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Research Article
Species discrimination of novel chloroplast DNA barcodes and their application for identification of Panax (Aralioideae, Araliaceae)
expand article infoNguyen Nhat Linh, Pham Le Bich Hang, Huynh Thi Thu Hue§, Nguyen Hai Ha§, Ha Hong Hanh, Nguyen Dang Ton§, Le Thi Thu Hien§
‡ Institute of Genome Research, Vietnam Academy of Science and Technology, Hanoi, Vietnam
§ Graduate University of Science and Technology, Hanoi, Vietnam
Open Access

Abstract

Certain species within the genus Panax L. (Araliaceae) contain pharmacological precious ginsenosides, also known as ginseng saponins. Species containing these compounds are of high commercial value and are thus of particular urgency for conservation. However, within this genus, identifying the particular species that contain these compounds by morphological means is challenging. DNA barcoding is one method that is considered promising for species level identification. However, in an evolutionarily complex genus such as Panax, commonly used DNA barcodes such as nrITS, matK, psbA-trnH, rbcL do not provide species-level resolution. A recent in silico study proposed a set of novel chloroplast markers, trnQ-rps16, trnS-trnG, petB, and trnE-trnT for species level identification within Panax. In the current study, the discriminatory efficiency of these molecular markers is assessed and validated using 91 reference barcoding sequences and 38 complete chloroplast genomes for seven species, one unidentified species and one sub-species of Panax, and two outgroup species of Aralia L. along with empirical data of Panax taxa present in Vietnam via both distance-based and tree-based methods. The obtained results show that trnQ-rps16 can classify with species level resolution every clade tested here, including the highly valuable Panax vietnamensis Ha et Grushv. We thus propose that this molecular marker to be used for identification of the species within Panax to support both its conservation and commercial trade.

Keywords

DNA barcode, Panax genus, Panax vietnamensis, petB, trnE-trnT, trnQ-rps16, trnS-trnG

Introduction

The genus Panax L. is well-known in culinary and medicinal traditions in many countries including China, Korea, Japan, and Vietnam. Its species produce ginsenosides, also known as ginseng saponins with strong antioxidant, antidiabetic, antitumor, and neuroprotective activities (Jung et al. 2017; Patel and Rauf 2017). Due to their high commercial demand, many species within Panax have been over-harvested and are at risk of extinction (Case et al. 2007; McGraw et al. 2013; Manzanilla et al. 2018). In Vietnam, there are three species of Panax including Panax vietnamensis Ha et Grushv., Panax stipuleanatus H.T.Tsai et K.M.Feng, and Panax bipinnatifidus Seem., all recorded and classified as endangered. Of these species P. vietnamensis is endemic to Vietnam and is considered to have the highest medical potential and is therefore the most commercially valuable (Nguyen 2005; Nguyen et al. 2007). Two varieties of P. vietnamensis, Panax vietnamensis var. fuscidiscus K.Komatsu, S.Zhu et S.Q.Cai and Panax vietnamensis var. langbianensis N.V.Duy. V.T.Tran et L.N.Trieu, are also present in Vietnam (Phan et al. 2013; Nong et al. 2016). Recently, an unidentified sample of Panax discovered on Puxailaileng Mountain of Nghe An Province was also reported by Phan et al. (2014) and referred hereafter as “Panax sp. Puxailaileng”.

Historically, morphological methods have been used to identify ginseng species, though this is challenging due to how similar different ginseng species can appear. Incorrect identification can lead to unintentional or intentional mislabeling and adulteration with low-quality ginsengs, and ultimately affect the consumers’ health and damage the providers’ integrity. Recently, molecular methods have been shown to be efficient for solving problems related to species identification. However, the most commonly used barcoding sequences are challenging to use in the genus Panax, because these often lack sufficient variability to unambiguously identify the species (Komatsu et al. 2001; Janzen et al. 2009; Hollingsworth et al. 2011; Zuo et al. 2011; Li et al. 2015). According to Zuo et al. (2011) rpoC1, rbcL, and rpoB were the low discriminatory with only four to eight variable sites. The region psbK-psbI had the higher discriminatory ability but low chance of successful sequencing (Janzen et al. 2009). Furthermore, psbA-trnH sequence analysis was reported inaccurate because of the complicated microevolution (Li et al. 2015). The attempts using above loci along with matK, trnD and ycf1 for identifying species in the genus Panax also were unable to completely solve the challenge (Komatsu et al. 2001; Shi et al. 2015). Other newly proposed InDel (Nguyen et al. 2017) and dCAPS markers (Nguyen et al. 2020) were also developed but the requirement for multi-locus analyses is time-consuming and labor-intensive. This raises the need to develop better molecular markers for identification of the species within Panax (Shneyer 2009; Li et al. 2015; Manzanilla et al. 2018).

