Psidium guajava) is an aggressive invasive plant in the Galapagos Islands. Determining its provenance and genetic diversity could explain its adaptability and spread, and how this relates to past human activities. With this purpose, we analyzed 11 SSR markers in guava individuals from Isabela, Santa Cruz, San Cristobal, and Floreana islands in the Galapagos, as well as from mainland Ecuador. The mainland guava population appeared genetically differentiated from the Galapagos populations, with higher genetic diversity levels found in the former. We consistently found that the Central Highlands region of mainland Ecuador is one of the most likely origins of the Galapagos populations. Moreover, the guavas from Isabela and Floreana show a potential genetic input from southern mainland Ecuador, while the population from San Cristobal would be linked to the coastal mainland regions. Interestingly, the proposed origins for the Galapagos guava coincide with the first human settlings of the archipelago. Through approximate Bayesian computation, we propose a model where San Cristobal was the first island to be colonized by guava from the mainland, and then, it would have spread to Floreana and finally to Santa Cruz; Isabela would have been seeded from Floreana. An independent trajectory could also have contributed to the invasion of Floreana and Isabela. The pathway shown in our model agrees with the human colonization history of the different islands in the Galapagos. Our model, in conjunction with the clustering patterns of the individuals (based on genetic distances), suggests that guava introduction history in the Galapagos archipelago was driven by either a single event or a series of introduction events in rapid succession. We thus show that genetic analyses supported by historical sources can be used to track the arrival and spread of invasive species in novel habitats and the potential role of human activities in such processes.Guava ( Psidium guajava in the Galapagos Islands, as well as to determine its origins in mainland Ecuador. Interestingly, our results were able to connect genetic data and historical data of human colonization of the islands with the dispersal of an invasive species in this iconic archipelago.We aimed to reconstruct the invasion pathway of  For lin2.2.2FST values using the ENA algorithm for null allele correction. Lastly, FreeNA was used to calculate the Cavalli‐Sforza & Edwards genetic distances .FreeNA software was used to estimate frequency of null alleles using the EM algorithm , observed heterozygosity (HO), expected heterozygosity (HE), and F‐statistics for each SSR locus using the adegenet  was considered for rarefaction standardization, and an N = 16 for the comparison among mainland regions. Due to the fact that null allele frequency was elevated, especially for the mainland and Isabela populations, we calculated HE with corrected allelic frequencies for null alleles using the EM algorithm obtained from FreeNA  were performed, the p‐value was corrected using the BY procedure. For the corrected HE estimates, we used the Wilcoxon signed‐rank test to compare the global Galapagos HE and mainland HE estimates. When comparing the corrected HE estimates between the four different islands, we used Mood's Median test.In order to determine whether the 2.2.4Migraine software  and the stepwise mutation model (SMM) in order to define the bounds of the different demographic parameters: Current effective population size (2Nµ current), scaled duration of population size change (Dg/2N), and ancestral effective population size . These preliminary runs were performed in 4 iterations, with 500 point estimates and 2000 runs per point. Once the bounds were defined, we performed our inferences using the OnePopFlounderFlush demographic model (two variations in past population size) and the stepwise mutational model (SMM); we performed 14 iterations with 500 point estimates and 5000 runs per point.OnePopFlounderFlush model includes MLEs for different ratios between demographic parameters: (a) the current population/ancestral population ratio, termed the “N‐ratio curr‐anc”; (b) the current population/founding population ratio, termed the “N‐ratio curr‐found”; and (c) the founding population/ancestral population ratio, “N‐ratio found‐anc.” These ratios measure the magnitude of change in population size and can therefore be used to detect population expansions and contractions, including founding events . To test the differences between the N‐ratios, we checked that the 95% confidence intervals (CIs) excluded a 1:1 ratio between populations (N‐ratio = 1.0) . Both Dgμ and 2Nµ are scaled to the mutation rate (µ) of SSRs  was evaluated between 1 and 10, with 10 independent runs performed for each K value. 1,000,000 Markov chain Monte Carlo (MCMC) steps were used, with a 100,000‐step burn‐in period. The optimum value of K was determined using the method described by Evanno et al. , we first detected which regions in mainland Ecuador most frequently present the private alleles found in Isabela as reported by Urquía et al. in 2019. Then, the lowest DCH values and Nei distances between regions of continental Ecuador and each Galapagos population were determined. Finally, we used approximate Bayesian computations (ABC) implemented in the DIYABC software 2 distance for each pair of populations. Posterior probabilities (PPs) of each scenario  were calculated from the higher 1% of the simulations that approximate the observed data based on a linear discriminant analysis on the sum of squares in a logistic regression (the point estimate of the PPs is defined as the intercept of this regression). Posterior distributions (PDs) were calculated from the best scenario, and the model checking implemented in DIYABC was done to test how well this scenario conforms to the observed data considering all summary statistics available. Two model checking approaches were used: (a) direct quantification of the scenario‐simulated data sets that showed a lower value than the observed data set, and (b) PCA for visualizing graphically how observed data fitted the model‐simulated data.2.2.8FST and (du)2 distance for each pair of populations, and admixture summary statistics assuming that the Santa Cruz population comes from the admixture of the Isabela/Floreana and San Cristobal populations. PPs and PDs were calculated, and model checking was run as mentioned above for best scenarios.We used the ABC implemented in DIYABC to find the scenario that best explains the colonization pathway of guava from mainland Ecuador to the different islands in the Galapagos archipelago. One problem that arises with ABC is that the number of candidate models to be tested increases drastically with each population considered. Thus, hundreds of different scenarios could be potentially tested from our starting 5 populations (4 islands + mainland). For this reason, we systematically performed our analyses in different stages, each one with a reduced and computationally manageable number of tested scenarios. In the first stage of our ABC analysis, we tested 16 different colonization scenarios File , consideFor the second stage of our ABC analysis, we chose the best scenario from the previous stage and used these to further dissect the invasion history in finer detail. Firstly, the populations from Floreana and Isabela were separated to determine which island was invaded first. Scenarios considering a second parallel introduction to Isabela and Floreana were also tested, as well as a scenario where guava first arrives in Floreana before the other islands. Santa Cruz was excluded from this stage of the analysis since its place was already consistently determined in our previous work  2 distance for each pair of populations, and admixture summary statistics assuming that the Santa Cruz population comes from the admixture of the Isabela, Floreana, and/or San Cristobal populations. PDs were calculated for the constructed scenario, and model checking was done as well to test how well this scenario conforms to the observed data considering all summary statistics available.The final colonization model was constructed based on the results from stages 1 and 2, considering all islands as separate the mainland population as the ancestral one. Priors were based on stage 1 and 2 priors Appendix . SMM mutμ = 3.5e−04 (per locus per generation) was determined for guava SSRs from this study. This value was then used to scale Dgμ parameters to numbers of generations, and to estimate the time at which changes in population size  occurred, a phenomenon expected to coincide or be close to the times of introduction events . We found a low to moderate frequency in null alleles along all groups, with frequencies ranging from ~0 to 0.327 and a global mean of 0.155; in average, null alleles had a higher frequency in the mainland and Isabela populations, and a lower frequency in San Cristobal and Floreana  . The mainland population showed a larger number of private alleles (PAs) compared with the Galapagos populations , and HE within the Galapagos Islands, which was significantly higher than the diversity in San Cristobal , Isabela (p = 0.005), and Floreana (p = .005); the two lowest HE values (Isabela and Floreana) were equivalent (p = .056) . Regardless of the null allele correction, the inbreeding level assessed through the FIS was high in the mainland Ecuador and Galapagos populations (Table All mainland groups had roughly a similar level of genetic diversity Appendix . In the 6) Table . When cons Table . OverallNμ) would