail in Bounas et al.34. Reliable genotypes from feather samples were obtained using the multiple tubes approach74 and consensus genotypes were retrieved using GIMLET75. Due to this approach, it was possible to calculate error rates in feather amplification, by counting directly the wrong genotypes in relation to the total number of genotypes retrieved76 across all loci. We used the package “MsatAllele”77 in R, version 3.2.278 to allocate the alleles to their respective size classes. Genotyping errors due to null alleles and stuttering were examined for each locus and reference population using Micro-Checker79. Deviations from Hardy-Weinberg proportions (HWE) at each locus and reference population as well as linkage disequilibrium (LD) between pairs of loci were tested in Genepop 4.280 following program’s default settings. The results of the above analyses are given in the Supplementary Results. Finally, we used GIMLET to check for duplicate genotypes in feathers collected each year to further avoid sampling the same individuals. Only feather samples that showed a unique genotype and amplified in more than 12 loci (n = 146) were used in further analysis.DNA from a total of 163 flight and tail feathers was extracted using both the basal tip of the calamus and the blood clot from the superior umbilicus of each feather sample81 (http://www.didac.ehu.es/genocline/). The method calculates the correlation coefficient between the frequency of each allele (after angular transformation) and the populations’ spatial location with respect to an axis that rotates 360 degrees in consecutive iterations of one degree. A statistically significant association (p < 0.05) will be indicative of a spatially patterned distribution of the allele frequencies. Feathers of unknown origin were then assigned to a reference population using a combination of the probabilities from the Bayesian method53 implemented in GeneClass2 and the membership coefficients (q) from the analysis in Structure. The sampled population of Central Greece (CGR) and the population of Kilkis (KIL) were merged together (CNG) as they were not found to be significantly differentiated and assignment attempts would be inconclusive34. All other sampled populations were considered as different sources, thus origin assignments were based on a total of eight reference populations. An individual was considered to be of resolved origin if the corresponding score in GeneClass2 was greater than 90 and the Structure membership coefficient was above 0.70. Those thresholds were chosen after comparison with other assignment approaches82. In cases where individuals did not meet the above criteria or the assignment result of the two methods disagreed, they were considered unassigned. For Structure analysis we considered the origin of individuals to be known (except the ones to be assigned), allele frequencies were updated using only the individuals of known origin and assumed admixture among reference populations18. Runs were set with a burn-in period of 2 × 105 iterations followed by 106 MCMC steps with 20 replicates for a fixed value of K = 8.We examined any spatial patterns of allele frequencies in the reference populations using the software Genocline v.1.083 in order to estimate allele frequencies at any location depending on all reference samples and the distance between them. This method seemed to be ideal for our case since it is based on the premise that allele frequencies show some spatial patterning, which is the case in our reference populations , using a relatively large number of iterations  in order to get estimates of the parameters α and β. Then we fixed the parameters to their estimated modal values  and performed five independent assignment runs, each one starting with a different seed for the pseudorandom number generator. For each run we discarded the first 2,000 iterations as burn-in, and stored every 10th of the following 1,000 iterations, resulting in 100 putative locations of origin for each sample. The range of allowable locations for the continuous assignment of individuals was specified by creating a boundary file of the contemporary extent of Lesser Kestrel distribution in the Central and Eastern Mediterranean and Middle East. Boundaries linked all discontinuous range but did not include open sea regions. The uncertainty of each assignment was assessed by examining the density of the plausible location points. If location points clustered tightly together in a single source of origin the individual was considered to be assigned with high confidence, whereas putative location points spreading all over the landscape or concentrated in two or more areas showed high uncertainty and the individuals were left unassigned. The spread of points and plausible locations were assessed and visualized using the heatmap plugin in QGIS v.2.12.3. As an error measurement we calculated the standard distance of the median coordinates for each assignment. The concentration of points around the median coordinates can then be represented as circle with a radius equal to the standard distance value. SCAT v.2.1 was compiled from the source code available at https://github.com/stephens999/scat. Finally, the assignment accuracy of each method was evaluated by performing self-assignment tests on the reference populations  and the average accuracy for each method was calculated .The Smoothed and Continuous Assignments (SCAT) analysis uses a Bayesian method implemented with MCMC spatial smoothingons Fig. . TherefoThe raw genotype dataset generated and analysed during the current study (DatasetLK) is included in this published article (and its Supplementary Information files).Supplementary informationSupplementary DatasetLK


Tricholoma matsutake) has consistently decreased in Japan over the past few decades. We used 15 polymorphic and codominant simple sequence repeat (SSR) markers, developed using next-generation sequencing, to carry out genetic analyses of 10 populations in Nagano, Japan. Using the SSRs, we identified 223 genotypes, none of which was observed in more than one population. The mean expected heterozygosity and standardized allelic richness values were 0.67 and 4.05, respectively. Many alleles appeared in only one of the 10 populations; 34 of these private alleles were detected with a mean number per population of 3.4. The fixation index (FST) and standardized genetic differentiation (G′ST) values were 0.019 and 0.028, respectively. Analysis of molecular variance (AMOVA) showed that the contribution of among population, among genets within a population, and within genets variation to the total variation was 2.91%, 11.62%, and 85.47%, respectively, with genetic differentiation being detected for all sources. Twenty-eight of 45 pairwise FST values were significantly larger than zero, and no pattern of isolation by distance was detected among the 10 populations. Bayesian-based clustering did not show clear differences among populations. These results suggest that reestablishment of a colony would be best accomplished