Previously performed an in silico analysis indicated that the chloroplast DNA markers trnQ-rps16, trnE-trnT, petB, and trnS-trnG had high species identification potential within the genus Panax (Manzanilla et al. 2018) and could be used in routine classification processes. In the present study, we assess and experimentally test the discriminatory efficiency of these commonly used and novel chloroplast markers in classifying species of Panax with an emphasis on those distributed in Vietnam.

Materials and methods

Plant materials

Leaf samples of five taxa belonging to the genus Panax were collected in the North and Central Vietnam (Table 1, Fig. 1). These included twenty-two samples of P. vietnamensis from eighteen distinct populations distributed on Ngoc Linh Mountain in Quang Nam and Kon Tum Provinces, samples of P. vietnamensis var. fuscidiscus and Panax sp. Puxailaileng collected in their natural habitats from Lai Chau and Nghe An Provinces, respectively, as well as, P. stipuleanatus and P. bipinnatifidus gathered from Lao Cai Province. All specimens were morphologically identified by plant taxonomists Nguyen Tap and Nguyen Quoc Binh using identification keys (Ha and Grushvitzky 1985; Nguyen 2005; Phan et al. 2013; Tran et al. 2016) and deposited at the Vietnam National Museum of Nature (VNMN). P. vietnamensis var. langbianensis is narrowly distributed in Lang Bian Mountain of Southern Vietnam and we were not able to collect samples from it. All lab and bioinformatics work was conducted at the Institute of Genome Research, Vietnam Academy of Science and Technology.

Table 1.

Sample collection information.

Sample ID Collector Collection date Collected location
Coordinates District Province
P. vietnamensis
TL25 Luong Duc Toan 10/16/2017 15°01.17'N, 108°00.76'E Nam Tra My Quang Nam
CP13 Luong Duc Toan 10/16/2017 15°01.40'N, 108°03.10'E Nam Tra My Quang Nam
TN22 Luong Duc Toan 10/16/2017 15°00.94'N, 108°03.08'E Nam Tra My Quang Nam
D42 Le Thi Thu Hien 09/28/2018 15°00.94'N, 108°02.58'E Nam Tra My Quang Nam
D43 Le Thi Thu Hien 09/28/2018 15°00.94'N, 108°02.58'E Nam Tra My Quang Nam
D11 Le Thi Thu Hien 09/28/2018 15°00.94'N, 108°02.58'E Nam Tra My Quang Nam
D6 Le Thi Thu Hien 09/28/2018 15°00.94'N, 108°02.58'E Nam Tra My Quang Nam
Q1 Le Thi Thu Hien 09/28/2018 15°02.53'N, 108°02.72'E Nam Tra My Quang Nam
B42 Le Thi Thu Hien 09/28/2018 15°03.11'N, 107°97.97'E Nam Tra My Quang Nam
ML043 Luong Duc Toan 10/11/2017 15°03.20'N, 107°97.90'E Nam Tra My Quang Nam
TL27 Luong Duc Toan 10/11/2017 15°03.18'N, 107°97.91'E Nam Tra My Quang Nam
TT15 Luong Duc Toan 10/11/2017 14°96.41'N, 108°10.05'E Nam Tra My Quang Nam
TR2 Luong Duc Toan 10/11/2017 15°07.73'N, 108°00.76'E Nam Tra My Quang Nam
PL073 Luong Duc Toan 10/11/2017 15°27.50'N, 107°87.90'E Phuoc Son Quang Nam
TG07 Luong Duc Toan 10/11/2017 15°79.20'N, 107°25.90'E Tay Giang Quang Nam
NLay1 Le Thi My Hao 10/11/2017 14°59.60'N, 108°14.80'E Tu Mo Rong Kon Tum
MR3 Le Thi My Hao 10/11/2017 14°97.08'N, 107°99.90'E Tu Mo Rong Kon Tum
TX1 Le Thi My Hao 10/11/2017 14°96.10'N, 107°95.40'E Tu Mo Rong Kon Tum
MR7 Le Thi My Hao 10/11/2017 14°97.10'N, 107°89.50'E Tu Mo Rong Kon Tum
NL1 Le Thi My Hao 10/11/2017 15°06.20'N, 107°94.40'E Dak Glei Kon Tum
X1 Le Thi My Hao 10/11/2017 15°07.60'N, 107°83.20'E Dak Glei Kon Tum
MH1 Le Thi My Hao 10/11/2017 15°73.00'N, 107°54.43'E Dak Glei Kon Tum
P. vietnamensis var. fuscidiscus
SLC Nguyen Tien Dung 07/31/2015 22°20.00'N, 103°42.40'E Sin Ho Lai Chau
Panax sp. Puxailaileng
SNA Nguyen Tien Dung 12/07/2015 19°53.06'N, 104°33.89'E Ky Son Nghe An
P. stipuleanatus
TTH Nguyen Tien Dung 08/26/2015 22°40.86'N, 103°80.67'E Sa Pa Lao Cai
P. bipinnatifidus
SVD Nguyen Tien Dung 08/26/2015 22°40.86'N, 103°80.67'E Sa Pa Lao Cai
Figure 1. 

