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Article

Population Genomics Study and Implications for the Conservation of Zabelia tyaihyonii Based on Genotyping-By-Sequencing

by
Halam Kang
1,
Sung-Mo An
1,
Yoo-Jung Park
1,
Yoo-Bin Lee
1,
Jung-Hyun Lee
2,
Kyeong-Sik Cheon
1,* and
Kyung-Ah Kim
3,*
1
Department of Biological Science, Sangji University, Wonju 26339, Republic of Korea
2
Department of Biology Education, Chonnam National University, Gwangju 61186, Republic of Korea
3
Environmental Research Institute, Kangwon National University, Chuncheon 24341, Republic of Korea
*
Authors to whom correspondence should be addressed.
Plants 2023, 12(1), 171; https://doi.org/10.3390/plants12010171
Submission received: 17 November 2022 / Revised: 26 December 2022 / Accepted: 26 December 2022 / Published: 30 December 2022
(This article belongs to the Special Issue Advances in Genetic Diversity and Population Structure of Plant Species)
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Abstract

:
Zabelia tyaihyonii (Nakai) Hisauti and H. Hara is a perennial shrub endemic to Republic of Korea that grows naturally in only a very limited region of the dolomite areas of Gangwon-do and Chungcheongbuk-do Provinces in the Republic of Korea. Given its geographical characteristics, it is more vulnerable than more widely distributed species. Despite the need for comprehensive information to support conservation, population genetic information for this species is very scarce. In this study, we analyzed the genetic diversity and population structure of 94 individuals from six populations of Z. tyaihyonii using a genotyping-by-sequencing (GBS) approach to provide important information for proper conservation and management. Our results, based on 3088 single nucleotide polymorphisms (SNPs), showed a mean expected heterozygosity (He) of 0.233, no sign of within-population inbreeding (GIS that was close to or even below zero in all populations), and a high level of genetic differentiation (FST = 0.170). Analysis of molecular variance (AMOVA) indicated that the principal molecular variance existed within populations (84.5%) rather than among populations (17.0%). We suggested that six management units were proposed for conservation considering Bayesian structure analysis and phylogenetic analysis, and given the various current situations faced by Z. tyaihyonii, it is believed that not only the in situ conservation but also the ex situ conservation should be considered.

1. Introduction

Zabelia tyaihyonii (Nakai) Hirsute and H. Hara (Taihyun’s abelia) (Figure 1A) belongs to Caprifoliaceae Juss., and is a deciduous broad-leaved shrub with a height of approximately 1–2 m. This species was first described as a species of the genus Abelia by Nakai in 1921 [1]. However, Hisauchi and Hara [2] separated Zabelia (Rehder) Makino from Abelia into a new genus based on the external morphological and anatomical characteristics suggested in a previous study [3], so this is generally treated as the current scientific name.
This species, first described as a species of the genus Abelia by Nakai in 1921 [1], has this current scientific name because Hisauchi and Hara [2] segregated Zabelia of the genus Abelia into a new genus, Zabelia (Rehder) Makino, based on the external morphological and anatomical characteristics suggested in a previous study [3]. This species is very similar to Zabelia mosanensis (T.H. Chung ex Nakai) Hisauti and Hara, but it is distinguished in that its leaf length is half or less, and hair on the filament is absent [4]. In the current classification system, however, it is common to treat the two taxa as one taxon and treat Z. mosanensis as a synonym for Z. tyaihyonii according to the principle of priority [5].
This species is a very important resource because it is a Korean endemic plant and an indicator species of limestone areas [6]. It is also listed as a rare plant [7,8], and V Grade of the Floristic Target Species (FT species) in the Republic of Korea [9] because it grows naturally in only a very limited region of the dolomite areas of Gangwon-do and Chungcheongbuk-do Provinces in the Republic of Korea [9]. Additionally, Z. tyaihyonii has very high value as garden material because it has gorgeous and fragrant flowers [10].
Since endemic plants are very sensitive to subtle changes in environmental factors, they should be prioritized for management and preservation [11,12]. Species with a very narrow range, such as Z. tyaihyonii, are particularly vulnerable. It is important to establish a conservation strategy based on ecological conditions and the genetic diversity suitable for each species to prevent extinction and maintain continuous natural populations [13,14,15]. Previous studies on Z. tyaihyonii were mainly focused on systematics [16,17,18,19,20,21], and only four studies have been performed on its conservation biology [4,10,22,23]. The ecological characteristics of Z. tyaihyonii habitats were very thoroughly described in three studies conducted on all native habitats [4,10,23]. However, information on genetic diversity is very scarce; only one previous study considered this topic and it included only two natural populations [22].
Next-generation sequencing (NGS) technology has transformed modern biology, including population genetics, due to its high throughput and low cost [23,24]. The two strategies for NGS include whole-genome resequencing (WGR) and reduced-representation sequencing (RRS) [24,25]. Genotyping-by-sequencing (GBS) is one of most widely used RRS methods in which the barcode system is improved to allow the discovery of genome-wide single nucleotide polymorphisms (SNPs) with a lower error rate and low cost [26]. Because of these advantages, the high-throughput SNPs detected by GBS are widely used for genetic diversity analysis in many plant species [24,27,28,29,30,31,32,33,34].
In this study, GBS was used to genotype 94 Z. tyaihyonii individuals collected from all known natural habitats (six populations) (Figure 1B). The main goals of this study were to: (1) Assess the genetic diversity and population genetic structure of this species; (2) Develop and implement the conservation strategies based on genetic diversity. The results obtained from this study will provide fundamental baseline knowledge for developing and implementing conservation strategies.

2. Results

2.1. SNP Analysis and Genetic Diversity

An initial quality check of 663,388,244 reads after sequencing resulted in a matrix of 48,326 SNPs. Initial filtering (i.e., missing SNP data, minor allele count, minimum quality score, and minimum read depth) resulted in the identification of 31,147 SNPs. A further filtering step (individuals with missing data) resulted in a total of 4085 SNPs, and the final filtering steps yielded 3088 final SNP loci in 94 genotyped individuals across six sampled locations.

2.2. Genetic Diversity

Genetic diversity indices within the six populations of Z. tyaihyonii were estimated and are summarized in Table 1. The means for the number of different alleles (Na) and number of effective alleles (Ne) were 1.734 and 1.389, respectively. Shannon’s information index (I) was the highest in BS (0.406) and the lowest in SH (0.249), with an average of 0.355. The ranges of observed heterozygosity and expected heterozygosity among the six populations were from 0.209 (SH) to 0.273 (TG) and from 0.170 (SH) to 0.263 (BS), respectively. Additionally, inbreeding coefficient (GIS) was negative in all populations except BS.

