SCoT Markers Analysis of Genetic Diversity of Polygonatum, A Medicinal and Edible Plant

doi:10.21203/rs.3.rs-652340/v1

Background: As a traditional Chinese medicine, Polygonatum has been demonstrated to have immunomodulatory, antibacterial, anti-inflammatory, anti-aging, anti-cancer, hypoglycemic and other pharmacological effects. However, the germplasm resources of Polygonatum have been destroyed in recent years and the research on its genetic diversity is extremely scarce. In this study, the genetic diversity of 28 Polygonatum germplasms from 11 different provinces in China was evaluated by Start codon targeted (SCoT) marker.

Results: A total of 365 bands were generated by 15 SCoT primers, of which 355 were polymorphic, with a high polymorphism of 97.3%. And the genetic similarity coefficient is between 0.59 and 0.75, indicating a high genetic diversity. UPGMA (Unweighted Pair Group Method with Arithmetic Mean) dendrogram, PCoA (Principal Coordinate Analysis) and Structure analysis have similar results in grouping Polygonatum germplasm and they are all divided into two populations. We found that there was a certain correlation between the genetic distance and geographical distance of Polygonatum germplasm. By analyzing other valid genetic diversity parameters (Na, Ne, H, I), it is clarified that Polygonatum has abundant alleles and abundant genetic diversity among populations.

Conclusions: This study suggests that Polygonatum germplasm resources from different provenances have rich genetic diversity. The SCoT molecular marker is a valuable marker system and can be used for genetic analysis of Polygonatum resources. This will be helpful to further study the preservation and genetic improvement of Polygonatum germplasm.

General Biochemistry

Molecular Biology

Agronomy

Polygonatum

SCoT

Genetic diversity

Genetic distance

Geographical distance

Polygonatum is a traditional Chinese medicine with high medicinal and edible value. There are about 60 species in the Polygonatum all over the world and about 39 species are reported in China (Zhang et al. 2018). Chinese Pharmacopoeia (2015 edition) delimits Chinese medicinal Polygonatum from the rhizomes of three Polygonatum genus: P. sibiricum Red., P. cyrtonema Hua. or P. kingianum Coll.et Hemsl.. The literature indicated that Polygonatum can enhance immunity and memory and has anti-inflammatory, anti-oxidation, anti-cancer, hypoglycemic, anti-aging effects(Khan et al. 2015; Kumar Singh and Patra 2018; Lee et al. 2016; Ma et al. 2019; Sharma et al. 2018; Wang et al. 2019; Zhang et al. 2018). Therefore, Polygonatum has a broad market prospect in terms of its pharmacological action and edible value. Due to the collection of Polygonatum is mainly based on wild resources and the supply capacity of the market is limited. Moreover, it is inevitabe that there will be a mixture of different polygonatum, such as Polygonatum filipes., which has different pharmacological characteristics. However, classification within the Polygonatum genus through morphological identification is difficult because of variations and inter-species hybridization (Feng et al. 2020). It is necessary to assess the genetic diversity of Polygonatum for better understanding, conservation, and utilization of these germplasm resources.

Assessment of genetic diversity is an essential step in plant breeding programs. Molecular markers based on Polymerase chain reaction (PCR) amplification technology can directly reveal the genetic relationship between species at the DNA level and have been widely used(Feng et al. 2018; Poczai et al. 2013), such as Random Amplified Polymorphic DNA (RAPD)(Cui et al. 2017), Inter-simple sequence repeat (ISSR) (Kumar et al. 2016), Sequence related amplified polymorphism (SRAP) (Zhao et al. 2020). However, the complexity, stability and ability of generating genetic information of molecular marker technology are different, and each has its advantages and disadvantages. Start codon targeted (SCoT) marker is designed by Collard and Mackill based on the short conserved sequences flanking the start codon (ATG) in plant genes (Collard and Mackill 2008). SCoT markers are related to functional genes, easy to operate, universal primers, higher annealing temperature (50°C), longer primers (18-mer), higher polymorphism and distinguishability (Golkar and Mokhtari 2018; Jalilian et al. 2018; Safari et al. 2019; Xiong et al. 2011; Yang et al. 2019). SCoT markers have been successfully applied to research on genetic diversity of a variety of crops, flowers, etc. (Tyagi et al. 2020), including Polygonatum (Feng et al. 2020; Jiao et al. 2018).

