DOI: https://doi.org/10.21203/rs.3.rs-2189943/v1
Erythropalum scandens Blume, an emerging medicinal plant with great potential for drug development, also possesses high edible value. In this study, we investigated the genetic diversity of the germplasm of E. scandens obtained from different geographical locations using inter simple sequence repeat (ISSR) markers. For this purpose, 18 ISSR primer pairs with a distinct background and adequate polymorphism were selected. We established an optimal ISSR–PCR reaction system (20 µL) with the following parameters: 1 µL DNA template (60 ng·µL-1), 1.2 µL primers (10 µmol·µL-1), 10 µL MasterMix, and 7.8 µL H2O. A total of 183 loci were amplified using the 18 primer pairs, of which 121 (66.12%) indicated polymorphism. Moreover, 34 germplasms of E. scandens exhibited genetic similarity coefficients ranging from 0.7104 to 0.9563, genetic distances ranging from 0.0447 to 0.3420, Nei’s genetic diversity index of 0.1946, and Shannon’s information index of 0.2982, suggesting high intraspecific genetic diversity. UPGMA cluster and PCoA analyses distinguished the germplasm of E. scandens obtained from Guangxi from those collected from Guangdong, Hainan, Fujian, and Guizhou. However, the Mantel correlation analysis revealed that the genetic variation among the 34 germplasms of E. scandens was not significantly related to geographical distance. The analysis of the genetic background of wild and cultivated germplasms of E. scandens can help guide variety selection and breeding. Furthermore, the present study revealed the genetic background and affinities among 34 germplasms of E. scandens. Overall, our findings lay the foundation for the conservation and utilization of germplasm resources, identification and classification of varieties, and variety selection and improvement of E. scandens at the molecular level.
Erythropalum scandens Blume, a perennial vine of the genus Erythropalum belonging to the family Olacaceae, is native to the tropical and subtropical regions of the world. In China, E. scandens is primarily distributed in Guangxi, Guangdong, Yunnan, and Hainan (Zhang et al. 2020). According to the Flora of China (Chinese Flora Committee 1988), E. scandens is pharmaceutically important, neutral, bitter, and targets the veins of the liver and kidneys. In addition, its stem possesses diuretic properties and can be used to treat jaundice, rheumatism, and ostealgia, whereas its roots dispel edema and bruises. The antigout effects of the stem and leaf extracts of E. scandens have been associated with the promotion of uric acid metabolism, anti-inflammation, and protection or improvement of renal function (Xu et al. 2019). Furthermore, coumarins, flavonoids, phenols, triterpenoids, polysaccharides, and other phytochemicals contained in the alcoholic extracts of E. scandens can significantly reduce serum uric acid and creatinine levels, thereby enhancing renal function, promoting uric acid excretion, and reducing uric acid levels in the body. The alcoholic extracts of E. scandens also exhibit low acute toxicity and exert significant inhibitory and protective effects in both rat and mouse models of hyperuricemia. Therefore, this species is an excellent potential alternative for the treatment and prevention of hyperuricemia (Pan et al. 2020; Huang et al. 2017).
In addition to its therapeutic applications, the young leaves of E. scandens are used as a vegetable with a pleasant aroma and unique flavor and can be consumed as fresh, fried, stuffed, boiled in soup, congee, and pickled. Moreover, the nutritional value of its edible shoots is high, with protein, fat, fiber, vitamin B1, vitamin B2, and vitamin C contents comparable to those of common nutritive vegetables such as lettuce, choy sum, mustard, water spinach, sweet potato leaves, pumpkin seedlings, boxthorn leaves, and cauliflower. E. scandens also exhibits high levels of minerals, such as copper, zinc, iron, calcium, and phosphorus, and its calcium content is as high as 1040 mg·kg-1, making it a calcium-rich vegetable (700–2300 mg·kg-1) (Huang et al. 2021).