2.3. Genetic Differentiation and Population Structure

The results from the analysis of molecular variance (AMOVA) (Table 2) revealed that only 17.0% of the total generic variation was due to among-population differentiation and that the majority of differentiation was within individuals (84.50%). The F-statistics from the analysis also showed that the species discussed in this study was moderately to highly structured, with a value significantly different from zero after 20,000 permutations (FST = 0.170, p < 0.001). Although there was a significant expected reduction in heterozygosity among all individuals (FIT = 0.155, p < 0.001), the slightly negative total inbreeding coefficient (FIS = −0.018) was not shown to significantly differ from zero (p > 0.05), indicating little or no inbreeding in the species.
The coefficient of genetic differentiation (FST) and a high level of historical gene flow (Nm) of pairs of populations were detected in Z. tyaihyonii (Figure S1). Population pairs including SH exhibited higher FST and lower Nm values than other pairs, while the lowest genetic differentiation (FST = 0.072) and the highest gene flow (Nm = 3.217) were observed between BS and CW (Figure S1). The positions of inferred gene flow barriers between populations were identified based upon the matrix of FST values (Figure 1).
All estimator criteria, median of means (MedMeak), maximum of means (MaxMeak), median of medians (MedMedK) and maximum of medians (MaxMedK), showed K = 6 as most likely (Figure 2A). Therefore, results indicated that all six populations had a genetically unique pattern (Figure 2B). At K = 2, clear genetic differentiation was observed between SH and all other populations. At K = 3, SC began to split from the group, while the rest of the populations remained clustered. At K = 4, the six Z. tyaihyonii populations could be divided into four groups: the first and second groups consisted of SC and SH alone, respectively, and the third group comprised BS and YC. The last group consisted of CW and TG. Additionally, at K = 5, TG was genetically distinct from CW (Figure 2B).
PCoA results are presented in Figure 3. Along Coordinate 1 (11.34%), genotypes from SH were shown to the far left and clustered very distinctly from all other populations, and along Coordinates 2 (7.20%) and 3 (5.2%), genotypes from SC, and BS and YC were clustered distinctly from all other populations, respectively.
To establish phylogenetic relationships among the 94 genotypes, a cladogram was constructed using the UPGMA technique and 3088 SNPs (Figure 4). The tree was clearly divided into geographical populations. Additionally, the tree showed a pattern very similar to those of the STRUCTRUE analysis: SH diverged the earliest, CW and TG, and BS and YC showed the closest relationships.

3. Discussion

3.1. Genetic Diversity in Z. tyaihyonii Populations

The genetic diversity of species reflects their long-term evolution and adaptation, as well as demographic history [35,36]. High genetic diversity is important because it can allow populations to adapt to environmental changes more easily. Therefore, understanding the level of genetic diversity within and among populations is essential for establishing species conservation strategies [37,38]. To assess the level of genetic diversity in this species, we compared our results with those of related studies that used a method similar to that used in this study. Our comparison showed that Z. tyaihyonii has lower genetic diversity (He = 0.233) than other species of endemic and woody perennials, such as Abeliophyllum distichum (He = 0.319) [34], Tetraena mongolica (He = 0.348) [39] and Rhododendron rex (He = 0.54) [35]. Given these comparisons, the genetic diversity of Z. tyaihyonii can be considered low.
The genetic diversity of plant species is related to their distribution range, population size, life cycle, mating system and gene flow [38,40]. Of these factors, a narrow distribution range and small population size tend to reduce genetic diversity [37,38] as a consequence of genetic drift and inbreeding [14,37,38,41,42,43]. Additionally, in species that reproduce both sexually and vegetatively, such as Z. tyaihyonii, the intensity of vegetative reproduction has a significant effect on the genetic diversity of a population. For example, if the intensity of vegetative reproduction is very high, the number of genets becomes extremely low compared to the number of ramets. At the other extreme, if one or only a few genets form a population, the genetic diversity is very low, and even if the population size is large and seed reproduction occurs, the population may face extinction due to high-intensity inbreeding [22,44,45]. The results of this study, however, showed no sign of within-population inbreeding, with all populations displaying a GIS value close to or even below zero. Therefore, it can be inferred that the reason for the low genetic diversity of Z. tyaihyonii is probably the effect of genetic drift. Many limestone (including dolomites) areas are destroyed each year due to mining, and roadsides and mountain edges, which this species prefers, are also areas with very high human interference. For these reasons, many populations of this species, and many individuals within each population, would have disappeared in a relatively short period of time.
In a previous study based on the inter simple sequence repeat (ISSR) method [22], the genetic diversity (Shannon’s index (I) = 0.336) of this species was evaluated as relatively high, in contrast to the findings of this study. However, a direct comparison cannot be made because the mean values of genetic parameters may differ depending on the markers used in the analysis [37]. However, since this study was conducted including almost all native populations, we believe that the reliability of our study results will be higher than that of the previous study.
The lowest He value among the populations of Z. tyaihyonii was observed in SH (He = 0.170), followed by SC (He = 0.225) and TK (He = 0.245). SH is located in the southernmost region of the distribution range of Z. tyaihyonii and is the most geographically isolated of all populations (approximately 30 km from the nearest population, YC). Additionally, the size of this population was the smallest (habitat size: approximately 250 m2, number of ramets: fewer than 40) among the investigated populations. Additionally, SC is located the farthest north among the Z. tyaihyonii populations and was confirmed to have the second smallest population size (after SH). Therefore, the low genetic diversity in these populations is thought to be due to their small size and repeated founder events [46,47,48].

