Genetic Relationships Among Ecotypes of Suaeda vermiculata in Saline Environments of Khuzestan Province (Iran) Using Multi-Marker Approaches

Suaeda vermiculata Forssk. ex J.F.Gmel., a halophytic species from the Amaranthaceae family (formerly Chenopodiaceae), is recognized as the accepted name in the Flora of Iran, with S. fruticosa Forssk. ex J.F.Gmel. treated as its synonym (Assadi, 2001). This species is naturally distributed across arid and semi-arid regions of the Middle East and North Africa, including Afghanistan, Pakistan, Iraq, Jordan, Palestine, Saudi Arabia, and Egypt (Assadi, 2001; Dinarvand, 2020). In Iran, it is predominantly found in southern provinces, particularly Khuzestan, where it inhabits saline flats, marshes, and roadsides (Akhani, 2015). S. vermiculata demonstrates exceptional tolerance to abiotic stresses, especially salinity, making it a valuable component of salt-affected ecosystems. Its ecological functions include soil stabilization, phytoremediation, and habitat restoration (Al-Shamsi et al., 2020). Moreover, its seeds are rich in unsaturated fatty acids, underscoring their potential as an alternative source of edible oil (Weber et al., 2007; Mahdavi Lasini et al., 2017). Recent investigations in Iran have further revealed that the seeds contain considerable amounts of both saturated fatty acids, predominantly margaric acid, and unsaturated fatty acids, mainly linoleic acid (Assadi et al., 2014).

Assessing genetic diversity is crucial for understanding plant adaptation mechanisms and guiding conservation efforts. Advances in molecular marker technologies, particularly PCR-based methods, have significantly improved the resolution of genetic diversity analysis (Bidyananda et al., 2024). Among these, inter-simple sequence repeat (ISSR) and start codon targeted (SCoT) markers are frequently used due to their technical simplicity, high reproducibility, and effectiveness in detecting polymorphisms. Both ISSR and SCoT are dominant, multilocus markers scored by the presence or absence of amplification products. They require no prior sequence information and have been applied across a wide range of plant taxa to evaluate population variability and ecological differentiation (Amom et al., 2020; Hromadová et al., 2023). By targeting inter-microsatellite regions (ISSR) and conserved ATG-flanking regions (SCoT), these complementary markers provide robust tools for examining genome-wide polymorphism and fine-scale genetic structuring in stressful environments such as saline habitats. Several studies highlight the utility of these markers in Suaeda and related halophytes. For instance, SCoT has revealed population structure in S. maritima (L.) Dumort. (Jayasundara et al., 2024) and high within-population variability in S. aegyptiaca (Hasselq.) Zohary from Khuzestan (Haghighipor et al., 2024). ISSR has facilitated comparative analyses of Suaeda species in the western Anbar plateau, Iraq (Alrawi et al., 2023), while combined ISSR/SCoT approaches have captured extensive polymorphism among 29 wild halophytes in Saudi Arabia (Alotaibi & Abd-Elgawad, 2022). Moreover, genetic studies on Suaeda species from the Mediterranean coast of Egypt confirmed high levels of polymorphism using ISSR markers (Abd El-Maboud & Khalil, 2013). Collectively, these findings substantiate the informativeness of ISSR and SCoT for quantifying genetic variability and geographic structuring in salt-affected ecosystems, thereby providing a comparative framework for the present investigation. Building on this evidence, it is notable that, despite the ecological significance of S. vermiculata in Iran’s saline landscapes, particularly in Khuzestan Province, no molecular study has been conducted on this species in the country to date. Given its remarkable adaptability and combined ecological and economic value, an analysis of its genetic makeup can provide valuable insights into local variation, support conservation efforts, and inform sustainable use.

