Aedes albopictus, a vector for more than 20 arboviruses, has spread worldwide. Aedes albopictus is the main vector of infectious diseases transmitted by Aedes mosquitoes in China, and it has caused concerns regarding public health. A comprehensive understanding of the spatial genetic structure of this vector species at a genomic level is essential for effective vector control and the prevention of vector-borne diseases.Since the second half of the 20th century, Ae. albopictus mosquitoes were collected from eight different geographical locations across China. Restriction site-associated DNA sequencing (RAD-seq) was used for high-throughput identification of single nucleotide polymorphisms (SNPs) and genotyping of the Ae. albopictus population. The spatial genetic structure was analyzed and compared to those exhibited by mitochondrial cytochrome c oxidase subunit 1 (cox1) and microsatellites in the Ae. albopictus population.During 2016–2018, adult female cox1 in 231 specimens were identified in the samples from eight locations in China. Principal component analysis revealed that samples from Lingshui and Zhanjiang were more genetically different than those from the other locations. The SNPs provided a better resolution and stronger signals for novel spatial population genetic structures than those from the cox1 data and a set of previously genotyped microsatellites. The fixation indexes from the SNP dataset showed shallow but significant genetic differentiation in the population. The Mantel test indicated a positive correlation between genetic distance and geographical distance. However, the asymmetric gene flow was detected among the populations, and it was higher from south to north and west to east than in the opposite directions.A total of 9,103 genome-wide SNP loci in 101 specimens and 32 haplotypes of Ae. albopictus population in China. The RAD-seq approach has great potential to increase our understanding of the spatial dynamics of population spread and establishment, which will help us to design new strategies for controlling vectors and mosquito-borne diseases.The genome-wide SNPs revealed seven gene pools and fine spatial genetic structure of the  Aedes (Stegomyia) albopictus , one of the 100 most dangerous invasive species worldwide, can be found on every continent except for Antarctica, because of global warming, human-aided transport, and insecticide resistance , and yellow fever virus   –20 and m1 (cox1) , 21–23. bopictus , 24, 25.bopictus . Many pobopictus  and Wei bopictus  reported regions .Ae. albopictus. However, limited numbers of mosquito populations have been sampled from the native population for studying the population genomics of this species, especially in China , identified using next-generation sequencing techniques, are the markers of choice because of their abundance in the genomes of virtually all populations . Restricin China . Genome-in China . Such inAe. albopictus across China. We used genome-wide SNPs to determine the distribution of genetic diversity and population structure of the Ae. albopictus populations across eight different geographical locations. Combined with the cox1 and microsatellite datasets from the same populations in our previous study  from our previous study  and cox1 sequencing. Sampling bias was examined using previous microsatellite data  and 2886R (5′-ATGGGGAAAGAAGGAGTTCG-3′)  . The 25 EcoRI , which identifies the 5′-GAATTC-3′ sequence. The Illumina P1 adapter  was ligated to the digested DNA. Then, the products from different samples were pooled and randomly fragmented using Covaris E210  with agarose gel selection for 300–500 bp. The products were purified using the QIAquick PCR Purification Kit . The fragments were end-repaired using End Repair Mix (Qiagen) and then purified. The repaired DNA was combined with A-Tailing Mix (Qiagen); Illumina P2 adaptors (BGI) were ligated to the adenylated 3′ ends of the DNA, followed by product purification. PCR amplification with PCR Primer Cocktail and PCR Master Mix  was performed to enrich the adapter-ligated DNA fragments. The PCR conditions were as follows: 98°C for 30 s; 15 cycles of 98°C for 10 s, 65°C for 30 s, and 72°C for 30 s; and a final extension at 72°C for 5 min. The PCR products were selected using agarose gel electrophoresis with target fragments and then purified. The library was quantified using the Agilent Technologies 2100 bioanalyzer  and ABI StepOnePlus Real-Time PCR System (Applied Biosystems). The libraries, with 16 samples pooled per library, were pair-end sequenced using the PE150 strategy on the HiSeq X Ten platform .Samples with total DNA quantity >1 μg were sequenced using RAD-seq, and the sample sizes from the eight locations for library construction were 13 (BJ), 13 (SJZ), 13 (HZ), 12 (WH), 13 (MS), 14 (GZ), 15 (ZJ), and 12 (LS). One microgram of genomic DNA was digested with Aedes albopictus Foshan strain (GenBank accession: GCA_001444175.2)   and C6/344175.2)  with the44175.2) . The ali44175.2) . Then, H44175.2) . In this44175.2) . In addi44175.2)  and thencox1 sequences from 231 mosquitoes were aligned using Clustal W multiple alignment in BioEdit version 7.2.5 (S), haplotype diversity (Hd), average number of nucleotide differences (k), and nucleotide diversity (π) within each population were determined using DnaSP v5.10.1 . According to cox1 sequencing and identification of cryptic species in our previous study , haplotype diversity (Hd = 0.890), and nucleotide diversity (π = 0.248) and the highest average number of nucleotide differences (k = 1.897). However, the BJ population had the lowest values for these genetic indices, as it had only two haplotypes . To determine the relationships between the specimens or haplotypes, we constructed a median-joining network using the haplotypes on the basis of sequence variation  to 0.106 (between HZ and ZJ); a few pairwise tests showed no significance on the basis of the cox1 and microsatellite data  between the genetic distance  and the geographical distance  of populations on the basis of the SNP and microsatellite data, with no significant correlation  on the basis of the cox1 data , 32.76% (cox1), and 2.18% (microsatellites) of the total variation. The fixation index among the populations showed significant genetic variation on the basis of Fisher's exact test for the three types of DNA marker data.The Bayesian clustering analysis based on the datasets of the three DNA markers showed that the ZJ and LS samples were clustered together and separated from the other populations when K = 2. In addition, the optimal cluster numbers (K) determined using the Delta K method for SNPs, ectively . The ML ectively . All samthe DAPC . A largeox1 data  overlappox1 data . The PCAox1 data  were conox1 data  and ML pox1 data  constructa  bopictus . (3) Thebopictus , 75.cox1 haplotypes (H05 and H06). We speculated that several mosquitoes from individual SJZ collection points may have originated from ZJ and LS populations because of human-assisted transportation over long distances. When compared with the customs of provincial capital cities such as BJ, HZ, and WH, the customs of SJZ may have a relatively loose control on commercial transportation and species invasion. The population structure bar plots generated using STRUCTURE on the basis of the SNPs showed that the WH population had the highest shared SNP alleles with neighboring populations; this is possibly because Wuhan is a central city in China and a transportation hub, leading to an increase in mosquito migration and gene flow. The overall gene flow showed a trend from south to north and from west to east, which is consistent with the trend determined using a large number of samples in our previous study  in Ae. albopictus , as they often do not provide reliable information on the true dispersal potential of a species (Genome-wide SNPs identified with next-generation sequencing (such as RAD-seq) that are used to analyze population genetics have two major advantages when compared with microsatellites and ormation , 83. SNPormation , 84. In ormation , a set obopictus . The Man species .Ae. albopictus are available, including reference genomes AaloF1  can be found in the article/YW and XZ conceived and designed the experiments. YW, SH, JW, PF, YH, KH, and YC performed the experiments. YW and DZ analyzed the data. YW, XZ, DZ, and GZ wrote and revised the manuscript. All authors read and approved the final manuscript.This work was supported by the National Natural Science Foundation of China (No. 31630011), Natural Science Foundation of Guangdong Province (No. 2017A030313625), and the Science and Technology Planning Project of Guangzhou (No. 201804020084).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Adonis vernalis), we aimed to gain insight into steppe florogenesis based on the species’ evolutionary history. Although the primary area of origin of the species group comprising A. vernalis, A. villosa and A. volgensis is in Asia, our results indicate that recent populations of A. vernalis are not of Asian origin but evolved in the southern part of Europe during the Pleistocene, with Spanish populations clearly genetically distinct from the Southeastern European populations. We inferred that A. vernalis migrated eastwards from the sub-Mediterranean forest-steppes of Southeastern Europe into the continental forest-steppe zone. Eastern European populations had the highest private allelic richness, indicating long-term large population sizes in this region. As a thermophilic species, A. vernalis seems unlikely to have survived in the cold deserts of the Last Glacial Maximum in Western Siberia, so this region was likely (re)colonized postglacially. Overall, our results reinforce the importance of identifying the area of origin and the corresponding ecological requirements of steppe plants in order to understand the composition of today’s steppe flora.The Euro-Siberian steppe flora consists of warm- and cold-adapted species, which may have responded differently to Pleistocene glacials and interglacials. Genotyping-by-sequencing individuals from across the distribution range of the pheasant’s eye ( The steppe areas display large-scale temperature and precipitation gradients and are divided into lowlands and mountain ranges, resulting in zonation by longitude, latitude, and altitude. In this study we are concerned with the western part of the Eurasian steppes, the Euro-Siberian steppes, which formed around the Altai Mountains in Central Asia  and the European chorological-climatic subtype, which reaches from the Ural Mountains to the area northwest of the Black Sea1. The European subtype corresponds to the Pontic steppes of Eastern Europe in biogeographic literature1. The characteristic zonal Euro-Siberian steppe vegetation extends throughout Eastern Europe and Middle Asia (southern Western Siberia) and consists of semi-dry grasslands of the Festuco-Brometea class, which adjoin the moister meadow steppes of the forest-steppe zone to the south3. The Pannonian region to the west is home to forest-steppe. Scattered patches of semi-natural azonal or extrazonal steppe-like grasslands resembling the climate-driven zonal steppes are found in forest climate in Central Europe as a result of human land use and/or on sites with dry edaphic conditions, for example on rocky or sandy terrain2.The Eurasian steppes form the largest contiguous temperate grassland region on Earth. They extend from the Mediterranean Basin towards