3.2. Genetic Differentiation and Population Structure

Two important parameters, gene flow (Nm) and the genetic differentiation coefficient (FST), are employed to assess the genetic structure of populations, and they are negatively correlated [14,49,50]. Our data also showed this trend (Figure S1). According to Wright [51], Nm is divided into three grades, high (≥1.0), medium (0.250–0.99) and low (0.0–0.249), and when Nm > 1 there is gene flow between populations [39,52]. Additionally, Wright [51] proposed that if the FST value of the populations is between 0 and 0.05, there is no genetic differentiation among populations; if the FST value is between 0.05 and 0.15, they are moderately differentiated; if the FST value is between 0.15 and 0.25, they are highly differentiated. The results of this study suggested that there was a high level of gene flow between all pairs of populations except those including SH. Additionally, the results showed a moderate level of genetic differentiation between BS, CW, TG and YC, and a high level between a population and SH or SC. Flowers of Z. tyaihyonii are entomophilous (pollinated by insects), and fruits with elongated calyx lobes are dispersed by wind [53,54]. Since the fruits are relatively large (approximately 5 mm) and cannot spread far [22], the high gene flow detected in this study is probably explained by insect pollination. Unfortunately, there have been no studies on the pollinators of this species, so further research is needed.
The AMOVA results (p < 0.001) supported a high level of population differentiation and showed major molecular variance within individuals rather than among populations. In outcrossing and long-lived plants in general, most genetic variation exists within populations, while selfing plants maintain the majority of genetic variation among populations [55]. Therefore, these results suggest that this species maintains its populations mainly by seed propagation.
Gardner and Mangel [56] predicted that favorable habitats would promote clonal growth over sexual reproduction. Additionally, Zhang and Zhang [57] reported that most resources should be allocated to sexual reproduction in habitats with changing environmental conditions and intense competition, whereas clonal growth should be dominant in stable habitats. Z. tyaihyonii grows naturally in only a very limited portion of the dolomitic limestone areas in the Republic of Korea [4,7,8,9,10,23]. Thus, this species appears to prefer the environmental characteristics offered by dolomitic limestone areas rather than being able to grow only in dolomite areas. Dolomite soils are rich in Mg and poor in nutrients, and when tectonic or weathering processes generate skeletal soils, predominantly sandy or gravelly in texture, they further complicate water retention, and as a result, make them very dry [58,59,60]. They differ chemically from their non-carbonate counterparts primarily in that they have a higher pH, and lower Fe, P and K [61]. Additionally, the dolomite distribution area is characterized by undeveloped crevices, and the thickness of the soil layer is generally less than 20 cm, which is unsuitable for the distribution of woody plants with deep root [62]. This probably provided a very suitable environment for the settlement of high light-demanding plants such as Z. tyaihyonii. However, the development of such vegetation would have made it easy for nutrients to accumulate in the soil, which would have facilitated the influx of competing plants, including subtrees and trees. Because of the consequences from these processes, this species is believed to maintain populations by seed propagation rather than by vegetative propagation.
A variety of methods are used to detect genetic diversity and population structure [63,64,65,66,67], and Wang [50] suggested combining three effective techniques, PCoA, STRUCTURE analysis and the UPGMA technique, to obtain reliable results. The STRUCTURE analysis in this study optimally divided the six selected populations into six clusters (Figure 2). This pattern was strongly supported by the UPGMA (Figure 4) result. These results will be useful in identifying important management units for effective conservation strategies.

3.3. Implications for the Conservation of Z. tyaihyonii

In this study, we evaluated the level and degree of genetic variation within and among populations, as well as the connectedness among populations of Z. tyaihyonii to provide useful information for the effective conservation planning of this endemic and rare plant. Genetic diversity is especially important for preserving the latent evolutionary capacity of a species to deal with changing environments [68]. In addition, information about genetic variation within and among populations in endangered and rare plants plays an important role in the process of formulating conservation and management strategies [69]. Z. tyaihyonii has a very low evolutionary potential to adapt to changing environmental conditions due to its low genetic diversity. Additionally, the results of this study suggested that inbreeding does not represent an immediate danger for this species, but genetic drift would have had a significant impact on population decline. The greatest reason for the low genetic diversity of this species is believed to be bottlenecks caused by the direct destruction of habitats by human interference, such as limestone quarries including dolomites, related facility construction, road construction, and cultivation activities. Additionally, the interspecies competition that accompanies the vegetation succession process was also considered to have a significant impact. For this species to be conserved naturally in situ, therefore, priority should be given to directly removing competing plants and minimizing disturbance by humans.
Protection of trailing-edge populations should be prioritized because the prolonged isolation and successful persistence of such groups suggest their evolutionary potential, which can be useful for the long-term conservation of genetic diversity and phylogenetic history of the species [34,70]. Additionally, isolated populations may accumulate through selective and stochastic processes, the genetic and chromosomal differences that render them independent and distinctive evolutionary entities, and if speciation involves few major changes promulgated by selection and/or genetic drift in small populations, speciation may be relatively rapid, perhaps saltational [71,72]. SH is believed to be more important than other populations, as it is located at the southernmost limit of the distribution range of this species. This population was revealed as the most heterogeneous and isolated by various results from this study, such as genetic differentiation, analysis, barrier reconstruction, STRUCTURE analysis, PCoA and the UPGMA technique. These findings suggest that transplanting individuals from SH into other populations and vice versa is not an advisable conservation strategy for this species. SH has a very high risk of natural culling due to its very small size (fewer than 40 individuals) and a very low genetic diversity (He = 0.170). Therefore, more active efforts to protect this population will be needed, such as setting up conservation areas and conducting periodic monitoring.
Given its geographic location at the northernmost limit of the distribution range of the species, the SC population is not recommended as a source of transplants, as previously suggested for SH. SC showed high gene flow with other paired populations except for SH and showed moderate genetic differentiation from BS (Figure S1). This probably means that pollen is transported by pollinators between this population and other populations except for SH (at least between this population and BS).
A recommended conservation strategy for endangered plants, in addition to in situ conservation, is the establishment of ex situ gene banks for each population in both the field and laboratory. Although this species is not listed as an endangered wild plant under legal protection in Korea [73], it is a serious challenge that most of its populations are adjacent to limestone quarries, including dolomites, villages, and roadsides, and are prone to destruction. Given this current situation, we believe that ex situ conservation of this species should be considered. For ex situ conservation of this species, conservation measures that include all populations with the goal of maximizing the collection of private alleles in each population would be most appropriate because the STRUCTIRE and UPGMA results showed that each population formed an independent clade, and the genetic differentiation between populations was relatively high (Figure 4 and Figure S1). Otherwise, ex situ conservation was observed by targeting private alleles of the four genetic groups (the first and second groups were SC and SH alone, respectively; the third group comprised BS and YC; and the last group consisted of CW and TG) identified in the UPGMA analysis (Figure 4).

4. Materials and Methods

4.1. Plant Materials

Since Z. tyaihyonii is not an endangered or protected species, plant materials were collected without permission. Distribution information for sampling was confirmed through the literature and specimens from the National Institute of Biological Resources and the Korea National Arboretum. A total of 94 individual plants were collected from six natural populations, and 14 to 22 individuals in each population were sampled at least 5 m apart to minimize the likelihood of sampling clones. During field sampling, the sampled site and altitude were recorded (Figure 1 and Table S1). One fresh leaf per individual was placed in plastic bags and placed on ice to be transported to the laboratory as soon as possible, where they were stored at −20 °C until DNA extraction. The voucher specimens for each population were deposited in the Sangji University Herbarium (SJUH).

4.2. DNA Extraction, Library Preparation, and Sequencing

Total genomic DNA was extracted using the DNeasy Plant Mini Kit (Qiagen Inc., Valencia, CA, USA), following the instructions of the manufacturer. The quality and quantity of extracted DNA were evaluated with a LabChip GX II (PerkinElmer Inc., Waltham, MA, USA), and DNA was visualized on a 1% agarose gel. Samples that passed quality and quantity filters were subsequently sent to Xenotype Inc. (Daejeon, Republic of Korea) for GBS library construction [27]. Using this approach, samples were digested with methylation-sensitive ApeKI restriction enzyme and barcoded with sequence adapters before pooling into sets of 94 individuals. Each library was amplified by PCR and sequenced in a single lane on a HiSeq X instrument (Illumina Inc., San Diego, CA, USA) using 150 bp paired-end sequencing runs.