Distribution of Panax in Vietnam and sample locations. P. vietnamensis (green) collected in Quang Nam and Kon Tum Provinces. P. vietnamensis var. fuscidiscus (brown) collected in Lai Chau Province. Panax sp. Puxailaileng (pink) collected in Nghe An Province. P. bipinnatifidus (blue) and P. stipuleanatus (yellow) collected in Lao Cai Province. The natural distribution of P. vietnamensis, P. vietnamensis var. fuscidiscus, and Panax sp. are marked as green, brown, and pink, respectively. The wild habitat for P. bipinnatifidus and P. stipuleanatus is shown in yellow, and the purple area represents the distribution region of P. vietnamensis var. langbiangensis (not included in this study).

DNA extraction, amplification, and sequencing of previously used and novel markers

Total genomic DNA was extracted from leaf specimens using GeneJET Plant Genomic DNA Purification Kit (Thermo Fisher Scientific, USA) with the provided protocol. The concentration of genomic DNA was determined using a NanoDrop Spectrophotometer 2000 (Thermo Fisher Scientific, USA). Primer pairs for amplification of psbA-trnH, matK and rbcL regions were designed based on available sequences deposited in GenBank, and for ITS region primers were designed as previously reported (Sun et al. 1994). Primers for the four barcodes identified in silico were designed based on the chloroplast genome sequence of P. vietnamensis (Manzanilla et al. 2018) and are shown in Table 2. Each target DNA region was amplified in a PCR volume of 20 μL containing 1X DreamTaq buffer, 200 mM of each dNTP, 2.5 μM of each primer, 1.5 mM MgCl2, 0.75 units of Dream Taq DNA polymerase (Thermo Fisher Scientific, USA) and 50 ng of template DNA. PCR amplification was performed on a Mastercycler (Eppendorf, Germany) using the following conditions: 2 min at 94 °C initial denaturation, 35 amplification cycles (30 s at 94 °C denaturation, 20 s at 55–62 °C annealing, and 1 min at 72 °C extension), 5 min at 72 °C extension, and a final hold at 4 °C. The amplified products were purified using GeneJET PCR Purification Kit (Thermo Fisher Scientific, USA) as described by the manufacturer, then screened on a 1% agarose gel. Purified products were sequenced using ABI 3500 Genetic Analyzer applying BigDye Terminator v3.1 Cycle Sequencing Kit (Thermo Fisher Scientific, USA).

Table 2.

Primers used in this study.