China, being more scattered towards the western and eastern peripheriesHipparion species spread from Asia to Europe in the Miocene under the then relatively warmer climate2. At the beginning of the Quaternary, in the Lower Early Pleistocene (2.6–1.8 Ma), global cooling, strong aridification, and increased seasonality of the climate led to a further opening of the landscape and the spread of more modern types of steppes4, a development that intensified further during the transition from the Early to the Middle Pleistocene (0.9 Ma)6. It is likely that the Pleistocene glacial and interglacial cycles resulted in alternating advances and retreats of warm- and cold-adapted species, respectively. During the cold periods, plant communities existed that did not or do not occur in this composition in the warm periods either before or after7, so that the repeated range shifts under alternating favourable growing conditions probably led to a mixing of species from different phytogeographic regions .It is assumed that archetypes of steppe characterised by a more savannah-like habit and the occurrence of nowadays extinct (mega) herbivores such as Astragalus, Camelina, Capsella, Clausia, Dontostemon, Krascheninnikovia and Sisymbrium as well as various species groups within Allium15. At a lower taxonomic level, namely the species level, various studies place the beginning of the spread and diversification of the present-day steppe species between the Early Pleistocene and the Holocene, and the areas of origin of these species from the Caucasus region at the border between Europe and Asia to the Altai Mountains region in Asia, for example for Astragalus onobrychis L., Capsella orientalis Klokov, Clausia aprica (Stephan ex Willd.) Korn.-Trotzky and Krascheninnikovia ceratoides (L.) Gueldenst17. Other species descended from Euro-Siberian/Circumboreal groups. For example, Schivereckia podolica Andrz. & Besser ex DC. may have immigrated into the steppe from an ancient arctic/subarctic vegetation belt via the Ural Mountains, which mark the boundary between Asia and Europe18. However, the areas of origin and evolutionary histories of many steppe plant species remain unknown because there are few range-wide phylogeographic studies due to the sheer size of the Eurasian steppe area. The response patterns of these species to Pleistocene climate fluctuations are also still poorly known.Molecular phylogenetic studies have confirmed that many steppe plants belong to genera or species groups within genera that originated in the Irano-Turanian floristic region such as for example the genera Adonis vernalis L.) is representative for the Euro-Siberian steppe flora and therefore a suitable model to study the history of the semiarid Euro-Siberian steppes and forest-steppes. For example, the species is listed in biogeographical literature as a “Pontic geoelement19” or in floristic works as growing “in dry and steppe grasslands (meadow steppes), also in pine forests20”. Occurring from Spain in the west to near the Yenisey River in Siberia in the east, its distribution is continuous in the east, but disjunct in the west  Europe and Western Siberia, the species grows in steppes, in the transition zones between forest and steppe, and in open birch forests. The plants are found on chernozem soil with high carbonate content, rocky slopes, and secondarily on cattle resting places22. In Central Europe, the species is found in extrazonal calcareous dry-warm grasslands in the deciduous forest zone3. From a phytosociological perspective, A. vernalis is listed as an “indicator species for steppe grasslands23”. While it is not “diagnostic”  for the order Brachypodietalia (= meadow steppes), it is diagnostic for the alliance “Cirsio-Brachypodion pinnati” within this order3 (as well as for the entire class Festuco-Brometea23), i.e., it can be called a typical “meadow steppe species”. The “meadow steppes” are those open grasslands that occur in the “forest-steppes” interspersed with (groups of) trees, which A. vernalis underlines by also colonizing light e.g., pine forests. The pheasant’s eye is an early-blooming, poisonous perennial with a vigorous sympodial rhizome that produces a dense clump of shoots that (if flowering) terminate in a showy yellow flower. It is pollinated by insects25. The nutritious elaiosomes of the nutlets attract ants, which then disperse the seeds (myrmecochory)24.From a chorological point of view, the submeridional and thermophilic pheasant’s eye  climate. In this context, we were also interested in where any refugia of A. vernalis were located during the cold phases of the Pleistocene. To achieve this aim, we genotyped individuals in populations from across the range of A. vernalis, as well as individuals from closely related species, using genotyping-by-sequencing (GBS) to determine the geographic origin of recent populations of the pheasant’s eye and phylogeographic patterns within the species. The phylogeographic approach was complemented by Sanger sequencing of chloroplast and internal transcribed spacer (ITS) sequences in combination with a secondary calibration approach, which we used to construct a dated phylogeny of the tribe Adonideae to determine the timing of diversification of recent populations of A. vernalis.The aim of this study was to determine the evolutionary history of the populations of the pheasant’s eye growing in the Euro-Siberian steppe and to interpret their history in relation to the formation of the Euro-Siberian steppes. We were interested in when, where, and in connection with which Earth history events recent populations of Adonis vernalis, five individuals of A. volgensis Steven ex DC., and one individual of A. turkestanica (Korsh.) Adolf. The ipyrad assembly of the ingroup  and the outgroup (A. volgensis and A. turkestanica) retained 229,597 single nucleotide polymorphisms  across 43,917 loci, of which 39,024 were unlinked SNPs and 23,242 were informative and unlinked SNPs. Adonis vernalis samples had on average 23,562 SNPs  and outgroup samples had on average 18,613 SNPs . The ingroup alignment  contained 160,130 SNPs  across 44,124 loci, of which 37,152 were unlinked SNPs. In this alignment, the samples had on average 23,903 SNPs, ranging from 12,032 to 31,518 SNPs. The two replicates of the same individual of the A. vernalis population from Lower Austria had 98.3% identical SNPs, and the two replicates of the Russian Kalmanka population of A. vernalis had 97.6% identical SNPs. Among all other individuals, only five pairs of individuals  had a higher similarity  and might represent ramets of the same plant.To investigate genetic relationships at the population level, we applied GBS to 184 individuals of Adonis vernalis was reported as uniformly diploid (2n = 16) with a genome size of approximately 18.9–19.5 pg (2C) in the eastern part of its range in Siberia26. Two individuals from Austria measured by us  had comparable values of approximately 19.3 and 19.5 pg, and one individual  had a somewhat higher value of approximately 20.1 pg. The values are not so accurate because leaf material dried with silica gel was used. Estimates of ploidy based on GBS data using nQuire and ploidyNGS indicated a diploid genome for all individuals except one from a population from South Siberia (Neudachino), which was most likely triploid according to nQuire, while its ploidy remained unclear using ploidyNGS.The number of SNPs can be related to genome size and ploidy. Adonis vernalis, we employed Bayesian admixture analysis and Principal Components Analysis (PCA). Admixture analysis with LEA found a most likely number of ancestral populations (K) of seven according to the cross-entropy value . The border between the two clusters is along the eastern Carpathians and corresponds to the border between the Pannonian and Pontic regions. Further independent clusters were formed progressively by individuals of the Brașov population in Romania (K = 4), the Kazakh population and the Kalmanka population in the Russian Altai region (K = 5 and 6), and the Košice population in Slovakia (K = 7). In the PCA  and maximum-likelihood (ML) analyses of three chloroplast markers and, separately, the internal transcribed spacer (ITS). The markers showed extensive agreement in the relationships, although there were also incongruencies  support in the MP and ML analysis, respectively) and in the ITS tree . Molecular dating rested on the secondary calibration of three nodes, two of which were much younger than the third node corresponding to the tribe Adonideae , the estimated age of the tribe Adonideae  was shifted. We therefore relied on the more accurate median age estimates of the analyses with a sigma of 1.0 for all three calibration nodes and on the 95% HPD intervals of the analyses with a sigma of 5.0 for the tribe Adonideae for the discussion of the results. According to this, the analyses revealed a crown group age of A. vernalis of 0.5 Ma  based on the ITS sequences and also of 0.5 Ma  based on the chloroplast sequences  based on the ITS sequences and 1.6 Ma  based on the chloroplast sequences. Given the extremely low variation in the chloroplast and ITS sequences of A. vernalis /ultrafast bootstrapping (UFBoot) support equal to 100/100. Next, the Romanian population from the Brașov Depression  was sister to all the remaining populations, which also grouped with very strong support (aLRT/UFBoot = 100/80). Other Pannonian populations from the Transylvanian Basin between the Eastern and Southern Carpathians in Romania (Cluj and Mureș Counties), the foot of the Bükk Mountains (Western Carpathians) in Hungary (Borsod-Abaúj-Zemplén County), and the foot of the Fruška Gora Mountain in Serbia (Vojvodina Province) grouped with very low support (aLRT/UFBoot = 1/5), essentially forming a polytomy. The remaining populations were divided into two well-supported groups. One group (aLRT/UFBoot = 100/79) comprised the Pannonian populations from Slovakia, Hungary, and Austria, as well as the German populations, whereby the Pannonian populations were paraphyletic regarding the German populations. The other group (aLRT/UFBoot = 100/81) comprised the Romanian population from Constanța County near the Black Sea coast as a sister to the populations further east, which also formed a well-supported group (aLRT/UFBoot = 100/88). East of the Constanța population, the Pontic populations from Ukraine and Crimea formed a sister group to the remaining Pontic and the Siberian populations (Russia and Kazakhstan). The network  in the centre of the network among the four Pannonian populations that received very little support in the tree , the Romanian Brașov population, and the Romanian Constanța population.A phylogenetic analysis of all ree Fig.  as well ree Fig.  to show A. vernalis (excluding Spain), the Pontic group had the highest value, and the middle and eastern Western Siberian group had the lowest value  calculated from the GBS data was used as an indicator of past population sizes, and we assume that higher pAr indicates longer in situ histories of populations and/or larger population sizes in the past. The Spanish population had a similarly high pAr when compared with the group of all other populations combined . Comparing the geographic groups of the eastern lineage of lue Fig.  online. lue Fig.  online.Adonis vernalis is closely related to A. villosa and A. volgensis. The three species differ in their distributions (with overlaps) as well as in their habitats , suggesting both speciation by geographic isolation  and/or ecological speciation as possible mechanisms. In the Eastern European and Western Siberian zonal steppe area, the range of A. volgensis  adjoins the range of A. vernalis  to the south22  or in Eastern or Southeastern Europe, e.g., in the Black Sea region. If we consider the median ages retrieved by the molecular dating analyses, the time period between the stem group and the crown group of A. vernalis ranges from 1.5 to 1.6 Ma  to 0.5 Ma  fit into the phylogenetic tree of the species32. The focus of our study was on the zonal Euro-Siberian steppes inhabited by the eastern lineage of A. vernalis. The Early-Middle Pleistocene Transition around 0.9 Ma brought a marked decrease in temperature and an increase in seasonality and aridity, with an intervening (more humid) period of  reduction of open grasslands in Europe and the Mediterranean 6. This transition and the major glacial/interglacial cycles of the Middle and Late Pleistocene may have provided opportunities for population differentiation in the southern part of Europe, in the western and central Mediterranean on the one hand and in Southeastern Europe on the other hand. Particularly the Southern Carpathians and adjacent regions were recently characterized as having long-term continuity of other meadow steppe plants33.The clear separation of the Spanish from the Southeastern European (Romanian) populations in A. vernalis, the analyses of population structure  region in two directions: It spread to the east (or northeast) and reached through the Pontic area Siberia and the region north of the Altai Mountains, and it spread to the west (or northwest) and reached northern Germany and southern Sweden. Our results thus suggest that A. vernalis migrated into the continental climate zone  from the southwest (sub-Mediterranean forest-steppe in Southeastern Europe34).Within the eastern lineage of re Figs.  and 3 anre Figs.  and 5 of35. Its private allelic richness (pAr) thus gives an indication of what value to expect (namely pAr × 100 < 0.5) if the population is postglacial in age colonization of today’s Western Siberian forest-steppe zone2 could have occurred from the west 38 and/or from small-scale refugia south of the present distribution range39.The GBS data also give us clues about the effects of Pleistocene glaciations on populations of the pheasant’s eye. The site of the Brandenburg population in Germany was buried under the Fenno-Scandian ice shield during the ice advances of the Weichselian/Valdai Glacial corresponding to the Last Glacial Period around 115–12 kaAdonis vernalis should have colonized the vast area east of the Ural Mountains within a few millennia, because its dispersal ability should be limited, if one assumes only barochory (with comparatively large nutlets) and myrmecochory24 as dispersal modes. This would make the time required to colonize such a large area very high  even assuming a continuous habitat. Grazing, however, promotes the growth of A. vernalis22. It would therefore also be conceivable that the transport of the nutlets was by grazing ungulates (which migrated extensively in the Eurasian steppe) or specialized small mammals39, particularly as the nutlets have a persistent and hooked style that might get caught in fur42.It may be surprising that a plant like 43. It is conceivable that the vast north–south extension of the steppe and forest-steppe zone in the Pontic region of Eastern Europe allowed greater stability  of these vegetation types during cold and warm periods (without major losses)44, while the small-scale mosaic distribution of steppe-like vegetation in the Pannonian as well as in the German  region made this more difficult48. This would explain the higher private allelic richness in the Pontic compared to the Pannonian and German region (given similar age of populations).Accumulation of private alleles over time should be steady in stable populations with constant sizes. Fluctuations in population size (bottlenecks), however, should lead to a loss of (private) alleles. Private allelic richness should therefore be indicative not only of long-term in situ persistence, but also of stable population sizes over time. It seems that the proportion of open, herb-rich vegetation transitional to steppes, as it is found today in the Pontic region, was comparatively stable during the stadials and interstadials of the Weichselian/Valdai Glacial in the Black Sea region, whereas deciduous oak forests and Anatolian steppes, for example, changed more in their relative abundances19. It comprises species that are distributed both in the Pontic steppe region and in the dry (mountain) grasslands of the Mediterranean region19, but do not necessarily occur further east, e.g., in the Trans-Volga-Kazakh steppes. The (phylogenetic) position of the Romanian populations in the population-level analyses of GBS data , providing genetic evidence that the Euro-Siberian steppe flora consists in addition to Irano-Turanian17 and Euro-Siberian18 also of sub-Mediterranean elements. It shows the need for a precise distinction between different steppe types with different ecological requirements to explain today’s composition of the steppe flora. The response of the steppe plants to Pleistocene climate oscillations should depend on their ecological specialization, especially with respect to temperature and humidity preferences2. Depending on the region, A. vernalis had to retreat to refugia either during the cold and continental phases of the glacials  or during the forested warm and oceanic phases of the interglacials (in the Mediterranean). In Central, Southeastern and Eastern Europe west of the Ural Mountains, the species appears to have approximately maintained stable population sizes throughout the Weichselian/Valdai Glacial . Adonis vernalis’ congenerics, A. villosa and A. volgensis, may have reacted differently. Since we lack phylogeographic data, we can only speculate about their Pleistocene history. However, both species occupy drier habitats and replace A. vernalis to the south and in the mountain steppes of Middle and Central Asia. According to Hoffmann22, temperature is unlikely to be a main determinant of their geographic ranges. Thus, increased aridity during the cold stages of the Pleistocene may have had less pronounced effects on these species than on A. vernalis. Truly drought-adapted species, like the eurythermal Irano-Turanian steppe element Krascheninnikovia ceratoides, in contrast, did not have to retreat during the cold periods in any region; on the contrary, this species took advantage of the cold periods to spread both south(west)ward into the Mediterranean and north(east)ward into Beringia12. This comparison shows how the different behaviour of steppe plants from different origins and with different ecological requirements determines the (heterogeneous) composition of the present steppe flora. The results of this and earlier studies are beginning to coalesce into a refined understanding of steppe florogenesis.Finally, our data on the species history of the pheasant’s eye, together with previously published phylogeographic studies of other Euro-Siberian steppe species, contribute to our understanding of the florogenesis of the Euro-Siberian steppes. The “Pontic-Mediterranean (or sub-Mediterranean) geoelement” has been described in biogeographical literatureta Figs. ,3,4,5 inA. vernalis was dried directly in the field with silica gel  Adolf, A. villosa Ledeb., A. volgensis Steven ex DC., and A. coerulea Maxim. (available from GenBank). Of these, A. turkestanica and A. volgensis were also used for GBS.Leaf material of all samples of We extracted genomic DNA from about 20 mg silica gel-dried leaf or seed material using the DNeasy Plant Mini Kit , the NucleoSpin Plant II kit  or the innuPREP Plant DNA Kit using the CTAB-containing lysis solution SLS  according to the manufacturers’ instructions. The concentration of the DNA was measured by fluorescent quantification using the DeNovix dsDNA Broad Range Assay  in a DS-11 FX spectrophotometer/fluorometer (DeNovix).Adonis vernalis L. by flow cytometry, we used the CyStain PI Absolute P kit  according to the manufacturer’s manual with leaf tissue of the sample and an internal standard . At least 5,000 nuclei were measured in a CyFlow Space  to estimate the nuclear DNA content.To measure the genome size of three samples of atpI-atpH intergenic spacer, matK, rpl16 intron) and the nuclear rDNA internal transcribed spacer (ITS) region were sequenced in all available Adonis and Trollius species. For each PCR reaction, Red HS Taq Master Mix , forward and reverse primer , DNA extract (1 μl), and water (7.4 μl) was used. The PCR program for atpI-atpH with primers atpI and atpH50 and for rpl16 with primers rpL16F71 and rpL16R151651 started at 95 °C for 1.5 min, followed by 35 cycles of 95 °C for 15 s, 53 °C for one minute, and 72 °C for one minute, followed by 72 °C for seven minutes and hold at 10 °C. Amplification conditions for matK with primers matK-413f.-4 and matK-1227r-452 were 95 °C for 1.5 min, 35 cycles of 95 °C for 30 s, 44 °C for one minute and 72° for one minute, followed by 72 °C for ten minutes and hold at 10 °C. The program for ITS with primers ITS5 and ITS453 was 94 °C for two minutes, 35 cycles of 94 °C for 30 s, 50 °C for 30 s, and 72 °C for two minutes, followed by 72 °C for five minutes and 10 °C hold. Amplification products were purified by enzymatic treatment with Exonuclease I (1 μl) and FastAP Thermosensitive Alkaline Phosphatase  at 37 °C for 15 min and at 85 °C for 15 min thereafter. Both DNA strands were sequenced. Cycle sequencing reactions consisted of BigDye Terminator v3.1 Ready Reaction Mix , 5 × sequencing buffer (1.5 μl), primer  and PCR product (6.5 μl). Cycling conditions after an initial denaturation at 96 °C for 1 min were 35 cycles of 96 °C for 10 s, 50 °C for 5 s and 60 °C for 4 min. Excess dye-labelled nucleotides from the sequence reaction were removed using Sephadex G-50 Fine  columns prepared in MultiScreen-HV  filter plates followed by a run on a 3500 Genetic Analyzer . The forward and reverse sequences were assembled, edited, and aligned in Geneious 6.1.8 .Three chloroplast markers , 20 trees held at each step, tree-bisection-reconnection with reconnection limit 8. For maximum-likelihood (ML) analysis, the alignments were loaded into the RAxML-NG web service maintained by Vital-IT57 . The three concatenated chloroplast loci each had their own GTR + FO + G evolutionary model. In ITS, ITS1 and ITS2, together with the last bases of the 5.8S rDNA (which were variable), each had their own GTR + FO + G evolutionary model (the remaining invariable bases of the rDNA were not used). The branch lengths were linked, bootstrapping with the automatic bootstopping option (bootstopping cut-off: 0.03) was requested, and the other settings were kept as default.The three concatenated chloroplast loci and nuclear ITS were analysed separately. The alignments were complemented with sequences downloaded from NCBI GenBank  and log normal relaxed clock model with default parameters. The trees were linked and had a Calibrated Yule model as the tree prior. We used a secondary calibration approach and normal priors for the three calibration nodes, which were fixed as monophyletic, to reflect the distribution of reported node ages27. The mean value of the Adonideae prior was set at 25.5 Ma, that of the Calathodes-Trollius prior at 