Orobanche crenata Forsk.) is a serious long‐standing parasitic weed problem in Algeria, mainly affecting legumes but also vegetable crops. Unresolved questions for parasitic weeds revolve around the extent to which these plants undergo local adaptation, especially with respect to host specialization, which would be expected to be a strong selective factor for obligate parasitic plants. In the present study, the genotyping‐by‐sequencing (GBS) approach was used to analyze genetic diversity and population structure of 10 Northern Algerian O. crenata populations with different geographical origins and host species . In total, 8004 high‐quality single‐nucleotide polymorphisms (5% missingness) were obtained and used across the study. Genetic diversity and relationships of 95 individuals from 10 populations were studied using model‐based ancestry analysis, principal components analysis, discriminant analysis of principal components, and phylogeny approaches. The genetic differentiation (FST) between pairs of populations was lower between adjacent populations and higher between geographically separated ones, but no support was found for isolation by distance. Further analyses identified four genetic clusters and revealed evidence of structuring among populations and, although confounded with location, among hosts. In the clearest example, O. crenata growing on pea had a SNP profile that was distinct from other host/location combinations. These results illustrate the importance and potential of GBS to reveal the dynamics of parasitic weed dispersal and population structure.Crenate broomrape ( Orobanche crenata populations we identified population genetic structure associated with A) geographic location and B) host plants. These data suggest that differentiation among these populations could result from the interaction of geographic separation and host specialization.Understanding the factors that shape obligate parasitic plant populations provides an important window on the evolutionary history of these unique plants. Using GBS‐derived markers across a number of  History tells us of the extent Orobanche damage at the beginning of the last century. In Faba beans and peas cultivation is made impossible in certain localities of the Sahel of Algiers and of the plateau of ‘Maison carrée’, so much has become common there, in the last fifteen or twenty years, the crenate broomrape.″ At that time, the same author estimated that in some localities 60% of the land had become unsuitable for the cultivation of pea and faba bean as a result of the damage caused by this broomrape, which could lead to the complete crop failure  following the manufacture's instruction. Samples were sent to the Institute of Genomic Diversity at Cornell University for genotyping by sequencing, libraries were prepared as described in the protocol by Elshire et al. . Briefly2.3Raw sequence data were processed using the Universal Network‐Enabled Analysis kit (UNEAK) pipeline implemented in the Iplant collaborative platform. This pipeline produced a hapmap file for downstream analysis. This file was used as input for SNP identification using the GBS pipeline implemented in TASSEL (Version: 3.0.166). Raw SNPs were filtered following the dDocent guidelines . Pairwise FST values ranged from a low of 0.0162  and chickpea (TH) was the second highest at 0.1135. Within faba bean host samples , the pairwise FST values ranged from 0.0216 to 0.0354, indicating that there was less genetic differentiation within faba bean hosts than across all samples.Population differentiation was estimated using Weir and Cockerham’s  FST  and population within host . The observed increased individual variation among O. crenata populations results from a significant excess of heterozygosity .A hierarchical AMOVA, as implemented in poppr with method = “ade4,″ was carried out using population within host  across populations. We do find, however, two distinct patches in the kernel density estimates for IBD .To test the role of isolation by distance (IBD), a Mantel test was conducted using Edward's genetic distance and a geographic distance matrix . Overall, we find no support for IBD  and cluster 2 (N = 22) with two samples having shared membership.The first 4 components from a PCA of genetic distance explained 66.16% of the total variation in the data. To further examine the relationship between samples within this PCA, we conducted a discriminant analysis of principle components (DAPC). Discriminant analysis of principle components identified four genetic clusters in the data across three axes Figure . Cluster4Orobanche spp. given their tremendous economic impact, knowledge of their genetic variability is still limited. Genetic diversity analysis is of great importance as it will facilitate understanding the genetic structure of parasitic weed populations. This knowledge will provide insights into parasite dispersal, host specialization, development of new races, and in establishing diverse collections of parasite races for use in crop breeding programs , RAPD , ISSR , SSR , SSR‐SNP , and SRAP . In recent years, genotyping by sequencing (GBS) has become an ideal tool for plant breeding and plant genetics studies  between pairs of O. crenata populations by collection location varied from 0.0076 to 0.1193 . This region is known for intensive vegetable cultivation where exchange and/or sharing and trading of agricultural material  are common practices  were recorded for the most geographically distant populations, in particular that of Ain Temouchent (AT), which is the farthest collection location. Genetic differentiation among populations is expected to increase with increased geographic distance  across these populations overall. Nonetheless, the Ain Temouchent population (AT) remained an outlier driving the linear relationship with geographic distance  and highest between carrot and pea in distant populations . These data are consistent with the AMOVA results  harvested on chickpea (TH) and tomato (TT) samples. Cluster 2 is made exclusively of carrot samples all from the population (AT) of “Ain Temouchent″ . Cluster 4 grouped pea samples, all from the population (BM) from “Blida‐Mouzaia″ . Cluster 3 and cluster 4 shared populations harvested on faba bean , almost all from the coastline .O. crenata populations are differentiated across this range. This is consistent with multiple possible evolutionary processes including drift associated with population isolation but also the possibility that host specialization and adaptation to local ecological conditions are driving population differences. For example, the most geographically separated populations AT and AA (432 km straight line distance), expected to have the highest FST value, appeared less genetically differentiated with an FST of 0.0858. This outcome is consistent with the hypothesis that both populations could have evolved from the same origin and that AT became differentiated from other populations . This is also consistent with the possibility of spread of O. crenata seeds from northeast to southwest (within northern Algeria). This direction seems most plausible since the oldest infestations were reported in the central part of the Algiers coastline (Sahel of Algiers), which is consistent with the study of Aouali et al.  contrasts with the majority of the populations located on the coastal plains. This geographic structuring could have eventually allowed the isolation of this population  did nO. crenata  was generated for the genetic diversity analyses. The study revealed low‐to‐moderate genetic differentiation between close and geographically separated populations, respectively. Population differentiation by geographic distance was more evident when coupled with crop hosts as supported by phylogenetic and clustering analyses. Four genetic pools were differentiated, clustered according to crop hosts, although this was confounded by population separation. AT and BM (Blida‐Mouzaia) populations were shown to be spatially and genetically isolated. This study identifies genetic differentiation among O. crenata populations in northern Algeria. Future studies are needed to identify the evolutionary processes shaping this differentiation.In this study we explored the genetic diversity, population structure, and potential host differentiation of 95 individuals from 10 populations of All authors declare no conflicts of interest.Farah Bendaoud: Investigation ; Methodology ; Writing – original draft ; Writing – review & editing . Gunjune Kim: Investigation (supporting); Methodology (supporting); Software (supporting); Supervision (supporting); Validation (supporting); Writing – original draft (supporting); Writing – review & editing (supporting). Hailey Larose: Investigation (supporting); Methodology (supporting); Project administration (supporting); Writing – review & editing (supporting). James H. Westwood: Conceptualization ; Funding acquisition ; Investigation (supporting); Project administration ; Resources ; Supervision ; Writing – original draft ; Writing – review & editing . Nadjia Zermane: Conceptualization ; Funding acquisition (lead); Investigation ; Project administration ; Resources ; Writing – original draft ; Writing – review & editing . David C. Haak: Data curation (lead); Formal analysis (lead); Investigation ; Methodology ; Project administration ; Resources ; Supervision (lead); Validation ; Visualization (lead); Writing – original draft (lead); Writing – review & editing (lead).https://doi.org/10.7294/14838213.This article has been awarded Open Materials, Open Data Badges. All materials and data are publicly accessible via the Open Science Framework at Figure S1Click here for additional data file.


