Halyomorpha halys) was unveiled using the coupled approach of phylogeography and ecological niche modelling. Rangewide molecular data suggests that the Taiwan and other native populations had diverged in mid-Pleistocene. In mainland China, the native BMSB did not experience population contraction and divergence during last glacial, but persisted in interconnected populations. Combined Bayesian Skyline Plot (BSP) and niche modelling revealed a rapid expansion occurred during the transition of Last Inter Glacial (LIG) to Last Glacial Maximum (LGM). High genetic diversity and multi-reticular haplotypes network exist in the original sources populations of BMSB invasion in northern China. They were speculated to be colonized from the central China, with many derived haplotypes evolved to adapt the novel environment. The ENM future prediction suggest that BMSB may expand northward to higher latitudes in the US and Europe, because of its high invasive ability, together with the available suitable climate space there.Invasive species’ Pleistocene history contains much information on its present population structure, dispersability and adaptability. In this study, the Pleistocene history of a global invasive pest (Brown Marmorated Stink Bug BMSB,  Invasive species’ Pleistocene history contains much information on its present population structure, dispersability and adaptability4Biological invasions and climate change are considered to represent major threats to biodiversity, ecosystem functioning and agroforestry1Recently, ecological niche modelling (ENM) emerged as an important tool in the studies of biological invasion and phylogeography1213Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), native to East Asia, has become an invasive species in the US and EuropeThe Brown Marmorated Stink Bug (BMSB), In this study, we first test climate niche conservatism across BMSB geographic populations and monophyletic clades, we then linked phylogeography and paleoclimate niche modelling to derive information on BMSB population in late Pleistocene. Here we use rangewide mitochondrial markers coupling with nuclear data to investigate the phylogeographic structure of BMSB, and to explore its demographic changes in response to Pleistocene fluctuations using coalescent-based methods. With lessons from the past, we recalibrate the niche model for BMSB to assess its climatic favorable zone under future climate scenarios in the end. The aims of this study are to (1) reveal the phylogeographic structure of BMSB in East Asia, (2) to explore their demographic response to Pleistocene climatic fluctuations, and (3) to predict the effect of future climatic change on the potential distribution of BMSB.2443 bp of protein-coding regions in mitochondrial genome were obtained  from 234 specimen. 183 unique haplotypes were derived. The 275 polymorphic sites included 100 singleton variable sites and 175 parsimony informative sites. Nucleotide diversities for mtDNA ranged from 0.00018 to 0.00563 , with anBayesian inference (BI) analysis suggests that the native BMSB populations could be separated into two clades , clade IThe potential area for each ancestral node within three monophyletic clades was identified . Assignment of ancestral areas indicates that clade I was originated from Taiwan . The hapD, Fu and Li’s D and Fu’s FS, and the larger than expected number of singleton mutations , the historical population dynamics were visually displayed (Divergence time between Clade I (Taiwan) and Clade II  was estimated to be 0.79 million years (MY) ago (95% HPD: 0.36–1.00 MY ago), which appeared in the mid–Pleistocene . In the utations . We thenisplayed ; the demisplayed .Principle component analysis of five bioclimatic variables associated with BMSB occurrence revealed reduced dimensions that account for the observed distribution . The firX2 = 106.89; df = 1, p < 0.05), suggesting climate niche stability across geographic space. When projecting the current niche into historical climate conditions, a range-expanding trend was observed throughout the LIG , LGM , and Mid-Holocene (~6000 years ago) periods. In binary predictions, during the LIG period, the suitable climate space is distributed in central and southwestern China, and most parts of Japan and South Korea. When the ice age arrived (LGM period), the suitable space in Japan and southwestern China vanished, whereas the central space in China showed expansion toward both the north and south; an eastern expansion was also observed in the land bridges that connected China and Japan during the LGM. When ice retreated, the suitable space continued its northward expansion, occupying most of Japan and Korea, forming the current BMSB distribution in East Asia  and using larger nuclear dataset (e.g. SNP) to reveal genetic structure and demographic history in the global process of biological invasion.H. halys were approved by the Committee for Animal Experimentation of the College of Life Science at Nankai University (no. 2008) and were carried out in accordance with the approved guidelines. Tissue samples were obtained from a total of 234 individuals corresponding to 32 different populations across the native rangewide of BMSB in East Asia , number of haplotypes (Nhap), haplotype diversity (Hd), and nucleotide diversity (π), which were calculated in DNASP 4.0Genetic diversity was estimated for each location and entire sample as the number of polymorphic sites (Bayesian inference (BI) was used to construct the phylogenetic tree. Model test (version 3.7) was then used to choose the appropriate substitution model and TIM+I+G was selected as the best. The number of generations was 15 million, with tree sampled every 1000 generations until the average standard deviation of split frequencies was below 0.01; the first 25% of generations was discarded. Genealogical relationships between haplotypes were investigated by constructing a phylogenetic network using Median-Joining model implemented in Network 4.6.1.1 software (Fluxus Technology Ltd.). Haplotype network can be used to infer population history, as the most ancient haplotypes should be located at the center of gene tree and be geographically widespread, whereas the most recent haplotypes should be at the tips and be localized geographicallyr) can be used to quantify the smoothness of mismatch distributionr values are expected to be low and can be tested for deviation from the constant population model. In addition, three neutrality tests, i.e., Tajima’s DDFS in Arlequin 3.5D, Fu and Li’s D and Fu’s FS tests would be interpreted as signatures of historical population expansion.Mismatch distribution was used to explore the native demographic history of BMSB. Multimodal mismatch distributions are assumed to characterize old populations of constant size whereas expanding populations tend to be unimodalt = τ/2u ; the value u was calculated using the formula u = μk (μ is the mutation rate per nucleotide and k is the number of nucleotides assayed). Referring to the molecular evolution in assassin bug (Hemiptera: Reduviidae)We used two methods to estimate population expansion time based on COI sequence data. One approach is using Insects are poikilothermic organisms and all aspects of their biology depend on the effective temperature−5), maximum number of iterations (500)). To hindcasting the Pleistocene climate effect, we adopted the 95 occurrence records in Zhu et al.et al.Maximum entropy that implanted in MaxentThe choice of threshold used to derive binary predictions altered projections of species range under current, historical and future climate conditions because any fixed threshold to transform model output will mask the possibility prediction and exaggerate prediction errorsHow to cite this article: Zhu, G.-P. et al. Range wide molecular data and niche modeling revealed the Pleistocene history of a global invader . Sci. Rep.6, 23192; doi: 10.1038/srep23192 (2016).


Cycas multipinnata C.J. Chen & S.Y. Yang is a cycad endemic to the Red River drainage region that occurs under evergreen forest on steep limestone slopes in Southwest China and northern Vietnam. It is listed as endangered due to habitat loss and over-collecting for the ornamental plant trade, and only several populations remain. In this study, we assess the genetic variation, population structure, and phylogeography of C. multipinnata populations to help develop strategies for the conservation of the species. 60 individuals from six populations were used for chloroplast DNA (cpDNA) sequencing and 100 individuals from five populations were genotyped using 17 nuclear microsatellites. High genetic differentiation among populations was detected, suggesting that pollen or seed dispersal was restricted within populations. Two main genetic clusters were observed in both the cpDNA and microsatellite loci, corresponding to Yunnan China and northern Vietnam. These clusters indicated low levels of gene flow between the regions since their divergence in the late Pleistocene, which was inferred from both Bayesian and coalescent analysis. In addition, the result of a Bayesian skyline plot based on cpDNA portrayed a long history of constant population size followed by a decline in the last 50,000 years of C. multipinnata that was perhaps affected by the Quaternary glaciations, a finding that was also supported by the Garza-Williamson index calculated from the microsatellite data. The genetic consequences produced by climatic oscillations and anthropogenic disturbances are considered key pressures on C. multipinnata. To establish a conservation management plan, each population of C. multipinnata should be recognized as a Management Unit (MU). In situ and ex situ actions, such as controlling overexploitation and creating a germplasm bank with high genetic diversity, should be urgently implemented to preserve this species. The Cycad is considered an old lineage because of its ancient morphological characters and fossil records which could date to the Early Permian  or possiCycas, as the basal lineage of the living cycads supported by both phylogenetic studies and the recent obtained genome size of nuclear DNA [Cycas from other Cycads in morphology is its leaflets with an obvious midrib, lacking lateral veins. The leaf of Cycas is pinnate or rarely bipinnate, and Cycas multipinnata C.J. Chen & S.Y. Yang is one of the four species characterized by the latter [C. multipinnata is 2n = 2x = 22 [lear DNA –14, is te latter . The som 2x = 22 , and theCycas multipinnata distributes in the Red River drainage zone under an evergreen forest canopy on the sharp limestone slopes of southwest China (Yunnan Province) and northern Vietnam (Yen Bai and Tuyen Quang Province) [Cycas species occur in this small region, which ranges from the coast of Vietnam well into the interior of China along the Red River. Cycas multipinnata is one of the 17 Cycas species endemic to this area [C. multipinnata in both China and Vietnam declined dramatically in recent decades due to the anthropogenic disturbances, particularly habitat loss and over-exploitation for the ornamental plant trade. Cycas multipinnata was assessed as Endangered (EN) by the IUCN  Categories and Criteria system [rovince) ,18. The rovince) ,20. At lhis area . Howevera system ,22.Cycas is maternally inherited [C. multipinnata. Further, we discuss the causes of the genetic consequences, such as an environment with climatic oscillations or human impacts. These results show the urgency and significant implications of the management and recovery of this endangered species.Chloroplast DNA of nherited , so it iCycas multipinnata is the First Grade conservation plant in China [Cycas samples in the wild. The sampling process was under the guidance of local rangers. Our sampling will not affect the regular growth of C. multipinnata, and it was solely used for scientific research.in China . It was in China . We got C. multipinnata . All six populations were located north of the Red River. Of the 105 samples, 60 individuals from the six populations were used for chloroplast DNA sequencing. The population known as SZD was eliminated from SSR analysis because there were only five individuals in the population. A total of 100 individuals from five populations were used for the microsatellite study. Information on each sampling location and the number of individuals from each population that were used in DNA sequences and SSR analysis is presented in A total of 105 individual samples were collected from six populations of Healthy leaves were dried and preserved in silica gel immediately after being collected. Genomic DNA was extracted from the leaves, which was ground into a powder after being frozen with liquid nitrogen, following the cetyltrimethyl ammonium bromide (CTAB) method . The totatpB-rbcL, psbA-trnH and psbB-psbH were selected. The PCR amplifying conditions and primers of atpB-rbcL and psbA-trnH were identical to those described by Zhan [psbB-psbH fragment were as follows: psbB (F) 5′-TCCAAAAACTGGGAGATCCAAC-3′, psbH (R) 5′-TCAATGGTCTGTGTAGCCAT-3′ [Three cpDNA regions  by Zhan . The priGCCAT-3′ ; one cycPurified PCR productions were sequenced in both directions using the same primers for the amplification reactions, using an ABI 3730 automated sequencer at Shanghai Majorbio Bio-pharm Technology Co., Ltd.Cycas have been developed by several research groups. 