Materials and Methods

Sample collection and DNA extraction

A total of 52 ecotypes of S. vermiculata were collected from diverse saline habitats across Khuzestan Province, Iran. Species identification was confirmed based on morphological characteristics using the Flora of Iran (Assadi, 2001) and the Flora of Khuzestan (Mozaffarian, 1999; Dinarvand, 2020). All specimens were properly documented and preserved in silica gel. From these, 27 ecotypes were selected based on ecological conditions and DNA quality/quantity. They were grouped according to geographic origin, with 19 from northern and 8 from southern Khuzestan (Table 1), reflecting differences in site accessibility. Genomic DNA was extracted from young shoots using a commercial kit (Parstous, Iran) following the manufacturer’s instructions. DNA quality, quantity, and integrity were assessed by 1% agarose gel electrophoresis, while purity was measured using a NanoDrop spectrophotometer (model ND-2000, Thermo Fisher Scientific) by determining the OD 260/280 ratio.

Table 1. Geographic coordinates of the 27 Suaeda vermiculata ecotypes collected from Khuzestan Province, Iran

PCR amplification

Twelve ISSR primers previously reported in different plant studies (Behera et al., 2008; Badlani, 2011; Kumar & Rajvanshi, 2015; Sharma et al., 2015; Rezaei et al., 2018) and six SCoT primers designed by Collard & Mackill (2009) were selected for the present analysis (Table 2). PCR reactions were performed in a 10 μL final volume containing 5 μL of 2X PCR Master Mix RED (Ampliqon), 0.8 μL of template DNA (35–50 ng), 0.3 μL of primer (10 pmol μL⁻¹), and ddH₂O up to 10 μL. Optimal annealing temperatures for each primer were determined using a gradient thermal cycler, and the final thermal cycling conditions are listed in Table 3. PCR products were separated on 1.5% agarose gels, stained, and visualized under UV light.

Table 2. Sequences and characteristics of ISSR and SCoT primers used in this study

Table 3. Thermal cycling conditions for PCR amplification using ISSR and SCoT markers

Data scoring and statistical analyses

Band scoring was performed in a binary format by recording the presence (1) or absence (0) of each band across the ecotypes. For subsequent analyses, ecotypes were classified into two regional groups representing northern and southern Khuzestan to facilitate regional comparisons of genetic diversity and structure. Polymorphism parameters, including the total number and percentage of polymorphic bands (P%), resolving power (Rp) (Prevost & Wilkinson, 1999), polymorphism information content (PIC) (Roldan-Ruiz et al., 2000), effective multiplex ratio (EMR), and marker index (MI) (Nagaraju et al., 2001), were calculated according to standard formulas. Additional genetic diversity indices, such as the observed number of alleles (Na), effective number of alleles (Ne), Nei’s gene diversity (h), Shannon’s information index (I), and the percentage of polymorphic loci (PL%) within each regional group, were calculated using GenAlEx v6.5 (Peakall & Smouse, 2012). Genetic similarity among 27 S. vermiculata ecotypes was estimated using the Jaccard coefficient, which is appropriate for presence/absence binary data. Multivariate genetic relationships were examined through UPGMA cluster analysis in NTSYS-pc v2.2 (Rohlf, 2005) and principal coordinates analysis (PCoA) implemented in GenAlEx v6.5 (Peakall & Smouse, 2012). Genetic structure was assessed using STRUCTURE v2.3.4 (Pritchard et al., 2000) under the admixture model with correlated allele frequencies and assuming a recessive alleles model appropriate for dominant markers (ISSR and SCoT). Analyses were conducted for K values ranging from 1 to 10, with ten independent runs per K. Each run consisted of a burn-in period of 10,000 iterations followed by 100,000 Markov Chain Monte Carlo (MCMC) repetitions. The most likely number of clusters (K) was determined using the ΔK method (Evanno et al., 2005). Run outputs were summarized and visualized using StructureSelector (Li & Liu, 2018). Both separate and combined datasets were analyzed using UPGMA, PCoA, and STRUCTURE to provide a comprehensive assessment of genetic relationships among ecotypes. Analysis of molecular variance (AMOVA) was performed in GenAlEx v6.5 (Peakall & Smouse, 2012) to partition genetic variation within and between northern and southern ecotype groups. Separate analyses were conducted for ISSR and SCoT datasets. Variance components and PhiPT (ΦPT) values were calculated, and statistical significance was assessed using 999 permutations.

