Zanthoxylum (Sichuan pepper), with its rich cultivars, has long been widely cultivated in China for its unique seasoning and medicinal uses, but most of its cultivars have similar morphological characteristics. Therefore, we hypothesized that the genetic diversity of Zanthoxylum cultivars is low because of their apomixis and long cultivation history. In this study, we aimed to investigate the genetic diversity of three Zanthoxylum species on the cultivar level based on express sequence tag–simple sequence repeat (EST-SSR) primers. In total, 121 samples of three Zanthoxylum species  were collected from different areas in China for genetic diversity analysis. A total of six specificity and polymorphism EST-SSR primers, which we selected from among 120 primers based on two transcriptomes  in our earlier study, were used to evaluate genetic diversity based on capillary electrophoresis technology. The results of our analysis using the unweighted pair group method with arithmetic mean (UPGMA) indicated that most of the samples are clustered in one clade in the UPGMA dendrogram, and the average genetic distance was 0.6409. Principal component analysis (PCA) showed that Z. piperitum may have a closer genetic relationship with Z. bungeanum than with Z. armatum. An analysis of molecular variation (AMOVA) showed that the genetic variation mainly stemmed from individuals within populations; the genetic differentiation coefficient (PhiPT) was 0.429, the gene flow (Nm) between populations was 0.333, and the differences among populations were not significant (p > 0.001). For the intraspecific populations of ZB, the percentage of genetic variation was 53% among populations and 47% within populations, with non-significant differences between populations (p > 0.001). The genetic differentiation coefficient (PhiT) was 0.529, and the gene flow (Nm) was 0.223. For the intraspecific populations of ZA, the results indicated that the percentage of genetic variation was 29% among populations and 71% within populations, with non-significant differences between populations (p > 0.001); the genetic differentiation coefficient (PhiPT) was 0.293, and the gene flow (Nm) was 0.223. Through genetic structure analysis (GSA), we predicted that these 121 samples belonged to two optimal subgroups, which means that all the samples probably originated from two gene pools. Above all, this indicated that the genetic diversity of the 121 Zanthoxylum samples was relatively low at both the species and cultivar levels, a finding which was consistent with our initial assumptions. This study provides a reference, with molecular-level data, for the further identification of Zanthoxylum species. Zanthoxylum (family Rutaceae), which includes a wide variety of shrubs and trees. To date, more than 250 species of Zanthoxylum have been identified, most of which are distributed in tropical and subtropical Oceania, Africa, and Asia . The genetic distances of the 121 samples used in this study ranged from 0 to 2.3811, with a mean of 0.6409. From an interspecies perspective, the average genetic distance between ZB and ZA was 0.7856, that between ZB and ZP was 0.8147, and that between ZA and ZP was 1.8888. Within a species, the average genetic distance was 0.5104 for all the ZB samples, 0.2333 for all the ZA samples, and 0.6481 for all the ZP samples. The genetic distances of some samples were even 0, especially for the ZA-TJ series. These data indicated that the genetic diversity of the Zanthoxylum samples in this study was not high, and the genetic differentiation of the intraspecific cultivars was relatively low, indicating that EST-SSR did not significantly discriminate between cultivars. All the ZP samples and several ZB samples , ZB-LWHJ(STI)-1, ZB-HYDHP(STi) and ZB-(JLHJ)) were clustered close together, even within one branch, and the average genetic distance between the ZB and ZP samples was 0.8147, whereas that between the ZA and ZP samples was 1.1888. This indicated that ZP and ZB may have closer kinship with each other than with ZA, respectively.As shown in As shown in Zanthoxylum in this study was 43% and 57%, respectively, and the differences among populations were not significant (p > 0.001). Furthermore, the genetic differentiation coefficient (PhiPT) was 0.429, and the gene flow between populations (Nm) was 0.333. For the intraspecific populations of ZB, the AMOVA showed that the percentage of genetic variation was 53% among populations and 47% within populations, with non-significant differences between populations (p > 0.001). The genetic differentiation coefficient (PhiT) was 0.529, and the gene flow (Nm) was 0.223. For the intraspecific populations of ZA, the results indicated that the percentage of genetic variation was 29% among populations and 71% within populations, with non-significant differences between populations (p > 0.001), that the genetic differentiation coefficient (PhiPT) was 0.293, and the gene flow (Nm) was 0.223. The percentage of genetic variation within populations was 71%, the difference between populations was highly insignificant (p > 0.001), the genetic differentiation coefficient (PhiPT) was 0.293, and the gene flow (Nm) was 0.605. Overall, the genetic variation of the Zanthoxylum populations in this study originated mainly within populations rather than among populations, and the interspecific gene flows and intraspecific gene flows were not high.As shown in As shown in Prunus armeniaca [Apiaceae [Piperaceae [Citrus [Camellia sinensis [Zanthoxylum are economically important trees in China [Z. bungeanum and Z. armatum using the Illumina-Hiseq sequencing platform, which provided a good basis for the screening of EST-SSR markers and the detection of genetic diversity [Zanthoxylum. Zhao et al. [Z. piperitum based on its transcriptome. Meanwhile, Feng et al. [Z. bungeanum. In addition, Fei et al. [Z. bungeanum using an miRNA-based technique. However, the majority of previous studies only focused on one species, with no comparisons being performed. On the interspecies level, numerous published studies have proved that EST-SSRs have shown accurate and clear results with respect to the identity and genetic diversity of crop plants, such as Triticum [Hordeum vulgare [Citrus [Zanthoxylum [Zanthoxylum species showed significant availability and polymorphism for the three Zanthoxylum species samples, though it seemed that they were not able to definitively identify cultivars of Zanthoxylum clearly, suggesting that this technique may be more appropriate for species-level identification than cultivar-level identification. Additionally, the polymorphism for Z. piperitum was not as good as that for Z. bungeanum and Z. armatum. One possible reason is that there were no EST-SSR primers from Z. piperitum; another is that the number of samples was probably too low.Different kinds of molecular markers are now universally used to analyze genetic diversity for many species rapidly and efficiently. Examples include SSR in grape ,47, chicrmeniaca ; RAPD inrmeniaca , ApiaceaApiaceae  and Pipeperaceae ; And CAP [Citrus , cotton  [Citrus  and Camesinensis . Althougin China , relativin China . In our iversity . The beniversity . These po et al.  reportedg et al.  employedi et al.  investigTriticum , Hordeum vulgare  and Citr [Citrus . On the thoxylum . In thisZanthoxylum genus. Among the different analytical methods used in this study, the K-value analysis of the genetic structure, in particular, showed that the most suitable subgroup number for these samples was two. This indicated that the genetic diversity of the Zanthoxylum genus is not high. This finding may be attributed to several reasons. First, although the total number of samples in this study was large, many of the samples were cultivars. Second, only six primer pairs were used in this study, and while it was possible to clearly identify three Zanthoxylum species, the identification of intraspecific cultivars was relatively difficult, which indicated that the ability of the EST-SSR primers to identify intraspecific cultivars was somewhat limited. Third, the genus Zanthoxylum has a mainly reproductive mode of apomixis and thus has a stable phenotype [In the present study, 121 samples were shown to belong to three species of the henotype ,14. AbovZ. bungeanum, Z. armatum and Z. piperitum based on previously reported research , a sample with only male flowers, did not show any significant differences from the rest of the samples in terms of clustering, PCA or genetic structure, probably because only one sample was analyzed. Three samples of ZB-HCDHP (Irr) were irradiated, and the clustering results revealed that these three samples did not show any significant differences when compared with the other samples. In addition, there was no genetic difference between the three samples. Furthermore, the PCA and GSA results revealed that these three samples showed no distinctive results. Irradiation mutation breeding is an approach used to induce gene mutations, promote gene recombination and improve the recombination rate ,66,67. NZ. armatum samples, whereas the ZA-TJs were a Z. armatum cultivar. The genetic distance results and dendrogram demonstrated that these two types of samples were relatively genetically remote, indicating that the wild Z. armatum type and the cultivars used in this study differed to some extent. Meanwhile, the clustering, PCA and GSA results revealed that all the ZA-TJ samples showed an extremely close genetic relationship; the genetic distances of some samples were almost 0, indicating the very limited genetic differentiation of the cultivar. This may be because the ZA-TJ samples collected in this study were derived from Sichuan Province, where the sampling was performed within a small area. Thus, based on the genetic distance results, Zanthoxylum’s apomixis and the small sampling areas, it is likely that the samples may have originated from a single gene pool.The ZA-Ws were wild Zanthoxylum genus, interspecies variation accounted for 43% of the total variation, and intraspecies variation accounted for 57%, indicating that the population variation in the three Zanthoxylum samples in this study mainly originated from within the populations. Specifically, 53% of the inter-population variation was accounted for in ZB, suggesting that this variation mainly originated from among populations, which may be due to the fact that a larger number of ZB samples were collected in the present study and that the collection was performed using a wide range of regional sources. The genetic differentiation coefficient (PhiPT) and gene flow (Nm) are important indicators for analyzing the genetic structure of populations. According to Wright et al. (1990), if the genetic differentiation coefficient (PhiPT) ranges from 0 to 0.05, this indicates that no differentiation exists between populations; if it is 0.05–0.15, this indicates that there is moderate differentiation between populations; and if it is 0.15–0.25, this indicates high differentiation. If the PhiPT is greater than 0.25, this indicates extremely differentiated populations [Zanthoxylum species and also between the intraspecific