In this study, SCoT markers were used to evaluate the genetic diversity of 28 Polygonatum germplasms and the genetic relationship between the provenances of Polygonatum from different sources is discussed. This provides references for the selection of Polygonatum germplasm resources, breed selection, production of Chinese medicinal materials, and provides a theoretical basis for the protection of Polygonatum resources.

Plant materials

In this study, a total of 28 Polygonatum germplasm resources from 11 different provinces in China were evaluated, covering most of the major distribution areas in China. Table 1 lists the relevant information of the sample germplasm. Fig. 1 shows the 11 different provinces of origin. The voucher specimens of plant materials have been deposited in the Laboratory of Molecular Biology of Zhejiang Chinese Medical University (No.: BJ-20160301-001 to NO.BJ20160301-050).

DNA extraction

Plant DNA was extracted from the fresh leaves by using modified cetyltrimethylammonium bromide (CTAB) method (Abarshi et al. 2010; Murray and Thompson 1980). 1% agarose gel electrophoresis was used to evaluate the quality and integrity of the extracted genomic DNA, and then stored at -20 °C for subsequent PCR amplification.

Table 1. Polygonatum germplasm resources from different geographical regions of China used in this study

Serial number

Polygonatum Accessions

Origin

Abbreviation

1

Polygonatum cyrtonema Hua.

Xiaoshan, Hangzhou, Zhejiang

PcH1

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

Polygonatum sibiricum.

Polygonatum cyrtonema Hua.

Polygonatum sibiricum.

Polygonatum filipes.

Polygonatum sibiricum.

Polygonatum cyrtonema Hua.

Polygonatum sibiricum.

Polygonatum sibiricum Red.

Polygonatum cyrtonema Hua.

Polygonatum sibiricum.

Polygonatum sibiricum Red.

Polygonatum kingianum Coll.et Hemsl.

Polygonatum sibiricum.

Polygonatum sibiricum Red.

Polygonatum sibiricum.

Polygonatum cyrtonema Hua.

Polygonatum sibiricum.

