Rst genetic distances demonstrated close Y-chromosome affinities among the three autochthonous Basque populations and between them and the male population of Ireland and Gascony. In a MDS plot, the population of Ireland segregates within the Basque cluster and closest to the population of Guipuzcoa, which plots closer to Ireland than to any of the other Basque populations. Overall, the results support the notion that during the Bronze Age a dispersal of individuals carrying the R-S116 mutation reached the Basque Country replacing the Paleolithic/Neolithic Y chromosome of the region.Here we report on the Y haplogroup and Y-STR diversity of the three autochthonous Basque populations of Alava (n = 54), Guipuzcoa (n = 30) and Vizcaya (n = 61). The same samples genotyped for Y-chromosome SNPs were typed for 17 Y-STR loci  using the AmpFlSTR Yfiler system. Six major haplogroups  were detected, being R-S116 (P312) haplogroup the most abundant at 75.0% in Alava, 86.7% in Guipuzcoa and 87.3% in Vizcaya. Age estimates for the R-S116 mutation in the Basque Country are 3975 ± 303, 3680 ± 345 and 4553 ± 285 years for Alava, Guipuzcoa and Vizcaya, respectively. Pairwise  In Spain, Basque communities are distributed among narrow valleys within mountainous terrains in the north central region of the Iberian Peninsula. This geography may have had an effect on the Basques’ unique cultural, linguistic and genetic characteristics.Traditionally, Basque populations have been considered one of the oldest human isolates and direct descendant of upper Paleolithic  groups. They are resident of the Franco-Cantabrian region since the Late Glacial and Postglacial periods2. These include studies based on blood groups, serum proteins and enzymes4, mini-satellites5, autosomal microsatellites6, Y-specific microsatellites10, Y-specific single nucleotide polymorphisms12, mitochondrial DNA (mtDNA)13, polymorphic Alu insertions (PAIs)14, and high-density SNPs15. A number of studies using various types of genetic markers including HLA16, mtDNA18, microsatellites19, minisatellites5, Y Chromosome-specific21, autosomal SNPs22 and high density SNPs23 have contested the uniqueness of the Basques claiming that the Basques fall well within the European genetic spectrum.Over the years studies have examined the Basques using linguistic, archaeological, anatomical and genetic markers24 and SNPs25. Furthermore, some data based on classical markers3 and HLA studies demonstrate a lack of subpopulation structure among the Basque16. On the other hand, other studies based on classical and autosomal markers29 indicate genetic heterogeneity among Basque populations. Furthermore, investigations using classical markers32, immunoglobin allotypes34 and mtDNA sequence comparisons35 illustrate variable levels of substructure among the Basque. In a comprehensive study of uniparental markers in Basques and neighboring Indo-European-speaking populations from the Franco-Cantabrian region of Europe, it was concluded that the Basque-speaking populations fall within the genetic spectrum of other Western European populations36. Furthermore, the study suggests that any genetic heterogeneity and substructure observed in the Basque today relative to geography result from pre-Roman tribal structure dating back to the Bronze Age.A number of genetic markers have clearly shown an underlying genetic similarity shared among Basque groups. These include HLA antigens37. The study describes the Basques as an Iron Age population genetically impacted by migrations from the Pontic-Caspian STEPPES. These population movements into Iberia likely correlated with the introduction of the Urnfield tradition and Indo-European languages to the region38. Yet, in Iberia only the Basque groups failed to adopt an Indo-European language. According to the study, these STEPPE migrants initially co-existed with the local Neolithic farming communities and eventually mixed to generate the Bronze Age Iberian population about 4000 years ago. On the average, the current Iberian populations possess about 40% Pontic-Caspian DNA39. In some Iberian communities the native Y-chromosomes of Neolithic farming communities were almost totally replaced by the Indo-European R1b lineages39. For unknown reasons, the replacement of Copper Age Western European Y chromosomes made up mainly of haplogroups I2, G2, and H by R1b Bronze Age chromosomes was more dramatic in Iberia. This sex-specific replacement suggests a higher contribution of incoming males than females, which is also supported by a lower X-chromosome input from the STEPPES. Today this Y chromosome turnover is particularly pronounced in the Basques, which exhibit 87% R1b19. In the rest of Iberia the abundance ranges from 43% in Malaga to 81% in Catalonia40. The population-dynamic mechanisms that generated such a sex-specific replacement are unknown.Recently, high-coverage genome-wide SNP data utilizing ancient DNA from Iberian samples from the past 8000 years confirms the genetic isolation of the Basques since the Bronze Age, ~ 2200–900 BCE41 the M269 mutation that defines Y haplogroup R1b originated in the Near East and travelled with Neolithic farmers to Northern Anatolia and then to the Pontic-Caspian steppe where a number of its subclades became closely associated with the spread of Indo-European languages into Western Europe. A subsequent mutation, S116 , likely occurred in what is today France approximately 5500–5000 years ago41. The R1b Y-chromosome haplogroup in Iberia is mainly represented by the R-S116 haplogroup, which reaches 80% in the Basque Country 42. A derivative lineage of S116, DF27, which likely originated in Iberia reaches a maximum value of 63% in the Basque Country and minimum value of 40% in Galicia12.According to Myers et al.Considering the elevated level of Indo-European Y chromosomes observed in the general Basque population, while retaining mtDNA and autosomal Neolithic sequences, we decided to investigate the Y-chromosome constitution of the three regional autochthonous Basque populations of Alava, Guipuzcoa and Vizcaya. In doing so, we were testing the hypothesis that Paleolithic/Neolithic Y chromosomes were replaced by S116 Y chromosomes in the three populations during the Bronze Age.43. Individuals were considered autochthonous Basque if the four grandparents were born in the Arratia (Vizcaya province) and Goiherri (Guipuzcoa province) valleys of the Basque Country as indicated in Fig. Whole blood samples were collected from 145 autochthonous Basque individuals from the provinces of Guipuzcoa (n = 30), Vizcaya (n = 61) and Alava (n = 54). Peripheral blood was collected in EDTA vacutainer tubes by venipuncture from unrelated healthy individuals. All samples were procured from donors voluntarily while closely adhering to the ethical guidelines stipulated by Colorado College, Colorado Springs, Colorado USA and the University of the Basque Country, UPV/EHU, Vitoria-Gasteiz, Spain. All donors gave their informed consent prior to inclusion in the study, following the ethical principles and guidelines of the Declaration of Helsinki for the protection of human subjects. DNA was extracted from leukocytes by the phenol–chloroform method described by Batzer and DeinigerA total of 30 geographically targeted key reference populations with Y-STR or Y-SNP frequency data were included for phylogenetic comparisons to the three Basque populations. The reference populations were strategically selected providing phylogenetic context to the Basques populations genotyped. All collections, their abbreviations, biogeographical origin, reference publication and total number of individuals analyzed are listed in Supplementary Table Alu), M35, M78, V65, M281, V12, V13, V22, V6, P72, M123, M107, M293, M183, M81, M201, P287, M377, P15, M286, P16, M258, M253, M21, L22, P109, M227, M26, P259, M304, P58, L24, M158, M9, M207, M198, M269, M412, U106, S116, U152, M126, M160, M529, M222, M65, M153, M167, M20) were examined using standard methods including PCR–RFLP44, allele-specific PCR46, PCR amplification and electrophoretic detection of Y-chromosome polymorphic Alu insertions (PAIs)47, as well as direct sequencing44 as deemed necessary. The Y-SNP markers were scored in a hierarchal order to determine the Y-haplogroup status of each individual sample. Y-SNP haplogroup assignment and nomenclature is in accordance with the Y Chromosome Consortium48 and subsequent updates by Underhill et al.49. The S116 frequency reported represent total S116 as previously reported41.A total of 49 bi-allelic markers (YAP (www.isfg.org).The same samples genotyped for Y-SNPs were typed for 17 Y-STR loci  using the AmpFlSTR Yfiler PCR amplification kit as recommended (Applied Biosystems of Life Technologies/Fisher Scientific). Resulting amplicons were separated on an ABI Prism 3130 XL Genetic Analyzer using the ABI GeneScan 500 LIZ as an internal size standard and fragment lengths were estimated by GeneMapper v3.2 (Thermo Scientific). Y-STR alleles were assigned by comparison with an allelic ladder provided by the manufacturer. The number of repeats at DYS389II was calculated after subtracting the number of repeats at DYS389I. Allelic nomenclature follows the recommendations of the International Society for Forensic Genetics (ISFG)  and the corresponding P-values were calculated for all given pairs of populations using the Arlequin v3.5 software51. The pairwise population comparisons were tested at a significance level of 0.01 with 10,000 permutations52. In order to compensate for potential inclusion of false positives, type I statistical errors, the Bonferroni correction was applied (α/m = 0.01/528 = 1.89394 × 10–5). The DYS385 locus was not included in population comparison for the reasons previously stated. All samples carrying non-consensus alleles and null alleles were excluded from the Rst calculations. Subsequently, multidimensional scaling (MDS) plots were generated in order to examine the phylogenetic relationships among populations in Supplementary Table 53 using the Rst pairwise values. A Neighbor