Retrotransposon-Based Genetic Diversity of Rhodiola rosea L. (Crassulaceae) from Kazakhstan Altai

Abstract

The analysis of genetic diversity in natural populations of valuable medicinal plant species experiencing overexploitation is a key aspect of their natural conservation strategy. Mobile genetic elements and other interspersed repeats, which are major components of eukaryotic genomes, serve as effective tools for studying plant biodiversity and variability. The genetic diversity of four valuable medicinal plant Rhodiola rosea L. populations was investigated using the inter-repeat amplified PCR method with inter-priming binding sites (iPBSs) for genome profiling. At the interpopulation level, unique amplicons characteristic of specific R. rosea populations were identified. Molecular variance analysis revealed that the biodiversity of R. rosea populations in the Kazakh Altai region is 56% attributed to interpopulation differences and 44% to intrapopulation differences. It was shown that populations located in favorable environmental conditions have greater genetic diversity compared to those in extreme habitats. This study identified a high degree of polymorphism among R. rosea populations using the inter-repeat amplified PCR method. The genetic diversity of the populations ranged from 0.105 to 0.156, with an average heterozygosity of 0.134. The findings provide new insights into the population structure of R. rosea in the Kazakh Altai, enabling the identification of different genotypes, which will significantly complement traditional methods for conserving this valuable medicinal plant.

1. Introduction

Biodiversity is strongly influenced by the genetic composition of species and their populations. Genetic diversity in a population is determined by the number of genes with multiple alleles (called polymorphic genes). The presence of a polymorphic gene results in heterozygous individuals in a population that receive different alleles from their parents. A significant decrease in genetic diversity threatens the species because the sustainability of reproduction in natural populations decreases. Moreover, species’ survival in ecosystems and agroecosystems depends directly on their capacity to adapt to changing environmental conditions. Species with low genetic diversity also have low adaptive potential [1].

Genetic polymorphisms are shaped by mutation, genetic drift, gene flow, and natural selection. While genetic drift reduces diversity, gene flow can counteract this, influenced by factors like distance and pollination. Natural selection, including balancing and stabilizing selection, maintains allele frequencies and heterozygosity as populations adapt [2].

Rare plant species often have disturbed habitats, and their populations are usually small and fragmented [3]. When populations decline, genetic drift can lead to decreased genetic diversity [4]. When the allele is fixed, the locus is homozygous, which reduces the expected He index [4]. This result leads to an increase in inbreeding. Inbreeding does not change the allele frequency in the population; it redistributes the genotype frequency, increases the proportion of homozygotes, and decreases the proportion of heterozygotes. Harmful mutations often occur in a recessive state, increasing the proportion of homozygotes (i.e., recessive alleles) and leading to inbreeding depression.

Inbreeding in plants depends on the pollination method and population size. Self-pollinating populations face less inbreeding depression, while smaller populations are more affected, allowing recessive alleles to accumulate [5,6]. At the same time, the level of inbreeding leads to a reduction in the overall viability of plants, which can delay or decrease the intensity of flowering, cause changes in flower morphology, reduce the number of seeds, and lower their viability [7]. At the same time, inbreeding in populations sometimes promotes adaptation to specific environmental conditions by fixing the most adapted phenotype [8].

However, if deleterious mutations are selected, initially, small populations may exhibit low levels of inbreeding depression. Studies on the effects of inbreeding depression on plant populations have shown that it affects plant yield, seed germination, survival, and stress tolerance [9]. Small and isolated populations are also characterized by the accumulation of “harmful” mutations and by impaired seed production as a result of the reduced diversity of complementary alleles [10].

Much knowledge has been accumulated in the field of the genetics of rare plant species and the genetic processes occurring in these populations. However, the available information is sometimes controversial. Therefore, studying the genetic diversity and population genetic structure of rare plant species would improve the understanding of the processes and identification of patterns that could lead to species extinction.

Various markers, including DNA-based molecular markers, have been used to study population genetic diversity. The most used molecular markers based on the PCR method are Cleaved Amplified Polymorphic Sequences (CAPSs), Sequence-Tagged Sites (STSs), Simple Sequence Repeats (SSRs), Random Amplified Polymorphic DNA (RAPD), Inter-Simple Sequence Repeats (ISSRs), Sequence Characterized Amplified Regions (SCARs), and Amplified Fragment Length Polymorphism (AFLP) [11], which play an important role in plant biology, including DNA fingerprinting [12], genetic labeling, and research on phylogenetic relationships in molecular breeding. Molecular markers should be highly polymorphic, co-dominant, optimally distributed in the genome, selectively neutral, easily evaluated, reproducible, and automatable.

