Daphnia pulex (a freshwater crustacean) from lakes across the Chernobyl area, genotyped them at ten microsatellite loci and also calculated the current radiation dose rates. We then investigated whether the pattern of genetic diversity was positively associated with radiation dose rates, consistent with radiation‐mediated supply of de novo mutations, or negatively associated with radiation dose rates, as would be expected with strong radiation‐mediated selection. We found that measures of genetic diversity, including expected heterozygosity and mean allelic richness (an unbiased indicator of diversity), were significantly higher in lakes that experienced the highest radiation dose rates. This suggests that mutation outweighs selection as the key evolutionary force in populations exposed to high radiation dose rates. We also found significant but weak population structure, indicative of low genetic drift and clear evidence for isolation‐by‐distance between populations. This further suggests that gene flow between nearby populations is eroding population structure and that mutational input in high radiation lakes could, ultimately, supply genetic variation to lower radiation sites.Populations experiencing varying levels of ionizing radiation provide an excellent opportunity to study the fundamental drivers of evolution. Radiation can cause mutations and thus supply genetic variation; it can also selectively remove individuals that are unable to cope with the physiological stresses associated with radiation exposure, or non‐selectively cull swathes of the population, reducing genetic variation. Since the nuclear power plant explosion in 1986, the Chernobyl area has experienced a spatially heterogeneous exposure to varying levels of ionizing radiation. We sampled  Daphnia populations. Measures of genetic diversity, including expected heterozygosity and mean allelic richness, were higher in lakes that experienced the highest radiation dose rates. This suggests that mutation outweighs selection as the key evolutionary force in populations exposed to high radiation dose rates. We examined population genetic diversity across Chernobyl  Daphnia are perfectly poised to study the effects of radiation because they are known to suffer reduced fitness  radiation‐mediated supply of genetic variation, (2) radiation‐mediated selection or (3) genetic drift associated with a massive population bottleneck.Here, we used 10 microsatellite loci to examine the population genetic structure of the freshwater crustacean, 22.1Daphnia pulex, sediment and water samples were collected from seven of the eight Daphnia‐inhabited lakes within and immediately outside the CEZ from the 7–16 July 2016. Individual daphnids were immediately stored in 1.5‐ml Eppendorf tubes in absolute ethanol at ambient temperatures and transported back to the UK, where they were stored at −20°C prior genotyping. A total of 205 samples were collected from seven lake populations  and radionuclides that were considered representative of others present within the water column and top sediment layer (241Am and 239Pu)  IAEA,  were useu) IAEA, . Where iu) IAEA, .Daphnia, we used the ERICA (version 1.2) software program. ERICA calculates dose rates using an extensive database of published values for radionuclide transfer through the environment and the activity concentrations in various media  and organisms, including over 24 000 data entries for freshwater organisms alone .To estimate dose rates experienced by 2.2Daphnia samples from the seven lake populations  using the GeneScan‐500 LIZ size standard (Applied Biosystems). Microsatellite band scoring was completed manually using GENEIOUS software . The strongest peak(s) within the loci were selected to determine allele size.Microsatellite genotyping was used to identify differences in allele frequencies and population structure within and across lake populations following the protocol previously outlined by Auld and Brand . First, es Table , though 2.3O and HE, respectively) were calculated , the total number of private alleles (PA), and both observed and expected heterozygosities  and among (FST) populations  was used to partition variation within and between populations; the significance of these within‐ and among‐population variation was then estimated using 999 permutations (ade4 package), which quantified the association between two matrices of pairwise Edward's genetic distances . This was done using a Mantel test  to retain . The α‐score procedure maximizes the capacity to discriminate between individuals whilst minimizing model overfitting  to allow a more comprehensive examination of population genetic structure  among the 205 individuals ; these patterns were clearly driven by the two populations experiencing the highest radiation dose rates (Gluboke and Krasnyansky). We tested the robustness of the relationship between dose rate and MAR by calculating the correlation coefficient (r = 0.82) and then performing a randomization test where we compared this correlation coefficient with 5000 resampled correlations where each of the MAR values was assigned a random dose rate value; we found the relationship between dose rate ad MAR to be robust  to also be robust  or HE .There was a significant effect of radiation dose rate on both MAR (3.2FIS) was 0.11, and the individual population FIS values ranged from −0.14 to 0.30 , demonstrating that even though there was evidence of gene flow (see later results), each population was indeed a separate entity.An AMOVA revealed significant variation within samples, within populations and between populations Table , confirm30 Table . The strthat is an isolation‐by‐distance effect  visible at the level of the phenotype.Ionizing radiation can cause mutations and thus supply genetic variation to populations  contained Daphnia populations. This does not, of course, mean that radiation‐mediated selection is absent or weak. The positive relationships between population genetic diversity and radiation dose rate are driven by the two highest dose rate populations, and we cannot exclude a negative relationship between radiation dose rate and population genetic diversity at lower radiation levels (a limitation from having seven available populations). Further, it could be that radiation‐mediated selection for Daphnia with effective anti‐stress or DNA repair mechanisms was particularly strong at the time of the accident  in two populations  . We found only one instance, in Gluboke lake (which had the highest radiation dose rate), where the same MLG was collected twice and, as discussed earlier, there were no significantly negative FIS values for that population. This could be because all the sampled lakes are sufficiently large to host very large Daphnia populations where the frequency of sex is high  and thus past clonal selection in Yampol, Buryakovka and Krasnyansky lakes. Importantly, the strength of this linkage disequilibrium was not associated with dose rate, suggesting that past bouts of clonal selection or sexual reproduction are caused by biotic or abiotic conditions that are unrelated to the nuclear accident.It is important to consider the complex reproductive biology of e Lynch, . Clonal e Lynch, , FIS vaDaphnia resting stages disperse, fuelling within‐population evolution and adaptation in the manner of a metapopulations (Hanski, Daphnia populations (Goodman et al., Finally, we found evidence that gene flow from dispersal from neighbouring populations is reducing levels of population structure (in the form of strong isolation‐by‐distance: Figure  Hanski, . As suchDaphnia populations. However, the relationships between radiation dose rate and measures of population genetic diversity are robust (Figure in spite of the low number of available populations, highly variable levels of linkeage disequilibrium and within‐population structure across lakes. This firmly points towards the explanation that Daphnia populations in high radiation lakes are experiencing greater mutation‐mediated supply of genetic variation than their low radiation lake counterparts. Of course, these findings provide the first insight into radiation‐mediated evolution in Chernobyl; the logical next step is to search for those mutations in coding regions and look for evidence of selection.It is important to note that this is a correlational study and not a common garden manipulation experiment, so we cannot completely exclude the idea that that an unmeasured variable could have shaped genetic diversity among these Chernobyl t Figure , in spitThe authors declare no conflict of interest.Daphnia sampling. GL determined the radioisotope activities. JG calculated the radiation dose rates. JG and JB did the microsatellite genotyping. SKJRA contributed reagents and analytical tools. JG and SKJRA conducted the genetic analyses and wrote the manuscript. All authors approved the final version of the manuscript.JG and SKJRA designed the research. JG conducted the https://publons.com/publon/10.1111/jeb.13983.The peer review history for this article is available at Supplementary MaterialClick here for additional data file.