6.6 Ma, and that of the Megaleranthis-T. asiaticus L. group prior at 2.8 Ma27. Two different settings were chosen for the sigma of the calibration nodes: First, sigma of all three nodes was set to 1.0, and second, sigma of the Adonideae prior was set to 5.0 and that of the other two nodes was set to 1.0 to better match the given ranges27. Three other groups were also fixed as monophyletic: the genus Adonis, the annual Adonis species, and the perennial Adonis species. The other priors had default values. The chain length was set at one billion for ITS and 200 million for the concatenated chloroplast sequences, tracelog and treelog at 5000 each. The runs for each combination of data and settings were started twice and the results were checked in Tracer v1.7.161. Although the posterior and prior traces fluctuated until the end of the runs and the posterior and prior ESS were below 100, all other parameters had stable traces and ESS values well above 200. In both runs for each combination of data and settings, the median and 95% HPD interval of the age of Adonis vernalis in millions of years were identical after rounding to one decimal place  and MspI (New England Biolabs). Library preparation followed published protocols63. Samples were sequenced on separate lanes in two consecutive runs on a HiSeq 2500 System  to achieve good genome coverage . Two individuals were sequenced twice to assess the reproducibility of the method. We used ipyrad64 to sort, filter, de-novo assemble and align the raw data. We let ipyrad cut off the restriction site overhangs “TGCAG” and “CGG”. We set the Phred quality score to 33 and filtered reads, which had more than five low quality base calls. We applied the strict adapter filtering option to remove the common Illumina adapters. We allowed a maximum of eight indels, 20% SNPs and 50% of samples sharing heterozygous sites for a locus, up to two alleles per site, 5% uncalled bases and 5% heterozygous sites in the consensus sequence. After finding that a threshold of 85%, 90% or 95% of sequence similarity of reads to be considered reads at the same locus had a negligible effect on the topology of the tree, we decided to use a threshold of 85%. Per locus, at least 10% of all individuals (19) had to have data. Only loci with a depth of six to 10,000 and a minimum length of 35 bp were kept. We repeated the assembly with and without the outgroup species. We estimated ploidy levels from GBS data using nQuire65 and ploidyNGS66 as described in a previous publication12.200 ng of genomic DNA were digested with the restriction enzymes A. vernalis, we estimated individual admixture coefficients from the genotypic matrix with the LEA package67 in R v3.5.068, with only the dataset of unlinked SNPs in the Variant Call Format (VCF) of the ingroup samples and setting the ploidy to diploid. We tested one to fifteen ancestral populations, each with 100 repetitions, and selected the correct number based on minimal cross-entropy. To display the result per population, we calculated the membership to each ancestral population per population as an average over its individuals and plotted it as a pie chart on a map. We also performed Principal Component Analysis (PCA) using the R package dartR69, again based on the ingroup dataset of unlinked SNPs. For LEA and PCA, the analyses were conducted twice, first with a maximum of 90% missing data per locus  and second with a maximum of 10% missing data per locus . We filtered the vcf-file from the ipyrad output using VCFtools v0.1.1370 to obtain the reduced data set. The LEA and PCA results based on the larger and smaller datasets, respectively, were very similar, so we only show the result based on either the larger or smaller dataset, namely the result based on the larger dataset with a maximum of 90% missing data per locus for LEA and the result based on the smaller dataset with a maximum of 10% missing data per locus is shown for PCA.To assess the population genetic structure of 71 with the GRT + G model and correction for ascertainment bias. Support of nodes was assessed using the SH-like approximate likelihood ratio test (aLRT)72 and ultrafast bootstrapping (UFBoot)73 with 1000 repetitions each. To display the splits as a network, the file with the splits output by IQ-TREE was opened in SplitsTree v4.14.574.Phylogenetic analysis including the outgroup was conducted on the dataset of unlinked SNPs of the complete sample (with a maximum of 90% missing data per locus) by applying the ML criterion using IQ-TREE v2.0.375. Only unlinked SNPs that were called in at least one individual in each population were used . The rarefaction sample sizes for calculating pAr for Spain versus all other populations were one population from each group and two nucleobases from each population, and for calculating pAr for geographic groups excluding Spain, they were five populations from each group and two nucleobases from each population. The rarefaction sample size used to calculate the population Ar and pAr values were two nucleobases per population.To calculate private allelic richness (pAr) per geographic group and (private) allelic richness (pAr and Ar) in populations within these groups, rarefaction analysis was performed in HP-RareSupplementary Information.


Anatomically modern humans originated in Africa and separated from their most likely recent common ancestor hundreds and thousands of years ago . They foThere is increasing evidence to suggest that the differences in the susceptibility of many common and rare diseases are primarily attributed to human populations’ diverse cultural, environmental, demographic, and genetic histories. The comprehensive understanding of fine-scale population evolutionary history will gradually change our understanding of the genetic architecture of diseases . Thus, tvia low-density genetic markers. It is also now possible to capture and sequence ancient DNA from ancient samples, which could provide pivotal insights into the formation of spatiotemporally diverse populations with unprecedented resolution. Although huge nationwide biobanks for characterizing the genotypes and phenotypes of millions of people have been established  . FIGG, oForensic investigative genetic genealogy and fine-scale structure of Human Populations”. In detail, this Research Topic aimed to characterize the genetic background and demographic history of ethnolinguistically and geographically diverse populations based on different densities of genetic marker. It would be helpful in exploring the long-range familial searches and fine-scale genetic localization within subgroups in other continents. This Research Topic attracted research focused on the basic knowledge exploration of the genetic background of one targeted population and included applied research focused on developing and validating forensic amplification systems.To summarize the new advances in FIGG and fine-scale population structure and illuminate the importance of full-scale genetic structure and diversity as the basis for the FIGG, we organized this Research Topic of the “Zhou et al. generated and analyzed genome-wide data of Liaoning Han people and found that genetic differences existed in geographically different Sinitic-speaking Han populations, which might result from other migration and admixture events of Hans during the period of “Chuang Guandong”. Hou et al. investigated the population history of Liaoning Mongolians based on ∼700,000 SNPs and provided new insights into the admixture history of Mongolic-speaking Mongolians according to shared allele-based analyses. He et al. explored the demographic history of Qiang people based on Eurasian modern and ancient reference populations. This study revealed that the Tibeto-Burman-speaking Qiang people derived their primary ancestry from Tibetan-related ancestral populations in North China. Wang et al. performed a genome-wide association study on 26,806 Chinese individuals. They identified 21 SNPs associated with widow’s peak, unibrow, double eyelid, earlobe attachment, and freckles. This study may facilitate a better understanding of the genetic basis of facial development in Chinese populations and provide new markers for forensic phenotype predictions. These studied Han, Mongolian and Qiang people are widely distributed in North China, and other populations from southern China and surrounding regions need to be further explored based on the array or sequencing data, such as Austronesian, Austroasiatic, Hmong-Mien and Tai-Kadai people. Generally, population genetic studies showed a strong correlation between Chinese cultural language and geographic patterns and population structure.Recent studies have demonstrated that population history reconstruction leveraging high-density genetic markers could uncover previously unrecognized population structures at a fine scale compared with forensically relevant loci . Zhou etGorin et al. selected 5,229 AISNPs and tested various mathematical models for biogeographic ancestry inference. The results showed that the accuracy of the prediction of this panel on one of 29 studied ethnic groups reached 71% and the proposed method could be employed to predict ancestries from Russian and neighboring populations. Huang et al. developed a machine learning approach for estimating the relationships with high error SNP profiles and found that this approach was more accurate and robust than the individual measures.The estimated patterns of genetic diversity in China can help accurately biogeographic ancestry inference and FIGG. Similar population stratifications were also identified in Siberian populations. Currently, available tools could effectively distinguish populations with different continental origins, but most of these are not efficient for differentiating people within the same continent. Huang et al. validated the forensic performance of a novel multiplex autosomal STR panel (including six CODIS STRs and 20 non-CODIS STRs). They found that this novel kit could be applied as a promising tool for forensic human identification and complex paternity analysis. Than et al. genotyped seven Lao Isan and three Laotian populations using Verifiler plus PCR Amplification kit. The allelic frequency results provided the genetic background of Austroasiatic and Tai-Kadai people from Laos and Thailand.STR genotyping has been applied in forensic investigations for nearly 30 years . NowadayLiu et al. developed and validated a six-color fluorescence multiplex panel including 59 autosomal InDels. Subsequently, Tibetan groups from China have been genotyped using the newly-developed 59-plex InDel panel. The comprehensive population genetic analyses showed that this homemade panel could be used as a powerful tool for individual forensic identification and paternity testing in Chinese Tibetan groups. Jin et al. developed a Next-Generation Sequencing (NGS) InDel panel, including 17 multi-InDels on the X chromosome. They found that the newly-developed panel could be adopted as an effective tool for individual forensic identification, paternity testing, and biogeographical ancestry inference.InDel loci, the second most abundant polymorphism across the human genome, possess low mutation rates and small amplicon lengths compared with STRs , which hJia et al. sequenced complete mitochondrial genomes of 146 Daur individuals in China. The results showed that the Daur ethnic group has high maternal genetic diversity and may have experienced recent population