be in Santa Cruz  was found in the full data set  tended to be higher among the Galapagos populations than between the mainland regions   Table .FST and Nei genetic distances were significantly correlated with pairwise geographic distances  private alleles were found in Isabela, the only insular population presenting unique alleles. However, we were unable to propose a putative origin for the Isabela guava population by locating these private alleles in the mainland, as these were distributed at high frequencies in several mainland regions indistinctly. The Nei and  Figures  and 4. N Figures . The nuln Figure  showed tOur ABC analyses based on the mainland lineages defined by the STRUCTURE output  guava generations ago, 123 (95% CI = 0–3697) generations ago for Floreana, 51 (95% CI = 22–346) generations ago for Santa Cruz, and 19 (95% CI = 1–1560) generations ago for San Cristobal.The aforementioned estimates do not coincide with those obtained from the 44.1HE = 0.740; Aranguren et al., HE = 0.678; da Costa & Santos, μ = 3.5e−04; Table The invasive populations of guava in the Galapagos Islands display a lower genetic diversity when compared not only to the Ecuadorian population studied here Table  but also4.2According to our results, the guava populations in the Galapagos are genetically distinct from the populations in mainland Ecuador  from other countries. Nevertheless, our sampling in mainland Ecuador covered a representative portion of the known guava populations in the country, significantly increasing the probability that the source populations of the Galapagos guava were included if they were originally in mainland Ecuador Figure . Likewisr Lundh, . Neverthr Lundh, .4.4There has been extensive debate regarding the importance of neutral genetic diversity on the invasion success of introduced species  and less severe genetic bottlenecks (N‐ratio) of the Isabela and Floreana populations compared with that observed in San Cristobal  that indeed contradict in some cases the ABC estimations. This is especially evident for the San Cristobal case, where according to the ABC, it diverged from the mainland population thousands of generations ago (t4, Figure migraine, the founding event in this island occurred more recently than in any other Galapagos population. The lower limits of the CIs of the migraine estimates for the founder event in Isabela (Table migraine MLEs (Table migraine estimates as a proxy for this. Thus, in the mentioned case of San Cristobal for instance, the t4 event in our ABC final model (see Figure The final colonization model we present had a good statistical support, and agrees with our other results and with historical sources as well. However, this model has important limitations. Firstly, as suggested above, our model failed in explaining the distinction of the Isabela/Floreana lineage, especially considering it does not support a second introduction of guava into these two islands. Nevertheless, there could be alternative explanations for the presence of a different gene pool in Isabela and Floreana, which include isolation, founder effects, and genetic drift (Hagenblad et al., la Table  and of tla Table  and Isabla Table  sound mola Table . The estla Table ; File S2Es Table . AdditioEs Table . Another5Our results highlight the severity of the invasive process of guava in the Galapagos islands given the observed genetic diversity and history of is the populations in several islands. Despite the relatively lower genetic diversity of the insular guava populations compared with their mainland counterparts, the contribution of multiple sources in the mainland to the invading population's gene pool could have contributed to a high adaptability and success when invading the archipelago (Hughes et al., Information as the one presented in this study can be a first crucial milestone in developing a route map to face the guava problem in the Galapagos Islands.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Diego Urquía: Data curation; formal analysis; investigation; methodology; software; validation; writing—original draft preparation; writing—review and editing. Bernardo Gutierrez: Formal analysis; software; validation; writing—original draft preparation; writing—review and editing. Gabriela Pozo: Formal analysis; writing—original draft preparation; writing—review and editing. Maria Jose Pozo: Formal analysis, writing—original draft preparation; writing—review and editing. Maria de Lourdes Torres: Conceptualization; funding acquisition; project administration; supervision; resources; investigation; visualization; writing—review and editing.https://doi.org/10.5061/dryad.f4qrfj6wv.This article has earned an Open Data, for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.


Salvia miltiorrhiza) is a widely used medicinal plant for treatment of cardiovascular and cerebrovascular diseases. Because of excessive excavation by huge market demand and habitat loss by human activities, the wild population resources of S. miltiorrhiza have reduced drastically in recent years. Meanwhile, population status of two closely related species S. bowleyana and S. paramiltiorrhiza were in a trend of decreasing due to their potential replacement of S. miltiorrhiza. Particularly, S. paramiltiorrhiza was threatened and endemic to a small region in eastern China. However, to date there has been no conservation genetic research reported for wild S. miltiorrhiza population and its endangered relatives. Assess the wild germplasm diversity for S. miltiorrhiza and its related species would provide fundamental genetic background for cultivation and molecular breeding of this medicinally important species. In the present study, we investigated the genetic diversity, population structure, and intra/inter-specific differentiation of S. miltiorrhiza and above two relatives using 2b-RAD genome-wide genotyping method. By investigating 81 individuals of S. miltiorrhiza, 55 individuals of S. bowleyana and 15 individuals of S. paramiltiorrhiza from 23 locations in China, we obtained 23,928 SNPs in total. A comparatively high genetic diversity was observed in S. miltiorrhiza . The observed and expected heterozygosity in populations of these three species ranged from 0.0297 to 0.1481 and 0.0251 to 0.831, respectively. Two major lineage groups were detected in the examined S. miltiorrhiza populations. The results indicated that Dabie Mountain as a genetic diversity center of S. miltiorrhiza and possible complex inter-specific genetic exchange/hybridization occurred between S. miltiorrhiza and the two relatives. We suggest that strategic conservation and germplasm preservation should be considered not only for wild populations of S. miltiorrhiza, but also for its related S. bowleyana and S. paramiltiorrhiza.Red sage ( Medicinal plants are invaluable resource of maintaining health for the majority of world’s population. At present, more than 80% of the world’s population depends on herbal medicine for primary healthcare needs, while millions gain income from their wild harvest or cultivation, or are involved in their trading or processing . With thOne way to relief this situation is domestic cultivation. A number of governments and agencies are recommending that wild medicinal species should be brought into cultivation systems . IncreasSalvia miltiorrhiza Bunge (Lamiaceae), the red sage, is an indigenous medicinal herb in China. Wild populations of S. miltiorrhiza usually grows on the hillsides, stream banks and understories in broad-leaved deciduous forests in central and eastern China. Its dried roots, commonly known as Danshen, have long been used in traditional Chinese medicine for treatment of cardiovascular and cerebrovascular diseases . Particularly, populations of S. paramiltiorrhiza was critically threatened and can only be found in restricted areas in Hubei and Anhui, China  using 2b-RAD sequencing. We investigated the phylogenetic relationships and several aspects of the population genetics of focusing on wild S. miltiorrhiza populations including genetic diversity, population structure, and differentiation, as well as estimation of demographic history. We hope the methods and results presented here could be useful in guidance of wild germplasm conservation and management for S. miltiorrhiza and other medicinal plants in the future.In present study, we assessed the genetic diversity of S. miltiorrhiza , S. bowleyana  and S. paramiltiorrhiza   . Our samlations) . First, BsaXI) at 37° for 1 h, followed by enzyme heat inactivation at 65° for 20 min. The ligation reaction was performed by combining 5 μl of digested DNA with 20 μl of a ligation master mix containing 0.4 μM each of library-specific adaptors with fully degenerate cohesive ends (5′ -NNN- 3′), 0.2 mM adenosine 5′-triphosphate (New England Biolabs), and 1000 U T4 DNA ligase. Then PCR amplification was performed. Ligation was carried out at 16° for 3 h, with subsequent heat inactivation for 10 min at 65°. In Multi-isoRAD protocol, the single-tag constructs can be further digested by SapI to generate distinct cohesive ends and then ligated in a predefined order to produce five concatenated tags for Illumina paired-end sequencing using modified adaptors and biotin-labeled primers. After individual libraries were pooled into equimolar amounts, the pool quality was verified on Agilent 2100 Bioanalyzer. The paired-end RAD-seq were generated using Illumina Hiseq X ten platform  using 150 bp pair-end sequencing.Library construction and sequencing were conducted following S. miltiorrhiza (p < 