Intra-species genetic homogenization arising from anthropogenic impacts is a major threat to biodiversity. However, few taxa have sufficient historical material to systematically quantify long-term genetic changes. Using archival DNA collected over approximately 100 years, we assessed spatio-temporal genetic change in Atlantic salmon populations across the Baltic Sea, an area heavily impacted by hydropower exploitation and associated with large-scale mitigation stocking. Analysis was carried out by screening 82 SNPs in 1680 individuals from 13 Swedish rivers. We found an overall decrease in genetic divergence and diminished isolation by distance among populations, strongly indicating genetic homogenization over the past century. We further observed an increase in genetic diversity within populations consistent with increased gene flow. The temporal genetic change was lower in larger wild populations than in smaller wild and hatchery-reared ones, indicating that larger populations have been able to support a high number of native spawners in relation to immigrants. Our results demonstrate that stocking practices of salmon in the Baltic Sea have led to the homogenization of populations over the last century, potentially compromising their ability to adapt to environmental change. Stocking of reared fish is common worldwide, and our study is a cautionary example of the potentially long-term negative effects of such activities. Access Releases of hatchery-reared fish to compensate for habitat loss and/or to increase fishing opportunities are common worldwide. While in some cases such interventions may be beneficial for assisting threatened populations, a number of genetic conservation concerns have been identified  that depend on how artificial propagation and stocking is carried out ,21–24. SSalmo salar L.) is a keystone species with high historically and contemporarily social, economic and cultural value. During the last century, Atlantic salmon populations have suffered from a range of anthropogenic activities such as hydropower development, habitat degradation and overfishing. Salmon in the Baltic Sea are no exception [The Atlantic salmon  compare the historical (1920s–1930s) genetic population structure with the contemporary state (2010–2015), (ii) quantify the amount and direction of genetic change between and within populations, and (iii) assess the relative role of different evolutionary forces that have led to the present genetic structure. In addition, we compared changes in wild and hatchery-reared populations, as a means to disentangle natural and anthropogenic processes behind observed temporal changes.. 2(a)A total of 956 historical and 814 contemporary individual samples from Baltic salmon in 13 Swedish rivers were analysed. The salmon rivers studied are located along with a coastline distance of greater than 1400 km. These span from large northern rivers  with a yearly spawning run of 10 000–150 000 adults to much smaller rivers (e.g. Öreälven and Rickleån) with only 50–200 spawning adults. Seven large rivers (e.g. Lule and Umeälven) are completely inaccessible due to dams for hydropower generation and today have no wild salmon production.  and five rivers where salmon production is fully supported by hatcheries (hereafter termed ‘reared') . At present, no hatchery stocking is undertaken in any of the wild populations. However, there has been historic stocking in all of the wild rivers, mainly with locally caught salmon (i.e. supportive breeding), but included the occasional use of non-native salmon.For comparative reasons, we pre-defined the following groupings when analysing our data: (A) all populations, (B) reared populations, (C) wild populations, and (D) wild populations except the southernmost one (Mörrumsån) that is located very distant from all other studied rivers . The lasn = 11 populations), 1946 (one population) and 1961–1963 (one population) while the contemporary samples originated from 2010–2015 . Historical samples consisted of dried scales from adult fish stored in labelled paper envelopes at the Swedish University of Agricultural Sciences (Älvkarleby and Drottningholm). Contemporary samples (fin tissue stored in 95% ethanol) were collected in rivers, either from juveniles (parr and smolt) or adult spawners.Historical samples were collected from 1920s–1930s ((b)et al. [The genetic markers employed were a subset of those described by Karlsson et al. . Because(c)DNA was extracted from scales using a Qiagen Symphony robot and the QiaSymphony DNA tissue kit according to the manufacturer's instructions. Extraction, PCR amplification and SNP genotyping all took place in separate access controlled rooms with dedicated equipment. Genotyping was performed on a Fluidigm Biomark microarray platform using the 96.96 dynamic array, following standard protocols with the exception of historic samples being pre-amplified for 30 cycles instead of the standard 14 used for the contemporary samples. All genotyping runs included three NTC (no template controls) and positive control reference samples. Samples were run in duplicates for quality control and error estimates. Only individuals that showed genotype completion greater than 95% were retained in the final analyses. Samples were checked for contamination by ensuring that they fell within the expected range for heterozygosity levels (contaminated samples show heterozygote excess). To quantify the level of genotyping error caused by a lack of amplification of one of the alleles (dropout), this rate was calculated from samples run in duplicates. The true dropout rate is likely to have been somewhat higher, but since we cannot detect dropout in homozygotes, this could not be easily established.(d)rlequin [ayescan [utflank [s = 13) and excluding (s = 12) the genetically and geographically most deviating population (Mörrumsån). When that deviating sample was included, both a non-hierarchical and a hierarchical analysis was performed with Arlequin. In total, 34 separate tests were carried out using different combinations of samples and statistical methods. Full details of all outlier analyses and program settings are described in electronic supplementary material, appendix S1 .A series of tests were carried out aimed at detecting putative outliers among the 82 SNPs . Three different statistical approaches were employed using the software Arlequin , Bayesca[ayescan  and Outf[utflank . Histori[utflank . Therefo(e)olony 2.0.4.4 [To counteract potential bias on genetic parameters due to non-representative sampling caused by family structure –46 we sc 2.0.4.4 ,48 We sutructure [tructure uses individual genotypic data to infer the number of populations or genetic clusters (K) that give the best/optimal solution based on the assumption that clusters should be in Hardy–Weinberg and linkage equilibrium. Individuals can be assigned to one or, in case of admixed ancestry, several clusters. We used a model assuming admixture with correlated allele frequencies [K 5 to 15, with 10 replicated runs per K. To define the most likely number of clusters, we applied the ΔK method [tructure Harvester [We used the program Structure  to invesquencies  and a buK method , as implarvester .tructure  has been discussed extensively [tructure analysis and compared cluster distributions over time. Differences in such temporal genetic changes (proportions of membership in dominant cluster K) across samples (populations) were investigated with the prop.test function in R [Collections of individual genotypes that share clusters are presumed to have a closer genetic relationship to each other. The biological meaning of clusters identified by Sensively –55. In oion in R . Historistat [He, FIS, global and pairwise FST [FST) between pairs of samples (6500 permutations), between pre-defined population groups (1000 permutations), and for deviations from Hardy–Weinberg equilibrium (42 640 randomizations). Differences in pairwise FST and He were investigated with permutation tests in Fstat and in R with Wilcoxon signed-rank paired test. We also performed an analysis of power to detect genetic heterogeneity for the present 82 SNP markers . The relationship between genetic (FST/1-FST) and geographic distance (pairwise waterway in km) was investigated using a Mantel test and linear regression in R. We tested for differences in regression intercepts and slopes using the R packages emmeans and lsmeans::lstrends. Pairwise waterway distances were calculated using a distance matrix for a number of points on a uniform raster, using the R package gdistance and its function costDistance. costDistance calculates the shortest path between points on a raster where raster values represent landscapes ‘friction'. In our case, all cells with water had value 1 whereas all cells including land were set as NA; this yielded the shortest path between points (river estuaries) without crossing land.The program Fstat  v. 2.9.3wise FST . The samhylip [igTree V. 1.4 [A multidimensional scaling analysis (MDS) based on 82 SNP genotypes was performed using the adegenet package in R . A dendrhylip  and visue V. 1.4 . Bootstr(f)m) and local variance effective size per generation (Ne), following the method described by Wang & Whitlock [lne [Ne and m) were varied from G = 5 years in the south (Mörrumsån) to G = 7 in the north , with G = 6 for the 10 intermediate rivers. We similarly adjusted temporal time intervals between our focal samples to make them compatible between rivers, by accounting for if adults, smolts and/or parr had been analysed .We produced population-specific estimates of average immigration rate . The final dataset thus comprised 893 historical and 787 contemporary individuals . The overall genotyping error (drop out) rate based on samples run in duplicates was found to be well below 1% and thus unlikely to affect any of the inferences or conclusions in this study.Of the total number