17 variable microsatellite loci were selected from the published 65 microsatellite loci [Cycas to investigate the genetic diversity of C. multipinnata (Table A in Microsatellite primers of ite loci –34 that After being edited and jointed in the SeqMan of software package (DNA Star), sequences were aligned using Clustal X version 1.81 , and finhttp://www.pierroton.inra.fr/genetics/labo/Software/Permut) was used to calculate the within-population diversity (HS), the total diversity (HT) and two measures of population differentiation, GST and NST [DnaSP version 5.10  was used and NST . Arlequi and NST  was used and NST  to estimST/ (1-FST) [We calculated the genetic distance (GD) among the six populations following the formula GD = F (1-FST)  using Ar (1-FST) . Geograp (1-FST) . A Mante (1-FST) .http://www.fluxus-engineering.com/sharenet.htm) following the media-joining calculation [C. panzhihuaensis serving as the outgroup. BEAST version 1.7 [7 iterations with a burn-in of 106 under the HKY (Hasegawa-Kishino-Yano) nucleotide substitution model, which was determined to be the most suitable model by Modeltest in Mega 6.06 [-9 substitution per site per year [The genealogical haplotype network was constructed using Network version 4.6.1.2  could indicate the presence of population structure or inbreeding [The dataset was edited and transformed to other formats in GenAlEx version 6.4.1 . We testbreeding . HWE wasbreeding . Linkagebreeding .T), the number of private alleles (AP), the mean number of alleles (NA), the effective number of alleles (NE), the observed heterozygosity (HO), the expected heterozygosity (HE), the information index (I), the fixation index (F) and the percentage of polymorphic loci (PPB) were calculated using GenAlEx version 6.4.1 [ST and tested with GenAlEx version 6.4.1. Allelic richness (AR) was estimated with FSTAT, version 2.9.3) was estimated with FSTAT, version 2.9.3 [The indices of genetic diversity within populations, such as the number of alleles (Non 6.4.1 . Differeon 2.9.3 .Nm = (1-FST)/4 FST.As in the analysis of cpDNA, genetic distance (GD) and geography distance (GGD) among the five populations was calculated using the Arlequin version 3.11  and GenAK = 1~8) was estimated by the Markov chain Monte Carlo (MCMC) method with 10 separate runs to evaluate the consistency of the results. Each run was estimated as 100,000 steps, with a 100,000-step burn-in. The best fit number of grouping [K in the STRUCTURE HARVESTER v. 0.6.93 tool [An individual-based principal coordinate analysis (PCO) was conducted in the MVSP version 3.12 software  using thgrouping  was eval.93 tool . Finally.93 tool , based oM = (k/r), where k is the number of alleles and r is the allelic range . This measure is based on the assumption that in a bottleneck event, the number of alleles decreases faster than the allelic range because the latter is only reduced if the shortest and/or longest allele is lost, whereas the loss of any allele reduces the former. The Garza and Williamson found critical values for M < 0.68, which indicated a bottleneck, and M > 0.80, which indicated no reduction of effective population size.A heterozygosity excess test at the population level from BOTTLENECK 1.2.02 was used to detect the recent population bottleneck . The comEffective population sizes (Ne) are among the most important parameters in wildlife management and conservation because they can inform management and help predict the extinction risk of populations. We estimated effective population sizes (Ne) using the linkage disequilibrium (LD) method in LDNe  at threeatpB-rbcL (delete the poly T), psbA-trnH and psbB-psbH, are 719, 597 and 644 bp in length, respectively (GenBank accession numbers: KP335666—KP335683). The partition-homogeneity test indicated that data sets of these cpDNA fragments are significantly congruent (P = 1). The 1960 bp combined cpDNA data set had 14 parsimony-informative polymorphic sites and 8 haplotypes (H1–H8) (Table B in d) is 0.7718, and the nucleotide diversity per site (π) is 0.00149. The total diversity (HT) is 0.896, and the within-population diversity (HS) is 0.225.The three cpDNA fragments, ST = 0.749 and an NST = 0.922, and the permutation test showed that GST and NST were not significantly different from each other . The results of the AMOVA analysis indicated that 92.3% variation occurs among the populations , Fu and Li’s D* 1.16049, Fu and Li’s F* 2.09321 (P < 0.01), Fu’ Fs 5.672, Tajima’s D and Fu and Li’s F* were all positive values. According to the variation pattern in cpDNA, the Bayesian skyline plot was reconstructed. It showed that the demographic scenario for population of C. multipinnata was a long history of constant population size, followed by a decline over the last 50,000 years with no subsequent expansion  of each population varied from 71 (HY) to 88 (GLJ) (P) than that in the three populations in China (A) and the effective number of alleles (NE) for each population ranged from 4.176 to 5.176 and 2.314 to 3.197, respectively (E) were 0.367 to 0.410 and 0.449 to 0.551, respectively (All 17 microsatellite loci were polymorphic in 88 (GLJ) . The twoin China . The meaectively . The obsectively . The perectively .ST across all loci and populations was 0.29569 (P < 0.0001), and the FST values for each population  ranged from 0.29386 to 0.29761. The Mantel test  in the Bayesian clustering analysis, when using the 17 microsatellite loci  except for the YB population (P < 0.01) . The allHowever, the Garza-Williamson indices  were lowThe effective population sizes (Ne) calculated using the linkage disequilibrium (LD) method with LDNe at the three lowest allele frequency levels with a 95% confidence interval are shown in C. multipinnata. The AMOVA analysis revealed that the variation partition of the three cpDNA intergenic spacers is 92.3% variation among populations and 7.7% within populations, whereas the 17 microsatellite loci indicated that 70.43% genetic variation occurs within populations and 29.57% among populations  is sus sites ,50), andus sites . The twoC. multipinnata is moderate in cpDNA sequence. It is higher than that of C. debaoensis  [C. revoluta  and C. taitungensis  [C. simplicipinna, a unique cpDNA haplotype was detected in all seven populations from both China and Laos [d = 0.864) and the total diversity (HT = 1.000) is higher than C. multipinnata, whereas the within-population diversity (HS = 0.076) is lower. The genetic variation within populations for C. multipinnata, C. debaoensis, and C. simplicipinna is low.Generally speaking, the genetic diversity of 0.00132)  but much 0.0181) . For C. and Laos , so the C. multipinnata, H2 is the predominant chloroplast haplotype among the eight haplotypes detected in the 60 individuals from six populations. The other five haplotypes in the four populations  in China with short branches to H2 represent recently evolved haplotypes. A unique cpDNA haplotype is detected in each of the two Vietnamese populations. The cpDNA genetic diversity in China tends to be higher than that in Vietnam because there are more populations of C. multipinnata in Yunnan, China, and greater gene flow among them.In the cpDNA analysis of Cycas multipinnata was characterized by isolation by distance (IBD), i.e., a significant positive correlation (P < 0.05) was detected between genetic distance (GD) and geographic distance (GGD), which was addressed by the accordant results of the Mantel test based on the cpDNA and SSR data.C. multipinnata plants are pollinated by insects, primarily by beetles [C. multipinnata has a high genetic differentiation  according to the Wright’s criterion [ST value greater than 0.25 would indicate that there is significant genetic differentiation among populations. Moreover, high genetic differentiation has been detected in many cycads, such as C. debaoensis  [C. simplicipinna  [Cycas species above, C. revoluta and C. taitungensis, which are coastal or island distributed, possess high genetic variation and low genetic differentiation between populations [Cycas species occurring inland and on islands. In detail, during the glacial period, migration corridors across islands may have formed that enhanced the gene flow, whereas on land, the environmental niche of Cycas plants became restricted to isolated refuges, resulting in limited gene flow. Another reason may be that different Cycas species have different lengths of evolution history; for example, the most recent common ancestor (TMRCA) of C. revolute and C. taitungensisis is estimated at 327.3 MYA in mtDNA and 204.0 MYA in cpDNA [C. revoluta and C. taitungensis experienced more complex in-range expansion and contraction fluctuations in population size.As with most Cycads, the dioecious  beetles . Seeds d beetles . The curriterion , which abA-trnH)  and C. ste loci) . In contulations . One posin cpDNA . In a loC. multipinnata can be divided into two groups: one included the populations  distributed in China and the other included the two populations (HY and YB) that occurred in northern Vietnam. The same result was obtained from three different analyses of the 17 microsatellite loci. First, in the principal coordinate analyses (PCO), 100 individuals from the five populations  were spilt into two parts: one included the three populations  in China, and the other contained the remaining two populations in Vietnam. Second, in the Bayesian clustering analysis using the STRUCTURE version 2.3 software, it was strongly recommended that the five populations should be divided into the same two groups suggested in the PCO analysis. Finally, the BARRIER analysis also showed that only one barrier existed between the populations in China and Vietnam. Overall, these analysis based on two different markers reached the same conclusion: C. multipinnata has a distinct structure, and it contains the China clade and Vietnam clade. The date of the most recent common ancestor (TMRCA) between the clades, based on the cpDNA data is approximately 1.0307 million years ago (MYA) i.e., during the Pleistocene.The genealogical haplotype network and topology of the Bayesian tree based on the data of the combined cpDNA sequences showed that C. multipinnata population size experienced a significant reduction approximately 50,000 years ago  due to overexploitation and habitat destruction. Population size is the most important factor among the five criteria to identify threatened species in IUCN [There are only six small and fragmented populations of  in IUCN . It is b in IUCN . When 0.In situ conservation is one important measure to take because the entire gene pools are preserved in their native habitat. Considering the limitation of the wild C. multipinnata resource and the apportionment of genetic diversity, we should regard all six populations as Management Units (MUs). In addition to public education and legal constraints to curtail overexploitation and habitat destruction, a long-term recovery of C. multipinnata package should be launched with the active participation of local people.Ex situ conservation is an insurance policy that can be carried out with living plants cultivated in nature reserves or botanic gardens. Because Cycas could propagate via vegetative techniques [C. multipinnata from as many populations as possible to increase the genetic diversity.chniques , the gerex situ and in situ conservation of C. multipinnata, we should increase the genetic diversity of the plant material during forest management. Of course, scientific research on C. multipinnata’s environment and pollination biology should also be carried out in time.Considering the main impact due to the population contraction is the low genetic variation and low gene flow between populations for both the C. multipinnata took place approximately 1.0307 MYA, namely in the Pleistocene. The reconstruction of the population demographic history of C. multipinnata indicates that over the last 50,000 years, this species underwent a population contraction, with no subsequent expansion. The severe climate oscillation during the Pleistocene is a factor that contributed to the currently isolated geographical distribution of C. multipinnata. Our study revealed that the extant C. multipinnata displays low genetic diversity within populations and high genetic differentiation among populations in cpDNA sequence. Overall, the pattern of genetic variation within and among populations in C. multipinnata was related to the geographic distance. Practical measures should be launched immediately to protect the Endangered C. multipinnata.The historical divergence between the main genetic clusters of S1 FileTable A. Information of 17 microsatellite loci used to study the population genetics. Table B. Variable sites from the three cpDNA combined sequence in Cycas multipinnata. Table C. P-value of Hardy-Weinberg equilibrium test for the five populations of C. multipinnata.(DOCX)Click here for additional data file.S2 FileThe boundaries detected using the BARRIER program based on matrices of Nei’s (1983) unbiased genetic distance.(DOCX)Click here for additional data file.


