Genetic and micromorphological differentiation within Sambacus ebulus (Adoxaceae) suggests divergence of populations from Iran

Genetic and micromorphological differentiation within Sambacus ebulus (Adoxaceae) suggests divergence of populations from Iran | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetic and micromorphological differentiation within Sambacus ebulus (Adoxaceae) suggests divergence of populations from Iran Marzieh Bayrami, Ali Sattarian, Mahmood Salehi, Elham Amini, Neda Atazadeh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4998002/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Sambucus ebulus is mainly distributed in the northern, northwestern and northeastern regions of Iran and is characterized by its perennial growth habit and distinctive long, creeping and branched rhizomes. In this study, genetic diversity of seven populations S. ebulus based on molecular ISSR data and the micromorphology of seeds and leaves of this species in Iran were investigated. Micromorphological examination revealed the anomocytic type of stomata and indicated that the epidermal cells of various S. ebulus populations exhibited irregular cell shapes with anticlinal walls ranging from straight to curved. The seed shape was described as predominantly almond-shaped, and the surface of the seed coat of the studied taxa showed a reticulate pattern. The AMOVA (analysis of molecular variance) test showed that 87% of the total genetic variance was due to differences inter-populations genetic differences, while 13% was due to within-populations genetic variability, indicating a high degree of genetic variation among S. ebulus populations. The discriminating power of ISSR (inter simple sequence repeat) loci as determined by Gst against Nm (the number of migrants) analysis, showed that almost all ISSR loci have an excellent discriminating power. Thus, ISSR markers are efficient in differentiating of the studied S. ebulus populations. The Mantel test presented a significant correlation between genetic and geographic distance. These results suggest that the selected markers for genetic analysis represent different regions of the genome and effectively capture the genetic variation within the studied populations. AMOVA Genetic Iran Populations SEM Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction The genus Sambucus , belonging to the Adoxaceae family, comprises approximately 30 species of deciduous shrubs, small trees, and a few perennial herbs (Mabberley, 2008 ) predominantly found in the northern hemisphere. In Iran, the genus is represented by two species: Sambucus ebulus L. and Sambucus nigra L. (Jamzad, 1993 ). Sambucus ebulus is mainly distributed in the northern, northwestern, and northeastern regions of Iran and is characterized by its perennial growth habit and distinctive long, creeping, and branched rhizomes (Judd et al., 2007 ). In recent years, research into the pharmacology of S. ebulus has increased, revealing both traditional and modern medicinal uses of the plant. Various sources have documented its diuretic, antiseptic, tonic, and laxative properties, highlighting its medicinal potential (Novelli, 2003 ; Uncinimangianelli et al., 2005). Genetic diversity plays a crucial role in the survival of populations, as highlighted in studies such as Pourmeidani et al., 2024. To understand the genetic information of plants, researchers often use markers and PCR techniques. Among these markers, ISSR (inter simple sequence repeat) molecular markers stand out for their stability, high reproducibility, and ease of use. This has made them a popular choice in various biological investigations, as noted in studies by Sheidai et al. ( 2012 , 2013 , 2014) and Atazadeh et al. ( 2020 ). The molecular study of Sambucus species has been a focus in a limited number of studies thus far. For example, Waswa et al. ( 2022 ) conducted research on the taxonomy and classification of Sambucus species. Their analysis revealed that Sambucus species form a monophyletic group with two main clades: one containing S. nigra , S. peruviana , S. maderensis , and S. canadensis , and the other containing the remaining species. Amini et al. ( 2019a ) carried out a molecular study in Iran using the ITS marker to evaluate 18 populations of two Sambucus species, S. ebulus and S. nigra , which led to the differentiation of these two species. Additionally, Shen et al. ( 2019 ) investigated genetic diversity in mackerel germplasm using ISSR markers. Their study did not find a clear correlation between clustering results and fruit characteristics, as the mackerel germplasms are related to native superior members. Micromorphological studies, particularly using scanning electron microscopy (SEM), play a significant role in botany by providing valuable diagnostic information for the identification of plant taxa, especially at the species level (Amini et al., 2018a ). This technique allows for the examination of stable traits that are not influenced by environmental conditions, making it useful for accurate plant identification. Epidermal traits are particularly effective for this purpose, as they are present on most green organs and fruits and can even be observed in herbarium samples. In the genus Sambucus , micromorphological studies have contributed to a better understanding of the morphological and anatomical characteristics of various species. For instance, Sedláčková et al. ( 2018 ) focused on flower morphology and antioxidant activities in the inflorescence of Sambucus . Alerico et al. (2016) studied the chemical compounds present in stem bark, while Amini et al. ( 2021 ) investigated the morphology and anatomy of Sambucus species, including S. ebulus and S. nigra . Their studies highlighted the micromorphological characteristics (such as pollen and seeds) that supported the differentiation of S. nigra and S. ebulus . Elkiran et al. (2021) examined the anatomy of S. nigra and S. ebulus in northern Turkey, focusing on differences in features such as drusen crystals, vascular bundle cells, margin shape, and collenchyma cells on the stems. The present study aims to 1) assess the genetic diversity and investigate the relationships among populations of S. ebulus using molecular ISSR data in seven populations of S. ebulus , and 2) examine the micromorphology of seeds and leaves in populations of this species. These comprehensive analyses, combining the genetic structure of the populations and micromorphological data, may provide valuable insights into the evolutionary relationships and characteristics of S. ebulus . Materials and Methods Plant material Genetic and morphological data from seven populations of Sambucus ebulus in North Iran were examined in this study (Figs. 1 , 2 ). Plant samples were collected from various locations and stored at the Gonbad Kavous University Herbarium (GKUH). Geographic coordinates and elevation of each genotype's habitat were determined using GPS technology. Table 1 Investigated Sambucus ebulus populations Pop. Province Locality Voucher number Latitude Longitude Altitude (m) 1 Mazandaran Babol 804509 E 52.6625° N 36.6001° -11 2 Golestan Golestan Forest 804502 E 55.7828° N 37.5793° 457 3 Mazandaran Noor 804500 E 53.6402° N 36.7013° 45 4 Gilan Amlash 804508 E 50.1844° N 37.0961° -7 5 Gilan Lahijan 804506 E 50.0028° N 37.2060° -3 6 Golestan Kordkoy 804504 E 54.1480° N 36.6686° 2302 7 Golestan Bandar Gaz 804503 E 54.5838° N 36.7813° 445 DNA extraction Genomic DNA from the plant samples was extracted using the CTAB-activated charcoal protocol as described in various studies (Doyle & Doyle 1987 ; Doyle & Dickson 1987 ; Cullings 1992 ; Amini et al., 2018b ; Nasrollahi et al., 2019 ). The quality and quantity of the extracted DNA were assessed by running it on a 0.8% agarose gel. ISSR-PCR The PCR experiment was conducted using 12 samples and four ISSR primers (refer to Table 2 ) in a 25 µL reaction volume. The reaction mixture included 2.5 mM MgCl2 (Cinna Gen Co, Iran), 0.2 µM of primer (Cinna Gen Co, Iran), 10 mM Tris-HCl pH 8.3, 1 mM dNTP mix (Cinna Gen Co, Iran), 1 U of Taq DNA polymerase-500 (Cinna Gen Co, Iran), and approximately 40 ng of template DNA. The ISSR-PCR was carried out using a thermocycler (Biorad, USA) with the program outlined in Table 3 . The amplified products were visualized by running them on a 1% agarose gel electrophoresis. Table 2 The used ISSR primers Code Sequences ISSR13 (ACG) 6 Ga ISSR826 CCCGGATCC (CA) 8 ISSR810 (GA) 8 T ISSR7 (AC) 8 AG Table 3 PCR program for ISSR primers Step Temperature Time Cycling Initial denaturation 94 ºC 3 min - Denaturation 94 ºC 50 s - Annealing 58 ºC 42 s 38 Extension 72 ºC 50 sec - Final extension 72 ºC 7 min 1 ISSR analysis The ISSR bands obtained were treated as binary characters, with the presence of a band coded as 1 and absence as 0. Genetic diversity parameters, including Nei's gene diversity (H), Shannon information index (I), number of effective alleles, and percentage of polymorphism, were calculated for each population following the methods described by Freeland et al. (2011). Nei's genetic distance was used for clustering analysis using Neighbor-Joining (NJ), WARD, and Unweighted Paired Group using Average (UPGMA) algorithms. Principal Coordinate Analysis (PCoA) and Multidimensional Scaling (MDS) methods were also employed for grouping the populations after 100 permutations, as outlined in Freeland et al. (2011). To assess the correlation between genetic and geographical distances among the populations, Mantel's test was conducted using PAST ver. 2.17 (Hammer et al., 2012 ) and DARwin ver. 5 (Perrier and Jacquemoud-Collet, 2006 ) software. For determining the genetic differentiation of the species, an AMOVA (Analysis of Molecular Variance) test was performed using GenAlex 6.4 (Peakall and Smouse, 2006 ). Gene flow was estimated using the Nm value, calculated from GST using Pop Gene ver.1.32 (Nm = 0.5(1 - GST) / GST) and by the least square method as implemented in T-REX (Boc et al., 2012). Scanning electron microscopy In the analysis process, three samples of each species were utilized. The samples were boiled for 20 minutes, and the openings were observed. Subsequently, they were preserved in 70% alcohol post-placement in Carnoy's solution for 24 hours. To prepare them for observation under a light microscope, the samples were initially immersed in distilled water until they became colorless and then rinsed with water. Light microscopy was employed to create slides, and an 8-megapixel Canon digital camera (model a63) was utilized for examination. The use of a scanning electron microscope enables the acquisition of high zoom images through advanced imaging techniques, allowing for the investigation of morphological, structural, and elemental details at intricate levels (URL-2, 2016). The leaf epidermis of each species was scrutinized under a stereomicroscope to verify normal size and development. The specimens were affixed directly onto aluminum stubs using double-sided adhesive, coated with a thin layer of gold (approximately 25 nm), and examined using a VEGA II TESCAN-LMU Electron Microscope at an accelerating voltage of 15–22 kV at the Research Institute of Razi in Tehran, Iran. Subsequent to this procedure, analysis and imaging were carried out utilizing the scanning electron microscope. Microphotographs of the samples were captured using suitable applications, micrometric measurements were taken, and data were digitized. Results ISSR assay and genetic diversity The DNA extraction process yielded high-quality molecules suitable for the genetic diversity study. Gel electrophoresis results indicated clear nucleic acid molecules without smearing, confirming their suitability for polymerase chain reaction (PCR) amplification. All examined primers generated bands within the desired size range of 200 to 900 bp. To ensure accuracy, only bands with optimal resolution were considered. ISSR primers revealed 19 bands per locus, with predominantly polymorphic bands and only two monomorphic bands. Population 4 and 5 exhibited the greatest band diversity (12 bands), while populations 1 and 3 displayed the lowest band count (9 bands). Notably, populations 5 and 6 uniquely featured two specific bands amid more general bands across all populations (Table 4 ). Tables 5 and 6 show the parameters of genetic diversity and Nei ’ s genetic distance for S. ebulus in detail. The discriminating power of ISSR loci as determined by Gst against Nm (the number of migrants) analysis, showed that almost all ISSR loci have an excellent discriminating power. Thus, ISSR markers are efficient in differentiating of the studied S. ebulus populations. The AMOVA test allows the calculation of the molecular variance components, which