Conventional genetic engineering techniques generate modifications in the genome via stable integration of DNA elements which do not occur naturally in this combination. Therefore, the resulting organisms and (most) products thereof can unambiguously be identified with event-specific PCR-based methods targeting the insertion site. New breeding techniques such as genome editing diversify the toolbox to generate genetic variability in plants. Several of these techniques can introduce single nucleotide changes without integrating foreign DNA and thereby generate organisms with intended phenotypes. Consequently, such organisms and products thereof might be indistinguishable from naturally occurring or conventionally bred counterparts with established analytical tools. The modifications can entirely resemble random mutations regardless of being spontaneous or induced chemically or via irradiation. Therefore, if an identification of these organisms or products thereof is demanded, a new challenge will arise for (official) seed, food, and feed testing laboratories and enforcement institutions. For detailed consideration, we distinguish between the detection of sequence alterations – regardless of their origin – the identification of the process that generated a specific modification and the identification of a genotype, i.e., an organism produced by genome editing carrying a specific genetic alteration in a known background. This article briefly reviews the existing and upcoming detection and identification strategies (including the use of bioinformatics and statistical approaches) in particular for plants developed with genome editing techniques.

Many food and feed additives result from fermentation of genetically modified (GM) microorganisms. For vitamin B2 (riboflavin), GM Bacillus subtilis production strains have been developed and are often used. The presence of neither the GM strain nor its recombinant DNA is allowed for fermentation products placed on the EU market as food or feed additive. A vitamin B2 product (80% feed grade) imported from China was analysed. Viable B. subtilis cells were identified and DNAs of two bacterial isolates (LHL and LGL) were subjected to three whole genome sequencing (WGS) runs with different devices (MiSeq, 454 or HiSeq system). WGS data revealed the integration of a chloramphenicol resistance gene, the deletion of the endogenous riboflavin (rib) operon and presence of four putative plasmids harbouring rib operons. Event- and construct-specific real-time PCR methods for detection of the GM strain and its putative plasmids in food and feed products have been developed.

Background: Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific DNA sequences introduced into the host genome. Information available regarding the GMOs’ molecular characterization is dispersed and not appropriately organized. For this reason, GMO testing is very challenging and requires more complex screening strategies and decision making schemes, demanding in return the use of efficient bioinformatics tools relying on reliable information. Description: The GMOseek matrix was built as a comprehensive, online open-access tabulated database which provides a reliable, comprehensive and user-friendly overview of 328 GMO events and 247 different genetic elements (status: 18/07/2013). The GMOseek matrix is aiming to facilitate GMO detection from plant origin at different phases of the analysis. It assists in selecting the targets for a screening analysis, interpreting the screening results, checking the occurrence of a screening element in a group of selected GMOs, identifying gaps in the available pool of GMO detection methods, and designing a decision tree. The GMOseek matrix is an independent database with effective functionalities in a format facilitating transferability to other platforms. Data were collected from all available sources and experimentally tested where detection methods and certified reference materials (CRMs) were available. Conclusions: The GMOseek matrix is currently a unique and very valuable tool with reliable information on GMOs from plant origin and their present genetic elements that enables further development of appropriate strategies for GMO detection. It is flexible enough to be further updated with new information and integrated in different applications and platforms.