Joining (NJ) tree, based on Fst distances54, was constructed with the software PHYLIP 3.52c55 in order to deduce phylogenetic relationships between the populations under analysis. Bootstrap analysis involved 1000 replications.Population pairwise genetic distances (http://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.Y-STR haplotypes of individuals belonging to the R-S116 haplogroup were used to generate a Median-Joining networks (NETWORK 4.5.1.6 at ρ)56 and weighted rho (ρW)12 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. The statistical significance of the time estimate differences were assessed using the Past 4.02 software .Y-STR haplotypes were used to estimate the time to the most recent common ancestor (TMRCA) of the R-S116 sub-haplogroup. With this aim, rho statistic . E-V65 is of Northern African origin and could have dispersed into Iberia across the Mediterranean at various times since its origin approximately 4300 years ago. All the other haplogroups range from 0 to 6.7% depending on the Basque population. J-L24 and G-M287 are markers associated with the agricultural/Neolithic revolution while I-M253 is linked to Norse dispersals of the late eighth to late eleventh centuries of the current era. When the full set of haplogroups are considered together among the Basque populations, the observed differences are not statistical significant .Y-SNP haplogroups and their frequencies are shown in Supplementary Table Rst genetic distances and the corresponding P values among Alava, Guipuzcoa and Vizcaya and the 30 geographically targeted reference populations are presented in Supplementary Table Rst distances were detected among Alava, Guipuzcoa and Vizcaya populations. Comparisons between Alava, Guipuzcoa and Vizcaya, and the reference populations generated close Rst distances in relation to Basque Country, Gascony, Ireland, USA Basques, Andalusia and Spain (Supplementary Table –5), additional pairwise Rst genetic distances were found to be statistically insignificant.Pairwise Rst distances 62 and autosomal DNA is not uniform in Western Europe62. It is not clear which evolutionary force(s) were at play to account for this sex-bias replacement. It has been proposed that the invading Bronze Age populations carrying the R-S116 mutation possessed superior technology including bronze weapons, horses and wheeled vehicles, thus could have easily subjugated and/or annihilated most of the native Neolithic farmers and any remaining hunter-gatherers. Culturally, these invaders were warlike and priced heroism and conquest63. Another potential factor that may explain the observed Y-chromosome bias is that invading armies are mainly made-up of men and casualties are usually inflicted on the male population leaving the woman for the winners to reproduce.The observed abundance of R-S116 in the autochthonous Basque populations is of particular interest. At 87.3% and 86.7% frequencies in Vizcaya and Guipuzcoa, respectively, these two Basques groups represent the highest recorded worldwide41 considering a migration to the Basque Country of a population carrying it. The TMRCA for the Spaninsh Basque population as a whole for haplogroups I2 and J2a have been reported at 7800 ya and 5500 ya, both older than R-S11612. These older ages for I2 and J2a in the Basque are expected considering that these haplogroups arrived in Europe during the Neolithic. Yet, similar expansion times (about 50 generations ago or 1200 ya) and estimated initial and final populations for haplogroups R-S116, G2a, I2, and J2a in the Spanish Basque as a whole have been reported12. It is not known if the same demographic forces affected the whole of the Y chromosome composution in other parts of Iberia.The age estimates of R-S116 are congruent with its origin somewhere in France approximately 5500–5000 years ago64 and Busby et al.65, mutation rates vary considerable among Y-STR loci and alleles, therefore, correspondence involving studies using different STR loci are difficult. Furthermore, age estimations computed using Y-STR diversity are affected by various factors that may overestimate the values, including several incursions from different ancestral populations. Therefore, age estimates should be considered as upper bounds. Notwithstanding these considerations, the ages reported in the present study are suitable for comparisons involving the populations analyzed in this study.As a result of the shortcomings related to the estimation of Y-STR mutation rates, the ages provided in this article should only be consider as relative assessments. As indicated by Ballantyne et al.Rst values  that brought about such a specific and dramatic replacement of Y-chromosome types, it demonstrates that the Bronze Age dispersal genetically linked populations as geographically dispersed as Ireland, Gascony and the Basque Country of Spain.Supplementary Information 1.Supplementary Figure 1.Supplementary Figure 2.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.


Plasmodium vivax has become the predominant parasite. To gain a better understanding of transmission dynamics, knowledge on the changes of P. vivax populations after the scale-up of control interventions will guide more effective targeted control efforts.Countries within the Greater Mekong Sub-region (GMS) of Southeast Asia have committed to eliminating malaria by 2030. Although the malaria situation has greatly improved, malaria transmission remains at international border regions. In some areas, P. vivax clinical samples collected at two time points in two international border areas: the China-Myanmar border (CMB) (n = 50 in 2004 and n = 52 in 2016) and Thailand-Myanmar border (TMB) (n = 50 in 2012 and n = 54 in 2015). Parasites were genotyped using 10 microsatellite markers.This study investigated genetic diversity and population structures in 206 HE = 0.66–0.86) and was not significantly different among the four populations (P > 0.05). Specifically, HE slightly decreased from 0.76 in 2004 to 0.66 in 2016 at the CMB and increased from 0.80 in 2012 to 0.86 in 2015 at the TMB. The proportions of polyclonal infections varied significantly among the four populations (P < 0.05), and showed substantial decreases from 48.0% in 2004 to 23.7 at the CMB and from 40.0% in 2012 to 30.7% in 2015 at the TMB, with corresponding decreases in the multiplicity of infection. Consistent with the continuous decline of malaria incidence in the GMS over time, there were also increases in multilocus linkage disequilibrium, suggesting more fragmented and increasingly inbred parasite populations. There were considerable genetic differentiation and sub-division among the four tested populations. Temporal genetic differentiation was observed at each site (FST = 0.081 at the CMB and FST = 0.133 at the TMB). Various degrees of clustering were evident between the older parasite samples collected in 2004 at the CMB and the 2016 CMB and 2012 TMB populations, suggesting some of these parasites had shared ancestry. In contrast, the 2015 TMB population was genetically distinctive, which may reflect a process of population replacement. Whereas the effective population size (Ne) at the CMB showed a decrease from 4979 in 2004 to 3052 in 2016 with the infinite allele model, the Ne at the TMB experienced an increase from 6289 to 10,259.Despite intensified control efforts, genetic diversity remained high (P. vivax at the TMB and CMB showed considerable spatial and temporal differentiation, but the presence of large P. vivax reservoirs still sustained genetic diversity and transmission. These findings provide new insights into P. vivax transmission dynamics and population structure in these border areas of the GMS. Coordinated and integrated control efforts on both sides of international borders are essential to reach the goal of regional malaria elimination.With enhanced control efforts on malaria,  Plasmodium vivax has become the main source of malaria infections in many endemic areas where Plasmodium falciparum and P. vivax co-exist [P. vivax to control measures [As the global incidence of malaria has been greatly reduced in recent years, co-exist . This isco-exist , which imeasures . In recomeasures . As the measures . These imeasures –8. In admeasures . While mmeasures .P. vivax seems to defy this principle. In most of its geographic range, P. vivax showed high levels of genetic diversity as revealed by population genetic studies using various genotyping markers [P. vivax still maintains high levels of diversity [P. vivax and P. falciparum co-endemicity, these two parasites tend to exhibit markedly different genetic diversity and population structures, with P. vivax showing more stable transmission patterns [P. vivax populations in areas with intensified control frequently showed relatively high genetic diversity, but substantial levels of multilocus linkage disequilibrium (LD) and population substructure [Since a major mechanism of generating genetic diversity in the malaria parasites is meiotic recombination of parasite strains in mosquito vectors, genetic diversity is intrinsically linked to the transmission intensity . Likewis markers –21. Paraiversity –26. As apatterns , 27–29. patterns , 31, butpatterns . As a retructure , 23, 33.P. vivax not only has become the predominant Plasmodium species in recent years [P. vivax populations from international border regions of Thailand with microsatellite (MS) markers clearly detected parasite population division, consistent with the separation of these parasite populations by the malaria-free central region [P. vivax clinical samples collected at different time points of the same study sites were used to determine the effect of intensified control efforts on genetic diversity and population dynamics of P. vivax in two border regions of the GMS.The scale-up of malaria control efforts in countries of the GMS has led to substantial changes in malaria epidemiology with a noticeable rising proportion of vivax malaria , 34. In nt years , but alsnt years , 36. Event years . Final al region , 38. HerP. vivax patients