|Year : 2020 | Volume
| Issue : 70 | Page : 290-299
DNA barcoding of endemic and endangered orchids of India: A molecular method of species identification
Deepti Srivastava, K Manjunath
Department of Microbiology and Biotechnology, Bangalore University, Bengaluru, Karnataka, India
|Date of Submission||28-Dec-2019|
|Date of Decision||28-Jan-2020|
|Date of Acceptance||21-Apr-2020|
|Date of Web Publication||28-Aug-2020|
Department of Microbiology and Biotechnology, Bangalore University, Bengaluru - 560 056, Karnataka
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Orchids are economically important, particularly in horticulture, floristry, pharmaceutical, and fragrance industries. India is a paradise for 1256 orchids, of which 31% (388 species) are endemic. Although Indian orchids are known in floristry, there is still a lot of room to use their bioactive compounds to promote their commercialization. Easy and accurate identification is first step towards conservation and commercial cultivation of endemic and endangered orchid species. This requirement can be accomplished using DNA barcoding technique. Materials and Methods: A total of 62 samples belonging to 35 species, 7 genera were collected for DNA barcoding studies. Evolutionary divergences and barcoding gap were calculated using MEGA-X software to screen the most suitable barcode region among the ITS, matK, rbcL , and trnH-psbA loci. BLAST analysis was used to identify barcoding locus presenting maximum species resolution. Phylogenetic analyses were performed to test harmony between barcoding and taxonomy. Results: We have generated 133 barcoding sequences, out of which, 46 sequences were found unique and new to GenBank database. Evolutionary divergence analysis showed the best result for ITS , where intra-specific and inter-specific divergence ranged between 0.0000–0.0300 and 0.0322–0.3765 correspondingly. It indicated clear barcoding gap, which was sufficient to robustly infer identities for taxa. BLAST-based evaluation concluded that largest number of barcode sequences (94.64%) could be identified using ITS locus followed by rbcL (78.69%) and matK (51.61%). In addition, the optimal phylogenetic tree was established using the ITS locus sequences, which complemented the orchid taxonomy. Conclusion: This study recommends ITS as best single locus barcoding region for identifying the orchids of India.
Keywords: Internal transcribed spacer, interspecific divergence, maturaseK, phylogenetic analysis, ribulose bisphosphate carboxylase large chain
|How to cite this article:|
Srivastava D, Manjunath K. DNA barcoding of endemic and endangered orchids of India: A molecular method of species identification. Phcog Mag 2020;16:290-9
|How to cite this URL:|
Srivastava D, Manjunath K. DNA barcoding of endemic and endangered orchids of India: A molecular method of species identification. Phcog Mag [serial online] 2020 [cited 2020 Sep 24];16:290-9. Available from: http://www.phcog.com/text.asp?2020/16/70/290/293786
- Orchids have been evoked worldwide eminence in recent years, owing to its wide range of long lasting flowers and medicinal properties. India is enriched with various species of orchids which require detail scientific exploration. DNA barcoding and molecular phylogenetic techniques allowed rapid and accurate species identification which is being used extensively for species identification and characterization of flora and fauna. ITS, matK, rbcL , and trnH-psbA , are the common genomic regions used for DNA barcoding of plants. Our study considered different endangered and endemic species of Aerides, Bulbophyllum, Coelogyne, Cottonia, Dendrobium, Paphilopedium , and Trias genera consisting of 62 specific samples from 35 orchid species of 7 genera. Our study based on distance, BLAST and tree-building methods suggested that ITS is the best barcoding region to be considered as the barcode for these samples in comparison to the other regions studied. Interestingly, we were able to identify 20, 12, and 14 sequences of ITS, matK , and rbcL respectively, which were unique and new for GenBank database; and taxonomic lineages of 10 endemic Western Ghats species, which were unrecognized to NCBI database.
