Caryologia. International Journal of Cytology, Cytosystematics and Cytogenetics 78(2): 3-19, 2025 Firenze University Press https://riviste.fupress.net/index.php/caryologiaCaryologia International Journal of Cytology, Cytosystematics and Cytogenetics ISSN 0008-7114 (print) | ISSN 2165-5391 (online) | DOI: 10.36253/caryologia-3633 Citation: Radmanesh, P. & Karimza- deh, G. (2025). Chromosome, ploidy anal- ysis, and flow cytometric genome size of caper (Capparis spinosa) medici- nal plant. Caryologia 78(2): 3-19. doi: 10.36253/caryologia-3633 Received: July 6, 2025 Accepted: September 30, 2025 Published: December 20, 2025 © 2025 Author(s). This is an open access, peer-reviewed article pub- lished by Firenze University Press (https://www.fupress.com) and distrib- uted, except where otherwise noted, under the terms of the CC BY 4.0 License for content and CC0 1.0 Uni- versal for metadata. Data Availability Statement: All rel- evant data are within the paper and its Supporting Information files. Competing Interests: The Author(s) declare(s) no conflict of interest. ORCID: PR: 0000-0002-1825-0097 Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant Parviz Radmanesh, Ghasem Karimzadeh* Department of Plant Genetics and Breeding, College of Agriculture, Tarbiat Modares University, Tehran P. O. Box 14115-336, Iran *Corresponding author. Email: karimzadeh_g@modares.ac.ir Abstract. Caper (Capparis spinosa) is a shrubby, deciduous perennial medicinal plant belonging to the Capparaceae family. Its use is in folk medicine, pharmacy, food, and spices. Chromosome, ploidy analysis, and flow cytometric genome size of 10 popula- tions collected from different parts of Iran were analyzed. The results showed that all populations were diploid, with nine populations having 2n = 2x = 30 (P1-P8, P10) and one population having 2n = 2x = 34 (P9) chromosomes. The average chromosome length (CL) for these two chromosome groups was 1.05 and 0.97 μm, respectively. The mean monoploid genome sizes for the populations with 30 and 34 chromosomes were 0.646 and 0.633 pg, respectively. As a whole, the mean genome size of all populations was 0.643 pg. The chromosome number as well as the genome size are being reported for the first time. Cluster analysis and principal component analysis revealed a catego- rization of the caper population into four distinct groups. The first group comprised three populations (P1, P3, and P4), while the second group included only P2 popula- tion, the third group was represented by two populations (P5 and P7), and the fourth group encompassed four populations (P6, P8, P9, and P10). Future research on the genetic traits and breeding methodologies of this species can build upon the founda- tional findings of this study. Keywords: caper, Capparis spinosa, chromosome, karyology, 2Cx DNA, genome size, flow cytometry. INTRODUCTION People of every culture have always experimented with endemic plants over thousands of years and have recognized that almost all of nature is used for food, clothing, shelter, and they have adapted based on the available resources. Plants that have beneficial pharmacological effects on the human body are called medicinal plants and are useful almost exclusively due to their natural ability to synthesize secondary metabolites (Sundarrajan and Bhagtaney, 2023). The presence of various secondary metabolites such as fla- vonoids, alkaloids, saponins, tannins, terpenoids, and phenolic compounds in medicinal plants has anti-inflammatory, antimicrobial, and antioxidant https://riviste.fupress.net/index.php/caryologia https://doi.org/10.36253/caryologia-3633 https://doi.org/10.36253/caryologia-3633 https://www.fupress.com https://creativecommons.org/licenses/by/4.0/legalcode https://creativecommons.org/publicdomain/zero/1.0/legalcode https://orcid.org/0000-0002-1825-0097 mailto:Karimzadeh_g@modares.ac.ir 4 Parviz Radmanesh, Ghasem Karimzadeh effects, confirming that the use of medicinal plants is a suitable alternative to current conventional methods in the treatment of many problems such as wounds (Cedil- lo-Cortezano et al., 2024). Caper (Capparis spinosa L.) is a common member of the Capparis genus of the Cap- paraceae (Capparidaceae) family, which is a thorny per- ennial shrub and an aromatic plant common in many parts of the world, especially the Mediterranean regions (Shahrajabian et al., 2021). This shrubby plant has woody stems and herbaceous branches with thick, shiny, bright green, oval-shaped, and alternate simple leaves. It has single, fragrant flowers with white to pinkish-white petals, and numerous long purple stamens. The fruit shape is oval-shaped and it has a dark green color (Con- durso et al., 2015; Chedraoui et al., 2017) (Figure 1). Although this plant is native to the Mediterranean, it grows well in Italy, North Africa, Greece, Central Asia, and Iran (Zarei et al., 2021). Caper prefers a rainy spring and a hot, dry summer with intense sunlight, with tem- peratures exceeding 40 °C and an average annual rain- fall of 350 mm (Barbera and Di Lorenzo, 1984). This plant grows both wild and cultivated, and prefers rocky soils in semi-arid regions, limestone slopes, and crev- ices in old walls. Additionally, caper is tolerant to both salt and drought stresses. Due to its ability to grow in harsh environments, this plant is recommended to pre- vent land degradation, control soil erosion, and main- tain and promote agriculture in areas exposed to severe climate change (Sakcali et al., 2008). C. spinosa is one of the most common aromatic plants in Mediterranean cuisine. The flower buds of this plant are edible. The flowers, which are harvested in the spring before they open, are usually processed in brine, pickled in vin- egar, or preserved in grain salt and used as a seasoning in salads, pasta, meat, sauces, and condiments to add a spicy and salty flavor and aroma to food (Cincotta et al., 2022). The fruit, leaves, and the younger branches of the caper plant are edible and consumed salted or pickled in vinegar, or as fresh or cooked vegetables (Moghaddasi, 2011). Different parts of this plant, including the roots, bark, leaves, buds, and fruits, have traditionally been employed to alleviate conditions such as joint diseases, hemorrhoids, rheumatism, rheumatoid arthritis, gout, fever, cough, asthma, and inflammation (Chedraoui et d b c a Figure 1. Whole plant (a), bud and leaf (b), flower (c), and fruit (d) of caper (Capparis spinosa) medicinal plant. 5Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant al., 2017). Furthermore, caper extract exhibits significant properties including antihypertensive, hepatoprotective, antidiabetic, anti-obesity, bronchodilator, antiallergic and antihistamine, antibacterial, antioxidant, and anti- cancer effects (Nabavi et al., 2016; Chedraoui et al., 2017; Merlino et al., 2024). Caper seeds are rich in antioxidant molecules and a source of omega-6, utilized in both the food and pharmaceutical industries (Ara et al., 2013; Tlili et al., 2015). On the other hand, C. spinosa con- tains bioactive lipids, glucosinolates (glucocaprin), and flavonoids (rutin); its seed oil is also rich in unsaturated lipids (Argentieri et al., 2012; Annaz et al., 2022). The most important phytochemical compounds identified, includes quercetin derivatives, kaempferol, isorhamnetin myristicin, eriodictyol, circimaritin, and gallocatechin (Bakr and El Bishbishy 2016). Moreover, it has the alka- loids caparicin A, caparicin B, and caparicin C, which are used in medical treatments (Marir, 2024). Karyotype, as an important genetic feature, rep- resents the phenotypic appearance of somatic chro- mosomes, including chromosome number and length (Ning et al., 2018; Vimala et al., 2021; Abbasi-Karin et al., 2022; Rasekh et al., 2023; Yari et al., 2024; Morova- ti et al., 2024), is used in systematic and evolutionary studies of plants (Peruzzi et al., 2017; Wang et al., 2020; Yari et al., 2024). The simplest technical feature related to the genome of a species is the chromosome number, which is the most fundamental feature. For this reason, since 1882 (Garbari et al., 2012), chromosome num- ber data have been collected for many plant organisms worldwide, representing about one-third of the plant currently known in this respect (Stace, 2000). The Cap- paraceae family consists of about 40-45 genera and 700- 900 species, whose members show significant diversity in terms of appearance, fruit, and floral features (Kamel et al., 2015). The most important genera of this family include Capparis, Cadaba, Boscia, and Maerua (Ali and Amar, 2020). The genus Capparis has about 250 spe- cies, the chromosome numbers for the few known spe- cies of this genus are (2n = 18, 30, 38, 40, and 84) (Rock, 2016). Cadaba indica and Cadaba triphylla, which are both species in the genus Cadaba, have chromosome numbers that are both 14 and 34, respectively reported by Subramanian and Pondmudi (1987). The species Crataeva nurvala belongs to the genus Crataeva has 26 chromosomes (Gupta and Gill, 1981). Another species of this genus, Crataeva religiosa, also has 26 chromosomes (Subramanian and Pondmudi, 1987). The species Mae- rua arenaria sensu Baillon (Subramanian and Pond- mudi, 1987), (Khatoon and Ali, 1993) M. arenaria (DC.) Hook. f. & Thoms. and M. crassifolia Forssk. (Khatoon and Ali, 1993), belonging to the genus Maerua each have 40, 20, and 20 chromosome numbers, respectively. The species Niebuhria linearis DC. of the genus Niebuhria has 102 chromosomes (Sharma, 1968). Capparis, the largest genus in the Capparaceae family, has 250 spe- cies with various chromosome numbers, including C. brevispina DC. (2n = 36) (Subramanian and Pondmudi, 1987), C. decidua