0.05).Quality control were performed with Trimmomatic  accordiniorrhiza  using thiorrhiza . Finallyiorrhiza  to removTo infer relationships among samples, we performed phylogenetic analyses with concatenated SNP dataset using maximum likelihood (ML) method. The optimal substitution models for the ML phylogenetic analyses was determined by ModelFinder program  using thHe, Ho), nucleotide diversity (π), and Wright’s F statistics of genetic differentiation (Fst) and inbreeding coefficient IS(F) were assessed using the “populations” program in Stacks v2.2  formatted file with VCF files and sample list file, and demographic history was then inferred using the program Stairway plot v.0.2 . The generation time was set to 1 year per generation. The program BAYESASS version 3.0.3 , allele frequencies, and inbreeding coefficients were adjusted to 0.50, 0.95, and 0.50, respectively. To confirm convergence, each run was executed with different seed numbers, and trace files were examined for consistent oscillations using Tracer 1.7  of south Zhejiang province. In clade C, SBAQ and one SBAH individual of S. bowleyana formed the basal clade C1 (SH-aLRT/UFBoot: 99.6/87). Clade C2 (SBHL and SBHY) is sister to clade C3 + C4. Clade C3 includes SBAH and SBZS of S. bowleyana populations is in turn sister to three S. miltiorrhiza populations  with weak support (SH-aLRT/UFBoot: 32.4/54). SMHS, SMAJ and SMHB of S. miltiorrhiza and SBAY, SBZT and SBJY of S. bowleyana showed inter-mixed relationships in clade D.The ML phylogeny inferred from TVM + F + R2 model identified four well-supported clades (A–D), with SH-aLRT/UFBoot values displayed above branches . Except S. miltiorrhiza populations, the observed and expected heterozygosity range from 0.0297 to 0.0647 and 0.0251 to 0.0571, respectively. The mean values of π and FIS are 0.0282 to 0.0641 and −0.0066 to 0.0095, respectively. Significant difference of the genetic parameters were detected among the populations . In S. bowleyana populations, Ho and He range from 0.0353 to 0.1481 and 0.0322 to 0.0831, respectively. The mean values of π and FIS are 0.0371 to 0.0890 and −0.1129 to 0.0078. Except FIS, significant difference of the genetic parameters were also detected among the S. bowleyana populations . The mean values of Ho, He, π and FIS in S. paramiltiorrhiza are 0.0464, 0.0445, 0.0462, and 0.0018, respectively. High values of private alleles are observed in some populations sampled in the present study , 787  and 353 (S. paramiltiorrhiza), respectively. The summary statistics of genetic diversity of all three species are given in In nt study . AverageK = 5. Salvia paramiltiorrhiza is dominated by cluster 1. Four major clusters were observed in S. miltiorrhiza (cluster 2–5). It also indicated that cluster 4 and 5 were shared by six populations of S. miltiorrhiza  and S. bowleyana (K = 5). Different degrees of inter/intra-specific admixtures were observed in the studied populations. Further insights into population structure were obtained by plotting the five genetic clusters on the map  show a clear distance with S. bowleyana populations (SBZT and SBJY).For PCA plots, PC1, PC2, and PC3 explained approximately 33.43% of the total variation. When we grouped the samples according to the five clusters in Admixture analysis, cluster 1 and 2 overlapped to each other in PC1-PC2 plot , while stogether . ClusterS. miltiorrhiza analyses, that high percentage of the genetic variance (65.52%) came from the differences within populations. In S. bowleyana, most of the genetic variation (56.36%) is due to differences between populations within clusters. Pairwise genetic differentiation (Fst) between samples from sampling sites were different significantly, as shown in S. miltiorrhiza: R2 = 0.0013, p = 0.460; S. bowleyana: R2 = 0.0174, p = 0.450).AMOVA analyses was performed among species and within each species separately. For within-species analysis, we grouped the populations according to the five ancestry clusters recovered by Admixture analysis. The results revealed that inter-specific differences account for 13.12% of the genetic variation. Most of genetic variation is due to the differences within populations (49.78%) . The samS. bowleyana to S. miltiorrhiza (21.45%) estimated in BAYESASS , cluster 1 to 2 (3.23%), and cluster 3 to 4 (2.56%). Cluster 4 received comparatively higher gene flows from other clusters. This is also observed in Admixture analyses that most individuals from cluster 4 showed differential admixture levels with other clusters.For inter-specific migrations, we detected significant gene flow from BAYESASS . It is cS. miltiorrhiza, an initial shallow population contraction occurred at ca. 60 kya (thousand years ago), after which followed a population expansion and then a flat period until 8 kya. Then, a second more severe population bottleneck occurred during ca. 8–6 kya, which followed another population expansion and then a flat growth period maintained to present. For S. bowleyana populations, a deep population bottleneck was also detected around 8–6 kya, which followed a similar population dynamics as S. miltiorrhiza. Salvia paramiltiorrhiza experienced an early population contraction at ca. 104 kya, and then rapidly expanded and maintained its population size to present.Effective population size and demographic history of three studied species were inferred based on SNP frequency spectra and displayed on stairway plots . For S. Coptis species  despite its small population size and restricted distribution. This could be due to its outcrossing behavior and possible historical introgression with S. miltiorrhiza, which is supported by PCA plot (S. paramiltiorrhiza is nested within S. miltiorrhiza populations (K = 5) and PCA plot , which indicate that the reproductive barriers between them might be weak to some extent, leading to inter-specific gene flow. On the other hand, since these two species occur in partial allopatry, the undifferentiated genetic divergence could also be a result of retention of ancestral polymorphism, as incomplete lineage sorting could lead to a similar phenomenon which was observed in many other closely related taxa . This indicated that both species could potentially contributed to the ancestry of cluster 4. It is also noteworthy that populations of S. miltiorrhiza  and S. bowleyana  in cluster 5 did not mixed to each other as showed in PCA plot . However, in S. miltiorrhiza, most of variation were detected within populations, and low genetic differentiation were observed in all group settings. This might imply that in spite of frequent gene follow, these two species might experienced differential evolutionary history. Further studies on S. miltiorrhiza and S. bowleyana at a larger population scale will be necessary to clarify the boundary between these two species.Relationships between lla lips . Geneticowleyana . On one  species , which i species . The weated taxa . Pairwisnificant . In phylPCA plot , despiteS. miltiorrhiza, S. bowleyana, and S. paramiltiorrhiza, revealing that populations located in the Dabie Mountain range harbor the greatest amount of diversity (S. miltiorrhiza from the north and S. bowleyana from the south. They might have experienced continuous gene flow over time, increasing toward the present day. According to the demographic history of S. miltiorrhiza and S. bowleyana illustrated by stairway plot, they experienced a contemporary bottleneck occurred at 8–6 kya (S. miltiorrhiza and S. bowleyana may have shared refugia during climatic oscillations, where hybridization occurred. Salvia miltiorrhiza experienced an additional population contraction occurred at ca. 60 kya, which was consistent with the abrupt climate change and ecological turnover in late Pleistocene glaciation period (Salvia bowleyana and S. paramiltiorrhiza might avoid the contraction during the glaciation due to their further south distribution range compare to S. miltiorrhiza. Therefore, genetic exchange could also occur among them when S. miltiorrhiza retreated further south during that period. Population expansion of both S. miltiorrhiza and S. bowleyana took place during 6–4 kya, after which the population size of both species reached a stable status to present. No recent reduction in population size was observed based on genetic data. However, due to recent excessive excavation and habitat destruction, the wild populations of S. miltiorrhiza and its relatives reduced drastically. This could be explained by that the populations we sampled in the study were mostly collected in the nature reserves, where human activities are rare and restricted. Moreover, the population destruction started just decades ago, as such the role of genetic drift will be limited over such a short period of time (Our analyses provided insights into the distribution of genetic diversity in iversity . This ar 8–6 kya , which w 8–6 kya , which in period . Salvia  of time . OtherwiS. miltiorrhiza, S. bowleyana, and S. paramiltiorrhiza. Incomplete lineage sorting, repeated gene flow, as well as localized events of hybridization together might have shaped the current genetic structure and intermixed relationship among these three closely related species. The molecular data indicates that S. paramiltiorrhiza exhibits a unique lineage after comparing with S. miltiorrhiza and S. bowleyana populations. Additionally, several novel compounds has been discovered from the roots of S. paramiltiorrhiza (S. bowleyana, a complex inter-specific interaction history between S. miltiorrhiza was revealed. It leads to a better understanding