
==== Front
J Genet Eng Biotechnol
J Genet Eng Biotechnol
Journal of Genetic Engineering & Biotechnology
1687-157X
2090-5920
Academy of Scientific Research and Technology, Egypt

S1687-157X(24)00108-2
10.1016/j.jgeb.2024.100405
100405
Full Length Article
Genetic diversity assessment of clonal plant Rosa persica in China
Li Na
Liu Xuesen
Zhang Xiaolong
Zhang Chenjie
Lu Xinyu
Sun Chenyang
Yu Chao
Luo Le luolebjfu@163.com
⁎
Beijing Key Laboratory of Ornamental Plants Germplasm Innovation and Molecular Breeding, National Engineering Research Center for Floriculture, Beijing Laboratory of Urban and Rural Ecological Environment, Engineering Research Center of Landscape Environment of Ministry of Education, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, State Key Laboratory of Efficient Production of Forest Resources, School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
⁎ Corresponding author at: 10 Dormitory, Beijing Forestry University, No.35 Qing Hua East Road, Haidian District, Beijing, China. luolebjfu@163.com
23 8 2024
12 2024
23 8 2024
22 4 10040517 5 2024
22 7 2024
25 7 2024
© 2024 Beijing Forestry University
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Rosa persica is considered a clonal plant because it is mainly propagated by clonal growth. Due to environmental degradation and habitat devastation, R. persica has been listed as a national second-class protected plant in China. However, the absence of research on wild populations of R. persica has impeded progress in formulating efficient conservation strategies. In this study, we investigated the clonal dispersal distance of R. persica to accurately determine the genetic diversity and population structure of the wild population in Xinjiang. We suggested that 20 m was the threshold distance with which to distinguish between different genets of plants. Based on this, we collated sequencing data from a total of 70 different genets of plants from 117 test samples. Eight populations of R. persica were primarily categorized into three subgroups: BL (Bole), TC (Tacheng) and CG (Changji). Of these, the CG subgroup exhibited the most genetic diversity. This research is the first to illustrates the clonal dispersal distance of R. persica, thus providing valuable reference guidelines for understanding the reproductive characteristics of clonal plants. In addition, the genetic diversity of R. persica provides a theoretical foundation for the formulation of conservation policies.

Keywords

Rosa persica
Clonal dispersal distance
Genetic diversity
Core collection
==== Body
pmc1 Introduction

Owing to its single leaves without stipules, Rosa persica, also known as Rosa berberifolia,37, 43 is distinct within the Hulthemia subgenus of the family Rosaceae,13.42 The natural habitat of R. persica encompasses Iran, Afghanistan, Central Asia, and the northern regions of western Siberia. China represents a marginal distribution area and R. persica only grows in some areas north of the Tianshan Mountains in Xinjiang.43 Due to climate change and human activity, the availability of key resources for this plant has significantly declined over recent years, leading to its classification as a national second-class endangered and protected plant.37.

R. persica is known for its unique purple and red floral patches on yellow flowers. Breeders consider this plant to be the best source of yellow traits18; as such, R. persica can be used as a parental material to introduce the patch trait to Rosa spp. In the market, popular varieties with flower patches rely on the incorporation of genetic material from R. persica. Therefore, this plant presents crucial breeding material for enhancing the characteristics of ornamental plants.18

Clonal growth refers to the process of producing potentially independent individuals in a natural habitat by asexual reproduction that are genetically identical to the mother plant.40 Plants capable of clonal growth are known as clonal plants. Their offspring, referred to as daughter plants or ramets, are often connected by spacers such as rhizomes, stolons, or horizontal roots, thus forming a large population known as a genet or clone.10 R. persica possesses both a horizontal and vertical root system. The vertical root system can penetrate up to 1.5 m underground, while the horizontal roots spread within the surface layers up to a depth of 0.8 m. In addition, a new plant can emerge from the rhizomes of horizontal roots. The rhizome functions as a subterranean structure that links the aboveground ramet, thus facilitating their spread.13,2 Current evidence suggests that R. persica is a clonal plant, although there is a significant lack of research relating to clonal dispersal distance. Amini et al.3 revealed that R. persica can reproduce via seeds. However, while our survey conducted from 2019 to 2023 reported the production of a significant number of seeds, no seedlings were observed in their natural habitat. This phenomenon aligns with the findings reported by He et al. (2005).

