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DNA Barcoding the Dioscorea in China, a Vital Group in the Evolution of Monocotyledon: Use of matK Gene for Species Discrimination

  • Xiao-Qin Sun,

    Affiliation Jiangsu Province Key Laboratory for Plant Ex Situ Conservation, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, People's Republic of China

  • Ying-Jie Zhu,

    Affiliation Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, People's Republic of China

  • Jian-Lin Guo,

    Affiliation Jiangsu Province Key Laboratory for Plant Ex Situ Conservation, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, People's Republic of China

  • Bin Peng,

    Affiliation Jiangsu Province Key Laboratory for Plant Ex Situ Conservation, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, People's Republic of China

  • Ming-Ming Bai,

    Affiliation Jiangsu Province Key Laboratory for Plant Ex Situ Conservation, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, People's Republic of China

  • Yue-Yu Hang

    hangyueyu@yahoo.com.cn

    Affiliation Jiangsu Province Key Laboratory for Plant Ex Situ Conservation, Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, People's Republic of China

DNA Barcoding the Dioscorea in China, a Vital Group in the Evolution of Monocotyledon: Use of matK Gene for Species Discrimination

  • Xiao-Qin Sun, 
  • Ying-Jie Zhu, 
  • Jian-Lin Guo, 
  • Bin Peng, 
  • Ming-Ming Bai, 
  • Yue-Yu Hang
PLOS
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Abstract

Background

Dioscorea is an important plant genus in terms of food supply and pharmaceutical applications. However, its classification and identification are controversial. DNA barcoding is a recent aid to taxonomic identification and uses a short standardized DNA region to discriminate plant species. In this study, the applicability of three candidate DNA barcodes (rbcL, matK, and psbA-trnH) to identify species within Dioscorea was tested.

Methodology/Principal Findings

One-hundred and forty-eight individual plant samples of Dioscorea, encompassing 38 species, seven varieties and one subspecies, representing majority species distributed in China of this genus, were collected from its main distributing areas. Samples were assessed by PCR amplification, sequence quality, extent of specific genetic divergence, DNA barcoding gap, and the ability to discriminate between species. matK successfully identified 23.26% of all species, compared with 9.30% for rbcL and 11.63% for psbA-trnH. Therefore, matK is recommended as the best DNA barcoding candidate. We found that the combination of two or three loci achieved a higher success rate of species discrimination than one locus alone. However, experimental cost would be much higher if two or three loci, rather than a single locus, were assessed.

Conclusions

We conclude that matK is a strong, although not perfect, candidate as a DNA barcode for Dioscorea identification. This assessment takes into account both its ability for species discrimination and the cost of experiments.

Introduction

Dioscorea is a genus of more than 600 plant species in the family Dioscoreaceae [1], which contains approximately 70 sections. These species are mainly found in Southeast Asia, Africa, Central America, South America, and in other tropical or subtropical regions where some Dioscorea species are an economically important supply of starch in the staple diet. The genus is also a favored source of medicinal plants used to extract precursors of cortisone and other steroid hormones [2][4]. The importance of Dioscorea in terms of food supply and pharmaceutical use, together with the controversy over classification [5][8], has given impetus to improve the identification of this genus.

In this study, we aimed to establish a high-quality system for taxonomic identification to meet the requirements of agriculture and the pharmaceutical industry. Since the early 20th century, morphology, cytology, palynology, and other traditional means of identification of this genus have been explored successively [9][16]. With the development of molecular biology, however, some DNA sequences, such as those of rbcL, matK and trnL-F, have been used to solve complicated taxonomic problems and to infer phylogenetic relationships among organisms, including members of the Dioscoreaceae [17][19].

DNA barcoding has recently emerged as an aid for global species identification and has been successfully used in several studies when morphological characteristics were absent [20][23]. In animals, the mitochondrial gene cytochrome c oxidase I (COI) has provided a favorable solution in species identification [24][29]; however this gene has limited usefulness in plants. Therefore, several candidate regions have been proposed for use in plants, including portions of some coding genes (matK, rbcL, rpoB and rpoC1) [23], noncoding spacers (psbA-trnH, atpF-atpH and ITS) [30][32], or a combination of several regions [33].

Little research has been carried out to investigate the applicability and effectiveness of different DNA regions as barcodes to identify species within Dioscorea. In particular, characterisation of species found in China, one of the most likely centers of origin [34], [35], was rarely included in previous studies. This study focuses on Dioscorea species distributed in China, and three candidate DNA barcode regions (matK, rbcL and psbA-trnH) in the plastid genome were evaluated for identification. We aimed to address several questions: for example, which of these three regions is the most useful as a barcode and how effective are these three regions and their combinations for this discrimination?

Results

Sequence analysis and amplification efficiency

The sequence information of three candidate DNA barcode markers, matK, rbcL and psbA-trnH, is provided in Table 1. For individual regions, aligned sequence lengths ranged from 535 bp for psbA-trnH to 752 for matK. rbcL was the most conserved gene (522/553 nucleotides), based on both sequence length and number of conserved sites. matK had the greatest nucleotide variation (110/752), followed by psbA-trnH (74/535), based on sequence length and number of variable sites. psbA-trnH had the highest percentage of parsimony (parsim)-informative sites (70/535), followed by matK (81/752). It could be inferred that psbA-trnH and matK are the best regions for use as DNA barcodes for phylogenetic reconstruction, whereas rbcL was the least suitable marker for Dioscorea.

