Litsea auriculata (Lauraceae), which is endangered and native to east China. Geographical and environmental factors including climatic fluctuations since the last glacial maximum (LGM) have also contribute to population demography and patterns of genetic structure. L. auriculata populations underwent expansion after divergence and dramatically decreased to the current small size with relative population bottlenecks due to climate changes. Populations separated by physical geographical barrier including geographic distance and Yangtze River, as a result contemporary gene flow among L. auriculata populations showed drastic declines in comparison with historical gene flow, resulting in a high level of population divergence. Thus, patterns of genetic structure of L. auriculata can result from both geographic and environmental factors including climate changes. This information is helpful in forming conservation strategies for L. auriculata in China.Detecting how historical and contemporary factors contribute to genetic divergence and genetic structure is a central question in ecology and evolution. We examine this question by intergrating population genetics with ecological niche modelling of  Litsea auriculata (Lauraceae) is restricted to eastern China, occurring within a limited range from 30°21′–33°33′N and 112°1′–119°26′E. The current populations of L. auriculata are only scattered and distributed in a few mountain locations, mainly due to habitat loss1. This species is listed as endangered in the Chinese Plant Red Book1. Most extant populations are small and consist of less than 40 individuals. Previous studies of L. auriculata focused on its habitat characteristics2 and seedling biology4, but nothing is known about its population genetics. Determining effective conservation actions for this endemic species often requires knowledge of contemporary population structure, along with an understanding of the historical processes by which populations were shaped. Although its historical geographic distribution is unknown, extant Eastern populations are thought to represent a remnant of a formerly more widespread distribution. Therefore, these geographic discrete populations of L. auriculata represent an ideal system to elucidate the roles of historical vs. contemporary processes in determining the current patterns of disconnected population remnants and genetic variation5.6. The distributions of various organisms experienced concomitant expansions and contractions caused by the global cyclical cooling-warming events in the Quaternary glacial cycles6. Therefore, these cyclical events have played a dominant role in shaping the current distribution and genetic structure of many temperate species in the Northern Hemisphere7. East Asia has harboured the most diverse temperate flora in the world and was the most important glacial refuge for “Tertiary relics” throughout the Quaternary ice-age cycles. This region was never covered by massive ice-sheets during these glacial periods8; however, it experienced severe climatic oscillations throughout the Quaternary, with a dramatic effect on the evolution and distribution of both plants and animals9. Apart from historical factors such as Pleistocene range fragmentation and past demographic changes, more recent human-caused range fragmentation and isolation have also contributed to contemporary patterns of genetic variation within and between populations of species11. Evaluation of the relative influences of historical and contemporary elements on genetic diversity of forest trees has been a major topic in forest conservation for many years12.Pleistocene climatic cycling is one of the most important drivers of contemporary diversity and genetic structure in many temperate species and communitiesNe) based on extant samples14. Recently, a very powerful and flexible approach, Approximate Bayesian computation (ABC), has been used to estimate demographic and historical parameters  and quantitatively compare alternative scenarios15. This approach can be used to resolve many important questions in ecology and evolutionary biology15. In addition, it should be emphasized that molecular markers with different rates of substitution can capture the signatures of historical and contemporary processes and could therefore help to determine historical demographic patterns18. Nuclear DNA (nDNA) is recombined, bi-parentally inherited and affected by both pollen and seeds, which can complicate attempts to reveal species phylogeographic, evolutionary history and gene flow patterns19. By contrast, chloroplast DNA (cpDNA) in angiosperms is usually maternally inherited, and thus, phylogeographical patterns revealed by cpDNA-based markers are solely due to seed dispersal20. In addition, the mutation rates in cpDNA are low and cpDNA markers are not affected by recombination22. Therefore, comparisons of genetic structure detected by nDNA and cpDNA marker analyses can also assess differences between pollen and seed flow dynamics. Furthermore, phylogeographic studies has been integrated ecological niche modelling (ENM), which provided relevant information about the geographic distributions of species or genetic lineages and their relationship with the spatial distribution of genetic diversity24.Various approaches have been used to evaluate these influences, including using different types of analytical methods to test historical and contemporary gene flow or effective population sizes  and chloroplast (cpSSR) microsatellite markers to assess historical and contemporary evolutionary processes, investigate the causes of the endangerment of this species and provide basic guidelines for its conservation. Second, we also use approaches for genetic variation to detect changes in population size over different time scales in the present study. Third, we used ENM to infer the climatic potential niche of L. auriculata under current and Last Glacial Maximum (LGM) conditions. The aims of this study were as follows: (i) to evaluate the genetic structure of L. auriculata; (ii) to assess historical and contemporary evolutionary processes in shaping the genetic structure; (iii) to infer the species population demography using an ABC approach; (iv) to investigate how climatic and geographical variation over space and time to shape the patterns of genetic structure; and (v) to propose conservation and management of L. auriculata populations based on genetic structure and evolutionary history.Microsatellites (SSRs) are known to be highly polymorphic, codominant markers that have been widely used in studies of population geneticsL. auriculata. The number of haplotypes per population yielded 3 to 17 haplotypes in the eight populations, and the mean number of haplotypes for the eight populations was 6.5. The most polymorphic populations were seen in AY in Anhui province, with 17 haplotypes. The HY population had only 3 haplotypes. The most common haplotypes were H1 (24.7%) and H2 (26.5%), found in all populations, followed by H6 (11.4%) and H7 (11.9%). The haplotype H2 (26.5%) showed the highest frequency in all populations. A high level of genetic diversity at the population level was detected. The number of different alleles (Na) ranged from 1.571 to 2.429, and the number of effective alleles (NE) ranged from 1.112 to 1.590 (Table I), diversity (h) and unbiased diversity (uh) values were 0.268 (0.160–0.511), 0.159 (0.088–0.315) and 0.167 (0.090–0.323), respectively  and total diversity  in L. auriculata populations.The results of sequencing indicated that variations in allele size were due to the increase or decrease in the number of repeats. The seven cpSSR loci yielded a total of 20 alleles and 30 different haplotypes H1 to H30), among 231 individuals of  to H30, L. auriculata showed no obvious geographic structure  was significantly less than GST (0.221) (P < 0.05), indicating a lack of significant phylogeographic structure in L. auriculata populations.Median-joining haplotype network reflecting topology and haplotype frequency was constructed for cpSSRs Fig. . The disure Fig. . These rHT = 0.657, HS = 0.530) were observed. Genetic diversity at the population level, the mean number of alleles per locus (A) and the allelic richness (AR) for each population ranged from 3.38 to 6.38 and from 3.03 to 4.16, respectively (Table HO) and expected (HE) heterozygosity for each population ranged from 0.329 to 0.506 and from 0.404 to 0.642, respectively  and lowest in HY . In total, 34 private alleles (PA) were detected within eight populations, and PA ranged from 0.00 to 0.38 in eight populations. The highest PA values were found in AY and HX populations. Inbreeding coefficients (FIS) ranged from 0.098 to 0.271 (Table Ne) values for all L. auriculata populations were less than 50 (Table Ar) and expected heterozygosity (HE) were significantly negative correlated to the latitude  = 0.285, wright FST(n) = 0.165) was also observed based on cpSSR and nSSR data, respectively. Pairwise GST values based on cpSSR data among populations ranged from 0.004 to 0.220. The highest GST value was found between populations ZQ and AS (GST = 0.220), and the lowest between populations HJ and HY (GST = 0.004) , and the lowest between populations HJ and HY  Table . Meanwhi2 = 0.0199, P = 0.241) and nSSR  analysis , which suggest that species have undergone major contraction of their ranges. Moreover, the N1 group has the largest effective population size, and the N4 group has the smallest effective population size (N1 > N2 > N3 > N4). The estimated mean mutation rate of nSSRs was 1.74 × 10−4 (95% CI: 1.05 × 10−4–5.65 × 10−4).Among the ten predesigned scenarios in DIYABC analysis Fig. , scenarimc) throughout all populations. The average migration rates in all pairwise comparisons ranged from 0.007 to 0.176, with standard deviations less than 0.05 (Table mh) estimated by Migrate-N were significantly high and ranged from 0.037 (ZD to HJ) to 0.367 (from HJ to HY) , based on both CCSM  and MIROC  appeared among the widely disjunct populations  model, which also proved to be consistent with fossil pollen evidence in indicating extensive latitudinal range shifts, typically in the form of southward retreats during glacial events, followed by rapid expansions northward during inter-/postglacial events35. The tropical southern populations from potential refugia perhaps maintain higher levels of genetic diversity, consistent with the EC model9. The climatic fluctuations throughout inter-/postglacial events would have altered the distribution of habitats for L. auriculata, leading to variation in population continuity and isolation. The values of HE and Ar were higher in the southern area than the northern area, and higher in the eastern area than western area. These values significantly decreased as latitude increased, but increased as longitude increased in the present study  throughout Quaternary ice-age cyclesudy Fig. . This reL. auriculata populations were assigned to four groups  exists in optimum suitable habitats wherever in LGM or current, which contains the highest haplotype diversity, with the most (unique) haplotypes and private alleles . Climate fluctuations have enormous impacts on changes in a species’ suitable habitat, however these impacts are also influenced by geographic features. This result supports the idea that climatic and geographic features can impact the evolutionary history of a species.37. As a result, the distribution area of L. auriculata is drastic decreased and scattered in several mountains along the Yangtze River. Therefore, L. auriculata populations were expected to experience erosion of genetic variation, significant population bottlenecks, reduced remnant population size and increased population genetic divergence due to increased random genetic drift, high levels of inbreeding and reduced gene flow39. In the present study, L. auriculata did exhibit genetic signs of a high level of population divergence (FST(c) = 0.285, wright FST(n) = 0.165), a significant population bottleneck (Table Ne = 13.5), significant increases in inbreeding coefficient (FIS = 0.184) and reduced gene flow—i.e., the contemporary gene flow (mc: 0.007–0.176) is lower than historical gene flow (mh: 0.037–0.367) in L. auriculata populations. Nevertheless, high levels of genetic diversity were observed in L. auriculata at both the species  and population level .Our ABC and ENM analysis through time suggested that populations likely experienced expansion and retraction into and out of local refugia, and Quaternary climatic fluctuation may have played role in genetic structure as well40. This is consistent with increasing human activity during the past century, including agriculture, urbanization and deforestation2, which resulted in a dramatic reduction in the number of sites and population sizes of L. auriculata. In addition, in the present study