GmoDetector: An accurate and efficient GMO identification approach and its applications

Specific detection of genetically modified potatoes containing asparagine synthetase-1 and polyphenol oxidase 5 genes derived from potato

Several genetically modified (GM) potatoes have been developed by introducing endogenous genes derived from potatoes, such as asparagine synthetase-1 (Asn1) and polyphenol oxidase 5 (Ppo5), to improve quality. Therefore, it is difficult to distinguish between GM and non-GM potatoes. In this study, we developed a sequence-specific polymerase chain reaction (PCR) detection method to identify innate and inserted genes. We designed four Asn1 gene-specific primers and eight construct-specific detection primers to evaluate GM potatoes (E12, X17, and Y9) and non-GM crops. Consequently, PCR products corresponding to the original endogenous potato genes and the inserted genes were clearly distinguished and simultaneously identified. In addition, the PCR method demonstrated sufficient sensitivity to identify GM content at levels as low as 0.5%. Thus, this study offers an effective detection method for monitoring or screening approved and unapproved GM potato events using Asn1 and Ppo5 transgenes in foods and feeds.

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

Next-generation-sequencing (NGS) becomes increasingly important for laboratories tasked with the detection of genetically modified organisms (GMOs) in food, feed and seeds. Its implementation into standardized workflows demands reliable intra- and inter-laboratory reproducibility. Here, we analyze the reproducibility of short- and long-read targeted NGS and long-read whole genome sequencing (WGS) data between three independent laboratories. Replicate samples were submitted for sequencing and comparatively analyzed. The targeted-NGS-samples consisted of oil seed rape (OSR) sampled from a commodity shipment spiked with a genome edited (GE) OSR and the WGS-samples consisted of leaf material from the GMOs' parental line. All laboratories delivered highly reproducible high-quality targeted NGS data with little variation. The detection of GMO-related sequences works well regardless of the facility, while the mapping to the complex genome is superior using long read data. Long read WGS is currently not suitable for routine use in enforcement laboratories, due to a large inter-laboratory variation.

Development of an inclusive 580K SNP array and its application for genomic selection and genome-wide association studies in rice

Rice is a globally cultivated crop and is primarily a staple food source for more than half of the world's population. Various single-nucleotide polymorphism (SNP) arrays have been developed and utilized as standard genotyping methods for rice breeding research. Considering the importance of SNP arrays with more inclusive genetic information for GWAS and genomic selection, we integrated SNPs from eight different data resources: resequencing data from the Korean World Rice Collection (KRICE) of 475 accessions, 3,000 rice genome project (3 K-RGP) data, 700 K high-density rice array, Affymetrix 44 K SNP array, QTARO, Reactome, and plastid and GMO information. The collected SNPs were filtered and selected based on the breeder's interest, covering all key traits or research areas to develop an integrated array system representing inclusive genomic polymorphisms. A total of 581,006 high-quality SNPs were synthesized with an average distance of 200 bp between adjacent SNPs, generating a 580 K Axiom Rice Genotyping Chip (580 K _ KNU chip). Further validation of this array on 4,720 genotypes revealed robust and highly efficient genotyping. This has also been demonstrated in genome-wide association studies (GWAS) and genomic selection (GS) of three traits: clum length, heading date, and panicle length. Several SNPs significantly associated with cut-off, -log10 p-value >7.0, were detected in GWAS, and the GS predictabilities for the three traits were more than 0.5, in both rrBLUP and convolutional neural network (CNN) models. The Axiom 580 K Genotyping array will provide a cost-effective genotyping platform and accelerate rice GWAS and GS studies.