by transplantation within a field; if this is not possible, then transplantation from within several dozen kilometers will cause little damage to the original population genetic structure.The annual yield of matsutake mushrooms ( Tricholoma matsutake (S. Ito et S. Imai) Singer) are a very popular and expensive food item. This mushroom can only be harvested from the wild, since the artificial cultivation of matsutake mushrooms has not yet been successful. The annual yield of matsutake mushrooms has declined steadily in recent decades after peaking in the 1950s [T. matsutake is an urgent matter.In Japan, matsutake mushrooms  to 53.1 (Populations A–I) km . We askeT. matsutake were developed using next-generation sequencing as described by Kurokochi et al. [3 (5 mm × 5 mm × 5 mm) were obtained. In order to get enough DNA with high quality, genomic DNAs were extracted from these pieces of tissue using a NucleoSpin® Plant II kit . Fragmented DNA was produced from the extracted DNA [TM Sequencer . The sequences were collected as described by Kurokochi et al. [http://pgrc.ipk-gate rsleben.de/misa/); 15 regions were selected and Primer3Plus software [New microsatellite markers (simple sequence repeat (SSR) markers) for i et al. ,15. Mushcted DNA ,15. DNA i et al.  and Sugii et al. . SSRs wesoftware  was usedIn order to extract DNA cheaply from the frozen stipes collected from the different areas, the CTAB method  was usedHE; [AR; [FIS) were calculated using FSTAT [FIS deviations from zero by 1000 random permutations. In addition, the number of private alleles, which were detected from only one population, over markers (PA) was calculated for each population using GenAlEx version 6 software [FST) and standardized genetic differentiation between populations (G′ST) were also calculated using FSTAT.After removing clonal replicates from each population, the following statistical analyses were conducted. For each population, Nei’s unbiased expected heterozygosity , alleliHE; [AR; ), and inng FSTAT ; this prsoftware . Nei’s sFST values calculated with Arlequin (1000 random permutations).Assuming that the populations belonged to one group, the contributions of among population, among genets within population, and within genets variation to the total variation were calculated by analysis of molecular variation (AMOVA) using the software Arlequin 2.0 . AMOVA wFST/(1 − FST)  and the natural logarithm of geographic distance, using GenAlEx version 6 software [Patterns of isolation-by-distance (IBD) were evaluated using a Mantel test between software . The sigK) for K = 1–11 using the admixture model with allelic frequencies correlated among populations and ignoring prior population information, with 50,000 MCMC (Markov chain Monte Carlo methods) repetitions and a burn-in period of 50,000 iterations, the optimal value of K was estimated by calculating ΔK [Bayesian-based clustering analysis was used for population partitioning with STRUCTURE ver. 2.3.2.1 . After pating ΔK  to identHE, AR, FIS, and PA values for each population are presented in AR values are standardized to a sample size of five genotypes per population. The FIS values of three populations  deviated significantly from zero (p < 0.05). Private alleles were detected in all populations; in total, 34 private alleles were identified  and six   .T. matsutake) are harvested in several Asian countries, including Japan, China, Korea, and Bhutan [Matsutake mushrooms  were in the same range in all 10 populations (The indexes we used to describe genetic diversity (ulations . As our FST values were significantly larger than zero (Although there was no significant IBD in this study , some pahan zero  and AMOVhan zero . In addihan zero . Intereshan zero , indicathan zero . In addiFST and G′ST. In addition, for the sustainable harvesting of matsutake mushrooms, genetic diversity as described by HE, AR, and FIS (If the considerable efforts of related research organizations lead to the establishment of transplantation methods for matsutake mushrooms, it will be important to conserve their genetic resources at a local level. The present study, which presents an example of genetic diversity at the local level in Nagano prefecture, demonstrates the genetic similarities and differences that need to be taken into account. Since each matsutake population includes its own genetic resources and history , as indi and FIS  could beConsidering these results, the reestablishment of a colony would be best accomplished by transplantation within a field; if this is not possible, then transplantation from within several dozen kilometers will cause little damage to the original population genetic structure.


Colossoma macropomum is the second largest scaled fish of theAmazon. It is economically important for commercial fisheries and for aquaculture,but few studies have examined the diversity and genetic structure of naturalpopulations of this species. The aim of this study was to investigate the levels ofgenetic variability and connectivity that exist between three natural populations ofC. macropomum from the Amazon basin. In total, 247 samples werecollected from the municipalities of Tefé, Manaus, and Santarém. The populations weregenotyped using a panel of 12 multiplex microsatellite markers. The genetic diversityfound in these populations was high and similar to other populations described in theliterature. These populations showed a pattern of high gene flow associated with thelack of a genetic structure pattern, indicating that the number of migrants pergeneration and recent migration rates are high. The values of the FST,RST, and exact test of differentiation were not significant forpairwise comparisons between populations. The Bayesian population clustering analysisindicated a single population. Thus, the data provide evidence for high geneticdiversity and high gene flow among C. macropomum populations in theinvestigated region of the Amazon basin. This information is important for programsaiming at the conservation of natural populations. Colossoma macropomum , commonly known as tambaqui in Braziland as gamitana in Peru, is the largest characid fish of the Amazon basin, belonging to thefamily Characidae, subfamily Serrasalminae. C. macropomum is a tropicalfish species found in the Orinoco and Amazon River basins as well as in their majortributaries. It reaches an average length of 1 m and weight of 30 kg , Manaus (89) and Santarém (63) in the Arém (63) and quanC.macropomum (The genotyping protocol was described in cropomum . To idenO)and expected (HE) heterozygosity and possible deviations from Hardy-Weinbergequilibrium (HWE) were calculated with the program Arlequin 3.5.1.3 (A) and allelic richness (AR)  , were esess (AR) . PolymorTo investigate how genetic variability is distributed across different populations,populations from Tefé and Manaus were randomly grouped, with the population from Santarémforming another group, and analysis of molecular variance (AMOVA) .ST  using the private alleles method , which wThe software BIMr 1.0 