The genomes of all eukaryotes frequently contain interspersed repeat elements, which effectively fulfill these requirements. Among them, retrotransposons, mobile genetic elements, constitute a predominant component of the plant genome [13]. These virus-related elements migrate through the plant genome via a “copy-and-embed” transposition mechanism, utilizing a viral RNA intermediate. Unlike traditional methods, marker systems based on mobile elements are uniquely capable of detecting significant genomic variation. This study explores genomic polymorphisms using PCR molecular genetic markers, specifically those based on DNA fragments flanked by retrotransposon sequences and their inverted repeats, or other repeat elements (IRAP, REMAP, and iPBS). These markers have significant potential for advancing plant genotyping methodologies [14,15].

The primers are designed to bind to both directions of the retrotransposon sites, and the length of the primer binding site (PBS) retrotransposon tRNA sites do not exceed 18 nucleotides [16]. The choice of this type of marker relies on its large distribution in the genome as well as its high informative value. This inter-repeat amplified PCR method is ideal for genome fingerprinting in rare and endemic species with poorly characterized genomes. During chromosomal recombination, many mobile elements are mixed, leading to the convergence of these conserved regions and allowing PCR amplification. The PBS primer site scheme involves the addition of at least 12 nucleotides to the tRNA chain, which is sufficient for use as a primer for PCR. Genetic polymorphisms caused by retrotransposon activity can be determined using PCR, which is an optimal alternative to existing assay methods, especially for poorly studied species [17,18] or species with a limited range of distribution. One of the most valuable plant species in Kazakhstan is Rhodiola rosea L., which inhabits mountainous regions in the Altai, characterized by conditions of intense solar radiation, significant temperature fluctuations, and nutrient deficiency. R. rosea L. contains over 140 components with potent stimulating effects on the human immune system. The beneficial effects of Rhodiola sp. extracts are attributed to the presence of biologically active substances: salidroside, tyrosol, flavonoids (kaempferol, quercetin, catechins, and proanthocyanidins), and phenolic acid glycosides, among others. Rhodiola contains up to 41.8% polyphenols, which account for its antioxidant properties. A distinctive feature of R. rosea is the presence of cinnamyl alcohol glycosides (rosin, rosavin, and rosin) [19,20].

Modern studies have identified antioxidant, adaptogenic, anti-stress, antimicrobial, immunomodulatory, and angiomodulating properties of R. rosea [21,22]. The global demand for R. rosea has led to it becoming rare and endangered, since raw materials are harvested from natural populations. Consequently, the species has been included in the Red Data Book in Kazakhstan and other countries [23,24]. Market analysis shows that the demand for Rhodiola-based products will continue to grow, which may negatively impact its conservation status and future availability for medicinal use [25,26]. Therefore, it is necessary to study the genetic variability of R. rosea populations in the Kazakh Altai.

R. rosea has a wide and diffuse distribution and is presumed to exhibit high genetic variability. Per ISSR markers, R. rosea has at least two different evolutionary lineages [27]. Isozymes were used to study genetic polymorphism, and an AFLP method was used to analyze the specific genetic variability of the R. rosea relatives [28].

Studies based on chloroplast DNA markers have revealed genetic differentiation of Scandinavian populations from European Alpine System (EAS) populations. The high variability and pronounced genetic pattern preserved in the European Alpine and Carpathian populations emphasize the role of the EAS in the diversification of the species, probably starting from the glacial cycles of the Pleistocene and preserving long-term refugia. In addition to the EAS, a common origin from the British Isles to Scandinavia was found along the Atlantic coast [29].

Molecular analysis of Rhodiola congeners commonly observed in North America revealed that Rhodiola species entered the American continent at least twice, starting in the Middle Pleistocene. R. rhodantha and R. integrifolia of different origins reached the American continent from the east via Beringia, and R. rosea primarily arrived via the Atlantic route [29]. In our previous study [30], we utilized the PCR amplification method with inter-priming binding sites (iPBSs) for genome profiling, which revealed a significant level of polymorphism in Rhodiola sp.

