Crotalaria is a plant genus that is found all over the world, with over 700 species of herbs and shrubs. The species are potential alternative food and industrial crops due to their adaptability to different environments. Currently, information on the genetic diversity and population structure of these species is scanty. Genotyping-by-sequencing (GBS) is a cost-effective high-throughput technique in diversity evaluation of plant species that have not been fully sequenced. In the current study, de novo GBS was used to characterize 80 Crotalaria accessions from five geographical regions in Kenya. A total of 9820 single nucleotide polymorphism (SNP) markers were obtained after thinning and filtering, which were then used for the analysis of genetic diversity and population structure in Crotalaria. The proportion of SNPs with a minor allele frequency (maf) > = 0.05 was 45.08%, while the Guanine-Cytosine (GC) content was 0.45, from an average sequence depth of 455,909 reads per base. The transition vs transversion ratio was 1.81 and Heterozygosity (He) ranged between 0.01–0.07 in all the sites and 0.04 to 0.52 in the segregating sites. The mean Tajima’s D value for the population was -0.094, suggesting an excess of rare alleles. The fixation index (Fst) between the different populations based on the Wright Fst (1943) ranged from 0.0119 to 0.066 for the Eastern-Western and Nairobi-Western populations. Model based techniques of population structure analysis including structure, k-means and cross-entropy depicted eight clusters in the study accessions. Non-model based techniques especially DAPC depicted poor population stratification. Correspondence Analysis (CA), Principal coordinate analyses (PCoA) and phylogenetic analysis identified a moderate level of population stratification. Results from this study will help conservationists and breeders understand the genetic diversity of Crotalaria. The study also provides valuable information for genetic improvement of domesticated species. Crotalaria L. is a plant genus comprising 702 herb and shrub species which are widely distributed especially in the Southern Hemisphere. Subtropical Africa and Madagascar are the primary centres of diversity for these species, with approximately 543 species [Crotalaria species occupy diverse habitats but are mostly found in open grasslands, forests edges and road sides [Striga hermonthica (Delile) Benth. [Crotalaria species whose potential not only as food but also industrial crops are immense. Only about 15 Crotalaria species are eaten around the world making it important to prospect within the genus for more edible varieties, as the plants are highly adaptable and relatively cheap to produce [Crotalaria species and determine their inter-species diversity as a prerequisite step. Diversity estimates and relationship studies on edible Crotalaria species will make it possible to develop breeding programs to improve the already domesticated species through interspecific hybridization. Currently, genetic diversity studies of the genus Crotalaria based on molecular data are scanty. Only two studies have been reported, one involved the use of the internal transcribed spacer (ITS) sequence data and the other used start codon targeted (SCoT) markers [ species . Crotala markers .Crotalaria species have different levels of ploidy, thereby increasing the complexity of the entire genus. Although the chromosome number for most species is 2n = 16, in some species such as Crotalaria incana L., the ploidy number is 2n = 14, while polyploidy has been reported in other species such as Crotalaria paulina Schrank and Crotalaria stipularia Desv [Crotalaria improvement by introducing novel traits from wild to domesticated species. However, before this can be achieved, there is need to determine species relatedness by establishing the genetic distances between them.In nature, ria Desv , 8. The ria Desv . InterspCrotalaria genus, morphological parameters are relatively uniform and therefore might not be the optimum tool for morphological analysis [Crotalaria species. The studies done so far include those of [Crotalaria species or to determine the relationship of involved accessions. Hence, most of these molecular markers cannot be extensively used for breeding purposes such as the identification of important QTLs for the improvement of Crotalaria. The current study involved the use of NGS for identification of SNP markers in Crotalaria and is the first of its kind in the genus.Plant diversity assessment is a crucial stage in breeding, conservation planning and evolution research . To asseanalysis . This neanalysis . This maanalysis . SNP ideanalysis . Plant banalysis . After tanalysis . Genomicanalysis . As yet,those of , 18–24. Crotalaria species are grown. Farmers were then selected in these regions and interviewed to determine the socio-economic impact of Crotalaria farming among their communities, and samples collected for diversity studies. Samples were collected from five regions in Kenya with varying rainfall and temperatures, namely; Nairobi, Western, Nyanza, Eastern and Rift Valley. The five sampled regions fall into three climatic regions of agricultural importance in Kenya which are the temperate zone, the coastal strip and the hot and dry zones [Crotalaria germplasm cordially provided by the Genetic Resources Research Institute of Kenya (samples with the prefix GBK) and farmer-held accessions totaling to 80 samples  and verbal consent was sought from the farmers at the time of seed collection. No minors were involved in the study.Samples for the study were collected using a subjective non-probability sampling technique . The prory zones . This br samples . These sCrotalaria leaf sample was transferred into 2ml Eppendorf tubes containing 2 steel beads then immediately immersed in liquid nitrogen. The tubes were then vortexed using the vortex-genie® 2T mixer at maximum speed and the leaf samples ground into fine powder. To the fine powder, 500μl of 3% cetyl trimethylammonium bromide (CTAB) extract buffer pH 5 with 0.2% β-mercaptoethanol and 1% polyvinylpyrrolidone were added and incubated at 65°C for 30 minutes in a water bath. After incubation, the tubes were filled with 500μl chloroform:isoamyl alcohol (24:1) and gently mixed until a homogenate mixture was obtained. The mixture was then centrifuged at 13000 revolutions per minute (RPM) at 4°C for 10 minutes. Using a pipette, the upper aqueous layer was carefully aspirated into clean tubes without the inter-layer or the organic layer. A volume of isopropanol that was two thirds of the aspirated liquid was added to the new tubes and mixed, then incubated at -20°C for 1 hour. The mixture was centrifuged at 13000 RPM at 4°C for 10 minutes following incubation, and the supernatant was carefully discarded to avoid losing the formed pellet. After centrifuging, 70% ethanol (500μl) was added to the tubes and tapped gently to dislodge the DNA pellet, and the supernatant discarded. This washing step was repeated twice and the tubes placed on a clean paper towel for an hour to dry the pellet. The dry DNA pellet was dissolved in 100μl nuclease free water and stored at -20°C prior to shipping to Hong Kong [One gram of each ong Kong .ApeKI restriction endonuclease, which recognizes a five base pair palindrome sequence (G/CWGC). The digested DNA was ligated to barcoded primers to create a GBS sequencing library. The adaptor information and library kit used to create the GBS library were as described by [GBS analysis was carried out at the BGI Tech Solutions Ltd in Hong Kong. Individual digestion of all DNA samples was done using ribed by . This waDe novo using the NGSEPcore software version 4.1.0 [Obtained FASTQ sequences were subjected to the FASTX-tool kit (v 0.0.13) for quality trimming and filtering, with the set parameters–q minBaseQ>20. After filtering and trimming, quality assessment of the obtained sequences was done using FastQC (v 0.11.4) to select sequences with a Phred score above Q30. Pass quality sequencing reads were then assembled on 4.1.0 . PLINK won 4.1.0 . The vcfon 4.1.0 , that ishttps://github.com/ mennodejong1986/ SambaR). Using the ’read.PLINK’ function from the R package adegenet-2.1.3, the data was imported into R and stored in a genlight object [SNP data management and analyses were performed in R-4.0.4  using wrt object , 33. TheCrotalaria.Correspondence analyses (CA) were performed using the function ’dudi.coa’ of ade4-1.7.16 R package , 35. DatCrotalaria individuals, PCAdapt and OutFLANK R packages were used. PCAdapt is based on PCA analysis while OutFLANK is based on atypical values of Fst [snmf function in LEA. Phylogenetic analysis was done using the MEGA software version 11.0.10 by the neighbor-joining method [Admixture coefficients were calculated using the functions ’obj.snmf’ and ’Q’ of the LEA-3.2.0 R package . Alpha ws of Fst , 44. Thes of Fst . To deteg method  and BEASg method . In MEGAg method .The function ’stamppNeisD’ of the StAMPP-1.6.1 R package was used to calculate Nei’s genetic distance . Genome Linkage disequilibrium (LD) estimates were calculated using PLINK (-genome—r2—ld-window-kb 1000000—ld-window -r2 0). Hardy-Weinberg Equilibrium (HWE), (2D) folded site frequency spectra (SFS), Tajima’s D and genome wide heterozygosity analyses were executed using the function ’calcdiversity’ of the R Package SambaR. Population specific SFS vectors were generated using the function ’getfoldedsfs’ of the R package SambaR, which bins SNPs into classes based on how many copies of the minor allele they possess and then calculates the size of each bin (number of SNPs within each bin). Genome wide He (genomeHe) was calculated for each sample using the formula: genome He = (He_seg * N_seg)/N_total), where: N_seg: is the number of segregating sites within the population to which the individual under investigation belonged, He_seg: is the fraction of heterozygous sites for those segregating sites within the examined individual and N_total: is the total length of all polymorphic and monomorphic sequenced sites that passed the filter parameters.Crotalaria samples from different regions in Kenya was successfully sequenced using the GBS technology to yield information on the number of reads in millions, number of bases and the percent guanine-cytosine content  was 0.036while the standardized multilocus heterozygosity (sMLH) was 0.970 for the entire population. The individual MLH and sMLH are as depicted in Crotalaria populations in this study were 0.05 for the Eastern population, 0.18 for Nairobi, 0.08 for both Nyanza and the Rift Valley populations and 0.06 for the Western population. These observed Π values differed from the expected values of 437.2, 2,162.9, 873.9, 788 and 631.8 for the Eastern, Nairobi, Nyanza, Rift Valley and Western populations respectively  was higher than the critical value (3.84). However, the Rift valley and Eastern sub-populations were in Hardy-Weinberg equilibrium (2) of the 9820 SNPs revealed expected mean r2 values of 0.55, 0.4, 0.28, 0.27 and 0.1 for the Eastern, Rift Valley, Western, Nyanza and Nairobi Crotalaria populations  Fst tabulation, there was moderate genetic drift between the Eastern-Nairobi (0.0233), Rift Valley-Western (0.0221), Nyanza-Rift Valley (0.0244) and Nairobi-Rift Valley (0.0334) Crotalaria populations. However, there was greater genetic drift between the Nairobi-Nyanza (0.0427) and Nairobi-Western (0.0666) populations while there was minimal genetic drift between all other