of individual samples analysed, 5.5%  and 1.7% (contemporary) were excluded due to an incomplete genotype (i.e. less than 95% loci genotyped). An additional 10 historical and 13 contemporary individuals were excluded following analysis with COutcomes of the various outlier tests carried out proved to be very sensitive to the parameter settings . Over all tests, a single locus (out of 82) appeared as potentially affected by directional selection under some test conditions. However, this locus was only identified as a putative outlier when historic or contemporary samples from Mörrumsån were included, and the outlier status of this SNP was not consistent across multiple genome scan approaches. In view of these observations, which suggested no strong and consistent selection at any loci, we retained all 82 SNPs for downstream statistical analyses.FIS values were significantly different from zero . However, only one sample, the historical sample from Luleälven (Lu_H), remained significant after correcting for multiple tests. Thus, we retained all 1680 individual samples for downstream statistical analyses.Across all 82 SNPs, a deviation from HW equilibrium was evident in five of 26 samples, as tructure [K = 9) based on the method described by Evanno et al. [p < 0.05). Three of those rivers, Luleälven (Lu), Dalälven (Da) and Mörrumsån (Mo), showed a decrease in the proportion of the historically dominating cluster (K = 7. For Luleälven (Lu), no dominating cluster was evident, and Ångermanälven (An) and Indalsälven (In) shared a dominating cluster .The model-based clustering analysis using Structure  providedo et al.  for all He) showed a temporal increase within all the pre-defined population groups, but this increase was only statistically significant when all samples were studied together , Rickleån (Ri) and Ljungan (Ln)) .Genetic diversity measured as expected heterozygosity (FST (historic versus contemporary) was noted when comparing all populations (A) and wild populations only (C) . By contrast, three large wild populations , Torneälven (To) and Vindelälven (Vi)) did not show any signs of genetic change. In line with pairwise allele frequency comparisons, global FST across populations and loci decreased over time in all pre-defined groups (A–D), although non-significantly . Power analysis showed that regardless of the number of samples and statistical method, power was 100% at FST = 0.015 (and above). When comparing two samples mimicking the present temporal comparisons, power was 80% at FST greater than 0.005 (for Chi2) and at FST greater than 0.009 (for Fisher's method) .Contemporary samples showed lower population divergence compared to historical samples. A significant decrease in average pairwise p < 0.05; linear regression, p < 0.05; Both historical and contemporary samples exhibited significant isolation by distance (IBD) patterns for all rivers (A) and for only wild ones (C and D)  and Mantel tests, thus underlining the overall reduction in population divergence in contemporary samples compared to historic ones (MDS based on a Neís genetic distance A matrix  and a nelne yielded effective population (Ne) point estimates in the range ca. 50 to 1000, with values corresponding to relative differences in river catchment size  and estimated potential productivity [Ne was surprisingly high (m) varied in line with the Structure results. For larger wild populations, estimated immigration rates were comparably low  while for smaller wild and reared populations m was considerably higher  compared to all other rivers  of our historical samples was collected in the 1920–1930s before large-scale development of hydropower production was initiated in the Baltic Sea area. In five of the studied rivers, this development peaked in the 1950s, which led to a diminishing wild salmon production that ended completely in the 1960–1970s ,64. To mStocking of young salmon  directly into wild rivers has also been performed in the Baltic Sea area during the last century, mostly in limited numbers . In some wild rivers, however, larger amounts of young salmon were released for assisting populations threatened by a combination of habitat destruction, health issues and a high fishing pressure. As an example, the wild salmon population in river Rickleån, which has shown remarkable genetic change over time, was considered depleted due to anthropogenic activities (pulp industry) in the 1950s. Substantial stocking efforts using salmon from several non-native populations were thus early initiated in this small river.delayed release  aimed aval rate , drasticAmong the studied wild populations, river Mörrumsån provides one example where elevated straying potentially could explain the observed temporal genetic change. There have been no documented releases with non-native salmon juveniles in this river. However, Mörrumsån flows into the southern Baltic Sea, and it is thus located very close to the main feeding area for most Baltic salmon populations ,67, whicet al. [During the last century, most wild Baltic salmon populations have experienced a sharp decline in abundance driven by habitat degradation  and hydret al. , who repSalmo trutta L.) [Onchorynchus kisutch) [Salvelinus fontinalis) [Oncorhynchus mykiss) [More generally, our findings are well in line with earlier studies reporting temporal declines in genetic divergence among populations of Baltic salmon ,70 and Autta L.) , coho sakisutch)  and brootinalis) . As obsetinalis)  and Cali mykiss) . The latIn summary, this study has revealed that large-scale hatchery and stocking practices have resulted in a partial breakdown of the genetic population structure of Baltic salmon during the past century, threatening the integrity of both wild and reared populations. As expected, we observed higher genetic resilience of large wild salmon populations which have been able to withstand genetic change by supporting a large number of native spawners in relation to immigrants. By contrast, most smaller wild populations and reared stocks experienced more severe genetic changes as a result of increased immigration stemming from a combination of genetic drift, past stock transfers and releases, and elevated straying by hatchery-reared salmon. As such, this work is among the first to document large-scale and long-term trends of human-induced genetic homogenization in salmonid fishes.Although the current results are generally not detailed enough to assess the relative importance of specific mechanisms associated with increased gene flow that have acted on specific populations , our findings are important. Genetic homogenization reduces one important aspect of intraspecific diversity. It further compromises individual and population fitness by disrupting local adaptations, at least in short to medium term, through the replacement of locally adapted alleles with non-adaptive ones, which is expected to reduce resilience to future environmental changes ,21,24. TA fundamental understanding of the mechanisms affecting levels of genetic diversity and genetic divergence between historical, remnant wild and hatchery populations is crucial for the establishment of effective conservation and restoration strategies. Our study demonstrates the dangers of human-invented mitigation strategies of rearing and releasing fish in nature, highlighting the importance of long-term monitoring and evaluation of human activities. Stocking of reared fish is common worldwide and our study should serve as a cautionary example of the potentially long-term negative effects of such activities, potentially hampering conservation and restoration of fish populations.Click here for additional data file.


Ulmus laevis, is highly affected. This phenomenon is particularly relevant at the margins of the natural habitat of the species, where populations are small and rare. In these cases, it is difficult to distinguish between relics or introductions, but it is relevant for the restoration of natural habitats and conservation strategies. The aim of this study was to study the phylogeography of the southern distribution of the species. We sequenced the entire chloroplast (cp) genomes of 54 individuals from five sampled populations across different European regions to highlight polymorphisms and analyze their distribution. Thirty-two haplotypes were identified. All the sampled populations showed private haplotypes that can be considered an indicator of long-term residency, given the low mutation rate of organellar DNA. The network of all haplotypes showed a star-like topology, and Serbian haplotypes were present in all branches. The Balkan population showed the highest level of nucleotide and genetic diversity. Low genetic differentiation between populations was observed but we found a significant differentiation among Serbia vs. other provenances. Our estimates of divergent time of U. laevis samples highlight the early split of above all Serbian individuals from other populations, emphasizing the reservoir role of white elm genetic diversity of Serbian population.Riparian ecosystems, in long-time developed regions, are among the most heavily impacted by human activities; therefore, the distribution of tree riparian species, such as  Modern biodiversity conservation strategies rely, or at least should, on the knowledge of genetic resources . Big effUlmus laevis Pall. = Ulmus effusa Willd. = Ulmus pedunculata Foug.) is a characteristic deciduous temperate forest tree species growing in river margins and lowland moist forests, and it can also tolerate dry soils of wooded steppe habitat in the central parts of the distribution. Seeds are generally anemochorous, but in the riparian habitats, hydrochory is an important means of transport, enabling long-distance dispersal   , a lethal disease caused by some non-native species of the genus mericana . U. laevvo-ulmi) , but it U. minor . It is sd by DED . EWE poppromised . This