The vast genetic diversity of medicinal plants is the basic foundation that dictates their phytochemical diversity, adaptability, and resilience against changing environments. The therapeutic efficacy of medicinal plants is directly correlated with their phytochemical diversity, which acts as a major source of modern drug discovery, traditional medicine, and sustainable healthcare systems. Various anthropogenic activities and climate change are imposing tremendous pressure on the genetic diversity of medicinal plants. The assessment and conservation of genetic diversity have been largely overlooked and less well exploited than species diversity. The application of traditional morphology- and phytochemical-based genetic diversity assessment is challenging due to low resolution, environmental influences, and cryptic speciation. In contrast, molecular approaches, such as random amplified polymorphic DNA, amplified fragment length polymorphism, inter-simple sequence repeat, simple sequence repeat marker, DNA barcoding, and single-nucleotide polymorphism (SNP), are more reliable and effective in unlocking the genetic architecture of medicinal plants. During their application, their advantages and limitations should be considered. Moreover, next-generation sequencing-based approaches, such as SNPs and whole-genome sequencing, are adding further resolution, precision, and consistency to genetic profiling and are frequently applied to understand intra- and interspecific genetic variation, identify unique, rare, or threatened genotypes, and understand population structure by genetic characterization, thereby supporting the adoption of effective ex-situ and in-situ conservation strategies. The integration of multi-omics techniques, bioinformatics, artificial intelligence, and machine learning models is a current trend in this field that may help reveal complex biosynthetic pathways of secondary metabolites (SMs), identify genes responsible for desired SMs, and accelerate the development of superior varieties using genomics-assisted breeding and transgenic approaches. Moreover, comprehensive genetic assessment helps to achieve sustainable utilization, informed conservation, and continued discovery of novel natural products essential for global health and well-being in the twenty-first century.

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Applications and Emerging Trends in Techniques for Assessing Genetic Diversity in Medicinal Plants

  • Dipasree Roychowdhury,
  • Mihir Halder

摘要

The vast genetic diversity of medicinal plants is the basic foundation that dictates their phytochemical diversity, adaptability, and resilience against changing environments. The therapeutic efficacy of medicinal plants is directly correlated with their phytochemical diversity, which acts as a major source of modern drug discovery, traditional medicine, and sustainable healthcare systems. Various anthropogenic activities and climate change are imposing tremendous pressure on the genetic diversity of medicinal plants. The assessment and conservation of genetic diversity have been largely overlooked and less well exploited than species diversity. The application of traditional morphology- and phytochemical-based genetic diversity assessment is challenging due to low resolution, environmental influences, and cryptic speciation. In contrast, molecular approaches, such as random amplified polymorphic DNA, amplified fragment length polymorphism, inter-simple sequence repeat, simple sequence repeat marker, DNA barcoding, and single-nucleotide polymorphism (SNP), are more reliable and effective in unlocking the genetic architecture of medicinal plants. During their application, their advantages and limitations should be considered. Moreover, next-generation sequencing-based approaches, such as SNPs and whole-genome sequencing, are adding further resolution, precision, and consistency to genetic profiling and are frequently applied to understand intra- and interspecific genetic variation, identify unique, rare, or threatened genotypes, and understand population structure by genetic characterization, thereby supporting the adoption of effective ex-situ and in-situ conservation strategies. The integration of multi-omics techniques, bioinformatics, artificial intelligence, and machine learning models is a current trend in this field that may help reveal complex biosynthetic pathways of secondary metabolites (SMs), identify genes responsible for desired SMs, and accelerate the development of superior varieties using genomics-assisted breeding and transgenic approaches. Moreover, comprehensive genetic assessment helps to achieve sustainable utilization, informed conservation, and continued discovery of novel natural products essential for global health and well-being in the twenty-first century.