of the evolutionary history and dynamics of this species complex group. As relatives with S. miltiorrhiza, S. paramiltiorrhiza and S. bowleyana could serve as valuable wild germplasm resources to improve the quality of S. miltiorrhiza or develop novel breedings. Protection of the wild relatives of the targeted plant species will greatly enhance the scale of the genetic diversity and increase resilience to the agricultural system through breeding practice (S. paramiltiorrhiza and S. bowleyana should be considered together as whole with S. miltiorrhiza in wild germplasm conservation practice. For S. paramiltiorrhiza, on the basis of its restricted geographical distribution and threatened condition, we suggested that in situ conservation efforts should be made such as establishing protected areas and population recovering in natural habitat. Our study also revealed Dabie Mountain as a genetic diversity center and corridor of these three species. This region should be prioritized as a potential area of conservation, which would ensure the survival and maintain the evolutionary potential of the group. In the meantime, seed bank construction and ex situ conservation through botanical gardens are also recommended, as it also effectively preserve the biological and genetic diversity of S. miltiorrhiza, S. bowleyana and S. paramiltiorrhiza for sustainable usage. We hope this study would provide a guidance to the conservation of other medicinal plants when species history are complex and wild relatives are involved.Our study suggests a complex scenario of inter/intra-specific evolutionary history of among iorrhiza . For S. practice . Therefohttps://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA716793.The raw sequencing data has been successfully uploaded to SRA in NCBI, Y-KW and Z-CQ conceived and designed the experiments and revised the manuscript. Y-BH and H-WX carried out investigation and collected materials. XZ, Z-CZ, J-JW, Z-CQ, and Y-KW analyzed the data and wrote the manuscript. Y-KW and Z-CQ acquired the funding. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Lobelia siphilitica across its range and genotyped plants using plastid and nuclear genetic markers. Similarity in spatial patterns of genetic and demographic variables may suggest that drift and/or gene flow have contributed to population sex-ratio variation in L. siphilitica. We found strong spatial structuring of extremely high female frequencies: populations with >50% female plants are restricted to the south–central portion of the range. However, we did not detect any spatial structuring in population size nor metrics of genetic diversity, suggesting that extreme variation in female frequency is not strongly affected by drift or gene flow. Extreme sex-ratio variation is frequently observed in gynodioecious plants, but its causes are difficult to identify. Further investigation into mechanisms that create or maintain the spatial structure of sex ratios in gynodioecious species will provide much needed insight.Variation in population sex ratio is particularly pronounced in gynodioecious angiosperms. Extremely high female frequencies in gynodioecious populations cannot be readily explained by selective forces alone. To assess the contributions of drift and gene flow to extreme sex-ratio variation, we documented sex ratio and population size in 92 populations of  Understanding the maintenance and partitioning of within-species phenotypic diversity is a critical goal of evolutionary ecology. One common type of within-species phenotypic diversity is variation in population sex ratio ,2,3,4,5.Rf) alleles, allowing them to produce pollen despite carrying CMS [Rf alleles enter populations through either mutation or gene flow. However, it is the maintenance of polymorphism at CMS and/or Rf loci within populations that results in the production of female plants. This is because random mating is likely to result in mismatched CMS and Rf alleles in offspring, especially when there are many unique alleles at CMS and/or Rf loci [Rf loci appears to be primarily maintained long-term by balancing selection  [Sex ratios in natural populations of gynodioecious angiosperms can be strongly female biased >50% female), but populations are more often hermaphrodite biased  0% female. In thesying CMS ,11,12,13lection) ,15,16 unlection)  show thaRf polymorphism [Rf alleles, especially in smaller populations [Rf polymorphism. This is especially the case when proximal populations harbor unique assemblages of CMS genes and Rf alleles [Non-selective forces, including genetic drift and gene flow, could contribute to extreme sex-ratio variation in gynodioecious species through effects on CMS–morphism ,17. The morphism . Howevermorphism . Geneticulations ,20,21,22 alleles ,24,25. I alleles ,27,28,29Lobelia siphilitica (Campanulaceae). Lobelia siphilitica L. var. siphilitica is a perennial wildflower that occurs throughout northeastern North America  and neutral nuclear genetic markers. We note that, although strong linkage disequilibrium (LD) between pt and mitochondrial (mt) variation is expected, it has been shown to be relatively weak in L. siphilitica [L. siphilitica, especially if multiple metrics show similar patterns of geographic structuring.In this study, we sampled and genotyped plants from 92 populations across a central–peripheral gradient to capture the demographic , geographic, and genetic correlates of female frequency. To test the hypothesis that genetic drift and/or gene flow have contributed to demographic and geographic structuring of high female frequencies in hilitica , meaningn = 91 populations). Female frequency varied between 0 and 1 , 0.1–10% (n = 23 populations), 10.1–50% (n = 23 populations), and >50% female plants (n = 20 populations). Two-thirds of the sampled populations were ‘small’ .Both population size and female frequency were highly variable. Population size ranged from two to several thousand flowering stems per site , these 120 haplotypes were condensed into 13 haplogroups using parsimony (h) ranged from 0 to 0.81 (mean = 0.187) across populations.We sequenced one hypervariable intergenic region of the plastid genome , respectively, for a total of 50 unique alleles (Na in Ho) and expected (He) heterozygosities were moderate (h) was significantly correlated with nuclear allelic diversity  but not with heterozygosity . We detected 12, 17, and 21 alleles for our three nuclear microsatellite loci  and mid-longitudes . Consequently, mean female frequency was more than 7-fold higher in central populations  than peripheral populations , and populations with >50% female plants (n = 20) were exclusively central. Based on Moran’s I, female frequency was highly spatially structured , and varied little in size across latitudes . Notably, while both population size and sex ratio varied with latitude, population size did not account for any variation in population sex ratio , and there was no significant difference in mean population size between central and peripheral populations .In contrast to sex ratio, population size was not spatially structured , nor in microsatellite diversity . Plastid haplogroup diversity (h) did not vary with sex ratio either continuously  or categorically . Likewise, h did not differ significantly between central and peripheral populations , nor with population size . For nuclear microsatellites, Na and Ne were slightly higher in large vs. small populations , but other groupings (including population sex ratio) showed no significant variation in any metric of nuclear genetic diversity.We detected no spatial structure in pt haplogroup diversity (FST = 0.75) and relatively isolated (estimated Nem = 0.166) based on pt haplogroups, consistent with effects of historical migration on population structure. Likewise, Mantel correlations revealed slight but significant isolation by distance  and notably high pairwise genetic distances for even the most proximal population pairs  and low rates of migration  and their relative abundance in populations . These five spatially clustered haplogroups were either predominantly eastern or predominantly western . One of these five structured haplogroups (C23) showed additional north–south structuring, with all but one case restricted to the southeastern corner of the sampled range in West Virginia and Virginia . However, for five of the six common haplogroups, the presence vs. absence of each haplogroup was not associated with differences in sex ratio between populations, suggesting no relationship between specific pt haplogroups and female frequency . Although populations that contained C23 had significantly lower female frequencies than those without C23 , these sites are likely low female because they are almost exclusively peripheral, not because they harbor haplogroup C23. Five of the six common pt haplogroups were significantly clustered based on both their presence in populations .Population genetic structure is poorly explained by demography and geography. Little molecular variation was explained by any among-group comparisons in the AMOVAs. However, the few small but significant effects were geographic rather than demographic . CentralL. siphilitica. Sex ratios were strongly spatially autocorrelated, with populations over >50% female restricted to the south–central portion of the sampled range  of genetic drift and gene flow to extremely high female frequencies in populations of gynodioecious ed range . Howevered range . Thus, sL. siphilitica are most strongly associated with unique mitochondrial haplotypes