Special emphasis was placed on the demographic history and genetic features of central, peripheral, and isolated populations. Results of median‐joining network and phylogenetic tree analyses indicate that Siberian roe deer from the Urals to the Pacific Ocean are genetically diverse and that geographical distribution and composition of haplogroups coincide with previously described ranges of the subspecies Capreolus pygargus pygargus and Capreolus pygargus tianschanicus. We found that peripheral populations in the northwestern parts of the species range , as well as the isolated population from Jeju Island, are genetically distinct from those in the core part of the range, both in terms of genetic diversity and quantitative composition of haplogroups. We also found that northwestern  and northern (Yakutia) peripheral populations share the same haplogroup and fall into the same phylogenetic clade with the isolated population from Jeju Island. This finding sheds light on the taxonomic status of the Jeju Island population and leads to hypotheses about the discordance of morphological and genetic evolution in isolated populations and specific genetic features of peripheral populations.Current understanding of phylogeographical structure and genetic diversity of Siberian roe deer remains limited mainly due to small sample size and/or low geographical coverage in previous studies. Published data suggest at least two phylogroups: western  and eastern , but their phylogenetic relationship remains unclear. Combined sequences of cytochrome  It includes two species: the European roe deer (Capreolus capreolus) and the Siberian roe deer  to provide reliable estimates of genetic diversity and analyzed phylogeographical patterns of the Siberian roe deer across Northern Asia, with special interest in genetic differentiation among central, peripheral, and isolated populations. In particular, we tested the hypothesis suggested by Lorenzini et al.  that the22.1C. pygargus from 12 locations in Russia, Mongolia, and South Korea  was amplified by polymerase chain reaction (PCR) using universal primers L14724 (5′—GAT ATG AAA AAC CAT CGT TG—3′) and H15915 (5′—AAC TGC AGT CAT CTC CGG TTT ACA AGA C—3′) , and 1 ×  PCR buffer. PCR products were purified using the Zymoclean™ Gel DNA Recovery Kit . Purified PCR products were sequenced using an ABI Prism™ 377 automated sequencer . The sequencing primers for both mtDNA regions were the same as those used for the amplification, except that in the case of the control region, the sequencing primers included a supplementary inner primer: L—362 (5′—AAT CAC CAT GCC GCG TGA AAC C—3′) . The mitochondrial cytochrome 2.2Capreolus species through BLAST searches  and nucleotide diversity (π) for each of geographical samples were estimated with DNASP version 5.1 . Network analysis effectively portrays the relationships among sequences and allows inference of haplotype genealogies at the population level because they explicitly allow for extant ancestral sequences and alternative connections . European roe deer (Capreolus capreolus) was used as the out‐group for phylogenetic tree construction. The NJ, MP, and ML trees were constructed using MEGA 5.05  were estimated using MRBAYES v 3.2.2  between mtDNA lineages was estimated among clades in the Bayesian tree. T was calculated as K/(2r)  was derived from the mean value of P‐distance between groups with mean distance determined using Mega 5.2  as proposed by Pesole, Gissi, De Chirico, and Saccone (Divergence time ((2r) Li, , where s Saccone .33.1b sequences  revealed 112 haplotypes, 181 polymorphic sites, and 187 mutations (excluding sites with gaps and missing data). Haplotype distribution and estimates of genetic diversity of each population are presented in Tables The combined alignment of the mitochondrial control region 923 bp) and cytochrome equences ,140 bp r3 bp and Most Central and Eastern Siberian roe deer  did not share haplotypes, except for Sokhondinsky, Russia (RSO), in which one haplotype (Hap98) was shared with Altay, Russia (RAL). On the other hand, the Western Siberia and Ural (RARN and RUKO) populations shared several haplotypes with each other. Yakutia, Russia (RYA) and Jeju Island, Korea (SKJ) were represented by a number of common haplotypes within each population, but haplotypes were not shared among themselves or with other populations Table .h = 0.841–0.993 for combined sequences and 0.786–0.984 for the control region) and nucleotide diversity (π = 0.769%–0.974% for combined sequences and 0.935%–1.229% for the control region). Mainland Korea (SKM) was characterized by relatively low nucleotide diversity (π = 0.491% and 0.699% for combined sequences), but high haplotype diversity (h = 0.959 and 0.915 for the control region) compared with other populations. Jeju Island, Korea (SKJ), showed the lowest level of genetic diversity for both combined sequences and the control region.In both combined and control region sequences, the highest levels of genetic diversity, apart from combined nucleotide diversity, were observed in the Trans‐Baikal region (RSMG). Russian Far East (RPRA), Yakutia (RYA), and Ural (RUKO) populations showed moderate to high levels of haplotype diversity  to 0.661 (SKJ vs. SKM)  were not statistically significant, except for SKM versus RSMG. Yakutia, Russia (RYA), was significantly differentiated from most populations , but not the Trans‐Baikal region (RSMG). Also, genetic differentiation between Yakutia, Russia (RYA), and the Russian Far East (RPRA) was low (0.109) but significant.Levels of pairwise population differentiation, 3.2FST's. Thus, we regarded these clusters as “all the rest” rather than separating small clusters, and they are designated as “group D” in further analyses. Geographical analysis of haplogroup distribution  and on Jeju Island (SKJ). Haplogroup C was found throughout all regions, except SKJ.Phylogenetic trees using NJ, MP, ML, and Bayesian approaches generated similar patterns of major branches, and therefore, only the Bayesian tree is presented. The Bayesian tree revealed three major haplogroups with strong posterior probability values >.99 and additional 10 minor clusters and singletons Fig. . These mion Fig. , Table 4The median‐joining network was star‐shaped Fig. , with haD and Fu's Fs) showed negative values, and Fu's Fs for RPRA and RSMG differed significantly from that expected under the null hypothesis of selective neutrality. Such results are typical in the case of incomplete lineage sorting or ancestral shared polymorphism under sudden population expansion   and the Trans‐Baikal region (RSMG) represent populations from the central part of the species’ modern distribution; populations from the Russian Far East (RPRA) and South Korea mainland (SKM) represent the eastern part. Samples from Jeju Island (SKJ) represent an isolated population. The roe deer in Yakutia (RYA) is situated on the northern periphery of the species range. To the west from Ural Moutains Siberian roe deer are sympatric with European roe deer (Capreolus capreolus)     are possible. Most Siberian roe deer populations in this study revealed similar levels of haplotype and nucleotide diversity, compared to those previously reported for Siberian roe deer  parts of the range may reflect relatively stable populations. This suggestion is supported by the mismatch distribution and neutrality tests. Relatively low genetic diversity in the sample from Western Siberia and Western Altay regions (RARN) could be explained by the small sample size. Siberian roe deer from Jeju Island (SKJ) showed the lowest level of genetic diversity in this study and compared to other species. This is presumably due to its geographical isolation  occupy the center of the star‐like shape in the median‐joining network, analysis of divergence time does not allow treating it as an ancestral. It is more likely that all haplogroups separated from a common ancestor at approximately the same time. The position of the haplogroups in the median‐joining networks suggests that all samples’ haplotypes and haplogroups could have originated from basal haplotypes not present in this study. Minor clusters (D) are probably the closest to this ancestral group, while groups A–C changed significantly since the time of divergence from this putative ancestor.FST value indicating significant genetic differentiation between the two populations. According to Zvychainaya et al.  and C. p. tianschanicus , which were previously described based on morphological and cytogenetic traits  and Yakutia (RYA), as well as of the isolated population on Jeju Island (SKJ). Samples from SKJ, RUKO, and RYA, respectively, had one, two, and three haplogroups. Interestingly, the only haplogroup (haplogroup B) detected in Jeju Island was also one of the main haplogroups found in the peripheral populations of the Urals and Yakutia, while it was not observed in the nearby Mainland Korea (SKM) population. This is the first finding that part of the Yakutia (RYA) population is genetically related (shares a haplogroup) to Jeju Island (SKJ). Migration of roe deer to the Jeju Island could have taken place only during periods of glaciation when the island was connected to the continent; thus, haplogroup B may represent one of the oldest genetic lineages. Interestingly, it constitutes the highest proportion of haplogroups mainly in peripheral populations (RUKO and SKJ). A similar pattern of distribution of mtDNA haplotypes was recently reported for another widely distributed mammal species—the European badger, 4.3There are several possible scenarios that could explain the observed distribution of genetic lineages of Siberian roe deer. One possible scenario is that all the analyzed samples originated from the same ancestral group, which was preserved in refugia during the periods of climate change in the Pleistocene. Possible locations of the putative ancestral group include the mountains of the southern Siberia, particularly the Altay, Tyan‐Shan, and Sayan mountains. This suggestion is supported by the distribution of several minor clusters (group D), which is present only in the central‐eastern part of the species’ range, and also by the fact that all haplogroups are present only in samples from Trans‐Baikal and Northern Mongolia (RSMG) and the Russian Far East (RPRA). On the other hand, this suggestion contradicts the lack of eastern haplotypes in Central Siberia in the Zvychainaya et al.  study. TC. pygargus’ geographical range is that several genetic lineages diverged independently from a common ancestor and were isolated from each other during formation of the large open spaces in Central Asia followed by periods of glaciation  of the Jeju Island population from all other populations does not allow classification of the Jeju roe deer as C. p. tianschanicus . Genetic distinction  part of the species range are genetically differentiated from those in the core part of the range in terms of proportional composition of haplotypes. Also, northern  and northwestern  peripheral populations share the same haplogroup and fall into the same phylogenetic clade with the Jeju Island (SKJ) population. The population of Siberian roe deer on Jeju Island is unique, where conservation of one of the ancient mitochondrial lineages is coupled with specific morphological features.Our data show that roe deer in the area from the Urals to the Pacific Ocean are genetically diverse and that the geographical distribution and composition of haplogroups support previously described ranges of the subspecies Korea Science and Engineering Foundation .None declared.