estimates for Ne values were all less than 30, with a mean of 13.5  even when experiencing drastic habitat fragmentation. Genetic variation may decrease with reduced remnant population size, but not all fragmentation events lead to genetic losses and different types of genetic variation38. Thus, genetic drift does not appear to lead to decreased genetic diversity, but still increased population differentiation42. Furthermore, L. auriculata is a perennial species, and this habit may delay time between generations and buffer the effect of habitat fragmentation on genetic erosion43. Similar results were found in other endangered species in the same family, such as L. szemaois  in SW China42, Machilus thunbergii  in Southeast Asia44, M. kusanoi  in southeast China44, and Neolitsea sericea  in Southeast Asia28.The significant population bottlenecks may be explained by a recent decline in population size due to habitat destruction. Eight populations appear to have undergone recent bottlenecks Table , resultimc = 0.007–0.176) among populations was lower than historical gene flow , which is influenced by the mating system and the limited gene flow48. We found that inbreeding coefficients ranged from 0.056 to 0.265, and all populations significantly deviated from mutation-drift equilibrium under IAM assumptions and a mode-shift test  = 0.285, wright FST(n) = 0.165). Similar results have been reported in other endangered or endemic species of the same family, such as L. szemaois (Φst = 0.2420)42 and N. sericea (FST(c) = 0.355; FST(n) = 0.141)28. In addition, hierarchical AMOVA  greater than 50 is proposed to prevent inbreeding depression in the short-term (5 generations) and a Ne greater than 500 was proposed to maintain the evolutionary potential in perpetuity52. However, all of the estimated Ne in populations of L. auriculata were less than 30 (Table L. auriculata should be established to protect the habitat for this species (in situ).L. auriculata, which could be managed as four evolutionary units and assigned the highest priority protection. Considering the highest number of private alleles and haplotypes detected in the AY population, special attention should be paid to genetic resources from this region. To preserve all extant populations and their habitats, comprehensive ex situ conservation is viable by collecting seeds or seedling individuals from different populations from the three mountains, especially from the AY population.Our study showed significant genetic differentiation among populations based on cpSSR and nSSR data, which resulted in geographically defined genetic clusters of populations. Four groups were detected in in situ populations because wild populations lack effective pollen53. Prohibition on deforestation in L. auriculata distribution areas should also be implemented. Taken together, these measures could protect L. auriculata from extinction.Furthermore, artificial pollination is necessary to augment L. auriculata populations showed drastic declines in comparison with historical gene flow, resulting in a high level of population divergence. L. auriculata populations underwent expansion after divergence and dramatically decreased to the current small size with relative population bottlenecks due to climate changes. Thus, both geographic environmental factors including climate changes have shaped patterns of genetic structure in L. auriculata, along with small population sizes, significant recent population bottlenecks, significant increases in the inbreeding coefficient and contemporary limited gene flow. Information on the genetic diversity, genetic structure, demographic history and integrated with ENM of L. auriculata can establish effective and efficient strategies for their conservation.In summary, by using population genetics and ecological niche modeling analysis together, we were able to identify the many factors, historical and contemporary, have shaped population genetic structure in this endangered species. Moreover, geographical, environmental and climatic factors also contribute to patterns of genetic structure. Contemporary gene flow among Litsea auriculata occurs in deciduous broad-leaved forests or mixed coniferous broad-leaved forests at 500–1,250 m elevation, preferentially on valleys covered by deep and nutrient-rich soil, and their most important associated species are Cyclocarya paliurus (Juglandaceae), Nyssa sinensis (Nyssaceae), Tilia tuan Szyszyl. (Tiliaceae), and Emmenopterys henryi (Rubiaceae)1. Litsea auriculata is a diploid, dioecious and insect-pollinated tree , with dark purple, one-seeded fruits (drupes) that are primary dispersed by birds54.L. auriculata were collected from eight locations. Sample size ranged from 7 to 40 individuals per location  method57; however, only seven of them  showed polymorphism across all samples.For cpDNA analysis, we employed 33 universal chloroplast SSR (cpSSR) markersL. auriculata. Three of these nuclear markers  were developed by58 and five of them  were obtained by Chiang, et al.59.For nuclear DNA analysis, eight nSSR markers were polymorphic in L. auriculata, we used a tailed primer method to perform PCR: a U19 (5′-GGTTTTCCCAGTCACGACG-3′) was tailed to the 5′ end of the forward primer, and the U19 primer labelled with 6-FAM, VIC, NED or PET, was added to the PCR reaction mix. PCR amplification was performed in a reaction mixtures (10 μL) containing approximately 10 ng of template DNA, 0.2 mM of each dNTP, 1 × PCR buffer (16 mM (NH4)2SO4, 67 mM Tris–HCl (pH 8.8), 0.01% Tween-20), 1.35 mM of Mg2+, 0.5 U of BIOTaq DNA polymerase , and 0.5 mM of each of the three primers: a forward primer with a tail of the U19 sequence, a non-tailed reverse primer, and a 5′-labeled U19 primer.To amplify the SSR loci of TM analysis software version 4.0 (Applied Biosystems) according to a GeneScanTM 500 LIZTM Size Standard (Applied Biosystems).The PCR reactions were conducted using a Veriti Thermal Cycler (Applied Biosystems). The PCR reaction was performed using the following cycling conditions: denaturation at 94 °C for 1 min; followed by 30 cycles of 30 s at 94 °C, 30 s at annealing temperature of primer pair and 1 min at 72 °C; and final extension at 72 °C for 5 min. The PCR products were genotyped on an ABI 3730 Genetic Analyzer (Applied Biosystems). Allele sizes were determined using the GeneMapperTo investigate allele-size variation at the seven cpSSR loci, PCR products of each allele at each locus was subjected to DNA sequencing on an ABI 3730XL DNA Analyzer .Na), the effective number of alleles (NE), the Shannon index (I), diversity index, and unbiased diversity (uh) using GenAlEx 6.560. Mean within-population genetic diversity, species total genetic diversity, and population genetic differentiation were calculated treating alleles as unordered  and ordered , following the methods described by Pons & Petit (1996) using PermutCpSSR 2.061.For cpSSRs, haplotype composition, number of haplotypes and number of unique haplotypes were calculated for each population. A unique haplotype was defined as one found in only that population. We constructed a haplotype frequency map to examine whether haplotype distribution was geographically structured. The haplotype diversity as defined by cpSSRs in each population was quantified in terms of the number of observed alleles per locus (GST and RST). GST is only based on haplotype frequencies, while RST also takes into account haplotype similarities. These two parameters were compared via a permutation test, using 10,000 permutations by PermutCpSSR 2.061. A higher RST than the estimated GST indicates the presence of a phylogeographical structure. To examine the phylogenetic relationships of haplotypes, a haplotype tree was constructed in Network 5.0 using a median-joining haplotype network algorithm62. The distance between each pair of haplotypes was the sum of nucleotide differences between them over seven chloroplast microsatellite loci.Phylogeographical structure was analysed by comparing two coefficients of population divergence (HT) and average gene diversity within populations (HS)63, and at the population level, as the mean number of alleles per locus (A), allelic richness (AR), private alleles (PA), observed (HO) and expected (HE) heterozygosity. These calculations were performed using FSTAT version 2.9.3.264 and GenAlEx 6.560. Inbreeding coefficients (FIS) were calculated using FSTAT version 2.9.3.264. The deviation of FIS from zero was tested in each population using 1,000 permutation tests with a sequential Bonferroni correction65. The effective population sizes of each population (Ne) were estimated at three levels of the lowest allele frequency  with a 95% confidence interval using the program LDNe66. Significant tests of a linear parametric regression were performed for the two parameters (Ar and HE) against the latitude and longitude of the eight populations.For nSSRs, genetic diversity was assessed at the species level, as gene diversity in the total population  for cpSSRs, wright FST(n) for nSSRs) was also obtained using Arlequin version 3.568.Analysis of molecular variance  was calculated using PopGene 1.3270. For nSSRs, pairwise FST between populations was calculated and tested for significant differences using FSTAT version 2.9.3.2 .For cpSSRs, Nei’s unbiased genetic distance for all population pairs [GST  or FST/(1 − FST) (nSSRs) values and the geographic distance matrix were evaluated by the Mantel test71 in GenAlEx 6.5 software with 9,999 random permutations72.Correlations between the pairwise 73. Fifteen independent runs were performed for each K between 1 to 8 without prior information using the admixture model and assuming correlated allele frequencies. Each run consisted of 1,000,000 MCMC (Markov Chain Monte Carlo) repetitions after burn-in with 100,000 iterations based on the LOCPRIOR model74, an admixture model and the correlated allele frequencies model  described by Falush, et al.75. The optimal K was determined using the ΔK method implemented in STRUCTURE HARVESTER76. CLUMPP version 1.177 were used to summarize parameters across 15 runs at the optimal K value. DISTRUCT 1.1 software78 was used to visualize the STRUCTURE results after processing with CLUMPP.To determine the optimal number of clusters that compose the studied populations, we implemented the Bayesian algorithm analysis in STRUCTURE 2.3 softwareL. auriculata, we employed an approximate Bayesian computation (ABC) analysis in DIYABC v 2.179 to test evolutionary scenarios based on nuclear loci. Populations covering the entire species distribution were analysed to infer the history of the genetic structure indicated by nSSR analysis. To simplify the scenarios in the ABC analysis, we pooled all populations into four large populations based on the results of STRUCTURE analysis of this core data set: Pop1 , Pop2 (AS and HX population), Pop3 (AY population) and Pop4 (HJ and HY population). Considering the result of haplotype diversity of L. auriculata, Pop3 (AY population) was inferred as the ancestry population. A set of ten evolutionary scenarios were built and tested  using the logistic regression method80. For each set of scenarios, the most likely scenario was the one with the highest posterior probability value. To check the goodness of fit of the scenario, principal component analysis (PCA) was performed on the first 100,000 simulated datasets of the reference table in the summary statistics using the “model checking” option in DIYABC. Finally, to assess confidence in the model choice, type I and type II error rates was estimated with 500 pseudo-observed datasets (PODs) using the option “evaluate confidence in scenario choice”.To further understand the population demographic history of see Fig. : either 81. Preliminary runs were performed to adjust the MCMC mixing parameters of migration rates (m), allele frequencies (a) and inbreeding coefficients (f), to ensure proposed acceptance rates approximately 20–60%81. For the final runs, the mixing parameters m = 0.15, a = 0.4 and f = 0.5 were used. Ten independent replicates with different random starting seeds were performed with a burn-in of 5,000,000 iterations followed by 50,000,000 MCMC iterations and a sampling frequency of 2,000.To evaluate the direction and rates of recent migration  among populations, the BAYESASS 3.0.4 program was usedmh) among populations, we used Migrate-N version 3.6 (http://popgen.sc.fsu.edu/Migrate/Migrate-n.html)82. MIGRATE is based on coalescent theory to estimate effective population sizes  and symmetrical migration rates (M)  between population pairs. Migrate-N assumes that populations are in migration-drift equilibrium, that population sizes and migration rates are constant through time, and that populations are randomly sampled. We ran three replicates of Migrate-N using Microsatellite mode using a simulation of the single