4.3. Sequence Analyses, Bioinformatics, and SNP Identification

NGSEP Wizard is a tool that implements all the steps necessary to obtain a population variant file with just one run screen, starting from raw sequencing data [74]. We obtained the VCFfile of SNPs using NGSEP v4.2.1. SNPs were removed using VCFtools v.4.2 [75] on the basis of the following filtering criteria: SNP missing data ≥ 50%, minor allele count ≥ 3, minimum quality score < 30, minimum mean depth ≤ 3, individuals missing data ≤ 50%, SNP data < 95%, minor allele frequency < 5%, minimum mean depth ≤ 20, and p value for Hardy–Weinberg equilibrium ≤ 0.01. Then, linkage disequilibrium (LD) (r2 > 0.8) was computed using the Plink v. 1.07 software [76]. The online program PGDSpider v.2.1.1.5 [77] was used to convert different file formats for all downstream analyses described below.

4.4. Data Analyses

The number of alleles (Na), the number of effective alleles (Ne), Shannon’s information index (I), observed heterozygosity (Ho), expected heterozygosity (He), AMOVA, gene flow (Nm), and PCoA were computed with the GenAlEx 6.5 software [78,79]. PCoA was visualized 3-dimensionally using the R package Scatterplot3d [80], and the inbreeding coefficient (GIS) was calculated by Genodive v.2.0b27 [81]. Population genetic structure was analyzed using a Bayesian clustering analysis method conducted in STRUCTURE v2.3.4 software [82]. An admixture model was used to estimate the number of population clusters (K) ranging from one to six, and each STRUCTURE run was performed with a burn-in size of 50,000 and 100,000 MCMC iterations with 10 runs per K value. Results were fed into StructureSelector [83] to identify the most likely number of clusters present based on the MedMeak, MaxMeak, MedMedK and MaxMedK criteria [84]. The results of population clustering were aligned and visualized using the CLUMPAK webserver [85]. The genetic relatedness of individuals was calculated using poppr [86] and adegenet [87] in R 4.0.4 [88]; then, a cladogram was constructed based on the UPGMA algorithm in R 4.0.4 [88]. Monmonier’s maximum difference algorithm was used with BARRIER v. 2.2 [89] to explore the geographical sites exhibiting maximal genetic discontinuities among populations. Sampling sites were mapped based upon geographical coordinates using this program, with barriers being indicated on the map by assessing maximum values within a population-pairwise genetic distance matrix.

5. Conclusions

A total of 3088 high-density SNPs were employed to estimate the genetic diversity and population structure in 95 Z. tyaihyonii accessions from six populations. This species maintained low genetic diversity levels, high genetic differentiation, and high gene flow among populations except for SH. This pattern mainly results from human interference, which gives this species a very low evolutionary potential to adapt to changing environmental conditions. For this species to be conserved naturally in situ, directly removing competing plants and minimizing disturbance by humans are very important. Additionally, special management of SH, which is highly isolated geographically and genetically, should also be included. This is the first study of the genetic diversity and population structure of Z. tyaihyonii using genotype-by-sequencing (GBS). The results of this study and our suggestions for conservation will serve as important information for the population conservation and management of this species.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants12010171/s1. Figure S1: Genetic differentiation coefficient FST (below diagonal) and gene flow Nm (above diagonal) between populations, Table S1: The sampling information of six populations of Zabelia tyaihyonii.

Author Contributions

Conceptualization, H.K., K.-S.C. and K.-A.K.; methodology, J.-H.L., K.-S.C. and K.-A.K.; software, H.K., S.-M.A., Y.-J.P., Y.-B.L. and K.-A.K.; validation, J.-H.L. and K.-S.C.; formal analysis, H.K., S.-M.A., Y.-J.P., Y.-B.L. and K.-S.C.; data curation, K.-A.K.; funding acquisition, K.-S.C. and K.-A.K.; writing—original draft preparation, H.K. and K.-S.C.; writing—review and editing, K.-S.C. and K.-A.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1I1A1A01064395), and the National Institute of Biological Resources of Korea (NIBR-202206201).

Data Availability Statement

Not applicable.