populations. Clustering using the 9,820 putative SNP loci revealed little genetic differentiation among the different Crotalaria samples. Therefore, OutFLANK and PCAdapt approaches were applied to identify the putative adaptive Crotalaria loci under local selection pressure. PCAdapt and OutFLANK detected 649 and 0 outlier SNPs as putatively adaptive loci under divergent selection  between the different populations based on different Fst tabulation methods and their associated P values were considered . The paielection . The remEight genetic clusters (K = 8) efficiently summarized the patterns of variation in the data, according to population structure analysis utilizing parametric and nonparametric (structure and k-means) approaches. The Bayesian Information Criterion (BIC) model established that 10 clusters (K) were required to control for population structure. The computed a score value (0.19) revealed a weak discrimination, while the stratified cross-validation revealed that the lowest mean square error was observed with 10 PCs. However, this K value had a lot of outliers hence K = 8 would be more appropriate. The number of clusters (K) was plotted against the BIC value to determine the most suited value of K. The plot revealed that the BIC value continually decreased from K = 1 up to K = 8, before increasing slightly. However, the lowest BIC value was observed at K = 10 . A crossCrotalaria samples was inferred using DAPC. Thirty principal components were retained after the initial dimension reduction step which contained 95% of the total genetic variation. The four retained linear discriminant eigenvalues after cross-validation with the first three PCs accounted for 82.7% of the total variability . Based on the CA plot for individual accessions, a wide distribution of the individual with tight overlaps was observed. Most of the accessions were located within the positive (upper) left quadrant, which comprised accessions from all sampled regions. However, there were single accessions among samples collected from Rift Valley, Nyanza and Eastern that did not fall in this quadrant. Nairobi accessions were distributed in all the four quadrants. The analysis revealed a level of population stratification  quadrant, while the Eastern and Rift Valley populations also fall in one (lower right) quadrant. Based on CA, the Western population was genetically closer to the Nyanza population, while the Rift Valley, Eastern and Nairobi Crotalaria populations were distantly related , start codon targeted (SCoT) and internal transcribed spacer derived markers [Crotalaria. The current study reports the first successful application of GBS for the study of Crotalaria species’ genetic diversity. The average number of reads per sample reported in this study is consistent with those reported by [Lens culinaris Medik) species. The number of reads and the GC content of the obtained sequences in the current study, indicate that GBS is an appropriate molecular technique for germplasm characterization in Crotalaria. Based on the generated de novo assembly statistics, the NGSEP software was deemed adequate for the assembly, since it produced a moderate ratio of clustered to total reads in the assembled genome. This could be because it uses a hybrid approach of long and short reads, compared to tools which only rely on the long reads to generate an assembly [Few studies have used genetic markers to study biodiversity in  markers , 6, 24.  markers . Despiteorted by , who useassembly .Crotalaria is usually expected to decay at a short distance [C. brevidens, C. ochroleuca and C. trichotoma. The LD decay over a known genetic distance is important in determining the numbers and densities of markers necessary for breeding purposes [Crotalaria species, the current study depicts a low level of LD. This could partly be due to the small population size involved in the study, or due to other aspects such as genetic drift which causes loss of rare allelic combinations [Crotalaria species as observed in the study based on the Fst calculations reveal aspects of genome differentiation, which could be attributed to domestication. The observation of relatively high Fst values between domesticated and wild accessions and low values between purely domesticated or entirely wild accessions supports the aspect of genome differentiation, which has also been observed in cotton [Linkage disequilibrium in cross pollinated species such as distance . Althougpurposes . Althouginations . The iden cotton .de novo assembly technique employed could have informed the low population stratification observed. Although GBS techniques are reliable and appropriate for genotyping individuals with a large numbers of SNPs, genotype call rates resulting from these techniques are low due to the low sequence depths involved [Crotalaria samples.Single nucleotide polymorphism genotyping provides an appropriate and powerful phylogenetic analysis basis to study relatedness in plants and other organisms. To achieve accurate results for kinship estimation, it is necessary to have a reliable reference of allele frequencies in addition to having a large sample size . A high involved . FurtherCrotalaria species involved in this study. The Nairobi sub-population had the highest number and range of loci with private alleles. This could be attributed to the fact that it had the highest number of accessions from different species considered in this study, hence making it the most genetically diverse sub-population compared to the other four sub-populations. Calculating private alleles has the advantage of providing information on alleles that exist in only that one sub-population. With 3,628 private alleles, the Nairobi sub-population had 3,446 more private alleles than the next most diverse sub-population (Western), portraying high genetic diversity among Crotalaria species from Nairobi. Similarly, based on the number of private alleles per population, the Nyanza (24) and Eastern (1) sub-populations had the least genetic diversity since they had the least private alleles after filtering. Private allele data is essential since it gives useful information on unique genetic variability in specific loci while identifying individuals/genotypes that might be used as parental lines in breeding programs to optimize allele richness in a population [Crotalaria species as alternative vegetables.Differentiation in the loci with private alleles was seen in the five populations of Kenyan pulation . The genCrotalaria population, which could have resulted from expansion of these populations after a bottleneck, positive selection or a selective sweep [Giardia duodenalis, Plasmodium falciparum and Brassica rapa [The effects of population structure on nucleotide polymorphism based on population genetic parameters especially the Tajima’s D revealed an overall low (negative) value. These low values suggest the presence of many rare alleles in the Kenyan ve sweep . Similarica rapa –62.The generated CA bi-plots for individual samples revealed overlaps in samples, depicting a high level of relatedness in individual accessions, hence a high level of sharing genetic material. The primary axes of the high-dimensional space formed by the simultaneous inclusion of many conditions and their related samples are revealed via CA. The decrease in dimension allows data to be projected in two or three dimensions of maximum variance, indicating that two or more variables are related if they appear close to each other in the plot . The lowCrotalaria accessions. Although the number of clusters observed were few when using the Bayesian based clustering method compared to the maximum likelihood method, both techniques revealed some level of population admixture and stratification. The presence of structure in Kenyan Crotalaria germplasm is not surprising due to two main reasons. First, there has been continuous domestication of certain edible Crotalaria species in Kenya particularly in the Western region. With domestication, continuous selection for desirable traits in domesticated species narrows the gene pool, thereby introducing an aspect of population structure. Out of the 80 accessions used in this study, 40 belonged to three domesticated species C. brevidens, C. ochroleuca and C. trichotoma whose domestication could have introduced a high level of population structure. In China, domestication was found to impact the diversity and structure of Saccharina japonica populations [Dendrogram analysis based on Maximum Likelihood method and Bayesian clustering techniques revealed some level of population stratification, in Kenyan ulations . Secondlulations . This coulations , 68. Theulations .Crotalaria accessions from Kenya was investigated using GBS. Based on the SNP diversity in these accessions, three structured populations/clusters are postulated. These clusters did not associate with the regions of origin but contained individuals spanning different geographical locations. From the Fst statistics, there is moderate genetic drift among Kenyan Crotalaria accessions, suggesting a relatively moderate level of germplasm exchange between the different regions. Demographically, it could be concluded that Kenyan Crotalaria accessions are expanding after a bottleneck event, most likely, a diversity shrink due to continuous domestication or a selection sweep. Additionally, this study determined that the Nairobi Crotalaria population is the most diverse based on the richness of private alleles, due to minimal domestication and species diversity in this region. Although the concept of predictive breeding in plants such as Crotalaria is yet to be embraced, independent studies in these species are slowly contributing important information necessary for the actualization of this technique. The current study reports the first GBS-based SNP markers in Crotalaria species, an important step in predictive breeding and marker assisted selection. This coupled with other studies on phenotypic parameters in Crotalaria could provide the two most important forms of information necessary for creating models for genotypic effects and the development of breeding values for Crotalaria populations. Furthermore, results from this study could be a beginning point for the development of QTLs in Crotalaria species for different important traits in the species. This together with other techniques such as the advanced backcross QTL method can be used to introgress exotic genes form the wild accessions to the domesticated individuals.The genetic diversity and population structure of wild and cultivated S1 Figa) Heterozygosity levels in all sites per population before data filtration, b) Heterozygosity levels in the segregating sites per population, c) Multi Locus Heterozygosity (MLH) per population and d) standardized Multi Locus Heterozygosity per population.(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Figa) Population assignment probabilities bar plot based on STRUCTURE, (b) Population stratification and assignment base on LEA, (c) population membership based on TESS. Contour lines represent spatial position of genetic discontinuities.((TIF)Click here for additional data file.S5 FigLow population stratification could be inferred from the plot.(TIF)Click here for additional data file.S6 Figa) CA bi plot for individual Crotalaria accessions from the five sampled regions. (b) Population CA plot for Crotalaria accessions from the five sampled regions in Kenya.((TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.


