Accurate Detection and Evaluation of the Gene-Editing Frequency in Plants Using Droplet Digital PCR

Abstract

Gene-editing techniques are becoming powerful tools for modifying target genes in organisms. Although several methods have been reported that detect mutations at targeted loci induced by the CRISPR/Cas system in different organisms, they are semiquantitative and have difficulty in the detection of mutants in processed food samples containing low initial concentrations of DNA and may not accurately quantify editing frequency, especially at very low frequencies in a complex polyploid plant genome. In this study, we developed a duplexed dPCR-based method for the detection and evaluation of gene-editing frequencies in plants. We described the design, performance, accurate quantification, and comparison with other detection systems. The results show that the dPCR-based method is sensitive to different kinds of gene-editing mutations induced by gene-editing. Moreover, the method is applicable to polyploid plants and processed food samples containing low initial concentrations of DNA. Compared with qPCR and NGS-based methods, the dPCR method has a lower limit of detection (LOD) of the editing frequency and a better relationship with the expected editing frequency in detecting the edited region of gene-edited rice samples. Taken together, the duplexed dPCR assay is accurate and precise, and it will be a powerful tool for the detection and evaluation of gene-editing frequencies in plants in gene-editing technology.

Keywords: CRISPR/Cas; accurate detection; dPCR; gene editing; quantity analysis.