Uncaria tomentosa (Willd. ex Schult.) DC., a plant native to the Amazon region, is used widely in popular medicine and by the pharmaceutical industry because of its anti-inflammatory activity. However, the survival of this species is endangered by deforestation and indiscriminate collection, and a preservation plan is urgently required. The objectives of this study were to determine the genetic and chemical variability between and within eight populations of U. tomentosa from the Brazilian states of Acre, Pará and Amapá, and to investigate possible correlations between genetic and geographical distances, and between geographical distances or altitude and the accumulation of bioactive oxindole alkaloids. Three sequence-related amplified polymorphism (SRAP) markers were employed to fingerprint genomic DNA, and the amounts of mitraphylline and isomitraphylline in leaf samples were established by high-performance liquid chromatography. Although significant divergence existed between the tested populations (FST = 0.246), the largest genetic diversity and the highest percentage of polymorphism (95.68%) was found within the population from Mâncio Lima, Acre. Gene flow was considered rather limited (Nm = 1.57), and no correlations between genetic and geographical distances were detected, suggesting that population structure followed an island model. Accumulations of mitraphylline and isomitraphylline varied in the range 32.94 to 0.57 and 3.75 to 0.36 mg g-1 dry weight, respectively. The concentration of isomitraphylline was positively influenced by altitude, such that the population collected at the site with the highest elevation  exhibited the greatest alkaloid content. SRAP markers were very efficient in fingerprinting genomic DNA from U. tomentosa populations and clearly showed that genetic variability within populations was greater than between populations. A conservation and management plan should prioritize the creation of germplasm banks to prevent the loss of existing genetic variability, particularly within alkaloid-rich populations such as those of Tarauacá. Uncaria tomentosa (Willd. ex Schult.) DC. (Rubiaceae) is indigenous to the Amazon biome and is distributed in various South American countries, including Brazil where it is found chiefly in the states of Acre, Amapá, Amazonas and Pará [U. tomentosa is commercialized worldwide and is included in the National List of Essential Medicines  disseminated by the Brazilian Ministry of Health to all municipalities through the National Health System  [and Pará . The speand Pará . For thede, SUS) .U. tomentosa is rich in alkaloids and contains various representatives of this class of natural products including tetracyclic indole , tetracyclic oxindole , pentacyclic indole , pentacyclic oxindole  and glycoindole (3α-dihydrocadambine and dolichantosin) alkaloids [U. tomentosa [lkaloids –6. Mitraomentosa .U. tomentosa, has compromised the survival of the species in the wild [U. tomentosa, making it difficult to devise strategies for the preservation of this important medicinal plant. In this context, studies on the genetic diversity of medicinal plants, and on the association between findings obtained by molecular techniques and chemical marker analyses, could contribute to the maintenance and management of resources that are in particular demand by the pharmaceutical industry [The extensive deforestation that has occurred in the Amazon region, along with indiscriminate collection and lack of concern about the regeneration of the wild . To dateindustry ,9.Among the various molecular techniques available for comparing DNA profiles of individuals and populations, the sequence-related amplified polymorphism (SRAP) method is particularly simple to use and provides results that are highly reliable and reproducible. Moreover, SRAP markers may be employed to target genetic variation in open reading frame (ORF) sequences of plant genomes .U. tomentosa collected in the Amazon region of Brazil, (ii) to establish correlations between genetic and geographical distances, and (iii) to investigate possible correlations between geographic distances or altitude and the accumulation of mitraphylline/isomitraphylline. The results of the study showed that SRAP markers are very efficient for fingerprinting U. tomentosa genotypes, and also afforded important indicators regarding strategies for the conservation and management of this important medicinal plant.The objectives of this study were, therefore: (i) to determine the genetic and chemical variability between and within eight populations of Uncaria tomentosa were identified by Dr. Piero Giuseppe Delprete, of Herbier de Guyane, Institut de Recherche pour le Développement. A voucher specimen was deposited in the Herbarium of Medicinal Plants at UNAERP with voucher number HPMU 2904–3066.Plants of U. tomentosa were collected from eight populations (20 specimens per population) located at different sampling sites in the Amazon region of Brazil, and coded according to location, namely Cruzeiro do Sul (UTCS), Feijó (UTFJ), Mâncio Lima (UTML) and Tarauacá (UTTA) in the state of Acre, Macapá (UTMC), Mazagão (UTMZ) and Santana (UTAS) in the state of Amapá, and Afuá (UTAF) in the state of Pará. The exact locations of the sampling sites are shown in U. tomentosa specimens investigated in this study was previously authorized by the Brazilian Council for the Administration and Management of Genetic Patrimony (CGEN) of the Brazilian Ministry of the Environment (MMA) via the National Council for Scientific and Technological Development (CNPq—CGEN/MMA Process number:010102/2015-9).A total of 160 specimens of For SRAP analysis, young healthy leaves were sampled from each specimen, transferred to labeled conical-bottom test tubes containing silica gel and stored in the freezer at -20°C until required for DNA extraction. For HPLC analysis, young and mature leaves were collected from each specimen, transferred to labeled paper bags and subsequently dried at 45°C in a forced-air oven .All experiments were performed in the Molecular Biology and Phytochemical Laboratories of the Biotechnology Department at the Universidade Federal de Ribeirão Preto (UNAERP) Ribeirão Preto, SP, Brazil.® P360 instrument .Genomic DNA was extracted from 100 mg samples of young leaves using the cetyltrimethylammonium bromide (CTAB) method  with som2 (25 mmol/L), 1 μL of dNTP mixture (2.5 mmol/L), 0.4 μL of forward primer (5 μM), 0.4 μL of reverse primer (5 μM), 0.2 μL of Taq DNA polymerase (5 U μL-1), 1 μL of DNA template (10 ng μL-1 for the UTAF sample and 5 ng μL-1 for the remainder) and deionized water to a final volume of 10 μL. The amplification procedure involved 5 cycles of denaturation at 94°C for 1 min, annealing at 35°C for 1 min and extension at 72°C for 1 min, followed by 35 cycles of denaturation at 94°C for 1 min, annealing at 50°C for 1 min and extension at 72°C for 1 min, with a final extension step of 7 min at 72°C. Amplicons were denatured at 95°C for 5 min and submitted to denaturing 6% polyacrylamide gel electrophoresis in 1 X TBE buffer for 2.5 h at a constant voltage of 80 and maximum temperature of 50°C. The gel was stained with silver nitrate and the bands revealed with sodium carbonate [SRAP analysis was carried out following an established protocol with five combinations of published forward (me) and reverse (em) primers  from whiarbonate .U. tomentosa were reduced to a fine powder in a Marconi MA048 cutting mill fitted with a 40 mesh sieve. A sample (100 mg) of the powder was mixed with 1 mL of methanol  in an amber flask and submitted to static maceration at room temperature (22 ± 1°C) for 24 h, following which the mixture was filtered and the filtrate reduced to dryness in a fume cupboard. All extractions were performed in triplicate  mixture of methanol  and Milli-Q Ultrapure water . Samples (15 mg) of the dried extracts were redissolved in 1 mL of the 80: 20 (v/v) methanol: water mixture and applied to SPE cartridges that were subsequently eluted with 3 mL of the same solvent mixture. Aliquots (20 μL) of eluents (5 mg mL-1) were analyzed on a Shimadzu  model LC-10ADvp instrument coupled to a Shimadzu SPD-M10Avp diode array detector and fitted with a Zorbax Eclipse XDB-C18 column  protected by a Zorbax Eclipse XDB-C18 pre-column . Gradient elution was performed at room temperature (22 ± 1°C) with 10 mmol/L aqueous ammonium acetate, pH adjusted to 6.9 with triethanolamine  and acetonitrile  and 10 mmol/L aqueous ammonium acetate adjusted to pH 6.9 with triethanolamine . The mobile phase was supplied at a continuous flow rate of 0.8 mL min-1 according to the program: 35% B between 0.01 and 18.00 min, 50% B between 18.01 and 25.00 min, 35 to 100% B from 25.01 to 40 min, and 35% B between 40.01 and 45 min. The detection wavelength was set at 245 nm and the acquired data were processed using LabSolutions Multi LC-PDA software from Shimadzu.Prior to analysis by high pressure liquid chromatography (HPLC), extracts were submitted to a solid-phase extraction (SPE) clean-up procedure on Supelco-57054 C18 cartridges  that had been previously eluted with 1 mL of methanol followed by 1 mL of an 80:20  was carried out following the Sanitary Vigilance National Agency guidelines [The content of alkaloids was determined by a previously validated HPLC-PDA method  using miidelines .-1 and each of these concentrations was injected in triplicate.Calibration curves for the alkaloids were constructed using concentrations in the range of 500; 250; 125; 62.5; 31.2; 15.6; 7.8; 3.9; 1.9 μg.mLRatio of the peak areas of the mitraphylline and isomitraphylline standards were calculated and plotted against the corresponding standard concentration using linear regression of the standard curves.Binary data were submitted to analysis of molecular variance (AMOVA), a statistical technique that allows the decomposition of total genetic variance into its between and within population components. Descriptive analysis of total variability was obtained by calculating the percentage of polymorphic loci, Nei’s genetic diversity index (H) and Shannon's diversity index (I). The unweighted pair group method with arithmetic mean (UPGMA) was used to group populations according to genetic divergence estimated from Nei’s genetic distances . GeograpK population genetic clusters based on their nuclear multilocus genotypes) and the admixed ancestry model. For each run, the initial burn-in was 200,000 iterations followed by a run-length of 500,000 iterations for K = 1 to 10 population genetic clusters [The variability and genetic structure of populations were investigated through principal coordinates analysis (PCoA) using the software packages GenAlEx version 6.5  and STRUclusters   and, when significant differences were detected, mean values were compared using Scott-Knott test at 5% probability . A dendrpackages . The EucU. tomentosa populations were selected for further experimentation. These SRAP primer pairs generated a total of 185 amplified bands with percentage polymorphism values of 97.5% with me3/em3 and 100% with me1/em6 and me5/em3. The average number of polymorphic loci per primer pair was 61.7 with me3/em3 presenting the most polymorphic loci and me1/em6 the least  exhibited the largest genetic variability (95.68%) and the highest values of Ne, H and I indices of genetic variation, while specimens from the population in Tarauacá, Acre (UTTA) presented the smallest genetic variability (62.16%) and, consequently, lower genetic variability. UTML specimens exhibited broad stems (15–20 cm) and were collected from a preserved forest area where the plants received little light. In contrast, UTTA specimens presented thin stems (3–5 cm) and were collected from the edge of the forest where the plants received direct sunlight. Moreover, the UTTA population was characterized by young individuals, most likely descendents of the original forest, and was located in an area of anthropic activity near to the village of São Vicente on the margins of the Gregório River.As shown in U. tomentosa populations