The analysis was carried out on individual specimens from five species of the Rhodiola family: R. rosea (populations from the Ivanovsky Ridge (KZ) and Russia (RU)), R. semenovii (Regel and Herder) Boriss., R. linearifolia Boriss., R. algida (Ledeb.) Fisch. and C.A. Mey., and R. quadrifida (Pallas) Fischer and Meyer.

In the present study, we aimed to investigate the intrapopulation variability of Rhodiola rosea across four geographically isolated populations from the Kazakhstan Altai Mountains using inter-priming binding site (iPBS) PCR amplification for genome profiling.

2. Materials and Methods

2.1. Plant Material

R. rosea plants from four populations in the Altai Mountain region were collected in 2020–2022.

(1)

Population 1 (Pop 1)—Ivanovsky mountain range (50°19′13.5″ N, 83°45′11.0″ E);

(2)

Population 2 (Pop 2)—Sarymsakty mountain range (49°07′49.9″ N, 86°02′19.8″ E);

(3)

Population 3 (Pop 3)—South Altai (49°04′06.8″ N, 86°05′14.8″ E);

(4)

Population 4 (Pop 4)—West Listvyaga (49°21′06.0″ N, 85°41′54.8″ E) (Figure 1).

The collected material underwent primary processing and was identified by Zhumagul, Z. and Kubentayev, S.A. in the Botanical Garden of Astana (Kazakhstan). Herbarium specimens were stored in the Herbarium Fund of the Botanical Garden of Astana.

2.2. Genetic Analysis

DNA extraction was performed from R. rosea leaves by using a high-salt gel electroelution trap or using an acidic CTAB solution (2% CTAB, 2 M NaCl, 10 mM Na₃EDTA, and 50 mM HEPES, pH 5.3) [31,32,33]. DNA detection was performed using electrophoresis in a 1% agarose gel placed in a chamber with 1 × THE buffer (20 mM Tris–HEPES, pH 8.06); gel scanning was conducted using the iBright™ CL1500 Imaging System (Invitrogen™) gel documentation system.

Universal PBS primers [16], complementary to PBS retrotransposon sites, were used to evaluate the genetic diversity of different populations of R. rosea (

Table 1. Sequences of PBS primers used in R. rosea study and their characteristics.

ID	Sequence	GC (%) *	Tm (°C) *	LC (%) *
2221	acctagctcacgatgcca	55.6	58.0	89
2224	atcctggcaatggaacca	50.0	56.6	83
2228	cattggctcttgatacca	44.4	51.9	86
2230	tctaggcgtctgatacca	50.0	54.0	92
2232	agagaggctcggatacca	55.6	56.6	83
2237	cccctacctggcgtgcca	72.2	65.0	78
2238	acctagctcatgatgcca	50.0	55.5	83
2240	aacctggctcagatgcca	55.6	58.9	89
2241	acctagctcatcatgcca	50.0	55.5	78
2373	gaacttgctccgatgcca	55.6	57.9	86

* Tm—melting temperature; GC (%)—GC content composition; LC—linguistic sequence complexity [16].

).

The PCR reaction was conducted in a volume of 20 µL of a reaction mixture including 10 ng DNA, 1 × Phire Reaction Buffer with MgCl₂, 1 µM PBS primer, 0.2 mM dNTP mixture, and 0.5 U Phire Hot Start II DNA Polymerase. The amplification protocol was as follows: preliminary denaturation at 98 °C for 2 min, and then 30 cycles at 98 °C for 10 s, 55–60 °C for 30 s, 72 °C for 1 min, and an additional elongation at 72 °C for 2 min. The amplification was performed using a T100 Thermal Cycler (Bio-Rad Laboratories, Inc., CA, USA). To confirm the reproducibility of the results, we performed the analysis for each DNA sample in two repetitions.

The obtained amplification products (amplicons) were visualized on 1.5% agarose gel with the addition of ethidium bromide. The sizes of the amplified DNA fragments were determined by comparing them with a standard marker (Thermo Scientific GeneRuler DNA Ladder Mix 100–10,000 bp). Fragment lengths were determined using the iBright™ CL1500 Imaging System (Invitrogen™) gel documentation system. The number of detected polymorphisms was determined by comparing the percentage of polymorphic amplicons to the total number of amplicons for each primer. The gels were evaluated using the fingerprint method, followed by the compilation of a binary matrix in which the presence of a fragment was denoted as 1 in the absence of 0.

