The mountainous region between the Caucasus and China is considered to be the center of domestication for grapevine. Despite the importance of Central Asia in the history of grape growing, information about the extent and distribution of grape genetic variation in this region is limited in comparison to wild and cultivated grapevines from around the Mediterranean basin. The principal goal of this work was to survey the genetic diversity and relationships among wild and cultivated grape germplasm from the Caucasus, Central Asia, and the Mediterranean basin collectively to understand gene flow, possible domestication events and adaptive introgression.ST analysis and assignment tests. All of these analyses identified three genetic groups: G1, wild accessions from Croatia, France, Italy and Spain; G2, wild accessions from Armenia, Azerbaijan and Georgia; and G3, cultivars from Spain, France, Italy, Georgia, Iran, Pakistan and Turkmenistan, which included a small group of wild accessions from Georgia and Croatia. Wild accessions from Georgia clustered with cultivated grape from the same area (proles pontica), but also with Western Europe , supporting Georgia as the ancient center of grapevine domestication. In addition, cluster analysis indicated that Western European wild grapes grouped with cultivated grapes from the same area, suggesting that the cultivated proles occidentalis contributed more to the early development of wine grapes than the wild vines from Eastern Europe.A total of 1378 wild and cultivated grapevines collected around the Mediterranean basin and from Central Asia were tested with a set of 20 nuclear SSR markers. Genetic data were analyzed  to identify groups, and the results were validated by Nei’s genetic distance, pairwise FThe analysis of genetic relationships among the tested genotypes provided evidence of genetic relationships between wild and cultivated accessions in the Mediterranean basin and Central Asia. The genetic structure indicated a considerable amount of gene flow, which limited the differentiation between the two subspecies. The results also indicated that grapes with mixed ancestry occur in the regions where wild grapevines were domesticated.The online version of this article (10.1186/s12870-018-1351-0) contains supplementary material, which is available to authorized users. Vitis vinifera L., the commonly cultivated grapevine, is one of the most widely grown fruit plants in the world  for different K gradually increased reaching a maximum value at K = 3 with non-significant variation among replicate runs, beyond which the rate of increase between successive K decreased and variance among runs increased  and the other from Europe , and one group with the French, Georgian, Italian and Spanish sativa accessions (G1). As observed in the NJ cluster analysis and PCoA, there were genotypes with mixed ancestry in all three groups. The populations with the highest percentage of admixed samples were Armenia (39%) and Georgia (49%) for wild groups and France (32%) for sativa accessions  , while the lowest FIT and FIS values were detected for the VMC4f3.1 locus , and VVMD25 had the lowest FST value (0.056). The number of migrants (Nm) after correction for sample size was 1.33, when samples were arranged in 12 populations. When the samples were arranged in two subpopulations (sativa and sylvestris), Nm was 4.88.Population structure among the 12 tested populations, irrespective of the subspecies, was summarized by the Wright’s F-statistics .The AMOVA analysis is presented in Additional file The main objective of this study was to analyze the pattern of genetic diversity within and between wild and cultivated grapes from the Mediterranean basin and Central Asia – considered to be the center of domestication. We pooled information from six previous studies that examined both wild and cultivated accessions, and genotyped an additiopnal 403 wild accessions from the Caucases region and Croatia at 20 microsatellite loci. The microsatellite marker data from 1378 accessions was subjected to NJ clustering and Bayesian methods to elucidate groupings of wild grapevine populations and to infer gene flow and gene frequency changes that occurred during domestication.sylvestris and sativa, are based on leaf morphology and the dioecious state of wild forms. According to the model of Antcliff [sylvestris samples [Taxonomic distinctions between the two subspecies, Antcliff , the floAntcliff , 28, 29. samples  with a mV. vinifera included in this study exhibited high levels of polymorphism and heterozygosity across the 20 microsatellite loci and significant diversity was observed within and between the subspecies , left a genetic footprint in the Western European proles occidentalis accessions. This genetic kinship could also be a reflection of early breeding programs in the Mediterranean region where sylvestris or hybrid feral vines with superior fruit were utilized in crosses with domesticated lines.Within ars Fig. , while tsylvestris accessions from Georgia and Armenia overlapped and were closely associated with cultivated forms from Georgia, Pakistan and Turkmenistan. The close association of Georgian wild grapevines with Georgian cultivated accessions strongly supports their involvement in the initial domestication of grapevine [sylvestris vines might have contributed to the selection and introgression of genes into Western European grapevines in the later part of the domestication process , and Western European . This observation confirms earlier studies that suggested that proles pontica were gradually introduced by human migration towards Western Europe [proles occidentalis grapevines contributed to the early development of wine grapes to a much greater extent than the wild vines from Eastern Europe. Previous studies using SNPs markers [vinifera and presented evidence of introgression from local sylvestris as the grape moved into Europe, but the degree to which local Western European wild sylvestris genetically contributed to Western European vinifera cultivars remains a contentious issue. Our results suggest and support at least two separate domestication events that gave raise to cultivated grape; one derived from the Transcaucasia wild grape, and another from the wild grapes of Western Europe.It is difficult to suggest that wild grape forms homogeneous populations considering the vast geographic expanse and the often fragmented and isolated populations that occur under heterogeneous climatic conditions. However, our results suggest Georgia as an ancient center of grapevine domestication with its wild grapes closely related to the cultivated grapes of the same region  and Western Europe . Results also suggest that Western European wild grapes were related to cultivated grapes, and that Western European sylvestris contributed to the development of Western European wine grapes. The results also support at least two separate domestication events that gave raise to cultivated grape; one derived from the Transcaucasian wild grape and another from the wild grape of Western Europe.The two sub-species of V. vinifera germplasm, but also sylvestris accessions from North Africa and Central Asia. These wild grape relatives will have a key role in future grape and wine industry.Finally, wild grape germplasm can contribute many useful traits such as resistance to damaging pests and diseases, and better adaptation to climate change. Thus, we must intensify efforts to collect, characterize and preserve not only the Western and Eurasian wild Additional file 1:Table S1. SSR allelic profile of 1378 sativa and sylvestris grapevine samples genotyped at 20 SSR molecular markers. (XLSX 643 kb)Additional file 2:Table S2. Determination of flower phenotype and genotype. The APT3 gene marker distinguished females (F) from males (M) or hermaphrodites (H). SSR marker VVIb23 is tightly linked to the flower sex locus and the unique allele 282 is linked to hermaphrodism. (XLSX 57 kb)Additional file 3:Table S3. Ancestry values  for the genetic groups inferred by STRUCTURE analysis of 1378 sativa and sylvestris grapevine samples genotyped at 20 SSR loci. (XLSX 145 kb)Additional file 4:Table S4. Locus-wise genetic differentiation parameter comparisons of 12 populations from both V. vinifera subspecies sativa and sylvestris. (DOCX 19 kb)Additional file 5:Table S5. Results of the AMOVA analysis carried out among and within 12 populations of wild and cultivated grapevine. (DOCX 16 kb)


Dactylis, an important forage crop, has a wide geographical distribution in temperate regions. While this genus is thought to include a single species, Dactylis glomerata, this species encompasses many subspecies whose relationships have not been fully characterized. In this study, the genetic diversity and phylogenetic relationships of nine representative Dactylis subspecies were examined using SSR and IT-ISJ markers. In total, 21 pairs of SSR primers and 15 pairs of IT-ISJ primers were used to amplify 295 polymorphic bands with polymorphic rates of 100%. The average polymorphic information contents (PICs) of SSR and IT-ISJ markers were 0.909 and 0.780, respectively. The combined data of the two markers indicated a high level of genetic diversity among the nine D. glomerata subspecies, with a Nei’s gene diversity index value of 0.283 and Shannon’s diversity of 0.448. Preliminarily phylogenetic analysis results revealed that the 20 accessions could be divided into three groups . Furthermore, they could be divided into five clusters, which is similar to the structure analysis with K = 5. Phylogenetic placement in these three groups may be related to the distribution ranges and the climate types of the subspecies in each group. Group A contained eight accessions of four subspecies, originating from the west Mediterranean, while Group B contained seven accessions of three subspecies, originating from the east Mediterranean.The genus  Dactylis L. comprises wind-pollinated and out-crossing cool-season perennial grasses belonging to the grass tribe Poeae, the subfamily Pooideae, and the family Poaceae [Dactylis glomerata L. [Dactylis is native to the northern hemisphere and can be found throughout Europe, temperate and tropical Asia, North Africa, and the Canary Islands [The genus  Poaceae ,2. This erata L. , which werata L. ,5 and re Islands ,7,8. It Dactylis can be either diploid (2n = 14), tetraploid (2n = 