or their legal guardians for participants under the age of 18 years. This study was approved by the Institutional Review Boards of Department of Disease Control, Thailand Ministry of Health and the Pennsylvania State University. Use of the de-identified blood samples was approved by the Ethics Review Committee of China Medical University.Written informed consent was obtained from all P. vivax populations in response to intensified malaria control efforts in the GMS, P. vivax isolates were collected at two time points from two different areas of the CMB and Thailand-Myanmar border (TMB)  and Nabang Township (China). These hospital and clinics are located within 2 km from each other, and are thus considered as a single study site. In Thailand, Tak Province has been among the most malaria-endemic areas. In the past decade, malaria incidence in Tak has experienced more than 10-fold reduction, from 13,706 in 2012 to 1364 in 2016 [P. vivax accounted for 57.5% and 86.7% of the total cases, respectively . Fifty P. vivax clinical samples obtained in 2012 from the Tha Song Yang hospital, Tak Province represented the parasites before the endorsement of malaria elimination plan, and were used to compare with samples collected from the same hospital in 2015 [P. vivax cases, ~ 100 μl of finger-prick blood were spotted onto Whatman filter paper, dried and stored in individually zipped plastic bags.In order to investigate the change of the ncidence , P. vivant years , 36. At Parasite genomic DNA was isolated from the dried blood spots on filter paper according to the protocol of QIAmp DNA Mini kit . The final purified DNA was eluted into 35 μl of elution buffer and used immediately or stored at − 20 °C until further use.Plasmodium 18S rRNA genes [P. vivax populations in Thailand [P. vivax samples. A multiplex primary PCR was done using all 10 primer pairs and followed by singleplex secondary PCR with a fluorescently labelled  forward primer as previously described [A volume of 2 μl of purified DNA was used as the template for malaria parasite detection by a genus-specific and species-specific nested PCR targeting the NA genes . Ten MS Thailand  were useescribed . PCR proescribed . GenotypIsolates containing more than one peak for any marker were considered to be multiple clone infections. The multiplicity of infection (MOI) was defined as the maximum number of alleles observed at any of the loci investigated. The mean MOI was calculated from the individual samples for each study site. Alleles were binned using the TANDEM software . IsolateHE) were calculated using Arlequin version 3.11 [FST using GenAlEx version 6.5. To estimate the partitioning of genetic variance for different hypothesized population groupings, analysis of molecular variance (AMOVA) was performed using GenAlEx version 6.5.The indices of genetic diversity within populations, such as the number of polymorphic loci, the number of haplotypes (Nh), the number of alleles (Na), the mean allelic richness, and the expected heterozygosity  was used [P. vivax calibrated from an eradicated European strain (5.57 × 10−7), which was ~ 3500× lower than that estimated for P. falciparum, was also used [The effective population size was calculated using the stepwise mutation model (SMM) and infinite alleles model (IAM) as previously described . Mutatiowas used . In addilso used .A heterozygosity excess test at the population level was used to detect the recent population bottleneck using BOTTLENECK 1.2.02  with theDeviations from Hardy–Weinberg equilibrium could indicate the presence of population structure or inbreeding . To inveP. vivax isolates were analysed using the Neighbour-Joining method [http://www.phyloviz.net/).To visualize genetic relationships among the parasite isolates from the four populations, an individual-based principal coordinate analysis (PCoA) was conducted in GenAlEx version 6.5 using the genetic distances among MS genotypes. In addition, phylogenetic relationships amongst g method  implemeng method . MinimumP. vivax isolates from two areas of the GMS were genotyped at 10 MS markers. Of the 10 MS markers, failure rates for MS7 (16.5%) and MS9 (15.0%) were the top two highest. Complete genotyping data at all 10 loci were obtained for 171 (83.0%) isolates. Since the maximum number of missing MS data for each sample was 4, all samples were included in the analysis. The 10 MS markers all were polymorphic with each one having 2-20 alleles when all parasite populations were considered and allele frequencies varied among the four populations  . At the CMB, compared with the 48.0% polyclonal infections observed in 2004, this proportion decreased to 30.7% in 2016. Similarly, at the TMB, the percentage of polyclonal infections also experienced a considerable decrease from 40.0% in 2012 to 23.7% in 2016. Accordingly, this was reflected in the reduction of mean MOI from 1.48 in 2004 to 1.33 in 2016 at the CMB, and from 1.50 in 2012 to 1.36 in 2015 in the TMB area  parasite isolates contained polyclonal infections (more than one peak for at least one MS marker), and the proportions of multiclonal infections were significantly different among the four parasite populations (t) Table . At bothP > 0.05). In comparison, the genetic diversity of parasite populations at the TMB had a slight increase from 0.80 in 2012 to 0.86 in 2015  and TMB (P < 0.0001) (Table SA = 0.0236) to 2016 (ISA = 0.0329) and at the TMB from 2012 (ISA = 0.0366) to 2015 (ISA = 0.0586) (Table The standardized index of association I1) Table . MultiloHE from the mutation-drift equilibrium, indicating events of population size reduction with possible clonal expansion in all four populations. The TPM only detected such events in the TMB populations. Likewise, the mean Garza-Williamson index was less than 0.68 in all the four populations, also suggesting a reduction of the effective population size.To detect whether there were significant changes in the parasite population size, BOTTLENECK analysis was performed under SMM and TPM, and the Garza–Williamson index was computed Table . The SMMP. vivax populations in the GMS were evaluated by estimating the Wright’s fixation index FST. As expected, the contemporary P. vivax populations from the CMB and TMB showed considerable genetic differentiation (FST = 0.169 and 0.237). The CMB P. vivax populations showed moderate differentiation between 2004 and 2016 (FST = 0.081), whereas the TMB parasite populations had substantial differentiation between 2012 and 2015 , but significant genetic differentiation from the 2015 TMB population (FST = 0.172). Overall, AMOVA indicated 87% of the variations was attributed to variations within populations, and 13% among populations. Specifically, at the CMB, 93% of the variations was attributed to variations within populations and 7% among populations, whereas at the TMB, 88% of the variation was attributed to variations within populations and 12% among populations.Genetic differentiation of the FST analysis , Thailand (0.76), central China (0.816), Laos (0.75), and India (0.72), as well as South America, such as Colombia (0.79) and Brazil (0.71) [HE only decreased slightly at the CMB and remained relatively unchanged in the TMB. This may reflect the differences in the time span of samples collected at the two sites: 12 years at the CMB versus 2–3 years at the TMB. An earlier study conducted using the CMB 2011–2013 samples also revealed stable genetic diversity (HE = 0.82) in these parasite populations [P. vivax-endemic areas [P. falciparum strains in the GMS [The GMS is malaria hypo-endemic with malaria transmission occurring along international borders. In both CMB and TMB, camps for refugees or internally displayed people have been established, where there is constant human population movement. Genetic diversity of l (0.71) , 62, 63.China 0.8, Laos  in the proportion of polyclonal infections and MOI. Yet, the proportion of polyclonal infections was unchanged at the CMB from 29% in 2011–2013  to 30.7%Another noticeable change is the detection of significant multilocus LD in the parasite populations despite high genetic diversity. This again seems to be a common finding in many vivax low-endemicity settings such as Indonesia, Papua New Guinea, South Korea, India, Vietnam, Colombia, and Brazil , 70, 71.P. falciparum parasites [Across different border regions of Thailand, a previous MS analysis detected substantial parasite population differentiation . This starasites . In addiarasites  and popuarasites . The notarasites . Moreovearasites , 78. Intarasites , and intarasites . In addiarasites  may havearasites , which mP. vivax population differentiation. However, the persistently high genetic diversity, moderate levels of polyclonal infections, and considerably large effective population sizes demand concerted efforts of border nations to implement more effective measures targeting this resilient parasite. Especially in western Thailand, both parasite genetic diversity and effective population size have experienced slight increases in recent years. The large degree of population movement, rapid ecological changes and complex vector population dynamics in western Thailand are very conducive to sustained malaria transmission [Overall, this investigation demonstrated that the scale-up of malaria control interventions for malaria elimination in the GMS has resulted in both spatial and temporal smission . With a smission , 83. TheAdditional file 1: Fig. S1. Map of GMS showing the two border regions (stars) where Plasmodium vivax clinical samples were collected.Additional file 2: Table S1. The number of alleles (#) and allelic richness of each microsatellite marker in the four populations.Additional file 3: Table S2. Effective population size (Ne) of the P. vivax populations estimated using the SMM and IAM models.Additional file 4: Table S3. Multilocus linkage disequilibrium (ISA) in the P. vivax populations analysed using 8 microsatellite loci.Additional file 5: Fig. S2. Estimation of the optimal number of populations (K) using the deltaK/K method.