hapromised . In westTypically, only populations that are recognized as native are included in the conservation process, while those that are considered introduced or have an uncertain status are not protected, which are excluded from regional Red Lists of the International Union for Conservation of Nature, even if they are rare and endangered . The genUlmus were based predominantly on neutral markers  investigate whether Italian stands of white elms are natural or the result of anthropogenic introductions, and (c) discuss, in the light of new outcomes, the consequences for conservation and management strategies for this species.Here, we aim to (a) explore the genetic structure of U. laevis were collected in four areas and included in the natural range of the species: two in France (southwest and northeast), one in Spain, and one in Serbia.1 In addition, U. laevis samples were collected in northwestern Italy  on an Illumina HiSeq 4000 platform . Illumina reads were trimmed using Trimmomatic  with thesion 3.7  with thaeference  and the th GeSeq  and BLASth GeSeq  analysish OGDRAW .GST and NST  in comparison with GST (that measure the only frequency of haplotypes) are obtained.Plastid sequences were aligned using MAFFT version 7 , and thePT, an analog of FST) subdivided into variation among populations and among individuals within populations was evaluated by a permutation test (n = 999). The software GenAlEx was used to perform principal coordinates analysis (PCoA), and then plotted in R with the package ggplot2  were aligned using MAFFT version 7.308 (U. laevis populations. The plastome phylogeny was inferred by applying the Bayesian inference (BI) method using the program BEAST2 version 2.6.3.0 ; (3) crown age of Zelkova was constrained to be 54.53 Mya ; (4) crown age of Hemiptelea was set to 72.59 Mya ; and (5) split between Ulmus americana and U. laevis was constrained to 17.5 Mya. The Bayesian posterior probabilities were sampled using the MCMC algorithm, which was run for 3.0 × 108 generations and sampled every 1,000. The stationarity of the chains and convergence of MCMC simulations were monitored using Tracer version 1.7.1 (The cpDNA sequences of 54 on 7.308 . We crea 2.6.3.0 . The tra 2.6.3.0 . After p 2.6.3.0 : (1) we on 1.7.1 , analyzion 1.7.1 , settingon 1.7.1 .Ne) through time for the five populations, applying a non-parametric analysis based on the coalescence theory to cpDNA genome alignments for each population separately. The Bayesian skyline plot (BSP) approach was employed with the TMV substitution site model using a relaxed lognormal molecular clock with rate 1.0 and running 3.0 × 108 MCMC simulations using the software BEAST2.We estimated the effective population size  content of 35.6%, and its map had the typical quadripartite structure of angiosperms, including two inverted repeats (IRs) of 26,424 bp separated by a large single copy (LSC) of 87,594 bp and a small single copy (SSC) of 18,644 bp , and 1 non-synonymous mutation in the rpoC1 gene .The alignment of the 54 cp genomes highlighted 190 nucleotide polymorphisms (14 SNPs and 176 indels). Most of the polymorphisms were neutral, and only 14 of these variations (6 SNPs and 8 indels) were in annotated regions. We found 3 mutations (SNPs) into coding sequences, 2 causing synonymous mutations (in –5) was low and ranged from the higher value 2.439 × 10–5 in Serbia to 0 in Spain, where all variants were indels. A comparison of diversity indices obtained with SNPs and indels is reported in All the polymorphisms allowed identifying 32 haplotypes . Twenty-The median-joining network of all haplotypes  showed aHT = 0.960), but the largest part of cpDNA variation was found within the populations (HS = 0.922). The analyzed U. laevis populations showed the low levels of population differentiation (GST = 0.050). Low but significant differentiation was observed among the pairs Italy–Serbia, Spain–Serbia, and Spain–Italy  were obtained, which did not correspond to the populations. The analysis with BAPS did not display a strong genetic structure along the western part of the sampled species distribution, and two major clusters contained individuals from all four populations ; nevertheless, two clusters were represented only in Serbia: one with few individuals and the other one included only one individual  and another one composed of other samples (clade II) . The mol studies , being aNe) are shown in the four Skyline plots in Ne) just after the coalescence, while no significant changes in Ne were observed in the other populations. French (NE and SW) and Italian populations share a stable ancestral size.Profiles for the effective population size  the unexplored glacial refugium in the Balkan Peninsula and (ii) whether small Italian stands in the north-west  are relic native ones or allochthonous.This study sought to explore the genetic structure of the species U. laevis was recently sequenced  (Considering that the mutation rate of organellar DNA is remarkably low (the mutation rate of cpDNA is in the order of 1.3 × 10–9) , private–9) . InteresThe high number of private haplotypes is reflected in the haplotype network that, alongside the star-like structure, has many tips. The central haplotype, haplotype I, common to France_SW and Italy, should represent the most ancient condition, according to the coalescent theory , while mU. laevis during the Pleistocene climate oscillations. Multiple refugia have been inferred in the Balkan Peninsula for many animals and plants during the Pleistocene glacial periods , while the overall observed genetic structuring could be originated by the accumulation of mutations in different refugia followed by recent population expansion. Consistent with these observations are the results of BSPs used for inference of coalescence patterns , which iAccording to Although the connection with Balkan refugia still needs deeper investigation, unfortunately, there are no warnings about the presence of white elms on the northeastern part of Italy, but long-range dispersal cannot be ruled out.In support of our hypothesis, there are also arguments linked to the ecology of the species and the habitat transformation: most of the sampled trees were at the margin of high intensively cultivated areas close to rivers or scattered not far from such small stands. The area where we hypothesized a native presence of white elms, on the western side of the Po valley, experienced a high rate of population growth since the Neolithic Age. During the Roman Age, an extensive deforestation occurred, due to the assignment of land grants to war veterans, and continued in different ways till nowadays . The proU. laevis is largely congruent with other previously studied European species, such as Hordelymus europaeus and Fagus sylvatica and another riparian tree, Alnus glutinosa (The pattern of genetic diversity observed in lutinosa ; in partU. laevis, this study, to the best of our knowledge, for the first time extended the population genetic analysis of EWE to Italian and Balkan populations, revealing probably the main refuge of the species during the last glaciation. In addition, we extended the natural range of U. laevis in Europe to northwestern Italy and highlighted their small size and fragmentation and also at risk. The risk comes more from population size and habitat erosion than from DED; anyway, proper management practices become important to preserve these small stands with both in situ and ex situ actions to preserve and hopefully restore riparian ecosystems.Although more intensive sampling of the European populations in combination with nuclear genotyping is needed to give a more complete picture of the phylogeography of https://www.ncbi.nlm.nih.gov/genbank/, PRJNA777116.The datasets presented in this study can be found in online repositories. The name of the repository and accession number can be found below: FS and ASa conceived the study. ST, FS, IP, and AP conducted all laboratory and population genetics analyses. GB, FP, ASa, LG, and ASe collected the samples. ST and FS led the writing of the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Our exploration of the genetic constitution of Nuku Hiva (n = 51), Hiva Oa (n = 28) and Tahuata (n = 8) of the Marquesas Archipelago based on the analyses of genome-wide autosomal markers as well as high-resolution genotyping of paternal and maternal lineages provides us with information on the origins and settlement of these islands at the fringe of the Austronesian expansion. One widespread theme that emerges from this study is the genetic uniformity and relative isolation exhibited by the Marquesas and Society populations. This genetic homogeneity within East Polynesia groups is reflected in their limited average heterozygosity, uniformity of constituents in the Structure analyses, reiteration of complete mtDNA sequences, marked separation from Asian and other Oceanic populations in the PC analyses, limited differentiation in the PCAs and large number of IBD segments in common. Both the f3 and the Outgroup f3 results provide indications of intra-East Polynesian gene flow that may have promoted the observed intra-East Polynesia genetic homogeneity while ALDER analyses indicate that East Polynesia experienced two gene flow episodes, one relatively recent from Europe that coincides roughly with the European incursion into the region and an early one that may represent the original settlement of the islands by Austronesians. Median Network analysis based on high-resolution Y-STR loci under C2a-M208 generates a star-like topology with East Polynesian groups  in central stem positions and individuals from the different populations radiating out one mutational step away while several Samoan and outlier individuals occupy peripheral positions. This arrangement of populations is congruent with dispersals of C2a-M208 Y chromosomes from East Polynesia as a migration hub signaling