Abbreviations used: accD : Acetyl-coenzyme A carboxylase carboxyl transferase subunit beta gene; atpF-atpH : ATP synthase subunit b-delta gene; EtBr: Ethidium bromide; matK : Maturase K gene; ndhJ : NAD(P)H-quinone oxidoreductase gene; nrDNA: Nuclear ribosomal DNA; rbcL : Ribulose bisphosphate carboxylase large subunit gene; rpoB : Beta subunit of RNA polymerase gene; rpoC1 : DNA-directed RNA polymerase subunit beta gene.
| Introduction|| |
Orchids have wide varieties and are spread all over the world. They are well-known for their beautiful, long-lasting flowers, and traditional medicinal values., A recent survey of orchids found that species concentration is highest in northeastern India, and endemism of orchids is largest in Western Ghats. Although orchids are rich in many useful bioactive compounds and can be important members of commercial herbal medicines, cosmetics, flavors, and fragrances market, they are always been ignorant by traders, researchers, and ecologist because of the lack of easy identification methods. Moreover, deforestation as well as illegal over-harvesting of orchids for their horticultural and floricultural values caused serious threat to orchid survival conditions such as specific pollination methods, climatic conditions, recent speciation, and improper distribution of symbionts. Correct identification of endangered, critically endangered and vulnerable species is necessary for planning and management of in situ and ex situ conservation methods in India which may lead to commercialization of orchids. This requirement has led to the development of a method for quick and accurate identification of species using DNA barcode technology. This technique relies on (i) developing on-line digital barcode library from the reliable sample vouchers of taxonomically identified species and (ii) comparing unknown samples of delimiting species to the library for their identification and molecular characterization., This method is also effective during scarcity of plant DNA samples, where minute amount of dry, damaged, immature, or processed sample is enough to provide appreciable outcome. Information gathered from DNA barcodes can be used beyond taxonomic studies and will have far-reaching implications across many fields of biology, including herbal drug producers, flavor and fragrance industry, ecology, evolutionary biology, conservation biology, and non-professional users such as customs officers and forensic specialists to identify morphologically similar species and their herbal products. Hence, the implementation of DNA barcoding methods for discrimination and identification is a need of hour to accelerate conservation and commercialization of endemic and endangered orchids of India.
Ample experiments lead to the identification of specific genes and genomic regions that could serve as the standard DNA barcode for plants, animals, or insects. Consortium for the Barcoding of Life working group proposed plastid genes: Partial ribulose bisphosphate carboxylase large chain (rbcL ) and maturase K (matK ) as universal barcode for land plants. In addition to these markers, conserved plastid genes: accD,ndhJ,rpoB,rpoC1, and ycf5 ; plastid intergenic spacer regions: trnH-psbA,atpF-atpHandpsbK-psbl ; and nuclear ribosomal internal transcribed spacer regions: ITS (ITS 1+5.8S+ITS 2), ITS1, and ITS2 were also found as promising DNA barcoding regions for the identification of different plant families.,, Although there are 1256 orchids found in India, very few reports are available on barcoding of Indian orchids.,, In the present study, the potential of four candidate barcodes rbcL,matK,psbA-trnH , and ITS for the identification of 35 species belonging to seven orchid genera was analyzed. Subsequently, phylogenetic mapping was conducted to find its harmony with taxonomy.
| Materials and Methods|| |
Sampling of orchids and herbarium preparation
Orchid samples were collected from different geographical regions of India: Agasthyamalai (Tamil Nadu); Gurukula Botanical Sanctuary (Kerala); Mullayanagiri, Kemmannugundi, Medikeri (Karnataka); Kalsubai (Maharashtra); forest region of Assam; forest of Nagaland; and from Botanic Garden of Meise (BGM), Meise, Belgium. GPS locations of collection points in India are shown in [Figure 1]. Belgium samples were originally collected from India and were conserved ex situ in BGM, Belgium. Many individuals of the same species were collected from different locations to find intra-specific distances among geologically far species. Field samples were identified by Dr. K Sashidhar, President of “The Orchid Society of Karnataka” (TOSKAR), based on the reproductive or vegetative characters available at the time of collection.
|Figure 1: Geographical mapping of orchids at hotspots in India. (a) Different colors denote collection sites based on the recorded GPS. (b) Dendrobium jerdonianum at its natural habitat|
Click here to view
Herbarium specimen of orchid samples were prepared and submitted for preservation to the Department of Microbiology and Biotechnology of the Bangalore University, Bengaluru, India. Accessions numbers of remaining six plants were obtained from the BGM, Belgium.