Palaemon elegans is an ecologically important crustacean species within the European coastline fauna. In the present study, genetic diversity and population structure and connectivity were assessed by examining 21 polymorphic microsatellite loci at 13 sampling sites located along the natural distribution range. All localities showed similar levels of genetic variability. Significant deficits of heterozygosity were recorded, most likely due to the presence of null alleles. Genetic structure analyses revealed two clearly genetically distinct groups within P. elegans but without following any geographical or oceanographic basis. Thus, our results provided nuclear evidence for the existence of a Mediterranean cryptic species within P. elegans, highlighting the need to revise its taxonomic status. Regarding P. elegans sensu stricto, population structuring was reported across the Atlantic–Mediterranean transition area, where the Almería-Orán Front restricts the gene flow between the Atlantic and the Mediterranean population. Moreover, while population connectivity was suggested between all Mediterranean localities, some substructure was found within the Atlantic group. Canary Islands exhibited a weak but significant genetic differentiation from all Atlantic mainland localities, consistent with the isolation-by-distance pattern detected throughout the Atlantic population. Overall, all these findings provided new insights into the population biology of P. elegans complex.The rockpool shrimp  Palaemon elegans Rathke, 1837 is a crustacean decapod common in tidal rockpools, Zostera, Posidonia and Cymodocea sea grasses meadows and it also can be found in hypersaline lagoons and in slightly brackish water close to river mouths1. This species is characterized by its capability to adapt to highly variable environments, as it can cope with a wide range of salinities, temperatures and oxygen conditions3. Regarding to the native geographical distribution of P. elegans, it ranges from the eastern Atlantic Ocean  to the entire Mediterranean Sea and the Black Sea4. Unintentional introductions resulted in this shrimp inhabiting the Caspian Sea and the Aral Sea nowadays. Similarly, P. elegans was introduced in the Baltic Sea, replacing the native counterpart P. adspersus in that region6. Palaemon elegans has been also recently reported to occur on the northeast coast of the United States7, so is currently distributed beyond European waters. Thus, even though P. elegans is considered an important species within the European coastline fauna due to its broad ecological niche and ongoing geographic expansion8, population genetics analyses are scarce.The rockpool shrimp 9. For many years, high levels of gene flow associated with little genetic structuring were assumed for marine species with planktonic larval phases10 as P. elegans. However, it has been proved that historical and oceanographic processes could drive genetic differentiation between marine populations, even in species with high dispersal abilities11. This is the case of the shrimp P. elegans since Reuschel et al.8 carried out a phylogeographic analysis using two mitochondrial DNA (mtDNA) markers, revealing the existence of three haplogroups, one of them in the Atlantic localities (type I) and two from the Mediterranean localities (types II and III). In that study, a genetic break was found in the Atlantic–Mediterranean transition area, restricting the gene flow between these basins and leading to genetic differentiation between the Atlantic (type I) and the Mediterranean (type II) population. Similar phylogeographic breaks across the Atlantic–Mediterranean transition have been reported in a wide variety of species . These genetic discontinuities are frequently attributed to the effect of different oceanographic discontinuities acting in this area, i.e. the Almería-Orán Front, the Strait of Gibraltar, the Balearic Front or the Ibiza Channel10.Genetic breaks occur when there is a marked genetic differentiation in a continuously distributed speciesP. elegans, genetic structure was not detected by Reuschel et al.8 neither within the Atlantic population (type I) nor within the Mediterranean one (type II). As for P. elegans type III, it was only recorded from Mediterranean localities and showed high nucleotide divergence from the other two types8. This genetic pattern was confirmed in later phylogeographic studies in the Mediterranean Sea also using mtDNA markers13. Reuschel et al.8 proposed that type III individuals could belong to a putative cryptic species existing within P. elegans. Cryptic species occur when two or more species are classified as a single nominal species because they are superficially morphologically indistinguishable14. The Mediterranean Sea is characterized by a high level of biodiversity and species richness with a proportion of endemism circa 25%15, largely related to its tortuous geological history. Consequently, cryptic speciation is not considered an uncommon phenomenon in the Mediterranean Sea and molecular markers have indicated the presence of cryptic species in several taxa including shrimps17. Given these findings in P. elegans, the need for further genetic studies using polymorphic nuclear markers, such as microsatellites, to clarify its phylogeography was highlighted.Back to 18 because of its codominant nature, biparental mode of inheritance and high levels of polymorphism19. Specifically in population genetics, microsatellites are extremely valuable tools as they might reveal the existence of genetically distinct populations even in fine-scale studies20. In fact, microsatellite loci have been crucial in understanding the population structure of several shrimp species as Penaeus vannamei21, Penaeus monodon22, Pandalus borealis23, Aristeus antennatus24 or Palaemon serratus25. Thanks to the advent of high-throughput sequencing technologies, the development of microsatellite markers in non-model species has become a rapid and cost-effective process26. Precisely, we isolated and characterized 21 novel polymorphic microsatellite loci for Palaemon elegans using Illumina MiSeq sequencing27.Microsatellite markers have been used in a wide range of applications in population genetics, ecological, conservation and evolutionary studiesP. elegans along the European coastlines, with particular attention to the Atlantic–Mediterranean transition, using microsatellite loci previously developed27 to shed light about the population biology of this species.The aim of the present study was to address for the first time the genetic diversity and population structure and connectivity of the shrimp 27. Thirteen coastal localities distributed along the natural distribution range of P. elegans were sampled. The number of individuals collected from each sampling site varied from 10 (Ebro Delta) to 50 (Collioure). No evidence of linkage disequilibrium between pairs of loci was detected across localities after the sequential Bonferroni correction. Hence, all microsatellites were considered as independent markers. Likewise, the Ewens–Watterson’s neutrality test confirmed that all loci were selectively neutral. Estimators of genetic variability per locality, per locus and per locality and locus are available in Table AR) across localities ranged from 2.032 (Santoña) to 2.453 (Livorno). The 21 microsatellites were highly polymorphic as the mean percentage of polymorphism was 98.53% (Table Ho) over localities for each locus ranged from 0.134 (Pe09) to 0.842 (Pe14), and the expected heterozygosity (He) from 0.201 (Pe09) to 0.876 (Pe14) (Supplementary Table Ho ranged from 0.372 (Santoña) to 0.499 (Ebro Delta) and He from 0.468 (Santoña) to 0.607 (Livorno). Ho and He averaged 0.450 and 0.531, respectively  showed no significant deviation from Hardy–Weinberg equilibrium (HWE). Nine out of the 21 loci  conformed to HWE in all localities, meanwhile the remaining 12 loci were out of HWE in at least one locality  sequence from them following the PCR conditions described in Reuschel et al.8. A COI fragment was successfully amplified for 64 out of the 69 individuals. BLASTn verified that the COI sequence of all these individuals corresponded to the COI sequence of those individuals named P. elegans type III (HE573177) and considered as a cryptic species in Reuschel et al.8. Therefore, the assignment of 69 individuals of our dataset to a putative cryptic species by the 20 microsatellite loci was also supported with a mtDNA marker. COI sequences from the individuals belonging to the putative cryptic species can be easily accessed in Supplementary File The assessment of the modal value of DeltaΔK and a plateau in the plot of K versus ln Pr(X|K)  and Granada were assigned to one of them, and individuals from the Mediterranean Sea  to the other.In accordance with the STRUCTURE analysis, a peak of ups Fig. b. One ofFST = 0.164). More AMOVA analyses were performed to test the grouping scenarios inferred by STRUCTURE. Granada, Almería, Collioure, Livorno and Mallorca localities, with individuals belonging to the putative cryptic species, were subdivided by samples of each species (i.e. P. elegans sensu stricto and cryptic species) to conduct these analyses. Two-group AMOVA  was explained by differences among groups in three-group AMOVA , indicating the genetic divergence of these two species supported by the other analyses. Focussing on the population structure of P. elegans sensu stricto, pairwise FST values revealed significant genetic differentiation between the Atlantic and the Mediterranean localities . DeltaK statistic distribution peaked at K = 2 , explaining the 9.37% of the total variance  was pared down to check the impact of the putative cryptic species on the genetic structure results of P. elegans sensu stricto into two groups   was lesser respecting to two-group AMOVA  was retrieved in P. elegans sensu stricto by the Mantel test, as genetic and geographical distances resulted to be significantly correlated . Another two Mantel tests were performed to test IBD within each population of P. elegans sensu stricto. No IBD was detected within the Mediterranean basin , meanwhile a significant relationship between genetic and geographical distances was found along the Atlantic population .By partitioning samples of ups Fig.  accordinP. elegans. Levels of polymorphism were in line with those found in the counterpart common littoral shrimp P. serratus29. Sampling sites showed similar levels of genetic diversity . Thirty-one locality-locus combinations significantly deviated from HWE, mainly caused by heterozygote deficiency (29 out of the 31 cases) reflected in positive FIS values. Stutter-related scoring errors were discarded as the source of HWE departures because markers with ambiguous interpretation patterns were not included in the microsatellite set during the characterization work27 nor reported during the genotyping step here. Different causes for HWE deviations are frequently invoked such as inbreeding, Wahlund effect or null alleles. Inbreeding should equally affect all loci, generating similar heterozygote deficit across them. Despite global positive FIS values were obtained in all localities, great differences in FIS values across loci were observed, discarding inbreeding. Heterozygote deficit caused by subpopulation structure (Wahlund effect) could not be completely ruled out in localities where an arbitrary admixture of individuals from putative different species was found. Nevertheless, the presence of null alleles is the most likely explanation for the observed departures from HWE. The instability of the flanking sequences of microsatellites leads to some alleles could not be amplified and consequently dropped out, resulting in a homozygote excess. Although microsatellite null alleles are widespread, marine invertebrates have demonstrated particularly higher frequencies than other groups31. The 12 loci that deviated from HWE due to heterozygote deficit showed evidence of occurrence of null alleles, even though mainly in a low proportion. Only one locus, the locus Pe11, showed certain consistency in high null allele frequency estimates across localities and overall. For this reason, we decided to exclude locus Pe11 in population structure analyses as it was advised in González-Castellano et al.27.In this study, microsatellite markers were used for the analysis of the genetic diversity