Genetic Diversity of Robinia pseudoacacia L. Populations from North-Western Romania Revealed by ISSR Markers

Abstract

This study aims to evaluate the genetic diversity of the species Robinia pseudoacacia L. using several populations selected from places located in the Crișana Region. The first six ISSRs tested gave distinct bands, with a total of 59 loci, of which 45 were polymorphic (63.85%). The percentage of polymorphic loci varied within populations from 33.33% to 100%. The average number of observed alleles (Na) is 1.7627 and the average effective number of alleles (Ne) is 1.4926, indicating that the effective variability is lower than the observed variability. For the Nei (h) gene diversity index, we recorded an average value of 0.2795, and for allelic entropy, the average value of the Shannon index (I) was 0.4137. The study finds a significant differentiation between populations, with a Gst coefficient value of 0.43 indicating that 43% of the variability is due to interpopulation differences.

1. Introduction

Robinia pseudoacacia L. is a deciduous tree of the Fabaceae family, native to North America but widely introduced throughout the world for erosion control and revegetation of mining areas and wastelands [1]. It is also an important species for honey production [2,3], forest restoration [4], soil improvement through nitrogen input [5], wood production [6], ornamental use [7], and a potential source for bio-oil production [8]. Its ecological and economic importance is significant [9,10], but its status as an invasive species in some regions raises concerns about biodiversity and ecosystem management [11]. Given these complexities, understanding the genetic biodiversity of Robinia pseudoacacia L. populations is crucial for conservation and genetic improvement programs and invasive species management [12].

In Romania, black locust (Robinia pseudoacacia L.) accounts for 4.4% of the total forested area, covering approximately 257,338 hectares, according to IFN reports [13]. The species was introduced around 1750, with large-scale plantations established from 1850 onward, primarily for the purpose of sand stabilization [14].

Genetic biodiversity is fundamental to the adaptability and resilience of a species, especially under changing environmental conditions such as climate change, habitat alteration, and human-induced pressures [12,15]. For Robinia pseudoacacia L., which was introduced to Europe for ornamental purposes in 1601 [16], genetic diversity influences its ability to thrive in new habitats, resist disease, and contribute to ecosystem services. Research shows that while native populations in North America exhibit high genetic diversity, those introduced in Europe display comparatively lower diversity. The reasons are related to the pronounced “Founder Effect”, as most European populations originate from a very small number of individuals (seeds or cuttings) originally brought from America (17th century).

This has led to a significant loss of alleles present in the native range. In Europe, black locust spreads aggressively through root suckers and cuttings. This leads to the formation of clones, where large areas can be occupied by genetically identical individuals [17,18], further reducing local genetic diversity. Even sexual reproduction often occurs between related individuals (due to high density and common ancestry), increasing inbreeding and reducing heterozygosity [19,20,21].

Inter-simple sequence repeat (ISSR) markers are highly polymorphic and inexpensive compared to other methods, with the same ISSR primers being universally applicable across the entire phylogenetic diversity of plants [20,22]. ISSR is a method based on polymerase chain reaction (PCR) that targets the regions between microsatellites and can produce highly polymorphic, informative, and reproducible bands [23].

Recent studies have demonstrated the effectiveness of ISSR markers in Robinia pseudoacacia L. A study published in the “Journal of Forest Science” [24] examined genetic diversity in Robinia populations in Istanbul and Kocaeli, Turkey, using ISSR markers. The study reported a 100% polymorphic locus percentage across multiple populations, while single populations ranged between 46% and 76%. Nei’s genetic diversity values varied from 0.165 to 0.251. Another study, conducted in China [25], employing SSR markers, revealed a high level of genetic diversity across seven populations of Robinia pseudoacacia L. In Brazil, Costa et al. (2011) [26] used ISSR markers to analyze genetic polymorphism in populations under drought conditions, showing differences in genetic structure based on hydrothermal regimes.