rather than between populations (25%) as shown by the FST value of 0.246 (P < 0.001). This genetic structure suggests that conservation plans would be more efficient and successful if a larger number of individuals were collected within populations rather than in different populations. High intra-population diversity implies greater plasticity of responses to temporary stress situations [U. tomentosa in dispersing seeds and pollen through wind and insect pollinators [The results obtained from AMOVA  revealedtuations . Speciestuations . Thus, tlinators  certainlU. tomentosa suggests that the species is allogamous, although the present study was not designed to consider this issue and little is known about the mechanisms of fertilization in this species.Allogamous species are expected to present high genetic variability within populations because intra-population divergence is inversely proportional to gene flow, in other words when gene flow is high genetic divergence is low . The higU. tomentosa populations were not correlated , and this may constitute a problem for the survival of this species. The existence of high gene flow among populations is of particular importance since new alleles can then be introduced into the population. As a consequence, the genetic variability between local populations would tend to decrease while genetic variability within the populations would increase . In thisST value, the lower the dispersion capacity of the species and the greater the difficulty in exchanging alleles between populations, thus increasing the probability of the populations becoming endogamous, as highlighted by Frankham et al. [m and FST found in the U. tomentosa populations of the present study reflect the environments where the specimens were collected which, despite their wide diversity of flora, were within anthroposized and fragmented landscapes.The higher the Fm et al. . These rm et al. , 33. TheST value. Genetic differentiation within a population, or even between distinct populations, may occur when geographical distances are relatively small and implies that genetic diversity is spatially structured [U. tomentosa, the Mantel test showed that the correlation between genetic and geographical distance was not statistically significant . This means that the organization of genetic variability of U. tomentosa populations occurs randomly along the geographic distribution of the species and that gene flow between populations, if any, occurs over spans that are shorter than the smallest distance between the populations analyzed in this study.The UPGMA dendrogram presented in ructured . HoweverU. tomentosa, with particular emphasis on the creation of in vitro and in situ germplasm banks to prevent the loss of existing genetic variability. The conservation of this species must be prioritized because, according to a study by Soares-Filho et al. [U. tomentosa in its natural habitat will be even greater because the growth and development of this woody vine depends on the support and protection of trees.Our study has shown that there is an urgent need for conservation projects involving o et al. , 40% of o et al. . If thisU. tomentosa plants collected at various sites in Peru suggested the existence of chemotypes since some specimens were found to accumulate pentacyclic oxindole alkaloids while others did not [Concentrations of the pentacyclic oxindole alkaloids mitraphylline and isomitraphylline varied considerably between and within the study populations Tables  and 7. F did not . Quantit did not –40.U. tomentosa specimens analyzed, while isomitraphylline was detected in 94.3% individuals. Plants from the UTTA and UTCS populations generally presented higher levels of these alkaloids compared with individuals from other populations  were detected in one plant from the UTCS population. In contrast, half of the specimens from the UTAF population did not accumulate mitraphylline, and this explains the very low mean concentration of the alkaloid in this population compared with the others  exhibited varying concentrations of mitraphylline and isomitraphylline. This finding demonstrates that the genes involved in the production of these alkaloids may be more expressed in one population than in the others. Thus, while the UTTA population occupied a prominent position in relation to the remainder regarding alkaloid content, it presented the lowest genetic variability.rm = 0.3005; P < 0.0344) between geographical distance and isomitraphylline accumulation. Although this correlation was not strong, it suggests that geographic distance may be an important factor in the accumulation of isomitraphylline in U. tomentosa, since populations in close proximity to each other accumulated similar amounts of this alkaloid  was also observed between altitude and isomitraphylline accumulation, signifying that the content of this alkaloid increased slightly at higher altitude Click here for additional data file.S2 Dataset(PDF)Click here for additional data file.S1 File(PDF)Click here for additional data file.


Pisum sativum subsp. elatius) is an important source of genetic diversity for further pea crop improvement harbouring traits useful in climate change context. The genetic structure was assessed on 187 individuals of Pisum sativum subsp. elatius from fourteen populations collected in the northern part of the Fertile Crescent using 18,397 genome wide single nucleotide polymorphism DARTseq markers. AMOVA showed that 63% of the allelic variation was distributed between populations and 19% between individuals within populations. Four populations were found to contain admixed individuals. The observed heterozygosity ranged between 0.99 to 6.26% with estimated self-pollination rate between 47 to 90%. Genetic distances of wild pea populations were correlated with geographic but not environmental (climatic) distances and support a mixed mating system with predominant self-pollination. Niche modelling with future climatic projections showed a local decline in habitats suitable for wild pea, making a strong case for further collection and ex situ conservation.Knowledge of current genetic diversity and mating systems of crop wild relatives (CWR) in the Fertile Crescent is important in crop genetic improvement, because western agriculture began in the area after the cold-dry period known as Younger Dryas about 12,000 years ago and these species are also wild genepools of the world’s most important food crops. Wild pea ( Genetic diversity of crop wild relatives (CWR) has only been rarely studied in natural populations. CWR are more diverse than domesticated crops because the latter have been forced through domestication bottlenecks. Nearly all current domestication models predict a reduction in genetic diversity in domesticated varieties compared to their wild progenitors . In natuPisum sativum L.) are predominantly self-pollinated .Differences in allele frequencies among wild rice populations separated by only 15 km within the same river system were found . We see Similarly to our study, a high inbreeding rate was found in self-pollinated wild rice populations . Conversex situ held wild pea accessions originate from limited number of individuals [The heterogeneity found within populations including self-pollinated species  also higividuals , are proividuals . In the ividuals .Hordeum vulgare subsp. spontaneum populations in Jordan. These authors interpreted the observed pattern by interplay among ruderal habitat preference, anthropogenic (zoochoric) movement of seeds, high self-pollination and much localized gene transfer. Most of these factors may apply to our Pisum data as discussed previously. However, direct analysis of the role of fine-scale abiotic and biotic variables  on Pisum genetic structure is not possible because such variables are presently not available in public databases.The interplay between historical land use and heterogeneous environmental conditions has given rise to considerable plant biodiversity in the Mediterranean , and raiSalvia species [Stipa species in Jordan [In contrast, several studies on various Mediterranean plants showed significant effect of IBE on genetic differentiation. Both environment  and geography shaped genetic differentiation in wild barley in Israel  suggesti species  and thren Jordan . Both lan Jordan ,76. All Besides anthropogenic factors, we have to consider the current climate change as a reason for decline of this species. In our study, due to climate change, the areas of high suitability for potential future establishment of the wild pea are moving away from the current points of occurrence of the species  and a loClimatic niche modeling has extensively been used to identify potential areas of introduction and establishment of several species in different climate change scenarios, but as an approach is less reliable to predict the degree of establishment of the studied species in the new areas . ClimatiObserved low heterozygosity and estimated selfing rate in wild pea natural populations support mixed mating system and predominant self-pollination of the species. Mating plasticity is not related with climate variability and there is no evidence of climate-enhanced selfing in natural populations of wild pea. Nevertheless, further studies are required for the role of the mixed mating system of wild pea in environmental change as well as for the use of this system in plant breeding.ex situ conservation. According to our analysis there is no evidence of climate-enhanced selfing in natural populations of wild pea. These are important insights because it suggests that for effective crop improvement we need more than a source of genetic diversity. We also need an understanding of what is influencing genetic structure, and how this interacts with phenotype. Only then do we have a chance of choosing the appropriate material to widen crop diversity by the introgression of adaptive traits.Here we show that in the northern Fertile Crescent, wild pea genetic variation is largely distributed between rather than within populations, and that differences between populations reflect geographic distance (IBD) rather than environmental distance (IBE). Accordingly, co-located populations are likely to be more similar than those more distant. Environment plays no role in the genetic structure we have detected. Because IBD rather than IBE is driving genetic structure in wild pea we conclude that most of the variation we detect within and between populations reflects genetic processes such as drift, founder effect and infrequent out-crossing with related individuals, rather than environmental selection pressure. Thus, if this variation is largely selectively neutral, we cannot assume that a diverse population of CWR will necessarily exhibit the wide ranging adaptive diversity required for further crop improvement. Human long term activities in the Middle East have severely fragmented the suitable habitat likely resulting in reduction of wild pea populations. The niche modelling with future climatic projections showed suitable areas decline and argue for further collecting and S1 Dataset(ZIP)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 TablePercentage of observed (Hobs), expected (Hexp) and missing datapoints derived from all and polymorphic DARTseq loci per 14 studied populations are shown.(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S1 Fig(DOCX)Click here for additional data file.S2 FigBlack points show mean distance of the distance groups.(DOCX)Click here for additional data file.S3 FigPositive correlation means higher environmental (a) or genetic  differentiation outside than inside the respective distance class. The significance of the normalized Mantel coefficient was calculated using a two-tailed Monte Carlo permutation test with 9999 permutations and the statistical significance of the coefficients was adjusted by Bonferroni correction. * P < 0.05, (*) 0.01 < P < 0.05 before significance correction.(DOCX)Click here for additional data file.S4 Fig(DOCX)Click here for additional data file.