Hangping, Pujiang, Zhejiang

Mountain, Jiangshan, Zhejiang

Yuyao, Ningbo, Zhejiang

Ninghai, Ningbo, Zhejiang

Tonglu, Hangzhou, Zhejiang

Cili, Zhangjiajie, Hunan

Huitong, Huaihua, Hunan

Xinhua, Loudi, Hunan

Xian'an, Xianning, Hubei

Chongyang, Xianning, Hubei

Yangxin, Huangshi, Hubei

Li, Longnan, Gansu

Xianghe, Shangnan, Shaanxi

Shimian, Ya'an, Sichuan

Yimen, Yuxi, Yunnan

Mengzi, Honghe, Yunnan

Libo, Qiannan, Guizhou

Chishui, Zunyi, Guizhou

Baiwanyao, Xingyi, Guizhou

Yizhou, Hechi, Guangxi

Changting, Longyan, Fujian

Yuanzhou, Yichun, Jiangxi

Ps2

PcH3

PcH4

Ps5

Pf6

Ps7

PcH8

PcH9

Ps10

Ps11

Ps12

PsR13

PcH14

Ps15

Ps16

Ps17

Ps18

Ps19

PsR20

PsR21

PkCH22

Ps23

PsR24

Ps25

PcH26

PcH27

Ps28

Polymerase chain reaction and agarose gel electrophoresis

Based on the analysis of two randomly selected germplasms, among 36 SCoT primers (Shanghai Shenggong Bioengineering Service Co., Ltd.) (Collard and Mackill 2008), primers with clear and rich polymorphic bands were selected to evaluate the genetic diversity of Polygonatum germplasm. The total volume of the PCR amplification system was 20 μl, 0.8 μl of primers (10 μM), 10 μl of 2 × Es Taq Master Mix (Beijing Kangwei Century Biotechnology Co., Ltd.), 1 μl of genomic DNA template, and 8.2 μl ddH₂O. S1000 ™ Thermal Cycler PCR (Shenzhen Yudeli Biotechnology Co., Ltd.) was used for amplification. The setup procedure was: an initial step at 95 °C for 4 min, followed by 36 cycles of 95 °C for 50 s, 72 °C for 2 min, and a 5 min final extension at 72 °C. 10 μl PCR amplification products were analyzed by electrophoresis in 1.5% agarose gel containing 5 mg/ml ethidium bromide and then observed and photographed under the ZF-90 dark box ultraviolet transmittance meter (Shanghai Gucun Electro-Optic instrument Factory).

Data analysis

In the products amplified by SCoT primers, only the clear and repeatable DNA bands were marked as (1), and the non-existence were marked as (0) and then a binary matrix was constructed. Cluster analysis was performed using NTSYS-pc version 2.10e software (Powell et al. 1996) and the Principal coordinate analysis (PCoA) two-dimensional distribution map was obtained. The unweighted Pair Group Method with Arithmetic Mean (UPGMA) and the dissimilarity index in Jaccard’s option were used to construct a dendrogram (Zhao et al. 2020). Nei’s genetic identity (H) (Nei 1972). Effective number of alleles (Ne), Shannon's information index (I) and other genetic diversity indexes were obtained by POPGENE software.1.32 (Yeh et al. 1997). In addition, the formula PIC = 2fi (1-fi) was used to calculate the polymorphic information content (PIC). Where " fi " is the frequency of the amplified allele (band presence) and " 1-fi " is the frequency of the null allele (Powell et al. 1996; Zargar et al. 2016). In addition, the genetic structure of the population was analyzed by STRUCTURE software ver.2.3.4. In order to determine the best K value of the population, the K value was preset from 1 to 15 and each K value was run five times independently. The burn-in period parameter was configured to 100,000 and the number of Markov Chain Monte Carlo (MCMC) (Bayesian statistics) replications (simulations) after burn-in was set over 1,000,000 (Karandikar 2006; Li et al. 2020). An online tool, Structure Harvester, is then used to process results of STRUCTURE analysis, using the delta K (ΔK) method to find the best K value (Earl and vonHoldt 2012).

SCoT analysis

From 36 SCoT primers, 15 primers that can generate reproducible and high-resolution polymorphic fragments were selected for sample research (Table 2). A total of 365 credible bands were obtained, of which 355 were polymorphic, and the percentage of polymorphism was 97.2%. The bands amplified by each primer range from 19 (SCoT 11) to 32 (SCoT 7), with an average of 24.3 and the number of polymorphic bands ranged from 18 (SCoT 11) to 32 (SCoT 7), with an average of 23.7. The percentage of polymorphism ranged from 87.5% (SCoT 14) to 100% (SCoT 28), each primer has 18-32 polymorphic bands, and SCoT 7 produced the most polymorphic bands (PB = 32). PIC values ranged from 0.307 (SCoT 14) to 0.426 (SCoT 33), with an average of 0.379 (Table 2). The amplification results showed that SCoT markers could be used to detect the high polymorphism of Polygonatum germplasm.

Table 2. Sequence and polymorphism information of the 15 SCOT primers selected in this study

Primer code

Primer sequence (5′-3′)

No. of

amplified

bands

No. of

polymorphic

bands (PB)

Polymor-

phic (%)

Polymorphic information content (PIC)

