Caryologia. International Journal of Cytology, Cytosystematics and Cytogenetics 75(4): 77-86, 2022 Firenze University Press www.fupress.com/caryologia ISSN 0008-7114 (print) | ISSN 2165-5391 (online) | DOI: 10.36253/caryologia-1629 Caryologia International Journal of Cytology, Cytosystematics and Cytogenetics Citation: Chnar Hama Noori Meerza, Basoz Sadiq Muhealdin, Sahar Hus- sein Hamarashid, Syamand Ahmad Qadir,Yusef Juan (2022). Delimiting spe- cies using DNA and morphological variation in some Alcea (Malvaceae) species based on SRAP markers. Caryologia 75(4): 77-86. doi: 10.36253/ caryologia-1629 Received: April 15, 2022 Accepted: December 20, 2022 Published: April 28, 2023 Copyright: © 2022 Chnar Hama Noori Meerza, Basoz Sadiq Muhealdin, Sahar Hussein Hamarashid, Syamand Ahmad Qadir,Yusef Juan. This is an open access, peer-reviewed article published by Firenze University Press (http://www.fupress.com/caryologia) and distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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. Delimiting species using DNA and morphological variation in some Alcea (Malvaceae) species based on SRAP markers Chnar Hama Noori Meerza1, Basoz Sadiq Muhealdin2, Sahar Hussein Hamarashid2,*, Syamand Ahmad Qadir3, Yusef Juan4 1 Food Science and Quality Control Department, Bakrajo Technical Institute, Sulaimani Polytechnic University, Sulaymaniyah, Iraq 2 Agricultural Project Management Department, Technical College of Applied Science Halabja, Sulaimani Polytechnic University, Iraq 3 Medical Laboratory Techniques Department, Halabja Technical Institute, Research cent- er, Sulaimani Polytechnic University, Sulaymaniyah, Iraq 4 Department of Biology, Faculty of Science, Behbahan Khatam Alanbia University of Technology, Khuzestan, Iran *Corresponding author. E-mail: sahar.rashid@spu.edu.iq Abstract. Species identification is fundamentally important within the fields of biol- ogy, biogeography, ecology and conservation. The genus Alcea (Malvaceae) includes approximately 70 species of mainly Irano-Turanian distribution and is considered one of the most challenging genera of the Middle East, due to its uniformity and pro- nounced plasticity in morphological traits. In spite vast distribution of many Alcea species that grow in Iraq, there are not any available report on their genetic diversi- ty, mode of divergence and patterns of dispersal. Therefore, we performed molecular (SRAP marker) and morphological studies of 80 accessions from 10 species of Alcea that were collected from different habitats in Iraq. The aims of present study are: 1) can SRAP markers identify Alcea species, 2) what is the genetic structure of these taxa in Iraq, and 3) to investigate the species inter-relationship? The present study revealed that combination of morphological and SRAP data can identify the species. Keywords: Alcea, SRAP, Morphology, Species Identification. 1. INTRODUCTION Alcea L. (Malvaceae) is considered one of the most complicated and challenging genera of the Middle Eastern flora (Iljin, 1949; Zohary, 1963b; Riedl, 1976; Townsend, 1980; Pakravan, 2001). The Irano-Turanian floristic region (Takhtajan, 1986) stretches from cen- tral Anatolia to the highlands of central Asia and is a main center of diver- sity for many medium- to large-sized genera. A well-suited system for investigating radiations in the Irano-Turanian region is the genus Alcea. It includes approximately 70 species, which are 78 Chnar Hama Noori Meerza et al. mainly of Irano-Turanian distribution with exten- sions into the Caucasus and the eastern Mediterranean (Zohary, 1963b). Riedl (1976) has reported 39 species in Iran, but the number has been reduced to 34 due to taxonomic rearrangement among them, 15 species are endemic (Pakravan 2008b). Alcea species are main- ly annual, biennial or perennial, mostly tall-growing hemicryptophytes. The stem is erect and rarely branched from the base or acaulescent in a few cases. The muci- lage that containing the plants of the Malvaceae family are sources of carbohydrates, which are used in medi- cine (Azizov et al., 2007). Any classifications are hampered by uniformity in many morphological and ecological traits (flower, inflo- rescence and fruit structure, habitat and life form) com- bined with a pronounced plasticity in the morphological characters considered important for species identifica- tion (indumentum, leaf shape and degree of division, calyx and epicalyx morphology, flower colour; Zohary, 1963b, c). Due to this