Addax nasomaculatus) now number fewer than 100 individuals, yet 1000 of addax remain in ex situ populations, which can provide addax for reintroductions, as has been the case in Tunisia since the mid‐1980s. However, integrated management requires genetic data to ascertain the relationships between wild and ex situ populations that have incomplete knowledge of founder origins, management histories, and pedigrees. We undertook a global assessment of genetic diversity across wild, ex situ and reintroduced populations in Tunisia to assist conservation planning for this Critically Endangered species. We show that the remnant wild populations retain more mitochondrial haplotypes that are more diverse than the entirety of the ex situ populations across Europe, North America and the United Arab Emirates, and the reintroduced Tunisian population. Additionally, 1704 SNPs revealed that whilst population structure within the ex situ population is minimal, each population carries unique diversity. Finally, we show that careful selection of founders and subsequent genetic management is vital to ensure genetic diversity is provided to, and minimize drift and inbreeding within reintroductions. Our results highlight a vital need to conserve the last remaining wild addax population, and we provide a genetic foundation for determining integrated conservation strategies to prevent extinction and optimize future reintroductions.Threatened species are frequently patchily distributed across small wild populations, ex situ populations managed with varying levels of intensity and reintroduced populations. Best practice advocates for integrated management across in situ and ex situ populations. Wild addax ( The European and North American populations are managed within their respective co‐ordinated population management programmes, the European Association of Zoos and Aquaria's EAZA Ex situ Programme (EEP) and the Species Survival Plan® (SSP) under the Association of Zoos and Aquariums (AZA). As in other species, founder histories are poorly known but founder numbers are thought to be relatively low for addax; the European studbook has 15 wild‐caught founders listed  and Chad . Samples from ex situ addax populations, including hair, tissue and blood (EDTA), were collected opportunistically during routine veterinary procedures from EEP (n = 56) and SSP (n = 43) institutions in Europe and North America, respectively, and Al Ain Zoo (n = 62) and the Environment Agency—Abu Dhabi  in the United Arab Emirates. Samples were collected from 102 of 108 censused addax across the three reintroduced populations in Tunisia using biopsy darts. Further sampling details are shown in Table Faecal samples were collected from wild addax during field surveys in the Tin Toumma region, Niger , QuickGene DNA whole blood kit S or tissue kit S  following the manufacturers' protocols. Samples from AZA institutions were additionally treated with RNase A as per Qiagen standard protocols for the tissue type. Faecal samples were extracted using the QIAmp DNA Stool Mini Kit (QIAGEN) or the Isohelix Xtreme DNA Kit (Cell Projects Ltd) by surface swabbing following the protocol described in Werhahn et al. .2.2All faecal samples were molecularly identified as addax through sequencing of cytochrome b following Verma and Singh . A 723‐bhaplotypes  library was prepared from samples submitted as blood or tissue following a modified Peterson et al.  protocolBriefly, DNA was fragmented using the restriction enzymes SphI and SbfI, and a unique pair of 5‐ or 7‐bp barcodes was ligated to each sample. The pooled library was then size selected between 400 and 700 bp using gel electrophoretic extraction, prior to PCR amplification to incorporate adapter sequences. Samples were sequenced across eight libraries, and positive controls were used to confirm repeatability within and between libraries , which is in line with other studies, suggesting that genomes of closely related species are suitable for SNP discovery in a conservation context . A stringent LD SNP set was generated for analyses requiring minimum LD (admixture) for which only SNPs with R2 < 0.2 were retained (1073 SNPs).adegenet . Results for both admixture and structure were visualized using the pophelper package for R , expected heterozygosity within populations (HS) and the fixation index (FIS) were calculated using the hierfstat package . Pairwise FST was calculated using the dartr package for R , with an average of 5,751,874 (91.2%) reads that were mapped against the scimitar‐horned oryx genome (range: 39.6%–97.1%). We identified a total of 24,395 SNPs, and after filtering, the relaxed LD SNP set retained 1704 SNPs with a genotyping rate of 95% across individuals.3.3p = 0.001, Table p = 0.001). FST ranged between 0.053 (AAZ–EAD) and 0.183 (EAD–Tunisia), shown in Figure p < 0.001). FST estimates within Tunisia . FST estimates within Tunisia were lower than comparisons between the Tunisian metapopulation as a whole and other global populations, though pairwise comparisons including Jbil NP  were similar or greater than estimates between some global populations .AMOVA showed that over 83.9% of the variation is partitioned within individuals  show ancestry similarly differentiated from other populations, but with varying levels of admixture at all estimates of K. The AAZ is composed of at least two clusters with varying levels of admixture from K = 4 onwards. After excluding the Tunisian population, there was no substantial difference in the resulting population structure , and FIS was raised . However, mean sMLH for AAZ was in line with the other ex situ populations despite high variation in individual sMLH estimates, and pairwise kinship (KING‐robust) estimates were very low (mean KING = −0.2).Estimates of genetic diversity were similar across the EAD, EEP and SSP populations, but deviations from Hardy–Weinberg expectations were detected in both AAZ and Tunisia Figure . For AAZFIS was raised (FIS = 0.044 [95% CI 0.036–0.053]) and this was largely driven by Haddej  with 43 control region haplotypes  with 11 control region haplotypes  was reduced compared with the contemporary wild population Figure  revealed4.1.1FIS  are thought to descend from a maximum of 42 individuals Enright, , above tUltimately, the ability of a population to adapt to its environment over the long term is determined by the amount of diversity in the form of allelic variation , Royal Zoological Society of Scotland (UK registered charity number SC004064), SaharaConservation and San Diego Zoo Wildlife Alliance. However, the funders did not have any additional role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.The authors declare that they have no competing interests in relation to this manuscript.Appendix S1Click here for additional data file.Figure S1Click here for additional data file.Table S1Click here for additional data file.


Spodoptera litura is an important agricultural pest widely distributed around the world, which can damage numerous crops. Despite its economic importance, research on the population genetics of S. litura has been limited, preventing insight into the spread of the pest. In this study, we conducted a population genetic analysis of 24 populations of S. litura in Southern China using microsatellite markers, demonstrating the information on the genetic diversity and genetic structure of the tested populations. The results will provide pest control management strategies for S. litura in Southern China.Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae) is an important tobacco pest in China causing serious damage to multiple crops. In this study, we explore its dispersal dynamics by clarifying the fine-scale population genetics using 545 S. litura samples collected from tobacco plantations at 24 locations . We analyzed the genetic diversity, genetic structure, and gene flow of these populations using seven microsatellite loci. Our results revealed high genetic diversity and low population genetic structure among S. litura. The genetic distance was uncorrelated with geographical distance, indicating the complete randomness of dispersal among the local populations. Our results suggest that the movement scope of contemporary S. litura might be much higher than the local-level spatial scale, which will provide a theoretical basis for pest management.Population genetic structure is strongly affected by dispersal events, especially for migratory species. The investigation of population structure is therefore conducive to increasing our understanding of species dispersal.  Grapholita molesta [Cydia pomonella [Mythimna seperata [Leptinotarsa decemlineata [Spodoptera exigua [Population genetics is the study of changes in gene frequency and genotype frequency in a biological population under the influence of natural selection, genetic drift, mutation, and migration . Populat molesta  and Cydiomonella , are weaseperata , Leptinomlineata , and Spoa exigua  with exta exigua ,9. PopulLaodelphax striatellus in 15 regions of northeastern China and observed a certain degree of genetic differentiation and variation in genetic structure among populations [Molecular marker techniques are widely used in population genetics as an important means for studying genetic variations and the degree of genetic differentiation among populations . Compareulations .Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae), is an omnivorous and gluttonous agricultural pest, mainly distributed in the Middle East, most of Asia, America, Africa, and the South Pacific [S. litura was first recorded in Hubei province in 1900 [S. litura feed on leaves, flowers, buds, and fruits and can attack 389 species of host plants from 109 families, including tobacco, pepper, taro, peanuts, and other cash crops [Spodoptera litura is a crucial pest in major tobacco-growing regions of Southern China. Large outbreaks, consequently related to high reproductive ability and long-distance migration, lead to serious economic losses to local growers [S. litura involves various aspects of its occurrence and damage, biology, ecology, and control techniques, but knowledge of the population genetics of S. litura is limited, which hinders the in-depth understanding of pest dispersal. Moreover, previous studies on the population genetics of S. litura have been conducted mainly at large spatial scales [The tobacco cutworm,  Pacific ,15,16,17 in 1900 . At pressh crops . Spodopt growers . The curl scales ,22, and S. litura in local areas, providing a theoretical basis for the dispersal blocking and control of the pest.In this present study, seven microsatellite loci were used to elucidate population genetic differentiation using fine-scale data modeling in Southern China. We analyzed the genetic diversity, genetic structure, and gene flow of the population. These studies will help to clarify the occurrence dynamics of S. litura larvae were collected from tobacco plants in 24 townships of Baise City, Hezhou City, and Hechi City in Guangxi Zhuang Autonomous Region, Southern China . GeneMarker 2.4 [The nine pairs of microsatellite primers , seven erker 2.4  was usedNa), polymorphism information content (PIC), and Shannon’s index (I) were estimated using Microsatellite Tools  and GenAlEx. Observed heterogeneity (HO), expected heterozygosity (HE), and allelic richness (AR) were assessed using the hierfstat R package [Micro−checker  was used package .K) was set as 1 to 10 with 10 repeat runs and a burn-in period of 100,000 and 1,000,000 Monte Carlo Markov Chains. The results were submitted to Structure Harvester Web 0.6.93 [K method [K were integrated using CLUMPP 1.12 [S. litura populations using GenAlEx.STRUCTURE 2.3.4  30 was ub 0.6.93  to confiK method . The memMPP 1.12 , and theMPP 1.12 . In addiFst) and the Nei’s genetic distance (D’) per geographical population were estimated using Fstat [The analysis of molecular variance (AMOVA) was calculated by ARLEQUIN 3.5  to assesng Fstat  and Popgng Fstat , respectFST  [The geographical distance among different populations was calculated based on latitude and longitude. A Mantel test, based on geographic distances and linearized pairwise 1 − FST) , was con1 − FST) . We diviS. litura populations. The program was run with 10,000,000 iterations, discarding the first 1,000,000 iterations, and sampling every 1000 iterations from the remaining 9,000,000 iterations, producing a sample of 9000 observations from the chain that will be used to estimate parameters.BAYESASS 3.0  with MarS. litura is displayed in Na) ranged from 4.14 to 6.86 with an average of 5.73. The mean number of observed heterogeneity (HO) and expected heterozygosity (HE) were 0.4793 and 0.5970, respectively. The average of Shannon’s index (I) was 1.2342. The highest allele richness (AR) was 5.7783 in ZB population, while the lowest AR was 4.1429 in SC population. Polymorphism information contents (PIC) of all populations were greater than 0.5.In all loci-population pairs, only 42 of 168 have significantly deviated from Hardy–Weinberg equilibrium, which was caused by heterozygote deficiency. Linkage disequilibrium occurred in 3 of 21 locus-locus pairs, including CWM−1 versus CWM−4, CWM−1 versus CWM−8, and CWM−7 versus CWM−9. However, no loci had significant global deviation linkage disequilibrium, so the independence of the loci was sufficient. The genetic diversity of 24 populations of Based on the Bayesian cluster analysis using STRUCTURE software, the optimal genetic clusters K = 3 was detected a. HoweveFST values ranged from 0.013 to 0.130. D′ ranged from 0.019 to 0.238. In particular, the CB and BD populations showed the lowest differentiation , and The SC and KX populations showed the highest differentiation .Based on the AMOVA, it showed a 1.92% of variation among populations, 20.02% of variation among individuals within populations, and 78.06% of variation among individuals . These rFST/(1 − FST) against natural log-transformed geographic distance (Ln) between populations revealed that genetic differentiation was weak-positively correlated with geographic distance  (The Mantel test of p = 0.4) . Spatialp = 0.4) .S. litura populations was 0.0061–0.1536. The self-assignment rate in the KX population was the highest (0.7868), and the two highest migration rates were calculated from LG to KX population. In addition, we found that most populations tend to migrate to Chengbei regions (CB).As shown , we markS. litura in Southern China, showing high genetic diversity and low genetic population structure.Owing to the neutral and high mutation rates of microsatellite markers, they are usually used to explore the level of genetic diversity and population differentiation within species ,42. In tHE for the S. litura population was 0.5970 and the average allelic richness (AR) of the S. litura populations was 5.1439, showing a high level of population genetic diversity. For other S. litura populations in China, genetic diversity was found to be generally high (HE from 0.19 to 0.89) by Wu et al., which suggested that the rich genetic diversity was mainly due to frequent individual migration [S. litura migration avoided severe bottlenecks and loss of rare alleles. We further suggested the importance of high-level gene flow in maintaining local population diversity, which may be one of the reasons for population outbreaks and insecticide resistance [The higher the genetic diversity of the species, the stronger it’s potential to adapt to environmental changes ,44. In tigration . In addisistance .S. litura in the study area. The PCoA results also provided similar evidence. Such patterns were observed in Helicoverpa gelotopoeon [Sitobion avenae [Based on the Bayesian clustering analysis, 24 populations in Southern China formed three clusters. However, there was no obvious geographic division pattern in the distribution of these three clusters, indicating that the geographic factors had little influence on the migration of otopoeon  and Siton avenae , where tn avenae . This fin avenae  and Domin avenae . These rS. litura populations based on the local-level spatial scale. Among them, genetic differentiation did not exist in XH and PH populations, even though they were more than 600 km apart. Similarly, Gandhi and Patil [S. litura in India, which were about 670 km apart. Moreover, according to Wu [S. litura in China, although the distance between the two farthest populations (Kunming and Shenyang populations) was about 2600 km. Therefore, we speculated that the genetic differentiation of S. litura may increase at a distance of more than 2600 km. How does our research on genetic differentiation measure up with other moths with high dispersal rates? Normally, moths with high dispersal rates exhibit lower STF. We discovered that there was no genetic divergence between populations at similar or much larger geographic scales than we studied. For example, Franklin et al. [Trichoplusia ni on the west coast of North America remained linked at distances greater than 600 km. However, some species began to diverge at scales greater than the national-level spatial scale. Lyons et al. [Plutella xylostella with geographic distances of over 3600 km, however, significant divergence occurred in these populations with the Malaysia and Kenya populations, which were 5000 km away. Understanding the degree of genetic differentiation of such moths with high migratory capabilities at the geographic scale will help to precisely track the approximate extent of population expansion and provide a basis for future pest management planning.Frequent migrations may offset the effects of genetic drift and mutation, thus reducing population genetic differentiation . Our stund Patil  found hing to Wu , geneticn et al.  also obss et al.  reporteds et al. , it can FST [S. litura populations that introduced genetic variations into partly local populations facilitated gene flow between populations. The high level of gene flow allowed resistance genes to disperse over long distances, leading to widespread dispersion of some chemical pesticide resistance genes, which may have resulted in adaptation to control strategies. The tobacco planting areas in Guangxi are mainly concentrated in Baise, Hechi, and Hezhou City with suitable geographical conditions for tobacco growth. These populations are mostly located in mountains, plateaus, and a few plains, among which Hechi and Baise Cities, near the Yunnan-Guizhou Plateau with rich Karst landscapes. Despite the complexity of geographical factors, the influence on the genetic differentiation of populations was minimal. We infer that the spread of these populations may be related to wind, climate, and human interference. It is noteworthy that high levels of gene flow can easily cause repeated outbreaks under appropriate conditions due to the transmission of rapidly resistant alleles among populations.The extensive gene flow revealed by our analysis may confirm the cause of weak genetic differentiation. Migration rates between populations were highly correlated with pairwise FST , indicatS. litura populations in Southern China. Overall, we consider that S. litura populations form a panmictic population on account of their long-distance migration, sufficient gene exchange, and low genetic differentiation. This helps explain the perennial susceptibility of S. litura to large outbreaks, resulting in extremely difficult prevention and control in local areas. Therefore, we suggest that, for migratory pests, the implementation & scope of management should be expanded to achieve the desired effect.Our study showed high genetic diversity and low genetic differentiation of