The efficiency of PCR amplification is one of the important indicators for evaluating the applicability of DNA barcodes. The amplification efficiency of matK using universal primers was 70.23% (the lowest efficiency found), while the amplification rate of rbcL and psbA-trnH was 83.33% and 74.07%, respectively. 81.4% amplification efficiency was achieved with another matK universal primer set 3F_Kim/1R_KIM. Samples that failed to amplify with universal primers were successfully amplified using specific primer sets designed by ourselves based on the Dioscorea sequences available in Genbank. Samples that amplified successfully using universal primers were randomly picked to be amplified by the self-designed primers to verify their scope of use; amplification success rates were all found to be 100%.

Intra-specific variation and inter-specific divergence

The maximum intra-specific divergence and the minimum inter-specific divergence of the three candidate barcodes and their combinations, matK+rbcL, matK+psbA-trnH, rbcL+psbA-trnH, matK+rbcL+psbA-trnH were estimated using six metrics [36]. The non-coding region (psbA-trnH) showed greater intra- and interspecific divergence than the coding regions (matK and rbcL; Table 2). PsbA-trnH had the highest interspecific divergence, followed by that of rbcL+psbA-trnH and matK+psbA-trnH, and the inter-specific divergence of rbcL was the lowest (Table 2). matK had the maximum intra-specific variation while rbcL had the minimum. Furthermore, all seven barcodes showed higher genetic variability between than within species.

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Table 2. Measures of inter- and intra-specific divergence and identification efficiency of the potential barcodes and combined barcodes.

https://doi.org/10.1371/journal.pone.0032057.t002

Statistical comparison of divergence

It can be seen from the Wilcoxon signed rank tests that the inter-specific divergence of matK was higher than that of rbcL, and rbcL exhibited a higher inter-specific divergence than did psbA-trnH (Table 3). P-values were less than zero showed that the differences were highly significant. These statistically analysed data suggest that matK would serve as an ideal candidate for identifying Dioscorea.

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Table 3. Wilcoxon signed rank test of the inter-specific divergences among the three loci.

https://doi.org/10.1371/journal.pone.0032057.t003

DNA barcoding gap assessment

We examined the distributions of intra-specific versus inter-specific divergence in the seven barcodes at a scale of 0.001 distance units. Although no distinct barcoding gaps as typical of CO1 were found in the distributions of all the loci, it does suggest a clearly defined range, where the intraspecific variation is considerably lower than the interspecific divergence (Fig. 1). And among them, matK revealed a relatively well separated distribution. For matK, the intra-specific distances mainly distributed in section 0.000–0.010, while the inter-specific distances mainly distributed in section 0.050–0.060. And for matK congeneric species with a genetic distance of zero accounted for only 4.914% of the total samples (8.209% for rbcL and 10.57% for psbA-trnH). So it's proposed that matK could be used to discriminate most species in this study. The loci combination matK+rbcL+psbA-trnH could also be used for species identification in Dioscorea with the lowest ratio of samples (0.486%) having an inter-specific distance of zero. For matK+rbcL+psbA-trnH, the intra-specific distances mainly distributed in section 0.000–0.010, and the inter-specific distances mainly distributed in section 0.060–0.070. Furthermore, it was confirmed that the interspecific divergences of all the seven loci was significantly higher than that of the corresponding intraspecific variations by Wilcoxon two-sample tests. And the most significant difference was observed in matK for single locus and matK+rbcL+psbA-trnH for loci combination (Table S1).

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Figure 1. Relative distribution of inter-specific divergence between congenic species and intra-specific variation.

(A) matK. (B) rbcL. (C) psbA-trnH. (D) matK+rbcL. (E) matK+psbA-trnH. (F) rbcL+psbA-trnH. (G) matK+rbcL+psbA-trnH.

https://doi.org/10.1371/journal.pone.0032057.g001

Applicability for species discrimination

BLAST1 searches and the nearest genetic distance were used to test the applicability of the three loci and four combinations for species identification (Table 2). Our results revealed that matK possessed the highest identification efficiency of the three loci. In contrast, the rates of successful species identification using psbA-trnH were the lowest. In addition, the success rates of combined barcodes were higher than those of the single locus using both methods. matK+rbcL+psbA-trnH had the highest authentication capability, which correctly identified 53.49% of the species by both the BLAST1 search and the nearest genetic distance methods.

Discussion

Assessment of the applicability of the three candidate barcodes

An ideal DNA barcode must have high PCR amplification efficiency, whilst containing enough variability to be used for species identification and adequate conserved regions for the design of universal primers [37]. In this study, it was found that the chloroplast matK gene was a promising candidate for authenticating Dioscorea species based on amplification efficiency, barcoding gaps, and success rate of identification. An amplification efficiency of 100% was obtained using specific primers and the identification efficiency was highest when using the three loci (23.26%). The chloroplast rbcL gene did not have enough inter-specific divergence, although its amplification efficiency was not low. The success rate of identification of psbA-trnH was too low to be useful for this purpose.

rbcL and psbA-trnH had individual advantages despite their poor capability for authentication of Dioscorea species. rbcL had high amplification efficiency, but the overlap of intra-specific and inter-specific divergence was too substantial to be of use for discrimination and the identification rate was only 9.30%. This situation arises because the rbcL gene does not have sufficient variation at the species level to be use as a DNA barcode [31], [38][41]. Approximately 10,300 rbcL sequences in the GenBank were compared using the distance based method. It was found that rbcL was not capable of discriminating between all species, but was able to distinguish some taxa at the genus and species levels [42].