28), or, in rare instances, hexaploid (2n = 42). Almost all diploids have restricted ranges and occur in particular regions, and together they account for about 5% of all wild Dactylis [According to chromosome number, Dactylis . TetraplDactylis . In manyDactylis , hexaploDactylis ,12,13,14Dactylis, making it difficult to validate any proposed species within the genus. Most subspecies were acknowledged by the early 1930s [Dactylis glomerata L., and eight subspecies [santai and “castellata” were described collectively, due to difficulties in differentiating them via flavonoid phytochemistry, enzyme, and morphology data [santai and “castellata” had been regarded as individual subspecies, since “castellata” was often treated as one subspecies since 1969 [It is clear that there is a large and continuous range of variation in the genus ly 1930s ,16,17,18ly 1930s . The taxbspecies ,20, therbspecies  have sugbspecies , the genbspecies  divided ogy data . Howeverogy data , in the Agropyron by Che et al., 2015 [Oryza by Nishikawa et al., 2005 [Sorghum bicolor and Sorghum sundanense by Zhan et al., 2008 [Glycine by Wu et al., 2000 [Cicer reticulatum by Sethy et al., 2006 [Dactylis genetic map [Dactylis [With the development of advances in biotechnology, DNA molecular markers have been used in the phylogenetic analysis of plants since the 1980s. Because DNA molecular markers are not affected by environment or gene expression but reflect the status of the entire genome, they offer some advantages over traditional phenotypic characters. They can be highly polymorphic while also being genetically stable, and so they are regarded as reliable tools for phylogenetic analysis. Simple sequence repeat (SSR) markers are tandem DNA repeats several nucleotides long that can be found in most eukaryotic genomes . Variatil., 2015 , Oryza bl., 2005 , Sorghuml., 2008 , Glycinel., 2000 , and Cicl., 2006 . These retic map  and in aDactylis ,36. IT-IDactylis  with refDactylis . IT-ISJ Dactylis .Dactylis.In this study, SSR and IT-ISJ markers were employed to test the nine subspecies, ranging from four different distribution ranges and three different climate types. The specific objectives were: (1) to study the genetic diversity of all nine subspecies; (2) to discuss the genetic relationship of these nine subspecies, hoping to provide more information for further study into the classification of the genus The 21 SSR primer pairs and 15 IT-ISJ primer pairs were used to amplify DNA fragments from the 20 accessions. A total of 196 bands were obtained from SSR primers, and all of these were polymorphic (100%), with an average number of 9.333 polymorphic bands per primer pair and a range of 6–13 bands. PIC values for SSRs ranged from 0.861 to 0.962, with an average of 0.909. The 15 IT-ISJ primer combinations amplified a total of 99 bands, and all of these were also polymorphic (100%) with a range of 3–10 bands. The average number of polymorphic bands per primer pair was 6.6, and the average PIC was 0.780, with a range from 0.545 to 0.957. These data indicate that SSR and IT-ISJ primer combinations exhibit high amplification efficiency and are reliable in the discovery of polymorphisms .The efficiencies of SSR and IT-ISJ markers were compared using the MI parameters . The IbaD. glomerata subsp. lusitanica) to 0.252 (D. glomerata subsp. hispanica), and Shannon’s diversity index ranged from 0.211 (D. glomerata. subsp. lusitanica) to 0.425 (D. glomerata subsp. hispanica). The average intra-population diversity was 0.321, and Shannon’s index for all taxa as a population was 0.448. Therefore, the proportion of intra-population diversity was 71.7%, and the proportion of inter-population diversity was 28.3%  to 0.491 .Nei’s gene diversity index within subspecies ranged from 0.135  to estimate the utility and efficiency of each marker . To our Dactylis subspecies contain abundant genetic diversity [Dactylis is a widespread genus, inhabiting many different geographical regions with different environments. In order to adapt to the environments of different geographical regions, Dactylis has been subject to long-term natural selection. Moreover, natural mutation and artificial selection have introduced high variation and abundant diversity in the genus.According to Vaiman et al. , loci poiversity ,47. Dactsmithii, belonging to the subtropical area, while it was clustered into Group A, together with some samples belonging to Mediterranean. All three groups contained samples from Europe, indicating they have a high level of genetic diversity and variation, and this result also indicated Europe to be one of the diversity differentiation centers of Dactylis [Dactylis subspecies.The phylogenetic analysis of the 20 accessions revealed that certain phylogenetic clades are correlated with distribution range and climate type. For the most part, the subspecies of different climate type clustered into different phylogenetic branches, with the exception of a single subspecies, Dactylis . GeneralDactylis , resultisantai and smithii were clustered into Cluster 1 in Group A, showing that the two subspecies appeared closely related, which is consistent with the study of Stewart and Ellison [lobata, a synonym of D. glomerata subsp. aschersoniana [lobata together with himalayensis and glomerata and forming Cluster 5 or Group C. However, it has been reported that subspecies lobata and himalayensis have both been found in cool temperate forests at relatively high altitudes in continental climates and thus have been assigned to the same group [himalayensis and glomerata was maximal at 0.491, which was also supported by the structure analysis result. The two subspecies had a very similarity genetic background, indicating that subspecies glomerata may have affinities with himalayensis, which were consistent with our phylogenetic analysis. Moreover, Stebbins and Zohary [glomerata may have evolved from the hybridization of lobata (aschersoniana) and woronowii and that some glomerata in the Alps may have evolved from the hybridization of rechenbachii and lobata (aschersoniana). Therefore, these three may have a very close relationship. In Group B and Cluster 4, two accessions of subspecies hispanica were closely related to marina, and structure analysis revealed them to have a very similar genetic background, which may reflect their similar distribution range and climate type. Moreover, according to the study reported by Martin Borrill et al. [hispanica is the principal subspecies found in regions with a Mediterranean climate, and marina Borrill can be found in Mediterranean coastal regions. Marina was separated from hispanica due to its epidermal papillae [The two subspecies  Ellison , in whicrsoniana , were alme group . They hame group , indicatpapillae , but thepapillae . TherefoD. glomerata subspecies (https://npgsweb.ars-grin.gov), and the climate type were listed in accordance with previous report [We selected 20 plant introduction (PI) accessions from 14 countries, including nine bspecies . Origin s report . US NatiEach accession was represented by 6–10 plants, and fresh leaf tissues were collected from each plant and preserved in silica gel desiccant. Genomic DNA was extracted using a modified CTAB method . The quaDactylis SSR primers have been described and 21 primers amplifying relatively more numbers and clear diversity bands were selected in our study , which includes the average band informativeness (Ibav) for the polymorphic markers and the effective multiplex ratio (EMR) [All analyses were conducted by grouping SSR and IT-ISJ marker data together. Unambiguous amplified bands of each SSR and IT-ISJ marker were scored as 1 for presence and 0 for absence. The total number of bands (TNB), number of polymorphic bands (NPB), and percentage of polymorphic bands (PPB) were obtained from the gels. The polymorphism information content (PIC) of each SSR and IT-ISJ locus was estimated using the method of Nei  accordinio (EMR) . Ibav waio (EMR) . Population genetic parameters including Nei’s gene diversity index (He)  and ShanDactylis subspecies may also be associated with their climate types. The materials from the Temperate type could be divided into individual Group C or Cluster 5, and the materials from the subtropical type together with some materials from the Mediterranean type formed one group (A), while the remaining materials of the Mediterranean were gathered into a different group (B). Furthermore, according to the origin of our materials, the materials from western and eastern Mediterranean could be divided into different groups (A and B).In this study, we compared the efficiencies of SSR and IT-ISJ markers, revealing that SSRs exhibit higher efficiency. The 20 accessions of 9 subspecies from various countries were included in our study, exhibiting a high level of genetic diversity. Furthermore, the result of cluster analysis had a certain relationship with distribution ranges. Phylogenetic analysis and structure analysis indicated that genetic relationships among