stepwise mutation model with constant mutation rates and starting parameters based on FST calculations. The program estimates the parameters θ and M using a Bayesian method84, both of which could be used to estimate the number of migrants per generation (Nm) into each population using the equation 4 Nm = θ* M. We estimated θ and M with slice sampling and uniform prior distribution . The three long chains were performed with 50,000-recorded genealogies at a sampling interval of 20 increments after discarding the first 10,000 genealogies (burn-in) for each chain. We used a static heating scheme at four temperatures  to efficiently search the genealogy space. The confidence interval for θ and the migration parameter M was calculated using a percentile approach84.To investigate historical migration rates , the Stepwise Mutation Model (SMM) and the Two Phase Model .In a recently bottlenecked population, the observed heterozygosity is higher than the expected equilibrium heterozygosity estimated from the observed number of alleles87. Maxent uses occurrence data along with environmental data to estimate the probability of species occurrence on the basis of a uniform probability distribution (maximum entropy) and on the presence data provided by the user88. L. auriculata occurrence points in the study were based on GPS data taken during our field work and from Nature Reserve records. We used all georeferenced localities. For occurrence points without geographic coordinates, which were then georeferenced by using the software Google Earth (http://www.ditu7.com/). A total of 26 occurrence points of L. auriculata were obtained to be used for ENM construction (Supplementary Table ENM were constructed using current climatic conditions and those of the LGM through the principle of maximum entropy model in Maxent version 3.4.1http://www.worldclim.org/)89. These variables represent summaries of means and variation in temperature and precipitation, and characterize dimensions of climate considered particularly relevant in determining species distributions89.We used 19 bioclimatic variables with a resolution of 2.5 min (~5 km) from WorldClim database 91 were used. Both models were run in Maxent using the settings chosen for current conditions. The area under receiver operating characteristic (ROC) curve (AUC) was then used to evaluate the model performance. An AUC score above 0.75 represent good model prediction92. All ENM predictions were then visualized in ArcGis 10.3 (http://www.arcgis.com/features/index.html), and the map of China (shapefile) is free downloaded from Global Administrative Areas version 2.8 (http://www.gadm.org/country).In order to construct niche model for LGM  conditions, we projected the current species’ bioclimatic niche onto past climate layers, which were downloaded from the WorldClim database at a resolution of 2.5 min as in the analysis above. Both the community climate system model (CCSM4)Supplementary Information


Brachypodium are promising model plants for energy crops since their selfing nature and short-life cycles are an advantage in breeding programs. The false brome, B. distachyon, has already been sequenced and new genomic initiatives have triggered the de-novo genome sequencing of its close relatives such as B. stacei, a species that was until recently mistaken for B. distachyon. However, the success of these initiatives hinges on detailed knowledge about the distribution of genetic variation within and among populations for the effective use of germplasm in a breeding program. Understanding population genetic diversity and genetic structure is also an important prerequisite for designing effective experimental populations for genomic wide studies. However, population genetic data are still limited in B. stacei. We therefore selected and amplified 10 nuclear microsatellite markers to depict patterns of population structure and genetic variation among 181 individuals from 19 populations of B. stacei occurring in its predominant range, the western Mediterranean area: mainland Iberian Peninsula, continental Balearic Islands and oceanic Canary Islands. Our genetic results support the occurrence of a predominant selfing system with extremely high levels of homozygosity across the analyzed populations. Despite the low level of genetic variation found, two different genetic clusters were retrieved, one clustering all SE Iberian mainland populations and the island of Minorca and another one grouping all S Iberian mainland populations, the Canary Islands and all Majorcan populations except one that clustered with the former group. These results, together with a high sharing of alleles (89%) suggest different colonization routes from the mainland Iberian Peninsula into the islands. A recent colonization scenario could explain the relatively low levels of genetic diversity and low number of alleles found in the Canary Islands populations while older colonization events are hypothesized to explain the high genetic diversity values found in the Majorcan populations. Our study provides widely applicable information about geographical patterns of genetic variation in B. stacei. Among others, the genetic pattern and the existence of local alleles will need to be adequately reflected in the germplasm collection of B. stacei for efficient genome wide association studies.Annual Mediterranean species of the genus  Brachypodium, a member of the Pooideae subfamily, has recently been developed as a new model system to study the evolution of grasses. The genome of the annual B. distachyon, commonly known as the false brome, has already been sequenced , 20 (4x), 30 (6x) chromosomes; B. distachyon  and B. stacei , and their derived allotetraploid B. hybridum  . The forthcoming genomes of B. stacei and B. hybridum will allow the development of several functional genomic analyses on these diploid and polyploid species and their potential transfer to other cereals and forage or biofuel crops. A recent update on phenotypic traits and habitat preferences of the three species has increased the number of discriminant features that distinguish them and has thrown new insights into their respective ecological adaptations  . This reptations . However. stacei . It woulBrachypodium stacei is a monophyletic annual diploid species that diverged first from the common Brachypodium ancestor, followed consecutively by B. mexicanum, B. distachyon and the clade of the core perennial taxa  of  studies , which celatives . We specB. stacei covering the whole distribution range of this species within the Iberia Peninsula, plus the continental Balearic (Gymnesic) Islands  and the oceanic Canary Islands   ; Fig. 1.B. distachyon , 5 μl PCR Master Mix (QIAGEN) and 2.5 μl DNA. The polymerase chain reactions (PCR) were carried out on a GeneAmp PCR System 9700 thermocycler with a thermal profile consisting of a 4-min initial denaturation step at 95 °C followed by 35 cycles of 30 s at 95 °C, 30 s at 55 °C and 1 min at 72 °C. A final 72 °C extension step of 30 min was included to promote non-templated nucleotide addition at the 3′end of the PCR product. Multiplexed PCR products were genotyped on an Applied Biosystems 3130XL Genetic Analyzer using 2 μl of amplified DNA, 12 μl of Hi-Di formamide and 0.4 μl of GeneScan-500 (LIZ) size standard (Applied Biosystem). Allele sizes were determined using Peak Scanner version 1.0 (Life Technologies). Within each population, all loci were checked for the presence of null alleles using MICRO-CHECKER v.2.2.3  according to the manufacturer’s protocol. The 181 samples used in this study were genotyped at 10 variable nuclear microsatellite markers (nSSRs) developed for  v.2.2.3 .Deviation from Hardy-Weinberg Equilibrium (HWE) was tested at both population and locus levels using FSTAT 2.9.3.2 . To calcaN, allelic diversity), mean expected heterozygosity (eH), mean observed heterozygosity (oH), allelic richness (RA), and inbreeding coefficient (FIS) using FSTAT 2.9.3.2  and mean observed heterozygosity (oH) for each population (s) was also estimated as s = 2FIS/(1 + FIS) (GenAlEx 6 software was used to estimate the mean expected heterozygosity (pulation . In addi1 + FIS) . SpatialK) from 1–10, imposing ancestral admixture and correlated allele frequencies priors, were considered. Ten independent runs with 50,000 burn-in steps, followed by run lengths of 300,000 interactions for each K, were computed. The number of true clusters in the data was estimated using STRUCTURE HARVESTER  for clusters identified in STRUCTURE, the results of the replicates at the best fit K were post-processed using CLUMPP 1.1.2  with ARLEQUIN 3.11 . In addiB. stacei. From the 19 populations sampled, only five were at HWE  at the 5% level after the sequential Bonferroni correction , and expected heterozygosity ranged from 0 to 0.145 (respectively for loci ALB139 and ALB087). FIS values varied between −0.068 and 0.8482  was preferred over the alternative ones  based on the DIC criterion.For each locus, observed heterozygosity values ranged from 0 to 0.058  as shown when projected into the geographic space  and 0.290 (Majorcan population BONA) with a CI of ± 0.03 at the 95% level, while mean expected heterozygosity varied between 0.090 (mainland population CALREL) and 0.239  varying between 0.0001  and 1 (Canary population of LAN). Therefore, the average rate of self-fertilization in B. stacei was estimated to be 71% considering all the populations  which differentiated all south (S) Iberian mainland populations from the southeastern (SE) mainland populations. The populations collected in the island of Minorca clustered with the SE mainland populations, whereas samples from the Canary Islands and most of the Majorcan populations were grouped with the S mainland populations, with the exception of the Majorcan population of BONA were most individuals were assigned to the same genetic group found only in the SE mainland populations (The Bayesian clustering program STRUCTURE found the highest LnP(D) and ΔK values for ulations . Some inulations . These rulations .K = 2. In this two-dimensional plot, the S mainland populations, as well as the SE ones and the Island populations  were well differentiated along the axis 2, which accumulated 26.2% of variance.The PCoA spatially separated SE Iberian mainland and the Minorca island populations from all remaining populations at both extremes of axis I, which accumulated 44.3% of variance , partialThe NJ tree separated all SE mainland populations, Minorca and the Majorcan population of BONA from the remaining populations, in a highly supported group (78% bootstrap support (BS) value; P < 0.00001). The analysis performed over the 19 populations sampled indicated that 75 and 25% of the genetic variation was attributed to variation among and within populations, respectively ] and the geographical distance of the populations studied here .The Mantel’s test did not detect any significant correlation between the genetic distance [FB. stacei were estimated as 79% across all populations, even reaching values as high as 95% in some populations (B. stacei is primarily a selfing species like its close congener B. distachyon (B. stacei) and 10.2 (B. distachyon) Mya ago  cleistogamous or cleistogamous-type florets having minute (< 0.8 mm) non-exerted anthers . However, islands could have also been colonized by North African coastal populations of B. stacei since ecological niche models predict the existence of conditions suitable for the existence of this species in that area  of the later island from multiple continental sources  will provide significant insights into the mechanisms of polyploid hybrid speciation within the complex B. distachyon–B. stacei–B. hybridum, also allowing comparative studies of genomics and development of functional traits in other crop plants. Biological features, such as a selfing system, a diploid genome and having amenable growing conditions are all advantages for the development of a model system and for genomic resources. All seem to be present in B. stacei. Previous studies showed that the species is diploid  a collection of different accessions reflecting different ecological pressures should be generated in order to recover the full genomic diversity of B. stacei; (2) the creation of a gene bank collection of these materials constitutes a practical and useful reservoir of genetic variation to avoid uniform cultivars and genetic erosion; (3) collections should be accessible to facilitate the interchange of material useful for breeding and other studies. Finally, there is a lack of information for other areas of the Mediterranean, especially the Eastern Mediterranean–SW Asian area, where B. stacei has been also found (B. stacei.Thus, to help future genomic initiatives involving so found . A compr10.7717/peerj.2407/supp-1Supplemental Information 1Click here for additional data file.