Culter alburnus), it is important to explore the current status of its genetic diversity. In this study, the mitochondrial DNA COI gene was used to analyze the genetic diversity, genetic differentiation, and historical dynamics of C. alburnus from five river basins in north and south China. The results showed that the genetic diversity is polarized in different populations but without new species differentiation and has significant geographical features, which are important for developing conservation strategies.To better protect and manage the germplasm resources of the topmouth culter  populations, we analyzed the genetic diversity of five C. alburnus populations from Songhua Lake (SH), Huaihe River (HH), Changjiang River (CJ), Taihu Lake (TH), and Gehu Lake (GH) based on mitochondrial COI gene sequences. The results showed that the average contents of bases T, C, A, and G in the 526 bp COI gene sequence were 25.3%, 18.1%, 28.1%, and 28.6%, respectively, which showed AT bias. A total of 115 polymorphic sites were detected in the five populations, and 11 haplotypes (Hap) were defined. The nucleotide diversity (iP) of the five populations ranged from 0.00053 to 0.01834, and the haplotype diversity (dH) ranged from 0.280 to 0.746, with the highest genetic diversity in the TH population, followed by the SH population, with lower genetic diversity in the HH, CJ and GH populations. The analysis of the fixation index (Fst) and the genetic distance between populations showed that there was significant genetic differentiation between the SH population and the other populations, and the genetic distances between all of them were far; the genetic diversity within populations was higher than that between populations. Neutral tests, mismatch distributions, and Bayesian skyline plot (BSP) analyses showed that the C. alburnus populations have not experienced population expansion and are relatively stable in historical dynamics.To study the genetic diversity of  Culter alburnus belongs to the genus Culter within the family Cyprinidae of the order Cypriniformes, which is a large fish in the Culterinae subfamily that is widely distributed in major freshwater lakes and reservoirs. It has a high economic value and ecological significance; it maintains the stability of the water ecosystem and is an important freshwater economic fish in China [C. alburnus is facing decreases in natural resources and population genetic diversity, reducing germplasm resources [in China . Howeveresources .C. alburnus were focused on its nutritional composition and feeding habits, anatomical and biological characteristics, anthropogenic reproduction and embryonic development, and genetic diversity [COI (cytochrome subunit I) is mainly used in species identification and population genetic analyses with close genetic relationships, where it is a commonly used genetic marker method in populations [C. alburnus populations in the Yangtze River was found to be low, closely related, and highly differentiated, which is probably due to a combination of environmental and human effects [C. alburnus in the Pearl River basin is high, but there are still many sampling sites where genetic diversity is at a low level [C. alburnus genetic diversity and the management of C. alburnus germplasm conservation has become a high-priority research area. However, most of the studies on wild C. alburnus have focused on only local water bodies, and the sample sizes and geographic diversity of populations have been limited. Few studies have been reported on large geographic scales.In recent years, studies on iversity ,4. With iversity ,6. Mitociversity . COI , 31 from the Taihu Lake (TH), 31 from Gehu Lake (GH), 30 from the Huaihe River (HH), and 44 from the Songhua Lake (SH) (Five ake (SH) . All indC. alburnus fins were cut in centrifuge tubes, and DNA was extracted using a kit method . The concentration and purity of the DNA were detected by agarose gel electrophoresis at a concentration of 1%, and DNA samples that met the requirements for subsequent amplification were stored at −20 °C for backup [About 30 mg tissue samples of r backup .COI gene amplification in C. alburnus [COI: 5′-CACAAAGACATTGGCACCCT-3′ and H6558-COI: 5′-CCTCCTGCAGGGTCAAAGAA-3′as primers in a 50 μL reaction volume mixture containing 25 μL of Premix Taq , and 4 mM Mg2+; TaKaRa, Dalian, China), 1.0 μL of each of 10 μM primer, 3.0 μL of total genomic DNA (approximately 100 ng as a template), and 18–22 μL of sterile distilled water. PCR was performed according to the reaction method as follows: pre-deformation at 94 °C for 5 min; denaturation at 94 °C for 35 s, annealing at 50 °C for 35 s, and extension at 72 °C for 50 s for 35 cycles; extension at 72 °C for 10 min; end at 4 °C. Purified PCR products were directly sequenced using primers from both ends in a semi-automated DNA analyzer .The primer sequences used for the mitochondrial alburnus  were L598 generations, and merged with Log Combiner. Tracer 1.5 software was used to detect the results of an effective sample size greater than 200 (ESS > 200), which were output as Bayesian skyline plots [After sequencing was completed, the COI gene sequences were compared and corrected using Clustal W software, and the base content composition of the sequences was analyzed using MEGA11 software to calculate the genetic distances within and between populations . DnaSP vne plots .COI gene sequences were proofread and edited by Clustal W, 168 gene sequences with 526 bp lengths were obtained, with 399 invariant sites, 46 parsimony-informative sites, and 115 variant sites. The average contents of bases T, C, A, and G in the COI sequences were 25.3%, 18.1%, 28.1%, and 28.6%, and the content of A+T (53.4%) was higher than that of C+G (46.7%), showing an AT bias , one haplotype in the HH population (Hap3), and five haplotypes in the TH population . Based on Kimura’s two-parameter model, the ML phylogenetic tree of the 11 haplotypes was constructed with C. dabryi (GenBank accession number: EF467625.1) as the out group. From the evolutionary tree, the haplotypes were mainly divided into three branches. Hap6 and Hap11 as well as Hap4 and Hap9 each clustered into one branch, mainly from the SH and TH populations, and the remaining seven haplotypes clustered into one branch, including five populations  with the CJ population and the smallest variation in the HH and GH populations  [C. alburnus population showed high haplotype diversity and high nucleotide diversity, and it is speculated that this situation may be due to the secondary contact of independent populations [C. alburnus has different ecological protections in the different lakes. The SH population is possibly affected by the active release of cultured fish, avoiding inbreeding and bottleneck effects and leading to population mixing and the random exchange of genes, resulting in increased genetic diversity. However, the CJ and HH populations have been overfished for many years, and the fishery resources have seriously declined. The habitats have changed, and the germplasm resources have declined. Under the influence of net-enclosure aquaculture facilities, GH has not yet fully restored its fishery resources, resulting in the low genetic diversity of C. alburnus.Genetic diversity is a prerequisite for species to adapt to environmental changes, and its level determines the long-term viability and evolutionary potential of species. The conservation of genetic diversity is of vital importance for the long-term survival of species. The genetic diversity of species is an important part of biodiversity research and reflects the ability of species to adapt and evolve in response to environmental changes. The higher the genetic diversity, the stronger the environmental adaptive ability . Among t= 0.007) , the Thr= 0.007) , Xingkai= 0.007) . Geneticulations . TH is tC. alburnus populations were calculated to evaluate the genetic differentiation among populations, and the results showed that the Fst of the SH population was larger (Fst > 0.25) than those of the other four populations, with the highest degree of differentiation with the Changjiang River population (Fst = 0.51712). The genetic variation was mainly from within the population, and the intra-population variation was much greater than the inter-population genetic variation, which was consistent with the genetic differentiation coefficient (Fst) of the C. alburnus population, which showed negative values when the intra-population variation was greater than the inter-population variation [Fst is an important indicator of the degree of genetic differentiation among populations . In thisariation .C. alburnus [Different geographic populations tend to have significant genetic differences due to isolation, and geographic isolation limits gene flow and leads to a high degree of genetic differentiation among populations . From thalburnus .C. alburnus both indicated that the C. alburnus population was relatively stable and that the historical population dynamics did not significantly deviate from equilibrium. The neutral test showed that the overall Tajima’s D was negative and Fu’sFs test results were positive values. The mismatch analysis plot was a multi-peaked curve, which also indicated that the population was stable. The BSP further verified that the effective population of C. alburnus did not experience significant population expansion. In terms of historical evolution, the population experienced the last major ice age during the late Quaternary ice age 0.29 million years ago. Although alternating climate changes had a significant impact on the population, the Bayesian skyline diagram reflects a small effect on the effective population size of C. alburnus with the end of the last ice age and sea level rise due to climate warming. Populations of C. alburnus continued to spread outward, and in subsequent evolution and habitat changes different haplotypes were gradually generated, which formed a rich pattern of genetic structures.Historical population dynamics can reflect the influence of historical events such as past geological climate change and human activities on the current species distribution ,34. GeneC. alburnus was analyzed, and it indicated that populations with higher genetic diversitycan be managed by establishing conservation units. For the low genetic diversity of C. alburnus, populations should be enhanced through the breeding of C. alburnus germplasm resources and the protection of the survival environment. However, using individual mitochondrial sequence markers for population genetic analyses still has limitations, and subsequent studies should be conducted in combination with other methods such as the RAD (restriction-site-associated DNA) and GBS (genotyping by sequence) research methods to ensure more accurate results and an all-round assessment of the germplasm resource to provide data to support the sustainable and healthy development of C. alburnus.In this study, a genetic diversity analysis of five different populations of