The amplification efficiency of psbA-trnH in Dioscorea was moderate and its identification accuracy was only 11.63%, therefore it is not a suitable candidate as a DNA barcode for Dioscorea, as it is for other species [43], [44]. In addition, the presence of a poly-A/T in this region often reduces the success rate of DNA sequencing.

Insertions or deletions appear to be a common characteristic of this genetic region, even in closely related species [45][50]. The variable lengths of this region make sequence alignment difficult. Large insertion or deletion was also found in different populations of Dioscorea. For example, Dioscorea zingiberensis C.H. Wright collected from Yichang, Madao and Enshi in China had a 234-bp insertion segment at 183 bp compared to other populations. The generation mechanism of indels in psbA-trnH remains ambiguous, and one hypothesis was raised by Aldrich et al., [45] that the deletion of insert often occurred between imperfect AT-rich repeats flanking the insert, which was also supported by the detection of imperfect AT-rich repeats flanking the indel in Dioscorea zingiberensis. In contrast with the problems of indels for sequence alignment, indels will ultimately enrich the information needed for species discrimination [30]. Such indel indicates a divergent trend of two groups separated by Yangtze River in Dioscorea zingiberensis [51]. The insertions were only detected in the three populations of north group, while the others exhibited deletion.

The combinations of psbK-psbI+atpF-atpH, matK+atpF-atpH+psbK-psbI and matK+atpF-atpH+psbA-trnH were used to discriminate 101 individual plants belonging to 31 species and 18 families, and achieved high success rate [40]. When combinations of two or three loci were used in Dioscorea, much higher identification efficiency was achieved than any of single locus.

Application of matK in discrimination of Dioscorea species

matK is a recommended DNA barcode candidate gene because of its high evolution rate [23], [52], [53]. Lahaye and colleagues amplified matK successfully in 398 samples using primers 390F/1326R in 2008 and more than 90% species could be identified. However, these results have been reviewed unfavorably by some researchers. Kress and colleagues [32] doubted whether amplification efficiency could remain high in plants from other families, as 96% of samples in Lahaye's study were orchids. The criticism of matK for use as a DNA barcode is its poor performance of primer universality [52], [54] so different primers are needed to amplify samples from different taxa. Kress and Erickson [31] achieved a 39.3% amplification rate for 96 species belonging to 48 genera, although 10 pairs of primers were used. Fazekas and colleagues [39] amplified 251 individual plants from 32 genera and 92 species, but their success rate was only 87.6%.

The amplification efficiency of Dioscorea were 70.23% and 81.40% with primers intF/intR and 3F_Kim/1R_KIM respectively and a 100% success rate was achieved using our in-house designed specific primers. For an ideal barcode a distinct gap with no overlap is essential [23], [36]. But in this study, no distinct barcoding gap was found even though intra-specific divergence and interspecific divergence was mainly non-overlapping (Fig. 1). Nevertheless, based on the histogram of DNA barcoding gap and species identification, matK was proven to be better than the other loci in our study.

ITS and ITS2 have been also proposed to be the most promising universal DNA barcode in plants [55], [56], unfortunately, because of the low sequencing success of the ITS and ITS2 region brought by serious endophyte interference in our study, this region was not included for further analysis.

In conclusion, our study shows that the matK is a strong, although not perfect, candidate for Dioscorea identification. It remains necessary to carry out further research on other more variable DNA barcodes such as psbK-psbI and atpF-atpH in species identification of this genus.

Materials and Methods

Plant materials

Plant samples were collected from different locations in China and identified by one of our authors, Prof. Yueyu Hang. In total, 148 individual samples belonging to 38 species, seven variants and one subspecies, representing majority species (46/61) and all six sections distributed in China of this genus, were collected for further analysis. Fresh leaves were dried in silica gel at the time of collection. Voucher specimens were deposited in the herbarium at the Kunming Institute of Botany, Chinese Academy of Sciences (KIM) (Table S2).

DNA extraction, amplification, sequencing

Genomic DNA was extracted following a cetyl trimethylammonium bromide (CTAB) protocol modified from Paterson et al. [57]. The universal primers intF and intR (RBG Edinburgh recommended), 1F and 724R [58], and psbAF and trnH2 [59] were used in the amplification of matK, rbcL and psbA-trnH regions of the cpDNA respectively. As to these samples failed to amplify using universal primers, specific primers were designed with the aid of OLIGO primer design software (Molecular Biology Insights, Inc., Cascade, Colorado, USA), based on genus Dioscorea sequences deposited in the GenBank database. For example the matK sequence of D. alata L. (AB040208), the rbcL sequence of D. alata L. (AY667098) and the psbA-trnH region of D. elephantipes (L'Her.) Engl. (EF380353.1) were used. In addition, the universal primer set 3F_Kim and 1R_KIM currently recommended by CBOL (http://barcoding.si.edu) was also adopted to evaluate the efficiency of PCR amplification in a sample pool composed of one randomly selected sample from all species. Detailed sequences of all the primers and reaction conditions are listed in Table S3.