and population structure of the shrimp P. elegans. Some individuals from Mediterranean localities showed a marked genetic divergence from the remaining specimens without following any geographical or oceanographic pattern. Since all shrimps from Granada, Almería, Collioure, Livorno and Mallorca were captured simultaneously in the same rockpools and unambiguously morphologically identified as P. elegans afterwards, we concluded that the explanation for the divergent individuals is the presence of a cryptic and sympatric species existing within P. elegans. Previous studies using mtDNA markers reported that some individuals from the Mediterranean Sea exhibited divergent haplotypes respecting the rest of the sampled collection, being those named P. elegans type III and considered as a cryptic species13. In fact, the individuals assigned with our microsatellite set to a cryptic species were confirmed to correspond with those P. elegans type III by their mtDNA COI sequences. The alternative hypothesis to explain this divergence in nuclear markers among our samples would be strong genetic structuring among individuals who live sympatrically and without exhibiting evident intrinsic reproductive barriers, what seems extremely unlikely.Microsatellite data provided evidence for the existence of two clearly genetically distinct groups within 32, being detected within various species using microsatellite markers35. Here, the 400 sampled shrimps were assigned to one of the two unveiled genetic groups, i.e. P. elegans sensu stricto or cryptic species. Only two individuals from Granada and two from Mallorca could not be assigned to one specific cluster, most likely because they presented missing data at several loci. Consequently, no hybrids between P. elegans sensu stricto and the cryptic species were found. Hence, unknown reproductive isolating mechanisms between these two species should be acting to explain the absence of genetic hybrids. The main question to be solved is the origin of the cryptic species. Given that it was confined in the Mediterranean Sea, it should be originated there. The Mediterranean basin has a very complex geological history that largely contributed to its high level of biodiversity and endemism15. Reuschel et al.8 postulated that P. elegans type III specimens might have their origin during the Messinian Salinity Crisis in late Miocene (around 5.6 Myr ago), when the Strait of Gibraltar was closed, isolating the Mediterranean Sea from the Atlantic Ocean and determining the extensive desiccation of the Mediterranean basin36. According to Reuschel et al.8, isolated P. elegans type III ancestors had to survive in local refugia in the Mediterranean Sea and genetically diverge from the Atlantic population of P. elegans, giving rise to the cryptic species detected within P. elegans nowadays. With the re-opening of the Strait of Gibraltar, the Mediterranean basin was flooded again with Atlantic water, so Atlantic P. elegans individuals should be re-introduced, but they should no longer be able to reproduce with the cryptic species ancestors, since none hybrids are currently detected. Similarly, the Messinian Salinity Crisis was considered the origin of two sister crab species of the genus Carcinus37 and of two sister brittle star species of the genus Ophiothrix38. Our analyses using microsatellite loci support the existence of two species within P. elegans, providing nuclear evidence for the divergence signatures previously detected at mitochondrial level. Future efforts should be directed to clarify the origin of the cryptic species by phylogenetic or phylogenomic studies with precise calibration and to revise the taxonomy of P. elegans complex.Cryptic species are distributed among taxa, but they are particularly prone in the marine environmentP. elegans sensu stricto (P. elegans hereafter), a genetic structure was revealed in the whole study. Genetic differentiation analyses  showed a pattern of two main populations: one composed by the Atlantic localities and Granada, and another composed by the Mediterranean localities. In other words, a clear geographic distinction between Atlantic and Mediterranean sampling sites was detected, with an extension of the Atlantic genotypes into Mediterranean Sea waters. Granada locality was genetically closer to the Atlantic localities than to the other Mediterranean localities. Therefore, a biogeographical barrier restricting the gene flow between these two populations should be located between Granada (Atlantic population) and Almería (Mediterranean population). Precisely, this genetic break matched with the location of the Almería-Orán Front, a semi-permanent dynamic oceanographic front consisted in two anticyclonic gyres that entails abrupt changes of temperature and salinity39. The Almería-Orán Front has been considered as the most important hydrographic boundary to gene flow between the Atlantic Ocean and Mediterranean Sea surface waters11. Indeed, it was confirmed that the Almería-Orán Front acts on the population structure of several species as in P. elegans, e.g. the cuttlefish Sepia officinalis40, some fish species41, the barnacle Chthamalus montagui42 or the wedge clam Donax trunculus43 among others . Notwithstanding, it is known that population connectivity across the Atlantic–Mediterranean transition is reduced in other species by different oceanographic discontinuities, namely the Strait of Gibraltar44, the Balearic Front and the Ibiza Channel46. Most recently, in the congeneric common littoral shrimp Palaemon serratus, both mtDNA47 and nuclear25 markers have reported strong genetic differentiation among Atlantic and Mediterranean localities with an unusual phylogeographical break located west of the Strait of Gibraltar in the Gulf of Cádiz. In the present study, microsatellite data unravelled that the Almería-Orán Front was the only oceanographic discontinuity affecting the population structure of P. elegans across the Atlantic–Mediterranean transition, so our results agreed with the phylogeographic pattern described in Reuschel et al.8 using mitochondrial data. However, it is important to note that the Almería-Orán Front experiences seasonal fluctuations in intensity, size and position39 that might mitigate its effects as oceanographic barrier between the populations of P. elegans.Regarding the population biology of FST values and also observed in the Bayesian analysis. Thus, the above results allowed us to report two subgroups within the Atlantic population: one formed by the South of France and the Iberian Peninsula localities; and another group comprising the Canary Islands localities. The lack of connectivity between these subgroups is consisted with the isolation-by-distance pattern observed along the Atlantic population of P. elegans. In this regard, lack of gene flow between Macaronesian Islands  and continental locations has been also reported for various marine invertebrates, such as limpets of the genus Patella48, starfishes of the genus Marthasterias spp50. or the sea cucumber Holothuria (Holothuria) mammata51, as well as for fishes as the triplefin Tripterygion delaisi52 and the white seabream Diplodus sargus53. The remoteness of the Canary Islands from the Atlantic mainland sampling sites may explain the weak differentiation of Canarian P. elegans samples. The duration of the larval stage compared to the great distance that separates the Canary Islands and the continent may not be enough to prevent this differentiation. Related to this, present-day surface currents in Macaronesia, mainly the Azores Current and the Canary Current54, could also favour the relative isolation of the Canary Islands by disrupting larval dispersion. A more extensive sampling would be needed to reveal whether there is more genetic structuring along the Atlantic distribution of this shrimp.Differentiation was more complex within each group. Within the Mediterranean population, all localities showed no genetic differentiation among them in the light of our data. Our shrimp samples only covered the northern of the Western Mediterranean basin, so it would be interesting to analyse more Mediterranean localities to study population connectivity throughout the entire Mediterranean Sea. As for the Atlantic group, genetic analyses indicated some substructure within this population. Specifically, Canary Islands localities (Tenerife and Lanzarote) showed low but significant genetic differentiation from the remaining Atlantic localities  as suggested by the pairwise 27, so they are specific markers for P. elegans sensu stricto. In order to study the genetic structure of the cryptic species found in the Mediterranean Sea, firstly we recommend revising its status as an independent new species, and then to develop novel specific microsatellite markers to carry out population analyses with them. De novo development of species-specific microsatellites is strongly recommended. Cross-amplification from congeneric species is not generally feasible because inherent problems like allele size homoplasy, polymorphisms biases, null alleles presence, broken repeats motifs or amplification of non-orthologous loci could arise58.Finally, the microsatellite loci used in this study were isolated and characterized from Atlantic individualsP. elegans using microsatellite markers. Two clearly genetically distinct groups were detected within what is taxonomically considered as P. elegans, indicating the existence of a Mediterranean cryptic species within P. elegans. Furthermore, P. elegans sensu stricto is genetically structured in two populations: the Atlantic population and the Mediterranean population. The genetic break that separates these populations was found across the Atlantic–Mediterranean transition, matching with the location of the Almería-Orán Front. The microsatellite loci were sensitive enough to also reveal certain differentiation within the Atlantic population mainly involving individuals from the Canary Islands, which may be explained by an isolation-by-distance pattern.In conclusion, this study encompasses the first assessment of the genetic diversity and population structure of the shrimp P. elegans used in this study were collected inshore between 2012 and 2019 from 13 European sampling sites: Ré Island (France), Santoña (Spain), Ártabro Gulf (Spain), Cádiz (Spain), Tenerife (Spain), Lanzarote (Spain), Granada (Spain), Almería (Spain), Ebro Delta (Spain), Collioure (France), Marseille (France), Livorno  and Mallorca (Spain)  following the manufacturer’s instructions. Extracted DNA quality and concentration were determined with the NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific).Specimens of .27 for P. elegans and following the wet-lab protocol described there. Fluorescently labelled polymerase chain reaction (PCR) products were run on a 3130xl Genetic Analysis System (Applied Biosystems) for fragment analysis in the Scientific Research Support Services (University of A Coruña), using GeneScan 500 (− 250) ROX internal size standard (Applied Biosystems). Geneious 8.0.559 was used for fluorescent profiles analysing and allele peaks calling.Individual genotypes were obtained for 21 polymorphic microsatellite loci (Pe01-Pe21: MH078079-MH078099) previously developed by González-Castellano et alNa), mean number of alleles (A), percentage of polymorphism (P), observed heterozygosity (Ho), expected heterozygosity (He) and deviations from Hardy–Weinberg equilibrium (HWE) for each locus and/or locality were estimated using GenAlEx 6.560. Significance levels were adjusted applying the sequential Bonferroni correction whenever multiple tests were performed. Allelic richness per locality was calculated using FSTAT 2.9.461. GENEPOP 4.262 was used to estimate inbreeding coefficient (FIS) and to test linkage disequilibrium between pairs of loci using Fisher's exact test. Significance was computed by a Markov chain method using 10,000 dememorizations, 5,000 batches and 5,000 iterations per batch. Departures from selective neutrality were evaluated for each locus applying the Ewens-Watterson test using the algorithm given in Manly63 and implemented in POPGENE 1.3264 after 1,000 simulations. Null allele frequency was estimated using FreeNA28 and the EM algorithm65 with a number of bootstrap replicates fixed to 10,000.Genetic variability was assessed with standard descriptive statistics. Number of