Skip to main navigation menu Skip to main content Skip to site footer
Plant Science Today (PST)

Research Articles

Early Access

Molecular identification of ethnomedicinal Calotropis using DNA barcoding

DOI
https://doi.org/10.14719/pst.8889
Submitted
15 April 2025
Published
11-03-2026

Abstract

The presence of high demand for the ethno-medicinally important plant Calotropis R.Br. (Apocynaceae Juss.) in the trade market makes substitution or adulteration likely. To address this problem of accurate species identification within this genus, DNA barcoding methods are employed. We investigated the species discriminating power of the recommended barcode loci (rbcL, matK, trnL-F and ITS) and their combinations using distance-based (inter- and intra-specific distances) and similarity-based (BM and BCM), phylogeny-based analyses of available Calotropis species. In the present study, the BLAST identity rate is high for the recommended barcode region rbcL (99.66–100 %), followed by matK (99.57–100 %), trnL-F (98.12–100 %) and ITS (97.50–100 %). A notable difference was found between inter- and intraspecific distances in all the selected genes except rbcL. The BM and BCM approaches revealed the highest rate of correct identification with ITS (60 %) as a single gene and the combination with ITS (50 %) as a double gene. It is further confirmed that only the ITS single gene successfully separated the Calotropis species in phylogenetic analysis, whereas the other single locus and double locus showed some ambiguity in discriminating the species properly. Therefore, we suggest that the nrITS gene is the most suitable barcode for differentiating Calotropis species.