Aphanius farsicus from four different water bodies in the Maharlu Lake basin was investigated by applying five microsatellite markers. All of the five examined microsatellite loci showed polymor-phism pattern. A total of four alleles were detected at five microsatellite loci, with an average of 2.8 to 3.5 alleles per locus. Average values of observed and expected heterozygosity were 0.95±0.09 and 0.64±0.02 respectively. None of the tests of linkage disequilibrium were significant between each pair of loci and no deviation from Hardy-Weinberg equilibrium were detected to test for heterozygote deficiency within populations. The Nei's genetic distance values ranged between 0.03 – 0.13. Analysis of pairwise genetic differentiation between each pair of the populations revealed that fixation index (FST) values ranged from 0.013 to 0.039 and RST ranged from 0.005 to 0.065. High genetic diversity observed within the populations (99%) and low diversity (1%) among them indicating probably high level of gene flow among the studied populations of Fars tooth-carp at the present time or in the past. Regarding low genetic differentiation among the studied populations and results of population assignment test, two hypotheses are suggested and supporting evidence for each hypothesis are provided.Genetic structure of an endemic tooth-carp fish,  Aphanius Nardo, 1827 are widely distributed in coastal habitats of the Mediterranean Sea, Red Sea and Persian Gulf, as well as brackish, freshwater and euryhaline inland water bodies in Iran, Pakistan and India . There is low differentiation between each pair of the populations according to Wright (1978) [FST values from 0 to 0.05, indicate low level of genetic differentiation. Wachirachaikarn et al. (2009) [ST is more powerful than FST in estimation of population differentiation. Results of this study did not show any significant difference between FST and RST values. In consistent to our study, Gholami et al. (2015) [Cytb mitochondrial gene. Analysis of Molecular Variance (AMOVA) is a scale for determining the level of genetic differentiation and genetic similarity between populations . In the ladykovi . In poput (1978)  that sta. (2009)  suggeste. (2015)  reportedAphanius farsicus can tolerate some degrees of salinity, so during this time, it may migrate from one spring to another. The genetic distances obtained in this study based on pairwise population comparisons, coupled with the results of ANOVA and population assignment analysis suggested one genetic population cluster. Regarding to the results, two hypotheses are suggested here. The first probability is that annual floods to the lake make a fresh water area in some parts of it, and fishes can be migrated from one spring to another. The lake is drained by incoming fresh water from rainfall and seasonal floods. Therefore, in a short period of time, the waters of northern and western parts of the lake  probably are partly saline or even fresh. A. farsicus may be relicts of a recently widespread species around the Maharlu Lake and therefore, isolated populations did not have enough time for differentiation and form part of a single genetic population. Study of Gholami et al. (2015) suggested that A. farsicus has experienced episodes of demographic expansion (e.g. after a bottleneck probably due to drought in 1967), and provided evidence that present isolated populations of the species might be caused by recently droughts.The second probability is that currently isolated populations of A. farsicus around the Maharlu Lake provides a major issue in the context of habitat management and conservation of this endangered species.The findings of this study on the close genetic resemblance among populations of


Mikania micrantha, which has rapidly expanded in to southern China after being introduced to Hong Kong in 1884. Seven chloroplast simple sequence repeats (cpSSRs) were used to investigate population genetics in 28 populations of M. micrantha, which produced 39 loci. The soil compositions for these populations, including Mg abundance, were measured. The results showed that M. micrantha possessed relatively high cpSSR variation and differentiation among populations. Multiple diversity indices were quantified, and none was significantly correlated with distance from the origin of introduction. No evidence for “isolation by distance,” significant spatial structure, bottlenecks, nor linkage disequilibrium was detected. We also were unable to identify loci on the chloroplast genome that exhibited patterns of differentiation that would suggest adaptive evolution in response to soil attributes. Soil Mg had only a genome-wide effect instead of being a selective factor, which highlighted the association between Mg and the successful invasion. This study characterizes the role of the chloroplast genome of M. micrantha during its recent invasion of southern China.Two fundamental questions on how invasive species are able to rapidly colonize novel habitat have emerged. One asks whether a negative correlation exists between the genetic diversity of invasive populations and their geographic distance from the origin of introduction. The other is whether selection on the chloroplast genome is important driver of adaptation to novel soil environments. Here, we addressed these questions in a study of the noxious invasive weed,  Mikania micrantha H. B. K. (Asteraceae) represents one of the world’s 100 worst weeds  whether a negative correlation exists between the genetic diversity of a population and its geographic distance from the origin of introduction; (ii) are there any adaptive cpSSR loci that are significantly associated with soil attributes? This study will provide additional information to improve our ability to predict the invasion of M. micrantha in southern China and mitigate its impact.In the present study, we have measured the soil composition and conducted a cpSSR assay for the invasive populations of M. micrantha populations covering its entire introduced range in southern China were sampled as described by Figure 1). To obtain environmental data, three soil samples per population were randomly selected and analyzed. Each soil sample, of about 0.5 g, was taken from a depth of 10–15 cm.Twenty-eight 2SO4 + HClO4 at a ratio of 5:1 (W/V) and then determined using the indophenol-blue and molybdenum-blue method, respectively. Total soil Al, Ca, Cu, Fe, K, Mg, Mn, Na, Si, and Zn concentrations were determined by using inductively coupled plasma atomic emission spectrometry (ICP-AES) after acid digestion.Soil samples were air dried and ground fine enough to pass through a 1.0 mm sieve. The measurement of soil pH was performed in suspension at a ratio of 2:5 (W/V) of soil to deionized water using a pH meter . Electrical conductivity was measured using a conductivity meter , soil moisture was determined by oven drying for 6 h at 105°C, and soil organic matter content was measured by the wet combustion method. Total nitrogen and total phosphate were digested with HTable 1). Only cpSS 02 was an anonymous marker. It is unclear whether cpSS 02 is located in a coding or non-coding region of the cp genome. Polymerase chain reaction (PCR) was performed in a 20 μL final volume containing 1 × buffer, 25 Mm MgCl2, 10 Mm each of dNTP, 0.5 U Taq polymerase, 5 mm of each primer, and 100 ng template DNA. The PCR program was as follows: an initial denaturation of 5 min at 94°C, followed by 35 cycles of denaturation at 94°C for 60 s, annealing at 55°C for 60 s, and elongation at 72°C for 120 s, and a final elongation of 72°C for 5 min. PCRs were conducted on a PTC-100 Peltier Thermal Cycler (MJ Research). The PCR products were sized on an ABI 377 automated sequencer (Applied Biosystems) using ROX-500 as the size marker.DNA extraction methods were presented in detail in a previous study . To opti1. GenALEx 6.3 was used to calculate population genetic parameters including percentage of polymorphic loci, observed number of alleles, effective number of alleles, Nei’s gene diversity, and Shannon’s Information index. The occurrence of null alleles in cpSSR data was determined using MICRO-CHECKER version 2.2.3.Raw fluorescent cpSSR data were collected and scored using software GeneScan 3.7 (Applied Biosystems) and genographer (version 1.6.0)B estimates, which can be obtained by HICKORY v1.0, comprised the matrix of genetic differentiation. To investigate correlation between genetic variation and dissimilarity in soil composition, a partial Mantel test was also performed to evaluate dependence between these variables implemented in GenAlEx (9999 permutations), controlling for the effect of geographic distance.Based on cpSSR data, we measured the population differentiation among and within populations using ARLEQUIN 3.0. Analysis of molecular variance (AMOVA) based on one thousand random permutations were performed at three levels: regional, among-population, and within-population. Also using the same software, isolation by distance, which is the correlation between geographical distance (km) and genetic differentiation among populations, was investigated using the Mantel test. The pairwise 𝜃I, which quantifies the correlation between allelic frequency and spatial distance classes. The distance classes were 0.1, 0.2, 0.3, 0.4, 0.5, 0.6 and 0.7 km in order to obtain a high spatial resolution and to assure a sufficient number of individual pairs per distance class. Tests of significance were carried out against 9999 random permutations and 95% confidence intervals (CIs) were estimated.We used SPAGeDi v. 1.3  to estimM. micrantha in Southern China  and the squared correlation coefficient (r2). Their significance was determined by a two-tailed Fisher’s exact test.Linkage disequilibrium (LD) across loci may bias the estimation of the population genetic variation and differentiation . In ordeThe program BOTTLENECK was used to test whether populations have suffered a bottleneck in the cp genome. The heterozygosity (Heq) expected at mutation-drift equilibrium was calculated based on both the stepwise mutation model (SMM) and the infinite allele model (IAM). The significance of heterozygosity excess was determined by the sign test.Nμ parameter value was set to 0.04 in all simulations. All 28 populations were used for a global analysis of M. micrantha. The outlier threshold was delimited by more restrictive significance levels of 0.005. In addition, to cross-check the reliability of the outlier loci detected by Dfdist, we also ran Bayescan analyses. Bayescan was run with 10 pilot runs of length 5000, followed by 50,000 iterations each, 5000 sample sizes, and 20 thinning intervals. Generally, outliers identified by both Dfdist and Bayescan are likely to be truly adaptive regions of the genome.We used two population genetic approaches to detect outlier loci, i.e., those that show a higher than expected differentiation between populations. First, the software Dfdist a frequentist method based on summary statistics of a symmetrical island model . We used Dfdist to test for the neutrality of cpSSR markers. The 4 FST values for each population and association of FST to environmental factors were estimated using a generalized linear model. The posterior probabilities for each model were provided using a reversible jump MCMC approach based on a sample size of 30,000. The model with the highest posterior probability was the one that best explained the data. We used a burn in of 100,000 iterations with 10 pilot runs of 5,000 iterations and a thinning interval of 50.Program GESTE 2.0, a hierarchical Bayesian method was used to analyze the relationship between genetic structure and environmental factors at each population site. M. micrantha. CpSS 02 was determined to be null alleles using the program Micro-Checker. We excluded this locus from further analyses. Genetic variation revealed with the cpSSR markers was high in M. micrantha. Across all of the populations, the percentage of polymorphic loci was 97.44%, and Nei’s gene diversity and Shannon’s Information Index were estimated to be 