The assessment of genetic diversity in some Lithuanian forests [27] using four SSR loci (Rops 02, Rops 05, Rops 06, and Rops 08) led to the conclusion that Robinia pseudoacacia is genetically diverse (the average number of alleles per plot was 3.66, and the average observed heterozygosity (Ho) was 0.83. The study also revealed that Robinia pseudoacacia L. forms dense clonal groups within the investigated plots, which are difficult to intermix. Seed propagation [28] was identified as the predominant form of reproduction, with 66 single-copy genotypes recorded across the five plots examined. Another study [29] revealed that Robinia pseudoacacia L. individuals growing in less favorable conditions have the highest polymorphism of ISSR loci. The highest proportion of polymorphism was found when using ISSR primers UBC 808 and UBC 826. Analysis of the physiological state and genetic structure of plants has shown that individuals with greater polymorphism have a more pronounced resistance to soil moisture deficiency. ISSR markers are considered promising molecular markers due to their reproducibility, codominance, ease of use, and high polymorphism [30].

ISSR markers can facilitate diversity mapping, helping to prioritize areas with unique genetic resources. Populations with high genetic diversity may be key to maintaining adaptability to climate change, while those with low diversity may require interventions to prevent extinction. In introduced areas, where Robinia pseudoacacia L. is often invasive, ISSR markers can reveal whether invasions originate from a few genetically similar individuals (indicating a founder effect) or from diverse populations, which could influence spread and adaptability [31,32]. This information is vital for developing targeted management strategies, such as preventing gene flow into native ecosystems.

The research hypotheses underpinning this study were formulated along three principal directions:

(a)

General hypotheses regarding genetic diversity, focused on measuring intra- and inter-population genetic variation.

(b)

Hypotheses regarding population structure, aimed at examining how populations are genetically structured.

(c)

Specific hypotheses addressing the utility of ISSR markers, namely, whether the selected markers exhibit sufficient polymorphism and efficiency to detect and differentiate genetic variation at the subspecies level across the six populations of black locust (Robinia pseudoacacia L.)

First, we aimed to assess genetic diversity both within and between populations. Secondly, we sought to quantify genetic differentiation (Gst) and gene flow (Nm) in order to understand the evolutionary forces shaping these populations. We also wanted to determine the genetic structure by analyzing structure tests on individual loci, as well as to characterize the evolutionary relationships between the six populations analyzed, using genetic distance matrices and phylogenetic representations obtained in the form of dendrograms. Finally, the synthesis of all these results aims to provide a comprehensive picture of the genetic organization and relationships between the acacia populations studied.

2. Materials and Methods

2.1. Biological Material Used

The plants were collected from six locations in northwestern Romania: Valea lui Mihai, Oradea, Paleu, Cetariu, Cauaceu, and Bârzești. Geographical characteristics and meteorological conditions, such as altitude, latitude and longitude, average precipitation, average temperature, and soil type, are presented in

Table 1. Pedoclimatic characteristics of the locations where the biological material originated.

Place	Altitude	Dominant Soil Types	Annual Precipitation (L/m2)	Average Annual Temperature (°C)
Valea lui Mihai	127	Sandy soils	600	9.7
Oradea	126	Brown soils	585	10.3
Paleu	145	White loamy soil	700	8.5
Cetariu	189	White loamy soil	700	8.5
Cauaceu	124	Cambic chernozem	600	10.5
Bârzești	300	Loamy soils	600	10.6

.

To capture the real diversity and ensure the representativeness of the populations, two categories of selection criteria were applied:

(a)

First, the physiological condition and overall health of the trees were assessed using the Nikolaevsky method (1999), selecting individuals that fell within the score range of 35–40 [33].

(b)

Second, a minimum spatial distance of 50–150 m was maintained between sampled trees within the same population to minimize the likelihood of collecting clonal individuals. From each population, apical leaves (derived from annual branches) were collected from 10 individuals, with approximately 5 g per tree, and subsequently stored at –80 °C until further processing.

The biological material was identified in the Plant Physiology Laboratory of the Faculty of Environmental Protection, University of Oradea, Romania. The study analyzed six local populations of Robinia pseudacacia L., which were assigned a coding system to facilitate data organization and interpretation. The populations were designated as follows: Valea lui Mihai (Pop1), Oradea (Pop2), Paleu (Pop3), Cetariu (Pop4), Cauaceu (Pop5), and Bârzești (Pop6).

