Caryologia. International Journal of Cytology, Cytosystematics and Cytogenetics 75(1): 65-76, 2022 Firenze University Press www.fupress.com/caryologia ISSN 0008-7114 (print) | ISSN 2165-5391 (online) | DOI: 10.36253/caryologia-1310 Caryologia International Journal of Cytology, Cytosystematics and Cytogenetics Citation: Tinglu Liu, Shuangshuan Zhang, Yonghe Hao, Xiao Liang, Mohsen Farshadfar (2022) Genome survey of pistachio (Pistacia vera L.) acces- sions revealed by Start Codon Tar- geted (SCoT) markers. Caryologia 75(1): 65-76. doi: 10.36253/caryologia-1310 Received: May 10, 2021 Accepted: August 24, 2021 Published: July 6, 2022 Copyright: © 2022 Tinglu Liu, Shuangsh- uan Zhang, Yonghe Hao, Xiao Liang, Mohsen Farshadfar. This is an open access, peer-reviewed article pub- lished by Firenze University Press (http://www.fupress.com/caryologia) and distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distri- bution, and reproduction in any medi- um, 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. Genome survey of pistachio (Pistacia vera L.) accessions revealed by Start Codon Targeted (SCoT) markers Tinglu Liu1, Shuangshuan Zhang1,*, Yonghe Hao1, Xiao Liang2, Mohsen Farshadfar3 1 Ordos agriculture and animal husbandry technology popularizing center, Ordos, Inner Mongolia 017000 2 Ordos city, this paper flag farming technology promotion center, Ordos, Inner Mongolia 017000 3 Department of Agriculture, Payame Noor University (PNU), Tehran, Iran *Corresponding author. E-mail: zhang123123301@163.com Abstract. Pistachio (Pistacia vera L.) is the only cultivated and commercially important species in the genus Pistacia, consisting of a deciduous, dioeciously and wind-pollinat- ed at least 11 tree species. Pistacia vera is native to north Afghanistan, northeast Iran, and central Asian republics. To investigate the genetic diversity of pistachio (Pistacia vera), we genotyped 30 cultivars of this species using 10 Start Codon Targeted (SCoT) markers. The SCoT markers generated 9-25 alleles (155 in total) with an average of 16 per locus. The highest value of percentage polymorphism (61.99%) was observed in Ghafori Rafsanjan (cultivars No.27) which shows high value for gene diversity (0.42) and Shanon, information index (0.39). Genotype Shahpasand (Pust Ghermez) (No.10) has the lowest value for percentage of polymorphism (20%) and the lowest value for Shanon, information index (0.15), and He (0.010). Genetic similarity values obtained from Dice’s coefficient ranged from 0.66 (between Akbari (Pust Ghermez) and Bada- mi Dishkalaghi) to 0.88 (between populations Menghar Kalaghi and Kaleghochi (Pust Ghermez). The main objectives of this study were to assess the genetic diversity and genetic relationship of pistachio cultivars in Iran. These results could benefit Irainian pistachio germplasm collection, conservation and future breeding. Keywords: population structure, gene flow, network, genetic admixture, pistachio (Pistacia vera L.). INTRODUCTION Genetic variability description specifies differences among individuals or populations of the same species and serves as a very good tool for plant breeding and conservation programmes (Minn et al. 2015). Different types of DNA markers have been applied in evaluation of genetic diversity of dif- ferent plants, considering also the effects of the plant growing environment and developmental stage (Hopla et al. 2021; Fikirie et al. 2020; Gondal et al. 66 Tinglu Liu et al. 2021). The existing genetic variability of the individual species within and among the populations is connected to this species ability to mirror the short- and long-term specific regimes of their living habitats. The analysis of the distribution of the genetic variability patterns specif- ic for landscape and ecological parameters is valuable for identification of the taxa most vulnerable to the anthro- pogenic impacts (Brandvain et al., 2014). The genus Pistacia is a member of the Anacardiace- ae family, which comprises 11 or more species (Zohary 1952). Pistacia vera L., is a diploid (2n=30) member of the Anacardiaceae family (Zohary 1952; Whitehouse 1957). Pistacia vera is native to north Afghanistan, northeast Iran, and central Asian republics (Browiez 1988; Kafkas 2006). Among the nut tree crops, pistachio tree ranks sixth in world production behind almond, walnut, Cashew, hazelnut and chestnut (Mehlenbacher 