Insert-seq enables high resolution mapping of genomically integrated DNA using long read technologies. Insert-seq

Comprehensive characterization of genome engineering with viral vectors, Transposons, CRISPR/Cas integrated DNA payloads and other DNA editors remains relevant for their development and safe use in human gene therapy. Current described methods for measuring DNA integration in edited cells rely on short read based technologies. Due to the repetitive nature of the human genome, short read based methods can potentially overlook certain insertion events. We implemented a model that shows significant dependency of read length for accurately resolving insertion sites. Based on that, we developed a method that combines targeted amplification of integrated DNA, UMI-based correction of PCR bias and oxford nanopore long-read sequencing for robust analysis of DNA payload integration in a genome. This method is capable of detecting events occurring up to 0.1% and is suitable for interrogating in-vivo samples. INSERTseq presents a complete handling of all insertions independently of repeat size. The experimental pipeline expands the mappable insertions >10% and repeats larger than the long read size are processed computationally to perform a peak calling in a repeat database. INSERTseq is a simple, cheap and robust method to quantitatively characterize payload integration and their performance in cell culture and mouse derived samples.