Anolis carolinensis was introduced onto one of the Ogasawara Islands, Japan, and subsequently expanded its range rapidly throughout two of the islands. Morphological comparison showed that lower hindlimb length in the introduced populations tended to be longer than those in its native Florida populations. Using re-sequenced whole genomic data, we estimated that the effective population size at the time of introduction was actually small (less than 50). We also inferred putative genomic regions subject to natural selection after this introduction event using SweeD and a method based on Tajima’s D, π and FST. Five candidate genes that were potentially subject to selection were estimated by both methods. The results suggest that there were standing variations that could potentially contribute to adaptation to nonnative environments despite the founder population being small.Invaded species often can rapidly expand and establish in novel environments through adaptive evolution, resulting in devastating effects on native communities. However, it is unclear if genetic variation at whole-genomic levels is actually reduced in the introduced populations and which genetic changes have occurred responding to adaptation to new environments. In the 1960s,  Furthermore, the success of an invasion might depend on adaptation to novel environments during the course of range expansion6. Several important evolutionary questions after a species invades a new area should be considered. First, the number of individuals  is often so small that low genetic diversity due to founder events could limit the species’ success and subsequent evolution1, however in many cases introduced species successfully expand their ranges by adapting to new environments. Several studies have suggested that repeated introductions into the nonnative population could provide the necessary genetic diversity for adaptive evolution12, but in some cases evolutionary changes after the initial introduction could still occur despite reduced genetic diversity of the populations13. A recent review14 concluded that many invaded species either have genetic diversity similar to or even greater than natives or do not face adaptive evolution to expand in the invaded area. These authors claimed that the genetic diversity in a small set of neutral genetic markers is not reflected in the genetic variation of ecologically relevant traits. Indeed, we are unaware of any study that estimates genetic variation of the introduced populations at the whole genomic level and reveals how such evolution was possible with reduced genetic variation in introduced population. Second, many studies on the evolution of invaded populations have examined evolutionary phenotypic changes18, but little is known about which genetic changes have occurred in response to adaptation to new environments.It has been recognized that evolutionary change is an important process in biological invasions, and many studies have reported evidence of rapid evolution of invasive speciesAnolis carolinensis (Sauria: Dactyloidae) is a lizard species native to the southeastern United States19. In addition to natural expansion within the United States, this species has been introduced to many areas around the world, including oceanic islands such as Taiwan, Hawaii, Guam, and some islands in Japan, where it has caused great impact on the native ecosystem by preying upon native animals24. Anolis carolinensis mainly inhabits trunks, branches and leaves on trees25. A recent study showed that native A. carolinensis on small artificial islands in Florida adapted and evolved larger toepads corresponding to the intentional introduction of A. sagrei within only 20 generations26. This suggests that A. carolinensis has the potential for rapid evolution responding to new environments over a short period of time.The green anole, Anolis carolinensis was introduced to Chichijima, one of the islands in the Ogasawara archipelago, in the 1960s, and it increased its population size after a lag-time phase27. Afterwards, it was introduced into the Hahajima islands in the 1980s from the Chichijima islands, and it has since expanded its range within these islands as well. This nonnative species is now believed to be responsible for local extirpation and disruption of the native ecosystem30. It is thought that A. carolinensis was introduced by the escape of pet animals and/or hitchhiking on transports of U.S. military forces27. Although the native range of the source population and the introduction pathway are uncertain, phylogenetic analysis suggests two mitochondrial DNA haplotypes in introduced Ogasawara populations, which are most closely related to the coastal region in Louisiana eastward to northern Florida32.The Ogasawara Islands (Bonin) consist of more than 30 small islands, and are located about 1,000 km south of the mainland of Japan  and Hahajima (n = 13) islands during 2011, and in northern Florida (n = 15) in 2010 . Note that sequences of ND2 for 4 out of 24 individuals were not detected by genome resequencing, and therefore we used only 20 individuals. Then we checked the position of these haplotypes in Bayesian inference phylogeny of 398 individuals of A. carolinensis (see ref.33 for details on the method for constructing phylogeny). The haplotypes of all the localities of the northern Florida and Ogasawara individuals were clustered into the “Gulf Coast/Inland” clade defined in Campbell-Staton, et al.31 . The following morphological variables were measured for each individual according to the established ecological significance of these traits in genus Anolis34: (1) snout–vent length (SVL) from the tip of the snout to the anterior end of the cloaca, which is used as the overall body size, (2) head length (HL) from the back of the parietal to the tip of the snout, (3) head width (HW), the distance across the head measured at the anterior end of the ear, (4) lower hindlimb length (LHL) from the apex of the knee to the center of the ankle. Morphological variables of Florida populations were obtained from a previous study 35. ImageJ64 v.1.47n software36 was used for all the measurements.Only adult males were used for morphological measurements  was conducted using these residual values. For statistical analysis, we used Tukey’s honestly significant difference (HSD) test.37 were used for the genome resequencing. The DNA libraries were clonally amplified on a flow cell and sequenced on HiSeq. 2500  with 101-mer paired-end sequences. Image analysis and base calling were performed using Real-Time Analysis Software . DNA genome sequence data for 24 A. carolinensis individuals have been deposited in DDBJ under accession numbers DRA004461 to DRA004485.Whole genome re-sequencing was conducted for 24 individuals . After measurements of morphological variables were taken, muscle tissue was preserved in 95% ethanol, stored at −20C°, and then used for DNA extraction using Qiagen genomic tip 100/g. The reference genome was used for mapping reads obtained from the re-sequencing experiment. The insert sizes and the number of reads for each sample are shown in Supplementary Table 38. We excluded low quality reads  and adaptor sequences by FASTX-toolkit v0.0.13 (http://hannonlab.cshl.edu/fastx_toolkit). Furthermore, we trimmed 3 bp from the 5′ and 3′ ends of sequences with a quality value of more than 20 for each read, because their read quality was relatively low. Note that we did not use trimmed reads when their length was less than 20 bp. These filtered reads were used for further analysis.To remove low quality reads, we checked the read quality by applying software FastQC v0.10.1http://broadinstitute.github.io/picard and then each read was mapped to the A. carolinensis reference genome  using bowtie v1.0.1. We performed SNP calling using SAMtools mpileup with default parameters v0.1.1839. Biallelic SNPs with a quality score >10 were used for our analyses. SNPs in high read coverage regions (>100) were excluded. SNP deviating from Hardy–Weinberg Equilibrium (P < 0.01) were excluded.Before read mapping, the insert size of each read was checked using picard-tools v1.114  from 2 to 5.To assess population structure, we used ADMIXTURE v1.2327 ; the model is described with four demographic parameters , the time of divergence between introduced and native population (T generations), the initial population size of introduced population (N2b), and the present population size of the introduced population (N2f). An exponential change in population size is assumed in the introduced population. We originally constructed a model with migration between the two populations, but higher likelihood was produced from lower migration rates. Moreover, their effect on likelihood was relatively weak presumably because of the very short time since the invasion. Thus, we excluded migration from the model for simplicity.We assumed the demographic model of the two populations following ref.43, which uses a diffusion method and joint allele frequency spectra (AFS) to evaluate the likelihood of the model. First, we calculated the observed joint AFS of the Chichijima and Florida populations. The number of total sites used in the analysis (only non-coding sites) was 1,212,784. The number of polymorphic sites in Chichijima and Florida were 506,335 and 1,041,548, respectively. T was fixed to 50 according to the record. Mutation rate was assumed to fall between 10−9 and 10−7 per site per generation46. We conducted the same analysis with three different mutation rates , and obtained very similar estimates and expected AFS, which generated almost identical null distributions of summary statistics for the downstream analyses. Here we report only the results with 10−8. N1 was calculated from the observed value of nucleotide diversity 14.0 per 10 kb and mutation rate, and set to 35,000. Then, the combination of N2b and N2f to maximize the likelihood was searched. The parameter ranges of N2b and N2f were 2–1,000 and 35–35,000, respectively. Note that this parameter space includes population decline after the introduction (N2b > N2f).Parameters were estimated with the software δaδi v1.7.047 were performed 1,000,000 times to generate the null distributions of summary statistics: Tajima’s D, nucleotide diversity (π) and FST48. We obtained the observed value of those summary statistics by performing a sliding window analysis on Ogasawara population genomes with 10 kb window size and 5 kb sliding size. P < 0.05 (one-tailed test) was used as a criterion to find potential regions evolving under directional selection in the invaded populations. We also examined the analysis using other window sizes , but the trends of our results did not change. We applied the simulation results from Chichijima for Hahajima analysis too, because the two populations were classified into the same cluster in ADMIXTURE analysis  patterns of SNPs. SweeD analysis using SNSs of Chichijima and Hahajima populations was conducted with default parameter settings except the number of windows .In addition, to infer the selective regions from the genome in Ogasawara populations, we performed an analysis using SweeD software (version 3.2.12)A. carolinensis based on chicken, mouse and human GO databases, deriving each orthologous relationship from the Ensembl database (http://www.ensembl.org). The GO identifier (ID) biological process was used. We calculated the P value for each GO ID by comparison of the number of observed GO IDs with that of expected GO IDs based on a hypergeometric distribution. The estimated P values were adjusted by Bonferroni correction.To assess enrichment of gene ontology terms of candidate genes, we performed gene ontology (GO) analysis. For analysis, we build the custom GO annotations for P = 0.0003, Hahajima vs. Florida P < 0.0005). Head width in Hahajima is significantly longer than in Chichijima and Florida , although there were no significant differences in head length among the populations . Principal component analysis (PCA) also showed the same trends  in the introduced populations was longer than in the native Florida population  and at the present time (N2f) were 14.4 and 1290, respectively  were considered, the number of originally introduced individuals should be small (less than 50).We inferred the demographic history modeled as shown in Supplementary Fig. D, FST and π were significant (P < 0.05). Seventeen and 15 candidate genes that might be subject to positive selection were detected in the Chichijima and Hahajima populations, respectively (Table capn13) among 20 genes  analysis using candidate genes detected by the method based on the values of Tajima’s Anolis carolinensis was introduced to one of the Ogasawara Islands in the 1960s, and it subsequently increased its population size. Our study estimated the effective size of the introduced population at the introduction and detected putative genomic regions subject to natural selection after this introduction event using 24 individuals of re-sequenced genomic data. We also compared morphological data between the introduced populations and the native Florida populations. The results suggest that the effective size at the time of introduction was actually small and we detected twelve candidate genes for selection in both the Ogasawara Islands.31. The Florida samples were scattered across the branches in the “Gulf Coast/Inland” clade. At the same time, the distribution of Tajima’s D obtained from sliding windows on Florida genomes was finely bell-shape and centered on zero, which indicates a non-structured and stable population  of Ogasawara individuals were clustered into the “Gulf Coast/Inland” cladeet al.14 concluded that many invaded species either have genetic diversity similar to or even greater than native species. The present results indicate that the effective population size  was small at the time of introduction. Although we cannot exclude the possibility that the genetic modifications after the introduction to Chichijima result from new mutations during population expansion, the positively skewed Tajima’s D distribution suggests that there were some initial standing genetic variations in introduced individuals that could potentially contribute to adaptation to nonnative environments and rapid expansion in the Ogasawara Islands.The estimated effective population size at the introduction was small (less than 50). This indicates that a small founder population with reduced genetic variation could have made such evolutionary responses during 50 generations. Many invaded species have experienced a bottleneck, which reduced genetic variation and suggests that they are supposed to have little evolutionary potential. Estoup Anolis lizards34. A long hindlimb is efficient for effectively moving around trunk and ground microhabitats by promoting running performance50. Anolis carolinensis usually inhabits trunk to tree crown, but it moves closer to the ground when a competitor is absent. According to reports of A. carolinensis in Ogasawara (Chichijima and Hahajima)51 and United States (three Florida and one Georgia population)52, perch height (PH) and perch diameter (PD) used by the anoles in Ogasawara  were lower and larger than those in Florida and Georgia , respectively. Although the morphology measures taken in Florida individuals were not necessarily those of the source population of the invaded ones, anoles in Ogasawara might use much lower microhabitats and thicker twigs or trunks than those in the United States. It has been reported that there is a positive correlation between relative hindlimb length and mean perch diameter53. Therefore, long hindlimb length observed in these introduced populations might be related to adaptive changes to microhabitat uses.Morphological comparison showed that lower hindlimb length in the introduced populations was significantly longer than in native Florida populations, although the sample size was not large enough for firm conclusions and it is unknown whether or not these differences were due to genetic components. Hindlimb length is one of the known characters that influence adaptation to structural habitats in FST, Tajima’s D and nucleotide diversity, twelve genes were inferred as candidate genes that had been potentially subject to selection in both Chichijima and Hahajima populations. SweeD based on site frequency spectrum inferred eight genes as candidate genes for selection. Among these genes, four genes  were inferred by both methods, A gene  was inferred by SweeD and it was also detected in the Ogasawara Islands based on the method used in FST, Tajima’s D and nucleotide diversity values. In the present study, we could use genome sequences of only 24 individuals. Owing to small sample sizes, we could not detect genes experiencing weak selection, and these candidate genes might be erroneously detected due to the larger effect of genetic drift. Although we could not rule out the effect of genetic drift, the frequencies of the candidate genes were high only in the Ogasawara Islands, but these were low (<0.3) in native Florida populations so that these genes could increase in frequency after the introduction. In addition, we could not fully rule out the possibility that successfully invaded individuals had particular genotypes conferring invasive success.Based on pik3cb, nebl, gadl1, ntn1, and ENSACAG5967) were detected that might be subject to selection in the Ogasawara Islands using both the methods. There were no significantly enriched GO functional categories for these detected candidate genes. However, it is worth discussing the function of these genes, although we could not provide any convincing evidence for the relationships between these genes and their functional importance after the introduction event. Among the five candidate genes, two genes (nebl and gadl1) have functions in muscle development and contraction, and two other genes (ntn1 and pik3cb) have a function in the metabolic process. In addition, other candidate genes detected only by one of the two methods also have functions in muscle development and muscle contraction , and the metabolic process (acot11). These genes related to muscle development and muscle contraction might be related to the evolution of longer hindlimb length and related changes in movements and microhabitat use in the introduced populations. Candidate genes, such as ntn1, acot11 and pik3cb, are related to changes in the metabolic process. All of the three genes have a function related to insulin resistance and obesity in mammals56. These selected genes imply that the evolutionary changes of insulin regulation might help adapting to changes in food items and diet composition after the introduction.Five candidate genes  have been subject to selection after the introduction event. These evolutionary changes during such a short period of time could occur since the initial standing variations in introduced individuals might be responsible for adaptation to nonnative environments despite the founder population being small. However, more robust genomic analyses such as haplotype-based inferences using larger sample sizes are necessary to provide firm conclusions.The impact of Supplemental Tables and Figures


California, USA, are hypothesized to have led to an increase in selection and evolution of resistance to the herbicide in Conyza canadensis populations. To gain insight into the evolutionary origins and spread of resistance and to inform glyphosate resistance management strategies, we investigated the geographical distribution of glyphosate resistance in C. canadensis across and surrounding the Central Valley, its spatial relationship to groundwater protection areas (GWPA), and the genetic diversity and population structure and history using microsatellite markers. Frequencies of resistant individuals in 42 sampled populations were positively correlated with the size of GWPA within counties. Analyses of population genetic structure also supported spread of resistance in these areas. Bayesian clustering and approximate Bayesian computation (ABC) analyses revealed multiple independent origins of resistance within the Central Valley. Based on parameter estimation in the ABC analyses, resistant genotypes underwent expansion after glyphosate use began in agriculture, but many years before it was detected. Thus, diversity in weed control practices prior to herbicide regulation in GWPA probably kept resistance frequencies low. Regionally coordinated efforts to reduce seed dispersal and selection pressure are needed to manage glyphosate resistance in C. canadensis.Recent increases in glyphosate use in perennial crops of  Agricultural weeds regularly adapt to multiple selective pressures at the contemporary timescale, including climate and soil conditions  of weed populations, which may reflect the timing of selection and resulting reduction in Ne, or the timing of resistance evolution and subsequent increase in Ne. As the timing of glyphosate use in agriculture is known, estimation of the timing of changes in Ne using ABC analysis may allow insights into the impact of glyphosate on the Ne of weed populations and the timing of the evolution of resistance to glyphosate. Such insights into the evolutionary and demographic processes underlying the origins and spread of herbicide‐resistant weed populations in an agricultural landscape are essential for the design of weed resistance management strategies.During the evolution and spread of weed resistance to herbicides, multiple mutations conferring resistance, strong positive selection, population bottlenecks, and founder events not only determine the spatial structuring of phenotypic variation across an agricultural landscape  how is glyphosate resistance distributed across the area sampled? (ii) is the distribution of glyphosate resistance correlated to the distribution of groundwater protection areas (GWPA)? (iii) is there spatial structuring of population genetic variation and multilocus genotypic variation associated with glyphosate resistance? (iv) are there distinct populations of glyphosate‐resistant plants that evolved resistance independently? (v) can we detect changes in Ne by ABC analysis that correspond to the timing of selection by glyphosate or the timing of evolution of glyphosate resistance? and (vi) how do the observed spatial patterns of phenotypic and genetic variation inform the design of strategies that slow or prevent the further evolution and spread of weed resistance to glyphosate?In this study, we examined the evolutionary origins and spread of glyphosate resistance in Conyza canadensis (L.) Cronquist  is native to North America  in a spray volume of 140 L ha−1 with deionized water as