Brassica tournefortii) is a facultative autogamous annual native to Eurasia that has rapidly invaded the southwestern United States within the past century, displacing natives, and altering water‐limited landscapes in the southwest. We used a genotyping‐by‐sequencing approach to study the population structure and spatial geography of Sahara mustard from 744 individuals from 52 sites across the range of the species’ invasion. We also used herbaria records to model range expansion since its initial introduction in the 1920s. We found that Sahara mustard occurs as three populations in the United States unstructured by geography, identified three introduction sites, and combined herbaria records with genomic analyses to map the spread of the species. Low genetic diversity and linkage disequilibrium are consistent with self‐fertilization, which likely promoted rapid invasive spread. Overall, we found that Sahara mustard experienced atypical expansion patterns, with a relatively constant rate of expansion and without the lag phase that is typical of many invasive species.The specific mechanisms that result in the success of any species invasion case are difficult to document. Reproductive strategies are often cited as a primary driver of invasive success, with human activities further facilitating invasions by, for example, acting as seed vectors for dispersal via road, train, air, and marine traffic, and by producing efficient corridors for movement including canals, drainages, and roadways. Sahara mustard ( We also included observation data from our field collections, bringing our total number of localities to 2,915.We utilized distribution and locality records from herbaria to examine the geographic spread of Sahara mustard in North America through time. We realize these data often provide an incomplete picture of a species range perhaps due to uneven collection efforts that do not accurately represent invasion patterns . Spatial units were delimited by rounding geographic degrees to the nearest hundredth. Thus, records were classed into ca. 1 km2.2In Spring 2015, we sampled 7–20 (with an average of 14) individuals each from 52 locations  spanning a ca. 10° latitudinal and ca. 15° longitudinal gradient across the species’ invaded U.S. range in Spring 2015 Figure . Sites rWe extracted DNA from 760 individuals from 52 populations using QIAGEN DNeasy Plant Mini Kits (Qiagen). We estimated DNA concentrations via fluorometry  and tested DNA quality for a subset of samples via 1% agarose gel electrophoresis. Single nucleotide polymorphism (SNP) data were generated via nextRAD  sequencing  to test for contamination from species other than Sahara mustard. No plausible contamination was detected in the tested reads.Raw sequence data were processed using Trimmomatic software  that constructs population differentiation relationships  for each site and to calculate population‐level selfing rates (S = 2Fis/(1 + Fis)) and levels of outcrossing , consistent with the lack of a lag phase in the history of the invaded range. Herbaria records tracked the spread of Sahara mustard to Tucson, Arizona in the late 1940s, coastal California in the late 1950s, and more recently to Texas, Nevada, New Mexico, and Utah. Overall, Sahara mustard's range based on sampling sites currently stretches approximately 500,000 km2 based on herbaria records and our field sampling .We used 2,915 historic and contemporary locality records to study the history of Sahara mustard's range expansion. By interpolating the year of sampling with its geographic range, we infer that Sahara mustard underwent an atypical invasion with no detectable lag phase and a relatively constant postintroduction expansion pattern  revealed no clear spatial patterns across the invaded range Figure b. ClustePCA revealed similar population structure across the invaded range of Sahara mustard but suggested more admixture than TESS Figure . PC1 higNipomo, CA Cluster 3) contained the highest number of rare variants which, combined with assignment probabilities from TESS, suggested that this is the most recent introduction of Sahara mustard and has yet to spread out of this area Figure a. Removi containe3.3r¯d = 0.120, p = 0.009; Table Fis = 0.8425) and selfing (S = 0.9145), and the lowest levels of outcrossing (T = 0.0855). Cluster 2 exhibited lower levels of inbreeding (Fis = 0.7827), selfing (S = 0.8778), and higher levels of outcrossing (T = 0.1222) than Cluster 1. Cluster 3 exhibited similar levels of fixation (Fis = 0.7865), selfing rates (S = 0.8805), and outcrossing rates (T = 0.1195) to Cluster 2; suggesting Clusters 2 and 3 are utilizing more of a mixed breeding system of self‐fertilization and outcrossing. That being said, all three populations appear to overwhelmingly self‐fertilized (Table Linkage disequilibrium and overall genetic diversity were low across the invaded range of Sahara mustard (4Our study suggests Sahara mustard exists as three populations in the United States. The rapid spread and low genetic diversity of Sahara mustard are likely promoted by self‐fertilization, consistent with the observed expansion patterns and estimated selfing rates. The unusual spatial structure of non‐native Sahara mustard populations is most consistent with multiple introductions at Nipomo, Palm Springs, and Malibu, CA. Our work also suggests that subsequent range expansions have resulted in admixture among populations, which contributes to complex population structure. Despite these multiple inferred introductions, genetic diversity is generally low throughout the sampled locations and ecoregions. Low genetic diversity is likely the result of high self‐fertilization rates combined with founder effects, as suggested by other studies that have found self‐fertilization to be an important trait for colonization and rapid population expansion (Kalisz, Vogler, & Hanley, Spartina alterniflora are cross‐pollination limited in the San Francisco Bay area of California and individuals that have high selfing rates also produce high viable seed sets compared to nonselfing individuals (Daehler, The reproductive strategies invasives employ are a primary driver of invasive success Baker, . In thisDaehler, . This isDaehler, .Invasive species traits and their relative importance oftentimes vary as a non‐native species goes through the phases of introduction, establishment, and spread (Bock et al., Attempts have been made to predict Sahara mustard's presence and abundance under future climate scenarios (Curtis & Bradley, We generally detected low levels of genetic diversity across the invaded range of Sahara mustard; a pattern similar to other invasive species studied including those with mixed‐mating systems (i.e., Lott et al., Sahara mustard has a similar invasion history in Australia where it was introduced in the early 1900s and is presumed to have dispersed via the transcontinental railroad Kloot, . The firIn summary, our study is the first to document the genetic patterns of Sahara mustard's invasion in the United States and reveals the species exists as three populations with low levels of diversity—likely the result of self‐fertilization, combined with human‐mediated dispersal. The native range origins of these introductions remain unidentified. Future research is needed that will apply similar population genetic methods in the species’ native range to identify source populations and reconstruct the species’ invasion history globally. It will also be valuable to investigate the genetics of herbarium samples in the invaded ranges of the species to better understand invasion dynamics of this species. Successful management efforts will likely be achieved if human‐mediated spread is curtailed along roadways first, with special focus on newly introduced populations like that at Nipomo, CA, which have not yet expanded. Future introductions should be expected, necessitating further investigation as new localities are discovered. Additionally, future research focusing on phenotypic plasticity is needed to reveal the strategies that enable Sahara mustard to invade multiple environments despite low genetic diversity.None declared.D.E.W. conceived of and designed the project with help from T.E.H., K.J.C., and J.D.G. Additionally, D.E.W. and K.J.C. carried out field and laboratory work. D.E.W., K.J.C., and O.F. performed analyses and drafted the manuscript with T.E.H. All authors contributed to writing the final version of the manuscript. Click here for additional data file. Click here for additional data file.


Filipendula vulgaris (Rosaceae) and related species.Polymorphic microsatellite markers were developed as a tool for genetic investigations of F. vulgaris using the Illumina MiSeq platform. Polymorphism of the 17 loci was tested in three populations. We identified a total of 203 alleles, ranging from four to 19 per locus, with levels of observed and expected heterozygosity ranging from 0.267 to 1.000 and 0.461 to 0.899, respectively. Primers were also tested for cross‐amplification in three related species. Seven loci successfully cross‐amplified in F. camtschatica and F. ulmaria, whereas we detected positive cross‐amplification in only three loci in Geum urbanum.Seventeen new polymorphic microsatellite markers were developed for F. vulgaris and related species.The newly developed microsatellite primers will serve as useful genetic tools for further population genetic studies on  Filipendula Mill. (Rosaceae) contains 15 species of perennial herbaceous flowering plants native to temperate regions in the Northern Hemisphere  Maxim. and F. vulgaris Moench   Ball, . WhereasFilipendula vulgaris is a perennial diploid species  Maxim., and Geum urbanum L. The microsatellite markers developed here will be used to assess genetic diversity in investigations of population genetic structures, mating systems, and phylogeographic patterns of these species.F. vulgaris was extracted from 20–25 mg of silica gel–dried leaf tissue using the DNeasy Plant Mini Kit , following the manufacturer's instructions. A DNA library was prepared with a NEBNext Ultra II DNA Library Prep Kit for Illumina  as described in Belyayev et al. (F. vulgaris were then removed by mapping the trimmed reads to the complete chloroplast sequence of Rosa roxburghii Tratt. (GenBank accession no. KX768420) using Bowtie 2 aligner with default settings  were randomly selected and tested for amplification in seven individuals of Appendix . Reactiof (Weir and Cockerham, Summary statistics were calculated for each microsatellite locus and population combination, i.e., the number of alleles, observed and expected heterozygosities, and inbreeding index The summary statistics for genetic variability of the loci and populations studied are presented in Table F. camtschatica and F. ulmaria, and three successfully cross‐amplified loci in Geum urbanum (Table Cross‐amplification testing showed seven successfully cross‐amplified loci in um Table .F. vulgaris. The cross‐species amplification of these markers indicates that half of them may also be useful in the related species F. camtschatica, F. ulmaria, and G. urbanum. The markers developed here constitute a valuable tool for genetic investigation of population structure, gene flow levels, and mating systems, as well as conservation genetic studies of the Filipendula genus and will facilitate ecological and evolutionary studies of F. vulgaris and related species.Seventeen polymorphic microsatellite loci were successfully developed for D.Č., K.K., P.V., and B.M. conceived and designed the study. K.K., P.V., and B.M. collected the plant material. D.Č. and K.K. supervised the laboratory work. D.Č. and B.M. analyzed the data and drafted the manuscript. All authors reviewed the manuscript and approved its final version.