Acknowledgments

We would like to thank Ha-Rim Lee and Jae-Hyeong Kim for field assistance. We also thank three anonymous reviewers for their helpful comments and suggestions.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Nakai, T. Tentamen systematic carprifoliacearum japonicarum. Journ. Coll. Sci. Univ. 1921, 42, 58. [Google Scholar]
  2. Hisauchi, K.; Hara, H. On the genus Zabelia Makino. J. Jap. Bot. 1954, 29, 143–144. [Google Scholar]
  3. Ikuse, M.; Kurosawa, S. Notes on sect. Zabelia Rehder of the genus Abelia. J. Jap. Bot. 1954, 29, 107–111. [Google Scholar]
  4. Kim, K.A.; Jang, S.K.; Cheon, K.S.; Seo, W.B.; Yoo, K.O. Environmental and ecological characteristics of habitats of Abelia tyahyoni Nakai. Korean J. Plant Taxon. 2010, 40, 135–144. [Google Scholar] [CrossRef]
  5. Won, H.S.; Kim, T.J. Zabelia. In The Genera of Vascular Plants of Korea; Park, J.W., Ed.; Academy Publishing Co.: Seoul, Republic of Korea, 2007; pp. 1242–1243. [Google Scholar]
  6. Chung, G.Y.; Chang, K.S.; Chung, J.M.; Choi, H.J.; Paik, W.K.; Hyun, J.O. A checklist of endemic plants on the Korean Peninsula. Korean J. Plant Taxon. 2017, 47, 264–288. [Google Scholar] [CrossRef] [Green Version]
  7. National Institute of Biological Resources. Red Data Book of Endangered Vascular Plants in Korea; National Institute of Biological Resources: Incheon, Republic of Korea, 2017; p. 128. [Google Scholar]
  8. Korea National Arboretum. The National Red List of Vascular Plant in Korea; Korea National Arboretum: Pocheon, Republic of Korea, 2021; p. 275. [Google Scholar]
  9. National Institute of Ecology. Floristic Target Species (FT Species) in Korea; National Institute of Ecology: Seocheon, Republic of Korea, 2018; p. 112. [Google Scholar]
  10. Kim, J.D.; Lee, H.J.; Lee, D.H.; Byeon, J.G.; Park, B.J.; Heo, T.I. Characteristics of environmental factors and vegetation community of Zabelia tyaihyonii (Nakai) Hisauti & H.Hara among the target plant species for conservation in Baekdudaegan. J. Korean Soc. For. Sci. 2022, 111, 201–223. [Google Scholar]
  11. Oh, B.U.; Jo, D.G.; Kim, K.S.; Jang, C.G. Endemic Vascular Plants in the Korean Peninsula; Korea National Arboretum: Pochen, Republic of Korea, 2005. [Google Scholar]
  12. Coelho, N.; Goncalves, S.; Romano, A. Endemic plant species conservation: Biotechnological approaches. Plants 2020, 9, 345. [Google Scholar] [CrossRef] [Green Version]
  13. Chang, C.S. Genetic analysis and conservation biology of rare plants in Korea. Annu. Rep. Res. Agric. Life Sci. 1998, 2, 200–204. [Google Scholar]
  14. Hamrick, J.L.; Godt, M.J.W.; Murawski, D.A.; Loveless, M.D. Correlations between species traits allozyme diversity: Implications for conservation biology. In Genetics and Conservation of Rare Plants; Falk, D.A., Holsinger, K.E., Eds.; Oxford University Press: New York, NY, USA, 1991; pp. 76–86. [Google Scholar]
  15. Barrett, S.C.H.; Kohn, J.R. Genetic and evolutionary consequences of small population sizes in plant: Implications for conservation. In Genetics and Conservation of Rare Plants; Falk, D.A., Holsinger, K.E., Eds.; Oxford University Press: New York, NY, USA, 1991; pp. 3–30. [Google Scholar]
  16. Chung, Y.H.; Sun, B.Y. Monographic study on the endemic plants of Korea IV. Taxonomy and interspecific relationships of the genus Abelia. Korean J. Plant Taxon. 1984, 14, 137–152. [Google Scholar] [CrossRef]
  17. Paik, W.K.; Lee, W.T. A taxonomic study of the genus Abelia in Korea. Korean J. Plant Taxon. 1989, 19, 139–156. [Google Scholar] [CrossRef]
  18. Kim, T.J.; Sun, B.Y.; Suh, Y. Palynology and cytotaxonomy of the genus Abelia s. l., Caprifoliaceae. Korean J. Plant Taxon. 2021, 31, 91–106. [Google Scholar] [CrossRef]
  19. Landrein, S.; Prenner, G.; Chase, M.W.; Clarkson, J.J. Abelia and relatives: Phylogenetics of Linnaeeae (Dipsacales-Caprifoliaceae s.l.) and a new interpretation of their inflorescence morphology. Bot. J. Linn. 2012, 169, 692–713. [Google Scholar] [CrossRef] [Green Version]
  20. Lee, W.; Youn, J.S.; Kim, S.C.; Pak, J.H. The complete chloroplast genome sequence of limestone endemic, Zabelia tyahyoni (Caprifoliaceae), in Korea. Mitochondrial DNA B Resour. 2020, 5, 1947–1948. [Google Scholar] [CrossRef] [Green Version]
  21. Wang, H.X.; Liu, H.; Moore, M.J.; Landrein, S.; Liu, B.; Zhu, Z.X.; Wang, H.F. Plastid phylogenomic insights into the evolution of the Caprifoliaceae s.l. (Dipsacales). Mol. Phylogenetics Evol. 2020, 142, 106641. [Google Scholar] [CrossRef] [PubMed]
  22. Jeong, J.H.; Kim, K.S.; Lee, C.H.; Kim, Z.S. Genetic diversity and special structure in populations of Abelia tyaihyoni. J. Korean For. Soc. 2007, 96, 667–675. [Google Scholar]
  23. Chae, H.H. Conservation Ecology on the Rare Plant Thalictrum petaloideum L. and the Endemic Plant Zabelia tyaihyoni (Nakai) Hisauti & Hara in Korea. Ph.D. Thesis, Gangneung-Wonju National University, Gangneung, Republic of Korea, 2021. [Google Scholar]
  24. Schuster, S.C. Next-generation sequencing transforms today’s biology. Nat. Methods 2008, 5, 16–18. [Google Scholar] [CrossRef]
  25. Wang, N.; Yuan, Y.; Wang, H.; Yu, D.; Liu, Y.; Zhang, A.; Gowda, M.; Nair, S.K.; Hao, Z.; Lu, Y.; et al. Applications of genotyping-by-sequencing (GBS) in maize genetics and breeding. Sci. Rep. 2020, 10, 16308. [Google Scholar] [CrossRef] [PubMed]
  26. Scheben, A.; Batley, J.; Edwards, D. Genotyping-by-sequencing approaches to characterize crop genomes: Choosing the right tool for the right application. Plant. Biotechnol. J. 2017, 15, 149–161. [Google Scholar] [CrossRef] [Green Version]
  27. Elshire, R.J.; Glaubitz, J.C.; Sun, Q.; Poland, J.A.; Kawamoto, K.; Buckler, E.S.; Mitchell, S.E. A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 2011, 6, e19379. [Google Scholar] [CrossRef] [Green Version]
  28. Gouesnard, B.; Negro, S.; Laffray, A.; Glaubitz, J.; Melchinger, A.; Revilla, P.; Moreno-Gonzalez, J.; Madur, D.; Combes, V.; Tollon-Gordet, C.; et al. Genotyping-by-sequencing highlights original diversity patterns within a European collection of 1191 maize flint lines, as compared to the maize USDA genebank. Theor. Appl. Genet. 2017, 130, 2165–2189. [Google Scholar] [CrossRef]