In recent years, the demand for E. scandens has also been increasing owing to its widely recognized edible and medicinal values. However, the supply of seedlings of E. scandens is insufficient to meet the present market demands, and the breeding technology is still evolving. As a result, growers primarily rely on cutting wild branches for propagation, which severely damages the wild resources and environment of E. scandens (Huang et al. 2021). Furthermore, varieties suitable for edible and medicinal purposes have not yet been identified and developed. In addition, few reports are available on the germplasm resources of E. scandens, resulting in inefficient germplasm collection, conservation, and seedling breeding. Therefore, genetic-diversity studies on the germplasm of E. scandens obtained from different geographical locations are necessary to improve the collection and conservation of germplasm resources, evaluation, and efficient utilization, as well as the selection and breeding of superior varieties to establish the theoretical basis for the breeding and improvement research programs on E. scandens.
Molecular markers—one of the most important tools used for analyzing genetic diversity—have been widely used in several plant species. The most commonly used molecular markers include simple sequence repeat (SSR), inter SSR (ISSR), start codon-targeted polymorphism (SCoT), and random amplified polymorphic DNA (RAPD) markers (Bernard et al. 2020; Sirangi et al. 2020). Of these, ISSR markers, which are used for amplifying simple, repetitive sequences, exhibit several advantages, such as high polymorphism, adequate stability, low cost, and simple operation (Shi et al. 2010; Li et al. 2020). They have been successfully applied for analyzing the genetic diversity of medicinal plants such as Cassia tora (Vikas and Krishna 2018), sand ginger (Subositi et al. 2020), and Dendrobium huoshanense (Tikendra et al. 2019).
In this study, ISSR primers were selected by optimizing the ISSR–PCR reaction system for analyzing the germplasms of E. scandens obtained from different geographical locations. In addition, a genetic diversity analysis was conducted to evaluate the genetic relatedness among the germplasms of E. scandens at the molecular level. Overall, our findings provide the foundation for the conservation and utilization of germplasm resources, identification and classification of varieties, and variety selection and improvement of E. scandens.
The samples were obtained from 34 germplasm resources (Table 1). The geographical distribution of the germplasms is shown in Fig. 1. The phenotypes of two cultivated germplasm (E. scandens No. 1 and 2) are shown in Fig. 2.
|
Germplasm No. |
Source |
Longitude |
Latitude |
|
|---|---|---|---|---|
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 |
Daxin, Guangxi 1 Daxin, Guangxi 2 Baise, Guangxi Cenxi, Guangxi Mashan, Guangxi Shangsi, Guangxi Lipu, Guangxi Hepu, Guangxi Xingye, Guangxi Cangwu, Guangxi Liuzhou, Guangxi Guiping, Guangxi Zhaoping, Guangxi Hechi, Guangxi Rong'an, Guangxi Long'an, Guangxi Longmen, Guangdong Xinyi, Guangdong Huaiji, Guangdong Haifeng, Guangdong Luoding, Guangdong Lianjiang, Guangdong Baoting, Hainan Ledong, Hainan 1 Ledong, Hainan 2 Qiongzhong, Hainan 1 Qiongzhong, Hainan 2 Anxi, Fujian Fuqing, Fujian 1 Fuqing, Fujian 2 Luodian, Guizhou Libo, Guizhou Anlong, Guizhou 1 Anlong, Guizhou 2 |
E107.1793 E107.1827 E106.5221 E110.9863 E108.1807 E108.0072 E110.3974 E109.2564 E109.8692 E111.5313 E109.3222 E110.0446 E110.8441 E108.0623 E109.4358 E107.7237 E114.2465 E110.9405 E112.1868 E115.3026 E111.5359 E110.2791 E109.7365 E109.1631 E109.1802 E109.7842 E109.8284 E118.2247 E119.3792 E119.3677 E106.7623 E107.7951 E105.4569 E105.4877 |
N22.8611 N22.8584 N23.9378 N22.9429 N23.7422 N22.1384 N24.5111 N21.6761 N22.7186 N23.8507 N24.3421 N23.4137 N24.1786 N24.7527 N25.2973 N23.2184 N23.7528 N22.3722 N23.9501 N22.9926 N22.7741 N21.6419 N18.6754 N18.8206 N18.7293 N19.0441 N19.0456 N25.1091 N25.7962 N25.7891 N25.3987 N25.4448 N25.1375 N25.1548 |
Artificial cultivation Artificial cultivation Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type Wild Type |
In this study, we used the ISSR primers UBC800–864 out of the 100 primers published by the University of British Columbia, Canada (http://www.biotech.ubc.ca/services/naps/primers.html).
