Molecular fingerprinting of helicanthus elastic (Desr.) danser growing on five different hosts by RAPD

Mistletoes are hemiparasitic plants growing on aerial parts of other host trees. Many of the mistletoes are reported to be medicinally important. The hemiparasitic nature of these plants makes their chemical composition dependent on the host on which it grows. They are shown to exhibit morphological...

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Veröffentlicht in:Saudi journal of biological sciences 2016, Vol.23 (3), p.335-340
Hauptverfasser: Rajakrishnan, R., al-Farhan, A. H., Maruthi, K. R., Kumar, K. N. Sunil, Thomas, J.
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Sprache:eng
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Zusammenfassung:Mistletoes are hemiparasitic plants growing on aerial parts of other host trees. Many of the mistletoes are reported to be medicinally important. The hemiparasitic nature of these plants makes their chemical composition dependent on the host on which it grows. They are shown to exhibit morphological dissimilarities also when growing on different hosts. Helicanthus elastica (Desr.) Danser (mango mistletoe) is one such less explored medicinal mistletoe found on almost every mango tree in India. Traditionally, the leaves of this plant are used for checking abortion and for removing stones in the kidney and urinary bladder while significant antioxidant and antimicrobial properties are also attributed to this species of mistletoe. The current study was undertaken to evaluate molecular differences in the genomic DNA of the plant while growing on five different host trees using four random markers employing random amplified polymorphic DNA (RAPD) followed by similarity matrix by Jaccard’s coefficient and distance matrix by hierarchal clustering analysis. Similarity and distance matrix data employing just 4 random markers, separately and the pooled data as well, revealed significant difference in the genomic DNA of H. elastica growing on five different hosts. Pooled data of similarity from all the 4 primers cumulatively showed similarity between 0.256 and 0.311. Distance matrix ranged from of 0.256 to 0.281 on pooling the data
ISSN:1319-562X