populations in the current study. Ellstrand et al. suggested that the proportion of genetic variation among populations of asexual plants increases greatly when there are large barriers to gene flow among the populations [Zanthoxylum species reproduce via apomixis, similar to asexual lineages; thus, it is reasonable to infer that the variation among populations is relatively large. According to Buso et al.’s research, a gene flow (Nm) > 1 results in a high degree of gene exchange and that of 0.250 < Nm < 0.999 results in a moderate degree of gene exchange [Nm) values in this experiment were beyond 1; therefore, the degree of gene exchange was not high, probably because of the apomixis reproduction.AMOVA is an important tool for studying genetic diversity among the populations of species. In this study, for the entire ulations . Accordiulations . Most ofexchange . None ofZanthoxylum market in China mostly consists of ZB and ZA species. Due to the different climatic conditions in China, Z. bungeanum is cultivated in the north and Z. armatum is cultivated in the south [Z. bungeanum, Z. armatum and their cultivars are the main types of Sichuan pepper commercially grown in China, it is vital to make considerable efforts to maintain the diversity of Zanthoxylum with respect to characteristics such as its aroma, stinglessness and pungency.The he south . TherefoZanthoxylum species, with 121 samples, using capillary electrophoresis technology. According to the UPGMA and PCA, the 121 samples were divided into three clades, and Z. piperitum and Z. bungeanum were more closely related to each other than either was to Z. armatum. On the basis of STRUCTURE, all the samples probably originated from two gene pools. Additionally, the AMOVA indicated that the differences among interspecies and intraspecies populations were not significant. Above all, the Zanthoxylum samples examined in this study showed relatively low genetic diversity at the cultivar level, which was consistent with our initial assumptions. However, we found that the EST-SSR primers can distinguish between the different species of Zanthoxylum but cannot clearly identify large numbers of cultivars; this topic requires further research. This study provides a reference, with molecular-level data, for further examination of the identity of Zanthoxylum.In this research, we used six EST-SSR primers to detect the genetic diversity of three


Local adaptations to the environment are an important aspect of the diversity of a species and their discovery, description and quantification has important implications for the fields of taxonomy, evolutionary and conservation biology. In this study, we scan genomes from several populations across the distributional range of the Eurasian lynx, with the objective of finding genomic windows under positive selection which may underlie local adaptations to different environments. A total of 394 genomic windows are found to be associated to local environmental conditions, and they are enriched for genes involved in metabolism, behaviour, synaptic organization and neural development. Adaptive genetic structure, reconstructed from SNPs in candidate windows, is considerably different than the neutral genetic structure of the species. A widespread adaptively homogeneous group is recovered occupying areas of harsher snow and temperature climatic conditions in the north‐western, central and eastern parts of the distribution. Adaptively divergent populations are recovered in the westernmost part of the range, especially within the Baltic population, but also predicted for different patches in the western and southern part of the range, associated with different snow and temperature regimes. Adaptive differentiation driven by climate does not correlate much with the subspecies taxonomic delimitations, suggesting that subspecific divergences are mostly driven by neutral processes of genetic drift and gene flow. Our results will aid the selection of source populations for assisted gene flow or genetic rescue programs by identifying what climatic patterns to look for as predictors of pre‐adaptation of individuals. Particularly, the Carpathian population is confirmed as the best source of individuals for the genetic rescue of the endangered, isolated and genetically eroded Balkan population. Additionally, reintroductions in central and western Europe, currently based mostly on Carpathian lynxes, could consider the Baltic population as an additional source to increase adaptive variation and likely improve adaptation to their milder climate. Although according to the IUCN the global status of this felid is Least Concern and most populations are stable, the status and trends vary greatly within its European range, with some populations being classified as endangered, while the status of Asian populations remain poorly known , one in the Northwest (L. l. lynx) and one in the Southern part of the distribution (L. l. dinniki). Another divergent mitogenomic lineage was suggested to occur in China (L. l. isabellinus) pending on nuclear corroboration , and sequencing reads were trimmed using the software trimmomatic 0.38 , until the variance explained by the full model including all the environmental predictors is reached or a permutation‐based significance test does not reach the desired significance threshold. We implemented this using the functions rda and ordiR2step of the package “vegan”  exceeded 0.85 with any other variable, keeping in the analysis the variable with highest adjusted r2 contribution to the RDA model.In order to select which of the WorldClim environmental predictors had the strongest effect on the genetic variance observed in lynx populations, we implemented a predictive approach based on forward selection using redundancy analysis (RDA), as described by Capblancq and Forester . Briefly2.3.3The relative contribution of three different components, geographic location (I), environmental conditions (II) and neutral genetic structure (III), to the overall genetic variation in Eurasian lynx was explored using an approach based on partial RDA (pRDA). The three components were represented by three sets of variables: (I) x and y coordinates for geographic location, (II) the selected environmental predictors for environmental conditions, and (III) the principal components selected using a broken stick model of a genetic PCA run with a set of neutral SNPs. To construct the neutral dataset we extracted the SNPs belonging to intergenic regions  from ou2.4To identify regions of the genome involved in local adaptation to the environment, we conducted genome‐environment association (GEA) tests. With the aim of improving the true discovery rate, we integrated a multivariate GEA analysis using all of selected environmental predictors at the same time, with multiple GEA analyses considering each individual predictor separately , a method that extracts and summarizes the variation in a set of response variables that can be explained by a set of explanatory variables, using the SNPs in our final‐set VCF as the response variables and the selected environmental predictors as the explanatory variables. To avoid possible confounding factors introduced by the effects of neutral genetic relationships among populations and based on the observed correlations between genetic structure and geographic location Figure , we opte2.4.2GEA tests for each of the selected environmental variables were carried out using the software BayPass v2.1 Gautier, . This sosplineAnalyze was run to calculate window boundaries and Wstat along each chromosome, and to correct for the whole‐genome mean and variance of BF values, with a resolution of 10 kbp in spline calculation and generalized cross validation. Windows with a Wstat value exceeding the 99th percentile of the overall distribution were considered as outliers and thus candidate selected regions.Signals of association with a particular environmental predictor shown by adjacent markers were combined in genomic windows using the R package “GenWin”  from ou2.5L. canadensis reference genome annotation  over‐ and under‐representations are reported.To explore what biological functions were associated to the genes with candidate SNPs, we used the PANTHER classification system . GDM is a distance based method that tries to estimate how a response variable  changes between sites because of the effect of a set of explanatory variables , by identifying which environmental gradient explains most of the biological variation, and determining where along the gradient the turnover is slower or faster , and lowest contribution to the variance explained by the RDA model  when compared to the average snow depth during the month of January (r2 = 0.165).A total of five environmental predictors were selected by the forward model building approach Table , Mean Tel Figure . As the The first two principal components of the neutral PCA were selected by the broken stick model to represent neutral genetic structure in the pRDAs Figure . The ana3.2A total of 2,100,553 autosomal SNPs passed our stringent filtering criteria and were used as input for genomic scans of selection. This set had a total genotype calling rate of 99.76%, with per‐sample genotype missing rates not exceeding 0.1%. These were pruned into a non‐correlated set of 966,029 SNPs with no missing data for multivariate RDA and into 50 independent datasets for the univariate BayPass analyses.r2 = 0.11) resulted in two significant RDA axes, which together accounted for over 60% of the constrained variance in the model  as a response to geographic location and different environmental predictors Figure . The perIn sharp contrast to neutral variation, the turnover of adaptive genetic composition is greatly influenced by two environmental predictors, T_range_day and Mean_snow_days, with 60.35% and 32.77% of the overall importance respectively Figure . Through4In this study, we examined range‐wide patterns of adaptive differentiation driven by environmental conditions across the distributional range of the Eurasian lynx. Loci potentially involved in local adaptation were identified through their association with environmental predictors. We assessed how local adaptation in Eurasian lynx populations affects global genetic structure of this large carnivore species by describing the way neutral and adaptive genetic differentiation patterns differ, and by estimating both the magnitude and the direction of these changes. We also described how genetic composition is expected to change throughout the species' range in response to geographic distance and environmental factors. By analyzing the changes in adaptive genetic compositions across the distributional range of the species we discovered areas of expected strong adaptive divergence driven by specific environmental conditions. We also identified the biological processes that were the main targets of this adaptive differentiation as those overrepresented among the genes with variation associated to environmental variables.4.1The genetic structure reconstructed with candidate adaptive loci was substantially different to that reconstructed with neutral