Healthy fresh leaves of all the samples collected from different locations were cut into small pieces and dried in shade for 1 day. All leaf pieces were desiccated in labeled silica gel dark bottles for 7–10 days prior to the DNA isolation. Genomic DNA of field samples was isolated using CTAB methodology. CTAB buffer was modified by adding 2% soluble PVP to remove phenolic compounds from plant leaves. GenElute, Plant Genomic DNA Miniprep Kit (Sigma) was used for rapid isolation of high-quality DNA from dried leaf samples collected from Belgium. The manufacturer's protocol was followed to pursue the DNA isolation. The isolated DNA obtained from any of the method was checked for quality by electrophoresis (0.8% TAE agarose gels containing Ethidium bromide at 7V/cm constant voltage) and visualized by a UV transilluminator. The DNA quantity was also checked using spectrophotometer. DNA samples having 260/280 ratio more than 1.6 were considered for amplification.
Amplification and sequencing of selected loci
Four major barcoding loci for plants–ITS , matK,rbcL , and trnH-psbA were amplified for all the orchids studied using known universal primers listed in [Table 1].
|Table 1: List of amplification criteria and primers used for amplification of the candidate DNA barcodes loci|
Click here to view
Polymerase chain reaction (PCR) amplification of targeted DNA regions was performed using Applied Biosystems GeneAmp PCR machine. PCR conditions and PCR reactions are explained in [Table 1]. All the PCR reagents were acquired from Invitrogen, Thermo Fisher Scientific Corporation and primers were synthesized from Sigma-Aldrich Corporation. PCR products were visualized using 1% agarose gels stained with ethidium bromide (0.5 mg/mL) in a Bio-Rad Gel imaging system. Amplified DNA was purified using GenElute™ PCR Clean-Up Kit. The cleaned PCR products were stored at −20°C and were sequenced thereafter. Sequencing was done using DNA Analyzer: 3730 × l by Applied Biosystems using Sanger method.
Polymerase chain reaction data analysis
Amplification success was computed by taking percentage ratio of amplified products and DNA samples used for PCR, whereas sequencing success rate was calculated by the percentage ratio of the number of high quality sequences and the total number of PCR product used for sequencing. The obtained DNA sequences were aligned using ClustalX 2.1 and gaps were filled based on necessity. These sequences were submitted to GenBank database through Banklt-NCBI-NIH.
Determination of candidate barcode sequences method
The sequences from each candidate loci were aligned using Clustal X2 software. A global multiple sequence alignment method was used for the ITS , rbcL , and matK sequences. Genetic distances were calculated to quantify sequence divergence among the individuals using Kimura two parameter (K2P) models in Molecular Evolutionary Genetics Analysis-version X (MEGA-X), computer software (developed by Pennsylvania State University, Pennsylvania). The pairwise distances were calculated using 1000 bootstrap replication for all the barcodes. Pairwise deletion option was chosen to treat the gaps and missing data. Individual locus wise K2P distance matrix was generated by aligning DNA sequences of particular locus for all the species. Two species were considered as distinct, if their inter-specific distance was more than the maximum intra-specific distance. Individuals of same species were considered different variety if there was intra-specific distance. The differ ence between the greatest intra-specific distance and the smallest inter-specific distance, i.e., “Barcoding Gap” was also determined. Candidate barcode sequence was identified based on the barcoding gap where there was no overlap between the intra- and inter-specific distances.
Percentage identity of our sequences with GenBank nucleotide database was determined using megablast option of BLASTn program (Basic Local Alignment Search Tool for nucleotides). Our sequences were taken as query sequence and BLASTn was run to find similarity with reference databases. The top hit with 100% query coverage and E value-0.00, was compared with query sequences to find percent similarity. Query sequences were claimed as barcoding sequences in two cases (i) when query and best match sequences were conspecific individual, i.e., individuals of same species, (ii) in case query species nucleotide data were not available on NCBI database and query sequence was best matched with congeneric species (other species of the same genus). If identified sequences were found 100% identical to the individual of same species, it intended our barcoding sequences are known to the NCBI database. In case of proximity (98.90%–99.99%) of the generated sequences with individuals of same species available in database, our sequences were considered as new barcodes and total number of individuals showing intra-specific differences was noted manually.
Prior existence of our sequences in the database with 100% identity to other species/genus and lesser similarity with alike species individuals does not allow our sequences to be used as barcodes. These sequences were considered incorrect. Identification was stated ambiguous when query sequence was found common (100% identical) among more than one species of that genus. Barcoding locus differentiating maximum species based on evolutionary distance and showing maximum number of barcoding sequences based on the percentage identity analysis was considered as preferred barcode candidate gene for the accounted orchids.