Russula is among the largest and morphologically most diverse basidiomycete genera in the world. They are broadly distributed both geographically and ecologically, forming ectomycorrhizal relationships with a diversity of plants. Aside from their ecological roles, some Russula species are gourmet mushrooms. Therefore, understanding their population biology and fundamental life history processes are important for illustrating their ecological roles and for developing effective conservation and utilization strategies. Here, we review recent population genetic and molecular ecological studies of Russula. We focus on issues related to genet sizes, modes of reproduction, population structures, and roles of geography on their genetic relationships. The sampling strategies, molecule markers, and analytical approaches used in these studies will also be discussed. Our review suggests that in Russula, genets are typically small, local recombination is frequent, and that long-distance spore dispersal is relatively uncommon. We finish by discussing several long-standing issues as well as future trends with regard to life history and evolution of this important group of mushrooms.The mushroom genus  In this relationship, fungi help plants obtain minerals and water as well as enhance plants’ resistances against pathogen infections and environmental stresses  are found in several continents  (Bergemann and Miller Russula changbaiensis (northeast China), Russula tsokae , Russula galbana , and Russula caeruleoanulata (west Africa) , challenging the “late-stage” definition of Russula.Species in the genus ons Nara . HoweverRussula were small, observations of a few large genets do require explanations. These large genets suggest that some genotypes can expand asexually by mycelia growth and/or persisted over a long period of time below ground. However, other factors could also contribute to the inferred large size for a small number of genets, including human activities, transportations by fungusivore, the physical movement of soil and/or other events that may act to repeatedly inoculate the same genotype in the forest. Additional factors including experimental factors, such as mistaken specimen identity and a limited power of the molecular markers to separate closely related genotypes , may also contribute to the identifications of identical genotypes from distant locations. Despite these potential problems, the current results suggest that the reproductive biology of Russula and other ECM fungi likely vary among species of the same genus and among ecological niches of a specific species.While most genets in Suillus bovinus and Suillus variegatus, genets in older forests are fewer but bigger than those in younger forests  has traditionally been used as an indicator to infer reproductive biology not only in EMF but also in other species , which suggested frequent outbreeding and recombination and heterozygous advantage in this population. In contrast, a positive ISF value (0.151) obtained in a location of the lodgepole pine suggested inbreeding and outbreeding depression. It should be noted that there was limited statistical support for either population to show significant departure from random mating. Despite the lack of statistical support, there seemed evidence for changes in reproductive biology of R. brevipes associated with tree stand age since the lodgepole pine forest (100 years) is much older than the Sitka spruce forest (40–60 years). As mentioned before, stand age was correlated to genet size of two Suillus species. However, genet sizes at both the Sitka spruce forest and the lodgepole pine forest are quite small. In addition, it is presently unknown whether the observed difference was due to tree-age and host plant species.Inbreeding coefﬁcient . Excluding the specific locus, no significant allele association was found among other loci, suggesting random recombination in natural R. brevipes population  . However, the role of wind-mediated gene flow in large-scale population genetic studies is still controversial. Several studies have assessed the aerodynamics of spore transmission in air. In nature, air-mediated dispersal pattern of spores seem to follow a Poisson distribution pattern with most spores land nearby their parental sporocarps . Results showed all five loci each had at least one haplotype distributed in most local populations. More importantly, the AMOVA test showed that over 90% of the observed genetic variation was found within individual local populations, consistent with significant gene flow among populations. However, while some pairs of populations showed significant genetic differentiation, the relationship between pairwise population genetic differences (STF) and geographical distances was statistically insignificant. The allelic association tests among loci indicated that population of R. virescens in southwestern China was randomly mating.Cao et al.  used seqR. virescens, phylogeographic analyses among distinct populations of the Russula griseocarnosa species complex in southwestern China showed significant genetic differentiation, with three distinct geographic regions each having a different genetic population . However, they found that those two morphological types have identical sequences at the internal transcribed spacer (ITS) regions and the two populations formed a randomly mating population. Here, the genetic results were incongruent with morphological data.In practice, it is often impossible or impractical to analyze all individuals from a population. Selective sampling based on an established set of criteria is often chosen to reduce the workload while still maintaining the sample’s representativeness  is often the problem. For example, for edible mushrooms, local residents may pick them, leaving relatively few or none for outside researchers to get samples. Indeed, without help from local residents and institutions, to gather the complete or representative fruiting body samples for genetic analyses in a big area is often very difficult or impossible. In addition, many years may be spent in collecting fruiting body samples when the analyses require samples from many distinct locations. An alternative approach is emerging recently that involves obtaining mycelial samples directly from the soil instead of relying on fruiting bodies. Here, species-specific primers are needed in order to obtain molecular information from the metagenome samples. In addition, since many mycorrhizal fungi are edible, especially for Russula species, including RADP, AFLP, SSR, ISSR, and sequencing of variable genetic loci (Sunnucks A common analysis in population genetic studies is to examine the relationship between genetic distance and geographical distance. It is often assumed that geographically closely related samples should be genetically more similar to each other due to their close breeding relationships. However, to effectively identify the genetic relationships among strains, adequate genetic markers are needed. These markers must have an adequate resolution to distinguish genetic individuals, particularly for a small quadrat. Several types of molecular markers have been used for fine-scale and large-scale population genetic analyses of Sunnucks . HoweverSunnucks . For popSunnucks . RAPD ma5.5.1.Russula are excellent candidates for population genomic studies on ecological issues. These organisms are broadly distributed EMF and can form extensive associations with numerous types of hardwood trees in various habitats. They play significant roles in plant health. For example, population genomic studies of Russula could help solve some historical biogeographic mysteries. The effects of the last ice age on flora and fungal communities have been hotly debated in recent years. The maximum glaciation in the Northern Hemisphere was considered to cover most of North America (Richmond and Fullerton Russula should be able to provide excellent information from which to understand these issues.Current high-throughput sequencing technologies are revolutionizing population genetic studies of many organisms. These technologies have reduced sequencing costs significantly and allowed obtaining thousands of sequences relatively affordably for most research labs in a relatively short period of time. In model species, population genomics has become feasible and the new norm. Population genomics mainly focuses on the patterns of evolutionary processes’ impact on genomes through inspecting the differentiation among genomes within and among populations (Luikart et al. 5.2.Russula can be highly variable and their species identifications are difficult, even for mushroom experts. Although the distribution of allele frequency and pairwise STF values can help identify the relationships among populations, population genetic analysis alone is often insufficient to provide a complete historical account of population histories and speciation (Bergemann and Miller Russula are difficult to distinguish morphologically, morphology-based species identification can provide misleading information on population structures within a species. Instead, other types of analyses such as phylogenetics and tree networks are necessary to help with species delineation and infer population level processes. As shown in Li et al. (R. griseocarnosa. Only after such cryptic species are identified and sorted can population genetic studies within individual species be accurately performed.Population genetics focuses on analyzing the distribution and alteration of allele frequencies within and between populations. The definition of population should reflect the natural mating community of a certain species. Morphological characteristics within and among species in i et al. , the ana5.3.Russula have been reported recently from tropical zones (Riviere et al. Russula is the most specious genus in family Russulaceae and was first established based on the studies of macro fungi in northern Europe. Historically, many species in Russula were established based primarily on European specimens and their taxonomic criteria. The tropical regions contain a high diversity of Russula species and some of the criteria used to identify species in northern Europe may not be applicable for identifying those in the tropics. To solve this problem, molecular systematic studies of samples from different geographic origins are needed in order to obtain accurate information about species distribution of Russula. Furthermore, by comparing population or community structures between temperate and tropical regions, the investigations of species differentiation, adaptive evolution, and species origin are now feasible.Tropical forests have been traditionally regarded as the Eden of saprophagous organisms but they are poor in EMF (Malloch et al. 5.4.Russula or any EMF based on below-ground mycelia alone, regardless of whether they produce above-ground fruiting bodies.While most population genetic studies have focused on analyzing above-ground fruiting bodies, the above-ground sporocarps are unlikely to reflect the below-ground ectomycorrhizal fungal community (Gardes and Bruns R. xerampelina and R. ochroleuca, their above- and below-ground populations seemed similar to each other while for R. amoenolens, there was little similarity between the two components (Agerer For species that frequently produce above-ground fruiting bodies, a central issue is whether population structures represented by below-ground ectomycorrhiza and above-ground fruiting bodies are consistent. At present, the results of such comparisons differ among species. In both s Agerer . HoweverR. brevipes could maintain a long-term connection with plants (Bergemann and Miller Russula can immediately form ectomycorrhizae with seedlings in a wildfire-burned forest by surviving hyphae (Horton et al. in vitro infection tests using monokaryotic strains have confirmed this prediction (Tranvan et al. Aside from such comparisons, another long-standing issue of ectomycorrhizae is the prevalence and longevity of monokaryotic hyphae in nature. Current researches have focused on dikaryotic mycelia and there was a report that dikaryotic hyphae of No potential conflict of interest was reported by the authors.