Results

Primer performance and polymorphism assessment

Out of twelve tested ISSR primers, ten yielded clear and reproducible bands, while ISSR2 and ISSR7 failed to amplify. Among the six SCoT primers, five were successful and reproducible, with SCoT13 not producing any bands. The amplified fragments ranged from 300 to 3000 bp for ISSR primers and 400 to 3000 bp for SCoT primers (Table 4). The ten ISSR primers generated a total of 88 bands, of which 86 (96.6%) were polymorphic. The five successful SCoT primers produced 51 bands, with 43 (79%) being polymorphic. Among SCoT primers, SCoT5 exhibited the highest polymorphism (100%), whereas SCoT26 had the lowest (33%). For ISSR primers, ISSR8 and ISSR10 showed the lowest polymorphism rates (80% and 86%, respectively), while the remaining primers displayed 100% polymorphism. The average polymorphism information content (PIC) was 0.31 for ISSR and 0.28 for SCoT primers. The marker index (MI) averaged 2.95 for ISSR and 2.35 for SCoT primers. The highest MI value was observed for SCoT5 (4.67), and the lowest for SCoT26 (0.09). Resolving power (Rp) varied from 4.48 to 12.29, with mean values of 6.34 for ISSR and 9.92 for SCoT, indicating a generally higher discriminatory capacity of SCoT primers (Table 4).

Table 4. Summary of the performance of ISSR and SCoT primers in Suaeda vermiculata

N: Total number of bands; Np: Polymorphic bands; P%: Percentage of polymorphism; Rp: Resolving power; PIC: Polymorphism information content; MI: Marker index; BZ: Band size (bp)

Intra-regional genetic diversity analysis

The percentage of polymorphic loci (PL%) within the northern ecotype group was 98.86% and 82.35% for ISSR and SCoT markers, respectively. In the southern group, PL% values were 72.73% (ISSR) and 60.78% (SCoT). Nei’s gene diversity (h) values indicated moderate genetic variation within groups, with mean values of 0.25 for ISSR and 0.21 for SCoT markers. Similarly, Shannon’s information index (I) averaged 0.39 for ISSR and 0.33 for SCoT, further supporting the presence of moderate genetic diversity within both regional groups (Table 5).

Table 5. Genetic diversity parameters estimated using ISSR and SCoT markers in Suaeda vermiculata ecotypes from Northern and Southern Khuzestan

Clustering patterns, principal coordinate analysis (PCoA) Bayesian STRUCTURE inference

Because ISSR and SCoT target different genomic regions, the datasets were first analyzed separately, and interpretations of clustering and PCoA were made independently for each marker system. To complement these findings, combined analyses were also performed. Cluster analysis using the UPGMA method based on Jaccard similarity coefficients (Figure 1A–C) revealed considerable genetic variation among the 27 studied ecotypes, with no clear grouping according to geographic origin (Northern Khuzestan vs. Southern Khuzestan). Ecotypes from both regions were intermixed throughout the dendrogram, indicating the absence of distinct regional clusters. A similar pattern was observed in the SCoT-based dendrogram, where northern and southern ecotypes also lacked clear separation. When ISSR and SCoT data were combined, the overall topology remained largely comparable to the single-marker analyses: two small southern subclusters were recovered, yet several southern ecotypes still grouped with northern ones, indicating no pronounced geographic partition.

The PCoA analysis based on ISSR (Figure 2A), SCoT (Figure 2B), and combined datasets (Figure 2C) showed no complete separation between northern and southern groups. In the ISSR dataset, the first two axes explained 19.7% of the total variance (PC1 = 10.63%, PC2 = 9.09%). Northern ecotypes generally clustered toward the right side, and southern ecotypes toward the left, although several northern ecotypes overlapped with the southern group, indicating only partial separation. For SCoT, the first two axes explained 22.3% of the variance (PC1 = 11.79%, PC2 = 10.59%), with some southern ecotypes forming small localized clusters. In the combined dataset, the first two axes accounted for 17.8% of the variance (PC1 = 9.0%, PC2 = 8.8%), where southern ecotypes tended to group more closely but still overlapped with those of the northern ecotypes. Overall, north–south differentiation was weak and relative.