Mustelus henlei (Triakidae). Data from the mitochondrial control region and six nuclear microsatellite loci revealed significant population structure among three populations: northern (San Francisco), central , and southern (Costa Rica). Patterns of long-term and contemporary migration were incongruent, with long-term migration being asymmetric and occurring in a north to south direction and a lack of significant contemporary migration observed between localities with the exception of Punta Lobos that contributed migrants to all localities within the central population. Our findings indicate that Point Conception may be restricting gene flow between the northern and central populations whereas barriers to gene flow within the central population would seem to be ineffective; additionally, a contemporary expansion of tropical M. henlei into subtropical and temperate waters may have been observed.We assessed the effects of the prominent biogeographic  and phylogeographic barriers (Los Angeles Region) of the northeastern Pacific on the population connectivity of the brown smoothhound shark,  Galeorhinus galeus, straddling the Equator, hypothesizing that the species affinity for cool temperate waters limits its ability to cross-warm equatorial waters.Biogeographic and phylogeographic barriers are known to disrupt population connectivity and are produced by currents, changes in sea surface temperature (SST), physical barriers, upwelling, and resource availability Palumbi . The easMustelus henlei  (Triakidae)   Yudin . During Compagno . HoweverM. henlei as well as to elucidate contemporary gene flow within the distribution of the species. The matrilineally transmitted, noncoding, mitochondrial control region (mtCR) is considered a selectively neutral marker that lacks recombination and mutates at a relatively high rate, making it effective for detecting historic or evolutionary structure among populations  and mitochondrial (control region) genetic markers were used to reconstruct the phylogeographic history of ns Avise . Due to ns Avise . The purM. henlei were collected from throughout the species' distribution by trawling, beach seine, and gill netting. An adult M. henlei from 2012 was deposited at the Scripps Institute of Oceanography as a voucher specimen (SIO 13–25). In total, 169 tissue samples were collected from six geographic locations: 31 from San Francisco Bay, CA , 34 from Santa Barbara, CA , 30 from Santa Catalina Island, CA , 30 from Punta Lobos, Baja California Sur, Mexico , 12 from the Upper Gulf of California (G.O.C.) at San Felipe, Baja California, Mexico  and 32 from Costa Rica . Fin clips (1 cm2) were taken from the first dorsal fin, placed in 95% ethanol, and stored at −20°C at UCLA for long-term storage until DNA could be extracted. DNA was extracted using the DNeasy Blood and Tissue Kit  following the manufacturer's protocols.Adult specimens of both male and female M. henlei: MhenFSeqPrimer 5′- TGC TAC GAC GCG CAA AAG CC and MhenRSeqPrimer 5′-CGT CGG CCC TCG TTT TAG GGG. Sequencing reactions were performed in an Applied Biosystems GeneAmp 9700 thermocycler (Life Technologies) for 35 cycles of 90°C for 10 sec, 50°C for 10 sec, and 60°C for 4 min, followed by direct sequencing in an Applied Biosystems 3130X Genetic Analyzer (Life Technologies). Sequencing products were validated by eye in GENEIOUS PRO 5.1.4  and aligned using CLUSTALW , mean nucleotide diversity (π), mean pairwise difference, and the population mutation parameter θs . Effective female population size, Nef, was estimated for each sample locality and based on the equation θs = 2Nefu . The mutation rate, μ, of 0.0067 sequence divergence per million years based on lemon sharks, Negaprion  . Pairwise estimates of ΦST were generated for all pairs of sample localities in GENALEX, and significance was tested via permutation. Significance was adjusted to correct for multiple tests using the sequential Bonferroni correction of Rice (M (where M = m/μ and m is the migration rate per generation and μ is the mutation rate). For the MIGRATE-N analysis, an initial analysis under the default parameters was used to estimate θ for all populations as well as migration rates for all population pairwise comparisons. Following this, two subsequent runs with different starting seeds using these estimates as priors were performed and averaged to generate θ and M. A median-joining network of haplotypes was constructed in NETWORK 4.6.1  to visualize haplotype clustering and diversity. Following the generation of an initial median-joining network, the MP option   are indicative of populations not in equilibrium due possibly to a recent range expansion or recovery from a population bottleneck  indicating an excess of novel haplotypes and a departure from equilibrium (Fu τ) values, the amount of mutational time in which all lineages within a sample coalesce, derived from mismatch distributions   Tajima , 1996. Ubrium Fu . Populati Cortes .M. henlei from all sample localities following the procedures of Chabot (O), and expected heterozygosity (HE) were estimated in GENEPOP 4.0 (Raymond and Rousset R).Six nuclear microsatellite loci from Chabot   was estimated with five independent runs of K = 1–10, each was performed with 106 MCMC repetitions and a burn-in of 105 steps under the admixture model with correlated allele frequencies. The optimal number of subpopulations was estimated using ΔK of Evanno et al.  due to bottlenecks, observed heterozygosity at neutral loci is generally greater than that expected by the number of alleles. To detect recent declines in Ne within populations of M. henlei, BOTTLENECK 1.2.02 , and Δg (average size of non-single-step mutations) were obtained from MIGRATE-N (θ) and Garza and Williamson (Ps = 0.88 and Δg = 2.8). Prebottleneck values of θ for CRITICAL_M were estimated from equilibrium heterozygosities (He)  Table and the lliamson  for Ps =M. henlei consisting of 16 transitions, 11 transversions, and a single insertion/deletion defining 27 haplotypes (GenBank Accession Numbers KC208467–KC208482 and KJ530691–KJ530703). Of the 27 haplotypes, 20 were unique to their sample locality . Of the remaining seven haplotypes, SB15 was observed in all localities (excluding Costa Rica) with frequencies ranging from 0.39 to 0.95; SB11, SB14, and PL18 were observed at Santa Barbara, Punta Lobos, and San Felipe, and SB19 was observed at Santa Barbara and Punta Lobos. Although the Costa Rica sample was composed almost entirely of unique haplotypes, haplotype SB14 was observed at this locality as well. Of the sampled localities, only Santa Catalina lacked any unique haplotypes and was dominated by haplotypes SB15 (0.95) and SB23 (0.05).PCR and sequencing were attempted for all 169 samples; however, of these samples, 126 yielded high-quality control region sequences of approximately 700 bp that were used for this study. Within all localities (excluding San Felipe), a minimum of at least 20 individuals were amplified successfully and sequenced. Nucleotide composition of control region sequences was as follows: cytosine, 19.00%, thymine, 35.84%, adenine, 30.14%, and guanine, 15.01%. Overall, 28 polymorphic sites were observed in control region sequences of M. henlei ranged between 0.10% and 0.60% (TableP < 0.00001) of the variation being observed among sampled localities  between all other localities  when all sample localities were analyzed together. When Costa Rica was excluded from the analysis, nonsignificant isolation by distance (P = 0.451) was observed. The median-joining network demonstrated a general lack of divergence among localities with many of the haplotypes diverging from the most frequently observed haplotype, SB15, by a single mutation  being observed in all but Costa Rica   Table. Results02) Table. Tau val02) Table.O) ranged between 0.40 and 0.54 and expected heterozygosities (HE) were between 0.40 and 0.56   when all sample localities were analyzed together. However, when Costa Rica was excluded from the analysis, significant, yet reduced isolation by distance was observed.  Long-term estimates of gene flow among population pairs were asymmetric with the predominant direction of gene flow being in a north–south direction  Table. Signifiove Table. Signifition Fig.. Interestion Fig.. Overalltion Fig.. Howevertion Fig.. Of notetion Fig. and 95% tion Fig. from PunM. henlei , and the California halibut, Paralichthys californicus, from the northeastern Pacific with distributions spanning the LAR and Point Conception have revealed similar patterns of gene flow across Point Conception but contrasting patterns across the LAR. Craig et al.  and the LAR. Based on these observations, Lewallen et al.  and leopard sharks have been observed among aggregations of M. henlei . Instead, our data show that the northern population of San Francisco is significantly differentiated from the central population. Hence, unlike P. californicus and T. semifasciata, Point Conception may be acting as a barrier to dispersal in M. henlei. In regards to the LAR, patterns of population connectivity throughout this area among localities of M. henlei , this finding is not surprising based on a tagging study of M. henlei in which an individual traveled a maximum distance of ∼150 km over a three-month period  due to lowered sea levels and shallower coastal basins. However, as sea level began to rise and coastal basins became deeper, population connectivity may have been reduced resulting in the more recent expansion estimate for Santa Catalina in the early to mid-Pleistocene and the observation of relatively low mitochondrial diversity . Deep-water basins have been shown to be effective barriers to population connectivity among the northern Channel Islands Bernardi  and in tM. henlei in South America. As populations of M. henlei are known from Peru and Ecuador , by artisanal and recreational fisheries for consumption, and by the aquarium trade  . Currently, the IUCN Red List has listed M. henlei with the threat category Least Concern due to the observed lack of overfishing of the species, its fast growth-rate coupled with a relatively low longevity, an early age at first maturity with a relatively high fecundity, and a lack of evidence of catch declines (Pérez-Jimenéz and Carlisle Nef) for M. henlei observed in this study were all relatively high ranging from ∼13,000 to 180,000  and Punta Lobos  would be expected to genetically buffer M. henlei from short-term population declines of small effect.As a family, the Triakidae has been the subject of global exploitation for greater than 80 years with members being exploited by commercial fisheries for their large vitamin-A-rich livers  and southern (Costa Rica) populations demonstrating significant divergence from the central population . Second, traditional biogeographic and phylogeographic barriers within the central population appear to have little effect on the population connectivity of M. henlei. And third, contemporary expansion of M. henlei from the tropics to subtropical and temperate regions may have been revealed. As always, further sampling from different localities would be expected to bolster the results of any population genetic study of a species in the wild. With this in mind, the further sampling of M. henlei from Washington, Humboldt Bay, CA, Tomales Bay, CA, Morro Bay, CA, Peru, and Ecuador would seem appropriate in order to elucidate patterns of gene flow among localities within the northern and southern limits of the species’ range. Finally, when these findings are integrated with those of other nearshore, northeastern Pacific taxa, the effect of biogeographic and phylogeographic barriers on population connectivity within the region will be made far clearer and our ability to predict and manage marine resources will be greatly improved.As this study is the first range-wide investigation into the gene flow and population connectivity of a member of the northeastern Pacific