2.2. Isolation and Amplification of Genomic DNA

Total genomic DNA was isolated from young leaf samples using the cetyltrimethylammonium bromide (CTAB) method [34] with some modifications to the extraction buffer composition (2% CTAB buffer (100 mM Tris-HCl pH 8.0, 1.4 M NaCl, 20 mM EDTA, 2% CTAB)), 0.2-0.3 M sorbitol, 2% PVP-40, 0.2% β-mercaptoethanol. The leaf tissue was ground with a mortar after freezing at −80 °C until a fine powder was obtained. For the lysis step, 200 mg of tissue powder was transferred to a 2 mL Eppendorf tube, 700 µL of extraction buffer was added, and it was incubated at 65 °C for 65 min with freshly added β-mercaptoethanol (Sigma Aldrich, Carl Roth GmbH + Co. KG, Karlsruhe, Germany). For the extraction of organic compounds, an equal volume (700 µL) of chloroform: isopropanol (24:1) was added and centrifuged at 12,000 rpm for 10 min at 4 °C. The aqueous phase was transferred to a new tube, and the step was repeated. DNA precipitation was performed by adding 0.7 volumes of cold isopropanol to the supernatant and incubating at −20 °C for 30 min, followed by centrifugation at 13,000 rpm for 15 min at 4 °C to precipitate the DNA. DNA washing was performed with 70% alcohol, drying at room temperature, and rehydration in 50 µL ultrapure water with the addition of 1 µL RNase A (10 mg/mL) (HighQu GmbH, Kraichtal Germany).

For calculating DNA concentration, we used the formula derived from the Beer–Lambert Law:

Double-stranded DNA concentration (µg/mL) = A260 × Conversion factor × Dilution factor.

We considered a conversion factor of 50 µg/mL, corresponding to an absorbance of 1.0 at 260 nm. Using the applied extraction protocol, the amount of DNA ranged from 70 to 120 µg per gram of plant tissue. DNA purity, calculated based on the absorbance ratio (A260/A280), ranged between 1.8 and 1.9.

DNA quality was checked by measuring DNA concentration and purity with a Shimadzu mini-UV-1280 spectrophotometer (Viola SRL, Shimadzu Corporation, Kyoto, Japan) and running on a 1.5% agarose gel (AppliChem GmbH) and staining with 0.3 µg EtBr/mL agarose solution to verify DNA integrity. PCR amplification with ISSR primers was performed according to Bornet and Branchard (2001) [35]. The six ISSR primers (

Table 2. Robinia pseudoacacia L., ISSR loci used in this study and their characteristics.

Code	Sequence	Primer annealing Temperature (Tm, °C)
UBC807	5′-AG AG AG AG AG AG AG AGT-3′	52 °C
UBC817	5′-CA CA CA CA CA CA CA CAA-3′	54 °C
UBC818	5′-CA CA CA CA CA CA CA CAG-3′	54 °C
UBC820	5′-GT GT GT GT GT GT GT GTC-3′	52 °C
UBC823	5′-TC TC TC TC TC TC TC TCC-3′	54 °C
UBC824	5′-AC AC AC AC AC AC AC ACG-3′	52 °C

), provided by SC Bio Zyme SRL, were used to amplify genomic DNA extracted from young Robinia pseudoacacia L. leaves.The PCR reaction was performed in a 25 µL mixture including 5 µL 5× ALLin™ PCR Buffer, 5 µL ALLin™ Taq DNA Polymerase (5 U/µL) 0.15 µL (HighQu GmbH), ISSR Primer (10 µM) 2 µL (Bio Zyme, Seraing, Belgium), DNA template (20 ng/µL) 2 µL, ultrapure water 15.85 µL.PCR amplification was performed using a BIORAD C1000 Thermal Cycler (Bio-Rad Laboratories, Hercules, CA, USA) with the following program: an initial denaturation at 94 °C for 3 min, followed by cycles consisting of denaturation at 94 °C for 30 s, annealing at 52 °C for 40 s, and extension at 72 °C for 1 min. A final extension step was carried out at 72 °C for 5 min. PCR products were separated by electrophoresis on a 1.7% agarose gel immersed in 1% TBE buffer and stained with ethidium bromide. DNA was visualized under UV light using a Zazi UV3 transilluminator (Zhuhai HEMA Medical Instrument Co., Ltd., Zhuhai, China). The fragment size was estimated using a CL 5000 bp Omega Bio-Tek DNA marker (Omega Bio-tek, Inc., Norcross, GA, USA). Gel analysis was performed using GelAnalyzer 23.1 software (http://gelanalyzer.com, accessed on 8 September 2025).