ones. The three main clades recovered in the neutral genome, that divide Eurasian lynx populations in three main lineages  and the ranges in mean diurnal temperature (T_range_day). Low values of both variables are expected to determine the genetic composition of lynx inhabiting the Latvian Courland Peninsula, while higher Mean_snow_days characterize the rest of the Latvia population and higher T_range_day influences the genetic composition of NE‐Poland. The high adaptive differentiation observed in these populations and the distinctive environmental conditions they are subjected to suggest an ongoing process of adaptive differentiation in the regions occupied by these populations. This contrasts with what is observed when looking at the neutral genome, where individuals from Latvia and NE‐Poland are relatively closer to other members of what is known as the European lowland or Baltic lynx populations, which also includes members of the Western‐Russia populations of Kirov and Urals  and the mean number of days with snow cover throughout the year (Mean_snow_days) appear to have the strongest effects on adaptive genetic variation of Eurasian lynx populations, indicating that these environmental variables – or others closely correlated with these (see below) – might be important factors for the biology and evolution of this species.Apart from its previously reported correlations with skull morphology and diet (Yom‐Tov et al., The identification of Mean_snow_days and T_range_day as the most important variables in shaping adaptive genetic composition should be taken with a grain of salt, as it might be the result of an indirect correlation. Other climatic or ecological variables correlated to these two might be the actual causal factors, and the effect we observe here could be a byproduct of their correlation. In particular, local adaptations in response to T_range_day might be associated with specific mechanisms that determine how Eurasian lynx directly cope with temperature fluctuations. On the other hand, T_range_day might represent a proxy of ecological environments, as diurnal ranges in temperature have been linked to forest structure heterogeneity (Ehbrecht et al., With the data at hand, precise descriptions of the mechanisms by which the genes involved in local adaptation directly affect the fitness of Eurasian lynx cannot be made. Our results suggest that four main categories of biological functions are carried out by the genes involved in local adaptation to the environment: metabolic processing of proteins and sugars by O‐glycosylation, locomotory and general behavior, synaptic regulation and organization, and nervous system development. O‐linked glycosylation is a type of protein glycosylation that adds sugar molecules to specific serine or threonine residues on proteins. This modification can have a very wide range of effects on a number of different biological processes, by influencing protein conformation and expression, by regulating processes mediated by the organisms molecular interaction events, such as fertilization or immune responses, and by modulating the activity of signaling molecules such as hormones (Hounsell et al., 4.3L. l. lynx in the west, L. l. wrangeli in the east, and L. l. dinniki in the Caucasian mountains, revealed by the neutral genome (Bazzicalupo et al., L. l. balcanicus from the Balkans and L. l. carpathicus from the Carpathian Mountains, we detect some differentiation at adaptive variants, which occurs however along less important axis of adaptive differentiation and is much weaker than that observed with neutral variants. It is thus likely that genetic drift might have affected allele frequencies in these otherwise selected variants (Bazzicalupo et al., The neutral variation observed in the Eurasian lynx and the adaptive variation described in this study are not similar in the way they differentiate among populations and subspecific clades. The divergent groups corresponding to the subspecies of L. l. lynx.The strongest signals of adaptive divergence driven by the environment were observed in the populations in Latvia and NE‐Poland, which seem to be locally adapted to different snow conditions and diurnal temperature fluctuations, experiencing a relatively mild climate when compared, for example, to northern Scandinavia or the mountainous ridges of the Carpathians and the Caucasus. However, without additional support from phenotypic and ecological data, we advise against using this evidence to classify Baltic populations as a novel subspecies separate from L. l. lynx subspecies, we were able to identify at least two possibly distinct adaptive units. One of them is adapted to harsher conditions of high snow and temperature fluctuations, which is widely distributed in areas of Western‐Russia and Scandinavia, and the other is adapted to the milder climatic conditions of European lowlands. Conservation and restoration programs might want to take these two adaptive units into consideration when selecting potential sources for reintroduction or reinforcement. In particular, reintroductions in western Europe, currently based mostly on Carpathian lynx (Mueller et al., L. l. balcanicus, whose adaptive differentiation observed in this study is hard to disentangle from the neutral divergence caused by intense genetic drift and prolonged low effective population sizes. Our previous assessment of the Carpathian population as representing the best source of individuals for genetic rescue of this highly endangered population, based on its closest relationship in neutral autosomal variation (Bazzicalupo et al., Apart from taxonomic inferences, understanding how adaptive variation shapes the relationships between different populations of Eurasian lynx can assist the identification of evolutionary significant units (ESUs; Funk et al., Our results are also relevant for evaluating the long‐term effects of climate change on the Eurasian lynx distribution. The two environmental variables identified as drivers of adaptive divergence are likely to alter their geographical distribution in the near future due to climate change, so associated variants may also expand and contribute to species resilience and persistence. In other species, the occurrence of adaptive responses to environmental pressures has been shown to reduce range loss projections under future climatic conditions (Razgour et al., The authors declare no conflicts of interest.Appendix S1.Click here for additional data file.


Cypripedium macranthos is one of the few wild orchids with high ornamental value in northern China. However, over the past decade, excessive collection, trading, tourism development, habitat fragmentation, deceptive pollination, and seed germination difficulties have all caused a sharp decline in the number of C. macranthos individuals and its population. In order to propose a scientific and effective conservation strategy, the genetic diversity, genetic structure and gene flow of the current CM population are urgent scientific issues to be clarified.Genetic diversity, genetic structure, and gene flow in plant populations and their influencing factors are important in conservation biology. C. macranthos from north and northeast China were analyzed to evaluate the genetic diversity, gene flow among populations, and genetic structure by genotyping-by-sequencing. More than 68.44 Gb high-quality clean reads and 41,154 SNPs were obtained. Our data based on bioinformatics methods revealed that C. macranthos has lower genetic diversity, high levels of historical gene flow, and moderate-to-high genetic differentiation between populations. The gene migration model revealed that the direction of gene flow was mainly from northeast populations to north populations in China. The results of genetic structure analysis showed that 11 C. macranthos populations can be considered as two groups, and further divided into four subgroups. Moreover, the Mantel test detected no significant “Isolation by Distance” between populations.Here, 99 individuals of C. macranthos populations were mainly caused by biological characteristics, human interference, habitat fragmentation, and restricted gene flow. Finally, constructive measures, which can provide a basis for the proposal of conservation strategies, have been suggested.Our study demonstrates that the present genetic diversity and genetic structure of  The genetic diversity of a species or population is the product of long-term evolution and the premise of its survival and adaptation. The higher the level of genetic diversity of a species, the richer the genetic variation, and the stronger the ability of adapting to different environments. On the one hand, many species may have different levels of genetic diversity and variation to adapt to different environments. On the other hand, habitat fragmentation caused by environmental change or human interference may lead to geographical isolation of natural populations, population degradation, decrease in gene flow, and eventually the loss of genetic diversity and the increase in inbreeding . The difex situ conservation [To formulate scientific and effective conservation strategies and measures for endangered species, it is necessary to understand its genetic diversity, spatial distribution, and relationship with environmental factors, and establish conservation units or select populations with high genetic diversity for in situ or ervation –15.Previous studies of genetic diversity, population genetics, and gene flow mainly used conventional molecular markers . However, on the one hand, few loci can be detected by conventional molecular markers, thus, there are some limitations in explaining geographical differentiation and genetic variation in populations, particularly of rare species. On the other hand, developing molecular markers have many steps and is tedious, time-consuming, and laborious. Excitingly, the rapid development of second and third generation sequencing technology, which comes at a lower cost with higher efficiency, provides researchers with more genetic and genomic datasets compared with traditional methods. In addition, a large number of loci that are evenly distributed throughout the genome can be screened. Therefore, using these datasets to analyze population genetic diversity, genetic structure, and gene flow may improve accuracy and resolution . As one Cypripedium macranthos (CM) belongs to the genus Cypripedium (Orchidaceae). The global distribution is only in Russia [Cypripedium has evolved into a pouch shaped like a slipper; thus, these orchids are often called slipper orchids or lady’s slipper orchids [n Russia , China [n Russia , Japan [n Russia , and then Russia . CM has  orchids . CM is o orchids . Therefo orchids , 28, mos orchids , morphol orchids , reprodu orchids , symbiot orchids , and see orchids .To understand the genetic variation, population structure, and gene flow in CM, and to identify the core population of genetic diversity and propose more accurate conservation strategies, we obtained SNPs of six populations from north China and five populations from northeast China by the GBS method, which can detect