Detection and Identification of Genome Editing in Plants: Challenges and Opportunities

Grohmann, Lutz; Keilwagen, Jens GND; Duensing, Nina GND; Dagand, Emilie; Hartung, Frank; Wilhelm, Ralf GND; Bendiek, Joachim GND; Sprink, Thorben GND

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.

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Grohmann, Lutz / Keilwagen, Jens / Duensing, Nina / et al: Detection and Identification of Genome Editing in Plants: Challenges and Opportunities. 2019.

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