The transition to agriculture occurred relatively late in Eastern Europe, leading researchers to debate whether it was a gradual, interactive process or a colonisation event. In the forest and forest-steppe regions of Ukraine, farming appeared during the fifth millennium BCE, associated with the Cucuteni-Trypillia cultural complex . Across Europe, the Neolithisation process was highly variable across space and over time. Here, we investigate the population dynamics of early agriculturalists from the eastern forest-steppe region based on the analyses of 20 ancient genomes from the site of Verteba Cave . Results reveal that the CTCC individuals’ ancestry is related to both western hunter-gatherers and Near Eastern farmers, has no local ancestry associated with Ukrainian Neolithic hunter-gatherers and has steppe ancestry. An Early Bronze Age individual has an ancestry profile related to the Yamnaya expansions but with 20% of ancestry related to the other Trypillian individuals, which suggests admixture between the Trypillians and the incoming populations carrying steppe-related ancestry. A Late Bronze Age individual dated to 980–825 cal BCE has a genetic profile indicating affinity to Beaker-related populations, detected close to 1000 years after the end of the Bell Beaker phenomenon during the third millennium BCE. There are two major groups of models that explain the Neolithisation process: demic diffusion models describe Neolithisation as a colonisation process by farmers which is propelled by exponential population growth characteristic of the Neolithic, whereas acculturation models outline the process as one in which at least some of the transition entails indigenous hunting-foraging groups that adopt farming following periods of variable length during which they interact with neighbouring exogenous farmers2. Across most of Europe, the Neolithic transition was genetically defined by a profound population replacement, consistent with the demic diffusion of peoples from Anatolia5. The Anatolian farmers reached the Balkans and other regions of Southeast Europe in the seventh millennium BCE7 and subsequently spread further via the Mediterranean and later through the Danube, substantially replacing indigenous Mesolithic European populations9.The Neolithisation process in Europe resulted in dramatic technological and cultural shifts, which included novel subsistence practices11, areas of Eastern Europe including Ukraine, Moldova, Western Russia, and Romania did not adopt agriculture until the Late Neolithic (~ 4500 BCE), although various sedentary and semi-sedentary hunter-gatherers Mesolithic groups in these regions began using pottery as early as 8500 BCE13.In contrast to Central Europe15. This complex stretches from the Transylvanian Alps to the Dnieper River and is named for the type-sites of Cucuteni in Iași County, Romania and Trypillia  in Kyiv oblast, Ukraine. The Cucuteni and Trypillia cultures have common roots in the Precucuteni culture; the earliest CTCC sites are found in the piedmont of the Carpathian Mountains and the earliest radiocarbon dates (from the Precucuteni 2 period) date to around 4800 BCE17. The CTCC originated from the interaction of several Danubian Neolithic groups, with evidence for similarities in house construction, ceramic styles, and lithic artifact production19.The Cucuteni-Trypillia cultural complex (CTCC) is a grouping of several interrelated Middle Neolithic/Eneolithic archaeological cultures in parts of Ukraine, Moldova, and Romania18. However, some population growth may have been the product of Trypillian populations incorporating indigenous hunting and gathering (HG) groups, such as members of the Bug-Dneister culture. Another mode of population increase could have been the acculturation of refugees following the collapse of the Neolithic in Romania, Hungary, and Bulgaria. During the middle-to-late periods of the Trypillia culture , some CTCC groups established extremely large settlements in Central Ukraine, often referred to as “giant-settlements'' or “megasites,” which attained sizes of 100–320 ha20. Rapid demographic growth within the CTCC around the turn of the fourth millennium BCE necessitated the exploitation of new territories, precipitating migrations to previously peripheral areas21.Following the origin of this cultural complex in the Carpathian piedmont, the CTCC eventually occupied a territory covering much of the modern territories of Ukraine, Moldova, and Romania. The first diagnostically Early Trypillia (Trypillia A) sites diverged from the Precucuteni culture ~ 4500 BCE in the Dniester River valley. Later population movements, occurring from the middle period (Trypillia BI) onward, saw the Trypillia culture expand to Volhynia in the west and the Dnieper River in the east. This territorial expansion is believed to have resulted primarily from demographic increases associated with a successful agropastoral subsistence strategy, and the search for new arable land for cultivation23, or that they simply represent ephemeral episodes of population agglomeration due to large-scale migration from the Dniester region24.Hypotheses for the rise of the megasites in particular are varied; it has been suggested that they may have been a defensive response to threats posed by steppe pastoralists or competing sub-groups within the CTCC25, very few burials have been located. Only a handful of cemeteries dating to the Late Trypillia period were excavated during the 1960s and 1970s, such as Chapaievka in Ukraine26 and Vykhvatyntsi in Moldova27. While these sites give some glimpse into Trypillian mortuary behavior, they are limited in their temporal scope and have not been subjected to modern laboratory analyses. To better understand the origins, connections, and diversity of the CTCC, we collected human remains from three chambers at the site of Verteba Cave (VC) in Ternopil oblast, Ukraine, one of the few sites that contain human remains associated with the CTCC 29. On the basis of the ceramic assemblages present in the cave and a sample of lower-resolution liquid scintillation 14C dates, it is probable that occupation continued for some time into the Late Trypillia (CII) period and Early Bronze Age transition30. More recently, AMS radiocarbon dating has also identified deposits at different locations throughout the cave dating to the Mesolithic , Bronze Age, Iron Age and Medieval period31. Skeletal assemblages were taken from three separate chambers  of the cave . Interpretations regarding the use of the cave are varied, including its use as a temporary shelter, ritual site or mortuary location34. There is additional evidence to support the idea that the burials in the cave, which are largely commingled and secondary in nature, are representative of victims of warfare or sacrifice35.Even though Trypillian populations established a high density of settlements in Western and Central Ukraineve Table , Fig. 1.36. Schmidt et al. found within a single chamber evidence for Haplogroup W, which has been observed for steppe populations associated with the Corded Ware and Unetice cultures of the middle Volga region8. Genome-wide analyses of CTCC individuals have shown ancestral components predominately of Early Neolithic farming groups (estimated to be 60–80%), confirming that the early farmers who settled Western and Central Ukraine were largely derived from the same source population as the farmers of Anatolia and Western Europe37. The remaining 20 percent of their ancestry is less certain. Mathieson et al. (2018) found that this ancestral component was a mix of western (WHG) and eastern (EHG) hunter-gatherers (HG) found in HG groups inhabiting the region during the Neolithic. Immel et al. recovered genome-wide data from four individuals buried at two separate sites in northern Moldova that date to 3500–3100 cal BCE (during the Late Trypillia period), five centuries younger than the radiocarbon dates from Verteba cave, and found a larger degree of steppe-related ancestry . This observation may be explained by the gradual assimilation of local Mesolithic and Neolithic HG groups into the Trypillian population, at least for groups who settled in Moldova.The paleogenetics of the Trypillian population is limited to the analysis of uniparental markers (mtDNA) and genome-wide analysis of 8 individuals. Mitochondrial haplogroups typical of ancient Eurasian farming groups  have been observed for these individuals scattered throughout the cave38. Some of these look nearly identical to pottery found at steppe sites, while others combine shell tempering with CTCC decorative motifs35. Symbolic objects influenced by—or directly imported from—steppe communities, such as stone mace heads, are found at some Middle-to-Late Trypillia sites35, and exchanges of pottery are evident as early as Trypillia BII39. There was undoubtedly some degree of interaction between Trypillian populations and the Dnieper-Donets culture, while any synchrony between the Trypillia culture and the following Yamnaya horizon was likely very brief. Regardless, however, some Trypillian populations were likely in permanent contact with steppe populations40. Interestingly, after around 3400 BCE, the Trypillian mega-sites were largely abandoned. The cause of this abandonment has been widely debated, one hypothesis is an increase in conflict due to the westward expansion of steppe populations. Such a hypothesis may find corroboration in the frequent evidence of violent death discovered in Verteba cave35.The settlement systems of the Trypillia culture interacted with both Central European and the steppe populations. Archaeological evidence for steppe interaction is found in shell-tempered pottery, which are similar to steppe-style wares14C to the interval of 3790 to 825 cal BCE  using our expanded dataset with higher coverage than in Mathieson et al.13, can we clarify the Neolithic ancestral component of the Trypillian population, i.e., can we show that they are more similar to early farmers from Anatolia, the LBK (Linearbandkeramik), or elsewhere; (3) since the CTCC individuals lived in close proximity to steppe populations, is there evidence for genetic admixture with the Yamnaya or earlier steppe populations; and (4) do later Bronze Age populations that settled in the region share genetic affinities with the CTCC group from Verteba Cave?Here, we recovered genome-wide sequence data from 20 individuals buried in VC, eight of which are directly dated by AMS CE Table . We use 41. Further details of the contamination assessment is provided in Supplementary information. We were able to assign molecular sex to all the individuals, from which 8 are female and 12 are male  date to 3790–3535 cal BCE , one individual (VERT-113) from Site 7 dates to 1960–1770 cal BCE  and one from Site 17 (VERT-114) dates to 980–825 cal BCE  Table . Endogenle Table . In all 5 as well as European Bronze Age individuals43. The LBA individual shows haplogroup T2, also associated with multiple BA individuals and cultures45. These haplogroups are typically found in European Neolithic and Bronze Age populations43. Male individuals exhibit Y-chromosome haplogroups G, I and C, which have also been previously reported in Neolithic and Bronze Age populations of Europe13. Both the mtDNA and Y-chr haplogroups of all individuals are fully concordant with the previously reported data.  using qpWave. The results have shown the absence of population structure, therefore all samples have been analyzed together, as no individual showed statistically significant pairwise differences to the rest using a threshold of 0.05 es Table  were pro47. The 