Herbal medicines are growing in popularity in the Western world and are becoming more stringently regulated under new EU legislation. Within the arena of herbal medicines, St. John’s Wort (SJW), Hypericum perforatum, is a top ten best seller with clinical evidence to support its use as an anti-depressant. A fundamental requirement of the new legislation is to prove the identity of the plant material in question. This is currently achieved via morphological and chemical methods, neither of which are ideal. A wide range of DNA based methods have been applied to this arena, standardisation is required to realise the potential of DNA based techniques. The DNA barcoding initiative aims to produce sequence data for all plant species, capable of species identification. The proposal is to use these data to design fast and effective DNA based methods of identification. For assay design, the putative barcode region nrITS was selected as a platform. Three assays were designed; • A PCR assay designed to hyper variable sequences within a barcode region. This assay is capable of distinguishing SJW from other closely related species. • A quantitative qPCR assay designed to measure total DNA and specific SJW DNA within a mixed sample. • A multiplex PCR incorporating fluorescently labelled primers, allowing amplicon detection by capillary electrophoresis. This assay identifies four separate Hypericum species, including SJW, with a mixed sample in one reaction. The suitability of the nrITS and three other barcode regions is assessed based on sequence data generated for 32 vouchered samples of different Hypericum species, and a Lithuanian sample set of 22 and 16 H. perforatum and H. maculatum samples respectively. The matK is currently unusable, the rbcL highly conserved, trnH-psbA problematically variable and the nrITS proved to be ideal for assay design.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:519141 |
| Date | January 2010 |
| Creators | Howard, Caroline |
| Publisher | De Montfort University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/2086/3972 |
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