Cucumis sativus L.). The GBS data, derived from 1234 cucumber accessions, provided more than 23 K high-quality single-nucleotide polymorphisms (SNPs) that are well distributed at high density in the genome (~1 SNP/10.6 kb). The SNP markers were used to characterize genetic diversity, population structure, phylogenetic relationships, linkage disequilibrium, and population differentiation of the NPGS cucumber collection. These results, providing detailed genetic analysis of the U.S. cucumber collection, complement NPGS descriptive information regarding geographic origin and phenotypic characterization. We also identified genome regions significantly associated with 13 horticulturally important traits through genome-wide association studies (GWAS). Finally, we developed a molecularly informed, publicly accessible core collection of 395 accessions that represents at least 96% of the genetic variation present in the NPGS. Collectively, the information obtained from the GBS data enabled deep insight into the diversity present and genetic relationships among accessions within the collection, and will provide a valuable resource for genetic analyses, gene discovery, crop improvement, and germplasm preservation.Germplasm collections are a crucial resource to conserve natural genetic diversity and provide a source of novel traits essential for sustained crop improvement. Optimal collection, preservation and utilization of these materials depends upon knowledge of the genetic variation present within the collection. Here we use the high-throughput genotyping-by-sequencing (GBS) technology to characterize the United States National Plant Germplasm System (NPGS) collection of cucumber ( Genetic analysis of the US cucumber collection provides valuable insights into the plant’s diversity and generates a core resource for future research. Breeding crop plants requires in-depth understanding of plant genetics and the identification of key genes that enhance traits such as disease and stress resistance. Zhangjun Fei at the Boyce Thompson Institute in Ithaca, Rebecca Grumet at Michigan State University, and co-workers across the US used high-throughput genetic sequencing to characterize the 1,234 cucumber accessions held by the US National Plant Germplasm System. The team uncovered 23,000 specific genome variations that revealed the genetic diversity, population structure and genetic differentiation of the cucumber. They identified genome regions associated with 13 traits important to cultivation and selected 395 accessions covering 96 percent of the collection’s genetic variation to make a publicly accessible core of data. Collections are typically made from locations throughout the globe, with particular emphasis on centers of crop diversity. The importance of such collections as a critical first step to conserve biological variation, especially in light of genetic erosion resulting from habitat loss, adoption of modern varieties, and climate change, is increasingly recognized as a critical global good, both in scientific and broader public spheres3. While creation and maintenance of these valuable collections is essential, questions arise as to how to catalog, unlock, manage, and preserve the valuable diversity they contain. How do we evaluate the extent and nature of variation that exists within the collection? How can we access that variation for crop improvement? Fortunately, the past decade has ushered in powerful genomic tools that allow for high throughput, high resolution, genetic characterization, while also providing breeders more efficient access to, and use of, the diversity available within collections.Improvements in crop yield, ability to withstand abiotic and biotic stresses, and superior product quality all depend on genetic variation for key agronomic and horticultural traits. In search of such variation, breeders frequently turn to germplasm collections to find new sources of valuable characteristics, especially resistances to diseases, insects, and environmental stresses such as heat, drought, salt, or cold. To facilitate these breeding efforts and maintain critical diversity for future generations, many national and international institutions have developed extensive germplasm collections to provide repositories of genetic variation. More than 1750 gene banks have been established worldwide4. Cucumber (Cucumis sativus L.), a member of the Cucurbitaceae family with origins in India, China, Burma, Thailand, is thought to have been domesticated ~3000 years ago6. The primary and secondary centers of diversity for the species are located in India and Southeast Asia, respectively8. Genomic analysis of cultivated cucumber (C. s. var. sativus) divided it into four geographic groups: India; Eurasia and the West; East Asia and China; and Xishuangbanna from Southwestern China10. The Indian group, which is thought to form the basal group, maintains a large proportion of the genetic diversity and also includes the wild cucumber, C. s. var. hardwickii, a feral form of var. sativus11. Deep resequencing of a core collection of 115 cucumber lines, sampled from 3342 accessions worldwide, suggests that the domestication process led to a severe genetic bottleneck, resulting in reduction in diversity relative to wild accessions10. More than 100 putative selective sweeps appear to be associated with domestication, including extended linkage disequilibrium in regions surrounding loci associated with key fruit traits such as size and bitterness. Results of the genomic analyses, including assignment of a basal role of the Indian group and separation of the orange-endocarp Xishuangbanna group, complement prior genetic and morphological assessments16. These analyses have allowed for evolutionary insight into the relationships and domestication trajectories among cucumber accessions.Collections for the Cucurbitaceae family, which includes many high-value crops consumed as vegetables and fruits throughout the world, face the above-mentioned challenges for germplasm preservation and utilizationhttps://npgsweb.ars-grin.gov/gringlobal/site.aspx?id=16). The NPGS collection comprises 1314 cucumber accessions representing the primary cucumber gene pool (C. s. var. sativus and C. s. var. hardwickii). This collection, which is primarily composed of cultivars, land races, and varieties collected from around the world, has been extensively utilized by breeders searching for a variety of traits, including resistance to downy mildew17 , powdery mildew18 , Phytophthora fruit rot20 , belly rot22 , and root knot nematodes (Meloidogyne spp.)23, as well as variations for fruit yield, fruit quality24, and above-ground and below-ground plant architecture26. However, to date, there have been very limited efforts to genetically characterize the US cucumber collection. Meglic et al.27 examined 757 accessions using seven isozyme loci, and Horejsi et al.28 characterized 118 accessions with 71 RAPD loci. Lv et al.9 included 883 accessions from the U.S. collection, which were characterized using a set of 23 SSR markers and 316 alleles. Current genomic technologies allow for much higher throughput and full genome analyses. The dramatically reduced cost of sequencing, high-throughput sample preparation, and efficient bioinformatics now make it feasible to perform genomic analysis on increasingly large numbers of samples for plant germplasm research30. In this study, we have performed genotyping on 1234 cucumber accessions from the NPGS, using genotyping-by-sequencing30 (GBS). The resultant high-throughput single-nucleotide polymorphism (SNP) markers provided high-definition genetic characterization of the US cucumber germplasm collection, allowing for assessment of genetic diversity and population structure, identification of markers that are highly associated with important agronomic traits through genome-wide association studies (GWAS), and development of a molecularly informed publicly accessible core population to facilitate breeding and preservation efforts.The cucumber collection in the United States is maintained at the Ames, Iowa facility of the USDA Agriculture Research Service National Plant Germplasm System  were collected from young (not fully expanded) leaves, freeze-dried, and ground to a fine powder using 5/32” stainless steel balls  in a Retsch Mixer Mill . DNA was isolated using the Omega Mag-Bind Plant DNA DS Kit  on a Kingfisher Flex Magnetic Particle Processor . The kit protocol was followed except that the initial 56 °C incubation was extended to 60 min instead of 30 min. The DNA was quantified using the Quant-iT PicoGreen dsDNA Kit  in a 384-well format on a CFX384 C1000 Real-Time thermal cycler . Normalization to 30–100 ng/ul was done using a GBFit Arise Pipetting System . Quality checks were performed on 10% of the genomic DNA samples from each batch of 96 samples by agarose gel observation of 300 ng of undigested and 30, using ApeKI as the restriction enzyme. The resulting 96-plex or 384-plex libraries were sequenced on a HiSeq 2500 system  with the single-end mode and read length of 101 bp.Genotyping of the cucumber accessions was performed following the GBS protocol31, using the cucumber Gy14 draft genome  as the reference. Briefly, the raw reads were first processed to retain reads possessing a barcode and a restriction enzyme cut site using GBSSeqToTagDBPlugin with the parameters “-kmerLength 90-minKemrL 30-mnQS 10-c 100-maKmerNum 200000000”. The resulting reads were then concatenated into distinct tags using the FastqToTagCount plug-in in TASSEL, and tags supported by at least ten reads were kept and mapped to the cucumber reference genome sequence using BWA (version 0.7.16a) with default parameters32. Based on the alignments, positions of aligned tags were determined using SAMtoGBSdbPlugin, and SNPs were identified from the aligned tags using DiscoverySNPCallerPluginV2 with default parameters. The identified SNPs were scored according to the coverage, depth, and genotypic statistics for a given set of samples using SNPQualityProfilerPlugin. SNPs were filtered based on their missing data rate and minor allele frequencies (MAF) using VCFtools33.SNP identification was performed using TASSEL 5.0 GBS Discovery Pipeline34 with parameters “-r -M 0.5 -m 0.01 -l 0.1 -B 100” and visualized using the ggtree package35. PI 618817 (Cucumis myriocarpus) and PI 282446 (C. heptadactylus) were used as the outgroup. Principal component analysis (PCA) was performed using Plink-1.9 (ref. 36). Population structure analysis was performed using the STRUCTURE program37. A total of 11,745 SNPs with linkage disequilibrium (LD) decay (r2) < 0.4 were used for the analysis. To determine the most likely group number, STRUCTURE was run 20 times using 8000 SNPs randomly selected from the 11,745 SNPs, for each K (K = 2–20). The highest ∆K, which indicates the most likely number of clusters in the population, was obtained. After determining the best K (K = 3), we then ran STRUCTURE using all 11,745 SNPs with 10,000 iterations for each K (K = 2–4).SNPs with MAF ≥ 1% and missing data rate ≤ 50% were used for phylogenetic and population structure analyses. The maximum-likelihood (ML) phylogenetic tree was constructed using SNPhylor2) for all pairs of SNPs within 500 kb that were calculated using PopLDdecay v3.27 (https://github.com/BGI-shenzhen/PopLDdecay) with the following parameters: -MaxDist 500 -MAF 0.05 -Het 0.88 -Miss 0.999. The maximum value of r2 was calculated using all pairs of SNPs within 500 bp. The nucleotide diversity (π) and population fixation index (FST) were calculated using Bio:PopGen implemented in the BioPerl package38. To visualize the pairwise FST values among different groups, multidimensional scaling (MDS) was conducted using the cmdscale function in R to transform FST values into two-dimensional values, which were used for plotting.LD decay was measured by correlation coefficients . The phenotypic data of 13 important traits for cucumber, including three related to disease resistance  resistance), three related to root knot nematode resistance , three related to fruit shelf life , and four other traits , were downloaded from the GRIN database. The phenotypic data were collected over the last 30 years by the Cucurbit Breeding program of North Carolina State University. Data sets for each trait were collected over multiple years and locations (http://cucurbitbreeding.com) for 750–950 cultigens per trait. Description of the data collection is available at The USDA-GRIN database archives phenotypic data for 39. In order to obtain the optimal imputation accuracy and filling rate, three accessions with few missing genotypes  were selected and 10%, 20%, and 30% SNP sites were randomly masked as missing genotypes for imputing. The imputation was performed using the fillGenotype with the following parameters: w , p , k , and r . The optimal combination of parameters  