Open Access Research article

Optimised padlock probe ligation and microarray detection of multiple (non-authorised) GMOs in a single reaction

Theo W Prins1, Jeroen P van Dijk1, Henriek G Beenen1, AM Angeline Van Hoef1, Marleen M Voorhuijzen1, Cor D Schoen2, Henk JM Aarts1 and Esther J Kok1*

Author Affiliations

1 RIKILT – Institute of Food Safety (WUR), Bornsesteeg 45, 6708 PD Wageningen, the Netherlands

2 Plant Research International BV (WUR), Droevendaalsesteeg 1, 6708 PB Wageningen, the Netherlands

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BMC Genomics 2008, 9:584  doi:10.1186/1471-2164-9-584

Published: 4 December 2008



To maintain EU GMO regulations, producers of new GM crop varieties need to supply an event-specific method for the new variety. As a result methods are nowadays available for EU-authorised genetically modified organisms (GMOs), but only to a limited extent for EU-non-authorised GMOs (NAGs). In the last decade the diversity of genetically modified (GM) ingredients in food and feed has increased significantly. As a result of this increase GMO laboratories currently need to apply many different methods to establish to potential presence of NAGs in raw materials and complex derived products.


In this paper we present an innovative method for detecting (approved) GMOs as well as the potential presence of NAGs in complex DNA samples containing different crop species. An optimised protocol has been developed for padlock probe ligation in combination with microarray detection (PPLMD) that can easily be scaled up. Linear padlock probes targeted against GMO-events, -elements and -species have been developed that can hybridise to their genomic target DNA and are visualised using microarray hybridisation.

In a tenplex PPLMD experiment, different genomic targets in Roundup-Ready soya, MON1445 cotton and Bt176 maize were detected down to at least 1%. In single experiments, the targets were detected down to 0.1%, i.e. comparable to standard qPCR.


Compared to currently available methods this is a significant step forward towards multiplex detection in complex raw materials and derived products. It is shown that the PPLMD approach is suitable for large-scale detection of GMOs in real-life samples and provides the possibility to detect and/or identify NAGs that would otherwise remain undetected.