SCoT1

CAACAATGGCTACCACCA

31

30

96.8

0.384

SCoT 2

SCoT 6

SCoT 7

SCoT 11

SCoT 13

SCoT 14

SCoT 15

SCoT 17

SCoT 20

SCoT 22

SCoT 28

SCoT 29

SCoT 31

SCoT 33

Mean

Total

CAACAATGGCTACCACCC

CAACAATGGCTACCACGC

CAACAATGGCTACCACGG

AAGCAATGGCTACCACCA

ACGACATGGCGACCATCG

ACGACATGGCGACCACGC

ACGACATGGCGACCGCGA

ACCATGGCTACCACCGAG

ACCATGGCTACCACCGCG

AACCATGGCTACCACCAC

CCATGGCTACCACCGCCA

CCATGGCTACCACCGGCC

CCATGGCTACCACCGCCT

CCATGGCTACCACCGCAG

-

22

23

32

19

25

24

27

21

22

21

20

25

28

25

24.3

365

22

32

18

24

21

27

21

20

25

27

25

23.7

355

100.0

95.7

100.0

94.7

96.0

87.5

100.0

95.5

95.2

100.0

96.4

100.0

97.2

-

0.413

0.386

0.380

0.363

0.352

0.307

0.409

0.341

0.383

0.341

0.410

0.406

0.377

0.426

0.379

-

Population genetic diversity

According to the provincial sources, 28 samples were divided into eleven populations, representing different provinces, table 3 shows their genetic diversity index. The values of Observed number of alleles (Na), Effective number of alleles (Ne), Nei's gene diversity (H) and Shannon's Information index (I) in Zhejiang Province were the highest, Na = 1.8630, Ne = 1.4561, H = 0.2796, I = 0.4275, and the standard deviations were 0.3443, 0.3129, 0.1601, 0.2194, respectively. The corresponding parameters of genetic diversity in Sichuan Province were the lowest, Na = 1.3315, Ne = 1.2344, H = 0.1373, I = 0.2005, and the standard deviations were 0.4714, 0.3333, 0.1953 and 0.2851, respectively. Among the 15 SCoT markers (Table 4), the spans of Ne, H, I values are 1.4057-1.7173, 0.2546-0.3947, 0.3959-0.5737, respectively and the standard deviations are 0.2466-0.3835, 0.1104-0.1834, 0.1302-0.2381 respectively.

According to Nei’s genetic identity and genetic distance, the highest genetic identity (0.9216) and the minimum genetic distance (0.0816) was recorded between Zhejiang province and Hunan province, while the lowest identity (0.5370) and the maximum genetic distance (0.6218) was recorded between Gansu province and Jiangxi province (Table 5). These results indicate that Polygonatum has high genetic diversity and SCoT markers can significantly distinguish the genetic differences of Polygonatum germplasm.

Table 3. Genetic diversity parameters for different provinces of Polygonatum

Province	Sample size	Na	Ne	H	I
Zhejiang	8	1.8630(0.3443)	1.4561(0.3129)	0.2796(0.1601)	0.4275(0.2194)
Hunan Hubei Yunnan Guizhou Sichuan Gansu Shanxi Jiangxi Fujian Guangxi	4 4 2 3 2 1 1 1 1 1	1.6712(0.4704) 1.7315(0.4438) 1.3781(0.4856) 1.5973(0.4911) 1.3315(0.4714) 1.0000(0.0000) 1.0000(0.0000) 1.0000(0.0000) 1.0000(0.0000) 1.0000(0.0000)	1.4084(0.3634) 1.4552(0.3696) 1.2673(0.3434) 1.3822(0.3723) 1.2344(0.3333) 1.0000(0.0000) 1.0000(0.0000) 1.0000(0.0000) 1.0000(0.0000) 1.0000(0.0000)	0.2416(0.1915) 0.2260(0.1883) 0.1566(0.2011) 0.2244(0.1979) 0.1373(0.1953) 0.0000(0.0000) 0.0000(0.0000) 0.0000(0.0000) 0.0000(0.0000) 0.0000(0.0000)	0.3621(0.2732) 0.3974(0.2648) 0.2286(0.2936) 0.3340(0.2854) 0.2005(0.2851) 0.0000(0.0000) 0.0000(0.0000) 0.0000(0.0000) 0.0000(0.0000) 0.0000(0.0000)
Mean	-	1.5954	1.3673	0.2109	0.3250