0.1686 and 0.2827, respectively.Of the 34 chloroplast microsatellites screened, seven loci  were polymorphic and contributed to 39 alleles in Table 2). In contrast, all estimates except effective number of alleles and Nei’s gene diversity were lowest in population HK87 (Table 2). At the region level, all estimates except effective number of alleles showed that region NLD had the highest level of genetic diversity. No region was found to have the least genetic variation across a majority of the estimates calculated.At the population level, all but one measure (the number of polymorphic loci) of cpSSR genetic diversity were highest in population NLD26. Measures that were highest in NLD26 were: the observed number of alleles, the effective number of alleles, Nei’s gene diversity, and Shannon’s Information Index . A random permutation test revealed that these variance partitions were all significant (P < 0.001). Wright’s FST was 0.1547.Analysis of molecular variance indicated that most (84.53%) of the variance was attributable to the differences within populations, 7.85% was accounted for by differences among populations within regions, while 7.62% was attributable to differences among regions . Both of the clusters exhibited substantial admixture, which is visualized in Figure 2.In the STRUCTURE analysis, the clustering level, r = 0.0711, P = 0.293). That is, no evidence of “isolation by distance” was detected. Because genetic diversity is expected to decrease during the invasion of new regions, regression of diversity on geographic distance from an inferred ancestral source population would reveal a negative correlation coefficient. However, we found that each diversity parameter had no significant correlation with increasing distance from Hong Kong Zoological and Botanical Gardens (Pearson’s r: P > 0.05), which followed the linear regression models reported in Figure 3. From Hong Kong to Guangdong, the genetic diversity of M. micrantha decreased. However, genetic variation in NLD 26 reaches a maximum, then it gradually decreased in other areas. In addition, we also compared the dissimilarity of soil attributes among populations with their genetic distances with the Mantel test; there was no significant relation between these variables.The matrix of genetic distances among populations was not significantly correlated with the corresponding matrix of geographical distances . Similarly, at a finer spatial scale, no significant value of I was detected across different distance classes, ranging from 0 to 0.8 km .Moran’s D’ and r2 statistics (Table 4).All 39 cpSSR alleles genotyped on the 28 populations were tested for linkage disequilibrium (LD). No allelic pairs were found to be in significant LD based on Table 2).When either the SMM or the IAM was assumed, no significant excess of heterozygosity was detected for any population up to and including at the level of the entire range . Only loci under negative selection were detected.We used global 10 PO > 2.0 as a threshold for decisive evidence for accepting a model under selection, which corresponded to a posterior probability greater than 0.91. No locus was found to exhibit a divergence pattern that deviated from neutral expectation .We adopted logSite pH values ranged from 4.07 to 8.13, and organic matter content ranged from 0.70 to 35.65%. Si concentration varied from 0.02 to 2.68 mg/g. In terms of metal concentrations, Mg, Zn, and Al concentrations varied greatly, ranging from 0.048 to 63.9 mg/g, 0.0039 to 0.067 mg/g, and 0.35 to 16.80 mg/g, respectively. Details of soil components were showed in the supplementary Data Sheet.Pr = 0.00390). Due to the fact that no adaptive loci were identified in the cp genome, Mg appeared to have only a genome-wide effect instead of being a selective factor.GESTE analyses were carried out on all cpSSR loci and environmental variables. Generalized linear models were run using all seven non-metal factors , resulting in a total of 128 models. For 10 metal factors, a total of 1024 models were produced. Mg was found to have the highest probability model, 513 . Moreover, lack of spatial genetic structure also indicates that populations of M. micrantha are not subdivided into local demes or subpopulations that are consisted of interbreeding, closely related plants. These results, which suggest that dispersal and establishment via seed prevail over vegetative expansion, may be helpful for developing an efficient control program.Besides seeds, rosettes . VegetatM. micrantha , instead of just being a selective factor, has a genome-wide effect on cpDNA. Mg is an essential element for plant growth and development, whose biological functions include key roles in photosynthesis, protein synthesis, and nucleotide metabolism . In partroplasts . Small v enzymes . More im enzymes . Our finM. micrantha. High genetic variability and differentiation, no linkage disequilibrium, and no severe bottlenecks were observed in the introduced populations of M. micrantha by using cpSSRs. Each genetic diversity parameter showed no significant correlation with increasing distance from the origin of introduction. Soil appeared not associated with the cpDNA variation of M. micrantha. Our results provide a framework for further exploring the cp genome evolution of M. micrantha.The present study is the first to report on chloroplast genomic diversity of the invasive weed TW designed and performed the experiments, and wrote the manuscript; ZW conducted data analysis and checked English grammar; GC performed the cpSSR experiment and soil analysis; CW performed data analysis; YS contributed to the supervision of the work and wrote the manuscript. All authors read and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Phytophthora infestans (Mont.) de Bary, the causal agent of potato late blight, was responsible for the Irish potato famine of the 1840s. Initial disease outbreaks occurred in the US in 1843, two years prior to European outbreaks. We examined the evolutionary relationships and source of the 19th-century outbreaks using herbarium specimens of P. infestans from historic (1846–1970) and more recent isolates (1992–2014) of the pathogen. The same unique SSR multilocus genotype, named here as FAM-1, caused widespread outbreaks in both US and Europe. The FAM-1 lineage shared allelic diversity and grouped with the oldest specimens collected in Colombia and Central America. The FAM-1 lineage of P. infestans formed a genetic group that was distinct from more recent aggressive lineages found in the US. The US-1 lineage formed a second, mid-20th century group. Recent modern US lineages and the oldest Mexican lineages formed a genetic group with recent Mexican lineages, suggesting a Mexican origin of recent US lineages. A survey of mitochondrial haplotypes in a larger set of global herbarium specimens documented the more frequent occurrence of the HERB-1 (type Ia) mitochondrial haplotype in archival collections from 1866–75 and 1906–1915 and the rise of the Ib mitochondrial lineage (US-1) between 1946–1955. The FAM-1 SSR lineage survived for almost 100 years in the US, was geographically widespread, and was displaced first in the mid-20th century by the US-1 lineage and then by distinct new aggressive lineages that migrated from Mexico. Phytophthora infestans (Mont.) de Bary exemplifies this threat and causes potato late blight. This disease is the most important biotic constraint to potato production globally [Movement of plant pathogens into new geographic ranges and expansion into new hosts is a major factor in the emergence of novel virulent lineages that threaten food security . The oomglobally . Historiglobally . Long diP. infestans results from a series of migrations and displacements of clonal lineages [P. infestans in the US and Canada has been simpler and largely consists of new introductions of a few multilocus genotypes that have been displaced over time [The current global population structure of lineages –9. Whilelineages , 10–12, ver time –15. Thisver time , 17.th-century US and European outbreaks of the disease. Some data support a Mexican source of the disease [P. andina occurs only in the Andean region and shares an ancestral haplotype lineage with famine-era lineages of P. infestans [Although we have improved our ability to track recent outbreaks of late blight , 14, an  disease , 18, 19  disease , 20–22 o disease . In the  disease , 24. Ear disease , 26. The disease . In addinfestans –30, thusth century, was suspected to be the cause of ‘famine-era’ outbreaks of P. infestans [th-century samples documented an entirely different Ia mtDNA haplotype [th century [P. infestans collected between 1845 and 1896 from herbarium samples [P. andina Adler & Flier, sp. nov in a study that included genomic data from both Yoshida et al. and Martin et al. and that the mitochondrial lineage diverged into several clades [P. infestans.A single clonal lineage named US-1 , which was globally distributed in the mid-20nfestans  until PCaplotype ,9. We co century . Two ind samples , 33, 34. samples . Althoug samples , 35, Marl clades , 32, 33.P. infestans from North, Central, and South America  loci to resolve the population structure and evolutionary relationships of historic New and Old World P. infestans and to characterize the SSR lineage from original outbreaks The primary objectives of our work were to: 1) Examine the evolutionary relationships of P. infestans from the first historic US late blight outbreaks; 2) Compare the genetic structure of these populations to historic European P. infestans; 3) Examine the genetic relationships of historic to modern US aggressive lineages; and 4) Explore migration scenarios that best describe the source of the first US historic outbreaks of P. infestans.We collected a larger set of historic specimens of  America  than prePhytophthora infestans was sampled from both historic US and European herbarium vouchers as well as modern isolates obtained from cultures derived from infected host tissue. A total of 183 samples were analyzed from historic US (1855–1958), European (1846–1970), South American (1913–1929), Central American (1941–1956), Mexican (1948–1966), and more recent global sources (1992–2014) (n = 66) include the oldest existing US specimen, collected in 1855, and one of the oldest existing European specimens, collected in 1846. Modern samples collected in North America (n = 34) included samples from the early 1950s-1990s  and recent US lineages [n = 83) include South America , Central America , Ireland, Canada, and Mexico. Two historic cultures (P445 and PA 222) of P. infestans collected in the 1950s and 1960s were shared by Mannon Gallegly. The P445 isolate is an A2 mating type and was collected in Mexico and is notable for its use in the US Cold War late blight research at Fort Detrick. The PA 222 is an A1 mating type and was collected in Pennsylvania.92–2014) . The hisopean 184–1970, So3, US-24). SampledFor specific analyses, samples were divided into eight populations: historic US (USHist), historic European (EUHist), US-1 lineages , modern US lineages (USAGG), South America (SA), Central America (CA), Mexico (MEX), and Ireland (IRE). With the exception of US-1, all groups were divided based on spatio-temporal boundaries.DNA from modern isolates was extracted using either a hexadecyltrimethylammonium bromide (CTAB) method  or a modras and PiAVR2) and one mitochondrial (P3) locus were sequenced  located in the 5’ untranslated region of the gene and a 600 bp portion (with RASF/RASR) covering part of exon 3, exon 4, exon 5, part of exon 6, and introns 3 and 4 [PiAVR2, was amplified with primers AVR2F1 and AVR2R2 [rp114, rp15, and tRNAs. For herbarium samples, a smaller 492 bp region nested within the P3 region was amplified with primers P3H4F/ P3H6R [Two nuclear loci , 0.25 μL BSA (20 mg/mL), 0.2 μL Taq (5 U/μL), and 5–10 ng of genomic DNA. For herbarium samples, reaction volumes were decreased to 25 μL. Thermal cycling conditions for nuclear genes were 96°C (1 min); then 35 cycles of 96° (1 min), 55° (1 min), 72° (2 