22 individuals (labeled ‘Verteba_Trypillia’) in the PCA that showed affinity with Eneolithic samples are mostly defined by the ancestral component dominant in Anatolia-Neolithic individuals, which suggests a strong relationship with European Neolithic populations, similar to previous studies37. However, these samples also show the presence of EHG, CHG, and WHG components as described in Mathiesson et al.13, with the exception of one individual (I3151), who seems to be absent of any EHG/CHG ancestry. Individual VERT-114 (LBA) shows a predominant Anatolia Neolithic component and a great presence of an EHG component. The MBA individual (VERT-113) exhibits a high degree of similarity with Corded Ware and Yamnaya steppe populations  = − 0.000525, Z score = − 1.843, which does not statistically connects the Trypillians with the Ukrainian or Russian Yamnaya populations.We ran ow Table , Fig. S2ow Table , with thf4 = 0.001603, Z score = 12.173, f4 = 0.001730, Z score = 6.380, f4 = 0.002037, Z score = 7.573, f4 = − 0.00047, Z score = − 1.879. Showing that Koros-HG is the WHG source with the highest genetic affinity to Ukraine Trypillians. When compared to Central European Eneolithic populations, the Eneolithic Verteba individuals do not seem to share a statistically significant affinity with the CTCC population of Moldova, as shown in the form of f4:,-0.000304 Z score = − 0.936. qpAdm also indicates that Ukraine_N and WHG are two likely sources of HG-related ancestry to Verteba_Trypillia, in addition to Hungary_LateC_EBA_Baden_Yamnaya  shows a clear tendency towards WHG: 0.001192, Z score = 6.26, suggesting very little presence of ancestry from the local Hunther_Gatherers in the Verteba individuals.We then explored the same individuals, but this time using populations representing different basal ancestries that might have contributed to the CTCC genetic pool  Table . Only onya Table . The staf4 individually  is tested individually the statistics show no differences : -0.00398 Z score = − 7.848. The same test with individual VERT-114 was not statistically significant (Z = 1.382). Relevantly, we observe a major affinity to Russia_Yamnaya over Ukraine_Yamnaya using f4 statistics : − 0.001276, Z score (Z = − 4.202). The distal models of qpAdm using basal ancestries reveal that this individual exhibits up to 33% of Ukraine_N and 66% of CHG, supporting high amounts of steppe-related ancestry. When modeled with close chronology populations the individual requires a single source related to the Corded_Ware , but the results  show that there is no statistical relationship, which indicates no evidence supporting the Srubnaya origin.VERT-113, dated to the MBA, shows a clear signal of steppe-related ancestry, and is the only individual in the dataset that shows a strong influx of this ancestry: cs Table . Furtherre Table . We trief4 − 0.002, Z score = − 8,64), similar to the results obtained for the aggregate group of 22 Verteba individuals. qpAdm results for this individual show that a single model with a Bell_Beaker population as a single source works. Many of the two-way models involve populations related to Ukraine_Globular_Amphora and to Steppe populations, with about 60% of ancestry from the former and the rest from the latter. We also explored the possible connections between this individual and the Cimmerians, who established themselves in present-day Ukraine around the year 1000 BCE, being contemporary to VERT-114. Both f4 f4 = 0.00428 Zscore = 7.171) and f4 f4 = 0.003301, Zscore = 4.043) showed a clear affinity of VERT-114 to the Bell_Beaker individuals over the Cimmerians. This individual can also be modeled as an admixture between Turkey_N (67%) and Ukraine_N (33%)  Table .48, to explore the presence of runs of homozygosity (ROH) in the sample. We observed that the samples tested present very few parts of the genome under ROH . The mtDNA haplogroup diversity suggests that local populations were largely replaced by those associated with the Trypillian culture. The majority of VC individuals exhibit the G2a2 Y haplogroup, which is widely present in Anatolia-related Neolithic European individuals13. The other identified haplogroups, C1 and I2, have been also reported among European Neolithic populations, pointing to an origin of the CTCC individuals without a sex-biased migratory past, which contrasts with the steppe migrations during the Bronze Age55.Previous analyses of CTCC individuals’ mitochondrial DNA HVRI indicated their close maternal ancestry with early Neolithic groups, with lineages that are representative of the Neolithic ‘package’, including haplogroups H, HV, T, V, J, and K37. These observations broadly suggest that Eneolithic CTCC individuals descended from the same, or closely related, population that spread the Neolithic across most of Europe and without little or no sign of admixture with earlier Ukrainian Mesolithic or Neolithic groups composed of hunter-gatherer-related ancestry and specifically pointing towards the Baden individuals from Hungary. In fact, most of the Trypillian individuals can be modeled by Eneolithic populations from Europe that have steppe ancestry, however four out of the 20 individuals could be modeled as Moldovan Trypillians. These results in the qpAdm modeling suggest that there were differences in the ancestry composition of the Trypillians of Verteba Cave, which could be linked to the proportion of HG in the individuals, although this variability is not substantial enough to differentiate the individuals into different populations.Population genetic analyses indicate that the individuals buried at Verteba Cave during the Late Eneolithic  genetically resemble other previously published CTCC individuals, and are closely related to other published CTCC individuals in Moldovaf4-statistics suggest that the source of the HG component would be mainly WHG. In addition, not a single qpAdm model using EHG as a source works, which supports that observation. The significant proportion of WHG ancestry found in the Trypillians (up to 18%) might be related to the hunter gatherer resurgence seen in other Middle Neolithic populations of Central Europe, likely due to admixture with groups in the west who already had a higher WHG component derived from Anatolia-related Neolithic groups prior to the origin of the CTCC56. This would also indicate that the HG Neolithic populations from Ukraine did not contribute much ancestry to the Trypillians. In addition, we also observe the presence of steppe-related ancestry in these individuals, as was revealed in Moldova37, although the proportion in the Verteba individuals is lower, which could correlate with the age of the individuals suggesting a continuous pulse from the East to the West gradually increasing the Yamnaya-related ancestry during the fourth millenium BCE.Previous studies of CTCC individuals could not provide a clear origin for the HG component of CTCC-associated groups. Here, despite observing that models including Ukranian_N individuals and WHG seem to work, the Individual VERT-113, dated to the Middle Bronze Age , has an ancestry profile that is quite different from the earlier CTCC individuals. There is significantly more Caucasus HG/Yamnaya and EHG ancestry, and thus this individual was related to the Yamnaya expansions. qpAdm results suggest a link between VERT-113 and Corded Ware populations from Poland, pointing to a similarity between this individual and these populations. Also, this is the only individual with a higher genetic affinity to the Ukraine_N than to the WHG, suggesting that the population that originated MBA in the second millenium BCE may have had shared affinities with the Ukraine_N populations.f3 values, who is clearly associated with the Yamnaya pastoralists. The genomic composition of VERT-114 suggests a relationship with Beaker-related populations, despite being almost 1000 years younger than the end of the Bell Beaker phenomenon57, and with a date that would be more coincident with the Cimmerians or Scythians58. However, no qpAdm models with these cultures work and the f4 results do seem to confirm the similarity with the Bell Beakers over the Cimmerians. The genetic background of this individual, with its strong western affinities, supports the evidence shown in Narasimhan et al.59 of a western influx into the Steppe during the Late Bronze Age. Further sequencing and analysis of individuals from the cave and the area surrounding VC dating from the third millennium BCE will be critical for exploring cave use after abandonment by the CTCC-related peoples.Interestingly, VERT-114 (Late Bronze Age) does not show many genetic connections with MBA VERT-113 according to the 60. This group was likely descendant from Mesolithic hunter-gatherers. The paleogenomics of the Verteba Cave individuals suggest that local Mesolithic hunter-gatherers did not contribute significantly to later Trypillian ancestry, indicating that the process to Neolithisation in western Ukraine was the product of substantial migration rather than indigenous adoption of agricultural practices.The results of our paleogenomic analysis have important implications for understanding the Neolithisation process in far eastern Europe. As the populations of the CTCC expanded from Romania and Moldova into the forest-steppe areas of western and central Ukraine, they would have come into contact with populations associated with the indigenous Bug-Dniester culture, a group whose subsistence system focused primarily on foraging60. Documenting the lack of admixture on this cultural frontier is key to understanding the context from which the Yamnaya migration occurred8.Our results also provide support to the idea that a long-lasting frontier existed between the sedentary agriculturalists of the forest-steppe ecozone and the neighboring nomadic pastoralists from the Pontic Steppe. This frontier is characterized by drastic contrasts in material culture and subsistence regimes, and was likely maintained in prehistory due to these factors as well as by major linguistic differencesIn conclusion, the results show that Verteba Cave represents a significant mortuary site that connects East and West. The genetic structure of the CTCC peoples includes ancestry related to both earlier hunter-gatherers from the west and farmers from the Near East, and one that is genetically distinct from those of Moldovan CTCC peoples. The lack of local ancestry associated with Ukrainian Neolithic hunter-gatherers suggests that these farmers mostly replaced local foragers and did not mix with the neighbouring steppe populations. Additionally, during the Bronze Age, Verteba Cave was used by successive waves of nomadic pastoralists from the east that eventually brought significant genetic and cultural changes to Europe that eventually mixed with the local descendants of Trypillia-culture population. Additional genomic sampling from these later time periods will help to answer questions of site chronology and possibly indicate how the Trypliian culture eventually collapsed.To perform the present study, 23 samples were collected from Verteba cave (Ukraine). Due to low coverage, two samples were not included in the final analyses. The complete description of the methods can be found in the Supplementary Information section.14C dating; here we report eight new dates run at the Pennsylvania State University Accelerator Mass Spectrometry Laboratory (lab code: PSUAMS) and the Oxford Radiocarbon Accelerator Unit (lab code: OxA)  and centrifuged 3 times for 20 min, diluted with Nanopure H2O, and centrifuged 3 more times for 20 min to desalt the solution. Carbon