Along with the expansion of commercial use of GM crops, some problems in GMO detection have been emerging. We present new GMO detection methods as a solution to these issues. Due to the increasing number of commercially available GM events, testing with using a series of conventional PCR methods has become labor-intensive. To solve this problem, we developed a real-time PCR array method for comprehensive GMO detection. In this method, genomic DNA extracted from an agricultural product is analyzed using various qualitative real-time PCR assays on a 96-well PCR plate, targeting individual GM events, recombinant DNA segments, taxon-specific genes, and so on. Additionally, a comparative analysis with the data and publicly available information on GM crops approved in Japan allows us to assume the possibility of unapproved GMO commingling. We established the information handling process and then developed a Microsoft Excel spreadsheet application, Unapproved GMO Checker, which enables the easy assumption of unapproved GM crop commingling. Because of the increasing use of maize hybrids with GM stacked events, the commonly-used bulk sample methods for PCR quantification of GM maize in non-GM maize are prone to overestimate the GMO content, compared to the actual weight/weight percentage of GM maize in the grain sample. As a solution for this, we designed and assessed a group testing strategy in which the GMO content is statistically evaluated based on qualitative analyses of multiple small pools of kernels. This approach enables the GMO content evaluation on a weight/weight basis, irrespective of the presence of stacked-event kernels. To enhance the method's user-friendliness in routine application, we devised an easy-to-use PCR-based qualitative analytical method comprising a sample preparation step in which maize kernels are ground in a lysis buffer and a subsequent PCR assay in which the lysate is directly used as a DNA template.

New approaches in GMO detection as a solution for emerging problems

246th National Meeting (2013)

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