Considering the prominent taxonomic status, ornamental characteristics, breeding value, and endangerment of R. persica, there is a critical need to investigate the genetic diversity of wild populations of this plant to understand its evolution and devise methods for its conservation. The investigation of population genetic diversity contributes to elucidate population dynamics and reproductive strategies.21, 28 There is a clear abundance of phenotypic variation in the leaves and flower patches of wild populations of R. persica.9 However, phenotypic traits represent a combination of both the genotype and environment,thus, the observed variation in phenotypic traits does not always reflect genetic variation. Molecular markers are not limited by the growth environment and can directly reflect differences at the gene level. Genome-wide single-nucleotide polymorphisms (SNPs) were widely used to evaluate genetic diversity and germplasm domestication in Lagerstroemia indica41, Amaranthus tricolor,15 and Lactuca sativa,33 and providing high levels of accuracy.

In the present study, we collected 131 germplasms to investigate the clonal dispersal distance, population structure, and genetic diversity of wild populations of R. persica. We then screened the core germplasm to provide a theoretical basis for the utilization of germplasm resources and the genetic improvement of R. persica.

2 Materials and methods

2.1 Materials

Based on the results of the investigation into the natural distribution of R. persica, populations with different habitats covering more than 1000 square meters were identified. Ultimately, eight large wild populations located in highly suitable areas were selected. One population, labeled TC, is located in Tacheng city. Bole city includes two populations, labeled BL and BSLT. Shihezi city has one population, labeled SHZ. Changji city comprises four populations situated in Shangdonggong (SDG), Dongliugong (DLG), Wugongtai (WGT), and Runhelu (RHL) (Fig. 1). Except for the BSLT population, plant leaves were randomly sampled from each population with a spacing of more than 5 m. For the BSLT population, which has a banded form, samples were taken along a straight line at intervals of 20 m. Ultimately, a total of 117 germplasm samples were collected (Table S1).Fig. 1 A distribution and sample collection information map of R. persica in Xinjiang. (The sampling points were indicated with green marker). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

It is worth noting that three plants (A1, B1, C1) were randomly selected in the BSLT population, and the daughter plants (roots connected together) were identified by digging (the soil was covered immediately after the excavation work). We collected a total of 11 leaf samples (A1 and its two daughter plants; B1 and its two daughter plants; C1 and its four daughter plants). Plant D1 was selected first, and then two plants were randomly selected at a distance of 10 cm (without observing the underground conditions). As a result, an additional 14 germplasm samples were collected from the BSLT population.

2.2 Methods

2.2.1 DNA library construction

Genomic DNA was extracted from the fresh leaves of 131 wild R. persica using the CTAB method. The quality and quantity of the extracted DNA were checked with 1 % agarose gel electrophoresis and a NanoDrop spectrophotometer (Thermo scientific, USA), respectively. Qualified DNA samples were randomly interrupted with 350 bp length fragments. Paired-end (PE) sequencing DNA libraries were then constructed using the VAHTS Universal DNA Library Prep Kit for MGI (Vazyme, NDM607-01). The libraries were sequenced on an Illumina Nova6000. Post-sequencing, the Fastp software5was used for quality control of the raw sequences. Low-quality sequences and adapter sequences were removed to obtain clean reads. The sequencing data have been deposited at the National Center for Biotechnology Information (NCBI) under BioProject PRJNA1129312.

2.2.2 Variant annotation, filtering and verification

SNPs and InDels for individuals were called by GATK HaplotypeCaller (v4.1.4.1;25). The variants were extracted using GATK SelectVariants, and low-quality variants were filtered with GATK VarianFilteration using the following parameters: QD<2.0 || FS>60.0 || MQ<40.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0 || DP >= 4. The variants were annotated and counted based on genomic locations by the software ANNOVAR32according to the R. persica genome annotation file (unpublished).