Region Primer name Sequence (5’-3’) Approximate amplicon length (bp)
ITS ITS_AB_101 ACGAATTCATGGTCCGGTGAAGTGTTCG 650
ITS ITS_AB_102 TAGAATTCCCCGGTTCGCTCGCCGTTAC 650
matK MatK_F1A ACYGTATTTTATGTTTACGACG 750
matK MatK_R1A TCCATHTDGAAATCTTGGTTCA 750
psbA-trnH PsbA_trnH_PF ACCCGGTCTTAGTGTATACGAG 390
psbA-trnH PsbA_trnH_PR TTCACTGCCTTGATCCACTTGG 390
rbcL RbcL_PF AGTGTTGGATTCAAGCTGGTG 550
rbcL RbcL_PR TGGTTGTGAGTTCACGTTCT 550
trnQ-rps16 (1) Pv_trnQ_rps16_F GAAGATTTAGGTCCTTAGTCGTTCG 590
trnQ-rps16 (1) Pv_trnQ_rps16_R GATTCAGCATTCCCAGAGAATTGG 590
trnS-trnG (2) Pv_trnS_trnG_F GCCGCTTTAGTCCACTCAGC 660
trnS-trnG (2) Pv_trnS_trnG_F GTGTTGACATTTTTCGTGGGGG 660
petB (3) Pv_petB_F AATATTCAGACCTCGCGGCC 580
petB (3) Pv_petB_R GGCTCAAGCAAAACACCCAA 580
trnE-trnT (4) Pv_trnE_trnT_F GAGTGGTTGGTCCGTCAGAA 520
trnE-trnT (4) Pv_trnE_trnT_R CATGGCGTTACTCTACCGCT 520

Nucleotide matrix construction

Raw sequencing data were checked for quality and cleaned using BioEdit version 7.0.9 (Hall 1999). Ambiguous nucleotides and poor signal regions were removed to avoid incorrect alignment in further analyses. A nucleotide matrix was assembled for both individual and concatenated markers. A matrix from the newly obtained and 91 reference barcoding sequences, and 38 complete chloroplast genomes representing seven species of Panax (P. vietnamensis, P. stipuleanatus, P. bipinnatifidus, Panax ginseng C.A.Mey, Panax japonicus (T.Nees) C.A.Mey, Panax notoginseng (Burkill) F.H.Chen ex C.Y.Wu et K.M.Feng, Panax quinquefolius L.), one unidentified species of Panax (Panax sp. Puxailaileng), and one sub-species of Panax (P. vietnamensis var. fuscidiscus), and two species of Aralia L. (Aralia elata (Miq.) Seem. and Aralia undulata Hand.-Mazz. in Broterus) used as outgroup (Suppl. material 1) were globally aligned using MAFFT version 7.407 (Katoh et al. 2002) followed by local re-alignment with MUSCLE version 3.8.1551 (Edgar 2004). Manual adjustments were made when necessary to improve the matrix. Variable sites, Parsimony informative (PI) sites, mean pairwise distances, and intra/interspecific mean distances were calculated based on nucleotide matrix by MEGAX software (Kumar et al. 2018).

Genetic distance-based methods for species discrimination

Pairwise summary and pairwise explorer modules in TaxonDNA version 1.8 (Meier et al. 2006) were used to calculate the distribution of intra/interspecific pairwise distances for barcoding gap analysis in order to analyze the space between intra- and interspecific distances using the Kimura-2-parameter (K2P) nucleotide substitution model. The Best Match/ Best Close Match (BM/ BCM) modules in TaxonDNA were also used to assess species discrimination power of the analyzed markers using the K2P distance as a model. Thresholds for the best close match were computed from the pairwise summary.

Tree-based method for species discrimination

The best substitution model for each matrix was searched for using the jModelTest2 (Darriba et al. 2012). Phylogenetic trees based on Maximum Likelihood (ML) method were constructed by both RAxML version 8.2.10 (Stamatakis 2014) and IQTREE version 1.6.12 (Bui et al. 2020). Two species A. undulata and A. elata, from the sister genus Aralia were used as outgroups. ML tree searches were performed with bootstrap calculation at 1000 bootstrap replicates. ML trees were then used to perform species delimitation using mPTP version 0.2.4 (Kapli et al. 2017) with two Markov chain Monte Carlo (MCMC) runs, one million steps for each run, and Likelihood ratio test set to 0.01.