  29. Hamon, P.; Grover, C.; Davis, A.; Rakotomalala, J.J.; Albert, V.; Sreenath, H.; Stoffelen, P.; Mitchell, S.; Couturon, E.; Hamon, S.; et al. Genotyping-by-sequencing provides the first well-resolved phylogeny for coffee (Coffea) and insights into the evolution of caffeine content in its species GBS coffee phylogeny and the evolution of caffeine content. Mol. Phylogenet. Evol. 2017, 109, 351–361. [Google Scholar] [CrossRef] [PubMed]
  30. Eltaher, S.; Sallam, A.; Belamkar, V.; Emara, H.A.; Nower, A.A.; Salem, K.F.M.; Poland, J.; Baenziger, P.S. Genetic diversity and population structure of F3:6 Nebraska winter wheat genotypes using genotyping-by-sequencing. Front. Genet. 2018, 9, 76. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Hong, U.V.T.; Tamiru-Oli, M.; Hurgobin, B.; Okey, C.R.; Abreu, A.R.; Lewsey, M.G. Insights into opium poppy (Papaver spp.) genetic diversity from genotyping-by-sequencing analysis. Sci. Rep. 2022, 12, 111. [Google Scholar] [CrossRef] [PubMed]
  32. Jara-Arancio, P.; Carvalho, C.S.; Carmona-Ortiz, M.R.; Bustamante, R.O.; Schmidt Villela, P.M.; Andrade, S.C.S.; Peña-Gómez, F.T.; González, L.A.; Fleury, M. Genetic diversity and population structure of Jubaea chilensis, an endemic and monotype gender from Chile, based on SNP markers. Plants 2022, 11, 1959. [Google Scholar] [CrossRef] [PubMed]
  33. Kumar, B.; Rakshit, S.; Kumar, S.; Singh, B.K.; Lahkar, C.; Jha, A.K.; Kumar, K.; Kumar, P.; Choudhary, M.; Singh, S.B.; et al. Genetic diversity, population structure and linkage disequilibrium analyses in tropical maize using genotyping by sequencing. Plants 2022, 11, 799. [Google Scholar] [CrossRef]
  34. Lee, J.H.; Ong, H.G.; Kim, B.Y.; Kim, Y.I.; Jung, E.K.; Chung, M.G.; Kim, Y.D. Population genomics study for the conservation management of the endangered shrub Abeliophyllum distichum. Conserv. Genet. 2022, 23, 683–697. [Google Scholar] [CrossRef]
  35. Zhang, X.; Liu, Y.H.; Wang, Y.H.; Shen, S.K. Genetic diversity and population structure of Rhododendron rex subsp. Rex inferred from microsatellite markers and chloroplast DNA sequences. Plants 2020, 9, 338. [Google Scholar]
  36. Feng, X.Y.; Wang, Y.; Gong, X. Genetic diversity, genetic structure and demographic history of Cycas simplicipinna (Cycadaceae) assessed by DNA sequences and SSR markers. BMC Plant Biol. 2014, 14, 187. [Google Scholar] [CrossRef] [Green Version]
  37. Ellstrand, N.C.; Elam, D.R. Population genetic consequences of small population size: Implications for plant conservation. Annu. Rev. Ecol. Syst. 1993, 24, 217–242. [Google Scholar] [CrossRef]
  38. Yun, S.A.; Kim, S.C. Genetic diversity and structure of Saussurea polylepis (Asteraceae) on continental islands of Korea: Implications for conservation strategies and management. PLoS ONE 2021, 16, e0249752. [Google Scholar] [CrossRef]
  39. Jin, C.; Huixia, K.; Shubin, D. Population genetic structure and gene flow of rare and endangered Tetraena mongolica Maxim. Revealed by reduced representation sequencing. BMC Plant Biol. 2020, 20, 391. [Google Scholar]
  40. Liu, F.; Hong, Z.; Xu, D.; Jia, H.; Zhang, N.; Liu, X.; Yang, Z.; Lu, M. Genetic diversity of the endangered Dalbergia odorifera revealed by SSR markers. Forests 2019, 10, 225. [Google Scholar] [CrossRef] [Green Version]
  41. Hedrick, P.W. Genetics of Populations, 2nd ed.; Jones and Bartlett Publishers: Sudbury, MA, USA, 2000; p. 675. [Google Scholar]
  42. Leimu, R.; Mutikainen, P.; Koricheva, J.; Fischer, M. How general are positive relationships between plant population size, fitness and genetic variation. J. Ecol. 2006, 94, 942–952. [Google Scholar] [CrossRef]
  43. Velasco-García, M.V.; Ramírez-Herrera, C.; López-Upton, J.; Valdez-Hernández, J.I.; López-Sánchez, H.; López-Mata, L. Diversity and Genetic Structure of Dioon holmgrenii (Cycadales: Zamiaceae) in the Mexican Pacific Coast Biogeographic Province: Implications for Conservation. Plants 2021, 10, 2250. [Google Scholar] [CrossRef] [PubMed]
  44. Swensen, S.M.; Allan, G.J.; Howe, M.; Elisens, W.J.; Junak, S.A.; Rieseberg, L.H. Genetic analysis of the endangered island endemic Malacothamnus fasciculatus (Nutt.) Greene var. nesioticus (Rob.) Kearn. (Malvaceae). Conserv Biol. 1995, 9, 404–415. [Google Scholar]
  45. Sydes, M.A.; Peakall, R. Extensive clonality in the endangered shrub Haloragodendron lucasii (Haloragaceae) revealed by allozymes and RAPDs. Mol Ecol. 1998, 7, 87–93. [Google Scholar] [CrossRef]
  46. Sagarin, R.D.; Gaines, S.D. The “abundant centre” distribution: To what extent is it a biogeographical rule? Ecol Lett. 2002, 5, 137–147. [Google Scholar] [CrossRef]
  47. Petit, R.J.; Aguinagalde, I.; de Beaulieu, J.L.; Bittkau, C.; Brewer, S.; Cheddadi, R.; Ennos, R.; Fineschi, S.; Grivet, D.; Lascoux, M.; et al. Glacial refugia: Hotspots but not melting pots of genetic diversity. Science 2003, 300, 1563–1565. [Google Scholar] [CrossRef] [Green Version]
  48. Eckert, C.G.; Samis, K.E.; Lougheed, S.C. Genetic variation across species’ geographical ranges: The central–marginal hypothesis and beyond. Mol Ecol. 2008, 17, 1170–1188. [Google Scholar] [CrossRef]
  49. Grant, V. The evolutionary process: A critical study of evolutionary theory. Stud. Hist. Phil. Sci. 1986, 17, 65–98. [Google Scholar]
  50. Wang, S.Q. Genetic diversity and population structure of the endangered species Paeonia decomposita endemic to China and implication for its conservation. BMC Plant Biol. 2020, 20, 510. [Google Scholar] [CrossRef] [PubMed]
  51. Wright, S. Evolution and the Genetic of Population, Variability within and among Natural Populations; University of Chicago Press: Chicago, IL, USA, 1978; Volume 4, pp. 213–220. [Google Scholar]
  52. Govindaraju, D.R. Relationship between dispersal ability and levels of gene flow in plants. Oikos 1988, 52, 31–35. [Google Scholar] [CrossRef]
  53. Manchester, S.R.; Donoghue, M.J. Winged fruits of Linnaeeae (Caprifoliaceae) in the tertiary of western North America: Diplodipelta gen. nov. Int. J. Plant Sci. 1995, 156, 709–722. [Google Scholar] [CrossRef]