Genomic DNA was extracted using a modified CTAB method (Safeena et al. 2021), and its quality was examined using 0.8% agarose gel electrophoresis. The concentration and purity of DNA were determined using an ultra-micro UV–Vis spectrophotometer (Thermo NanoDrop One, America). Subsequently, high-quality DNA was diluted to appropriate concentrations for PCR amplification, and the remaining DNA was stored at − 20°C.
The three factors affecting the ISSR–PCR amplification, including the amount of template, primers, and 2× ES Taq MasterMix (CW0690M; Kangwei Century Biotechnology Co. Ltd. China), were optimized using the L9 (34) orthogonal test table (Table 2). The PCR (20 µL) conditions were as follows: pre-denaturation at 94°C for 3 min, denaturation at 94°C for 30 s, annealing at 57°C for 30 s (35 cycles), and extension at 72°C for 5 min. The results of the orthogonal test were analyzed using intuitive analysis (He et al. 1998). Finally, the number and definition (clarity) of amplified bands were scored to identify the most suitable reaction conditions.
|
Level |
Factor |
||
|---|---|---|---|
|
DNA (ng) |
Primer (10 µmoL·µL− 1, µL) |
2×Es Taq Master Mix (µL) |
|
|
1 2 3 4 |
30 40 50 60 |
0.6 0.8 1.0 1.2 |
9 10 11 12 |
We performed the initial screening of 64 ISSR primers using the optimized ISSR–PCR system. The primers that resulted in unclear bands in the initial screening were subjected to gradient PCR (annealing temperature: 49°C, 51°C, 53°C, 55°C, 57°C, and 59°C) for re-screening. The primers with clear bands and high polymorphism in the two rounds of screening were selected for validating the ISSR–PCR system.
The reaction conditions for ISSR–PCR amplification was as follows: initial denaturation at 94°C for 2 min, followed by 30 cycles of denaturation at 94°C for 30 s, annealing for 30 s (annealing temperature of primers), extension at 72°C for 30 s, and final extension at 72°C for 5 min. Finally, the results were analyzed using agarose gel electrophoresis.
The number and position of DNA bands were converted into binary data (0 and 1), where the presence or absence of bands at the same locus with the same mobility was recorded as “1” and “0,” respectively, to form a (0, 1) matrix. Thereafter, the genetic diversity indexes were calculated and clustering analysis was performed for 34 germplasms of E. scandens using PopGene 32, GenAlEx 6.51b2 and STRUCTURE software. Finally, the correlation between geographical location and germplasm was determined using the RStudio software.
The optical density (A260/A280) and concentration of genomic DNA isolated from 34 germplasms of E. scandens were in the range of 1.81–1.97 and 298.1–1693.9 ng·µL-1, respectively. Agarose gel electrophoresis depicted single bands with no smears for all samples, indicating that the extracted DNA was of good quality and could be used for ISSR analysis (Fig. 3).
The PCR amplification results suggested that the different orthogonal combinations amplified bands with large differences in the number and the degree of clarity (Fig. 4). Among them, treatment 16 exhibited the best amplification, with the highest score of 16 in the visual analysis method (Table 3). In general, a good amplification profile resulted in high scores. The mean Ki of each factor at different levels and the extreme difference of the mean between different levels of the same factor was derived from the scoring result R. The degree of influence of the three factors on the ISSR–PCR amplification of E. scandens germplasms was ranked using the R-value: DNA template amount > primer amount > Mix mixture amount. Finally, the following optimal reaction composition (20 µL) was determined using the Ki value: 1 µL DNA template (60 ng·µL-1), 1.2 µL primer (10 µmoL·µL-1), 10 µL MasterMix, and 7.8 µL H2O.