2003). Iran is the main world producer with more than 400,000 tons followed by Turkey, USA and Syria (Faostat 2004). The main cultivars grown in Iran are Ohady, Kaleh ghochi, Ahmad Aghai, Badami Zarand, Rezaii and Pust piazi (Esmailpour 2001). Iran is the center of origin for four important Pistacia species: P. vera, P. khinjuk Stocks, P. eurycarpa Yalt. (P. atlantica subsp. Kurdica Zoh.), and P. atlantica Dsef. (Karimi et al. 2009). Three essential wild Pistacia species, including P. vera, P. khinjuk, and P. atlantica grow in Iran. Although Wild P. vera has spread to a territory of around 75,000 ha, in focal Asia, which envelopes Turk menistan, Afghanistan, and Northeast Iran, where P. vera devel- ops in the Sarakhs region, covering around 17,500 ha (Behboodi 2003). Numerous studies have addressed genetic variability in Pistacia that were based on evalu- ation of morphological, physiological, and biochemical characteristics (Zohary 1952; Barone et al. 1993; Dollo 1993; Tayefeh Aliakbarkhany et al. 2013). Among them, RAPD (Williams et al. 1990) has been the most commonly used method in pistachio cultivars characterization (Hormaza et al. 1994, 1998; Kafkas et al. 2002; Katsiotis et al. 2003; Golan-Gpldhirsh et al. 2004; Mirzaei et al. 2005). AFLP and SSR techniques have been also used in pistachio to study genetic rela- tionship among Pistacia species and cultivars (Golan- Goldhirsh et al. 2004; Katsiotis et al. 2003; Ibrahim Basha et al. 2007; Ahmad et al. 2003; Ahmad et al. 2005; Ahmadi Afzadi et al. 2007). Although previous studies have partially character- ized pistachio diversity in Iran, they did not conduct a full analysis regarding discrimination of wild Pistacia and its potential breeding and implication of its con- servation. Induction of diversity in Pistacia species are based on morphological characteristics which usually can be achieved by budding or grafting selected scions onto seedling rootstocks of the same species or other Pistacia species. Pistacia species have a high genetic diversity due to their dioecious character, pollination mechanism. Because of these factors high selectivity in rootstocks breeding is required, and therefore knowl- edge of the genetic relationships among Pistacia species would be very useful in pistachio rootstock breeding. With the progress in plant molecular biology, numer- ous molecular marker techniques have been developed and used widely in evaluating genetic diversity, population structure and phylogenetic relationships. In recent years, advances in genomic tools provide a wide range of new marker techniques such as, functional and genetargeted markers as well as develop many novel DNAbased marker systems (Collard and Mackill 2009). Start codon targeted (SCoT) polymorphism is one of the novel, simple and reli- able gene-targeted marker systems. This molecular marker offers a simple DNA-based marker alternative and repro- ducible technique which is based on the short conserved region in the plant genes surrounding the ATG (Collard and Mackill 2009) translation start codon. This technique involves a polymerase chain reaction (PCR) based DNA marker with many advantages such as low-cost, high poly- morphism and extensive genetic information (Collard and Mackill 2009; Wu et al. 2013; Luo et al. 2011). The SCoT system has been successfully used to assess genetic diver- sity, carry out structure analysis, identify cultivars, map quantitative trait loci (QTL), as well as perform DNA fin- gerprinting and diagnosis in different species (Elshibli and Korpelainen 2008; Rhouma et al. 2009). The present study is the first attempt to use SCoT markers to assess the level of genetic diversity of Irain- ian pistachio cultivars which were collected from the wild populations. The main objectives of this study were to assess the genetic diversity and genetic relationship of pistachio cultivars in Iran. These results could benefit Irainian pistachio germplasm collection, conservation and future breeding. MATERIALS AND METHODS Plant materials Thirty specimens belonging to three geographical populations of Pistacia vera were collected from different localities that were placed between three provinces Sem- nan, Damghan, Khorasan, Mashhad and Kerman, Raf- sanjan. Details of geographical populations are given in Table 1, Fig. 1. Different references were used for the cor- rect