rather than high cytonuclear polymorphism overall, as is commonly predicted [While we observed strong central–peripheral structuring of female frequencies, none of the other predictions of the abundant-center hypotheses were supported by our data. We did not observe higher levels of pt or nuclear genetic diversity in central populations nor in populations with more female plants. Central populations were not larger in size and did not experience more gene flow than peripheral populations. Combined with results of our previous work , these rredicted ,23,33. WL. siphilitica is consistent with studies of some gynodioecious species but not others. They are consistent with results from Beta vulgaris ssp. maritima (Chenopodiaceae), where non-selective forces also do not strongly affect population sex ratios, despite high population differentiation and low migration [L. siphilitica as well as several other gynodioecious species [Our finding that genetic drift and gene flow have not contributed significantly to extreme sex-ratio variation in igration ,34. Howeigration ,22 or geigration  can cont species ,35,36. L. siphilitica: female plants were much more frequent in southern-central populations compared to northern or peripheral populations (Nemophila menziesii (Boraginaceae) also found that female plants were more common in the central portion of the species range [Plantago maritima (Plantaginaceae) [Kallstroemia grandiflora (Zygophyllaceae) [Lobelia spicata (Campanulaceae) [Beta vulgaris ssp. maritima [We documented strong central–peripheral structuring of population sex ratios in ulations . A rangees range . It is yinaceae) ; Kallstrllaceae) ) or decrulaceae) ), and a maritima ). Howevemaritima ,35,36 ormaritima , such thL. siphilitica that occupy previously glaciated areas. The significant spatial autocorrelation we observed for individual pt haplogroups (Campanulastrum americanum (Campanulaceae) [C. americanum, the pt spatial genetic structure in L. siphilitica is less pronounced across the species range [Lobelia siphilitica also exhibits high within-population pt diversity relative to C. americanum; several of the pt haplogroups were present range wide and even proximal L. siphilitica populations were highly genetically differentiated. A more fine-grained assessment of historical biogeography in this species would help evaluate whether historical events may have contributed to the geography of population sex ratios.While genetic drift and gene flow can reflect contemporary population dynamics, present-day populations also bear the signatures of historical processes, particularly in northern-temperate species such as logroups  suggestslogroups . Post-glulaceae) ,40. The es range . LobeliaL. siphilitica var. ludoviciana in parts of the range where L. siphilitica var. siphilitica is absent , which are inferred to be greater in L. siphilitica populations that host more female plants [Rf should result in more female plants [Lobelia siphilitica populations with more female plants host more rare mitochondrial haplotypes likely to carry novel sterility genes [While our results show that population sex ratios in gynodioecious e plants ,42,43. We plants , there ie plants , then coty genes . If mechL. siphilitica that is not readily explained by the effects of genetic drift or gene flow. Given that female plants are largely geographically restricted to the southern-central portion of the species range, environmental conditions may play a key role in sex-ratio patterns. Other gynodioecious species studied to date differ from each other in the role of selective and non-selective processes affecting sex-ratio variation, the range of female frequencies observed among populations, and the degree of spatial/geographic structuring of population sex ratios [L. siphilitica (as well as other gynodioecious species) will provide much needed insight into how evolutionary forces cause populations to become differentiated.In conclusion, we see strong spatial structuring of extremely high female frequencies in x ratios . This laLobelia siphilitica L. var. siphilitica (Campanulaceae) is a perennial wildflower that occurs throughout northeastern North America  [a A. DC.  occurs fterility . The sexe plant) . In natue plant) . Seeds ae plant) .L. siphilitica across its range. We obtained samples from 71 of these sites between July and September of 2009 and from 21 new sites plus 14 resampled sites in 2011. Very few sites were ambiguous in terms of delimiting clusters of L. siphilitica plants as populations; in this analysis, we considered plants to be in separate populations when one patch was not visible from another. Along with GPS coordinates at each site, we estimated the adult population size by counting flowering stems; we did not include immature, non-flowering leaf-rosettes in estimates of population size. We determined population sex ratio using floral morphology. In 18 populations, a few individual plants produced both floral sex phenotypes ; these ‘partially sterile’ (gynomonoecious) individuals were included in our analyses but were not considered to be ‘female’ in the calculation of female frequency.Using specimen-collection databases . For six of seven additional sites hosting very large populations and three additional populations extending into private property, we estimated population size by counting a subset of flowering stems and estimating the total population size by eye based on area and plant density. Female frequency for all seven very large and three partially inaccessible populations was determined based on a subsample of at least 100 plants along transects or on all accessible individuals, respectively. For the 14 populations resampled in 2011, analyses were conducted with the 2009, 2011, and averaged population sizes and sex ratios; sampling year did not affect the results, so we present data based on averaged population sizes and sex ratios (data not shown). We collected whole plants as voucher specimens for all populations >20 plants but used photographs to voucher smaller populations; specimens are lodged at the Kent State University Herbarium (KE) with accession numbers 64476–64499, 65918–65947 and 66054–66071 (midwestherbaria.org) and photos are available by request from the authors.We collected and dried bud and/or leaf tissue in silica gel from 2 to 66 plants in 91 of the 92 populations surveyed and generally sampled 10% of the censused population size. Plants were sampled systematically such that we collected tissue from every 10th plant counted in the census. If populations were smaller than 20 plants, we collected tissue from all individuals. Dried buds (when possible) or leaf tissue samples were transferred to −80 °C for at least one week before DNA isolation. We extracted DNA from bud and leaf tissue using a modified CTAB/chloroform protocol of Doyle and Doyle  and storpsbK–rps16; psbK–rps16 region in a single PCR reaction, we ran two separate reactions with primer pairs 297/426 and 425/427 amplifying into rps16  [psbK–rps16 voucher sequences. New sequences were manually checked to confirm variable sites and haplotype before being added to the haplotype library. In total, we haplotyped 2–46 individuals (mean = 6.98) from each of 83 L. siphilitica populations   and manuifs see: .psbK–rps16 sequences to construct a pairwise distance matrix that excluded the minisatellite locus. We then inferred maximum parsimony trees using PAUP* 4.0b10 [We used inferred and complete * 4.0b10 . Details* 4.0b10 , which wLob6, Lob9, and Lobtri1 , all pt genetic analyses were carried out using 13 inferred phylogenetic haplogroups based on the topology of the maximum parsimony tree . The comh) asip is the frequency of a haplogroup, and n is sample size per population [Ho) at nuclear microsatellites across all populations and the total number of alleles per population using GenAlEx [h, Ho, and the total number of alleles to increase with female frequency and tested this using linear regressions. We tested whether female plants were more likely to be heterozygous than hermaphrodites using a χ2 test in JMP v. 14  [We calculated metrics of population-genetic diversity for both pt and nuclear markers. We calculated pt haplogroup diversity  .h, Ho, and the total number of alleles would be higher in populations with more female plants. We used analyses of molecular variance . We ranquin 3.5 ) to see ite data . We usedFST for both pt haplogroups using Arlequin 3.5 [Nem from FST values, whereFST values for nuclear microsatellites. We interpolated missing data. For estimates of isolation by distance, we used the package ‘fossil’ [To estimate population differentiation based on the distribution of alleles among populations, we calculated quin 3.5  and nuclquin 3.5 . We estiquin 3.5 . To look markers  and(3)N GenAlEx . We used‘fossil’  to calcu‘fossil’ .h, Ho, and the total number of alleles, expecting these metrics to decrease with population size . In add NC, USA ) and gro NC, USA ). We als NC, USA ).o,h, H total number of alleles, and individual pt haplogroups (both presence and relative abundance). Significant Moran’s I tests were followed by linear and non-linear regressions against latitude and longitude on quantitative metrics and with 2-tailed t-tests on presence of particular haplogroups. We also used 1-tailed t-tests to test the a priori expectation that h, Ho, and the total number of alleles would be higher in central vs. peripheral populations. We used AMOVAs to examine how well central–peripheral groupings explained genetic differences among populations .