2.3. Statistical Analysis

The data used in the analysis were obtained based on amplifications performed in three replicates for each primer. The resulting loci were evaluated based on presence (1) or absence (0), generating a binary matrix. This matrix was processed in the POPGENE program, version 1.32, which allowed the calculation of genetic parameters associated with population variability. The following indicators were determined: Na (absolute number of alleles), Ne (effective number of alleles), h (genetic diversity according to Nei), I (Shannon–Lewontin information index, 1972) [36], Gst (genetic differentiation coefficient), and Nm (estimated gene flow).

Principal component analysis (PCA) was applied to highlight the relationships between ISSR markers and genetic diversity parameters, as well as to evaluate population structure. PCA was performed based on the binary presence/absence matrix (1/0), using values corresponding to genetic parameters (Na, Ne, h, I, Ht, Gst). The PCA diagrams were generated based on the experimental data, using the program available at https://www.statskingdom.com/index.html (accessed on 15 September 2025). The results were represented graphically in the form of biplots: in the first analysis, ISSR markers were plotted alongside genetic parameter vectors to determine which markers contributed most to overall variability; in the second analysis, the six populations investigated were represented in the two-dimensional space of the first two principal components to visualize the degree of similarity/differentiation between them.

3. Results and Discussion

The analysis of ISSR markers provided a comprehensive set of data on the genetic variability of the six populations of Robinia pseudacacia. The findings were compared with literature data to assess their consistency and specificity. The following section presents both the general characteristics of the markers used and the differences in genetic variability observed at the intra- and interpopulation levels. The markers were selected based on previous studies and data from the literature [24,29].

Our analysis revealed that the UBC824 marker displayed the highest genetic differentiation (Gst = 0.5876), which means that 58.76% of the total genetic diversity is explained by the differences between the studied populations (

Table 3. Average genetic diversity parameters calculated for 6 markers (UBC807–UBC824).

Marker	Na 1	Ne 2	Ht 3	Hs 4	Gst 5
UBC807	1.6667	1.3715	0.3250	0.1471	0.5180
UBC817	1.8750	1.4529	0.2980	0.1730	0.4332
UBC818	1.9333	1.7825	0.4498	0.2976	0.3383
UBC820	1.3333	1.2440	0.4162	0.2351	0.4130
UBC823	1.8889	1.3911	0.2809	0.1601	0.3552
UBC824	1.8333	1.5882	0.4024	0.1700	0.5876

Note. ¹ Na: Average number of alleles observed, calculated for all marker loci; ² Ne: Effective average number of alleles, calculated for all marker loci; ³ Ht: Average total genetic diversity (Nei’s gene diversity), calculated only for polymorphic loci; ⁴ Hs: Average genetic diversity in the population, calculated only for polymorphic loci; ⁵ Gst: Average genetic differentiation coefficient, calculated only for polymorphic loci.

). This marker also exhibits a high effective number of alleles (Ne = 1.5882) and high total diversity (Ht = 0.4024). With the highest genetic diversity (Ht = 0.4498) and effective allele count (Ne = 1.7825), UBC818 stands out as an especially informative marker for representing overall variability in the sample. Genetic differentiation (Gst = 0.3383) is moderate. The UBC823 marker shows the lowest total genetic diversity (Ht = 0.2809) and the smallest differentiation between populations (Gst = 0.3552). This marker is less informative compared to the others, suggesting that the sequence it amplifies is more conserved (less variable) between individuals. The UBC817 marker has relatively low diversity within the population (Hs = 0.1730), but fairly high genetic differentiation (Gst = 0.4332). This suggests that although individuals within a population are similar, populations themselves are quite different from one another. The UBC807 and UBC820 markers show moderate values for most parameters.

Marker analysis showed that all six displayed considerable genetic diversity (Ht > 0.28), confirming their relevance for the current investigation. Regarding population structure, Gst values ranged from 0.33 to 0.58, reflecting moderate to high genetic differentiation among the studied populations and indicating restricted gene flow. Among the markers, UBC824 proved to be the most informative, with a notably high Gst value (0.5876) (Table 3).

The PCA (Principal Component Analysis) diagram shows the distribution of data on the first two principal components (PC1 and PC2), which explain 47.55% and 30.91% of the total variability, respectively (78.46% together). The graph shows a good separation of samples according to their characteristics (Figure 1). The UBC818 sample is the most distinct, being strongly correlated with the variables in Na and Ne. Samples UBC823 and UBC824 are very similar. The UBC807 sample appears to have a different influence, being negatively correlated with PC1, while UBC817 is in an intermediate position.