  54. Nam, J.I.; Kim, M.S.; Song, J.H.; Seo, J.M.; Choi, G.E.; Kim, Y.K. Analysis of morphological characteristics and variation in five populations of Zabelia tyaihyonii in South Korea. J. People Plants Environ. 2021, 24, 619–628. [Google Scholar] [CrossRef]
  55. Nybom, H. Comparison of different nuclear DNA markers for estimating intraspecific genetic diversity in plants. Mol. Ecol. 2004, 13, 1143–1155. [Google Scholar] [CrossRef] [PubMed]
  56. Gardner, S.N.; Mangel, M. Modeling investments in seeds, clonal offspring, and translocation in a clonal plant. Ecology 1999, 80, 1202–1220. [Google Scholar] [CrossRef]
  57. Zhang, Y.F.; Zhang, D.Y. Asexual and sexual reproductive strategies in clonal plant. Acta Phytoecol. Sin. 2006, 30, 174–183. [Google Scholar] [CrossRef]
  58. Allison, J.R.; Stevens, T.E. Vascular flora of Ketona dolomite outcrops in Bibb Country, Alabama. Castanea 2001, 66, 154–205. [Google Scholar]
  59. Jones, H.T. Magnesium as a plant nutrient. Chem. Ind. 1951, 15, 1108–1110. [Google Scholar]
  60. Mota, J.F.; Medina-Cazorla, J.M.; Mavarro, F.B.; Pérez-Gracía, F.J.; Pérez-Latorre, A.; Sánchez-Gómez, P.; Torres, J.A.; Benavente, A.; Blanca, G.; Gil, C.; et al. Dolomite flora of the Baetic Ranges glades (South Spain). Flora 2008, 203, 359–375. [Google Scholar] [CrossRef]
  61. Mota, J.; Merlo, E.; Martínez-Hernández, F.; Mendoza-Fernández, A.J.; Pérez-García, F.J.; Salmerón-Sánchez, E.S. Plant on rich-magnesium dolomite barrens: A global phenomenon. Biology 2021, 10, 38. [Google Scholar] [CrossRef]
  62. Liu, H.; Jiang, Z.; Dai, J.; Wu, X.; Peng, J.; Wang, H.; Meersmans, J.; Green, S.M.; Quine, T.A. Rock crevices determine woody and herbaceous plant cover in the karst critical zone. Sci. China Earth Sci. 2019, 62, 1756–1763. [Google Scholar] [CrossRef]
  63. Zhang, P.; Zhou, Z.C.; Jin, G.Q.; Fan, H.H.; Hu, H.B. Genetic diversity analysis and provenance zone allocation of Schima superba in China using RAPD markers. Sci. Silvae Sin. 2006, 42, 38–42. [Google Scholar]
  64. Zong, X.X.; Guan, J.P.; Gu, J.; Wang, H.; Ma, Y. Differentiation on population structure and genetic diversity of pea core collections separately constituted from Chinese land races and international genetic resources. J. Plant Genet. Resour. 2009, 10, 347–353. [Google Scholar]
  65. Tan, X.J.; Wu, Z.K.; Cheng, W.D. Association analysis and its application in plant genetic research. Chin. Bull. Bot. 2011, 46, 108–118. [Google Scholar]
  66. Zhang, J.S.; Yang, C.Y.; Wu, C.; Hu, Z.Y.; Wang, R.G.; Guo, Y.S.; Ren, X.L. Study on genetic diversity, population structure and specificity of subpopulations of fluecured tobacco germplasm. Acta Tab. Sin. 2012, 18, 21–49. [Google Scholar]
  67. Lai, G.; Lai, Z.; Liu, W.; Ye, W.; Lin, Y.; Liu, S.; Chen, Y.; Zhang, Z.; Wu, G. ISSR analysis of 3 natural populations of the wild banana distributed in the middle of Fujian province based on NTSYS and STRUCTURE. Chin. J. Trop. Crops 2014, 35, 223–231. [Google Scholar]
  68. Booy, G.; Hendriks, R.J.J.; Smulders, M.J.M.; Van Groenendael, J.M.; Vosman, B. Genetic diversity and the survival or populations. Plant Biol. 2000, 2, 379–395. [Google Scholar] [CrossRef]
  69. Milligan, B.G.; Leebens-Mack, J.; Strand, A.E. Conservation genetics: Beyond the maintenance of marker diversity. Mol Ecol. 1994, 3, 423–435. [Google Scholar] [CrossRef]
  70. Hampe, A.; Petit, R.J. Conserving biodiversity under climate change: The rear edge matters. Ecol. Lett. 2005, 8, 461–467. [Google Scholar] [CrossRef] [Green Version]
  71. Carson, H.L.; Templeton, A.R. Genetic revolution in relation to speciation phenomena: The founding of new populations. Ann. Rev. Ecol. Syst. 1984, 15, 97–131. [Google Scholar] [CrossRef]
  72. Levin, D.A. Metapopulations: An arena for local speciation. J. Evol. Biol. 1995, 8, 635–644. [Google Scholar] [CrossRef]
  73. Heywood, V.H.; Iriondo, J.M. Plant conservation: Old problems, new perspectives. Biol. Conserv. 2003, 113, 321–335. [Google Scholar] [CrossRef]
  74. Perea, C.; De La Hoz, J.F.; Cruz, D.F.; Lobaton, J.D.; Izquierdo, P.; Quintero, J.C.; Raatz, B.; Duitama, J. Bioinformatic analysis of genotype by sequencing (GBS) data with NGSEP. BMC Genom. 2016, 17, 498. [Google Scholar] [CrossRef] [Green Version]
  75. Danecek, P.; Auton, A.; Abecasis, G.; Albers, C.A.; Banks, E.; DePristo, M.A.; Handsaker, R.E.; Lunter, G.; Marth, G.T.; Sherry, S.T.; et al. 1000 Genomes Project Analysis Group. The variant call format and VCFtools. Bioinformatics 2011, 27, 2156–2158. [Google Scholar] [CrossRef]
  76. Purcell, S.; Neale, B.; Todd-Brown, K.; Thomas, L.; Ferreira, M.A.R.; Bender, D.; Maller, J.; Sklar, P.; de Bakker, P.I.W.; Daly, M.J.; et al. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 2007, 81, 559–575. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. Lischer, H.E.L.; Excoffier, L. PGDSpider: An automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics 2012, 28, 298–299. [Google Scholar] [CrossRef]
  78. Peakall, R.; Smouse, P.E. GENALEX 6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 2006, 6, 288–295. [Google Scholar] [CrossRef]
  79. Peakall, R.; Smouse, P.E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—An update. Bioinformatics 2012, 28, 2537–2539. [Google Scholar] [CrossRef] [Green Version]
  80. Ligges, U.; Mächler, M. Scatterplot3d-an R package for visualizing multivariate data. J. Stat. Sofw. 2003, 8, 1–20. [Google Scholar]
  81. Meirmans, P.G.; Van Tienderen, P.H. GENOTYPE and GENODIVE: Two programs for the analysis of genetic diversity of asexual organisms. Mol. Ecol. Notes 2004, 4, 792–794. [Google Scholar] [CrossRef]
  82. Evanno, G.; Regnaut, S.; Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 2005, 14, 2611–2620. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Li, Y.L.; Liu, J.X. StructureSelector: A web-based software to select and visualize the optimal number of clusters using multiple metods. Mol. Ecol. Resour. 2018, 18, 176–177. [Google Scholar] [CrossRef] [PubMed]
  84. Puechmaille, S.J. The program structure does not reliably recover the correct population structure when sampling is uneven: Subsampling and new estinators alleviate the problem. Mol. Ecol. Resour. 2016, 16, 608–627. [Google Scholar] [CrossRef]