Phylogenetic trees were constructed implementing discrete character method-Maximum Likelihood (ML) with 100 bootstraps available in MEGA X version. ML method applies complex evolutionary model and is known to be reliable to infer phylogenetic analysis. In ML method-based exercises, Kimura two-parameter (K2P) model were used. Complete deletion option was chosen to treat the gaps and missing data. Barcoding sequences identified using similarity analysis of BLASTn method were used to construct phylogenetic tree. Species identification was considered successful only when all conspecific and congeneric individuals formed a single clade supported by bootstrap P > 50 in the ML tree. Obtained results of the phylogenetic analysis were compared with existing taxonomic classification to confirm complementary character of barcoding and taxonomy.
| Results|| |
Sampling of orchids
A total of 62 samples belonging to 35 different orchid species were collected, out of which, 23 species were endemic to Western Ghats of India and 12 were endemic to Northeast India. Vouchers for 56 specimens were deposited in the Bangalore University herbarium and accession numbers were collected. Accession numbers of 6 vouchers were collected from BGM, Belgium. Species name, voucher number, accessions numbers, geographical distribution, conservation status based on Convention on International Trade in Endangered Species of Wild Fauna and Flora, specific date of collection and place of collection of orchid samples were recorded and represented in [Table 2].
Amplification and sequencing success of barcoding loci
The amplification success of four loci, namely, ITS,matK,rbcL , and trnH-psbA were noted as 97%, 100%, 100%, and 41%, respectively. These outcomes were further condensed to 93%, 100%, 98%, and 25%, respectively, after sequencing of the PCR products using the same primers. As trnH-psbA locus showed very low success rate for amplification and sequencing of orchids, we did not consider that for species resolution and identification studies.
Chromatograms generated by automated DNA sequencers were further interpreted and analyzed to remove the outcome of the improper and heterozygous (double) peaks of sequences. In total, we obtained 178 sequences of ITS,matK , and rbcL loci from the 62 samples, representing 35 species of 7 genera. These sequences accession number are mentioned in [Table 3]. Among 35 species studied, taxonomic lineages of 10 endemic Western Ghats species were noted “unrecognized” to NCBI database. Thus, this study make scientific populace familiar with barcoding sequences of 10 unrecognized species of Western Ghats, India, namely Bulbophyllumacutiflorum,Bulbophyllumfimbriatum,Bulbophyllumfuscopurpureum,Bulbophyllummysorense,Bulbophyllumtremulum,Coelogynemossiae,Coelogyneodoratissima,Dendrobiumpanduratum,Triasstocksii , and Triasbonaccordensis .
|Table 3: Accession number assigned by GenBank for Internal Transcribed Spacer , maturase K, and Ribulose bisphosphate carboxylase large chain sequences of the listed orchid species and voucher numbers|
Click here to view
Determination of candidate barcode sequences
Genetic distance method
The analysis of evolutionary divergence between sequences of all the species using K2P model of distance matrix method showed ITS had the much higher inter-specific divergence (0.0322–0.3765) compared to matK and rbcL (0.0000–0.0802 and 0.0000–0.1294, respectively). The intra-specific divergence was also noted highest for ITS (0.0000–0.0300) followed by rbcL and matK (0.0000–0.0072 and 0.0000–0.0042, respectively). Obvious barcoding gap was found in ITS and the overlap between inter-specific and intra-specific variation was noted in matK and rbcL [Graph 1]. Hence, genetic distance method concluded that sequences generated using ITS locus can be considered as the potent DNA barcode for orchids considered in the present study.
