Prospects for discriminating Zingiberaceae species in India using DNA barcodes

Vinitha, M R; Kumar, U. Suresh; Aishwarya, K.; Sabu­, M.; Thomas, George H.

doi:10.1111/jipb.12189

Cited by 29 publications

(47 citation statements)

References 74 publications

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“…As a consequence, we generated 60 species signatures to classify closely related sequences by using the PSSM information (Additional file 5). These results are consistent with earlier plant DNA barcoding studies that mentioned matK as a suitable barcode; this gene can discriminate morphologically similar and closely related species [13, 20, 30, 31]. …”

Section: Discussionsupporting

confidence: 92%

“…Seven chloroplast loci have been tested for plant species identification by The Consortium for the Barcode of Life (CBOL) Plant Working Group, where the suitability of matK and rbcL loci as a barcode was showed [12]. Vinitha et al [13] studied a total of 20 species belonging to the family Zingiberaceae from India by using nine plastids and two nuclear loci and reported that matK and rbcL aids in the determination of 15 species (75%) into monophyletic groups. Techen et al [14] mentioned that the matK region was preferred as a barcode candidate because of high evolutionary rate, low transition/transversion rate, and inter-specific divergence.…”

Section: Introductionmentioning

confidence: 99%

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matK-QR classifier: a patterns based approach for plant species identification

Mane²,

Purohit

2016

BioData Mining

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BackgroundDNA barcoding is widely used and most efficient approach that facilitates rapid and accurate identification of plant species based on the short standardized segment of the genome. The nucleotide sequences of maturaseK (matK) and ribulose-1, 5-bisphosphate carboxylase (rbcL) marker loci are commonly used in plant species identification. Here, we present a new and highly efficient approach for identifying a unique set of discriminating nucleotide patterns to generate a signature (i.e. regular expression) for plant species identification.MethodsIn order to generate molecular signatures, we used matK and rbcL loci datasets, which encompass 125 plant species in 52 genera reported by the CBOL plant working group. Initially, we performed Multiple Sequence Alignment (MSA) of all species followed by Position Specific Scoring Matrix (PSSM) for both loci to achieve a percentage of discrimination among species. Further, we detected Discriminating Patterns (DP) at genus and species level using PSSM for the matK dataset. Combining DP and consecutive pattern distances, we generated molecular signatures for each species. Finally, we performed a comparative assessment of these signatures with the existing methods including BLASTn, Support Vector Machines (SVM), Jrip-RIPPER, J48 (C4.5 algorithm), and the Naïve Bayes (NB) methods against NCBI-GenBank matK dataset.ResultsDue to the higher discrimination success obtained with the matK as compared to the rbcL, we selected matK gene for signature generation. We generated signatures for 60 species based on identified discriminating patterns at genus and species level. Our comparative assessment results suggest that a total of 46 out of 60 species could be correctly identified using generated signatures, followed by BLASTn (34 species), SVM (18 species), C4.5 (7 species), NB (4 species) and RIPPER (3 species) methods As a final outcome of this study, we converted signatures into QR codes and developed a software matK-QR Classifier (http://www.neeri.res.in/matk_classifier/index.htm), which search signatures in the query matK gene sequences and predict corresponding plant species.ConclusionsThis novel approach of employing pattern-based signatures opens new avenues for the classification of species. In addition to existing methods, we believe that matK-QR Classifier would be a valuable tool for molecular taxonomists enabling precise identification of plant species.Electronic supplementary materialThe online version of this article (doi:10.1186/s13040-016-0120-6) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

matK-QR classifier: a patterns based approach for plant species identification

Mane²,

Purohit

2016

BioData Mining

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“…9,12) Using clone sequencing for ITS-LSU D1/D3, we identified 2-10 haplotypes within each sample. Our results are consistent with other studies 10,11) reported different ITS sequences among specimens. Therefore, our findings support the use of clone sequencing rather than the direct sequencing of PCR products to obtain accurate sequence data for ribosomal DNA (rDNA) fragments (ITS, ITS2, ITS-LSU D1/D3).…”

Section: Discussionsupporting

confidence: 94%

“…Previous studies tested the ability of DNA barcoding to identify Curcuma species. [9][10][11][12] This research yielded sequence data that are stored in GenBank and can be used as a reference library. To improve the efficiency of rbcL and matK, we used the nuclear ribosome fragment ITS-LSU D1/D3 (Fig.…”

mentioning

confidence: 99%

Assessment of Genetic and Chemical Variability in Curcumae Longae Rhizoma (<i>Curcuma longa</i>) Based on DNA Barcoding Markers and HPLC Fingerprints

Zhong-gang

Song

Chen

et al. 2017

Biological & Pharmaceutical Bulletin

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Curcumae Longae Rhizoma (Curcuma longa L.) is an important traditional Chinese medicine with multiple beneficial effects. To elucidate the genetic and chemical differences among Curcumae Longae Rhizoma samples, three DNA barcoding markers (rbcL, matK, and ITS-LSU D1/D3) and HPLC fingerprinting were employed in this study. The discriminatory power of rbcL and matK was low, as they only detected one sequence type that showed 100% similarity with more than 20 congeneric species in the Barcode of Life Data Systems (BOLD) database. In contrast, ITS-LSU D1/D3 showed sufficient discriminatory power to precisely identify all of the market samples as C. longa L. in a BLAST search as well as differentiate each sample based on 2-10 ITS-LSU D1/D3 haplotypes with intragenomic variability (mean p-distance: 0.7%, range: 0-2.6%; mean number of differences: 9.6 sites, range: 0-38 sites). HPLC fingerprinting of 13 commercial samples showed a similarity that ranged from 0.769 to 0.996, indicating that the sample quality varied. A cluster analysis based on 5 common peak areas from the HPLC chromatogram resulted in two groups. Group I included 9 samples with a relatively high chemical content, and group II contained 4 samples with a low chemical content. A Mantel test revealed a low correlation (r 0.1721, p 0.047) between genetic and chemical differences. Our findings suggest that the integrated approach of ITS-LSU D1/D3 DNA barcoding and HPLC fingerprinting provides a comprehensive, precise, and convenient method to clarify the genetic and chemical differences in Curcumae Longae Rhizoma.

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“…However, DNA barcoding has been emerging as the primary diagnostic strategy for authentication of plant material used for the preparation of HMPs. In this regard, a large number of nuclear and plastid DNA based barcodes have now become a realistic and accurate diagnostic tool for identification of genuine plant species and determination of adulterants in herbal products (Mahadani and Ghosh, 2013, Pang et al , 2013, Selvaraj et al , 2012, Thompson and Newmaster, 2014, Vinitha et al , 2014. A novel DNA mini-barcode assay, as developed for the authentication of G. biloba herbal supplements with a high degree of sensitivity and specificity (Little, 2014), has offered a practical resolution to authenticate herbal supplements both for manufacturers and regulatory authorities.…”

Section: Dna Barcoding and Metabolite Profiling Can Resolve The Qualimentioning

confidence: 99%