and nitrogen concentrations and stable isotope ratios were measured at the Yale Analytical and Stable Isotope Center with a Costech elemental analyzer (ECS 4010) and Thermo DeltaPlus analyzer. Sample quality was evaluated by examining the % crude gelatin yield, %C, %N and C:N ratios before AMS 14C dating. C:N ratios for the dated samples fell between 3.15 and 3.42, indicating acceptable collagen preservation64. Collagen samples were combusted for three hours at 900 °C in vacuum-sealed quartz tubes with CuO and Ag wires. Sample CO2 was reduced to graphite at 550 °C using H2 and a Fe catalyst, with reaction water drawn off with Mg(ClO4)265. Graphite samples were pressed into targets in Al cathodes and loaded on the target wheel for AMS analysis. The 14C ages were corrected for mass-dependent fractionation with measured δ13C values66 and compared with samples of Pleistocene whale bone , late Holocene bison bone (~ 1850 14C BP), late AD 1800s cow bone and OX-2 oxalic acid standards for calibration. Sample preparation protocols at OxA follow similar standards and have been published in depth elsewhere .Bone collagen extraction for 67 using OxCal 4.468. Six of the eight dates display a tight distribution ranging from 3790 to 3535 cal BCE (2σ), with mean results spread across a single ~ 80-year period from 3720–3640 cal BCE. These results are comparable with dates from other sites in Romania, Moldova and Ukraine dating to the latter part of period Trypillia CI, and are consistent with the late Trypillia CI  occupation identified at the site . A single date corresponds with the Middle Bronze Age , dating to the range of 1960–1770 cal BCE (2σ).Dates were calibrated according to the IntCal20 Northern Hemisphere calibration curveAll laboratory work was performed in dedicated ancient DNA laboratories at University College, Dublin. These facilities are physically located from other molecular biology laboratories, and measures are taken to minimize contamination of ancient individuals, including head-to-toe suits, face masks, hair nets, multiple layers of gloves, bleaching of all surfaces and UV decontamination of all (non-sensitive) reagents. All laboratory tools used to process samples were decontaminated using bleach (1:5 concentration) and UV irradiated in a cross-linker. The final step of library preparation (amplification) was performed outside the ancient DNA laboratory. We included extraction negative controls (no powder), library and PCR negative controls (extract was supplemented by water) in every batch of samples processed and carried them through the entire wet laboratory processing to test for reagent contamination.70 using a sandblaster (Renfert). Fragments of the cochlea were then powdered using a mixer mill (Retsch Mixer Mill 400). Twenty-three petrous bone samples were initially screened. Using ~ 75 mg of powder, DNA was extracted using an optimized DNA extraction protocol71. Illumina sequencing libraries were constructed using 12.5-25uL of extract, amplified using Accuprime Pfx Supermix (Thermo Fisher Scientific), following Gamba et al.72; a protocol adopted from73. Quality assessment of the amplified library was performed on an Agilent 2100 Bioanalyzer and a Qubit 2.0 Fluorometer. All amplified libraries were initially screened using an Illumina MiSeq. After screening, additional libraries were sequenced to ~ 1X on the NextSeq platform.Samples were initially UV irradiated on both sides for ~ 10 min. We targeted the inner ear region of the petrous bone74 and aligned to the human reference genome (GRCh37), with the mitochondrial genome replaced by the revised Cambridge reference sequence (rCRS) using BWA75 (Version 0.7.5). Duplicate mapped reads were removed using Picard Tools76. Reads with mapping qualities below 30 were also removed. Unique and filtered reads were analyzed with qualimap-277 to assess the coverage of the genomes. MapDamage-278 was used to estimate the level of deamination and the authenticity of the data. We have clipped two bases per read end to minimize the effect of damage.Sequencing reads were trimmed using cutadapt (Version. 1.2.1)79 filtering the calls with mapping and base quality below 30. As a reference panel we used the positions of the 1240 k capture dataset8. The Verteba calls were merged with a panel of 750 modern individuals from 46 populations3 and 611 individuals from 67 ancient populations89. Molecular sex was determined using ry_compute.py90, we also explored the presence of familiar relationships with READ91.Pseudo-haplotypes were called using sequenceTools92 to generate a consensus sequence of the mitochondrial genomes using –uselength option. We determined the mitochondrial haplogroups of the mitochondrial consensus sequences with Haplogrep v2.093. Y chromosome haplogroups of male individuals were determined using Yleaf94.Mitochondria aligned reads were processed with Schmutzi46. Resulting data was plotted using R95. Ancient samples were projected in the PCA built with the modern ones using the option lsqproject. Two rounds of outlier removal were used. Results were plotted with R.Principal component analysis was built with 597,573 SNPs and 750 modern genomes using smartpca from Eigensoft package47. 611 ancient individuals, 2068 modern individuals together with the 20 Verteba individuals were used for the analysis. From the 597,573 SNPs of the Human Origins dataset was filtered removing SNPs with MAF below 0.05 and more than 5% of missing sites. Filtered SNPs were pruned by linkage-disequilibrium (LD) using PLINK 1.996 flag –indep-pairwise with a windows size of 200 SNPs, advanced by 50 SNPs and establishing an r2 threshold of 0.4. The ADMIXTURE analysis was performed with 417,913 SNP s, with K ranging from 2 to 15 and 10 bootstrap replications. Admixture was plotted with R.An unsupervised ADMIXTURE analysis was performed with ADMIXTUREF-statistics were run using admixtools46 in the form f3 using all the ancient European populations available. D statistics were also run using the same package. We have used the form f4 using a list of possible sources of Hunter-Gatherer, Neolithic and steppe components. In this analysis, we excluded results with less than 100,000 shared SNPs.46 In this analysis we have used the same proxies as the ones used for D statistic plus Verteba in case of modeling VERT-113 and VERT-114 individuals and setting allSNPs: NO. The list of samples included in each category is displayed in table 97. We also performed qpWave analysis to assess the presence of substructure in the Verteba_Trypillia population using the same software and right population set listed below, the threshold was set to a p-value of 0,05.We performed qpAdm using the admixtools package48. The phenotypic positions analyzed were genotyped using the pseudo haploid calls. The frequencies of the present day populations were obtained from the 100 genomes data98.We calculated the ROH segment distribution following the protocol described in Ringbauer et al.Supplementary Information 1.Supplementary Information 2.


Ancestry informative markers are regarded as useful tools for inferring the ancestral information of an individual, which have been widely used in the criminal investigations and population genetic studies. Previously, a multiplex amplification panel containing 39 AIM-InDel loci was constructed. This study aims to investigate the genetic polymorphisms of these 39 AIM-InDel loci in Yunnan Hani and Miao ethnic groups, and to uncover their genetic affinities with reference populations based on the AIM-InDel markers.Nei’s genetic distances, pairwise fixation indexes, principal component analyses, phylogenetic analyses, and STRUCTURE analyses.In this research, 39 AIM-InDel profiles of 203 unrelated Miao individuals and 203 unrelated Hani individuals in Yunnan province of China were acquired. Additionally, we evaluated the genetic polymorphisms of 39 InDel loci in Yunnan Miao and Hani groups. Moreover, the genetic relationships among Yunnan Miao, Hani and reference populations were also clarified based on Genetic diversity analyses demonstrated that these InDel loci showed varying degrees of genetic polymorphisms, and could be utilized in forensic identifications in Yunnan Miao and Hani groups. The results of principal component analyses, phylogenetic analyses and Structure analyses revealed that Yunnan Miao and Hani groups had closer genetic relationships with East Asian populations, especially with the populations from Southern China. This research enriched the genetic data of Chinese ethnic minority, and provided ancestral information of Yunnan Miao and Hani groups from the perspective of population genetics.The online version contains supplementary material available at 10.1186/s41065-022-00238-9. Ancestry inference of unknown DNA donors acquired from crime scene is important to narrow the scope of criminal investigation and uncover the genetic affinities among populations. Single nucleotide polymorphisms (SNPs), with the merits of low mutation rates, widespread distributions in human genome, small amplified fragments, various detection methods as well as relevance to human phenotypes and so on, have been the most common ancestry informative markers (AIMs) in the forensic genetics –3. InserYunnan province, bounded by Qinghai-Tibet Plateau in the northwest and the Yunnan-Guizhou Plateau in the east, is a mountainous province in the southwest part of China. The Hani nationality is one of the unique ethnic minorities in Yunnan province. According to the statistical data from the 6th census of China in 2010, there are more than 1.6 million Hani individuals living in Yunnan province . BesidesWith a population of greater than 9 million in China, Miao ethnic minority (or Hmong) is an ethnic group with long history residing in southwest part of China like Guizhou, Guangxi and Yunnan provinces. There are more than 1.2 million Miao individuals in Yunnan province, accounting for 12.76% of the total Miao individuals . BesidesMost of the population genetic studies on the Chinese Miao and Hani ethnic groups were limited to individual identification panels based on autosomal STRs, InDel markers, or Y-chromosomal and X-chromosomal STRs –20. HoweThe study protocol has been reviewed, permitted, and supervised by the ethics committee of Xi’an Jiaotong University Health Science Center . This research was conducted in accordance with the ethical principles for medical research involving human subjects recommended by the World Medical Association Declaration of Helsinki. A total of 406 bloodstain samples  were collected from Yunnan province, China. All volunteers were unrelated healthy Hani or Miao individuals and declared that their families lived in Yunnan for at least three generations. Every volunteer finished a questionnaire about personal information and health status, and then signed a written informed consent before sample collection. Peripheral venous blood was dried on FTA card and then stored at room temperature.2 bloodstain was directly amplified by the multiplex PCR system of 39 AIM-InDel panel on GeneAmp PCR system 9700 . The components of PCR reagents and thermal cycle parameters were depicted in previous articles [The 1.2 mmarticles , 23. CapThe whole experimentation was implemented in an accredited laboratory (Multi-Omics Innovative Research Center of Forensic Identification) by China National Accreditation Service for Conformity Assessment (CNAS). This AIM-InDel panel has already passed the developmental and internal validations .In the evaluations of genetic affinities between the studied groups and reference populations, the 38 out of 39 AIM-InDel