Genetic diversity and population structure of ginseng in China based on RAPD analysis

Shi-jie Wang; Xiao-lin Chen; Feng-bo Han; Ru-sheng Li; Gang Li; Yan Zhao; Yong-hua Xu; Lian-xue Zhang

doi:10.1515/biol-2016-0051

Article Open Access

Genetic diversity and population structure of ginseng in China based on RAPD analysis

Shi-jie Wang , Xiao-lin Chen , Feng-bo Han , Ru-sheng Li , Gang Li , Yan Zhao , Yong-hua Xu and Lian-xue Zhang

Published/Copyright: December 2, 2016

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From the journal Open Life Sciences Volume 11 Issue 1

Abstract

Population genetic diversity was estimated from forty-four individual ginseng (Panax ginsengC.A. Meyer) plants collected from seven geographical populations located in Heilongjiang, Liaoning, and Jilin Provinces of China as well as the People’s Republic of Korea by using randomly amplified polymorphic DNA (RAPD) markers. Overall, 41 polymorphic loci were amplified using ten primer pairs. The polymorphism percentage ranged from 50% to 100% among seven local populations of ginseng, indicating that there is plentiful genetic diversity in wild ginseng populations. The genetic diversity at the species level was higher than that at the population level. Variance analysis showed that there was a significant difference among populations in genetic diversity. The genetic differentiation coefficient (i.e., F_ST) indicates that 43% of the variation occurred among populations, which indicates that substantial genetic differentiation occurred among populations. At the same time, the measured value of gene flow (Nm) was 0.66 based on the observed genetic differentiation coefficient among populations, suggesting there was moderate gene flow among populations.

Keywords: Panax ginseng; RAPD; genetic diversity; population structure

1 Introduction

For thousands of years, ginseng (Panax ginseng C.A. Meyer; Araliaceae) has been used as a traditional medicine in East Asia [1]. Ginseng is indigenous to northeastern China as well as Korea and other parts of East Asia. It is a slow-growing, herbaceous perennial. Some ginseng species have been reported to be allotetraploids (i.e., 2n = 48 rather than 2n = 24) [2]. In order to adapt to environmental changes, species must contain sufficient genetic variability within and among populations [3]. While there are many biological complexities that increase survival of populations, such as heterozygosity and cross-incompatibility, both of which maintain heterozygosity, more and more scholars are studying the genetic structure and population structure of species in this context. Zhuravlev [4] reported genetic variation of wild ginseng populations, and Seo [5] analyzed diversity of Panax ginsengcollected in Korea, but there are fewer reports on genetic variation and population structure in ginseng populations from China.

Population genetic structure is inseparable from the biology of species, and standing genetic variation represents the raw material upon which evolution operates, making it an important prerequisite for evolution [6]. Randomly amplified polymorphic DNA (RAPD) analysis is a quick and effective way to detected genetic variations among numerous plant populations [7-9].

In this study, we evaluated seven populations in order to estimate the genetic diversity present within these populations as well as to characterize the distribution of genetic variation within and among the populations. Additionally, we also estimated the gene flow between populations. Further, we analyzed the genetic differentiation among populations in order to determine if they correspond to the geographical distances between these locations. This study provides an analysis of the genetic variability of ginseng inbred lines, which is essential for germplasm conservation and long-term breeding plans.

2 Material and methods

2.1 Plant material

Forty-four ginseng samples were collected from seven different regions (Table 1) for subsequent RAPD analysis. Fresh leaves were randomly collected from adult individuals that were at least more than 2 meters apart in order to prevent repeated sampling of the same individual or clone. Depending on the availability of adult plants in each location, 5–9 plants were collected from each population.

Table 1

The population names and geographic locations of study sites.