Results

Amplification and sequencing efficiency

To evaluate the species discrimination efficiency for both the commonly used as well as newly proposed DNA markers for Panax we assessed the amplification success as well as the amplicon lengths. Bidirectional Sanger DNA sequencing of each fragment showed the amplicon lengths to be as follows: ITS 618–619 bp, matK 751 bp, psbA-trnH 352–361 bp, rbcL 521 bp, trnQ-rps16 575–590 bp, trnS-trnG 648–658 bp, petB 576–577 bp, and trnE-trnT 490–514 bp. ITS and matK did not amplify efficiently despite optimization of PCR amplification conditions, while other chloroplast regions were easily amplified. Despite some challenges, both PCR amplification and sequencing were successful for all regions (Table 3).

Table 3.

Amplification and sequence information for all analyzed markers and their combinations.

Marker Amplification/ Sequencing success rate (%) Matrix size (bp) Variable sites (%) No. of PI sites Mean pairwise distance Intraspecific distances (mean) Interspecific distances (mean)
ITS 100/ 100 623 17.17 75 0.0259 0.0000 –0.0292 (0.0107) 0.0082 –0.0400 (0.0261)
matK 100/ 100 751 4.26 29 0.0054 0.0000- –0.0016 (0.0003) 0.0000 –0.0216 (0.0091)
psbA-trnH 100/ 100 362 10.22 27 0.0175 0.0000 –0.0029 (0.0010) 0.0000 –0.0297 (0.0212)
rbcL 100/ 100 521 2.50 11 0.0061 0.0000 –0.0007 (0.0002)* 0.0019 –0.0101 (0.00615)
trnQ-rps16 (1) 100/ 100 657 6.54 35 0.0116 0.0000 –0.0025 (0.0007) 0.0067 –0.0222 (0.0131)
trnS-trnG (2) 100/ 100 674 5.34 22 0.0068 0.0000 –0.0027 (0.0005) 0.0017 –0.0133 (0.0082)
petB (3) 100/ 100 591 5.58 30 0.0164 0.0000 –0.0025 (0.0004) 0.0013 –0.0340 (0.0196)
trnE-trnT (4) 100/ 100 614 13.84 16 0.0075 0.0000 –0.0004 (0.0001) 0.0039 –0.0274 (0.0108)
1+2 100/ 100 1331 5.94 57 0.0090 0.0000- –0.0021 (0.0006) 0.0047 –0.0167 (0.0105)
1+3 100/ 100 1248 6.09 65 0.0139 0.0000- –0.0025 (0.0006) 0.0040 –0.0251 (0.0164)
1+4 100/ 100 1271 10.07 51 0.0096 0.0000 –0.0014 (0.0004) 0.0054 –0.0238 (0.0120)
2+3 100/ 100 1265 5.45 52 0.0112 0.0000 –0.0014 (0.0005) 0.0017 –0.0210 (0.0135)
2+4 100/ 100 1288 9.39 38 0.0071 0.0000 –0.0017 (0.0003) 0.0034 –0.0195 (0.0093)
3+4 100/ 100 1205 9.79 46 0.0121 0.0000 –0.0013 (0.0003) 0.0025 –0.0240 (0.0154)
1+2+3 100/ 100 1922 5.83 87 0.0113 0.0000 –0.0016 (0.0005) 0.0036 –0.0196 (0.0134)
1+2+4 100/ 100 1945 8.43 73 0.0086 0.0000 –0.0016 (0.0005) 0.0045 –0.0199 (0.0106)
1+3+4 100/ 100 1862 8.65 81 0.0119 0.0000 –0.0017 (0.0004) 0.0040 –0.0213 (0.0146)
2+3+4 100/ 100 1879 8.20 68 0.0101 0.0000 –0.0011 (0.0004) 0.0027 –0.0186 (0.0127)
1+2+3+4 100/ 100 2536 7.77 103 0.0104 0.0000 –0.001 (0.0005) 0.0037 –0.0181 (0.0128)

Nucleotide matrix

The nucleotide matrices for the amplified markers and complemented with the 89 reference barcoding sequences and 36 complete chloroplast genomes from the seven species of Panax, one unidentified species and one sub-species of Panax present in GenBank, showed that the matrix sizes ranged from 362 to 751 bp for individual markers and 1205 to 2536 bp for concatenated markers (Table 3). Among all individual and concatenated markers, ITS possessed the highest proportion of variable sites (17.17%), followed by trnE-trnT (13.84%), psbA-trnH (10.22%), and trnQ-rps16 and trnE-trnT combined (10.07%). ITS also had the most divergence (0.0259) when calculating the mean pairwise distances for each barcode, followed by psbA-trnH (0.0175) and petB (0.0164) (Table 3). Higher numbers of variable sites and pairwise distances indicate higher species divergence, though a previous study has suggested that the proportion of variable sites may not affect a marker’s classification ability (Manzanilla et al. 2018).