ФST = 0.159, rst = 0.392, P > 0.001; Analysis of molecular variance [AMOVA]). We identified from c. 5% to 10% cryptic hybrids in southern and central European populations. In contrast, wild‐living cats in Hungary and Scotland showed deep signatures of genetic admixture and introgression with domestic cats. The European wildcats are subdivided into five main genetic clusters  corresponding to five biogeographic groups, respectively, distributed in the Iberian Peninsula, central Europe, central Germany, Italian Peninsula and the island of Sicily, and in north‐eastern Italy and northern Balkan regions (Dinaric Alps). Approximate Bayesian Computation simulations supported late Pleistocene–early Holocene population splittings (from c. 60 k to 10 k years ago), contemporary to the last Ice Age climatic changes. These results provide evidences for wildcat Mediterranean refuges in southwestern Europe, but the evolution history of eastern wildcat populations remains to be clarified. Historical genetic subdivisions suggest conservation strategies aimed at enhancing gene flow through the restoration of ecological corridors within each biogeographic units. Concomitantly, the risk of hybridization with free‐ranging domestic cats along corridor edges should be carefully monitored.Extant populations of the European wildcat are fragmented across the continent, the likely consequence of recent extirpations due to habitat loss and over‐hunting. However, their underlying phylogeographic history has never been reconstructed. For testing the hypothesis that the European wildcat survived the Ice Age fragmented in Mediterranean refuges, we assayed the genetic variation at 31 microsatellites in 668 presumptive European wildcats sampled in 15 European countries. Moreover, to evaluate the extent of subspecies/population divergence and identify eventual wild × domestic cat hybrids, we genotyped 26 African wildcats from Sardinia and North Africa and 294 random‐bred domestic cats. Results of multivariate analyses and Bayesian clustering confirmed that the European wild and the domestic cats (plus the African wildcats) belong to two well‐differentiated clusters (average  Past climate changes, historical evolutionary events and, eventually, more recent anthropogenic pressures shaped the partition of genetic diversity within and among populations Hewitt . MammaliFelis silvestris) comprises a number of poorly described subspecies that inhabit the entire Old World , distributed from Portugal to Romania; the African wildcat , in the Mediterranean islands of Sardinia, Corsica and Crete; and the domestic cat (F. s. catus). According to archeological remains, the European wildcat appeared in the continent around 450,000–200,000 years ago, but its fossil record was limited to the three southern Mediterranean peninsulas during the last glaciations  estimate the extent of genetic diversity within and between wild and domestic cat populations; (2) evaluate the patterns of population structuring and fragmentation in European wildcats; (3) identify genetic signatures of demographic fluctuations; and (4) obtain estimates of population divergence times. The evaluation of the genetic consequences of historical and recent fragmentations is helpful to define European wildcat conservation units and forecast their conservation perspectives.Fsi), domestic cats (Fca), and African wildcats (Fli) were opportunistically collected over a 12 year period  or in Longmire et al.  Tris/SDSP‐value corresponding to Δ = 0.05 after Bonferroni correction , observed (HO), and expected heterozygosity (HE); (2) test for deviations from Hardy–Weinberg equilibrium (HWE), with a Markov Chain length of 105 and 3000 dememorization steps; (3) test for pairwise linkage disequilibrium (LD), with 100 initial conditions followed by 16,000 permutations, for all locus–population combinations, based on Guo and Thompson's  was estimated following a rarefaction method that compensates for uneven sample sizes . Genetic diversity within each of the five European wildcats clusters identified by Bayesian structure analyses (see below) and also evaluated. We used Arlequin 3.5.1.2  over their range in fragment sizes (r), which is predicted to decline in a bottleneck because the number of alleles should decrease faster than the range in fragment sizes. The significance of m was determined by comparison with critical values (Mc), calculated from hypothetical populations in mutation‐drift equilibrium using the program Critical_M with 10,000 simulation replicates. We used a microsatellite “two‐phase mutation model” with an average size of multistep mutations Δg = 3.5, assuming 90% stepwise mutations (Ps), as recommended by Garza and Williamson  to evaluate the sensitivity of the method to this parameter.We tested for very recent bottlenecks (up to the first 10th generations ago) using the “heterozygote excess” and the “mode‐shift” procedure . We aimed to: (1) infer the number K of a‐priori unknown genetic clusters in the sample; (2) estimate the average proportion of membership (Qi) of the sampled populations to each cluster; and (3) assign each multilocus genotype to one or more cluster, according to their posterior individual probability of membership (qi). Based on previously published admixture analyses of observed and simulated cat datasets .Population genetic clusters were estimated using Structure 2.3.4 : European wildcats versus domestic cats, and African wildcats versus domestic cats. The analyses were replicated within each of the five European wildcat biogeographic clusters to overcome a possible bias due to within‐subspecies population structuring. Cats’ ancestry was computed using K = 2 with prior population information (option usepopinfo activated) for the domestic and wildcats that were genetically preidentified in the first runs of Structure. We subsequently excluded all the hybrids and the admixed cats from Scotland and Hungary. Then, we used a hierarchical approach to determine the divergence among the three cat subspecies and the five European wildcat clusters, assuming K from 1 to 15. We also explored the patterns of differentiation among cat subspecies and European wildcat clusters  by Discriminant Analysis of Principal Components (DAPC) in the Adegenet package  or during the Holocene , we used popABC (REF). Three alternative population histories  were modeled in each of the following datasets: (I) three population groups that could have originated during colonization–fragmentation events in central Europe, that is wildcats sampled from central European regions , central Germany, and north‐eastern Alpine–Dinaric regions; (II) three population groups that could have originated in Pleistocene Mediterranean refuges: wildcats from the Iberian peninsula , peninsular Italy (excluding Sicily), and north‐eastern Alpine–Dinaric regions ; (III) isolation in Sicily, comparing samples from peninsular Italy and Sicily. All simulations were modeled using the STR generalized stepwise mutation model (Goldstein and Pollock R using scripts developed by M. Beaumont (http://code.google.com/p/popabc/model_choice.r) and modified to fit our analyses. We also used the (δμ)2 genetic distance 2 = 2μT  and μ = 2.05 × 10−4 , 26 African wildcats (Fli), 294 domestic cats (Fca), and 136 admixed cats from Hungary (n = 98), Scotland (n = 21), and Italy . The mean values of heterozygosity were not significantly different among the three cat subspecies , 0.19 (Fsi), and 0.13 , suggesting the pooling of samples from genetically distinct populations within the same subspecies. The number of significant pairwise correlations between loci (testing for departure from LE) was zero in Fli, three in Fca, and 81 in the total Fsi sample, but much smaller in the five genetic clusters  confirmed the deep domestic x wild admixture in Scottish and Hungarian cats  with average QFca = 0.968 and QFli = 0.920, respectively, clearly different from all the European wildcats, which were assigned to cluster II (the Fsi cluster) with membership values > 0.920 , while wildcats from Germany showed the highest . In contrast, cat genotypes from Scotland and Hungary were admixed showing intermediate values of QFsi = 0.515 and 0.405, respectively  plotted into two distinct clusters in a DAPC computed using the entire sample set Fig. A, with tK = 1 to 15, popinfo = 0, “F” or “I” models, admixed genotypes excluded) revealed the presence of 5–6 main clusters  showing that: (1) at K = 2, European wildcats sampled in central Europe  clustered separately from all the other samples; (2) at K = 3, the samples from central Germany and from south‐western Germany  were assigned to distinct clusters; (3) at K = 4, the samples from the Italian north‐eastern Alps and Slovenia were assigned to the same distinct cluster; (4) at K = 5, the samples from the Iberian and the Italian peninsulas were split into two distinct clusters; (5) at K = 6, the samples from Belgium, Luxembourg, and Switzerland joined their own cluster  showed persistent signals of admixture with different population clusters. Thus, the most stable pattern of population structuring supported a partition of the European wildcats into five main biogeographic clusters: Fsi‐1 (eastern and Dinaric Alps) Fsi‐2 , Fsi‐3 , Fsi‐4 , and Fsi‐5 (Iberian Peninsula). Because of the low sample size in some regions, we did not explore evidences of further substructure, although Structure results suggest that local populations could be genetically subdivided at smaller geographical scale. For instance, the European wildcats from Sicily were assigned to a distinct cluster in 1 of 4 replicates at K = 6 , in 2 of 4 replicates at K = 8, and at 3 of 4 replicates at K ≥ 9. We observed the same subdivision in five population clusters in nonmodel DAPC, computed excluding the admixed cats, which showed that (1) the three cat subspecies are genetically differentiated  and among the five European wildcats biogeographic groups . A substantial proportion of genetic variation was attributed to mutations (as measured by RST) especially when comparing the three cat subspecies: the rst/fst ratio was = 5.8 among subspecies, and 1.3 among the European wildcat biogeographic groups. Divergence between African wildcats and domestic cats  was smaller than between African and European wildcats , in comparison with the other European wildcat groups. There were no significant differences in genetic diversity among the remaining European wildcat populations , suggesting population substructuring. However, the number of loci out of HWE within the clusters was smaller than in the pooled European wildcat sample, supporting the population substructure 2 calibrated by mutation rates μ = 5.6 × 10−4 or μ = 2.05 × 10−4 were roughly in agreement with the ABC estimates  among the five population clusters, estimated using the popABC procedure, are shown in Table Sound conservation plans should be based on robust knowledge of species’ biology, distributions, population genetic structure, and dynamics, which are still missing for the European wildcat. We planned this study to reconstruct a first framework of European wildcat phylogeographic structure, aiming at delimiting evolutionary and management units for conservation planning. We hypothesized that the extant patterns of genetic structuring of European wildcat populations distributed in the central and south‐western regions of the continents should have been mainly determined by late Pleistocene climatic changes rather than by recent anthropogenic habitat fragmentation. Our results support this hypothesis.c. 5% to 10% putative hybrid individuals in the Iberian and Italian peninsulas and Germany.The studied populations of European wildcat are geographically structured and present relative high levels of genetic diversity. Model‐based structure analyses and nonmodel multivariate clustering concordantly indicate that the sampled European wildcat populations are subdivided into five main genetic clusters showing congruent geographical distributions. Results