Pax (2n = 40) (Khatoon and Ali, 1993), (Subramanian and Pondmudi, 1987) C. divaricata (2n = 160), C. diversifolia Wight & Arn. (2n = 98) (Subrama- nian and Pondmudi, 1987), (Subramanian and Pond- mudi, 1987) C. grandis L. f. (2n = 42), C. leucophylla DC. (2n = 10, 20) (Sandhu, 1989), C. rotundifolia (2n = 42) (Subramanian and Pondmudi, 1987), C. sandwichiana var. Zoharyi, O. Deg. & I. Deg. (2n = 40) (Carr, 1978), C. sepiaria (2n = 40) (Sharma, 1968; Subramanian and Pondmudi, 1987), C. zeylanica (2n = 40, 44) (Singhal and Gill, 1984; Subramanian and Pondmudi, 1987), C. spino- sa (2n = 24, 38) (Magulaev, 1979; Al-Turki et al., 2000), C. spinosa subsp. Rupestris (2n = 38) (Runemark 1996), and C. spinosa var. herbacea (Willd.) (2n = 42) (Wang et al., 2022). Given the valuable medicinal and nutritional value of caper, this study aimed to investigate intraspe- cific diversity among Iranian populations in terms of karyotypic characteristics and genome size. Genome size refers to the amount of genomic DNA present in the gametes of a species, which is generally constant in an organism and is represented as a C-value (Swift, 1950; Greilhuber et al., 2005; Pellicer et al., 2018; Kocjan et al., 2022). The C-value estimation is essen- tial for sequencing and genomic analysis, as well as for plant species identification and classification (Gregory, 2005; Bourge et al., 2018; Sliwinska, 2018). Genome sizes vary considerably among the flowering plants overall, as well as within smaller taxonomic groups such as fami- lies or even genera. Monoploid genome size is refers to the amount of DNA of one chromosome set, 1 Cx-value, with chromosome base number x) and holoploid genome size to the amount of DNA of the whole chromosome complement, 1 C-value, with chromosome number n, regardless of the degree of polyploidy, aneuploidies, etc.) as described by Greilhuber et al. (2005). Flow cytom- etry (FCM) has been used to estimate the plant nuclear DNA content since the 1980s. It is commonly used in plant breeding (especially in polyploid and hybrid breed- ing) (e.g. Doležel and Bartoš, 2005; Doležel et al., 2007; Tavan et al., 2015; Bourge et al., 2018; Javadian et al., 2018; Hamidi et al., 2018; Tarkesh Esfahani et al., 2020) and seed production (Sliwinska, 2018). Recently, studies of karyomorphology and genome size, using flow cytom- etry technique have been conducted in a diverse array of plant communities, such as: Thymus species (Mah- davi and Karimzadeh, 2010; Tavan et al., 2015), Satureja 6 Parviz Radmanesh, Ghasem Karimzadeh (Shariat et al., 2013; Zare Teymoori et al., 2021), Tulipa (Abedi et al., 2015, Papaver bracteatum (Tarkesh Esfa- hani et al., 2016), Artemisia khorassanica (Hamidi et al., 2018), Medicago monantha (Zarabizadeh et al., 2022), Epilobium spp. (Abbasi-Karin et al., 2022), Ferula assa- foetida (Firoozi et al., 2022), berry (Mohammadpour et al., 2022), Allium spp. (Sayadi et al., 2022), Papaver som- niferum (Rasekh and Karimzadeh, 2023), Cymbopogon olivieri (Yari et al., 2024), Coriandrum sativum (Khak- shour et al., 2024), Sapindus mukorossi (Gao et al., 2024), Cyphomandra clade (Mesquita et al., 2024), Nigella and Garidella species (Aydın et al., 2024), and Datura spp. (Morovati et al., 2024) have been used to identify intra- and inter-specific diversity. MATERIALS AND METHODS Plant materials Seeds from 10 endemic Iranian caper (Capparis spi- nosa L.) populations were collected from various regions of Iran during the growing season within their natural habitats. Population codes, geographical coordinates (latitude, longitude), altitude (m), mean annual tempera- ture (°C), and mean annual rainfall (mm) are presented in Table 1 and illustrated in Figure 2. Chromosome analysis Seeds mucilage was first removed by washing with water. The seed coats were then mechanically scari- fied to break dormancy (Olmez et al., 2006; Agah et al., 2020; Radmanesh et al., 2023). For this purpose, seeds were disinfected by immersing in 5% (v/v) sodium hypochlorite for 5 min, followed by 70% (v/v) ethanol for 1 min (Aguilar-Rito et al., 2023; Qi et al., 2023). Sub- sequently, healthy seeds were placed on a layer of What- man filter paper within 9 cm diameter glass petri dishes (Honarmand et al., 2016). To induce germination, seeds were moistened with distilled water at room temperature (RT). Petri dishes were then placed in a growth room under controlled conditions: 16/8 h light/dark at 25 °C (Honarmand et al., 2016). Approximately, 0.5-mm length roots were incubated in a 0.002 M 8-hydroxyquinoline solution for 3 h in the dark at RT (Mehravi et al., 2022a, b; Anjum et al., 2023). Roots were fixed in Carnoy’s fixa- tive (glacial acetic acid:ethanol, 1:3 v/v) for a minimum of 24 h at 4 °C (Karimzadeh et al., 2011; Firoozi et al., 2022; Khakshour et al., 2024; Yari et al., 2024). Follow- ing fixation, Carnoy’s fixative was removed by washing with distilled water for 5 min. Subsequently, root meris- tems were hydrolyzed in 1 M HCl for 10 min at 60 °C. Root samples were stained with 4% (w/v) hematoxylin solution for 3 h at RT in the dark (Mohammadpour et al., 2022). Slides were prepared, using the squash meth- od in 45% (v/v) acetic acid. Photomicrographs were taken with a DP12 digital camera (Olympus Optical Co., Tokyo, Japan) mounted on a BX50 Olympus micro- scope (Olympus Optical Co., Tokyo, Japan). In cytologi- cal studies of plants with small chromosomes (almost one micrometer), accurately measuring the lengths of the long and short arms are often challenging due to the difficulty in identifying the centromere (Morales Val- verde, 1986; Mahdavi and Karimzadeh, 2010; Abbasi- Karin et al., 2022; Rasekh and Karimzadeh, 2023, Yari et al., 2024; Morovati et al., 2024). Hence, in the current study, the chromosome length (CL) was measured, using MicroMeasure software version 3.3. Table 1. Geographic distribution and climatic data of endemic Iranian caper (Capparis spinosa) populations. Populations codes Local collection locations Latitude (N) Longitude (E) Altitude (m) Mean Temp. (˚C) Mean rainfall (mm) P1 Dargaz, Khorasan-e Razavi 37°26’33.25” 59° 6’26.06” 408 12.75 266.70 P2 Balanej, Azarbayjan-e Gharbi 37°24’6.72” 45° 9’54.19” 1303 14.20 341.00 P3 Tehran, Tehran 35°44’38.00” 51° 9’54.71” 1286 18.68 250.98 P4 Torbat-e-Jam, Khorasan-e Razavi 35°15’8.38” 60°35’42.42” 909 26.00 254.00 P5 Ahvaz, Khozestan 31°28’21.02” 48°43’21.48” 17 26.65 191.20 P6 Kharg Island, Bushehr 29°14’16.05” 50°18’58.48” 1 26.18 265.60 P7 Borazjan, Bushehr 29°13’12.64” 51°14’34.86” 104 27.63 283.10 P8 Firuzabad, Fars 28°50’23.45” 52°35’30.92” 1333 20.87 379.70 P9 Fathabad-e Deh-e Arab, Fars 28°40’42.01” 52°41’18.26” 1148 21.20 377.00 P10 Dasht-e Lar, Fars 28°22’11.55” 52°46’38.95” 924 25.70 302.20 7Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant Flow cytometric genome size estimation To estimate genome size, seeds were first germinat- ed in petri dishes. After two weeks, the seedlings were transferred to pots containing a mixture of soil, sand, perlite, and cocopeat in the research greenhouse of the College of Agriculture at Tarbiat Modares University, where suitable growth conditions were maintained. Dur- ing growth, NPK fertilizer was applied after five months when the grown plants having developed leaves suitable for flow cytometric analysis. Then, 1 cm² of young devel- oped leaves from C. spinosa and radish (Raphanus sati- vus cv. Saxa; 2C DNA = 1.11 pg) as an internal reference standard (Doležel et al., 1992) were chopped simultane- ously with a sharp blade in a glass petri dish containing 1 ml of Woody Plant Buffer (WPB; Loureiro et al., 2007). No peaks were identified in the analysis. Hence, instead General Plant Buffer (GPB; 0.5 mM Spermine·4HCl, 30 mM Sodium citrate·3H₂O, 20 mM MOPS, 20 mM NaCl, 80 mM KCl, 1% PVP-10, and 0.5% v/v Triton X-100, pH 7.0) (Loureiro et al., 2007) was used. The resulting nucle- ar suspension was passed through a 30 μm green nylon filter (Partec, Munster, Germany) to remove large tissue fragments and debris. This was followed by the addi- tion of 50 μg ml⁻¹ of RNase (for RNA removal) (Sigma- Aldrich Corporation, MO, USA) and 50 μg ml⁻¹ of pro- pidium iodide (PI, Fluka) fluorescent dye (for nuclear DNA staining) to the samples (Loureiro et al., 2007). The nuclear suspension was then analyzed using a BD FACSCanto™ flow cytometer (Biosciences, Bedford, MA, USA) with BD FACSDiva™ software. The output data were transferred to FloMax ver. 2.4.1 software for gat- Figure 2. Map of Iran showing the collection locations of endemic Iranian medicinal plant caper (Capparis spinosa) populations, using Arc- GIS. 8 Parviz Radmanesh, Ghasem Karimzadeh ing the output histograms. Relative fluorescence inten- sity measurements of stained nuclei were performed on a linear scale, with at least 5,000 nuclei analyzed for each sample. The absolute DNA content of a sample was cal- culated based on the average G1 peak values. The fol- lowing formula was used to determine the genomic DNA content (in pg) of an unreplicated gamete (2Cx DNA) based on the mean G1 peak values in caper (Doležel et al., 2007; Loureiro et al., 2007; Firoozi et al., 2022; Saya- di et al., 2022; Mehravi et al., 2022a; Mohammadpour et al., 2022). Sample 2Cx DNA (pg) = (Sample G1 peak mean/Stand- ard G1 peak mean) × Standard 2C DNA (pg) Moreover, the size of the monoploid genome (2Cx DNA) in base pair terms is based on the converting for- mula proposed by Doležel et al. (2003), where 1 pg of DNA is equivalent to 978 Mbp. Statistical analyses The normality test was first applied to the residuals data of chromosome length (CL) and genome size data, the data were then analyzed according to a completely randomized