Lolium perenne L. ssp. multiflorum is increasingly common in California, USA, causing economic losses and the loss of effective management tools. To gain insights into the recent evolution of glyphosate resistance in L. perenne in perennial cropping systems of northwest California and to inform management, we investigated the frequency of glyphosate resistance and the genetic diversity and structure of 14 populations. The sampled populations contained frequencies of resistant plants ranging from 10% to 89%. Analyses of neutral genetic variation using microsatellite markers indicated very high genetic diversity within all populations regardless of resistance frequency. Genetic variation was distributed predominantly among individuals within populations rather than among populations or sampled counties, as would be expected for a wide‐ranging outcrossing weed species. Bayesian clustering analysis provided evidence of population structuring with extensive admixture between two genetic clusters or gene pools. High genetic diversity and admixture, and low differentiation between populations, strongly suggest the potential for spread of resistance through gene flow and the need for management that limits seed and pollen dispersal in L. perenne.Management of agroecosystems with herbicides imposes strong selection pressures on weedy plants leading to the evolution of resistance against those herbicides. Resistance to glyphosate in populations of  Weeds aWhether or not a weed population is able to adapt in response to management practices depends on whether that population contains the necessary genetic variation  is an annual grass weed that causes economic losses in annual and perennial cropping systems worldwide  do populations of outcrossing weeds contain high genetic diversity and is this diversity reduced in populations with a high frequency of glyphosate‐resistant individuals, (ii) is there evidence of genetic structuring and differentiation among populations of this widespread weed across an agricultural landscape, and (iii) is there potential for spread of resistance alleles across the landscape through gene flow?The goal of the current study was to characterize genetic variation of northwestern California 22.1L. perenne ssp. multiflorum populations in northwest California, we sampled 13 orchards and vineyards in 2013 from Sonoma County and Lake County  with two seedlings per pot and grown in the glasshouse at 27/15°C with ambient light conditions. At the tillering stage, individual plants were divided into genetically identical clones following the method described by Boutsalis  delivering 200 L/ha. Three weeks after glyphosate treatment, we scored each plant as alive or dead and characterized the percentage of resistant plants in each population by the percentage of plants surviving glyphosate treatment of the total number of plants treated. Plants from a previously characterized susceptible reference seed collection  method with 1,000 bootstrap replicates. We tested standard and adjusted FST values for differences using Student's t‐test.To assess genotyping errors, we tested for null alleles or genotyping stutter using Microchecker version 2.2.3  using FSTAT software version 2.9.3.2  was estimated for each of the 14 populations and averaged over populations for each locus, and Wright's fixation index (FST) was calculated over the 14 populations by locus, also in FSTAT. Statistical significances of FIS and FST were determined with 1,000 permutations. Observed heterozygosity (HO) and total gene diversity or expected heterozygosity (HE) at each locus were calculated using Genepop on the Web software version 4.2 , mean allelic richness (AR) defined as the number of alleles rarified to the smallest population sample size, and Wright's inbreeding coefficient (FIS) in FSTAT. Statistical significance of FIS was determined with 1,000 permutations. We also calculated HO and HE for each population in Genepop on the Web . We did not estimate population differentiation based on the statistic RST because stepwise mutations at microsatellite loci likely contribute relatively little to genetic differentiation between recently founded populations, such as those of weedy Lolium perenne . To test for linkage disequilibrium between each pair of loci in each population, we performed a pairwise log likelihood ratio test for disequilibrium in Genepop on the Web  with default Markov chain parameters. To detect recent changes in effective population sizes or population bottlenecks, we performed a one‐tailed Wilcoxon sign‐rank test for heterozygote excess compared to that expected under a drift–mutation model using Bottleneck software version 1.2.02  ranging from K = 1 to K = 12. Five independent runs at each value of K were performed using the population admixture model for potentially interbreeding populations and correlated allele frequencies. Likelihood values of ln P(D) were assessed for each run. The most likely value of K was inferred using the ΔK method , also interpreted as the proportion of an individual's genome that originated in each cluster  ranged from 0.147 to 0.754, while expected heterozygosity (HE) varied from 0.678 to 0.899. All loci revealed a reduction in observed heterozygosity compared to expected heterozygosity. Correspondingly, values of the inbreeding coefficient, FIS, were statistically significant for all loci and ranged from 0.068 to 0.824. Because a reduction in heterozygosity compared to that expected under Hardy–Weinberg conditions was observed across all loci regardless of whether null alleles were detected, it is unlikely that null alleles are the major cause of heterozygosity deficits. Per locus estimates of FST ranged from 0.006 to 0.088, indicating little genetic differentiation among populations at each locus  was high ranging from 8.7 to 12.1. Correspondingly, allelic richness (AR) ranged from 7.7 to 9.2 with an average of 8.4 over all populations (Table E) ranged from 0.74 to 0.81 among populations, whereas observed heterozygosity (HO) ranged from 0.40 to 0.52, indicating a heterozygote deficiency relative to Hardy–Weinberg expectations in all populations. Accordingly, values of the inbreeding coefficient FIS for populations were high ranging from 0.374 to 0.475  (Table A = 12.1) and the highest allelic richness (AR = 9.2), and no bottleneck was detected. Correspondingly, there is no significant correlation between frequency of resistant plants within populations and allelic richness . If population 13 is removed from the analysis, the correlation is stronger but still not significant .Three populations  containing a high frequency of resistant individuals (% R > 70%) all show a lower than average allelic richness , indicating that the genetic differentiation observed among populations is not related solely to geographic isolation.A principal coordinate analysis (PCA) of genetic distances between populations revealed differentiation among populations with grouping of some populations by geographic origin Figure . Most poRT = 0.018, p = .001), among populations within counties , and among populations within the total sample   and among individuals within the total sample  are high. Because of large genetic differences among individuals, 45.6% of the genetic variation is distributed among individuals within populations and 47.4% among individuals in the total sample, with 1.8% of genetic variation distributed between counties, 1.8% among populations within counties, and 3.5% among populations in the total sample, based on the F‐statistic for the corresponding measure.As population clustering by county was not explained by geographic distance, an AMOVA was conducted to determine how much of the genetic variance could be attributed to county or population differences. The AMOVA revealed low, but significant, genetic differentiation among counties (F1) Table . GeneticK values ranging from 1 to 12 with no clear maximum likelihood  indicating admixture between genetic clusters  still contained high levels of observed genetic diversity, despite evidence of a population bottleneck in some populations. The lack of correlation between the frequency of resistant plants within populations and the fixation index (FIS) , within‐population genetic diversity (HE) , and allelic richness (AR)  suggests that weed population size and genetic diversity may have been influenced by other weed control practices or environmental conditions, in addition to treatment with glyphosate. Herbicide rotations and mixtures, tillage, mowing, and pest and environmental pressures present variable selection pressures, which may reduce genetic diversity in all populations, making it difficult to detect reductions in diversity in populations with a high frequency of glyphosate‐resistant individuals. Repeated introductions of L. perenne seeds from other fields may serve to increase within‐population genetic diversity and compensate for alleles lost through selective sweeps and bottlenecks. It is also possible that less‐intensively managed L. perenne plants growing in roadsides or noncrop areas near the sampled populations may be experiencing less intense selection and subsequently a less intense population bottleneck and that gene flow through pollen exchange with these plants may restore some genetic diversity in populations undergoing selection for resistance.Populations which have undergone recent population bottlenecks and strong selective sweeps for adaptive traits may be expected to contain lower genetic diversity than populations, which have not yet adapted to the selection pressure. Populations with a high frequency of resistant individuals would be expected to contain lower genetic diversity than those with a lower frequency of resistant individuals. However, L. perenne was higher than that observed in other herbicide‐resistant agricultural weeds. Populations of another outcrossing grass weed species, Alopecurus myosuroides, in France with evolved resistance to ACCase‐inhibiting herbicides had lower values (0.246 and 0.240) of expected heterozygosity based on AFLP markers  based on microsatellite markers  based on microsatellite markers  was similar to values observed (HO = 0.40 and HO = 0.44) in some studies of perennial cultivars   in California populations was also similar or higher than that seen in studies of L. perenne cultivars using some of the same microsatellite markers  contain mostly individuals that assign to cluster 1 with q > 0.7, while populations with high frequencies of resistant individuals  contain a large proportion of individuals that assign to cluster 2 with q > 0.7 (Figure Together, data on spatial patterns of population structuring and frequencies of glyphosate‐resistant phenotypes allow comparison of hypotheses regarding single or multiple evolutionary origins and subsequent spread of glyphosate resistance in 7 Figure , in agreL. perenne ssp. rigidum (Busi, Yu, Barrett‐Lennard, & Powles, L. perenne. Spread of resistance alleles through gene flow could also result in populations and individuals containing multiple mechanisms of glyphosate resistance.STRUCTURE analysis revealed potential for future spread of resistance alleles through gene flow. Many admixed individuals with genotypes that assigned partially to each cluster were identified Figure . While tL. perenne populations in perennial cropping systems will likely require implementation of integrated pest management programs that include chemical and nonchemical techniques to not only control currently resistant plants, but reduce the intensity of selection pressure for future