Selection of transgenic Petunia plants using the green fluorescent protein (GFP) View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-12

AUTHORS

Viola Mußmann, Margrethe Serek, Traud Winkelmann

ABSTRACT

Selectable marker genes are needed for efficient transformation of plants. The present study focused on testing the applicability of green fluorescent protein (GFP) for selecting transgenic Petunia hybrida plants without applying antibiotics or herbicides. Based on a transient gene expression assay, the efficiency of two gfp genes, mGFP-4 and smRS-GFP, was compared. Two days after infiltration of Agrobacterium tumefaciens, GFP expression was recorded in leaf epidermal cells. The intensity of smRS-GFP fluorescence was higher than that of mGFP-4 and easier to distinguish from other unspecific fluorescent signals in Petunia. Transformations using the pMen65smRS-GFP vector, which contained the neomycin phosphotransferase II (nptII) gene, resulted in callus and shoots that visually and clearly expressed detectable GFP levels; in addition, this vector made it possible to exclusively select transformed plants using GFP. The transformation efficiencies achieved by using GFP selection versus combined kanamycin and GFP selection (nptII+GFP) were compared in four Petunia genotypes with a transformation experiment with four replications. In three out of four Petunia cultivars a higher transformation frequency was achieved by using nptII+GFP selection. Southern blot hybridisation revealed single and multiple integrations of smRS-GFP in Petunia. Single copy plants showed intensive expression in all parts of the plants, whereas a higher copy number led to only weak or partial expression of smRS-GFP allowing the visual selection of single copy events. Thus, it is possible to select transgenic Petunia plants based on their GFP expressions without applying antibiotics or herbicides. More... »

PAGES

483-492

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    http://scigraph.springernature.com/pub.10.1007/s11240-011-9998-3

    DOI

    http://dx.doi.org/10.1007/s11240-011-9998-3

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    https://app.dimensions.ai/details/publication/pub.1007120309


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