min); and a final extension of 72° (10 min). For mitochondrial gene regions, thermal cycling conditions followed Griffith and Shaw [PCR reactions were performed in 50 μL volumes for each sample. Each reaction contained 5 μL of 10X PCR buffer , 2.5 μL dNTPs (2 mM per nucleotide), 2 μL each 10 μM forward and reverse primer, 1.8 μL MgCland Shaw . PCR reaP. infestans isolates by creating multiple sequence alignments of genotype calls from Martin et al. [Gene sequences were determined for some of the target loci  within In et al. . BAM filn et al. . GATK waP. infestans SSR loci were genotyped using a modified version of the protocol for 12-plex single sequence repeat genotyping as described previously [eviously . The Qiaeviously . FragmenK values from 1 to 10 with 20 replicate runs at each value of K. The optimal K was estimated using the Evanno method in the web tool Structure Harvester [K value onto maps of Europe, Latin America, and the United States. To further visualize groupings, a discriminant analysis of principal components (DAPC) was conducted using the R library adegenet [Analysis of SSR genotypes was conducted using the program Structure v.2.3.3 . The datarvester . In addiarvester  and visuarvester . The geoadegenet . The R ladegenet  was usedras dataset contained 12 of the 14 documented SNPs in the dataset, while no recombination was detected in PiAVR2 or in P3.All statistical analyses of the nucleotide sequences were performed in SNAP Workbench version 2.0 . All seqw was calculated using Watterson’s θ [s, and the average pairwise nucleotide diversity, π [The nuclear and mitochondrial DNA sequences were analyzed using Arlequin . For eacrson’s θ , based orsity, π  were estrsity, π , 61 wereras, PiAVR2, and P3. Coalescent analyses were conducted using genetree [ras) times, each using different random seeds to evaluate convergence. The representative tree was chosen by examining the consensus of topology and mutation structure between all trees.Ancestral recombination graphs and coalescent analyses were generated using the loci genetree  as implegenetree . Analyseras sequence data and IM to calculate migration rates between populations for US historic, South American, and Mexican lineages and US-1, South American, and Mexican lineages [We used the lineages . These rlineages . Tested lineages  and thena) was calculated for clone corrected data  and SA populations, indicating no linkage among markers and clonal populations.Samples were divided into eight populations by geography and time: historic US (USHist), historic European (EUHist), US-1 lineages , modern US lineages (USAGG), South America (SA), Central America (CA), Mexico (MEX), and Ireland (IRE). A total of 179 multilocus genotypes (MLG) were detected within 12 microsatellite loci. The greatest number of MLGs was observed within the US historic (USHist), US Aggressive (USAGG) and South America (SA) populations, while the least number of MLGs was observed among modern Irish (IRE) populations. USHist, USAGG and SA lineages had the highest MLG diversity indices. The Index of Association  and Old World historic (EUHist) outbreaks belonged exclusively to the same genetic cluster, representing a nuDNA SSR lineage that was named FAM-1 (K (P. infestans genotypes recovered from the two oldest South American (SA) samples from Colombia collected in 1913 and 1929 and the oldest sample from Costa Rica collected in 1942. With K = 4, the US-1 genotype (mtDNA haplotype Ib) formed a second distinct genetic group  was conducted utilizing SSR data. USHist and EUHist populations formed two overlapping populations largely separate from all other groups. The FAM-1 lineage shared allelic diversity with some samples from SA populations . The larras gene (intron 1 and exon regions 3–6); 200 nucleotides of the PiAVR2 gene; and 379 nucleotides in the mitochondrial genome region P3   . Twelve ormative . A totaleviously (S5 and Sras gene (W) than populations from MEX  (One synonymous substitution site and 4 nonsynonymous substitutions were found in exons 3–6 of the ras gene . Populatfrom MEX . All pop p>0.05) .PiAVR2, and it was phylogenetically informative and resulted in a nonsynonymous substitution site and two haplotypes were observed (W) than populations from USHist, US-1, SA and IRE (One segregating nucleotide site was identified in observed . Populat and IRE .W) compared to those from MEX , including one haplotype (H4) unique to the SA population and one (H3) unique to the MEX population  and PiAVR2 (m2 = 6.99 vs m1 = 5.05)  . Mean po1 = 6.34) than MEX (m2 = 5.70) populations for ras, indicating asymmetric migration (2 = 6.25) than USHist (m1 = 4.62), also indicating asymmetric migration. Only a slightly higher mean number of migrants and symmetrical migration between SA and USHist populations was observed for PiAVR2 .Although migration into both USHist and MEX populations was detected, a higher mean population mutation rate and higher mean number of migrants was observed into USHist (migration . Additio2 = 7.02 vs m1 = 5.03) and SA than US-1 populations (m2 = 6.18 vs m1 = 4.85) was observed for ras. Similarly, a higher mean number of migrants into MEX than US-1 populations (m2 = 6.48 vs m1 = 4.45) and SA than US-1 populations (m2 = 6.54 vs m1 = 5.78) was observed for PiAVR2  was chosen as the most likely model. This scenario was a model in which the USHist lineage diverged first from a common ancestor that then diverged into MEX and SA populations . ConfideWe tested the migration scenarios between US-1, SA, and MEX populations and the scenario with the highest probability  was a scenario in which SA populations diverged first from a common ancestor followed by divergence of US-1 and MEX populations . Estimatn = 66) and modern samples (n = 117) examined to date. Our data revealed the widespread occurrence of a unique historic nuDNA SSR lineage of P. infestans that we have named the FAM-1 lineage. This lineage was found in historical US specimens collected from 1855 to 1939  and type Ia mitochondrial lineages are sister lineages [P. infestans from Peru that were clustered with the US-1 lineage. Herbarium samples from the US placed the US-1 lineage in Texas in 1931 Click here for additional data file.S2 FigYellow dot indicates the point of coalescence. Numbers along branches indicate the number of mutations between points.(TIF)Click here for additional data file.S3 FigYellow and green dots indicate the points of coalescence. Numbers along branches indicate the number of mutations between points.(TIF)Click here for additional data file.S4 FigProbabilities are based on the highest value of a logistic regression of data.(TIF)Click here for additional data file.S5 FigProbabilities are based on the highest value of a logistic regression of data.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table2, and maximum likelihood coefficient of admixture.Summary statistics for all runs: within population statistics: mean number of alleles and mean genetic diversity; between sample statistics: mean number of alleles, mean genetic diversity, Fst, shared allele distance, (δμ) (DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.S9 Table(DOCX)Click here for additional data file.S10 TableProbabilities listed are the highest values as calculated over a 10-sample logistic regression.(DOCX)Click here for additional data file.


Pseudacris feriarum and P. nigrita to investigate geographic variation in hybridization frequencies and to assess whether reinforcement may have contributed to increased genetic divergence within species. Previous work indicated these species have undergone reproductive character displacement (RCD) in male acoustic signals and female preferences due to reinforcement. We also examined acoustic signal variation across the contact zone to assess whether signal characteristics reliably predict hybrid index and to elucidate whether the degree of RCD predicts hybridization rate. Using microsatellites, mitochondrial sequences, and acoustic signal information from >1,000 individuals across >50 localities and ten sympatric focal regions, we demonstrate: (1) hybridization occurs and (2) varies substantially across the geographic range of the contact zone, (3) hybridization is asymmetric and in the direction predicted from observed patterns of asymmetric RCD, (4) in one species, genetic distance is higher between conspecific localities where one or both have been reinforced than between nonreinforced localities, after controlling for geographic distance, (5) acoustic signal characters strongly predict hybrid index, and (6) the degree of RCD does not strongly predict admixture levels. By showing that hybridization occurs in all sympatric localities, this study provides the fifth and final line of evidence that reproductive character displacement is due to reinforcement in the chorus frog contact zone. Furthermore, this work suggests that the dual action of cascade reinforcement and partial geographic isolation is promoting genetic diversification within one of the reinforced species.Reinforcement contact zones, which are secondary contact zones where species are diverging in reproductive behaviors due to selection against hybridization, represent natural laboratories for studying speciation‐in‐action. Here, we examined replicate localities across the entire reinforcement contact zone between North American chorus frogs  If hybridization and/or recombination are too high, the evolution of isolation will be hindered due to homogenization of the interacting taxa Barton, . At leasTheory also predicts that upon formation of a reinforcement contact zone, introgression should occur at a relatively high rate initially but should decline as prezygotic isolation evolves Blair, . LongituRecent work has suggested that interactions between species in contact zones can not only lead to increased isolation between the two focal taxa, but via a process termed cascade reinforcement, these interactions between species can promote diversification within each of the interacting species Howard, . IntraspPseudacris). Specifically, we focused on examining the contact zone between P. feriarum and P. nigrita, two species that are sympatric along the Fall Line, which separates the Coastal Plain and Piedmont regions of the southeastern United States. Phylogeographic data suggest that P. feriarum and P. nigrita diverged approximately ~8 mya  Is the level of admixture higher in more recent contact zones (northern regions) compared to older contact zones (southern regions)? (3) Is gene flow bidirectional or are females of the species exhibiting stronger RCD less likely to hybridize, leading to asymmetric hybridization? (4) Do the interacting species show evidence for greater genetic differentiation between sympatric–sympatric and sympatric–allopatric localities compared to allopatric–allopatric localities? (5) Do reproductive (acoustic) behaviors predict hybrid index? (6) Does the degree of RCD predict admixture levels in populations? We address these questions utilizing nuclear, mitochondrial, and behavioral data from >1,000 individuals across >50 localities and ten focal sympatric regions across the southeastern United States. This work satisfies the final of five criteria put forth by Howard  Does natural hybridization occur between y Howard  that we y Howard  to demon22.1P. feriarum and P. nigrita) from 51 localities (counties) across the southeastern United States ; the multiplexes are listed in Tables ™ Formamide (ABI) and 0.35 μl GeneScan™ 500 ROX™ or 500 LIZ™ dye size standard (depending upon the multiplex) for fragment analysis on an ABI 3730 Genetic Analyzer at Florida State University. Fragment sizes were visualized as histogram distributions in R , and boundaries between peaks representing bin ranges were recorded and applied to the raw data to determine alleles (fragment lengths).A total of 1,118 individuals were genotyped at 12 polymorphic tetra‐ and dinucleotide microsatellite loci, including some previously published markers . The 51 groups are referred to as populations for analyzes