Figure 2. Principal coordinate analysis (PCoA) of 27 ecotypes of Suaeda vermiculata based on (A) ISSR (B) SCoT, and combined ISSR + SCoT (C) datasets. Northern (Group 1) and Southern (Group 2) ecotypes are indicated with different symbols.

Bayesian clustering analysis in STRUCTURE, using the recessive alleles model appropriate for dominant markers, indicated different optimal K values across datasets. For the ISSR dataset, the ΔK method identified K = 5 as the most likely number of clusters. However, the bar plot (Figure 3A) showed that all 27 ecotypes shared membership across all five clusters, revealing extensive admixture and no clear separation between northern and southern groups. For the SCoT dataset, the ΔK method supported K = 2; however, two alternative clustering modes were recovered at equal frequency across runs. Because both modes showed pervasive admixture and no clear geographic correspondence, only one representative bar plot is presented (Figure 3B). When ISSR and SCoT data were combined, the optimal clustering was inferred at K = 6, consistently recovered in all runs (Figure 3C). Yet, each ecotype exhibited contributions from all six clusters, demonstrating widespread admixture and the absence of region-specific structuring. Collectively, these results indicate that S. vermiculata in Khuzestan exhibits a largely panmictic genetic structure, and lacks clear geographic differentiation.

Analysis of molecular variance

Analysis of molecular variance (AMOVA) revealed that most genetic variation occurred within regions (91% for ISSR, 95% for SCoT), whereas only a small proportion was attributable to differences between northern and southern ecotypes (9% and 5%, respectively). Despite this low inter-regional differentiation, both marker systems produced statistically significant PhiPT values (ISSR: 0.093, p = 0.001; SCoT: 0.049, p = 0.019), indicating weak but significant regional structuring (Table 6; Figure 4A–B).

Table 6. Analysis of molecular variance (AMOVA) partitioning genetic variation among and within Northern and Southern ecotype groups of Suaeda vermiculata based on ISSR and SCoT markers.

Figure 4. Analysis of molecular variance (AMOVA) of 27 Suaeda vermiculata ecotypes from Northern and Southern regions of Khuzestan using (A) ISSR and (B) SCoT markers.

Discussion

Marker efficiency and polymorphism

In this study, both ISSR and SCoT markers were effective in detecting genetic polymorphism among S. vermiculata ecotypes. However, their performances differed notably. ISSR primers generally amplified more bands and exhibited higher polymorphism. This reflects their ability to capture genome-wide variability. ISSR targets non-coding, microsatellite-flanking regions, which are often highly variable even among closely related individuals (Zietkiewicz et al., 1994; Bornet & Branchard, 2001). In contrast, SCoT primers generated fewer bands but showed higher values for certain efficiency indices, such as resolving power (Rp) and marker index (MI). Their gene-targeted nature, amplifying regions adjacent to the ATG start codon, may make them more informative for identifying functionally relevant differences among ecotypes. A similar pattern was observed in S. maritima populations in Thailand, where 28 SCoT primers produced 162 distinct bands (140–1200 bp), confirming their efficiency for DNA fingerprinting in halophytes, even when local genetic variation was low (Rittirongsakul et al., 2020). The effectiveness of ISSR markers in assessing genetic variation within Suaeda species has been demonstrated in previous studies. For example, Abd El-Maboud and Khalil (2013) reported a high level of polymorphism (99%) using ISSR primers across three Suaeda species (S. vera Forssk. ex J.F.Gmel., S. pruinosa Lange, and S. vermiculata) collected from diverse habitats along the Mediterranean coast of Egypt. These findings are consistent with our results, which also revealed high polymorphic efficiency and informativeness of ISSR markers in distinguishing among S. vermiculata ecotypes from Khuzestan. Overall, ISSR markers provide a broader view of genomic diversity, while SCoT markers offer finer resolution at the ecotype level, as indicated by minor local clustering observed in the PCoA for the southern ecotypes. Their complementary nature supports the combined use of both marker systems to assess neutral and potentially adaptive variation in halophytes such as S. vermiculata.