3.1. Statistical Analysis of the Population Structure for Each Locus

(Chi-square and G-square tests) indicates significant genetic differentiation between populations. Previous studies screening gene relationships in Robinia pseudoacacia L. have also found high polymorphism in separate populations [15,25,37].

These suggest that allele frequencies vary between populations, possibly due to natural selection (various selective pressures), genetic drift (isolation, founder effect), or reduced flow between species. Overall genetic diversity is moderate (h = 0.28), with most diversity found within populations (Hs = 0.1591), but there is also significant genetic differentiation between populations (Gst = 43.06%). One of the main results of this study is the high average value of the Gst index (0.4306). According to the interpretation guidelines proposed by Wright (1978) [38], a Gst value above 0.25 indicates “high” genetic differentiation. The value of 0.4306 falls firmly into this category, suggesting that a substantial part of the total genetic variability is due to differences in allele frequency between populations, rather than intrapopulation diversity.

This conclusion is supported by the gene flow estimate (Nm). The average value of 0.6611 indicates that less than one individual per generation migrates between populations on average. This low migration rate is a determining factor in maintaining and amplifying genetic differences.

There is a strong inverse relationship between Gst and Nm: as gene flow decreases, genetic differentiation increases because genetic drift and local forces can act independently on each population. In this case, the observed values align perfectly with this theoretical principle, indicating that populations are largely reproductively isolated, which has allowed for genetic divergence. There is considerable variability in Gst and Nm values between loci. Loci with extremely high Gst values (>0.80), indicating almost complete differentiation, and, at the opposite end of the spectrum, loci with low Gst values (<0.05), suggesting minimal genetic differentiation.

This variability highlights the importance of analyzing population structure at a more granular scale. The estimated gene flow (Nm = 0.66) is below 1, indicating that genetic drift has a significant impact on population structure. Chi-square tests on loci show that 15 of 59 loci (labeled A1 to A59) have significantly different allele frequencies (p < 0.05) between populations (

Table 4. Evaluation of the PCR amplification product of ISSR markers in populations Robinia pseudoacacia L.

Primer Code	Size Range (bp)	Total Loci	Polymorphic Loci	% Polymorphism
UBC807	150–850	13	9	69.23%
UBC817	250–800	8	6	75%
UBC818	200–1250	14	14	100%
UBC820	220–850	9	3	33.33%
UBC823	250–700	9	8	88.89%
UBC824	250–700	6	5	83.33%

), suggesting that these loci may be subject to selection or are associated with traits that differentiate populations.

Average diversity is typical for species with partial sexual reproduction or small populations, but lower than in outcrossing species (usually h > 0.4). Polymorphic loci (e.g., UBC818-8 with h = 0.499) contribute significantly to variability, while monomorphs (e.g., UBC807-5) indicate conserved regions or regions under selective pressure. An image showing the amplification products of the UBC807 and 817 markers is shown in Figure 2. The standard deviation (St. Dev. for h = 0.1976) shows heterogeneity between loci, suggesting different influences (selection vs. neutrality). Genetic diversity is sufficient for population differentiation, but populations may be vulnerable to loss of variability through inbreeding or habitat fragmentation.

3.2. Assessment of Intra-Population Genetic Variability

Gene variation statistics were calculated according to Nei’s methodology (1978) [39]. The mean number of alleles observed (Na) is 1.7627, with a relatively high standard deviation of 0.4291. This significant deviation is largely due to the presence of monomorphic loci, which have a value of Na = 1. The effective number of alleles (Ne) is 1.4926, which is lower than Na. Nei’s gene diversity index (h), which measures the probability that two randomly selected alleles from a population will be different, has a mean value of 0.2795. This average value suggests moderate genetic diversity. Monomorphic loci show zero diversity (h = 0.0000), while loci such as A2 and A33 have a maximum diversity of 0.5, indicating a balanced distribution of allele frequencies. Shannon’s information index (I), which quantifies allelic uncertainty or heterogeneity, has an average value of 0.4137 and reveals marked heterogeneity between loci. The large standard deviations for all indices (Na, Ne, h, I) indicate an uneven distribution of genetic diversity in the studied genome, caused either by intrinsic differences between the types of markers used, where some loci are natively more polymorphic than others, or by the fact that populations have undergone significant genetic drift or founder effect events, thus drastically reducing intrapopulation diversity.