Polymerase chain reaction (PCR) amplification of the three candidate barcodes was carried out using the following program: a premelt of 3 min at 94°C, followed by 35 cycles of 45 s denaturation at 94°C, 30 s annealing reaction at 53–58°C, and finally a 1.5 min 30 s extension at 72°C. Each 20-µl reaction mixture contained 30 ng of genomic DNA template, 2.5 mmol/L MgCl2, 1× Mg-free DNA polymerase buffer, 0.12 mmol/L dNTPs, 0.3 µmol/L each primer, 1 U Taq DNA polymerase. PCR products were examined electrophorectically using 0.8–1.2% agarose gels. Purification and bidirectional sequencing were completed by Beijing Genomics Institute (BGI) using the amplification primers.

Sequence alignment and data analysis

Sequences were aligned and adjusted manually using Sequencer v.4.5 software (GeneCodes, Ann Arbor, MI, USA). The nucleotide sequence data of the three regions were deposited in the GenBank database (Table S2). All genetic distances were calculated using MEGA (4.0 Version) software.

Average intra-specific distance, mean theta and coalescent depth were calculated to determine intra-specific variation [36], [55], and average interspecific distance, theta prime and the minimum interspecific distance were calculated to determine interspecific divergence [36], [55], [60]. Wilcoxon signed-rank tests were performed as previously described [23], [31]. The distribution of intra-specific versus interspecific variability was evaluated by assessment of the presence of DNA barcoding gaps [31], [36]. Two methods of species identification, including BLAST1 protein similarity search and the nearest distance method, were carried out as described previously [61]. BLAST1 searches were conducted on a local reference library constructed for each region. The barcode sequence of each species was queried against the local library with the “blastn” command. The identity of a sample was based on the best hit and the E-value for the match must be lower than the cutoff value. In comparison, for the nerest genetic distance method, the identity of a sample was determined based on the subject sequence which has the smallest genetic distance and the distance must be less than a distance threshold. The traffic light approach was used to identify the combination of markers [62].The combination would have identification power as long as the sequences could be identified by any of the markers in combination, while the combination would be incapable of identifying sequences if none of the markers in combination could identified sequences successfully.

Supporting Information

Table S1.

Wilcoxon two-sample tests for distribution of intra- vs. inter-specific divergences.

https://doi.org/10.1371/journal.pone.0032057.s001

(DOC)

Table S2.

Samples for testing potential barcodes and accession numbers in GenBank.

https://doi.org/10.1371/journal.pone.0032057.s002

(DOC)

Table S3.

Primers and reaction conditions used in the study.

https://doi.org/10.1371/journal.pone.0032057.s003

(DOC)

Acknowledgments

We are grateful to H. Yao (Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, P. R. China) for computational assistance and discussions of this manuscript.

Author Contributions

Conceived and designed the experiments: YYH. Performed the experiments: XQS JLG BP MMB. Analyzed the data: XQS YJZ YYH. Contributed reagents/materials/analysis tools: XQS YJZ. Wrote the paper: XQS YYH.