expansion. He et al. developed and validated the AGCU-Y30 Y-STR panel and conducted a Y-STR-based study to explore the paternal history of the Qiang people. The validated results showed that the novel Y-STR kit was sensitive and robust enough for forensic applications. Population genetic analyses revealed that the Qiang people are closely related to lowland Tibetan-Yi corridor populations.Genetic surveys based on uniparentally inherited markers have identified many paternal and maternal founding lineages in regional populations and their corresponding expansion events . Jia et WCH and ChinaMap, were recently launched to explore the genetic features of under-represented populations. Characterizing the genetic architecture of ethnolinguistically and geographically diverse populations will promote our understanding of population origin, separation, admixture, adaptation, and gene flow from archaic individuals.Human genetics needed the fundamental foundation supporting large-scale population genomic projects to characterize the full landscape of human genetic diversity and population structure, such as NHLBI TOPMed , gnomAD Knowledge of the fine-scale genetic structure and population-specific genomic database is the base for FIGG. Synthesizing our growing knowledge of evolutionary history with forensic investigations will help to achieve the promise of long-range familial searches and fine-scale genetic localization. For human population genetics and FIGG, we also had some challenges that needed to be overcome in the next step:Firstly, European bias in worldwide human genetic studies and Han Chinese bias in Chinese cohort research hinder in heath equality of genetic studies and forensic genetics. More population genomic studies from under-reported populations need to be conducted to characterize their uncharacterized genetic polymorphisms and the genetic spectrum of different genetic markers.Second, a population-specific genomic database should be constructed to provide a comprehensive landscape of different genetic markers and even include structural variations and mobile elements via the PacBio sequencing plateau.Third, cooperation of national genomic studies should be formed to promote data sharing in different institutions.Forth, population genomic projects should be conducted among included subjects with deep phenotypes, which would provide values for exploring the genetic basis for physical traits and medical phenotypes.Fifth, regional population-specific genomic datasets, FIGG panels, algorithms, and forensic databases should be developed and validated. FIGG has promoted successful inspection of criminal suspects among American or European populations, as there are publicly available European/American genomic databases and DNA. Land and GEDmatch severs. Similar databases from other countries or regions should be constructed in the future.Seventh, IBD-based algorithms need the high-density phased SNPs or whole genome sequencing data. Many forensic samples were highly degraded or had minute amounts of genetic materials. Thus, the primary focus is to develop more FIGG panels based on low-density SNP markers and non-linkage algorithms .In short, more ethnolinguistically and geographically diverse populations are needed to be studied based on different genetic markers and algorithm models, and population-specific panels based on different genetic variations and corresponding forensic databases need to be developed to achieve long-range familial searches and fine-scale genetic structure reconstruction.


Wikstroemia monnula was evaluated by sequencing 12 nuclear microsatellite loci of 905 individuals from 38 populations. The STRUCTURE analysis suggested the most likely number of clusters was two, but using multi-hierarchical structure analysis, almost every population was determined with an endemic genetic component. The latter result is consistent with the extremely low gene flow among populations and a large number of unique cpDNA haplotypes in this species, indicating one level of structure analysis would extremely underestimate its genetic component. The simulation analysis shows the number of populations and the genetic dispersion among populations are two key factors to affect the estimation of K value using the above tools. When the number of populations is more than a certain amount, K always is equal to 2, and when a simulation only includes few populations, the underestimation of K value also may occur only if these populations consist of two main types of significantly differentiated genetic components. Our results strongly support that the hierarchical STRUCTURE analysis is necessary and practicable for the species with lots of subdivisions.Population genetic structure can provide valuable insights for conserving genetic resources and understanding population evolution, but it is often underestimated when using the most popular method and software, STRUCTURE and delta K, to assess. Although the hierarchical STRUCTURE analysis has been proposed early to overcome the above potential problems, this method was just utilized in a few studies and its reliability needs to be further tested. In this study, the genetic structure of populations of  Revealing the correct population genetic structure (the “true” number of clusters) of a species can provide the scientific basis for formulating conservation strategies and sustainable utilization of genetic resources of the species . STRUCTUHierarchical STRUCTURE analysis may be one possible approach to solve the problem of underestimation of the optimal K value when using delta K method. For STRUCTURE version 2.1 , the autWikstroemia monnula as the research material to examine the above problems. W. monnula Hance (Thymelaeaceae) is a deciduous shrub endemic to southeast China. Populations of this species are scattered on isolated rock walls, mountain tops, cliffs, or slopes, at elevations ranging from c.200-1365 m above sea level    Table S1Total RNA was extracted from the leaves and was sequenced by the HiSeqTM 2500 NGS platform. ‘Clean reads’ were assembled using Trinity software (v2.0.6) . The traWikstroemia monnula samples (different populations). Finally, 12 pairs of EST-SSR primers (W. monnula.The software MISA was used to search the SSR sites (Simple sequence repeats) in all unigenes . The con primers Table S22O. The PCR procedure was as follows: initial denaturation at 94°C for 3 min, followed by 35 cycles of 30 s at 94°C, 40 s at 56-62°C, and 45 s at 72°C, with an additional extension at 72°C for 10 min. The PCR products were detected using an ABI3730XL DNA Analyzer , and alleles were scored manually using GeneMapper (version 3.7.0).Total genomic DNA was extracted using a plant genomic kit  following the manufacturer’s manual. Twelve polymorphic nuclear microsatellites were screened by PCR amplification followed by denaturing polyacrylamide gel electrophoresis Table S2For the nSSR dataset, we first conducted the neutral test and the test for deviations from Hardy-Weinberg equilibrium (HWE). We used STRUCTURE v.2.3.4 (Pritchard and Wen 2003) to infer genetic structure and define the number of clusters in the dataset. We performed 12 runs at each value of the fixed parameter K (the number of clusters) ranging from one to 12. Each run consisted of 500,000 replicates of the MCMC after a burn-in of 100,000. All other parameters were set to default values. The most likely number of homogeneous clusters was assessed by standardizing the second-order rate of change of the mean likelihood of K  and Nei’s genetic distance (FST) among populations were calculated using Arlequin V.3.11 .The gene flow (distance  were estdistance . The pain V.3.11 . The unwn V.3.11 . A princn V.3.11  based onWikstroemia monnula were obtained from our previous work (Data of chloroplast haplotypes of ous work .Wikstroemia monnula was from 0.005 to 0.063 (Fst) among 38 populations was between 0.372 and 0.743, with an average of 0.474. According to Balloux and Lugon-moulin (2002), the Fst value greater than 0.25 indicated a high level of population differentiation; hence, a high differentiation occurred among the populations of W. monnula characterized in the present study. In the AMOVA, 12.66% (P < 0.001) of the total EST-SSR variation was distributed among groups, 31.72% was explained by variation among populations within groups, and 55.61% was apportioned within populations. These results showed genetic variation was high within populations, among groups, and among populations.The gene flow among 38 populations of to 0.063 Table S3The delta K analysis including 905 individuals from 38 populations suggested the most likely number of clusters was two K=2, Figure 2Cluster 2 (including 23 populations) produced two sub-groups Figure 2UPGMA using Nei’s genetic distance method was shown in In this study, PCoA analysis was also conducted on 905 individuals based on genetic distance matrix, and the results were shown in Genetic structures of eighty randomly sampled groups from 38 populations were analyzed using the delta K method in this study Figure 5The results of 60 simulations with 4 populations but including different clades and/or subclades were shown in Wikstroemia monnula has extremely low gene flow among 38 populations . However, when we used STRUCTURE 2.3.4 to analyze the structure of this species, the optimal K value was observed at K=2 with maximum delta K, with all individuals divided into two clusters  The gene flow among the 38 populations of the target species was extremely low (0.005 to 0.063), and when gene flow is far below 1, it was difficult for populations to share the same genetic components . (2) Eve monnula Figure 6Retropinna spp, W. monnula containing its specific genetic component and showed that the full hierarchical STRUCTURE analysis is not only necessary but also reliable.Is it possible to overestimate population genetic structure? That is, the hierarchical analysis of the same genetic component produces new genetic types. In the study on Does the number of populations have an effect on the optimal K value? Some simulations suggested that the species with many subpopulations had a large impact on STRUCTURE analysis . In the Generally, no matter how many randomly sampled populations were included in the STRUCTURE analysis, population genetic structure  may be underestimated. However, the population number of analysis has a significant impact on the extent of underestimation of the K value; with an increase in the sampling population number, the optimal K value would be underestimated more strongly and more frequently. This result indicates that the hierarchical structure analysis is necessary regardless of whether the population number is large or small. But when analyzing more populations, the necessity of the hierarchical structure analysis is even stronger.Wikstroemia monnula, featuring low gene flow among populations and extremely high population differentiation, with almost every population having its own unique genetic component. The usual STRUCTURE analysis, which obtained the optimal K=2, extremely underestimated the population genetic structure of W. monnula. Larger population numbers and more complex hierarchical genetic differentiation were two important factors to result in the underestimation of K value and the optimal K=2. For revealing the true population genetic structure, hierarchical structure analysis is necessary and practicable for species with highly subdivided populations.The study demonstrated a very complex population genetic structure of https://www.ncbi.nlm.nih.gov/, accession number PRJNA379203 .The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: W-JZ, Y-GW, L-FL, Z-PS, JY, YZ and G-HY conceived the study. C-QZ, Y-YH and PN collected the materials. C-QZ, Y-WT and D-FT performed the statistical analyses and C-QZ wrote the first draft of manuscript. All authors contributed to the article and approved the submitted version. This work was supported by the Science and Technology Commission of Shanghai Municipality (19511104401), and the Young Doctor Foundation of Colleges and Universities in Gansu Province (2022QB-153) and the Natural Science Foundation of China (31670223 and 31270407).