2.2.3 Population structure and population divergence

SNPs were used to calculate the genetic distances between different accessions. The neighbor-joining method in the software Treebest (v1.9.2)31 was then employed to construct a phylogenetic tree based on the distance matrix. The tree was subsequently visualized using iTOL.17 The ADMIXTURE program was used to assess population structure employing the maximum likelihood method with 10,000 iterations, with the number of clusters (K) set from 1 to 10.1 The optimal K value was determined by cross-validation based on the lowest cross-entropy.11 Principal component analysis (PCA) of the selected SNPs was performed using PLINK.26 Observed Heterozygosity (Ho), Expected Heterozygosity (He), and Minor Allele Frequency (MAF) were also calculated with PLINK.26 Nucleotide Diversity (π) and Fixation Index (Fst) between pairwise populations were calculated using VCFtools.7 LD decay (correlation coefficient, r2) for all pairs of SNPs was measured using the PopLDdecay software35to assess the LD level in each subgroup. The final LD decay figures were generated with an R script.

2.2.4 Construction of core collection

The SNP set of 70 different genet plants was used to develop the R. persica core collection using the R package ‘corehunter’.8 Randomly, 5 %, 10 %, and 20 % of the accessions from the whole collection were selected to form the core collection of R. persica. Nucleotide diversity (π) was calculated using VCFtools. Subsequently, the core collection was evaluated for genetic diversity, and PCA was performed using PLINK.26 An appropriate core collection should retain at least 70 % of the genetic diversity present in the entire collection.20 .

3 Results

3.1 Clonal dispersal distance of R. persica

Plants from the same genet were connected by spacers and had the same genetic background, while plants from different genets belonged to different genetic individuals. Thus, we hypothesized that the number of common SNPs among plants from the same genet would be higher than those from different genets. To prove this hypothesis, we compared SNP data from six groups of R. persica.

In group I, sequencing data of a genet (A1, B1, C1) and one connected daughter plant were collected. In group Ⅱ, the two samples were derived from two randomly selected plants within the BSLT population, separated by a 10 cm ground distance (D1). In group III, the samples came from two randomly selected plants within the BSLT population, separated by a 20 m ground distance. In group IV, the samples were collected from populations BSLT and BL, which were 2 km apart. In group V, the samples were collected from populations BSLT and TC, 180 km apart. In group VI, the samples were collected from populations BSLT and TC, 411 km apart (Fig. 2).Fig. 2 Sample collection information of 6 groups (I. the genet and daughter plants from BSLT with underground roots connected, II. two plants from BSLT with a distance of 10 cm, III. two plants from BSLT with a distance of 20 m, IV. two plants from different populations (BSLT and BL) with a distance of 2 km, V. two plants from different populations (BSLT and TC) with a distance of 180 km, VII. two plants from different populations (BSLT and SDG) with a distance of 411 km.).

We then compared the common SNPs (cSNPs) shared by the two samples and the proportion of common SNPs (pSNPs), defined as the number of common SNPs divided by the total number of SNPs in a single sample, to determine the clonal dispersal distance.

Analysis showed that the number of cSNPs and pSNPs in group I (793338–926946, 71.04–82.39 %) were significantly higher than those in groups Ⅲ, IV, V, and VI (Fig. 3, Table S2), indicating that it is feasible to use the number of cSNPs and pSNPs to distinguish whether two plants are from the same genet or not.Fig. 3 Comparison of the proportion of common SNPs among 6 groups(I, II and III was from the same population, IV, V and VII was from the different population).

There was no significant difference between groups I and II in terms of pSNPs (Fig. 3), suggesting that the two plants could be classified as being from the same genet when they were 10 cm apart. The numbers of cSNPs and pSNPs in group III (418443–496225, 34.95–44.82 %) were significantly lower than those in groups I and II, but there was no significant difference with group IV. This indicates that two plants could be recognized as being from different genets when the distance between them is 20 m. Comparisons of cSNPs from groups IV to VI revealed that, as the geographical distance between the two plant sampling sites increased, the number of cSNPs and pSNPs decreased.

