Natural and artificial sources of genetic variation used in crop breeding: A baseline comparator for genome editing

Abstract

Traditional breeding has successfully selected beneficial traits for food, feed, and fibre crops over the last several thousand years. The last century has seen significant technological advancements particularly in marker assisted selection and the generation of induced genetic variation, including over the last few decades, through mutation breeding, genetic modification, and genome editing. While regulatory frameworks for traditional varietal development and for genetic modification with transgenes are broadly established, those for genome editing are lacking or are still evolving in many regions. In particular, the lack of “foreign” recombinant DNA in genome edited plants and that the resulting SNPs or INDELs are indistinguishable from those seen in traditional breeding has challenged development of new legislation. Where products of genome editing and other novel breeding technologies possess no transgenes and could have been generated via traditional methods, we argue that it is logical and proportionate to apply equivalent legislative oversight that already exists for traditional breeding and novel foods. This review analyses the types and the scale of spontaneous and induced genetic variation that can be selected during traditional plant breeding activities. It provides a base line from which to judge whether genetic changes brought about by techniques of genome editing or other reverse genetic methods are indeed comparable to those routinely found using traditional methods of plant breeding.

Reproducibility of next-generation-sequencing-based analysis of a CRISPR/Cas9 genome edited oil seed rape

“…Joint Research Centre., 2021 ), have changed the scenario for detection considerably ( Bortesi and Fischer, 2015 , Grohmann et al, 2019 ). NGTs allow for relatively precise changes of the host’s genetic material, which can impact single bases, potentially not leaving obvious traces of their use ( Bessoltane et al, 2022 , Martínez-Fortún et al, 2022 ). The detection of small changes, like single nucleotide variants (SNVs), while still possible with established PCR systems, ideally utilizes technologies with a much higher resolution.…”