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Fusarium commune, a major fungal pathogen causing strawberry root rot, from diseased strawberry root tissues in southcentral China. A total of 354 isolates were obtained from 11 locations that spanned about 700 km from both south to north and east to west. Multilocus genotypes of all isolates were obtained using seven polymorphic simple sequence repeat markers developed in this study. Our analyses revealed significant genetic diversity within each of the 11 local populations of F. commune. STRUCTURE analysis revealed that the optimal number of genetic populations for the 354 strains was two, with most local geographic populations containing isolates in both genetic clusters. Interestingly, many isolates showed allelic ancestry to both genetic clusters, consistent with recent hybridization between the two genetic clusters. In addition, though alleles and genotypes were frequently shared among local populations, statistically significant genetic differentiations were found among the local populations. However, the observed F. commune population genetic distances were not correlated with geographic distances. Together, our analyses suggest that populations of F. commune causing strawberry root rot are likely endemic to southcentral China, with each local population containing shared and unique genetic elements. Though the observed gene flow among geographic regions was relatively low, human activities will likely accelerate pathogen dispersals, resulting in the generation of new genotypes through mating and recombination.Strawberry plants and fruits are vulnerable to infections by a broad range of pathogens and pests. However, knowledge about the epidemiology of pathogens causing strawberry diseases is limited. In this study, we analyzed  Fragaria × ananassa) is an economically important berry fruit crop worldwide. It is rich in vitamins, minerals, anthocyanins, antioxidants, and other nutrients, and is a highly recommended healthy food for humans [2, accounting for about 30% of the world’s total strawberry planting area and about 40% of the global strawberry production [The commercially cultivated strawberry , we confirmed and selected Fusarium commune for further genotyping analyses. Here, we developed seven polymorphic SSR markers for F. commune and used these markers to genotype 354 F. commune strains collected for this study. The genotype information was used to identify the genetic diversity and relationships among strains and populations of F. commune causing strawberry root rot in southcentral China. Furthermore, this information was used to infer the epidemiology of Fusarium root rot and to suggest potential future areas of research.In this study, we aimed to understand the epidemiology of From April to May 2019, we collected strawberry plants with typical symptoms of root rot disease (wilting and discolored roots) from 11 sites in the following nine counties/municipalities in southcentral China: Chenzhou, Hengyang, Xiangtan, Yueyang, Yiyang, Changde, Zhangjiajie, and Xiangxi in Hunan Province, and Laifeng in Hubei Province. The sampling sites spanned from Chenzhou, Hunan, in the south to Yueyang in the north, and from easternmost Hengyang and Chenzhou to Xiangxi in Hunan and Hubei’s Laifeng in the west. The sampled sites included a variety of terrains and climates . DetailsTo isolate the infecting pathogen, the strawberry plant root system was divided into three parts, corresponding to fibrous roots, main root epidermis, and main root stem pith. From each of the 11 sites, 30 pieces of diseased tissue were taken for each of the three root tissue types for pathogen isolation. Here, for samples from fibrous roots, each piece of diseased tissue represented a distinct infected fibrous root. For samples from main root epidermis, each piece of diseased tissue represented a distinct site along the main root. Similarly, for samples from the main root pith, each piece of diseased tissue represented a distinct section within the main root stem. Up to five pieces of infected tissues from each plant for each of the three root tissue types were used for isolating the infecting pathogen. The different root tissue samples were used to investigate whether there were tissue-specific differences among the alleles and genotypes of the infecting pathogen populations.3, transferred onto a potato dextrose agar (PDA) medium plate containing 50 μg/mL streptomycin, and placed in an incubator at 25 °C. Three tissue pieces were placed on each plate. When the fungal colony grew to about 2 cm in diameter, a sterile toothpick was used to pick a small clump of hyphae from the edge to cultivate pure culture. Fungal colonies with vigorously growing aerial hyphae and macroconidia resembling a spindle were selected for downstream analyses.For pathogen isolation, strawberry roots with typical symptoms of root rot were washed with clean tap water to remove soil remnants and soft rotten tissues. Each diseased tissue was then surface sterilized with 75% ethanol for 1 min, followed by soaking in 2% sodium hypochlorite solution for 10 min, and washed with sterile pure water 3 times. The surface-sterilized diseased tissue was then dried using sterile filter paper, cut using a sterile scalpel into small pieces of about 0.01 cmtef1α) gene from each isolate. Briefly, mycelia were collected from 5-day-old cultures grown on PDA for each Fusarium isolate. The total genomic DNA was extracted following the protocol described in Fang et al. [tef1α barcode region was amplified with primers EF1 (5′ ATGGTAAGGARGAGAAC 3′) and EF2 (5′ GGARGTCAGTSATCATG 3′). PCR amplification was performed in a T100TM PCR instrument . The initial denaturation was performed at 94 °C for 5 min, followed by 35 amplification cycles. Each amplification cycle included denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, extension at 72 °C for 1 min, and finally extension at 72 °C for 10 min. The amplification was verified by agarose gel electrophoresis (1× agarose buffer). The amplified PCR products were purified and sequenced by Tsingke Biotechnology .For species identification, we followed the method of O’Donnell et al.  and obtag et al. . PCR amptef1α DNA sequence obtained from each isolate was compared with those in the GenBank database. After BLAST comparison, we retrieved the representative GenBank tef1α sequences of Fusarium species that were closely related to our sequences, especially those within the Fusarium oxysporum species complex. These retrieved sequences were combined with our own sequences for phylogenetic analysis to confirm the species identity of our strains, using the MEGA 7.0 software [https://itol.embl.de, accessed on 15 March 2022) [The software . The maxsoftware . The outch 2022) .F. commune, we first developed new SSR markers for genotyping F. commune strains. To develop polymorphic SSR markers, we first retrieved the genome sequence of F. commune from NCBI. The F. commune genome data were mined using the MISA v2.1  program. The default setting of the MISA program defined SSR markers as containing one of the following: 1 base repetitions ≥10 times; 2 base repetitions ≥6 times; 3 base, 4 base, 5 base, and 6 base repetitions ≥5 times. When the distance between two SSR markers is less than 100 bp, they form a composite SSR marker and were included as a single SSR marker for testing. After SSR marker identification, we used Primer 3.0 (http://primer3.sourceforge.net/) software  to design primers (default parameters).Because there is currently no reported multilocus polymorphic marker for F. commune, we selected eight strains representing different tef1α sequence types and screened 30 pairs of SSR primers, following protocols described previously [To identify potential polymorphic markers for our strains of eviously . The infF. commune isolates and using fluorescent marker standards for each run as fragment size references and following the default setting as recommended by the program. An example graph for allele calling is shown in To obtain multilocus genotype information for all strains in the population, one primer in each of the seven SSR primer pairs was fluorescently labeled with FAM or HEX (Tsingke Biotechnology). For each isolate at each SSR marker, the PCR reaction (15 µL) consisted of 7.5 µL 2× Tsingke MasterMix, 1 µL of each primer (10 nM), and 1 µL template DNA. PCR cycles consisted of a 5 min denaturation (at 94 ℃), followed by 30 cycles of denaturation (94 ℃), annealing (50–55 ℃), and extension (at 72 ℃), each for 30 s. PCRs were terminated after a final 5 min extension at 72 ℃. Successful amplifications of the SSR markers were confirmed by agarose gel electrophoresis. After confirmation, 5 µL of each amplification product was mixed with 10 µL of a mixture containing highly deionized formamide and rox-500 fluorescent molecular-weight internal standard as recommended by the manufacturer. The mixtures were then denatured at 95 ℃ for 5 min, placed on ice for 10 min, and loaded onto an ABI 3730xl automatic DNA analyzer for capillary electrophoresis. The output files were analyzed using GeneMapper 4.1 software to identify the lengths of amplified fragments of http://taylor0.biology.ucla.edu/structureHarvester, accessed on 10 January 2022).The strain relationships based on SSR genotype data were inferred based on the UPGMA algorithm using MEGA7 software. For each of the 11 local populations, the mean numbers per locus for the following diversity features were calculated using PowerMarker v3.25: (i) observed alleles, (ii) alleles with a frequency ≥5%, (iii) effective alleles, (iv) the Shannon’s diversity index, (v) private alleles, (vi) locally common alleles (Freq. ≥5%) found in 25% or fewer populations, (vii) locally common alleles (Freq. ≥5%) found in 50% or fewer populations, (viii) expected heterozygosity, and (ix) unbiased expected heterozygosity. The optimal number of genetic populations (K) in the total sample was inferred by STRUCTURE 2.3.4. The STRUCTURE analysis used the admixture model, with 10 replicated runs of K = 1 to 10 after an initial burn-in of 100,000 generations followed by a run length of 1,000,000 generations. The optimal K value was identified following the method described in Evanno et al. , using SSTF, and principal components, we used GenAlEx v 6.5 software [F. commune samples  were similarly analyzed to identify their potential contributions to the total observed genetic variation. The overall relationship between geographic and genetic distances between all pairs of the 354 strains was analyzed using the nonparametric Mantel test through GenAlEx v6.5 software  [For genetic analyses between local geographic populations such as the