molecular identification of physalis species (solanaceae ... · draft 2 30 abstract: 31 physalis...

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Molecular identification of Physalis species (Solanaceae)

using a candidate DNA barcode: the chloroplast psbA–trnH intergenic region

Journal: Genome

Manuscript ID gen-2017-0115.R2

Manuscript Type: Article

Date Submitted by the Author: 07-Sep-2017

Complete List of Authors: Feng, Shangguo; Hangzhou Normal University, College of Life and

Environmental Sciences Jiao, Kaili; Hangzhou Normal University Zhu, Yujia; Hangzhou Normal University Wang, Hongfen; Shandong Xiajin First Middle School Jiang, Mengying; Hangzhou Normal University Wang, Huizhong; Hangzhou Normal University, College of Life and Environmental Sciences

Is the invited manuscript for consideration in a Special

Issue? : This submission is not invited

Keyword: Physalis, DNA barcoding, psbA–trnH region, molecular identification

https://mc06.manuscriptcentral.com/genome-pubs

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Molecular identification of Physalis species (Solanaceae) using a candidate DNA 1

barcode: the chloroplast psbA–trnH intergenic region 2

Shangguo Feng 1, 2

, Kaili Jiao 2, Yujia Zhu

2, Hongfen Wang

3, Mengying Jiang

2, 3

Huizhong Wang 2, * 4

1 College of Bioscience & Biotechnology, Hunan Agricultural University, Changsha 5

410128, China 6

2 Zhejiang Provincial Key Laboratory for Genetic Improvement and Quality Control 7

of Medicinal Plants, College of Life and Environmental Sciences, Hangzhou Normal 8

University, Hangzhou 310036, China 9

3 Shandong Xiajin First Middle School, Xiajin 253200, China 10

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*Corresponding author 13

Huizhong wang: [email protected]. 14

The email addresses of the other co-authors: [email protected] (Shangguo 15

Feng), [email protected] (Kaili Jiao), [email protected] (Yujia Zhu), 16

[email protected] (Hongfen Wang), [email protected] (Mengying Jiang). 17

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Abstract: 30

Physalis L., an important genus of the family Solanaceae, includes many 31

commercially important edible and medicinal species. Traditionally, species 32

identification is based on morphological traits; however, the highly similar 33

morphological traits among Physalis species make this approach difficult. In this 34

study, we evaluated the feasibility of using a popular DNA barcode, the chloroplast 35

psbA–trnH intergenic region, in the identification of Physalis species. Thirty-six 36

psbA–trnH regions of Physalis species and of the closely related plant Nicandra 37

physalodes were analyzed. The success rates of PCR amplification and sequencing of 38

the psbA–trnH region were 100%. MEGA V6.0 was utilized to align the psbA–trnH 39

sequences and to compute genetic distances. The results show an apparent barcoding 40

gap between intra- and inter-specific variations. Results of both BLAST1 and 41

nearest-distance methods prove that the psbA–trnH regions can be used to identify all 42

species examined in the present study. In addition, phylogenetic analysis using 43

psbA–trnH data revealed a distinct boundary between species. It also confirmed the 44

relationship between Physalis species and closely related species, as established by 45

previous studies. In conclusion, the psbA–trnH intergenic region can be used as an 46

efficient DNA barcode for the identification of Physalis species. 47

Keywords: Physalis; DNA barcoding; psbA–trnH region; molecular identification 48

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Introduction 60

Physalis is one of the important genera of the plant family Solanaceae, 61

comprising ranged from 75 to 120 species (Maggie 2005; Martinez 1998; Chinese 62

Academy of Sciences 1978; Wei et al. 2012). Most Physalis species are distributed in 63

tropical and temperate regions of the Americas, and a few species are native to 64

Eurasia and Southeast Asia (Feng et al. 2016; Maggie 2005; Martinez 1998; Chinese 65

Academy of Sciences 1978; Wei et al. 2012). In China, there are five Physalis species 66

(Physalis alkekengi, P. angulate, P. peruviana, P. pubescens, and P. minima) and two 67

varieties (P. alkekengi var. franchetii, P. angulate var. villosa), which are mainly 68

distributed in the eastern, central, southern and southwestern regions (Chinese 69