References

  1. 1. Coursey DG (1967) Yams: an account of the nature, origins, cultivation, and utilization of the useful members of Dioscoraceae. London: Longmans, Green and Co. Ltd. 230 p.DG Coursey1967Yams: an account of the nature, origins, cultivation, and utilization of the useful members of DioscoraceaeLondonLongmans, Green and Co. Ltd230
  2. 2. Fujii K, Matsukawa T (1936) Saponins and sterols. 8. Saponin of Dioscorea tokoro Makino. J pharm Soc Japan 56: 408–414.K. FujiiT. Matsukawa1936Saponins and sterols. 8. Saponin of Dioscorea tokoro Makino.J pharm Soc Japan56408414
  3. 3. Correll DG, Schubert BG, Gentry HS, Hawley WO (1955) The search for plant precursors of cortisone. Econ Bot 9: 307–375.DG CorrellBG SchubertHS GentryWO Hawley1955The search for plant precursors of cortisone.Econ Bot9307375
  4. 4. Applezweig N (1962) Steroid drugs. New York: McGraw Hill. 32 p.N. Applezweig1962Steroid drugsNew YorkMcGraw Hill32
  5. 5. Miège J, Lyonga SN (1982) Yams-Ignames. Oxford: Clarendon Press. pp. 243–249.J. MiègeSN Lyonga1982Yams-IgnamesOxfordClarendon Press243249
  6. 6. Okonkwo SNC (1985) The botany of the yam plant and its exploitation in enhanced productivity of the crop. In: Osuji GO, editor. Advances in Yam Research. Nigeria: Biochem Soc Nigeria/ASUTECH. pp. 3–25.SNC Okonkwo1985The botany of the yam plant and its exploitation in enhanced productivity of the crop.GO OsujiAdvances in Yam ResearchNigeriaBiochem Soc Nigeria/ASUTECH325
  7. 7. Lawton JRS, Lawton JR (1967) The morphology of the dormant embryo and young seedling of five species of Dioscorea in Nigeria. Proc Linn Soc Lond 178: 153–159.JRS LawtonJR Lawton1967The morphology of the dormant embryo and young seedling of five species of Dioscorea in Nigeria.Proc Linn Soc Lond178153159
  8. 8. Degras L (1993) The Yam: A Tropical Root Crop. London: The Macmillan Press Ltd. 233 p.L. Degras1993The Yam: A Tropical Root CropLondonThe Macmillan Press Ltd233
  9. 9. Smith BW (1937) Notes on the cytology and distribution of the Dioscoreaceae. Bull Torr Bot Club 64: 189–197.BW Smith1937Notes on the cytology and distribution of the Dioscoreaceae.Bull Torr Bot Club64189197
  10. 10. Ramachandran K (1968) Cytological studies in Dioscoreaceae. Cytologia 33: 401–410.K. Ramachandran1968Cytological studies in Dioscoreaceae.Cytologia33401410
  11. 11. Dahlgren G (1989) An undated angiosperm classification. Botanical Journal of the Linnean Society 100: 197–203.G. Dahlgren1989An undated angiosperm classification.Botanical Journal of the Linnean Society100197203
  12. 12. Zhang MZ, Wu ZJ, Qin HZ, Ding ZJ (1982) Comparative anatomy of Chinese Dioscorea and its meaning in sectional divisions. Nanjing: Jiangsu Science and Technology Press. pp. 1–8.MZ ZhangZJ WuHZ QinZJ Ding1982Comparative anatomy of Chinese Dioscorea and its meaning in sectional divisionsNanjingJiangsu Science and Technology Press18
  13. 13. Su P (1987) Pollen morphology of Dioscorea in China. Acta Phytotaxonomica Sinica 25(5): 357–365.P. Su1987Pollen morphology of Dioscorea in China.Acta Phytotaxonomica Sinica255357365
  14. 14. Qin HZ, Zhang MZ, Lin PP, Ding ZZ, Dou FP (1985) A Cytotaxonomic Study on Chinese Dioscorea L.—The chromosome numbers and their relation to the origin and evolution of the genus. Acta Phytotaxonomica Sinica 23(1): 11–18.HZ QinMZ ZhangPP LinZZ DingFP Dou1985A Cytotaxonomic Study on Chinese Dioscorea L.—The chromosome numbers and their relation to the origin and evolution of the genus.Acta Phytotaxonomica Sinica2311118
  15. 15. Schols P, Furness CA, Wilkin P, Smets E, Cielen V, et al. (2003) Pollen morphology of Dioscorea (Dioscoreaceae) and its relation to systematics. Botanical Journal of the Linnean Society 143: 375–390.P. ScholsCA FurnessP. WilkinE. SmetsV. Cielen2003Pollen morphology of Dioscorea (Dioscoreaceae) and its relation to systematics.Botanical Journal of the Linnean Society143375390
  16. 16. Schols P, Wilkin P, Furness CA, Huysmans S, Smets E (2005) Pollen evolution in Yams (Dioscorea: Dioscoreaceae). Systematic botany 30: 750–758.P. ScholsP. WilkinCA FurnessS. HuysmansE. Smets2005Pollen evolution in Yams (Dioscorea: Dioscoreaceae).Systematic botany30750758
  17. 17. Kawabe A, Miyashita NT, Terauchi R (1997) Phylogenetic relationship among the section Stenophora in the genus Dioscorea based on the analysis of nucleotide sequence variation in the phosphoglucose isomerase (Pgi) locus. Genes and Genetic Systems 72: 253–262.A. KawabeNT MiyashitaR. Terauchi1997Phylogenetic relationship among the section Stenophora in the genus Dioscorea based on the analysis of nucleotide sequence variation in the phosphoglucose isomerase (Pgi) locus.Genes and Genetic Systems72253262