analysis of molecular variance (AMOVA), pairwise population software . Two typstralia) .tef1α locus, we obtained a total of 354 F. commune isolates. The number of F. commune isolates from each location is shown in F. commune strains were isolated from all three types of root tissues, with 174 strains from full fibrous roots, 120 from the main root epidermis, and 60 from the main rhizome pith. The tef1α sequence of all 354 F. commune isolates have been deposited in GenBank under accession numbers MZ041792–MZ042021. tef1α sequence types and those of closely related Fusarium species based on tef1α sequences. The relationships among all 354 strains based on tef1α sequences are shown in Based on colony and microscopic morphological characteristics and DNA sequences at the F. commune, we identified a total of 2432 SSR loci belonging to the nine types of SSR. The most abundant type was single nucleotide repeats (46.6%), followed by di- (19.2%), tri- (20.4%), quad- (4.2%), penta- (3.0%), and hexa- (1.8%) nucleotide repeats. From these, we randomly chose 30 to design primer pairs to screen for potential polymorphisms using eight geographically diverse strains from our collection. Among these 30 SSR markers, seven showed 100% amplification success, an unambiguous single amplified product for each strain at each marker, and more than four alleles each among the eight tested strains  to 36 (for marker locus CM22) . TogetheThe seven SSR markers identified 158 multilocus genotypes (MLGs) among the 354 isolates . Among tF. commune causing strawberry root rot within individual local populations as well as in the total sample in southcentral China. For each of the seven SSR loci, two or more alleles were found within each of the 11 local geographic populations. In addition, private allele(s) were found within 10 of the 11 local geographic populations. The only exception was YD2, where no private allele was found while in the WL1 population a total of nine private alleles were found at the seven SSR loci. Overall, among the 11 local populations, the YD1 population had the lowest numbers of observed alleles and effective alleles, and the lowest gene diversity per locus. In contrast, the GY population had the highest number of observed alleles (7.9 per marker locus) while the YJ population had the highest number of effective alleles (4.3 per marker locus) and the highest expected heterozygosity within the population. The details about allelic richness and allelic frequency distribution patterns within each of the 11 local geographic populations are shown in F. commune analyzed here.Our analyses revealed that overall, there was considerable genetic diversity of F. commune. The lowest number of MLGs was found in the LS and YD1 populations (with 7 MLGs each) while the highest was found in the WL1 population (28 MLGs). However, the observed variation in the number of MLGs was likely due to sample size differences among the local populations because the number of MLGs was positively correlated with sample size . As described in the previous section, among the total 158 MLGs, most  were only found in one of the 11 local populations while 12 were shared between two to three local populations. Two local populations (XX and YD1) shared no MLG with other geographic populations. These two local populations were about 300 km from each other and located close to the middle of our sampled regions . Though still statistically significant (p < 0.001), after clone-correction the percentage of contribution to the total genetic variance by geographic separation was reduced to 6%  revealed that geographic separation among the 11 local populations contributed 13% to the total genetic variance while individual populations contributed 87%. Both the within- and among-population contributions to the total genetic variation were statistically significant  to 0.333 (between YD1 and XX). Here, the STF values of 0.036 and 0.333 represent the percentages (3.6% and 33.3% respectively) of the total genetic variance contributed by geographic separation between pairs of local population. Overall, based on the total sample of 354 isolates, the YD1 population showed the highest genetic differentiation from other geographic populations /2 = 55) pairwise comparisons showed statistically significant differences at an 0.001 . The paiulations . The cloulations . HoweverF. commune in southcentral China and their geographic distances from each other. Specifically, in the strain-based Mantel test, the R2 value was 0.0006 and the p value was 0.051 . Together, this result suggests no evidence of strawberry root tissue-specific specialization for strains of F. commune in southcentral China.Different from the significant geographic contributions to the genetic variation, we found no statistically significant evidence for root tissue-based genetic differences in our samples of F. commune isolates  identified strains of “F. oxysporum” causing strawberry diseases (including root rot) likely belonged to F. commune. Regardless, our results here clearly indicated that a diversity of F. commune genotypes can cause strawberry root rot.Before the name  complex . Howeverd losses ,39,40,41Fusarium species, SSR markers have been used to study the epidemiology of several plant pathogens such as F. proliferatum [F. culmorum [F. oxysporum, F. fujimorium [F. mexicanum [F. commune populations. The results showed that these seven SSR markers were highly polymorphic and together, they helped reveal the diversity and distributions of F. commune genotypes across 11 local populations in southcentral China. We note that within the seven SSR markers, aside from the nucleotide repeat number differences among alleles, single nucleotide insertions/deletions outside of the repeated regions but within our amplified DNA fragments were also present  that can easily become airborne and disperse by wind. However, if wind-aided natural dispersal were prevalent, we should expect a significant correlation between genetic distance and geographic distance among our strains. The absence of such a statistically significant correlation between genetic and geographic distances suggest that wind-aided dispersals were likely uncommon. Alternatively, human travel between regions, strawberry seedling trade, and other agricultural activities could bring strains of F. commune from one location to another. The longest-distance shared genotypes identified here between the GY and LF populations  recent shift from a saprophyte or a pathogen on other plants/crops to strawberries. Indeed, the two or more genetic clusters identified in our sample and the diverse genotypes found in most geographic populations suggest that multiple switches by F. commune have likely occurred in southcentral China to colonize and infect strawberries. Furthermore, the differential distributions of different MLGs, with some being more common and more broadly distributed than others, suggest that some of the F. commune genotypes identified here are likely more adapted to strawberries than other F. commune genotypes. Whether the frequently observed genotypes of F. commune are also more frequently found in the soil and/or in other plants at these sites remain to be investigated. In a study of Fusarium graminearum from different sources in Lithuania and Latvia, low but statistically significant genetic difference  were found between the soil population and those from living plants [F. graminearum populations from different groups of host plants or from different years. Their results suggested evidence for potential differential infectiousness/pathogenicity among strains in the soil population of F. graminearum [F. commune in their pathogenicity toward strawberries is not known. To address this question, comparable number of soil strains of F. commune from each of the 11 corresponding strawberry fields analyzed here will need to be isolated and analyzed using the same molecular markers for comparison. In addition, if differences were found, the differentially distributed alleles and genotypes of F. commune strains between these two ecological niches should be tested to confirm their potential pathogenicity differences on strawberries. Regardless, the high-frequency and broadly distributed genotypes identified in our study represent ideal materials from which to investigate the genetic bases of F. commune pathogenicity causing strawberry root rot and as priority test genotypes for developing root rot-resistant strawberries.The observed high allelic and genotypic diversities are consistent with the local populations of g plants . Howeverminearum . At presF. commune infecting each tissue type might be genetically different from the other two types. However, based on the seven SSR markers, no evidence for significant genetic difference was found among the three types of samples of F. commune based on their infecting root tissue types in southcentral China. It should be noted that our data  do not exclude the possibility that there might be genes in F. commune responsible for a certain degree of root tissue-specific trophism and pathogenesis. Interestingly, despite relatively equal efforts spent in trying to isolate F. commune from the three root tissue types, the isolation success ratio from fibrous roots, the main root epidermis, and the main rhizome pith was about 3:2:1. This ratio likely reflects the infection process of strawberry root rot where fibrous roots are likely the easiest for the pathogen to infect and grow inside, followed by the main root epidermis, and then inside the main rhizome. However, the frequent sharing of F. commune genotypes among the three root tissues and the lack of overall genetic differentiation among them are consistent with most F. commune strains and genotypes identified here being capable of infecting all three strawberry root tissues in southcentral China.Because of structural differences among the three types of root tissues in strawberries, we hypothesized that strains of F. commune causing strawberry root rot in southcentral China. Our analyses revealed high genetic diversity and significant differences among the 11 local populations of F. commune. The SSR markers developed here should help facilitate future studies on the epidemiology of strawberry root rot in other geographic regions and the relationships between F. commune populations from strawberries and other crops. Information from such studies could help identify the origins and route(s) of spread of genotypes, especially the high-frequency virulent genotypes, which in turn can help design better strategies to minimize their spread and disease impact.In summary, our study provides the first insights into the genetic diversity and population structure of


