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    Author(s): Hongwen Huang; Desmond R. Layne; Thomas L. Kubisiak
    Date: 2003
    Source: J. Amer. Soc. Hort. Sci. 128(1):85-93. 2003.
    Publication Series: Miscellaneous Publication
    PDF: View PDF  (544 KB)

    Description

    Thirty-four extant pawpaw [Asimina triloba (L.) Dunal] cultivars and advanced selections representing a large portion of the gene pool of cultivated pawpaws were investigated using 71 randomly amplified polymorphic DNA (RAPD) markers to establish genetic identities and evaluate genetic relatedness. All 34 cultivated pawpaws were uniquely identified by as few as 14 loci of eight primers. Genetic diversity of the existing gene pool of cultivated pawpaws, as estimated by Nei's gene diversity (He), was similar to that of wild pawpaw populations. The genetic relatedness among the cultivated pawpaws examined by UPGMA chaster analysis separated 34 cultivars and selections into two distinct clusters, a cluster of PPF (The PawPaw Foundation) selections and a cluster including a majority of the extant cultivars selected from the wild and their derived selections. The results are in general agreement with the known selection history and pedigree information available. The consensus fingerprint profile using the genetically defined RAPD markers is a useful and reliable method for establishing the genetic identities of the pawpaw cultivars and advanced selections. This also proved to be an improved discriminating tool over isozyme markers for the assessment of genetic diversity and relatedness. RAPD profiling of data presented in this study provides a useful reference for germplasm curators engaged in making decisions of sampling strategies, germplasm management and for breeders deciding which parents to select for future breeding efforts.

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    Citation

    Huang, Hongwen; Layne, Desmond R.; Kubisiak, Thomas L. 2003. Molecular Characterization of Cultivated Pawpaw (Asimina triloba) Using RAPD Markers. J. Amer. Soc. Hort. Sci. 128(1):85-93. 2003.

    Keywords

    DNA fingerprinting, cultivar identification, genetic relatedness, cluster analysis

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