was used to detect the recent migration rates (m) and the possibilityof asymmetrical rates based on the Bayesian assignment test ; this alO values ranging from 0.43 (Cmacrμ02) to 0.88 , NA values ranging from 6 to 17 (Cmacrμ07) alleles, AR values ranging from 5.7 (Cmacrμ01) to 15.9(Cmacrμ07), and PIC values ranging from 0.63 Cmacrμ10 to 0.87 (Cmacrμ07)  . Based oST and FST values between paired populations were equal to zeroand not significant . The results of the exact test of populationdifferentiation were also not significant at a level of 5% when we compared thepopulations, this indicating the absence of genetic differentiation between pairs ofpopulations. The results of the Structure program showed that the highest averagelikelihood was a single cluster K=1 , Tefé/Manaus (11.1)and Manaus/Santarém (8.3). The studied populations had few private alleles, with four inTefé, two in Manaus and five in Santarém, among the total of 145 alleles found. The averagefrequency of private alleles between populations was also small, with values close to 0.1.The m values between populations were high and very similar, with all values close to 31%.In addition, the Bayesian approach implemented in BIMr did not identify significantasymmetric gene flow between populations .The popO mean > 0.70) and similar to datareported in the literature for these same markers used for different populations in theAmazon region (Arapaima gigas, haveshown a similar pattern of high genetic variability, including studies reported by For an intensively exploited species such as the tambaqui, the discovery of the level ofgenetic diversity within natural populations is critical to the prognosis of the viabilityof the species. The values for genetic diversity found in the populations analyzed withthese microsatellite markers were high (HThe present results indicate that the populations studied are genetically homogeneous.Similarly, C. macropomum from the Amazon basin. That studyalso found little genetic differentiation and high gene flow between populations, leadingthe authors to propose that these populations form a large panmictic population in thetributary system of the Amazon River. Using mtDNA control regions, C. macropomum populations from these basins,although genetic differences were found to exist between themThe results showing high gene flow are similar to those found by C. macropomum, which isa species that exhibits migratory behavior in search of food, protection, and reproduction.C. macropomum, which is a frugivorous species, is an importantlong-distance seed disperser for various species of plants in the Amazon floodplain, andoverexploitation of C. macropomum can be considered a threat to thediversity of these plants (These results seem consistent with the biology of e plants .C. macropomum,with high genetic variability and high gene flow in the Amazon basin. However, this currentscenario does not guarantee the maintenance of this diversity over time. Only themaintenance and improvement of public policies regulating capture and management can ensurethe viability of this important species. Another needed approach includes an examination ofthe levels of genetic variability in unstudied populations of C.macropomum to determine whether the maintenance of this pattern of geneticstructure is coupled to high genetic diversity and high gene flow.Our results suggest the absence of a genetic structure in


Cave Salamander, Eurycea lucifuga, across its range. In order to perform these analyses, we sampled 233 individuals from 49 populations, using sequence data from three gene loci as well as genotyping data from 19 newly designed microsatellite markers. We find, as in many other species studied in a phylogeographic context, discordance between patterns inferred from mitochondrial relationships and those inferred by nuclear markers indicating a complicated evolutionary history in this species. Our results suggest Pleistocene‐based divergence among three main lineages within E. lucifuga corresponding to the western, central, and eastern regions of the range, similar to patterns seen in species separated in multiple refugia during climatic shifts. The conflict between mitochondrial and nuclear patterns is consistent with what we would expect from secondary contact between regional populations following expansion from multiple refugia.Our understanding of the evolutionary history and ecology of cave‐associated species has been driven historically by studies of morphologically adapted cave‐restricted species. Our understanding of the evolutionary history and ecology of nonrestricted cave species, troglophiles, is limited to a few studies, which present differing accounts of troglophiles’ relationship with the cave habitat, and its impact on population dynamics. Here, we used phylogenetics, demographic statistics, and population genetic methods to study lineage divergence, dates of divergence, and population structure in the  Phylogeographic analysis, examining populations’ evolutionary histories in the context of their spatial distribution, often gives us a better understanding about the formation of lineages and species. Many such studies have examined cave‐dwelling species, which present an interesting and complex look into population divergence given their reliance on such a specific habitat and the adaptive morphological changes that often accompany divergence from surface‐dwelling relatives. The majority of research on cave systems has focused on troglobites (cave‐restricted species), which are characterized by a suite of acquired traits known collectively as troglomorphy. These morphological and physiological traits are thought to act both as a mechanism behind subterranean speciation , likely due to the inhospitable surface environments that discourage dispersal outside of caves . Eurycea is particularly notable for its abundance of troglobitic species. Although the ancestors in this genus were surface‐dwelling, troglobitism evolved independently at least five times within the genus . However, there are anecdotal reports of adult E. lucifuga observed in the forest matrix surrounding caves , and one nuclear locus, proopiomelanocortin (POMC). Primer information and thermocycling conditions are shown in Table S2 (Supporting Information). We cleaned the PCR products using ExoSAP‐IT  and then sequenced both directions using Sanger sequencing on an ABI 3730xl at GENEWIZ . We used the software program Geneious v6.1.6  to edit and build contigs of the resulting sequence. For each locus, sequences passing a quality threshold  were aligned using the Geneious alignment option. Our resulting alignments were unambiguous, and there were no gaps in the sequence. We included sequence data for each locus from E. longicauda (this study) and Pseudotriton ruber . All sequences are deposited in GenBank . We used Xia's Index of Sequence Saturation in DAMBE v5.2 . We extracted total genomic DNA from each sample using either a phenol–chloroform method . Whole sample RNA was extracted using a Qiagen RNEasy