Our analysis also revealed that the pSNPs in plants from the same genet ranged from 71.04 % to 82.39 %, but ranged from 26.34 % to 44.82 % in plants from different genets. Furthermore, we evaluated 117 resequencing results using thresholds of 55 % and 70 % for the cSNPs. The majority of the samples, over 70 %, were plants from the same genet, whereas fewer than 55 % were plants from different genets. Finally, 70 samples from different genets (SDG 8 samples, DLG 5 samples, WGT 13 samples, RHL 9 samples, SHZ 3 samples, TC 10 samples, BL 7 samples, and BSLT 15 samples) were screened for follow-up analysis.

3.2 Total number of SNPs varied in various populations

After sequencing and removing low-quality sequences, we obtained 280.98 Gb of high-quality sequencing data (clean data) for 70 R. persica samples (genome size approximately 400 Mb, unpublished) (Table S3). The average proportion of base error rate below 1 % (Q20) was 98.51 %, and the average proportion of base error rate below 0.1 % (Q30) was 94.64 %, indicating high sequencing quality. The average GC content, the ratio of guanine (G) and cytosine (C) bases, was 38.37 %, suggesting a reasonable distribution (Table S3).

The total number of SNPs varied across different populations, as detailed in Table 1. After filtering, a total of 76,052,466 high-quality SNPs were obtained for subsequent analysis. Notably, the BSLT population exhibited the highest number of variants (17,712,686), indicating a substantial level of genetic diversity within this population. The heterozygosity across the eight populations ranged from 53.67 % to 73.75 %, underscoring a significant degree of genetic diversity.Table 1 Summary of SNPs from all varieties of R. persica.

Population	Sample number	SNP	Heter LociNum	Homo LociNum	Hetloci-ratio	
BL	7	8,089,709	5,322,219	2,767,490	65.79 %	
BSLT	15	17,712,686	10,691,310	7,021,376	60.36 %	
DLG	5	5,238,100	3,862,987	1,375,113	73.75 %	
RHL	9	9,088,215	6,086,317	3,001,898	66.97 %	
SDG	8	8,308,717	5,401,413	2,907,304	65.01 %	
SHZ	3	3,442,986	2,404,394	1,038,592	69.83 %	
TC	10	10,759,400	5,775,053	4,984,347	53.67 %	
WGT	13	13,412,653	8,780,569	4,632,084	65.46 %	
Total	70	76,052,466	48,324,262	27,728,204	63.54 %	

3.3 Genetic evolution and population analysis

After screening, a final dataset comprising 1,365,933 SNPs was obtained by excluding sites with a missing allele ratio greater than 0.2 and a MAF less than 0.05 from the raw SNP data. These high-quality SNPs were used for the phylogenetic analysis of 70 R. persica samples, which originated from different genetic backgrounds according to the screening results in section 3.1. The neighbor-joining algorithm in MEGA software was utilized to conduct the evolutionary analysis, resulting in a phylogenetic tree of the 70 samples. The analysis revealed that the samples could be divided into three major subgroups (Q1, Q2, and Q3): the 10 germplasm resources from the TC population clustered into the first group (Q1); the 22 germplasm resources from the BL and BSLT populations clustered into the second group (Q2); and the remaining 38 germplasm resources, mainly from Changji, clustered into the third group (Q3) (Fig. 4A). The phylogenetic tree clearly reflects the geographical origin of the germplasm based on their source locations.Fig. 4 Population structure of 70 R. persica germplasms. (A. Phylogenetic tree of 70 samples; B. Principal components analysis (PCA) of 70 samples; C. Structure analysis. The results contain K from 2 to 10; D. K selection of population structure).

A PCA was subsequently conducted, classifying the 70 germplasms into three distinct groups: 10 germplasms from the TC population, 22 germplasms from the BL population, and 38 germplasms from the CG population (Fig. 4B).