  18. 18. Wilkin P, Schols P, Chase MW, Chayamarit K, Furness CA, et al. (2005) A plastid gene phylogeny of the yam genus, Dioscorea: roots, fruits and Madagascar. Systematic Botany 30: 736–749.P. WilkinP. ScholsMW ChaseK. ChayamaritCA Furness2005A plastid gene phylogeny of the yam genus, Dioscorea: roots, fruits and Madagascar.Systematic Botany30736749
  19. 19. Gao X, Zhu YP, Wu BC, Zhao YM, Chen JQ, et al. (2008) Phylogeny of Dioscorea sect. Stenophora based on chloroplast matK, rbcL and trnL-F sequences. Journal of Systematics and Evolution 46(3): 315–321.X. GaoYP ZhuBC WuYM ZhaoJQ Chen2008Phylogeny of Dioscorea sect. Stenophora based on chloroplast matK, rbcL and trnL-F sequences.Journal of Systematics and Evolution463315321
  20. 20. Schindel DE, Miller SE (2005) DNA barcoding a useful tool for taxonomists. Nature 435: 17.DE SchindelSE Miller2005DNA barcoding a useful tool for taxonomists.Nature43517
  21. 21. Savolainen V, Cowan RS, Vogler AP, Roderick GK, Lane R (2005) Towards writing the encyclopedia of life: an introduction to DNA barcoding. Philos Trans R Soc Lond B: Biol Sci 360: 1811–1850.V. SavolainenRS CowanAP VoglerGK RoderickR. Lane2005Towards writing the encyclopedia of life: an introduction to DNA barcoding.Philos Trans R Soc Lond B: Biol Sci36018111850
  22. 22. Marshall E (2005) Taxonomy. Will DNA bar codes breathe life into classification? Science 307(5712): 1037.E. Marshall2005Taxonomy. Will DNA bar codes breathe life into classification?Science30757121037
  23. 23. Lahaye R, van der Bank M, Bogarin D, Warner J, Pupulin F, et al. (2008) DNA barcoding the floras of biodiversity hotspots. Proc Natl Acad Sci U S A 105: 2923–2928.R. LahayeM. van der BankD. BogarinJ. WarnerF. Pupulin2008DNA barcoding the floras of biodiversity hotspots.Proc Natl Acad Sci U S A10529232928
  24. 24. Hebert PDN, Stoeckle MY, Zemlak TS, Francis CM (2004) Identification of birds through DNA barcodes. PLoS Biol 2: e312.PDN HebertMY StoeckleTS ZemlakCM Francis2004Identification of birds through DNA barcodes.PLoS Biol2e312
  25. 25. Yoo HS, Eah JY, Kim JS, Kim YJ, Min MS, et al. (2006) DNA barcoding Korean birds. Molecules and Cells 22: 323–327.HS YooJY EahJS KimYJ KimMS Min2006DNA barcoding Korean birds.Molecules and Cells22323327
  26. 26. Ward RD, Zemlak TS, Innes BH, Last PR, Hebert PDN (2005) DNA barcoding Australia's fish species. Philos Trans R Soc Lond B: Biol Sci 360: 1847–1857.RD WardTS ZemlakBH InnesPR LastPDN Hebert2005DNA barcoding Australia's fish species.Philos Trans R Soc Lond B: Biol Sci36018471857
  27. 27. Yancy HF, Zemlak TS, Mason JA, Washington JD, Tenge BJ, et al. (2008) Potential use of DNA barcodes in regulatory science: Applications of the regulatory fish encyclopedia. Journal of Food Protection 71: 210–217.HF YancyTS ZemlakJA MasonJD WashingtonBJ Tenge2008Potential use of DNA barcodes in regulatory science: Applications of the regulatory fish encyclopedia.Journal of Food Protection71210217
  28. 28. Hajibabaei M, Janzen DH, Burns JM, Hallwachs W, Hebert PDN (2006) DNA barcodes distinguish species of tropical Lepidoptera. Proc Natl Acad Sci U S A 103: 968–971.M. HajibabaeiDH JanzenJM BurnsW. HallwachsPDN Hebert2006DNA barcodes distinguish species of tropical Lepidoptera.Proc Natl Acad Sci U S A103968971
  29. 29. Hajibabaei M, Singer GAC, Clare EL, Hebert PDN (2007) Design and applicability of DNA arrays and DNA barcodes in biodiversity monitoring. BMC Biol 5: 24.M. HajibabaeiGAC SingerEL ClarePDN Hebert2007Design and applicability of DNA arrays and DNA barcodes in biodiversity monitoring.BMC Biol524
  30. 30. Kress WJ, Wurdack KJ, Zimmer EA, Weigt LA, Janzen DH (2005) Use of DNA barcodes to identify flowering plants. Proc Natl Acad Sci U S A 102(23): 8369–8374.WJ KressKJ WurdackEA ZimmerLA WeigtDH Janzen2005Use of DNA barcodes to identify flowering plants.Proc Natl Acad Sci U S A1022383698374
  31. 31. Kress WJ, Erickson DL (2007) A two-locus global DNA barcode for land plants: the coding rbcL gene complements the non-coding trnH-psbA spacer region. PloS One 2: e508.WJ KressDL Erickson2007A two-locus global DNA barcode for land plants: the coding rbcL gene complements the non-coding trnH-psbA spacer region.PloS One2e508
  32. 32. Kress WJ, Erickson DL (2008) DNA barcodes: Genes, genomics, and bioinformatics. Proc Natl Acad Sci U S A 105: 2761–2762.WJ KressDL Erickson2008DNA barcodes: Genes, genomics, and bioinformatics.Proc Natl Acad Sci U S A10527612762
  33. 33. Thomas C (2009) Plant barcode soon to become reality. Science 325: 526.C. Thomas2009Plant barcode soon to become reality.Science325526
  34. 34. Burkill IH (1951) Dioscoreaceae. In: Steenis CGGJvan, editor. Flora Malesiana, Series I, Volume 4. Djakarta: Noordhoff-Kolff NV. pp. 293–335.IH Burkill1951Dioscoreaceae.CGGJvan SteenisFlora Malesiana, Series I, Volume 4DjakartaNoordhoff-Kolff NV293335