  85. Kopelman, N.M.; Mayzel, J.; Jakobsson, M.; Rosenberg, N.A.; Mayrose, I. CLUMPAK: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 2015, 15, 1179–1191. [Google Scholar] [CrossRef] [Green Version]
  86. Kamvar, Z.N.; Tabima, J.F.; Grünwald, N.J. Poppr: An R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2014, 2, e281. [Google Scholar] [CrossRef] [Green Version]
  87. Jombart, T. Adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 2008, 24, 1403–1405. [Google Scholar] [CrossRef] [Green Version]
  88. Jombart, T.; Ahmed, I. Adegenet 1.3-1: New tools for the analysis of genome-wide SNP data. Bioinformatics 2011, 27, 3070–3071. [Google Scholar] [CrossRef]
  89. Manni, F.; Guerard, E.; Heyer, E. Geographic patterns of (genetic, morphologic, linguistic) variation: How barriers can be detected by using Monmonier’s algorithm. Hum. Biol. 2004, 76, 173–190. [Google Scholar] [CrossRef]
Plants 12 00171 g001 550
Figure 1. Photos of habitat (A), flowers (B) and fruits (C), of Taihyun’s abelia (Zabelia tyaihyonii), and (D) geographic distribution of six populations of Zabelia tyaihyonii, and genetic barriers (red lines) computed from pairwise FST. Gray lines correspond to hypothetical boundaries between populations, which are labeled with corresponding codes.
Figure 1. Photos of habitat (A), flowers (B) and fruits (C), of Taihyun’s abelia (Zabelia tyaihyonii), and (D) geographic distribution of six populations of Zabelia tyaihyonii, and genetic barriers (red lines) computed from pairwise FST. Gray lines correspond to hypothetical boundaries between populations, which are labeled with corresponding codes.
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Plants 12 00171 g002 550
Figure 2. Population structure of 94 Z. tyaihyonii individuals from 6 different populations. (A) The optimal K number indicated by alternative measures MedMeak, MaxMeak, MedMedK and MaxMedK applied in StructureSelector and (B) STRUCTURE bar plot (K from 2 to 6). Each bar represents a single individual and its proportion of assignment to each of the sample sites separated by solid black lines.
Figure 2. Population structure of 94 Z. tyaihyonii individuals from 6 different populations. (A) The optimal K number indicated by alternative measures MedMeak, MaxMeak, MedMedK and MaxMedK applied in StructureSelector and (B) STRUCTURE bar plot (K from 2 to 6). Each bar represents a single individual and its proportion of assignment to each of the sample sites separated by solid black lines.
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Plants 12 00171 g003 550
Figure 3. Results of principal coordinate analysis (PCoA) of genetic distances for all 94 genotyped individuals.
Figure 3. Results of principal coordinate analysis (PCoA) of genetic distances for all 94 genotyped individuals.
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Plants 12 00171 g004 550
Figure 4. A cladogram of the 94 Zabelia tyaihyonii accessions from six populations. Different colors represent different populations.
Figure 4. A cladogram of the 94 Zabelia tyaihyonii accessions from six populations. Different colors represent different populations.
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Table
Table 1. Estimates of genetic diversity within Zabelia tyaihyonii populations.
Table 1. Estimates of genetic diversity within Zabelia tyaihyonii populations.
Pop.NNa (±SE)Ne (±SE)I (±SE)Ho (±SE)He (±SE)GIS
BS211.881 (±0.006)1.428 (±0.006)0.406 (±0.004)0.266 (±0.003)0.263 (±0.003)0.014
CW181.821 (±0.007)1.419 (±0.006)0.384 (±0.004)0.262 (±0.004)0.252 (±0.003)−0.013
TG141.797 (±0.007)1.405 (±0.006)0.375 (±0.004)0.273 (±0.004)0.245 (±0.003)−0.079
SC141.671 (±0.008)1.380 (±0.007)0.339 (±0.005)0.267 (±0.005)0.225 (±0.003)−0.150
YC141.791 (±0.007)1.405 (±0.006)0.375 (±0.004)0.260 (±0.004)0.245 (±0.003)−0.025
SH131.441 (±0.009)1.299 (±0.007)0.249 (±0.005)0.209 (±0.005)0.170 (±0.004)−0.194
mean 1.734 (±0.003)1.389 (±0.003)0.355 (±0.002)0.256 (±0.002)0.233 (±0.001)−0.057
N, no. of samples; Na, no. of alleles; Ne, no. of effective alleles; I, Shannon’s information index; Ho, observed heterozygosity; He, expected heterozygosity; GIS, inbreeding coefficient; SE, corresponding standard error.
Table
Table 2. Results of analysis of molecular variance (AMOVA) and significance after 20,000 permutations.
Table 2. Results of analysis of molecular variance (AMOVA) and significance after 20,000 permutations.
SourceDfSSMSEst. Var.%F-Statisticsp ValueNm
Among populations514,276.1212855.22479.49017.00FST = 0.170p < 0.0011.221
Among individuals8833,547.943381.227−6.993−1.5FIS = −0.018p > 0.05
Within individuals9437,150.0395.213395.21384.50FIT = 0.155p < 0.001
Total18784,974.064 467.71100.00
Df, degrees of freedom; SS, sum of squares; MS, mean of squares; Est. Var., estimated variance; %, percentage of variation; Nm, inferred gene flow.
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Kang, H.; An, S.-M.; Park, Y.-J.; Lee, Y.-B.; Lee, J.-H.; Cheon, K.-S.; Kim, K.-A. Population Genomics Study and Implications for the Conservation of Zabelia tyaihyonii Based on Genotyping-By-Sequencing. Plants 2023, 12, 171. https://doi.org/10.3390/plants12010171

AMA Style

Kang H, An S-M, Park Y-J, Lee Y-B, Lee J-H, Cheon K-S, Kim K-A. Population Genomics Study and Implications for the Conservation of Zabelia tyaihyonii Based on Genotyping-By-Sequencing. Plants. 2023; 12(1):171. https://doi.org/10.3390/plants12010171

Chicago/Turabian Style

Kang, Halam, Sung-Mo An, Yoo-Jung Park, Yoo-Bin Lee, Jung-Hyun Lee, Kyeong-Sik Cheon, and Kyung-Ah Kim. 2023. "Population Genomics Study and Implications for the Conservation of Zabelia tyaihyonii Based on Genotyping-By-Sequencing" Plants 12, no. 1: 171. https://doi.org/10.3390/plants12010171

APA Style

Kang, H., An, S.-M., Park, Y.-J., Lee, Y.-B., Lee, J.-H., Cheon, K.-S., & Kim, K.-A. (2023). Population Genomics Study and Implications for the Conservation of Zabelia tyaihyonii Based on Genotyping-By-Sequencing. Plants, 12(1), 171. https://doi.org/10.3390/plants12010171

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