Arapaima gigas is the only living representative of the Arapamidae family. Environmental pressures and illegal fishing threaten the species’ survival. To protect wild populations, a national regulation must be developed for the management of A. gigas throughout the Amazon basin. Moreover, the reproductive genetic management and recruitment of additional founders by aquaculture farms are needed to mitigate the damage caused by domestication. To contribute to the sustainable development, we investigated the genetic diversity of wild and cultivated populations of A. gigas and developed a panel composed by 12 microsatellite markers for individual and population genetic tracing. We analyzed 368 samples from three wild and four farmed populations. The results revealed low rates of genetic diversity in all populations, loss of genetic diversity and high inbreeding rates in farmed populations, and genetic structuring among wild and farmed populations. Genetic tracing using the 12 microsatellite markers was effective, and presented a better performance in identifying samples at the population level. The 12-microsatellite panel is appliable to the legal aspects of the trade of the A. gigas, such as origin discrimination, reproductive genetic management by DNA profiling, and evaluation and monitoring of genetic diversity.The Amazonian symbol fish  Arapaima gigas  is the only living representative of the Arapamidae family. It is commonly referred to as pirarucu, a name that comes from two indigenous native terms, pira (which means fish) and urucum , because of the species’ red tail color [The Amazon symbol fish  Schinz, 822 is thA. gigas’ marketing extremely profitable, compared with other species. Additionally, it has great cultural and economic value for riverside communities that survive from the A. gigas’ fishing [The species was given the title of “Amazonian’s codfish”, and features such as its large size (weighing up to 200 kg) and excellent flavored meat make the A. gigas’ marketing is mostly supplied by specimens coming from fishing, and the largest fishing landing harbor is located in the state of Amazonas, with production coming from federal and state environmental conservation units, indigenous lands and regions with current fishing agreements due to predatory fishing and risk of extinction of the species. Another smaller portion of A. gigas’ commercial trade originates from farming, in various aquaculture production systems.The A. gigas meat was produced, which represents 0.43% of all aquaculture production in Brazil [According to the last farming census, 3.246 tons of A. gigas products and by-products have broadened in Brazil and abroad. The fillet of A. gigas’ meat is already in high demand by the international gourmet market [In recent years, commercial sales to consumers of t market . AdditioA. gigas, due to the increase in commercial activity to mainly serve the rising leather market. Data from the United States Law Enforcement Management Information System (LEMIS) show that, among the incidents involving arapaima leather products, 89% were originated from wild-caught animals, and they all originated from Brazil [In a recent study , there im Brazil .A. gigas in Brazil were on the verge of collapse in the 60s and 70s due to overfishing; consequently, part of the genetic diversity has been lost. Despite positive signs of recovery in terms of population size in managed areas, there are still data deficits regarding the diversity and genetic structure of wild populations of A. gigas—until now there is also an absence of these data for the farmed ones. The genetic diversity is the starting point of adaptation, evolution, and survival, without which the population is more susceptible to extinction [It is important to emphasize that wild stocks of tinction , thus thA. gigas is the illegal trade, by which animals are caught in prohibited areas and traded illegally or, even, with an indication that they come from a farming environment [Nowadays, one of the main threats to the wild populations of ironment . The Conironment . A. gigas, the genetic tracing can be useful against the illegal trade through genetic proof of the origin of the marketed animals, and it could also help in the implantation of breeding genetic management in the aquaculture farms based on the identification of DNA profiles. This process is based on the identification of individuals and populations by genetic tracing. At the individual level, the process is based on parental screening for the identification of individuals. At the population level, it is based on identifying allelic frequencies using probabilistic or deterministic approaches . For theA. gigas and the potential of a panel composed by 12 microsatellite markers, combined in a multiplex-PCR system, for the individual and population genetic tracing of this species.In studies of diversity and genetic tracing of aquatic species, microsatellite molecular markers are the most used genomic markers, mainly due to their high polymorphism rates, their abundance throughout the genome, and the practicality and affordable cost of analysis using these markers. In this context, aiming to contribute to the economic development and the sustainable management, the objective of this study is to investigate the genetic diversity of wild and cultivated populations of This research was approved by the Ethics Committee on Animal Use (CEUA) of the Federal Rural University of Amazon (UFRA), protocol number 055/2017 (CEUA)–23084.017501/2017-02 (UFRA). A. gigas belonging to seven populations, including farmed and wild ones. One-hundred and ninety of these samples were obtained from four farmed populations located at the state of Pará, in the Northern region of Brazil (Tucumã—TUC and Moju—MOJ), and from the states of Maranhão and Ceará, in the Brazilian Northeast (Imperatriz—IMP and Pentecostes—PEN). The other 178 samples come from three wild populations, located at the states of Pará and Amazonas, in the Northern region of Brazil  (We collected 2 g of muscle tissue of 368 specimens of ana—MEX) .The samplings were preserved in 70% ethanol  and posteriorly stored in −20 °C. Total genomic DNA was extracted from the digested tissue in proteinase K solution/Sodium Dodecyl Sulfate (SDS)  and purified in Phenol/Chloroform , followed by precipitation in Isopropanol  . The DNAA. gigas by [Twelve microsatellite loci were analyzed , developed and selected as the most polymorphic loci for The multiplex PCR was run in a final volume of 9.5 µL, using a 5.0 µL 2X Qiagen Multiplex PCR Master Mix , 1.0 µL of Q-Solution (Qiagen), 2.0 µL of H2O, 0.5 µL of primer mix, and 1.0 µL of genomic DNA, described by . AmplifiThe samples were genotyped in an ABI 3130 Genetic Analyzer  using a mixture of 1 μL of the PCR product, 8.5 μL of formaldehyde and 0.5 μL of GeneScan 500 LIZ (Applied Biosystems). The determination of fragment size and allele designation was conducted with the GeneMapper 3.7 software (Applied Biosystems).The presence of the null allele in the markers was checked using the program Micro-Checker 2.2.3 . The PolR) were analyzed in Fstat 2.9.3.2 [O), the expected heterozygosity (HE) and Hardy–Weinberg Equilibrium (HWE) was determined in Arlequin 3.5.2.2 [p-values were adjusted by Bonferroni correction [The genetic diversity indexes, the number of alleles per locus (NA) and the allelic richness (A 2.9.3.2 . The obs 3.5.2.2 . HWE p-vrrection .E.The effective population size (Ne) was estimated in COLONY v2.0.6.4  assumingST [ST, calculated in Arlequin 3.5 [The genetic differentiation among populations was estimated by pairwise FST  and RST,quin 3.5 , accordiquin 3.5 . The exiquin 3.5 , adjustequin 3.5 . Besidesquin 3.5 .A. gigas was evaluated for both individual and population identification methods. This analysis was based on 1000 genotypes from each population , simulated by P-Loci [The capacity for the tracing of the y P-Loci  based onThe efficacy of the tracing by the identification of individuals was evaluated using the methods full likelihood, run in COLONY v2.0.6.4 . To idenThe performance of each method used to allocate the specimens to their respective populations was evaluated based on the criteria adopted by Larrain et al., 2014 , i.e., sThe results of the Micro-Checker analysis indicated that there were null alleles in the markers Agig93614, Agig90836, Agig70664, Agig08912, and Agig06409. The 12-microsatellite system used in this research presented extremely informative PIC average rates for the MAM, SAN, MEX, and TUC populations. PIC moderate rates were observed for the populations of PEN, IMP, and MOJ .The indices of genetic variability for each of the 12 microsatellites analyzed for each population are shown in complement A value varied from 2.83 to 7.08 and the average AR varied from 2.79 to 5.99.  