Mini Kit  following manufacturer's suggested protocols and processed in the Genomic Core Facility at the University of Virginia's Department of Biology for the construction of individual paired‐end, non‐normalized cDNA libraries using a NEBNextmRNA library Prep Master Mix Set . Individual libraries were given barcodes and pooled, and sent to Genewiz  for sequencing on the Illumina HiSeq 2500 using a PE 2 × 100 bp format. Resulting sequences from each sample were assembled using the program Trinity v.11‐10‐2013  to call alleles at each marker locus for each individual.Loci were amplified in multiplexed reactions using PCR, and products were sent to the DNA Analysis Facility on Science Hill  for fragment analysis using a 3730b, ND2, and POMC individually and as a combined, partitioned dataset under maximum likelihood (ML) and Bayesian inference (BI) using RAxML 7.2.6 (Stamatakis b), HKY+I (ND2), and HKY (POMC). We performed ML phylogenetic analysis using the ML + thorough bootstrap analysis option with two independent runs and 1000 nonparametric bootstraps. We used Bayes Factors implemented in MrBayes to compare the heuristic mean likelihood of two BI analyses, in which one model specified partitioning among codons and one model specified a simpler partitioning scheme with only partitioning among the gene loci. This comparison indicated that the simpler partitioning model was more successful at predicting the data . Accordingly, we used previously published rates to calibrate the clock for cytb and ND2 .We used *BEAST v1.8.1 . The two iterative runs for each K scenario included 20,000 steps as a burn‐in, followed by 200,000 more. The most appropriate number of clusters was determined using the Evanno method  in the program GenoDive v2.0b27  in the program DIYABC v2.0 , ND2 (565 bp), and POMC (409 bp)  from 84 individuals from 27 populations (indicated in Table S1) were included in our phylogenetic reconstructions and demographic statistical analyses. None of our loci exhibited significant saturation , indicating that our sequence data contain useful phylogenetic information.Fragments of cytEurycea lucifuga collected from 49 populations across its range ; 5 loci exhibited inconsistent amplification and were dropped from further analyses. Allele number at each locus (k) ranged from 2–7 . Observed and expected heterozygosity (Ho and HE) were estimated using GenoDive v.2.0b27 . Assignment to these genetic clusters partitions the samples into clear geographic groups: western, north‐central (Indiana), south‐central (Kentucky), south‐central (Tennessee), and eastern populations  and in the south‐central region . When compared directly, the central regions contain significantly more heterozygosity than the western or eastern regions  and strong population genetic divergence among regions . Thirty‐three percent of genetic variance is partitioned among regions and 6% among localities within each region. A substantial amount of variation is partitioned among individuals within localities  (Table P = 0.03) and 18.97% (P = 0.04) of the total variance, respectively, and exhibited significant clustering among populations. There were significant differences in the variation in PC1 among all regions except between the eastern and north‐central regions, and significant differences in variation in PC2 between all regions except for between the south‐central and north‐central regions . However, it has been found that microsatellite data tends to underestimate timing of events, specifically ancient events  and north‐central populations (located in Indiana). However, reconstructions of the evolutionary history of these regions using DIYABC indicated that the eastern and central populations diverged most recently, and that the western populations are the most divergent. The timing of these divergence events was predicted to be much more recent in DIYABC than was estimated using gene loci data, which may reflect a tendency for the underestimation of these events when using microsatellite markers, but also may lend support for recent divergence among these lineages.Analysis using microsatellite data tell a slightly different story about genetic structuring across the range of E. lucifuga is partitioned among the four major geographic regions, and population structure within each region, although significant, is quite low (RST = 0.038). This low structure contrasts with closely related cave‐restricted species  to 0.80  , the taxa in question had experienced secondary contact following divergence (Toews and Belsford, Chioglossa lusitanica (Sequeira et al. Plethodon glutinosis and P. shermani (Weisrock et al. Triturus cristatus and T. marmoratus (Arntzen et al. Triturus montandoni and T. vulgaris (Babik et al. Salamandra salamandra (Pereira et al. Ambystoma barbouri and A. texanum (Denton et al. Ambystoma macrodactylum (Lee‐Yaw and Irwin Plethodon salamanders, the mitochondrial patterns were favored despite unusually high numbers of strongly supported conflicts. This is similar to the results we observe in E. lucifuga, with mitochondrial signal overwhelming the nuclear signal in combined trees.The discordance we see between sequence and microsatellite analyses, which we infer to be a conflict of signal from the mitochondrial and the nuclear DNA due to the minimal signal from the POMC locus, is not uncommon in the literature, and could be indicative of underlying complexities in the evolutionary history of E. lucifuga suggest that mitochondrial gene loci reflects a more ancient evolutionary history, wherein the central and eastern/western lineages diverged during the climatic shifts of the Pleistocene, possibly taking refuge in two locations as has been seen in other species (Phillips The results we see in the case of Phillips . HoweverNone declared.Figure S1. Maximum likelihood tree of cytb, on which the major geographic regions are labeled.Figure S2. Maximum likelihood tree of Nd2, on which the major geographic regions are labeled.Figure S3. Maximum likelihood tree of POMC.Figure S4. Divergence points for times estimated using microsatellite data in diyABC.Table S1. Collecting localities and accession numbers.Table S2. Primer sources and sequence for both PCR and sequencing steps, as well as thermocycler conditions for each primer set.Table S3. Summary of the sequencing results and assembly of the two paired‐end libraries.Table S4. Microsatellite markers developed for Eurycea lucifuga, reported with primer sequence information as well as multiplex configuration and motif.Table S5. Results of jModelTest indicating the most likely model of substitution for each gene locus.Table S6. Hardy‐Weinberg estimations for each locus within each population.Table S7. Results of Structure Harvester indicating the most likely number of genetic clusters in the microsatellite dataset, highlighted in yellow.Table S8. Mode and quantiles of the posterior distributions of the estimated demographic parameters for the Eurycea lucifuga microsatellite dataset using DIYABC.Click here for additional data file.