In his famous 1972 paper, Richard Lewontin used ‘classical’ protein-based markers to show that greater than 85% of human genetic diversity was contained within, rather than between, populations. At that time, these same markers also formed the basis of forensic technology aiming to identify individuals. This review describes the evolution of forensic genetic methods into DNA profiling, and how the field has accounted for the apportionment of genetic diversity in considering the weight of forensic evidence. When investigative databases fail to provide a match to a crime-scene profile, specific markers can be used to seek intelligence about a suspect: these include inferences on population of origin (biogeographic ancestry) and externally visible characteristics, chiefly pigmentation of skin, hair and eyes. In this endeavour, ancestry and phenotypic variation are closely entangled. The markers used show patterns of inter- and intrapopulation diversity that are very atypical compared to the genome as a whole, and reinforce an apparent link between ancestry and racial divergence that is not systematically present otherwise. Despite the legacy of Lewontin's result, therefore, in a major area in which genetics coincides with issues of public interest, methods tend to exaggerate human differences and could thereby contribute to the reification of biological race.This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’. Lewontin found that 85.4% of total human diversity was contained within populations, and he emphasizes his point that ‘less than 15% of all human genetic diversity is accounted for by differences between human groups’ with an exclamation mark. However, in 1972, these same polymorphic markers formed the basis of another field, with a different aim: attributing a biological sample to an individual [When Richard Lewontin wrote his seminal 1972 article, ‘The apportionment of human diversity’ [The lens of Lewontin allows us to see how unchanging and intractable some of the problems are: what characteristics we use to classify populations, how we name them and how they should be grouped in higher level comparisons. Lewontin's reliance on proteins, rather than DNA, brings phenotypes into play, and this leads to the uncomfortable intersection between genetic diversity and natural selection, and the characteristics, such as pigmentation, that are among the traditional racial classifiers. The fact that forensic genetics exists to serve criminal justice systems, and that such systems fail to treat all ethnic groups equitably, lends particular importance to this link with race.. 2a), providing him with an ‘embarras de richesse’ of data [The very first known human genetic polymorphism, variation in the ABO blood group system, was identified by Karl Landsteiner in 1900  and formfigure 1 of data . A syste of data : ‘to detForensic biologists went on to combine sets of these classical polymorphisms to reduce the random match probability RMP; , the cha−26 [It was the development of DNA-based analysis in the mid-1980s that relegated Lewontin's classical polymorphisms from forensics and began the modern era of robust individual identification. Initially, this was via DNA fingerprinting , based o−26 .STR profiles are digital—each allele is designated by a number reflecting its number of repeat units—and therefore ideal for databasing. This allowed the development of large investigative databases containing profiles obtained from convicted individuals, suspects and crime-scene samples. The first national DNA database to be developed (in 1995) was that of the UK , which b. 3The forensic geneticist needs genotypes that provide robust individual identification, an aim that emphasizes variation within the population: calculating a RMP to evaluate the significance of a match can then be done by compiling allele frequency data from that population, and assuming homogeneity and random mating. However, this raises two issues: which population is relevant to a particular case? And can population substructure invalidate the assumptions made in RMP calculations? These questions formed some of the battle-lines in the so-called ‘DNA fingerprinting wars’ of the 1990s, in which Lewontin, together with Daniel Hartl , was a vx should be assumed, where x is the population database size [Accustomed to the compendious collections of population data on classical markers , Lewontiase size . Howeverase size . LewontiN, where N is the number of individuals in the database (and 2N the number of genomes). A second NRC recommendation was for an adjustment to account for population structure, using a correction factor known as θ. For US populations, a conservative value of θ = 0.01 is recommended—this is at least an order of magnitude higher than empirically measured values; for ‘some small, isolated populations’, a higher value of 0.03 can be used. When factored into calculations [θ has the effect of somewhat elevating genotype frequencies.When a crime-scene profile matches a suspect, but the only information available about the perpetrator is the DNA profile itself, then the choice of reference population for calculating the RMP becomes particularly important. If there were major differences in allele frequencies between different populations, then a DNA profile might be very rare in one population, strongly incriminating the suspect, but orders of magnitude more common in another. The United States National Research Council (NRC) 1996 report [ulations , θ has tThese kinds of compromises lack rigour but were justified as part of a conservative approach to statistics that favoured the defendant in a case . However. 4No nation holds a ‘universal’ DNA database containing the DNA profiles of all its citizens . A consIntelligence can also be sought more directly by attempting to infer characteristics of the suspect from the crime-scene sample. Here, three areas have been focused upon: BGA, externally visible phenotypes and age . This reIf a population geneticist today wished to study the ancestry of an unknown individual sample, they would resort to genomewide analysis via a chip typing hundreds of thousands of SNPs, or even whole-genome sequencing. But forensic scientists do not usually have this luxury, since the amount and quality of DNA available is often low ,33. FurtFST of approximately 4.5%, measured in the highly diverse Human Genome Diversity Project (HGDP) panel of indigenous populations [FST-based analysis of a large worldwide dataset based on the 13 CODIS loci indicated that these STRs systematically underestimate inter-population genetic variation [FST , theθ (discussed in the section above), is equivalent to FST if random mating is assumed within sub-populations. The θ values recommended by the NRC  are considerably smaller than the global CODIS data ; such lta  individuals were resistant to infection by the malaria parasite Plasmodium vivax [To build panels of markers to predict the population of origin more robustly, loci were sought that maximized allele frequency differences between populations . As Lewontin observed , such maum vivax . This saum vivax , and todum vivax .δ  but today most sets are SNP-specific. One example designed for forensic use at a global level is a panel of 55 AIM SNPs [K) was eight, and the pattern of regional variation essentially resembled that observed for larger numbers of genomewide markers [Binary AIMs were defined as variants exceeding some threshold, e.g. 50% ) in paire.g. 50% ; with anAIM SNPs  that is  markers ,45. Othe markers , and Eas markers . At the . 5Traits that are forensically useful are those that a witness might observe and are collectively known as externally visible characteristics (EVCs). EVCs that are predictable from DNA variants need be largely genetically determined, and to have relatively simple genetic architecture. One such phenotype that has long been incorporated into standard DNA profiling is sex, predicted via a test for the presence or absence of the male-determining Y chromosome . Beyond The global apportionment of diversity in skin colour differs from that of hair and eye colour, reflecting differing evolutionary histories. Skin colour in indigenous populations shows a globally non-random geographical distribution, with people having the darkest skin in the tropics, and those with lighter skin in more northerly regions. The most widely held theory to explain the pattern of depigmentation from the human ancestral state of dark skin is the need to synthesize vitamin D in regions of low UV radiation . FollowiMany years of research into the genetic basis of human pigmentation  have yie. 6b), involved some rather arbitrary choices [b) include Caucasian and Mongoloid, two of Blumenbach's eighteenth-century races.In order to consider the apportionment of diversity among groups, we first need to define the groups. Lewontin's list of 169 populations [ choices , and raiAs well as using an SNP chip, today's population geneticist would also be likely to use a classification scheme informed by ethnolinguistic affiliation, geography and subject self-definition: the 1000 Genomes Project  providesEDAR gene associated with thicker hair in Asians and a variant in the acetaldehyde dehydrogenase gene responsible for Asian alcohol flush reaction [Pigmentation phenotypes are a hallmark of many traditional race-based classifications , and in reaction . A move reaction .As well as robust prediction, an EVC has utility if it is generally rare in a population , since i. 7Lewontin , p. 397 It would be naïve to imagine that forensic scientists will give up their efforts to maximize intelligence from DNA evidence. However, it is also important to remember that these creative endeavours are undertaken because of the absence of universal forensic DNA databases. Indeed, the biases, ethical problems and invasions of privacy that the armoury of investigative methods present have been used to bolster the arguments for universal databasing. It has been argued that universal databases would be fairer to all citizens than the current discriminatory investigative databases, would aid exonerations of innocent people, would deter crime and would eliminate the invasion of privacy represented by mass-screens (or ‘dragnets’) and familial searching . The risHow can the current situation be mitigated? There is a clear need for good practice in considering human classifications in imperfect but important forensic probability estimates. Labels matter, and should be used more carefully; this should include a nuanced consideration of admixture, rather than the shoe-horning of DNA donors into individual groups. It is promising that the field has woken up recently to the issue of ethics, and in particular to the question of the informed consent of participants in forensic population studies . This suFinally, as with those who study and write about population genetics and genomics, there is a responsibility for the scientist who uses and reports on forensic prediction of ancestry and phenotypes to think carefully about the language, the narrative, and the message that they convey to the public .