of ABC simulations and calibrated genetic distances suggest that the main phylogeographic splittings among European wildcat populations were the consequences of late Pleistocene events, and not of very recent anthropogenic fragmentation. However, recent fragmentations could have eroded the within‐cluster genetic diversity, leaving signatures of bottlenecks in all clusters except the European wildcats samples in Iberia. We identified wild × domestic cat hybrids across the entire distribution in Europe. However, hybrid prevalence and introgression depth vary severely among the different countries (indicate range). Wild‐living cats in Scotland and Hungary are deeply introgressed, making difficult the identification of pure parental cats, as previously described using smaller STR panels and cat sample sizes , wolf (Canis lupus), red deer (Cervus elaphus), roe deer (Capreolus capreolus), wild boar (Sus scrofa), chamois (Rupicapra rupicapra), and in wildcats (Felis silvestris)  were mixtures of individuals sampled from genetically distinct natural populations .Table S3. Values of the mean Ln posterior probability (Mean lnPD) and maximum lnPD increase (ΔK) computed by structure analyses  assuming a number of K clusters variable from 1 to 15, and using: A) three cat subspecies, two introgressed populations sampled in Hungary and Scotland, and putative admixed cats identified in other populations in Europe; and B) only European wild cat samples excluding the two introgressed populations and the 78 putative admixed genotypes identified in A).Table S4. Average proportion membership (Qi) of wildcat populations obtained by structure with K = 2, the admixture and the I and F models, using the three cat subspecies and all the sampled European wildcat populations.Table S5. Average proportion of membership of European wildcat geographical population samples, as determined by structure with K values from 2 to 6 .Click here for additional data file.Figure S1. Plot of delta K and mean likelihood L(K) as a function of K averaged over five independent runs of structure run with the ‘admixture and the F model’.Click here for additional data file.Figure S2. Evidence of a distinct European wildcat population in Sicily identified by structure with K > 6.Click here for additional data file.Figure S3. Demographic histories assumed to estimate divergence times among European wildcat population clusters. Divergence time  is reported on the left, ranging from present (T0) to the ancestral population splitting time (T1 and T2).Click here for additional data file.


AbstractBactroceracarambolae, is an invasive pest in Southeast Asia. It has been introduced into areas in South America such as Suriname and Brazil. Bactroceracarambolae belongs to the Bactroceradorsalis species complex, and seems to be separated from Bactroceradorsalis based on morphological and multilocus phylogenetic studies. Even though the Carambola fruit fly is an important quarantine species and has an impact on international trade, knowledge of the molecular ecology of Bactroceracarambolae, concerning species status and pest management aspects, is lacking. Seven populations sampled from the known geographical areas of Bactroceracarambolae including Southeast Asia  and South America , were genotyped using eight microsatellite DNA markers. Genetic variation, genetic structure, and genetic network among populations illustrated that the Suriname samples were genetically differentiated from Southeast Asian populations. The genetic network revealed that samples from West Sumatra  and Java  were presumably the source populations of Bactroceracarambolae in Suriname, which was congruent with human migration records between the two continents. Additionally, three populations of Bactroceradorsalis were included to better understand the species boundary. The genetic structure between the two species was significantly separated and approximately 11% of total individuals were detected as admixed (0.100 ≤ Q ≤ 0.900). The genetic network showed connections PageBreakbetween Bactroceracarambolae and Bactroceradorsalis groups throughout Depok (DP), JK, and Nakhon Sri Thammarat (NT) populations. These data supported the hypothesis that the reproductive isolation between the two species may be leaky. Although the morphology and monophyly of nuclear and mitochondrial DNA sequences in previous studies showed discrete entities, the hypothesis of semipermeable boundaries may not be rejected. Alleles at microsatellite loci could be introgressed rather than other nuclear and mitochondrial DNA. Bactroceracarambolae may be an incipient rather than a distinct species of Bactroceradorsalis. Regarding the pest management aspect, the genetic sexing Salaya5 strain (SY5) was included for comparison with wild populations. The SY5 strain was genetically assigned to the Bactroceracarambolae cluster. Likewise, the genetic network showed that the strain shared greatest genetic similarity to JK, suggesting that SY5 did not divert away from its original genetic makeup. Under laboratory conditions, at least 12 generations apart, selection did not strongly affect genetic compatibility between the strain and wild populations. This knowledge further confirms the potential utilization of the Salaya5 strain in regional programs of area-wide integrated pest management using SIT.The Carambola fruit fly,  Bactroceracarambolae Drew & Hancock, the Carambola fruit fly, is a key insect pest belonging to the Bactroceradorsalis species complex . Its native distribution covers the western part of the Indo-Australian Archipelago , including the Thai/Malay Peninsula and Western Indonesia ; in 1993 in Orealla, Guyana, at the border of Suriname (approximately 220 km from Paramaribo); and in 1996 in the Brazilian city of Oiapoque at the border with French Guyana (about 500 km from Paramaribo)   , 2013. Iamaribo) . Currentamaribo) , 2013. Bapefruit . Howeverhylogeny , compari(Hendel) .Bactroceradorsalis species complex, Bactroceracarambolae is still valid, even though a few members  of the complex were recently synonymized with Bactroceradorsalis , or Ceratitiscapitata (Wiedemann)  is commonly used to prevent, suppress, eradicate, or contain these pests . In prin Salaya5 . This st Salaya5 . The genedemann) . Mating edemann) .Ceratitiscapitata  (Bactroceraoleae (Gmelin)  , Bactroc(Gmelin) ). In add cluster  or weak  cluster , suggestsolation . Althougsolation . BecauseBactroceracarambolae, using modified cross-species amplification of microsatellite DNA markers derived from Bactroceradorsalis and the junior synonym, Bactrocerapapayae, with regard to three aspects of species status and pest management. Intra-specific variation was analyzed among seven populations, consisting of native and trans-continentally introduced populations, for inference of colonization processes. Moreover, samples of Bactroceradorsalis were included to examine the population genetic structure and as an attempt to better understand the species boundary between Bactroceracarambolae and Bactroceradorsalis. Lastly, concerning pest management aspect, we validated the potential for use the genetic sexing Salaya5 strain in regional SIT programs. The Salaya5 were genotyped and genetically compared to other wild Bactroceracarambolae populations, in order to evaluate genetic compatibility between them.The aim of this research, therefore, is to study the population genetics of PageBreakBactroceracarambolae (http://www.cabi.org/isc/datasheet/8700). In Indonesia, six populations were collected from three main islands; two populations  were sampled from Sumatra; three populations  were sampled from Java; and another  was sampled from Borneo. In Thailand, one population was collected from the southern region (Nakhon Sri Thammarat-NT). All fruit fly samples were firstly characterized as Bactroceracarambolae based on Nine wild fruit fly populations were collected from four geographical areas: Indonesia (6), Malaysia 1), Thailand (1), and Suriname (1)  and characterized as Bactroceradorsalis using the same methods described before  and a part of the Y-pseudo linked autosome carrying a dominant allele of white pupae alleles of Salaya1 strain , 5 μM of each primer, and 100 ng of genomic DNA. PCRs were performed using the thermal cycler Flexcycler  using the conditions described by Bactroceradorsalis were cloned and sequenced using an ABI PRISM 310 genetic analyser . All sequences, except Bp173, showed homology to the original sequences in Genbank , previopapayae , were anTo improve null allele problems due to mutations on primer-binding sites and/or unsuitable PCR conditions, a new set of primers were designed and renamed for the 11 loci using OLIGO version 4.0-s . MoreoveFifteen flies from Jakarta and North Sumatra, Indonesia were initially screened with the 11 sets of new primers using the PCR conditions mentioned above. Electrophoresis and allele scoring were determined as in na), mean effective number of alleles (ne), mean number and frequency of private alleles , and mean observed and expected heterozygosity . Null allele frequency (An) was estimated following The descriptive parameters of population genetics were estimated using GENALEX v.6.5 . These pFST) among 13 populations was measured using MICROSATELLITE ANALYSER (MSA) (Dieringer and Schlötterrer 2003). In addition, genetically distinct groups (or clusters) were determined using the Bayesian approach implemented in STRUCTURE v.2.3.1 (F model), assuming correlated allele frequencies, was run. The program computed the number of possible clusters (K) from one to 13, with the condition of the burn-in period being 100,000 steps, followed by 500,000 MCMC repetitions. For each K value, five iterations were performed. The other parameters were set at default values: a standard deviation of 0.05, prior FST mean of 0.01, and different values PageBreakPageBreakof FST for different subpopulations. The optimal number of hypothetical clusters was indicated by the Delta K method  uncorrelated allele frequency and (2) missing data as recessive homozygotes for the null alleles were set to avoid the shared descent of samples and to verify possible bias from null alleles, respectively.Genetic differentiation  was used to display genetic divergence among fruit fly populations in multidimensional space. This analysis was based on allele frequency data and performed on genetic distance using GENALEX v.6.5 . The subTo test genetic homogeneity in different hierarchical population structures, Analysis of Molecular Variance (AMOVA) in ARLEQUIN v.3.1.1 was used . After 1The correlation analysis between genetic and geographic distance was performed using the subprogram ISOLDE in the GENEPOP package .a priori assumptions of the clustering of populations and some of the constraints  compulsory in phylogenetic trees. Data types of ‘genotype matrix, diploid, sampling site based’ were used as input. The genetic distance metrics or network files were calculated using the FST-based distance of Reynolds  determines the relative importance of a node within the network as an intermediary in the flow of information. Each network was weighted demonstrating genetic similarity associated with each link.Networks consist of nodes (or vertices), corresponding to populations, connected by links (or edges), representing their relationships or interactions. Connectivity degree (or Degree) is the number of edges connected to a node summarizing how strongly a population associated with the other populations in the system and whether or not it is a source population. Betweenness-centrality (thr). thr is the maximum distance considered as generating a connection in the network. One meanPageBreakingful distance is the one corresponding to the percolation threshold (Dp), edges with weights below the threshold were removed from the weighted network, and only the most important links were retained. Above the Dp level, there is a giant component containing almost all the nodes in the