Detection of nonauthorized genetically modified organisms using differential quantitative polymerase chain reaction : application to 35S in maize
2008
Cankar, Katarina | Ancel, Valerie | Fortabat, Marie-Noelle | Gruden, Kristina | Kobilinsky, Andre | Zel, Jana | Bertheau, Yves | Department of Plant Physiology and Biotechnology ; National Institute of Biology [Ljubljana] (NIB) | Wageningen University and Research [Wageningen] (WUR) | UR 0256 Phytopathologie et Méthodologies de la Détection ; Institut National de la Recherche Agronomique (INRA)-Santé des plantes et environnement (S.P.E.)-Phytopathologie et Méthodologies de la Détection (PMDV) | UR 0256 Phytopathologie et Méthodologies de la Détection. PMDV, Centre de recherche de Versailles-Grignon. Santé des plantes et environnement ; Institut National de la Recherche Agronomique (INRA) | Mathématiques et Informatique Appliquées (MIA-Paris) ; Institut National de la Recherche Agronomique (INRA)-AgroParisTech | Département Santé des Plantes et Environnement (DPT SPE) ; Institut National de la Recherche Agronomique (INRA)
Detection of nonauthorized genetically modified organisms (GMOs) has always presented an analytical challenge because the complete sequence data needed to detect them are generally unavailable although sequence similarity to known GMOs can be expected. A new approach, differential quantitative polymerase chain reaction (PCR), for detection of nonauthorized GMOs is presented here. This method is based on the presence of several common elements (e.g., promoter, genes of interest) in different GMOs. A statistical model was developed to study the difference between the number of molecules of such a common sequence and the number of molecules identifying the approved GMO (as determined by border-fragment-based PCR) and the donor organism of the common sequence. When this difference differs statistically from zero, the presence of a nonauthorized GMO can be inferred. The interest and scope of such an approach were tested on a case study of different proportions of genetically modified maize events, with the P35S promoter as the Cauliflower Mosaic Virus common sequence. The presence of a nonauthorized GMO was successfully detected in the mixtures analyzed and in the presence of (donor organism of P35S promoter). This method could be easily transposed to other common GMO sequences and other species and is applicable to other detection areas such as microbiology.
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