Multiplex genotyping method to validate the multiallelic genome editing outcomes using machine learning-assisted long-read sequencing

Abstract

Genome editing induces various on-target mutations. Accurate identification of mutations in founder mice and cell clones is essential to perform reliable genome editing experiments. However, no genotyping method allows the comprehensive analysis of diverse mutations. We developed a genotyping method with an on-target site analysis software named Determine Allele mutations and Judge Intended genotype by Nanopore sequencer (DAJIN) that can automatically identify and classify diverse mutations, including point mutations, deletions, inversions, and knock-in. Our genotyping method with DAJIN can handle approximately 100 samples within a day and may become a new standard for validating genome editing outcomes.