The diagram (Figure 3) is a principal component analysis (PCA) that visualizes the distribution of six populations (Pop1–Pop6) based on four diversity indicators (represented by the red vectors: Nm, Hs, Ht, Gst). Axes PC1 and PC2 are the first two principal components, which capture a large part of the total variance in the data (56.01% and 32.28%, respectively). Pop4 and Pop5 stand out with high gene flow, Pop1 and Pop2 with moderate gene flow and lower diversity, and Pop6 with low genetic diversity, found in high genetic isolation. Pop3 is distinct from the other groups due to its very high genetic diversity, Ht (0.41) and Hs (0.304). This pattern suggests that there is significant variation between populations of black locust, similar to the conclusions of a study on other forest species: for example, for Syzygium cumini, Gst ≈ 0.50 and Nm ≈ 0.50 were found, signaling marked differentiation between populations [35,40], leading to the recommendation to conserve seeds from at least five distinct populations to cover the available genetic variability. Furthermore, this pattern suggests a balance between genetic variation between and within populations. A comparable study on Avicennia marina showed that approximately 48% of the total variation is found between populations and 52% within them [41]. In the case of the acacia populations analyzed, it can be deduced that the internal diversity of each population remains high, but there are also notable differences between subpopulations.

Furthermore, the average Nm index observed indicates moderate gene flow (average value Nm ≈ 0.6), which implies that, although there is gene circulation between populations, it is not intense enough to completely eliminate local differences.

3.3. Genetic Distance

Matrix analysis revealed a clear clustering pattern. The most similar pair of populations is formed by the Cetariu and Cauaceu populations. This is demonstrated by the highest genetic identity value (0.8872 for Nei) (1972) [42] and the lowest genetic distance value (0.1197). On the other hand, the most distinct pair is represented by the Paleu and Bârzești populations, which have the lowest genetic identity (0.7551) and the greatest genetic distance (0.2809). The UPGMA dendrogram, constructed on the basis of these distances, visually confirms these groupings. There is a close grouping of the Cetariu and Cauaceu populations, linked by a very short branch, suggesting a recent common evolutionary history. The populations of Valea lui Mihai and Oradea also form a group, while the populations of Paleu and Bârzești remain relatively distinct or form a separate, more dispersed cluster.

The fact that some populations are so genetically close, even in the context of a generally low gene flow (average Nm = 0.6611), suggests that their divergence was a recent event, probably a founder effect. Therefore, the short branch in the dendrogram does not necessarily indicate a continuous gene flow at a high level, but rather a short evolutionary time since separation, in which genetic drift has not had enough time to differentiate them significantly (

Table 5. Combined Matrix of Genetic Identity and Nei’s Standard Genetic Distance (1972) among the investigated populations [42]. Reprinted/adapted with permission from the American Society of Naturalists—Publisher: University of Chicago Press—Publication Years: 1867–Present.

Pop ID	Valea lui Mihai	Oradea	Paleu	Cetariu	Cauaceu	Bârzești
Valea lui Mihai	****	0.8342	0.7822	0.7669	0.7708	0.7828
Oradea	0.1813	****	0.8502	0.8402	0.8464	0.8156
Paleu	0.2456	0.1623	****	0.8665	0.7551	0.8256
Cetariu	0.2448	0.1741	0.1432	****	0.9201	0.8815
Cauaceu	0.2654	0.1668	0.1916	0.0833	****	0.8872
Bârzești	0.2604	0.2809	0.1261	0.2038	0.1197	****

Note. (****) indicates maximum identity (1.0000) and, implicitly, zero distance of a population with itself.

).

To evaluate the degree of genetic similarity and differentiation among the analyzed populations, we calculated the genetic identity matrix and the genetic distance matrix. Table 5 presents the combined results, where the elements above the diagonal reflect the values of Genetic Identity (I), while the elements below the main diagonal represent Nei’s Standard Genetic Distance (DST), according to the methodology described by Nei (1972) [42].

From the analyzed data, it can be observed that the highest genetic identity is recorded between the Cetariu and Cauaceu populations, with a value of 0.9201. This suggests an extremely high genetic similarity. In contrast, the lowest identity was found between the Paleu and Bârzești populations, with a value of 0.7551, suggesting that these are the most genetically distinct (Figure 4). The smallest genetic distance has a value of 0.0833, while the largest distance (the greatest divergence) has a value of 0.2809.