illustrate the contributions of the variances intra- and inter-groups to the total genetic variation. The test results revealed significant genetic differentiation among the studied populations (P = 0.001), indicating distinct genetic clustering (Table 7 ). The AMOVA test showed that 87% of the total genetic variance was due to differences inter-populations genetic differences, while 13% was due to within-populations genetic variability (Fig. 3 ). This substantial inter-population genetic diversity highlights the valuable genetic resources present in these populations for future breeding programs. The results emphasize the marked genetic diversity observed in samples of the same species from different regions. Moreover, the Mantel's test conducted to assess the relationship between geographic and genetic distances demonstrated a significant correlation among populations (P = 0.01). This implies that as populations become geographically more distant from each other, they also exhibit increasing genetic divergence. Table 4 Items of ISSR bands in Sambacus ebolus populations (Populations 1–7 matching Fig. 1 ) Pop1 Pop2 Pop3 Pop4 Pop5 Pop6 Pop7 No. Bands 9 10 9 12 12 10 10 No. Bands Freq. (≥ 5%) 9 10 9 12 12 10 10 No. Private Bands 0 0 0 0 1 1 0 No. Common Bands (≤ 25%) 0 0 0 0 0 0 0 No. Common Bands (≤ 50%) 0 0 0 2 2 0 0 Table 5 Genetic diversity details in Sambacus ebolus populations (Pop. 1–7 are according to Fig. 1 ) Pop N Na Ne I He uHe %P Pop1 3.000 0.474 1.000 0.000 0.000 0.000 0.00% Pop2 3.000 0.579 1.050 0.036 0.026 0.031 5.26% Pop3 3.000 0.474 1.000 0.000 0.000 0.000 0.00% Pop4 3.000 0.684 1.050 0.036 0.026 0.031 5.26% Pop5 3.000 0.684 1.050 0.036 0.026 0.031 5.26% Pop6 3.000 0.526 1.000 0.000 0.000 0.000 0.00% Pop7 3.000 0.526 1.000 0.000 0.000 0.000 0.00% Note: N = Number of studied plants, Na = Number of Different alleles, Ne = Number of Effective alleles, I = Shannon's Information Index, He = Expected Heterozygosity, uHe = Unbiased gene diversity, and P% = Percentage of Polymorphic Loci. Table 6 Nei , s genetic identity (above diagonal) and genetic distance (below diagonal) (Populations numbers matching to Fig. 1 ) Pop ID 1 2 3 4 5 6 7 1 *** 0.991 1.000 0.884 0.777 0.947 0.947 2 0.009 *** 0.991 0.918 0.810 0.937 0.982 3 0.000 0.009 *** 0.884 0.777 0.947 0.947 4 0.123 0.085 0.123 *** 0.856 0.831 0.937 5 0.252 0.210 0.252 0.156 *** 0.724 0.831 6 0.054 0.065 0.054 0.186 0.323 *** 0.895 7 0.054 0.018 0.054 0.065 0.176 0.111 *** Table 7 Pair-wise AMOVA between Sambacus ebolus populations (PhiPT Values below diagonal. Probability values based on 99 permutations are shown above diagonal) AMOVA Pop 1 Pop 2 Pop 3 Pop 4 Pop 5 Pop 6 Pop 7 Pop1 0.000 0.354 0.001 0.123 0.089 0.001 0.001 Pop2 0.500 0.000 0.421 0.135 0.080 0.090 1.00 Pop3 0.686 0.500 0.000 0.113 0.111 0.001 0.001 Pop4 0.875 0.667 0.875 0.000 0.117 0.113 0.124 Pop 5 0.929 0.833 0.929 0.750 0.000 0.095 0.111 Pop 6 1.00 0.800 1.00 0.909 0.941 0.000 0.001 Pop 7 1.00 0.000 1.00 0.800 0.909 1.00 0.000 The population clustering and grouping based on ISSR data by NJ (Figure not given), UPGMA tree, PCO and MDS plot (Figure not given) showed similar results. Upon evaluation of the ISSR data, the UPGMA analysis illustrated the presence of two primary clusters (Fig. 4 ). Within the first cluster, population 6 (Golestan, Kordkoy) appeared as a distinct sub-cluster from the other populations. Furthermore, populations 1 (Mazandaran, Babol) and 3 (Mazandaran, Noor) clustered together, separate from populations 2 (Golestan, Golestan Forest) and 7 (Golestan, Bandar Gaz) which formed another close cluster. The second cluster also exhibited two sub-clusters, with populations 5 (Gilan, Lahijan) and 4 (Gilan, Amlash) forming a separate cluster. The results of the PCOA plot aligned with those of the UPGMA chart. Populations 2 (Golestan, Golestan Forest) and 7 (Golestan, Bandar Gaz) along with populations 1 (Mazandaran, Babol) and 3 (Mazandaran, Noor) appeared to constitute closely related genetic groups. Population 6 (Golestan, Kordkoy) exhibited genetic resemblance to populations 1 and 3. Populations 4 (Gilan, Amlash) and 5 (Gilan, Lahijan) displayed significant genetic differentiation from the other populations (Fig. 5 ). Further, The CCA plot of genetic data and environmental features revealed that geographic factors such as latitude and longitude are effective in separation of studied S. ebolus populations, particularly in populations 4 and 5 (Fig. 6 ). Micromorphology Leaf epidermal cell In the research conducted, leaf epidermal traits were analyzed, focusing on characteristics such as the shape of epidermal cells, anticlinal wall, stomatal type, stomatal index, stomatal length, and width at the lower surface. Examination of the epidermis of the studied populations using electron microscopy revealed the presence of stomata on the lower surface across all populations, with all exhibiting the anomocytic type of stomata. The investigation indicated that the epidermal cells of various S. ebulus populations featured irregular cell shapes with anticlinal walls ranging from straight to curve. The electron microscope images in Figs. 7 , 8 , 9 , 10 , and 11 provide visual representations of the epidermis of different populations, showcasing the observed characteristics of the epidermal cells and stomata for comparative analysis and detailed examination. The measurements conducted revealed that the population from Golestan province had the highest average width and length of the aperture among the studied populations of this species, with an average width of 40.68 µm and an average length of 55.44 µm. In contrast, the population from Mazandaran province exhibited the lowest averages, with an average width of 41.28 µm and an average length of 52.24 µm. These comparative values are detailed in Table 8 of the study. Additionally, the examination of trichome characteristics in the populations of the studied species highlighted various types of covering trichomes on the epidermis of S. ebulus . These included simple single-cell trichomes, multi-cell trichomes, glandular trichomes, and conical or triangular trichomes. Despite the presence of these different types of trichomes across populations, variations were observed in the density of trichomes among the studied populations. These findings add further insights into the morphological diversity within different populations of S. ebulus . Table 8 Description of the observed variation in the epidermal features of S. ebulus Population Cell Shape Anticlinal Wall Mean Stomata size (width*Length) Mean trichome length Density of trichome Golestan irregular straight to curved 62.44*47.97 3.62 dense Gilan irregular straight to curved 62.18*37.55 3.44 sparse Mazandaran irregular straight to curved 52.24*41.28 3.23 dense Seed surfaces The seed characteristics deemed to have potential taxonomic significance in S. ebulus have been summarized in Table 9 . The seeds were found to range in length from 2.58 to 2.77 mm and in width from 1.19 to 1.35 mm. Upon examining the seeds from various populations of the species, it was observed that all seeds exhibited an almond shape. Furthermore, the seed shape was described as predominantly almond-shaped, and the seed-coat surface of the studied taxa displayed a reticulate pattern, as illustrated in Fig. 12 . These findings provide valuable insights into the consistent seed morphology and surface features across different populations of S. ebulus , which can be important for taxonomic classification and identification purposes. Table 9 Characteristic features of the investigated seeds in S.ebulus . Population Shape Length (mm) Width (mm) Length/ Width Seed surface Golestan Almond shape 2.58 1.30 1.98 Reticulate Gilan Almond shape 2.77 1.19 2.32 Reticulate Mazandaran Almond shape 2.60 1.35 1.92 Reticulate Discussion Genetic relationship estimations among individuals are influenced by multiple factors, including the number and distribution of markers in the genome, as well as the underlying evolutionary mechanisms (Powell et al., 1996 ). The effectiveness of the ISSR method in providing genetic information is highly dependent on the choice of primers. Ellis et al. ( 1997 ) demonstrated that selecting six optimal primer combinations could account for 80% of the expected relationships. In this study, four primary primers were selected based on established protocols and previous successful outcomes (Talebi Kohyakhy et al., 2008 ; Ahkami et al., 2007 ; Antonio et al., 2004 ). The genetic diversity among populations was found to be 87% in this investigation. Melchinger (1997) emphasized that the accuracy of genetic similarity estimation relies on the number of markers, level of polymorphism, and genomic coverage of markers employed. The results of Canonical Correspondence Analysis (CCA) in our study indicate that environmental factors such as latitude, longitude, and altitude have a simultaneous impact on gene flow and genetic structure within the studied populations. These variations among populations may suggest distinct taxonomic groups within S. ebulus below the species level. Previous research on various plant species, including wheat ( Triticum turgidum and Triticum durum ), has also shown a correlation between genetic diversity and geographical distribution. Genotypes from different regions and latitudes often exhibit genetic differentiation (Omidbakhshfard et al., 2009; Ahkami et al., 2007 ). Many studies have reported the existence of different ecotypes resulting from genetic differences among populations, leading to morphological divergence (Sheidai et al., 2012 ; 2013 ; 2014; Minaeifar et al., 2015; Atazadeh et al. 2020 ). It is interesting to note that in Ferula gummosa , a lack of correlation between molecular diversity and geographic diversity has been reported (Khonani et al., 2009). This highlights the complexity and variability of genetic and environmental interactions across different plant species and populations. In Principal Coordinate Analysis (PCO), when the principal components account for a lower percentage of variation, it suggests that they provide a more proper distribution at the genome level. This indicates that the selected markers are effectively capturing genetic diversity. By sampling markers from different parts of the genome that have less correlation with each other, the analysis can provide a broader representation of genetic variation. The study by Messmer et al. ( 1992 ) supports using principal component analysis as a complementary method to cluster analysis to optimize the utilization of molecular data and extract maximum information. The PCO plot (Fig. 5 ) and UPGMA clustering (Fig. 4 ) in our study show that the distribution of genotypes in the two-dimensional axis aligns well with the dendrogram, indicating consistency between the different analytical approaches. These results suggest that the selected ISSR markers for genetic analysis represent diverse regions of the genome and are effectively capture the genetic variation within the studied populations. This comprehensive approach can provide valuable insights into the genetic diversity and structure of the populations under investigation. The results of our study suggest that there is a high level of diversity among the ecotypes of Sambucus from different geographical regions in the north of the country. The presence of morphological diversity indicates that the observed differences in the samples are not solely influenced by environmental factors but are also under genetic control. The study highlights the effectiveness of the Inter-Simple Sequence Repeat (ISSR) method as a rapid, powerful, and cost-effective tool for genetic analysis. This method requires minimal initial work and can identify numerous gene locations that may not be easily accessible with other techniques within the same time frame and budget constraints. The work of Powell et al. ( 1996 ) also supports the utility of the ISSR technique, emphasizing its high repeatability and ability to measure a large number of gene locations efficiently in a single test. The repeatability of the ISSR method is crucial in assessing the quality of genetic markers, as it ensures consistent results that can be used for accurate clustering and genetic analysis of diverse samples. The ISSR method provides researchers with a reliable and efficient approach to capture genetic variation and understanding the underlying factors influencing diversity within Sambucus ecotypes from different regions. The use of scanning electron microscopy (SEM) in studying Sambucus ebulus has provided valuable insights into the plant's morphology, revealing significant variation and introducing novel morphological features that contribute to a better