alleles ) and the ΔK statistic following Evanno, Regnaut, & Goudet69. CLUMPP 1.1.270 was used to permute the admixture coefficients for the several independent runs resulting for the chosen K-value. STRUCTURE PLOT 2.071 was employed to visualize the output from CLUMPP. Genetic discrimination among samples was additionally assessed through a factorial correspondence analysis (FCA) using GENETIX 4.0572.Genetic structure was assessed using the Bayesian model-based clustering method implemented in STRUCTURE 2.3.4FST values  between localities using ARLEQUIN 3.5.1.273. Significance level was adjusted applying sequential Bonferroni correction for multiple comparisons and false discovery rate (FDR) correction (B-Y method as described in Narum74). Several hierarchical locus-by-locus analyses of molecular variance (AMOVA) were carried out using ARLEQUIN 3.5.1.273 in order to estimate partitioning of genetic variance among groups (FCT), among localities within groups (FSC) and within localities (FST). Individuals were pooled according to a geographic/oceanographic criterion or based on the results previously obtained with STRUCTURE to test different groupings.Genetic differentiation was estimated as pairwise 75 to test isolation-by-distance (IBD) using the program ISOLDE implemented in GENEPOP 4.262 with 10,000 permutations. Pairwise genetic differentiation among localities was estimated using linearized FST [FST/(1 − FST)] to construct a genetic distance matrix. Pairwise geographic distance between localities was measured in kilometres following the coastline in Google Earth (Google Inc.) to create a geographic distance matrix.Lastly, the relationship between genetic distance and geographic distance was assessed with a Mantel testSupplementary file1 (DOCX 18 kb)Supplementary file2 (XLSX 36 kb)Supplementary file3 (PDF 380 kb)Supplementary file4 (TXT 39 kb)


Brickellia veronicifolia is a native Asteraceae from Mexico that persists in fragmented habitats. This investigation reports the genetic and chemical diversity of B. veronicifolia. The diversity analysis based on iPBS markers showed an averaged Shannon index (S) of 0.3493, a Nei genetic diversity (h) of 0.2256, and a percentage of polymorphic loci average (P) of 80.7867%. The population structure obtained by AMOVA revealed that the highest variation found within populations was 94.58%. GC-MS profiling of six populations indicated that major volatiles were β–caryophyllene (11.63%), spathulenol (12.85%), caryophyllene oxide (13.98%), α–cadinol (7.04%), cubedol (6.72%) and tau-muurolol (4.81%). Mantel tests suggested a statistically significant relationship between minor volatiles and geographical distance . Likewise, major volatiles showed a significant correlation with the soil pH  and maximum temperature . Our study suggests that the variation and genetic divergence of B. veronicifolia has no relationship with climatic parameters, whereas the volatiles are probably influenced by environmental factors and not by the genotype per se. Based on the characteristics of B. veronicifolia, this plant could be considered as a candidate for restoring fragmented shrublands in Mexico. The environmental disturbance caused by anthropogenic activity is a critical factor that confines plant populations to fragmented habitats. As a consequence, genetic diversity is modified causing changes in the viability and adaptation of populations . It is kThe maintenance of the genetic diversity of plant species with potential use for habitat restoration can improve the fitness of individuals and self-sustaining of populations . GeneticBrickellia veronicifolia (Kunth) Gray  Gray , is an Aiculture . The plaed zones . More thed zones ,15. Due B. veronicifolia is an aromatic plant with interesting pharmacological properties which have been elucidated by several scientific investigations  with a score plot showing high statistical values of R2x = 0.726 and Q2 = 0.256  with values of R2x = 0.850, R2y = 1.00, and Q2 = 0.999. The OPLS-DA model produced two groups which were effectively separated and chemically related, using projections into two dimensions (PC1 = 59.9% and PC2 = 25.1%). The first group was constituted by San Luis Potosí, Querétaro, and Guanajuato populations. The second one contained Oaxaca, Puebla, and Hidalgo populations  data produced a 2D projection [ = 0.256 A. The re = 0.256 B. The 3D= 20.6%] C. An ortulations D. The S-ulations E. The y-icifolia F. The CONAGUA data showed that Guanajuato had 67.7 mm annual average precipitation and 19.6 °C temperature . Both par = 0.2216; p = 0.2980) nor with ecological distance . These results suggest that the geographical distance cannot explain the genetic divergence of wild B. veronicifolia populations. The Mantel Test performed with distance matrices of multiple variables revealed that the genetic distance did not have a significant statistical correlation with geographical distance among populations  but it had a correlation with the distance matrix of latitude  and longitude . The genetically different populations showed a negative correlation with chemical distance indicating nonsignificant differences . On the other hand, analysis between minor compounds and geographical distance revealed a statistically significant correlation  (r = 0.3941 p = 0.0230). Specifically, minor volatiles showed a correlation with precipitation and temperature . Interestingly, the most abundant volatiles showed a correlation with pH  and maximum temperature . Likewise, geographical distance did not show a significant correlation with environment factors ( 0.0470) . SimilarQ2 = −0.328, R2Y = 0.000 and R2X = 0.725). Interestingly, the results of the permutation test  revealed that genetic diversity was not linearly correlated with environmental variables (p > 0.05)  showed no significant values ( > 0.05) A. These  > 0.05) B. B. veronicifolia were generated by iPBS markers and were similar to those reported for populations of Smallanthus sonchifolius  and delta K (ΔK) in accordance with the procedure described by Evanno et al. 2005 [Well-defined DNA bands were categorized as present (1) or absent (0) using Image Lab™ software and carefully checked. Data were deposited in an Excel spreadsheet app as a binary matrix. The observed number of alleles (sity (h) , geneticsoftware . All thesoftware . Three gsoftware . An Admicy model . The ranal. 2005 . The datal. 2005 . Considering that STRUCTURE estimates the results using a constant number of populations, we additionally performed the PCO-MC approach described by Reeves and Richards  in orderFST values with a bootstrapping of 1000 permutations in AFLP-SURV ver. 1.0 [PCO analysis was done with NTSYS 2.11 using Jaccard distances and DCENTER/EIGEN modules to compute principal coordinates along all axes. The cluster analysis was carried out using the MODECLUS procedure with SAS 9.1 . Dendrogram were constructed with the means of the unweighted pair group method based arithmetic means (UPGMA) using MEGA X Software  and CONSver. 1.0 .w/w). GC-MS used an Agilent technologies 7820A instrument with a HP-5 capillary columns (30 m × 0.32 mm I.D. covered with a 0.25 µm of 5:95 phenyl-dimethylpolysiloxane plate). The mobile phase was helium at 1 mL min−1 flow rate and 180 °C injector temperature; the oven program was from 60 °C for 3 min, 75 °C for 5 min, 150 °C for 10 min, and up to 250 °C for 20 min. Software was set for 30–600 m/z range, and the mass spectra was recorded at 70 eV. The relative retention index (RRI) was calculated with a standard mix of C8–C20n-alkanes  under identical conditions [Leaf essential oils were obtained by hydrodistillation (100 g leaves) using a Clevenger type apparatus for 3 h. The essential oils were collected in dichloromethane, dried over silica gel, and stored at 4 °C in amber glass vials until analysis. Essential oil yield was calculated on a moisture-free basis as 0.08–0.19%  to identify possible trends and outliers among these populations. A hierarchical cluster analysis (HCA) was constructed to observe data distribution and to explore the classification of samples. Orthogonal projection for latent structures discriminant analysis (OPLS-DA) was performed to identify differential metabolites among plant groups. For this analysis, a hoteling Ter. 16.0 .In order to estimate environmental variability, altitude, latitude, longitude, averaged soil properties, temperature and precipitation rates were recorded for each studied population. These variables were selected because of their relationship with changes in genetic and chemical variation reported in previous works ,42,78. FAnalyses of soil properties were carried out in accordance with the Mexican norm NOM-021-SEMARNAT-2000. Briefly, soil samples were simultaneously obtained during the collection of plant material. Fifteen soil samples were manually extracted at 30 cm depth after defining a zigzag pattern within the sampling zone. Posteriorly, samples were mixed, homogenized and separated in fourth fractions until obtaining 1.5 kg soil . OrganicFST), geographic distance (measured in kilometers), chemical distance, and climatic factors of populations were performed by Mantel tests with 999 permutations and a p ˂ 0.05 using TFPGA ver. 1.3 [p ˂ 0.05 using XLSTAT ver. 2020 software. Correlations between the genetic distance  with genetic and chemical properties of B. veronicifolia populations should be further addressed.This investigation reports for the first time the genetic and chemical diversity of wild populations of


Mimulus guttatus from North America to Europe and the Southwest Pacific. By sampling 521 plants from 158 native and introduced populations genotyped at >44,000 loci, we determined that invasive M. guttatus was first likely introduced to the British Isles from the Aleutian Islands (Alaska), followed by admixture from multiple parts of the native range. We hypothesise that populations in the British Isles then served as a bridgehead for vanguard invasions worldwide. Our results emphasise the highly admixed nature of introduced M. guttatus and demonstrate the potential of introduced populations to serve as sources of secondary admixture, producing novel hybrids. Unravelling the history of biological invasions provides a starting point to understand how invasive populations adapt to novel environments.Imperfect historical records and complex demographic histories present challenges for reconstructing the history of biological invasions. Here, we combine historical records, extensive worldwide and genome-wide sampling, and demographic analyses to investigate the global invasion of  Mimulus guttatus from North America to Europe and the Southwest Pacific. They found that M. guttatus was first likely introduced to the British Isles from the Aleutian Islands (Alaska), followed by admixture from multiple parts of the native range, and hypothesise that populations in the British Isles then served as a bridgehead for vanguard invasions worldwide.Vallejo-Marín et al. combine historical records, extensive worldwide and genome-wide sampling, and demographic analyses to investigate the global invasion of  Most biological communities now include introduced members that have recently moved beyond their native ranges, often with negative impacts6. Finding the origins of invaders helps develop strategies for prevention, management and eradication8. It is also crucial for understanding to what extent invaders adapted to novel environments, along with the mechanisms of such adaptations10.Increasing global connectivity is leading to widespread species translocations13. In most cases, historical records of first introduction are unavailable or unreliable. Genetic data has greatly improved our ability to study the origins of invasions, and often uses information derived from extant populations10. However, genetic inferences are usually confounded by demographic processes that shape the introduced populations, including multiple introduction events, bottlenecks, evolution in the introduced range, admixture and hybridisation15.Tracing the migration and spread of invasives is typically very challenging. Inferring introduction histories is often accomplished using historical records, genetic analyses, or a combination of bothMimulus guttatus Fischer ex DC. (Erythranthe spp. (L.) G. L. Nesom; Phrymaceae), a herbaceous plant native to Western North America that was