identification of species Pistacia vera (Zohary 1952; Barone et al. 1993; Dollo 1993). Vouchers were deposited 67Genome survey of pistachio (Pistacia vera L.) accessions revealed by Start Codon Targeted (SCoT) markers at the herbarium of Islamic Azad University, Science and Research Branch, Tehran, Iran (IAUH). DNA extraction and SCoT-PCR amplification Fresh leaves were used randomly from four to elev- en plants in each of the studied populations. These were dried by silica gel powder. CTAB activated charcoal protocol was used to extract genomic DNA (Esfandani- Bozchaloyi et al. 2019). The quality of extracted DNA was examined by running on 0.8% agarose gel. A total of 25 SCoT primers developed by Collard and Mackill (2009), 10 primers with clear, enlarged, and rich poly- morphism bands were chosen (Table 2). PCR reactions 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 thermal program was carried out with an initial denaturation for 1 min at 94°C, followed by 40 cycles in three segments: 35 s at 95°C, 40s at 55°C and 55s at 72°C. Final extension was performed at 72°C for 5 min. The amplification products were observed by running on 1% agarose gel, followed by the ethidium bromide staining. The fragment size was estimated by using a 100 bp molecular size ladder (Fermentas, Germany). DATA ANALYSES Morphological studies In total nineteen morphological (nineteen quanti- tative) characters were studied. Four to twelve samples Table 1. List of pistachio cultivars examined for genetic relatedness using SCoT marker system in this study.by Majid Khayatnezhad. No Genotypes Locality Latitude Longitude 1 Sarakhs Khorasan, Mashhad 36.321247 59.532639 2 Ebrahimi Khorasan, Mashhad 36.321247 59.532639 3 Karimi Khorasan, Mashhad 36.321247 59.532639 4 Aliabadi Khorasan, Mashhad 36.321247 59.532639 5 Kaleghochi (Pust Sefid) Semnan, Damghan 36°9'52.6824' 54°21'27.52 6 Shahpasand (Pust Sefid) Semnan, Damghan 36°9'52.6824' 54°21'27.52 7 Akbari (Pust Ghermez) Semnan, Damghan 36°9'52.6824' 54°21'27.52 8 Khanjari Damghan Semnan, Damghan 36°9'52.6824' 54°21'27.52 9 Kaleghochi (Pust Ghermez) Semnan, Damghan 36°9'52.6824' 54°21'27.52 10 Shahpasand (Pust Ghermez) Semnan, Damghan 36°9'52.6824' 54°21'27.52 11 Fakhri Semnan, Damghan 36°9'52.6824' 54°21'27.52 12 Akbari (Pust Sefid) Semnan, Damghan 36°9'52.6824' 54°21'27.52 13 Abbas-Ali Semnan, Damghan 36°9'52.6824' 54°21'27.52 14 Ahmad Agaei Semnan, Damghan 36°9'52.6824' 54°21'27.52 15 Menghar Kalaghi Semnan, Damghan 36°9'52.6824' 54°21'27.52 16 Pust Khormaei Kerman, Rafsanjan 30.3548893 56.002705 17 Ghazvini Kerman, Rafsanjan 30.3548893 56.002705 18 Fandoghi Kerman, Rafsanjan 30.3548893 56.002705 19 Javad Aghaei Kerman, Rafsanjan 30.3548893 56.002705 20 Badami Dishkalaghi Kerman, Rafsanjan 30.3548893 56.002705 21 Vahedi 30.3548893 56.002705 22 Behesht Abadi Kerman, Rafsanjan 30.3548893 56.002705 23 Hasan Zadeh Kerman, Rafsanjan 30.3548893 56.002705 24 Gholamrezaei Kerman, Rafsanjan 30.3548893 56.002705 25 Ohadi Kerman, Rafsanjan 30.3548893 56.002705 26 Saiffodini Kerman, Rafsanjan 30.3548893 56.002705 27 Ghafori Rafsanjan Kerman, Rafsanjan 30.3548893 56.002705 28 Ravare Kerman, Rafsanjan 30.3548893 56.002705 29 Italiaei Kerman, Rafsanjan 30.3548893 56.002705 30 Shasti Kerman, Rafsanjan 30.3548893 56.002705 68 Tinglu Liu et al. from each population were randomly studied for mor- phological analyses (Appendix 1). Morphological char- acters were first standardized (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) and Ward (Minimum spherical characters) as well as ordination methods of MDS (Multidimensional scaling) were used (Podani 2000). PAST version 2.17 (Hammer et al. 2012) was used for multivariate statistical analyses of morphological data. Molecular analyses Excel 2013 was used to calculate the total num- ber of bands (TNB), the number of polymorphic bands (NPB), and the percentage of polymorphic bands (PPB). The polymorphism information content (PIC) of SCoT primers was determined using POWERMARKER v3.25. Binary characters (presence = 1, absence = 0) were used to encode SCoT bands and used for further analyses. Parameter like Nei’s gene diversity (H), Shannon infor- mation index (I), number of effective alleles, and per- centage of polymorphism (P% = number of polymorphic loci/number of total loci) were determined (Weising et al. 2005; Freeland et al. 2011). Shannon’s index