Home Mathematics 15 Evaluation of genetic diversity in Rauvolfia species using Random Amplification of Polymorphic DNA (RAPD) technique
Chapter
Licensed
Unlicensed Requires Authentication

15 Evaluation of genetic diversity in Rauvolfia species using Random Amplification of Polymorphic DNA (RAPD) technique

  • Varsha Umesh Ghate , Ajay G. Namdeo , Abhay Harsulkar , Anupam Mukherjee , Yashwant Chavan , Suresh Jagtap , Devasis Pradhan and Mehdi Gheisari
Become an author with De Gruyter Brill
Drug Discovery and Telemedicine
This chapter is in the book Drug Discovery and Telemedicine

Abstract

Background: Rauvolfia serpentina (L.) Benth. ex Kurz is one of the threatened medicinal plants. Owing to demand and scarcity, R. serpentina roots are adulterated or substituted with other Rauvolfia species, but in homoeopathy only Rauvolfia serpentina species are used to prepare mother tincture or dilutions.Methods: For identification and discrimination based on genetic information among R. serpentina, R. densiflora, R. tetraphylla, R. vomitoria, and R. micrantha, DNA fingerprints were developed with RAPD analysis using 12 random primers by standard protocol. Genetic polymorphism was quantified by generating a similarity matrix based on the presence or absence of polymorphic bands.Results: The obtained dendrogram represents the genetic relationships among the samples. As per the analysis, R. serpentina and R. densiflora are most closely related species; whereas R. tetraphyla and R. vomitoria have maximum genetic distance indicating their distant phylogenetic relation.Conclusion: These findings emphasize importance of RAPD analysis in identifying genetic differences among various Rauvolfia species. Furthermore, DNA fingerprinting can holds the potential in supporting the pharmaceutical and nutraceutical industries by facilitating standardization and quality evaluation of medicinal plants.

Abstract

Background: Rauvolfia serpentina (L.) Benth. ex Kurz is one of the threatened medicinal plants. Owing to demand and scarcity, R. serpentina roots are adulterated or substituted with other Rauvolfia species, but in homoeopathy only Rauvolfia serpentina species are used to prepare mother tincture or dilutions.Methods: For identification and discrimination based on genetic information among R. serpentina, R. densiflora, R. tetraphylla, R. vomitoria, and R. micrantha, DNA fingerprints were developed with RAPD analysis using 12 random primers by standard protocol. Genetic polymorphism was quantified by generating a similarity matrix based on the presence or absence of polymorphic bands.Results: The obtained dendrogram represents the genetic relationships among the samples. As per the analysis, R. serpentina and R. densiflora are most closely related species; whereas R. tetraphyla and R. vomitoria have maximum genetic distance indicating their distant phylogenetic relation.Conclusion: These findings emphasize importance of RAPD analysis in identifying genetic differences among various Rauvolfia species. Furthermore, DNA fingerprinting can holds the potential in supporting the pharmaceutical and nutraceutical industries by facilitating standardization and quality evaluation of medicinal plants.

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. List of Contributing Authors VII
  4. 1 Introduction: fundamentals of drug discovery, telemedicine, artificial intelligence, computer vision, and IoT 1
  5. 2 Machine learning transformations in drug discovery: a paradigm shift in development strategies 11
  6. 3 Explainable AI approaches in drug classification from biomarkers of epileptic seizure 27
  7. 4 Harnessing predictive analytics and machine learning in personalized medicine: patient outcomes and public health strategies 41
  8. 5 A data-driven framework for future healthcare diagnosis through predictive analytics 59
  9. 6 Revolutionizing home healthcare: telemedicine, predictive analytics, and AI-driven drug discovery 71
  10. 7 AI-driven insights: a machine learning approach to lung cancer diagnosis 91
  11. 8 Efficient gene selection for breast cancer classification using Brownian Motion Search Algorithm and Support Vector Machine 109
  12. 9 A hybrid feature gene selection approach by integrating variance filter, extremely randomized tree, and Cuckoo Search algorithm for cancer classification 127
  13. 10 HySleep_Net: a hybrid deep learning model for automatic sleep stage detection from polysomnographic signals 151
  14. 11 Ambulance booking and tracking website 183
  15. 12 Entropy based emergency rescue location selection with uncertain travel time 207
  16. 13 Performance comparison of different deep learning ensemble models for sentiment classification of movie reviews 225
  17. 14 Elevating standards in homoeopathic medicine: chemometric standardization of medicinal plant for quality assurance 253
  18. 15 Evaluation of genetic diversity in Rauvolfia species using Random Amplification of Polymorphic DNA (RAPD) technique 259
  19. Index
Downloaded on 10.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/9783111504667-015/html
Scroll to top button