Species discrimination power assessment for different markers

Genetic distance-based and sequence similarity-based analyses

Distance-based classification methods rely on intraspecific and interspecific distances to set a threshold to distinguish distinct species. In this study, genetic distances were calculated between individuals both within and between species using MEGAX and Pairwise Explorer (TaxonDNA). Due to the complexity in the species group consisting of P. bipinnatifidus and P. stipuleanatus, these two species were treated as a single group when calculating pairwise distances and assessing the species classification ability of different markers. For interspecific distances, MEGAX computed the average distance of all pairwise distances between each two species while TaxonDNA returned all the distances for every pair of sequences. According to the distances obtained from MEGAX a barcoding gap exists in rbcL, trnQ-rps16, trnE-trnT, and all combined markers (Table 3). However, distribution analysis of pairwise distances in TaxonDNA shows that there was no barcoding gap in eight individual and eleven concatenated marker pairs (Fig. 2). The overlap of intraspecific and interspecific distance distribution was mainly due to the complex genetic distances inside P. ginseng species and similarity between them and P. quinquefolius. High divergence within species and low diversity between species in a complex genus like Panax results in difficulties in setting threshold values for species discrimination using distance-based methods.

Figure 2. 

Percent relative abundance in distribution of intra/interspecific K2P pairwise distances estimated for markers.

BM/BCM analysis from TaxonDNA discriminates species based on similarity between sequences. For separated barcodes, analysis results showed that trnS-trnG and rbcL regions had the strongest discriminatory power with 100% correct identification for both BM calculations, followed by trnE-trnT (98.76%), trnQ-rps16 (97.53%), and ITS (93.82%). BCM analysis returned more stringent calculations of successful identified sequences than BM with 100% for trnS-trnG, 98.76% for trnE-trnT, 96.87% for rbcL, and 95.06% for trnQ-rps16. Markers that had the lowest identification success rate were petB (BM: 72.83%, BCM: 71.60%), matK (BM: 62.50%, BCM: 60.93%), and psbA-trnH (BM: 60.93%, BCM: 60.93%). Combinations made from the four newly proposed markers were also estimated for species identification tests. Discriminatory abilities of concatenated markers were observed to be slightly better than most separated barcodes. Combinations 2+3, 2+4, 3+4, and 2+3+4 showed correct classification rates of 100% for both BM and BCM calculations (Fig. 3).

Figure 3. 

Successful identification rates among analyzed barcodes by Best Match and Best Close Match function.

Tree-based analysis

Both separate and concatenated matrices were used to reconstruct ML trees. We found that most of the markers could separate most of the clades with strong bootstrap support, with the exception of P. bipinnatifidus and P. stipuleanatus. These sister species had poor branch structure and weak support values. The taxonomic circumscription of P. bipinnatifidus has been controversial. Recent studies from Nong et al. (2016), Pham et al. (2020) suggested identifying the leaflet ginseng, which was previously recorded as P. bipinnatifidus in Vietnam, as P. stipuleanatus. Based on morphological characteristics and ITS region, Wen and Zimmer (1996) suggested that the division of the leaflet does not warrant recognition of a novel species or variety. We therefore grouped these species into one group since the initial analysis steps and clade complexity excluded further classification tests. High intraspecific divergence in P. ginseng resulted in this clade being divided into two subgroups in the phylogenetic analysis. In contrast, although there are nucleotide differences between sequences of P. vietnamensis TX1, P. vietnamensis var. fuscidiscus SLC, and other samples of P. vietnamensis, our analysis clearly showed that all samples of P. vietnamensis, and a taxon Panax sp. Puxailaileng belonged to the same clade with strong support (Fig. 4). Phylogenetic trees were also used to estimate the species delimitation using mPTP. The results indicated that among eight individual markers only trnQ-rps16 region could classify all six clades of Panax with strong support. Other regions performed more poorly in delimitation of tested taxa and only weakly supported speciation between P. ginseng and P. quinquefolius and/or P. vietnamensis and P. japonicus. The ITS region is an exception as its nucleotide sequence has the highest variability among species leading to over-splitting of sequences into many small subgroups. The excessive segregation limited the discriminatory ability of this ITS marker at species level. For concatenated barcodes, 1+4, 1+2+4, 1+3+4, and 1+2+3+4 showed the ability to classify all six clades in the genus Panax (Figs 4, 5).