below. Detailed analyzes were conducted for each microsatellite locus in the two largest reference allopatric populations: one of P. feriarum from Macon Co., Alabama (n = 83) and one of P. nigrita from Walton Co., Florida  across loci using GENEPOP version 4.2 , and all allopatric P. nigrita were pooled into a second reference group (n = 80). A hybrid index was then estimated for each of the ten sympatric focal regions with these references in separate analyzes.A hybrid index was estimated for each of the five focal sympatric regions with large sample sizes , as well as for five sympatric regions of P. feriarum females × P. nigrita males from Liberty Co., FL, USA) were genotyped for the same microsatellite loci used in this study, and their hybrid index was estimated using the same methods and reference populations as above. The boundaries of F1 hybrid versus pure genotypes were then set based on the range of hybrid index values exhibited by these control samples . Thus, all wild‐sampled individuals with hybrid indices falling within the range of the laboratory hybrid controls were classified as putative F1 hybrids, although we are aware that this hybrid index range may also have included some backcross and introgressed progeny as well. Precision in estimation of F1 hybrid index is expected to improve with the inclusion of additional markers  F1 hybrids and (2) any type of hybrid, using the two methods above, across the five regions. Tests were performed in the R statistical environment version 3.1.0  with up to five published reference sequences per species to establish the species of origin for the mitochondrial genome in each F1 hybrid. Of the 190 F1 hybrids identified using microsatellites, sufficient DNA remained to sequence 185 for the 16sc mitochondrial regions. Five additional putative F1 hybrids (based on morphology and acoustic data) from R6 (n = 1) and R8 (n = 4) were also sequenced, though not genotyped. To determine whether there was evidence for asymmetric introgression , exact binomial tests were performed on localities with the number of F1 hybrids >15 individuals: (1) Florida R2 individuals (n = 109), (2) Virginia R8 (n = 26), (3) Virginia R9 (n = 16), (4) Georgia R10 (n = 18), and (2) all regions combined (n = 190).For individuals identified as F1 hybrids using the microsatellite‐based method above (for either the 12‐locus or 10‐locus datasets), the maternal parent was characterized through Sanger sequencing of a fragment of the 16S rRNA gene of the maternally inherited mitochondrion. The methods employed follow Moriarty and Cannatella , Lemmon,2.6P. feriarum only, and (3) P. nigrita only. Analyzes were conducted in GenAlEx 6.5  were performed on microsatellite data (binned fragment lengths) from: (1) both species together, (2) Fst values  and the average residual of comparisons involving only allopatric populations . The null distribution was estimated by recomputing the test statistic after randomizing the assignment of allopatry or sympatry to each locality. A total of 200 randomizations were performed, and the test statistic was compared to the null distribution.The degree of isolation‐by‐distance  was tested using a Mantel test Mantel, . The tes Wright, , 1978 be3 Ersts,  using GP2.7n = 318) and from additional frogs recorded (n = 155) since publication of the study  were collected and analyzed following Lemmon . Because these analyzes did not require individual genotypes to be matched to acoustic signals, a broader dataset from 441 published and unpublished acoustic recordings was utilized  in the allopatric P. nigrita from Walton Co., FL . Therefore, analyzes were conducted with and without these two loci to ascertain their effects on the results. As the effect was minimal, most results are presented based on the 12‐locus dataset only.All 12 of the microsatellite loci had high levels of variation, ranging from 6 to 32 alleles per locus (mean = 20) in the allopatric L Tables . A totalts Rice, . Linkagets Rice, . Evidenc3.2P. feriarum and P. nigrita sampled along their contact zone throughout the southeastern U.S. in Alabama, Florida, Georgia, South Carolina, and Virginia. STRUCTURE analyzes identified the presence of two main clusters in the dataset, corresponding to P. feriarum and P. nigrita , Virginia R8 (p = 1.05e−05), Georgia R10 (p = 7.63e−06), but this pattern was not significant in Virginia R9 (p = 8.04e−01). Overall, when all regions were combined there was strong evidence that P. nigrita is the primary maternal parent in F1 hybrids (p = 1.85e−11). Small sample sizes for F1s in six localities precluded an in depth examination of geographic variation in direction of introgression across regions.Mitochondrial sequencing revealed both types of F1 hybrid crosses in natural populations Table . Exact b3.4P. feriarum between sympatric South Carolina R6 and other P. feriarum  and all other P. nigrita , P. feriarum shows differentiation into an Inland and Coastal clade, which was previously described by Wright and Wright . Strong IBD was found in P. nigrita . The IBD randomization test indicated that in P. feriarum, genetic divergence between allopatric locality pairs was lower than between other types of locality pairs  after controlling for genetic distance . This pattern was not observed in P. nigrita (p = .94).A weak pattern of IBD was detected for 3.5r2 = .72, p < .0001 and r2 = .57, p < .0001, respectively; Figure r2 = .77, p < .0001 and r2 = .60, p < .0001, respectively; Figure r2 = .79, p < .0001 and r2 = .63, p < .0001, respectively) according to both the Akaike Information Criterion  and advanced hybrids , or F1 hybrids . For P. nigrita, RCD did not predict admixture in terms of undetermined hybrids , advanced hybrids , or F1 hybrids . Sampling of additional sympatric regions would improve the power (P. feriarum n = 8 and P. nigrita n = 6 sympatric regions) of these analyzes.Level of RCD was not a strong predictor of degree of admixture in sympatric regions in either 4The presence of hybridization in all sympatric regions spanning the chorus frog contact zone indicates that the opportunity for reinforcement to promote the evolution of reproductive isolation exists throughout sympatry. Moreover, in all regions examined to date, premating isolation has increased in sympatry: A pattern of reproductive character displacement in male signals is present in one of the interacting species Lemmon, , which i4.1s = 0.14), but males experience strong negative sexual selection (s = −0.95) due to their intermediate acoustic mating signals, as well as partial sterility  compared to other regions Tables . One queResults from this study do not support the prediction that putative recent contact zones have higher rates of hybridization. This prediction was derived from the expectation that hybridization rates should decline through time as reinforcement proceeds Blair, . InsteadP. feriarum in Florida R2 and South Carolina R6), to island‐type sympatric distributions , is predicted to contribute further to narrowing of the female P. feriarum preference function, resulting in even lower hybridization in these three‐species regions , and in the total dataset  suggest that these populations have low levels of gene flow with allopatric P. feriarum to the northwest along the floodplains of the Wateree and Congaree Rivers above Lake Marion. Our surveys, however, have not detected large populations along this corridor . In P. nigrita, the populations showing the highest genetic differentiation are from a disjunct sympatric “island” relative to the main distribution of the species, R7‐R9 in eastern Virginia . These sympatric populations are ~200 mi from the current main distribution of the species, although museum records suggest that the distance was less in the last century. In both areas, RCD of the “peninsula” or “island” species rather than the widespread species has occurred, and the resulting displaced acoustic signals are not only divergent from the heterospecific taxon but also from other allopatric and sympatric conspecific populations , but alternatively, the relationship between these variables may be subtle. For example, it is likely that the direction of behavioral phenotypic evolution matters more than absolute magnitude of RCD. In P. feriarum, the locality with the lowest hybridization level (South Carolina R6) is also the only locality that that exhibits the unique pattern of RCD only in pulse number, compared to other localities that diverged in pulse rate or in both variables .Dryad Data Repository (None declared. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Chromaphis juglandicola, and its introduced parasitoid, Trioxys pallidus, provide insights into the localized breakdown of biological control services in walnut orchards in California. We found that sampled populations of C. juglandicola exhibited higher estimates of genetic differentiation (FST) than co‐occurring populations of T. pallidus. In contrast, estimates of both the inbreeding coefficient (GIS) and contemporary gene flow were higher for T. pallidus than for C. juglandicola. We also found evidence of reciprocal outlier loci in some locations, but none showed significant signatures of selection. Synthesis and applications. Understanding the importance of coevolutionary interactions for the sustainability of biological control remains an important and understudied component of biological control research. Given the observed differences in gene flow and genetic differentiation among populations of T. pallidus and C. juglandicola, we suspect that temporary local disruption of biological control services may occur more frequently than expected while remaining stable at broader regional scales. Further research that combines genomewide single nucleotide polymorphism genotyping with measurements of phenotypic traits is needed to provide more conclusive evidence of whether the occurrence of outlier loci that display significant signatures of selection can be interpreted as evidence of the presence of a geographic mosaic of coevolution in this system.Coevolution may be an important component of the sustainability of importation biological control, but how frequently introduced natural enemies coevolve with their target pests is unclear. Here we explore whether comparative population genetics of the invasive walnut aphid,  As is typical for nonhost alternating aphids, walnut aphids reproduce through cyclical parthenogenesis  to compare levels of genetic differentiation among populations of T. pallidus and C. juglandicola in California, (2) to estimate rates of gene flow and inbreeding among these populations for both species, and (3) to use population genetics to detect outlier loci and the potential for reciprocal selection as preliminary evidence for the existence of a geographic mosaic of coevolution in the walnut aphid biological control program.In a previous study, we examined whether hybridization among descendants of two different introduced populations of 22.1T. pallidus either by aspirating adults or by collecting mummified walnut aphids and placing small cut‐out sections of leaf material with each mummy into glass vials (9.5 mm × 3 mm). These vials were closed with a foam stopper and stored at room temperature until adults emerged. Whether aspirated, or reared, adults of T. pallidus were then stored in 95% ethanol at −20°C for molecular analysis. Individuals of C. juglandicola were collected in the field and immediately placed in 95% ethanol and then stored at −20°C for molecular analysis. Effort was taken to collect only a few individuals per tree and to prioritize sampling from as many different trees as possible in each orchard to reduce the sampling of clonally related individuals , within‐population heterozygosity (Hs), total heterozygosity (Ht), and the inbreeding coefficient (GIS) were all estimated using the software program GenoDive v.2.0b27 , the average effective number of alleles per locus (Eff_num), the observed heterozygosity  were then estimated between each population using the BayesAss Edition v. 3.0 (BA3) software package  between these and other locations can be estimated for each locus and used to look for outlier loci. If outliers are detected at a particular location for both interacting species, the location may be a coevolutionary hot spot, whereas if outliers are present for only one or neither of the interacting species, the location may be a coevolutionary cold spot. These same neutral loci can then be used to estimate levels of gene flow between locations. Finally, evidence for population structure (genetic diversity) and outlier loci can be used to identify potential hot and cold spot locations, which in conjunction with measurements of phenotypic or behavioral traits, and can be used to confirm whether the interacting species are under reciprocal selection. By combining measures of gene flow and inbreeding with outlier detection using both known cold spot and undetermined hot and cold spot locations, this approach addresses the three underlying processes that form the basis for testing the geographic mosaic theory of coevolution; (1) coevolutionary hot and cold spots, (2) selection mosaics, and (3) trait remixing  (Hemiptera: Aphididae). The reference cold spot for our C. juglandicola analyses was located near Linden, CA, where we found walnut aphids, but were unable to locate any adult T. pallidus or aphid mummies. To identify outliers, we then estimated locus‐specific measures of genetic differentiation for both C. juglandicola and T. pallidus using our above null‐allele estimates of FST and RhoST in GenePop based on pairwise comparisons between the reference cold spots and each candidate location. Using the “boxplot” function in the statistical software package R v. 3.1.3  was notably low (Table GIS) for T. pallidus populations  was considerably higher than that for C. juglandicola populations , although these differences were not significant based on post hoc t test analyses as implemented in R . Of the four populations from which both T. pallidus and C. juglandicola were both collected, three of these  had higher estimates of GIS for T. pallidus than for C. juglandicola. For T. pallidus, all but one population (Newark) displayed significant deviations from HWE (p < .017), whereas for C. juglandicola only a single population (Arbuckle) displayed significant deviations from HWE .Genotyping results for the individuals analyzed are available in Appendix T. pallidus , and five of the 66 pairwise LD comparisons for the microsatellite loci amplified from C. juglandicola  showed a significant presence of LD. However, only the pairwise comparison between Cj_MSAT8 and Cj_MSAT19 displayed significant LD after Bonferroni's correction for multiple comparisons .Three of the 105 pairwise LD comparisons for the microsatellite loci amplified from T. pallidus and C. juglandicola showed evidence of significant population differentiation . In contrast, for C. juglandicola, seven of the ten pairwise comparisons showed evidence for significant differentiation of populations . For T. pallidus, there were no clear patterns of geographic structuring, as one population from the northern end of the sampled region (Upper Lake) was more similar to a population from the southern end of the sampled region  than it was to more geographically proximal locations. However, for C. juglandicola, populations in the southern end of the sampled region  were more similar to each other  varied between population pairs for both of the interacting species; however, gene flow was only significant (95% CI's not including 0) for populations of us Table . There w3.2FST for each population pair using the “boxplot” function in R identified outliers in three of the pairwise comparisons for T. pallidus , and in all four comparisons for C. juglandicola   and two loci were outliers in one of the four pairwise comparisons . For C. juglandicola, two loci were identified as potential outliers in two of the four pairwise population comparisons  and three loci were identified as potential outliers in one of the four pairwise comparisons . Using the approach of Vermeer et al. (p < .05) signatures of selection.Analyses based on identifying outliers from values of null‐allele corrected ) Figure . For T. r et al. , results4C. juglandicola by T. pallidus, our results indicate that these two species differ in regard to their levels of genetic differentiation, with the former showing greater geographic structure than the latter. In addition, while we did find reciprocal outlier loci, indicative of the potential for coevolutionary hot and cold spots, none provided a significant signature of selection. Consequently, this study provides us with a curious and apparently contradictory pattern—namely that T. pallidus showed lower levels of genetic differentiation among populations while displaying elevated levels of inbreeding within populations compared to C. juglandicola.The study of coevolutionary interactions has not only helped to explain patterns of species diversity . While aphid species have shown evidence of rapid evolution in response to changes in their environment  in North America (Callaway, Hierro, & Thorpe, If as expected, coevolutionary interactions are both spatially and temporally dynamic Torres,  and are C. juglandicola and T. pallidus, and trait remixing based on gene flow among populations, provides some of the first support for the potential of a geographic mosaic of coevolution in a classical biological control program. However, as Vermeer et al. (Therefore, our finding from this study of the reciprocal presence of outlier loci among populations of r et al.  outline,r et al. . Given tConsequently, understanding the importance of coevolutionary interactions for the sustainability of biological control remains an important and understudied component of biological control research. This is in part due to the fact that there have been very few long‐term, postrelease studies of biological control agents and their targets (McCoy & Frank, None declared.JCA conduct the field sampling, generated the molecular data, and performed analyses. NJM oversaw the collection of data and provided laboratory support. Both authors contributed equally to the study design and the drafting of the manuscript. Click here for additional data file.


We set out to describe the fine-scale population structure across the Eastern region of Nepal. To date there is relatively little known about the genetic structure of the Sherpa residing in Nepal and their genetic relationship with the Nepalese. We assembled dense genotype data from a total of 1245 individuals representing Nepal and a variety of different populations resident across the greater Himalayan region including Tibet, China, India, Pakistan, Kazakhstan, Uzbekistan, Tajikistan and Kirghizstan. We performed analysis of principal components, admixture and homozygosity.We identified clear substructure across populations resident in the Himalayan arc, with genetic structure broadly mirroring geographical features of the region. Ethnic subgroups within Nepal show distinct genetic structure, on both admixture and principal component analysis. We detected differential proportions of ancestry from northern Himalayan populations across Nepalese subgroups, with the Nepalese Rai, Magar and Tamang carrying the greatest proportions of Tibetan ancestry.We show that populations dwelling on the Himalayan plateau have had a clear impact on the Northern Indian gene pool. We illustrate how the Sherpa are a remarkably isolated population, with little gene flow from surrounding Nepalese populations.The online version of this article (doi:10.1186/s12864-016-3469-5) contains supplementary material, which is available to authorized users. The Himalaya was first colonised by modern humans approximately 25,000 years ago , 2. SpanNepal is a “multi-ethnic” country, with 125 ethnic groups recorded in the 2011 Nepalese census , 4. ReflPrevious studies have applied mitochondrial DNA (mtDNA) and Y-chromosome genetic systems as tools to reconstruct historic demographic events in Nepal. These studies have pointed to significant genetic structure across populations dwelling in Nepal. For example, a South-Central European origin has been attributed to Y chromosome haplotypes prevalent in the Nepalese Newar population, interpreted as suggesting gene flow from India into Nepal. In contrast, haplotypes observed in the Nepalese Tamang population are commonly observed in Tibetan populations, suggesting ancestry from the North of the Himalaya –12. ThesThe study of autosomal genetic variation appears to support the theory of admixture in Nepalese populations. A recent survey of multiple Nepalese and Burmese populations pointed to significant genetic differentiation between populations residing within the Himalaya. This differentiation appeared to be structured according to the principal linguistic phyla in the region-Tibeto-Burman and Indo-European, suggesting that both language and geography were influencing gene flow in the region . HoweverA recent study, using dense autosomal genotype data, explored the genetic history of Tibetans and Sherpa residing at high altitude . The stuWe set out to describe fine-scale population structure and admixture of the Sherpa and their neighbouring Nepalese populations using dense genomic datasets. We performed a detailed investigation of the genetic architecture of seven Sherpa villages located in the Khumbu region of Eastern Nepal and five Nepalese ethnic groups, which collectively represent the majority of the Nepalese population.We performed principal component analysis (PCA) (see methods), to provide a broad overview of population structure across the Himalaya see Fig. . Four brThe Nepalese as a whole appear as a potentially admixed population on the PCA, lying between the ‘southern’ (Indian) and ‘northern Himalayan’ (Tibetan) clusters. Interestingly, the distinct Nepalese ethnic subgroups  to quantify population differentiation across the Himalaya observed by PCA and admixture , we performed a 3-population test using two source populations, Tibetans  and each of the four ancestral Indian ethnic groups  . We identified significant signals of admixture (Z < −5) in the Nepalese for northern and southern Himalayan ancestry, the most significant admixture event being between the ANI and Tibetans  admixture events were then dated in the admixed Nepalese subgroups  using Rolloff . ResultsWe investigated the extent of homozygosity in populations across the Himalaya to shed further light on the demographic history of the region. Elevated levels of runs of homozygosity (ROH) can be used to inform on isolation and consanguinity within a population , 25. We e, with little recent consanguinity (indicated by negligible ROH16).Notably elevated levels of ROH16 were also observed in the Sherpa and Nepal cohorts  segments between pairs of individuals within a population, to ROH within individuals from the population. Where recent consanguinity is present, one would expect a significant increase in ROH within, compared to IBD between, members of that population. We set an IBD segment threshold of 16 Mb as indicative of a recent common shared ancestor between a pair of individuals. Results are illustrated in Additional file Our findings reveal that geography has influenced the shaping of genetic structure in the Himalaya at both a macro and micro level. The observation from PCA of four broad population clusters across the Himalaya is consistent with recent reports , 14, 28.We have illustrated the presence of a Himalayan ancestry component in contemporary Indian populations, specifically those defined as Ancestral Tibeto-Burman (ATB) by Basu et al. . It is iLarge mountainous regions can be expected to influence favourable directional gene flow between frontiers. Physiological stress imposed by high altitude may restrict gene flow from areas of low altitude to high altitude . HoweverAlthough it is well established that the Nepalese are a highly admixed population, the extensive structuring of admixture across subpopulations has