Ambrosia psilostachya DC.) arrived from North America to Europe in the late nineteenth century and behaves invasive in its non-native range. Due to its efficient vegetative propagation via root suckers, A. psilostachya got naturalized in major parts of Europe forming extensive populations in Mediterranean coastal areas. The invasion history, the spreading process, the relationships among the populations as well as population structuring is not yet explored. This paper aims to give first insights into the population genetics of A. psilostachya in its non-native European range based on 60 sampled populations and 15 Simple Sequence Repeats (SSR). By AMOVA analysis we detected 10.4% of genetic variation occurring among (pre-defined) regions. These regions represent important harbors for trading goods from America to Europe that might have served as source for founder populations. Bayesian Clustering revealed that spatial distribution of genetic variation of populations is best explained by six groups, mainly corresponding to regions around important harbors. As northern populations show high degrees of clonality and lowest levels of within-population genetic diversity (mean Ho = 0.40 ± 0.09), they could preserve the initial genetic variation levels by long-lived clonal genets. In Mediterranean populations A. psilostachya expanded to millions of shoots. Some of those were obviously spread by sea current along the coast to new sites, where they initiated populations characterized by a lower genetic diversity. For the future, the invasion history in Europe might get clearer after consideration of North American source populations of western ragweed.The perennial western ragweed ( Beyond biodiversity threats, invasive plants could also reduce yield from agricultural fields3 and directly affect human health4. The latter holds for species of the genus Ambrosia that produce highly allergenic pollen5. Particularly, A. artemisiifolia L. (common ragweed) is well-documented to cause health problems like allergic rhinitis (hay fever) and asthma in its native range (North America6) as well as in invaded continents like Europe, Asia, Australia, and Africa7. All Ambrosia species are wind-pollinated and produce high numbers of pollen during summer8. Common ragweed is most striking for its release of allergic pollen9, and some other species  are also known to cause allergic diseases10. At the moment, five non-native Ambrosia species are documented from Europe11: A. artemisiifolia, A. psilostachya, A. tenuifolia Schreb., A. trifida, and A. tomentosa Nutt. A sixth species, A. maritima L., is supposed to be native to the Old World13. Only one of the alien ragweed species is widespread throughout temperate Europe (i.e. A. artemisiifolia14), continuously enlarging its distribution area towards northern regions–possibly favored by climate warming17. Western  ragweed, A. psilostachya, is documented from several continents18 and occurs in many European countries19 behaving invasive in some regions21. It is treated taxonomically as conspecific to some other taxa from North America, i.e. to A. coronopifolia Torrey & Gray8. In its native range in Northern Mexico, USA  and all southern states of Canada6, A. psilostachya prefers open vegetation on sandy soils, i.e. prairie grasslands, but also alluvial areas and ruderal places21. This perennial herb is co-dominant to other grassland herbs and grasses, specifically in the Great Plains23, but prefers ruderal places towards the Great Lakes area and South-eastern Canada24. Naturalization of western ragweed happened even over a wider geographical range than in common ragweed due to the formation of root sprouts that survive cold winters belowground and allow clonal growth. An extensive review of specimens in European herbarium collections by the first author uncovered about 10% misidentifications by the collectors. Problems with identification resulted mostly from less accurate determination keys in floras like those by Hansen25, Sell & Murrell26, or Pignatti27. A. psilostachya is perennial with an extensive belowground root and shoot system11. Extensive populations are known from the Mediterranean coast of Spain28, France3, and Italy29 but also from the easternmost continental part of Europe (Russia20). A. psilostachya populations along the Northern European coastlines and inland sand habitats in Central Europe (Germany and Poland) are scattered. Perennation by root sprouts allows this invasive alien to survive in stabile populations on sandy substrates even in rather northern climates like Sweden  or north-western England . In such regions the annual A. artemisiifolia cannot naturalize due to failure of seed production12. The northernmost ephemeral finding of western ragweed is from Kurtto, Finland .Invasive species increase the local species richnessA. psilostachya to Europe is not well-documented; the first specimens were reported from Great Britain in 188030, France in 189131, Germany in 1894 , Italy in 1924 (herbarium Pisa), Spain in 194732, and Russia in 1934 (specimen in the herbarium of Ufa). In Northern Africa, the first specimen was documented in 1918 from Algiers . It is assumed that A. psilostachya arrived to Europe by traded crops21, i.e. potatoes from the Americas may have been contaminated by root fragments of western ragweed. No data is available about the likely source regions in America for the introductions to Europe. In Southern Europe, the invasion or expansion process is ongoing. In contrast, towards the north, there is no documentation about any increase of population sizes or further spread from initial places of introduction. Several accidental introductions in Central or Northern Europe  turned out to be ephemeral33.However, invasion history of A. psilostachya like the prevailing asexual reproduction by root sprouts were documented mostly from its native range in North America34. Wagner & Beals24 described a rapid increase of single shoot spatial expansion up to 2 m2 within the second year of establishment. Consequently, clonal growth might result in phenotypically uniform populations. In the native as well as in the (European) invasive range, A. psilostachya regenerates rarely from seeds35. From Europe there is only few data available about biology and ecological preferences. E.g. Fried et al.3 reported biological traits of French A. psilostachya seed lots and established populations’ habitat as well as soil preferences. Obviously, belowground spreading rates are quite high what can be deduced from the huge dominant stands in Italian coastal dunes21. Djemaa35 documented germination rates of only 3% in French seed lots. This can be due to unfavorable pollination conditions or to population genetics (e.g. inbreeding depression).Important biological traits of A. artemisiifolia is relatively well analyzed49, no research group has yet studied the population genetics of the clonal A. psilostachya neither in the native nor in its invasive range. No detailed taxonomic study was performed on this difficult diploid-polyploid complex since the monograph by Payne13. Greatly varying chromosome counts at diploid, tetraploid, hexaploid and octoploid levels are documented from North American populations of A. psilostachya52. In addition, reports from North America showed considerable morphological24 and phytochemical variation51 of A. psilostachya. But none of the authors linked this trait variation to ploidy levels.While population genetics and invasion history of A. psilostachya, one has to adapt methods when analyzing population genetic structure54. By setting the ranges for screening multilocus genotypes and adjusting the admixture models55, the outcome of the analyses  may be influenced. Newly introduced populations of partially clonal plants tend to sustain the initial within-population genetic structure56. Bottleneck effects as well as gene flow have less or even almost no consequence on the population genetics of clonal species57.In case of clonal species like 45 developed nuclear SSR-markers (Simple Sequence Repeats) for A. artemisiifolia and tested them in a population of A. psilostachya. These authors claimed that most of these markers are useful in describing western ragweed population genetics. In the present paper, we utilized these SSR markers to dissect the population genetic structure of A. psilostachya in Europe, providing insights into the genetic differences considering varying population sizes and local introduction histories.Meyer et al.A. psilostachya populations in Europe? (2) Is there an effect of different degrees of clonality within the populations on the invasion process and success across Europe? (3) How are genetic diversity patterns correlated to presumed age of populations  and/or population sizes? (4) Are there different possible centers of introduction detectable based on the genetic structuring? (5) How much do population genetic characteristics differ between the two successful Ambrosia invaders, i.e. the annual A. artemisiifolia and the perennial A. psilostachya?We therefore aim to answer the following questions: (1) How strong is the genetic differentiation of 58. The frequencies of null alleles estimated over all populations ranged between 0.01 and 0.27 . Significant linkage disequilibrium was detected among loci as well as among populations and regions.Based on extensive studies on literature and herbarium collections reviewed by the first author, we sampled 60 populations from Middle Sweden to Southern Italy and from Spain to Croatia. From 1005 analyzed individuals representing 60 European populations, 50 individual samples were excluded from further analysis due to unreliable genotyping fragment patterns and/or missing data. Therefore, running 955 remaining individuals, we could avoid that some R applications treat missing states as novel alleles which would lead to bias in our results59, our 15 loci should be adequate to detect a reliable number of unique MLGs. When comparing the genetic parameters calculated with and without clone correction . After clone correction, we gained 2.45 ± 0.63 alleles per locus  gives an estimate of the degree of clonality within the populations  or in populations up to a geographical distance of 170 km  across all populations was 2.45 ± 0.62 when only unique MLGs were analyzed . ANOVA and consecutive Tukey-HSD-Test for significant group median differences revealed no effect of regions (p = 0.371), population age (p = 0.457), or population size (p = 0.069) on Ho.The mean observed heterozygosity (He) across all populations was 0.43 ± 0.13 with the lowest within-population diversity (He = 0.18) observed in the Swedish population  and the highest (He = 0.63) observed in population Psi-6  , and specifically differing when He median values of Northern Europe populations are compared with those from Montpellier (p = 0.026) and from Venice (p < 0.001). He was also negatively correlated to latitude in both data sets . There were no differences of He with respect to population size (p = 0.103), but differences by age classes  was − 0.19 (± 0.30)  were detected; populations of Venice differed significantly from those of Northern Europe (p = 0.004) as well as from those of Barcelona (p = 0.014). Fis showed no difference with respect to population size (p = 0.987). Age matters for Fis in general ; but the differences between the specific age classes were not significant with respect to median Fis.The mean inbreeding coefficient  calculations  also showed relatively low levels of admixture. The populations around Montpellier, in the Venice region , and along the Southern Adriatic coastline (Bari region) are characterized by high degrees of admixture on average. Given these high levels of admixture in Bayesian Clustering, Principal Coordinate Analysis not surprisingly indicated relatively weak genetic structure  affiliated to the predefined regions showed that 10.4% of genetic variation occurred among these regions, and 40.3% of the genetic variation was found among populations within regions Table . Most geA. psilostachya, but also dispersal of clonal offspring between populations throughout Europe. Duplicated MLGs were found in 62% of the analyzed populations. This can be expected from the morphological traits of creeping roots and added buds producing shoot sprouts from belowground34. We provide prove for this obvious species trait based on genetic data for the first time. Expecting an important role of clonal reproduction in A. psilostachya our sampling strategy was to collect individual ramets at a minimum distance of one meter. Due to our sampling strategy, we expected that our sampling might catch enough ramets from different genets to perform a reasonable analysis of genetic variation. Wagner & Beals24 stated, from their explorative analysis of