independent origins of resistance and limit the spread of resistance through gene flow. Increasing tillage where possible, mowing to reduce seed set, applying herbicide alternatives to glyphosate, or applying glyphosate in mixtures with other herbicides may help prevent or delay future origins of resistance by reducing population sizes and reducing the selection pressure of glyphosate in these systems. To limit spread of resistance through gene flow, cleaning weed seed from equipment and shoes moved between infested fields may help reduce long‐distance seed transfer. Mowing or tillage may also reduce short‐distance gene flow through pollen dispersal by reducing the number of flowers resistant plants produce, although these management techniques may not be able to entirely eliminate pollen production. It is not yet known whether a fitness cost is associated with glyphosate resistance in these L. perenne populations, and whether the frequency of resistance would be maintained in the absence of continued glyphosate use, as no fitness studies have yet been conducted in California populations of L. perenne and fitness costs associated with herbicide resistance vary depending on mechanism, the measure of fitness used, and genetic background of the population (Giacomini, Westra, & Ward, Successful management of glyphosate‐resistant L. perenne in orchards and vineyards of northwest California. In addition, microsatellite marker analyses revealed very high genetic diversity. All populations contained high diversity regardless of the frequency of resistant plants, contrary to what might be expected in populations undergoing strong selection for resistance. Genetic variation among populations and counties was low, in accordance with expectations for widespread and common species with highly outcrossing mating systems. The low genetic differentiation among populations and counties makes it difficult to draw conclusions about the specific origins and routes of spread of glyphosate resistance in northwest California from microsatellite variation. However, we can conclude that there were multiple origins of resistance in the region. In addition, there is potential for future spread of the resistance trait through gene flow, based on the high genetic diversity observed within all populations, the relatively low genetic differentiation among populations and counties, and the considerable admixture among populations detected in this study.The results of this study show that glyphosate resistance is common in populations of https://doi.org/10.5061/dryad.gs27k.Microsatellite genotype data have been archived in the Dryad Digital Repository:  Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Genetic distances, a phylogenetic tree and principal component analysis (PCA) revealed that the MCH, KGZ and UZK are genetically closer to the Han population of Liaoning and the Mongol population of Mongolia while the MGL are closer to Han, Japanese, Korean, Malaysian, Hong Kong Han and Russians living in China.The Xinjiang Uyghur Autonomous Region of China (XUARC) harbors 47 ethnic groups including the Manchu (MCH: 0.11%), Mongols (MGL: 0.81%), Kyrgyz (KGZ: 0.86%) and Uzbek (UZK: 0.066%). To establish DNA databases for these populations, allele frequency distributions for 15 autosomal short tandem repeat (STR) loci were determined using the AmpFlSTR Identifiler PCR amplification kit. There was no evidence of departures from Hardy–Weinberg equilibrium (HWE) in any of the four populations and minimal departure from linkage equilibrium (LE) for a very small number of pairwise combinations of loci. The probabilities of identity for the different populations ranged from 1 in 1.51 × 10 Many ethnic groups, including the Manchu (MCH), Mongols (MGL), Kirgiz (KGZ) and Uzbek (UZK) have lived there for hundreds of years2.Xinjiang is a multi-ethnic region and has played an important role in connecting eastern Eurasia and western Eurasia. It was crossed by the famous Silk Road, which linked trade between East Asia, Central Asia, and Europe3, they represent only 0.11% of the Xinjiang population4.The Manchu founded two Chinese Dynasties on the country’s inner plains: the Jin Dynasty, founded by the Nvzhen people, and the Qing Dynasty, founded by Huang Taijin in 1635. The history of the Manchu can be traced back 6000–7000 years ago (6–7 kya). Although the Manchu people can be found in all over China5. As well as Mongolia, Mongols currently live mainly in the Inner Mongolia Autonomous Region and some prefectures of Xinjiang Uygur Autonomous Region like Bayingolin (South East) and Bortala (North West). They represent 0.81% of the Xinjiang population4.The Mongols came from the area around the east bank of the ancient Wangjian River (present-day Eerguna River) in Inner Mongolia. “Mengwu” is the earliest Chinese name for “Mongolia”. It first appeared in the Tang dynasty (618–907). “Mongol” was initially the name for one of the Mongolian tribes. At the beginning of the 13th century, the Mongolian tribe headed by Genghis Khan unified the other tribes in the region and gradually formed a new ethnic community. Therefore, “Mongolia” became the name for a nationality instead of a tribe2. While the Kyrgyz are primarily located in Kyrgyzstan, they represent only 0.86% of the Xinjiang population4.The Kyrgyz (or Kirgiz) live mainly in the southwest of Xinjiang, especially in the Kezhilesu Kyrgyz autonomous state. They have a long history and have been known in China by many names. In the Han dynasty, they were called “Gekun” or “Jiankun”. Later they were called “Qigu” in the Jin dynasty; “Jiankun”, “Jikasi” or “Qiliqisi” in the Tang and Song dynasty; and “Jirjisi” or “Qirjisi” in the Yuan and Ming periods. All these names were based on “Kyrgyz”, which has had different Chinese translation at different times. The etymology of “Kyrgyz” is thought to be “40 tribes” or “40 girls”1. They represent 0.066% of the Xinjiang population4.The name “Uzbek” first originated with Uzbek Khan, a local ruler in the Mongol Empire in the 14th century. The Uzbeks are an ancient Iranian people that intermingled with nomadic Mongol and Turkic tribes that invaded Central Asia between the 11th and 15th centuries. The Uzbeks that live in China live mostly in Xinjiang near the border with Russia and the former Soviet Central Asian republics. Uzbeks have been trading in western China for centuries. In the 16th century, they began to settle in cities in Xinjiang. Most Uzbeks in China still live in the cities and are engaged in trading or business7. All these features render STRs as powerful genetic markers for inter-population studies8 and for the reconstruction of recent human evolutionary history9. In view of their high level of variability, autosomal STRs have been the most common genetic markers used in forensic applications, including personal identification and paternity testing10. Most forensic laboratories use commercially available kits for multiple STR genotyping11.Short tandem repeat (STR) loci, also referred to as microsatellites or simple sequence repeats (SSRs), are DNA sequences that contain a repeat motif of 2–6 bp and are characterized by a high level of relatively stable polymorphisms, a dense, uniform chromosomal distribution as well as short sequence lengths, which facilitates detection and analysis by PCR and sequencing12 and Kazak13 populations of Xinjiang but the Manchu, Mongol, Kyrgyz and Uzbek populations remain uncharacterised. In the present study, the 15autosomal STRs in the AmpFLSTR Identifiler kit  were examined in the MCH, MGL, KGZ and UZK minorities of the Xinjiang Uyghur Autonomous Region (XUAR).There have been previous studies of STR genotypes in the Uighur17, 1/1.75 × 1018, 1/3.66 × 1018 and to 1/9.94 × 1018, respectively. D2S1338 had the highest heterozygosities and powers of discrimination (PDs) in all four populations. FGA was the most polymorphic locus in the Mongol  and Uzbek  populations, respectively. D18S51 was most polymorphic in the Manchu population  while D18S51, D21S11 and FGA all had 15 unique alleles in the Kyrgyz population. Informativeness can be quantitatively measured by the polymorphism information content. Theoretically, PIC values can range from 0 to 1. At a PIC of 0, the marker has only one allele. At a PIC of 1, the marker would have an infinite number of alleles. A PIC value of greater than 0.7 is considered to be highly informative. Clearly, markers with greater numbers of alleles tend to have higher PIC values and thus are more informative14. The Manchu and Mongol populations have four loci with PIC < 0.7 while the Uzbek and Kyrgyz populations have only two loci with PIC < 0.7. Therefore, most loci exhibited a high informativeness, showing the potential of the Identifiler panel for differentiation of individuals and for paternity testing for the four ethnic minority populations in the Xinjiang Uyghur Autonomous Region of China.The distribution of allele frequencies and forensic statistical parameters in the four Xinjiang ethnic minorities are available from the authors upon request. Totals of 152, 165, 153 and 168 unique alleles were found in the Manchu, Mongol, Kyrgyz and Uzbek populations, respectively. The combined powers of discrimination (CPDs) for the 15 STR loci were 0.999 999 999 999 999 984 833, 0.999 999 999 999 999 990 057, 0.999 999 999 999 999 996 333 and 0.999 999 999 999 999 998 244, respectively. The combined powers of exclusion (CPE) for the 15 STR loci were 0.999 999 416, 0.999 999 483, 0.999 997 932 and 0.999 998 973, respectively. The probabilities of identity for the different populations were 1/1.51 × 10p > 0.05), while one STR locus was out of HWE for Manchu (D7S820), two loci for Mongol  and four loci for Uzbek . However, when a sequential Bonferroni correction15 was applied to mitigate against the so-called “multiple comparison problem” , no loci in any of the four populations were found to be out of HWE.All of the loci were in Hardy-Weinberg Equilibrium (HWE) in the Kyrgyz population (16. Exact tests for linkage equilibrium (LE) showed that the p-values of 50 pairwise combinations of STR loci  were below 0.05 and thus displaying LD. After a sequential Bonferroni correction15, only five pairs were out of LE. These were TH01/D8S1179 and D18S51/D13S317 in the Manchu population, vWA/D21S11 and D2S1338/D19S433 in the Uzbek population and FGA/D13S317 in the Kyrgyz population. All pairwise combinations of loci were in LE in the Mongol population. Therefore, of the 105 pairwise LE tests in each population, a maximum of two were out of LE in any population. Application of the “product rule” for calculation of random match probabilities across multiple loci is fully justified in the Mongol population and is unlikely to produce significant errors in the other three populations.Linkage disequilibrium (LD) can be caused by association between adjacent alleles co-inherited from single, ancestral chromosomes but may also be a result of selection, random genetic drift, the rate of mutation or recombination, nonrandom mating, founder effects, sampling effects, recent admixture, and population substructureK. That is, each repetition yielded ancestry proportions for each individual that were approximately equally distributed between each ancestral cluster and were no different between the four populations. STRs for forensic identity testing, such as those included in the Identifiler panel, are selected for high heterozygosity and minimal allele frequency differences between populations and so they generally make poor ancestry informative markers (AIMs) which require