A preliminary RAPD-PCR analysis of Cimicifuga species and other botanicals used for women's health

Traditional taxonomic methods of botanical identification that rely primarily on morphological observations cannot be used efficiently when only powdered plant materials are available. Thus, our objectives were to determine if we could apply a molecular approach to: a) produce unique DNA profiles that are characteristic of the species, and b) determine if the geographical area or time of collection influences these DNA profiles. Towards this end, random amplified polymorphic DNA (RAPD) analyses were performed on a number of botanicals currently used for women's health. The test materials included samples from three species each of the genera Cimicifuga (Actaea) and Trifolium, as well as samples of Vitex agnus-castus L., Glycyrrhiza glabra L., Gingko biloba L., Valeriana officinalis L., Angelica sinensis (Oliv.) Diels, Viburnum prunifolium L., Humulus lupulus L., Vaccinium macrocarpon Ait., Panax ginseng C.A. Mey. Cimicifuga racemosa (L.) Nutt. and Trifolium pratense L. are currently under clinical investigation in our basic research laboratories and medical clinic for the relief of post-menopausal symptoms. Characteristic profiles produced with the OPC-15 primer could distinguish the three Cimicifuga species: C. racemosa, C. americana and C. rubifolia. Similar results were obtained with the three Trifolium species: Trifolium pratense L., Trifolium incarnatum L., and Trifolium repens L. Accessions of cultivated T. pratense collected from the same field at different times, produced identical profiles. Accessions of Cimicifuga species collected from different geographical areas produced similar but not identical DNA profiles; however, species-specific DNA fragments were identified. These results demonstrate that RAPD analysis can be applied to distinguish species when only powdered material is available for testing. This methodology can be applied to identify species of commercial value regardless of collection time or geographic area.