Figure 4. 

Results of mPTP species delimitation analysis for several markers based on ML trees A Species delimitation for marker trnQ-rps16 B Species delimitation for the combination of markers 1+3+4. Bootstrap values are displayed on the branches. The red branches represent supported species delimitations. Sequences highlighted in orange originate from this study.

Selecting markers for identification of Panax spp

Incongruence between genetic distance-based, sequence similarity-based and tree-based methods has led to difficulties in choosing robust markers for species discrimination in complex genera like Panax. Here we examined the identification abilities of two methods for four newly proposed markers and combinations thereof in comparison with four commonly used barcodes (Fig. 5). Distance-based methods failed to detect the barcoding gap between intraspecific and interspecific distances for analyzed markers due to the complex divergence in sister species P. ginseng and P. quinquefolius. RbcL had the least overlapping intra/interspecific distances, but also had the lowest variation in pairwise distance. This leads to low resolution in species classification. Barcoding analysis based on sequence similarity showed high correct identification percentages for two of the four common barcodes and three of the four novel barcodes. All concatenated markers showed high identification power, but this was not the case for classification results calculated by tree-based methods. The highest identification rates were observed in trnQ-rps16, 1+4, 1+2+4, 1+3+4, and 1+2+3+4 regions with mPTP analysis. Other robust markers identified by TaxonDNA had lower species resolution in mPTP. We thus propose that trnQ-rps16 is the best single marker for species identification in the Panax genus since it provides the best classification resolution in both sequence similarity-based and tree-based analyses.

Figure 5. 

Percentage of variable sites, mean pairwise distances, and correct classification percentages of all markers and combinations

Discussion

Phylogenetic studies on Panax using different DNA barcodes, different reference sequences or samples have resulted in conflicting tree topologies and clade placements for several species (Wen and Zimmer 1996; Komatsu et al. 2001; Zuo et al. 2011; Ali et al. 2012; Le et al. 2017; Manzanilla et al. 2018). For example, two sister species P. bipinnatifidus and P. stipuleanatus were separated into two distant clades based on the combined dataset of six markers by Zuo et al. (2011). Meanwhile, these two above taxa could not be separated into two clades using the ITS region alone (Wen and Zimmer 1996). This inability to resolve a clear sister relationship between these two species was also supported by the four novel markers assessed in our study. Similarly, P. vietnamensis was reported to belong to the same clade as Panax japonicus var. major (Burkill) C.Y.Wu et Feng, Panax pseudoginseng subsp. himalaicus H.Hara based on 18S rRNA and matK (Komatsu et al. 2001), and to be closely related to Panax zingiberensis C.Y.Wu et Feng and Panax wangianus S.C.Sun based on ITS2 (Ali et al. 2012), P. notoginseng based on ITS, matK, rbcL, psbA-trnH, and 18S rRNA (Le et al. 2017), as well as P. japonicus based on in silico data of four potential markers (Manzanilla et al. 2018). With regard to an unidentified sample Panax sp. Puxailaileng, our phylogenetic trees based on comprehensive datasets of the marker trnQ-rps16 or combined markers 1+3+4 (Fig. 4) obviously revealed this taxon belonged to the same clade with all samples of P. vietnamensis. Relevant bootstrap values at 90–99 by Maximum Likelihood method indicated that confidence intervals were eligible for genetic correlation of these samples. The obtained results on these novel markers are congruent with or different from previous studies. Panax sp. Puxailaileng was suggested to be P. vietnamensis based on its morphological characteristics and ITS-rDNA sequence, though further studies are still needed to unambiguously resolve its identity (Tran et al. 2016). Similarly, morphology and molecular-based phylogenetic analyses suggested Panax sp. Puxailaileng found in the wild in Ky Son District, Nghe An Province were P. vietnamensis var. fuscidiscus (Pham et al. 2020). In another study, samples of Panax sp. collected from Puxailaileng Mountain were reported to be closely related to P. stipuleanatus based on the commonly use markers ITS-rDNA and matK (Vu et al. 2020). Present results based on empirical data support the results of the in silico study by Manzanilla et al. (2018). P. vietnamensis is closely related to P. japonicus. This apparent contradiction with other studies might result from differences in dataset structures, the number of species and taxa included, and classification methods. Indeed, different approaches can return different results in DNA barcoding analyses (Wen and Zimmer 1996; Komatsu et al. 2001; Zuo et al. 2011; Ali et al. 2012; Le et al. 2017; Manzanilla et al. 2018). The genetic distances calculated in MEGAX suggest that barcoding gaps exist in the markers rbcL, trnQ-rps16, trnE-trnT, and all concatenated markers, whereas TaxonDNA showed overlap between intra and interspecific distances in all analyzed markers (Table 3, Fig. 2). This incongruence could make a tremendous difference in the output of the analyses. Nevertheless, results obtained from the BM/BCM module in TaxonDNA are similar to distances calculated in MEGAX. In general, the discriminatory power assessed in TaxonDNA is higher than in the tree-based method mPTP (Fig. 5). Especially for rbcL, distance-based methods provide the highest percentage of correctly identified species while the tree-based method gave the lowest percentage of correctly identified species. The low number of variable sites within some markers can explain the differences in results between the two methods (Fig. 5). Highly conserved regions with low percentages of variable sites might lead to sound results when calculating genetic distances, but might make the construction of a phylogenetic tree challenging. This limitation for distance-based methods can sometimes result in biologically meaningless results (Meier et al. 2008; Ross et al. 2008). However, the comparison between the two methods generated several common similarities for the marker trnQ-rps16 and a number of different marker combinations with high discriminatory power, e.g., 1+4, 1+2+4, 1+3+4, 1+2+3+4 (Fig. 5).