and SAN  presented high rates of genetic diversity, in contrast to the farmed population of IMP, which presented the lowest rates . The remaining populations presented intermediate NA and AR rates (The average Nto 5.99. . Wild poAR rates .O and HE were observed for the populations of MOJ (HO = 0.47) and PEN (HE = 0.51), respectively, while the highest values were observed in IMP (HO = 0.71) and TUC (HE = 0.69)  presented at least one marker in disequilibrium, either for deficiency and/or heterozygosity . The low = 0.69) .E, and endogamic depletion by F statistics. The wild population of MAM presented a higher value of NE = 168 and a low inbreeding rate, F = 0.003. Critical records of NE and F rates were observed for the farmed populations of IMP, NE = 4 and F = 0.125  presented a drastic reduction in N = 0.125 . ST and FST rates above 0.150 revealed high genetic differences among the farmed populations of PEN, IMP, and MOJ when compared to the wild populations of MAM, SAN and MEX. RST and FST rates varying from 0 to 0.050 indicate low differences between MAM and SAN populations, and that both populations are highly different from the MEX one. The comparison among the farmed populations (PEN × IMP × MOJ), revealed FST and RST rates varying from 0.050 to 0.150, indicating that they have a moderate differentiation. The population from TUC presented high differences when compared to the populations from MAM, MEX, PEN, IMP, and MOJ, and moderate difference when compared to SAN . The other populations, MAM, MEX, TUC, IMP and PEN, had more than 90% of their genotype identified .The identification at the population level, using the Bayesian method was able to distinguish 100% of the simulated genotypes for the populations of MEX, TUC and MOJ. The analysis for the populations of MAM, SAN, PEN, and IMP was able to correctly identify more than 99% of the genotypes. Maximum specificity was observed for all populations and maximum sensibility was seen for the populations of MAM, SAN, MEX, TUC, and MOJ. A lower sensibility was observed for the populations of PEN and IMP .A. gigas is one of the main sources of food, fishing and trade in riverside communities in the Amazon, and more recently has aroused the interests of aquaculture farming.The Amazon basin is home to the largest biodiversity of freshwater fish in the world, there are about 2300 recognized species, corresponding to more than 15% all of the freshwater fish species described on the planet , not couA. gigas has been on the IUCN list of endangered species, within the “data deficient” category, meaning there is a lack of data to assess its population status. Thus, tools such as the multiplex microsatellite panel described by [A. gigas, being efficient in answering questions on genetic diversity and tracing. The PIC values of the 12 combined markers allowed the obtention of accurate data t for statistical analysis.Unfortunately, since 1975 ribed by  are critA. gigas investigated in this study showed low rates of genetic diversity, NA, AR, HO, HE, PIC, NE and F—especially in the NA and AR rates  [As in all farmed populations, the reduction of Nimum NE) , meaningimum NE) , which himum NE) . For wilWe believe that actions commonly used in fish farming environments, such as consanguineous mating and the low number of breeders, contributed to the high genetic differentiation of the farmed populations from PEN, IMP, and MOJ in comparison to the wild ones from MAM, SAN and MEX . The intA. gigas is considered a sedentary species in the literature. Ref. [A. gigas that were up to 1500 km distant, pointed out the important role for juvenile dispersal as a means of conveying gene flow between subpopulations, requiring further studies.The low differentiation between the wild populations of SAN and MAM , supportre. Ref. , upon fiThe high differentiation of the wild population of MEX from the MAM and SAN populations  and the The formation of two clusters (K = 2) in the Bayesian analysis reinforces the loss of genetic diversity in the farmed populations from PEN, IMP, and MOJ, which is reflected in the pattern of distribution of allele frequencies of these populations in a different cluster apart from the wild populations and also from the population from TUC . We beliA. gigas along the Amazon basin, [When analyzing the structuring of wild populations of the n basin,  concluden basin, . Our datA. gigas, we reiterate the importance of measures to control the A. gigas fishing in the state of Amazonas. We also emphasize the need for the authorities responsible for fisheries management of developing a national standard for species management throughout the entire Amazon basin.In view of the low genetic diversity of the wild populations of Food traceability is becoming increasingly important for ensuring international food-safety and assisting in the control and sustainability of commercial activities. For this, tools based on DNA analysis have been highlighted, as they present many advantages for DNA being found in all cells—requiring a small amount of material for analysis, and the possibility of the collection at any stage of the production chain . The individual and population discrimination tests used for species tracing can be used in different contexts. For instance, in conservation circumstances, they can be used to assess the genetic impact of domesticated specimens on wild populations. Moreover, the genetic tracing can be used in the combat against illegal fishing through the identification of the origin of seized materials, among others. In aquaculture, these tests are commonly used to track farm fleeting, create genetic relationships maps among breeders, and to identify the farm of origin of contaminated stocks, in cases of detection of diseases or toxins in commercialized fish.A. gigas, identification at the population level had better performance than the individual discrimination, which corroborates the findings of [For the dings of ,28. A sidings of . Based odings of .A. gigas comes to meet the growing need for reliable, fast and low-cost molecular tools for direct application to improving legal aspects of fish trading, such as the discrimination of farmed individuals from wild ones in/from different locations. For further studies, we recommend an increase in the number of markers on the tested panel, aiming to reach greater accuracy in the analyses, especially in populations that have a lower genetic diversity.The 12-loci microsatellite panel tested for the A. gigas, such as origin discrimination, reproductive genetic management by DNA profiling, and evaluation and monitoring of genetic diversity. Genetic tracing using the 12 microsatellite markers was effective and presented a better performance in identifying samples at the population level. The 12-microsatellite panel is appliable in the legal aspects of the trade of the


However, their fine-scale genetic landscapes  based on the high-density allele/haplotype sharing patterns have not been deeply characterized. Here, we collected and generated genome-wide data of 50 Han Chinese individuals from four populations in Guizhou Province, one of the most ethnolinguistically diverse regions, and merged it with over 3,000 publicly available modern and ancient Eurasians to describe the genetic origin and population admixture history of Guizhou Hans and their neighbors. PCA and ADMIXTURE results showed that the studied four populations were homogeneous and grouped closely to central East Asians. Genetic homogeneity within Guizhou populations was further confirmed via the observed strong genetic affinity with inland Hmong-Mien people through the observed genetic clade in Fst and outgroup f3/f4-statistics. qpGraph-based phylogenies and f4-based demographic models illuminated that Guizhou Hans were well fitted via the admixture of ancient Yellow River Millet farmers related to Lajia people and southern Yangtze River farmers related to Hanben people. Further ChromoPainter-based chromosome painting profiles and GLOBETROTTER-based admixture signatures confirmed the two best source matches for southwestern Hans, respectively, from northern Shaanxi Hans and southern indigenes with variable mixture proportions in the historical period. Further three-way admixture models revealed larger genetic contributions from coastal southern East Asians into Guizhou Hans compared with the proposed inland ancient source from mainland Southeast Asia. We also identified candidate loci  with strong natural selection signatures in Guizhou Hans via iHS, nSL, and ihh, which were associated with the susceptibility of the multiple complex diseases, morphology formation, alcohol and lipid metabolism. Generally, we provided a case and ideal strategy to reconstruct the detailed demographic evolutionary history of Guizhou Hans, which provided new insights into the fine-scale genomic formation of one ethnolinguistically specific targeted population from the comprehensive perspectives of the shared unlinked alleles, linked haplotypes, and paternal and maternal lineages.The evolutionary and admixture history of Han Chinese have been widely discussed  Howevers (CNVs) . Additios (CNVs) . There as (CNVs)  and lackvia genome-wide ancient DNA data. These earlier findings extracted from ancient genomes documented that the gene flow from the behaviorally and anatomically modern human flowed into Southeast Asians over 65 thousand years ago (kya), which had left major genetic traces in modern Austroasiatic people  in the central valley of the Yellow River about 5,000 years ago . Based oincomers . Subsequincomers . They coincomers  and genoincomers , which cincomers . Currentincomers ; thus, catistics , shared atistics  and GLOBatistics , and shavia STRs included in the AGCU X19 amplification system or InDels included the Investigator DIPplex kit . We first confirmed the close genetic relationship between Guizhou Hans and southern Han Chinese as the identified largest f3-values among them (To explore the intra/interpopulation genetic relationships between four genotyped Hans and other references (both modern and ancient populations), we calculated pairwise Fst genetic distances among 87 East Asian groups . We did ong them , and thef3-statistics in the form f3 to identify and describe plausible admixture events. We identified 4,451 pairs that showed statistically negative f3-values in Anshun Hans which denoted that the allele frequency of the targeted Anshun Hans intermediated between that in source1 and source2. The observed significant f3-values suggested that Anshun Han was a genetic admixture population. The most negative source pairs were produced from northern Hans and southern East Asian Tai-Kadai people . Northern Hans-linked ancestral sources were also related to Tibeto-Burman people and some of the Altaic-speaking populations. Indeed, these population pairs of one source from Tibeto-Burman or