plasticity, accurate species iden- tification requires character state combinations of the sequence of change of leaf morphology along the main stem (hereafter leaf sequence), relative proportions of calyx and epicalyx lobes and (mature) mericarp mor- phology, which are rarely found together on herbarium specimens. Additionally, due to political tensions in the Middle East and the Caucasus, Alcea has received only limited attention in recent studies of Malvaceae (La Duke & Doebley, 1995; Alverson & al., 1998; Nyffeler & al., 2005; Tate & al., 2005; Escobar García & al., 2009). So far, only two infrageneric classification systems have been suggested. Boissier (1867) defined two sections, Pterocarpae Boiss. and Apterocarpae Boiss., distin- guished by winged versus unwinged mericarps. Zohary (1963b, c) proposed nine informal groups based on over- lapping character combinations (leaf shape and degree of leaf division, mericarp morphology, relative dimensions of calyx and epicalyx, indumentum). Previous study on species delimitation and species relationship performed in this genus. Badrkhani et al (2014) sequence-related amplified polymorphism (SRAP) marker was employed to assess the genetic diversity and genetic similarity relationships among 14 species of Alcea collected from northwest of Iran. Two main clus- ters were detected using UPGMA, which did not correspond to geographical origin of the species. Their study indicates that SRAP markers could be good candidates for assessing genetic variation in Alcea. Escobar García et al. (2012) examines the phylog- eny of Alcea using three molecular markers (nrDNA ITS and the plastid spacers psbA-trnH and trnL-trnF), their results show that while molecular data unambiguously support the circumscription of Alcea inferred from mor- phology, they prove to be of limited utility in resolving interspecific relationships, suggesting that Alceas high species diversity is due to rapid and recent radiation. Literature revealed that studies are mainly dealing with taxonomy, seed and pollen morphology, stem and leaf anatomy (Arabameri and Khodayari 2019; Esco- bar García et al. 2012) of Alcea species and also, genet- ic diversity of Alcea species have been reported in only some studies by (Badrkhani et al (2014)) but there is no attempt to study genetic diversity, ecological adaptation and intra- and inter-specific differentiation along with morphometric studies on of Iraq. Therefore, we per- formed morphological and molecular study of 80 col- lected specimens of 10 of Alcea species. We try to answer the following questions: 1) Is there infra and interspecif- ic genetic diversity among studied species? 2) Is genetic distance among these species correlated with their geo- graphical distance? 3) What is the genetic structure of populations and taxa? 4) Is there any gene exchange between Alcea species in Iraq? 2. MATERIALS AND METHODS 2.1. Plant materials We performed morphological and molecular analy- sis of 10 Alcea species growing in Iraq. For morphomet- ric studies we used 80 plant specimens (5-15 samples from each species) and for SRAP analysis, we used 80. Different references were used for the correct identifica- tion of species (Zohary, 1963b; Riedl, 1976; Townsend, 1980; Pakravan, 2001). Details of sampling sites are men- tioned (Table 1). 2.2. Morphological studies In total 36 morphological quantitative characters were studied (supplementary Table 2). Data obtained were standardized (Mean= 0, variance = 1) and used to estimate Euclidean distance for clustering and ordina- tion analyses (Podani 2000). 2.3. Dna extraction and srapassay Fresh leaves were used randomly from 5-11 plants in each of the studied species. These were dried by silica gel powder. CTAB activated charcoal protocol was used to extract genomic DNA. The SRAP analysis was per- formed as described by Li and Quiros (2001). Ten SRAP 79Delimiting species using DNA and morphological variation in some Alcea (Malvaceae) species based on SRAP markers primer combinations (PCs) were used (Table 3); these were synthesized by Bioneer (Daejeon, Korea). PCR reac- tions were carried in a 25μl volume containing 10 mM Tris-HCl buffer at pH 8; 50 mM KCl; 1.5 mM MgCl2; 0.2 mM of each dNTP (Bioron, Germany); 0.2 μM of a sin- gle primer; 20 ng genomic DNA and 3 U of Taq DNA polymerase (Bioron, Germany). The amplifications, reac- tions were performed in Techne thermocycler (Germa- ny) with the following program: 5 min initial denatura- tion step 94°C, followed by 40 cycles of 1 min at 94°C; 1 min at 52-57°C and 2 min at 72°C. The reaction was completed by final extension step of 7-10 min at 72°C. The amplification products were observed by running on 1% agarose gel, followed by the ethidium bromide stain- ing. The fragment size was estimated by using a 100 bp molecular size ladder (Fermentas, Germany). 