  35. 35. Wan JR, Ding ZZ, Qin HZ (1994) A phytogeographical study on the family Dioscoreaceae. Acta Botanica Boreale-Occidentalia Sinica 14: 128–135.JR WanZZ DingHZ Qin1994A phytogeographical study on the family Dioscoreaceae.Acta Botanica Boreale-Occidentalia Sinica14128135
  36. 36. Meyer CP, Paulay G (2005) DNA barcoding: Error rates based on comprehensive sampling. PLoS Biol 3(12): e422.CP MeyerG. Paulay2005DNA barcoding: Error rates based on comprehensive sampling.PLoS Biol312e422
  37. 37. CBOL Plant Working Group (2009) A DNA barcode for land plants. Proc Natl Acad Sci U S A 106: 12794–12797.CBOL Plant Working Group2009A DNA barcode for land plants.Proc Natl Acad Sci U S A1061279412797
  38. 38. Sass C, Little DP, Stevenson DW, Specht CD (2007) DNA barcoding in the cycadales: testing the potential of proposed barcoding markers for species identification of cycads. PloS One 2: e1154.C. SassDP LittleDW StevensonCD Specht2007DNA barcoding in the cycadales: testing the potential of proposed barcoding markers for species identification of cycads.PloS One2e1154
  39. 39. Fazekas AJ, Burgess KS, Kesanakurti PR, Graham SW, Newmaster SG, et al. (2008) Multiple multilocus DNA barcodes from the plastid genome discriminate plant species equally well. PloS One 3: e2802.AJ FazekasKS BurgessPR KesanakurtiSW GrahamSG Newmaster2008Multiple multilocus DNA barcodes from the plastid genome discriminate plant species equally well.PloS One3e2802
  40. 40. Lahaye R, Savolainen V, Duthoit S, Maurin O, Bank Mvd (2008) A test of psbK-psbI and atpF-atpH as potential plant DNA barcodes using the flora of the Kruger National Park as a model system (South Africa). R. LahayeV. SavolainenS. DuthoitO. MaurinMvd Bank2008A test of psbK-psbI and atpF-atpH as potential plant DNA barcodes using the flora of the Kruger National Park as a model system (South Africa).Nature Precedings Available: http://hdl.handle.net/10101/npre.2008.1896.1. Accessed 2008. Nature Precedings Available: http://hdl.handle.net/10101/npre.2008.1896.1. Accessed 2008.
  41. 41. Newmaster SG, Fazekas AJ, Steeves RAD, Janovec J (2008) Testing candidate plant barcode regions in the Myristicaceae. Molecular Ecology Resources 8: 480–490.SG NewmasterAJ FazekasRAD SteevesJ. Janovec2008Testing candidate plant barcode regions in the Myristicaceae.Molecular Ecology Resources8480490
  42. 42. Newmaster SG, Fazekas AJ, Ragupathy S (2006) DNA barcoding in the land plants: evaluation of rbcL in a multigene tiered approach. Canadian Journal of Botany 84: 335–341.SG NewmasterAJ FazekasS. Ragupathy2006DNA barcoding in the land plants: evaluation of rbcL in a multigene tiered approach.Canadian Journal of Botany84335341
  43. 43. Whipple IG, Barkworth ME, Bushman BS (2007) Molecular insights into the taxonomy of Glyceria (Poaceae: Meliceae) in North America. American Journal of Botany 94: 551–557.IG WhippleME BarkworthBS Bushman2007Molecular insights into the taxonomy of Glyceria (Poaceae: Meliceae) in North America.American Journal of Botany94551557
  44. 44. Logacheva MD, Valiejo-Roman CM, Pimenov MG (2008) ITS phylogeny of West Asian Heracleum species and related taxa of Umbelliferae-Tordylieae W.D.J. Koch, with notes on evolution of their psbA-trnH sequences. Plant Systematics and Evolution 270: 139–157.MD LogachevaCM Valiejo-RomanMG Pimenov2008ITS phylogeny of West Asian Heracleum species and related taxa of Umbelliferae-Tordylieae W.D.J. Koch, with notes on evolution of their psbA-trnH sequences.Plant Systematics and Evolution270139157
  45. 45. Aldrich JBW, Cherney E, Merlin LC (1988) The role of insertions/deletions in the evolution of the intergenic region between psbA and trnH in the chloroplast genome. Current Genetics 14: 137–146.JBW AldrichE. CherneyLC Merlin1988The role of insertions/deletions in the evolution of the intergenic region between psbA and trnH in the chloroplast genome.Current Genetics14137146
  46. 46. Mast AR, Givnish TJ (2002) Historical biogeography and the origin of stomatal distributions in Banksia and Dryandra (Proteaceae) based on their cpDNA phylogeny. American Journal of Botany 89: 1311–1323.AR MastTJ Givnish2002Historical biogeography and the origin of stomatal distributions in Banksia and Dryandra (Proteaceae) based on their cpDNA phylogeny.American Journal of Botany8913111323
  47. 47. Miller JT, Grimes JW, Murphy DJ, Bayer RJ, Ladiges PY (2003) A phylogenetic analysis of the Acacieae and Ingeae (Mimosoideae: Fabaceae) based on trnK, matK, psbA-trnH, and trnL/trnF sequence data. Systematic Botany 28: 558–566.JT MillerJW GrimesDJ MurphyRJ BayerPY Ladiges2003A phylogenetic analysis of the Acacieae and Ingeae (Mimosoideae: Fabaceae) based on trnK, matK, psbA-trnH, and trnL/trnF sequence data.Systematic Botany28558566