was calculated by the formula: H’ = -Σpiln pi. Rp is defined per primer as: Rp = ∑ Ib, were “Ib” is the band informativeness, that takes the values of 1-(2x [0.5-p]), being “p” the proportion of each genotype containing the band. The percentage of polymorphic loci, the mean loci by accession and by population, UHe, H’ and PCA were calculated by GenAlEx 6.4 software (Peakall and Smouse 2006) Nei’s genetic distance among populations was used for Neighbor Joining (NJ) clustering and Neighbor-Net networking (Freeland et al. 2011; Huson and Bryant 2006). The comparison of genetic divergence or genetic distances, estimated by pairwise FST and related statis- tics, with geographical distances by Mantel test is one of the most popular approaches to evaluate spatial pro- cesses driving population structure. The Mantel test was performed as implemented in PAST ver. 2.17 (Hammer et al. 2012). For this, Nei genetic distance was deter- mined for scot data, while Geographic distance of PAST was determined for geographical data. It is calculated based on the sum of the paired differences among both longitude as well as latitude coordinates of the stud- ied populations. The Mantel test, as originally formu- lated in 1967, is given by where gij and dij are, respectively, the genetic and geographic distances between populations i and j, considering n populations. Because Zm is given by the sum of products of distances its value depends on how many populations are studied, as well as the magnitude of their distances. 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 and 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). To assess the population structure of the pistachio genotypes, a heuristic method based on Bayesian clus- tering algorithms were utilized. The clustering method based on the Bayesian-model implemented in the soft- ware program STRUCTURE (Pritchard et al. 2000; Falush et al. 2007) was used on the same data set to better detect population substructures. This clustering method is based on an algorithm that assigns genotypes to homogeneous groups, given a number of clusters (K) and assuming Hardy-Weinberg and linkage equilibrium within clusters, the software estimates allele frequencies in each cluster and population memberships for every individual (Pritchard et al. 2000). The number of poten- tial subpopulations varied from two to ten, and their contribution to the genotypes of the accessions was cal- culated based on 50,000 iteration burn-ins and 100,000 iteration sampling periods. The most probable number Figure 1. Map of Iran shows the collection sites and provinces where of Pistacia vera species were obtained for this study. 69Genome survey of pistachio (Pistacia vera L.) accessions revealed by Start Codon Targeted (SCoT) markers (K) of subpopulations was identified following Evanno et al. (2005). In K-Means clustering, two summary sta- tistics, pseudo-F, and Bayesian Information Criterion (BIC), provide the best fit for k (Meirmans 2012). Gene flow (Nm) which were calculated using POPGENE (ver- sion 1.31) program (Yeh et al. 1999). Gene flow was esti- mated indirectly using the formula: Nm = 0.25(1 - FST)/ FST. In order to test for a correlation between pair-wise genetic distances (FST) and geographical distances (in km) between populations, a Mantel test was performed using Tools for Population Genetic Analysis (TFP- GA; Miller 1997) (computing 999 permutations). This approach considers equal amount of gene flow among all populations. RESULTS SCoT polymorphisms Twenty-five SCoT primers were tested with four of Pistacia vera cultivars as DNA templates; all prim- ers produced amplification products, and only prim- ers showing clear and reproducible band patterns were selected for further analysis. The size of the amplified fragments ranged from 100 to 2500 bp (Fig. 2). Ten primers were then chosen for the genotypes identifica- tion and phylogenetic analysis. As shown in Table 2, all 10 primers used for SCoT analysis. A total of 155 frag- ments were obtained, and 143 of the fragments were polymorphic. The number of polymorphic fragments for each SCoT primer ranged from 8 (ST3) to 25 (ST14), with an average of 12. The percentage of polymorphic fragments was from 84.57% to 100.00%, with an average of 94.55% polymorphism. Polymorphism information content (PIC) values were 0.22 to 0.59, with an average