design (CRD) with five and three replica- tions, respectively, using Minitab 17 software (Cardoso et al., 2023). Chromosome length data were not normal- ized; instead, they were transformed in the reverse way (Osborne, 2010), resulting in normalized data. Analysis of variance (ANOVA) and subsequent comparison of means, using the least significant difference (LSD) meth- od (Hinkelmann, 2012) were performed with the general linear model (GLM) procedure in SAS 9.1 software (SAS Institute Inc., 2009). Furthermore, multivariate statisti- cal analysis (MANOVA) of mean CL, genome size, and geographical parameters (Karimzadeh et al., 2011) was conducted in Minitab 17 software (Yeshitila et al., 2023). RESULTS Karyotype analysis The karyotypic study results indicated that all 10 populations of the caper (Capparis spinosa) medici- nal plant were diploid (2x) in terms of ploidy level. The results of ANOVA indicate a significant difference (P < 0.01) in chromosome length (CL) among the studied populations, reflecting intraspecific diversity (Table 2). Interestingly, within such a ploidy level, two chromosome numbers were identified. Hence, nine populations had 2n = 2x = 30 chromosomes, while one population (P9) had 2n = 2x = 34 chromosomes (Fig. 3, Table 3). This study is being reported for the first time in Iran. The mean chro- mosome length (CL) in the nine populations (P1-P8, P10) with 30 chromosomes was 1.05 μm, ranging from 0.97 μm (P9) to 1.12 μm (P2). The P9 population, which had 34 chromosomes, also measured 0.97 μm, while the mean CL for all 10 populations was 1.05 μm. Means with the same symbol letters are not signifi- cantly different at either (P < 0.01) for CL column or (P < 0.05) for 2Cx DNA column, using LSD Nuclear genome size estimation The analysis of variance of monoploid genome size (2Cx DNA) revealed no significant differences (P < 0.05) among the studied populations (Table 2). The flow cyto- metric nuclear monoploid DNA amount (2Cx DNA) of the studied populations is shown in Figure 4. The mean genome size in the nine populations (P1-P8, P10) with 30 chromosomes was 0.646 pg, ranging from 0.608 pg (P10) to 0.677 pg (P2; Table 3). It was 0.633 pg in the P9 population with 34 chromosomes. Overall, the mean 2Cx DNA for all 10 populations was 0.643 pg or 628.85 Mbp (Table 3). However, to explore potential differenc- es, mean comparisons were performed, using the LSD method at P < 0.05, indicating a significant difference between populations P2, P6, and P10 (Table 3). Addi- tionally, histogram analysis complemented the karyo- typic examination, confirming the diploid nature of the studied populations. Multivariate statistical analysis The correlation between mean monoploid genome size (2Cx DNA) and either chromosome length (CL), or geographical parameters (latitude, longitude, alti- tude, mean temperature, and mean rainfall) in the populations of the medicinal plant caper is presented in Table 4. The correlation coefficient between 2Cx Table 2. Analysis of variance for chromosome length and monop- loid genome size in populations of caper (Capparis spinosa). SOV df MS CL df MS 2Cx DNA Population 9 0.2819** 9 0.0015ns Error 750 0.562 20 0.0009 CV% – 23.4 – 4.71 ns, ** Non-significant at P < 0.05, significant difference at P < 0.01. 9Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant DNA and CL was positive and significant (P < 0.05; r = 0.66*). However, no significant differences were found for the geographical parameters. Given the sig- nificant correlation between monoploid genome size and CL, linear regression analysis (b = 0.25*) was con- ducted (Figure 5). Additionally, cluster analysis was per- formed to identify distinct groups of individuals based on their genetic similarity. This analysis was based on mean original data for 2Cx DNA, chromosome length (CL), and the geographical parameters. To determine the distance between populations, Euclidean distance was calculated, and cluster merging was performed, using the unweighted pair group method with arith- metic mean (UPGMA) method. Moreover, to evaluate the efficiency of the classification method, the cophe- netic coefficient was calculated, using NTSYS 2.02e software. Various classification methods were tested with this software. Ultimately, the method that deter- mined the Euclidean distance and merged the average cluster, which had a higher cophenetic coefficient value (r = 0.92), was selected to present the results (Table 5). It should be noted that the higher the cophenetic coef- ficient for a method, the better it is for cluster analysis (Batagelj, 1988; Gong et al., 1995). Subsequently, cluster Table 3. Means comparison (± SE) chromosome length (CL) and monoploid genome size (2Cx DNA; pg) of populations of the Iranian endemic caper (Capparis spinosa). Pop. Local collection locations 2n CL (μm ± Se) Monoploid 2Cx DNA (pg) Monoploid 2Cx DNA) (Mbp) P1 Dargaz 30 1.106 ± 0.033ab 0.659 ± 0.005abc 644.50 P2 Balanej 30 1.122 ± 0.029a 0.677 ± 0.002a 662.10 P3 Tehran 30 1.073 ± 0.027abc 0.639 ± 0.028abc 624.94 P4 Torbat-e-Jam 30 1.117 ± 0.032a 0.652 ± 0.018abc 637.66 P5 Ahvaz 30 0.988 ± 0.030c 0.660 ± 0.008abc 645.48 P6 Kharg 30 1.009 ± 0.030bc 0.620 ± 0.022bc 606.36 P7 Borazjan 30 1.067 ± 0.028abc 0.668 ± 0.015ab 653.30 P8 Firuzabad 30 1.037 ± 0.029abc 0.627 ± 0.009abc 613.20 P9 Fathabad-e Deh-e Arab 34 0.974 ± 0.025c 0.633 ± 0.029abc 619.08 P10 Dasht-e Lar 30 0.975 ± 0.030c 0.608 ± 0.015c 594.62 Means Total P1-P8, P10 P9 – 1.047 1.055 0.974 0.643 0.646 0.633 628.86 631.78 619.08 LSD – – LSD1% = 0.108 LSD5% = 0.052 – P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 Figure 3. Somatic chromosomes of 10 populations of caper (Capparis spinosa). Scale bar = 5 μm. 10 Parviz Radmanesh, Ghasem Karimzadeh P9 P4 P5 P6 P10 P1 P8 P2 P3 P7 N um be r o f n uc le i Relative nuclear DNA content (Arbitrary units) File: Capparis spinosa (P01) + Rs- R1 Selected Particles: 5000 Acq.-Time: 43 s 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 24 48 72 96 120 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 24 48 72 96 120 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 1512 1512 - 30.24 51.78 53.67 27.68 77.50 78.55 17.66 File: Capparis spinosa (P02) + Rs- R2 Selected Parti 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 13 26 39 52 65 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 13 26 39 52 65 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 1010 1010 - 20.20 78.42 80.61 22.73 84.39 85.50 17.38 File: Capparis spinosa (P03) + Rs- R1 Selected Particles: 5000 Acq.-Time: 105 s 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 10 20 30 40 50 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 10 20 30 40 50 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 892 892 - 17.84 60.24 63.21 30.48 78.35 79.50 18.57 File: Capparis spinosa (P04) + Rs- R1 Selected Particles: 5000 Acq.-Time: 48 s 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 9 18 27 36 45 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 9 18 27 36 45 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 704 704 - 14.08 66.78 69.33 28.12 80.95 81.77 14.63 File: Capparis spinosa (P05) + Rs- R2 Selected Particles: 5000 Acq.-Time: 68 s 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 15 30 45 60 75 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 15 30 45 60 75 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 941 941 - 18.82 61.16 63.44 27.96 80.06 81.02 16.44 File: Capparis spinosa (P06) + Rs- R3 Selected Particles: 5000 Acq.-Time: 44 s 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 23 46 69 92 115 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 23 46 69 92 115 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C- A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 1454 1454 - 29.08 75.12 79.00 33.08 84.88 87.74 28.46 File: Capparis spinosa (P07) + Rs- R1 Selected Parti 000 Acq. 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 19 38 57 76 95 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 19 38 57 76 95 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 1344 1344 - 26.88 54.49 56.51 27.70 75.24 76.15 16.96 File: Capparis spinosa (P08) + Rs- R2 Selected Particles: 5000 Acq.-Time: 93 s 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 13 26 39 52 65 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 13 26 39 52 65 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 761 761 - 15.22 60.74 63.32 29.52 88.51 90.44 21.99 File: Capparis spinosa (P08) + Rs- R2 Selected Particles: 5000 Acq.-Time: 93 s 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 13 26 39 52 65 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 13 26 39 52 65 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 761 761 - 15.22 60.74 63.32 29.52 88.51 90.44 21.99 File: Capparis spinosa (P10) + Rs- R2 Selected Particles: 5000 Acq.-Time: 50 s 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts 0 50 100 150 200 250 0 20 40 60 80 100 SSC-A co un ts 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 FSC-A co un ts Gate: R1 0 50 100 150 200 250 0 20 40 60 80 100 SSC-A co un ts Gate: R1 0 50 100 150 200 250 0 200 400 600 800 1000 PerCP-Cy5-5-A co un ts Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 FSC-A SS C -A 0 50 100 150 200 250 0 50 100 150 200 250 SSC-A Pe rC P- Cy 5- 5- A R1 Gate: R1 0 50 100 150 200 250 0 50 100 150 200 250 PerCP-Cy5-5-A Pe rC P- Cy 5- 5- W partec PAS Region Gate Ungated Count Count/ml %Gated GMn-x Mean-x CV-x% GMn-y Mean-y CV-y% R1 1029 1029 - 20.58 51.67 54.04 30.91 74.84 75.59 15.24 Figure 4. Flow cytometric histograms illustrating the genome size of the medicinal plant caper (Capparis spinosa). The left peaks represent the G1 phase of the caper plant, while the right peaks correspond to the G1 phase of the internal standard, radish (Raphanus sativus cv. Saxa; 2C DNA = 1.11 pg). 11Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant analysis was performed, using Minitab 17.0 software by standardizing the parameters. The results of the clus- ter analysis are presented in the form of a dendrogram (Figure 6). According to which, the populations of caper medicinal plant were divided into four groups. The first group included three populations of P1, P3, and P4, the second group included P2 population, the third group comprised two populations of P5 and P7, and the fourth group included four populations of P6, P8, P9, and P10 (Figure 7). Furthermore, to determine the total varia- tion in populations and the contribution of parameters to this variation, principal component analysis (PCA) was performed on the 2Cx DNA, CL, and geographic parameters. The analysis revealed that the first four principal components accounted for 93% of the cumula- tive variation. The first two coordinates were displayed in a 2-dimensional graphic based on the desired param- eters in four categories (Figure 6). The results showed that CL (0.53), 2Cx DNA (0.41), latitude (0.55), and mean annual temperature (-0.45) had a stronger correla- tion with the first coordinate, which accounted for 42% of the variation in the calculated data. In the second component, altitude (0.61), average annual precipitation (0.65), and average annual temperature (-0.31) played a vital role in explaining 20% of the total variation. In the third component, 2Cx DNA (0.38) and longitude (-0.91) had the highest contributions. In the fourth component, 2Cx DNA (-0.51), average annual rainfall (0.53), and average annual temperature (-0.40) played the most sig- nificant roles. Together, these two components account- ed for 23% of the total variance (Table 6). Table 4. Correlation coefficients between monoploid genome size (2Cx DNA; pg) wither either chromosome length (CL; µm) or geograph- ical parameters in populations of caper (Capparis spinosa) medicinal plant. Trait CL (μm) Latitude (N) Longitude (E) Altitude (m) Mean Temp. (˚C) Mean rainfall (mm) 2Cx DNA (pg) 0.66* 0.62 ns -0.13 ns -0.16ns -0.32 ns -0.23 ns ns, * Non-significant and significant at P < 0.05. Table 5. Cophenetic coefficient of different clustering methods for populations of the caper (Capparis spinosa) related to chromosome length parameter, genome size, and geographical parameters). Linkage Method Euclidean Distance Squared Euclidean Distance UPGMA Single Complete UPGMA Single Complete Cophenetic Coefficient 0.92 0.90 0.91 0.83 0.83 0.82 P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 Y = 0.38 + 0.25* (± 0.102) X 0,60 0,62 0,64 0,66 0,68 0,70 0,96 0,98 1,00 1,02 1,04 1,06 1,08 1,10 1,12 1,14 2C x D N A (p g) CL (µm) Figure 5. Linear relationship between monoploid genome size (2Cx DNA) and chromosome length (CL) in caper (Capparis spinosa) medicinal plant. Figure 6. Dendrogram related to chromosome length parameter, genome size, and geographical conditions of the medicinal plant caper (Capparis spinosa), using Euclidean distance and unweighted pair group method with arithmetic mean (UPGMA; r = 0.92). 12 Parviz Radmanesh, Ghasem Karimzadeh DISCUSSION The results of this study provide, for the first time, accurate snapshots of the chromosome number of endemic Iranian populations of the caper (Capparis spinosa) medicinal plant. Little information is avail- able about the chromosome number of this plant. In the studied populations, information on chromosome and monoploid genome size (2Cx DNA) was completely inadequate. As a result, this study provides basic cytoge- netic, genetic, and genomic information for these popu- lations, which is useful for constructing genetic and physical maps and for whole genome sequencing in the future. The findings of the present study showed a dip- loid (2x) ploidy level, as well as two different chromo- some numbers of 30 and 34. In previous studies, the chromosome numbers reported as 24 (Magulaev, 1979), 38 (Al-Turki et al., 2000), and 42 (Wang et al., 2022). Variation in somatic chromosome number has been reported in the root tips of many flowering plant species (angiosperms) (e.g. Kula, 1999; Winterfeld et al., 2015, 2020; Mehravi et al., 2022a). In the present report, the average chromosome length was determined to be 1.055 μm in populations (P1-P8, P10) with 30 chromosomes and 0.974 μm in a P9 population with 34 chromosomes. Flow cytometry has been successfully employed to estimate nuclear genomic DNA content (Doležel and Bartoš, 2005; Doležel et al., 2007; Bourge et al., 2018) and to accurately determine ploidy levels in a diverse array of plant species (Mahdavi and Karimzadeh, 2010; Tavan et al., 2015; Abedi et al., 2015; Tarkesh Esfahani et al., 2016, 2020; Javadian et al., 2017; Hamidi et al., 2018; Mehravi et al., 2022a, b; Firoozi et al., 2022; Moham- madpour et al., 2022; Zarabizadeh et al., 2022; Rasekh and Karimzadeh, 2023; Khakshour et al., 2024; Morovati et al., 2024; Yari et al., 2024). In the current report, the genome size of caper (Capparis spinosa) populations with 30 chromosomes (P1-P8, P10) was determined to be 0.646 pg (631.78 Mbp) and that of P9 popula- tion with 34 chromosomes was 0.633 pg (619.08 Mbp). Following a previous study on Thymus species (Lami- aceae) reported by Mahdavi and Karimzadeh (2010), in the present study, we calculated the average genome size per chromosome (pg/chr) by dividing the genome size by the chromosome number. Therefore, the average genome size per chromosome (pg/chr) for populations P1-P8 and P10 (30 chromosomes) and P9 (34 chromo- somes) was 0.021 pg/chr and 0.019 pg/chr, respectively, or 20.54 and 18.58 Mbp/chr, respectively. Hence, such a slight smaller genome size of a 34-chr P9 population can be verified by its slight smaller chromosomes (0.974 μm; Table 3). In other words, such a reduction in DNA content in the 34-chr P9 population is fully consistent with the reduction in chromosome length compared to the 30-chr populations (P1-P8, P10). Our results can be compared to a study on caper (Capparis spinosa var. her- bacea) in China, which reported a chromosome number of 42 (2n = 2x), a genome size of 549.06 Mbp, and an average of 13.07 Mbp/chr (Wang et al., 2022). Thus, the genome size of the caper population studied in China, with 42 chromosomes, was approximately 57% and 42% smaller than that of 30- and 34-chr caper populations studied in the current report, respectively. Consequently, it can be concluded that the chromosomes of the Iranian endemic caper populations exhibit approximately twice Figure 7. Population classification based on the first and second components in principal component analysis on the chromosome length parameter, genome size, and geographical conditions of pop- ulations of the medicinal plant caper (Capparis spinosa). Table 6. Eigenvalues, relative and cumulative variances, and eigen- vectors for the four principal components resulting from principal component analysis on the chromosome length, genome size, and geographical conditions of populations of caper (Capparis spinosa) medicinal plant. Characteristics Components First Second Third Fourth Eigenvalue 2.93 1.94 1.10 0.49 Relative variance 0.42 0.28 0.16 0.07 Cumulative variance 0.42 0.70 0.86 0.93 CL (μm) 0.53 -0.08 -0.11 -0.33 2Cx DNA (pg) 0.41 -0.28 0.38 -0.51 Latitude (N) 0.55 -0.11 -0.05 0.36 Longitude (E) 0.09 -0.10 -0.91 -0.21 Altitude (m) 0.18 0.61 -0.09 0.11 Mean temp. (°C) -0.45 -0.31 -0.06 -0.40 Mean rainfall (mm) -0.03 0.65 0.06 -0.53 13Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant the genome size compared to the caper plant reported in China. This suggests that the average chromosome length of the endemic Iranian caper plant is likely to be longer than that of the Chinese plants. Cytogenetic studies can be used to better under- stand the relationships between different species and populations of a species, and to guide the evolutionary trends of plants (Stebbins, 1971). The first step towards understanding the genetic characteristics of a plant is to determine the status of its chromosomes. Chromo- somal information allows for the comparison of spe- cies and their populations (Singh 2016). Populations of each species exhibit their own genomic adaptations to the environment in which they grow. As adaptive differ- ences increase, new varieties and even new species may emerge in plant habitats (Weigel and Nordborg, 2015). Therefore, chromosomes are suitable factors on which to determine the evolutionary process of plants (Lev- in, 2002). Chromosomal differences are different from morphological, physiological, and ecological differences (Caceres et al., 1998). Because these differences reflect differences in the products of gene action that change due to environmental factors, while chromosomal dif- ferences are more or less due to the genetic content of individuals (Beckmann et al., 2007). Differences in chro- mosome size can indicate differences in the gene prod- ucts or proteins that an individual produces, or they can indicate duplication of genes that can affect the rate of synthesis of various proteins (Kondrashov et al., 2002). Differences in karyotype morphology indicate differ- ences in gene arrangement, which can significantly affect how genes segregate and recombine during Mendelian inheritance. Finally, differences in chromosome num- ber can indicate differences in gene arrangement, gene duplication, or both (Stebbins 1950, 1971; Goldblatt et al., 1979; Levin, 2002; Patwardhan et al., 2022). The present study revealed significant variation in chromo- some length (CL), providing