understanding of the species. The scanning electron microscopy (SEM) is a specialized tool that has undergone significant advancements in recent years, although it may not be readily available in all laboratories due to its complexity and cost. In our study, SEM was employed to characterize and describe the surface characteristics of leaves and seeds of Sambucus ebulus . The examination of epidermal structures in populations from Golestan, Gilan, and Mazandaran regions revealed differences in cellular and stomatal characteristics among the species, likely influenced by varying environmental conditions in those regions. Stomata, such as the anomocytic-type aperture found on the lower surface of the species, play a crucial role in species recognition across different taxonomic, ecological, and physiological levels. These apertures are important features that can help differentiate species and are indicative of the plant's evolutionary adaptations to its environment. By studying these structural features using SEM, researchers can gain a deeper understanding of the unique characteristics of Sambucus ebulus and its variations across different geographical regions. The stomatal density of plants, including Sambucus ebulus , is influenced by a combination of natural, environmental, and ecological factors. Studies have shown that factors such as water availability, leaf size, and stomatal size play a significant role in determining stomatal density (Blum et al., 1981 ). These characteristics are closely linked to the habitat of the species and can vary at different levels of taxonomic classification and across different environmental conditions. Genetic factors also have a notable influence on the development of stomatal traits in plants (Miller 1983 ). Research on S. ebulus has revealed variations in stomatal index among different populations, with the population in Golestan province exhibiting the highest stomatal index and the population in Mazandaran province having the lowest stomatal index. These differences are attributed to the specific humidity conditions and habitats in which the populations are found. In habitats with higher humidity and ample water resources, plants tend to have lower stomatal indexes compared to those in drier environments. This relationship highlights the adaptive responses of plants to their specific environmental conditions. The aperture index, which is influenced by stomatal density, is also lower in populations with sufficient humidity, such as those in Mazandaran province, compared to populations in drier regions like Golestan province. These findings are consistent with previous studies, such as those by Van de Roovaaort and Fuller ( 1935 ), which showed that plants subjected to drought stress tend to have higher stomatal density as a response to water scarcity. The data from this research provide valuable insights into the stomatal characteristics of S. ebulus and offer a foundation for further investigations into the species and its adaptation to varying environmental conditions. The morphology of seeds, including characteristics such as shape, size, and surface ornamentation, can provide valuable insights for identifying and classifying plant species. Studies have indicated that these seed attributes are influenced by genetic and phylogenetic differences among taxa and are relatively stable across different environmental conditions (Barthlott 1984 ; Ozcan 2002 ). In the case of the target species population, all seeds were observed to be almond-shaped with reticulate grain surfaces. This uniformity in seed morphology suggests that these features are genetically determined and can serve as distinguishing traits for identifying the species. The presence of such consistent seed characteristics supports the idea that these traits hold taxonomic significance and can help clarify relationships among species that share morphological similarities. The importance of seed morphology in plant classification has been emphasized in various studies, validating its value as a systematic trait for species identification (Amini et al., 2019b ; Amini et al., 2024 ). The results of the research highlight grain size and surface ornamentations as key distinguishing features that can aid in the identification of plant species in Iran. These seed attributes provide valuable systematic information that can enhance our understanding of plant diversity and assist in resolving taxonomic ambiguities. Conclusion In the present study, the genetic diversity of S. ebulus populations was investigated using ISSR molecular data. Our results showed a high degree of genetic variability among populations of S. ebulus , which is important for assessing the genetic diversity of this species. The UPGMA dendrogram based on the molecular data provided valuable information on the relationships among the studied populations. This comprehensive approach can provide valuable insights into the genetic diversity and genetic structure of the studied populations. The ISSR method provides researchers with a reliable and efficient approach to capture genetic variation and to understand the underlying factors that influence diversity within Sambucus ecotypes from different regions. Examination of the epidermal structures in populations from the Golestan, Gilan and Mazandaran regions revealed differences in the cellular and stomatal characteristics of the species, which are likely to be influenced by the different environmental conditions in these regions. Declarations Clinical trial number not applicable. Ethics approval and consent to participate Not applicable Consent for publication Informed consent was obtained from all individual participants included in the study. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This research received no external funding. Author Contribution "Elham Amini wrote the main manuscript text and Ali Sattarian and Marzieh Bayrami and Mahmood Salehi prepared figures 1-12. Neda Atazadeh prepared the analyses. All authors reviewed the manuscript. Acknowledgements The authors would like to thank Miss Beyk Mohammadi for the advice lab and wish to express our gratitude to Mr. Hosseini for constative suggestion. The present study was financially supported by Gonbad Kavous University, Gonbad (Iran). Availability of data and material No data was used for the research described in the article. References Ahkami AH, Naghavi MR, Hossein Zadeh A, Pirseiedi SM, Patki P, Kazemi Almoti M, Poor Irandoost H, Omid Bakhsh MA. Genetic Relationship in Durum Wheat (Triticum durum) Using AFLP Markers. Iran Agric Sci. 2007;1:25–35. Amini E, Nasrollahi F, Sattarian A, Kor S, Boozar pour S. 2018a. Molecular and micro-morpholog-ical evidences of the genus Cuscuta in Iran. Rostaniha 19(2), 113–129. (PDF) Palynological studies of some species of the genus Cuscuta with emphasis on taxonomy. Amini E, Kazempour-Osaloo S, Maassoumi AA, Zare-Maivan H. Phylogeny, biogeography, and divergence times of Astragalus section Incani DC. (Fabaceae) inferred from nrDNA ITS and plastid rpl 32 -trn L (UAG) sequences. – Nordic j bot. 2018b;1:1–20. Amini E, Nasrollahi F, Sattarian A, Isazadeh-Araei M, Habibi M. Systematic and molecular biological study of Sambucus L.(Caprifoliaceae) in Iran. Thaiszia J Bot. 2019a;29:133–50. Amini E, Nasrollahi F, Sattarian A, Khormali A, Habibi M. Micromorphological and molecular study of four species of Lonicera (Caprifoliaceae) in Iran. Phytologia Balcanica. 2019b;25:181–90. Amini E, Nasrollahi F, Sattarian A, Isazadeh-Araei, Habibi M. 2021. Morphological and anatomical study of the genus Sambucus L.(Adoxaceae) in Iran. Mod Phytomorphology, 15 (1). Amini E, Sattarian A, Nasrollahi F, Daneshvar A, Mohammad Esmaeili M, Hamidzadeh Sani L, Haghighi S. Micromorphological study of some Salsola species (Amaranthaceae) in Iran and its systematic significance using scanning electron microscopy. Microsc Res Tech. 2024. 10.1002/jemt.24623 . Antonio AFG, Benchimol LL, Barbosa AMM, Geraldi IO, Souza CL. Comparison of RAPD, RFLP, AFLP and SSR markers for diversity studies in tropical maize inbred lines. Gen Mol Bio. 2004;27:579–88. Atazadeh N, Sheidai M, Attar F, Koohdar F. (2020). Genetic and morphological diversity in Cousinia calocephala jaub. & spach (Asteraceae; section Cynaroideae bunge) populations. Genetika, 52(1): 199–214. Barthlott W. Microstructural Features of Seed Surface. In: Heywood VH, Moore DC, editors. Current Concepts in Plant Taxonomy. Cambridge: Academic; 1984. pp. 95–105. Blum A, Gozlan G, Mayer J. The Manifestation of dehydration avoidance in wheat breeding germplasm 1. Crop Sci. 1981;21:495–9. BOC A, DIALLO AB, V., MAKARENKOV. T-REX: a web server for inferring, validating and visualizing phylogenetic trees and networks. Nucleic Acid Res. 2012;40:W573–9. Cullings KW. Design and testing of a plant-specific PCR primer for ecological and evolutionary studies. Mol Ecol. 1992;1(3):233–40. Doyle JJ, Dickson EE. Preservation of plant samples for DNA restriction endonuclease analysis. Taxon. 1987;36(1):715–22. Doyle JJ, Doyle JL. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bull. 1987;19:11–5. Ellis RP, Mcnicol JW, Baird E, Booth A, Lawrence P. The use of AFLP to examine genetic relatedness in barley. Mol Breeding. 1997;3:359–69. Freeland JR, Kirk H, S.D., Peterson. Molecular Ecology. second ed. UK: Wiley-Blackwell; 2011. p. 449. Gintzburger G, Toderich KN, Mardonov BK, Makhmudov MM. Rangelands of the Arid and Semi_Arid Zones in Uzbekistan. Montpellier: CIRAD; 2003. Hammer Q, Harper DAT, Ryan PD. PAST: Paleontological Statistics software package for education and data analysis. Palaeontologia Electronica. 2012;4:9. Jamzad Z. (1993): Sambucus L. - In: Assadi, M., Khatamsaz, M. and Maassoumi, A.A, editor, Flora of Iran 8. Dipsacaceae – Tehran: Research Institute of Forests and Rangelands. JUDD WS, STEVENS CAMPBELLCSKELLOGGEA P.F., DONOGHUE MJ. Plant systematics: a phylogenetic approach. 3rd ed. - Sunderland, MA: Sinauer; 2007. Khounani Z, Naghavi M, Omidi M, Sabokdast M, Talebi Kohyakhi E. (2011). Assessment of Genetic Diversity in the Landraces of Ferula gummosa from Iran Using AFLP Marker, Journal of Medicinal Plants , 10(38), 117. magiran.com/p893514. Mabberley DJ. The Plant Book, a Portable Dictionary of Higher Plants. Cambridge: - Cambridge University; 2008. Melchinger AE, Gumber RK. Overview of heterosis and heterotic groups in agronomics crops. In: K.R. Lamkey and J.E. Stuber, editors. Concepts and breeding of heterosis in crop plants. Madison, WI. CSSA. 1999, pp: 29–43. Messmer MM, Melchinger AA, Boppenmair J, Hermann RG, Brunklaus-Jung E. RFLP analysis of early-maturing European maize germplasm. I. Genetic diversity among flint and dent inbreds. Theor Appl Genet. 1992;83:1003–12. Miller EC. 1983. Plant Physiology.Mc Grow-Hill Book Company Inc. New York. U.S.A. Minaeifar A, Sheidai M, F., Attar. Genetic and morphological diversity in Cousinia cylindracea (Asteraceae) populations: Identification of gene pools. Biodiversitas. 2015;16:288–94. Nasrollahi F, Kazempour-Osaloo S, Saadati N, Mozaffarian V, Zare-Maivan H. Molecular phylogeny and divergence times of Onosma (Boraginaceae s.s.) based on nrDNA ITS and plastid rpl32-trnL (UAG) and trnH–psbA sequences. Nord J Bot. 2019;37(1):1–12. Novelli S. (2003): Developments in berry production and use. pp. 5–6. Bi-weekly Bul., Vol. 16. Agriculture et Agroalimentaire Canada. Omid bakhsh fard MA, Naghavi MR, Mardi M, Bihamta MR, Kazemi M, Pirseyedi SM. A study of genetic diversity in Durum Wheat (Triticum turgidum) using microsatellite markers. Iran Agric sci. 2009;2:75–83. Ozcan M. Nutrient Composition of Rose (Rosa canina L.) Seed and Oils. J Med Food. 2002;5:137–40. Peakall R, Smouse PE. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes. 2006;6:288–95. Perrier X, jacquemoud-collet JP. (2006): DARwin Software. http://darwin.cirad.fr/darwin Pourmeidani A, Amini E, Nasrollahi F, Mohammadi Y. Genetic Diversity and Population Structure of Haloxylon Aphyllum in Iran by ISSR Markers. Acta Bot Hungarica. 2023;65(3–4):385–98. https://doi.org/10.1556/034.65.2023.3-4.9 . Powell W, Morgante M, Andre C, Hanafey M, Vogel J, Tingey S, Rafalsky A. The comparison of RFLP, RAPD, AFLP and SSR markers for germplasm analysis. Mol Breeding. 1996;2:225–38. Rabizadeh F, Amini E, Nasrollahi F. The anatomical and micromorphological properties of endemic species to gypsic soils of Semnan, Iran. J Struct Biol. 2023;215(2):107968. Sedláčková VH, Grygorieva O, Fatrcová-Šramková K, Vergun O, Vinogradova Y, Ivanišová E, Brindza J. The Morphological and Antioxidant Characteristics of Inflorescences within wild-growing Genotypes of Elderberry ( sambucus nigra L). – Potr S J F Sci. 2018;12/ 1:444–53. Sheidai M, Seif E, Nouroozi M, Z., Noormohammadi. Cytogenetic and molecular diversity of Cirsium arvense (Asteraceae) populations in Iran. J Jap Bot. 2012;87:193–205. Sheidai M, Zanganeh S, Haji-ramezanali R, Nouroozi M, Noormohammadi Z, Ghasemzadeh-Baraki. Genetic diversity and population structure in four Cirsium (Asteraceae) species. Biologia. 