a large number of whole genome SNPs. The analysis of SNP characteristics in these different populations provided an insight into the genetic diversity, genetic structure, and gene flow in CM populations under biological barriers (pollinator feeding range and seed germination difficulties) and geographical barriers (Yanshan Mountains and Bohai Sea). Furthermore, we discuss factors that possibly contribute to the genetic diversity and biogeographical pattern of CM populations. Moreover, we assessed the correlation between genetic and geographic distances of CM populations using isolation by distance (IBD) models. Finally, we put forward some suggestions for CM conservation management.Illumina Hiseq Xten PE150 platform was used to sequenced the remaining 99 samples, and 68.44 Gb of data were obtained, with 468,849,522 reads, average reads per accession was 4,735,853.7, average sequencing depth of all samples was 23.2×, and Q20 value of each sample was above 95.5%. By SNP calling and rigorous screening  ≥ 0.01, read depth (DP) ≥ 4), 41,154 SNPs were obtained from data of all samples. Several main indices of genetic diversity were calculated, and 99 individuals were analyzed, as can be seen from the following indices, the overall level of genetic diversity of CM was low, and the effective number of alleles (Ae) varied from 1.0208 to 2.0000 and average was 1.2342, expected heterozygosity (He) ranged from 0.0204 to 0.5000 with an average of 0.1534, and the extent of observed heterozygosity (Ho) ranged from 0.0000 to 1.0000 and average was 0.1335, the polymorphism information content (PIC) values varied from 0.0202 to 0.3750 with an average of 0.1296, and the nucleotide diversity (Pi) varied from 0.0205 to 0.5031 with an average of 0.1543  of all the other populations were positive, and that of BHS population was the highest (Fis = 0.0774). In northeast China, two populations were positive , and three populations were negative , indicating that inbreeding occurred in most populations in North China. In the Northeast China, both inbreeding and outbreeding occurred.To understand the relationship between CM populations and visualize their genetic distance, a phylogenetic tree was constructed based on 41,154 SNPs  was performed based on SNPs obtained from all 99 CM individuals Fig. . PCA shoTo complement the PCA and phylogenetic tree analysis and better understand the population structure, an admixture analyses was performed to evaluate the population structure of 99 CM samples Fig. . UsuallyCorresponding to the results of the phylogenetic tree and genetic structure analyses, strong gene flow (Nm) and moderate-to-high levels of genetic differentiation were detected between population pairwise comparisons Table . The genTreemix software was used to estimate historical gene flow and determine its direction. The main direction of gene flow was from northeast China populations to north China populations, and between north China populations Fig. . Such ge2 = 0.1506, P (rxy-rand ≥ rxy-data) = 0.010) , the population of North China , this indicated that IBD was detected in the North China population to a certain extent, which corresponded to the distribution pattern of the North China population.A Mantel test was run on all samples to evaluate the effect of geographic distance on population genetic distance. No significant correlation was observed between genetic and geographic distances for the 11 CM populations  [Cypripedium flavum  [Cypripedium tibeticum  [Cypripedium kentuckiense  [Based on our experimental data, we found some evidence of genetic diversity in CM, several major indices of genetic diversity  indicated that the genetic diversity of 99 CM was lower than that of Korea and Japan, Ho and He were 0.140 and 0.185 in Korea and 0.163 and 0.187 in Japan, respectively , 28. Com= 0.572) , Cypripe= 0.288) , Cypripe± 0.119) , Cypripe= 0.522) . Several= 0.522) . MoreoveOrchis purpurea, another plant in the orchid family [Each population was analyzed separately, and the BHS population of CM had the highest level of genetic diversity among all populations. This population is located in the Baihuashan National Nature Reserve, which was established in 1985. The number of conserved CM individuals was higher than the other five north China populations. In addition, based on the natural global distribution of CM and its preference for cold climate, the BHS population may be the population that CM spread from north to south and settled down in North China in history, and developed a local CM diversity center. In contrast, the XAS population is located at the Xing’an Temple scenic spot in the center of Yichun city, which is surrounded by the Yichun River and several national roads, forming a geographical barrier. Therefore, the low level of genetic diversity of this population was mainly caused by human interference and the gene flow barrier. Unexpectedly, although SLS population was the smallest population with only three individuals, it was not the lowest in genetic diversity. Considering that this population was located only 21.3 km away from the BHS population, both SLS and BHS populations may have belonged to the same large population historically, SLS populations were split out due to interference from human activities, historical events, and the reproductive characteristics of CM. Thus, it still retains some genetic information of the original large population. Similar results were found not only in the CM population in South Korea , but alsd family . In addiFrom the perspective of large-scale geographical scope, the genetic structure analysis, PCA, and phylogenetic tree analysis showed that CM was divided into two groups. The first group consisted of six populations from north China and the second group included five populations from northeast China. These results were consistent with the geographical distribution of CM populations; these populations of north and northeast China were more than 1,000 km apart, separated by the Yanshan Mountains, the Qilaotu Mountains, and the Bohai Sea. On a finer scale, the north China populations were divided into three subgroups. Based on the geographical distribution pattern, these populations were isolated from each other and were scattered in several high mountains. Therefore, substructures were detected in all samples from north China. The distribution pattern of northeast China populations was different. Except for the PDS population, the distribution of most northeast China populations was in plain and hilly areas, and the gene flow barrier was small, especially the individuals of the XAS, HLHZ_HLHC, and JSTZB_JSTZ populations showed obvious genetic admixtures. Thus, the northeast China populations showed up as a whole. Interestingly, 16 samples of the YWS population were divided into different subgroups, suggesting that this population was formed as a result of the intermixing of several ancestors. On the whole, these results of the population structure were similar to those of the PCA and phylogenetic tree analysis, in which although there was some degree of admixture, all the samples still showed a distinct genetic structure.Cypripedium [We calculated genetic differentiation and gene flow among populations, and the levels of genetic differentiation were significantly different among populations, with high genetic differentiation among populations across regions. Based on the classification of genetic differentiation levels by Wright , moderatripedium . Althougripedium , the intripedium , 55. Genripedium , for exaripedium . In addiripedium , 58. TheWe evaluated the direction of gene flow using Treemix software. Our data indicated that the direction of historical gene flow was mainly from northeast China populations to north China populations. It implied that the north China populations were formed by the gradual migration and settlement of northeast populations by seed-mediated gene flow, which is consistent with the dominant distribution of CM and its preference for cold climates. In the resource survey, northeast China populations were widely distributed, ranging from the plain at 200 m above sea level to the Greater Khingan Mountains at more than 1,200 m above sea level, whereas the north China populations were only distributed in the subalpine meadows of several mountains. In addition, the petals of CM individuals in northeast China were purplish red, pure white, and light pink, and individuals with rich color variations in their petals have also been found in the Russian Far East and in Rebun Island, Japan , 25. How2 = 0.3117, P = 0.010), this result corresponds to the pattern of North China populations distributed independently in several high mountains, and inbreeding occurred in most populations. Therefore, more attention should be paid to the population in North China. On the whole, external factors  and internal factors (deceptive pollination and low seed germination rate) have accelerated the rapid decline in CM population size and distribution area in the past, weakened or even hindered recent gene flow, and finally led to the genetic differentiation of the population. The present distribution pattern and genetic diversity of CM have been formed due to these factors.The Mantel test is often used to detect IBD in populations in order to understand the relationship between genetic and geographic distances between populations of different geographical origins . AlthougCypripedium, a highly evolved group of plants in the Orchidaceae.The results of the bioinformatics analyses revealed that CM had a low level of genetic diversity and that genetic differentiation occurred between populations of north and northeast China, showing a distinct genetic structure; in particular, substructures were found among north China populations. These results were mainly due to the comprehensive effects of over-collection, habitat fragmentation, limited recent gene flow, and biological characteristics of CM. Our results provide information on the level of genetic diversity, genetic differentiation, population genetic structure, gene flow, and IBD of CM distributed in mainland China, and provide scientific reference for conservation and rational management measures. To protect the existing population and to re-establish population, we propose the following recommendations: (1) Popularize CM as a national key protected plant and improve awareness of CM protection, especially at forest parks or scenic spots where it is distributed. (2) Strengthen resource surveys and monitor the population size of CM to ensure the accuracy and the integrity of conservation. (3) Collect germplasm resources to establish a germplasm bank for rare and endangered species. Although CM tissue culture was a breakthrough in the laboratory, large-scale tissue culture technology and the survival rate of tissue culture seedlings require to be improved. (4) Gradually reintroduce allogeneic individuals in regions suitable for the growth of CM, such as the middle region of north and northeast China, to build a bridge of gene flow and reduce genetic differentiation between populations. (5) Prioritize protection of north China