To verify the evolutionary genetic relationship between the samples, a detailed analysis of the genetic structure of each sequencing sample was conducted using SNP data. The population structure of all samples was analyzed, followed by cluster analysis. Various K values were used to represent the distribution of ancestral genetic material among different populations, assuming the existence of K ancestral groups. As illustrated in Fig. 4C, when K=3, the samples were divided into three subgroups: group 1 samples appeared predominantly red, group 2 samples predominantly orange, and the group 3 samples predominantly green. The TC samples clustered into group 1, while the BL and BSLT samples clustered into group 2. Similarly, the RHL, SDG, SHZ, WGT, and DLG samples clustered into group 3, indicating genetic exchange among the three subgroups. The cross-validation (CV) error graph (Fig. 4D) showed that the CV error reaches its minimum value at k = 3, suggesting significant genetic differences and distant genetic relationships between the samples. These results preliminarily suggest that the eight R. persica populations in Xinjiang originate from three distinct ancestral groups.

Based on the results from phylogenetic analysis, PCA, and genetic structure analysis, the eight populations of R. persica were consistently divided into three subgroup. This consistent division suggests that the geographical distribution is a key factor in explaining the germplasm source of R. persica.

3.4 Genetic diversity comparison in different subgroups

To elucidate the genomic diversity within each subgroup and the population differentiation among subgroups, we calculated Ho, He, MAF, π, and Fst (Fig. 5A; Table 2) for the three subgroups. The Ho, He, and MAF of accessions in the CG subgroup were higher compared to the other two subgroups, with the TC subgroup exhibiting the lowest values (Table 2). The CG subgroup had a median π value (π = 1.074 × 10-3), which differed only marginally (0.011 × 10-3) from the BL subgroup (π = 1.085 × 10-3). Consequently, the CG subgroup displayed the highest genomic diversity among the three subgroups, while the TC subgroup had the lowest. Additionally, the decay of LD, where r2 dropped to half its maximum value, was least pronounced in the CG subgroup (Fig. 5C), further indicating that the CG subgroup possessed greater genomic diversity.Fig. 5 The genetic diversity in different subgroups(A. Summary of nucleotide diversity (π), fixation index (Fst) among different subgroups; B. Common and unique SNPs across different subgroups; C. LD attenuation maps of 3 subgroups of R. persica).

Table 2 Genetic diversity indexes of R. persica subgroups.

GroupName	Ho	He	MAF	
TC（10 Samples）	0.237	0.249	0.177	
BL（22 Samples）	0.300	0.310	0.222	
CG（38 Samples）	0.317	0.311	0.234	
Total（70 Samples）	0.302	0.335	0.246	
(Ho: observed heterozygosity; He: expected heterozygosity; MAF: minor allele frequencies).

The analysis of genetic diversity across different populations revealed that the TC population exhibited the lowest values for π, Ho, He, and MAF, indicating it had the least genetic diversity among all populations. Among the eight populations, BSLT (1.098 × 10−3) had the highest π value, followed by SHZ (1.075 × 10−3). The highest observed Ho (0.401) was found in DLG, whereas WGT had the highest He (0.344) and MAF (0.259) (Table 3). The genetic diversity within these populations was generally consistent with the diversity observed in subgroups.Table 3 Genetic diversity information from 8 populations of R. persica.

Population	π	Ho	He	MAF	
SDG	1.050 × 10-3	0.347	0.335	0.252	
DLG	1.010 × 10-3	0.401	0.306	0.233	
WGT	1.051 × 10-3	0.351	0.344	0.259	
RHL	0.993 × 10-3	0.360	0.326	0.249	
SHZ	1.075 × 10-3	0.386	0.279	0.220	
TC	0.844 × 10-3	0.284	0.266	0.200	
BL	1.051 × 10-3	0.384	0.318	0.243	
BSLT	1.098 × 10-3	0.337	0.328	0.246	
(π: nucleotide diversity; Ho: observed heterozygosity; He: expected heterozygosity; MAF: minor allele frequencies).

Fst quantifies the degree of population differentiation among individual subgroups. The Fst values among the three subgroups ranged from 0.101 to 0.150 (Fig. 5A), indicating a moderate level of genetic differentiation between TC and CG, CG and BL, and TC and BL (0.05 < Fst ≤ 0.15). Furthermore, a similar moderate level of genetic differentiation was observed among the various populations (Table S4).