2013;68:384–97. Sheidai M, Ziaee S, Farahani F, Talebi SM, Noormohammadi Z. Y., Hasheminejad ahangarani Farahani (2014): Infra-specific genetic and morphological diversity in Linum album (Linaceae). Biologia, 69: 32–9. Shen Z, Tang Z, Yuan D, Ding X, Cheng J. Genetic diversity of elderberry germplasm with ISSR makers. J Northeast Forestry Univ. 2019;47(10):8–15. Talebi Kohyakhy E, Mohammad Aliha M, Naghavi MR. Genetic diversity in Ferula gummosa Bioss. Populations of Iran using RAPD molecular markers. Iran J Med Aromatic Plants. 2008;23(4):514–22. Toderich KN. (2008). Genus Salsola of Central Asian flora: its structure and adaptive evolutionary trends. PhD Thesis, Tokyo University of Agriculture and Technology. UNCINIMANGANELLI RE, ZACCARO L., TOMEI PE. Antiviral activity in-vitro of Urtica dioica L., Parietaria diffusa and Sambucus nigra L. J Ethnopharmacol. 2005;98:323–7. Van de Roovaaort E, Fuller GD. Stomatal frequency in cereals. J Ecol. 1935;16:278–9. Waswa EN, Mutinda ES, Mkala EM, Katumo DM, Oulo MA, Odago WO, Amenu SG, Ding S-X, Hu G-W. Understanding the Taxonomic Complexes and Species Delimitation within Sambucus L.(Viburnaceae). Diversity. 2022;14(11):906. Additional Declarations No competing interests reported. Supplementary Files Gel.png Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4998002","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":350310619,"identity":"29de3abf-8bac-42fe-9cac-d0b2ee4388b5","order_by":0,"name":"Marzieh Bayrami","email":"","orcid":"","institution":"Gonbad Kavous University","correspondingAuthor":false,"prefix":"","firstName":"Marzieh","middleName":"","lastName":"Bayrami","suffix":""},{"id":350310620,"identity":"6b5948fd-0156-4b29-bb62-baf2c8a46802","order_by":1,"name":"Ali Sattarian","email":"","orcid":"","institution":"Gonbad Kavous University","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Sattarian","suffix":""},{"id":350310621,"identity":"8333ec7b-794f-4123-8d17-47ba8da5d628","order_by":2,"name":"Mahmood Salehi","email":"","orcid":"","institution":"Gonbad Kavous University","correspondingAuthor":false,"prefix":"","firstName":"Mahmood","middleName":"","lastName":"Salehi","suffix":""},{"id":350310622,"identity":"c498c3e7-e74e-4dc4-a204-dc113daf8fb6","order_by":3,"name":"Elham Amini","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBAC+3YeCIONgbHhgEQFmxwDAw9+LQbMCC2NByzO8BkTrwUImA9UtsklNhDWwnvw0w0Gu2g+6eaGAzfbzNI3HD978MEHBjs53QYcfmHmS5bOYUjObZM52HBwxrm03A1n8pINZzAkG5sdwOkwA6AW5tw2icSGwxJlx3I3HMgxk+ZhOJC4DbcW4985DPUQLX/Y/qcbnH9DUIsZ0JbDYC0HJNrYEgxuELbFzDqH4ThUyxk2w5k33hgbzjDA7Rf79h7j2zkM1bnzZ6Q//gCMSnm+8zmGDz5U2Mnh0gIGjP+QOApglQZ4lGMA+QZSVI+CUTAKRsFIAAAf6FwqEJ/bMwAAAABJRU5ErkJggg==","orcid":"","institution":"Gonbad Kavous University","correspondingAuthor":true,"prefix":"","firstName":"Elham","middleName":"","lastName":"Amini","suffix":""},{"id":350310623,"identity":"533d6731-38ad-4d2e-85f8-51709516c5f7","order_by":4,"name":"Neda Atazadeh","email":"","orcid":"","institution":"Yasuj University","correspondingAuthor":false,"prefix":"","firstName":"Neda","middleName":"","lastName":"Atazadeh","suffix":""}],"badges":[],"createdAt":"2024-08-29 13:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4998002/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4998002/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66276698,"identity":"c4d524a4-29b6-4ea2-a113-d8841f7b4a97","added_by":"auto","created_at":"2024-10-09 13:55:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":222284,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution map of the studied \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSambucus ebulus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e populations in Iran.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/803bcbfd0759001f4aaa7302.png"},{"id":66276936,"identity":"fdc295a7-4b30-4058-af49-da9d7a3f0133","added_by":"auto","created_at":"2024-10-09 14:03:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1538079,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe natural habitat of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSambucus ebulus\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/465bd5b3fdfab7aa1ae3e834.png"},{"id":66276705,"identity":"9d98a965-23eb-42da-ba81-c34d139d7f3f","added_by":"auto","created_at":"2024-10-09 13:55:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":13843,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePercentages of molecular variance\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/ad58c6f2eedd57285fdf43f1.png"},{"id":66277860,"identity":"43a20aed-ed66-4400-af5a-772dbc6c1010","added_by":"auto","created_at":"2024-10-09 14:19:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":12917,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUPGMA clustering of the studied populations based on ISSR data\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/baa27a312fded5c92fbc6a66.png"},{"id":66276696,"identity":"42b843ea-df5b-41b6-bd02-7284e97700c7","added_by":"auto","created_at":"2024-10-09 13:55:36","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13308,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePCoA plot after 1000 times permutation\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/d312d9d8a2b8fb7dec921a03.png"},{"id":66277778,"identity":"f2395ff5-6a21-49db-9168-2f48eabc19bc","added_by":"auto","created_at":"2024-10-09 14:11:36","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":24830,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCCA plot of ISSR loci in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eS. ebulus\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/ca501de4793ee1e40d88e69f.png"},{"id":66276939,"identity":"4dbf062c-384d-456e-96b8-9566a006468d","added_by":"auto","created_at":"2024-10-09 14:03:36","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1016980,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScanning elecctron micrographs (SEM) of the abaxial leaf surface in Golestan population.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/2a45b2bee3b100746774be71.png"},{"id":66276701,"identity":"0900b5ae-34b7-4c9c-9fa9-d32ed2b05f9d","added_by":"auto","created_at":"2024-10-09 13:55:36","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1135541,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScanning elecctron micrographs (SEM) of the abaxial leaf surface in Gilan population.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/55e5bb3d1ae3c01d71caf20d.png"},{"id":66277780,"identity":"8bf2bb1e-cee4-406d-b5be-978c6d1d7bb1","added_by":"auto","created_at":"2024-10-09 14:11:36","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":922739,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScanning elecctron micrographs (SEM) of the abaxial leaf surface in Mazandaran population.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/550f982ba69a162cb0cfec96.png"},{"id":66277783,"identity":"d11c34c1-2556-4069-abb9-1f22ab70ed7c","added_by":"auto","created_at":"2024-10-09 14:11:36","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1114526,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScanning elecctron micrographs (SEM) of the abaxial leaf surface in Mazandaran population.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure10.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/56fe32507fe62e843b4276e1.png"},{"id":66276706,"identity":"2291e485-106e-45cd-8f2c-c57fde3c9ae7","added_by":"auto","created_at":"2024-10-09 13:55:36","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":1101364,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScanning elecctron micrographs (SEM) of the abaxial leaf surface in Mazandaran population.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure11.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/9525c207cbe25ebc5c45dde4.png"},{"id":66276942,"identity":"2ff3256c-a904-4a42-b2c0-2531f3c380ec","added_by":"auto","created_at":"2024-10-09 14:03:36","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":902667,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScanning elecctron micrographs (SEM) of seed surface in Golestan (A-D), Mazandaran (E-F) and Gilan (G-H) populations.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure12.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/a1c1132bec56f815780e06f3.png"},{"id":73520764,"identity":"91bb6a86-48ef-4b5e-b8da-6f4eef718eb8","added_by":"auto","created_at":"2025-01-10 18:23:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11743423,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/4d361617-bd1e-4e34-8d86-4231be21446e.pdf"},{"id":66277861,"identity":"049665b2-f584-4cce-bdaf-e038d257f37b","added_by":"auto","created_at":"2024-10-09 14:19:36","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":235150,"visible":true,"origin":"","legend":"","description":"","filename":"Gel.png","url":"https://assets-eu.researchsquare.com/files/rs-4998002/v1/1442006db59e31b64383e746.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetic and micromorphological differentiation within Sambacus ebulus (Adoxaceae) suggests divergence of populations from Iran","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe genus \u003cem\u003eSambucus\u003c/em\u003e, belonging to the Adoxaceae family, comprises approximately 30 species of deciduous shrubs, small trees, and a few perennial herbs (Mabberley, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) predominantly found in the northern hemisphere. In Iran, the genus is represented by two species: \u003cem\u003eSambucus ebulus\u003c/em\u003e L. and \u003cem\u003eSambucus nigra\u003c/em\u003e L. (Jamzad, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). \u003cem\u003eSambucus ebulus\u003c/em\u003e is mainly distributed in the northern, northwestern, and northeastern regions of Iran and is characterized by its perennial growth habit and distinctive long, creeping, and branched rhizomes (Judd et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In recent years, research into the pharmacology of \u003cem\u003eS. ebulus\u003c/em\u003e has increased, revealing both traditional and modern medicinal uses of the plant. Various sources have documented its diuretic, antiseptic, tonic, and laxative properties, highlighting its medicinal potential (Novelli, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Uncinimangianelli et al., 2005).\u003c/p\u003e \u003cp\u003eGenetic diversity plays a crucial role in the survival of populations, as highlighted in studies such as Pourmeidani et al., 2024. To understand the genetic information of plants, researchers often use markers and PCR techniques. Among these markers, ISSR (inter simple sequence repeat) molecular markers stand out for their stability, high reproducibility, and ease of use. This has made them a popular choice in various biological investigations, as noted in studies by Sheidai et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, 2014) and Atazadeh et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe molecular study of \u003cem\u003eSambucus\u003c/em\u003e species has been a focus in a limited number of studies thus far. For example, Waswa et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) conducted research on the taxonomy and classification of \u003cem\u003eSambucus\u003c/em\u003e species. Their analysis revealed that \u003cem\u003eSambucus\u003c/em\u003e species form a monophyletic group with two main clades: one containing \u003cem\u003eS. nigra\u003c/em\u003e, \u003cem\u003eS. peruviana\u003c/em\u003e, \u003cem\u003eS. maderensis\u003c/em\u003e, and \u003cem\u003eS. canadensis\u003c/em\u003e, and the other containing the remaining species. Amini et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e) carried out a molecular study in Iran using the ITS marker to evaluate 18 populations of two \u003cem\u003eSambucus\u003c/em\u003e species, \u003cem\u003eS. ebulus\u003c/em\u003e and \u003cem\u003eS. nigra\u003c/em\u003e, which led to the differentiation of these two species. Additionally, Shen et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) investigated genetic diversity in mackerel germplasm using ISSR markers. Their study did not find a clear correlation between clustering results and fruit characteristics, as the mackerel germplasms are related to native superior members.