|
Treatment No. |
DNA (ng) |
Primer (10 µmol·µL− 1, µL) |
2×ES Taq Master Mix (µL) |
Score |
|---|---|---|---|---|
|
T 1 T 2 T 3 T 4 T 5 T 6 T 7 T 8 T 9 T10 T11 T12 T13 T14 T15 T16 K1 K2 K3 K4 R |
30 30 30 30 40 40 40 40 50 50 50 50 60 60 60 60 11.4 11.2 12.9 14.7 3.5 |
1.0 0.6 1.2 0.8 0.8 0.6 1.2 1.0 0.8 0.6 1.2 1.0 0.6 0.8 1.0 1.2 11.8 12.2 13.0 13.1 1.3 |
12 9 10 11 12 10 9 11 9 11 12 10 12 11 9 10 12.4 13.0 12.4 12.4 0.6 |
11.2 10.8 12.0 11.7 11.2 10.2 11.7 11.8 12.0 12.2 13.2 14.2 14.2 14.0 15.0 15.7 |
| Note: K1, K2, K3, and K4 are the mean values of scores at different levels for each factor, and R is the extreme difference in the mean values of scores between different levels for the same factor. | ||||
The initial screening of primers UBC800–864 and the re-screening of a few primers (using gradient PCR) indicated the primer pairs and annealing temperatures suitable for ISSR–PCR amplification of E. scandens germplasms (Table 4). A total of 18 primer pairs resulting in bands with distinct backgrounds, adequate stability, and high polymorphism were identified. In total, 183 markers were amplified using the 18 ISSR primers, including 121 polymorphic markers (66.12%), with an average of 10.2 markers and 6.7 polymorphic markers per primer pair, an average allele number (Na) of 1.66, and an average effective allele number (Ne) of 1.32.
|
ISSR Primer |
Annealing temperature |
Total site number |
Polymorphic site |
Percentage of polymorphic site |
Na |
Ne |
H |
I |
|---|---|---|---|---|---|---|---|---|
|
UBC808 UBC811 UBC812 UBC822 UBC823 UBC824 UBC825 UBC826 UBC827 UBC834 UBC835 UBC836 UBC842 UBC849 UBC850 UBC855 UBC856 UBC859 Total Average |
59°C 57°C 53°C 51°C 51°C 49°C 51°C 59°C 49°C 59°C 51°C 55°C 55°C 49°C 55°C 55°C 55°C 49°C |
8 8 9 9 10 12 11 6 13 12 11 12 11 7 10 10 13 11 183 10.2 |
2 6 5 6 7 8 6 3 12 9 6 8 9 3 7 7 10 7 121 6.7 |
25.00% 75.00% 55.56% 66.67% 70.00% 66.67% 54.55% 50.00% 92.31% 75.00% 54.55% 66.67% 81.82% 42.86% 70.00% 70.00% 76.92% 63.64% / 64.29% |
1.25 1.75 1.56 1.67 1.70 1.67 1.55 1.50 1.92 1.75 1.55 1.67 1.82 1.43 1.70 1.70 1.77 1.64 / 1.66 |
1.13 1.33 1.30 1.32 1.42 1.29 1.30 1.22 1.39 1.46 1.19 1.26 1.43 1.22 1.32 1.38 1.39 1.40 / 1.32 |
0.0696 0.2037 0.1797 0.1940 0.2403 0.1746 0.1771 0.1491 0.2365 0.2676 0.1291 0.1696 0.2381 0.1290 0.1815 0.2144 0.2308 0.2279 / 0.1946 |
0.1032 0.3196 0.2738 0.3000 0.3601 0.2744 0.2671 0.2360 0.3686 0.4005 0.2079 0.2714 0.3565 0.1943 0.2795 0.3235 0.3528 0.3397 / 0.2982 |
The genetic diversity indexes of Guangxi, Guangdong, Hainan, Fujian, and Guizhou regions are shown in Table 5. We observed that the number of samples, Nei’s genetic diversity index (H), and Shannon’s information index (I) were higher in germplasms collected from Guangxi than those collected from other regions.