networks while below the Dp level, the network is fragmented into small disconnected components and the system therefore loses its ability to transport information across the whole system. Therefore, scanning at different thresholds was performed to analyze possible sub-structured systems to observe the sequential forms of clusters  to highly polymorphic at 16 (Bcar9)) and allele size range, as presented in Table Bactroceracarambolae samples collected from Southeast Asia showed relatively higher genetic variation than the introduced population (PR) for all parameters . In addition, the values of genetic variation of three Bactroceradorsalis populations, two unidentified populations, and the SY5 strain were in the same range as Bactroceracarambolae. The np values were observed in all populations, except for the NS, DK and PR populations, varying from 0.125  to 0.625 (RB) per locus. Likewise, rare alleles  were also detected in all populations (nr: ranging from 0.375 to 1.875 per locus), except KS. The average HE values varied from 0.185 (PR) to 0.668 (RB). However, a deficiency in the average HO values was found in all populations. Inbreeding (FIS) was detected in all populations, ranging from 0.095 to 0.628. The average for null alleles was 0.12, varying from low (0.01) to high frequency (0.25), which may contribute to the deficiency of heterozygosity observed in the given populations.Overall genetic variations detected in each population is summarized in Table FST), as shown in Table FST values range PageBreakfrom 0.134 (between PK and JK) to 0.631 (between DK and PR). Genetic differentiation was relatively high between native and introduced populations, ranging from 0.444 to 0.631. The introduced population (PR) was most similar to population PK (FST = 0.444) and JK (FST = 0.448). Within native areas of Bactroceracarambolae, the pairwise FST values ranged from 0.134 (PK and JK) to 0.344 (PK and DK). On the other hand, the pairwise FST values among samples of Bactroceradorsalis varied from 0.210 (RB and CM) to 0.357 (CM and KS). Without PR, the degree of genetic differentiation between Bactroceracarambolae and Bactroceradorsalis ranged from 0.181 (DP and RB) to 0.524 (NS and KS). The SY5 strain was revealed to be genetically closest to JK (FST = 0.278). The degree of pairwise FST among pairs of the SY5 strain and others varied from 0.372 (SY5 and DP) to 0.507 (SY5 and PR) (Table Genetic differentiation among 13 populations was measured by the fixation index (Q) distributed in hypothetical clusters (K) whereas PCoA illustrated the genetic divergence of fruit fly populations in multidimensional space, as shown in Figure Bactroceracarambolae populations, the Delta K value  as the optimal number. At K = 2, genetic clusters were divided into two groups: native and introduced Bactroceracarambolae. Cluster 1 contained all native populations (NS (Q = 0.979), PK (Q = 0.969), DP (Q = 0.984), JK (Q = 0.953), DK (Q = 0.991), and NT (Q = 0.995)) whereas the introduce population (PR) was distinguished, forming its own cluster (Q = 0.988)  Figure . This suPageBreakPageBreakPageBreakPageBreakBactroceradorsalis  and two unidentified populations (BD and WK) were included in the STRUCTURE analysis, the optimal number for K was three. Genetic clusters were separated into two groups: Bactroceradorsalis belonged to cluster 1 while Bactroceracarambolae belonged to clusters 2 and 3 , PK (Q = 0.954), DP (Q = 0.519), JK (Q = 0.910), DK (Q = 0.970), and NT (Q = 0.758)). However, PR formed its own cluster, cluster 3 (Q = 0.986). Three Bactroceradorsalis samples (RB (Q = 0.927), CM (Q = 0.955), and KS (Q = 0.952)) were grouped into the same genetic memberships (cluster 1) with two unidentified populations BD (Q = 0.927) and WK (Q = 0.953). Co-ancestor distribution between the Bactroceracarambolae and Bactroceradorsalis clusters (Q ≥ 0.001) was observed in populations DP (Q = 0.457) and NT (Q = 0.236). Using PCoA, the first plane  of multidimensional space also separated PR from the rest of the populations. Although the other two axes  did not clearly divide samples into two groups in accordance with the STRUCTURE results, the group of Bactroceradorsalis appeared to be plotted separately from the Bactroceracarambolae group.When three additional populations of 3 Figure . Six natK = 3 is presented in Figure Q) between 0.100 to 0.900 (0.100 ≤ Q ≤ 0.900) were identified as admixed individuals . Among the Bactroceracarambolae group, 18 of 185 individuals (9.73%) were admixed individuals. On the other hand, 13 of 104 individuals (12.5%) of the Bactroceradorsalis group were admixed individuals. Pure individuals (Q > 0.900) were identified between the two groups. Eight individuals from the Bactroceracarambolae group were labelled as Bactroceradorsalis whereas one individual from the Bactroceradorsalis group was indicated to be Bactroceracarambolae.The individual-admixture plot for K. At K = 2, genetic clusters formed two groups likely corresponding to Bactroceracarambolae and Bactroceradorsalis groups. Six populations of Bactroceracarambolae (NS (Q = 0.981), PK (Q = 0.913), JK (Q = 0.948), DK (Q = 0.964), and PR (Q = 0.993) belonged to cluster 1 . Cluster 2 consisted of the Bactroceradorsalis group (CM (Q = 0.909), RB (Q = 0.960), KS (Q = 0.964), BD (Q = 0.918), and WK (Q = 0.933)). However, populations DP (Q = 0.596) and NT (Q = 0.677) also shared membership in this cluster and became an admixture structure. The principal coordinates did not clearly delineate the two clusters using the three-dimensional plot. The PR population was still isolated from the others while the Bactroceradorsalis group seemed to form a peripheral group.Adding the SY5 strain to the genetic cluster analysis, two was the optimal number for 1 Figure . The SY5Bactroceracarambolae were divided into subpopulations according to micro- and macro- geographies. At the micro-geographical level, seven populations were divided into five groups: Sumatra, Indonesia (NS and PK); Java, Indonesia (DP and JK); Malaysia (DK); Thailand (NT); and Suriname (PR). Non- significant differPageBreakences among those groups were detected (scenario 1: P = 0.1877). Likewise, when all seven populations were divided based on macro-geography (Southeast Asia vs. South America), a non-significant difference between groups was still observed (scenario 2: P = 0.1953). A test of genetic homogeneity between Bactroceracarambolae and Bactroceradorsalis is presented in scenario 3, illustrating a significant difference (P = 0.0479). Even though BD and WK were included in the Bactroceradorsalis group, a significant difference was still detected (scenario 4: P = 0.0156). In scenarios 5 to 7, the SY5 strain was included to compare the genetic variation among other samples. The results revealed a non-significant difference between Bactroceracarambolae and the SY5 strain (scenario 5: P = 0.2483) and among Bactroceracarambolae, Bactroceradorsalis and the SY5 strain (scenario 6: P = 0.0694). However, a significant difference was indicated when BD and WK were included in the Bactroceradorsalis group (scenario 7: P = 0.0342). The last two scenarios was set following the STRUCTURE results .Analysis of Molecular Variance (AMOVA) was used to study the hierarchical structure of populations for different scenarios Table . OverallBactroceracarambolae and Bactroceradorsalis populations. The correlation between genetic and geographical distance became non-significant  when Bactroceracarambolae samples were analysed. This fact indicates that there is no limitation of gene flow among Bactroceracarambolae across the region. Among Bactroceracarambolae and Bactroceradorsalis populations, analysis showed significant correlation between genetic and geographical distances , even though only the PR sample was excluded .The correlation between genetic and geographic distance was analyzed using only wild samples consisting of PageBreakBactroceracarambolae populations, (2) among 12 populations belonging to Bactroceracarambolae and Bactroceradorsalis clusters, and (3) among 13 populations, including the SY5 strain  and lower threshold chosen (thr) to reveal the sequential substructure at decreasing thresholds. The first scenario was constructed based on data among seven Bactroceracarambolae populations  than others and played a role connecting between native and introduced populations  among seven  Figures . The nets Figure . The pers Figure . The nod among seBactroceradorsalis cluster were included in the network analyses , JK  and NT    . At the percolation threshold Dp = 0.23, non-substructured network was recognized  Figure . The SY5d Figure . ScanninBactroceracarambolae from Southeast Asia and South America, the populations across the species’ native range possessed higher genetic variation than the introduced population, which is generally expected for invasive species. The first genetic connections between native and introduced populations were identified as Jakarta (JK) and Pekanbaru (PK), Indonesia. However, the genetic structure of the Suriname population (PR)  was differentiated from the Carambola fruit fly in Southeast Asia. These results were congruent with multilocus phylogenetic analysis established by Bactroceracarambolae in the introduced area potentially include genetic drift during the colonization process and local adaptation. Based on the genetic data in this study, JK and PK are possible sources of the PR population. Bactroceracarambolae accidentally invaded South America, likely by tourists and trade from Indonesia to Suriname. Even though this species was detected in 1975, it took up to 21 years (1975–1996) to establish its new populations in other areas, expanding 500 km eastward and westward from the original point of introduction in Suriname  in Suriname were limited to backyards; agricultural production had not yet developed. Hosts for the fly were occasionally recorded to be different between native and introduced areas (van Sauers-Muller 2005), as shown in Table PageBreakPageBreaknear Suriname may slow down species distribution in South America. This pattern is similar to the case of the related species Bactroceradorsalis in several introduced areas such as Hawaii, Myanmar, and Bangladesh, in that their genetic variation and population structure were shaped by genetic drift and different local adaptations  were estimated from Bactroceradorsalis  to 18,022 km (Paramaribo) from Jakarta, Indonesia. Research using more samples from different locations on a fine scale and/or more genetic markers may provide more details.Pairwise dorsalis . The mosanalyses . Howeverocations . SamplesCeratitis FAR complex , varying from low (0.01) to high frequencies (0.25). The high departure from HWE was also observed in other study using a single set of microsatellite markers for different species such as the x 52.4%, . We veri2, varyinBactroceracarambolae and Bactroceradorsalis while 14 and 27 alleles were detected in only Bactroceracarambolae and Bactroceradorsalis, respectively. Coincidence of similar/different allele profiles between them at microsatellite loci may be due to several phenomena including retention of ancestral alleles in both sister species; substantial gene flow between the two species; size homoplasy . To avoid the shared descent, a stricter model using uncorrelated allele frequencies was tested. The results still presented species’ genetic cluster and admixed inPageBreakdividuals  in both clusters with relatively similar ratio  were included. More analyses on genetic variation, population structure and genetic network were performed between the SY5 strain and wild populations. We found that the SY5 strain had genetic variation, population structure, and genetic similarity comparable to Bactroceracarambolae, rather than Bactroceradorsalis, in Southeast Asia. The results strongly confirmed that the Salaya5 strain had not diverted away from its original genetic makeup. Under laboratory condition, at least 12 generations