\u003c/p\u003e \u003cp\u003eMicromorphological studies, particularly using scanning electron microscopy (SEM), play a significant role in botany by providing valuable diagnostic information for the identification of plant taxa, especially at the species level (Amini et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). This technique allows for the examination of stable traits that are not influenced by environmental conditions, making it useful for accurate plant identification. Epidermal traits are particularly effective for this purpose, as they are present on most green organs and fruits and can even be observed in herbarium samples.\u003c/p\u003e \u003cp\u003eIn the genus \u003cem\u003eSambucus\u003c/em\u003e, micromorphological studies have contributed to a better understanding of the morphological and anatomical characteristics of various species. For instance, Sedl\u0026aacute;čkov\u0026aacute; et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) focused on flower morphology and antioxidant activities in the inflorescence of \u003cem\u003eSambucus\u003c/em\u003e. Alerico et al. (2016) studied the chemical compounds present in stem bark, while Amini et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) investigated the morphology and anatomy of \u003cem\u003eSambucus\u003c/em\u003e species, including \u003cem\u003eS. ebulus\u003c/em\u003e and \u003cem\u003eS. nigra\u003c/em\u003e. Their studies highlighted the micromorphological characteristics (such as pollen and seeds) that supported the differentiation of \u003cem\u003eS. nigra\u003c/em\u003e and \u003cem\u003eS. ebulus\u003c/em\u003e. Elkiran et al. (2021) examined the anatomy of \u003cem\u003eS. nigra\u003c/em\u003e and \u003cem\u003eS. ebulus\u003c/em\u003e in northern Turkey, focusing on differences in features such as drusen crystals, vascular bundle cells, margin shape, and collenchyma cells on the stems.\u003c/p\u003e \u003cp\u003eThe present study aims to 1) assess the genetic diversity and investigate the relationships among populations of \u003cem\u003eS. ebulus\u003c/em\u003e using molecular ISSR data in seven populations of \u003cem\u003eS. ebulus\u003c/em\u003e, and 2) examine the micromorphology of seeds and leaves in populations of this species. These comprehensive analyses, combining the genetic structure of the populations and micromorphological data, may provide valuable insights into the evolutionary relationships and characteristics of \u003cem\u003eS. ebulus\u003c/em\u003e.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlant material\u003c/h2\u003e \u003cp\u003eGenetic and morphological data from seven populations of \u003cem\u003eSambucus ebulus\u003c/em\u003e in North Iran were examined in this study (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Plant samples were collected from various locations and stored at the Gonbad Kavous University Herbarium (GKUH). Geographic coordinates and elevation of each genotype's habitat were determined using GPS technology.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInvestigated \u003cem\u003eSambucus ebulus\u003c/em\u003e populations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLocality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVoucher number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAltitude (m)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMazandaran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBabol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e804509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eE\u003c/p\u003e \u003cp\u003e52.6625\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e36.6001\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGolestan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGolestan Forest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e804502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eE\u003c/p\u003e \u003cp\u003e55.7828\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e37.5793\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e457\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMazandaran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e804500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eE\u003c/p\u003e \u003cp\u003e53.6402\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e36.7013\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmlash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e804508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eE\u003c/p\u003e \u003cp\u003e50.1844\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e37.0961\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLahijan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e804506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eE\u003c/p\u003e \u003cp\u003e50.0028\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e37.2060\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGolestan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKordkoy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e804504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eE\u003c/p\u003e \u003cp\u003e54.1480\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e36.6686\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGolestan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBandar Gaz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e804503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eE\u003c/p\u003e \u003cp\u003e54.5838\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003cp\u003e36.7813\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction\u003c/h2\u003e \u003cp\u003eGenomic DNA from the plant samples was extracted using the CTAB-activated charcoal protocol as described in various studies (Doyle \u0026amp; Doyle \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Doyle \u0026amp; Dickson \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Cullings \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Amini et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e; Nasrollahi et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The quality and quantity of the extracted DNA were assessed by running it on a 0.8% agarose gel.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eISSR-PCR\u003c/h2\u003e \u003cp\u003eThe PCR experiment was conducted using 12 samples and four ISSR primers (refer to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) in a 25 \u0026micro;L reaction volume. The reaction mixture included 2.5 mM MgCl2 (Cinna Gen Co, Iran), 0.2 \u0026micro;M of primer (Cinna Gen Co, Iran), 10 mM Tris-HCl pH 8.3, 1 mM dNTP mix (Cinna Gen Co, Iran), 1 U of Taq DNA polymerase-500 (Cinna Gen Co, Iran), and approximately 40 ng of template DNA. The ISSR-PCR was carried out using a thermocycler (Biorad, USA) with the program outlined in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The amplified products were visualized by running them on a 1% agarose gel electrophoresis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe used ISSR primers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSequences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISSR13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(ACG) \u003csub\u003e6\u003c/sub\u003eGa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISSR826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCCGGATCC\u003c/p\u003e \u003cp\u003e(CA)\u003csub\u003e8\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISSR810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(GA) \u003csub\u003e8\u003c/sub\u003e T\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISSR7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(AC) \u003csub\u003e8\u003c/sub\u003e AG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePCR program for ISSR primers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCycling\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial denaturation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 \u0026ordm;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDenaturation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 \u0026ordm;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnealing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 \u0026ordm;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 \u0026ordm;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 sec\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinal extension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 \u0026ordm;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eISSR analysis\u003c/h2\u003e \u003cp\u003eThe ISSR bands obtained were treated as binary characters, with the presence of a band coded as 1 and absence as 0. Genetic diversity parameters, including Nei's gene diversity (H), Shannon information index (I), number of effective alleles, and percentage of polymorphism, were calculated for each population following the methods described by Freeland et al. (2011). Nei's genetic distance was used for clustering analysis using Neighbor-Joining (NJ), WARD, and Unweighted Paired Group using Average (UPGMA) algorithms. Principal Coordinate Analysis (PCoA) and Multidimensional Scaling (MDS) methods were also employed for grouping the populations after 100 permutations, as outlined in Freeland et al. (2011). To assess the correlation between genetic and geographical distances among the populations, Mantel's test was conducted using PAST ver. 2.17 (Hammer et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and DARwin ver. 5 (Perrier and Jacquemoud-Collet, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) software.\u003c/p\u003e \u003cp\u003eFor determining the genetic differentiation of the species, an AMOVA (Analysis of Molecular Variance) test was performed using GenAlex 6.4 (Peakall and Smouse, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Gene flow was estimated using the Nm value, calculated from GST using Pop Gene ver.1.32 (Nm\u0026thinsp;=\u0026thinsp;0.5(1 - GST) / GST) and by the least square method as implemented in T-REX (Boc et al., 2012).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eScanning electron microscopy\u003c/h2\u003e \u003cp\u003eIn the analysis process, three samples of each species were utilized. The samples were boiled for 20 minutes, and the openings were observed. Subsequently, they were preserved in 70% alcohol post-placement in Carnoy's solution for 24 hours. To prepare them for observation under a light microscope, the samples were initially immersed in distilled water until they became colorless and then rinsed with water. Light microscopy was employed to create slides, and an 8-megapixel Canon digital camera (model a63) was utilized for examination.\u003c/p\u003e \u003cp\u003eThe use of a scanning electron microscope enables the acquisition of high zoom images through advanced imaging techniques, allowing for the investigation of morphological, structural, and elemental details at intricate levels (URL-2, 2016). The leaf epidermis of each species was scrutinized under a stereomicroscope to verify normal size and development. The specimens were affixed directly onto aluminum stubs using double-sided adhesive, coated with a thin layer of gold (approximately 25 nm), and examined using a VEGA II TESCAN-LMU Electron Microscope at an accelerating voltage of 15\u0026ndash;22 kV at the Research Institute of Razi in Tehran, Iran. Subsequent to this procedure, analysis and imaging were carried out utilizing the scanning electron microscope. Microphotographs of the samples were captured using suitable applications, micrometric measurements were taken, and data were digitized.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eISSR assay and genetic diversity\u003c/h2\u003e \u003cp\u003eThe DNA extraction process yielded high-quality molecules suitable for the genetic diversity study. Gel electrophoresis results indicated clear nucleic acid molecules without smearing, confirming their suitability for polymerase chain reaction (PCR) amplification. All examined primers generated bands within the desired size range of 200 to 900 bp. To ensure accuracy, only bands with optimal resolution were considered. ISSR primers revealed 19 bands per locus, with predominantly polymorphic bands and only two monomorphic bands. Population 4 and 5 exhibited the greatest band diversity (12 bands), while populations 1 and 3 displayed the lowest band count (9 bands). Notably, populations 5 and 6 uniquely featured two specific bands amid more general bands across all populations (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e show the parameters of genetic diversity and Nei\u003csup\u003e\u0026rsquo;\u003c/sup\u003es genetic distance for \u003cem\u003eS. ebulus\u003c/em\u003e in detail.