2.4. Data analyses 2.4.1. Morphological studies Morphological characters were f irst standard- ized (Mean = 0, Variance = 1) and used to establish Euclidean distance among pairs of taxa (Podani 2000). For grouping of the plant specimens, The UPGMA (Unweighted paired group using average) ordination methods were used (Podani 2000). ANOVA (Analysis of variance) were performed to show morphological differ- ence among the populations while, PCA (Principal com- ponents analysis) biplot was used to identify the most variable morphological characters among the studied populations (Podani 2000). PAST version 2.17 (Hammer et al. 2012) was used for multivariate statistical analyses of morphological data. 2.4.2. Molecular analyses SRAP bands obtained were coded as binary char- acters (presence = 1, absence = 0) and used for genetic diversity analysis. Parameter like Nei’s gene diversity (H), Shannon information index (I), number of effec- tive alleles, and percentage of polymorphism were Table 1. Alcea species and populations, their localities and voucher numbers. Sp. A. sachsachanica Iljin A. flavovirens (Boiss. & Buhse) Iljin A. rechingeri (Zohary) I. Riedl A. arbelensis Boiss. & Hausskn., A. koelzii I. Riedl, A. hyrcana (Grossh.) Grossh. A. peduncularis Boiss. & Hausskn. A. glabrata Alef. A. tabrisiana (Boiss. & Buhse) Iljin A. persarum Bornm. Table 2. Morphological characters in studied species. No Characters 1 Plant height (mm) 2 Length of stem leaves petiole (mm) 3 Length of stem leaves (mm) 4 Width of stem leaves (mm) 5 Length / Width of stem leaves (mm) 6 Number of segment stem leaves (mm) 7 Length of basal leaves petiole (mm) 8 Length of basal leaves (mm) 9 Width of basal leaves (mm) 10 Length / Width of basal leaves (mm) 11 Number of segment basal leaves 12 Calyx length (mm) 13 Calyx width (mm) 14 Calyx length/ width (mm) 15 Petal length (mm) 16 Petal width (mm) 17 Petal length / width (mm) 18 Fruit length (mm) 19 Mericarp length (mm) 20 Mericarp width (mm) 21 Mericarp length/width (mm) 22 Seed length (mm) 23 Seed width (mm) 24 Seed length/ width (mm) 25 Stipules length (mm) 26 Stipules width (mm) 27 Stipules length/ width (mm) 28 Bract length (mm) 29 Bract width (mm) 30 Bract length / width (mm) 31 Pedicel length (mm) 32 Peduncle length (mm) 33 Rostrum length (mm) 34 Style length (mm) 35 Stamen filament length (mm) 36 Number of flowers per inflorescence (flower, inflorescence and fruit structure, habitat and life form) combined with a pronounced plasticity in the morphological char- acters considered important for species identification (indumen- tum, leaf shape and degree of division, calyx and epicalyx morphol- ogy, flower colour. 80 Chnar Hama Noori Meerza et al. determined (Freeland et al. 2011). Nei’s genetic distance among populations was used for Neighbor Joining (NJ) clustering and Neighbor-Net networking (Freeland et al. 2011, Huson & Bryant, 2006). Mantel test checked the correlation between geographical and genetic distance of the studied populations (Podani 2000). These analy- ses were done by PAST ver. 2.17 (Hammer et al. 2012), DARwin ver. 5 (2012) and SplitsTree4 V4.13.1 (2013) software. AMOVA (Analysis of molecular variance) test (with 1000 permutations) as implemented in GenAlex 6.4 (Peakall and Smouse 2006), and Nei,s Gst analysis as implemented in GenoDive ver.2 (2013) (Meirmans & Van Tienderen 2004) were used to show genetic differ- ence of the populations. Moreover, populations, genetic differentiation was studied by G’ST est = standardized measure of genetic differentiation (Hedrick 2005), and D_est = Jost measure of differentiation (Jost 2008). The genetic structure of populations was studied by Bayesian based model STRUCTURE analysis (Pritchard et al. 2000), and maximum likelihood-based method of K-Means clustering of GenoDive ver. 2. (2013). For STRUCTURE analysis, data were scored as dominant markers (Falush et al. 2007). The Evanno test was per- formed on STRUCTURE result to determine proper number of K by using delta K value (Evanno et al. 2005). In K-Means clustering, two summary statistics, pseudo- F, and Bayesian Information Criterion (BIC), provide the best fit for k (Meirmans 2012). Gene