Phlebotomus papatasi sand flies are major vectors of Leishmania major and phlebovirus infection in North Africa and across the Middle East to the Indian subcontinent. Population genetics is a valuable tool in understanding the level of genetic variability present in vector populations, vector competence, and the development of novel control strategies. This study investigated the genetic differentiation between P. papatasi populations in Egypt and Jordan that inhabit distinct ecotopes and compared this structure to P. papatasi populations from a broader geographical range.b (cyt b) gene was PCR amplified and sequenced from 116 individual female sand flies from Aswan and North Sinai, Egypt, as well as Swaimeh and Malka, Jordan. Haplotypes were identified and used to generate a median-joining network, FST values and isolation-by-distance were also evaluated. Additional sand fly individuals from Afghanistan, Iran, Israel, Jordan, Libya, Tunisia and Turkey were included as well as previously published haplotypes to provide a geographically broad genetic variation analysis.A 461 base pair (bp) fragment from the mtDNA cytochrome P. papatasi collected in Egypt and Jordan. No private haplotypes were identified from samples in North Sinai, Egypt, two were observed in Aswan, Egypt, four from Swaimeh, Jordan and two in Malka, Jordan. The Jordan populations clustered separately from the Egypt populations and produced more private haplotypes than those from Egypt. Pairwise FST values fall in the range 0.024–0.648.Thirteen haplotypes displaying nine variant sites were identified from FST values indicate a strong differentiation between Egyptian and Jordanian populations, although this population structure is not due to isolation-by-distance. Other factors, such as environmental influences and the genetic variability in the circulating Le. major parasites, could possibly contribute to this heterogeneity. The present study aligns with previous reports in that pockets of genetic differentiation exists between populations of this widely dispersed species but, overall, the species remains relatively homogeneous.The clustering patterns and pairwise The online version of this article (10.1186/s13071-018-2785-9) contains supplementary material, which is available to authorized users. Phlebotomus papatasi is the primary vector of Leishmania major, one of the causative agents of cutaneous leishmaniasis in the Old World, the Middle East, and North Saharan Desert. Phlebotomus papatasi also transmits viruses that cause febrile illness in humans, including sand fly fever Naples virus and sand fly fever Sicilian virus [Approximately 0.7–1.2 million cases of cutaneous leishmaniasis (CL) are reported each year –5. Phleban virus .Leishmania major infects approximately 1–2.4% of P. papatasi sand flies in Egypt and up to 5.5% in Jordan depending on the season [Gerbillus pyramidum whereas in Jordan, the typical rodent reservoir is Psammomys obesus [e season , 8. Diffs obesus , 9. Apprs obesus , 8.Phlebotomus papatasi boasts a wide geographical distribution ranging from southern Europe around the Mediterranean Sea, northern Africa, the Middle East, and into India. These sand flies are able to inhabit a variety of ecological niches from tropical climates to arid desert [P. obesus [Leishmania transmission in the Old World. Currently, there is no efficacious vaccine or cure and current treatments can be toxic, time- and cost-prohibitive to those afflicted by poverty and CL, and many people lack access to treatment for cultural reasons or distance from treatment facilities.d desert . Like otd desert , which p. obesus . Female . obesus , 14. ConLe. major infections in mice but pre-exposure to saliva from uninfected sand fly bites protects mice and attenuates the infection outcome through a delayed-type hypersensitivity immune reaction [P. papatasi salivary protein 15 (PpSP15), to be used as a vaccine [P. papatasi populations would demonstrate greater genetic diversity complicating the development of a saliva targeted vaccine [Research has shown that exposure to sand fly saliva exacerbates reaction , 16. The vaccine –21. Give vaccine .Lutzomyia longipalpis [b (cyt b) gene, is maternally inherited, and its slow rate of silent mutations allow enough differentiation to be detected between closely related populations that are within close geographical vicinity or conversely are separated by large geographical distances [Population genetic studies on sand fly vectors provide knowledge concerning speciation, cryptic species, vector dispersal capabilities, population structure, vector competence, and adaptability to changing environmental conditions such as climate, topography and vegetation –26. Althgipalpis , 29. MtDistances , 30–32. istances , 24.cyt b, have been employed to determine genetic variability among P. papatasi populations. Genomic DNA markers and DNA microsatellites have been previously utilized and revealed evidence of population subdivision among this species [cyt b analysis, observed genetic differentiation among widely separated P. papatasi populations [P. papatasi in Egypt and Jordan that inhabit distinct ecotopes through cyt b sequence analysis and compared this structure to P. papatasi populations from a broader geographical range.A variety of molecular markers, in addition to  species , 34. Oneulations . Analysiulations , 35. In Phlebotomus papatasi were collected (n = 133) from 21 field site and colony populations in 8 countries in 2006, 2007 and 2015  and females  were used for DNA extraction. Following the protocol outlined by Lane, P. papatasi were identified by microscopic examination of female spermateca [cted n = 33 from 2cted n = 33 from 2ermateca .Fig. 1PhDNA was extracted using the Invitrogen PureLink® Genomic DNA Mini Kit  according to the manufacturer’s specifications. Individual male flies and the bodies of female flies were processed and DNA samples were stored at -20 °C.cyt b gene was amplified in 25 μl reaction volume: 10× Ex Taq Buffer , 2.5 mM dNTP mixture , 5 U/μl Ex Taq HS  and 10 μM each primer (CB3: 5'-CA(T/C) ATT CAA CC(A/T) GAA TGA TA-3' and N1N-PDR: 5'- GGT A(C/T)(A/T) TTG CCT CGA (T/A)TT CG(T/A) TAT GA-3') [The 3'-end of the T GA-3') .Samples were amplified in an Eppendorf Mastercycler  using the following protocol: denaturation at 95 °C for 