BLAST-based similarity analysis inferred 53, 32, and 48 barcodes for ITS,matK, and rbcL respectively. The maximum number of query sequences (94.64%) could be identified as barcoding sequences using ITS locus followed by rbcL (78.69%) and matK (51.61%). Incorrect identification rate was noted 3.57%, 38.71%, and 16.39% for the barcoding candidate genes ITS,matK , and rbcL, respectively. In this study, 1.76%, 4.91%, and 8.06% sequences of ITS,rbcL, and matK, respectively, were found ambiguous based on megablast analysis of nucleotides. In case of ITS locus, the sequence of D.jerdonianum (DS045) was found incorrect; and A.rosea (DS012) was found ambiguous based on the similarity analysis [Table 4].
|Table 4: Basic local alignment search tool for nucleotides similarity analysis based barcoding efficiency of candidate loci|
Click here to view
As orchid samples were collected from different geographical locations, intra-specific distance was noted among the conspecific individuals. Intra-specific variations were shown by individuals of 72.72% species studied based on ITS. Whereas rbcL,matK barcoding loci-based evaluation could find intra-specific variations in 45.83% and 12.5% conspecific individuals, respectively. The sequences showing intra-specific variations were considered as barcode of said species variety. These variations were ranged between 0.01%–1.01% for all three loci [Supplementary Table S1]. In other case, among congeneric species showing inter-specific variation, percentage similarity of nucleotides ranged between 92.00%–98.00% for ITS , 98.00%–99.50% for matK, and 97.00%–99.50% for rbcL . Hence, BLAST-based similarity analysis found ITS locus is comparatively potent and precise to identify congeneric and conspecific individuals, whereas percentage of ambiguous or incorrect sequences was quite higher for matK and rbcL .
Phylogenetic matrices and species resolution
ML-based tree of ITS showed higher bootstrap values and species of each genus were clustered on different branches and nodes as monophyletic taxon and then clustered with genus of other clades. These could be correlated with orchid classification. Aerides and Cottonia genus, which belong to Aeridenae subtribe were clustered together. Bulbophyllinae and Dendrobiinae subtribe of Dendrobieae tribe were clustered next to each other. Statistically, all the operational taxonomic units were perfectly bifurcated from their respective nodes with a bootstrap P > 50 for most of the subtrees. It confirmed that ITS is having high resolution power for molecular classification of orchids. Samples collected from BGM (DS025, DS035, and DS037) were clustered with individuals of the same species collected from India. C.nervosa individuals made monophyletic group with bootstrap value 89. C.pandurata individuals displayed coalescent stochasticity with branch support value 100 [Figure 2]. Thus, ITS locus-based ML phylogenetic tree can be used to identify unknown samples of studied species for molecular classification and identification.
A low bootstrap value (<50) was shown by ML subtrees of Bulbophyllum,Dendrobium , andCoelogyne constructed using matK locus. Which made this locus unfit for species identification [Figure 3]. Mixed population of Paphilopedium (subfamily-Cypripedioideae ) and Bulbophyllum (subfamily-Epidendroideae ) as well as Aerides (Tribe-Vandeae) and Trias (Tribe-Dendrobieae) was displayed on evolutionary tree of rbcL . Furthermore, lower bootstrap values confirmed that rbcL cannot discriminate and identify species according to the taxonomic classification of orchids [Figure 4]. Thus, in this study, ITS region showed perfect universality and identification of orchids at congeneric and conspecific level using distance, blast, and tree-Building methods.
| Discussion|| |
DNA barcoding has been proposed as a powerful taxonomic tool for species identification. In this study, the core barcodes (matK and rbcL) had better performance in PCR amplification and sequencing when compared with ITS . Deprived success of existing ITS primers and reduced sequencing success of this regionmight be explained by the incomplete concerted evolution of this nuclear multiple-copy region.,,psbA-trnH exhibited a low success rate, whereby 75% samples failed to generate high quality bidirectional sequences might be due to the presence of a poly (T) tail at about 100 bp from the psbA primer. Previous studies found that Nuclear ribosomal DNA region (ITS ) evolves rapidly, leading to create genetic distances that can differentiate closely related, congeneric species., The inter-specific divergence among different species, accountable for identification and phylogenetic variations in present study might be due to the same reason. Higher intra-specific variation among conspecific species may be explained by the issue of intragenomic diversity in ITS due to the presence of sequences in multiple copies in the genome., Higher inter-specific diversity and larger barcoding gap is always considered suitable to find DNA barcode. In this study, ITS loci were found most suitable for the distinguishing orchids based on higher inter-specific diversity and barcoding gap.