flow was deter- mined by (i) Calculating Nm an estimate of gene flow from Gst by PopGene ver. 1.32 (1997) as: Nm = 0.5(1 - Gst)/Gst. This approach considers equal amount of gene flow among all populations. (ii) Population assignment test based on maximum likelihood as performed in Genodive ver. in GenoDive ver. 2. (2013). The presence of shared alleles was determined by drawing the reticu- logram network based on the least square method by DARwin ver 5. (2012). RESULTS 3.1. Species identification and inter-relationship Morphometry ANOVA showed significant differences (P <0.01) in quantitative morphological characters among the species studied. In order to determine the most variable charac- ters among the taxa studied, PCA analysis has been per- formed. It revealed that the first three factors comprised over 76% of the total variation. In the first PCA axis with 41% of total variation, such characters as seed out- line, seed length, stipules length, shape of petal, pedun- cle and pedicel hair, stem hair, Stipules length/ width bract and leaf hair have shown the highest correlation (>0.7). Length of bract and peduncle, length of petal, sepal hair, number of flowers per inflorescence were characters influencing PCA axis 2 and 3 respectively. Different clustering and ordination methods pro- duced similar results. Therefore PCA plot of morpho- logical characters are presented here (Fig. 1). In general, plant samples of each species, were grouped together and formed separate cluster. This result show that mor- phological characters studied can differentiate the Alcea species in two different major clusters or groups. In the studied specimens we did not encounter intermediate forms. The PCA plot of morphological characters (Fig. 1) separated the species into distinct groups with no inter- mixing. This is in agreement with UPGMA tree. 3.2. Species identification and genetic diversity All SR AP primer produced polymorphic bands. Genetic diversity parameters determined in the stud- ied species (Table 3) revealed that A. rechingeri had the highest level of genetic polymorphism (49.13%), while the lowest level of genetic polymorphism (17.22%) occurred in A. sachsachanica. A. glabrata also had the highest values for effective number of alleles (Ne = 1.264) and Shannon information index (I =0.235). AMOVA test showed significant genetic difference (P = 0.01) among studied species. It revealed that 60% of total variation was among species and 40% was within species. Pair-wise FST values showed significant difference among all studied species (Table 4). Moreover, genetic differentiation of these species was demonstrated by significant Nei’s GST (0.89, P = 0.01) and D_est values (0.587, P = 0.01). NJ tree based on Nei,s genetic distance (Fig. 2), showed that A. flavovirens; A. arbelensis; A. persarum are separated from the other studied species and join the others with a great distance. This dendrogram showed close genetic affinity between A. koelzii and A. hyrcana. Similarly, A. rechingeri and A. peduncularis were placed close to each other, to which, E. litvinovii was joined with some distance. In general, this indicates that SRAP molecular markers can be used in Alcea species differen- tiation. This is in agreement with AMOVA and genetic diversity parameters presented before. The species are genetically well differentiated from each other. The Nm analysis by Popgene software also produced mean Nm= 0.78, that is considered very low value of gene f low among the studied species. Mantel test with 5000 permutations showed a sig- nificant correlation (r = 0.24, p=0.0002) between genetic 81Delimiting species using DNA and morphological variation in some Alcea (Malvaceae) species based on SRAP markers distance and geographical distance, so isolation by dis- tance (IBD) occurred among the Alcea species studied. Nei’s genetic identity and the genetic distance deter- mined among the studied species (Table is not included). The results showed that the highest degree of genetic similarity (0.83) occurred between A. koelzii and A. hyr- cana. The lowest degree of genetic similarity occurred between A. arbelensis and A. persarum (0.64). Figure 1. Alcea species:a, i: A. flavovirens; b: A. sachsachanica; c: A. rechingeri;d, h: A. arbelensis; e: A. koelzii; f, g: A. hyrcana 82 Chnar Hama Noori Meerza et al. 3.3. The species genetic structure We performed STRUCTURE analysis followed by the Evanno test to identify the optimal number of genet- ic groups. We used the admixture model