populations from the perspective of ecological edge effect and island effect. (6) Perform more research on the pollinators of CM and understand the pollination biology of the genus In this study, one healthy leaf was collected from each individual as experimental material before June 2021, as CM is mainly propagated by rhizomes, in order to avoid cloning plants, the individuals we sampled were more than 10 m apart, and 106 individuals were randomly selected. The collection was approved by the local forestry departments in Heilongjiang, Hebei and Beijing. The samples were carefully identified by Engineer Shang Dong of Yichun Branch of Heilongjiang Academy of Forestry, a voucher specimen was deposited in the Yichun Forest Museum with an accession number ycl20210607005.The extraction of DNA from each sample was followed the kit manufacturer’s procedure (TIANGEN BIOTECH (BEIJING) CO., LTD), the quality and concentration of DNA were detected until the requirements for library sequencing were met.The libraries were prepared by following the protocol developed by Qi et al. . BrieflyIn order to ensure the quality of subsequent analysis, Raw Reads were filtered according to the following conditions , and fasBased on the comparison results between samples and reference, the SNP sites in samples were predicted by GATK software (V3.8-1) Unified program . And usep value was calculated VCFtools software (V0.1.16) [Ho, He, A, Ae, PIC, indexes of CM populations that primarily reflect levels of genetic diversity were analyzed by R package genepop (V1.1.4) as described , Pi and V0.1.16) .To understand the relationship between populations and visualization of genetic distance, Neighbor-joining tree was constructed with Treebest (V1.9.2)  under thhttps://speciationgenomics.github.io/Treemix/) [The StAMPP program package (V1.6.1)  and Weirreemix/)  was usedThe Mantel test program in GenAlEx (V6.5)  was perf


P. vivax ETRAMP11.2 gene (pvetramp11.2) remains undefined. The genetic variability of an antigen may limit the effectiveness of its application as a serological surveillance tool and in vaccine development and, therefore, the aim of this study was to investigate the genetic diversity of pvetramp11.2 in parasite populations from Amazonian regions and worldwide. We also evaluated amino acid polymorphism on predicted B-cell epitopes. The low variability of the sequence encoding PvETRAMP11.2 protein suggests that it would be a suitable marker in prospective serodiagnostic assays for surveillance strategies or in vaccine design against P. vivax malaria.ETRAMP11.2 (PVX_003565) is a well-characterized protein with antigenic potential. It is considered to be a serological marker for diagnostic tools, and it has been suggested as a potential vaccine candidate. Despite its immunological relevance, the polymorphism of the pvetramp11.2 of P. vivax isolates collected from Brazil (n = 68) and Peru (n = 36) were sequenced and analyzed to assess nucleotide polymorphisms, allele distributions, population differentiation, genetic diversity and signature of selection. In addition, sequences (n = 104) of seven populations from different geographical regions were retrieved from the PlasmoDB database and included in the analysis to study the worldwide allele distribution. Potential linear B-cell epitopes and their polymorphisms were also explored.The pvetramp11.2 sequences revealed a low polymorphism and a marked geographical variation in allele diversity. Seven polymorphic sites and 11 alleles were identified. All of the alleles were detected in isolates from the Latin American region and five alleles were detected in isolates from the Southeast Asia/Papua New Guinea (SEA/PNG) region. Three alleles were shared by all Latin American populations . The H1 allele , which was absent in the SEA/PNG populations, was the most represented allele in populations from Brazil (54%) and was also detected at high frequencies in populations from all other Latin America countries (range: 13.0% to 33.3%). The H2 allele was the major allele in SEA/PNG populations, but was poorly represented in Latin America populations (only in Brazil: 7.3%). Plasmodium vivax populations from Latin America showed a marked inter-population genetic differentiation (fixation index [Fst]) in contrast to SEA/PNG populations. Codon bias measures (effective number of codons [ENC] and Codon bias index [CBI]) indicated preferential use of synonymous codons, suggesting selective pressure at the translation level. Only three amino acid substitutions, located in the C-terminus, were detected. Linear B-cell epitope mapping predicted two epitopes in the Sal-1 PvETRAMP11.2 protein, one of which was fully conserved in all of the parasite populations analyzed.The multiple alignments of 208 P. vivax populations from different endemic areas of the world. The reduced polymorphism and the high degree of protein conservation supports the application of PvETRAMP11.2 protein as a reliable antigen for application in serological assays or vaccine design. Our findings provide useful information that can be used to inform future study designs.We provide an overview of the allele distribution and genetic differentiation of ETRAMP11.2 antigen in The online version contains supplementary material available at 10.1186/s13071-023-05851-9. Plasmodium vivax malaria is endemic in most of the world's malaria areas, with a global burden of 5.9–7.1 million estimated cases in 2020 ) and few candidates in preclinical trials [P. vivax malaria needs to focus on appropriate surveillance systems. process . Howeverl trials . Since tP. vivax malaria require appropriate surveillance systems. Particular attention should be directed towards the assessment of transmission levels as this knowledge is crucial to understanding infection status and transmission dynamics. To this end, serological assays that measure malaria antibody responses are increasingly being used to estimate the malaria exposure of individuals in at-risk populations, with the aim to overcome the limitations of conventional diagnostic tests that are not sensitive enough to detect low-density malaria infections in malaria residual areas [Successful strategies for the control of al areas . In thesal areas  that areal areas  and alsoAntibody responses to only a few parasite proteins have been specifically investigated to identify potential antigens for malaria serosurveillance, and most of these proteins are primarily target proteins of interest for malaria vaccine . UnfortuP. vivax is the early transcribed membrane protein (PvETRAMP) 11.2 (PVX_003565), a member of the PvETRAMP gene family that was first recognized in P. falciparum [P. vivax [P. falciparum [One of the serological markers expressed in lciparum , 13. NinP. vivax . All of lciparum .P. vivax proteins [P. vivax ETRAMP family proteins, high serum positivity was found for PvETRAMP11.2 [P. vivax-exposed individuals, revealed PvETRAMP11.2 as one of the most abundant immunogenic proteins of P. vivax [PvETRAMP11.2 has been defined as antigenic target associated with immune response by immunogenic profiles of human sera against proteins . It has proteins . Among tRAMP11.2 . A bloodP. vivax , stronglP. vivax .pvetramp11.2) is a single-exon gene located on chromosome 4 which encodes a protein consisting of 110 amino acids (aa), with a predicted molecular weight of 12 kDa [pvetramp11.2 is one of the most expressed genes in P. vivax blood stage and schizont transcriptomes [The PvETRAMP11.2 gene , aimed at developing inter-country standardized serosurveillance tools to accurately monitor changes in P. vivax transmission intensity in Amazonian regions. In addition, we analyzed allelic variants, using pvetramp11.2 from publicly available sequences of clinical isolates from different malaria endemic regions worldwide. Linear B-cell epitopes were predicted and their polymorphisms analyzed. The present study reports the first analysis of pvetramp11.2 diversity and provides baseline information to assess its usefulness as a potential antigen for implementing molecular surveillance tools and for malaria vaccine development.Despite PvETRAMP11.2 being a well characterized antigen, its genetic variability has not been studied. Therefore, the aim of this study was to characterize the genetic variability of The Amazon extends across nine countries in northern South America. Most malaria transmission occurs in riverine villages, farming settlements, gold mining camps and Amerindian reserves . AmazoniP. vivax populations from Brazil (n = 68) were collected in two sites in the state of Acre, northwestern Brazil. Two samples were collected during a cross-sectional survey conducted in rural sites around the town of Acrelândia in September–October 2004 [n = 36) were collected during epidemiological surveys conducted in Mazan district, in the northeastern Peruvian Amazon Department of Loreto between July 2015 and April 2017 [Samples of ber 2004 , and 66 ber 2004 . Samplesril 2017 , 24.DNA was extracted from dried blood spot samples from the Peruvian collection using the Pure Link Genomic DNA Extraction Mini Kit  following the manufacturer's protocol. Purified DNA from Brazilian samples , 22 werepvetramp11.2 gene sequence of P. vivax Salvador-1  strain (PVX_003565). The partial sequence of pvetramp11.2 was amplified by nested (F2-R2) or semi-nested (F1-R2) PCR. All PCR reactions were performed using 0.5 U of GoTaq DNA Polymerase  in Green reaction buffer (Promega) plus 0.5 µl of 10 mM PCR Nucleotide Mix  and 0.1 µl of each primer pair (stock 100 pm/µl), in a final reaction volume of 25 µl containing 3 μl of template DNA. DNA amplifications were carried out with a pre-amplification denaturation step at 94 °C for 5 min, followed by 39 cycles of denaturation at 94 °C for 30 s, annealing at 55 °C for 30 s and extension at 72 °C for 1 min, with a final elongation at 72 °C for 5 min. All DNA amplifications were performed on a TurboCycler Lite thermo cycler . Amplicons were run in a 1.5% agarose gel in order to assess their amount, the correct size and absence of background or unspecific bands before sequencing. The PCR products were purified with the GeneAll Kit  following the manufacturer’s protocol, and then sequenced both in the forward and reverse directions by Eurofins Genomic. Sequencing primers were the upstream and downstream primers of the secondary PCR.Outer primers F1 (5ʹ-TGCTTGTCATCTCGAGTGGT-3ʹ) and R1 (5ʹ-TTTCCAACTCTGTTGCTTA-3ʹ) and internal primers F2 (5ʹ-GCTCAGGTCTTTGCTCCATG-3ʹ) and R2 (5ʹ- ACCTCTTCGCTGCTTTGTTAG-3ʹ) were designed based on the reference n = 68) and Peruvian parasite samples (n = 36) and additional sequences of pvetramp11.2 (n = 104) from parasite samples collected in different geographical areas  that were downloaded from the PlasmoDB [pvetramp11.2 genetic polymorphisms in populations from different malaria endemic areas of the world  was used as the query to retrieve the FASTA files from the plasmoDB database, in the section “genetic variation.” Only pvetramp11.2 sequences with no ambiguity in terms of nucleotides or gaps were selected, including from Peru (n = 26), China (n = 10), Mexico (n = 15), Papua New