Sequence analysis using BLAST yielded higher species resolution for ITS region among all the markers used in the present study. BLAST's higher resolution can be explained by ITS greater sensitivity to sequence length, as well as inclusion of indel variation and orthology/paralogy conflation. Earlier reports on Dendrobium and medicinal plants of Iran also found BLAST analysis as a proficient method for species identification. ITS sequence data are universally used in plant phylogenetic studies despite of its complex and unpredictable evolutionary behavior. Their highly variable noncoding regions may not be useful to study the phylogenetic relationships of high-level taxa, but could be a good source to investigate phylogenetic relationships at lower levels, such as intra-generic levels and intra-specific varieties., This might be the reason why individuals of same species and genus were clustered as monophyletic clade in our study.ITS sequence-based identification and phylogenetic relationship of orchids have been studied earlier in Dendrobium,,Habenaria, and Paphiopedilum and was found successful.
China Plant BOL Group proposed that the nuclear ribosomal DNA-ITS , or subset of this marker-ITS 2, should be incorporated alongside rbcL + matK into the core barcode for seed plants, particularly for angiosperms. Several recent studies also recommended that ITS region in combination with trnH-psbA , matK and/or rbcL are best barcode region for Schisandraceae family,Terminalia and many orchid species. In contrast, our study found matK and rbcL loci could not discriminate Indian orchids, might be because we sampled many more closely related species within single genera to assess absolute rather than relative discriminatory power of the tested barcode markers. Hence, the present study outcome based on different methods (distance, BLAST, and tree-building) is strongly supporting earlier report that suggests ITS region as most successful barcoding region for Dendrobium ,Crawfurdia, and other medicinal plants like Saussurea subg Amphilaena.
| Conclusion|| |
In this study, we worked on 62 samples of 35 endemic and endangered Indian orchids species belongs to 7 genera. This study made scientific populace of NCBI familiar with 10 unrecognized species of Western Ghats, India. We identified 133 barcoding sequences, out of which, 20, 12, and 14 sequences were found unique and new to GenBank for ITS,matK, and rbcL, respectively. Further, our study based on distance, BLAST and tree-building methods suggested that ITS is the best region to be considered as single locus barcode for the identification of orchids of India.
We thank Dr. K. S. Sashidhar, President, TOSKAR, and his team for their help in orchid collection and identification.
Financial support and sponsorship
DST-SERB, Gov. of India financially supported this work by providing National Post Doctoral Fellowship grant (PDF/2015/000692) to Deepti Srivastava.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Rajendran A, Rao NR, Kumar KR, Henry AN. Some medicinal orchids of Southern India. Anc Sci Life 1997;17:10.
Hossain MM. Therapeutic orchids: Traditional uses and recent advances – An overview. Fitoterapia 2011;82:102-40.
Singh SK, Agarwala DK, Jalal JS, Mao AA. Orchids of India: A Pictorial Guide. Kolkata: Botanical Survey of India; 2019.
Phelps J, Webb EL. “Invisible” wildlife trades: Southeast Asia's undocumented illegal trade in wild ornamental plants. Biol Conserv 2015;186:296-305.
Das A, Krishnaswamy J, Bawa KS, Kiran MC, Srinivas V, Kumar NS, Karanth KU. Prioritisation of conservation areas in the Western Ghats, India. Biol Conserv 2006;133:16-31.
Hebert PD, Cywinska A, Shelley L, Balland J, de Waard R. Biological identifications through DNA barcodes. Proc R Soc Lond B Biol Sci 2004;270:313-21.
Armenise L, Simeone MC, Piredda R, Schirone B. Validation of DNA barcoding as an efficient tool for taxon identification and detection of species diversity in Italian conifers. Eur J Forest Res 2012;131:1337-53.
Ghorbani A, Saeedi Y, de Boer HJ. Unidentifiable by morphology: DNA barcoding of plant material in local markets in Iran. PLoS One 2017;12:E0175722.
CBOL Plant Working Group. A DNA barcode for land plants. Proc Natl Acad Sci USA 2009;106:12794-7.
China Plant BOL Group. 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 2011;108:19641-6.
Singh HK, Parveen I, Raghuvanshi S, Babbar SB. The loci recommended as universal barcodes for plants on the basis of floristic studies may not work with congeneric species as exemplified by DNA barcoding of Dendrobium
species. BMC Res Notes 2012;5:42.
Yao H, Song J, Liu C, Luo K, Han J, Li Y, et al
. Use of ITS2
region as the universal DNA barcode for plants and animals. PLoS One 2010;5:e13102.