the carrier at 207 kPa. Response to glyphosate was assessed visually for each plant 35 days after glyphosate treatment and characterized at the population level by the proportion of plants surviving glyphosate treatment of the total number of plants treated per replication and averaged over replications.Equal amounts of seed from each plant, by volume, were bulked to produce a seed sample for each of the 38 populations. The bulked population seed samples were germinated on the surface of moist soil in 30‐cm‐diameter plastic pots. Young seedlings were transplanted into 5 × 5 cm square pots with one seedling per pot. Modified UC soil mix  was used. Plants were watered almost daily as needed and fertilized biweekly with Hoagland solution. In total, 40–90 plants were tested for glyphosate response with 2–3 replications per population and up to 30 plants per replication with the exception of population MEN1, which had one replication of 27 plants due to mortality Table  were inc2 of land that is vulnerable to the movement of pesticides into ground water by either leaching or runoff processes . The total area designated as GWPA within counties was compiled from the list available at http://www.cdpr.ca.gov/docs/emon/grndwtr/gwpa_lists.htm. To test for correlation between frequency of resistant plants within populations and the size of GWPA within counties in which the populations were sampled, the cor.test function based on Pearson's product‐moment correlation was used in R 2.14.2 (R Development Core Team Each of the areas designated as GWPA is 2.6 kmEU652944.1), and six additional new microsatellite markers . Primer sequences for the six new markers were developed using the assembled contigs from 454 sequencing of the C. canadensis genomic DNA samples . Contigs containing microsatellites were identified using the Simple Sequence Repeat Identification Tool . Primers flanking the microsatellite sequences were designed using Primer Premier 5.0 . Polymerase chain reactions (PCR) were performed in multiplex of three microsatellite markers in a total volume of 5 μL containing 10 ng of template DNA, 0.6–0.8 μm each of fluorescence‐labeled forward primer and unlabeled reverse primer, 125 μm dNTPs, 0.375 unit of Taq polymerase , and 1× PCR buffer (QIAGEN) using 384‐well PCR plates. PCR products were separated and sized on an ABI Prism 3100 Genetic Analyser  with GENEMAPPER version 3.7 using GENESCAN 500 ROX for markers HW02, HW29, and HWSSR09 and GENESCAN 400HD ROX for all other markers as internal size standard. A total of 13 individuals  exhibited allelic profiles of a polyploid similar to the often co‐occurring hexaploid Conyza bonariensis (2n = 6x = 54), obviously in addition to the diploid C. canadensis alleles (2n = 2x = 18) in some cases, suggesting rare incidences of interspecific hybridization. However, for the purposes of the analyses of population genetic diversity and structure in C. canadensis in this study, the 13 individuals were excluded from analyses following re‐analysis of the original leaf samples verifying the genotyping results.DNA was extracted from dried leaf tissue using the CTAB procedure (Doyle and Doyle TA), expected heterozygosity (HE), observed heterozygosity (HO), and Weir and Cockerham's (FIS) and fixation index (FST) were calculated for each locus using FSTAT 2.9.3 , HE, HO, FIS were calculated for each population using FSTAT 2.9.3. To assess the pattern of mating in populations, the rate of self‐fertilization (s) was estimated as 2FIS/(1 + FIS). To test for correlations between resistance and genetic diversity measures or selfing rates, the cor.test function based on Pearson's product‐moment correlation was used in R 2.14.2   in the history of the resistant populations. Scenarios 2, 3, and 4 included historical admixture events prior to the use of glyphosate in agriculture. Scenarios 5, 6, and 7 modeled recent admixture, that is, after glyphosate came into use. Recent admixture since the herbicide glyphosate came into use could have led to spread of resistance from one lineage to another following a single origin of resistance. Alternatively, support for scenarios with no such recent admixture indicates independent origins of resistance. For sets B  analyses using the program DIYABC . The susceptible populations were modeled to remain in a state of bottleneck to the present. Because of the annual life cycle, the number of generations should equal the number of years.To estimate the timing of changes in Glyphosate has been commercially available since 1974  and mean coefficient P  were chosen. In addition, susceptible populations were modeled as consisting of two closely related but divergent lineages from the same cluster in all scenarios. The model of multiple lineages within a population is consistent with high allelic and genotypic diversity despite high selfing rates in many susceptible populations.To check whether simulated data sets based on the prior distributions and the models can potentially generate summary statistics close to the observed data, 10 000 simulations per scenario were performed by using the option ‘quality of scenario/prior combinations’ in DIYABC  to the area in km2 of the GWPA within each county in which populations were sampled based on Pearson's product‐moment correlation.Population‐level resistance to glyphosate, estimated as the proportion of survivors of the total number of plants treated with glyphosate per population, varied from 0 to 1.00 among populations and was strongly spatially structured Table A. AveragHO) within populations ranged from 0.000 to 0.024, whereas expected heterozygosity (HS) ranged from 0.003 to 0.445. Accordingly, inbreeding coefficients (FIS) ranged from 0.850 to 0.966 over loci and were highly significant, consistent with the highly selfing mating system. Expected heterozygosity (HT) over all samples ranged from 0.003 to 0.894 over loci, and FST ranged from 0.034 to 0.753 and indicated significant differentiation among populations at all loci.A total of 125 alleles were detected over the 12 microsatellite loci with the number of alleles ranging from 2 to 23 per locus, indicating that the loci were highly variable and informative (Table S2). Observed heterozygosity (A) ranged from 1.0 to 4.3 among populations (Table HE) varied from 0.00 to 0.45 among populations, whereas observed heterozygosity (HO) ranged from 0.00 to 0.10. No heterozygous individuals were observed in 20 of the 44 populations. Inbreeding coefficients (FIS) were uniformly high and significant in all populations, indicating a highly selfing mating system, with the exception of population F2  and selfing rates (s) were not significantly correlated with the frequency of glyphosate‐resistant plants over all sampled populations  or over all orchard or vineyard populations  based on Pearson's product‐moment correlation.Within populations, allelic richness . Most populations were highly differentiated with 946 significant pairwise FST values between populations of the 986 tested, as expected for a highly selfing species  and accounted for 50% of all plants sampled. Two of the 35 were prominently widespread, occurring 159 and 151 times among the 1300 individuals, and in 15 and six populations, respectively . The distribution of the 35 MLG among populations corresponded to the three groups shown in Fig. R ≥ 0.95) populations, E2, F2, H2, H3, I1, K1, L1, L2, and N1 , but no clear maximum, with increasing K values ranging from 1 to 42  was not the most frequent clustering solution within five runs for K = 3 (data not shown). Multimodality in the assignment in many individuals among runs persisted with increased MCMC replications of 2 000 000 with a 1 000 000 burn‐in period (data not shown).InStruct analysis  populations, F2 and N1  of the start of expansion (spread) of resistant populations was not restricted to the period after the advent of glyphosate, the estimates were well within the time period of glyphosate selection. The start of expansion  was estimated to be between 31 and 14 generations ago in the lineages leading to resistant populations, based on the mean of the posterior distribution. For the lineages leading to recombinant MLGs i and k, the timing of admixture with other resistant MLGs was estimated to be 32 and 31 generations ago, respectively, and the start of expansion estimated to be 10 and nine generations ago, respectively. Also, the posterior distributions of bottleneck effective population sizes  were smaller than, and did not overlap with, effective population size prior to bottleneck (Ne) or the expansion effective population size in resistant populations (Nr), consistent with the model. The timing of the start of bottleneck  leading to population S and MLGs a, b, c, d, e, and f was estimated to be around 100 years ago, which is before glyphosate use in agriculture. In contrast, in the susceptible population from the northern gene pool, C2, , it was recent and within the time period for glyphosate selection.Posterior distributions of parameters estimated for the supported scenarios were similar to each other and consistent with the timing of the evolution of resistance to glyphosate but showed wide 95% credible intervals (Tables S7–S10). Although the prior distribution of the timing  to glyphosate in the sampled populations can be explained by variation in selection pressure by glyphosate. The recent spread of glyphosate resistance in ley Fig. . Our resley Fig. . AlthougConyza canadensis populations with glyphosate‐resistant plants were detected throughout the Central Valley and surrounding areas . The results indicate that glyphosate resistance in C. canadensis of California was present many years before it was first detected in 2005 by Shrestha et al.  showed two groups of glyphosate‐resistant populations  was estimated to be around 100 years ago in lineages leading to all populations and MLGs  with the exception of the susceptible population C2. Our finding that population expansion (increase in Ne) in resistant populations/MLGs was estimated to have occurred only after glyphosate use in agriculture, despite the bottleneck approximately 100 years ago, indicates a long period of successful management of C. canadensis populations until the evolution of resistance, consistent with observations of recent increases in the abundance of the species  across multiple ABC analyses using different populations or MLGs provided further insights into the population histories of resistant and susceptible populations. The timing of increase in C. canadensis populations was positively correlated to the size of GWPA in each county where glyphosate use, and thus selection for resistance, has increased recently. Genetic evidence of spread of resistance was found in counties with larger area designated as GWPA, consistent with greater landscape uniformity in high selection pressure promoting resistance spread. The reliance on glyphosate for weed control in GWPA, the multiple independent origins of resistance, and the wind dispersal of resistant seed long‐ and short‐distances (Dauer et al. C. canadensis, is no longer desirable in this area, and growers are quickly running out of options (Shrestha et al. C. canadensis under control.Glyphosate resistance in 10.5061/dryad.s21k2.Data deposited in the Dryad repository: doi:Supplemental dataClick here for additional data file.