dispersals in various directions. The equivalent ages of the C2a-M208 lineage of the populations in the Network corroborate an east to west flow of the most abundant Polynesian Y chromosome. It is approximated that at the time of first contact about 80,000 people inhabited the Marquesas located about 1,500 km northeast of Tahiti2  signals from Taiwan in East Polynesia, clear contribution from Tonga and Samoa in West Polynesia is observed4. This robust connection between East Polynesia with West Polynesia is corroborated by high-resolution autosomal STR markers17. These genetic affinities seen in the structure analysis are diluted out in Vanuatu and Bougainville (Solomon Archipelago) located further west. In the islands of Sulawesi, Timor and Sumba of Indonesia the main structure component of West and East Polynesia are only minor constituents4. These observations are consistent with bottleneck, founder effect and genetic drift processes that likely culminated in the fixation of only two components in East Polynesia 19. Starting in the Solomon Islands, the frequency of haplogroup B (75%) exhibits a clinal increase from west to east3 while the B4 subhaplogroup accounts for almost all individuals within B in Fiji and B4a1a, B4a1a1a and their sublineages predominate in West Polynesia20. In Central Eastern Polynesia (Cook Islands) there is an increment in the B4a1a1m, B4a1a1m1 and B4a1a1c lineages compared to West Polynesia3, the later almost fixed in Marginal Eastern Polynesia (the Hawaiian Islands). In the Society Islands of East Polynesia, all mtDNAs are B4a1a1, most of the subhaplogroups belonging to the B4a1a1m1 and B4a1a1c lineages seen in Central Eastern Polynesia as well as a number of unique lineages such as B4a1a1k, B4a1a1t and B4a1a1a22. In Marginal Eastern Polynesia, all Maori of New Zealand are B4a1a1 and previously seen sublineages B4a1a1a and B4a1a1c as well as novel subhaplogroups such as B4a1a1a3 and B4a1a1a520. The observed pattern of gradual diminution of genetic heterogeneity, fixation of specific subhaplogroups and the appearance of unique ones are indicators of random bottlenecks and founder events that marked the settlement of Eastern Polynesia out of Western Polynesia.Similarly, mtDNA markers in Polynesia exhibit strong affinities with ISEA and Taiwan, congruent with archaeological models4 while the Asian ancestry seen in the Y chromosome is made up mainly by O3-M122 and its sublineage O3a’i-P164 which constitutes 54% in Tonga, West Polynesia and 19% in the island of Taha’a of East Polynesia4.The phylogenetic signals provided by the Y chromosome in Polynesia are very different from the mtDNA indicators, with Melanesia lineages  predominating at frequencies ranging from 57 to 81% with no striking demic changes observed in any direction. In West Polynesia C2a-M208 is the most abundant lineage reaching 71% in the Samoan island of Manua and 81% in the Society island of Taha’a in East PolynesiaThe Marquesas Islands are the eastern-most archipelago of East Polynesia representing the extreme of a continuum of Pacific islands settled by Austronesian. As such, they provide us with the opportunity to examine the underlying mechanisms that led to their settlement from a genetic perspective. It also allows us to shed light on the origins of the population and the timing of their settlement. With this in mind, we provide information and analyses based on genome-wide autosomal as well as high-resolution genotyping of paternal and maternal lineages. In this study we aim to test if this group of islands at the eastern fringe of East Polynesia represents a population derived from West Polynesia whose genetic constitution was shaped by repeated bottleneck and founder effect events that have led to random drift and homozygosity.Buccal swabs were collected from a total of 87 unrelated male individuals from Nuku Hiva (n = 51), Hiva Oa (n = 28) and Tahuata (n = 8) in the Marquesas Archipelago of French Polynesia. As of 2017 the populations of these three islands were 3120, 2190 and 653, respectively. The samples were collected throughout the islands. Genealogical information was gathered for a minimum of two generations to confirm the descent of potential donors. Individuals were questioned to verify lack of familial links to other donors. Buccal swabs were processed utilizing the Gentra Buccal Cell Kit  according to the manufacturers' specifications.21. All samples were procured from donors voluntarily with informed consent while closely adhering to the ethical guidelines stipulated by Colorado College, Colorado Springs, Colorado USA and following the ethical principles and guidelines of the Declaration of Helsinki for the protection of human subjects. The IRB of Colorado College and the Research Ethics Committee of the University of Tartu, Estonia approved this study.NanoDrop 1000 Spectrophotometer (Thermo Scientific) was used for DNA quantitationReference populations were employed for comparison across the mtDNA, Y-chromosome STR and autosomal SNP markers examined. The geographical locations, abbreviations used to define populations throughout the article, number of individuals and references are provided in Supplementary Table https://www.ncbi.nlm.nih.gov/ under accession numbers MT135508 – MT135515. The Y-chromosome data have been successfully submitted and are now included in the YHRD database at https://yhrd.org/ under the following accession numbers: Nuku-Hiva YA004253; Hiva-Oa YA004254. The eight donors from the island of Tahuata were reported as part of the Hiva-Oa population due to the geographical proximity of the two islands. The GenBank accession numbers for the SNP data are GSM5736361 – GSM5736384.Eight novel complete mtDNA sequences are available online in GenBank at https://technelysium.com.au/wp/chromaspro/). The examined Y chromosomal biallelic markers examined were M45, M175, M122, P201, JST002611, P164, M188, Page 125, Page23, B451, B450, B435, F16950, M119, M110, B398, M110 (xB398), F31, F343 (xB386), F819 and B390. We designed primers for P164, M188, Page 125, Page23, B435, F16950, B398, M110 (xB398), F31, F343 (xB386), F819 and B390 using Primer3 software23. The designations of the Y chromosomal biallelic markers follow that of Karmin, et al.24. The specificity of the primers was checked with Primer-BLAST25 and GenomeTester v.1.3 software26 in silico and verified by Sanger sequencing. The O1 and O3 markers genotyped and the primer sequences designed for PCR amplification and sequencing are found in Supplementary Table All Nuku Hiva (n = 51), Hiva Oa n = 28) and Tahuata (n = 8) chromosomes were genotyped using PCR and subsequent Sanger sequencing or restriction fragment length polymorphism analysis. Sequencing results were viewed in ChromasPro 2.1.8  analysis was performed using PROXSCAL28 included in the SPSS version 20 statistical package .Allelic frequencies for a total of 27 loci , and Y GATA H4) were accessed using the Yfiler plus multiplex PCR system . Amplification reactions were performed in an ABI PRISM GeneAmp 9700 Silver block Thermal Cycler (Life Technologies) using the 9600 emulation mode for 30 cycles. All analyses used the internal lane standard and the allelic ladder mix provided by the Y27-STR Yfiler plus system. PCR products were separated and detected on an ABI PRISM 3130xl Genetic Analyzer (Life Technologies) following manufacturer's specifications using the LIZ-120 internal size standard as a basis for comparison. Fragment sizes were assigned using the software GeneMapper v3.1  and alleles were designated by comparison to an allelic ladder supplied by the manufacturer (Applied Biosystems). Slatkin’s linearized Rst valueshttp://www.fluxusengineering) in which the Y-STR markers were weighted inversely to their repeat variance and the Maximum Parsimony (MP) option was employed to produce the least complex topology.The 15-loci Y-STR haplotypes of Hiva Oa and Nuku Hiva from the Marquesas Archipelago, Rai’atea and Bora Bora from the Society Archipelago, American Samoa, Maoris and Ontong from the Solomon Archipelago belonging to the C2a-M208 sub-haplogroup were used to generate a Median-Joining Network (NETWORK 4.5.1.6 at ρ)29 and weighted rho (ρW)30 were estimated with an R script available in GitHub . The number of repeats at DYS389II was calculated after subtracting the number of repeats at DYS389I. Mutation rates were obtained from the Y-Chromosome STR Haplotype Database  on March, 2020.Y-STR haplotypes were used to estimate the time to the most recent common ancestor (TMRCA) of the C2a-M208 sub-haplogroup in the populations examined in the Median-Joining Network analysis. With this aim, rho statistic (31 using rCRS (https://www.mitomap.org/MITOMAP/HumanMitoSeq) as a reference sequence32 and ISFG guidelines35. For sequence alignments the software package ChromasPro  was used. Nomenclature followed that of Phylotree. org, mtDNA tree Build 1734. A phylogenetic tree based on complete mtDNA sequences was generated using HaploGrep236.The DNA extracts of four Nuku Hiva, three Hiva Oa and one Tahuata were genotyped for mitochondrial haplogroups by complete mtDNA sequencing using Sanger sequencing and following the protocol ofThe mitochondrial haplogroup data was analyzed in conjunction with other from reference populations from Taiwan and the Society Islands of French Polynesia.A set of 713,014 single nucleotide polymorphisms (SNPs) was screened in nine Nuku Hiva, nine Hiva Oa and six Tahuata healthy unrelated individuals using the Illumina OmniExpress Bead Chips array. For comparative purposes, a dataset of 701 samples from 49 previously published reference populations . Using cross-validation procedures, we found that at K = 12 the cross-validation error was the lowest  were used to test for admixture involving the reference populations. Significant positive values in the f4 analysis would mean that population 1  shares ancestry with a given test population