Population	Sample size	Place
pop1	5	Dongning
pop2	9	Changbai
pop3	6	Ji’an
pop4	9	Kuandian
pop5	5	Ji’an
pop6	5	Fusong
pop7	5	Korea

2.2 DNA extraction and RAPD analysis

Whole genomic DNA was extracted from 0.5-g samples of fresh leaves using the CTAB method ^[10]. In brief, extracted DNA was resuspended in Tris-EDTA buffer, which includes Tris–HCl (10 mM) and EDTA (1 mM, pH 8.0), and the DNA concentration of each sample was then determined using a spectrophotometer (N60, Geneflow Ltd., Lichfield, UK).

A total of 100 RAPD primers (produced by Sangon Biotech Ltd., Shanghai, China) were tested for RAPD. Clear, polymorphic, and reproducible bands were selected and amplified under conditions similar to those used by Williams et al. [11]. A 25-µL PCR reaction mixture containing 200 ng of genomic DNA was amplified in a PTC200 thermalcycler (MJ Research, Watertown, MA, USA) under the following reaction conditions: initial denaturation for 4 min at 94°C, followed by 40 cycles of 1 min at 94°C (denaturation), 1 min at 36°C (annealing), and 2 min at 72°C (extension), and finished with a final extension at 72°C for 10 min. Amplified DNA samples were then subjected to electrophoresis on a 1.4% agarose gel run in a 0.5× TBE buffer and stained with ethidium bromide. The gels were then observed and photographed under ultraviolet light.

2.3 Data analysis

RAPD products were recorded for presence (as 1) or absence (as 0) of bands, with the exclusion of smeared and weak bands as determined by visual inspection. Genetic diversity indexes and parameters, including the proportion of polymorphic bands (PPB), the number of alleles observed (na), effective allele number (Ne), Nei’s gene diversity (H), and Shannon’s diversity index (I), were calculated for a diploid organism with POPGENE 32 [12], which assumes of Hardy–Weinberg equilibrium. At the species level, total population heterozygosity (Ht) was also estimated. Genetic differentiation was also estimated based on an AMOVA procedure implemented in the Arlequin Software Package (Ver. 3.0), which estimate the among population component of genetic variation (F_ST), and statistical significance of the variance component estimate was inferred using 3000 permutations of the data between the seven individual populations. F_ST estimates were used for an indirect calculation of historical levels of gene flow, in accordance with the related effective migration rate equation Nm = 0.5 (1 - F_ST)/F_ST.

3 Results

3.1 RAPD polymorphisms

The 44 ginseng individuals subjected to RAPD genotyping yielded a total of 52 bands ranging between 100 and 1200 bp in size, and the 10 primers produced an average of 5.2 bands. Of these bands, 41 were polymorphic, and PPB was 78.8%.

The number of polymorphic bands amplified per primer varied from 2 to 6, averaging 4.1 (Table 2). Each of the 44 individuals had a distinct RAPD genotype, which indicates that no wild plants were clones or otherwise genetically identical.

Table 2

Summary of polymorphic bands generated by randomly amplified polymorphic DNA (RAPD) applied to seven local populations of ginseng.

Primer	Number of bands	Number of polymorphic bands
S45	5	4
S46	6	4
S80	4	4
S1122	4	3
S1125	6	6
S1127	5	4
S1188	5	4
S2021	4	2
S2029	7	6
S2031	6	4
Total	52	41
Mean	5.2	4.1

3.2 Within population genetic diversity

The PPB within populations ranged from 29.4% (Pop1) to 79% (Pop4), with an average value of 50.1%. According to Hardy–Weinberg equilibrium, the average values of Nei’s gene diversity were 0.2918 at the whole species level and 0.1497 for populations. The Shannon’s diversity index varied between 0.1510 (Pop1) to 0.2642 (Pop4), with an average of 0.2223 at the population level and 0.4486 at the species level. Estimates of Nei’s gene diversity for all bands in individual populations was highest in Pop6 (0.1887) and lowest in Pop1 (0.1063; Table 3). Estimates of Shannon’s index had different values, but exhibited trends that corresponded with Nei’s gene diversity.

Table 3

Genetic diversity statistics for the seven ginseng populations and the entire species based on RAPD data.