Academy of Sciences 1978). Because of their high content of vitamins, minerals, and 70

antioxidants, many Physalis species possess potential medicinal properties such as 71

anti-bacterial, anti-inflammatory, and anti-cancer activity (Hong et al. 2015; Ji et al. 72

2012; Wei et al. 2012). For example, P. alkekengi var. franchetii, a standard medical 73

plant recorded in the Pharmacopoeia of the People’s Republic of China, is used in 74

traditional Chinese medicine for the treatment and prevention of sore throat, tumors, 75

cough, leishmaniasis, eczema, hepatitis, and urinary problems (Chinese 76

Pharmmacopoeia Editorial Committee 2015; Yang et al. 2016). Moreover, some 77

Physalis species such as P. philadelphica, P. peruviana, and P. pubescens are 78

extensively cultivated for their edible fruits in many regions of the world (Sang-Ngern 79

et al. 2016; Zamora-Tavares et al. 2015; Zhang et al. 2016). 80

Because of their highly similar morphological characteristics, misidentification 81

of Physalis species is common (Fig. 1). For example, P. minima can be confused with 82

P. angulate or P. pubescens in applications in traditional Chinese medicine (Feng et al. 83

2016; Chinese Academy of Sciences 1978). In addition, some species of another 84

genus such as Nicandra physalodes are often mistaken for Physalis species (Feng et al. 85

2016) (Fig. 1). The amounts of biologically active compounds and their application 86

value differ among Physalis species and their related species. Thus, incorrect 87

identification of Physalis species can lead to their inappropriate usage and failures in 88

their genetic resource conservation. The traditional morphological authentication 89

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approach is often affected by heritable variation and growth environment (Maggie 90

2005; Vargas-Ponce et al. 2011). Hence, a rapid and reliable identification method for 91

Physalis is essential. 92

DNA barcoding, a technique based on sequence diversity within short and 93

standardized nuclear or chloroplast DNA (cpDNA) region, is often used in species 94

authentication (Chen et al. 2010; Feng et al. 2016; Feng et al. 2015; Hebert et al. 95

2004). cpDNA sequences (atpF–atpH, psbA–trnH, matK, rbcL) have been widely 96

used as a tool in studies on plant phylogenetics and species identification. In particular, 97

the psbA–trnH intergenic region has been found to be ubiquitous in plants; it has thus 98

emerged as one of the popular DNA barcodes (Cbol Plant Working Group 2009; Gao 99

et al. 2013; Kress and Erickson 2007; Kress et al. 2005; Yao et al. 2009). However, 100

few studies have reported the use of the psbA–trnH intergenic region in the barcoding 101

of Physalis species. In the present study, we examined the feasibility of using the 102

psbA–trnH intergenic region as a DNA barcode in the identification of eight Physalis 103

species including four collected from China and four obtained from GenBank (Clark 104

et al. 2016). 105

Materials and Methods 106

Plant Materials 107

In this study, 32 samples belonging to eight Physalis species and four samples of 108

N. physalodes (often mistaken for Physalis species because of its similar 109

morphological characteristics) were collected (Table 1, Fig. 1). Among the specimens, 110

31 were collected from the main distribution regions from China for sequencing 111

(Table 1). Other psbA–trnH sequences of Physalis species were obtained from 112

GenBank (Clark et al. 2016). All collected samples were verified on the basis of the 113

specimens stored in the Chinese Virtual Herbarium (http://www.cvh.ac.cn/). 114

DNA Extraction, Amplification, and Sequencing 115

Fresh young leaves of the collected samples were used for genomic DNA 116

isolation, as previously reported (Feng et al. 2016; Feng et al. 2013). The pair of 117

universal primers used to amplify chloroplast psbA–trnH sequences consisted of 118

psbAF (5ʹ- GTTATGCATGAACGTAATGCTC-3ʹ) and trnHR 119

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(5ʹ-CGCGCATGGTGGATTCACAAATC-3ʹ) (Sang et al. 1997). PCR amplification 120

was conducted using 25 µL volumes containing 1× PCR buffer with MgCl2, 0.4 mM 121

dNTPs, 0.4 µM of each primer (synthesized by Sangon Biotech Co., Ltd., Shanghai 122