while significant negative values would indicate that population 2  shares ancestry with the test population. Nonsignificant values would mean that Nuku Hiva and Tahuata, Hiva Oa and Nuku Hiva or Hiva Oa and Tahuata are equally related to the Test population. In addition, the outgroup f3 test was implemented as a measure of the shared branch length between each of the three Marquesas populations and all the other populations. For outgroup in the f3 test, the Yoruba population from West sub-Sahara Africa was employed.A series of three- and four-population tests were performed with ADMIXTOOLS-143 was used first to phase and then to run Refined identity-by-descent (IBD)44 analyses, where we studied the sharing of DNA segments of IBD between the Nuku Hiva, Hiva Oa or Tahuata and the reference populations in our dataset. From the results, we extracted the count of segments shared between every two individuals and found population medians for 0–1 cM, 1–2 cM and > 2 cM segments to find patterns.Beagle 3.3.2In this report we provide a new genomic dataset from the Nuku Hiva, Hiva Oa and Tahuata Islands of the Marquesas Archipelago in French Polynesia. The information includes high-resolution autosomal SNP genotyping data from 24 individuals . In addition, we report the complete mtDNA of four Nuku Hiva, three Hiva Oa and one Tahuata individuals as well as the haplogroups of 51 Nuku Hiva, 28 Hiva Oa and eight Tahuata Y chromosomes. High-resolution Y-STR haplotypes were generated and utilized to assess male-driven relationships among Nuku Hiva, Hiva Oa and Tahuata Islands and key geographically targeted reference populations. Median Network analysis based on Y-STR loci was used to examine the relationship of C2a-M208 individuals in key Polynesian populations and outliers. The totality of the dataset is analyzed together with publicly available data from populations from MSEA, ISEA, Melanesia and Polynesia  . In some of the reference populations such as the Ami and Yami aborigines of Taiwan, the Igorot of the Philippines and the Dusun and Murut of Brunei this component represent the entire genome. This DNA element is about 80% of the Marquesas and Society DNAs. The other constituent (purple) representing approximately 20% of the genome of the Marquesas and Society genomes is likely of Papuan/Melanesian origin representing about 70–100% of their DNA. This purple element is also 80% of the Australian aboriginal genome. In addition to the characteristic predominant purple element of Papuans/Melanesians, the population from Melanesia also exhibits the ISEA/East Asia component (~ 30%). In addition, a number of Marquesas and Society individuals exhibit minor amounts of a red signal likely of European origins likely resulting from recent admixture. At higher K values (K = 5–18) all East Polynesian populations adopt a single deep blue component with some individuals exhibiting traces of Papuan/Melanesian (light blue), ISEA/East Asian (aquamarine and/or light cream) and /or European (red) ancestry. No additional elements are seen in the Marquesas and Society after K = 5. Greater resolution of components within the Structure analysis at K = 12 is provided in Fig. The admixture analysis based on the autosomal SNP data indicates homogeneity in the genetic constitution among the islands of the Marquesas and Society Archipelagos examined at all the 18) Fig. A. The lolues K = –18   segment sharing between Hiva Oa Fig.  Nuku Hiv4. Furthermore, B4a1a1c and B4a1a1m1, the most frequently detected sub-haplogroups in the Marquesas are also the most abundant in the Society populations of Bora Bora, Rai’atea, Taha’a4.Complete mtDNA sequencing of four Nuku Hiva, three Hiva Oa and one Tahuata individuals were performed , O3a’1-P164  and O3′6-M324 . In addition, other haplogroups such as R1b1′12-M269 (European origin), G-M201 (European origin), I-M170/M258 (European origin), K-M9 (Melanesian origin) and Q-M242 (Asian origin) were detected mostly at minor frequencies and only in specific islands: R1b1′12-M269, 3.9% in Nuku Hiva and 3.6% in Hiva Oa; G-M201 7.1% in Hiva Oa; I-M170/M258, 13.7% in Nuku Hiva; K-M9, 28.6% in Hiva Oa and Q-M242, 9.8% in Nuku Hiva. This uneven distribution of markers from different sources suggests that complex differential patterns of migrations likely involving drift and/or founder effects impacted the islands of Nuku Hiva, Hiva Oa and Tahiti.The most abundant Y chromosomal haplogroup in the Marquesas Islands of Nuku Hiva, Hiva Oa and Tahuata is C2a-M208   are represented by two individuals each. The limited genetic diversity that is seen in the populations of Hiva Oa, Nuku Hiva and Tahuata likely derives from repeated bottleneck episodes, genetic drift, founder effects and inbreeding since the settlement of the islands.10. Except for one individual from Bora Bora that segregates with the Bajo of Indonesia, most of the samples from the Marquesas and Society Islands plot into a distinctly separate and tight cluster with a number of them radiating out towards a Indonesian-Filipino conglomerate. Nevertheless a gap is evident between the East Polynesians and the Filipino-Indonesian cluster. This topological relationship suggests a level of phylogenic discontinuity between the East Polynesians and the ISEA populations as well as a degree of isolation of the former. The limited intermingling of individuals from the Marquesas and Society Islands within this tight clutch also indicates genetic homogeneity and lack of sub-population structure among them. The age estimations of the most abundant C2a-M208 lineage of the Y-chromosome in the Marquesas and Society populations examined are recent and comparable  individuals with this sub-haplogroup.Supplementary Legends.Supplementary Figure 1.Supplementary Figure 2.Supplementary Figure 3.Supplementary Figure 4.Supplementary Figure 5.Supplementary Figure 6.Supplementary Figure 7.Supplementary Figure 8.Supplementary Figure 9.Supplementary Table 1.Supplementary Table 2.Supplementary Table 3.Supplementary Table 4.Supplementary Table 5.Supplementary Table 6.Supplementary Table 7.Supplementary Table 8.Supplementary Table 9.Supplementary Table 10.Supplementary Table 11.Supplementary Table 12.Supplementary Table 13.Supplementary Table 14.Supplementary Table 15.Supplementary Table 16.Supplementary Table 17.Supplementary Table 18.Supplementary Table 19.Supplementary Table 20.Supplementary Table 21.Supplementary Table 22.Supplementary Table 23.Supplementary Table 24.Supplementary Table 25.


Hyalomma  lusitanicum in Andalusia (the south of the Iberian Peninsula) were examined using mtDNA sequence data from 887 bp of cytochrome oxidase subunit I (COI) gene. The sequence for the COI region was determined for 84 individuals collected in several localities of Andalusia, and 10 for other localities  and one from Canary Island). Seventeen haplotypes were detected, including 27 polymorphic sites. The number of amino acid substitutions per site from mean diversity calculations for the entire population was 0.017. AMOVA analysis revealed a low gene flow that characterises the genetic population structure of this species in South Iberian Peninsula, with a haplotype diversity (h) value of 0.815. No geographically induced differentiation was observed, and separate evolutionary units were not detected. Our results indicate low genetic diversity across the geographical range of H. lusitanicum tick in Andalusia. Our data do not show any genetic discontinuity between the tick populations studied, including specimens from Canary Island and Sicily .The genetic population structure relationships of  Hyalomma lusitanicum Koch has been included in the ‘anatolicum’ group, together with several species and subspecies   in central Iberian Peninsula  in the centre and southwest of the Iberian Peninsula in various species of ungulates  and associated tick species Hyalomma genus are very scarce and partial in the taxonomic and geographical scopes. More recently, the use of mtDNA sequences to study the phylogenetic relationships and evolutionary history of Eurasian and African Hyalomma species has been advocated   Fig. . After cly) Fig. .Fig. 1MaTicks were kept individually, rinsed with distilled water, dried on sterile filter paper and then crushed in sterile Eppendorf tubes. DNA was extracted using a DNA tissue kit according to the manufacturer’s instructions . During DNA extraction, we included sterile water as a negative control using a ratio of one control for every 15 samples. DNA extracts were stored at −20 °C until further processing.2, 0.033 U of Biotaq DNA polymerase in 1 × PCR ammonium buffer , and sterile distilled water to a final volume of 80 μL. PCR cycles included an initial 90 s denaturation step at 96 °C, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 48 °C for 30 s, and extension at 72 °C for 50 s. Amplification was completed by holding the reaction mixture at 70 °C for 7 min to allow complete extension. PCR products were resolved by electrophoresis in 1.5% SeaKem agarose  in 1 × buffer Bionic gels  using a 100 bp ladder as molecular weight marker . Products containing positive results were purified by using the Montage PCR kit  prior to sequencing. Negative controls were further processed by PCR as tick specimens. In order to reduce the risk of contamination no positive controls were used.A 887-bp fragment of the cytochrome oxidase subunit I (COI) gene was amplified and sequenced for each specimen. PCR amplifications were carried out in a MJ Mini Personal Thermal Cycler  using the primers hylCOIfor 5′-AATTTACAGTTTATCGCCT and HylCOIrev 5′-CATACAATAAAGCCTAATA . Each PCR mixture consisted of the following: 4 μL of DNA, 20 pmol of each primer, 200 µM of dATP, dCTP, dTTP, dGTP, 2.0 mM MgClDrosophila melanogaster using the UCSC (https://genome.ucsc.edu/cgi-bin/hgBlat)—both the forward and reverse primers did not display homology with any nuclear sequence. Second, the software