large allele frequency differences between populations. Further, pairwise FST between the four populations were generally < 0.03 except for Mongols at D5S818, D13S317, D16S539, D18S51, D19S433, FGA, TPOX and vWA. While we may have expected Mongols to exhibit some differentiation from the other three populations, it is not surprising that Manchus, Kyrgyz and Uzbeks are not differentiated by the STRs in the Identifiler panel using STRUCTURE.STRUCTURE analysis of the four populations from Xinjiang provided no evidence of population structure for any repetition at any value of FST) and associated p-values for each locus are available from the authors upon request.. The largest genetic distances in the Manchu, Mongol, Kyrgyz and Uzbeck populations were observed at vWA, D19S433, FGA and TPOX, respectively, while the lowest distances were observed at D8S1179 in the Manchu population and at CSF1PO in the Mongol, Kyrgyz and Uzbek populations. Genetic distances between populations based on Nei’s formula17 are available from the authors upon request. These were used to construct a neighbor-joining tree of the four populations from Xinjiang and the other populations , including 306 Manchu , 507 Mongols , 550 Kyrgyz  and 479 Uzbek . All participants gave their informed consent either orally and with thumb print (in case they could not write) or in writing after the study aims and procedures were carefully explained to them in their own language. The study was approved by the ethical review board of the China Medical University, Shenyang Liaoning Province, People’s Republic of China and in accordance with the standards of the Declaration of Helsinki. All blood samples were stored at −20 °C before DNA extraction. Genomic DNA was extracted from blood stains using the TIANamp Blood Spots DNA Kit  according to the manufacturer’s instructions and the concentration of DNA was quantified by absorption at 260 nm using an ultraviolet spectrophotometer .PCR co-amplification of fifteen autosomal STR loci  were performed in a fluorescence-based multiplex reaction using the AmpFLSTR Identifiler kit . From 1 to 2 ng of the target DNA was amplified according to the manufacturer’s recommended protocol. Thermal cycling was conducted under the following conditions: 95 °C for 11 min; 28 cycles of 94 °C for 60 s, 59 °C for 60 s, 72 °C for 60 s; and a final extension of 60 °C for 45 min. All loci were amplified in a GeneAmp PCR System 9700 thermal cycler .Amplified products were analyzed with reference to ABI GeneScan 500 LIZ internal size standard (Life Technologies) and AmpFlSTR Identifiler Allelic Ladder using an ABI 3130xl genetic analyzer  according to the AmpFLSTR Identifiler standard protocol. Analysis of data obtained from the genetic analyzer was performed using GeneMapper software v3.5.2O) and positive (AmpFlSTR Control DNA 9947 A) controls were employed for DNA extraction, DNA quantitation, PCR amplification and capillary electrophoresis. All negative controls displayed an absence of amplified product while positive controls were consistent with known genotypes.Negative (autoclaved deionized H18. Observed heterozygosity (Ho), expected heterozygosity (He), pairwise FST and exact tests for Hardy–Weinberg equilibrium (HWE) and linkage equilibrium (LE) between pairwise combinations of loci were performed using Arlequin v3.5 based on a likelihood ratio test for unknown gametic phase19. Empirical distributions were obtained from 10,000 permutations. Principal components analysis was performed with MVSP 3.1 (http://www.kovcomp.com) based on allelic frequencies of the 15 autosomal STR loci. Nei’s standard genetic distances between currently studied and previously published populations , Hungarian29, South Iran30, Azerbaijan31, Turkish Cypriot32, Afghanistan33, Bangladesh34, Malaysia35, Kadazan Malaysia36, Sindh Pakistan37, Iraq38, Pashtuns Afghanistan39, Tajik Afghanistan39, Uzbek Afghanistan39, Turkmen Afghanistan39, Mongols of Mongolia40, Hazara Afghanistan39, Kuala Lumpur Malaysia41, Miao42, East Mongolia of China43, Dong44, Bouyei45, Han Liaoning46, Manchu Liaoning47, Hui Qinghai48, Uyghur China49, Russian in China50, Dongxiang Qinghai51, Salar Qinghai51, Kazakh China13) were generated using the Phylip 3.69 package52 and visualized with Mega7 software53.Allelic frequencies and important forensic parameters, such as match probability (MP), power of discrimination (PD), power of exclusion (PE) and polymorphism information content (PIC) were calculated using PowerStats V1.254 was used to determine if there was any population structure within and between the Manchu, Mongol, Kyrgyz and Uzbek populations from Xinjiang. Raw genotypes are available from the authors upon request. The Admixture model with correlated allele frequencies was employed without prior population information (USEPOPINFO = 0). The number of inferred clusters (K) was varied from 2 to 10 with 10 repetitions of each K value and a total of 10,000 burnins and 10,000 Markov chain Monte Carlo (MCMC) simulations for each repetition.STRUCTURE (version 2.2)


Stenella longirostris) and the pantropical spotted dolphin (Stenella attenuata), using more than 3000 nuclear DNA single nucleotide polymorphisms (SNPs) in each species. Analyses for population structure indicated significant genetic differentiation between almost all subspecies and populations in both species. Bayesian phylogeographic analyses of spinner dolphins showed deep divergence between Indo-Pacific, Atlantic and eastern tropical Pacific Ocean (ETP) lineages. Despite high morphological variation, our results show very close relationships between endemic ETP spinner subspecies in relation to global diversity. The dwarf spinner dolphin is a monophyletic subspecies nested within a major clade of pantropical spinner dolphins from the Indian and western Pacific Ocean populations. Population-level division among the dwarf spinner dolphins was detected—with the northern Australia population being very different from that in Indonesia. In contrast to spinner dolphins, the major boundary for spotted dolphins is between offshore and coastal habitats in the ETP, supporting the current subspecies-level taxonomy. Comparing these species underscores the different scale at which population structure can arise, even in species that are similar in habitat (i.e. pelagic) and distribution.Little is known about global patterns of genetic connectivity in pelagic dolphins, including how circumtropical pelagic dolphins spread globally following the rapid and recent radiation of the subfamily delphininae. In this study, we tested phylogeographic hypotheses for two circumtropical species, the spinner dolphin ( Circumtet al. ). Pelagiet al. ,6, show et al. , show paet al. , or reflet al. . Generalet al. [Cetaceans are capable of long-distance movements, presumably increasing the tendency towards connectivity and stasis via gene flow. Davies , postulaet al.  describeet al.  did not Perrin  describeUnfortunately, testing hypotheses about populations in pelagic cetaceans is difficult given the logistical hurdles of sample collection from remote open ocean habitats . Unlike S. longirostris and S. attenuata, respectively) present an opportunity to test these phylogeographic hypotheses. Both species exhibit intraspecific morphological variation (figures S. l. longirostris) is distributed throughout the tropics with the exception of the eastern tropical Pacific (ETP), (ii) the Central American spinner dolphin (S. l. centroamericana), a coastal endemic subspecies in the ETP [S. l. orientalis), an offshore (pelagic) endemic subspecies in the ETP [S. l. roseiventris) [Two circumtropical cetaceans, the spinner dolphin and spotted dolphins  t the ETP , and (ivventris) . Finallyventris) .Figure et al. [et al. [et al. [These divisions were initially described using morphometric analyses ,15, but et al.  conducteet al. . This suet al. , using a [et al.  also fou [et al. , all theS. a. attenuata), and (ii) a coastal endemic subspecies in the ETP (S. a. graffmani) [Pantropical spotted dolphins are divided into two subspecies globally: (i) the nominate subspecies (affmani) ,20. Thesaffmani) , nuclearaffmani)  and mitoaffmani) . These gUsing broader sampling and novel sets of more than 3000 nuclear SNPs, we expand upon recent studies ,18 to teS. a. attenuata inhabiting offshore waters of the ETP), and another lineage that is exclusively the ETP coastal subspecies (S. a. graffmani) [Tursiops and Delphinus) [For the spotted dolphins, our null hypothesis is two lineages: one including all populations of nominate pantropical subspecies (including the affmani) –21. Thisaffmani)  in that lphinus) . The spolphinus) . Unfortuet al. [F-statistics. In fact, one of their simulations had characteristics very similar to our study . In this simulation the authors accurately detected genetic differentiation as low as FST = 0.01. Given the difficulty of obtaining larger sample sizes from many of the remote locations in this study, we have made use of large numbers of markers to obtain higher statistical power and precision for detecting population differentiation. Willing et al. [et al. [et al. [et al. [Analysing data from more than 3000 bi-allelic markers enabled us to test population structure hypotheses using relatively small samples sizes, such as those available for these animals from remote areas around the globe. Willing et al.  simulateg et al.  do make  [et al. , Narum e [et al.  and Smit [et al. ).2.2.1.https://www.marinemammalscience.org/about-us/ethics/marine-mammal-treatment-guidelines/), according to the permissible sampling techniques as stated on the project-specific Marine Mammal Protection Act (MMPA) Permit, and according to internal IACUC-approved methods.Skin samples were collected from spotted dolphins and spinner dolphins via biopsy dart  on reseaSpinner dolphin samples collected on research cruises in the ETP were assigned to a population based on the external morphology of the majority of animals in the school. This approach was taken because: (i) these often-large groups  contained individuals exhibiting a range of morphology; only after observing the group for some time could observers classify it to population, (ii) researchers collecting biopsies from dolphins near the bow of the research vessel found it very difficult to confidently classify fast-swimming individuals at sea, and (iii) there is significant overlap in range; therefore, geography was not a reliable predictor of population identity. Samples were selected from areas where the eastern and whitebelly types are known to overlap, as well as from outside the overlap region . The mosTissue samples were preserved in salt-saturated 20% DMSO or 70% ethanol and stored frozen at −20°C, or frozen at −80°C with no preservative. DNA was extracted using silica-based filter membranes  or by NaCl precipitation . DNA wasHiSeq 2000/2500  were completed at the Cornell University Institute of Biotechnology's Genomic Diversity Facility (http://www.biotech.cornell.edu/).Sequencing libraries were constructed using a ‘genotyping-by-sequencing’ protocol  as previ2.2.http://dx.doi.org/10.5061/dryad.h9q13 [A subset of the samples and resulting data have previously been used to investigate population structure in the ETP . For thead.h9q13 .2.3.strataG [FST) for each pairwise combination of populations [strataG package in R [Per-population heterozygosity was calculated using the strataG  package strataG . We thenulations –40. Poinage in R .Adegenet [. DAPC calculates principal components and then estimates a centroid and measures the variance for predefined