loci were included because population data of rs3034941 were not available in 1000 Genome Project. Population data of the same 38 AIM-InDel loci in 30 reference populations selected from public database and published researches were included in the present study as reference database. Among these reference populations, 26 of which were acquired from 1000 Genome Project while population data of Chinese Qinghai Tibetan (CTQ), Chinese Tibet Tibetan (CTT), Chinese Kirgiz (CKX) and Chinese Uyghur (CUX) were acquired from previously published articles , 23, 25.DA) between Yunnan Hani (or Yunnan Miao) and other reference populations were calculated by DISPAN program [FST) and corresponding p-values between Yunnan Hani (or Yunnan Miao) and other reference populations were calculated by Arlequin v3.5 software [R software. Phylogenetic analyses were conducted by different algorithms to evaluate the phylogenetic relationships among Hani, Miao and reference populations. A neighbor-joining (NJ) tree was conducted based on insertion allelic frequencies of AIM-InDel loci by Phylip 3.69 package [R software. Ancestry component analyses were conducted by STRUCTURE v2.3.4 software with predefined K values from 2 to 6 [http://clumpak.tau.ac.il/) online tools were used to further analyze and visualize the results of STRUCTURE.The Fisher’s exact tests of Hardy-Weinberg equilibrium (HWE) for all loci were performed by the Arlequin software . Forensi program . Pairwissoftware , and the package , and the package . We perf package . Principm 2 to 6 . Admixtum 2 to 6  and CLUMP-values of the Fisher’s exact tests of HWE for all loci in Yunnan Hani and Miao groups were listed in Supplementary Tables r2 values for pairwise loci in the LD analyses were shown in Supplementary Tables r2 = 0.5312; Yunnan Hani: r2 = 0.4948).In the present study, rs5896844 locus was excluded in the analyses of HWE and LD since only deletion allele was found at this locus in Yunnan Hani and Miao groups. Allelic frequencies of 39 AIM-InDel loci as well as their forensic statistical parameters were calculated in Yunnan Hani and Miao groups, respectively, and the results were shown in Fig. For Yunnan Miao group, bar plots of insertion allelic frequencies and violin plots of forensic statistical parameters of 39 AIM-InDel loci were shown in Fig. DA values and pairwise FST values were calculated to measure the genetic differentiations between the studied groups and 30 reference populations. The DA distances between the Hani, Miao and reference populations were shown in Fig. DA value was found between Hani and Southern Han Chinese , followed by Kinh in Ho Chi Minh City Vietnam  and Chinese Dai in Xishuangbanna , as shown in Fig. DA = 0.0068) and KHV (0.0076), as shown in Fig. FST values between the studied groups and reference populations were displayed in Supplementary Table FST value was found between Hani and CHS , followed by CDX  and KHV , whereas the largest FST values were found between Hani and African populations. For Miao group, the smallest FST value was observed between Miao and CHS , followed by CHB  and KHV  groups.The A heatmap was conducted to evaluate the insertion allelic frequency distributions of 38 AIM-InDel loci in Yunnan Miao, Hani and reference populations, and the plot was shown in Fig. For the cluster analyses of InDel loci, four main clusters could be identified: (1) loci rs3033760, rs10538061, rs146391383, rs2307840, rs2307783, and rs3840222 displayed large insertion allele frequencies in East Asian populations and large δ values between African and East Asian populations; (2) rs3831885, rs3842715, and rs3045215 displayed high insertion allelic frequencies in African and European populations. The δ values of these three loci were greater than 0.5 between African and East Asian populations, and greater than 0.4 between European and East Asian populations; (3) loci rs36038238, rs4647655, rs5788637 and rs3835409 displayed relative high frequencies in East Asian populations but low frequencies in African and European populations. The δ values of these four loci were greater than 0.5 between East Asian and African populations, and were greater than 0.39 between East Asian and European populations; (4) loci rs3029066, rs10569275, rs3216799, rs10533439 and rs5891435 displayed relative high insertion allelic frequencies in African populations but relative low frequencies in non-African populations. Large δ values of most InDel loci were observed among African and non-African populations. The largest δ value of rs5891435 locus was found between African and European populations.Cluster analyses for both InDel loci and populations were conducted, and the results were shown in Fig. Phylogenetic analyses of 32 groups based on the same AIM-InDel loci were conducted using NJ and ML methods. Overall speaking, all 32 groups could be divided into four main clusters according to their intercontinental locations  in NJ tree Fig. . The YunTo further evaluate the phylogenetic relationships from different population scales, we performed genetic distance-based ML trees among Yunnan Hani, Miao and reference populations. We constructed the ML trees with ESN as the root population firstly, and 0–10 mixture events were gradually added to construct the migration events. As shown in Fig. Genetic affinities of Yunnan Hani, Miao and reference populations based on the allelic frequencies of 38 AIM-InDel loci were also conducted by performing PCA at different population scales. PCA plots among 32 worldwide populations based on PC1 and PC2, PC1 and PC3 were conducted, and the plots were shown in Fig. To further analyses the genetic relationships on a fine scale among Yunnan Hani and Miao groups, the PCA plots among 23 population from African, European and East Asian populations were conducted, and the plots were shown in Fig. In Fig. K = 3, populations from Africa, Europe, East Asia and Eurasia were apparently distinguished from each other, and identified by purple, cyan, orange and a combination color of cyan and orange, respectively. East Asian-specific ancestral component (orange) was maximized in the Yunnan Hani and Miao groups  error results calculated by ADMIXTURE suggested that the three-source model with the smallest CV value (0.64215) could be used to explain the genetic variations of continental populations. At Nei’s genetic distances, pairwise fixation indexes, principal component analyses, phylogenetic analyses, and STRUCTURE analyses.The development of economy and society promotes the continuous communications among people from different regions. Frequent gene exchanges among Yunnan Miao, Hani and neighboring populations make their genetic relationships become closer, and also make their gene pools carry the genetic traits of other ethnic groups to some extent. Exploring the genetic feature and genetic structure of Yunnan Miao and Hani groups are of great significance for understanding the population genetic background of the Chinese nation. In the present study, we evaluated the genetic polymorphisms of 39 InDel loci in Yunnan Miao and Hani groups. Moreover, this research aimed to clarify the genetic relationships among Yunnan Miao, Hani and reference populations based on Before we calculated the forensic statistical parameters of 39 AIM-InDel loci in Yunnan Hani and Miao groups, Fisher’s exact tests of HWE for all the loci in Yunnan Hani and Miao groups were performed, and the results demonstrated that all loci (except for rs5896844) reached Hardy-Weinberg equilibrium both in Yunnan Hani and Miao groups. According to the genotype data of rs5896844 in 1000 Genome Project Phase III (GRCh38.p13) and dbSNP (build 155), the locus rs5896844 was a diallelic InDel marker. The deletion allele frequencies of rs5896844 in African, European and East Asian populations were 0.4800, 0.7890 and 0.9960, respectively. The genetic polymorphisms were decreasing from Africa to East Asia accordingly. This might be due to bottlenecks in the history of the non-African populations . In the LD analyses were used to evaluate the relevance between pairwise loci. In this study, rs5896844 locus was excluded to conduct pairwise LD analyses because only deletion allele was observed in the Yunnan Miao and Hani groups. The results of LD analyses showed that the rs3033760 and rs36038238 were observed the strong LD, which might result from the close position between rs3033760  and rs36038238  (about 0.019546 cM).The CPD and CPE values of 37 AIM-InDel loci demonstrated that these InDel loci showed high discriminability for individual identifications in Yunnan Hani and Miao groups, though linkage disequilibrium between rs3033760 and rs36038238 was observed. Population genetic researches for Chinese Miao or Hani groups were also evaluated based on different InDel panels. Jiang et.al found that the CPD and CPE values of 21 InDel loci in Miao group were 0.999998008541708 and 0.85884504, respectively [DA, FST values and phylogenetic analyses. Estimations for ancestral components of Yunnan Hani and Miao groups using admixture model demonstrated that the ancestry components of Yunnan Miao and Hani groups were dominated by East Asian ancestry components.The ancestry components of Yunnan Hani and Miao groups, as well as the genetic relationships among Yunnan Hani, Miao and reference populations were also investigated. Phylogenetic analyses showed that Yunnan Miao and Hani groups had close relationships with East Asian populations, especially with groups from Southern China (CHS and CDX). A set of PCA plots at different population scales were conducted to analyze the genetic relationships between the studied groups and reference populations, confirming that this AIM-InDel panel could be an effective tool for distinguishing East Asian, European and African populations. At individual level, it was demonstrated that Yunnan Miao and Hani individuals had closer ties with East Asian populations, especially with the groups living in Southern China, compared with other intercontinental populations. These PCA results were also in accordance with the results of pairwise http://www.chinadaily.com.cn/culture/art/2014-06/17/content_17591898_6.htm). During the long history, part of the Miao ancestors gradually migrated to the Southern and Western regions of China, and entered the mountainous areas of Southwest China and Yunnan-Guizhou Plateau. During Qin and Han Dynasties (from about 221 B.C. to 220 A.D.), Miao people mainly settled in Guizhou, Hunan and Hubei provinces (Southern China). After that, there were close and frequent genetic and cultural exchanges among Miao, Yao, Han and other groups in Southwest regions of China [According to the Miao’s myths and legends handing down from generation to generation, the ancestor of Miao group is Chi You. Around 5000 years before present, the ancestors of the Miao people migrated to the middle reach of the Yangtze River because of the wars and conflicts . Supplementary Table 3. r2 values, x2 and their p-values for pairwise loci in the linkage disequilibrium analyses (Yunnan Miao group). Supplementary Table 4. Forensic parameters of 39 AIM-InDel loci as well as their p values for Hardy-Weinberg equilibrium tests in Yunnan Miao ethnic group of China (n = 203). Supplementary Table 5. Forensic parameters of 39 AIM-InDel loci as well as their p values for Hardy-Weinberg equilibrium tests in Yunnan Hani ethnic group of China (n = 203). Supplementary Table 6. The FST values between the studied groups and reference populations. Supplementary Table 7. Allele frequency differential (δ) of 38 AIM-InDel loci in pairwise intercontinental populations.