was selected after comparing the filling rate and imputation accuracy of each combination of parameters, to impute the missing genotypes in the raw dataset. Only biallelic imputed SNPs with minor allele frequency ≥ 1% and missing data rate ≤ 20%  were used for GWAS. GWAS were performed using the linear mixed model (LMM) implemented in Fast-LMM40. The genome-wide significance thresholds of the GWAS were determined using the Bonferroni correction at α = 0.05 for significant and α = 0.01 for extremely significant associations as described in Li et al.41. In this study, the significance thresholds of α = 0.05 and α = 0.01 corresponded to raw P values of 1.75 × 10–6 and 3.49 × 10−7, or −log10(P) values of 5.76 and 6.46, respectively.We used a total of 72,982 biallelic SNPs without any filtering to construct the kinship (K) matrix, which was used to correct for population structure and kinship in the GWAS analyses. For GWAS, the missing genotypes in the raw biallelic SNP dataset were imputed using the k-nearest neighbor (KNN) algorithm implemented in the fillGenotype software42 was used to select a subset of accessions that captured the majority of the allelic diversity of the 1234 cucumber accessions, with the following parameters: -d 0.01%, -cv 100%. Combined with phenotypic analysis, we obtained the final core collection containing 395 cucumber accessions, of which 354 were genotyped in the current study. The percentage of the allelic diversity captured by the 354 accessions in this core collection was determined using GenoCore. The core collection was further evaluated by PCA, using the same methods described above for the entire collection.GenoCore43. The Indian/South Asia group also included three accessions of C. s. var. hardwickii. In addition, since Turkey is a country straddling Asia and Europe, we put accessions from Turkey as an independent group. We genotyped these cucumber accessions, as well as two non-cucumber but closely related accessions PI 618817 (C. myriocarpus) and PI 282446 (C. heptadactylus), using the GBS technology, which generated a total of ~1.35 billion reads of 101 bp in length. The numbers of reads for each sample ranged from ~176 K to 4.8 million, with a median of 677 K reads (Supplementary Table Shttp://cucurbitgenomics.org), with 55.5% (0.69 billion corresponding to 279 K tags) aligned to unique positions and 17.3% (0.21 billion corresponding to 50 K tags) to multiple locations; the remaining 27.2% (0.33 billion corresponding to 225 K tags) unaligned reads were mainly from mitochondrion and chloroplast, as well as genome regions that were absent in the reference genome. Approximately 3.7% (9.5 Mb out of 258.6 Mb) of the Gy14 genome was covered by the aligned GBS reads, which is typical for reduced complexity GBS data30.Seed was successfully germinated for 1234 cucumber accessions from the NPGS, which represents 94% of the collection (1314 accessions for which seed was available). Based on their geographic distribution (countries of origins), we classified these accessions mainly into seven groups, 216 from India/South Asia, 293 from East Asia, 113 from Central/West Asia, 161 from Turkey, 314 from Europe, 33 from Africa, 97 from North America, as well as 7 from other regions . After retaining SNPs with ≤ 50% missing data (representing at least 617 accessions) and MAF ≥ 0.01 , we obtained a total of 24,319 SNPs distributed across the cucumber Gy14 genome with an average of one SNP per 10.6 kb Table . The disC. myriocarpus) and PI 282446 (C. heptadactylus) as the outgroup  represented the best number of clusters for these 1234 cucumber accessions , the India/South Asia group was clearly separated from the East Asia group. The population structure result at this optimal K was consistent with the phylogenetic tree and PCA results; all suggested three primary clusters in the cucumber accessions collected from NPGS. At K = 4, a new subpopulation emerged mainly in accessions from Europe and North America. A large portion of accessions from Europe, North America, Africa, Turkey, and Central/West Asia showed genetic admixture, while most of the East Asia accessions had a homogeneous genetic background.To investigate the population structure of cucumber, the Bayesian clustering algorithm implemented in the STUCTURE programons Fig. . As show44. The Indian accessions were differentially distributed among the different subclades, especially those from Rajasthan that were primarily associated with subclade 2, suggesting that the subclades, in part, reflect geographic distribution within India. Accessions from prior collections from South or Southwest India  clustered in subclade 3. Subclade 1 primarily contained accessions from Madhya Pradesh in central India. The great majority of the East Asian accessions were collected from China. Those from Japan and South Korea largely clustered with each other; the remaining subclades were almost exclusively composed of accessions from China  with increasing physical distance between SNPs was calculated for each group . Variable LD decays were detected in different groups. The Africa group and the North American group had the longest physical distances over which LD decayed to half of its maximum value, 64 kb and 96 kb, respectively, while the India group had the shortest, 16 kb. The Europe, Turkey, East Asia, and the Central/West Asia groups showed comparable LD decay patterns and physical distances .The LD decay  for Central/West Asia, Europe, North America, Africa, Turkey, East Asia, and India/South Asia groups were 0.87 × 10FST) values. Pairwise weighted FST values among North America, Central/West Asia, Africa, Turkey, and Europe groups ranged from 0.042 to 0.14, while the values between East Asia and other six groups ranged from 0.284 to 0.413, and between India/South Asia and other six groups from 0.176 to 0.284  was 0.269. There was much less divergence among the North America, Europe, Turkey, Africa, and Central/West Asia groups, and between the Western group and India/South Asia (0.15) , three related to fruit shelf life , and four other traits . For each trait, data were available for around 600–700 accessions that were genotyped using GBS in this study  and possible candidate genes for important horticultural traits. We collected historical phenotypic data of cucumber accessions from the NPGS for 13 agronomic traits, which included three traits related to disease resistance , three related to root knot nematode resistance  was identified to be significantly associated with resistance to M. arenaria race 2 , two on chromosome 3 in a region at 27.86 Mb, three on chromosome 4 , and three on chromosome 5 in a region spanning from 2.847 to 2.864 Mb  and two on chromosome 7 (696 and 978 kb) were identified for weight loss, one SNP on chromosome 3 (27.23 Mb) was identified for loss of firmness, and one SNP on chromosome 2 (3.18 Mb) was identified for shriveling  and capture largely the allelic diversity of the entire collection, and also include accessions with some unique and important agronomic traits.42. The results showed that the 720 top-ranked accessions captured 100% of the allelic diversity of the whole set, and the top 100, 200, 300, and 400 top-ranked accessions captured 93.87%, 97.09%, 98.47%, and 99.20% of the allelic diversity, respectively  were identified. With the exception of highly methylated centromeric or pericentromeric regions, the SNPs were well distributed at high density in the genome with an approximate frequency of 1 SNP per 10.6 kb. These data allowed for comprehensive analysis of phylogentic relationships, population structure, and LD patterns of accessions in the collection and provide a resource for genetic analysis and gene discovery.6 and prior phylogenetic analyses10, the U.S. cucumber PI collection comprised three major clades. The basal clade predominantly comprised accessions from India/South Asia, the presumed center of domestication for C. sativus. While this clade had the deepest branches suggesting greater divergence among members of this clade, the overall diversity of accessions from this region was reduced relative to the study of Qi et al.10. This is likely due to sampling. The 216 accessions from India/South Asia in the U.S. collection included only three (1.4%) accessions of C. s. var. hardwickii, a highly diverse wild botanical variety believed to be either a progenitor or a feral relative of the cultivated cucumber, C. s. var. sativus44. In contrast, 13 of 30 accessions (43.3%) from the Indian accessions studied by Qi et al.10 were var. hardwickii.Consistent with our current understanding about the geographic origin of cucumber45. The strong differentiation between the East and West groups likely reflects a long period of divergent domestication (written Chinese records mentioning cucumber date as early as 164 BCE) as well as geographical isolation due to the Himalayan mountains46. Patterns of LD decay were consistent with the phylogenetic and population structure analyses. The Indian group had the shortest physical distance to reach half-maximal value (16 kb), vs. 32–48 kb for East Asia, Central/West Asia, and Europe. The reduced rate of LD for North American and Africa accessions (96 and 88 kb) may reflect the greater genetic relatedness of the samples in this collection, or the migration route for cucumber, which is thought to have been introduced into these regions comparatively recently from Europe47.From its origins in India and initial domestication ~3000 years ago, it appears that cucumber moved both East (to East Asia) and West , following distinct trajectories in each case9,10,28,44,46,48. Our phylogenetic analyses also reflected these sources of divergence. In addition to the separation observed among the three primary clades, we saw examples of differentiation within clades as evidenced by countries of origin, regions of collection within India, subgroups from Turkey, and between processing and fresh market cucumbers in North America. Among the Indian PIs, accessions from Madhya Pradesh, Uttar Pradesh, and Rajasthan were preferentially, but not exclusively, distributed in different subclades, suggesting diversity both within and between regions. Separation of accessions from Rajasthan relative to other regions in India was previously observed based on isozyme analysis performed following initial collection44. The current SNP-based analysis allowed for more nuanced assessment of relationships among the accessions. The Turkish germplasm also was associated with several subclades. For the two largest subclades containing Turkish accessions, one was extensively mixed with accessions from Central/West Asia, while the second was extensively mixed with accessions from Europe. Examination of collection locations within Turkey showed predominance of samples from the European-mixed subclade from western Turkey and samples from the Asian-mixed subclade from Eastern Turkey. There were some exceptions, however, possibly reflecting seed exchange across different regions of the country. Separation among the North American accessions reflected market class. As public and commercial breeding efforts have largely catered to either pickling or slicing cucumber, with delineated breeding efforts, it is not surprising to observe genetic divergence. Differentiation between pickling and slicing cucumbers also has been observed with RFLP markers and metabolomic analyses of cucumber fruit peels49.Several studies have indicated that the overall level of genetic diversity within cultivated cucumber is quite narrow, and that most of the genetic differentiation was observed between geographic regions or market classes56.An important value of genetic characterization of the collection is the development of genomic tools for breeders. QTL analyses of key traits of economic importance can allow for the development of markers for marker assisted selection, focusing phenotypic selection on population subsets containing desired markers and facilitating gene pyramiding for complex traits. The GWAS presented here using the high-density SNP markers and historical phenotyping data for several disease resistance and physiological traits show the identification of significantly associated genomic regions. At this time QTL have been mapped for a limited number of traits in cucumber. Of the traits examined here, recent studies have reported QTL for downy mildew, GSB, and flowering timedm2.1, dm3.1, dm3.2, dm4.1, dm5.1, dm5.2, dm5.3, and dm6.1. Among them, dm2.1, dm4.1, dm5.2 and dm6.1 seem to be shared by the two PI lines51. Another