\u003c/p\u003e \u003cp\u003eThe discriminating power of ISSR loci as determined by Gst against Nm (the number of migrants) analysis, showed that almost all ISSR loci have an excellent discriminating power. Thus, ISSR markers are efficient in differentiating of the studied \u003cem\u003eS. ebulus\u003c/em\u003e populations.\u003c/p\u003e \u003cp\u003eThe AMOVA test allows the calculation of the molecular variance components, which illustrate the contributions of the variances intra- and inter-groups to the total genetic variation. The test results revealed significant genetic differentiation among the studied populations (P\u0026thinsp;=\u0026thinsp;0.001), indicating distinct genetic clustering (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The AMOVA test showed that 87% of the total genetic variance was due to differences inter-populations genetic differences, while 13% was due to within-populations genetic variability (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This substantial inter-population genetic diversity highlights the valuable genetic resources present in these populations for future breeding programs. The results emphasize the marked genetic diversity observed in samples of the same species from different regions.\u003c/p\u003e \u003cp\u003eMoreover, the Mantel's test conducted to assess the relationship between geographic and genetic distances demonstrated a significant correlation among populations (P\u0026thinsp;=\u0026thinsp;0.01). This implies that as populations become geographically more distant from each other, they also exhibit increasing genetic divergence.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eItems of ISSR bands in \u003cem\u003eSambacus ebolus\u003c/em\u003e populations (Populations 1\u0026ndash;7 matching Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePop1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePop2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePop3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePop4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePop5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePop6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePop7\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. Bands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. Bands Freq.\u0026nbsp;(\u0026ge;\u0026thinsp;5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. Private Bands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. Common Bands (\u0026le;\u0026thinsp;25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. Common Bands (\u0026le;\u0026thinsp;50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGenetic diversity details in \u003cem\u003eSambacus ebolus\u003c/em\u003e populations (Pop. 1\u0026ndash;7 are according to Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003euHe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e%P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNote: N\u0026thinsp;=\u0026thinsp;Number of studied plants, Na\u0026thinsp;=\u0026thinsp;Number of Different alleles, Ne\u0026thinsp;=\u0026thinsp;Number of Effective alleles, I\u0026thinsp;=\u0026thinsp;Shannon's Information Index, He\u0026thinsp;=\u0026thinsp;Expected Heterozygosity, uHe\u0026thinsp;=\u0026thinsp;Unbiased gene diversity, and P% = Percentage of Polymorphic Loci.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eNei\u003c/b\u003e\u003csup\u003e,\u003c/sup\u003e\u003cb\u003es genetic identity (above diagonal) and genetic distance (below diagonal) (Populations numbers matching to\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003ePair-wise AMOVA between\u003c/b\u003e \u003cb\u003eSambacus ebolus\u003c/b\u003e \u003cb\u003epopulations (PhiPT Values below diagonal. Probability values based on 99 permutations are shown above diagonal)\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMOVA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePop 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePop 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePop 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePop 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePop 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePop 6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePop 7\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePop 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe population clustering and grouping based on ISSR data by NJ (Figure not given), UPGMA tree, PCO and MDS plot (Figure not given) showed similar results. Upon evaluation of the ISSR data, the UPGMA analysis illustrated the presence of two primary clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Within the first cluster, population 6 (Golestan, Kordkoy) appeared as a distinct sub-cluster from the other populations. Furthermore, populations 1 (Mazandaran, Babol) and 3 (Mazandaran, Noor) clustered together, separate from populations 2 (Golestan, Golestan Forest) and 7 (Golestan, Bandar Gaz) which formed another close cluster. The second cluster also exhibited two sub-clusters, with populations 5 (Gilan, Lahijan) and 4 (Gilan, Amlash) forming a separate cluster.\u003c/p\u003e \u003cp\u003eThe results of the PCOA plot aligned with those of the UPGMA chart. Populations 2 (Golestan, Golestan Forest) and 7 (Golestan, Bandar Gaz) along with populations 1 (Mazandaran, Babol) and 3 (Mazandaran, Noor) appeared to constitute closely related genetic groups. Population 6 (Golestan, Kordkoy) exhibited genetic resemblance to populations 1 and 3. Populations 4 (Gilan, Amlash) and 5 (Gilan, Lahijan) displayed significant genetic differentiation from the other populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurther, The CCA plot of genetic data and environmental features revealed that geographic factors such as latitude and longitude are effective in separation of studied \u003cem\u003eS. ebolus\u003c/em\u003e populations, particularly in populations 4 and 5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMicromorphology\u003c/h2\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003eLeaf epidermal cell\u003c/h2\u003e \u003cp\u003eIn the research conducted, leaf epidermal traits were analyzed, focusing on characteristics such as the shape of epidermal cells, anticlinal wall, stomatal type, stomatal index, stomatal length, and width at the lower surface. Examination of the epidermis of the studied populations using electron microscopy revealed the presence of stomata on the lower surface across all populations, with all exhibiting the anomocytic type of stomata. The investigation indicated that the epidermal cells of various \u003cem\u003eS. ebulus\u003c/em\u003e populations featured irregular cell shapes with anticlinal walls ranging from straight to curve. The electron microscope images in Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, \u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, and \u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e provide visual representations of the epidermis of different populations, showcasing the observed characteristics of the epidermal cells and stomata for comparative analysis and detailed examination. The measurements conducted revealed that the population from Golestan province had the highest average width and length of the aperture among the studied populations of this species, with an average width of 40.68 \u0026micro;m and an average length of 55.44 \u0026micro;m. In contrast, the population from Mazandaran province exhibited the lowest averages, with an average width of 41.28 \u0026micro;m and an average length of 52.24 \u0026micro;m. These comparative values are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e of the study.\u003c/p\u003e \u003cp\u003eAdditionally, the examination of trichome characteristics in the populations of the studied species highlighted various types of covering trichomes on the epidermis of \u003cem\u003eS. ebulus\u003c/em\u003e. These included simple single-cell trichomes, multi-cell trichomes, glandular trichomes, and conical or triangular trichomes. Despite the presence of these different types of trichomes across populations, variations were observed in the density of trichomes among the studied populations. These findings add further insights into the morphological diversity within different populations of \u003cem\u003eS. ebulus\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of the observed variation in the epidermal features of \u003cem\u003eS. ebulus\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCell Shape\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnticlinal Wall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Stomata size\u003c/p\u003e \u003cp\u003e(width*Length)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean trichome\u003c/p\u003e \u003cp\u003elength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDensity of\u003c/p\u003e \u003cp\u003etrichome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGolestan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eirregular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003estraight to curved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.44*47.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003edense\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGilan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eirregular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003estraight to curved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.18*37.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esparse\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMazandaran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eirregular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003estraight to curved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.24*41.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003edense\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSeed surfaces\u003c/h2\u003e \u003cp\u003eThe seed characteristics deemed to have potential taxonomic significance in \u003cem\u003eS. ebulus\u003c/em\u003e have been summarized in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. The seeds were found to range in length from 2.58 to 2.77 mm and in width from 1.19 to 1.35 mm. Upon examining the seeds from various populations of the species, it was observed that all seeds exhibited an almond shape. Furthermore, the seed shape was described as predominantly almond-shaped, and the seed-coat surface of the studied taxa displayed a reticulate pattern, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e. These findings provide valuable insights into the consistent seed morphology and surface features across different populations of \u003cem\u003eS. ebulus\u003c/em\u003e, which can be important for taxonomic classification and identification purposes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristic features of the investigated seeds in \u003cem\u003eS.ebulus\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eShape\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLength (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWidth (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLength/ Width\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSeed surface\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGolestan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlmond shape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eReticulate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGilan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlmond shape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eReticulate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMazandaran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlmond shape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eReticulate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGenetic relationship estimations among individuals are influenced by multiple factors, including the number and distribution of markers in the genome, as well as the underlying evolutionary mechanisms (Powell et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). The effectiveness of the ISSR method in providing genetic information is highly dependent on the choice of primers. Ellis et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) demonstrated that selecting six optimal primer combinations could account for 80% of the expected relationships. In this study, four primary primers were selected based on established protocols and previous successful outcomes (Talebi Kohyakhy et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Ahkami et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Antonio et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The genetic diversity among populations was found to be 87% in this investigation. Melchinger (1997) emphasized that the accuracy of genetic similarity estimation relies on the number of markers, level of polymorphism, and genomic coverage of markers employed.