Abstract

Solanum tuberosum L. was transformed using an Agrobacterium tumefaciens binary vector containing DNA encoding a translational fusion between the Bacillus thuringiensis var. kurstaki (B.t.k.) HD-73 ÎŽ-endotoxin and neomycin phosphotransferase II (NPT II). Two hunded forty-three shoots were regenerated from 50 inoculated leaf explants. Putatively transformed shoots were selected based on their ability to root in Murashige and Skoog medium supplemeted with 50 mg/1 kanamycin. DNA sequences encoding NPT II were detected using the polymerase chain reaction in several plants which formed roots in the selection medium. Southern blot hybridization of total DNA isolated from greenhouse grown transformed plant demonstrated integration of the translational fusion into the plant genome. In addition, transcription of the gene fusion in the transgenic potato plant was detected by reverse transcription of mRNA followed by amplification using the polymerase chain reaction (PCR). Insect assays, using tobacco hornworm (Manduca sexta) neonate larvae, indicated a significant reduction of leaf consumption in the transgenic plant when compared to a control potato plant (Cheng et ah., 1992). Second generation transgenic plants were grown from tubers and bioassayed against potato tubermoth (Phthorimaea operculella) and European corn borer (Ostrinia nubilalis). Ten percent mortality mortality of potato tubermoth was observed in transgenic plants but leaf consumption of surviving larvae was almost the same as in control plants. European corn borer larvae were significantly less capable of surviving in transgenic potato than in control plants as alternative host. Preference test showed that leaf disks of transgenic plants were less preferred than the control plants by 3rd instar European corn borer after 24 hours of exposure.KeywordsTransgenic PlantLeaf DiskPotato PlantSouthern Blot HybridizationTransgenic PotatoThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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