not previously been described. We identified the Rai, Magar and Tamang to carry the greatest proportions of Tibetan ancestry, respectively. These three Nepalese ethnicities have been recognized to have Tibetan origins, and all speak Tibeto-Burman languages , 19, 29.Despite the Sherpa’s residence in Nepal for the past 400–600 years, the Sherpa remain as an isolated homogenous population with little or no gene flow from their immediate Nepalese neighbours or any populations south of the Himalaya. The Sherpa genome is enriched for the previously reported ‘high altitude ancestral component’  Fig. 2)2), refleWe detected considerable levels of autozygosity within the Sherpa and their neighboring Nepalese populations. The patterns of ROH we observed across the majority of Sherpa and Nepalese subpopulations indicate both ancient and recent parental relatedness. IBD analysis confirmed that the Nepalese Indo-Aryan appear to be the only significant consanguineous subgroup. We believe the elevated IBD16 in the Sherpa reflects a history of population isolation due to the remote location of high altitude villages in eastern Nepal and is also suggestive of founder effect . This caWe note an important limitation of our study: that of the 125 recognized ethnic groups in Nepal , we onlyIn summary, analysis presented here illustrates the impact of broad Himalayan geography on genetic structure in the region. Significant gene flow from north of the Himalaya to Nepal is clearly evident, with relatively little gene flow in the opposite direction. Ethnic subgroups within Nepal show distinct genetic structure, reflecting differing histories of admixture and isolation. The Sherpa appear as a remarkably isolated population, with little gene flow from surrounding Nepalese populations.Nepal Federation of Indigenous Nationalities”, we selected the most common indigenous Nepalese ethnic groups that collectively represent approximately 50% of the population of the Eastern Mountain and Hill Region of Nepal , Magar (n = 10), Tamang (n = 18) and Newar (n = 17). We also included the Indo-Aryan (n = 11) considering their close ethnic relation to the Newar [The 2011 Nepalese census recorded 125 distinct ethnic groups . Using the Newar . For thehe Newar –40.n = 43), Khumjung (n = 30), Namche (n = 19), Lukla (n = 9), Khunde (n = 7), Forte (n = 3) and Solukhumbu (n = 7). Details of two of these recruitment efforts have been described previously [We established a cohort of 118 Sherpa from three distinct recruitment efforts, including 49 previously genotyped individuals . The Sheeviously , 41. We For fine scale population analysis we have catagorised the Sherpa by village and the Nepalese by their ethnic group , Yunnan (n = 35), Tuo Tuo river (n = 46), Maduo (31), and Tibetans resident in the UK (n = 27) [We extended our cohort to include other populations representing the greater Himalayan region. We included formerly genotyped Tibetans from Lhasa ((n = 27) –45.n = 59), Bukhara, Karshi, and Tashent in Uzbekistan (n = 83), Shing, Zeravshan, Kalaikhum, Khorog, and Rushan in Tajikistan (n = 83) and Krakoi and Kara-koo in Kirghizstan (n = 184). We refer to these populations collectively as the “Pamir” cohort.Previously genotyped individuals representing populations along the Silk Road were also included, considering their cultural and economic ties with populations of Central Asia . These cn = 44), and individuals from Lahore . See Additional file We also included genotype data for 331 individuals from 18 mainland Indian populations kindly provided to us by Basu et al. [DNA isolation and purification was completed for 36 Nepalese and 21 Sherpa . Venous blood was collected from each subject in 2 ml EDTA vacuettes. White blood cells were isolated following a standard lysis protocol and DNA was purified using the QIAamp DNA mini kit, Qiagen.Genotyping was performed on 82 Nepalese, and 69 Sherpa individuals at the Wellcome Trust clinical research facility, Edinburgh. The Illumina OmniExpressExome BeadChip 8v1–2 system captured 964,193 SNPs.p < 0.001 were excluded. Individuals in each population were checked for cryptic relatedness and where identity by descent (IBD) scores of >0.125 (3rd degree relative) were identified one from each such pair was removed. An exception to this IBD filter was made for the Sherpa where an IBD score <0.180 was accepted since the Sherpa seemed in general to have a higher degree of cryptic relatedness, possibly due to the isolation of the villages and small population numbers [Quality control (QC) was performed in PLINK V1.07  on each  numbers , 49. Ind2) between each pair of SNPs in a 1000 SNP window, and one of a pair of variants dropped from the dataset where LD (r2) between that pair was >0.8. The sliding window was then shifted 50 SNPs and the process repeated throughout the entire dataset.For downstream analysis we refer here to ‘full’ or ‘thinned’ datasets. The ‘full’ dataset is that where all SNPs that passed standard QC were used, including the SNPs that are in high linkage disequilibrium. The ‘thinned’ dataset was prepared in PLINK, on the merged population datasets. Linkage disequilibrium was calculated , 137 Tibetans, 44 Han, 168 Pakistan, 326 Indians  was performed on the ‘thinned’ dataset using routines available via Genome-wide Complex Trait Analysis (GCTA) . ResultsMaximum likelihood estimation of individual ancestries was run using the software package ADMIXTURE . Using oTo quantify admixture events between populations we applied the 3-population test, d-statistic, F4 ratio estimation and Rolloff following standard protocols as implemented in the software package AdmixTools (V. 3.0) . All theTo model gene flow patterns between populations north and south of the Himalaya into Nepal we used the software tool Treemix (V 1.12) . This wast was used to measure population differentiation [st calculations were performed on the “thinned” datasets.Weir and Cockerham’s pairwise Fntiation . Fst calWe performed ‘runs of homozygosity’ (ROH) analysis in PLINK, applying the following parameters: a cross-genome sliding window of 5 Mb, allowing 1 heterozygous and 5 missing calls through a ROH. A density of SNP coverage within the ROH was set as no more than 1 SNP per 50 kb. Thresholds for accepting ROH, were set to runs of at least 100 consecutive homozygous SNPs spanning lengths of 1, 5, 10 and 16 Mb of the genome. The total mean ROH length across the genome was then calculated per population and plotted using Matlab. All ROH analysis was performed on the “full” datasets, 201,573 SNPs and 637,670 SNPs for the Sherpa and Nepalese.T-test.We tested for consanguineous unions by comparing identity-by-descent (IBD) runs between pairs of individuals within a population, to IBD runs within individuals  of the same population. Where consanguineous unions are common in a population, one expects longer ROH within, compared to IBD between individuals of that population. We used default parameters in PLINK (v1.07) to calculate IBD segments between individuals on a “full” dataset, and ROH within an individual was calculated as described above. We specified a segment-length threshold of >16 Mb for both ROH and IBD, as recent consanguinity would generate runs above this threshold. Where pairs of individuals did not share segments of IBD satisfying the threshold we assigned a value of zero. IBD segment values were summed for all autosomes between each pair of individuals. The summed IBD segments between pairs were compared to the ROH within individuals using a two-tailed unequal variance


Due to the unique inheritance pattern, X-chromosomal short tandem repeats (X-STRs) have several advantages in complex kinship cases, such as deficiency cases or grandparent-grandchild and half-sisters testing. In our study, 541 unrelated individuals gathered from Mongolian and Eastern Chinese Han populations were successfully genotyped using the Investigator Argus X-12 kit. We calculated allele/haplotype frequencies and other forensic parameters of the two populations and further explored their genetic distance with already published Chinese populations and six global populations. Our results showed that the 12 X-STR markers were highly informative in the two populations when compared with nine other Chinese populations: significant differences were found at several loci. Geographically neighboring populations or different ethnic groups within the same area appeared to have closer evolutionary relationships. We also analyzed population genetic structure by performing clustering with the STRUCTURE program and Principal Coordinate Analysis (PCoA), and we found that the Chinese and other populations enrolled in this study could be distinguished. Furthermore, Mongolian males were distinguishable from the other studied males by a moderate genetic distance. Our study also expanded the X-STR database, which could facilitate the appropriate application of the 12 X-STR markers in the forensic field in China. These different approaches can complement each other with their characteristic genetic information. For instance, the ancestral information of populations deduced from genetic analyses could be quite different depending on the type of genetic marker used3. Meanwhile, in the identification of some certain kind of mixed stains, X-STRs can be used to exclude male individuals from the same paternal line. Moreover, because of the unique genetic inheritance of the X chromosome, the use of X-STRs is of great benefit in the identification of victims of war or mass disaster4.Short tandem repeats (STRs) are relatively mature genetic markers that were widely used in forensic applications. Genotyping of X-chromosomal STR (X-STR) markers has developed into a valuable method used by many forensic researchers as a supplement to the information provided by autosomal STR (AS-STR), Y-chromosomal STR (Y-STR), and mitochondrial DNA, particularly in deficiency and complex kinship cases9. To our knowledge, five Chinese Han subpopulations14 and eight ethnic minority groups from China19 have been previously studied using this kit. There are 56 ethnic groups in China, which has the largest population and third largest territory in the world. Each ethnic group has different geographical distributions, religions, customs, etc. Throughout history, some of these groups have been relatively isolated from each other, which may have resulted in relatively stable genetic differences between populations in defined areas. Therefore, for a better forensic application of the 12 X-STRs, it is important to understand the similarities or differences in genetic distance between different Chinese populations.There are several X-STR multiplexes being applied to forensic cases and genetics research. Among them, the Investigator Argus X-12 kit , which includes 12 X-chromosomal STR markers as well as the amelogenin locus, has been used worldwide in a number of population setsThe purpose of this study was to investigate the frequency distribution data and forensic parameters of 12 X-STR loci in Mongolian and Eastern Chinese Han unrelated individuals as well as to illustrate the X-chromosomal evolutionary relationships between different Chinese populations and in comparison to other global populations. Additionally, this study enriched the X-STR database in order to highlight its significance in forensic identification and kinship analysis in different ethnic populations of China.20. Eastern China also has a large Mongolian population and accounts for 29.3% of the total population of China. In our study, samples from 541 healthy unrelated individuals  were collected. Blood samples were obtained from volunteer donors had information available under informed consent, following the protocols approved by the ethics committee at the Academy of Forensic Science, Ministry of Justice, P.R. China. DNA isolation was carried out by a Chelex-100 extraction protocol21. All the methods were carried out in accordance with the approved guidelines of the Academy of Forensic Sciences, Ministry of Justice, P.R. China.More than 70% of