cucumber accession, PI 197087, possesses multiple resistances to downy mildew , anthracnose (by the cla locus) and angular leaf spot (by the psl locus). Pan et al.52 and Wang et al.54 showed that dm1/cla/psl locus for the triple disease resistances in this PI line was controlled by the same staygreen gene (CsSGR), which was located in the short arm of chromosome 5 (~5 Mb in Gy14 V2.0). The several peaks on chromosome 5 detected from GWAS in this study  originated from PI 197087 (ref.54). However, no downy mildew QTL was detected on chromosome 4 in the natural population, whereas no QTL on chromosome 7 were detected from bi-parental mapping populations, which was identified in GWAS. These differences may reflect the power of QTL detection with different approaches. The different virulence structure of field downy mildew pathogens may also contribute to the observed differences.Recent QTL mapping studies for downy mildew resistances in two PI lines  identified eight resistance QTL, C.s. var. hardwickii) accession PI 183967 have been reported with some contradictory results55. Liu et al.55 identified six QTL on chromosomes 3, 4, 5, and 6  with gsb5.1 as a major QTL. On the other hand, Zhang et al.53 identified five QTL  for resistance to GSB in PI 183967 with gsb-s6.2 having the largest effect. While not directly overlapping, gsb-s2.1 (ref.53) and gsb5.1 (ref. 55) seem to be at nearby regions of the two peaks we identified from GWAS in this study on chromosomes 2 and 5, respectively, which obviously need further investigation to confirm. In addition, a recent report also identified a candidate gene for GSB resistance in melon located on chromosome 4 around 4.0 Mb57; however, it does not appear to reside in syntenic regions58 with the QTL identified this study.QTL for GSB resistance have been recently identified in cucumber and melon. Two QTL mapping studies on GSB resistances from the wild cucumber (56), and on chromosomes 1, 5, and 6 in a cross between American pickling cucumber and semi-wild var. Xishuangbanna16. There appears to be potential overlap among the identified QTL in those studies and the current GWAS. In all three studies significant regions were located on the distal end of chromosome 1 and on the central region of chromosome 6, suggesting potentially robust loci influencing flowering time over a range of genetic backgrounds.QTL for flowering time was previously mapped on chromosomes 1, 2, 5, and 6 in recombinant inbred lines derived from a cross between an American pickling type and little leaf (ll) line H-19  of the PIs from the prior core45 were included in the current core collection. It has also been recommended that germplasm collections include important breeding materials where key traits have been introgressed into cultivated inbred lines29. To this end, the proposed core also includes 41 accessions, including historical cultivars, widely used breeding lines and individuals with identified traits of interest. To make the core maximally valuable for future breeding efforts and genetic studies, we are in the process of deep resequencing of the genomes, and creating seed stocks of the selected accessions in the final core collection, under the current USDA CucCAP project (https://cuccap.org/). Both the genotype data and seeds of the core collection will be accessible to the public.A prior core of 147 accessions from the NPGS cucumber collection was proposed based on isozyme analysis of 970 PIs, along with data regarding disease resistance , water and heat stress tolerance, and morphological characteristicsThis work has provided detailed genetic analysis of the cucumber germplasm collection maintained by the US NPGS, which includes more than 1200 accessions collected throughout the world. The information provided by the GBS data has provided deep insight into the diversity present within the collection and genetic relationships among the accessions. These data can be used for genetic analyses such as GWAS to identify potential genomic regions associated with valuable traits, and for informed management of the collection to conserve genetic resources. Development of the genetically informed core collection will enable more efficient genetic analyses that can be coupled with sophisticated genomic tools to facilitate crop improvement. While it is clear that a great deal of valuable diversity is represented among the materials in the NPGS collection, these observations also illustrate the importance of careful and extensive germplasm collection to ensure that our collections reflect the extant diversity available worldwide.Supplementary Note and FiguresSupplementary File 1Supplementary Tables


Turkey presents a great diversity of common bean landraces in farmers’ fields. We collected 183 common bean accessions from 19 different Turkish geographic regions and 5 scarlet runner bean accessions to investigate their genetic diversity and population structure using phenotypic information , geographic provenance and 12,557 silicoDArT markers. A total of 24.14% markers were found novel. For the entire population (188 accessions), the expected heterozygosity was 0.078 and overall gene diversity, Fst and Fis were 0.14, 0.55 and 1, respectively. Using marker information, model-based structure, principal coordinate analysis (PCoA) and unweighted pair-group method with arithmetic means (UPGMA) algorithms clustered the 188 accessions into two main populations A (predominant) and B, and 5 unclassified genotypes, representing 3 meaningful heterotic groups for breeding purposes. Phenotypic information clearly distinguished these populations; population A and B, respectively, were bigger (>40g/100 seeds) and smaller (<40g/100 seeds) seed-sized. The unclassified population was pure and only contained climbing genotypes with 100 seed weight 2–3 times greater than populations A and B. Clustering was mainly based on A: seed weight, B: growth habit, C: geographical provinces and D: flower color. Mean kinship was generally low, but population B was more diverse than population A. Overall, a useful level of gene and genotypic diversity was observed in this work and can be used by the scientific community in breeding efforts to develop superior common bean strains. Phaseolus vulgaris L.) is one of the most ancient grain legumes of America [Phaseolus contains more than 70 species five of which  being the most cultivated [P. coccineus commonly known as scarlet runner bean is close relative of common [rd most economically important bean species after common bean and P. lunatus [Common bean  from various farmers’ fields in different geographical provinces across Turkey. The sampling sites covered a wide range of natural eco-geographical locations  under dihaseolus .-1. The DNA samples were processed at Diversity Array Technology Pty, Ltd, Australia (http://www.diversityarrays.com/) for DArTseq analyses using genotyping-by-sequencing platform.Genomic DNA was extracted from 2-week old seedlings derived from the 188 selfed mini core selections, according to modified CTAB protocol of Doyle and Doyle,  with somDArTseq represents a combination of complexity reduction method and sequencing of resulting representations on next generation sequencing platforms –37–38 anDArTsoft v.7.4.7  was used to analyze all the images from DArTseq platform. DArTseq-detected silicoDArT markers are genetically dominant and were scored in a binary fashion, with 1 and 0, respectively, standing for presence and absence of a restriction fragment in the genomic representation of each sample –37. TheyGenetic distances among the evaluated common bean materials were calculated from the proportion of shared alleles obtained from silicoDArT markers by using Euclidean genetic distance coefficients. In addition to the above algorithm, a number of other diversity-relevant metrics were computed. Expected heterozygosity (Hs), overall gene diversity (Ht), and inbreeding coefficient (Fis) were computed using hierfstat R package  followinhttp://itol.embl.de/; [i = 1,….,s clusters, j = 1,….,n genotypes within a cluster iji, y is the response variable of genotype j in the cluster i appropriately expressed as best linear unbiaised estimate from the 2-year augmented design described above, e is the residual. Mean comparisons were done by performing Tukey's test or bootstrapping with 1000 resamples and Student t-test as appropriate. Computations were executed using R software.Genetic structure was assessed using principal coordinate analysis (PCoA), UPGMA, and model-based Bayesian clustering algorithms. The PCoA is an eigen-analysis of a distance or dissimilarity matrix, and was performed under R software environment  by runnimbl.de/; ). The Bambl.de/;  followinmbl.de/; . The nummbl.de/; ) and thembl.de/;  method. mbl.de/; . For cohmbl.de/; –48. Genembl.de/;  followinmbl.de/;  and Yangmbl.de/; . AnalysiWhole genome DArTseq profiling of Turkish common bean germplasm was performed, and yielded 15,608 silicoDArT markers  from 3,6The distribution of PIC values in the original unfiltered silicoDArT marker dataset obtained from the GBS Company is shown in The Bayesian clustering model implemented in STRUCTURE software divided the evaluated bean accessions into two main groups: 112 landraces (59.57%) in the group A (red) and 71 landraces (37.76%) in the group B (blue) . Five geIn order to statistically describe the importance of genetic structure and diversity in the evaluated Turkish common bean germplasm, different diversity metrics such as genetic distance, expected heterozygosity (Hs), overall gene diversity (Ht), pairwise kinship (Φ), Fstatistic (Fst) and inbreeding coefficient (Fis) were computed. For the entire population (188 accessions), the expected heterozygosity was 0.078 and overall gene diversity, Fst and Fis were 0.14, 0.55 and 1, respectively. The expected heterozygosity values for both populations A and B were, respectively, 0.039 and 0.150. . The aveThe analysis of variance showed significant differences between clusters  in terms of plant height and 100 seed weight . Using TAfter the seed weight, growth habit, geographical provinces and flower color actively participated in clustering. Population A contains indeterminate bushes, prostrate and climbering genotypes, while population B grouped landraces having only indeterminate and climber growth habit and mostly genotypes in both populations from different provinces clustered with genotypes having similar growth habit. Geographical provinces also played a role in clustering and genotypes belonging to same provinces generally clustered together in both populations. However, it was also observed that genotypes with same provenance also clustered in different groups. For instance, landraces from Hakkari, Mus and Van provinces displayed the phenotypic characteristics of population A but, some of the landraces from these provinces grouped with B population. On the other hand, Elazig, Bitlis and Balikesir provinces provided landraces reflecting the phenotypic characteristics of B population, but some landraces from these provinces clustered in A population. Flower color clearly differentiated the genotypes by clustering white flower genotypes population A and purple, white and lilac colors were invariably found in population B.Investigation of genetic diversity is very important because it can provide insight into sources of novel alleles to be used in breeding programs. The use of molecular markers to assess genetic diversity represents a significant breakthrough –51–52. VThe distribution of the silicoDArT markers used in this work was generally homogeneous on each common bean chromosome but, the number of markers per chromosome was variable. Chromosome 2 had 11.43%, while 7.21% of the markers were found on chromosome 6. On average, 1,076.27 (6.89%) markers were identified per chromosome. These results are supported by earlier studies –56–58 reThe identification of 24.14% novel markers with unknown positions represents important findings in this study, particularly for the breeding perspectives. Novel markers can be used in genome wide association studies (GWAS) for the discovery of genetic factors of interest. We are conducting multi-location/year morphological experiments and these newly identified markers will be used for common bean GWAS in upcoming years. A good range of PIC value (0.10–0.5) was found in this study, which is in line with previous works on common beans. Valdisser et al.  found PIWhole-genome silicoDArT molecular markers, growth habit, and 100 seed weight were used to characterize the