Metabolomics should be deployed in the identification and characterization of gene‐edited crops

Abstract

Gene-editing techniques are currently revolutionizing biology, allowing far greater precision than previous mutagenic and transgenic approaches. They are becoming applicable to a wide range of plant species and biological processes. Gene editing can rapidly improve a range of crop traits, including disease resistance, abiotic stress tolerance, yield, nutritional quality and additional consumer traits. Unlike transgenic approaches, however, it is not facile to forensically detect gene-editing events at the molecular level, as no foreign DNA exists in the elite line. These limitations in molecular detection approaches are likely to focus more attention on the products generated from the technology than on the process in itself. Rapid advances in sequencing and genome assembly increasingly facilitate genome sequencing as a means of characterizing new varieties generated by gene-editing techniques. Nevertheless, subtle edits such as single base changes or small deletions may be difficult to distinguish from normal variation within a genotype. Given these emerging scenarios, downstream 'omics' technologies reflective of edited affects, such as metabolomics, need to be used in a more prominent manner to fully assess compositional changes in novel foodstuffs. To achieve this goal, metabolomics or 'non-targeted metabolite analysis' needs to make significant advances to deliver greater representation across the metabolome. With the emergence of new edited crop varieties, we advocate: (i) concerted efforts in the advancement of 'omics' technologies, such as metabolomics, and (ii) an effort to redress the use of the technology in the regulatory assessment for metabolically engineered biotech crops.

Broadening the GMO risk assessment in the EU for genome editing technologies in agriculture

“…However, we have shown here that genome editing can cause specific unintended effects and can be used to generate novel genetic combinations that cannot readily be achieved using conventional breeding or mutagenesis techniques. In a more general sense, genome editing utilises SDNs and oligonucleotides, which can be classified as biological mutagens [191]. In contrast to chemical or physical mutagens used in traditional mutagenesis, these agents can interact in a targeted way with the biological mechanisms in the cell, on the level of the genome and/or epigenome.…”

“…These techniques are either being, or could be, further developed to refine their capabilities to be used to analyse GMOs [196][197][198], and in the near future, submission of data from these techniques could be a requirement in support of an application to commercialise all genome-edited organism. Further developments and improvements of metabolomics methods are potentially useful to assist the traceability and labelling of genome-edited organisms [191]. Plants share their habitat with a variety of microbes that include bacteria, fungi, oomycetes and viruses [199][200][201].…”

“…1d). Such examinations will require further development of WGS and 'omics approaches [191], and may be assisted by new analytical tools in the future. Such tools may also facilitate the detection and identification of genome-edited crops and animals, which in turn could assist in the traceability and labelling of GMOs to enable consumer choice [209], and protection of agricultural systems that exclude GMOs, e.g.…”

Obligatory metabolomic profiling of gene‐edited crops is risk disproportionate

“…Even as such challenges are reduced in the future, the unique identification of a gene-edited crop via metabolomics would face the same fundamental challenge as the DNA-based approaches currently used for the unique identification of genetically engineered crops. As acknowledged by Fraser et al (2020), gene editing introduces genetic changes that are often indistinguishable from those that could occur in plants spontaneously or through the application of classical mutagenesis techniques. Thus, although metabolomics could detect metabolic consequences of a genetic change, it cannot uniquely identify the origin of the change, i.e.…”

“…Why focus methods designed to detect unexpected adverse compositional alterations specifically on crop varieties developed by methods least likely to induce unexpected compositional changes? Fraser et al (2020) wrote the following in their article: 'For example, despite the lack of consumer acceptance, it is impressive that the vast body of multidisciplinary outputs have been able to establish first-generation transgenic crops as a safe technology. Given this endorsement of scientific robustness and approaches, is it not sensible to treat the emerging technologies of © 2020 Corteva Agriscience.…”