introduced across the world in the nineteenth century20. Unlike many invasive and non-native species, detailed historic botanical records21 and travel diaries of early explorers22 allow us to clearly retrace the history of the first introduction of M. guttatus into Europe. Historical records of M. guttatus reaching the United Kingdom (UK) paint a clear picture, but beyond this little is known. Here, we consider the hypothesis that the UK acted as a bridgehead (where invasive populations serve themselves as sources for further invasions23) for worldwide invasion.Here, we use historical and genomic data to generate and test hypotheses in order to unravel the rapid worldwide invasion by the common yellow monkeyflower, M. guttatus appears in Curtis’s Botanical Magazine21, which presents a plate of Langsdorff’s Mimulus (Mimulus langsdorfii Donn ex Sims), featuring a flowering individual of M. guttatus. The provenance of the depicted material is from Grigori von Langsdorff who “…brought it, as we are informed, from Unalashka, one of the Fox Islands” 21, in his capacity as a naturalist on a Russian expedition to the Alaskan territories in 1805. Langsdorff describes how the expedition reaches Unalaska on 16 July 1805, and, after anchoring in Sea-Otters Bay (probably present-day Ugadaga Bay), they travelled on foot to Iluluk (Dutch Harbor). Here, Langsdorff first encounters M. guttatus: “splendid flowers were in blow upon the shore, among which a new Mimulus and Potentilla, which has never yet been described, were particularly to be distinguished”.22 (p. 329). Material brought by Langsdorff made its way to various Botanic Gardens, including Moscow (where it is listed as M. guttatus Fischer nom. nudum) and Montpellier . The seeds of M. guttatus also reached the Botanic Gardens at Cambridge in 1812, and it is therefore almost certain that the original species description included specimens collected by Langsdorff in Unalaska19.The first European record of Botanical Magazine recognised the potential for M. guttatus to become established outside western North America, and the 1812 entry states that because the taxon has showy flowers and is “easily propagated by seeds, and most probably by its runners, must soon be very common.”21. In fact, the first naturalised populations in the British Isles are recorded by 183024, rapidly spreading throughout the UK25. The introduction history of M. guttatus outside of the UK is much less well understood. Mimulus guttatus seems to have reached New Zealand and become naturalised by 187826, and the introduction of this taxon to eastern North America may have occurred much later in the second half of the twentieth century27. Therefore, the material brought in by Langsdorff represents the first introduction of M. guttatus outside its native range, and the subsequent arrival and naturalisation on the British Isles is the best documented, and currently most widespread, monkeyflower invasion29.Presciently, the M. guttatus in the United Kingdom31. However, these studies did not include material from the putative origin (Aleutian Islands), and due to their focus on UK populations, did not examine genetic relationships between native populations and introduced populations in other parts of the range such as in Eastern North America, the Faroe Islands, mainland Europe and New Zealand. Native M. guttatus presents an enormous breadth of ecological and genetic diversity33, and it remains unknown how much of this diversity is represented among introduced populations and the extent to which non-native populations have diverged. Recently, Da Re et al.20 used climatic niche modelling to compare the climatic envelope of native and introduced M. guttatus populations, finding no evidence of niche shift in the introduced UK populations compared to the native ones. Moreover, the highest niche similarity of invasive UK populations occurred in the Aleutian Islands20, lending support to the historical hypothesis that traces their origin to Langsdorff.The historical hypothesis of an Alaskan origin of European monkeyflowers is consistent with results from previous genetic analysis of M. guttatus by marrying historical information with genomic analyses. Specifically, we: (1) Resolve range-wide relationships at the population-level in the introduced range, as well as in the native range including the previously under-sampled regions of the Aleutian Islands and mainland Alaska; and (2) use genomic data to reconstruct the population genetic history of introduced UK populations and test the hypothesis that UK populations have a simple Aleutian origin or are the product of a more complex invasion history. Our results show that populations from the British Isles were first likely introduced from the Aleutian Islands in Alaska, followed by rapid admixture from other parts of the native range. We hypothesise that these British populations then served as a bridgehead for invasions worldwide into the rest of Europe, New Zealand and eastern North America. Our findings emphasise the highly admixed nature of introduced M. guttatus and raise the possibility that introduced populations might serve as sources of secondary admixture, producing novel hybrids.Here, we provide the first global genetic analysis of native and introduced populations of M. guttatus, including populations sampled across ~5000 km of its distribution in North America .The global sampling of ica Fig. , allowedica Fig. , with foade Fig. . This clM. guttatus populations are scattered across the phylogeny, indicating many independent introductions from across the native range  Fig. . As in tent Fig. .Fig. 3PrK-means cluster analysis . UK populations form a separate group with multiple affinities to New Zealand and eastern North American samples. Furthermore, the distinctiveness of Aleutian populations relative to other native populations is also obvious , UK populations show, on average, a relatively high level of diversity compared to Alaskan populations , but only slightly lower than the overall average of other native North American populations , although the number of sampled populations in each of these regions is small . However, model comparisons favour scenarios with additional waves of introductions (Table p = 0.48) and is more likely than a single introduction scenario  and Alaska-British Columbia (AKBC), both of which form part of the North Pacific clade, and the North (NORTH), South (SOUTH), and Coastal (COAST) clades  Mimulus guttatus achieved a broad distribution across geographic boundaries through multiple introductions from genetically distinct source populations. (2) In some cases, the establishment of M. guttatus in the invasive range might have been achieved via a bridgehead process, where invasive populations serve themselves as sources for further, more distant vanguard invasions. This is well illustrated in our discovery of the establishment of invasive populations in New Zealand and eastern North America by way of UK invasive populations. (3) Admixture in the introduced range has given rise to genetically distinct populations generating novel genetic, and therefore phenotypic, combinations .Here, we provide the first global picture of the genetic relationships between native and introduced populations of M. guttatus spans from Mexico to the Aleutians and covers >6000 km of coastline33. To identify potential sources of specific invasion events, sampling large geographic regions is required. Mimulus guttatus has been the subject of continuous study for the last 60 years32, and previous work has collected population samples across nearly its entire native range42. Our analyses of large-scale population samples from the native range builds on the recent finding of geographic genetic structure corresponding to separate coastal and northern colonisation events in North America37. Here, we fill in crucial gaps with sampling from Alaska and the Aleutian Islands, which reveals strong geographic structure in the far north west of the species range, with genetic clusters by islands in the Aleutians. This extensive sampling in the native range allows us to show that Aleutian populations have acted as important conduits to the invasion of Mimulus in Europe and beyond.Widely distributed taxa that serve as a source of invasive populations pose a particular challenge for molecular studies aiming to reconstruct the history of biological invasions. The distribution of 9. Here, we found clear evidence that introduction of M. guttatus into various geographic regions has occurred by colonisation from multiple genetically distinct sources. For example, among the four populations we sampled in eastern North America, where M. guttatus was introduced in the last century, there is evidence of three genetically distinct groups, one of which also occurs in the Faroe Islands  rather than recent reintroductions. In addition, we did not find evidence of large-scale admixture from M. luteus shaping genetic variation in M. guttatus, consistent with the strong reproductive barriers imposed by differences in ploidy level between these Mimulus taxa43.Many biological invasions by both plants and animals are associated with multiple introductions, to the extent that single introduction invasions are considered the exceptionnds Fig. . SimilarM. guttatus from the Aleutian Islands, which is consistent with the historical records of Langsdorff’s expedition and subsequent transfer of material to Russian, European and British collections. The colonisation of the UK by these exotic Aleutian monkeyflowers may have been facilitated by the close similarity of the ecological niche of M. guttatus in the British Isles and the Aleutian Islands20. Climatic pre-adaptation44 of Aleutian monkeyflowers provided early arrivals with an opportunity for initial establishment. It is also clear that an initial introduction from the Aleutian Islands was accompanied or quickly followed by multiple introductions from other parts of the range. The UK seems to have become a melting pot for M. guttatus resulting in admixture of previously differentiated populations, which resulted in the creation of a unique set of genotypes that are now characteristic of UK populations . Our ABC analyses reconstruct this history and show that extant populations are composed of a combination of multiple genetic groups from across the native range. Reconstruction of demographic events during introduction  occurred not from native North American populations, but from populations in the introduced European range23. Our results indicate that UK populations served as a stepping-stone for secondary invasions in other parts of the non-native range. This potential bridgehead effect in invasive monkeyflowers is most clearly illustrated in the invasion of New Zealand. Some invasive populations in New Zealand share a close genetic affinity to UK populations. The genetic similarity is consistent with the exchange of biological material, including horticultural taxa, in the nineteenth century, as British people migrated to New Zealand45. The single sampled population in continental Europe (Germany) also shows a close relationship to UK populations. Unfortunately, without further sampling it is difficult to establish whether UK populations contribute to the extant populations of M. guttatus in Europe. The hypothesis that UK populations have served as bridgeheads to other invasions remains to be further investigated. Morphologically, M. guttatus populations in Russia, Germany and the Czech Republic resemble UK material  but the genetic identity of continental Europe populations remains to be investigated. In this regard, genomic analyses of herbarium specimens could provide important additional insights46. Particularly tantalising would be to compare specimens from herbaria in Russia, France and the UK, where historical links connect early Mimulus collections with Langsdorff’s expedition to Alaska in the early 19th century. Finally, we also detected a close affinity between UK populations and a population in the non-native range in eastern North America. Populations of M. guttatus in eastern North America are generally small, occurring in the states of Michigan, New York, USA and in New Brunswick, Canada27. These small and sparsely distributed populations show diverse genetic origins and seem to be much more recently established . The mechanism of