Han Chinese, Japanese and Korean, the three major ethnic groups of East Asia, share many similarities in appearance, language and culture etc., but their genetic relationships, divergence times and subsequent genetic exchanges have not been well studied.We conducted a genome-wide study and evaluated the population structure of 182 Han Chinese, 90 Japanese and 100 Korean individuals, together with the data of 630 individuals representing 8 populations wordwide. Our analyses revealed that Han Chinese, Japanese and Korean populations have distinct genetic makeup and can be well distinguished based on either the genome wide data or a panel of ancestry informative markers (AIMs). Their genetic structure corresponds well to their geographical distributions, indicating geographical isolation played a critical role in driving population differentiation in East Asia. The most recent common ancestor of the three populations was dated back to 3000 ~ 3600 years ago. Our analyses also revealed substantial admixture within the three populations which occurred subsequent to initial splits, and distinct gene introgression from surrounding populations, of which northern ancestral component is dominant.These estimations and findings facilitate to understanding population history and mechanism of human genetic diversity in East Asia, and have implications for both evolutionary and medical studies.The online version of this article (10.1186/s41065-018-0057-5) contains supplementary material, which is available to authorized users. East Asia is one of the world’s most populated places, consisting of about 38% of the Asian population or about 22% of the world-wide population. East Asian peoples, especially the three major ethnicities, Han Chinese, Japanese and Korean, share many similarities in characteristics, for example, yellow skin, black eyes and black hair, short and flat noses, which make them hard to be distinguished by appearance. Moreover, East Asian people use similar languages and words, for example, Chinese characters are shared in Japanese, and also existed in Korean until their recent abolition in the 1940s  = 0.0014), between Chinese Dai in Xishuangbanna (CDX) and Kinh in Ho Chi Minh City of Vietnam (KHV) (FST[CDX-KHV] = 0.0024), and between CHB and Korean (KOR) (FST[CHB-KOR] = 0.0026). Genetic difference between KOR and Japanese (JPT) (FST[JPT-KOR] = 0.0033) is larger than that between KOR and CHB, but smaller than that between two Mongolian populations (Buryat Mongolian (BMON) and DU Mongolian in Qinghai (QHM) [ST[BMON-QHM] = 0.0053). These results are largely consistent with the geographic distribution of populations. Generally, pairwise FST between Han Chinese, Japanese and Korean (0.0026~ 0.0090) are greater than that within Han Chinese (0.0014), but are much smaller than that between European (CEU) and any East Asian groups, for example, the smallest FST between CEU and East Asian populations  are higher by an order of magnitude. These results suggested a comparatively closer relationship between Han Chinese, Japanese and Korean. More detailed information about the populations can be found in Additional file To assess the genetic relationship among East Asian groups, we examined genome-wide single nucleotide polymorphism (SNP) data in 1032 individuals representing 12 populations. We first calculated pairwise FA maximum likelihood (ML) tree reconstructed based on pairwise allele frequency difference provides a better visualization of the genetic relationship of populations Fig. . All theAn individual level neighbor-joining (NJ) tree of 1002 world-wide individuals based on genotyping differentiation was also constructed  to reconstruct an individual tree, we found the phylogeny of the populations became clearer  to examine the population structure on individual level Figs.    (3)  (3) , where cmosomes) . DivergeeFST (4) . Here, Fation Ne .We used D test and F test to detect and estimate gene flow . All thep < 0.01) suggests the existence of gene flow either from W to Y or from W to Z. X is out group. In population genetics, D is calculated byIn D test, D value indicates the difference of the two allele patterns ABBA and BABA  and can be looked as the drift on edge A to B in a phylogeny tree. Andene flow , 12, 13.If there was gene flow in history, the drift from one population to another would go through more than one path in the phylogeny tree; the ratio of drift along each path is decided by the ratio of gene flow. If there were gene flow from population A to population C (with a ratio α) and from population B to population C (with a ratio 1-α), thenl and m are unknown, but if there is a series of population C that are admixed with ancestry from both population A and population B (A’ and B′) with different ratio, we can use a linear regression to eliminate these parameters, so that we can calculation each gene flow ratio α [Where  ratio α .Additional file 1:Figure S1. A heat map of pair-wise FST. A warmer (red) color means a larger FST value (generated by R 2.15.2). (PDF 6 kb)Additional file 2:Table S2. Global FST values between East Asian populations and world-wide groups. (DOCX 16 kb)Additional file 3:Table S1. Genotype data used in this research. (DOCX 21 kb)Additional file 4:Figure S2. Individual level Neighbor-Joining Tree. (A) The NJ tree was constructed according pair-wise genotyping difference; (B) Individual NJ Tree of Han Chinese, Japanese, Korean and Mongolian individuals (generated by MEGA version 4.0). (PDF 6971 kb)Additional file 5:Figure S3. Principle component analysis (PCA). (A~B) PCA results of East Asian groups with CEU and YRI. (C) PCA result of groups within East Asia populations, excluding JPRK individuals for a higher marker density. (D) PCA result of four East Asian populations, including Han Chinese, Japanese and Koreans samples. (PDF 2458 kb)Additional file 6:Figure S4. K-means Cluster of PCA results. The results of Figure S3D were used to conduct the K-means cluster. Individuals that cluster together according to the top 10 PCs would be painted by the same color. Results of K = 3 and K = 4 are shown (generated by R 2.15.2). (PDF 116 kb)Additional file 7:Figure S5. Matthews correlation coefficient (MCC) values increase when more AIMs are used to distinguish individuals. X axis is number of SNPs and Y axis is MCC values. (A) CHB-CHS; (B) CHB-JPT; (C) CHB-KOR; (D) CHS-JPT; (E) CHS-KOR; (F) JPT-KOR (generated by Microsoft Excel 2010). (PDF 99 kb)Additional file 8:Figure S6. Effective population size varied along time. Results from 10,000 generations ago (GA) to 200 GA are shown (generated by Microsoft Office 2010). (PDF 112 kb)Additional file 9:Figure S7. STRUCTURE analysis of East Asian samples with worldwide populations. Results from K = 3 to K = 7 are shown. Each vertical bar represents an individual and each color stands for a genetic component (generated by R 2.15.2). (PDF 141 kb)Additional file 10:Figure S8. STRUCTURE Analysis of ten East Asian populations. Results from K = 2 to K = 6 are shown. Each vertical bar represents an individual and each color stands for a genetic component (generated by R 2.15.2). (PDF 152 kb)Additional file 11:Figure S9. Cross-validation (CV) plot for the Admixture analysis. Result of K = 3 to K = 7 are shown. (PDF 158 kb)Additional file 12:Table S3. Part of F3 test results. (DOCX 18 kb)Additional file 13:Figure S11. Models used in gene flow study. (A) Model of D test. X is an out group, we put CEU or YRI in X; W is the contributor while Y and Z are the receivers. By comparing the two allelic patterns BABA and ABBA, we can infer the relationship of scale of gene flow between W to Y and W to Z. (PDF 30 kb)Additional file 14:Figure S10. Results of linear regression in F4 test. For each group , X axis is F4, Y axis is F4. (A) Outgroup is YRI or CEU, donate populations are TIB and CDX, target population is Han Chinese or KOR; (B) Outgroup is YRI or CEU, donate populations are CDX and JPRK, target population is Han Chinese or JPT or KOR; (C) Outgroup is YRI or CEU, donate populations are TIB and JPRK, target population is JPT or KOR (generated by Microsoft Excel 2010). (PDF 226 kb)