apart, selection did not strongly affect genetic compatibility between the strain and wild populations. Therefore, the SY5 strain could be included in the pest control programs using male-only SIT for control Bactroceracarambolae at local and regional levels. However, an actual mating test is still required between the strain and samples from introduced populations.PageBreakBactroceracarambolae and Bactroceradorsalis were reported to be sympatric species in some areas . Although several lines of evidence suggested that both species showed mating compatibility to some degree  cannot  and one of 104 individuals (0.96%) belonging to the ) cannot . In thisBactroceracarambolae from an introduced population genetically differs from populations from the native range. Genetic drift during colonization process and local adaptation may be factors shaping its genetic diversity and population structure. However, only sampling from South America might not be sufficient to trace back the process of colonization within and between continents. West Sumatra (Pekanbaru-PK) and Java (Jakarta-JK) were identified as sources of the Suriname population, congruent with historical record of human migration between the two continents. A different pattern of population structure was observed in Bactroceracarambolae within native range, where free human movement and trading can promote genetic homogeneity. Between Bactroceracarambolae and Bactroceradorsalis groups, potential hybrids provide evidence through individual-based admixture plots. This was additional supportive data suggesting that reproductive isolation between Bactroceracarambolae and Bactroceradorsalis is somewhat leaky. Although morphoPageBreaklogical characterization and several nuclear and mitochondrial markers revealed distinct species, the hypothesis of semipermeable species boundaries between them cannot be rejected. Alleles at microsatellite loci could be introgressed rather than other nuclear and mitochondrial sequences. Regarding the final conclusion on pest management aspect, the genetic sexing Salaya5 strain for Bactroceracarambolae had not diverted away from its original genetic makeup (JK) and other neighbor populations. Under laboratory condition, at least 12 generations apart, selection did not strongly affect genetic compatibility between the strain and wild populations. Therefore, the Salaya5 strain could be possible to include in the pest control programs using male-only SIT in local and regional levels, although an actual mating test is still required between the strain and samples from introduced populations.Pattern of connectivity and population structure, based on microsatellite DNA markers, showed that


However, genetic signals of population mixture cease after ~1200 bce when Bronze Age civilizations in the Eastern Mediterranean world suddenly and violently collapsed. Armenians have since remained isolated and genetic structure within the population developed ~500 years ago when Armenia was divided between the Ottomans and the Safavid Empire in Iran. Finally, we show that Armenians have higher genetic affinity to Neolithic Europeans than other present-day Near Easterners, and that 29% of Armenian ancestry may originate from an ancestral population that is best represented by Neolithic Europeans.The Armenians are a culturally isolated population who historically inhabited a region in the Near East bounded by the Mediterranean and Black seas and the Caucasus, but remain under-represented in genetic studies and have a complex history including a major geographic displacement during World War I. Here, we analyse genome-wide variation in 173 Armenians and compare them with 78 other worldwide populations. We find that Armenians form a distinctive cluster linking the Near East, Europe, and the Caucasus. We show that Armenian diversity can be explained by several mixtures of Eurasian populations that occurred between ~3000 and ~2000  We have previously shown that studying genetic isolates also provides insights into human genetic variation and past demographic events.5 For example, by studying Jews, Druze, and Christians from the Near East, we showed that the region had more genetic affinity to Europe 2000 years ago than at present.5Insights into the human past come from diverse areas including history, archaeology, linguistics, and, increasingly, genetics. The observed patterns of present-day genetic diversity can be compared with models that include past population processes such as migration, divergence and admixture, and the best model chosen. These models often require representing ancestral populations and mostly consider present-day populations as direct descendants of the ancient inhabitants of a region. However, archaeological and genetic data reveal that human history has often been shaped by regional or localized population movements that can confound simple demographic models.6 Furthermore, Armenia's location may have been important for the spread of Indo-European languages, since it is believed to encompass or be close to the Proto-Indo-European homeland (Anatolia or Pontic Steppe) from which the Indo-Europeans and their culture spread to Western Europe, Central Asia, and India.In the present study, we investigate the Armenians, a population today confined to the Caucasus but who occupied Eastern Turkey, reaching as far as the Mediterranean coast, until the start of the twentieth century CE; . Politic8Previous genetic studies of Armenians are scarce and genome-wide analysis is limited to a few Armenian samples in broad surveys without any detailed analysis. Armenians were found to have genetic affinity to several other populations including the Jews, Druze, and Lebanese Christians, in addition to showing genetic continuity with the Caucasus.In this study, we analyse newly generated genome-wide data from Armenians, as well as available data from 78 other worldwide populations. We investigate genetic signatures of past events such as the emergence of Armenians as an ethnic group, the cultural changes in the Near East, and the expansions of ancient populations in this region.n=39) and Armenia: Chambarak (n=30), Dprabak (n=18), Gavar (n=12), Martuni (n=19), Yegvard (n=11), and Yerevan (n=9). Armenian individuals recruited in Lebanon traced their ancestry to East Turkey; they signed informed consent approved by the IRB of the Lebanese American University and were genotyped on Illumina 610 or 660 K bead arrays.Armenian samples were collected from Lebanon . Samples were genotyped on Illumina HumanOmniExpress and described previously by Mezzavilla www.ebi.ac.uk/eva under accession number PRJEB9822 or as plink files from ftp://ngs.sanger.ac.uk/scratch/project/team19/Armenian.Genotype data can be downloaded as VCF files from the European Variation Archive n=35) were added along with 1509 samples from the literature that represent 78 worldwide populations.10In addition, Armenian samples  was computed by mclust (http://www.stat.washington.edu/mclust) over the first 10 principal components of the projected Armenian samples on the global PCA. The best model to classify the Armenians according to the BIC values was with three components  between populations to estimate their time of divergence. Fst was calculated using the software 4P.17 The generation time used was 28 years.The effective population size of the Armenians was estimated from linkage disequilibrium (LD) and the time of divergence between the two major groups was calculated using f3 statistics18f3, where a significantly negative statistic provides evidence that A is derived from an admixture of populations related to B and C. We tested all possible f3 statistics in our data set and calculated SE using blocks of 500 SNPs.19 To date the time of admixture, we used ALDER20, which computes the weighted LD statistic to make inferences about population admixture. The reference populations consisted of 1300 samples and 53 populations reduced from the original data set by removing populations that are themselves highly admixed (z-score >|4|) and summarize the findings in 21 and samples from the Early Neolithic Körös culture.22We used  admixed . We coll21 We downloaded the BAM file mapped to hg18 and called all variants using GATK.23 liftOver (http://genome.ucsc.edu) was used to convert the coordinates to hg19; the final data set consisted of 91 115 SNPs.For tests of genetic affinity to Neolithic Europeans, we merged our samples with the genome of the Tyrolean Iceman.24 We downloaded the BAM file mapped to hg19 and called the variants using GATK. The final data set consisted of 103 627 SNPs.For tests of genetic affinity to Mesolithic Europeans, we merged our data set with the genome of the La Braña sample.TreeMix19, rooting the tree with a Denisovan genome, and estimated SEs using blocks of 500 SNPs. We generated 100 bootstrap replicates by resampling blocks of 500 SNPs to assess the stability of the tree topology. We used outgroup f3 statistics18 in the form of f3 and f3 to assess the shared genetic history of the ancient Europeans with the modern populations. In the absence of admixture with Yoruba, deviation from 0 will be a function of the shared genetic history of the ancient Europeans and the non-African population.We applied 14 , where a significantly negative value of the f3 statistic implies that Armenians descend from a mixture of the populations represented by A and B, chosen from the 78 global populations. We found signals of mixture from several African and Eurasian populations  East Asian ancestry in Turks from admixture occurring 800 (±170) years ago. We also detect sub-Saharan African gene flow 850 (±85) years ago in Syrians, Palestinians and Jordanians.MCLUST suggests the best model to classify the Armenians is λkA  with three components (clusters). We observe the following: (1) Armenians in the diaspora that trace their origin to historical Western Armenia (modern-day East Turkey) form one group  in a data set using the haplotypes of other individuals (donors) in the data set. We then constructed a tree that infers population relationships and similarities , always leading from the Iceman to Armenians  in the absence of admixture with Yoruba will be a function of the shared genetic history of the Iceman and X (non-African populations). Most shared ancestry of the Iceman is with Sardinians and other Europeans (This structure was further investigated using outgroup uropeans . This isf3 statistics and replaced the Iceman with a 7000-year-old European hunter-gatherer from Spain (La Braña).24 West European hunter-gatherers have previously been shown to have contributed ancestry to all Europeans but not to Near Easterners.6 Consistent with this, we found reduced affinity and no noticeable structure in the Near Easterners in their relation to La Braña , we repeated the outgroup The origins of the Armenians and their cultural uniqueness are poorly understood. Here, we investigate the information that can be obtained by genetic analysis of present-day Armenians and comparisons with other present-day and ancient samples.26 and has the oldest known monumental complex built by hunter-gatherers in the tenth millennium bce.27 It is believed to have been the origin and/or route for migrating Near Eastern farmers towards Europe during the Neolithic,28 and has probably also played a major role in the dispersal of the Indo-European languages.29The position of the Armenians within global genetic diversity appears to mirror the geographical location of Turkey, which forms a bridge connecting Europe, the Near East, and the Caucasus. Turkey's location and history have placed it at the centre of several modern human expansions in Eurasia: it has been inhabited continuously since at least the early Upper Palaeolithic,bce. This period spans the Bronze Age, characterized by extensive use of metals in farming tools, chariots, and weapons, accompanied by development of the earliest writing systems and the establishment of trade routes