Guinea (n = 4), Colombia (n = 23), Thailand (n = 14) and Myanmar (n = 12). The Peruvian sequences retrieved from PlasmoDB were kept separate from those of the Peruvian population sequenced in the present study and named Peru_PDB. The P. vivax Salvador-1 etramp11.2 sequence  was used as reference for the alignments. A total data set of 208 sequences was generated. Nucleotide sequences were aligned using the ClustalW multiple sequence aligner in Accelrys Gene v2.5  and CLC-Main workbench v21 software .TheStatistical analyses were carried out using DnaSP v6 , DnaSP vSliding window analysis of nucleotide diversity (Pi), with a window size of 10 bp and step size of 5 bp, was performed for all the populations . Tajima’s D, Fu and Li’s D* and F* test statistics, carried out using DnaSP v5, were used to assess the selective pressure on the gene.P-value significance level to P < 0.05.Pairwise genetic differentiation and its significance was estimated for all populations by the Wright fixation index (Fst) using Arlequin version 3.5 . We set n = 208) were translated into amino acid sequences applying the standard genetic code with DnaSP v6. Deduced proteins from reference sequences Brazil I, India VII, Mauritania, Chesson, Belem, IQ07 and PVP01 and field samples from parasite populations collected in Madagascar  and Cambodia  retrieved from the PlasmoDB database were added to the analysis.The sequences from the total data set , the measure that quantifies the effective number of codons used in a gene , and theThe Fast Unconstrained Bayesian AppRoximation (FUBAR) method  implemenpvetramp11.2 (PVX_003565), corresponding to the region from nucleotides (nt) 55 to 333 of the Sal-1 reference sequence and encoding 92 aa residues (from aa 19 to 110) was successfully sequenced in 68 field samples from Brazil and 36 field samples from Peru. Brazilian samples showed one synonymous polymorphism (C198G) and four non-synonymous polymorphisms , giving rise to seven alleles . The H1 allele  was the predominant allele (54.4%) in the Brazilian parasite population. Peruvian samples showed four single nucleotide polymorphisms (SNPs) , which led to the identification of five different alleles . Peruvian and Brazilian isolates shared three alleles . In total, nine alleles were observed that showed marked geographical variation in terms of frequency  than in those from Peru (K = 1.416). The allele diversity was higher in parasites from Peru (Hd = 0.730) than in those from Brazil (Hd = 0.659). A preponderance of non-synonymous over synonymous mutations was detected , and nucleotide diversity per site (Pi) values were also similar (0.00566 for Brazil and 0.00507 for Peru). The average number of nucleotide differences was marginally higher in parasites from Brazil (ed Table .Table 2Epvetramp11.2. The data set included pvetramp11.2 sequences from Brazil (n = 68) and Peru (n = 36) generated in the present study, as well as additional pvetramp11.2 sequences (n = 104) retrieved from the PlasmoDB database, including sequences from Peru_PDB (n = 26), Colombia (n = 23), Mexico (n = 15), Thailand (n = 14), China (n = 10), Papua New Guinea (n = 4) and Myanmar (n = 12). Analysis of the sequences retrieved from PlasmoDB confirmed the presence of all nine SNPs detected in the Brazilian and Peruvian samples evaluated in this study. Only two additional synonymous mutations were observed, C66T in samples from Colombia and Peru_PDB and A96G in samples from Colombia, which defined two additional alleles, H4 restricted to Colombia (13%) and H5 shared among Peru_PDB (11.5%) and Colombia (8.7%)  among geographic locations (range: 0.00000–0.00587). The lowest levels of Pi were detected in SEA/PNG populations (range: 0.00000–0.00255) . Significant inter-population differentiation was observed between the Latin American and the SEA/PNG parasite populations. Fst values also showed a statistically significant differentiation between populations from Brazil and Peru, as in most pairwise comparisons between Latin American populations. Low genetic differentiation was observed in parasite populations from the SEA/PNG area, suggesting the presence of gene flow among these populations. Results of this analysis are summarized in Table Neutrality indices estimated by Tajima's D, Fu and Li’s D* and Fu and Li’s F* were calculated to detect deviation from the standard neutral model of evolution  and Madagascar , were also compared. .The Sal-1 PvETRAMP11.2 protein sequence was used as input to identify regions recognized as linear B-cell epitopes by the BepiPred 2.0 web-server set to a default threshold of 0.50. The analysis predicted the occurrence of two epitope regions corresponding to residues 23F-50Q and 77 K-107S  and overlapped  with those predicted by BepiPred. pvetramp11.2, we analyzed the relative usage of synonymous codons along the pvetramp11.2 gene fragment by estimating differential codon usage indices (ENC and CBI) to assess preferential use of the synonymous codons. All P. vivax populations from Latin America showed lower ENC values (range: 32.489–33.935) compared to SEA/PNG populations (range: 36.611–38.104). The ENC values of all populations analyzed suggested a preferential use of synonymous codons. CBI values for all populations ranged from 0.556 to 0.584, which is far from random codon usage (CBI = 0) [Low polymorphism in a gene could be a result of a bias in codon usage. To better characterize the low genetic variability ofCBI = 0) . Values We also used the Fast Unconstrained Bayesian AppRoximation (FUBAR), with a posterior probability of 0.9, to identify sites targeted by selection. In this analysis, we grouped populations of Latin America and those of SEA/PNG as two groups, and the results for these two geographical areas showed evidence of selection only in the Latin America group. Episodic negative/purifying selection was detected at three codons  and evidence of episodic positive/diversifying selection was found only at codon 90.P. vivax etramp11.2 gene in parasite populations from Brazil and Peru. A low protein variability in these populations was concluded, based on the observation of only three amino acid substitutions . Changes in amino acids that were present in the samples of Brazilian and Peruvian parasites were shared by parasites of other populations of Latin America  as well as by those outside of Latin America  although the prevalence did differ by country. The amino acid substitutions were found to be located in the region spanning aa 90 to 110 in the C-terminus, presumed to be oriented facing the host cytosol [This study provides evidence for limited genetic polymorphism in the  cytosol  and therP. falciparum AMA-1 alleles [Two of the three polymorphic residues (aa 90 and 107) fell in one of the two predicted linear B-cell epitopes (77 K-107S). Amino acid substitutions could alter the epitope and consequently antibody recognition, or the amino acid changes may not necessarily represent key polymorphisms contributing to immune evasion. Antigenic diversity may be more restricted than DNA sequence diversity, as has been observed for  alleles . The pre alleles . ConsideWe estimated that the parasite populations analyzed in the present study share similar patterns of nucleotide diversity (Pi), and nucleotides with high diversity were found in the terminal coding region, regardless of their geographical origin, which is consistent with the signature of a constrained sequence. The absence of polymorphisms in specific protein regions in parasite populations from very distant geographical areas may reflect the existence of functional and/or structural constraints that severely limit PvETRAMP11.2 to accept alternative modifications .etramp11.2 allele (H1) was absent in parasite populations in the SEA/PNG area, suggesting that any vaccine studies based on this reference strain should be performed with caution in this specific area.We found differences both in the number of alleles and in the prevalence of individual alleles in the samples of parasite populations from the different endemic regions considered. Latin American populations harbor all alleles identified, and H1  is highly represented. SEA/PNG populations have restricted allele diversity, and the H2 allele dominates in this area. The Sal-1 Fst estimates indicated substantial genetic differentiation between the SEA/PNG and Latin American populations, despite the low sequence polymorphism observed. Most of the parasite populations from Latin America are clearly differentiated from those on the same continent as well as from SEA/PNG populations, possibly due to factors such as local adaptation and/or limited gene flow or random genetic drift. Low and non-significant Fst values in parasite populations from the SEA/PNG area suggest much less differentiated populations with respect to those of Latin America, based on the presence of the few circulating alleles, of which one predominant allele  is shared by the populations. The low differentiation between populations and the low number of alleles could facilitate vaccine study for this area.pvetramp11.2, a limited sequence diversity has also been detected in other genes, such as the gene for the P. vivax proteins P41 [P. vivax [As observed for eins P41 , PvRON4 eins P41  and PvRAeins P41 . Unfortueins P41 , 46. Maneins P41 , 48. NeuP. vivax . This reP. vivax  and is hP. vivax  like PvECodon usage bias is determined by a balance between selection and mutational bias . Since c P. vivax populations, and study should be expanded to provide a better view of the distribution of pvETRAMP11.2 polymorphisms. Also, the small sample size may not represent the full range of variation in parasite populations, possibly resulting in incorrect diversity estimates.Limitations of this study include the absence of the full-length sequences (54 nucleotides missing). The geographic range considered does not allow us to clarify whether the results can be extended to globalP. vivax malaria patients. Consequently, the high degree of protein conservation identified in our study further supports PvETRAMP11.2 as a promising target antigen that deserves to be further studied in depth.In conclusion, the main finding of the current study is the reduced genetic variation of PvETRAMP11.2 antigen. Given that most vaccine antigens are characterized by regions of high polymorphism , such aspvetramp11.2 diversity, which has been poorly characterized so far, and for providing information facilitating the identification of sequence features that may aid the design of improved serological assays and vaccine formulations.The results of this study are useful for improving our understanding of Additional file 1. List of P. vivax samples retrieved from Plasmo DB with their IDs.Additional file 2: Figure S1. Sliding window plot of global P. vivax etramp11.2 nucleotide diversity (Pi).Additional file 3: Table S1. Neutrality test estimates for pvetramp11.2 in P. vivax populations.Additional file 4: Table S2. Amino acid sequence polymorphisms in P. vivax ETRAMP11.2 protein worldwide.Additional file 5: Figure S2. Sal-1 PvETRAMP11.2 sequence, predicted B-cell epitopes and protein sequence conservation.