In the present study, the discriminatory power of four chloroplast markers proposed by Manzanilla et al. (2018), for Panax spp. was evaluated. The highly valuable P. vietnamensis species and collected samples from eighteen distinct populations across the country were analyzed. The obtained results did not show any significant differences between the populations, which suggests that trnQ-rps16 marker is appropriate for identification at the species level and does not lead to misidentifications of P. vietnamensis regardless of their origins or geographical distributions. Only small differences between experimental and in silico analyses were observed. The in silico study included only a limited number of P. vietnamensis accessions, and this may explain why the empirical data contains more variable sites in P. vietnamensis. Our results support the use of trnQ-rps16 as a single molecular marker for species identification in the genus Panax. An advantage of using a single region for species identification is the reduced time and effort necessary for routine analyses, though it can be combined with other markers (petB, trnE-trnT) when necessary if a single marker is not enough to unambiguously provide a species-level identification. Beside its discriminatory power, trnQ-rps16 can also be easily amplified.

Acknowledgements

This work was supported by the Ministry of Science and Technology of Vietnam under the project: “Transcriptome sequencing and analysis of Panax vietnamensis Ha et Grushv.” (Grant number 16/2017-HĐ-NVQG). We deeply appreciate Le Thi My Hao and Luong Duc Toan who kindly providing the samples of P. vietnamensis and Nguyen Tien Dung for providing the samples of P. vietnamensis var. fuscidiscus, Panax sp.Puxailaileng, P. stipuleanatus, and P. bipinnatifidus. We would like to thank Nguyen Tap and Nguyen Quoc Binh for the morphological identification of the samples. Marcella Orwick Rydmark, Hugo J. de Boer, and Nguyen Tuong Van are acknowledged for proofreading the text.

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Supplementary material

Supplementary material 1 

NCBI accession numbers of DNA barcoding sequences, and complete chloroplast genomes used in this study.

Nguyen Nhat Linh, Pham Le Bich Hang, Huynh Thi Thu Hue, Nguyen Hai Ha, Ha Hong Hanh, Nguyen Dang Ton, Le Thi Thu Hien

Data type: NCBI accession numbers of DNA sequences and complete chloroplast genomes

Explanation note: The NCBI accession numbers of newly obtained and 91 reference barcoding sequences, and 38 complete chloroplast genomes representing seven Panax species, one unidentified species and one sub-species of Panax, and two outgroup Aralia species.

This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited.
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