of 0.41. The number of different alleles was 0.43 at the species (Table 3). These results indicated that a high level of polymorphism could be detected among Pistacia vera cultivars using SCoT markers. Populations, genetic diversity Genetic diversity parameters determined in three geographical populations of Pistacia vera are presented in Table 3. The percentage of polymorphic loci (P) and Nei’s gene diversity (H) were important parameters for measuring the level of genetic diversity. In Table 3, the genetic diversity parameters of the 30 Pistacia vera cul- tivars are shown. The highest value of percentage poly- morphism (61.99%) was observed in Ghafori Rafsanjan (cultivars No.27) which shows high value for gene diver- sity (0.42) and Shanon, information index (0.39). Geno- type Shahpasand (Pust Ghermez) (No.10) has the low- est value for percentage of polymorphism (20%) and the lowest value for Shanon, information index (0.15), and He (0.010). Population genetic differentiation AMOVA (PhiPT = 0.29, P = 0.010), revealed signifi- cant difference among the studied genotypes (Table 4, Fig. 3). It also revealed that, 23% of total genetic variabil- ity was due to within genotypes diversity and 55% was due to among genotypes genetic differentiation. Moreover, pair-wise AMOVA revealed significant genetic difference almost among all the studied geno- types. These results indicate that of pistachio geno- types are genetically differentiated and we can use such genetic difference in future breeding programs of this Figure 2. Electrophoresis gel of Pistacia vera species from DNA fragments produced by SCoT-11 molecular markers, (Population numbers are according to Table 1). 70 Tinglu Liu et al. Table 2. SCoT primers used for this study and the extent of polymorphism. TNP: total number of bands; NPB: number of polymorphic bands; PPB: percentage of polymorphic bands; PIC: polymorphism information content. Primer name Primer sequence (5’-3’) TNB NPB PPB PIC SCoT-1 CAACAATGGCTACCACCA 13 13 100.00% 0.55 SCoT-3 CAACAATGGCTACCACCG 9 8 86.99% 0.43 SCoT-6 CAACAATGGCTACCACGC 19 19 100.00% 0.34 SCoT-11 AAGCAATGGCTACCACCA 17 16 94.33% 0.47 SCoT-14 ACGACATGGCGACCACGC 25 25 100.00% 0.35 SCoT-15 ACGACATGGCGACCGCGA 14 12 94.74% 0.59 SCoT-16 CCATGGCTACCACCGGCC 15 12 92.31% 0.49 SCoT-17 CATGGCTACCACCGGCCC 10 10 100.00% 0.22 SCoT-18 ACCATGGCTACCACCGCG 12 10 84.57% 0.50 SCoT-19 GCAACAATGGCTACCACC 24 24 100.00% 0.37 Mean 16 12 94.55% 0.41 Total 155 143 Table 3. Genetic diversity parameters in the studied populations of pistachio cultivars (N = number of samples, Na = Number of different alleles, Ne = number of effective alleles, I= Shannon’s information index, He = genetic diversity, UHe = unbiased gene diversity, P%= per- centage of polymorphism, populations). Code genotypes N Na Ne I He UHe %P Sarakhs 5.000 0.555 1.020 0.22 0.25 0.28 43.53% Ebrahimi 8.000 0.431 1.088 0.20 0.22 0.25 49.53% Karimi 8.000 0.255 1.021 0.25 0.28 0.22 37.15% Aliabadi 5.000 0.261 1.024 0.292 0.23 0.23 53.15% Kaleghochi (Pust Sefid) 5.000 0.886 1.183 0.184 0.116 0.122 24.29% Shahpasand (Pust Sefid) 8.000 0.686 1.157 0.30 0.11 0.22 39.43% Akbari (Pust Ghermez) 4.000 0.344 1.042 0.28 0.23 0.20 33.53% Khanjari Damghan 5.000 0.455 1.077 0.277 0.24 0.22 53.05% Kaleghochi (Pust Ghermez) 3.000 0.255 1.021 0.15 0.18 0.19 48.45% Shahpasand (Pust Ghermez) 3.000 0.643 1.173 0.154 0.010 0.010 20.00% Fakhri 8.000 0.431 1.088 0.20 0.22 0.25 49.53% Akbari (Pust Sefid) 9.000 0.255 1.021 0.25 0.28 0.22 37.15% Abbas-Ali 6.000 0.261 1.024 0.292 0.23 0.23 40.15% Ahmad Agaei 10.000 0.287 1.253 0.266 0.254 0.28 50.99% Menghar Kalaghi 5.000 0.358 1.430 0.28 0.20 0.29 23.50% Pust Khormaei 6.000 0.299 1.029 0.231 0.28 0.23 24.38% Ghazvini 5.000 0.462 1.095 0.288 0.29 0.22 22.05% Fandoghi 8.000 0.399 1.167 0.24 0.21 0.213 32.88% Javad Aghaei 5.000 0.336 1.034 0.23 0.25 0.29 41.83% Badami Dishkalaghi 4.000 0.344 1.042 0.28 0.23 0.20 57.53% Vahedi 5.000 0.455 1.077 0.277 0.24 0.22 55.05% Behesht Abadi 3.000 0.255 1.021 0.15 0.18 0.19 38.45% Hasan Zadeh 3.000 0.643 1.173 0.154 0.102 0.109 30.00% Gholamrezaei 8.000 0.431 1.088 0.20 0.32 0.25 41.53% Ohadi 9.000 0.255 1.021 0.25 0.28 0.22 27.15% Saiffodini 6.000 0.261 1.024 0.292 0.23 0.23 43.15% Ghafori Rafsanjan 10.000 0.287 1.253 0.396 0.424 0.44 61.99% Ravare 3.000 0.567 1.062 0.24 0.224 0.213 34.73% Italiaei 3.000 0.499 1.067 0.24 0.281 0.24 