to illustrate interspecific gene flow or / and ancestrally shared alleles in the species studied. STRUCTURE analysis followed by Evanno test pro- duced ΔK =10. The STRUCTURE plot (Fig. 3) produced more detailed information about the genetic structure of the species studied as well as shared ancestral alleles and / or gene flow among Alcea species. This plot revealed that Genetic affinity between A. rechingeri and A. arbelensis (similarly colored), as well as A. koelzii and A. hyrcana (similarly colored) due to shared common alleles. This is in agreement with Neighbor joining dendrogram pre- sented before. The other species are distinct in their allele composition and differed genetically from each other. The low Nm value (0.78) indicates limited gene flow or ancestrally shared alleles between the species studied and supports genetic stratification as indicated by K-Means and STRUCTURE analyses. Population assignment test also agreed with Nm result and could not identify significant gene flow among members of Table 3. Genetic diversity parameters in the studied Alcea species. (N = number of samples, Ne = number of effective alleles, I= Shannon’s information index, He = gene diversity, UHe = unbiased gene diversity, P%= percentage of polymorphism, populations). Pop N Na Ne I He UHe %P A. sachsachanica Iljin 13.000 0.178 1.017 0.016 0.002 0.019 17.22% A. flavovirens (Boiss. & Buhse) Iljin 10.000 0.276 1.061 0.053 0.036 0.044 29.68% A. rechingeri (Zohary) I. Riedl 17.000 0.355 1.145 0.234 0.288 0.211 49.13% A. arbelensis Boiss. & Hausskn., 10.000 0.301 1.009 0.211 0.154 0.177 43.23% A. koelzii I. Riedl, 7.000 0.677 1.087 0.093 0.057 0.099 23.66% A. hyrcana (Grossh.) Grossh. 10.000 0.699 1.156 0.143 0.094 0.205 27.96% A. peduncularis Boiss. & Hausskn. 4.000 0.376 1.054 0.055 0.035 0.021 21.83% A. glabrata Alef. 5.000 0.452 1.264 0.235 0.039 0.044 24.90% A. tabrisiana (Boiss. & Buhse) Iljin 5.000 0.269 1.021 0.023 0.011 0.023 22.15% A. persarum Bornm. 8.000 0.548 1.013 0.029 0.012 0.019 19.68% Figure 2. PCA plots of morphological characters revealing species delimitation in Alcea species 83Delimiting species using DNA and morphological variation in some Alcea (Malvaceae) species based on SRAP markers the studied species. However, reticulogram obtained based on the least square method (Figure not included), revealed some amount of shared alleles between species 2 and 1,3,5 and between 9 and 1,3-5 also between 3 and 1, 2, 9-10. As evidenced by STRUCTURE plot based on admixture model, these shared alleles comprise very limited part of the genomes in species studied and all these results are in agreement in showing high degree of genetic stratification in species studied 4. DISCUSSION 4.1. Species identification and taxonomic consideration Species delimitation is important in different bio- logical disciplines, like ecology, biogeography, and plant conservation (Mayr 1982). Species delimitation is done by tree-based and non-tree-based approaches (Wiens 2007). In the first method, species form distinguishing clades (phylogenetic species concept), whereas in non- tree-based method, the species are recognized on the basis of gene flow assessments (biological species con- cept; Pérez-Losada et al. 2005). Wiens & Penkrot (2002), proposed to use DNA data, morphological data and character data for species delim- itation while, Knowles & Carstens (2007) addressed how molecular data (i.e., gene trees from DNA sequence data) can be used in species delimitation. The latter authors used coalescent simulations to test the species limits and incorporated data from multiple loci. They showed the importance of population genetics in species delimita- tion. Similarly, Medrano et al. (2014), applied population genetics methods to the species delimitation problem in Narcissus Linnaeus (1753: 289) (Amaryllidaceae J.St.-Hil. nom. cons.) by the help of amplified fragment length polymorphism (AFLP) molecular markers. In the present study we used morphological and molecular (SRAP) data to evaluate species relationship in Alcea. Morphological analyses of the studied Alcea species showed that they are well differentiated from each other both in quantitative measures (the ANOVA test result) and qualitative characters (The PCA plot result). In addition, PCA analysis suggests that charac- ters like bract length, stipule length, bract shape, calyx shape, petal shape, length and width of stem-leaf, length and width of petal, peduncle and pedicel hair, mericarp hair density, mericarp surface could be used in species groups delimitation. This morphological difference was due to quantitative and qualitative characters. 