|
Region |
Sample size |
Polymorphic site |
Na |
Ne |
H |
I |
|---|---|---|---|---|---|---|
|
Guangxi Guangdong Hainan Fujian Guizhou |
16 6 5 3 4 |
100 76 66 41 55 |
1.55 1.42 1.36 1.22 1.30 |
1.31 1.28 1.25 1.16 1.18 |
0.1838 0.1574 0.1383 0.0908 0.1077 |
0.2761 0.2317 0.2029 0.1325 0.1615 |
The ISSR data of 34 germplasms of E. scandens were analyzed using PopGen32 (Fig. 5). The genetic similarity coefficients and genetic distances among the germplasms of E. scandens based on ISSR markers were 0.7104–0.9563 (mean: 0.7995) and 0.0447–0.3420 (mean: 0.2247), respectively. The lowest genetic similarity coefficient was observed for the germplasms obtained from both Cengxi City and Shangsi County, Guangxi (0.7104) with Ledong County, Hainan, and the germplasm obtained from them showed the maximum genetic distance (0.3420), indicating a high genetic variation and distance between them. The genetic similarity coefficient between the two germplasms collected from Qiongzhong County, Hainan, was the highest (0.9563), and their genetic distance was the lowest, indicating less genetic variation and relatedness between them.
The genetic similarity coefficients of the 34 germplasms of E. scandens were analyzed using UPGMA clustering and mapped using the software PopGen32 and MEGA7. The results of cluster analysis (Fig. 6) revealed that the 34 germplasms of E. scandens were classified into three clusters. Cluster 1 contained 93.75% of Guangxi and 33.3% of Fujian germplasms, cluster 3 contained 50% of Guangdong and 20% of Hainan germplasms, and cluster 2 included germplasms collected from Guangxi (6.25%), Guangdong (50%), Hainan (80%), Fujian (66.7%), and Guizhou (100%) regions. The genetic similarity coefficients among the germplasms of E. scandens in Guangxi were high, with a few differences in genetic backgrounds among the germplasms of E. scandens from Guangdong, Hainan, Fujian, and Guizhou.
The ISSR data of the 34 germplasms of E. scandens were transformed into genetic distances for PCoA analysis using the GenAlEx software (Fig. 7). The two-dimensional PCoA plot of the 34 germplasm resources of E. scandens was constructed using the first and second principal components as the horizontal and vertical coordinates, respectively. The two principal components explained 10.45% and 8.87% of the variations, respectively. In addition, the germplasms of E. scandens were divided into five groups based on geographical locations, namely Guangxi, Guangdong, Hainan, Fujian, and Guizhou, and the germplasm of each group can be roughly clustered together. The germplasms of E. scandens from Guangxi could be distinguished from those collected from Guangdong, Hainan, Fujian, and Guizhou, whereas those from Guangdong, Hainan, Fujian, and Guizhou were not strictly divided by geographical location.
The Bayesian clustering model was performed to evaluate the population structure of 34 E. scandens samples. The optimal cluster value (K) was two (Fig. 8a), with the highest values of both LnP(K) (log probability of data, -1921.17) and delta K (5.27) obtained from the STRUCTURE. The results showed that it was more appropriate to divide 34 germplasms into two groups. Two run results ( K = 2 and K = 3) are shown in Fig. 8b, the main difference between the results of K = 2 and K = 3 is the germplasm division in Guangdong, Fujian, Hainan and Guizhou. Structure analysis results are generally consistent with UPGMA clustering analysis.
The geographical distances between sampling sites were calculated using RStudio based on the latitude and longitude information of each sampling site. Subsequently, the correlation between geographic and genetic distances among different germplasms was analyzed using Mantel’s correlation test [Mantel’s r = 0.1176; P = 0.084) (Fig. 9)], and no significant correlation between geographic and genetic distances was observed among germplasms of E. scandens obtained from different locations.
The study of genetic diversity is an important way to understand the genetic variation and relatedness of germplasm resources, which can promote the effective conservation, management, and utilization of medicinal plant species (Soltis and Soltis 1991). E. scandens is the only species belonging to the genus Erythropalum of the family Olacaceae. Field visits and research revealed that most of the E. scandens germplasms were extremely similar in morphology, making it difficult to distinguish between different germplasms. In this regard, DNA molecular markers, one of the most important techniques for examining genetic diversity, can rapidly identify and characterize germplasms that cannot be accurately distinguished phenotypically, regardless of the developmental stage and growing environment of the plant (Shahid et al. 2012). Each molecular marker has its advantages and disadvantages. However, ISSR markers combine the advantages of several molecular markers such as high polymorphism, reproducibility, low cost, ease of use, and no need for genome sequencing (Singh et al. 2021). Therefore, the analysis of the genetic diversity of 34 germplasms of E. scandens from different locations using ISSR markers provided the foundation for the identification of E. scandens germplasm resources for breeding.