Blast Primer (https://www.ncbi.nlm.nih.gov/tools/primer-blast) did not predict any amplification from the Ixodes scapularis nuclear genome.For the purpose of checking for potential amplification of nuclear mitochondrial paralogs (numts)   and a CEQ 2000XL capillary DNA sequencer (Beckman Coulter) according to the manufacturer’s instructions. In addition to forward and reverse primers two internal primers (HylCOIfor2 5′-GGATAACAATAGAACGTATAC and HylCOIrev2 5′-CAGTTCCTGCTCCTGATC) were used to read terminal regions. The forward and reverse sequences obtained were assembled into contigs with the program Bioedit v.7.0.1 Hall . The reswww.megasoftware.net; Kumar et al. The COI gene region was nearly length invariant for all the samples, making alignment trivial. Nucleotide variation and substitution patterns were examined using the software package MEGA7  networks algorithms   for the tree was 0.875 and the retention index (RI) 0.952. The frequencies obtained for each haplotype and the population of origin are represented in Fig. Because of unequal sample sizes, it is not always possible to compare the genetic diversity obtained from distinct geographical regions. Higher genetic variability is expected in source populations. Haplotypes 2 and 7 were present in four of the Iberian Peninsula sites plus in Canary Island (ht 2) and Sicily (ht 7) Table . Seven hsH) is due to differences within the five sites considered.The AMOVA analysis Table  indicateThe graph representing the phylogenetic network visualizes population relationships defined by haplotypes separated by a maximum of 13 mutations (Fig. H. lusitanicum in Andalusia. No genetic discontinuity is apparent between the tick populations, including specimens from Canary Island and Sicily.Our mitochondrial data indicate low genetic diversity across the geographical range of Hyalomma ticks based on their evolutionary history in relation with tectonic events and large-scale environmental changes registered during a long period, with a divergence time around 10 million years ago. In this context, H. lusitanicum occupied a marginal area of distribution in the Iberian Peninsula and a scarce number of historically related island territories. The presence of this species out of this area is mainly anecdotic (Santos-Silva Sands et al.  show a pH. lusitanicum haplotypes is the result of a long interaction of this species with its natural hosts. However, the current distribution of the various haplotypes has been influenced by anthropogenic action, manifested as habitat modification and the introduction of new host species through domestication (Hoberg and Brooks H. lusitanicum. Migratory movements also represent a unique dispersal mechanism (Bauer and Hoyer Hyalomma species, as has been hypothesized by Estrada-Peña et al. (H. marginatum. Wild fauna displacements, megafauna disappearance in southwest Europe (Malhi et al. The distribution of a et al. , b for H


Channa gachua) on Hainan Island and mainland China, as well as two populations in Vietnam. We attempted to elucidate the origins of freshwater fish in South Hainan by incorporating genetic data from DNA markers on both the mitochondrial cytochrome b gene (cyt b) and the nuclear recombination‐activating gene 1 (RAG‐1). Mitochondrial phylogenetic analysis identified two major lineages (lineages A and B), which may represent separate species. Divergence data suggested that C. gachua populations diverged between 0.516 and 2.376 myr. The divergence of the two cryptic species is congruent with sea‐level rise, which subsequently isolated Hainan from the mainland. During the Pleistocene glaciations, the entire region of the Gulf of Tonkin and the Qiongzhou Strait became part of the coastal plain of the Asian continent, which might have resulted in the current distribution patterns and dispersal routes of C. gachua populations. The formation of three sublineages in lineage A indicated that the Gulf of Tonkin was a geographical barrier between Hainan Island and mainland China but not between Vietnam and Hainan Island. The results of this study may help to elucidate the origins of freshwater fish in South Hainan and the phylogeographic structure of C. gachua.Geological events, landscape features, and climate fluctuations have shaped the distribution of genetic diversity and evolutionary history in freshwater fish, but little attention has been paid to that around the Gulf of Tonkin; therefore, we investigated the phylogeographic structure of the dwarf snakehead ( C. gachua populations.During the Pleistocene glaciations, the entire region of the Gulf of Tonkin and the Qiongzhou Strait became part of the coastal plain of the Asian continent, which might have resulted in the current distribution patterns and dispersal routes of  Accordingly, the species of Hainan Island might originate from the north (China) or west (Vietnam). However, to the best of our knowledge, there is no research on the population relationship between North Vietnam and Hainan Island. Therefore, we propose investigating whether the freshwater fish in southwestern Hainan Island and the freshwater fishes of the Red River in mainland China belong to the same fish zoogeographical region. The above studies reflect that the freshwater fishes of Hainan Island may not have a single origin, but due to the lack of information on freshwater fishes in northern Vietnam, the relationship between freshwater fish in Vietnam and Hainan has not been studied. Therefore, the phylogenetic process of freshwater fish on Hainan Island has not been effectively and reasonably explained. To date, there have been no comparable data on freshwater fish from geographically separated populations between Hainan Island and the Red River, although such data will provide additional insights into the phylogeographic history of the species and contemporary factors shaping the population genetic structure and supporting the implementation of effective management and conservation strategies for freshwater fish.In addition, some studies have shown that freshwater fish on Hainan Island may have originated in northern Vietnam in the west, rather than in southern China in the north  belongs to the order Anabantiformes, family Anabantiformes, and genus Channa, and is a freshwater fish restrictively distributed in various water systems of the Hainan Island zoogeographical region and Nujiang–Lancangjiang zoogeographical region in China but is primarily distributed in Nepal, the Indian subcontinent, Afghanistan, and Southeast Asia abroad  cytochrome b gene (cyt b) and nuclear gene rag 1 region (RAG‐1) to establish the phylogeographic patterns in South China and northern Vietnam. There are two major questions investigated by our study: (1) What is the genetic diversity and genetic structure of C. gachua? and (2) How did C. gachua colonize the rivers of different geographical districts on Hainan Island? Whether the freshwater fish in southwestern Hainan Island and the freshwater fishes of the Red River in mainland China belong to the same fish zoogeographical region has not been elucidated. The results of this study may help to elucidate the population genetic structure of C. gachua that may contribute to conservation, management, and sustainable utilization of freshwater fish on Hainan Island and may also help to provide context for other threatened endemic fish species in the same or similar river systems.22.1b gene and nuclear gene RAG‐1 region were amplified by polymerase chain reaction (PCR) using primers L14724 (5’‐GACTTGAAAAACCACCGTTG‐3’) and H15915 (5’‐CTCCGATCTCCGGATTACAAGAC‐3’) . The PCR program run on a thermal cycler (Eppendorf Mastercycler) was as follows: one cycle of denaturation at 94°C for 2 min, 35 cycles of denaturation at 94°C for 45 s, annealing at 50–55°C for 45 s min, and extension at 72°C for 1 min 15 s followed by extension at 72°C for 10 min and holding at 4°C for storage. The purified PCR products were sequenced by Sangon Biotech Co., Ltd. (Shanghai) using an ABI PRISM 3730XL sequencer  with the BigDye Terminator Kit (Applied Biosystems). The chromatograms were assessed using CHROMAS software , and the sequences were manually edited using BIOEDIT 6.0.7 , 9.5 μL ddH.7 Hall, .2.2b gene and RAG‐1 gene were aligned with Clustal X v2.1  and nuclear genes (RAG‐1) were the GTR + G + I model using the Akaike information criterion (AICc) in SMS (Smart Model Selection in PhyML)  by running 106 generations. We employed TreeAnnotator v.2.2.1  for theta and G  for tau. We ran the MCMC analyses for 500,000 generations, sampled every five generations, and discarded samples from the first 50,000 generations as burn‐in. Each analysis was repeated at least twice to confirm consistency between runs. Topology based on Cyt b was used as a guide tree. We used the A10 model  and the species tree of the BEAST analyses (see below) as a user‐specified guide tree , haplotype diversity (h)   following the method of Pons and Petit  by Arlequin version 3.5 , within‐group (FSC), and among‐group (FCT) components to evaluate the most likely population configuration and geographical subdivision with K2P distance and 20,000 permutations. The table was prepared using R v.3.2.4. For the hierarchical analysis, populations according to the different geographical barriers were grouped together to investigate the potential effects of various geographical barriers: (1) Two geographical groups were primarily divided by the Gulf of Tonkin: Hainan Island + Vietnam and mainland China; (2) two geographical groups were primarily divided by the Gulf of Tonkin: Hainan Island and Vietnam + mainland China; (3) three geographical groups were divided according to the three geographical regions: Vietnam, Hainan Island, and mainland China; and (4) four geographical groups were primarily divided by the WY Range in the Hainan region, Vietnam, and mainland China. The program SAMOVA  when the program was instructed to