4.2. Genetic structure and gene flow This is the first study on the use of SRAP markers for genetic diversity, species delimitation and determin- ing genetic relationships among Alcea species in Iraq. Alarcón, et al., (2012) showed that SRAP technique along with proper statistical tools could be successfully applied to assess the genetic diversity and phylogenetic analysis among Alcea species in Iraq. Our results clearly demonstrated that SRAP markers can be used in genetic diversity study as well as genetic identification of Alcea. Moreover, our results indicate a very high efficiency of the SRAP markers in the identification and delimitation of Alcea species. Similar efficiency of the SRAP mark- ers has also been reported by other authors (Alarcón, et al., 2012; Li, et al, 2021; Sun, et al. 2021; Xu, et al, 2021; Zhang, et al. 2022). AMOVA and STRUCTURE analysis revealed that the species of Alcea are genetically differentiated but have some degree of shared common alleles. Several trends in pollination mechanism can be observed in Alcea with gradual transition between them. Based on RAPD markers analysis, Kazemi et al. (2011) showed Figure 3. STRUCTURE plot of Alcea species based on SRAP data. 84 Chnar Hama Noori Meerza et al. 93% polymorphism level with high variation in genetic similarity (0.31 to 0.75) within A. rosea populations in Iran. Öztürk et al. (2009) analyzed genetic profile of 18 Alcea species using RAPD markers and reported wide differentiation (0.13 to 0.69) among them. According to Badrkhani et al (2014) sequence-related amplified poly- morphism (SRAP) marker was employed to assess the genetic diversity and genetic similarity relationships among14 species of Alcea collected from northwest of Iran. Seventeen SRAP primer combinations gener- ated 104 fragments, of which 97 (93%) were polymor- phic, with an average of 5.7 polymorphic fragments per primer. Percentage of polymorphism ranged from 50% (ME2-EM6) to a maximum of 100%, and mean polymorphism information content value obtained was 0.3. The lowest genetic similarity (0.17) was observed between A. sophiae and A. flavovirens, while the high- est was found between A. digitata and A. longipedicellata (0.68). Two main clusters were detected using UPGMA, which did not correspond to geographical origin of the species. Their study indicates that SRAP markers could be good candidates for assessing genetic variation in Alcea. Iranian Alcea species have only been character- ized with morphological data, so far. However, the genus has a complicated taxonomy due to small number of characters. Based on study of Pakravan (2008) on Alcea, only examination of the leaf sequence and configura- tion of the carpels would represent valuable characters. For example, A. fl avovirens and A. glabrata differ only in the size of the carpel and width of wing (Pakravan 2008). Our results grouped these two species into two different clusters. The methods we used are indirect estimation of gene flow and if it is identified to occur among species may be either due to ancestral shared alleles or ongoing gene flow. The Nm value obtained based on SRAP data, revealed very limited amount of gene flow among the studied species that was also supported by STRUCTURE analysis as Alcea species mostly had distinct genetic structure. Reticulation analysis also showed some degree of gene flow for SRAP. We did not observe any interme- diate forms in our extensive plant collection, but mor- phological variability within each species did occur to some extent. To conclude, the present study revealed the use of SRAP molecular markers along with morpho- logical characters in Alcea species identification. Some degrees of interspecific genetic admixture occur in Alcea species, but the studied species are strongly differenti- ated during the speciation process and invasion in new habitats. Genetic drift, strong inbreeding and local adap- tation are effective evolutionary forces operating in Alcea species and population divergence and adaptation. Plant species identification is of central importance in phylogenetic systematics, evolution, biogeography and biodiversity. It is significant to infer patterns and mecha- nisms of speciation and hybridization, the evolutionary process by which new biological species arise and gene flow between closely related phylogenetic species can occur (Al-Quran 2008; Bi, et