We used population genetic data as well as ecological niche modelling to examine the evolutionary history and glacial refugia during the Last Glacial Maximum (LGM) of this group. We recovered 133 cpDNA and 68 nuclear haplotypes. The star-phylogeny of the recovered cpDNA and nuclear haplotypes and demographic analyses suggested distinct range expansion of I. bungeana complex have occurred during the early and middle Pleistocene. The climate change of the LGM might have affected little on the distribution of this complex based on the niche modelling. However, these climate changes and geographic isolation probably resulted in fixtures of the private haplotypes and genetic differentiations between regions. Our results suggested that this arid-tolerant species complex may have different responses to the Quaternary climate changes with those climate-sensitive species.East Asia harbors the highest level of floristic diversity among the world’s temperate regions. Despite the increase in phylogeographic studies of temperate plants in East Asia, far less attention has been paid to widely distributed deciduous shrubs that widespread across several floral regions. We sequenced two chloroplast DNA (cpDNA) fragments ( Two general hypotheses on forest responses to the Quaternary climate changes in East Asia have been proposed3. Palaeovegetation data from East Asia showed that temperate forests in this region were considerably more restricted than today and would have retreated southward to c. 30°N during the LGM2. Conversely, Harrison et al. suggested that temperate forests in this region did not migrate on a large scale, but rather retained in local low-altitude refugia and formed discontinuous forest vegetation during glacial periods3. A limited number of phylogeographic studies appear to support the latter hypothesis. For example, in northern and northeast China, two species of shrubs, Ostryopsis davidiana Decne. and Quercus mongolica Fischer ex Ledebour, survived in multiple glacial refugia and showed regional postglacial expansions5 while in southern and southeast China multiple refugia were recovered for a few trees and accompanying species, such as Tetrastigma hemsleyanum Diels & Gilg6, the East Asian Kirengeshoma7, and the species of the fir genus8. In subtropical China, the evergreen broad-leaved forest constituents conform to either an in situ survival model or an expansion-contraction model, such as Castanopsis tibetana, Machilus thunbergii and Schima superba9, Sargentodoxa cuneata10, and Loropetalum chinense11. In addition, in the eastern Himalaya, some species from multiple refugia during the Last Glacial Maximum expanded their range to colonize extensive regions before the middle Quaternary14, although some climate-sensitive trees retreated and recolonized high-altitude regions after the LGM16. Up to now, no studies have examined the phylogeographic structure of a single species/species complex or monophyletic group whose current distributions cover all of these regions in East Asia.It is now well appreciated that climate oscillations during the Quaternary have profoundly shaped the geographic distributions and current genetic diversity of many temperate species in the Northern HemisphereIndigofera bungeana complex (Fabaceae), a complex of deciduous shrubs widespread in temperate East Asia , with a continuous geographic distribution covering southern China, northern China and the Hengduan Mountains region (HMR). Four species have been ascribed to this complex17, I. bungeana Walpers, I. amblyantha Craib, I. silvestrii Pampanini, and I. ramulosissima Hosokawa. Species delimitations between them remains unclear due to the lack of clear morphological and genetic gaps. Our unpublished phylogenetic analyses suggested that numerous individuals of each species intermixed, but formed a highly supported monophyletic clade sister to the species of Indigofera from the Cape region of South Africa. We therefore treated them as a single evolutionary lineage in our phylogeographic analyses. Members of this complex grow in sunny, arid habitats at elevations between 100‒2700 m17. Their widespread distribution provides a unique opportunity to examine how plants responded to past climate changes over a large region in East Asia.In this study, we focused on the phylogeographic patterns of the 18, due to the merits of rare recombinations and smaller effective population size19. This type of population genetic data allows an inference of historical range shifts and recolonization routes22. Second, we also sequenced one nuclear DNA fragment. Population data from nuclear genetic polymorphisms can confirm the phylogeographic inferences from cpDNA26. Sequence variation data from a single nuclear locus is becoming popular for such an aim27.We sequenced two types of DNA fragments with contrasting backgrounds of inheritance. First, two maternally inherited chloroplast DNAs (cpDNAs) were used, as in most phylogeographic studiesI. bungeana complex retreat southward or survive in situ during the LGM?We finally used ecological niche modelling to infer the possible distributions of this complex during the LGM in East Asia. We expected that the simulated distributions should be consistent with the phylogeographic inferences of the population genetic data. We aimed to address the following questions: (1) Are phylogeographic inferences from cpDNA data consistent with those from nuclear DNA data? (2) When and how did this complex obtain its widespread distribution in East Asia? (3) Did the ndhJ-trnF and trnD-trnT fragments across the 472 individuals sampled was 2933 bp, containing 155 substitutions and 43 indels (insertion/deletion) (4‒116 bp). A total of 133 chlorotypes (C1‒C133) was identified, 104 (78.2%) of which occurred in a single population (Table Hd) and nucleotide (π) diversity of the cpDNA data was 0.982 and 0.0033, respectively. Seven of the 51 populations surveyed contained only one haplotype, whereas the remaining populations were polymorphic ; the second B clade contained three, C8, C9 and C47, distributed in the Hengduan Mountains region and southern China. Clade C included all the remaining numerous chlorotypes with unresolved relationships, indicating radiative diversification. The haplotype network showed the star phylogeny, and most cpDNA haplotypes were arranged as a radiative phylogenetic tree relative to the central ones, e.g. C67, C36, C24, C75, C74 and C8 . These polymorphisms defined 68 haplotypes, with 42 (61.8%) haplotypes unique to a single population (Table Hd) and nucleotide (π) diversity of the Pgk1 was 0.927 and 0.0106, respectively. Among the 51 populations surveyed, five were fixed for a single haplotype, and the remaining ones were polymorphic  haplotypes clustered into three clades , while the clade III comprised the remaining haplotypes that occurred throughout the whole distribution areas of I. bungeana complex. The haplotype network showed the same star phylogeny with most haplotypes relative to the central ones  which occurred at a high frequency  Ma. The common ancestors of clades I, II and III were estimated to have occurred 0.67 (95% HPD: 0.26‒1.28) Ma, 0.35 (95% HPD: 0.01‒0.93) Ma and 0.98 (95% HPD: 0.51‒1.66) Ma  Hengduan Mountains region (HMR), (B) Northern China, (C) Southern China  across the overall populations was much higher than the average within-population gene diversity HS (Table Pgk1: 0.922), in accordance with the occurrence of the most divergent haplotypes in this region  was observed in the HMR, which was consistent with the significantly higher GST values than in other regions (Table FCT = 0.076) and 4.76% (FCT = 0.048), those among populations within species 53.33 (FSC = 0.577) and 76.12% (FSC = 0.799), and those within populations 39.11% (FST = 0.609) and 19.11% (FST = 0.809) of the total cpDNA and nuclear DNA genetic variation, respectively  phylogeny displayed a bimodal or multimodal mismatch distribution  of the statistical comparisons between these observed distributions and simulated ones under a sudden expansion model significantly rejected the expansion model  and Tajima’s D  values, indicated a historical demographic expansion within cpDNA clade C and Pgk1 clade III. Based on the corresponding τ, and assuming minimum and maximum substitution rates of 1.0 × 10−9 and 3.0 × 10−9 s s−1y−1, the expansion of clade C was estimated to have occurred at 698 (95% CI: 493‒961) and 232 (95% CI: 164‒320) thousand years ago (Kya), respectively. Bayesian skyline plots suggested that effective population size of the cpDNA clade C increased quickly  Kya  and ion Fig. . Howeverkly Fig. . The expI. bungeana complex was high (0.984), indicating a good predictive model performance. The projection of the model over present bioclimatic conditions shows a good habit suitability between 23°N and 45°N in East Asia  increased in the early and middle Pleistocene. What’s more, the results of mismatch distribution and neutral tests further supported the expansion hypothesis. All these available evidences seem to support that a common expansion have occurred within I. bungeana complex. The range expansions detected in cpDNA clade C and nuclear clade III were estimated to have occurred approximately between 60 and 961 Kya, in the early and middle Pleistocene. Although we could not pinpoint the expansion accurately, it is highly possible that climate change of the Quaternary might have facilitated this expansion30. Some cold-tolerant plants, such as the species of the fir genus, expanded extensively and continuously in high-elevation regions during the Quaternary34.This phylogeographic pattern may be better explained by the hypothesis that all examined populations have experienced a common expansion followed by the fast isolationspes Figs  and 4. T37. The Quaternary climate changes after the range expansions should have mainly accounted for such fixtures of the private haplotypes in the different regions and great among-regions differentiations. The limited seed and pollen dispersals of this specie complex may have also played an important role.However, it remains unknown how the ancestral haplotypes disappeared in different regions/populations. It is highly likely that geographic isolations following the range expansions promoted the private haplotypes displaced the ancestral ones. Such scenarios were usually found for isolated species or populations−1 than the present, respectively40. The Quaternary climate changes have strongly affected distribution and genetic diversity of the temperate plants in East Asia, resulted in experienced glacial southward migrations, or in situ glacial survival26. Species