China), and 1.0 U Taq DNA polymerase (TaKaRa Bio., Kyoto, Japan). PCR 123

amplification was conducted in a Mastercycler Nexus gradient thermocycler 124

(Eppendorf AG, Hamburg, Germany) with the following parameter settings: holding 125

at 94ºC for 5 min followed by 32 cycles at 94ºC for 50 s, at 55ºC for 50 s, and at 72ºC 126

for 1.5 min, and a final extension at 72ºC for 10 min. The amplification products were 127

sequenced in both directions by Sunny Biotechnology Co., Ltd., Shanghai, China. 128

Data Analysis 129

The program Clustal W (Thompson et al. 2002) was used to align the chloroplast 130

psbA–trnH regions obtained from all samples, but this was assisted by manual editing. 131

MEGA 6.0 was used to calculate the genetic distances with the Kimura two-parameter 132

(K2P) model (Tamura et al. 2013). Inter-specific divergences were evaluated by 133

average inter-specific distance, minimum inter-specific distance, and average theta 134

prime calculated using the K2P model, while the intra-specific variation was 135

determined from the metrics average intra-specific distance, coalescent depth, and 136

theta based on the K2P model (Chen et al. 2010; Meyer and Paulay 2005). The 137

distributions of intra-specific variability were compared against those of the 138

inter-specific variability using DNA barcoding gaps (Chen et al. 2010; Meyer and 139

Paulay 2005). Wilcoxon two-sample tests were carried out as previous study (Chen et 140

al. 2010). BLAST1 and nearest-distance methods were performed to assess the 141

discriminatory efficacy of psbA–trnH sequences for the collected species (Feng et al. 142

2015; Slabbinck et al. 2008). For the BLAST1 method, the reference database for 143

all psbA–trnH regions were searched using the BLAST program 144

(http://blast.ncbi.nlm.nih.gov/Blast.cgi). For the nearest-distance method, 145

identification was based on all pairwise genetic distances calculated between each 146

query and each of the reference sequences, as well as among the reference sequences. 147

Phylogenetic analysis was conducted according to the neighbor-joining (NJ) and 148

maximum likelihood (ML) methods using MEGA 6.0 (Tamura et al. 2013), with the 149

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following parameters: 1000 bootstrap replicates, Tamura-Nei model, and complete 150

elimination of all positions containing gaps and missing data. 151

Results 152

PCR Efficiency, Sequencing, and Characteristics of the psbA–trnH regions 153

The success rates of PCR amplification and sequencing of the psbA–trnH regions 154

from the sampled specimens were 100%. The lengths of the psbA–trnH regions were 155

in the range 492 to 553 bp, having an average of 515 bp (Table 1). The GC content 156

ranged from 26.95% to 29.47%, with an average of 28.28%. Therefore, the sequence 157

length and GC content of the psbA–trnH regions varied. The GenBank accession 158

number of each psbA–trnH region is given in Table 1. 159

Genetic Divergence within and between Species 160

Genetic divergences were calculated using MEGA 6.0. The six metrics used to 161

evaluate the inter-specific versus intra-specific variation are shown in Table 2. The 162

genetic distances of the three intra-specific metrics (average intra-specific distance, 163

coalescent depth, and theta) are far less than the genetic distances of the three 164

inter-specific metrics (average inter-specific distance, minimum inter-specific distance, 165

and theta prime) (Table 2). Significant differences between the inter-specific and 166

intra-specific divergences were also demonstrated by Wilcoxon two-sample tests 167

(Table 3). 168

Assessment of the Barcoding Gap 169

The distributions of genetic distance of all tested samples calculated using the 170

K2P model of intra- versus inter-specific variation on a scale of 0.004 distance units 171

were analyzed (Fig. 2). We observed a barcoding gap between intra-specific and 172

inter-specific variation (Fig. 2). The intra-specific genetic distance was in the range of 173

0.000–0.008 and the proportion of intra-specific genetic distance that equal zero 174

reached 89.89%. The inter-specific genetic distance ranged from 0.002 to 0.922, and 175

the proportion of inter-specific genetic distance of ≥0.011 was 82.33% (Fig. 2). 176