We also analyzed the common and group-specific SNPs among the different subgroups using Venn diagrams. The CG subgroup exhibited the highest proportion of specific SNP sites (896,924, 21.597 %) (Fig. 5B; Table S5). This high proportion of specific SNPs might contributes to the elevated genomic diversity.

3.5 Evaluation of the core collection

Core germplasm was randomly selected using ‘corehunter’ R package, representing 5 %, 10 %, and 20 % of the total germplasm collection, resulting in the identification of 14, 7, and 4 core germplasms, respectively (Table 4). Analysis of genetic diversity parameters π, Ho, He, and MAF revealed that a 20 % sampling ratio retained the highest level of genetic diversity, with nucleotide diversity preserved at 99.7 % (Fig. 6). Further evaluation of the core germplasm accuracy was performed using PCA. The two-dimensional principal component clustering plots of PC1 and PC2, PC1 and PC3, and PC2 and PC3 (Fig. 7) demonstrated that the core germplasm was distributed across the entire principal coordinate map. This distribution mirrors that of the original germplasm, indicating that the constructed core germplasm is representative of the overall genetic diversity.Table 4 Information of core germplasm.

Sampling ratio (%)	the Number of core germplasms	Information	
20	14	BL subgroup (4, BL-5, BL-7, BSLT-5, BSLT-6)
TC subgroup (3, TC-1, TC-5, TC-8)
CG subgroup (7, RHL-7, RHL-9, SHZ-1, WGT-1, WGT-12, DLG-3, DLG-5)	
10	7	BL subgroup (1, BSLT-2)
TC subgroup (1, TC-3)
CG subgroup (5, RHL-7, WGT-3, WGT-5, WGT-13, DLG-4)	
5	4	BL subgroup (1, BL-1)
TC subgroup (1, TC-3)
CG subgroup (2, RHL-2, DLG-1)	

Fig. 6 Genetic diversity of core germplasm retention with different sampling ratios (Orange represents the sampling ratio was 20%; Blue represents the sampling ratio was 10%; Yellow represents the sampling ratio was 5%; π: nucleotide diversity; Ho: observed heterozygosity; He: expected heterozygosity; MAF: minor allele frequencies). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 7 PCA results of core germplasm (Orange represents PCA results for all germplasms; Blue represents PCA results for core germplasms). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

4 Discussion

4.1 Clonal dispersal distance of R. persica

The collection of multiple samples can comprehensively reflect the population structure and genetic diversity of a species. Zhao et al.38 determined the genetic and evolutionary relationships of different species of Sorbus spp. and different populations of Sorbus pohuashanensis using 22 germplasms. A total of 795 wheat germplasms were then selected to reconstruct the population evolutionary history of bread wheat and its relatives.39 However, for clonal plants, which are often connected by spacers, the genetic background between the spacer-connected daughter plants and the genet is similar,therefore, the population gene composition reflected by the daughter plant and the mother plant is highly redundant19. To compensate for the unknown clonal dispersal distance, it is necessary to increase the number of samples collected, thereby increasing experimental costs to accurately reflect the true genetic structure of a population. Determining the clonal distance of the perennial woody plant R. persica is challenging when using typical excavation methods because of its deep roots, numerous spacers, and the gravel-dominated soil environment of its underground system. Using an innovative approach, we investigated the variations in cSNPs between plants from the same genet and plants from different genets to determine the clonal dispersal distance of R. persica.

We found that plants were classified as different genets if the distance between them exceeded 20 m and the pSNPs between the plants were less than 55 %. Surprisingly, after screening, we found that the BL population remained intact at a sampling distance of 20 m. This demonstrated the reliability of this screening method and provided a new concept for investigating the distance of clonal plants. However, further research is needed to determine more accurate distances that can be used to identify plants from the same genet or different genets.