A. psilostachya in the field, that clonal exploration of genets might cover many meters distance. We also observed secondary thickening of the horizontal roots as well as expansion of still connected roots of three meters length. This allows the assumption of a relatively long-lived clonal integration.We identified substantial clonal reproduction within populations of A. psilostachya34. The degree of sexual reproduction can vary from one individual clone to another by many to no fruits produced31. Furthermore, the latter authors stated that individual clones may differ also by specific, but in their study not detected, morphological characters. In general, identification of different genets can be indicated from MLG heterogeneity at the population level. Interestingly, our analysis provided evidences in various directions. Based on Wagner & Beals24 clonal growth can expand up to hundreds of m2 in A. psilostachya. Consequently, we expected to find clonal duplicates, especially in older spatially structured populations that had enough time to expand by hectares. Interestingly, this phenomenon could be found only in one case: Psi-51 and Psi-52 , but not in the case of subpopulations along the coast near Venice  – each population at only about 100–200 m apart from its neighbor. Lack of human disturbance due to conservancy regulations may have limited these small parceled coastal populations in the Venice region to spread one hundred or more meters or more. In contrast, the military training area in Germany was formerly utilized by tanks that can easily transport contaminated sandy soil containing ragweed root fragments60 over hundreds of meters. Dispersal of either seeds or clonal fragments of A. psilostachya over long distances of up to 170 km from and to coastal dunes was also proved by our data  differed significantly by regions  of the perennial A. psilostachya correspond to Ho-estimate levels of the annual A. artemisiifolia (0.21–0.76) given by various authors (i.e. 69). Van Boheemen et al.46 gained on average lower Ho-values (0.16–0.30) for A. artemisiifolia, likely due to the use of SNPs (not SSRs) and to admixture processes. Mean values of expected heterozygosity of A. psilostachya were similar for the original and the clone corrected data. This corresponds to invasive Carpobrotus acinaciformis showing also no effect of clone correction in this respect70. Differences of Ho and He in A. psilostachya were significant when comparing the populations of Northern Europe, Bari and Barcelona regions (Mann–Whitney-U-Test: p < 0.001). Thereby, Northern Europe and Barcelona cover populations with low levels of admixture  for the original data set  and still significantly negative values  for clone corrected data. In comparison, the related C. edulis showed rather homozygosity excess possibly due to partial selfing.We found strikingly low values of Fis -values of many A. psilostachya populations are in contrast to those of the annual A. artemisiifolia that turned out to have significantly positive deviation from Hardy–Weinberg equilibrium in practically all publications available49. A. psilostachya populations in Europe are exposed to various effects that may cause distinct excess of heterozygosity. In case of small absolute population sizes, Balloux72 stated that there is a clear tendency to heterozygosity excess due to small effective population size . Such could hold for our small and old populations (relicts) in Northern Europe, where we have to assume problems with seed production and the dominancy of few well-adapted clones. But very small-sized Mediterranean populations with high genetic variation possibly represent remnants of formerly bigger populations that eroded along the sandy coastline . The longevity of successful, but few genets in isolated populations can go along preference of favoring basically heterozygous individuals over homozygous due to heterosis73 and inducing an excess of heterozygosity also in neutral loci of the genome by hitch-hiking71.The strictly negative Fis values were found in larger populations. However, in this case low sexual reproduction rates and spatially restricted dispersal may cause sub-structuring of even large populations71. Such could have happened with three nearby populations Psi-10, -11, and -12  that possibly developed from one founder population a long time ago, because they show ± the same degree of admixture  populations68. As self-incompatible species produce no offspring through selfing, this can lead to a significant deviation from random mating , significantly influencing Fis and generating heterozygote excess72. This factor might have caused genetic erosion of some few older populations of A. psilostachya. Distinct negative Fis means at population level may also be indicative of an insufficient number of MLGs represented in the samples74.Balanced ure Fig. ; on the Fis = 0.13). Comparable situations were observed in Psi-31  and Psi-15  with population totals of 80 and 60 ramets, and 18 sampled ramets each that were almost all unique MLGs . In all three cases the sites suffered from coastal erosion at the front line of old grey dunes. This argues for historical (old) admixture at place. Other small populations like Psi-27 , Psi-33  and Psi-49  represent spatially delimitable populations of only few m2 each, at young roadsides that were obviously of recent age. While Psi-27 was represented only by unique MLGs (G/N = 1), the other two populations comprised of several multiplied genets . In consequence, the mean Fis of Psi-27 was moderate (−  0.29) whereas the other two populations showed strongly negative values of Fis =  −  0.70 and −  0.79, respectively. These very low population means of Fis might indicate significant undersampling74 or an initial population undergoing a bottleneck phase72, respectively. Based on our data we could not identify any bottleneck effects, in general. Small but older populations like Psi-15, Psi-31 and Psi-34 obviously consisted of several MLGs that may have survived since foundation due to clonal persistence and may therefore still represent the genetic structure of the initial colonization stage.There is no clear mono-factorial picture in our data. In a very isolated small population with very few ramets  all 20 sampled ramets  turned out to represent unique MLGs  or “A. artemisiifolia” in the north, respectively. Our sampling of verified A. psilostachya finally resulted in 60 populations listed in Table A. coronopifolia Torr. & A. Gray that was and is still in use in some databases83 and older literature is synonym to our taxon. Ten of the selected populations were tested for nuclear DNA-contents providing graphs that indicate identical ploidy levels relative to the respective reference  based on 15 microsatellite loci  previously developed at INRAE Dijon, France for A. artemisiifolia45. PCR products were labelled with one of four fluorescent tags  and loaded on an ABI 3730XL capillary DNA analyzer (Applied Biosystems) using the size standard GS500 LIZ. We used Peakscanner version 1.0 (Applied Biosystems) to read allele sizes. Poorly performing individuals with missing genotype call were excluded from further analysis to avoid bias in the data analysis58.For DNA extractions, one small fragment of each leaf sample was placed in a 2 ml microtube containing one steel bead and 400 µl extraction buffer85 estimating a bootstrap confidence interval for each locus using the methods of Brookfield86.The presence and frequency of null alleles was checked for each marker using R-package “PopGenReport” version 3.0.4A. psilostachya the minimum genetic distance was calculated from a relative dissimilarity distance matrix (threshold = 0.558). The number of 15 loci used in our study fits to the needs for detecting unique MLGs59. Using these identified MLGs per population , we estimated the following components of genotypic diversity in each population: Shannon’s diversity index (H), genotypic evenness (E), and the ratio of number of MLGs to the number of individuals analyzed (genets to ramets = G:N). G:N indicates the degree of clonality within the population. A value of one indicates purely sexual reproduction, while a value near zero indicates purely clonal reproduction.For identification of unique multilocus genotypes (MLGs) and genotypic  diversity of A. psilostachya, asexual reproduction can result in a single genet being represented by multiple physiologically independent ramets87. Thus, we identified shared multilocus genotypes (MLGs) within or (even) across different populations using R-package “poppr” version 2.8.258, which can be used to infer clonal membership to the same genet87. We kept only one of each MLG per population in the “clone corrected” (cc) data set that served finally for additional calculations of the genetic diversity measures H, E and allelic richness.In clonal organisms such as 88. To determine deviations from HWE in the 60 European populations of A. psilostachya GenAlEx version 6.50289 was used. Tests for conformity with HWE were based on Chi-square tests, determining whether the observed genotypic frequencies are deviating from expected frequencies by chance or due to a lack of random mating.As the concept of a population representing a group of interbreeding individuals is not straight forwardly applicable to species with clonal as well as sexual reproduction significant deviations from Hardy–Weinberg equilibrium (HWE) can be expected, as sexual and asexual reproduction may occur in parallelA) proposed by Brown et al.90. Fixation index (FST) matrices based on pairwise FST values were calculated for all pairs of populations and regions using R-package “hierfstat” version 0.04–2291.Furthermore, we checked for linkage disequilibrium (LD) based on 999 permutations using R-package “poppr” version 2.8.2 testing if populations are clonal (where significant disequilibrium is expected due to linkage among loci) or sexual (where linkage among loci is not expected), expressed by the index of association  best fitting the data93. The length of the burn-in period was 100,000 runs followed by 500,000 Markov Chain Monte Carlo permutations. 20 iterations were performed for each value of K ranging from 1 to 15. Optimal values of K were determined based on log likelihood values as described by Pritchard et al.92. Principal Coordinate Analysis was calculated to show the interference of all individuals based on their genotypic similarity using Nei’s genetic distances95.In addition, population structure was assessed using STRUCTURE 2.3.489 to describe the degree of similarity among regions and among populations within the regions. In addition, isolation by distance (IBD) was analyzed using R-packages “adegenet” version 2.1.196 and “MASS”97 based on Mantel test with 999 replicates between a matrix of Euclidean distances and a matrix of geographic distances. Spatial autocorrelation test in GenAlEx was based on the distribution of permuted (rp) values under the assumption of no spatial structure and 999 random shuffling of individuals among distance classes.In the next step, spatial autocorrelation analysis was performed using GenAlEx version 6.503IA, and FST-matrices were performed for two data sets, one containing all individuals, including multiples (duplicates) of the same MLGs (“ori”), and a second data set including only unique MLGs, subsequently called “clone corrected” data set (“cc”). Allelic richness per population was estimated using a rarefaction approach to correct for differences in populational sample size using R-package “diveRsity” version 1.9.9098. In addition, we estimated observed heterozygosity (Ho), expected heterozygosity (He), and the inbreeding coefficient (Fis) for both, the ori and the cc data.All genetic diversity calculations including null allele frequency analysis, HWE, Fis were obtained using 999 bootstrap permutations. Moreover, a hierarchical Analysis of Molecular Variance (AMOVA99) for populations and regions was performed using the R-package “adegenet” version 2.1.196 with statistical significance testing based on 999 permutations.Confidence intervals for Ho (ori and cc) and Fis (ori and cc) were treated by ANOVA and consecutive Tukey HSD for testing significant group median differences, and all other parameters were tested by non-parametric ranked Kruskal–Wallis-Test followed by a post-hoc Mann–Whitney-U-Test for significant group median differences. We tested for differences by six regions, four population age classes and five population size classes applying a significance level of p < 0.05 after adjusting by the Bonferroni correction for multiple tests (cf. Table To analyze the genetic structure among different groupings, each genetic parameter was at first tested by Kolmogorov–Smirnov for normality. In consequence, Supplementary Information.