Shorealeprosula from Peninsular Malaysia. A total of 1410 individual trees were sampled from 44 natural populations throughout Peninsular Malaysia. Four cpDNA regions were used to generate a cpDNA haplotype database, resulting in a haplotype map comprising 22 unique haplotypes derived from 28 informative intraspecific variable sites. This cpDNA database can be used to trace the origin of an unknown log at the regional level. Ten SSR loci were used to develop the SSR allele frequency database. Bayesian cluster analysis divided the 44 populations into two genetic clusters corresponding to Region A and Region B. Based on conservativeness evaluation of the SSR databases for individual identification, the coancestry coefficients (θ) were adjusted to 0.1900 and 0.1500 for Region A and B, respectively. These databases are useful tools to complement existing timber tracking systems in ensuring only legally sourced timbers are allowed to enter the wood supply chain.International timber trade communities are increasingly demanding that timber in the wood supply chain be sourced from sustainably harvested forests and certified plantations. This is to combat illegal logging activities to prevent further depletion of our precious forests worldwide. Hence, timber tracking tools are important to support law enforcement officials in ensuring only sustainably harvested timbers are traded in the market. In this study, we developed chloroplast DNA (cpDNA) and simple sequence repeat (SSR) databases as tracking tools for an important tropical timber tree species,  Shorealeprosula Miq.  is a tropical tree species belonging to the Dipterocarpaceae family native to Southeast Asia, where it is widely distributed throughout the tropical rainforests of Peninsular Malaysia, Sumatra, and Borneo1. It is commonly found in lowland and hill dipterocarp forests below 700 m elevation1. It is classified as a near-threatened species under the International Union for Conservation of Nature (IUCN) Red List2. The harvested wood is internationally traded under the Light Red Meranti timber group as a general utility timber for the production of furniture, panelling, flooring, and plywood3. Due to easy accessibility of the species from lowland forests, it is prone to be targeted for illegal logging. Illegal logging is a lucrative business, which is associated with a total global market value between USD30-157 billion annually4. To address the issue of illegal logging, consumer countries have developed measures to ban the import of illegally-logged timber by implementing legality verification systems; such as through the United States Lacey Act (2008), the European Union Timber Regulation (2010), Australia Illegal Logging Prohibition Act (2012), the Japanese Clean Wood Act (2017); and most recently, the United Kingdom Timber Regulation (2021). In addition, the United Nations Office on Drugs and Crime (UNODC) has also produced a guide on best practices for forensic timber identification, aiming to overcome the challenges posed by illegal logging and environmental degradation 5. Such a complex set of urgent issues need to be addressed as reports have shown that an area of forest approximately equivalent to the size of Austria  disappears worldwide every year as the result of illegal logging6.7. In comparison, methods based on inherent wood characteristics such as visual identification (wood anatomy), genetics , and chemical methods  can provide more reliable forensic timber identification8. Each tool has its own strength and in combination they complement one another allowing authorities to overcome limitations of more traditional methods in species identification, geographic origin verification or linking illegal logs to the stumps of origin.To prevent illegal timber from entering the wood supply chain, enforcement authorities use timber tracking methods to verify the legality of the harvested wood. The most commonly used methods include paper based documentation, painted identification marks and radio frequency identification (RFID) tagsNeobalanocarpusheimii10, Gonystylusbancanus11, Acermacrophyllum12, Cedrelaodorata13 and Chamaecyparistaiwanensis14. To develop timber tracking tools suitable for these species, researchers applied the principles of population genetics such as mutation, genetic drift, migration, adaptation, and speciation8. These methodologies utilise genetic material (genetic markers) common across groups of individuals to define populations for provenance testing or to define species for species identification8. During forensic timber identification, enforcement officers need to identify unknown samples at genus or species level correctly from the start, before further investigating geographic origin or individual identification. This process is commonly supported by wood anatomists through the examination of the internal structure of the specimen in comparison to reference materials15. In addition, such identifications can also be achieved using DNA barcoding technology based on nucleotide variation at specific gene regions16. One example of this is the CITES listed species with the genus Gonystylus which can be distinguished from other closely related species using a combination of genetic markers including internal transcribed spacer (ITS2), trnH-psbA intergenic spacer and trnL11. Once the particular species is identified, we can track the geographic region of origin using a population identification database developed from cpDNA17 or single nucleotide polymorphisms (SNP) markers13. If the suspected log can be traced back to a particular geographic region, we can use an individual identification database to link the log to the original stump12. Subsequently, the confidence level of the match probability can be tested by calculation of random match probability between the log and stump.Genetic approaches have been used to determine the origin of wood samples from many important species, including N.heimii10, G.bancanus11, S.platyclados18, Intsiapalembanica19 and Aquilariamalaccensis20. As an extension, this study aimed to develop tracking tools for S.leprosula in the context of forensic identification. Specifically, we utilised cpDNA markers to develop a haplotype database and SSR markers to establish an allele frequency database for this important tropical timber species. We can use the cpDNA haplotype database to infer the geographic origin of an unknown sample to the regional level. Subsequently, by using the SSR allele frequency database, we can calculate the random match probability to support the strength of evidence in cases where the suspect log matches the tree stump. This gives a new impetus for higher acceptance of evidence by the judge, which will improve the success rate of prosecutions of illegal logging perpetrators.The Forest Research Institute Malaysia (FRIM) has developed comprehensive DNA profiling databases for several important tropical timber species for timber tracking, namely atpB-rbcL); 487 bp (petG-trnP); 500 bp (trnL1-trnL2); and 593 bp (psbM-trnD). Alignment of the 352 individuals from the 44 populations yielded a total 28 variable sites: 11 in the atpB-rbcL spacer, seven in both the petG-trnP and psbM-trnD spacers, and three in the trnL1-trnL2 spacer (Supplementary Table DNA sequencing of the choloroplast (cp) markers produced sequences of the following lengths: 573 bp  and expected (He) heterozygosity ranged from 0.3570 to 0.8346 and 0.4375 to 0.8795, respectively for populations in the Region A database; and ranged from 0.3298 to 0.8356 and 0.3469 to 0.8793, respectively for populations in the Region B database. The power of discrimination (PD) for the SSR loci ranged from 0.601 to 0.972 and 0.554 to 0.975, in Region A and B databases, respectively. The most discriminating locus was Sle605 in both the Region A (PD = 0.972) and Region B (PD = 0.975) databases. Minimum allele frequency was adjusted for alleles falling below the thresholds of 0.0066 (Region A) and 0.0024 (Region B).SSR allele frequency databases were established according to Region A and B, and characterized to evaluate the relative usefulness of each SSR marker in forensic investigation. The distribution of allele frequencies for each locus is listed in Table SleT11, SleT15, SleT17 and Sle465) and six SSR loci in Region B . We evaluated these loci in each population independently to rule out the possible presence of null alleles. There were four populations in Region A  where a single one locus deviated from HWE; whereas there were eight populations in Region B  with a single locus and a single population (GLedang) with two loci that deviated from HWE  to 81.3% (CTongkat) between population Table . At the θ) for Peninsular Malaysia (0.0579) was higher than those of Region A (0.0454) and Region B (0.0500) (Table f), the value for the Region A database (f = 0.0892) was highest, followed by Peninsular Malaysia (f = 0.0822) and Region B (f = 0.0666). All the θ and f values were significantly greater than zero, demonstrated by the 95% confidence intervals not overlapping with zero. Both of the θ and f values were used to calculate the conservativeness of each database by testing the cognate database (Porigin) against the regional database (Pcombined). The databases were non-conservative at the calculated θ value. In order for both the Region databases (A and B) to be conservative, the value of θ was adjusted from 0.0454 to 0.1900 for Region A and from 0.0500 to 0.1500 for Region B. For the Region A database, the most common SSR profile frequency is 2.69 × 10–7 or 1 in 3.72 million and the rarest profile frequency is 1.84 × 10–14 or 1 in 54.3 trillion. For the Region B database, the most common SSR profile frequency is 1.06 × 10–7 or 1 in 9.43 million and the rarest profile frequency is 4.03 × 10–16 or 1 in 2.48 quadrillion.The coancestry coefficient (0) Table . A totalAt the moment, the database is not accessible to the public. However, the public can contribute by reporting suspicious illegal logging activities to the relevant enforcement unit, so that actions can be taken and suspicious samples collected for forensic timber identification. In addressing forensic timber identification questions, we use a cpDNA haplotype database to investigate the geographic origin of a suspect log at a regional level. Subsequently, we use an SSR allele frequency database to narrow down the geographic origin to population level. After the population is identified, the state forest department’s enforcement officials can verify in their system if the area was permitted for logging activities. If that area is a forest reserve where no logging permit is being issued, efforts to locate potential stumps belonging to the sampled log can be initiated. Once potential stumps are found, we can try to link the log to the potential stumps by comparing their SSR DNA profiles. A random match probability between the log and the potential stumps can be established by using the SSR allele frequency database.24. The remaining rare haplotypes, H6-H22, present in one or two individuals are endemic to certain populations, as shown in Fig. From the cpDNA haplotype database, haplotypes H1 and H2 were most prevalent in Peninsular Malaysia, with a frequency of 47.2% and 42.6%, respectively. The distribution of cpDNA