Genetic diversity

The analysis of genetic diversity indices based on both ISSR and SCoT markers revealed consistently higher levels of variation in northern ecotypes of S. vermiculata compared with southern ones (Table 5). In particular, the number and percentage of polymorphic loci (NPL and PL%), as well as the observed and effective number of alleles (Na and Ne), were greater in the northern group, indicating richer allelic diversity and lower allele fixation. The elevated Ne/Na ratio in the north further suggests more balanced allele frequencies, consistent with sustained gene flow or historically larger and more connected ecotype assemblages. Nei’s gene diversity (h) and Shannon’s information index (I) also supported this pattern, showing higher values in the northern region for both marker systems. Collectively, these results indicate that ecological heterogeneity and the historical connectivity of northern habitats have promoted the maintenance of a more diverse and genetically stable gene pool compared with the environmentally more fragmented southern habitats. These observations are consistent with recent findings on S. salsa (L.) Pall., where distinct ecotypes adapted to saltmarsh and inland habitats were differentiated not only morphologically and genetically but also in terms of metabolite composition (Wang et al., 2023). Such habitat-driven differentiation highlights the role of environmental heterogeneity as a key evolutionary force shaping allelic richness and intraspecific variation among halophytic taxa. It is noteworthy, however, that the northern group included more sampled ecotypes (19 vs. 8), which may have partially inflated diversity estimates by capturing a broader allelic spectrum. Thus, while higher genetic diversity in the north is evident, part of this trend may be attributed to sampling imbalance. Future studies with more evenly distributed sampling will help refine the understanding of regional diversity patterns.

Genetic structuring and ecotype relationships

The North–South sampling imbalance (19 vs. 8 ecotypes) may have influenced the resolution of genetic patterns. Nevertheless, results from multilocus analyses, including UPGMA, PCoA, and STRUCTURE, consistently indicated extensive admixture and no clear geographic separation between northern and southern ecotypes. STRUCTURE assigned all 27 ecotypes to multiple clusters regardless of K (ISSR, K = 5; SCoT, K = 2; combined, K = 6), demonstrating a largely panmictic genetic organization. In UPGMA and PCoA analyses, a slight tendency for some southern ecotypes to cluster together was observed, particularly with SCoT markers. However, the low percentage of variance explained and the lack of support from STRUCTURE suggest that such clustering does not represent strong or consistent geographic differentiation. Despite habitat differences, gene flow and the retention of shared ancestral polymorphisms appear to maintain high levels of genetic variation within regions. Similar patterns have been reported in other halophytes. As reported by Jena & Das (2006), S. nudiflora (Willd.) Moq. populations maintain high within-population variability despite geographic isolation and distinct cytotypes. This indicates that inter-population divergence can occur alongside high local diversity under heterogeneous conditions. Habitat-driven differentiation may also explain the minor local structuring in S. vermiculata. Environmental selection pressures likely interact with ongoing gene flow to influence the genetic structure of ecotypes. Comparable findings were reported by Prinz et al. (2013) in S. maritima. Inland populations, although fragmented and isolated, still shared alleles with coastal populations. This was interpreted as evidence of occasional gene flow and persistence of ancestral polymorphisms across habitats. Such results support our observation that northern and southern ecotypes of S. vermiculata overlap in both PCoA and STRUCTURE analyses. Overall, weak genetic differentiation between regions appears to be moderated by three main factors: high dispersal capacity, mixed mating systems, and retention of ancestral polymorphisms. Halophyte species often maintain substantial within-group diversity even in fragmented or heterogeneous habitats (Dar et al., 2024). At the same time, localized substructuring can emerge without complete geographic separation, reflecting a balance between gene flow, historical connectivity, and habitat-specific selective pressures. The partial overlap of ecotypes from different regions further suggests ongoing or historical gene flow. Limited seed dispersal, facilitated by the small seed size and lack of specialized structures in S. vermiculata (El-Keblawy et al., 2018), likely suffices to maintain genetic connectivity across regions.