The main indicators of genetic biodiversity, such as the number of alleles (Na), Shannon Information Index (I), and genetic differentiation index (PHIPT), were determined using GenAlEx 6.5. Analysis of molecular variance (AMOVA) among and within populations along with principal coordinates analysis (PCoA) was performed using GenAlEx 6.5 [34].

3. Results

As a result of expeditionary studies, R. rosea specimens were collected from their natural habitats. The studied populations were located at altitudes ranging from 1700 to 2300 m above sea level and were associated with various phytocenotic communities (Figure 2,

Table 2. Population characteristics and habitat description of R. rosea.

Population	Habitat Coordinates	Altitude	Projective Cover	Population Characteristics
Pop 1	50°18′36.9″ N, 83°44′44.7″ E Ivanovsky Ridge, near Lake Maloye	2000–2100 m	15–25%.	The thickets of R. rosea occupy a narrow coastal strip no wider than 1.5–2 m, right at the water’s edge. The vegetation cover is represented by individual plants or small groups of communities, where species such as Carex aterrima, Deschampsia cespitosa, Festuca borissii, Trisetum altaicum, Phleum alpinum, Swertia obtusa, Primula nivalis, Rhodiola algida, Sanguisorba alpina, Caltha palustris, Bistorta vivipara, Allium schoenoprasum, and Gentiana algida are often found. Salix lanata and Salix rectijulis are relatively rare. In the herbaceous layer, R. rosea occurs relatively abundantly, with habitat conditions for the species considered close to optimal. The population is of a normal type and fully structured.
Pop 2	49°07′49.9″ N, 86°02′19.8″ ESarymsakty Ridge, Burkhat Pass (Southern Altai)	1950–2050 m.	55%.	The standing herbaceous cover forms diffusely along rock crevices, between block fragments, and in depressions where a fertile soil layer accumulates. The community includes species such as Coptidium lapponicum, Aquilegia glandulosa, Sanguisorba alpina, Rumex acetosa, Bistorta elliptica, Trollius altaicus, Geranium albiflorum, and others. The R. rosea population comprises all age stages, with a predominance of mature generative individuals. The shrubs resemble small tussocks. The plants are stunted and suppressed, with poorly developed roots and an almost complete absence of adventitious roots. The condition of this R. rosea population is characterized as stable and capable of self-renewal.
Pop 3	49°04′06.8″ N, 86°05′14.8″ ESouth Altai Tarbagatai, Karakaba Depression, Kara-Kaba River Valley	2000–2300 m.	85%.	The vegetation cover is poorly developed and relatively species-poor. The most common herbaceous plants include Carex capillaris, C. orbicularis, C. rupestris, Schulzia crinita, Micranthes punctata, Papaver croceum, Salix rectijulis, Dryas oxydontha, Silene graminifolia, Koenigia alpina, Minuartia verna, and Patrinia sibirica, which are relatively common among the shrubs. In this population, R. rosea is predominantly represented by aging generative individuals and very old plants, with the generative individuals failing to produce fruit. An analysis of the development status of R. rosea at the upper boundary of its distribution suggests that these habitats can be considered extreme.
Pop 4	49°21′06.0″ N, 85°41′54.8″ EWestern Listvyaga range, upper reaches of the Repnaya River	1700–1900 m	65–80%.	Alchemilla altaica, Primula nivalis, Carex curaica, and C. aterrima are common in the community, while Carex orbicularis, Cerastium davuricum, Bistorta vivipara, Trollius altaicus, Deschampsia cespitosa, Allium schoenoprasum, Myosotis scorpioides, Delphinium elatum, and Caltha palustris are rarely encountered. R. rosea is associated with narrow strips 1.5–2 m wide along the shorelines. There are no shrubs here. In rare cases, Lonicera altaica is observed along the coastal line. R. rosea forms small clusters in areas devoid of grass. In this population type, generative individuals of R. rosea dominate.

).

Samples were collected from each population, with no fewer than 10 plants selected from a considerable distance apart to exclude vegetatively propagated individuals. The extracted DNA samples were used for iPBS profiling.

Preliminarily, all primers listed in Table 1 were tested to assess the possibility of their use as markers for the genetic diversity of R. rosea (total DNA samples were used). Primers that generated insufficiently clear PCR fragments or fragments in small quantities were excluded from further analyses.