49.26% Shasti 9.000 0.352 1.083 0.23 0.22 0.24 45.05% 71Genome survey of pistachio (Pistacia vera L.) accessions revealed by Start Codon Targeted (SCoT) markers valuable plant species. The results of this study showed that there is a relatively low level of genetic diversity in the studied samples which are expected in view of the dioecius and outbreeding nature of the cultivated pista- chio cultivars and high level of heterozygosity due to the cross-pollinating nature of the plant established during the evolution and domestication processes which have been conserved by the propagation of clones through vegetative reproduction. The pairwise comparisons of ‘Nei genetic identity’ among the studied populations of Pistacia vera (Table not included) have shown a higher a genetic similar- ity (0.887) between populations Menghar Kalaghi (prov- ince Semnan) and Kaleghochi (Pust Ghermez) (prov- ince Semnan), while the lowest genetic similarity value (0.667) occurs between Akbari (Pust Ghermez) (prov- ince Semnan) and Badami Dishkalaghi (province Ker- man). Populations, genetic affinity NJ tree and Neighbor-Net network produced simi- lar results therefore only NJ tree is presented and dis- cussed (Fig. 4). This result show that molecular charac- ters studied can delimit Pistacia vera genotypes in two different major clusters or groups. In general, two major clusters were formed in NJ tree (Fig. 3), four genotypes of cultivars Sarakhs, Ebrahimi, Karimi and Aliabadi formed a single cluster, and these genotypes were all from Khorasan, Mashhad province. Cluster II contained two sub-clusters, and most of individuals Kaleghochi (Pust Sefid); Shahpasand (Pust Sefid); Akbari (Pust Ghermez); Khanjari Damghan and Kaleghochi (Pust Ghermez), Shahpasand (Pust Ghermez); Fakhri; Akbari (Pust Sefid); Abbas-Ali and Ahmad Agaei (Semnan Province) formed cluster II. There were 26 individuals in this cluster. Besides, principal coordinate analysis (PCoA) was performed to visualize the association among the geno- types in more detail. The PCoA results showed that the first three principal coordinates account for 64.88% of the total variation (not shown). Based on the results of PCoA analysis, cultivars Sarakhs, Ebrahimi, Karimi and Aliabadi genotype showed the highest dissimilarity with other genotypes. Additionally, the results from Bayesian clustering analysis using STRUCTURE software (Fig. 4) confirmed the groupings we observed in NJ and PCoA clusterings. Table 4. Analysis of molecular variance (AMOVA) of the studied species. Source Df SS MS Est. Var % Among Regions 12 39.211 23.648 0.266 19% Among Pops 15 96.822 18.802 0.114 55% Among Indiv 57 64.553 21.130 0.283 20% Within Indiv 71 15.500 0.284 0.204 8% Total 141 215.007 1.678 100% df: degree of freedom; SS: sum of squared observations; MS: mean of squared observations; EV: estimated variance. Figure 3. AMOVA test of the studied populations. Figure 4. NJ tree of populations in Pistacia vera based on SCoT molecular markers. 72 Tinglu Liu et al. Th e present study indicated that a higher genetic diversity was found in the older genotypes. Th is fact con- fi rms our speculation that pistachio cultivations have increasingly led to the reduction of their genetic variation due to deployment of improved cultivars and to the avail- ability of private or public graft ed seedling nurseries for pistachio, as well as the changing livelihood conditions. Recently, the method of pistachio cultivation is chang- ing leading towards an increased reduction of crop diver- sity deployed on farm. In the past, pistachio diversity was maintained high in the fi eld through a number of culti- vation practices, s. a. use of male varieties derived from seed, use of wild Pistacia species to boost pollination and hence the fruit setting, use of natural populations of wild Pistacia (P. atlantica) as a rootstock due to their well- known resistance to stony and calcareous soils. Th is is in agreement with AMOVA and genetic diver- sity parameters presented before. Mantel test aft er 5000 permutations produced signifi cant correlation between genetic distance and geographical distance in these pop- ulations (r = 0.87, P = 0.001). Th erefore, the populations that are geographically more distant have less amount of gene fl ow, and we have isolation by distance (IBD) in Pistacia vera genotypes. Th e most popular approaches