Species Discriminability of psbA–trnH 177

The results of both BLAST1 and nearest-distance methods indicate that the 178

identification rates at the species level using psbA–trnH are 100.0% accurate (Table 4) 179

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and that psbA–trnH therefore possesses high discriminability for the eight Physalis 180

species and N. physalodes collected in the study. 181

Both the NJ and ML phylogenetic trees constructed based on psbA–trnH regions 182

suggest that all of the tested samples can be grouped into three main clusters (Fig. 3). 183

Cluster I is the most complex and contains ungrouped samples of P. angulata and four 184

strongly supported species clades containing (I-1) P. pubescens, (I-2) P. gracilis + P. 185

pruinosa, (I-3) P. minima, and (I-4) P. heterophylla + P. peruviana with strong support 186

(BS = 99 for NJ method, and 96 for ML methods). Cluster II, which has strong 187

support (BS = 100 for both NJ and ML methods), contains six samples of P. alkekengi 188

var. franchetii. All samples of N. physalodes from genus Nicandra are distant from 189

any Physalis species, and constitute cluster III with strong support (BS = 100 for both 190

NJ and ML methods). Both NJ and ML trees also show that more than one sample 191

from the same species can be grouped into one branch (Fig. 3, A and B). 192

Discussion 193

The commercial value of many Physalis species has received more attention 194

because of their edible fruits, medicinal value, and ornamental value (Feng et al. 2016; 195

Valdivia-Mares et al. 2016; Zhang and Tong 2016). Therefore, their accurate 196

identification is highly important. However, their identification based on 197

morphological characteristics, which are similar, is extremely difficult. In fact, the 198

psbA–trnH region has been used as a DNA barcode to authenticate various plants with 199

similar morphological traits (Chen et al. 2010; Gao et al. 2013; Ma et al. 2010; Yang 200

et al. 2011; Yao et al. 2009). In the present work, we used for the first time the 201

chloroplast psbA–trnH region for barcoding Physalis species. 202

Many researchers have reported that the intra-specific variation of psbA–trnH 203

region is very low while the inter-specific divergence is very large in a wide variety of 204

plants (Gao et al. 2013; Ma et al. 2010; Yang et al. 2011; Yao et al. 2009). Similar 205

results were found in our study. We found that the genetic distance between most 206

samples from the same species in this study is 0.000 (P. angulate, P. pubescens and P. 207

alkekengi var. franchetii, and P. peruviana), which means that most of the Physalis 208

species have a unique psbA–trnH sequence. This feature is thus useful for identifying 209

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different Physalis species and related species. 210

According to results of the BLAST1 and nearest-distance methods, psbA–trnH 211

leads to high species discriminability (100.00% identification success rates for both 212

methods). Interestingly, P. pubescens and P. pruinosa have highly similar 213

morphological traits. Hence, they cannot be easily distinguished from each other by 214

traditional morphological approach and by use of nuclear ribosomal ITS2 sequences 215

(Feng et al. 2016), but they can be accurately identified on the basis of their 216

psbA–trnH regions. The results strongly suggest that the psbA–trnH region can be 217

used as a complementary barcode (Chen et al. 2010). 218

The NJ and ML phylogenetic trees constructed with the psbA–trnH regions 219

indicate that different samples from the same species can be grouped together. 220

Previous studies (Feng et al. 2016; Maggie 2005) reported that P. alkekengi var. 221

franchetii, which is distant from any other Physalis species, constitute a separate 222

cluster (II) with strong support (Fig. 3, BS = 100 for both NJ and ML methods). This 223

result supports the inclusion of P. alkekengi var. franchetii in the Chinese 224

Pharmacopoeia as the source of Herba Physalis (Chinese Pharmmacopoeia Editorial 225

Committee 2015). In addition, N. physalodes, a species often mistaken for Physalis 226

species because of its similar morphological traits, is separated from any Physalis 227

species by the psbA–trnH regions (Fig. 3, BS = 100 for both NJ and ML methods). 228