and commerce. Many civilizations such as in ancient Egypt, Mesopotamia, and the Indus valley grew to prominence. Major population expansions followed, triggered by advances in transportation technology and the pursuit of resources. Our admixture tests show that Armenian genomes carry signals of an extensive population mixture during this period. We note that these mixture dates also coincide with the legendary establishment of Armenia in 2492 bce. Admixture signals decrease to insignificant levels after 1200 bce, a time when Bronze Age civilizations in the Eastern Mediterranean world suddenly collapsed, with major cities being destroyed or abandoned and most trade routes disrupted. This appears to have caused Armenians' isolation from their surroundings, subsequently sustained by the cultural/linguistic/religious distinctiveness that persists until today. The genetic landscape in most of the Middle East appears to have been continuously changing since then. For example, we detect East Asian ancestry in Turks from admixture occurring 800 (±170) years ago coinciding with the arrival of the Seljuk Turks to Anatolia from their homelands near the Aral sea. We also detect sub-Saharan African gene flow 850 (±85) years ago in Syrians, Palestinians, and Jordanians consistent with previous reports of recent gene flow from Africans to Levantine populations after the Arab expansions.30We investigated Armenians further by inferring their admixture history. The Armenians show signatures of an origin from a mixture of diverse populations occurring from 3000 to 2000 5 Our tests suggest that Armenians had no significant mixture with other populations in their recent history and have thus been genetically isolated since the end of the Bronze Age, 3000 years ago. In recent times, we detect genetic structure within the Armenian population that developed ~500 years ago. The date coincides with the start of the Ottoman–Persian wars and the split of Armenia into West and East between the Ottoman Empire in Turkey and the Safavid Empire in Iran.The admixture pattern in Armenians appears similar to patterns we have observed in some other genetic isolates in the region, such as Sephardic Jews and Lebanese Christians, who show limited admixture with culturally different neighbouring populations in the last two millennia.One of the most-studied demographic processes in population genetics is the Neolithic expansion of Near Eastern farmers into Europe beginning ~8000 years ago. Armenians' location at the northern tip of the Near East suggests a possible relationship to the expanding Neolithic farmers. We find in Armenians and other genetic isolates in the Near East high shared ancestry with ancient European farmers, with ancestry proportions being similar to present-day Europeans but not to present-day Near Easterners. These results suggest that genetic isolates in the Near East – Cypriots (an island population), Near Eastern Jews and Christians (religious isolates), and Armenians (Ethno-linguistic isolate) – probably retain the features of an ancient genetic landscape in the Near East that had more affinity to Europe than the present populations do. Our tests show that most of the Near East genetic isolates' ancestry that is shared with Europeans can be attributed to expansion after the Neolithic period.Armenians' adoption of a distinctive culture early in their history resulted in their genetic isolation from their surroundings. Their genetic resemblance today to other genetic isolates in the Near East, but not to most other Near Easterners, suggests that recent admixture has changed the genetic landscape in most populations in the region. Armenians' genetic diversity reveals that the ancient Near East had higher affinity to Neolithic Europe than it does now, and that Bronze Age demographic processes had a major impact on the genetics of populations in this region.31 Armenians' emergence from founders in the Bronze Age, accompanied by a long period of subsequent isolation, may have enriched rare disease alleles and therefore merits future medical exploration.The importance of populations like the Armenians is not limited to the study of past demographic processes; isolated populations are emerging as a powerful tool for many different genetic investigations such as rare variant associations with complex phenotypes and the characterization of gene–environment interactions.


Nm). Our results, based on spatially explicit analysis with Bayesian methods, indicate that leopards in the region exist in a fragmented population structure with lower than expected genetic diversity. Three population groups were identified, between which low to moderate levels of gene flow were observed (Nm 0.5 to 3.6). One subpopulation exhibited low genetic differentiation, suggesting a continuous population structure, while the remaining two appear to be less connected, with low emigration and immigration between these populations. Therefore, genetic barriers are present between the subpopulations, and while leopards in the study region may function as a metapopulation, anthropogenic activities threaten to decrease habitat and movement further. Our results indicate that the leopard population may become isolated within a few generations and suggest that management actions should aim to increase habitat connectivity and reduce human–carnivore conflict. Understanding genetic diversity and connectivity of populations has important conservation implications that can highlight management of priority populations to reverse the effects of human-caused extinctions.While African leopard populations are considered to be continuous as demonstrated by their high genetic variation, the southernmost leopard population exists in the Eastern and Western Cape, South Africa, where anthropogenic activities may be affecting this population's structure. Little is known about the elusive, last free-roaming top predator in the region and this study is the first to report on leopard population structuring using nuclear DNA. By analyzing 14 microsatellite markers from 40 leopard tissue samples, we aimed to understand the populations' structure, genetic distance, and gene flow ( Ensuring the maintenance of genetic diversity and connectivity among populations facilitates the continuation of dynamic evolutionary and ecological processes. Genetic data provide insights into the population structure of a species and the rate of genetic movement between populations, which helps to determine the possibility of local adaptation and of adaptive evolution in complex landscapes  is characterized by a matrix of land uses, highly fragmented natural habitat and human–carnivore conflict, all of which result in carnivore mortality. Such landscape characteristics have resulted in reduced gene flow in other carnivore species around the world , 1 U Taq DNA polymerase, and 50 ng genomic DNA template. PCR was conducted in the BOECO TC-PRO Thermal Cycler. The amplification conditions were as follows: five minutes at 95°C, 30 cycles for 30 sec at 95°C, 30 sec at 50–60°C, and 30 sec at 72°C, followed by extension at 72°C for 40 min. The dye-labeled PCR products of the microsatellite primer sets were pooled and diluted together based on size range and fluorescent dye, so that 3 to 6 loci could be multiplexed, electrophoresed, and subsequently analyzed in an ABI3130 automated sequencer. Microsatellite allele sizes were estimated by comparison with a LIZ™ 500  internal size standard. Data were collected and analyzed using the ABI programs GENESCAN (version 1.2.2-1) and GENOTYPER (version 1.1). We conducted a minimum of two replicate PCRs per tissue sample per locus. Alleles included in the final consensus genotypes were observed twice; if observed once, additional replicates were conducted. We also included a negative and positive control in each PCR as checks for contamination and to ensure standardized genotypes among experiments.Genomic DNA was extracted from tissue using the QIAGEN DNeasy® Blood and Tissue Kit , following the manufacturer's protocol. Leopard samples were analyzed using 14 microsatellite loci developed from the domestic cat (Menotti-Raymond and O'Brien O), Nei's (E), and percentage/number of private alleles, all of which were calculated using the software GenAlEx 6.5 , Nei's  unbiasedK was determined across 10 iterations using GENELAND. All runs were conducted using 1,000,000 Markov chain Monte Carlo (MCMC) iterations. Genetic differentiation was examined between the inferred clusters using F-statistics calculated in GENEPOP /4 , He values ranged from 0.50 to 0.81, and the average number of alleles per locus was 6.5  and south and north  populations supports a strong substructuring of the diversity. Gene flow among these populations was therefore low . However, a moderate genetic distance measure was observed between the central and south populations , suggesting some gene flow between these populations (Nm 3.68). This may be explained by one museum sample, which formed part of the south population, collected in 1986 on the western edge of the large central population. This individual probably migrated between these two populations. Private alleles were observed in all three populations, namely 27 in the central population, three in the south population, and two in the north population.This study provided important insights into the population structure and gene flow of leopards in the Eastern and Western Cape provinces of South Africa. All GENELAND runs produced a mate Fig.. Based omate Fig.. SupportAlthough leopards in Africa are considered to have high genetic diversity and little population structuring  indicates that more habitat fragmentation exists between the north and the remaining populations. While the south and central populations indicate some gene flow between them (Nm 3.68), one sample forming part of the south population was collected in 1986 on the western edge of the central population. Therefore, the finding of lower genetic distance between the central and south populations may be due to remnant connectivity. The high number of private alleles maintained by the central population (n = 27), compared to both south and north populations, further suggests that the latter populations have been isolated from genetic transfer of the continuous central population and have undergone a severe genetic bottleneck effect.Our findings highlight the sensitivity of leopard to landscape changes involving human occupation. The higher genetic differentiation observed in the north population (These results indicate that the leopard population can broadly be described as a metapopulation (see Hanski and Gilpin P.p. fusca) (0.696) and Persian leopard (P.p. saxilcolor) (0.616) populations  (0.356)  based on predicted leopard habitat for the Eastern and Western Cape  in a human-dominated landscape indicated that, even when high immigration rates were used in models, small populations became extinct within 100 years (Sweanor et al. It has been proposed that only one migrant per generation is needed to prevent population differentiation (Kimura and Ohta To ensure gene flow between populations, habitat connectivity and opportunities for genetic movement between discontinuous populations are essential (Ernest et al. The detection of population divergence in leopard populations in South Africa indicates an increasingly fragmented landscape for carnivores. As the human population continues to increase rapidly, the need to maintain connectivity of natural populations is becoming greater. The conservation implications with this genetic index can be useful to conservation biologists. To ensure population persistence of carnivores, their management requires identifying and securing leopard habitat, promoting habitat connectivity, considering local translocations as opposed to killing individuals, curbing human-carnivore conflict and ensuring future development considers species-specific alternatives to ensure connectivity.