The manipulation and modification of tomato fruit ripening by expression of antisense RNA in transgenic plants View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1995-02

AUTHORS

Steve Picton, Julie E. Gray, Don Grierson

ABSTRACT

The common cultivated tomato (Lycopersicon esculentum Mill.) provides a major focus for improvement of crop quality through genetic engineering. Identification of ripening-related cDNAs has enabled the modification of specific aspects of ripening by manipulating gene expression in transgenic plants. By utilizing ‘antisense RNA’ to modify expression of ripening genes, we have inhibited the production of the cell wall-metabolising enzymes polygalacturonase and pectinesterase and created transgenic plants that contain, effectively, single, targeted mutations affecting these genes. Furthermore, this approach has been used with previously unidentified cDNA clones to enable both functional identification and manipulation of genes involved in ethylene production (ACC oxidase) and carotenoid biosynthesis (phytoene synthase). The use of antisense RNA targeted to specific genes to alter ripening phenotypes and improve commercial utility of fruit by affecting shelf-life, processing characteristics and nutritional content is discussed. We have used the extreme ripening-impaired mutant, ripening inhibitor (rin) to identify additional genes implicated in the ripening process. This approach has resulted in the cloning of several novel ripening-related mRNAs which are now being studied by antisense experiments. This may enable identification and manipulation of additional genes involved in processes such as softening, flavour and aroma generation and susceptibility to pathogens. More... »

PAGES

193-202

References to SciGraph publications

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  • Journal

    TITLE

    Euphytica

    ISSUE

    1-3

    VOLUME

    85

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/bf00023948

    DOI

    http://dx.doi.org/10.1007/bf00023948

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1039359384


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