Paula A. Giraldo, Hiroshi Shinozuka, German C. Spangenberg, Kevin F. Smith and Noel O. I. Cogan

Front. Plant Sci., 04 February 2021 | https://doi.org/10.3389/fpls.2020.602313

Molecular characterization of genetically modified plants can provide crucial information for the development of detection and identification methods, to comply with traceability, and labeling requirements prior to commercialization. Detailed description of the genetic modification was previously a challenging step in the safety assessment, since it required the use of laborious and time-consuming techniques. In this study an accurate, simple, and fast method was developed for molecular characterization of genetically modified (GM) plants, following a user-friendly workflow for researchers with limited bioinformatic capabilities. Three GM events from a diverse array of crop species—perennial ryegrass, white clover, and canola—were used to test the approach that exploits long-read sequencing by the MinION device, from Oxford Nanopore Technologies. The method delivered a higher degree of resolution of the transgenic events within the host genome than has previously been possible with the standard Illumina short-range sequencing strategies. The flanking sequences, copy number, and presence of backbone sequences, and overall transgene insertion structure were determined for each of the plant genomes, with the additional identification of moderate-sized secondary insertions that would have previously been missed. The proposed workflow takes only about 1 week from DNA extraction to analyzed result, and the method will complement the existing approaches for molecular characterization of GM plants, since it makes the process faster, simpler, and more cost-effective.

See: https://www.frontiersin.org/articles/10.3389/fpls.2020.602313/full

Figure 2: Workflow for the molecular characterization of genetically modified plants, using the MinION device of ONT. Graphic illustration from DNA extraction (left), library preparation and sequencing (middle), and data analysis (right).