\u003c/p\u003e \u003cp\u003eThe results of Canonical Correspondence Analysis (CCA) in our study indicate that environmental factors such as latitude, longitude, and altitude have a simultaneous impact on gene flow and genetic structure within the studied populations. These variations among populations may suggest distinct taxonomic groups within \u003cem\u003eS. ebulus\u003c/em\u003e below the species level. Previous research on various plant species, including wheat (\u003cem\u003eTriticum turgidum\u003c/em\u003e and \u003cem\u003eTriticum durum\u003c/em\u003e), has also shown a correlation between genetic diversity and geographical distribution. Genotypes from different regions and latitudes often exhibit genetic differentiation (Omidbakhshfard et al., 2009; Ahkami et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Many studies have reported the existence of different ecotypes resulting from genetic differences among populations, leading to morphological divergence (Sheidai et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; 2014; Minaeifar et al., 2015; Atazadeh et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It is interesting to note that in \u003cem\u003eFerula gummosa\u003c/em\u003e, a lack of correlation between molecular diversity and geographic diversity has been reported (Khonani et al., 2009). This highlights the complexity and variability of genetic and environmental interactions across different plant species and populations.\u003c/p\u003e \u003cp\u003eIn Principal Coordinate Analysis (PCO), when the principal components account for a lower percentage of variation, it suggests that they provide a more proper distribution at the genome level. This indicates that the selected markers are effectively capturing genetic diversity. By sampling markers from different parts of the genome that have less correlation with each other, the analysis can provide a broader representation of genetic variation. The study by Messmer et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1992\u003c/span\u003e) supports using principal component analysis as a complementary method to cluster analysis to optimize the utilization of molecular data and extract maximum information. The PCO plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) and UPGMA clustering (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) in our study show that the distribution of genotypes in the two-dimensional axis aligns well with the dendrogram, indicating consistency between the different analytical approaches. These results suggest that the selected ISSR markers for genetic analysis represent diverse regions of the genome and are effectively capture the genetic variation within the studied populations. This comprehensive approach can provide valuable insights into the genetic diversity and structure of the populations under investigation.\u003c/p\u003e \u003cp\u003eThe results of our study suggest that there is a high level of diversity among the ecotypes of \u003cem\u003eSambucus\u003c/em\u003e from different geographical regions in the north of the country. The presence of morphological diversity indicates that the observed differences in the samples are not solely influenced by environmental factors but are also under genetic control. The study highlights the effectiveness of the Inter-Simple Sequence Repeat (ISSR) method as a rapid, powerful, and cost-effective tool for genetic analysis. This method requires minimal initial work and can identify numerous gene locations that may not be easily accessible with other techniques within the same time frame and budget constraints. The work of Powell et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) also supports the utility of the ISSR technique, emphasizing its high repeatability and ability to measure a large number of gene locations efficiently in a single test. The repeatability of the ISSR method is crucial in assessing the quality of genetic markers, as it ensures consistent results that can be used for accurate clustering and genetic analysis of diverse samples. The ISSR method provides researchers with a reliable and efficient approach to capture genetic variation and understanding the underlying factors influencing diversity within \u003cem\u003eSambucus\u003c/em\u003e ecotypes from different regions.\u003c/p\u003e \u003cp\u003eThe use of scanning electron microscopy (SEM) in studying \u003cem\u003eSambucus ebulus\u003c/em\u003e has provided valuable insights into the plant's morphology, revealing significant variation and introducing novel morphological features that contribute to a better understanding of the species. The scanning electron microscopy (SEM) is a specialized tool that has undergone significant advancements in recent years, although it may not be readily available in all laboratories due to its complexity and cost. In our study, SEM was employed to characterize and describe the surface characteristics of leaves and seeds of \u003cem\u003eSambucus ebulus\u003c/em\u003e. The examination of epidermal structures in populations from Golestan, Gilan, and Mazandaran regions revealed differences in cellular and stomatal characteristics among the species, likely influenced by varying environmental conditions in those regions. Stomata, such as the anomocytic-type aperture found on the lower surface of the species, play a crucial role in species recognition across different taxonomic, ecological, and physiological levels. These apertures are important features that can help differentiate species and are indicative of the plant's evolutionary adaptations to its environment. By studying these structural features using SEM, researchers can gain a deeper understanding of the unique characteristics of \u003cem\u003eSambucus ebulus\u003c/em\u003e and its variations across different geographical regions. The stomatal density of plants, including \u003cem\u003eSambucus ebulus\u003c/em\u003e, is influenced by a combination of natural, environmental, and ecological factors. Studies have shown that factors such as water availability, leaf size, and stomatal size play a significant role in determining stomatal density (Blum et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). These characteristics are closely linked to the habitat of the species and can vary at different levels of taxonomic classification and across different environmental conditions.\u003c/p\u003e \u003cp\u003eGenetic factors also have a notable influence on the development of stomatal traits in plants (Miller \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). Research on \u003cem\u003eS. ebulus\u003c/em\u003e has revealed variations in stomatal index among different populations, with the population in Golestan province exhibiting the highest stomatal index and the population in Mazandaran province having the lowest stomatal index. These differences are attributed to the specific humidity conditions and habitats in which the populations are found. In habitats with higher humidity and ample water resources, plants tend to have lower stomatal indexes compared to those in drier environments. This relationship highlights the adaptive responses of plants to their specific environmental conditions. The aperture index, which is influenced by stomatal density, is also lower in populations with sufficient humidity, such as those in Mazandaran province, compared to populations in drier regions like Golestan province. These findings are consistent with previous studies, such as those by Van de Roovaaort and Fuller (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1935\u003c/span\u003e), which showed that plants subjected to drought stress tend to have higher stomatal density as a response to water scarcity. The data from this research provide valuable insights into the stomatal characteristics of \u003cem\u003eS. ebulus\u003c/em\u003e and offer a foundation for further investigations into the species and its adaptation to varying environmental conditions.\u003c/p\u003e \u003cp\u003eThe morphology of seeds, including characteristics such as shape, size, and surface ornamentation, can provide valuable insights for identifying and classifying plant species. Studies have indicated that these seed attributes are influenced by genetic and phylogenetic differences among taxa and are relatively stable across different environmental conditions (Barthlott \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Ozcan \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the case of the target species population, all seeds were observed to be almond-shaped with reticulate grain surfaces. This uniformity in seed morphology suggests that these features are genetically determined and can serve as distinguishing traits for identifying the species. The presence of such consistent seed characteristics supports the idea that these traits hold taxonomic significance and can help clarify relationships among species that share morphological similarities.\u003c/p\u003e \u003cp\u003eThe importance of seed morphology in plant classification has been emphasized in various studies, validating its value as a systematic trait for species identification (Amini et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e; Amini et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The results of the research highlight grain size and surface ornamentations as key distinguishing features that can aid in the identification of plant species in Iran. These seed attributes provide valuable systematic information that can enhance our understanding of plant diversity and assist in resolving taxonomic ambiguities.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn the present study, the genetic diversity of \u003cem\u003eS. ebulus\u003c/em\u003e populations was investigated using ISSR molecular data. Our results showed a high degree of genetic variability among populations of \u003cem\u003eS. ebulus\u003c/em\u003e, which is important for assessing the genetic diversity of this species. The UPGMA dendrogram based on the molecular data provided valuable information on the relationships among the studied populations. This comprehensive approach can provide valuable insights into the genetic diversity and genetic structure of the studied populations. The ISSR method provides researchers with a reliable and efficient approach to capture genetic variation and to understand the underlying factors that influence diversity within \u003cem\u003eSambucus\u003c/em\u003e ecotypes from different regions. Examination of the epidermal structures in populations from the Golestan, Gilan and Mazandaran regions revealed differences in the cellular and stomatal characteristics of the species, which are likely to be influenced by the different environmental conditions in these regions.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eClinical trial number\u003c/strong\u003e \u003cp\u003enot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e\"Elham Amini wrote the main manuscript text and Ali Sattarian and Marzieh Bayrami and Mahmood Salehi prepared figures 1-12. Neda Atazadeh prepared the analyses. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors would like to thank Miss Beyk Mohammadi for the advice lab and wish to express our gratitude to Mr. Hosseini for constative suggestion. The present study was financially supported by Gonbad Kavous University, Gonbad (Iran).\u003c/p\u003e\u003ch2\u003eAvailability of data and material\u003c/h2\u003e \u003cp\u003eNo data was used for the research described in the article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhkami AH, Naghavi MR, Hossein Zadeh A, Pirseiedi SM, Patki P, Kazemi Almoti M, Poor Irandoost H, Omid Bakhsh MA. Genetic Relationship in Durum Wheat (Triticum durum) Using AFLP Markers. Iran Agric Sci. 2007;1:25\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmini E, Nasrollahi F, Sattarian A, Kor S, Boozar pour S. 2018a. Molecular and micro-morpholog-ical evidences of the genus Cuscuta in Iran. Rostaniha 19(2), 113\u0026ndash;129. (PDF) Palynological studies of some species of the genus Cuscuta with emphasis on taxonomy.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmini E, Kazempour-Osaloo S, Maassoumi AA, Zare-Maivan H. Phylogeny, biogeography, and divergence times of \u003cem\u003eAstragalus\u003c/em\u003e section \u003cem\u003eIncani\u003c/em\u003e DC. (Fabaceae) inferred from nrDNA ITS and plastid \u003cem\u003erpl\u003c/em\u003e32\u003cem\u003e-trn\u003c/em\u003eL\u003csub\u003e(UAG)\u003c/sub\u003e sequences. \u0026ndash; Nordic j bot. 2018b;1:1\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmini E, Nasrollahi F, Sattarian A, Isazadeh-Araei M, Habibi M. Systematic and molecular biological study of Sambucus L.