of the I. bungeana complex have high cold tolerance as well as drought tolerance with the most northward distributions between c. 23°N and 45°N in the genus41.Although northern and southern China have never been covered by large ice sheets during the LGM, it is estimated that the climate was cooler by at least 7‒10/4‒6 °C and dryer by c. 200‒300/400‒600 mm yrI. bungeana complex during the LGM also indicated that the distribution did not migrate southward significantly although the core distributions shrank, which is also consistent with the species with similar distribution in East Asia, such as Juglans cathayensis42, Quercus variabilis43, and Tetrastigma hemsleyanum44.Most private haplotypes in this complex derived from the range expansion in the early and middle Pleistocene, earlier than the LGM. Our simulations of the distributions of the I. bungeana complex might have survived in situ or in multiple large refugia in response to the climate change of the LGM. However, this and other Quaternary climate oscillations might have together accelerated the regional isolations of the I. bungeana complex that promoted the fixture of the numerous private haplotypes. Our results seem to suggest not all woody species growing under the temperate deciduous forests in northern China migrated southward3. However, these climatic changes might have promoted the species or genetic differentiations of plants occurring in East Asia as suggested by Qian and Ricklefs2.Given the above evidence, we tentatively suggested that the I. bungeana complex in China .A total of 472 individuals representing four species were collected from 51 populations, with 1‒13 individuals per population (spaced at least 50 m apart), covering the whole range of the atpF-atpH, rpl32-trnL, rps16-trnQ, ndhJ-trnF, matK, trnL-trnF, ndhC-trnV, trnD-trnT, ndhF-rpl32 and psbA-trnH) for the representative samples of I. bungeana complex, we chose two cpDNA intergenic spacer (IGS) regions (ndhJ-trnF and trnD-trnT)47 for the phylogeographic study. In addition, Pgk1, a single-copy nuclear (scn) gene responsible for coding plastid phosphoglycerate kinase isoenzymes, was surveyed among 51 populations using two new primers .Total genomic DNA was extracted from silica-gel-dried leaves using the plant genomic DNA extraction kit . After preliminary screening of ten chloroplast fragments  Taq DNA polymerase , and 0.5 µL genomic DNA (10‒50 ng). The PCR amplifications were performed as follows: initial denaturation at 94 °C for 5 min, followed by 33 cycles of denaturation at 94 °C for 45 s, annealing , and extension at 72 °C , and a final extension at 72 °C for 7 min prior to holding at 12 °C forever. PCR products were purified using an E.Z.N.A gel extraction kit . The purified PCR products were sequenced by Life TechnologiesTM .All amplifications were performed in 25 µL reactions containing 17 µL deionized sterile water, 1.5 µL of 25 mM MgCl49 and subsequent manual adjustments. Nuclear (Pgk1) allelic phases were resolved using the algorithm of PHASE27 implemented in DnaSP 5.050, using 1,000 iterations with a 1,000 generation burn-in iterations and a thinning interval of 10. Indels were treated as single mutation events and coded as substitution (A or T). Haplotypes of cpDNA (chlorotypes) and Pgk1 were recognized using DNASP 5.050. Genealogical relationships among chlorotypes and nuclear (Pgk1) haplotypes were constructed using a statistical parsimony algorithm51 as implemented in Network v. 4.6 (http://fluxus-engineering.com).Sequences were assembled and edited with Sequencher 4.1 , aligned using Clustal X 1.81HS, HT) and between-population differentiation  were estimated using PERMUT52 with the 1,000 permutations test. A higher NST than GST usually indicates the presence of phylogeographic structure, that is, the more frequent occurrence of closely related haplotypes in the same area than less closely related haplotypes52. A comparison was made between NST and GST using the U-statistics test.Population gene diversity  ranging from 2 to 20. To verify the consistency, we ran the analysis five times for each K value with 1,000 independent iterations, starting from 100 random initial conditions. We assessed the optimal K as the one for which FCT  was the highest and significant.The spatial analysis of molecular variance (SAMOVA) was conducted using SAMOVA 1.054 to estimate the partition of genetic variance among groups, within and among populations. In the AMOVA analysis, populations were partitioned by geography or species, respectively. Geographical groups were obtained from SAMOVA analysis. If the SAMOVA analysis was unable to detect suitable groups, populations were grouped following Wu & Wu28.Hierarchical analysis of molecular variance (AMOVA) was performed in ARLEQUIN 3.1Indigofera (I. szechuensis Craib and I. lenticellata Craib) were chosen as outgroups in the phylogenetic analyses according to the phylogenetic analyses of Indigofera (our unpublished results). Phylogenetic relationships of the chlorotypes and nuclear (Pgk1) haplotypes were reconstructed with Neighbor-joining (NJ) and Bayesian inference (BI) methods, using MEGA 5.0555 and MrBayes 3.156, respectively. In the NJ analysis, we used the Kimura’s 2-parameter model57. Confidence values at the nodes were tested by performing 1,000 bootstrap replicates. Prior to BI analyses, the optimal nucleotide substitution model was determined using jModeltest 2.1.258 via the Akaike Information Criterion (AIC)59. The TVM + I + G model (cpDNA) and GTR + I + G model (Pgk1) were selected as the best-fit models. Four Markov chain Monte Carlo (MCMC) chains were run for 20,000,000 generations, starting from random trees and sampling one tree per 1,000 generations with the first 4,000,000 samples discarded as burn-in. The program Tracer 1.560 was used to check the parameter convergence and effective sample size. A 50% majority-rule consensus tree was summarized with posterior probabilities as nodal support.Two species of 61 in PAUP 4.10b62 suggested that the chloroplast and nuclear datasets rejected a strict molecular clock (P < 0.01), therefore we used a relaxed molecular clock. Divergence times between the chloroplast and nuclear haplotype clades were estimated under a Bayesian approach63 in BEAST 1.6.264. As there is no fossil record of Indigofera, we adopted a substitution rate method. The cpDNA substitution rates for most angiosperm species have been estimated to vary between 1.0 × 10−9 and 3.0 × 10−9 substitutions per site per year (s s−1y−1)65. Given the uncertainties of these rate values in Indigofera, we used a minimum (1.0 × 10−9 s s−1y−1), mean (2.0 × 10−9 s s−1y−1) and maximum (3.0 × 10−9 s s−1y−1) substitution rate, respectively. For Pgk1, we adopted a nucleotide substitution rate of 13.6 × 10−9 s s−1y−1 according to Huang et al.66.A likelihood-ratio testD67 and Fu’s FS68 tests, which are expected to show significant negative values under population expansion and positive under a population bottleneck. A mismatch distribution analysis69 (MDA) was also conducted to explore the demographic history of major chlorotypes and nuclear (Pgk1) haplotype clades. Populations that have experienced expansion are expected to have a unimodal shape, whereas stable populations are expected to have a bi- or multi-modal mismatch distribution. The goodness-of-fit was assessed by the sum of squared deviations (SSD), Harpending’s raggedness index70 (HRag) and 95% confidence interval (CI) around τ under a sudden-expansion model. Statistical significance was determined by 1,000 bootstrap replicates. These analyses were conducted using ARLEQUIN 3.158. To obtain estimates of changes in demographic growth over the history of major clades, the historical demographic dynamics of the I. bungeana complex were inferred from Bayesian skyline plot (BSP) analyses using BEAST 1.6.264. Linear and stepwise models were explored using an uncorrelated lognormal relaxed clock. Runs consisted of 50,000,000 generations, with trees sampled every 1000 generations. The BSP was visualized in the program Tracer version 1.5, which summarizes the posterior distribution of population size over time.To test the assumption of selective neutrality, we performed Tajima’s 71 to infer the potential geographic range of the I. bungeana complex at the present, the LGM (ca. 21 ka) and last interglacial  based on the bioclimatic layers downloaded from the WorldClim database72 (http://www.worldclim.org) at 2.5-arcmin resolution. The paleo-climatic conditions during the LIG were simulated by Community Climate System Model73 (CCSM), while we used two available models for the LGM: CCSM and MIROC74. Distribution records of the species of I. bungeana complex were sourced from the database of GBIF (http://www.gbif.org/) and Chinese Virtual Herbarium (http://www.cvh.org.cn), as well as our own field collections. After initial screening for duplicates and records aggregation into a 2.5 resolution raster, 181 unique records were used. Highly correlated variables (r > 0.7) were excluded, and we ultimately selected five bioclimatic variables . To statistically evaluate model performance, we used the area under the “Receiver Operating Characteristic (ROC) Curve”75 (AUC), a threshold-independent measure of model performance as compared to null expectations.We used the maximum entropy modelling implemented in MAXENT 3.3.3kSupplementary Information