Note: Standard deviations are in parentheses, Na Observed number of alleles, Ne Effective number of alleles, H Nei’s gene diversity, I Shannon’s Information index

Table 4. Analysis of genetic diversity of Polygonatum by SCoT markers

Maker

Ne

H

I

SCoT1

1.5237(0.2616)

0.3232(0.1255)

0.4936(0.1562)

SCoT2

SCoT6

SCoT7

SCoT11

SCoT13

SCoT14

SCoT15

SCoT17

SCoT20

SCoT22

SCoT28

SCoT29

SCoT31

SCoT33

Mean

1.6093(0.2975)

1.4946(0.2466)

1.4756(0.2683)

1.5820(0.3619)

1.5224(0.3298)

1.4057(0.3093)

1.5489(0.2575)

1.4914(0.3183)

1.5330(0.2892)

1.5803(0.3835)

1.7173(0.3115)

1.5684(0.2767)

1.5249(0.2955)

1.5971(0.2618)

1.4396

0.3562(0.1287)

0.3562(0.1701)

0.2992(0.1333)

0.3304(0.1752)

0.3111(0.1567)

0.2546(0.1638)

0.3357(0.1189)

0.3004(0.1450)

0.3238(0.1356)

0.3254(0.1834)

0.3947(0.1352)

0.3416(0.1250)

0.3195(0.1344)

0.3567(0.1104)

0.3286

0.5321(0.1535)

0.4811(0.1539)

0.4629(0.1705)

0.4893(0.2285)

0.4705(0.2055)

0.3959(0.2246)

0.5095(0.1460)

0.4639(0.1770)

0.4911(0.1749)

0.4813(0.2381)

0.5737(0.1617)

0.5156(0.1520)

0.4871(0.1691)

0.5353(0.1302)

0.4922

Note: Standard deviations are in parentheses, Na Observed number of alleles, Ne Effective number of alleles, H Nei’s gene diversity, I Shannon’s Information index

Table 5. Nei's genetic identity (above diagonal) and genetic distance (below diagonal) among eleven provinces of Polygonatum

POP ID	Zhejiang	Hunan	Hubei	Guizhou	Gansu	Shanxi	Jiangxi	Yunnan	Guangxi	Fujian	Sichuan
Zhejiang	****	0.9216	0.9185	0.9266	0.6892	0.7179	0.7809	0.8814	0.7765	0.7805	0.8947
Hunan	0.0816	****	0.8809	0.8679	0.6637	0.6797	0.7769	0.8501	0.7568	0.7668	0.8451
Hubei	0.0850	0.1268	****	0.8891	0.7064	0.7244	0.7365	0.8079	0.7524	0.7606	0.8381
Guizhou	0.0762	0.1416	0.1175	****	0.6881	0.6937	0.7295	0.8454	0.7334	0.7663	0.8644
Gansu	0.3722	0.4100	0.3475	0.3738	****	0.5973	0.5370	0.6538	0.5753	0.5726	0.6291
Shanxi	0.3315	0.3861	0.3224	0.3657	0.5154	****	0.6164	0.6364	0.6000	0.6137	0.6691
Jiangxi	0.2474	0.2524	0.3058	0.3154	0.6218	0.4838	****	0.7151	0.6822	0.6411	0.7126
Yunnan	0.1263	0.1624	0.2133	0.1679	0.4250	0.4520	0.3354	****	0.7238	0.7409	0.8369
Guangxi	0.2529	0.2786	0.2845	0.3101	0.5528	0.5108	0.3824	0.3232	****	0.7288	0.7303
Fujian	0.2478	0.2655	0.2736	0.2661	0.5576	0.4883	0.4446	0.2999	0.3164	****	0.7339
Sichuan	0.1112	0.1683	0.1767	0.1457	0.4635	0.4018	0.3389	0.178	0.3143	0.3093	****

Cluster analysis and Population structure

Cluster analysis of 28 germplasm materials was carried out by UPGMA program and a tree diagram was generated. On the whole, it is divided into two groups: Group I and Group II, when the similarity index is 0.606, these germplasm materials can be clustered into four subgroups (Fig. 2). Two-dimensional PCoA analysis of SCoT markers amplification products showed that Polygonatum germplasm was mainly divided into two groups, which was similar to the results shown by UPGMA dendrogram (Fig. 3). In addition, the correlation analysis also shows that the similarity matrix fits well and the similarity coefficient is 0.7335, indicating that the two analysis methods (PCoA and UPGMA) have obtained comparable results (Fig. 4).