haplotypes is overlaid by the division of populations in Region A and B as suggested by the STRUCTURE analysis. For Region A, haplotype H2 was found in all the populations, either in all the samples (BPerangin and BEnggang) or part of the samples. The less common haplotypes, H3 (1.7%) and H4 (1.1%) were also found in Region A. Overall, we observed haplotype H2 dominates the populations in this region. Whereas for Region B, 78% of populations carried haplotype H1 in all the samples , with the exception of some populations which exhibited part of their samples carried haplotype H1 . In addition, the less common haplotype H5 (1.1%) is found solely in this region. As a whole, haplotype H1 dominates the populations in Region B. Those haplotype H2 found in the populations of Region B might be due to the retention of ancestral polymorphism by the maternally inherited cpDNA markerS.leprosula individuals from Peninsular Malaysia can be traced back to their geographical origin in either Region A or B. In forensic investigation, if the generated haplotype of an unknown log belongs to haplotype H3 or H4, we can postulate that it might have originated from Region A. Similarly, if haplotype H1 or H5 were detected, then Region B would be the most likely source of origin. However, based only on the cpDNA haplotype database, it is impossible to track an unknown log back to a specific population or forest reserve because forest reserve boundaries were defined according to political governance and thus may not necessarily reflect the distribution of natural populations of the species. It should be noted that some rare haplotypes might not be represented in the database, as it is impossible to collect all S.leprosula trees from every forest reserve in Peninsular Malaysia. We can include more sampling sites in the future to improve the comprehensiveness of the cpDNA haplotype database. Particularly, the inclusion of populations from other distributions such as Sumatra and Borneo could provide some insights on the evolutionary history and gene flow of the species due to isolation and separation by South China Sea between Peninsular Malaysia and Borneo as well as by Straits of Malacca between Peninsular Malaysia and Sumatra.Based on the cpDNA haplotypes, θ = 0.058) observed in this species. The value of θ shows that only 5.8% of genetic variability was found distributed among populations, thus suggesting high genetic similarity. This θ value (0.058) was higher than I.palembanica (0.026)19 and S.platyclados (0.033)18 but lower than G.bancanus (0.067)11, A.malaccensis (0.097)20 and N.heimii (0.127)10. Previous study suggested that populations of S.leprosula sampled from Peninsular Malaysia were a continuous, connected forest in the past, particularly in the low inland forests25. Continuous distribution would promote gene flow among populations through the sharing of a common gene pool, as shown by the common haplotypes H1 and H2 observed in the cpDNA population database. The current mean assignment rate at the population level is 45.90%, which is lower than those seen in other tropical species such as G.bancanus (54.80%)11, I.palembanica (62.20%)19, S.platyclados (77.78%)18 and A.malaccensis (92.09%)20. At the regional level, the mean assignment rate to region is 88.70%, which is higher than seen in I.palembanica (80.21%)19 but lower than A.malaccensis (94.96%)20, S.platyclados (99.11%)18 and G.bancanus (100%)11.Once the geographical origin at regional level is ascertained, an assignment test based on the SSR allele frequency database can be used to trace the samples origin to population level. In this study, we observed low assignment rates to origin populations, which may be due to the weak genetic structure , representing the estimated frequency at which a particular SSR profile would be expected to occur in a population21. This will help to determine the probability of a match between an unknown log and its potential origin stump. The possible profile frequency based on the 10 SSR loci ranges between the profile frequency of the most common genotype which would be the least powerful in terms of differentiating between two unrelated individuals 28, and the rarest theoretical profile. Based on the Region A database, the possible SSR profile frequencies range from 2.69 × 10–7 to 1.84 × 10–14, and for the Region B database, from 1.06 × 10–7 to 4.03 × 10–16. With such low profile frequencies, we can rule out the possibility of a random match between the DNA profiles of any log and stump21.The identification of illegal logging sites can be achieved under two circumstances. Firstly, by utilising assignment tests based on the SSR allele frequency database to locate the original population for the suspected illegal log. Secondly, if the Forest Department has received report on illegal logging activities in a specified area. As such, with help from experienced foresters and local indigenous people who are familiar with their local forest area, it is possible to find and sample the potential stumps which potentially match the suspect log within the forest. Once potential stumps are found, a tissue sample can be collected for DNA testing following FRIM’s standard operating protocol on DNA forensics for plant species identification and wood trackingS.leprosula, our future study is to develop a suitable DNA extraction method for dry wood and processed sample. The extracted DNA is then tested by PCR amplification on both cpDNA and SSR markers utilized in the DNA databases.In this study, we obtained cpDNA fragment and SSR loci using high quality samples such as inner bark or leaf tissue preserved in liquid nitrogen. However, many seized woods or logs are usually have been dried or processed in practice. Thus, this may pose a challenge to extract sufficient and good quality DNA from dry wood for subsequent DNA analysis. To close the DNA extraction gap in S.leprosula in Peninsular Malaysia. The cpDNA haplotype database enables the tracing of unknown log at the regional level. The SSR allele frequency database was validated for specificity and accuracy for the calculation of random match probability of an unknown log to a potential origin stump. This database along with the existing reference databases in other important forest timber species will serve as an impetus and increase the use of DNA technology in illegal logging investigations and verification of legality in wood supply chains.We report on the development of cpDNA haplotype and SSR allele frequency databases for an important timber species, S.leprosula wild samples representing 44 populations from the natural forests distributed throughout Peninsular Malaysia . For cpDNA analysis, eight purified DNA samples per population were used (8 × 44 populations = 352 samples), while all the purified DNA samples  were used for SSR analysis.In this study, 1,410 atpB-rbcL, petG-trnP, trnL1-trnL2 and psbM-trnD , 0.2 μM each primer and 10 ng of template DNA on a 2720 Thermal Cycler . The thermal cycling conditions consist of a first activation step at 95 °C for 5 min, followed by 35 cycles of denaturation at 95 °C for 30 s, annealing at 50 °C for 90 s, and extension at 72 °C for 1 min; with a final extension step at 60 °C for 30 min. An ABI 3130xl capillary sequencer (Applied Biosystems) was used to sequence both forward and reverse directions of each PCR product. The sequence data was edited and analysed using Sequencher v.5.1 . We identified chloroplast haplotypes by taking into account insertion/deletion, and substitution among sequences. A total of 32 sequences were deposited in GenBank with accession numbers ranging from MZ419000 to MZ419031.The target cpDNA regions were amplified using four intergenic spacer primers namely SleT01, SleT09, SleT11, SleT15, SleT17, SleT29, SleT31 , Sle267, Sle465 and Sle60530 to genotype the 1410 individuals. Information on primer sequence, repeat motifs, allele size range, fluorescent label and GenBank accession number for the ten SSR markers are listed in supplementary Table 31.We used ten SSR loci, namely 32. We applied models of admixture with sampling locations included as prior population information. Correlated allele frequencies were applied with K values ranging from 1 to 10 for 10 repetitions. The optimal number of genetic clusters was estimated based on the Delta K method33 of STRUCTURE SELECTOR34. For the optimal K, data from the 10 independent runs of STRUCTURE analyses were graphically represented using CLUMPAK35. To support the analysis of the population structure, a UPGMA dendrogram was constructed based on Nei’s DA using POPTREE236. 1000 bootstrap replicates were applied to determine the relative strength of the nodes.For cluster analysis, we used STRUCTURE v2.3.4 to run our dataset using a burn-in length of 100,000 and 200,000 steps for the Markov Chain Monte Carlo (MCMC)S.leprosula were divided into two regions, Region A and Region B based on the optimal value of K = 2 derived above. Subsequently, the SSR database was built for Region A and B, comprising 381 (12 populations) and 1029 (32 populations) individuals, respectively. Allele frequency for each locus was calculated using Microsatellite Toolkit37. The number of alleles per locus (A), observed (Ho) and expected heterozygosity (He), conformity to Hardy–Weinberg equilibrium (HWE) expectations and linkage disequilibrium (LD) between loci were assessed using Fisher’s exact tests in Genetic Data Analysis (GDA) v1.1 38. The p value for departure from HWE and LD was adjusted by Bonferroni correction39. Forensic parameters including polymorphic information content (PIC), matching probability (MP) and power of discrimination (PD) were assessed using PowerStats v1.240. Coancestry (θ) and inbreeding (f) coefficients for the combined database  and regional database (Region A and B) were calculated with 1000 bootstrap replicates in GDA41. Self-assignment tests were used to evaluate the proportion of correctly assigned individuals to the designated population and region as implemented in GENECLASS242.The populations of 43. The most common and rarest profile frequencies were calculated by considering an individual sample that is heterozygous at all loci possessing the two most common alleles and rarest alleles at each locus, respectively. The conservativeness of the database was estimated by calculating the full profile frequency of each individual using genotype frequencies derived from the cognate database (Porigin) against profile frequency of each individual using genotype frequencies derived from the regional database (Pcombined). The relative difference between the databases (d) were defined as d = log10 (Porigin/Pcombined). If the d value was negative, in the case of Porigin was less than Pcombined, it suggests that the database is conservative27. For a non-conservative database, in the case of positive d value, a series of θ adjustments were applied to recalculate Pcombined until all samples present a negative d value.The subpopulation-cum-inbreeding model was used to calculate the profile frequency by multiplying the frequency of each locus across all the lociWe declare that all our experimental research and field sampling of plant material comply with local, national or international guidelines and legislation.Supplementary Information.