Accurate and effective application of ISSR marker technology requires the establishment of a stable and reliable ISSR–PCR amplification (Deng et al. 2019). However, ISSR–PCR amplification is affected by several factors, and each factor exhibits different effects on the system based on the sample (Li et al. 2020; Huang et al. 2011; Mohamad et al. 2017; Jamil et al. 2022).
The widespread use of PCR MasterMix has resulted in a shift from the traditional five-component PCR reaction system (Mg2+, DNA template, primers, DNA polymerase, and dNTPs) to the three-component PCR system (MasterMix, DNA template, and primers), thereby reducing the additional steps and making PCR results highly stable and reliable with enhanced reproducibility (Khodaee et al. 2021; Akhtar et al. 2021; Sheikh et al. 2021). In this study, the optimization of the ISSR–PCR system was performed using a three-component, four-level orthogonal test. Finally, the optimal ISSR–PCR system (20 µL) was established as follows: 1 µL DNA template (60 ng·µL-1), 1.2 µL primer (10 µmol·µL-1), 10 µL MasterMix, and 7.8 µL H2O.
In total, 18 primer pairs were identified from 64 ISSR universal primers using the optimized ISSR–PCR system. The ISSR primer pairs with high polymorphism and adequate stability were used for analyzing the genetic diversity of E. scandens. Thus, in this study, PCR amplification was performed for 34 E. scandens germplasm with different geographical distributions using 18 pairs of ISSR primers, followed by data transformation for genetic diversity analysis. We amplified a total of 121 polymorphic markers (66.12%).
High genetic diversity indexes (H and I) indicated high genetic diversity and an increasingly complex genetic background (Zhang et al. 2011). In addition, the germplasms of E. scandens exhibited H and I values of 0.1946 and 0.2982, respectively, indicating some genetic variation among the germplasms from Guangxi, Guangdong, Hainan, Fujian, and Guizhou regions of China, with high genetic diversity. Furthermore, H and I were higher for Guangxi germplasms than for other regions, according to the statistical results of genetic diversity indexes based on different provinces.
According to the UPGMA clustering analysis of genetic similarity coefficients of the 34 germplasms of E. scandens, the germplasms of E. scandens for Guangxi were classified in the same cluster and could be distinguished from those in Guangdong, Hainan, Fujian, and Guizhou. Subsequently, PCoA was performed using the genetic distances among the 34 germplasms of E. scandens. The coordinates of the germplasm of E. scandens from each province could be roughly distributed together. The germplasms from Guangxi could be separated from those from other provinces. In contrast, the germplasms from Guangdong, Hainan, Fujian, and Guizhou were cross-distributed on the main coordinate map and did not exhibit an obvious distribution pattern, which was consistent with the results of UPGMA cluster analysis. The results of the Mantel correlation test revealed no significant correlation between the geographical and genetic distances among the germplasms. Moreover, the genetic variation among the 34 germplasms of E. scandens was not significantly related to the geographical distance, which was consistent with the results of the genetic diversity of the homolog of E. scandens—Malania oleifera Chun & S.K. Lee (Lai 2006).
The kinship (genetic) analysis can rapidly screen target germplasms with similar genetic backgrounds from numerous germplasm resources, which improves the screening efficiency of good germplasms (Sulima et al. 2017; Gupta et al. 2021) and facilitates the rapid advancement in breeding. In this study, 34 germplasms of E. scandens included two cultivated and 32 wild germplasms. The two cultivated germplasm (E. scandens No. 1 and 2) were obtained from the wild germplasm in Daxin County, Guangxi. E. scandens No. 1 exhibited outstanding growth potential and number of buds, whereas E. scandens No. 2 exhibited distinctive aroma and taste (Zhang et al. 2020). The results of cluster analysis suggested that E. scandens No. 1 could be distinguished from other germplasms from Guangxi, indicating that the genetic background of E. scandens No. 1 was different from those of other germplasms, which may be associated with its high-yield and high-quality germplasm characteristics. Nonetheless, the germplasm E. scandens No. 2 and those from Guangxi Lipu City and Guangxi Hepu County (No. 7 and 8) were clustered into a small category, indicating that the genetic backgrounds of these three germplasms were closely related and may exhibit similar phenotypic characteristics. Therefore, we must focus on the phenotypic traits related to aroma and taste in the two wild germplasms, E. scandens No. 7 and 8.