Primers with weak profiles and those generating mainly monomorphic amplification products were excluded from further analysis. The evaluation of the detection ability of the primers showed that four primers (2228, 2230, 2232, and 2240) generated saturated polymorphic profiles in most R. rosea samples (Figure 3, Figure 4 and Figure 5).

Evaluation of the amplifications showed that the number of amplified fragments forming the genetic profile of the samples depended on the specific population and the primers used. The genetic profiles of the samples contained unique amplicons and characteristics commonly observed in each population. Based on the DNA fingerprinting results, a matrix was compiled to determine the biodiversity indicators for this species (

Table 3. Characteristics of the PBS primers used to analyze the genetic diversity of R. rosea.

ID	TL *	PL *	PPL (%) *	PIC *	Amplicon Lengths (bp)
2228	140	46	32.8	0.472	550–3250
2230	384	127	33.1	0.405	400–2000
2232	143	81	56.6	0.455	550–4000
2240	136	54	39.7	0.408	400–3500

* TL, total number of loci; PL, number of polymorphic loci; PPL, percent of polymorphic locus; PIC, polymorphic information content.

).

PBS primers generated fragments ranging from 136 to 384 bp and polymorphic bands ranging from 54 to 127 bp. The size of the fragments varied from 400 to 3500 bp. Depending on the primer used, the polymorphism level varied from 25% (primer 2240) to 30.4% (primer 2228).

As determined using PBS profiling, the coefficients of genetic diversity in the R. rosea populations showed that Pop 1 had the highest values (

Table 4. Genetic diversity of R. rosea populations based on the results of the iPBS fingerprints.

Population	Na *	Ne *	I *	He *	uHe *	PPL (%) *	R *
Ivanovsky mountain range (Population 1)	1.145	1.247	0.242	0.156	0.164	50.91	4
Sarymsakty mountain range (Population 2)	0.945	1.175	0.162	0.105	0.111	36.36	4
South Altai (Population 3)	0.945	1.227	0.200	0.133	0.140	40	2
West Listvyaga (Population 4)	1.055	1.242	0.217	0.144	0.152	41.82	6
Average	1.023	1.233	0.025	0.134	0.141	42.27	4

* Na, number of alleles at each locus; Ne, effective alleles; I, Shannon index; He, heterozygosity; uHe, unbiased heterozygosity; % PPL, proportion of polymorphic loci; R, rare fragments.

). The number of polymorphic loci in samples of this population was 50.91%, and the Shannon diversity index was higher than the average value of this indicator in populations of R. rosea in the region.

The highest Shannon index value was 0.242 for the Ivanovsky mountain range (Pop 1), and the lowest was 0.200 for the South Altai population (Pop 3). The average value of the diversity index value of 0.205 suggests that approximately 20% of the genetic diversity of R. rosea is due to differences between individual plants in the population studied. The average He in Pop 1 and Pop 4 (0.156 and 0.144, respectively) were similar, indicating an equal degree of genetic diversity within the populations studied. The lowest He values were observed for Pop 2 (Sarymsakty), with Pop 3 and Pop 4 having intermediate values. This result indicates nonsignificant variability in genetic traits.

The highest number of private amplicons was observed in the West Listvyaga population (Pop 4), with six unique amplicons. The Ivanovsky mountain range (Pop 1) and Sarymsakty mountain range (Pop 2) each exhibited four unique amplicons. The South Altai population had the lowest number of private amplicons (Pop 3; Table 3).

In Pop 1, the value of Ne ≤ Na shows the predominance of dominant alleles in this population compared with Pops 2–4. Pop 1 indicates the highest level of genetic diversity and possibly the main initiating population, from which other populations of R. rosea separated during the process of divergence.

Based on the iPBS profiling data, we concluded that the genetic variability of R. rosea populations in the region was mainly due to within-population differences (44%), and the proportion of interpopulation variability was 56% (

Table 5. Analysis of molecular variance (AMOVA) of R. rosea populations according to PBS profiling data.

Variability	Df *	SS *	MS *	Est. Var. *	%	PhiPT *	p (r and ≥ Data)
Between populations	3	131.875	43.958	3.908	44%	0.445	0.001
Within populations	36	175.700	4.881	4.881	56%
Overall	39	307.575		8.788	100%

* Df, number of degrees of freedom; SS, sum of squares; MS, average square; Var, variance; PhiPT, index of genetic differentiation of populations.

).