  48. 48. Kyndt T, Droogenbroeck BV, Romeijn-Peeters E, Romero-Motochi JP, Scheldeman X, et al. (2005) Molecular phylogeny and evolution of Caricaceae based on rDNA internal transcribed spacers and chloroplast sequence data. Molecular Phylogenetics and Evolution 37: 442–459.T. KyndtBV DroogenbroeckE. Romeijn-PeetersJP Romero-MotochiX. Scheldeman2005Molecular phylogeny and evolution of Caricaceae based on rDNA internal transcribed spacers and chloroplast sequence data.Molecular Phylogenetics and Evolution37442459
  49. 49. Shaw J, Lickey EB, Beck JT, Farmer SB, Liu W, et al. (2005) The tortoise and the hare II: relative utility of 21 noncoding chloroplast DNA sequences for phylogenetic analysis. American Journal of Botany 92: 142–166.J. ShawEB LickeyJT BeckSB FarmerW. Liu2005The tortoise and the hare II: relative utility of 21 noncoding chloroplast DNA sequences for phylogenetic analysis.American Journal of Botany92142166
  50. 50. Winkworth RC, Donoghue MJ (2005) Viburnum phylogeny based on combined molecular data: implications for taxonomy and biogeography. American Journal of Botany 92: 653–666.RC WinkworthMJ Donoghue2005Viburnum phylogeny based on combined molecular data: implications for taxonomy and biogeography.American Journal of Botany92653666
  51. 51. Huang CH, Hang YY, Zhou YF, Shi DR, Guo KY (2003) Population genetic structure of Dioscorea zingiberensis in China. Acta Botanica Yunnanica 25(6): 641–647.CH HuangYY HangYF ZhouDR ShiKY Guo2003Population genetic structure of Dioscorea zingiberensis in China.Acta Botanica Yunnanica256641647
  52. 52. Chase MW, Cowan RS, Hollingsworth PM, van den Berg C, Madrinan S, et al. (2007) A proposal for a standardized protocol to barcode all land plants. Taxon 56: 295–299.MW ChaseRS CowanPM HollingsworthC. van den BergS. Madrinan2007A proposal for a standardized protocol to barcode all land plants.Taxon56295299
  53. 53. Pennisi E (2007) Taxonomy: Wanted a barcode for plants. Science 318: 190–191.E. Pennisi2007Taxonomy: Wanted a barcode for plants.Science318190191
  54. 54. Hollingsworth PM (2008) DNA barcoding plants in biodiversity hot spots: Progress and outstanding questions. Heredity 101: 1–2.PM Hollingsworth2008DNA barcoding plants in biodiversity hot spots: Progress and outstanding questions.Heredity10112
  55. 55. Chen SL, Yao H, Han JP, Liu C, Song JY, et al. (2010) Validation of the ITS2 region as a novel DNA barcode for identifying medicinal plant species. PLoS ONE 5: e8613.SL ChenH. YaoJP HanC. LiuJY Song2010Validation of the ITS2 region as a novel DNA barcode for identifying medicinal plant species.PLoS ONE5e8613
  56. 56. Li DZ, Gao LM, Li HT, Wang H, et al. China Plant BOL Group (2011) Comparative analysis of a large dataset indicates that internal transcribed spacer (ITS) should be incorporated into the core barcode for seed plants. Proc Natl Acad Sci U S A 108(49): 19641–19646.DZ LiLM GaoHT LiH. WangChina Plant BOL Group2011Comparative analysis of a large dataset indicates that internal transcribed spacer (ITS) should be incorporated into the core barcode for seed plants.Proc Natl Acad Sci U S A108491964119646
  57. 57. Paterson AH, Brubaber CL, Wendel JF (1993) A rapid method for extraction of cotton (Gossypium spp) genomic DNA suitable for RFLP of PCR analysis. Plant Mol Bio Rep 11(3): 122–127.AH PatersonCL BrubaberJF Wendel1993A rapid method for extraction of cotton (Gossypium spp) genomic DNA suitable for RFLP of PCR analysis.Plant Mol Bio Rep113122127
  58. 58. Fay MF, Swensen SM, Chase MW (1997) Taxonomic affinities of Medusagyne oppositifolia (Medusagynaceae). Kew Bulletin 52: 111–120.MF FaySM SwensenMW Chase1997Taxonomic affinities of Medusagyne oppositifolia (Medusagynaceae).Kew Bulletin52111120
  59. 59. Tate JA, Simpson BB (2003) Paraphyly of Tarasa (Malvaceae) and diverse origins of the polyploid species. Systematic Botany 28: 723–737.JA TateBB Simpson2003Paraphyly of Tarasa (Malvaceae) and diverse origins of the polyploid species.Systematic Botany28723737
  60. 60. Meier R, Zhang GY, Ali F (2008) The use of mean instead of smallest interspecific distances exaggerates the size of the “Barcoding Gap” and leads to misidentification. Syst Biol 57(5): 809–813.R. MeierGY ZhangF. Ali2008The use of mean instead of smallest interspecific distances exaggerates the size of the “Barcoding Gap” and leads to misidentification.Syst Biol575809813
  61. 61. Ross HA, Murugan S, Li WL (2008) Testing the reliability of genetic methods of species identification via simulation. Syst Biol 57: 216–230.HA RossS. MuruganWL Li2008Testing the reliability of genetic methods of species identification via simulation.Syst Biol57216230
  62. 62. Chase MW, Salamin N, Wilkinson M, Dunwell JM, Kesanakurthi RP, et al. (2005) Land plants and DNA barcodes: short-term and longterm goals. Phil Trans R Soc B 360: 1889–1895.MW ChaseN. SalaminM. WilkinsonJM DunwellRP Kesanakurthi2005Land plants and DNA barcodes: short-term and longterm goals.Phil Trans R Soc B36018891895