5 min, followed by 10 cycles at 94 °C for 30 s, 40 °C for 30 s, 72 °C for 1.5 min, followed by 30 cycles at 94 °C for 30 s, 45 °C for 30 s, 72 °C for 1.5 min and a final elongation at 72 °C for 10 min. Samples were quantified and purity checked using Nanodrop™ Spectrophotometer .cyt b sequences from 116 individual P. papatasi from Egypt and Jordan were analyzed. Twenty-one previously published, haplotypes available on GenBank [P. papatasi from field caught and colony populations originating in Afghanistan, Iran, Israel, Jordan, Libya, Tunisia and Turkey.Sequences were generated in the University of Notre Dame’s Genomics and Bioinformatics Core Facility using the DNA Sanger Sequencing Applied Biosystems 96-capillary 3730xl DNA Analyzer. Sequencing was carried out in both directions and the same primers were used. Sequences were edited using Geneious Pro 5.6.7 [ GenBank   values were calculated using Arlequin [versus geographical distance to elucidate possible isolation of populations by distance. Geographical distances were calculated using GPS coordinates.Multalin was used to align all equences . Gaps weequences . For medequences  was usedArlequin . The corP. papatasi cyt b gene from 116 individual sand flies was PCR amplified and sequenced. The primers that hit the 3' end of cyt b were found to be an informative region and contain sequence variations that could be used for P. papatasi populations. This method has been in use since 1997 [cyt b fragment sequences indicated no insertions or deletions. The predicted amino acid sequences for all 116 fragments were obtained using the Drosophila mitochondrial code. A total of 13 haplotypes were identified  population, whereas two private haplotypes (PPH22 and PPH23) were found for AW (Egypt) population. The Jordanian collected P. papatasi exhibited six private haplotypes; four from Swaimeh  and two from Malka (PPH29 and PPH30). Three haplotypes  were shared by both Jordan populations.Haplotype PPH04 is the most frequent and found in all four populations investigated; Aswan, Egypt, North Sinai, Egypt, Swaimeh, Jordan and Malka, Jordan Table . HaplotyA median-joining network of the 13 haplotypes depicts the relatedness between the haplotypes Fig. . PPH01 iP. papatasi from Egypt and Jordan. Pairwise FST values reveal the highest (0.64815) between North Sinai, Egypt and Swaimeh, Jordan  occurred between Aswan and North Sinai, both in Egypt. There is also very little genetic differentiation between the two Jordan populations with an FST value of 0.03049. Comparisons between Egypt and Jordan populations indicate very great genetic differentiation, as defined by Wright [FST/(1-FST) values and geographical distance  came from Aswan, Egypt. It was expected that the North Sinai individuals would cluster with the Jordanian samples from Swaimeh and Malka due to their close geographical proximity; approximately 170 and 250 km away, respectively. However, the Egypt populations and the Jordan populations clustered separately. More private haplotypes, occupying external node positions in the median-joining network, arose from Swaimeh, Jordan and Malka, Jordan, indicating these haplotypes are more recently diverged [P. papatasi from sand flies sampled around the Mediterranean Sea. More specifically, sand flies sampled from Egypt and Jordan clustered into population B, which further arranged into two subpopulations with no indication of geographical isolation [cyt b analysis in that more haplotypes were present in the Jordan, Israel, Palestine region when compared to Egypt [This study ascertained the genetic variability of four diverged . Previoudiverged  revealedsolation . This stto Egypt .P. papatasi from Jordan (n = 6) is greater than those from Egypt (n = 2); this may indicate that the Jordanian samples are more heterogeneous than those from Egypt. On the other hand, in Egypt, the Aswan samples look more heterogeneous than the North Sinai samples. The variation of topography, as well as differences between the North Sinai biome, which is a desert area with poor agricultural activity and the Aswan biome, which is more diverse and relies on the High Dam to provide water for extensive agriculture, may provide an explanation for the heterogeneous Aswan population.It is interesting to note that the number of private haplotypes present in FST comparisons reveal little genetic differentiation between Aswan and North Sinai in Egypt and Swaimeh and Malka in Jordan but exhibits large differentiation between the Egypt and Jordan study sites. The data suggest significant genetic differentiation between the Egypt and Jordan populations; however, this variation is not attributed to isolation by distance. This result was surprising, but not completely unexpected. As suggested by Khalid et al. [P. papatasi collected in Sudan and Egypt was not due to isolation-by-distance even though the study sites were approximately 1600 km apart. Here, as well as the previous study [P. papatasi. Moreover, anthropogenic changes can also lead to an increase in the dispersal of sand flies [P. papatasi opportunistically inhabit human dwellings increasing the likelihood of disease transmission [Le. major circulating in the same geographical areas [The clear variation in clustering between Egypt and Jordan haplotypes suggest genetic differentiation between these populations. Indeed, pairwise d et al. , geneticus study , 46, 47,nd flies . As a prsmission , 49. It al areas .FST= 0.1565) between the Le. major population in Egypt, ME1 and the Jordan population, ME2, possibly correlating with different native rodent species specific to Egypt and Jordan, as well as, greater biotope diversity in the Middle East [Le. major exhibits a high degree of homogeneity with predominantly two zymodemes circulating in the same geographical range as P. papatasi [Le. major zymodeme variants may contribute to the genetic diversity seen between the Egypt and Jordan P. papatasi populations as well. In a study from Iran, three subpopulations of Le. major coincide with three subpopulations of circulating P. papatasi, which may be due to topography and human movement [P. papatasi and Le. major may be in a genetic arms-race [P. papatasi and Le. major will inform Leishmania transmission and future control strategies [Microsatellite analysis demonstrated a moderate differentiation  