(Caprifoliaceae) in Iran. Thaiszia J Bot. 2019a;29:133\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmini E, Nasrollahi F, Sattarian A, Khormali A, Habibi M. Micromorphological and molecular study of four species of Lonicera (Caprifoliaceae) in Iran. Phytologia Balcanica. 2019b;25:181\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmini E, Nasrollahi F, Sattarian A, Isazadeh-Araei, Habibi M. 2021. Morphological and anatomical study of the genus Sambucus L.(Adoxaceae) in Iran. Mod Phytomorphology, \u003cem\u003e15\u003c/em\u003e(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmini E, Sattarian A, Nasrollahi F, Daneshvar A, Mohammad Esmaeili M, Hamidzadeh Sani L, Haghighi S. Micromorphological study of some Salsola species (Amaranthaceae) in Iran and its systematic significance using scanning electron microscopy. Microsc Res Tech. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jemt.24623\u003c/span\u003e\u003cspan address=\"10.1002/jemt.24623\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntonio AFG, Benchimol LL, Barbosa AMM, Geraldi IO, Souza CL. Comparison of RAPD, RFLP, AFLP and SSR markers for diversity studies in tropical maize inbred lines. Gen Mol Bio. 2004;27:579\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAtazadeh N, Sheidai M, Attar F, Koohdar F. (2020). Genetic and morphological diversity in \u003cem\u003eCousinia calocephala\u003c/em\u003e jaub. \u0026amp; spach (Asteraceae; section \u003cem\u003eCynaroideae\u003c/em\u003e bunge) populations. Genetika, 52(1): 199\u0026ndash;214.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarthlott W. Microstructural Features of Seed Surface. In: Heywood VH, Moore DC, editors. Current Concepts in Plant Taxonomy. Cambridge: Academic; 1984. pp. 95\u0026ndash;105.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlum A, Gozlan G, Mayer J. The Manifestation of dehydration avoidance in wheat breeding germplasm 1. Crop Sci. 1981;21:495\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBOC A, DIALLO AB, V., MAKARENKOV. T-REX: a web server for inferring, validating and visualizing phylogenetic trees and networks. Nucleic Acid Res. 2012;40:W573\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCullings KW. Design and testing of a plant-specific PCR primer for ecological and evolutionary studies. Mol Ecol. 1992;1(3):233\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoyle JJ, Dickson EE. Preservation of plant samples for DNA restriction endonuclease analysis. Taxon. 1987;36(1):715\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoyle JJ, Doyle JL. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bull. 1987;19:11\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEllis RP, Mcnicol JW, Baird E, Booth A, Lawrence P. The use of AFLP to examine genetic relatedness in barley. Mol Breeding. 1997;3:359\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFreeland JR, Kirk H, S.D., Peterson. Molecular Ecology. second ed. UK: Wiley-Blackwell; 2011. p. 449.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGintzburger G, Toderich KN, Mardonov BK, Makhmudov MM. Rangelands of the Arid and Semi_Arid Zones in Uzbekistan. Montpellier: CIRAD; 2003.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHammer Q, Harper DAT, Ryan PD. PAST: Paleontological Statistics software package for education and data analysis. Palaeontologia Electronica. 2012;4:9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJamzad Z. (1993): \u003cem\u003eSambucus\u003c/em\u003e L. - In: Assadi, M., Khatamsaz, M. and Maassoumi, A.A, editor, Flora of Iran 8. \u003cem\u003eDipsacaceae\u003c/em\u003e\u0026ndash; Tehran: Research Institute of Forests and Rangelands.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJUDD WS, STEVENS CAMPBELLCSKELLOGGEA P.F., DONOGHUE MJ. Plant systematics: a phylogenetic approach. 3rd ed. - Sunderland, MA: Sinauer; 2007.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhounani Z, Naghavi M, Omidi M, Sabokdast M, Talebi Kohyakhi E. (2011). Assessment of Genetic Diversity in the Landraces of Ferula gummosa from Iran Using AFLP Marker, \u003cem\u003eJournal of Medicinal Plants\u003c/em\u003e, 10(38), 117. magiran.com/p893514.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMabberley DJ. The Plant Book, a Portable Dictionary of Higher Plants. Cambridge: - Cambridge University; 2008.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelchinger AE, Gumber RK. Overview of heterosis and heterotic groups in agronomics crops. In: K.R. Lamkey and J.E. Stuber, editors. Concepts and breeding of heterosis in crop plants. Madison, WI. CSSA. 1999, pp: 29\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMessmer MM, Melchinger AA, Boppenmair J, Hermann RG, Brunklaus-Jung E. RFLP analysis of early-maturing European maize germplasm. I. Genetic diversity among flint and dent inbreds. Theor Appl Genet. 1992;83:1003\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller EC. 1983. Plant Physiology.Mc Grow-Hill Book Company Inc. New York. U.S.A.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinaeifar A, Sheidai M, F., Attar. Genetic and morphological diversity in \u003cem\u003eCousinia cylindracea\u003c/em\u003e (Asteraceae) populations: Identification of gene pools. Biodiversitas. 2015;16:288\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNasrollahi F, Kazempour-Osaloo S, Saadati N, Mozaffarian V, Zare-Maivan H. Molecular phylogeny and divergence times of \u003cem\u003eOnosma\u003c/em\u003e (Boraginaceae s.s.) based on nrDNA ITS and plastid rpl32-trnL\u003csub\u003e(UAG)\u003c/sub\u003e and trnH\u0026ndash;psbA sequences. Nord J Bot. 2019;37(1):1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNovelli S. (2003): Developments in berry production and use. pp. 5\u0026ndash;6. Bi-weekly Bul., Vol. 16. Agriculture et Agroalimentaire Canada.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOmid bakhsh fard MA, Naghavi MR, Mardi M, Bihamta MR, Kazemi M, Pirseyedi SM. A study of genetic diversity in Durum Wheat (Triticum turgidum) using microsatellite markers. Iran Agric sci. 2009;2:75\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOzcan M. Nutrient Composition of Rose (Rosa canina L.) Seed and Oils. J Med Food. 2002;5:137\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeakall R, Smouse PE. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes. 2006;6:288\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerrier X, jacquemoud-collet JP. (2006): DARwin Software. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://darwin.cirad.fr/darwin\u003c/span\u003e\u003cspan address=\"http://darwin.cirad.fr/darwin\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePourmeidani A, Amini E, Nasrollahi F, Mohammadi Y. Genetic Diversity and Population Structure of Haloxylon Aphyllum in Iran by ISSR Markers. Acta Bot Hungarica. 2023;65(3\u0026ndash;4):385\u0026ndash;98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1556/034.65.2023.3-4.9\u003c/span\u003e\u003cspan address=\"10.1556/034.65.2023.3-4.9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePowell W, Morgante M, Andre C, Hanafey M, Vogel J, Tingey S, Rafalsky A. The comparison of RFLP, RAPD, AFLP and SSR markers for germplasm analysis. Mol Breeding. 1996;2:225\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRabizadeh F, Amini E, Nasrollahi F. The anatomical and micromorphological properties of endemic species to gypsic soils of Semnan, Iran. J Struct Biol. 2023;215(2):107968.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSedl\u0026aacute;čkov\u0026aacute; VH, Grygorieva O, Fatrcov\u0026aacute;-Šramkov\u0026aacute; K, Vergun O, Vinogradova Y, Ivanišov\u0026aacute; E, Brindza J. The Morphological and Antioxidant Characteristics of Inflorescences within wild-growing Genotypes of Elderberry (\u003cem\u003esambucus nigra\u003c/em\u003e L). \u0026ndash; Potr S J F Sci. 2018;12/ 1:444\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSheidai M, Seif E, Nouroozi M, Z., Noormohammadi. Cytogenetic and molecular diversity of \u003cem\u003eCirsium arvense\u003c/em\u003e (Asteraceae) populations in Iran. J Jap Bot. 2012;87:193\u0026ndash;205.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSheidai M, Zanganeh S, Haji-ramezanali R, Nouroozi M, Noormohammadi Z, Ghasemzadeh-Baraki. Genetic diversity and population structure in four \u003cem\u003eCirsium\u003c/em\u003e (Asteraceae) species. Biologia. 2013;68:384\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSheidai M, Ziaee S, Farahani F, Talebi SM, Noormohammadi Z. Y., Hasheminejad ahangarani Farahani (2014): Infra-specific genetic and morphological diversity in \u003cem\u003eLinum album\u003c/em\u003e (Linaceae). Biologia, 69: 32\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShen Z, Tang Z, Yuan D, Ding X, Cheng J. Genetic diversity of elderberry germplasm with ISSR makers. J Northeast Forestry Univ. 2019;47(10):8\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTalebi Kohyakhy E, Mohammad Aliha M, Naghavi MR. Genetic diversity in Ferula gummosa Bioss. Populations of Iran using RAPD molecular markers. Iran J Med Aromatic Plants. 2008;23(4):514\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eToderich KN. (2008). Genus Salsola of Central Asian flora: its structure and adaptive evolutionary trends. PhD Thesis, Tokyo University of Agriculture and Technology.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUNCINIMANGANELLI RE, ZACCARO L., TOMEI PE. Antiviral activity in-vitro of Urtica dioica L., Parietaria diffusa and Sambucus nigra L. J Ethnopharmacol. 2005;98:323\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan de Roovaaort E, Fuller GD. Stomatal frequency in cereals. J Ecol. 1935;16:278\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaswa EN, Mutinda ES, Mkala EM, Katumo DM, Oulo MA, Odago WO, Amenu SG, Ding S-X, Hu G-W. Understanding the Taxonomic Complexes and Species Delimitation within Sambucus L.(Viburnaceae). Diversity. 2022;14(11):906.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"AMOVA, Genetic, Iran, Populations, SEM","lastPublishedDoi":"10.21203/rs.3.rs-4998002/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4998002/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eSambucus ebulus\u003c/em\u003e is mainly distributed in the northern, northwestern and northeastern regions of Iran and is characterized by its perennial growth habit and distinctive long, creeping and branched rhizomes. In this study, genetic diversity of seven populations \u003cem\u003eS. ebulus\u003c/em\u003e based on molecular ISSR data and the micromorphology of seeds and leaves of this species in Iran were investigated. Micromorphological examination revealed the anomocytic type of stomata and indicated that the epidermal cells of various \u003cem\u003eS. ebulus\u003c/em\u003e populations exhibited irregular cell shapes with anticlinal walls ranging from straight to curved. The seed shape was described as predominantly almond-shaped, and the surface of the seed coat of the studied taxa showed a reticulate pattern. The AMOVA (analysis of molecular variance) test showed that 87% of the total genetic variance was due to differences inter-populations genetic differences, while 13% was due to within-populations genetic variability, indicating a high degree of genetic variation among \u003cem\u003eS. ebulus\u003c/em\u003e populations. The discriminating power of ISSR (inter simple sequence repeat) loci as determined by Gst against Nm (the number of migrants) analysis, showed that almost all ISSR loci have an excellent discriminating power. Thus, ISSR markers are efficient in differentiating of the studied \u003cem\u003eS. ebulus\u003c/em\u003e populations. The Mantel test presented a significant correlation between genetic and geographic distance. These results suggest that the selected markers for genetic analysis represent different regions of the genome and effectively capture the genetic variation within the studied populations.\u003c/p\u003e","manuscriptTitle":"Genetic and micromorphological differentiation within Sambacus ebulus (Adoxaceae) suggests divergence of populations from Iran","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-09 13:55:31","doi":"10.21203/rs.3.rs-4998002/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"232a7c9f-b7bb-4031-96f5-31877be5e587","owner":[],"postedDate":"October 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-10T18:23:11+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-09 13:55:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4998002","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4998002","identity":"rs-4998002","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}