Molecular variance and gene flow

AMOVA results indicate that most genetic variation in S. vermiculata is retained within groups, while differentiation between the northern and southern groups is relatively low. Nevertheless, our analyses detected weak but statistically significant regional structuring (Table 6). The high intra-regional diversity aligns with S. vermiculata’s reproductive biology, which includes partial gynodioecy and notable pollen sterility (Fernández-Illescas et al., 2010). This mixed mating system, combining self-fertilization and outcrossing, influenced by male fertility and environmental factors, likely helps maintain genetic diversity and resilience in fragmented and saline habitats. Such reproductive plasticity is vital under environmental stress, as highlighted by Prinz et al. (2009), and probably contributes to the predominance of within-group genetic variation, a pattern common in long-lived, outcrossing plant species (Nybom, 2004). Comparable patterns have been documented in S. aegyptiaca populations from Khuzestan, where SCoT markers revealed high polymorphism and AMOVA confirmed predominant within-group variation (Haghighipor et al., 2024). These findings underscore a broader ecological and evolutionary strategy among halophytes to sustain genetic diversity through adaptive reproductive and dispersal mechanisms.

Collectively, the molecular variance data provide important insights for conservation management, emphasizing the need to preserve intra-regional genetic variation and the ecological processes sustaining it.

Implications for conservation and genetic resource management

The genetic structure of S. vermiculata ecotypes in Khuzestan, characterized by high intra-regional diversity and weak differentiation between northern and southern groups, carries significant implications for conservation and germplasm management. These results indicate that geographic proximity does not necessarily equate to genetic similarity, highlighting the need to preserve the full spectrum of genetic variation within each region. Conservation strategies should therefore move beyond simple geographic criteria. The selection of ecotypes for ex situ germplasm banks or in situ restoration programs should be informed by molecular genetic data, prioritizing genetically distinct ecotypes identified through clustering and PCoA analyses. This approach ensures comprehensive representation of the species’ genetic resources and enhances adaptive potential amid environmental changes. Moreover, the reproductive plasticity of S. vermiculata, as suggested by previous studies, may confer resilience to habitat fragmentation and salinity stress. Protecting ecotypes from diverse ecological contexts within each region can help conserve not only neutral genetic diversity but also adaptive variation important for long-term survival. Practically, conservation efforts should target several genetically divergent ecotypes from both northern and southern Khuzestan. Such an approach will support sustainable maintenance of S. vermiculata and improve the effectiveness of habitat restoration in saline environments.

Conclusion

This study provides the first comprehensive molecular characterization of genetic diversity and structure in 27 ecotypes of S. vermiculata from northern and southern Khuzestan, based on ISSR and SCoT markers. The complementary use of these marker systems revealed high overall polymorphism and showed weak regional structuring with substantial admixture among ecotypes. The analyses indicated that most genetic variation is distributed within regions rather than between them, highlighting substantial intra-regional heterogeneity. This pattern likely reflects moderate gene flow, ecological connectivity among saline habitats, and the species’ reproductive flexibility, including partial gynodioecy and variable male fertility. Northern and southern ecotypes largely shared overlapping genetic profiles, with only minor local differentiation. This underscores the importance of integrating molecular data into conservation and restoration planning, as geographic proximity alone does not reliably predict genetic similarity. Overall, these findings advance our understanding of genetic variation in S. vermiculata and provide a foundation for effective genetic resource management. Prioritizing genetically distinct ecotypes from different ecological contexts for germplasm collection and habitat rehabilitation can help safeguard the species’ adaptive potential and ensure its long-term persistence under environmental pressures.

Acknowledgments

We are grateful to the Research Council of Shahid Chamran University of Ahvaz for financial support (GN.SCU.AA1402.165). We also thank the anonymous reviewers for their constructive comments and valuable suggestions that improved the quality of this manuscript.