4.2 Reproductive strategies of R. persica

The propagation strategy of R. persica is a subject of debate; indeed, some researchers believe that this species adopts both asexual and sexual propagation methods.2 However, in the present study, we did not identify any wild seedlings during field investigations conducted in Xinjiang; similar findings were reported by He et al.13 Compared to populations generated from seeds, populations generated from vegetative organs have a more uniform genetic background. It is well established that populations derived from seeds exhibit greater genetic diversity compared to populations that reproduce via rhizomes.19 Our analysis showed that the Fst values among different subgroups ranged from 0.101 to 0.150, thus indicating that the genetic differences between subgroups were not significantly and that the genetic variation predominantly originated from within the population.14 Thus, it is highly probable that sexual reproduction occurs within the population. In addition, we discovered that plants within the same population, separated by a distance of 20 m, were plants from different genets. This finding further supports the occurrence of sexual reproduction in R. persica. Therefore, the wild population of R. persica adopts both sexual and asexual reproduction strategies. The absence of seedlings may be attributed to the distinct growth strategy employed to adapt to harsh surroundings.

4.3 The genetic diversity of R. persica

Plants cannot migrate to find favorable environmental conditions for survival; thus, their strategy for improving adaptive capacity relies on abundant genetic variation. Although R. persica is usually propagated asexually and theoretically has low levels of genetic diversity (Liu et al., 2020); however, we identified high SNP diversity in the three subgroups (0.844 × 10-3 ∼ 1.085 × 10-3), consistent with the findings reported by Basaki et al.4 The reproductive strategy of flowering plants includes inbreeding, outcrossing, or a combination of both. This strategy facilitates the introduction of new genetic material and has a significant impact on genetic diversity within a population.24 It is plausible that this reproductive strategy is critical for preserving extensive genetic variation in R. persica and enhancing resistance to harsh environments.4 However, further experiments are needed to elucidate the specific mechanisms underlying this strategy.

PCA analysis, structure analysis, and the generation of phylogenetic trees consistently classified the 70 germplasms into three subgroups according to their geographical distribution. However, it is worth noting that the wild population in Iran was not strictly grouped according to geographical origin.4 R. persica is indigenous to Iran and exhibits a broad geographical range,16 although its distribution is limited to the northwest region of Xinjiang in China,37 which represents the margins of its global distribution. Differences in the regional distribution of germplasm, the quantity of germplasm, and the environmental circumstances in both China and Iran may have resulted in the variances reported in the study by4 compared to our present findings. Additionally, these differences may have arisen from the research methods. Various methods such as simple sequence repeats (SSR), sequence-related amplified polymorphism (SRAP), and amplified fragment length polymorphism (AFLP) have been employed to investigate the genetic diversity of populations,30, 22 while SNP molecular markers are known to provide higher levels of accuracy and were used in our present study.34 Previously, Basaki et al.4 employed AFLP to clarify the genetic diversity of R. persica. In contrast, we employed the more precise SNP molecular marker technology and incorporated the additional processes of screening and eliminating plants from different genets to enhance the reliability of our research methodology.

4.4 Screening of core germplasm

Core germplasm refers to the scientific selection of specific components of germplasm resources that represent the genetic diversity of the resources with the minimum number and genetic duplication. Establishing the core germplasm primarily relies on both phenotypic and molecular marker data. Compared to phenotypic data, molecular-level detection is not constrained by temporal or spatial limitations. Furthermore, molecular detection provides genetic variety and higher levels of polymorphism. Despite limitations imposed by differences across species, the extent of original germplasm collection, and the necessity for study, it is not possible to establish a perfect ratio or fixed size for core germplasm. According to previous research, typically 5 % to 30 % of the initial resources are chosen for core germplasm, and results are more favorable when the genetic representation exceeds 70 %.6 The findings of our current investigation preserved 99.7 % of the genetic variation present in the initial population while utilizing only 20 % of the original germplasm resources. Nevertheless, the germplasm materials utilized in this study were limited and did not comprehensively encompass all of the genetic resources of R. persica. Therefore, it is necessary to supplement and improve the findings with a more extensive collection of germplasm.