The dendrogram (UPGMA) based on Nei’s distance (1972) [42] shows a consistent structure. Populations 4 and 5 are the closest, forming a cluster. Population 6 is the most diverse and joins the last structure, illustrating a high genetic differentiation (0.66). This shows that history and isolation of populations have led to this pattern of differentiation.

The Ewens-Watterson test shows that most loci are in equilibrium (the observed F falls within the expected range under neutrality), but some (UBC807-4, UBC824-4) deviate, suggesting possible directional selection. The large distances between the population of Valea lui Mihai and other populations suggest isolation. Reduced gene flow between populations highlights the need to facilitate connectivity (ecological corridors) to prevent inbreeding. Under conditions of isolation, small populations lose alleles or fix them by the simple effect of chance. The fact that the neutrality test cannot reject the neutral model for these highly differentiated loci is a strong argument that genetic drift is the main evolutionary force shaping population structure. This observation suggests that the strong differentiation is not caused by recent divergent selection, but rather by severe genetic drift resulting from very low gene flow.

A study initiated by Guo et al. in China (2018, 2022) [15,43] to assess genetic differentiation and diversity in Robinia pseudoacacia L. using SSR markers concluded that there is a level of genetic diversity within populations and that geographical distribution among native populations of Robinia pseudoacacia L. is not a determining factor affecting genetic diversity.

Unlike the study conducted on Robinia pseudoacacia L. populations in Istanbul and Kocaeli [24], where nine ISSR primers were selected that generated a total of 100 loci (an average of 11.1 bands per primer), in the present study, six primers were used, which produced a total of 59 loci, with an average of 9.8 bands per primer. Although the number of primers used is smaller, they provided clear, reproducible, and sufficiently informative bands to highlight the genetic differences between the populations analyzed. Therefore, the quality of the selected markers partially compensated for the smaller number of loci, allowing for a relevant characterization of genetic diversity. The authors of the study explain the differences observed in Robinia pseudoacacia L. populations by highlighting the impact of urban environments, propagation methods, and the inherent genetic characteristics of the species.

In assessing genetic diversity in black locust, the use of appropriate markers is essential. In recent years, with the improvement of sequencing technologies, single-nucleotide polymorphism (SNP) markers [44] or efficient markers for simple repetitive sequences derived from expressed sequence tags (EST-SSR) have been synthesized [45]. However, ISSR markers remain a powerful tool in studying genetic diversity and determining population structure due to their good reproducibility and cost-effectiveness [46].

4. Conclusions

The study investigated the genetic diversity and phylogenetic relationships of Robinia pseudoacacia L. genotypes collected from six habitats using ISSR markers. We found moderate average genetic diversity h = 0.2795 and Shannon Index (I) = 0.4137, with 63.85% of loci being polymorphic, suggesting a diverse genetic basis for adaptation. The genetic differentiation coefficient (Gst) = 0.4306 (43.06%) indicates that almost half of the diversity is due to differences between populations.

Locus-by-locus analysis showed that this differentiation is profound at certain loci, but surprisingly, neutrality tests suggest that the differentiation is a result of genetic drift and isolation rather than divergent selection. This finding represents a nuanced aspect, indicating that the lack of connectivity (reduced gene flow) is likely the main driver of genetic structure shaping.

Distance matrices and dendrograms clearly visualize these relationships, showing a close grouping of the Cetariu and Cauaceu populations, indicating a recent history of divergence and more distinct positions for other populations.

Intra-population genetic diversity is moderate but heterogeneous, with many monomorphic loci suggesting a history of genetic drift. Differentiation measures (Gst > 0.4) and gene flow (Nm < 1) confirm that populations are isolated, allowing independent evolutionary forces to act upon them.

These results are important for conservation programs, genetic resource management, and understanding the history and connections between different populations or varieties of the species Robinia pseudoacacia L. Integrated analysis of all genetic data conclusively demonstrates a pronounced genetic structure and significant differentiation between the six populations. All lines of evidence—from diversity and differentiation statistics to individual locus analyses and phylogenetic representations—converge toward a single picture.

Since the populations analyzed do not represent a panmictic unit, they should be considered and managed as separate entities. The reduced level of genetic diversity may heighten their susceptibility to future disturbances, including disease or environmental variation.