populations. The discriminant analysis tests the probability of each individual falling in the space of each of the populations based on the ‘geometric space’ created by the centroid and variation. Before conducting the DAPC analyses, we examined the cumulative variance explained by the eigenvalues for the full range of principal components.We also directly tested hypotheses of population differentiation using multivariate analyses, specifically the discriminant analysis of principal components (DAPC) in the R package Adegenet . DAPC caAdegenet (simulated 10 times).Because of the size and variability of these datasets, spurious ad hoc solutions might be found. These include, but are not limited to, over-fitting . To assess if over-fitting was occurring, we calculated alpha-scores for each population and each dataset overall, simulated in To complete the DAPC, we then constructed synthetic discriminant functions that represent linear combinations of the allelic data with the largest between-group variance and the smallest within-group variance. In all analyses, we kept only the first three eigenvalues, as they represented the vast majority of the information. Finally, we plotted the first two discriminant functions as two-dimensional scatters in R .2.4.SNAPP, a Markov chain Monte Carlo (MCMC) sampler for bi-allelic data used to infer phylogenetic trees [FST and DAPC), we did not replicate these analyses with different samples selected from each population.Phylogeographic analyses were performed using ic trees . BecauseSNAPP was implemented in the software package BEAST 2 [strataG format (gtype) to nexus format, input into Beauti  and expSNAPP log files were read into Tracer  to evalDensiTree  to visu. 2.3.1; ) was use. 1.4.2; ).SNAPP can create long branches which make parameter estimation difficult and violate the assumptions of the Yule prior used in SNAPP .1 Midpoint rooting often results in the root being assigned to the longest branch, which is the case in both of our species. This may not, however, reflect reality in terms of ancestry. Thus, we have tried to avoid making inferences dependent on the location of the root. It is also possible that phylogeographic patterns in nuDNA trees could represent shared ancestry, admixture (i.e. genetic exchange between populations) or a combination of both.Although, there are methods for inferring the location of the root  based on3.The average read depth for spinner and spotted dolphin SNP genotypes was 36.8 and 31.71, respectively. To remove genotypes with high coverage possibly due to clonality, repetitive elements or gene duplications, those with coverage depth greater than 65.22 and 57.88 (the mean read depth plus >1.5 times the standard deviation) were removed from the spinner and spotted dolphin datasets, respectively. The final datasets for each species included 118 spinner dolphins and 75 spotted dolphins genotyped at 3340 and 3524 SNPs, respectively.H) is indicative of the overall genetic variation within the populations. The datasets for the two species were comparable in terms of overall heterozygosity: spotted dolphins = 0.2452 (s.d.: 0.1272); spinner dolphins = 0.2494 (s.d.: 0.1317).Summaries of the sample sizes and mean heterozygosity for spinner and spotted dolphins are found in tables et al. [The disparity in sample sizes between ETP populations and those from the global sampling made comparisons of heterozygosity within species difficult. However, in both spinner and spotted dolphin datasets, Hawaiian dolphins fell in the lower range. In addition, dwarf spinner dolphins from Australia exhibited the lowest mean heterozygosity measured in this dataset. Low heterozygosity could indicate smaller populations, inbred individuals, or poor sample quality that results in allelic dropout ,50. Finaet al.  estimateet al. . Despite3.1.FST estimates for spinner and spotted dolphins were significantly different from zero. For spinner dolphins, two pairwise comparisons were not significantly different: Central American versus Tanzania and Maldives versus Tanzania. The non-significant estimates for comparisons involving Tanzania could be a result of the small sample size for that group (n = 3). The lowest point estimate for FST was between the eastern spinner subspecies and the Tres Marias population (FST = 0.0035), but all point estimates between ETP populations were low (i.e. FST < 0.022). For spotted dolphins, all pairwise comparisons were significantly different from zero (p < 0.05). The largest differences observed involved comparisons of the ETP coastal subspecies with populations from the central and western Pacific Ocean. Lower pairwise values were found between the populations of the pantropical subspecies, despite long distances between them. Pairwise statistics for comparisons with the Maldives were not included because only one sample from this population was genotyped.Pairwise tests of population differentiation based on allele frequencies showed high levels of differentiation in both species tables  and 4 de3.2.k = 20) indicated that there was no reason for keeping a small number of PCs . To examine the breadth of possible reasonable results from the data, we conducted hypothesis testing using both the maximum recommended number of PCs and the ‘optimum’ number of PCs. The maximum number of PCs recommended by the developers of Adegenet is n/3, or 39 and 25 PCs for spinner and spotted dolphin analyses, respectively. We determined the optimal number of PCs using alpha scores. Alpha is the reassignment probability calculated using the given populations minus the reassignment probability for randomly permuted clusters, and indicates the optimum number of PCs . For our datasets 7 PCs was the optimum for the spinner dolphins and 6 PCs for the spotted dolphin data .The distribution of genotypes for spinner and spotted dolphins was analysed using discriminant analysis of principal components (DAPC). Before conducting the DAPC analyses, we examined the cumulative variance explained by the eigenvalues for the full range of principal components. This test , the populations are relatively tightly clustered with closely related populations overlapping figures , whereasGenomic variation across spinner dolphin individuals and populations was represented well by the first two eigenvalues of the DAPC although one eigenvalue was clearly dominant inset . This doAs shown in the inset of 3.3.The preceding has largely focused on population structure and not on relationships among different populations and processes leading to the patterns we observe today. To help visualize the results in an unbiased way, we present both unrooted and midpoint-rooted trees in figures SNAPP for a total of 401 000 chains. This was short of our desired >1M chains, but the sampler converged well during this amount of iterations . The developers of SNAPP suggest letting the chain run until the estimated sample size (ESS) is greater than 100, although they make clear that this is not an empirically tested threshold for stability. Our run resulted in an ESS for the posterior of 235, indicating adequate stability using this somewhat subjective criterion.Spinner dolphin phylogeographic topology was evaluated in c). One clade consists of the eastern tropical Pacific Ocean groups, comprised of whitebelly, eastern, Central American and Tres Marias populations. Within this ETP clade, whitebelly spinners were well supported as the most basal lineage.Spinner dolphins form two major, strongly supported (posterior probability = 1) clades of diversity c. One clThe second major clade contained samples from three ocean basins: North Atlantic, Indian Ocean, and central and western Pacific Ocean. The most basal lineage in this clade was the Atlantic Ocean spinner dolphins, followed by an Indo-Western Pacific clade with Hawai‘i as the most basal lineage. Relationships among the geographically disjunct Indo-Western Pacific groups were less well resolved, except for the strongly supported dwarf spinner dolphin clade.The spotted dolphin dataset was analysed for a total of 1 M MCMC chains. The trace of the posteriors resulting from MCMC sampler showed minor variability  and the ESS was 67—indicating a possible need for additional MCMC iterations. Aside from some of the terminal nodes, the consensus tree was well supported . The top4.Davies  proposed4.1.For spinner dolphins, our analyses supported: (i) a geographically widespread Indo-western Pacific lineage, (ii) a divergent ETP lineage, comprised of closely related subspecies/populations, (iii) a whitebelly spinner dolphin related to the ETP group, (iv) a divergent Atlantic lineage sister to the Indo-western Pacific group, (v) an independent Hawaiian lineage, and (vi) a dwarf spinner dolphin lineage sister to the Indo-western Pacific group.4.1.1.FST to detect allele frequency differences when using a large number of genetic markers (i.e. greater than 1000), even from small sample sets (n > 4–6) [FST results should remain preliminary given the sample size of only three [FST results that showed non-significant differences between Tanzania and Central America are probably anomalous as this connection was not supported by either the phylogeny or the DAPC results.A geographically disparate set of three spinner dolphin populations in the Indo-western Pacific  overlapped in genetic DAPC space and formed a clade in the Bayesian phylogeographic analysis. We were surprised by the amount of similarity between these groups, that included western tropical Pacific (Philippines), western Indian Ocean (Tanzania) and Central Indian Ocean . Separated by up to 5441 km, these populations have remained genetically similar. These results suggest that the Indo-Pacific boundary is not a barrier to genetic connectivity. Interestingly, Galver , using sn > 4–6) . The twoly three . Note th4.1.2.The longest branch in our Bayesian species tree separated spinner dolphins in the eastern tropical Pacific Ocean from the rest of the global distribution of pantropical and dwarf subspecies . This suOur modern conception of spinner dolphin relationships within the eastern Pacific Ocean  says there are two separate evolutionary lineages  and eastern) despite some ongoing genetic connection ,16–18. TFST estimates in that study and the present study support differences between these subspecies based on allele frequencies. However, viewed within the context of the overall global genetic diversity, the morphometrically and genetically distinct endemic ETP subspecies effectively occupy an overlapping ‘genetic space’. The two endemic subspecies of the ETP are joined by the shortest branches in our phylogeographic analysis as well; thus, despite being classified as independent subspecies, they are genetically the most similar of any pair of populations or subspecies in our dataset. The low support of nodes within the subspecies clade (posterior = 0.42) is not surprising, given how closely related they are thought to be [Our DAPC analysis showed CA, eastern and Tres Marias Island spinner dolphins in an overlapping cluster at one end of the DAPC space. Using a similar SNP dataset and the same DAPC analyses, Leslie & Morin  found seht to be . These r4.1.3.et al. [et al. [The whitebelly (WB) spinner dolphins were near the ETP endemics in the DAPC results—about half way between these subspecies and the pantropical Indo-western Pacific group. This is what we would expect given the hypothesis that it is a hybrid swarm between eastern and central Pacific pantropical spinner dolphins. Contemporary bi-directional gene flow would ensure the whitebelly genome