of the ribosomal DNA from 27 populations throughout the Mediterranean Basin, North Africa, Middle East and India, revealed no phylogeographical structure exhibiting molecular homogeneity as well [P. papatasi exhibited two main populations implying species homogeneity [cyt b in Tunisian populations of P. papatasi. Shared haplotypes were found at different nodes, including external nodes, in their analysis as well as reflected in our analysis with five haplotypes at external nodes  suggesting no phylogeographical pattern [cyt b gene of 27 individual P. papatasi from 12 countries that produced 17 variant positions and 16 haplotypes. The majority of their haplotypes differed by 1–4 mutations with the highest number of mutations being six. Overall, they determined low genetic variability between wide spread P. papatasi populations. Similar mutational differences were observed in this paper as the majority of haplotypes differed by 1–4 mutations from the ancestral haplotype, with the most mutational steps being 7. Although, Esseghir et al. [P. papatasi populations are sampled over a wide geographical distribution, the species seems to be relatively homogenous making sand fly control strategies possible.This global analysis aligns with other studies , 34, 44  as well . Restric as well . Using m pattern  analyzedr et al.  reportedRecent population genetics studies, like the research presented here coupled with future studies that delve into the trifecta of vector-parasite-environment interactions are vital to expose what drives genetic differentiation, how vectorial competency is impacted and changes in vector and parasite dispersal dynamics , 60, 61.P. papatasi populations from Aswan and North Sinai, Egypt, and Swaimeh and Malka, Jordan, using the mitochondrial cyt b gene. Although the Egypt populations exhibit very great genetic differentiation when compared with the populations from Jordan, this is not due to isolation-by-distance. Other factors, such as genetic variability in the circulating Le. major parasites, other environmental conditions, and/or a variety of reservoir and intermediate hosts present for each study site, may contribute to the detected genetic differentiation. The present study aligns with the growing body of literature in that localized or pockets of genetic differentiation exists between the populations of this widely dispersed species but overall, the species remains relatively homogeneous. The continued surveying of sand fly population genetics helps monitor the dispersal dynamics and vector competency as well as informs the development of control strategies against this important Le. major vector.The present study confirms the presence of genetic variation between Additional file 1:Table S1.Phlebotomus papatasi unique cytochrome b mt gene haplotypes (461 bp) from geographically distant populations. Alignment of variant positions. Dots indicate consensus with the first haplotype sequence, PPH01. (DOCX 21 kb)Additional file 2:Table S2.Cytochrome b haplotype frequencies found in geographically distant Phlebotomus papatasi populations. (DOCX 16 kb)


Aconitum austrokoreense, is a species with limited dispersal ability. Our molecular analysis revealed that within-population level genetic diversity is low, whereas the among-population divergence is high in this species. Moreover, several populations of A. austrokoreense might have experienced recent bottlenecks. The results suggested that the species might have declined and/or still decline in population size, resulting in increased extinction risk. Coupled with the life history traits such as dispersal and pollination, recent habitat fragmentation may further increase the extinction risk of the species.Human-driven habitat fragmentation leads to spatial isolation of endangered plant species, increasing extinction risk. An endangered medicinal herb,  Aconitum austrokoreense, an endangered and endemic species in Korea, is a perennial herb commonly used for medicinal purposes. We used five nuclear microsatellites and one chloroplast marker to investigate genetic diversity and population structure for 479 individuals of A. austrokoreense from seven populations throughout South Korea. A multivariate approach, discriminant analysis of principal components analysis, revealed broad-scale spatial patterns of A. austrokoreense populations across three major mountains that were composed of seven genetically distinct subgroups. High pairwise FST values  suggested significant differentiation among populations. Overall within population genetic variation was low. Based on Mantel test, there was significant correlation between geographical and genetic distances indicating pattern of isolation by distance. Our results suggest that A. austrokoreense populations may have undergone recent population bottlenecks. Given the limited dispersal ability of the species and ongoing habitat fragmentation, population isolation may further be exacerbated leading to increased extinction risk.Human-driven habitat fragmentation leads to spatial isolation of endangered plant species increasing extinction risk. Understanding genetic variability and population structure of rare and isolated plant species is of great importance for assessing extinction risk and setting up conservation plans.  Chersophilus duponti), genetic diversity and inbreeding appeared to be strongly influenced by size of populations  evaluate genetic isolation by geographical distance; (iii) estimate genetic bottlenecks in small and isolated populations; and (iv) propose directions useful for management and recovery plans based on the geographic distribution of genetic diversity. Given that the population sizes are expected to be small with population bottlenecks, we hypothesized that the genetic diversity would be low. We also hypothesized that the populations of A. austrokoreense might have greatly diverged over space due to the population isolations derived from biological nature of the species, i.e. specific habitat preferences and limited seed dispersal.In this study, we investigated genetic diversity and the spatial pattern of genetic structure of Aconitum austrokoreense (Ranunculaceae) belongs to the subgenus Aconitum sect. Flagellaria ser. Racemulosa. Generally, Aconitum species have protandrous flowers that can produce ~10 to 20 minute