Trifolium montanum individuals from 13 semi‐dry grassland locations of Central Europe. Modern statistical analyses based on a multivariate framework  with preselected linear regression models revealed that the variation of abiotic factors (in contrast to factors per se) almost completely, significantly explained fluctuations in population size (R2 = .93). In general, abiotic habitat variation (heterogeneity) was not affected by habitat area. Population size significantly explained genetic diversity , inbreeding (FIS: R2 = .35), and differentiation (GST: R2 = .20). We also found that iFDCV (ITV) was significantly explained by abiotic habitat heterogeneity, and to a lesser extent by genetic diversity He (R2 = .81). Nevertheless, habitat heterogeneity did not statistically affect genetic diversity. This may be due to the use of selectively neutral microsatellite markers, and possibly by insufficient abiotic selective pressures on habitats examined. Small T. montanum populations in nonoptimal habitats were characterized by reduced genetic and functional trait diversity, and elevated genetic inbreeding and differentiation. This indicates reduced adaptability to current and future environmental changes. The long‐term survival of small populations with reduced genetic diversity and beginning inbreeding will be highly dependent on habitat protection and adequate land‐use actions.Population size, genetic diversity, and performance have fundamental importance for ecology, evolution, and nature conservation of plant species. Despite well‐studied relationships among environmental, genetic, and intraspecific trait variation (ITV), the influence of population size on these aspects is less understood. To assess the sources of population size variation, but also its impact on genetic, functional trait, and performance aspects, we conducted detailed population size estimations, assessed 23 abiotic and biotic environmental habitat factors, performed population genetic analyses using nine microsatellite markers, and recorded nine functional traits based on 260  Despite well‐studied relationships among environmental, genetic, and plant intraspecific trait variation (ITV), the influence of population size on these aspects is less understood. Small mountain clover populations in nonoptimal (niche pessimum) habitats are characterized by reduced genetic diversity and ITV based on functional traits, and increased genetic inbreeding and differentiation. The long‐term survival of small populations will thus be highly dependent on further habitat protection and appropriate land‐use actions. Formerly, T. montanum was widespread, but its abundance in Central Europe declined during the last decades due to habitat degradation and fragmentation, and today the species is regionally threatened  abiotic and biotic environments, in their (2) functional trait characteristics, and (3) genetic diversity, inbreeding, and differentiation? And (4) how population size affected by environmental factors impacts genetic features and intraspecific trait variation (ITV)? Results will subsequently be discussed in the context of long‐term viability and nature conservation of T. montanum populations.22.1Trifolium montanum L., Fabaceae) is distributed across Eurasia; it is a diploid (2n = 16), perennial, up to 70 cm tall herb of extensively used grasslands . In addition, the main root varies remarkably in thickness and length  multiplied by the area occupied by a population . In total, we sampled up to 20 individuals per population and 260 individuals in Riezlern (KW) in July 2015 and in Central Germany from May to June 2016.A “population” was defined as a group of individuals of the same species separated by their closest conspecifics by at least 100 m or by natural barriers such as agricultural areas or forests , resulting in a final sample size of 64 records. The Schmidt scale , for sodium (CECNa), potassium (CECK), calcium (CECCa), and magnesium (CECMg), and soil reaction with de‐ionized water (pHH2O or pH) and potassium chloride (pHKCl), organic carbon (Corg), lime (CaCO3), nitrogen (N), plant available phosphor (P), and plant available potassium . Mean annual temperature (Ta) and mean annual precipitation (Pa) were calculated by interpolation using ArcMap vers. 10.5 (ESRI Inc.) and data derived from WorldClim 1.4 global climate database from 1960 to 1990  and evenness , slope exposure (CVslope exposure), slope (CVslope), leaf area index (CVLAI), soil depth (CVsoil depth), soil cation‐exchange capacity (CVCECpot), pH (CVpH), soil nitrogen content (CVN), soil phosphor content (CVP), and soil potassium content , private allelic richness , observed (Ho) and expected heterozygosity (He), and Shannon's diversity index (I), inbreeding coefficient (FIS), and differentiation of a single population relative to all populations (GST) using GenAlEx vers. 6.503  to homozygotes in a given population ; I also indicates genetic diversity, but this parameter is not limited to −1/1, making it highly appropriate in cases of large diversity differences. NA is the simplest genetic index, but unlike other indices, it depends strongly on population history ; FIS depends on the ratio of Ho and He and indicates homozygote excess , or heterozygote excess (<0), and GST indicates the genetic distinctiveness of a given population relative to all examined populations  and proved to be the best index to explain the relationships among trait variation, habitat heterogeneity, and genetic diversity in T. montanum. Therefore, He as GD was also used here.We calculated allelic richness (03 Table . Ho refv/Fm), performance index on absorption basis (PI), stomatal pore surface (SPS), and stomatal pore area index . This measure focuses on trait variation rather than trait differences, captures trait space and variation, and is suitable for studying environmental and genetic effects on trait variation , total dry aboveground biomass (AGB), leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), the ratio of variable fluorescence to maximum fluorescence  as the ratio of standard deviation to mean. We applied QQ plots to test for normal distribution, but additionally performed Shapiro–Wilk tests when results were inconclusive. To infer location‐/population‐wise differences in environmental factors, genetic indices, or functional traits, we conducted analyses of variance , or Kruskal–Wallis tests  when data normality and homoscedasticity were not fulfilled. We then used either Tukey‘s HSD test or pairwise Wilcoxon rank‐sum tests (Holm correction) to examine differences between specific groups within a variable. In separate multiple linear regression models, variable contribution of scaled variables was extracted from the models by using the ratio of the respective variable estimate to the sum of the total estimates.Statistical analyses were performed using R vers. 4.0.1 , we performed principal component analyses . Populations were highlighted according to size to examine their environmental and trait (dis)similarity. In addition, we correlated each PCA axis with population size, and significant PCA axes with environmental factors or traits, to elucidate the most important features separating small and large populations.To infer whether small and large pot, pH, N, P, K); (ii) HD explained by habitat area; (iii) population size explained by single nonautocorrelated habitat heterogeneity factors  and HD; (iv) population genetic indices  explained by population size. We ensured that the diversity variables used are saturated, that is, that enough individuals per population were sampled to obtain a good diversity estimate of the entire population  until we reached the final model , and to only include relevant relationships in the subsequent multivariate framework , we conducted linear regression models (LMs). We used logarithmized population size and habitat area to achieve linearity, and specified the following main formulas: (i) Population size explained by single nonautocorrelated habitat factors  and HD; (iii) HD explained by habitat area; (iv) population genetic diversity indices (except for nonsignificant PAp) explained by population size, and, following Karbstein, Prinz, et al.  iFDCV explained by GD (except for nonsignificant interaction between HD and GD). In total, the model comprises 84 unspecified variable combinations , of which 10 were significant and classified as correlated errors because they are not causal and/or unidirectional  within the SEM structure. To perform the SEM, we applied the function psem within the R package “piecewiseSEM” vers. 2.3.0 . We only included previously significant relationships  GD 33.1Ta) and annual precipitation (Pa) ranged from 6.7–8.7°C and 511–767 mm, respectively. Riezlern, located in the Northern Alps, was characterized by remarkably cooler Ta of 5.7°C and higher Pa of 1045 mm. Habitats are moderately species‐rich (19–33 species in 20 m2 transect) and are dominated by a few grass species with minor abundances of other semi‐dry grassland species (E 0.60–0.83). Most T. montanum populations grew on north‐ to west‐exposed grassland locations, which varied considerably in density and height of vegetation and thus in biotic competition . In addition, habitats were predominantly characterized by flat slopes (2.0–16.1°), slight continentality (wK 3.0–4.5), and shallow (soil depth 9.6–21.5 cm), slightly acidic to calcareous , relatively dry (wF 3.1–5.5), and low to medium nutrient‐rich  soils.Central German locations are spread across different landscapes, representing an environmental gradient from relatively warm and dry lowlands (Thuringian Basin) to cooler and wetter Central German mountain systems , while small populations tend to be found above the center towards the edge (niche