References

  1. 1. Valiathan MS. Ayurveda: Putting the house in order. Curr Sci. 2006;90:5–6.
  2. 2. Ved DK, Goraya G. Demand and supply of medicinal plants in India. New Delhi: NMPB; Bangalore: FRLHT; 2007.
  3. 3. Seethapathy GS, Ganesh D, Santhosh Kumar JU, Senthilkumar U, Newmaster SG, Ragupathy S, et al. Assessing product adulteration in natural health products for laxative yielding plants, Cassia, Senna and Chamaecrista in southern India using DNA barcoding. Int J Legal Med. 2015;29:693–700. https://doi.org/10.1007/s00414-014-1120-z
  4. 4. Prakash O, Jyoti Kumar A, Kumar P, Manna NK. Adulteration and substitution in Indian medicinal plants: an overview. J Med Plants Stud. 2013;1:127–32.
  5. 5. Sagar PK. Adulteration and substitution in endangered ASU medicinal plants of India: a review. Int J Med Aromat Plants. 2014;4:56–73.
  6. 6. Keshari P. Controversy, adulteration and substitution: burning problems in Ayurveda practices. In: El-Shemy HA, editor. Pharmacognosy – medicinal plants. London: IntechOpen; 2021. p. 1–12. https://doi.org/10.5772/intechopen.98220
  7. 7. Prasanth M, Anvar K. An ethnobotanical survey on adulterants of medicinal plants used by traditional practitioners of Palakkad district, Kerala, India. Int J Res Pharm Chem. 2019;9:78–84. https://doi.org/10.33289/IJRPC.9.3.2019.937
  8. 8. Ladani MR, Parabia FM. DNA barcoding: an identification of medicinal plants, databases and a promising future. Quest. 2014;2:12–7.
  9. 9. Naskar AK, Bhunia AK, Mondal AK. A survey on ethnomedicinal plants used by forest-dependent communities of the southwestern part of West Bengal, India. J Tradit Folk Pract. 2021;9:1–34. https://doi.org/10.25173/jtfp.2
  10. 10. Das S, Das S, Das M, Basu S. Evaluation of anti-inflammatory effect of Calotropis gigantea and Tridax procumbens on Wistar albino rats. J Pharm Sci Res. 2009;1:123–6.
  11. 11. Chitme H, Chandra R, Kaushik S. Studies on anti-diarrhoeal activity of Calotropis gigantea R Br in experimental animals. J Pharm Pharm Sci. 2004;7:70–5.
  12. 12. Rahaman C, Karmakar S. Ethnomedicine of Santal tribe living around Susunia hill of Bankura district, West Bengal, India: the quantitative approach. J Appl Pharm Sci. 2015;5:127–36. https://doi.org/10.7324/JAPS.2015.50219
  13. 13. Chaudhury S, Singh H, Rahaman CH. Ethnomedicinal uses of plants by the Lodhas tribal group of West Bengal, India. J Tradit Folk Pract. 2018;6:32. https://doi.org/10.25173/jtfp.106
  14. 14. Cameron KM, Chase MW, Whitten WM, Kores PJ, Jarrell DC, Albert VA, et al. A phylogenetic analysis of the Orchidaceae: evidence from rbcL nucleotide sequences. Am J Bot. 1999;86:208–24. https://doi.org/10.2307/2656938
  15. 15. 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. https://doi.org/10.1186/1756-0500-5-42
  16. 16. Li DZ, Gao LM, Li HT, Wang H, Ge XJ, Liu JQ, et al. Comparative analysis of a large dataset indicates that ITS should be incorporated into the core barcode for seed plants. Proc Natl Acad Sci USA. 2011;108:19641–6. https://doi.org/10.1073/pnas.1104551108
  17. 17. Techen N, Parveen I, Pan Z, Khan AI. DNA barcoding of medicinal plant material for identification. Curr Opin Biotechnol. 2014;25:103–10. https://doi.org/10.1016/j.copbio.2013.09.010
  18. 18. Jai SK, Rao RR. A handbook of field and herbarium methods. New Delhi: Today and Tomorrow’s printers and Publishers; 1977.
  19. 19. Hall TA. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser. 1999;41:95–8.
  20. 20. Tamura K, Stecher G, Kumar S. MEGA11: molecular evolutionary genetics analysis version 11. Mol Biol Evol. 2011;38:3022–7. https://doi.org/10.1093/molbev/msab120
  21. 21. Kimura M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol. 1980;16:111–20. https://doi.org/10.1007/BF01731581
  22. 22. Puillandre N, Lambert A, Brouillet S, Achaz G. ABGD: automatic barcode gap discovery for primary species delimitation. Mol Ecol. 2012;21:1864–77. https://doi.org/10.1111/j.1365-294X.2011.05239.x
  23. 23. Meier R, Shiyang K, Vaidya G, Ng PKL. DNA barcoding and taxonomy in Diptera: a tale of high intraspecific variability and low identification success. Syst Biol. 2006;55:715–28. https://doi.org/10.1080/10635150600969864
  24. 24. Darriba D, Taboada G, Doallo R, Posada D. jModelTest 2: more models, new heuristics and parallel computing. Nat Methods. 2012;9:772. https://doi.org/10.1038/nmeth.2109
  25. 25. Stamatakis A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics. 2006;22:2688–90. https://doi.org/10.1093/bioinformatics/btl446
  26. 26. Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol. 2012;29:1969–73. https://doi.org/10.1093/molbev/mss075
  27. 27. Quanxi M, Xiaolu C, Li X, Yue L, Yanyan S, Yuqiao G, et al. DNA barcode for identifying Folium Artemisiae argyi from counterfeits. Biol Pharm Bull. 2016;39:1531–7. https://doi.org/10.1248/bpb.b16-00336
  28. 28. Hollingsworth PM, Graham SW, Little DP. Choosing and using a plant DNA barcode. PLoS One. 2011;6:e19254. https://doi.org/10.1371/journal.pone.0019254
  29. 29. Yang JB, Wang YP, Möller M, Gao LM, Wu D. Applying plant DNA barcodes to identify species of Parnassia (Parnassiaceae). Mol Ecol Resour. 2012;12:267–75. https://doi.org/10.1111/j.1755-0998.2011.03095.x
  30. 30. Kress WJ. Plant DNA barcodes: applications today and in the future. J Syst Evol. 2017;55:291–307. https://doi.org/10.1111/jse.12254
  31. 31. Lv YN, Yang CY, Shi LC, Zhang ZL, Xu AS, Zhang LX, et al. Identification of medicinal plants within the Apocynaceae family using ITS2 and psbA-trnH barcodes. Chin J Nat Med. 2020;18:594–605. https://doi.org/10.1016/S1875-5364(20)30071-6
  32. 32. Cabelin VLD, Alejandro GJD. Efficiency of matK, rbcL, trnH-psbA and trnL-F to authenticate Philippine ethnomedicinal Apocynaceae through DNA barcoding. Pharmacogn Mag. 2016;12:S384–8. https://doi.org/10.4103/0973-1296.185780
  33. 33. Kress WJ, Wurdack KJ, Zimmer EA, Weigt LA, Janzen DH. Use of DNA barcodes to identify flowering plants. Proc Natl Acad Sci U S A. 2005;102:8369–74. https://doi.org/10.1073/pnas.0503123102
  34. 34. Steven GN, Subramanyam R. Testing plant barcoding in a sister species complex of pantropical Acacia (Mimosoideae, Fabaceae). Mol Ecol Resour. 2009;9:172–80. https://doi.org/10.1111/j.1755-0998.2009.02642.x
  35. 35. Mahadani P, Sharma GD, Ghosh SK. Identification of ethnomedicinal plants (Rauvolfioideae: Apocynaceae) through DNA barcoding from northeast India. Pharmacogn Mag. 2013;9:255–63. https://doi.org/10.4103/0973-1296.113284
  36. 36. Selvaraj D, Sarma RK, Shanmughanandhan D, Srinivasan R, Ramalingam S. Evaluation of DNA barcode candidates for the discrimination of the large plant family Apocynaceae. Plant Syst Evol. 2015;301:1263–73. https://doi.org/10.1007/s00606-014-1149-y
  37. 37. Sidhu MC, Kumari A, Jain B, Kaur S, Kamra A, Rai J. Morphological and DNA barcoding-based identification of Calotropis procera and Calotropis gigantea. Biol Bull Russ Acad Sci. 2023;50:474–7. https://doi.org/10.1134/S1062359022602968

Downloads

Download data is not yet available.