seeds (ca. 20 mm long) from ellipsoidal follicles , 0.25 μL forward and 1 μL reverse primers (8 pmol each), and 1 μL fluorescently labelled M13 primer . PCR cycling conditions were as follows: 5 min pre-denaturation at 94 °C followed by 30 cycles of 30 s at 94 °C, 45 s at 56 °C and 45 s at 72 °C, followed by eight cycles of 30 s at 94 °C, 45 s at 53 °C and 45 s at 72 °C, and then a final 20 min extension step at 72 °C. The fluorescently labelled PCR products were pooled with a loading buffer of Hi-Di™ formamide  and a size standard GS500LIZ . Amplified fragments were then separated out on an ABI 3730XL automated sequencer . The results of the microsatellite profiles were examined with GeneMarker program  using automated scoring and manual double-checking.Five microsatellite markers  developepsbA-tranH  (psbA-tranH IGS). Amplifications of the selected region were performed in a final reaction volume of 20 µL, containing 10 ng genomic DNA, 10 pmol each of primer and PCR Premix Accupower PCR Premix . We conducted PCR amplification using primer sets as in Based on preliminary laboratory screening, we chose the chloroplast intergenic spacer, NA), expected heterozygosity (He) and observed heterozygosity (Ho). Allelic richness (NA) was calculated using rarefaction curves to standardize across seven populations to 60 genes  and Euclidean distance for 21 population pairs in GENALEX 6.5 , and chose the best K model based on Bayesian information criterion (BIC). To avoid overfitting, we calculated the optimal number of PCs to be retained for DAPC analysis using function ‘optim.a.score’ in R package ‘adgenet’ (We assessed departure from Hardy–Weinberg equilibrium (HWE) and pairwise linkage disequilibrium (LD) for each locus in Arlequin version 3.5 . Becauseadgenet’ .Population at mutation-drift equilibrium approximately shows an equal probability of heterozygosity excess or heterozygosity deficit. To examine whether a population has experienced recent bottlenecks, we tested for excess of heterozygosity as described in psbA-trnH IGS, using 95 % statistical parsimony (http://popart.otago.ac.nz). Because of the non-recombining nature of the chloroplast genome, chlorotypes were then treated as alleles at a single locus. Gene diversity index (Hcp), equivalent to the expected heterozygosity for diploid data, was calculated using ARLEQUIN version 3.5  to identify sequence variants. The integrated software package DnaSP version 5  was usedsion 3.5  using thsion 3.5 .NA) and number of effective alleles (NE) showed different patterns across the populations investigated (NE was the lowest at Choijeong (1.21) and the highest at Chilseon (2.18), whereas NA was the lowest at Mangun (1.80) and the highest at Baengmu (3.39) (He) within populations ranged from 0.143 (Choijeong population) to 0.538 .Allelic richness (stigated . NE was u (3.39) . LikewisP < 0.05). There was no evidence of null alleles in any of five loci after correcting for missing values. Significant LD was observed among 5 of the 10 locus pairs (P < 0.05 using Fisher’s exact test). Overall pairwise population divergences (FST) were high across all seven populations of A. austrokoreense in South Korea, particularly in four populations  exhibited significant deviations from HWE , suggesting a pattern of IBD. We also performed the Mantel test with FST [i.e. FST/(1 − FST)]; however, the transformation was not suitable as the FST values were normally distributed and appeared to have stronger correlations with the Euclidean distance than did the linearized FST.Non-parametric clustering analysis, DAPC analyses, showed the highest support for IC value . DiscrimIC value . Four poIC value . CJ and IC value . ConsistpsbA–trnH region was successfully amplified and aligned for length of 271 bp including 15 nucleotide variations (DNA sequences: GenBank accessions MH078578–MH079047). We identified four haplotypes  from 479 individual plants in seven populations throughout South Korea (Hcp) was 1 for all seven populations . Alleles are more vulnerable to be lost when there is abrupt reduction in population size (A. austrokoreense may be the result of drastic decline in population size (i.e. recent bottlenecks). In fact, our analysis of BOTTLENECK showed that there was a significant excess of heterozygosity for CS population , which is consistent with recent bottleneck. Although it was only marginally significant in statistical analysis, the rest populations also showed signs of recent bottlenecks .As populations become small, population growth and persistence is highly influenced by stochastic events such as genetic drift and inbreeding resulting in reduced genetic diversity and fitness  along Mt. Jiri with dense forests were more tightly clustered from the rest central populations (CR and CJ; see A. austrokoreense have the limited genetic variability and high genetic structure, which might be detrimental to species persistence, as the species may be more vulnerable to novel selection pressure (One of the primary goals for conservation genetics is to understand patterns of genetic diversity and ultimately identify conservation units that are genetically similar. Our study revealed that populations of pressure . Human ipressure  may haveA. austrokoreense would be of great help. For example, neighbouring populations around Mt. Jiri that share high genetic similarity may well be a conservation unit, whereas the other two populations in the central part of South Korea (CR and CJ; Nevertheless, in the light of population connectivity, ongoing habitat destruction could lead to even more increased isolation between populations for the species. For management practices, we propose that maintaining connectivity of the small habitats within the scattered localities and constant monitoring for This work was supported by the grant, NIBR201503101, from the National Institute of Biological Resources, Republic of Korea.C.E.L. and B.-Y.L. designed the project and arranged supporting grant. Sample collections, laboratory work and microsatellite genotyping were conducted by J.-E.C. and J.-N.Y. S.-R.L. conducted genetic and related statistical analyses and wrote the manuscript. C.E.L. and S.-R.L. conceived ideas and revised the manuscript. All authors edited the manuscript and agreed to submit current version of manuscript.None declared.