pessimum). PCA axis 2 is mainly responsible for the separation according to population size, as confirmed by significant correlations of PCA2 with population size , and PCA2 with environmental factors . Consequently, large compared to small populations tend to be located in extensively used, species‐rich Bromus erectus habitats in hilly regions characterized by lower continentality, higher light availability (wL) and annual precipitation (Pa), and lower annual temperatures (Ta). The remaining environmental factors do not differentiate between large and small populations . In poorly managed meadows dominated by the grasses Brachypodium pinnatum and Dactylis glomerata , and HD did not significantly depend on habitat area .The PCA based on abiotic and biotic environmental factors explained 45% of variation with the first two principal components Figure . We did R2adj = .00, F2,10 = 0.33, p = .90), even after model simplification. Single LMs for each environmental factor separately also revealed no significant associations . Interestingly, the variation (CV) of certain environmental factors nearly completely, and significantly explained population size : The higher the variation  of soil depth (18%), altitude (10%), N (9%), and slope exposure (8%) the lower the population size, and the higher the variation of LAI (19%), K (14%), pH (12%), P (5%), and slope (5%), the larger the population size.In contrast to multivariate PCA and related correlation results, a multiple LM between population size and single environmental factors exhibited no significant relationships (p > .05). Large populations are predominantly characterized by medium functional trait values. More extreme trait combinations are situated in niche‐pessimum conditions, for example, (i) the small continental dry grassland populations (Ba) exhibits individuals with small height, leaf area, and stomata, and of low‐biomass, which correlate with high annual temperatures and light availability but low precipitation; (ii) the small Arrhenaterum grassland population (Di) comprises individuals with large height and stomata size but also stressed (low Fv/Fm and PI), associated with high biotic competition , soil depth, and nutrient supply (K); (iii) further small populations  are characterized by unstressed (high Fv/Fm and PI) individuals with small to medium plant height, biomass, and leaf area, correlated with low biotic competition, medium light availability, and low soil depth and pH. In addition, all functional traits differed significantly among locations  from 49 to 71 alleles, private allelic richness (PAp) from 0 to 5.8%, observed heterozygosity (Ho) from 0.531 to 0.690, expected heterozygosity (He) from 0.570 to 0.686, Shannon's information index (I) from 1.185 to 1.473, inbreeding coefficient (FIS) from −0.049 to 0.159, and genetic differentiation (GST) from 0.032 to 0.067 , Ho , He , and I  when the population Steinthaleben (St) is removed , followed by Ho and I , NA and I , Ho and He , and Ho and NA . The strongest significant negative relationships were observed for Ho and FIS , followed by I and GST , Ho and GST , and He and GST . PAp was not significantly associated with other diversity indices . For single microsatellite loci, similar relationships between genetic indices and population size were detected (not shown). Allelic size ranges were comparable to Matter et al. , HD (R2 = .05), NA (R2 = .42), Ho (R2 = .67), He (R2 = .43), I (R2 = .59), FIS (R2 = .35), GST (R2 = .20), iFDCV (R2 = .81), and their respective predictors  represents the formulated hypothesis and underlying data well , CVsoil depth , CVK , CVN , CVpH , and CValtitude . In contrast to previous LM analyses, CVP and CVslope exposure were not correlated with population size. With increasing variation in soil depth, soil nitrogen content, and altitudes, and decreasing variation of light availability, soil potassium content, and soil pH within habitats, population sizes become larger. Variation of habitat environmental factors (HD) is not statistically affected by habitat area (p = .49), as also shown previously. All population genetic diversity indices are again significantly positively affected by population size, with strongest relationships found for Ho (p < .001), followed by I (p < .01), NA (p < .05), and He . With increasing population size, inbreeding (FIS) decreased significantly (p < .05), and genetic differentiation (GST) again showed no significant association with population size . HD did not statistically significantly explain He . Intraspecific trait variation (iFDCV) is significantly positively explained by both HD  and GD .In detail, we observed significant relationships between population size and CV4Understanding the characteristics and responses of plant populations under different environmental conditions is an important evolutionary and ecological challenge, and a critical target of biodiversity and nature conservation research. This study unraveled population size as an important prerequisite of population performance derived from plant functional traits; it shed new light on complex, population size‐dependent genotype–phenotype‐environment interactions by recording detailed location‐wise information about abiotic and biotic environmental habitat factors, genetic diversity, inbreeding and differentiation, and functional traits (ITV) using up‐to‐date statistical modeling approaches within a multivariate framework Figure .He, NA, Ho, I) increased, whereas inbreeding (FIS) and genetic differentiation (GST) decreased in T. montanum  could be largely attributed to habitat heterogeneity (68%) and to a lesser extent to genetic diversity , higher  and lower  variability of certain abiotic environmental factors, lowered genetic diversity, elevated inbreeding and differentiation, and finally lower ITV and performance , while small populations showed intermediate to extreme value combinations  leads to high growth rates and population sizes, whereas nonoptimal habitat quality (niche pessimum) results in low growth rates and small population sizes, which are characterized by nontypical or novel phenotypic trait responses  habitats with relatively high light availability, moderate continentality, temperatures, and precipitation, and low biotic competition, located along shrub and forest edges as well as way‐ and roadsides. According to the literature, T. montanum should occur predominantly in nutrient‐poor, calcareous, sub‐Mediterranean to continental grasslands . These continental grassland populations comprise individuals with low plant heights (RH) and biomass (AGB), smaller stomata (SPS), potential stomatal conductance (SPI), and small (LA), more robust leaves (LDMC). Individuals at these locations respond to increased heat, drought, and light stress. This is known to affect nutrient uptake, photosynthesis, plant growth, and thus certain functional traits  to compete for light with surrounding grass species  and reduced vitality  and inbreeding (FIS), and partly differentiation  at larger sizes  represents a critical prerequisite for high variability of functional traits within populations, ITV (iFDCV), and therefore population performance . The interaction between He and HD did not affect ITV, suggesting phenotypic plasticity‐based ITV, rather than ITV associated with specific site‐adapted genotypes. Accordingly, although abiotic environment can act on genetic diversity via natural selection  to ensure sufficiently high population growth rates, and second, to increase the habitat area of a given population, either by enlarging suitable habitat area or by connecting previously isolated habitats. Applied to T. montanum populations in Central Germany, optimal habitats are characterized by extensively managed, species‐rich, calcareous Bromus erectus semi‐dry grasslands with low vegetation density (less biotic grass competition), and moderate soil nutrient supply and humidity  because of higher investment in plant height and lower investment in flowering structures, recruitment, and survival, resulting in aged populations  can rapidly increase population growth rates of even small T. montanum populations and reduce the risk of population extinction ; data curation (lead); formal analysis ; funding acquisition (supporting); investigation (lead); methodology ; project administration (supporting); resources (supporting); software (lead); supervision (supporting); validation (lead); visualization (lead); writing – original draft (lead); writing – review and editing (lead). Christine Römermann: Conceptualization (lead); data curation (supporting); formal analysis (supporting); funding acquisition (lead); investigation (supporting); methodology ; project administration (lead); resources (lead); software (supporting); supervision (lead); validation (supporting); visualization (supporting); writing – original draft (supporting); writing – review and editing . Frank Hellwig: Conceptualization (lead); data curation (supporting); formal analysis (supporting); funding acquisition (lead); investigation (supporting); methodology (supporting); project administration ; resources (lead); software (supporting); supervision ; validation (supporting); visualization (supporting); writing – original draft (supporting); writing – review and editing (supporting). Kathleen Prinz: Conceptualization (lead); data curation ; formal analysis ; funding acquisition (lead); investigation (supporting); methodology ; project administration (lead); resources (lead); software ; supervision (supporting); validation ; visualization (supporting); writing – original draft (supporting); writing – review and editing .None.R scripts used in analyses are available from the corresponding author on request.Appendix S1Click here for additional data file.