The medicinal components of E. scandens are primarily attributed to old stems and roots (Xu et al. 2019; Huang et al. 2021). Therefore, phenotypic characteristics, such as root biomass, stem thickness, and medicinal components, must be analyzed. In contrast, edible components are primarily distributed in newly sprouted shoots and branches (Long et al. 2017), which can be associated with phenotypic characteristics such as shoot number, taste, and aroma. The combination of phenotypes in future studies and the database of ISSR markers used in this study can further improve the screening efficiency of excellent germplasms.
The collection of E. scandens germplasm resources is difficult owing to their narrow distribution and severely damaged wild resources. Several locations from where the data were recorded previously are no longer available. Therefore, the ecological conservation of the germplasm resources of Erythronium is necessary. The number of germplasm samples and the level of genetic diversity among germplasms found in the wild in Guangxi were higher than those collected from Guangdong, Hainan, Fujian, and Guizhou. Nonetheless, the germplasms from each region can be propagated and transplanted to enhance the genetic exchange between regions and enrich genetic diversity. However, the samples collected in the present study were limited. Thus, future studies must focus on collecting and analyzing more germplasms to enrich the germplasm resource database. In addition, an extensive analysis of multiple molecular markers should be conducted to comprehensively and accurately evaluate the genetic diversity and relatedness of E. scandens, thereby facilitating the screening of excellent germplasms and meeting the increasing market demands.
In the present study, an optimal ISSR–PCR system was established for analyzing the genetic diversity of E. scandens. Eighteen ISSR primer pairs that could amplify genetic markers with distinct backgrounds and adequate polymorphism in 34 germplasms of E. scandens were selected. The germplasm resources from Guangxi, Guangdong, Hainan, Fujian, and Guizhou in China exhibited a relatively high level of genetic diversity. However, a few genetic differences were observed between the germplasms of Guangxi and those of Guangdong, Hainan, Fujian, and Guizhou, but the genetic variation among the 34 germplasms was not significantly correlated with geographical distance. Thus, the 34 E. scandens germplasms could be propagated and transplanted onto each other to enhance genetic exchange between regions and improve genetic diversity in each region, thereby elevating the overall genetic diversity of E. scandens. The kinship analysis of wild and cultivated germplasms of E. scandens indicated that wild germplasms exhibited genetic backgrounds similar to those of cultivated varieties, which could be used for variety selection and breeding. Thus, in this study, we used ISSR markers to study the genetic diversity of E. scandens and revealed the genetic background and affinities of 34 E. scandens germplasms. The findings of this study lay the foundation for further research focusing on the conservation and utilization of E. scandens germplasm resources, identification and classification of varieties, and variety selection and improvement at the molecular level.
Author Contributions: Yang, T.W. and Zhang, S.W.: Conceptualization, Methodology, Experimental design, Formal analysis, Writing—Original draft preparation; Huang S.Y.: Resources, Investigation; Gao M.R., Li, T.: Software, Data curation, Visualization; Zhang X.J.: Writing—Review and Editing, Funding acquisition. All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by Guangxi Key Research and Development Program, grant number Guike21220042; Basic scientific research business special project of Guangxi Academy of Agricultural Sciences, grant number Guinongke2017YM27; Basic scientific research business special project of Guangxi Academy of Agricultural Sciences, grant number Guinongke2022JM51; Guangxi Characteristic Crop Test Station ‘Guangxi Long'an Chinese Herbal Medicine Test Station’, grant number GuiTS2022002; Guangxi Soil and Water Conservation Society's innovation projects in key areas, grant number 202009001 and The APC was funded by Guangxi Key Research and Development Program.
Acknowledgments: We thank Nannning Current Science Biotechnology Co., Ltd. for editing this manuscript.
Conflicts of Interest: The authors declare no conflict of interest.