Rhanterium epapposum Oliv. is a perennial medicinal shrub growing mainly in desert habitats in the Arabian Peninsula. In western Saudi Arabia, the remaining few populations of this species are exposed to many threats, including overcutting, overgrazing, and recently, increasing human activities. These threats are predicted to be exacerbated by the advancement of aridification caused by climate change. The conservation and recovering of the diminished populations of R. epapposum necessitate measurement of their genetic diversity and genetic differentiation. To accomplish this objective, we tested 150 simple sequence repeat (SSR) primer pairs, with which 40 polymorphic loci were identified. These polymorphic loci were used to determine the population genetics of 540 plant accessions sampled from a total of 45 populations of R. epapposum located in 8 sites in western Saudi Arabia: Wadi Khurieba, Wadi Al Khamas, Gebel Al Twaal, Al Asaafer, Wadi ALHamda, Wadi Al Nassayeif, Wadi Qaraba, Wadi Kuliayah, and Wadi Dahban. Low levels of genetic diversity were found in all populations  along with a declined value of HT (0.123) and a considerable inbreeding value (F = 0.942), which confirmed a noticeable shortage of heterozygotes. High genetic differentiation among the populations and a low value of gene flow are indicative of high isolation among the R. epapposum populations, which has caused a severe deficiency in gene migration. The data obtained herein inspire several recommendations for conservation and retrieval of the existing populations, including seed banks, restoration of diminished populations, and monitoring and prevention of cutting and grazing activities at threatened sites. All of these measures are urgently required to avoid imminent extinction. Rhanterium epapposum Oliv. (Asteraceae) is a medicinal and persistent shrub growing in xeric habitats of north-western Africa and the Arabian Peninsula. R. epapposum is the only species of its genus found and disseminated throughout Saudi Arabia [i Arabia . Its drii Arabia . It alsoRhanterium epapposum populations are limited mainly to valleys, low-level plains, and medium-level mountains in western Saudi Arabia. The apparent smallness of R. epapposum populations could be due to the elevated contemporary arid environmental conditions in the region [R. epapposum and other important plant species in desert habitats such as the Arabian Peninsula.e region . Human-de region ,5, are eRhanterium epapposum plants may be subject to low genetic diversity as a result of coincided genetic drift, which is a major reason for depleted fitness and the diminished ability of some populations to adapt to environmental changes [R. epapposum is necessary to conserve and retrieve this plant species [ changes ,7,8. The species , and may species .R. epapposum, its self-incompatible mating system is considered an extra limitation affecting its persistence [The main concern for plant species with small population sizes is their ability to perform outcrossing and pursue successful reproduction in extreme arid habitats. For sistence . As a mesistence .R. epapposum, are now confronted with the threat of extinction, due to collapses in population size and the subsequent erosion of genetic diversity. For assessing genetic diversity and genetic structure, microsatellite DNA loci are considered to be among the most reliable markers; they offer a precise measure of genetic variation because of their ability to reveal variable repeat regions of the genome. They are referred to as co-dominant genetic markers [Plant populations in xeric habitats with this reproductive system are enduring threats to their survival, including deficiencies in polymorphic genes, genetic drift, and inbreeding ,14. Beca markers . Moreove markers ,16,17.R. epapposum utilizing microsatellite loci. The resulting data on the inbreeding levels within R. epapposum populations constitute necessary information for design conservation strategies. The proposed genetic analyses of this species will also support the preservation of its genetic diversity.The present study represents an insight into the distribution, genetic diversity, and genetic structure of R. epapposum were sampled from nine sites in the valleys and mountains in certain western regions of Saudi Arabia , 0.5 μL of a dNTP mix, 0.2 μL of a forward primer (including the M13-tail (10 μM)), 0.5 μL of a reverse primer (10 μM), 0.5 μL of the universal M13 primer (10 µM) labelled with a fluorophore , 0.1 μL of Taq DNA polymerase , 1.0 μL of bovine serum albumin (20 mg/mL), 1.0 μL of 10 ng/µL genomic DNA, and dH2O up to the final volume. All the PCRs were conducted as singleplex assays with a C1000 Thermal Cycler . The reactions were conducted under the following conditions: initial denaturation at 94 °C for 5 min; 50 cycles at 94 °C for 35 s, 50 cycles at 55 °C for 40 s, and 50 cycles at 72 °C for 50 s; 8 cycles at 94 °C for 30 s, 8 cycles at 53 °C for 45 s, and 8 cycles at 72 °C for 1 min; and a final extension step at 72 °C for 5 min. The fluorescently tagged PCR products were tested in multiplexes on a 3130xl Genetic Analyzer  with LIZ500  as a size standard. The Electropherograms of amplified fragments were detected using GeneMapper 4.0 , and the lengths of the amplified fragments ranged from 112 to 300 bp in accordance with Arif et al., 2010 [DNA was isolated from leaf samples collected from a total of 540 plant accessions by a DNeasy Plant Mini Kit . A total of forty-four primers were tested for polymorphisms, using published primers that were successfully designed and tested for other related species in the family Asteraceae ,19,20. Fl., 2010 .RST, corresponding to FST developed for microsatellite loci [R. epapposum populations was assessed by AMOVA (999 permutations))[Nm) was determined by the private allele method [Ho), the expected heterozygosity (He) under Hardy–Weinberg equilibrium, and Wright’s fixation index (F = 1−Ho/He) were evaluated for each locus in each population to test deviations from the Hardy–Weinberg equilibrium, which determines inbreeding. UPGMA dendrogram and principal component analysis (PCA) were implemented using PAST 4.02 [He), heterozygosity (Ho), and percentage of polymorphic loci (P).The measurement of the parameters of genetic diversity, genetic structure, and inbreeding was conducted using GenAlEx 6.1 . The genite loci . The gentations)),25. The e method . The estAST 4.02  based onR. epapposum, as the average fixation index (F) was equal to 0.587, confirming an explicit deficit of heterozygotes  ranged between 1.75 (Wkhb 1 population) and 1.225 (Wdah 2 population). The means of the number of effective alleles per locus (eN), Shannon index (I), and expected heterozygosity (eH) varied from 1.492, 0.369, and 0.229 in the Wkhb1 population, respectively, to 1.108, 0.085, and 0. 0.047 in the Wdah 2 population, respectively (HT) for all the loci and populations was 0.123.The mean number of alleles per locus . The highest genetic differentiation occurred between the populations , whereas the lowest value  was detected among individuals within the populations.This finding confirmed the UPGMA cluster analysis, e.g., resemblance existed between PCA-I and first cluster C.A. The AMOVA revealed considerable genetic differentiation among the studied R. epapposum, all the genetic diversity parameters revealed a modest to severe decline in values among all the remaining populations studied, in accordance with other studies on the same species growing in arid habitats of Kuwait [In the current analysis of the molecular genetics of f Kuwait . Moreovef Kuwait ,29,30,31R. epapposum populations are vulnerable to severe genetic drift and inbreeding, which worsens the problem of the polymorphic allele loss due to the ambient environmental circumstances [The main reasons behind the modest to severe decline in genetic diversity of these populations may be due to their low population size. As a result of the limited population size, the existing mstances ,33,34.The pattern of genetic diversity distribution among the studied locations showed substantial variability, with a relatively moderate polymorphism determined in the populations of Wadi Khurieba, Gebel Al Twaal, Wadi Qaraba, and Wadi Al Khamas, which could be explained by the relative abundance of water reserves in these regions. Wadi Khurieba is situated to the south of Bany Ayoub Mountain, where many water aggregations are available from frequent inundations of rain in this site. The small gorges in Gebel Al Twaal (700–900 m a.s.l) permit the growth of plant populations, as they have access to more water. Wadi Qaraba and Wadi Al Khamas are low-level valleys with more water reserves, permitting the growth of many plant populations. Al-Gharaibeh et al. 2017  mentioneThe PCA confirmed the relationship between the proportion of genetic diversity and the availability of water resources. The populations with higher polymorphisms were grouped in the PCA-I group, which included populations from Wadi Khurieba, Gebel Al Twaal, and Wadi Qaraba.The high inter-population genetic differentiation values obtained by AMOVA analysis is inferred as relating to the high isolation among the studied sites. The main factors leading to this isolation can be summarized in terms of local human activities, including overcutting and severe overgrazing by camels and sheep, which increases during spring time, as these herds are transported by their owners from drier regions during this season . MoreoveR. epapposum flowers, as it has a negative effect on pollination and will thus likely increase the possibility of selfing [Greater declines in existing population size and further isolation are expected with co-occurring higher temperatures and drier conditions, which are evident in the decreasing frequency of rain in these regions ,5. Moreo selfing .R. epapposum fruit of the achene type, with its membranous cover, facilitate its dispersal over long distances, a noticeably low level of gene migration among existing populations in the current study suggests that the extensive anthropogenic and climatic causes of isolation have contributed to elevating the value of genetic differentiation among the studied populations. This is confirmed by the population divergence, as shown in the UPGMA dendrogram [Despite the fact that the morphology and size of the ndrogram ,39.R. epapposum.The values revealed in the gene flow assessment fell short of the values necessary for stopping the increase in genetic drift . The joiR. epapposum in habitats of western Saudi Arabia, and was conducted in order to help manage conservation actions to protect this valuable medicinal species. The species faces imminent extinction due to a severe decline in gene polymorphism coupled with high inter-population genetic differentiation and considerable inbreeding.Our current research represents a first assessment of the genetic diversity and genetic structure of R. epapposum should be primarily based on decreasing the degradation and deterioration of its current habitats. Many actions can be taken in this regard, including the following. Firstly, wire-fenced enclosures around the populations severely affected by low genetic polymorphism can be established [The long-term plan for the conservation of ablished , as idenR. epapposum seeds from all the remaining populations [Thirdly, the evident decline in genetic diversity and the high genetic differentiation in these populations support the idea that they could be restored by collection and preservation of ulations .R. epapposum recuperation programmes, in which the seeds would be planted in nurseries and the well-developed seedlings would then be reintroduced into highly threatened populations. The seedlings would be reintroduced into habitats resembling those of their parent populations in order to reduce potential ramifications, including further inbreeding and severe decreases in gene flow. Some of the collected healthy seeds should be protected using appropriate seed-maintenance protocols in special test banks; these would be valuable for future efforts to conserve R. epapposum in its original habitats.The collected seeds would primarily be involved in