for estimating divergence include calculation of genetic distances and variance partitioning among and within populations using Wright’s FST and other related statis- tics, such as GST, AST, RST, θST and ΦST. For instance, the FST gives an estimate of the balance of genetic variability among and within populations, and is an unbiased esti- mator of divergence between pairs of populations under an island-model in which all populations diverged at the same time and are linked by approximately similar migration rates. However, migration rates usually vary proportionally with geographical distances, so that pair- wise FST estimates between pairs of populations vary. Th erefore, the populations that are geographically more distant have less amount of gene fl ow, and we have isola- tion by distance (IBD) in Pistacia vera genotypes. Populations genetic structure Th e number of genetic groups was determined by two methods of 1—K-Means clustering which is based on the maximum likelihood approach, and 2—Evanno test which is based on STRUCTURE analysis and is a Bayesian approach based method. K-Means clustering based on pseudo-F and BIC (Bayesian Information Cri- terion) recognized 3 and 5 genetic groups, respectively. Th is is in agreement with AMOVA result, showing sig- nifi cant genetic diff erence among date populations of Pistacia vera genotypes. Evan test based on delta k (Fig. 5) identifi ed the opti- mum number of genetic groups 3. We performed STRUC- TURE analysis based on k = 3, to identify the genetic groups (Fig. 6). In the plot of k = 3, the cultivars Sarakhs, Ebrahimi, Karimi and Aliabadi (red colored) are placed in the fi rst genetic group, while the populations of Kaleg- hochi (Pust Sefi d); Shahpasand (Pust Sefi d); Akbari (Pust Ghermez); Khanjari Damghan and Kaleghochi (Pust Ghermez), Shahpasand (Pust Ghermez); Fakhri; Akbari (Pust Sefi d); Abbas-Ali and Ahmad Agaei (Semnan Prov- ince) (blue colored) formed the second genetic group and fi nally the populations of Kerman province (green color- ed) formed the third genetic group. Th ese diff erent genetic groups may be used in future breeding and hybridization programs of Iranian date Pistacia vera genotypes. Th e mean Nm = 0.65 was obtained for all SCoT loci, which indicates low amount of gene fl ow among the populations and supports genetic stratifi cation as indicated by K-Means and STRUCTURE analyses. Th is result is in agree with grouping we obtained with PCA plot, as these populations were placed close to each oth- er. As evidenced by STRUCTURE plot based on admix- ture model, these shared alleles comprise very limited part of the genomes in these populations and all these results are in agreement in showing high degree of genetic stratifi cation within of Pistacia vera genotypes. Morphometric analyses In present study we used 30 plant accessions (six to fourteen samples from each populations) belonging to four diff erent populations. In order to determine the most Figure 5. Delta k plot of Evanno’s test based on STRUCTURE anal- ysis. 73Genome survey of pistachio (Pistacia vera L.) accessions revealed by Start Codon Targeted (SCoT) markers variable characters among the taxa studied, PCA analysis has been performed (Fig. 6). It revealed that the first three factors comprised over 73% of the total variation. In the first PCA axis with 40% of total variation, such charac- ters as length of leaves; width of leaves; length of petioles; length of the terminal leaf; width of the terminal leaf; length of inflorescence have shown the highest correlation (> 0.7), fruit length; fruit width; fruit thickness; number of fruit per inflorescence; kernel infestation were charac- ters 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. 6). The result showed morphological difference/ divergence among most of the studied populations. This morphological dif- ference was due to quantitative characters only. DISCUSSION The coupling of ecological and genetic data will pro- vide the most suitable background for preserving the ability of the biota to respond the rapid environmental changes ((Sawadogo et al. 2021; Paul et al. 2021)). The literature reports the following basic factors influenc- ing the distribution of genetic variation: habitat specify, plant-insect interactions, connectivity and disturbance, dispersal ability, species lifespan, reproductive rates Fig. 6. Top: STRUCTURE plot of Pistacia vera populations based on k = 3, Numbers are according to Table 1.Bottom: PCA plot of Pistacia vera populations based on morphological characters. Numbers are according to Table 1. 