Turkish common bean germplasm. More importance was given to molecular markers as suggested in Habyarimana, , becauseGenomic inbreeding and kinship coefficient were computed as part of diversity metrics. Within a population, individual genomic inbreeding represents the probability that two alleles at a randomly chosen locus are identical by state, whereas pairwise kinship measures the relatedness represented by the probability that two alleles, one sampled at random from each individual, are identical by state. Therefore, kinship predicts the future level of inbreeding which represents the repository for future genetic diversity.The overall gene diversity and the range of Euclidean distance  were higThe Fst statistic achieved in this work is much higher than in earlier reports by McClean et al.  working Euclidean distance is a mean quantitative measure of the genetic divergence and can be calculated between populations, species or individuals at DNA sequence level or allele frequency level . InformaLandraces Bilecik-8 and Mus-42 showed the highest genetic distance within the population A. As Turkish people like seeds with medium to large size in their diet, these landraces can be candidate parents for the development of common bean variety having favorable traits for the consumer. Similarly, we found Erzincan-5 and Bitlis-48 landraces most genetically similar to each other in population A, as they showed minimum pairwise genetic distance. Within the population B, the maximum genetic distance was found between Mus-46 and Bingol-6 landraces, while Bingol-6 and commercial cultivar Akman showed higher levels of similarity. The genetically distinct landraces identified in this work  within and between both populations represent a great common bean breeding potential for the scientific community to develop improved cultivars according to farmer and consumer interest.Structure analysis divided the common bean accessions into 2 main populations: population A was the dominant population with 112 accessions and population B was smaller and contained 71 genotypes. Clustering algorithms were in good agreement with statistical inferences made on phenotypic data (growth habit and seed size). Plant height of population B was higher than in population A , becauseOn the average, landraces clustered in the population A contained seed size greater than 40g/100 seeds and landraces present in the population B contained the seed size less than 40g/100 seeds . On the In this study, 5 genotypes  did not clustered to any population due to membership coefficient  and considered as unclassified genotypes as suggested by Habyarimana,  and werePhaseolus [Various morphological characteristics were also observed by following the IBPGR descriptors for haseolus , white, Pv-shatterproof1 and Phaseolin type, while Gioia et al. [The 24% and 26% of individuals in populations A and B, respectively, showing seed size below 40g/100 seeds (for population A) and above 40g/100 seeds (for population B), can possibly be considered as hybrids. A good proportion of landraces were collected from Van, Bitlis and Hakkari provinces of Turkey and these provinces reflected higher level of hybridization than the other provinces. Turkey is not an origin center for common bean and therefore, the possible reasons for the presence of more hybridization events in these provinces may be their closeness with each other that favored horizontal gene transfer in the direction that most satisfied the interests of the farmer and the taste of the consumer. Presence of hybrids in this study are also confirmed by the recent study of Nemli et al.  and Ceyla et al.  used theThe findings in this study showed high genetic diversity with both phenotypic and genotypic information. Genetic relatedness was generally low and heterotic groups were identified that can be used for breeding purposes. Morphological information clearly reflected the existence of variation in Turkish common bean germplasm and supported the genotypic information. Seed weight was the main factor in clustering, while growth habit, geographical provinces, and flower color also played active role in the clustering. Now, there is a need to take initiatives and start executing hybridization programs in common bean in order to develop varieties responding to end user preferences. One of the possible successful breeding objectives can be initiated by developing high-yielding dwarf common bean ideotype that is generally preferred by farmers due to less labor requirement and ease of harvesting. A good number of dwarf accessions were identified in this study. Further dwarf common bean cultivars can be developed through hybridization between distant parents with desired traits. In this study, all genotypes of unclassified population reflected phenotypic and genotypic uniqueness and will be used to start various common bean breeding activities in near future. Endeavors in this direction are underway at the Abant Izzet Baysal University, Bolu, Turkey, where a common bean germplasm mini-core is being increased by collecting more landraces within Turkey and from core countries harboring good common bean diversity such as Mexico and Latin American nations. Currently, we are conducting multiyear/location experiments of this mini-core and markers produced in this study will be used to perform genome wide association studies and marker-aided common bean breeding. In perspective, standard Andean and Mesoamerican checks will be integrated in field trials to confirm the results presented herein. We will use the variety of information collected for the identification of molecular markers linked with yield and yield component traits. The appropriate silicoDArT markers for various traits of interest will be cloned and converted into kompetitive allele specific PCR (KASP). Anyone willing to initiate knowledge based breeding program and interested in Turkish common bean genetic resources based on the information generated in this study can contact us.


The basis of genetic fingerprinting and DNA profiling in forensic laboratories is the use of Short Tandem Repeats (STRs) according to local and ethnical genetics characteristics.Forensic parameters and allele frequencies for 15 autosomal STRs in 100 unrelated individuals from Khuzestan province, south Iran were determined. PCR was carried out for amplification of STRs and GeneMapper ID software was used for genotyping and allelic analyzing.The Power of Exclusion (PE) varied between 0.332 (TPOX) and 0.768 (FGA). With exception of the THO1 (0.020), TPOX (0.014) and D18S51 (0.003), other STRs showed no deviation from the Hardy-Weinberg equilibrium (p>0.05).Out of 15 STRs, 12 repeats seemed to be more useful and more powerful tools in identity and paternity determination for our studied population. Variation in our data analysis revealed that effective use of these 15 STR loci in forensic cases needed to be localized by collection and analysis of population data from the general population. The law organizations have greatly benefited from current improvements in the genetic micro and nano-techniques. The advanced forensic laboratories outfitted by bunch of biological evidence from a crime scene to the guilty can reliably exclude falsely accused individuals. In the past three decades, numerous advances in genetic technologies have occurred and most of them included the development of DNA testing and especially Polymerase Chain Reaction (PCR)-based typing methods The basis of genetic fingerprinting and DNA profiling is that twins are the only individuals who have identical copies of the human genome. Of course, the human genome is almost the same in everybody, although it contains many polymorphisms, positions where causes different nucleotide sequence to occur in every member of the population. These polymorphisms include Restriction Fragment Length Polymorphisms (RFLPs), Short Tandem Repeats (STRs), and Single Nucleotide Polymorphisms (SNPs), that can occur within genes as well as in intergenic regions, and altogether there are millions of these polymorphic sites in the human genome. The more powerful technique of DNA profiling is the use of STRs, a short sequence, 1–13 nucleotides in length, which is repeated several times in a tandem array In the population, generally, there might be as many as ten different versions of a particular STR, each of the alleles characterized by a different number of repeats. In DNA profiling, the alleles of a selected number of different STRs are identified. This can be achieved quickly and with very small amounts of DNA by PCRs. The size of the band or bands that are seen in the agarose gel electrophoresis indicate the allele or alleles present in the DNA sample that has been tested. Two alleles of an STR can be present in a single DNA sample because there are two copies of each STR, one on the chromosome inherited from the mother and one on the chromosome from the father Blood samples were collected under informed consent, from 100 healthy unrelated men and women  belonging to three ethnic groups  living in Khuzestan province. The research conformed to the provisions of the declaration of Helsinki in 1995 (as revised in Edinburgh 2000) and ethical approval was obtained from the ethics committee of Khuzestan Legal Medicine Organization and informed consent was obtained from all participants. Genomic DNA was extracted by using dried blood samples on FTA cards according to the manufacturer’s instructions For amplification of 15 autosomal STR , PCR procedure was performed according to the manufacturer’s instruction , by using the AmpFlSTRIdentifiler PCR Amplification kit. PCR products electrophoresis was performed on an ABI 3500 Genetic Analyser 8-capillary array system . 3500 series data collection version 1.0 software was used for data collection. For genotyping and allelic calls, GeneMapper ID software version 3.2  was used by comparison of samples profile with allelic ladder included in the kit.Arlequin software version 3.5 was used to calculate allele frequencies and to obtain expected heterozygosity (He), observed heterozygosity (Ho) and probability value  of Hardy-Weinberg equilibrium Forensic parameters and allele frequencies of 15 autosomal STR loci  are shown in et al presented a PCR-based DNA-typing method using 13 unlinked STR loci from unrelated individuals presenting to a Houston area blood bank. They reported that this valid statistical analysis is generally simpler than similar analysis of RFLP-VNTR results et al analyzed the genetic differentiation among African populations based on their cultural or linguistic differences et al in 2013 analyzed allele frequencies for 15 autosomal STR loci in Fars province population, southwest of Iran and by using our similar STR loci, got similar results in Hardy-Weinberg equilibrium, resembling to our heterozygosities. They reported that with exception of D13S317 and TPOX, other STRs were in Hardy-Weinberg equilibrium, same as our report about these two markers in addition to THO1. Fars and Khuzestan are two proximate provinces in Iran, so genetic and ethnic similarities of their population can justify this symmetry et al analyzed allele frequencies’ distribution for 15 STRs loci in a population sample of unrelated individuals from the region of Wallachia, South Romania and presented their more genetic similarity et al in 2014 evaluated the genetic structure and genetic affinity between Thai-Malay Muslims and Thai Buddhists by analyzing 15 autosomal short tandem repeats. They used exact STRs which were used in our study as well A set of autosomal STR loci were analyzed in a mixed ethnical population group in Khuzestan province, in order to obtain a genetic characterization of south Iran. Several local studies on molecular genetics loci have been reported in different parts of the world. Hammond Analysis of autosomal STR loci can reveal heterogeneity of geographically and culturally related individuals and different populations, thus, it might be possible to better differentiate populations through the procedure. Today, STRs are used for crime forensic identity, paternity and corpse identity in many related laboratories, while for effective use of these 15 STR loci in forensic cases, it is needed to collect and analyze population data from the general population region in which the crime has happened and adjust them by local characteristics. In order to contribute in construction of STR profiling of the different ethnic groups in geographical areas, similar study with the present population can be useful.