Altaic-speaking populations and the other from Austronesian and Tai-Kadai groups also produced significant admixture signals. Ancient people from Mongolia and the Yellow River Basin could also be used as the candidates of northern sources, and ancient populations from Fujian and Taiwan in southeastern coastal regions and Southeast Asia also could be used as effective southern ancestral sources for four Guizhou Hans. We conducted 30,288 pairs of symmetric f4-statistics in the form f4 and found more shared ancestry between Guizhou Hans and Tai-Kadai-speaking populations  = –25.375∗SE. Compared with modern coastal southern East Asians related to Amis, Guizhou Hans shared more alleles with inland modern southern East Asians related to Hmong, f4 = –2.818, which was consistent with the observed patterns compared with Taiwan Hanben (Z-scores = –5.382). Affinity f4-statistics in the form f4 were conducted to explore if some additional ancestries contributed to Guizhou Hans compared with other Eurasian comparative subjects. Compared with geographically close Guizhou Dong, Guizhou Hans harbored more ancestry related to Tibeto-Burman-speaking Tibetan , as well as related to the Yellow River Basin ancient populations of middle Neolithic Wanggou people (–4.364), suggesting that more northern East Asian ancestry existed compared with southern indigenous people. Compared with Yellow River farmers (Haojiatai_LBIA), Guizhou Hans also possessed more ancestry related to southern East Asian indigenous populations related to Mlabri (–4.016) and others, which suggested that Guizhou Hans were formed with the gene pool from northern and southern sources.We further performed admixture i people . The plaulations , such asvia qpGraph-based phylogeny framework with population split and admixture events , including 11 Han populations from Shaanxi Province , Lanzhoup < 0.05). Anshun Hans were inferred as the one-date admixture results in the best-guess inference, which was mixed from 0.17 haplotypes from local Kaili Xijia people and other 0.83 from northern Hanzhong Hans occurred around 13 generations ago. A similar pattern of one-date admixture model was also obtained in others with similar best-guess ancestral sources, admixture dates, and corresponding proportions, such as Qiannan Hans that were mixed with minor ancestry (0.2) from Xijia and major ancestry (0.8) from Hanzhong Hans at 15 generations ago.Autosomal haplotype data also could provide new insights into the population admixture history. Previous genetic analyses focused on the shared haplotype have reconstructed the admixture sources and processes of Bantu expansion and Arab slave trade in Africa, the Mongol Empire and the first millennium CE migrations in Eurasia . Here, wvia the observed signatures from other natural selection indexes . Three SNPs from MTUS2 genes located in chromosome 13  also possessed negative nSL values .We also identified and characterized the plausible exiting natural selection signals in Guizhou Hans based on the phased haplotypes using the integrated haplotype score (iHS), nSL, and integrated haplotype homozygosity pooled (iHH12). We used 329,863 phased loci from 100 haplotypes in Guizhou Hans . The mosFinally, we focused on the genetic diversity and structure within 230 individuals from 14 Guizhou or Chongqing populations. PCA results based on the allele frequency distribution of single SNPs showed three genetic clines  and Guizhou Hans clustered in the intermediated position among three clines , which wWe genotyped 3,746 maternal lineage informative SNPs (LISNPs) in 50 female Hans and 24,047 LISNPs in 19 male Hans . We idenvia migration and admixture but a limited contribution to modern Guangxi and surrounding populations. Although advanced in deep population history reconstruction of ancient East Asians, the direct genetic contribution from ancient populations to Han Chinese populations needed to be further characterized. A large number of studies have been conducted to explore the genetic structure of Han Chinese groups across China, which suggested that genetic homogenization existed among the Han populations and the genetic differentiation was identified among populations from different language families  residing in Guizhou Province and other Hans from the surrounding provinces as our references . PCA andcultures . Thus, wvia the fineSTRUCTURE-based population clustering patterns. We also identified the recent admixture time based on the ALDER and GLOBETROTTER. The inferred that differentiated admixture signatures may be the plausible explanation for the observed genetic differentiation between Guizhou Hans and their non-Han neighbors. In the qpGraph- and qpAdm-based admixture models, we identified all northern and southern Neolithic farmers who participated in the formation of Guizhou Hans, which was related to the descendants of Yangtze Valley farmers and Yellow River Basin farmers , which provided more autosomal genetic supporting evidence for the common origins of Sino-Tibetan language and people from the Yellow River Basin in northern China  and southwestern Hans (Guizhou) and minority ethnic groups (Guizhou) and natural selection signatures based on the reconstructed ancestral chunks. We identified genetic differences among Shaanxi, Sichuan, and Guizhou Hans, as well as the genetic distinction between Han Chinese and minorities  farmers , suggeste models , which srn China .We had explored the genome-wide candidate loci targeted by natural selections based on the reconstructed haplotype data. Among the identified natural selection loci, the top hundreds of SNPs were located in NOTCH4 and HLA in chromosome 6, which was associated with the susceptibility of complex diseases. SNP rs9262558 linked to the HLA gene family located in chromosome 6 was recently evidenced by obvious positive natural selection in Taiwan Hans (| iHS| = 7.5), and it also showed similar signatures in Guizhou Hans (–3.1243) .Interestingly, we did not observe the most significant selection signals in EDAR  and SLC24A5 (pigmentation gene in western Eurasians). Among 11 functional SNPs located in EDAR in chromosome 2 , the first three SNPs were likely subjected to natural selection in Guizhou Hans with iHS values larger than 1. All of them except SNP rs72939934 harbored nSL values ranging from 1.1930 to 1.4646. SNP rs3827760, one variation being recently evidenced harboring greater genetic differentiation between Gansu Huis and Hans , also haWe conducted one comprehensive population genomic analysis based on three types of shared ancestries  among Guizhou Hans and all publicly available genome-wide data from the early Neolithic to the modern Eurasian populations. We explored and reconstructed the genetic origin, migration, and admixture history of Guizhou Hans, as well as illuminated the candidate loci targeted for positive natural selection. Our survey illuminated that the present-day Guizhou Hans mainly derived the major ancestry from the Yellow River millet farmers and also obtained additional admixture ancestry from an indigenous southern source related to Yangtze River rice agriculturalists. Genetic clustering analysis based on the sharing of IBD patterns and paternal and maternal lineages also demonstrated that the Guizhou Hans were located in the middle position of the North–South genetic gradient consistent with their geographical origin. Additionally, we identified great genetic differentiation between Guizhou Hans and northern Shaanxi Hans, as well as between Guizhou Hans and Guizhou indigenous non-Han people based on the fineSTRUCTURE-based shared ancestry fragments, although we found a strong genetic homogeneity within four Guizhou Han populations. Finally, we searched for signatures of positive selection in the Guizhou Hans by scanning for SNPs that displayed unusually long haplotype lengths using iHS and identified hundreds of loci located in chromosome 6 (including HLA and NOTCH4) associated with the susceptibility of the complex diseases and other loci located in EDAR, ADH1B, and ABCG2 associated with morphology formation, alcohol, and lipid metabolism.® Global Screening Array (GSA) was used to genotype around 700K SNPs from both autosomal and uniparental chromosomes. Genotyping success rate and missing rate per loci or individual were further controlled via PLINK 1.9 following our recent similar work ; here, the central African Mbuti population was used as the outgroup. Allele-based admixture signatures were explored using the admixture statistics in the form f3, in which the observed negative values with Z-scores less than –3 denoted a strong admixture evidence. Four population-based analyses (both affinity f4- and asymmetric f4-statistics) were conducted using the qpDstat package  among eastern Eurasian or other local-scale populations was conducted using the smartpca package . Ancientpackages  with the package  with thepackages , and qpG(qpGraph . We also(qpGraph . ALDER ((qpGraph  was used3. Maternal haplogroups were determined using HaploGrep 2 (We first phased all populations included in the high-density dataset using ShapeIT v2 . Four GuloGrep 2 .The original data contributions presented in the study are included in the article/This work was approved by the Ethics Committee of Xiamen University. The sample was collected with informed consent. The patients/participants provided their written informed consent to participate in this study.C-CW, BZ, CL, and GH designed this study. MW, DY, and GH wrote the manuscript. MW, GH, XZ, ZW, H-YY, JL, and L-HW conducted the experiment. MW, GH, XZ, ZW, H-YY, JL, and L-HW analyzed the results. C-CW, BZ, CL, and GH revised the manuscript. All the authors reviewed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past co-authorship with the authors GH, H-YY, L-HW, C-CW, BZ, and CL.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.