74 Tinglu Liu et al. and existing genetic diversity (Esfandani–Bozchaloyi, et al. 2018a, 2018b, 2018c, 2018d). Genetic diversity when analysed by neutral markers does not correspond to the adaptive ability of plant populations, but these types of markers are very useful for the interpretation of the past landscapes, refugia and gene flow (Wankiti et al. 2021; Lucena et al. 2021). That is, why the selected genes or markers of active parts of plant genomes are used to interprete the plant genome response to the changes to the local climate and environment. Molecular-based population genetic data are very useful for determin- ing the ecological and habitat events in the past and for detection of patterns of the recent genetic divergence. This can be achieved using different types DNA mark- ers. SCoT markers are novel molecular markers that target the translation initiation site and preferentially bind to genes that are actively transcribed. These prim- ers have been shown to exhibit relatively high levels of polymorphism (Collard and Mackill 2009). It was more informative than IRAP and ISSR for the assessment of diversity of plants (Collard and Mackill 2009). Pistachio has important socio-economic and ecologi- cal impacts in the arid and semi-arid agricultural regions of Iran (Kafkas et al. 2006). In addition, Iran hosts a wide genetic diversity of Pistacia spp. and more than 300 pis- tachio genotypes have been collected across the country. Iran therefore possesses valuable germplasm for pista- chio improvement and conservation programs. Assess- ing genetic diversity and relationships among cultivars of Iranian pistachio, using discriminative and robust mark- ers, is therefore important (Mirzaei et al. 2005). In the present work, 30 P. vera cultivars were char- acterized with 10 SCoT markers. The results confirm the efficiency of microsatellite markers for fingerprinting purposes. Our results demonstrated that the Polymor- phism information content (PIC) ranged from 0.22 to 0.59 with an average value of 0.41, while the percentage of polymorphism (P%) ranged from 0.20 to 0.61 with an average value of 0.42 and also the expected heterozy- gosity (He) varied from 0.011 to 0.42 with an average of 0.20.These values were higher than those reported by Arabnejad et al. (2008), who detected an average of 3.69 alleles per primer pairs and an average PIC of 0.46 detected in 20 commercial cultivars of Iranian pistachio; and also higher than those reported by Baghizadeh et al. (2010) (an average of 2.75 alleles per primer pairs and an average of 0.44 for detected in 31 Iranian pistachio cul- tivars) and by Ahmad et al. (2005) (an average of 3.30 alleles per locus in 17 pistachio cultivars). Kolahi-Zonoo- zi (2014) assessed genetic diversity of 45 commercially Iranian cultivars using 12 nSSR markers and detected that PIC varied from 0.19–0.56 with an average of 0.33 and the mean of Ho and He were 0.49 and 0.35, respec- tively. Mirzaei et al. (2005) reported 80.00%polymor- phism among 22 Iranian pistachio cultivars and wild pistachio species. In a study reported by Golan- Gol- dhirsh et al. (2004) in assessing polymorphisms among 28 Mediterranean pistachio accessions, 27 selected prim- ers produced 259 total bands (an average of 9.59). Some cultivars in different locations have the same name and some morphological identity, while molecular results showed differences between them. For instance, Badami-Zarand cultivar was differentiated from Bada- mi- Kaj and Badami-Zoodras. Also, Ghazvini-Zodras showed differences with Ghazvini. These differentiations can be due to the intrinsic nature of nSSRs, since it is very unlikely that the microsatellites amplified corre- spond to the mutated DNA region when they have been randomly isolated from the whole genome. The results from this study showed that the studied cultivars had high genetic variation due to the species’ dioeciously and cross-pollination nature (Ahmad et al. 2005). CONCLUSION: This study was aimed at evaluating the genetic diver- sity of Iranian pistachio in order to aid the conservation of its germplasm. 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