Chattopadhyay P, Banerjee G, Banerjee N. Distinguishing orchid species by DNA barcoding: Increasing the resolution of population studies in plant biology. Omics J Integ Biol 2017;21:711-20.
Parveen I, Singh HK, Raghuvanshi S, Pradhan UC, Babbar SB. DNA barcoding of endangered Indian Paphiopedilum
species. Molecular Ecol Res 2012;12:82-90.
Doyle JJ, Doyle JS. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 1987;19:11-5.
Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al
. Clustal W and Clustal X version 2.0. Bioinformatics 2007;23:2947-8.
Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 2018;35:1547-9.
Chase MW, Cameron KM, Freudenstein JV, Pridgeon AM, Salazar G, Berg CV,et al
. An updated classification of Orchidaceae. Bot J Linnean Soc 2015;177:151-74.
Zhang D, Jiang B, Duan L, Zhou N. Internal transcribed spacer (ITS), an ideal DNA barcode for species discrimination in Crawfurdia
wall. (gentianaceae). Afr J Tradit Complement 2016;13:101-6.
Xu S, Li D, Li J, Xiang X, Jin W, Huang W, et al
. Evaluation of the DNA barcodes in Dendrobium
(Orchidaceae) from mainland Asia. PLoS One 2015;10:e0115168.
Mishra P, Kumar A, Nagireddy A, Shukla AK, Sundaresan V. Evaluation of single and multilocus DNA barcodes towards species delineation in complex tree genus Terminalia
. PLoS One 2017;12:e0182836.
Zhang J, Chen M, Dong X, Lin R, Fan J, Chen Z. Evaluation of four commonly used DNA barcoding loci for Chinese medicinal plants of the family schisandraceae. PLoS One 2015;10:e0125574.
Giudicelli GC, Mäder G, Freitas LB. Efficiency of ITS sequences for DNA barcoding in Passiflora
(Passifloraceae). Int J Mol Sci 2015;16:7289-303.
Duong, Khoa NT. Molecular phylogeny of the endangered vietnamese Paphiopedilum
species based on the internal transcribed spacer of the nuclear ribosomal DNA. Adv Stud Biol 2013;5:337-46.
Wu CT, Gupta SK, Wang AZ, Lo SF, Kuo CL, Ko YJ, et al
. Internal transcribed spacer sequence based identification and phylogenic relationship of Herba Dendrobii
. J Food Drug Anal 2012;20:143-51.
Duan H, Wang W, Zeng Y, Guo M, Zhou Y. The screening and identification of DNA barcode sequences for Rehmannia. Sci Rep 2019;9:17295.
Tsai CC, Chiang YC, Huang SC, Chen CH, Chou CH. Molecular phylogeny of Phalaenopsis
Blume (Orchidaceae) on the basis of plastid and nuclear DNA. Plant Syst Evol 2010;288:77-98.
Zhai JW, Zhang GQ, Chen LJ, Xiao XJ, Liu KW, Tsai WC, et al
. A new orchid genus, Danxiaorchis and phylogenetic analysis of the tribe calypsoeae. PLoS One 2013;8:e60371.
Zhu S, Li Q, Chen S, Wang Y, Zhou L, Zeng C, et al
. Phylogenetic analysis of Uncaria
species based on internal transcribed spacer (ITS) region and ITS2 secondary structure. Pharma Biol 2018;56:548-58.
Dong W, Liu J, Yu J, Wang L, Zhou S. Highly variable chloroplast markers for evaluating plant phylogeny at low taxonomic levels and for DNA barcoding. PLoS One 2012;7:E35071.
Batista JA, Borges KS, De Faria MW, Proite K, Ramalho AJ, Salazar GA, et al
. Molecular phylogenetics of the species-rich genus Habenaria
(Orchidaceae) in the New World based on nuclear and plastid DNA sequences. Mol Phylogenet Evol 2013;67:95-109.
Trung KH, Khanh TD, Ham LH, Duong TD, Khoa NT. Molecular phylogeny of the endangered vietnamese Paphiopedilum
species based on the internal transcribed spacer of the nuclear ribosomal DNA. Adv Stud Biol 2013;5:337-46.
Chen S, Yao H, Han J, Liu C, Song J, Shi L, et al
. Validation of the ITS2 region as a novel DNA barcode for identifying medicinal plant species. PLoS One 2010;5:e8613.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4]