identify K = 2–6 potential population units.The genetic diversity of each population was estimated by using the number of haplotypes  and mistest Fu, . BayesiaC. gachua, ancestral areas were reconstructed using statistical dispersal–vicariance (S‐DIVA) in RASP 3.2  the mainland China region ; (2) the southern Hainan region ; (3) the northern Hainan region ; and (4) the Vietnam region (V: V1 and V2).To further discover the historical biogeography of 33.1b gene sequences from 336 specimens and 1,194 base pairs (bp) of nuDNA RAG‐1 gene sequences from 329 specimens were analyzed. All sequences of the nuDNA RAG‐1 gene were phased, and the final datasets with inferred phased sequences consisted of 658 sequences for C. gachua. The obtained sequences were deposited in GenBank under accession numbers for cyt b: MW233899‐MW233949 and for RAG‐1: MW233950‐MW234070. The nucleotide sequences in the mtDNA cyt b gene were A + T‐rich (55.5%), which consisted of 13.8% guanine, 25.3% adenine, 30.2% thymine, and 30.7% cytosine, and the nuDNA RAG‐1 gene was not A + T‐rich (45.8%), which consisted of 27.8% guanine, 26.4% adenine, 21.9% thymine, and 23.9% cytosine. A total of 51 haplotypes  in the mtDNA cyt b gene and a total of 122 haplotypes  in the nuDNA RAG‐1 gene were obtained. Among the 51 haplotypes, only five  were shared by populations SN2, SN3, SN4, and NN3 on Hainan Island, and four (haplotype H14‐H17) were shared by populations MC1, MC2, MC3, and MC4 in mainland China in the mtDNA cyt b gene (Table C. gachua was low (0.0318), ranging from 0.000 (NN2 and V1) to 0.0169 (SN4)  of mtDNA cyt 3.2NST and GST fixation indices demonstrated that NST was larger than GST , demonstrating the presence of phylogeographic structure in C. gachua  and minimum‐spanning networks were largely concordant. Lineage A was distributed on Hainan Island and Vietnam as a separate species, and the specimens from mainland China (lineage B) were delimited as a separate putative species  to 1.000 (between NN2 and V1 populations) in mtDNA cyt b gene. Moreover, the pairwise FST values between populations from different regions were relatively high and significant, indicating that high differentiation existed among these populations  but was only 5.85%  among populations within groups and 8.34%  within populations  Hainan Island and Vietnam, (2) the V2 population in Vietnam, and (3) mainland China revealed the highest FCT value  based on estimates of the SAMOVA.The value of overall 3.4D and Fu's Fs tests were positive, and multimodal mismatch distributions were observed for all three clades (Table C. gachua. The Bayesian skyline plot (BSP) analyses also indicated a decline in effective population size 75,000 years ago (75 Kya)  Figure .C. gachua. Molecular dating estimated that sublineage A1 + A2, lineage A and lineage B coalesced to TMRCA 0.516 (95% highest posterior density (HPD): 0.343–0.716) and 1.282 (95% HPD: 0.909–1.688) myr ago, respectively. The results of the S‐DIVA analysis indicated that the common ancestor of C. gachua was distributed on Hainan Island, Vietnam, and mainland China with an occurrence frequency of 100%. Hainan Island was isolated from mainland China and separated the populations into two groups, that is, south and north of the Gulf of Tonkin. Two vicariance events occurred: The rise of the WY Range on Hainan Island separated the populations into two groups (lineage A1+A2 and lineage A3), and the formation of the Qiongzhou Strait separated the Hainan Island population (lineage A1) and the Vietnam population (lineage A2). After a vicariance event in the formation of the WY Range, the populations in the South Hainan region moved northward to the North Hainan region  across the samples was 0.955, indicating a high level of genetic diversity in C. gachua, which is similar to the results obtained for other freshwater fishes in South China, such as G. hainanensis  was higher than that of other species  of the C. gachua populations on Hainan Island was similar and comparable to the results reported for O. hainanensis (θπ = 1.63%)  , which is suspected to cause genetic drift by effective population size decline and a high level of genetic diversity in the total population (θπ = 3.18%). As in previous studies, the reason for effective population size decline in freshwater fish has occurred not only due to overfishing but also due to massive loss of their natural habitat in mainland China , demonstrating the presence of phylogeographic structure. Channa gachua displayed a high level of genetic differentiation (FST = 0.876), with the most unique haplotypes and partially shared haplotypes demonstrating that the populations of C. gachua were differentiated from each other  and all other populations (FST between 0.805 and 0.976), suggesting strong genetic differentiation and consisting of two cryptic species (described below).Moreover, the population analyses of C. gachua could be attributed to genetic differences between the two geographical regions (Hainan Island + Vietnam and mainland China), whereas only 5.85% variation was observed among populations within groups. However, 83.27% of the total genetic variation among the three geographical regions  may indicate that the Gulf of Tonkin is not a major geographical barrier between Hainan Island and Vietnam for C. gachua. The genetic data suggest that this current spatial distribution was achieved relatively recently, given that populations had weak genetic differentiation between Hainan Island and Vietnam, supporting the occurrence of enabling mixing of populations across this ocean barrier (Gulf of Tonkin). To the best of our knowledge, this report describes the first time that the Gulf of Tonkin has not represented an important geographical barrier between Hainan Island and Vietnam for freshwater fish.According to the SAMOVA results and the partitioning of genetic variation through AMOVA, 85.81% of the total genetic variation in 4.2Rhodeus ocellatus  indicated a decline in effective population size 75,000 years ago (75 Kya), coinciding with the last glacial period in relation to sea‐level rise in the Gulf of Tonkin. We suggest that Hainan Island is located in the transitional zone between the subtropical and tropical zones and that C. gachua exhibits a more restricted habit in the headwaters of a drainage system. During glacial cycles leading to sea‐level fluctuations, the habitat area will not increase for C. gachua, which indicates that the effects of population expansion are more significant for downstream fishes than for upstream fishes. Therefore, the results of demographic analysis of O. hainanensis in downstream fish displayed a pattern of population expansion . During glaciations after the warmer Miocene and Pliocene, marine transgressions were extensive, and most of the continental shelves of the South China Sea, including the Gulf of Tonkin, were underwater  was absent during glaciations.According to all results, our study suggests that the ancestral populations of C. gachua between mainland China, Vietnam, and southern Hainan Island was restricted during Pleistocene glaciations. The ancestral populations of C. gachua dispersed from southern Hainan Island to northern Hainan Island, including the Changhua River and Wanquan River (lineage A3)  and the Gulf of Tonkin  and Hainan Island in both types of DNA markers could be caused by recent large‐scale dispersal and colonization events. We suggest that the fall in sea levels would result in the Gulf of Tonkin becoming terrestrial along with the old Red River drainage system, which appears to have existed during periods of glacial maxima. According to the phylogenetic tree, the V2 population in Vietnam formed a monophyletic group and was located in the basal position of lineage A. We suggest that rising sea level, during glacial retraction, would flow on the Gulf of Tonkin from the south direction and the V2 population located in the southern part of the Gulf of Tonkin was the first population to be isolated geographically after the retreat of glaciation. The monophyly of O. hainanensis populations in the Changhua River and Red River indicated a close relationship of populations between Hainan Island and mainland China  and mainland China . Four well‐supported evolutionary lineages were identified in the mtDNA trees, which may include two cryptic species (lineages A1‐A3 and lineage B)   between the two cryptic species was 0.916, which is also indicative of high differentiation between them  Figure . Moreove) Figure . The hapa Figure . The gen4.5C. gachua were represented and should be considered two cryptic species  were the first to differentiate as independent sub‐branches, and their FST was significantly high, suggesting that they should be regarded as different MUs. We also suggest that two lineages (A1–A2) should be regarded as different MUs distributed in the other population of Hainan Island and the population in Vietnam.According to the model proposed by Moritz, evolutionarily significant units (ESUs) are recommended on the basis of reciprocal mtDNA monophyly, while management units (hereafter MUs) have been defined as geographical areas with restricted interchange in allele frequency distributions in mitochondrial or nuclear loci Moritz, . Understs Figure . The impThe authors declare no competing interests in the preparation or execution of this study.Junjie Wang: Data curation ; Investigation ; Writing‐original draft . Chao Li: Data curation ; Investigation ; Methodology . Jiaqi Chen: Methodology . Jujing Wang: Investigation . Jinjin Jin: Investigation . Shuying Jiang: Investigation . Luobin Yan: Investigation . Hung‐Du Lin: Conceptualization ; Writing‐original draft ; Writing‐review & editing . Jun Zhao: Conceptualization ; Funding acquisition (lead); Project administration (lead); Resources ; Writing‐review & editing .Fig S1Click here for additional data file.Fig S2Click here for additional data file.