al., 2021; Duan, et al., 2022; Guo, et al, 2021; Guo, et al, 2022). Isolation by distance, local adaptation and gene flow are different mechanisms responsible for species differ- entiation and genetic diversity (Freeland et al. 2011, Fri- chot et al. 2013). REFERENCES Alarcón, M., Vargas, P., Sáez, L., Molero, J., Aldasoro, J.J., 2012. Genetic diversity of mountain plants: Two migration episodes of Mediterranean Erodium (Geraniaceae) Molecular Phylogenetics and Evolu- tion 63, 866–876 Al-Quran S. 2008. Taxonomical and pharmacological survey of therapeutic plants in Jordan. Journal of Natural Products, l (1):10-26. Azizov U.M., Mirakilova D.B., Umarova N.T., Salikhov S.A., Rakhimov D.A. and Mezhlumyan L.G.(2007). Chemical composition of dry extracts from Alcea rosea. Chemistry of Natural Compounds 43:508-511. Alefeld, F.G.C. (1862). Ueber die Malveen. Oesterreichis- che Botanische Zeitschrift 12: 246–261. Boissier, P.E. (1867). Flora Orientalis, Vol. 1. Basel, Gene- va, Leiden. Bi, D., C. Dan, M. Khayatnezhad, Z. Sayyah Hashjin, Z. Y. Ma 2021. Molecular Identification And Genetic Diver- sity In Hypericum L.: A High Value Medicinal Plant Using Rapd Markers Markers. Genetika 53(1): 393-405. Chen, Weimiao; Khayatnezhad, Majid; Sarhadi, Nima 2021. Protok gena i struktura populacije kod allochrusa (Caryophylloideae, Caryophyllaceae) pomocu molekularnih markera. Genetika 53(2): 799- 812. Duan, F., Fei Song, Sainan Chen, Majid Khayatnezhad, Noradin Ghadimi, 2022. Model parameters identi- fication of the PEMFCs using an improved design of Crow Search Algorithm. International Journal of Hydrogen Energy, 47(79): 33839-33849. Evanno, G., Regnaut, S. & Goudet, J. 2005: Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14: 2611–2620. Escobar G.P., Schönswetter P., Fuertes A.J., Nieto F.G. and Schneeweiss G.M. (2009). Five molecular markers 85Delimiting species using DNA and morphological variation in some Alcea (Malvaceae) species based on SRAP markers reveal extensive morphological homoplasy and retic- ulate evolution in the Malva alliance (Malvaceae). Molecular Phylogenetics and Evolution 50:226-239. Falush, D., Stephens, M. & Pritchard, J.K. 2007: Inference of population structure using multilocus genotype data: dominant markers and null alleles. Molecular Ecology Notes 7: 574–578. Frichot, E., Schoville, S. D., Bouchard, G. & Francois, O. 2013: Testing for associations between loci and envi- ronmental gradients using latent factor mixed mod- els. Molecular Biology and Evolution 30: 1687–1699. Freeland, J.R., Kirk, H. & Peterson, S.D. 2011: Molecular Ecology (2nded). Wiley-Blackwell, UK, 449 pp. Fiz O, Vargas P, Alarcon ML, Aldasoro JJ. 2006. Phyloge- netic Relationships and Evolution in Erodium (Gera- niaceae) based on trnL-trnF Sequences. Syst Botany 31: 739- 763 Guo, H., Wei Gu, Majid Khayatnezhad, Noradin Ghadi- mi, 2022. Parameter extraction of the SOFC math- ematical model based on fractional order version of dragonfly algorithm. International Journal of Hydro- gen Energy, 47(57):24059-24068. Guo, L.N., She, C., Kong, D.B., Yan, S.L., Xu, Y.P., Khay- atnezhad, M. and Gholinia, F. 2021. Prediction of the effects of climate change on hydroelectric generation, electricity demand, and emissions of greenhouse gases under climatic scenarios and optimized ANN model. Energy Reports 7: 5431-5445. Huson, D.H. & Bryant, D. 2006: Application of Phyloge- netic Networks in Evolutionary Studies. Molecular Biology and Evolution 23: 254−267. Hammer, O., Harper, D.A. & Ryan, P.D. 2012: PAST: Paleontological Statistics software package for educa- tion and data analysis. Palaeonto Electro 4: 9. Hedrick, P. W. 2005: A standardized genetic differentia- tion measure. Evolution 59:1633–1638. Iljin, M.M. 1949. Malvaceae. Flora of the USSR 15: 21–137. Kazemi M., Aran M. and Zamani S. 2011. Evaluation of genetic diversity of Iranian wild Alcea rosea popula- tion using RAPD. World Applied Sciences Journal 13:1234-1239. Jia, Y., M. Khayatnezhad, s. mehri (2020). Population dif- ferentiation and gene flow in Rrodium cicutarium: A potential medicinal plant. Genetika 52(3): 1127-1144. Jost, L. 2008: GST and its relatives do not measure differ- entiation. Molecular Ecology 17: 4015–4026. Knowles, L.L., & Carstens, B. 2007: Delimiting species without monophyletic gene trees. Systematic Biology 56: 887-895. doi:10.1080/10635150701701091. Li, Ang; Mu, Xinyuan; Zhao, Xia; Xu, Jiamin; Khayat- nezhad, Majid; Lalehzari, Reza; Developing the non- dimensional framework for water