introduction of UK material into eastern North America is unknown but it could be associated with horticultural exchanges47. Our results combined with previous work on other systems , highlight the importance that bridgehead populations can have on biological invasions. Bridgehead populations may have already been selected for their ability to colonise beyond their native range, making them particularly good candidates for additional range expansions.Invasive populations can themselves become sources for subsequent invasions, a phenomenon termed the “bridgehead effect”50. Multiple introductions from genetically distinct sources introduce variation and alleviate the negative effects of demographic bottlenecks associated with colonisation. Moreover, genetically diverse populations are less likely to experience the deleterious effects of inbreeding depression51 and can increase individual fitness through heterosis49, which can potentially make invasive populations more difficult to control. In contrast, admixture may reduce overall fitness if gene flow results in outbreeding depression52, a phenomenon that can occur due to epistatic interactions or, for example, the breakdown of locally adapted genotypes. In M. guttatus, experimental work indicates that both positive and negative effects of admixture can be observed in invasive populations. For example, crossing native and introduced populations results in an increase in biomass, and both clonal and sexual reproduction in greenhouse conditions54. In field conditions, the effects of admixture can be reversed, and a common garden study shows that admixture between UK M. guttatus and both annual and perennial populations from the native range result in lower fitness as estimated using population growth rates39. The effects of admixture may be particularly strong on invasive species with a widespread, highly diverse native distribution, such as M. guttatus. Native populations that occur over large, biogeographically diverse areas may serve as reservoirs of genetic and ecological variation. This wide range of ecogeographic variation may facilitate the colonisation of new regions in the introduced range and potentiate the effects of subsequent introductions and admixture on the performance and adaptive potential of invasive populations.Multiple introductions and admixture can, in principle, both increase or decrease the performance and adaptive potential of invasive populationsMimulus guttatus Fischer ex DC , the common monkeyflower, is a widespread species with a native range extending across western North America from northern Mexico to the farthest reaches of the Aleutian Island chain in Alaska33. The invasive range includes much of the UK, the Faroe Islands, parts of mainland Europe, New Zealand, and Eastern North America20. The species is self-compatible and predominantly outcrossing55. Most populations are diploid, although tetraploid populations occur throughout the native range56 and tetraploid populations have also evolved in the introduced range56. In the native range, populations comprise either small annual plants that reproduce exclusively by seed or perennial plants that reproduce by both seed and vegetative stolons. Only perennial plants are documented in the invasive range.M. guttatus in the native range of western North America and the main areas of introduction in eastern North America, Europe and New Zealand for a total of 521 individuals from 158 populations  , three M. × robertsii, and three M. peregrinus  for 100 bp single-end sequencing on the Illumina HiSeq 4000 at the University of Oregon. We analysed raw sequence reads using the Tassel5-GBSv2Pipeline59, using the M. guttatus v2 genome60 as a reference. Alignment with the reference genome was done with BWA with default parameters in Tassel5-GBSv2Pipeline. To obtain variant sites we used a minimum allele frequency of mnMAF = 0.01. For the genotyping step  we used the following options: kmerLength = 64, mnQs = 20, minPosQS = 20. For population genomic analyses, we retained only variable sites (SNPs), but for estimating nucleotide diversity across the genome (πGENOME) and for tree reconstruction, we generated a sequence matrix with both SNPs and invariant sites (setting mnMAF = 0).To obtain DNA for genotyping, we germinated field-collected seeds from all new populations in a controlled environment facility at the University of Stirling. We extracted genomic DNA from fresh leaves or flower buds using the DNeasy Plant Kit , with samples standardised to 100 ng DNA for library preparation. We used genotyping by sequencing (GBS) to generate genome-wide polymorphism dataM. guttatus populations (πGENOME), we filtered the data set containing both variant and invariant sites  using VCFtools version 0.1.1561. We kept only biallelic loci that were genotyped in at least 75% of all individuals, which reduced the data set to 26,012 loci. We then removed individuals with <50% genotyped loci, reducing the number of individuals from 521 to 475. Nucleotide diversity per site was calculated separately for each of 155 populations, both native and invasive, using the option --site-pi in VCFtools. An overall pairwise nucleotide diversity across the (πGENOME) for each population was then obtained by averaging across all sites.To estimate pairwise nucleotide diversity across the genome of M. guttatus, we filtered the SNP data  using VCFtools version 0.1.1561 and kept only biallelic loci that were genotyped in at least 75% of all individuals, which reduced the number of genotyped SNPs to 1820 loci. The parameters we used in this filtering step were: max-missing = 0.75, mac = 3, min-alleles = 1, max-alleles = 2. We then removed individuals with <50% genotyped loci, reducing the number of individuals from 521 to 474. Finally, we used PLINK version 1.962 to thin the data set to reduce linkage disequilibrium among SNPS using a pairwise correlation coefficient of 0.5 (--indep-pairwise 50 5 0.5). The final M. guttatus data set contained 1498 SNPs from 474 individuals in 155 populations . We analysed two datasets, one for all sampled Mimulus taxa, and one for M. guttatus, with both datasets, including M. glabratus as an outgroup. Each analysis used the full GBS sequences with invariant sites , filtered to include 8798 sites with <50% missing data. We calculated population allele frequencies using the counts file library (cflib) python scripts that accompany64. Model-fitting was performed with ModelFinder65. IQ-TREE analyses subsequently used the best-fitting model (TVM + F + G4) allowing for excess polymorphism (+P) and with five chromosome sets per population (+N5). Tree searches were performed with settings recommended for short sequences, including a small perturbation strength (-pers 0.2) and large number of stop iterations (-nstop 500). Topological support was assessed using an ultrafast bootstrap approximation approach66, with 1000 bootstrap replicates. Trees were visualised with FigTree67.We sought to resolve evolutionary relationships between populations and species using polymorphism-aware phylogenetic models implemented in IQ-TREEglPca function in adegenet68 in R ver. 4.0.069. We used K-means grouping implemented with the function find.clusters in adegenet to identify clusters of individuals in the data without using a priori groupings. For this analysis, we used 100 randomly chosen centroids for each run, and calculated the goodness of fit for each model for values of K between two and 15. For the selected K-value, we also ran a discriminant analysis of principal components (DAPC)70 using the inferred groups for assigning individual membership. We further used fastStructure version 1.071 to infer population structure across M. guttatus populations using a Bayesian framework. For this analysis, we randomly subsampled the data to include a maximum of three individuals per population  from both native and introduced ranges, and analysed values of K from 2 to 8.To analyse population genetic structure, we conducted a principal component analysis using the M. guttatus had a complex origin with multiple introductions in different non-native regions. In order to gain a more detailed understanding of the demographic history of non-native populations, we focused on the introduction of M. guttatus to the UK, which has been best studied both historically and genetically31. Therefore, we implemented an approximate Bayesian computation (ABC) approach to determine the most likely M. guttatus introduction history in the UK. For this analysis, we used the pruned data set consisting of 1498 SNPs but included only individuals from the native range or the UK . Individuals from the native range were grouped into one of five groups (“genetic group”). Four of these groups  have been previously identified in analyses using native populations only37. The fifth group  is identified in the present study (see Results section). To assign native individuals to each of these genetic groups, we used the group membership obtained in the K-means cluster analysis, which produced genetic groups that closely correspond to the native clades previously identified in Twyford and Friedman34 and Twyford et al.37 (see “Results” section). The number of individual in each group is as follows: NORTH, N = 62; SOUTH, N = 42; COAST, N = 30; AKBC (Alaska-British Columbia), N = 70; and ALE, N = 45. Six individuals from two populations (SWC and HAM) that formed a separate genetic group in the native range were not included in this analysis. Individuals from the UK were considered to belong to a single population .Our preliminary analyses indicated that introduced t4, from which the South population diverged at time t5. In addition, the Coastal population diverged from the ancestral population at time t3 from which the Alaska-British Columbia population diverged at time t2, and the Aleutian population diverged from there at time t1. The simulated demographic models share this native population divergence history and only differed by their introduction history into the UK.As all possible scenarios of divergence between the five native groups would have been computationally impossible to test, native group genetic relationships were determined from the phylogenetic tree topology (see “Results” section). All the simulations assumed that the North population diverged from an ancestral population at time t0a . This strategy resulted in the definition of eight different two-waves introduction models . In addition, we computed summary statistics within and between three defined regional groups  representing an additional set of 29 summary statistics.For each demographic model, we simulated 10,000 genetic datasets consisting of 1435 independent SNP genotypes for 798 haploid individuals distributed following the sample size of all six populations in the real data set using R package abcrf76.We performed iterative model comparisons by comparing increasingly complex models Table . In the abcrf based on the summary statistics using 1000 trees. We estimated the posterior median, 0.05 and 0.95 quantiles of the model parameters by random forest regression model based on the summary statistics of the observed genotypic composition.We built a classification random forest model using 1000 trees and a training data set consisting of the summary statistics computed for the 10,000 simulated genetic datasets for each model. We estimated the classification error rate for each model using an “out-of-bag” procedure to quantify the power of the genetic data given the models and prior distribution specifications to differentiate the different demographic models. Then, we used the summary statistics computed based on the observed genotypic data to predict the demographic model that best fit the data using a regression forest with 1000 trees. We report the number of “votes” for each demographic scenario and the approximation of the posterior probability of the most likely model. We used the overall most likely scenario to simulate 100,000 genetic datasets using parameters and prior distributions described above to estimate demographic model parameters. We built a regression random forest model implemented in Further information on research design is available in the Supplementary InformationSupplementary Data 1Supplementary Data 2Peer Review FileReporting SummaryDescription of Additional Supplementary Files