Therefore, the psbA–trnH region is useful for species identification, as well as 229

contributes to the phylogenetic analysis of Physalis and its closely related species. 230

Conclusions 231

Our study demonstrates that the chloroplast psbA–trnH intergenic region 232

possesses high species discriminability and that it could be an ideal universal DNA 233

barcode for Physalis species tested in this study. However, more Physalis species 234

should be collected in the future to verify whether psbA–trnH region could be used to 235

identify all species of Physalis. In addition, NJ and ML tree analyses provided solid 236

evidence that the psbA–trnH region has potential use in the phylogenetic analysis of 237

Physalis and plants closely related to it. 238

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Acknowledgments 239

This study was supported in part by the National Natural Science Foundation of China 240

(31470407), the Zhejiang Provincial Public Welfare Technology Applied Research 241

Foundation of China (2014C32090), the Hangzhou Scientific and Technological 242

Program (20150932H04), and the Hangzhou Scientific and Technological Program 243

(20150932H03). 244

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Table 1 Voucher information, GenBank accession numbers, sequence lengths and GC content of the psbA-trnH sequences for all samples 347

examined in the study 348

Species Name Locality information Longitude (E) Latitude (N)

Voucher No. GenBank

Accession No.

Sequence

lengths (bp)

GC content

(%)

Physalis angulata L. Xiaoshan, Hangzhou, Zhejiang, China 120°15′ 30°11′ PHZ0001 KY263828 504 29.17

P. angulata Lin’an, Hangzhou, Zhejaing, China 119°43′ 30°14′ PHZ0002 KY263829 504 29.17

P. angulata Pujiang, Jinhua, Zhejiang, China 121°30′ 31°04′ PHZ0003 KY263830 504 29.17

P. angulata Yueqing, Wenzhou, Zhejiang, China 120°58′ 28°06′ PHZ0004 KY263831 504 29.17

P. angulata Luotian, Huanggang, Hubei, China 115°23′ 30°47′ PHZ0005 KY263832 504 29.17

P. angulata Xiajin, Dezhou, Shandong, China 116°00′ 36°57′ PHZ0006 KY263833 504 29.17

P. angulata Baohua, Honghe, Yunnan, China 102°20′ 23°17′ PHZ0007 KY263834 504 29.17

P. alkekengi var. franchetii

(Mast.) Makino

Nong’an, Changchun, Jilin, China 125°10′ 44°25′ PHZ4001

KY263848

501

26.95

P. alkekengi var. franchetii Faku, Shenyang, Liaoning, China 123°24′ 42°30′ PHZ4002 KY263850 501 26.95

P. alkekengi var. franchetii Donggang, Dandong, Liaoning, China 124°08′ 39°51′ PHZ4003 KY263851 501 26.95

P. alkekengi var. franchetii Donggang, Dandong, Liaoning, China 124°08′ 39°51′ PHZ4004 KY263852 501 26.95

P. alkekengi var. franchetii Zoucheng, Jinan, Shandong, China 116°59′ 35°24′ PHZ4005 KY263853 501 26.95

P. alkekengi var. franchetii Zoucheng, Jinan, Shandong, China 116°59′ 35°24′ PHZ4006 KY263854 501 26.95

P. gracilis Miers GenBank – – – HG963529 509 28.09

P. heterophylla Nees GenBank – – – HQ596787 492 29.47

P. minima L. Tangshan, Hebei, China 118°10′ 39°37′ PHZ3001 KY263844 506 28.66

P. minima Pingdingshan, Henan, China 113°11′ 33°46′ PHZ3002 KY263845 506 28.66

P. minima Heze, Shandong, China 115°28′ 35°14′ PHZ3003 KY263846 506 28.66

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P. minima Lishui, Zhejiang, China 119°55′ 28°28′ PHZ3004 KY263847 506 28.85