Popultion	Sample size	No of PB^[a]	PPB(%)^[b]	Na^[c]	Ne^[d]	H^[e]	I^[f]
1	5	10	29.4	1.2381	1.2020	0.1063	0.1510
2	9	18	48.6	1.4524	1.2655	0.1542	0.2312
3	6	19	54.2	1.4524	1.2344	0.1390	0.2134
4	9	24	79.0	1.5714	1.2923	0.1726	0.2642
5	5	22	52.3	1.4762	1.3022	0.1720	0.2559
6	5	21	48.8	1.4762	1.3338	0.1887	0.2761
7	5	13	38.2	1.2619	1.2149	0.1152	0.1645
average			50.1	1.4183	1.2635	0.1497	0.2223
species	44		78.9	2.0000	1.4825	0.2918	0.4486

3.3 Population genetic structure

According to the AMOVA procedure, genetic differentiation was significant (P < 0.01) among the seven populations, and the coefficient of genetic differentiation among populations (F_ST) was 0.43, indicating that 43% of the genetic variability occurred among populations, with 57% occurring within populations (Table 4). Thus, the AMOVA results corresponded with the estimates of Nei’s gene diversity, and Shannon’s diversity index, which indicates that variation existed mostly among groups.

Table 4

Analysis of molecular variance (AMOVA) for 44 individuals from the seven natural populations of ginseng using RAPD markers.

Source of variation	Degrees of freedoms	Sum of squares	Variance components	Percentage of variation	P-value
among populations	6	129.910	21.652	43	0.01
within populations	37	138.522	3.771	57	0.01
total	43	269.432		100

4 Discussion

4.1 Genetic diversity

The genetic diversity of plant species depends largely on the life history of species (for example, seed dispersal mechanisms, breeding systems, geographical range, and life styles), but the impact of environmental factors is also important. In this study, ginseng PPB was 78.9% at the species level based on RAPD data, and PPB at the population level was 50.1%, indicating that ginseng populations contain relatively high levels of genetic variation. Ginseng is a perennial herb that can survive in a broad range of biological conditions, which can help create and maintain genetic diversity observed at a higher level. Based on species-level estimates of genetic diversity, the genetic diversity of ginseng was higher than those of other species with similar life history characteristics. Because of weak genetic differentiation, habitat loss hinders species migration and gene flow; our findings suggest that this differentiation should be taken into when ginseng is bred and cultivated.

4.2 Genetic structure

The analysis of the genetic structure of these ginseng populations using AMOVA revealed that there was less genetic variation shared among the populations than within. Mantel’s test showed that geographic distance and gene flow did not correspond with genetic distance, suggesting that isolation by distance did not play an important role in the genetic structure of ginseng populations. However, other factor may have some impact on the genetic structure of ginseng, including human-mediated gene flow and natural selection. Breeding systems have been shown to be related to seed dispersal mechanisms, in particular, the among population proportion of genetic variation. As an outcrossing species, cultivated ginseng mainly relies on human activities, so seeds are dispersed over much longer distances than would be otherwise possible. Because of its biological characteristics, ginseng has maintained higher levels of genetic diversity and lower population differentiation, along with high rates of gene flow (i.e., the Nm estimate is 0.66) among populations at the same time. When the Nm value reaches 1.0 there is no population divergence; in this paper, we demonstrate that the Nm values of ginseng populations cannot exceed 1.0 without very high migration rates, indicating that genetic drift did not likely play a significant role in determining the population genetic structure of ginseng.

Acknowledgements

This research was supported by the Research Foundation of the Education Bureau of Jilin Province (grant number 111022013033); the Department of Science & Technology of Jilin Province (grant number 111042014010); the Seed Fund of Jilin Agricultural Science and Technology University (grant number 119032014004)

Conflict id interest: Authors declare nothing to disclose.

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Received: 2016-4-12

Accepted: 2016-8-24

Published Online: 2016-12-2

Published in Print: 2016-1-1

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.