STRUCTURE software ver.2.3.4 was used to estimate the population structure of 28 accessions based on fragments obtained from 15 SCoT primers. Structure Harvester was used to estimate the best number of populations using the ΔK method (Earl and vonHoldt 2012). The highest value for ΔK was obtained at K = 2 (ΔK = 137.01); indicating the entire germplasm could be divided into two groups (Fig. 5). The results indicated that STRUCTURE analysis, PCoA analysis and UPGMA analysis had similar results and the same germplasm was divided into two populations. In Group I, four germplasms belong to Zhejiang, two germplasms belong to Hunan, three germplasms belong to Hubei, and the rest belong to Guizhou, Shaanxi, Gansu. In Group II, Zhejiang contains four germplasms, Hunan, Yunnan, Guizhou, Sichuan contain two germplasms respectively and Hubei, Guangxi, Jiangxi, Fujian each have one.

Studying the genetic diversity of plants is of great significance to plant breeding and genetic protection. Genetic evaluation conduces to broaden the genetic basis of varieties and prevent gene insertion or deletion (Mulpuri et al. 2013; Talebi et al. 2008). DNA molecular marker technology with higher polymorphism and higher accuracy provides a simple and effective method for studying the genetic diversity of Polygonatum germplasm (Yu et al. 2017). Unlike RAPD, Inter-simple sequence repeat (ISSR) and other similar markers, SCoT markers are related to functional genes and corresponding traits and have better marker resolution, so they are suitable for marker-assisted breeding (Collard and Mackill 2008; Feng et al. 2016; Mulpuri et al. 2013). In recent years, SCoT markers have been widely used to reveal the genetic diversity of many plants, such as Green Tea (Xu et al. 2019), Bletilla striata (Guo et al. 2018), Capsicum annuum (Igwe et al. 2019), Miscanthus lutarioriparius (Yang et al. 2019), etc. Even though there have been related reports on Polygonatum germplasm (Jiao et al. 2018), based on SCoT markers, few primers are used and the analysis method is single, the data may lack validity.

In this study, the percentage of polymorphic bands (PPB) amplified by 15 SCoT primers was 97.2%, which was higher than that in Mango (PPB = 76.19%) (Luo et al. 2010), Switchgrass (PPB = 90%) (Zhang et al. 2015). According to PIC value (PIC = 0.379), SCoT markers are highly polymorphic and informative. In addition, the high polymorphism of SCoT markers also indicates that there is considerable genetic diversity among tested Polygonatum varieties.

The average value of population genetic diversity is 0.21, which is higher than the previous analysis in Polygonatum (H = 0.1943, H = 0.1279) (Feng et al. 2020), indicating that SCoT markers are more superior than EST-SSR markers and SRAP markers. However, in previous reports that also used SCoT markers, H values were found to be lower than in Capsicum annuum (H = 0.5936) and Miscanthus lutarioriparius (H = 0.32), which may be due to different germplasm or the number of individuals in the population (Igwe et al. 2019; Yang et al. 2019). The average value of genetic diversity in SCoT marker is 0.3286, which also indicates that SCoT marker is highly polymorphic. But it is lower than in Vigna unguiculata L (Igwe et al. 2017), this may be due to the different sample germplasm used by both parties. According to Nei's genetic identity and genetic distance, it can be found that the germplasm of Hunan and Zhejiang are highly correlated. This indicates that there may be frequent gene flow among Polygonatum species between the two provinces in recent years, and similar results have been found in the study of commercial and wild pear species (Jalilian et al. 2018).