P. minima Lou’An, Anhui, China 116°31′ 31°44′ PHZ3005 KY263848 506 28.66

P. peruviana L. GenBank – – – HQ216179 509 28.88

P. peruviana GenBank – – – HQ216178 509 28.88

P. pruinosa (Waterf.) M.

Martinez

GenBank – – –

HG963524 509

28.49

P. pubescens L. Faku, Shenyang, Liaoning, China 123°24′ 42°30′ PHZ2001 KY263835 525 28.38

P. pubescens Guta, Jinzhou, Liaoning, China 121°07′ 41°06′ PHZ2002 KY263835 525 28.38

P. pubescens Changhai, Dalian, Liaoning, China 122°35′ 39°16′ PHZ2003 KY263837 525 28.38

P. pubescens Chaoyang, Zhaodong, Heilongjiang, China 126°15′ 45°52′ PHZ2004 KY263838 525 28.38

P. pubescens Baiquan, Qiqiha’er, Heilongjiang, China 126°05′ 47°35′ PHZ2005 KY263839 525 28.38

P. pubescens Aihui, Heihe, Heilongjiang, China 127°29′ 50°14′ PHZ2006 KY263840 525 28.38

P. pubescens Nong’an, Changchun, Jilin, China 125°10′ 44°25′ PHZ2007 KY263841 525 28.38

P. pubescens Nong’an, Changchun, Jilin, China 125°10′ 44°25′ PHZ2008 KY263842 525 28.38

P. pubescens Tonghua, Changchun, Jilin, China 125°45′ 41°40′ PHZ2009 KY263843 525 28.38

Nicandra physalodes (L.)

Gaertn.

Yiwu, Jinhua, Zhejiang, China

120°04′ 29°18′ NHZ0001

KY263855

552

27.54

N. physalodes Jiujiang, Jiangxi, China 115°59′ 29°42′ NHZ0002 KY263856 552 27.72

N. physalodes Changsha, HuNan, China 112°56′ 28°13′ NHZ0003 KY263857 553 27.12

N. physalodes Xiaoshan, Hangzhou, Zhejiang, China 120°15′ 30°11′ NHZ0004 KY263858 553 27.12

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Table 2 Analyses of inter-specific divergence and intra-specific variation of the 349

chloroplast psbA–trnH regions 350

Measurement K2P value

All inter-specific distance 0.280 ± 0.027

Theta prime 0.246 ± 0.024

Minimum inter-specific distance 0.243 ± 0.024

All intra-specific distance 0.000 ± 0.000

Theta 0.001 ± 0.001

Coalescent depth 0.002 ± 0.001

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

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374

Table 3 Results of Wilcoxon two-sample tests for the distribution of intra- vs. 375

inter-specific divergences 376

No. of inter-specific distances No. of intra-specific distances Wilcoxon W P value

533 89 4357 4.06e-50

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

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401

Table 4 Comparison of efficiencies of authentication of chloroplast psbA–trnH region 402

using different methods 403

Methods of

identification

No. of

samples

No. of

species

Correct

identification

Incorrect

identification

Ambiguous

identification

BLAST1 36 9 100% 0 0

Nearest-distance 36 9 100% 0 0

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

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Figure captions 427

Fig. 1 Plant morphology of P. angulate, P. alkekengi var. franchetii, P. minima, P. 428

pubescens, and Nicandra physalodes. 429

Fig. 2 Relative distributions of inter-specific divergence and intra-specific variation of 430

the psbA–trnH region based on K2P genetic distance. 431

Fig. 3 Neighbor-joining (NJ) and maximum likelihood (ML) trees based on 432

psbA–trnH sequences. Numbers above branches indicate bootstrap support (BS) 433

values (BS≥50). (A): NJ tree and (B): ML tree. 434

435

436

437

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Fig. 1 Plant morphology of P. angulate, P. alkekengi var. franchetii, P. minima, P. pubescens, and Nicandra physalodes.

169x107mm (300 x 300 DPI)

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Fig. 2 Relative distributions of inter-specific divergence and intra-specific variation of the psbA–trnH region based on K2P genetic distance.

150x107mm (300 x 300 DPI)

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Fig. 3 Neighbor-joining (NJ) and maximum likelihood (ML) trees based on psbA–trnH sequences. Numbers

above branches indicate bootstrap support (BS) values (BS≥50). (A): NJ tree and (B): ML tree.

166x103mm (300 x 300 DPI)

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molecular identification of physalis species (solanaceae ... · draft 2 30 abstract: 31 physalis...

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