Ficushirta (Moraceae), which is widely known as a medical and edible plant distributed in South China. As the increasing demand for Wuzhimaotao, the wild F.hirta has been extremely reduced during the past years. It is urgent to protect and rationally develop the wild resources of F.hirta for its sustainable utilization. However, a lack of genetic background of F.hirta makes it difficult to plan conservation and breeding strategies for this medical plant. In the present study, a total of 414 accessions of F.hirta from 7 provinces in southern China were evaluated for the population genetics using 9 polymorphic SSR markers.Wuzhimaotao (Radix Fici Hirtae) originates from the dry root of He) varied from 0.142 to 0.861 (mean = 0.706) in nine SSR loci. High genetic diversity  and low genetic differentiation among populations (G’ST = 0.147) were revealed at population level. In addition, analysis of molecular variance (AMOVA) indicated that the principal molecular variance existed within populations (96.2%) was significantly higher than that among populations (3.8%). Meanwhile, the three kinds of clustering methods analysis  suggested that the sampled populations were clustered into two main genetic groups (K = 2). Mantel test showed a significant correlation between geographic and genetic distance among populations . Pollen flow, seed flow and/or geographical barriers might be the main factors that formed the current genetic patterns of F.hirta populations.A mean of 17.1 alleles per locus was observed. The expected heterozygosity (F.hirta in southern China. We revealed the high genetic diversity and low population differentiation in this medicinal plant and clarified the causes of its current genetic patterns. Our study will provide novel insights into the exploitation and conservation strategies for F.hirta.This is a comprehensive study of genetic diversity and population structure of  Ficushirta Vahl. is a perennial deciduous shrub or small tree which widely distributed in Southeast Asia, Northeast India and South China [F.hirta. The wild resources of this species are continuously shrinking due to over-exploitation and environmental destruction mediated by human beings [F.hirta for its sustainable utilization.th China . In soutth China –4. It coth China , 6. In ath China  for Radin beings . It is uF.hirta have been successfully cultivated in some areas, to some extent, which also relieved the pressure on nature resources, long term cultivation and directional selection of this species may also cause the loss of genetic diversity, further lose their ability of resisting the epidemic of pests and diseases [F.hirta resources in China, which makes it difficult to develop breeding and conservation strategies for this species. Thus, it is of great significance to study the genetic diversity and population structure of wild F.hirta throughout all distribution areas in China.Researches on genetic diversity and population structure of medicinal plants are the premise and fundamental issues for the protection and utilization of medicinal plant germplasm resources. The protection of medicinal plant germplasm resources is to protect its genetic diversity and evolutionary potentials , 10. Altdiseases , 12. TheF.hirta. In this study, we aimed: (1) to systematically reveal genetic diversity and population structure of F.hirta from 18 populations located in 7 provinces in South China; (2) to clarify the causes of the current genetic patterns of this species; (3) to provide references for the conservation and breeding of germplasm resources of F.hirta.In recent years, simple sequences repeat (SSR) marker has become one of the most popular tools for analyzing genetic diversity and population structure, gene flow, phylogenetics in conservation genetics, because of its co-dominant inheritance, high polymorphism, high abundance, selective neutrality and excellent repeatability . During Na) varied greatly among loci, from 7 to 23 alleles (mean = 17.1), while the number of effective alleles per locus (Ne) ranged from 1.23 to 7.9 (mean = 4.9). The observed heterozygosity (Ho) ranged among loci from 0.179 to 0.905 (mean = 0.638), while the expected heterozygosity (He) ranged from 0.142 to 0.861 (mean = 0.706)  varied across populations of F.hirta. The Na per population varied from 5.4 (ZJ) to 9.4 (SD), with a mean of 7.8, while the Ne ranged from 3.7 (ZJ) to 6.2 (SD) (mean = 4.9). The mean He and Ho across all populations ranged from 0.525 (WN) to 0.731 (ZP) and 0.613 (ZJ) to 0.751 (SD), with means of 0.638 and 0.706, respectively. The private allele richness (PAr) of each population ranged from 0  to 0.778 (NN), with a mean of 0.228. All populations showed significant (P < 0.05) deviations from HWE that were not significant after sequential Bonferroni correction. And no bottleneck effects were detected under the TPM model  values, the optimal number of genetic clusters equaled two K = 2). The 18 populations formed in to two clusters. The cluster I included 4 populations from eastern region , while the cluster II included 14 populations in mid-south region    to 0.434 (between WN and MZ) with a mean of 0.147 (Table F.hirta (96.2%), while the variation among populations was only 3.8%   Fig. .Table 3PF.hirta have been used as important herb medicine to prevent and treat many human diseases, such as asthma, stomachache, rheumatism and irregular menstruation in China for hundreds of years [F.hirta are under over-exploitation, and furthermore, the ecological environments of the original distribution area are under destruction year by year [F.hirta plants. Generally, genetic diversity underlies adaptation and evolution of plants, which allows for mitigating against various stresses of the changing environments [F.hirta for proposing the conservation strategies and breeding programs.The roots of of years . Given t by year . In orderonments , 20. TheF.hirta in China maintained abundant genetic variation at species level . Compared with previous studies on congeneric dioecious fig species, the genetic diversity of F.hirta was higher than those (He = 0.370—0.663) of F.carica, F.hispida, F.heterostyla, F.squamosa and F.pumila [. At population level, all populations also maintained high genetic diversity (He > 0.6). For the high genetic variation of F.hirta, according to our observation, the pollinator (Blastophagajavana) of this species can pollinate almost all a year round (except for severe cold winter). The long pollinating period combined with the monsoon climate in southern China may be conducive to the wide-ranging dissemination of pollen and seed [Phyllanthusemblica, Trifoliumrepens, which have proved outbreeding species, were trend to have higher genetic diversity [FIS = -0.027) of F.hirta populations suggested that most of populations, except for the Hainan island populations , were consistent with the low inbreeding level of congeneric species (average FIS = -0.056—0.054) [FIS was relatively high in WN population (0.345) and LS population (0.116), indicating heterozygotes deficiency in both populations, which could be explained by the large number of plant individuals of F.hirta occupied within Hainan island. As high plant density of F.hirta will shorten the pollinating distance of the pollinators between figs. Another plausible explanation for the lower genetic diversity with island populations is the special geographical distance isolated by Qiongzhou strait , which hinders the gene exchanges between islands and Chinese mainland. High inbreeding occurring within Hainan island populations may also explain the relative low genetic diversity of WN and LS populations to other populations in China mainland.In this study, all of the nine loci used are highly informative with an average of 17.1 alleles per locus, which is higher than previous report which was made by Zheng et al. . A varie.pumila , 23. At and seed , 25. On and seed . Partialand seed , 27. Maniversity , 28, 29.6—0.054) . The FISF.hirta. The correlation between the geographical distance and genetic divergence of F.hirta populations were further supported by an IBD analysis with Mantel test . This may be related to the geographical isolation barrier of Luoxiao Mountains and Nanling Mountains between the mid-south and northeast populations, diminishing the gene flow between the above two clusters   Table . Moleculene pool . In addiene pool , 35. Mea.pumila  and Oryzffipogon  that geoF.hirta from South China we investigated had the genetic patterns of low differentiation among populations and high diversity within populations.In this part, we confirmed that the F.hirta is widely distributed in the Subtropical and tropical China, a rising demands on the roots of F.hirta for medicine and food industry has resulted in a severe decline of this plant resources. GAP bases of this traditional herbal medicine have been established in Guangdong, Guangxi and Hainan provinces in recent years, but it’s still unable to meet the needs of the medicine and food market. Nevertheless, the progress in breeding and conservation of F.hirta has been slow because of lacking the genetic background knowledge. Our large-scale population genetics study of F.hirta showed the highest genetic diversity found in SD and SZ populations, while ZJ population was found to be the lowest within the 18 populations. The private alleles were found in most populations (14/18), implicating the specific genes or haplotypes in these populations. The highest PAr was found in NN (0.778), followed by SZ (0.444), while no private allele was detected in WN, SX, ND and a cultivated population ZP. That indicated these populations might maintain a subset of the total genetic diversity present in their wild ancestors.Although F.hirta, it is necessary for us to preserve the two detected clusters and also take into account the populations with high levels of genetic diversity along with those with private alleles . In addition to in situ conservation, ex situ germplasm collection efforts should focus on as many populations as possible for breeding and resources protection. Particularly, individuals from SD, SZ populations in Mid-South cluster, which have higher level of genetic diversity than other populations, and those from NN population which are rich in private alleles also should be taken into consideration  [F.hirta is expected to be further applied in commercial planting (breeding practice), so as to improve its yield and quality and ensure the sustainable utilization of the wild plant resources.According to genetic structure of .hirta) . FinallyF.hirta in southern China. Our results showed: (a) F.hirta maintained relatively high genetic variation and most of the populations contain a number of private alleles and although there was a relatively low genetic differentiation among populations of F.hirta, it still performed a significant IBD pattern. (b) The population genetic clustering suggested that the 18 populations formed into two distinctive clusters which just corresponded to their geographical distribution (mid-south cluster and eastern cluster), of which the mid-south cluster could further be subdivided into mid cluster and south cluster. It is inferred that the formation of current genetic patterns in F.hirta was mainly resulted from pollen flow, seed flow and geographical barriers. (c) Although our results showed that the genetic resources of F.hirta in China were relatively abundant, we should still concern about the large consumption of its wild resources and take actions to protect this eatable and medicinal plant. Our results will provide molecular biological basis for variety improvement, germplasm conservation and establishment of Core Germplasm Bank for F.hirta.In this study, we used nine highly polymorphic SSR markers to study the genetic diversity and population structure of F.hirta from 18 populations involving 7 provinces which almost ranged all its distribution areas in South China  method . The int2+), 2 μl of 10 mM dNTPs, 1 μl of each primer (10 μM), 1 U of Taq DNA polymerase  and 10.8 μl ddH2O water. The reaction was run using a Thermal Cycler  with the following program: 94℃for 5 min, 35 cycles of 45 s denaturation at 94℃, then 60 s at a primer-specific annealing temperature at the range of 50℃ ~ 60℃, and 45 s extension at 72℃, followed by 7 min extension at 72℃, and then a final holding temperature at 4℃. PCR amplification products were separated on 1.5% agarose gels, and visualized under UV light and further sent to Thermo Fisher Technology Co., Ltd  for sequencing. Liz 500 (Applied Biosystems) was used as internal standard, and Peakscanner v1.0 was used to read SSRs genotypes data.Nine highly polymorphic SSR primers were screened in previous studies –17 and wNa), number of effective alleles (Ne), observed heterozygosity (Ho) and expected heterozygosity (He) for each locus were computed with GenAlEx software v.6.5 [https://genepop.curtin.edu.au/) [F-statistics inbreeding coefficient (FIS) [For evaluating the polymorphism of the nine SSRs, the indexes of number of observed alleles  . After tedu.au/) . Wright’nt (FIS)  for eachnt (FIS) . Usuallynt (FIS) . The Botnt (FIS)  was usednt (FIS)  with 70%nt (FIS) . A signiK) was set from 1 to 8 and 5 iterations were run for each K. The 1,000,000 initial burn-in replications were followed by 1,000,000 Markov Chain Monte Carlo (MCMC) replications. The optimal K capturing the major structure of the populations of F.hirta was determined using Structure Harvester web v.0.6.94 (http://taylor0.biology.ucla.edu/structureHarvester/). The Nei’s genetic distances between populations were calculated in GenAlEx v.6.5, as an input for clustering analysis using Principal coordinate analysis (PCoA) implemented in GenAlEx v.6.5.To determine the population genetic structure, a Bayesian clustering approach was used with software of Structure v.2.3.4 . The numG-statistics genetic differentiation (G’ST) matrix [F.hirta.The analysis of molecular variance (AMOVA) was computed with significance determined by permutation test (1000 replicates) using Arlequin v.3.5 . The pai) matrix  was comp) matrix  program F.hirta. Which estimate the correlations between two matrices, a matrix of standardized genetic differentiation (G’ST) computed by GenAlEx and a matrix of geographical distances (Km) between locations calculated using the Geographic Distance Matrix Generator v.1.2.3 [Mantel test  was cond v.1.2.3 . Signifi