evidence for intraspecific chromosomal diversity (Table 2). Chromosomal number variation among populations indicates that chromosom- al structural changes may provide a valuable tool for dif- ferentiating closely related populations that exhibit mini- mal morphological divergence (Mayrose et al., 2021). Chromosomal differences, such as variations in chromo- some number and length, can be utilized in breeding programs to generate hybrid populations. Parental com- binations exhibiting differences in chromosome number/ length, particularly those affecting chromosome pair- ing, can facilitate successful hybridization (Hamidi et al., 2018; Akbarzadeh et al., 2021). On the other hand, in the present report, the P2 population exhibited the highest average genome size (0.677 pg) and the longest average chromosome length (1.122 μm) among the stud- ied Iranian caper populations. It is noteworthy that this population was placed in a separate group in the prin- cipal component analysis and cluster analysis compared to the other populations, as illustrated in Figs. 1 and 2. An increase in nuclear DNA content is typically associ- ated with an increase in total chromosome volume and subsequently cell size, which can lead to larger seed size (Karimzadeh et al., 2011). Considering that the fruits of this medicinal caper plant are edible and its seeds con- tain valuable oil for medicinal and industrial uses (Mat- thäus and Özcan, 2005; Ara et al., 2013). Thus, the P2 population can potentially be a valuable resource for polyploidy induction or hybridization programs aimed at producing larger seeds with enhanced oil content. Furthermore, genome size can serve as an effective marker for identifying hybrids (Ellul et al., 2002). In the present report, the positive and significant correlation between chromosome length (CL) and 2Cx DNA content suggests a strong association between changes in nuclear DNA content and structural altera- tions in chromosomes. This finding is consistent with previous reports of such correlations in Vicia (Naran- jo et al., 1998), Tulipa (Abedi et al., 2015), Hypericum (Mehravi et al., 2022a), and Pimpinella (Mehravi et al., 2022b). Cluster analysis based on cytological data and geographical conditions revealed four distinct clusters of populations. These results suggest that populations within a cluster exhibit the lowest metric distances and the highest degree of homology in terms of chromo- some length, genome size, and geographical parameters. This information can be valuable for selecting paren- tal lines in breeding programs aimed at maximizing genetic diversity. To assess the overall variation within the population and the relative contribution of different karyotypic parameters, principal component analysis (PCA) was also performed. The first two principal com- ponents explained 70% of the cumulative variation, and were subsequently visualized in a two-dimensional plot (Fig. 6). Furthermore, PCA analysis applied to different caper populations demonstrated the strong discrimina- tory power of karyological parameters, genome size, and geographical conditions in distinguishing between these populations. As previously reported, PCA is a valuable tool for establishing karyological relationships (Peruzzi and Altinordu, 2014). While karyological data provide valuable insights into evolutionary relationships, they are not sufficient on their own to establish robust phyloge- netic relationships between species. It is crucial to inte- grate karyological data with independent sources of sys- tematic information, such as morphological, molecular, and ecological data (Siljak-Yakovlev and Peruzzi, 2012; 14 Parviz Radmanesh, Ghasem Karimzadeh Peruzzi and Eroǧlu, 2013; Harpke et al., 2015). Conse- quently, geographical data were incorporated into the cluster analysis and PCA to enhance the phylogenetic inference. CONCLUSION This study examined the genetic diversity of the medicinal plant Capparis spinosa across ten distinct pop- ulations in Iran, utilizing chromosome analysis, ploidy level assessment, and genome size determination via flow cytometry. The findings revealed that all popula- tions were diploid, with two distinct chromosome counts observed: 2n = 30 and 2n = 34. This represents the first documented instances of these chromosome numbers in C. spinosa. Genome size assessment indicated that while there were no significant differences in genome size among the populations, notable variations in chro- mosome length were detected. Clustering and principal component analysis demonstrated significant genetic diversity across the populations, categorizing them into four separate groups. These results contribute essential baseline data regarding the karyotype and genome size of C. spinosa in Iran. Such information may be instru- mental for future endeavors in genetic mapping, genome sequencing, and breeding programs for this valuable medicinal species. The observed genetic diversity among populations underscores the potential for developing new cultivars with desirable traits. ACKNOWLEDGMENT Authors gratefully acknowledge the academic finan- cial support provided by the Tarbiat Modares University, Tehran, Iran AUTHOR CONTRIBTIONS PR, and GK conceived and designed this study. PR conducted the experiments. PR and GK analyzed the data. PR wrote the manuscript. GK revised the manu- script. DATA AVILABITY STATEMENT The original contributions presented in the study are included in the article/supplementary material, fur- ther inquiries can be directed to the corresponding author/s FUNDING This research was supported by the University of Tarbiat Modares University, Iran. REFERENCES Abbasi-Karin Sh, Karimzadeh G, and Mohammadi- Bazargani M. 2022. Interspecific chromosomal and genome size variations in in vitro propagated wil- low herb (Epilobium spp.) medicinal plant. Cytolo- gia 87(2): 129-135. https://doi.org/10.1508/cytolo- gia.87.129. Abedi R, Babaei A, and Karimzadeh G. 2015. Karyologi- cal and flow cytometric studies of Tulipa (Liliaceae) species from Iran. Plant Syst. Evol. 301: 1473-1484. https://doi.org/10.1007/s00606-014-1164-z. Agah F. Esmaeili M. A. Farzam M. and Abbasi R. 2020. Effect of dormancy breaking treatments and seed bed medium on seed germination and morphol- ogy of Capparis spinosa L. Seedlings. Iran. J. Seed Sci. Technol. 9(3): 45-57. https://doi.org/10.22034/ ijsst.2019.125542.1262. Aguilar-Rito M. G. Arzate-Fernández A. M. García- Núñez, H. G. and Norman-Mondragón T. H. 2023. Establishment of an efficient protocol for in vitro dis- infection of seeds of seven Agave spp. species. Rev. Mex. Fitopatol. Mex. J. Phytopathol. 42. https://doi. org/10.18781/r.mex.fit.2310-1. Ahmadi-Roshan M, Karimzadeh G, Babaei A, and Jafari H. 2016. Karyological studies of Fritillaria (liliaceae) species from Iran. Cytologia (Tokyo). 81: 133-141. https://doi.org/10.1508/cytologia.81.133. Akbarzadeh M,Van Laere K, Leus L, De Riek J, Van Huylenbroeck J, Werbrouck SP, and Dhooghe E. 2021. Can knowledge of genetic distances, genome sizes and chromosome numbers support breeding programs in hardy geraniums? Genes (Basel). 12. htt- ps://doi.org/10.3390/genes12050730. Ali MES, and Amar MH. 2020. A systematic revision of Capparaceae and Cleomaceae in Egypt: an evalua- tion of the generic delimitations of Capparis and Cle- ome using ecological and genetic diversity. J. Genet. Eng. Biotechnol. 18: 58. https://doi.org/10.1186/ s43141-020-00069-z. Al-Turki TA, Filfilan SA, and Mehmood SF. 2000. A cyto- logical study of flowering plants from Saudi Arabia. Willdenowia 30: 339-358. https://doi.org/10.3372/ wi.30.30211. Anjum N, Dash CK, and Sultana SS. 2023. Karyological diversity among six medicinally important species https://doi.org/10.1508/cytologia.87.129 https://doi.org/10.1508/cytologia.87.129 https://doi.org/10.1007/s00606-014-1164-z https://doi.org/10.22034/ijsst.2019.125542.1262 https://doi.org/10.22034/ijsst.2019.125542.1262 https://doi.org/10.18781/r.mex.fit.2310-1 https://doi.org/10.18781/r.mex.fit.2310-1 https://doi.org/10.1508/cytologia.81.133 https://doi.org/10.3390/genes12050730 https://doi.org/10.3390/genes12050730 https://doi.org/10.1186/s43141-020-00069-z https://doi.org/10.1186/s43141-020-00069-z https://doi.org/10.3372/wi.30.30211 https://doi.org/10.3372/wi.30.30211 15Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant of Acanthaceae with three new chromosome counts. Nucl., 1-9. https://doi.org/10.1007/s13237-023- 00443-5. Annaz H, Sane, Y, Bitchagno GTM, Ben Bakrim W, Dris- si B, Mahdi I, El Bouhssini M, and Sobeh M. 2022. Caper (Capparis spinosa L.): An updated review on its phytochemistry, nutritional value, traditional uses, and therapeutic potential. Front. Pharmacol. 13: 1-22. https://doi.org/10.3389/fphar.2022.878749. Ara KM, Karami M, and Raofie F. 2014. Application of response surface methodology for the optimization of supercritical carbon dioxide extraction and ultra- sound-assisted extraction of Capparis spinosa. Else- vier. https://doi.org/10.1016/j.supflu.2013.10.016. Argentieri M, Macchia F, Papadia P, Fanizzi F P, and Ava- to P 2012. Bioactive compounds from Capparis spi- nosa subsp. rupestris. Ind. Crops Prod. 36(1): 65-69. doi.org/10.1016/j.indcrop.2011.08.007. Aydın ZU, Eroğlu HE, Şenova MK, Martin E, Tuna M, and Dönmez AA. 2024. Chromosome characteriza- tion and genome size in Nigella and Garidella species (Ranunculaceae) with their taxonomic implications. Cytologia 89: 117-125. https://doi.org/10.1508/cyto- logia.89.117. Bakr RO, and El Bishbishy MH. 2016. Profile of bioac- tive compounds of Capparis spinosa var. aegyptiaca growing in Egypt. Rev. Bras. Farmacogn. 