Screening core germplasm resources from a large number of germplasm resources in crops such as mung bean,27 eggplant,23 and rice36 serves two important purposes. Firstly, this strategy helps to preserve the genetic diversity of germplasm resources. Secondly, it facilitates the improvement of resource research and utilization efficiency, speeding up the breeding process. However, the habitat of R. persica has suffered severe degradation, leading to a progressive reduction in its living space over time.37 A highly effective conservation strategy for preserving the genetic variety of wild populations is to carefully select the core germplasm and ensure its preservation to the maximum extent possible. Thus, the protection and exploitation of the germplasm of R. persica are highly significant.

4.5 Implications for conservation

The loss of genetic variation poses a significant threat to endangered species; therefore, it is imperative to protect and restore genetic diversity. Due to the severe threat to the natural habitat of R. persica and the rapid decline of its population, both in situ and ex situ conservation measures are imperative. All populations, especially those with high genetic diversity or significant genetic differences, should be protected. In situ conservation is considered the most effective way to protect endangered plants, as it preserves the entire gene pool in their natural habitat. Populations BSLT, SHZ, DLG, and WGT, which exhibit high levels of genetic diversity, should be prioritized for in situ conservation.

The populations of R. persica are close to areas that have been damaged by human activities or urban expansion, facing habitat destruction, loss or fragmentation.12 Given this challenge, in addition to in situ conservation, it is highly recommended to establish gene banks ex situ, both in the field and in the laboratory. Populations BSLT, SHZ, DLG and WGT, with their relatively high levels of genetic diversity, should be the primary targets for ex situ conservation. Due to the minimal genetic differentiation among populations, each population may encompass a significant portion of the genetic variation within the species. Therefore, a seed collection strategy can be developed to collect as much seed germplasm as possible within the natural geographical distribution range of various genetic backgrounds Hoban et al., 201844 Furthermore, vegetative propagation technology can be utilized to preserve germplasm resources.

The distribution area of R. persica is narrow. After the seeds mature, the habitat conditions include prolonged drought and minimal rainfall. Consequently, seed germination is hindered; furthermore, even if seedlings manage to sprout, they are at risk from low temperatures and struggle to develop into adult plants within their original habitat.12 Therefore, for populations with low levels of genetic diversity (e.g., TC), seeds can be collected from populations with high levels of genetic diversity, sown and cultivated in various locations. Subsequently, seedlings can be introduced to enhance the genetic diversity of the population. Thus, the genetic resources of R. persica should be integrated into both in situ and ex situ conservation efforts.

5 Conclusion

In the present study, a total of 131 genome-wide resequencing data sets were utilized to investigate the clonal dispersal distance and genetic diversity of R. persica. Our findings revealed that plants may be classified as belonging to different genets if the distance between the two plants exceeded 20 m. We also found that R. persica can be categorized into three subgroups according to their geographical origin. Of these subgroups, the CG subgroup exhibited the greatest level of genetic diversity. A total of 14 core germplasms were screened, with 9 belonging to the CG subgroup. A sampling ratio of 20 % was considered optimal for screening core germplasms, and the 14 core germplasms accounted for 99.7 % of the overall genetic diversity of all germplasms. Populations BSLT, DLG, SHZ and WGT should be regarded as a crucial region for the conservation of R. persica.

CRediT authorship contribution statement

Na Li: Writing – original draft, Visualization, Software, Resources, Investigation, Formal analysis, Data curation. Xuesen Liu: Visualization, Software, Resources, Formal analysis, Data curation. Xiaolong Zhang: Supervision, Investigation, Formal analysis, Data curation, Conceptualization. Chenjie Zhang: Writing – original draft, Software, Resources, Investigation. Xinyu Lu: Writing – original draft, Software, Project administration, Investigation. Chenyang Sun: Project administration, Investigation, Formal analysis. Chao Yu: Visualization, Supervision, Funding acquisition. Le Luo: Writing – review & editing, Visualization, Supervision, Methodology, Funding acquisition, Conceptualization.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A Supplementary data

The following are the Supplementary data to this article:Supplementary Data 1

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 32071820), the National Key Research and Development Project of China (2023YFD120010502), and the National Key Research and Development Project of China (2022YFF1301704).

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.jgeb.2024.100405.
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