China’s Mongolian population lives in Inner Mongolia, which is located on the Eurasian continentXL Genetic Analyzer  with the protocol guide for genotyping and the allele designation was analyzed using the Genemapper ID v3.2.1 software .All DNA samples and positive control samples (9947 A and XX28) were amplified with the Investigator Argus X-12 kit  on a GeneAmp PCR System 9700 Thermal Cycler , according to the manufacturer’s protocol. PCR products were detected by capillary electrophoresis on an ABI PRISM 313022 for female samples and were counted for male samples. Arlequin v3.5.223 was used to calculate haplotype frequencies of the four linkage groups in male samples; Hardy-Weinberg equilibrium (HWE) in female samples; the exact test of population differentiation based on allelic frequencies of males and females; linkage disequilibrium (LD) in males and females; and pairwise Fst genetic distances per locus among Mongolian, Eastern Chinese Han and nine other published populations from China19. Forensic parameters for 12 X-STRs including polymorphism information content (PIC), homozygosity (HOM), heterozygosity (HET), power of exclusion (PE), paternity index (PI), paternity exclusion chance in duos and trios (MECD and MECT)24, as well as power of discrimination for males (PDM) and females (PDF) were calculated with pooled allelic frequencies of the two populations using the online tool of the Forensic ChrX Research database (http://www.chrx-str.org).Allelic frequencies of the 12 X-STRs were calculated with CERVUS software/PowerStats v1.2.xlshttps://www.R-project.org). The evolutionary history of eleven Chinese populations was inferred using the Unweighted Pair Group Method with Arithmetic mean (UPGMA) method25, and the optimal tree with the sum of branch length = 0.00821881 was shown (next to the branches). The evolutionary distances were used for phylogenetic analyses conducted in MEGA7 software26. Detailed population genetic structure analysis was performed with STRUCTURE v2.3.428 under the condition of the admixture model and correlated allelic frequencies between populations. We analyzed the structure of Mongolian/Eastern Chinese Han populations and nine other populations from previous studies based on the same 12 X-STRs. The analysis results were uploaded to the Structure Harvester29 to detect the true K value of the data. Further comparisons among different male populations based on the Nei’s unbiased genetic distance31 were calculated and Principal Coordinate Analysis 32 was performed using GENALEX 6.5 software.China map was generated by and Package (ggplot2) and (maptools) of R: A Language and Environment for Statistical (All data generated during this study are included in this published article (and its Supplementary Information files) and from the corresponding author on reasonable request.33. In the Mongolian samples, a total of 164 alleles were typed using the Argus X-12 kit and no statistically significant deviation from HWE was observed except for the DXS10134 locus in female samples (p = 0.0027) even after applying the Bonferroni’s correction for multiple testing (p = 0.05/12). This deviation from HWE may be caused by the substructure of the chosen population, which could result in a bias of the samples. In addition, no statistically significant LD was found in Mongolian females after Bonferroni’s correction (p = 0.05/66), which was different from the Eastern Chinese Han analysis. This might be due to the rigorous statistical methods. On the other hand, statistically significant LD was found between DXS10101 and DXS10103 loci in Mongolian males (p < 0.0001), which has also been reported in other populations35.The results of HWE and LD tests in Eastern Chinese Han were presented in our previous reportThe 12 X-STR markers are clustered into 4 linkage groups based on their physical localizations: LG1 (Xp22) DXS8378-DXS10135-DXS10148, LG2 (Xq11) DXS7132-DXS10074-DXS10079, LG3 (Xq26) DXS10101-DXS10103-HPRTB, LG4 (Xq28) DXS7423-DXS10134-DXS10146, and thus each cluster of 3 markers is considered as one haplotype for the genotyping of males. The numbers of observed haplotypes in Mongolian males were 99, 71, 76 and 81 for LG1, LG2, LG3 and LG4, respectively  by the Exact Test; therefore, males and females were pooled for calculating forensic parameters. The allelic frequencies of 12 X-STRs are shown in Supplementary Table F, PDM, MECD and MECT were calculated as exceeding 0.9999999999, 0.9999999983, 0.9999987070 and 0.9999999931, respectively. All these forensic parameters demonstrated that the 12 X-STR markers were highly polymorphic and will be useful in forensic applications or anthropological research among the Mongolian population of Inner Mongolia and the Eastern Chinese Han population.The allelic frequency and forensic parameters of Eastern Chinese Han were also presented in our previous reportF of the 11 populations were greater than 0.999999999, except for the Guangdong Yao ethnic group (cPDF = 0.999999998); the combined PDM ranged from 0.999999997 to 0.999999999; and the combined MECD and MECT ranged from 0.999998065 to 0.999999993 and 0.999998732 to 0.999999998, respectively. The abovementioned forensic parameters perfectly illustrated that the 12 X-STRs had great application value in forensic identification and kinship analysis among Chinese populations.For a better understanding of the genetic structures of these 12 X-STRs in Chinese populations, we assembled data from five Chinese Han subpopulations and four ethnic minority groups from different areas of China Fig. . Detailest value is usually used for analyzing genetic distances between populations37, we calculated the pairwise Fst genetic distances , it often locates at the modal value of the distribution of ΔK; therefore, the most appropriate K was 2 43. Meanwhile, the Emirati males from the Arabian Peninsula of Western Asia also located in the lower left quadrant and could not be distinguished from the Europeans by the 12 X-STRs, which was consistent with the result of the STRUCTURE analysis in our study. This may due to the complex biogeography and history background of UAE. Among the cluster of Chinese populations, Hebei Han, Liaoning Han and Korean from Jilin shared a closer genetic distance, which supported the results observed from the phylogenetic tree. Additionally, the Mongolian population was located in the lower right corner, slightly far from other Chinese groups in terms of genetic relationship. Similar results were found in a study of Mongolian Y-STRs, and this probably reflects customs and territory restriction to some extent47. Our analysis indicated that the 12 X-STR loci had some advantages in distinguishing Mongolian males from others by the PCoA method.The genetic pattern of the male X chromosome inherited from the mother, normally referred to as the haplotype data set, makes the genetic distribution of X-STRs in males worth exploring. PCoA provides a way of visualizing the essential patterns of genetic relationships contained in a special matrix  and allows us to find and plot the major patterns within a multivariate data set. PCoA gives a reasonable assumption at a higher taxonomic level, compared to the algorithms that always assume a hierarchical genetic structure in Tree building methods. In this respect, PCoA is an effective complement to the evolutionary tree. Therefore, PCoA was carried out to test for significant variation in the genetic distribution of 12 X-STR markers among the males of abovementioned eleven populations in the STRUCTURE analyses. As shown in Fig. 49. On the one hand, there is a single copy of the X chromosome in males, it is possible to detect their haplotypes which are needed to infer the phylogeny of a region. The X/Y chromosome and mitochondrion are candidates for researches that use phylogenies, an advantage that explicates their dominant role in human historical studies52. On the other hand, recombination on women X chromosome also creates vast quantities of information that is vital for providing a complete view of the history of human populations. Although the bulk of human historical researches have been done with Y chromosome or mitochondrion, X chromosome has the advantage of existing in both genders and much lower rates of genetic drift50. The X-STR markers included in Argus X-12 kit are the most developed and widely used, there have been a great amount of 12 X-STRs data of different populations, by which we can conduct the analysis of population characteristics or geographical studies. Therefore, we conducted genetic analysis of Mongolian and Eastern Chinese Han populations based on 12 X-STR markers and achieved significant and prominent results that might be used in more precise substructure detection of Eastern Asian population and the estimation of individual biogeographical ancestry in further study.The Mongolian is a traditional nomadic nationality mainly distributed in Eastern Asia, it is one of the largest minority nationalities in China, and also the main nation of Mongolia. In addition, the Mongolians are also distributed in Asian and European countries such as Russia. The Mongolian nationality first originated from the eastern bank of the ancient Wangjian River. In the early thirteenth century, the Mongolian ministry, headed by Genghis Khan, unified the Mongolia region, and gradually formed a new national community. In the history of China and even in the world, the Mongolian people have had a profound influence and significant role in the economy, politics and culture. Besides, Eastern China is a densely populated area, the population there accounts for 29.3% of the total population of China, which has the most common characteristics of Chinese. Therefore, they are both very important and particular population groups in China, that’s why our study focused on them. Its particular genetic inheritance that makes the X chromosome valuable for human evolutionary and historical researchOur current study indicated that the Investigator Argus X-12 kit used in Mongolian and Eastern Chinese Han sample sets provided highly polymorphic data for discriminating individuals and testing kinship, which enriched the Chinese ethnic genetic information. The significant deviations from HWE observed at the DXS10134 locus in the Mongolian population could possibly be eliminated by increasing the sample size from geographically closed regions in Inner Mongolia. The genetic comparison among eleven Chinese populations demonstrated that the statistically significant genetic distances were consistent with the known situation of these national mixed, small-settled and staggered populations living in China. In addition, neighboring populations and different ethnic groups within the same area appeared to have closer evolutionary relationships in the phylogenetic tree. The STRUCTURE analyses revealed that the Mongolian and Eastern Chinese Han populations belonged to the same cluster as the other Chinese populations, but were apparently distinct from other global populations. The PCoA analysis indicated that the 12 X-STRs could not only be applied in distinguishing Chinese males and the males from the abovementioned countries, but also able to show a moderate genetic distance between Mongolian and the other Chinese male populations. To our best knowledge, this is the first report to demonstrate that the 12 X-STR markers could be useful in dealing with the genetic relationship between Mongolian males and others.However, for some populations, such as the Manchu and Miao with their large populations, or the Kazak with significant differences from other Chinese populations in other genetic markers, there are still no published data concerning the 12 X-STRs panel. Therefore, further studies should be focus on increasing the sample size of current ethnic groups and including more nationalities. Hopefully, our endeavor will help to establish an appropriate and integrated X-STR database that is suitable for the large population of China.Supplementary informationTable S1Table S2Table S3Table S4Table S5