remains similar to both the pantropical and eastern subspecies. According to our phylogeographic analyses, the WB spinner dolphin is a sister lineage to the ETP endemic subspecies. Although our unrooted analysis limits our ability to strongly infer ancestry, if this is a case of strict ancestry, the similarities in morphology between WB and the pantropical subspecies are synapomorphies, and the novel traits of the eastern and Central American subspecies are apomorphies. Alternatively, the WB spinners could represent reconnection between subspecies separated and independent for some time and only recently interbreeding. Andrews et al. , in theiet al. . We did  [et al.  saw in dFST estimates) of connection between the ETP spinner groups (including WB) and the Hawaiian pantropical spinners. Unfortunately, our sampling in the central Pacific was geographically sparse and may not have included the island-associate populations most closely related to the WB spinners. If there were going to be connections with the WB they might come from south of Hawai‘i. Adding data from these regions could be informative with regard to the level of connection between WB and the central Pacific populations. We recommend further testing for admixture in closely related ETP populations to examine the origin of the whitebelly spinner using methods such as those outlined by Durand et al. [We saw little evidence in this analysis  would decrease. Misassignment would create sample outliers in the PCA results, which could also expand population ellipses. In the phylogeography analysis, misassigned samples could bring ETP lineages closer together and decrease branch support within the ETP, but would not impact the broader global phylogeny.Misassignment of samples to the wrong ETP subspecies could have occurred in the field, and it would impact our results. However, the effects would be mostly restricted to comparisons among ETP groups that have been analysed more thoroughly in other treatments ,18. Sinc4.1.4.et al. [e slowed the effect of genetic drift over time.Based on Davies , we woulet al.  did inclCoryphaena hippurus) [Panamanian uplift occurred approximately 3.2 Ma , althougippurus) . These aNeither of these hypotheses adequately explains the positioning of the Atlantic genotypes near the whitebelly spinner group in genomic PC space. Of course, these explanations are not mutually exclusive.Alternatively, if large populations harbouring diverse genomes continued to disperse around southern Africa and the east Pacific basin, it is possible that similarities could remain even with low levels of ongoing or sporadic gene flow. Atlantic spinner dolphins tend to be more pelagic (found exclusively in water of greater than 2000 m) and form larger groups than the island-associated central Pacific spinner dolphins . They arOur ability to test the hypothesis of east–west pantropical stepwise dispersal patterns hinges on the evolutionary history of the Indian Ocean populations. If early stepwise dispersal occurred, leading to an Atlantic population in the North Atlantic and Caribbean, followed by extinction within the Indian Ocean, and subsequent recolonization events, the tight connection between Atlantic and Indian that anchor our null hypotheses of ocean-basin phylogeography might have been erased. Employing a method to root within-species trees, combined with the inclusion of additional samples for the eastern Atlantic and additional Indian Ocean localities, might help resolve this question.4.1.5.Despite being morphologically similar to other pantropical spinner dolphins, Hawaiian spinners are genetically unique and geographically isolated. The Hawaiian spinner genotypes occupied a very unique DAPC space and formed their own lineage within the pantropical + dwarf clade, the base of a well-supported Indo-Pacific clade. Although most closely related to this Indo-western Pacific core group of populations in the first eigenvalue, the second eigenvalue spread the Hawaiian genotypes away from the other populations. Mounting evidence, including those presented here, indicate that Hawaiian spinner dolphins are on a unique evolutionary trajectory and may warrant a unique subspecies.et al. [Other lines of evidence ,18,61 haet al.  define a4.1.6T-test. The two estimates were not significantly different at 95% confidence, indicating that our data do not show a significant difference in heterozygosity.Opposite the ETP arm in our DAPC analysis  are the two populations of dwarf spinner dolphins: Indonesia and Northern Australia. The Indonesian dwarf spinner ellipse overlaps somewhat in genotype space with the Indo-western Pacific core populations, but has one individual midway between the core and the distant Northern Australia cluster. This could indicate a potential area of admixture between the western Pacific and Indian Ocean populations and the dwarf populations, or it could indicate a cline of diversity from these Indo-Pacific pantropical groups through the Indonesian Archipelago and south towards the genetically distant Australian dwarf spinners. The Australia dwarf spinners had the lowest observed heterozygosity compared to the other populations, indicating that this might be a small population. But the variance in this measure was high. We tested whether there was significant difference between the heterozygosity of the Indonesian population and the Australian population using a FST between populations of spinner dolphins involved the Australian population of dwarf spinner dolphins . These results were corroborated by our DAPC analyses that indicated Australian dwarf spinners occupy a very different genomic PC space than the other subspecies and populations. In the pairwise comparison with the other dwarf population (Indonesia), FST was an order of magnitude larger (0.1698) than between the two morphologically distinct endemic ETP subspecies (CA and eastern: 0.0119). These results were unexpected given the morphological similarity between Australian and Indonesian dwarf spinner dolphins [sensu [The largest point estimates of pairwise dolphins . Howevers [sensu ) has bees [sensu ,64. CollIn our Bayesian species tree, the Indo-Pacific clade is split between the Indo-western Pacific group and a clade that links the dwarf spinner dolphin subspecies. Despite having relatively low support, this clade corresponds to the ‘Indo-western Pacific core’ from our DAPC analysis. Interestingly, within the dwarf spinner dolphin clade, the large differences in the DAPC analysis are not detected and the two dwarf spinner dolphin populations group together phylogenetically as suggested by morphological analyses .et al. [Orcaella) was described east of Wallace's line [Sousa was found to be separate from the Indo-Pacific Sousa species by a wide distributional gap that coincides with Wallace's Line [In the broader sense, Barber et al.  proposede's line  and recee's Line .FST and the distance in genotype space detected with DAPC, this Australian population of dwarf spinner dolphins  could warrant a unique population of dwarf spinner or a unique subspecies. Perrin et al. [S. l. roseiventris based on detailed morphometric analyses. They examined specimens from the Timor Sea and found them to be consistent with the dwarf spinner dolphins from the Gulf of Thailand. The only notable difference was northern Australia dwarf spinner dolphins had fewer vertebrae than those from the Gulf of Thailand. These authors did not examine dwarf spinner dolphins from Indonesia, but speculated that these animals inhabit shallow coastal waters of much of Southeast Asia. Further research effort should be applied to these areas to determine the geographical range and genetic diversity of dwarf spinner dolphins in Southeast Asia.Certainly, efforts should be made to estimate the abundance of these populations and better characterize them. Our sample set for northern Australia dwarf spinners was skewed heavily towards male dolphins , but Y chromosome linked SNPs would represent only approximately 1/44th the SNPs—a very small fraction of the overall data. Therefore, this is unlikely to contribute to the uniqueness of this population. Given our very high significance in pairwise comparisons using n et al.  erected 4.5.FST point estimates showed a similar pattern to the spinner dolphins in that pairwise comparison of the coastal ETP subspecies with the offshore ETP population of pantropical spotted dolphins had reduced FST compared to pairwise comparisons between other global populations . These results indicate a close relationship found in previous studies between the inshore/offshore subspecies in the ETP [n = 1) within the ellipse of the Guam/NMI population. It is difficult to draw conclusions based on one sample; therefore further studies should focus on expanding the sample of spotted dolphins in the Indian Ocean to test the uniqueness of the Maldivian population. The cluster of ellipses comprised from genotypes of spotted dolphins from Guam/MNI, Maldives and Indonesia is reminiscent of the ‘Indo-western Pacific core’ for spinner dolphins, with the exception of Indonesia, which in spinner dolphins was a more distant population. Hawaiian spotted dolphins spread out on the second eigenvalue, similar to spinner dolphins, to form a very distinct cluster. Again, this result in concert with the FST estimates, suggests that Hawaiian spotted dolphins may be on a separate evolutionary trajectory. Although also significantly different from zero, one of the lowest estimates was between Hawai‘i and Guam/NMI, suggesting similarities in allele frequency between these two Pacific island archipelagoes. FST comparisons involving the Indonesian and Hawaiian spotted dolphins had small sample sizes  and future studies should include more. The largest p-value observed was in the comparison of these two populations (0.0359); it is possible this is large because of low sample sizes and not because of a lack of population structure between these two distant localities.Spotted dolphins were highly structured across their range ; however the ETP ,21. MoreFor many marine taxa, including the spinner dolphin, the east Pacific basin is a major biogeographic barrier . Due to 5.Both spinner and spotted dolphins appear to have tightly clustered Indo-western Pacific core relationships characterized by recent divergences, incomplete lineage sorting and/or ongoing gene flow.S. l. roseiventris) is nested within the nominate pantropical subspecies (S. l. longirostris) making the latter non-monophyletic. Furthermore, our results do not support the connection between the Atlantic Ocean and the Indian Ocean via the South African species gate [In spinner dolphins, the east Pacific basin appears to be an important biogeographic barrier. Our results indicate deep separation between eastern Pacific clades and other conspecifics. The sister clade to the ETP group includes all other pantropical and dwarf populations. It is largely consistent with the morphology and current taxonomy with one issue; the dwarf spinner dolphin (ies gate . Insteadies gate  in a shaies gate ,64.Our analyses support the current taxonomic designation of the offshore spotted dolphin in the eastern tropical pacific as part of the pantropical subspecies. Although we were not able to test relationships with Atlantic populations of spotted dolphins, our results support the current taxonomy and indicate that, in contrast to the phylogeographic pattern in spinner dolphins, the inshore–offshore boundary in the ETP is stronger than the ecological and spatial divide of the pelagic expanse of the eastern Pacific.