26: 514- 520. https://doi.org/10.1016/J.BJP.2016.04.001. Barbera G, and Di Lorenzo R. 1984. The caper culture in Italy. Acta Horticulturae: 167-172. https://doi. org/10.17660/actahortic.1984.144.21. Batagelj V. 1988. Generalized Ward and related cluster- ing problems. Classification and Related Methods of Data Analysis, 30: 67-74. Beckmann J, Estivill X, and Antonarakis S. 2007. Copy number variants and genetic traits: closer to the resolution of phenotypic to genotypic variability. Nat. Rev. Genet. 8: 639-646. https://doi.org/10.1038/ nrg2149. Bourge, M., Brown, S. C., and Siljak-Yakovlev, S. (2018). Flow cytometry as tool in plant sciences, with empha- sis on genome size and ploidy level assessment. Gen- et. Appl. 2, 1-12. https://hal.science/hal-03937019v1. Caceres M, De Pace C, Mugnozza GS, Kotsonis P, Cec- carelli M, and Cionini PG. 1998. Genome size vari- ations within Dasypyrum villosum: correlations with chromosomal traits, environmental factors and plant phenotypic characteristics and behaviour in repro- duction. Theor. Appl. Genet. 96: 559-567. https://doi. org/10.1007/s001220050774. Cardoso FC, Berri RA, Lucca G, Borges EN, and Mat- tos VLD. 2023. Normality tests: a study of residuals obtained on time series tendency modeling. Exacta. https://doi.org/10.5585/2023.22928. Carr GD. 1978. Chromosome numbers of Hawaiian flowering plants and the significance of cytology in selected taxa. Am. J. Bot. 65: 236-242. https://doi. org/10.1002/j.1537-2197.1978.tb06061.x. Carra A, Sajeva M, Abbate L, Siragusa M, Sottile F, and Carimi F. 2012. In vitro plant regeneration of caper (Capparis spinosa L.) from floral explants and genetic stability of regenerants. Plant Cell Tiss. Org. Cult. 109: 373-381. https://doi.org/10.1007/s11240-011- 0102-9. Carta A, Bedini G, and Peruzzi L. 2018. Unscrambling phylogenetic effects and ecological determinants of chromosome number in major angiosperm clades. Sci. Rep. 8: 14258. https://doi.org/10.1038/s41598- 018-32515-x. Cedillo-Cortezano M, Martinez-Cuevas LR, López JAM, Barrera López IL, Escutia-Perez S, and Petricevich VL. 2024. Use of medicinal plants in the process of wound healing: a literature review. Pharmaceuticals, 17(3): 303. https://doi.org/10.3390/ph17030303. Chedraoui S, Abi-Rizk A, El-Beyrouthy M, Chalak L, Ouaini N, and Rajjou L. 2017. Capparis spinosa L. in A systematic review: A xerophilous species of multi values and promising potentialities for agrosystems under the threat of global warming. Front. Plant Sci. 8. https://doi.org/10.3389/fpls.2017.01845. Cincotta F, Merlino M, Verzera A, Gugliandolo E, and Condurso C. 2022. Innovative process for dried caper (Capparis spinosa L.) powder production. Foods 11. https://doi.org/10.3390/foods11233765. Condurso C, Mazzaglia A, Tripodi G, Cincotta F, Dima G, Maria Lanza C, and Verzera A. 2016. Sensory analysis and head-space aroma volatiles for the char- acterization of capers from different geographic ori- gin. J. Essent. Oil Res., 28(3): 185-192. https://doi. org/10.1080/10412905.2015.1113205. Doležel J, and Bartoš J. 2005. Plant DNA flow cytometry and estimation of nuclear genome size. Ann. Bot. 95: 99-110. https://doi.org/10.1093/aob/mci005. Doležel J, Bartos ., Voglmayr H, and Greilhuber J. 2003. Nuclear DNA content and genome size of trout and human. Cytometry. A 51: 127-128; author reply 129. https://doi.org/10.1002/cyto.a.10013. Doležel J, Greilhuber J, and Suda J. 2007. Estimation of nuclear DNA content in plants using flow cytometry. Nat. Protoc. 2: 2233-2244. https://doi.org/10.1038/ nprot.2007.310. Doležel J, Sgorbati S, and Lucretti S. 1992. Compari- son of three DNA fluorochromes for flow cyto- metric estimation of nuclear DNA content in https://doi.org/10.1007/s13237-023-00443-5 https://doi.org/10.1007/s13237-023-00443-5 https://doi.org/10.3389/fphar.2022.878749 https://doi.org/10.1016/j.supflu.2013.10.016 http://doi.org/10.1016/j.indcrop.2011.08.007 https://doi.org/10.1508/cytologia.89.117 https://doi.org/10.1508/cytologia.89.117 https://doi.org/10.1016/J.BJP.2016.04.001 https://doi.org/10.17660/actahortic.1984.144.21 https://doi.org/10.17660/actahortic.1984.144.21 https://doi.org/10.1038/nrg2149 https://doi.org/10.1038/nrg2149 https://hal.science/hal-03937019v1 https://doi.org/10.1007/s001220050774 https://doi.org/10.1007/s001220050774 https://doi.org/10.5585/2023.22928 https://doi.org/10.1002/j.1537-2197.1978.tb06061.x https://doi.org/10.1002/j.1537-2197.1978.tb06061.x https://doi.org/10.1007/s11240-011-0102-9 https://doi.org/10.1007/s11240-011-0102-9 https://doi.org/10.1038/s41598-018-32515-x https://doi.org/10.1038/s41598-018-32515-x https://doi.org/10.3390/ph17030303 https://doi.org/10.3389/fpls.2017.01845 https://doi.org/10.3390/foods11233765 https://doi.org/10.1080/10412905.2015.1113205 https://doi.org/10.1080/10412905.2015.1113205 https://doi.org/10.1093/aob/mci005 https://doi.org/10.1002/cyto.a.10013 https://doi.org/10.1038/nprot.2007.310 https://doi.org/10.1038/nprot.2007.310 16 Parviz Radmanesh, Ghasem Karimzadeh plants. Physiol. Plant. 85: 625-631. https://doi. org/10.1111/j.1399-3054.1992.tb04764.x. Ellul P, Boscaiu M, Vicente O, Moreno V, and Rosselló JA. 2002. Intra- and inter-specific variation in DNA content in Cistus (Cistaceae). Ann. Bot. 90: 345-351. https://doi.org/10.1093/aob/mcf194. Firoozi N, Karimzadeh G, Sabet MS, and Sayadi V. 2022. Intraspecific karyomorphological and genome size vari- ations of in vitro embryo derived Iranian endemic Asa- foetida (Ferula assa-foetida L., Apiaceae). Caryologia 75: 111-121. https://doi.org/10.36253/caryologia-1721. Gao Y, Zhao G, Xu Y, Hao Y, Zhao T, Jia L, and Chen Z. 2024. Karyotype analysis and genome size estimation of Sapindus mukorossi Gaertn. an economical impor- tant tree species in China. Bot. Lett. 171(12): 116- 124. https://doi.org/10.1080/23818107.2023.2244179. Garbari F, Bedini G, and Peruzzi L. 2012. Chromosome numbers of the Italian flora. From the Caryologia foundation to present. Caryologia 65: 62-71. https:// doi.org/10.1080/00087114.2012.678090. Goldblatt P. and Johnson ED. 1979. Index to plant chro- mosome numbers. Missouri Botanical Garden. Inc. Ann Arbour, Michigan. Available at: http://www. tropicos.org/Project/IPCN. Gregory TR. 2005. Genome size evolution in animals. In the evolution of the genome. Academic Press. Pp. 3-87. https://doi.org/10.1016/B978-012301463-4/50003-6. Greilhuber J, Doležel J, Lysák MA, Bennett MD. 2005. The origin, evolution and proposed stabilization of the terms ‘genome size’ and ‘C-value’ to describe nuclear DNA contents. Annals of Botany, 95(1): 255- 260. https://doi.org/10.1093/aob/mci019. Guerra M. 2012. Cytotaxonomy: The end of childhood. Plant Biosyst. 146: 703-710. https://doi.org/10.1080/1 1263504.2012.717973. Gupta RC, and Gill BS. 1981. In chromosome number reports LXXI. Taxon 30: 514. http://www.jstor.org/ stable/1220167. Hamidi F, Karimzadeh G, Rashidi Monfared S, and Sale- hi M. 2018. Assessment of Iranian endemic Artemi- sia khorassanica: Karyological, genome size, and gene expressions involved in artemisinin production. Turk. J. Biol. 42: 322-333. https://doi.org/10.3906/ biy-1802-86. Harpke D, Carta A, Tomović G, Randelović V, Randelović N, Blattner FR, and Peruzzi L. 2015. Phy- logeny, karyotype evolution and taxonomy of Crocus series Verni (Iridaceae). Plant Syst. Evol. 301: 309- 325. https://doi.org/10.1007/s00606-014-1074-0. Hinkelmann K . 2012. Design and Analysis of Experiments. John Wiley & Sons. https://doi. org/10.1002/9781118147634 Honarmand SJ, Nosratti I, Nazari K, and Heidari H. 2016. Factors affecting the seed germination and seedling emergence of muskweed (Myagrum perfoliatum). Weed Biol. Manag. 16: 186-193. https://doi.org/10.1111/ wbm.12110. Jang TS. and Weiss-Schneeweiss H. 2018. Chromosome numbers and polyploidy events in Korean non-com- melinids monocots: A contribution to plant system- atics. Korean J. Plant Taxon. 48: 260-277. https://doi. org/10.11110/kjpt.2018.48.4.260. Javadian N, Karimzadeh G, Sharifi M, Moieni A, and Behmanesh M. 2017. In vitro polyploidy induction: changes in morphology, podophyllotoxin biosyn- thesis, and expression of the related genes in Linum album (Linaceae). Planta 245: 1165-1178. https://doi. org/10.1007/s00425-017-2671-2. Kamel W, Abd El-Ghani MM, and El-Bous M. 2009. Tax- onomic study of Capparaceae from Egypt: revisited. African J. Pl. Sci. Biotech, 3: 27-35. Karimzadeh G, Danesh-Gilevaei M., and Aghaalikhani M. 2011. Karyotypic and nuclear DNA variations in Lathyrus sativus (Fabaceae). Caryologia 64: 42-54. https://doi.org/10.1080/00087114.2011.10589763. Khakshour A, Karimzadeh G, Sabet MS, and Sayadi V. 2024. Karyomorphological and genome size variation in Iranian endemic populations of coriander (Cori- andrum sativum L.). Cytologia 89: 21-27. https://doi. org/10.1508/cytologia.89.21. Khatoon S, and Ali SI. 1993. Chromosome atlas of the angiosperms of Pakistan. Karachi Univ. Karachi vii, 232 p., ISBN 1104765435. Kocjan D, Dolenc Koce J, Etl F, and Dermastia M. 2022. Genome size of life forms of Araceae-A new piece in the C-value puzzle. Plants (Basel, Switzerland) 11. https://doi.org/10.3390/plants11030334/ Kondrashov FA, Rogozin IB, Wolf YI, and Koonin EV. 2002. Selection in the evolution of gene duplications. Genome Biol. 3: 1-9. https://doi.org/10.1186/gb-2002- 3-2-research0008. Kula A. 1999. Cytogenetic studies in the cultivated form of Bromus carinatus (Poaceae). W. Szafer Institute of Botany, Polish Academy of Sciences. 