The value of genetic variance (PHIPT) between populations was high (0.445). However, it did not exceed 0.5 and generally corresponded to the level of variability due to intrapopulation differences.

The band patterns across the four populations of R. rosea based on iPBS marker data are shown in Figure 5. The bar chart shows the number of band types in each population, and the lines represent the mean expected He values. Pop 1 (Ivanovsky mountain range) had the highest number of bands overall, including frequent bands (≥5%) and low-commonality bands (≤25% and ≤50%), indicating significant genetic diversity within this population. The large number of private bands highlights their genetic uniqueness. Mean He was relatively high, suggesting a considerable level of genetic variation. Pop 2 and Pop 3 exhibited fewer bands than Pop 1, especially private and low-commonality bands. This population exhibited reduced He, indicating reduced genetic variation within the population. Pop 4 had an intermediate number of bands. Relatively few private bands, a moderate level of frequent bands (≥5%), and a low level of commonality bands were observed.

The PCoA plot shown in Figure 6 reveals the spatial distribution and genetic variation among the four populations based on iPBS marker variation.

The first axis (PCo1) accounted for 55,02% of the total variation, and the second axis (PCo2) explained 28,94% of the variation, capturing most of the genetic differentiation observed, and PCo3 accounted for 16,04%. (Figure 7) Together, these three axes captured 100% of the total genetic variation. Populations Pop 1 and Pop 3 are genetically closer, as evidenced by their proximity in the lower-left quadrant of the plot. Conversely, Pop 4 is genetically more distant from the other populations, particularly Pop 1 and Pop 3, as indicated by its position in the upper-right quadrant. Pop 2 occupies an intermediate position, as it appears intermediate in the PCoA analysis. The genetic distance between R.rosea populations is presented in

Table 6. Genetic distance matrix between R.rosea populations.

Pop 1	Pop 2	Pop 3	Pop 4
12,267	17,060	14,740	19,840	Pop 1
17,060	7244	16,200	21,660	Pop 2
14,740	16,200	9356	15,960	Pop 3
19,840	21,660	15,960	10,178	Pop 4

.

The results of the genetic distance analysis show that Pop 1 has the smallest genetic distance to Pop 3 (14,740), suggesting a closer genetic relationship between these two populations. In contrast, Pop 2 and Pop 4 exhibit the greatest genetic distance (21,660), indicating significant genetic divergence.

4. Discussion

Studying rare plant species based on the evaluation of their genetic diversity, population polymorphism, and genetic differentiation, as well as biology, systematics, the geobotanical description of populations, identification of the age spectrum features, and limiting factors, allows a complete understanding of the nature and characteristics of rare species and prevents species extinction. This information helps preserve the evolutionary potential of species [35]. Preserving every population is impossible. For this purpose, selecting certain populations or specimens for preservation and storing them under artificial conditions or in a gene bank is required. Modern molecular genetic methods are necessary to evaluate genetic diversity within and between populations to characterize the population genetic structure of a species. The use of molecular markers is important when choosing strategies for the conservation of rare plant species.

Molecular markers can be used to estimate the quality of the gene pool of a certain population to preserve the variable genetic progeny of species populations. The preparation of genetic passports for rare species by obtaining valuable information about the genetic heterogeneity and genetic structure of the population using markers simplifies the selection process for collection and replenishes the gene pool.

Previously, the PCR amplification method with inter-priming binding sites (iPBSs) for genome profiling was assessed for its efficacy in evaluating genetic variability among Allium species populations using the Shannon information index (I) and expected heterozygosity (He). Among the primers tested, PBS primer 2232 exhibited the highest values (I = 0.297; He = 0.186), whereas PBS primer 2228 recorded the lowest (I = 0.160; He = 0.105) in a study on Colobanthus quitensis using the iPBS amplification method. These findings confirmed the informativeness and reliability of PBS primers [36]. The use of this type of marker for rare plant species indicates the direct involvement of motile elements in plant adaptation to stress. The activity of retrotransposons under stress can be genetically fixed, especially in species with vegetative reproduction. R. rosea is often sustained under conditions of exposure to environmental stressors (e.g., isolation, exposure to ultraviolet radiation, and significant fluctuations in daily temperature). Studies have shown that transcriptionally active retrotransposons possibly indirectly participate in gene regulation and adaptation to environmental stress because their activities depend on environmental stress [29].

In recent decades, the use of molecular techniques to detect polymorphisms at the DNA level has played an important role in improving conservation strategies for rare species and their genetic diversity.