distribution formu- lation to evaluate sprinkler irrigation; Irrigation and Drainage, 70: 659-667. Liu, S., Wang, Y., Song, Y., Khayatnezhad, M., & Minaei- far, A. A. 2021. Genetic variations and interspe- cific relationships in Salvia (Lamiaceae) using SCoT molecular markers. Caryologia, 74(3), 77-89. Medrano, M., Lo´ Pez-Perea E. & Herrera, C.M. 2014: Population genetics methods applied to a species delimitation problem: Endemic trumpet daffodils (Narcissus section Pseudonarcissi) from the Southern Iberian Peninsula. International Journal of Plant Sci- ences 175: 501-517. doi: 10.1086/675977 Mayr, E. 1982: The Growth of Biological Thought: Diver- sity, Evolution, and Inheritance. Cambridge, MA: Harvard University Press.1-992 Meirmans, P.G. & Van Tienderen, P.H. 2004: GENO- TYPE and GENODIVE: two programs for the analy- sis of genetic diversity of asexual organisms. Molecu- lar Ecology Notes 4: 792–794. Meirmans, P.G. 2012: AMOVA-based clustering of popu- lation genetic data. Journal of Heredity 103: 744–750. Öztürk F., Babaoğlu S., Uzunhisarcikli M.E., Açik L., Vural M. and Gürcan I.S. 2009. Genetic differen- tiation of Turkish Althaea L. and Alcea L. species. Advances in Molecular Biology 1:47-56. Pakravan M. 2008. A new species and a new combination in Iranian Alcea (Malvaceae). Annales Botanici Fen- nici 45:133-136. Peng, X., Khayatnezhad, M. and Ghezeljehmeidan, L. 2021. Rapd profiling in detecting genetic variation in stellaria l. (caryophyllaceae). Genetika-Belgrade 53: 349-362. Peakall, R. & Smouse, P.E. 2006: GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6: 288–295. Podani, J. 2000: Introduction to the Exploration of Multi- variate Data English translation. Backhuyes publisher, Leide,407 pp. Pritchard, J.K., Stephens, M. & Donnelly, P. 2000: Infer- ence of population structure using multilocus geno- type Data. Genetics 155: 945–959. Pérez-Losada, M., Eiroa, J., Mato,S., & Domínguez, J. 2005: Phylogenetic species delimitation of the earth worms Eiseniafetida (Savigny,1826) and Eiseniaan- drei Bouché,1972(Oligochaeta,Lumbricidae) based on mitochondrial and nuclear DNAsequences. Pedobio- logia 49: 317–324.doi: 10.1016/j.pedobi.2005.02.004 Riedl I. 1976. Malvaceae. In: Rechinger K.H. Ed. Flora Iranica 120, pp 1-86, Akademische Druck und Ver- lagsanstalt, Graz. Townsend, C.C., Guest, E. & Al-Rawi, A. 1966– 1985. 86 Chnar Hama Noori Meerza et al. Flora of Iraq. Ministry of Agriculture of the Republic of Iraq. Baghdad. Shi, B., Khayatnezhad, M., Shakoor, A. 2021. The inter- acting effects of genetic variation in Geranium subg. Geranium (Geraniaceae) using scot molecular mark- ers. Caryologia, 74(3), 141-150. Sun, Q., Deli Lin, Majid K., Mohammad T., 2021. Inves- tigation of phosphoric acid fuel cell, linear Fresnel solar reflector and Organic Rankine Cycle polygen- eration energy system in different climatic condi- tions. Process Safety and Environmental Protection, 147:993-1008. Xu, Y.-P., Ping Ouyang, Si-Ming Xing, Lu-Yu Qi, Majid khayatnezhad, Hasan Jafari,2021. Optimal struc- ture design of a PV/FC HRES using amended Water Strider Algorithm. Energy Reports, 7: 2057-2067. Wang, C., Y. Shang, M. Khayatnezhad 2021. Fuzzy Stress- based Modeling for Probabilistic Irrigation Planning Using Copula-NSPSO. Water Resources Manage- ment. 35, 4943–4959 Wang, J., Ye, Q., Zhang, T., Shi, X., Khayatnezhad, M., Shakoor, A. 2021. Palynological analysis of genus Geranium (Geraniaceae) and its systematic implica- tions using scanning electron microscopy. Caryolo- gia, 74(3), 31-43. Wiens, J.J. 2007: Species Delimitation: New approaches for discovering diversity. Systematic. Biology 56: 875- 878. doi:10.1080/10635150701748506. Wiens, J.J. & Penkrot,T.A. 2002: Delimiting species using DNA and morphological variation and discordant species limitsinspinylizards (Sceloporus). Systematic. Biology 51: 69–91. Zohary, M. 1963a. Taxonomical studies in Alcea of south- western Asia. Part I. Bulletin of the Research Council of Israel 11: 210–229. Zohary, M. 1963b. Taxonomical studies in Alcea of south- western Asia. Part II. Israel Journal of Botany 12: 1–26. Zhang, J., M. Khayatnezhad, and N. Ghadimi, 2022. Opti- mal model evaluation of the proton-exchange mem- brane fuel cells based on deep learning and modified African Vulture Optimization Algorithm. Energy Sources, Part A: Recovery, Utilization, and Environ- mental Effects, 44(1):287-305. Caryologia International Journal of Cytology, Cytosystematics and Cytogenetics Volume 75, Issue 3 - 2022 Firenze University Press