According to Cluster analysis, Polygonatum germplasm was divided into two populations by UPGMA dendrogram. PCoA analysis and population structure analysis also proved this result. Most studies using SCoT markers have used similar methods and have similar results (Golkar and Mokhtari 2018; Xu et al. 2019). When the similarity coefficient is 0.606, the two populations can be divided into four subgroups. From the map (Fig. 1), we can find that Zhejiang Province, Hubei Province, Hunan Province are geographically close, and subgroup I mainly clusters most of the germplasm in these three provinces together. Subgroup II contains four different provinces, and also have close geographical locations. Subgroup III contains only one sample from the mountainous area, and this may be due to the geographic blockage of information communication. Similar results were found in Miscanthus lutarioriparius (Yang et al. 2019). Subgroup Ⅳ clusters several provinces with close geographical location, such as Yunnan, Guizhou, Sichuan, and Jiangsu, Zhejiang, Fujian. Polygonatum germplasm in the same province will basically be grouped into the same category, like Hunan and Sichuan. However, we found that Polygonatum germplasm in the same province may be divided into different populations, such as Zhejiang, Hubei, Hunan, Guizhou. This shows that the genetic communication of Polygonatum in some areas will still be limited, although they are not far apart. We also found that some germplasms from Fujian and Sichuan or Gansu and Zhejiang, which are far away from each other, have also been grouped together. This may be due to the convenient transportation, the rapid development of network information, the frequent intensification of human activities and the increase of information exchange among species. In addition, the dendrogram shows that Polygonatum of the same species is mainly clustered into different subgroups. This may be caused by the geographical distance of these species. Among them, there are great similarities between Polygonatum sibiricum. and Polygonatum cyrtonema Hua., and between Polygonatum sibiricum. and Polygonatum sibiricum Red.. This may be caused by interspecific hybridization between Polygonatum. Polygonatum kingianum Coll.et Hemsl. was clustered together with Polygonatum sibiricum. and Polygonatum cyrtonema Hua. This result is similar to the previous report by Jiao et al (Jiao et al. 2018). In summary, Polygonatum germplasm has higher genetic diversity. The genetic distance and geographical distance of Polygonatum germplasm have a certain degree of correlation. This provides an important reference value for the construction of DNA fingerprint, population structure analysis, germplasm preservation and breeding of Polygonatum. For example, Polygonatum within the same province or between neighboring provinces should avoid gene interflow as much as possible, and Polygonatum with far geographical distance can be used as parents for hybridization.

In this study, we evaluated 28 Polygonatum germplasms from 11 different provinces in China using SCoT molecular markers. The results showed that Polygonatum germplasm has higher genetic diversity. In addition, UPGMA cluster analysis and STRUCTURE analysis showed that the genetic distance of Polygonatum germplasm was correlated with geographical distribution to some extent. Among them, geographical location, human activities, climate, temperature, and other conditions will affect the genetic communication of Polygonatum germplasm. The number of samples is often closely related to the study of genetic diversity. To further understand the genetic diversity of Polygonatum, it is necessary to use other efficient molecular marker techniques and use more widely Polygonatum samples for in-depth analysis.

Funding

This work was supported by the Natural Science Foundation of Zhejiang Province, China (LY17H280007).

Competing interests

The authors declare that they have no conflict of interest.

Availability of data and material

The data used to support the findings of this study are available from the corresponding author upon request.

Code availability

Not applicable.

Authors' contributions

Bo Jin and Nipi Chen conceived and designed the study. Shidong Cao, Senmiao Chen and Shuyu Cao performed the experiments. Shidong Cao wrote the paper. Shidong Cao reviewed and edited the manuscript. All authors read and approved the manuscript.

Ethics approval and consent to participate

Not applicable.

Consent for publication

All authors agree to publication.

Acknowledgements

We are very grateful to the teachers and reviewers for their valuable help in completing this article.

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SCoT Markers Analysis of Genetic Diversity of Polygonatum, A Medicinal and Edible Plant

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Abstract

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Introduction

Materials And Methods

Results

Discussion

Conclusion

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References

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Version 1