The current state of Kazakhstani populations of R. rosea was studied in the work of S. Kubentayev et al. (2021), where variability in botanical features, ontogenetic phases, and the ecological and phytocenotic structure of the rare and endangered populations of R. rosea (golden rose root) from the highlands of Eastern Kazakhstan were identified [30].

Previously, PBS primers were used to identify the interspecific diversity of Rhodiola species in the territories of the Western Altai and Trans-Ili Alatau. That study demonstrated that the genetic diversity of the studied Rhodiola species exhibited a high level of interspecific genetic differentiation and was associated with their adaptability and the diversity of their reproductive systems. However, R. rosea samples had low genetic diversity compared to other species of the genus. In the current work, we investigated the intrapopulation variability of R. rosea across four geographically isolated populations using PBS markers (Table 2) developed by Kalendar et al. to assess their genetic diversity [30,37].

Genetic diversity studies on commonly observed bean (Phaseolus vulgaris L.) populations based on iPBS markers were highly informative, and the successful use of PBS primers was confirmed. The authors used the same 18-nucleotide primers used in this study [38,39,40].

After correlating the genetic analysis data using PBS profiling with the characteristics of the populations, we observed that Pop 1 and Pop 4 were in the most favorable habitat conditions. The two populations exhibited high Shannon biodiversity indices for (I) and He. Their existence under optimal conditions contributes to an increasing level of interpopulation exchange and the presence of genotypes with unique alleles that can be donors of genetic diversity, as evidenced by the high Na values in these populations. Despite this result, the level of genetic variability in all populations was low, and He and uHe exhibited low values in all populations. This pattern likely reflects limited genetic diversity within the populations studied, potentially caused by allele deficiency due to inbreeding and reduced plant survival.

We observed that Pop 2 from Sarymsakty (Na < 1) has a background of low Shannon (I) genetic diversity. According to Altukhov (2006), this phenomenon is characteristic of species with small populations, in which even a slight change in allele frequencies can significantly affect the level of diversity as the number of homozygous individuals increases [41]. Furthermore, the population of South Altai (Pop 3) was mainly represented by aging generative individuals. A similar phenomenon of reduced genetic diversity was observed in populations of R. dumulosa, R. granulata, and R. sachalinensis, which consisted of reproductively mature plants resulting from outbreeding or clonal propagation [39,42].

These individuals, under extreme conditions that hinder pollination and seed propagation, limit the full genetic potential of the species. Prolonged exposure to stress conditions may make seed reproduction impossible. However, vegetative reproduction plays a significant ecological role by preserving heterozygous genotypes and preventing inbreeding. In favorable conditions for existence, with sufficient heat, light, and moisture, the level of diversity will be higher than in stressful conditions, where only adapted individuals survive, for which vegetative reproduction will prevail over sexual reproduction [43]. This could explain why Pop 3 maintains an intermediate value He value, compared to other populations. Pop 1 from the Ivanovsky mountain range and Pop 4 (Western Listvyaga) produce seeds, and competitive genotypes can accumulate in the studied populations. The ability to develop vegetation was evidenced by a low Shannon index. Genetic markers on Allium in South Altai populations show that the species in this population are on the verge of extinction [43,44]. The low diversity observed might be influenced by the habitat of the species, climatic conditions, and terrain features.

These methods have made identifying and estimating the levels of genetic polymorphisms in R. rosea populations possible. The results obtained using different methods were compared for all types, which indicated the possibility of using the data obtained by the method individually and in a complex manner. This study is the first to apply iPBS molecular markers to describe the genetic diversity of the R. rosea population in Kazakhstan.

5. Conclusions

Our results show that genetic variability in Kazakh R. rosea populations is higher in the Ivanovsky mountain range and the Western Listvyaga region than in the South Altai region. The majority of genetic variation (56%) occurred within populations, while 44% was attributed to variability among populations. This study revealed that R. rosea populations from the Kazakhstan Altai Mountains differed in the degree of genetic polymorphism. Population polymorphisms (population groups) of the studied species depend on the type of reproduction, the nature of the distribution of suitable habitats, and possibly the time of population isolation. Favorable conditions contribute to preserving a high level of interpopulation gene exchange and the presence of unique genotypes that can be donors of genetic diversity in cases where the impact of anthropogenic factors is minimal and allows gene flow among the population.