ptxD gene in combination with phosphite serves as a highly effective selection system to generate transgenic cotton (Gossypium hirsutum L.)
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KEY MESSAGE: This report demonstrates the usefulness of ptxD/phosphite as a selection system that not only provides a highly efficient and simple means to generate transgenic cotton plants, but also helps address many of the concerns related to the use of antibiotic and herbicide resistance genes in the production of transgenic crops. Two of the most popular dominant selectable marker systems for plant transformation are based on either antibiotic or herbicide resistance genes. Due to concerns regarding their safety and in order to stack multiple traits in a single plant, there is a need for alternative selectable marker genes. The ptxD gene, derived from Pseudomonas stutzeri WM88, that confers to cells the ability to convert phosphite (Phi) into orthophosphate (Pi) offers an alternative selectable marker gene as demonstrated for tobacco and maize. Here, we show that the ptxD gene in combination with a protocol based on selection medium containing Phi, as the sole source of phosphorus (P), can serve as an effective and efficient system to select for transformed cells and generate transgenic cotton plants. Fluorescence microscopy examination of the cultures under selection and molecular analyses on the regenerated plants demonstrate the efficacy of the system in recovering cotton transformants following Agrobacterium-mediated transformation. Under the ptxD/Phi selection, an average of 3.43 transgenic events per 100 infected explants were recovered as opposed to only 0.41% recovery when bar/phosphinothricin (PPT) selection was used. The event recovery rates for nptII/kanamycin and hpt/hygromycin systems were 2.88 and 2.47%, respectively. Molecular analysis on regenerated events showed a selection efficiency of ~ 97% under the ptxD/Phi system. Thus, ptxD/Phi has proven to be a very efficient, positive selection system for the generation of transgenic cotton plants with equal or higher transformation efficiencies compared to the commonly used, negative selection systems.
author list (cited authors)
Pandeya, D., Campbell, L. M., Nunes, E., Lopez-Arredondo, D. L., Janga, M. R., Herrera-Estrella, L., & Rathore, K. S.