101-106. Levin DA. 2002. The role of chromosomal change in plant evolution. Oxford University Press, USA. Loureiro J, Rodriguez E, Doležel J, and Santos C. 2007. Two new nuclear isolation buffers for plant DNA flow cytometry: A test with 37 species. Ann. Bot. 100: 875-888. https://doi.org/10.1093/aob/ mcm152. Magulaev AJ. 1979. The chromosome numbers of flow- ering plants in the northern Caucasus. part 3. Flora north Caucasus Quest. Its Hist. 3: 101-106. https://doi.org/10.1111/j.1399-3054.1992.tb04764.x https://doi.org/10.1111/j.1399-3054.1992.tb04764.x https://doi.org/10.1093/aob/mcf194 https://doi.org/10.36253/caryologia-1721 https://doi.org/10.1080/23818107.2023.2244179 https://doi.org/10.1080/00087114.2012.678090 https://doi.org/10.1080/00087114.2012.678090 http://www.tropicos.org/Project/IPCN http://www.tropicos.org/Project/IPCN https://doi.org/10.1016/B978-012301463-4/50003-6 https://doi.org/10.1093/aob/mci019 https://doi.org/10.1080/11263504.2012.717973 https://doi.org/10.1080/11263504.2012.717973 http://www.jstor.org/stable/1220167 http://www.jstor.org/stable/1220167 https://doi.org/10.3906/biy-1802-86 https://doi.org/10.3906/biy-1802-86 https://doi.org/10.1007/s00606-014-1074-0 https://doi.org/10.1002/9781118147634 https://doi.org/10.1002/9781118147634 https://doi.org/10.1111/wbm.12110 https://doi.org/10.1111/wbm.12110 https://doi.org/10.11110/kjpt.2018.48.4.260 https://doi.org/10.11110/kjpt.2018.48.4.260 https://doi.org/10.1007/s00425-017-2671-2 https://doi.org/10.1007/s00425-017-2671-2 https://doi.org/10.1080/00087114.2011.10589763 https://doi.org/10.1508/cytologia.89.21 https://doi.org/10.1508/cytologia.89.21 https://doi.org/10.3390/plants11030334/ https://doi.org/10.1186/gb-2002-3-2-research0008 https://doi.org/10.1186/gb-2002-3-2-research0008 https://doi.org/10.1093/aob/mcm152 https://doi.org/10.1093/aob/mcm152 17Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant Mahdavi S, and Karimzadeh G. 2010. Karyological and nuclear dna content variation in some Iranian endemic Thymus species (Lamiaceae). J. Agric. Sci. Technol. 12: 447-458. Mahmoudi S, and Mirzaghaderi G. 2023. Tools for Drawing Informative Idiograms Methods in Molec- ular Biology, (Springer). 515-527. https://doi. org/10.1007/978-1-0716-3226-0_31. Marir EMA. 2024. Propagation of medicinal capers (Cap- paris spinosa L.) and production of some medicinal secondary metabolic compounds using plant tissue culture technology. Euphrates J. Agric. Sci. 16. Matthäus B, and Özcan M. 2005. Glucosinolates and fatty acid, sterol, and tocopherol composition of seed oils from Capparis spinosa var. spinosa and Capparis ovata Desf. var. canescens (Coss.) Heywood. J. Agric. Food Chem. 53: 7136-7141. https://doi.org/10.1021/ jf051019u. Mayrose I, and Lysak MA. 2021. The evolution of chro- mosome numbers: mechanistic models and experi- mental approaches. Genome Biol. Evol. 13. https:// doi.org/10.1093/gbe/evaa220. Mehravi S, Karimzadeh G, Kordenaeej A, and Hanifei M. 2022a. Mixed-ploidy and dysploidy in Hypericum perforatum: A karyomorphological and genome size study. Plants 11(22): 3068. https://doi.org/10.3390/ plants11223068. Mehravi S, Ranjbar GA, Najafi-Zarrini H, Mirzaghaderi G, Hanifei M, Severn-Ellis AA, Edwards D, and Bat- ley J. 2022b. Karyology and genome size analyses of Iranian endemic Pimpinella (Apiaceae) species. Front. Plant Sci. 13: 1-14. https://doi.org/10.3389/ fpls.2022.898881. Merlino M, Condurso C, Cincotta F, Nalbone L, Ziino G, and Verzera A. 2024. Essential oil emulsion from caper (Capparis spinosa L.) leaves: exploration of its antibacterial and antioxidant properties for possi- ble application as a natural food preservative. Anti- oxidants 13(6) : 718. https://doi.org/10.3390/anti- ox13060718. Mesquita AT, Braz GT, Shimizu GH, Machado RM, Romero-da Cruz MV, and Forni-Martins ER. 2024. Karyotype diversity and genome size in the Cypho- mandra clade of Solanum L. (Solanaceae). Bot. J. Linn. Soc. https://doi.org/10.1093/botlinnean/ boae047. Moghaddasi MS. 2011. Caper (Capparis spp.) importance and medicinal usage. Adv. Environ. Biol. 5(5): 872- 879. Mohammadpour S, Karimzadeh G, and Ghaffari SM. 2022. Karyomorphology, genome size, and variation of antioxidant in twelve berry species from Iran. Car- yologia 75: 133-148. https://doi.org/10.36253/CARY- OLOGIA-1633. Morales Valverde R. 1986. Taxonomia De Los Gen- eros Thymus (Excluida De La Seccion Serpyllum) Y Thymbra En La Peninsula Iberica). CSIC – Real Jar- din Botanico (RJB), Ruizia. Monografias del Jardin Botanico 3: 324 p. http://hdl.handle.net/10261/66682. Morovati Z, Karimzadeh G, Naghavi MR, and Rashidi Monfared S. 2024. Chromosome, ploidy analysis, and flow cytometric genome size estimation of Datura stramonium and D. innoxia medicinal plant. Caryo- logia, 77(3): 53-61. https://doi.org/10.36253/caryolo- gia-2768. Nabavi SF, Maggi F, Daglia M, Habtemariam S, Rastrelli L, and Nabavi SM. 2016. Pharmacological effects of Capparis spinosa L. Phyther. Res. 30(11): 1733-1744. https://doi.org/10.1002/ptr.5684. Naranjo CA, Ferrari MR, Palermo AM, and Poggio L. 1998. Karyotype, DNA content and meiotic behav- iour in five South American species of Vicia (Fabace- ae). Ann. Bot. 82: 757-764. https://doi.org/10.1006/ anbo.1998.0744. Ning H, Ao S, Fan Y, Fu J, and Xu C. 2018. Correlation analysis between the karyotypes and phenotypic traits of Chinese Cymbidium cultivars. Hortic. Envi- ron. Biotechnol. 59: 93-103. https://doi.org/10.1007/ s13580-018-0010-6. Olmez Z, Gokturk A, and Gulcu S. 2006. Effects of cold stratification on germination rate and percentage of caper (Capparis ovata Desf.) seeds. J. Environ. Biol. 27(4): 667-670. Osborne JW. 2010. Improving your data transformations: Applying the Box-Cox transformation. Pract. Assess- ment, Res. Eval. 15. https://doi.org/10.7275/qbpc- gk17. Patwardhan D, Varshini SA, and Galoth L. 2022. Study of Chromosome. In Genetics Fundamentals Notes. Singapore: Springer Nature Singapore. pp 239-298. https://doi.org/10.1007/978-981-16-7041-1_5. Pellicer J, Hidalgo O, Dodsworth S, and Leitch IJ. 2018. Genome size diversity and its impact on the evolu- tion of land plants. Genes (Basel). 9(2): 88. https:// doi.org/10.3390/genes9020088. Peruzzi L and Altinordu,F. 2014. A proposal for a mul- tivariate quantitative approach to infer karyologi- cal relationships among taxa. Comp. Cytogenet. 8: 337-349. https://doi.org/10.3897/CompCytogen. v8i4.8564. Peruzzi L and Eroǧlu HE. 2013. Karyotype asymmetry: Again, how to measure and what to measure? Comp. Cytogenet. 7: 1-9. https://doi.org/10.3897/CompCy- togen.v7i1.4431. https://doi.org/10.1007/978-1-0716-3226-0_31 https://doi.org/10.1007/978-1-0716-3226-0_31 https://doi.org/10.1021/jf051019u https://doi.org/10.1021/jf051019u https://doi.org/10.1093/gbe/evaa220 https://doi.org/10.1093/gbe/evaa220 https://doi.org/10.3390/plants11223068 https://doi.org/10.3390/plants11223068 https://doi.org/10.3389/fpls.2022.898881 https://doi.org/10.3389/fpls.2022.898881 https://doi.org/10.3390/antiox13060718 https://doi.org/10.3390/antiox13060718 https://doi.org/10.1093/botlinnean/boae047 https://doi.org/10.1093/botlinnean/boae047 https://doi.org/10.36253/CARYOLOGIA-1633 https://doi.org/10.36253/CARYOLOGIA-1633 http://hdl.handle.net/10261/66682 https://doi.org/10.36253/caryologia-2768 https://doi.org/10.36253/caryologia-2768 https://doi.org/10.1002/ptr.5684 https://doi.org/10.1006/anbo.1998.0744 https://doi.org/10.1006/anbo.1998.0744 https://doi.org/10.1007/s13580-018-0010-6 https://doi.org/10.1007/s13580-018-0010-6 https://doi.org/10.7275/qbpc-gk17 https://doi.org/10.7275/qbpc-gk17 https://doi.org/10.1007/978-981-16-7041-1_5 https://doi.org/10.3390/genes9020088 https://doi.org/10.3390/genes9020088 https://doi.org/10.3897/CompCytogen.v8i4.8564 https://doi.org/10.3897/CompCytogen.v8i4.8564 https://doi.org/10.3897/CompCytogen.v7i1.4431 https://doi.org/10.3897/CompCytogen.v7i1.4431 18 Parviz Radmanesh, Ghasem Karimzadeh Peruzzi L, Carta A, and Altinordu F. 2017. Chromosome diversity and evolution in Allium (Allioideae, Ama- ryllidaceae). Plant Biosyst. 151: 212-220. https://doi. org/10.1080/11263504.2016.1149123. Peruzzi L, Góralski G, Joachimiak AJ, and Bedini G. 2012. Does actually mean chromosome number increase with latitude in vascular plants? An answer from the comparison of Italian, Slovak and Pol- ish floras. Comp. Cytogenet. 6: 371. https://doi. org/10.3897/CompCytogen.v6i4.3955. Qi J, Liang W, Yunlin Z, Guiyan Y, Tianci T, Yingzi M, Zhenggang X. 2023. Methods for rapid seed germina- tion of Broussonetia papyrifera. Pak. J. Bot. 55: 941- 948. https://doi.org/10.30848/PJB2023-3(2). Radmanesh P, Karimzadeh G, Kashkoli AB, and Hei- darzadeh A. 2023. Study on phytochemical traits and improving seed germination methods of Ira- nian endemic populations of caper (Capparis spi- nosa L.) medicinal plant. Iran. J. Seed Sci. Res. 10: 41-52. (In Persian with English Abstract). https://doi. org/10.22124/jms.2023.23352.1729. Rasekh SZ and Karimzadeh G. 2023. Chromosomal and genome size variations in opium poppy (Papaver somniferum L.) from Afghanistan. Caryologia, 76(4): 15-22. https://doi.org/10.36253/caryologia-1955. Rock BN. 2016. The woods and flora of the Florida Keys : “Pinnatae” /. woods flora Florida Keys “Pinna- tae” https://doi.org/10.5962/bhl.title.123255. Runemark H. 1996. Mediterranean chromosome number reports 6 (590-678). Flora Mediterr. 6, 223-243. Sakcali MS, Bahadir H, and Ozturk M. 2008. Eco- physiology of Capparis spinosa L.: A plant suit- able for combating desertification. Pak. J. Bot, 40(4): 1481-1486. https://www.academia.edu/down- load/31556522/PJB40(4)1481.pdf. Sandhu PS. 1989. SOCGI plant chromosome number reports 8. J. Cytol. Genet. 24, 179-183. Sayadi V, Karimzadeh G, Naghavi MR, and Rashidi Monfared S. 2022. Interspecific genome size varia- tion of Iranian endemic Allium species (Amarylli- daceae). Cytologia (Tokyo). 87: 335-338. https://doi. org/10.1508/cytologia.87.335. Shahrajabian MH, Sun W, and Cheng Q. 2021. Plant of the millennium, caper (Capparis spinosa L.), chemi- cal composition and medicinal uses. Bull. Natl. Res. Cent. 45. https://doi.org/10.1186/s42269-021-00592-0. Shariat A, Karimzadeh G, and Assareh MH. 2013. Kary- ology of Iranian endemic Satureja (Lamiaceae) spe- cies. Cytologia (Tokyo). 78: 305-312. https://doi. org/10.1508/cytologia.78.305. Sharma A. (1968). Chromosome number reports of plants. In Annual Report, Cytogenetics Laboratory, Department of Botany, University of Calcutta. Res. Bull. 2: 38-48. Siljak-YakovlevS and Peruzzi L. 2012. Cytogenetic char- acterization of endemics: Past and future. Plant Bio- syst. 146, 694-702. https://doi.org/10.1080/11263504. 2012.716796. Singh RJ. 2016. Plant Cytogenetics (3rd ed.). CRC Press. 548 p. https://doi.org/10.1201/9781315374611. Singhal VK and Gill BS. 1984. SOCGI plant chromosome number reports II. J. Cytol. Genet 19: 115-117. Sliwinska E. 2018. Flow cytometry-a modern method for exploring genome size and nuclear DNA synthesis in horticultural and medicinal plant species. Folia Hortic. 30: 103-128. https://doi.org/10.2478/fhort-2018-0011. Stace CA. 2000. Cytology and cytogenetics as a funda- mental taxonomic resource for the 20th and 21st cen- turies. Taxon 49: 451-477. doi.org/10.2307/1224344. Stebbins GL. 1950. Variation and Evolution in Plants. Columbia University Press, USA. Stebbins GL. 1971. Chromosomal Evolution in Higher Plants. Edward Arnold Ltd, UK. Subramanian D. and Pondmudi R. 1987. Cytotaxonomi- cal Studies of South Indian Scrophulariaceae. Cyto- logia (Tokyo). 52: 529-541. https://doi.org/10.1508/ cytologia.52.529. Sundarrajan P and Bhagtaney L. 2023. Tradition- al Medicinal Plants as Bioresources in Health Security. Apple Academic Press. https://doi. org/10.1201/9781003352983-3. Swift HH. 1950. The constancy of desoxyribose nucleic acid in plant nuclei. Proceedings of the National Academy of Sciences, Washington 36: 643-654. htt- ps://doi.org/10.1073/pnas.36.11.643. Tarkesh Esfahani S, Karimzadeh G, and Naghavi MR. 2016. 2C DNA value of Persian poppy (Papaver brac- teatum Lindl.) medicinal plant as revealed by flow cytometry analysis; a quick effective criteria for dis- tinguishing unidentified Papaver species. Internation- al Journal of Advanced Biotechnology and Research, 7(2): 573-578. http://www.bipublication.com. Tarkesh Esfahani S, Karimzadeh G, and Naghavi MR. 2020. In vitro polyploidy induction in persian poppy (Papaver bracteatum Lindl.). Caryologia 73: 133-144. https://doi.org/10.13128/caryologia-169. Tavan M, Mirjalili MH, and Karimzadeh G. 2015. In vitro polyploidy induction: changes in morphologi- cal, anatomical and phytochemical characteristics of Thymus persicus (Lamiaceae). Plant Cell Tiss. Org. Cult.122: 573-583. https://doi.org/10.1007/s11240- 015-0789-0. Tkach N and Röser M. 2024. Genome sizes of grasses (Poaceae), chromosomal evolution, paleogenomics https://doi.org/10.1080/11263504.2016.1149123 https://doi.org/10.1080/11263504.2016.1149123 https://doi.org/10.3897/CompCytogen.v6i4.3955 https://doi.org/10.3897/CompCytogen.v6i4.3955 https://doi.org/10.30848/PJB2023-3(2) https://doi.org/10.22124/jms.2023.23352.1729 https://doi.org/10.22124/jms.2023.23352.1729 https://doi.org/10.36253/caryologia-1955 https://doi.org/10.5962/bhl.title.123255 https://www.academia.edu/download/31556522/PJB40(4)1481.pdf https://www.academia.edu/download/31556522/PJB40(4)1481.pdf https://doi.org/10.1508/cytologia.87.335 https://doi.org/10.1508/cytologia.87.335 https://doi.org/10.1186/s42269-021-00592-0 https://doi.org/10.1508/cytologia.78.305 https://doi.org/10.1508/cytologia.78.305 https://doi.org/10.1080/11263504.2012.716796 https://doi.org/10.1080/11263504.2012.716796 https://doi.org/10.1201/9781315374611 https://doi.org/10.2478/fhort-2018-0011 http://doi.org/10.2307/1224344 https://doi.org/10.1508/cytologia.52.529 https://doi.org/10.1508/cytologia.52.529 https://doi.org/10.1201/9781003352983-3 https://doi.org/10.1201/9781003352983-3 https://doi.org/10.1073/pnas.36.11.643 https://doi.org/10.1073/pnas.36.11.643 http://www.bipublication.com https://doi.org/10.13128/caryologia-169 https://doi.org/10.1007/s11240-015-0789-0 https://doi.org/10.1007/s11240-015-0789-0 19Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant and the ancestral grass karyotype (AGK). https://doi. org/10.21203/rs.3.rs-3914153/v1. Tlili N, Mejri H, Anouer F, Saadaoui E, Khaldi A, and Nasri N. 2015. Phenolic profile and antioxidant activ- ity of Capparis spinosa seeds harvested from different wild habitats. Industrial Crops and Products, 76: 930- 935. https://doi.org/10.1016/j.indcrop.2015.07.040. Vimala Y, Lavania S, and Lavania UC. 2021. Chromo- some change and karyotype differentiation-implica- tions in speciation and plant systematics. Nucl. 64: 33-54. https://doi.org/10.1007/s13237-020-00343-y. Wang LJ, Gao MD, Sheng MY, and Yin J. 2020. Cluster analysis of karyotype similarity coefficients in Epi- medium (Berberidaceae): Insights in the systemat- ics and evolution. PhytoKeys 161: 11-26. https://doi. org/10.3897/PHYTOKEYS.161.51046. Wang L, Fan L, Zhao Z, Zhang Z, Jiang L, Chai M, and Tian C. 2022. The Capparis spinosa var. herbacea genome provides the first genomic instrument for a diversity and evolution study of the Capparaceae family. Gigascience 11: 1-14. https://doi.org/10.1093/ gigascience/giac106. Weigel D and Nordborg M. 2015. Population genom- ics for understanding adaptation in wild plant spe- cies. Annu. Rev. Genet. 49(1): 315-338. https://doi. org/10.1146/annurev-genet-120213-092110. Winterfeld G, Ley A, Hoffmann MH, Paule J, and Röser M. 2020. Dysploidy and polyploidy trigger strong variation of chromosome numbers in the prayer- plant family (Marantaceae). Plant Syst. Evol. 306: 1-17. https://doi.org/10.1007/s00606-020-01663-x. Winterfeld G, Schneider J, Becher H, Dickie J, and Röser M. 2015. Karyosystematics of the Australasian stip- oid grass Austrostipa and related genera: chromo- some sizes, ploidy, chromosome base numbers and phylogeny. Aust. Syst. Bot. 28: 145-159. https://doi. org/10.1071/sb14029. Xiaofeng G and Richman MB. 1995. On the applica- tion of cluster analysis to growing season precipi- tation data in North America east of the Rockies. J. Clim. 8: 897-931. https://doi.org/10.1175/1520- 0442(1995)008<0897:otaoca>2.0.co;2. Yari A, Karimzadeh G, Rashidi Monfared ., and Sayadi S. 2024. Mixed-ploidy in Iranian endemic Cymbopogon olivieri (Boiss.) Bor: A chromosomal and holoploid genome size study. Cytologia, 89 (2): 127-131. htt- ps://doi.org/10.1508/cytologia.89.127. Yeshitila M, Gedebo A, Tesfaye B, Demissie H, and Olan- go TM. 2023. Multivariate analysis for yield and yield-related traits of amaranth genotypes from Ethi- opia. Heliyon. 9: 100184. https://doi.org/10.1016/j. heliyon.2023.e18207. Zarabizadeh H, Karimzadeh G, Rashidi Monfared S, and Tarkesh Esfahani S. 2022. Karyomorphology, ploidy analysis, and flow cytometric genome size estimation of Medicago monantha populations. Turk. J. Botany 46: 50-61. https://doi.org/10.3906/bot-2105-22. Zare Teymoori S, Karimzadeh G, and Shariat A. 2021. Chromosomal and genome size diversity in savory (Satureja spp.) medicinal plant. Iranian Journal of Rangelands and Forests Plant Breeding and Genetic Research, 29(2): 236-250. https://doi.org/10.22092/ ijrfpbgr.2021.354486.1383. (In Persian with English abstract). Zarei M, Seyedi N, Maghsoudi S, Nejad MS, and Sheiba- ni H. 2021. Green synthesis of Agnanoparticles on the modified graphene oxide using Capparis spi- nosa fruit extract for catalytic reduction of organ- ic dyes. Inorg. Chem. Commun. 123. https://doi. org/10.1016/j.inoche.2020.108327. https://doi.org/10.21203/rs.3.rs-3914153/v1 https://doi.org/10.21203/rs.3.rs-3914153/v1 https://doi.org/10.1016/j.indcrop.2015.07.040 https://doi.org/10.1007/s13237-020-00343-y https://doi.org/10.3897/PHYTOKEYS.161.51046 https://doi.org/10.3897/PHYTOKEYS.161.51046 https://doi.org/10.1093/gigascience/giac106 https://doi.org/10.1093/gigascience/giac106 https://doi.org/10.1146/annurev-genet-120213-092110 https://doi.org/10.1146/annurev-genet-120213-092110 https://doi.org/10.1007/s00606-020-01663-x https://doi.org/10.1071/sb14029 https://doi.org/10.1071/sb14029 https://doi.org/10.1175/1520-0442(1995)008 https://doi.org/10.1175/1520-0442(1995)008 https://doi.org/10.1508/cytologia.89.127 https://doi.org/10.1508/cytologia.89.127 https://doi.org/10.1016/j.heliyon.2023.e18207 https://doi.org/10.1016/j.heliyon.2023.e18207 https://doi.org/10.3906/bot-2105-22 https://doi.org/10.22092/ijrfpbgr.2021.354486.1383 https://doi.org/10.22092/ijrfpbgr.2021.354486.1383 https://doi.org/10.1016/j.inoche.2020.108327 https://doi.org/10.1016/j.inoche.2020.108327 Chromosome, ploidy analysis, and flow cytometric genome size of caper (Capparis spinosa) medicinal plant Parviz Radmanesh, Ghasem Karimzadeh* Karyotype analysis and chromosome evolution in Menyanthaceae using FISH Hye-rin Kim, Kweon Heo* Karyological data of five autumn-flowering Crocus L. species from Iran Alireza Dolatyari Divergence in the chromosomal distribution of repetitive sequences in Neotropical cichlid species of the genus Lugubria Luan Felipe da Silva Frade1, Carlos Eduardo Vasconcelos dos Santos1, Bruno Rafael Ribeiro de Almeida2, Cleusa Yoshiko Nagamachi3, Julio Cesar Pieczarka3, Luís Adriano Santos do Nascimento5, Cesar Martins4, Adauto Lima Cardoso4, Renata Coelho Rodrigues Nor Cytotoxic effects of %70 Thiophanate methyl fungicide Yasin Eren Avian DNA extraction: An economical and efficient alternative for Farmer-fixed samples Lilian de Oliveira Machado1,2,*, Hybraim Severo Salau1,2, Larissa Rodrigues Pereira1,2, Adriana Koslovski Sassi3, Fabiano Pimentel Torres1, Analía del Valle Garnero1,2, Ricardo José Gunski1,2,*