An efficient and adaptable workflow for editing disease-relevant single nucleotide variants using CRISPR/Cas9

Single nucleotide variants are the commonest genetic alterations in the human genome. At least 60,000 have been reported to be associated with disease. The CRISPR/Cas9 system has transformed genetic research, making it possible to edit single nucleotides and study the function of genetic variants in vitro. While significant advances have improved the efficiency of CRISPR/Cas9, the editing of single nucleotides remains challenging. There are two major obstacles: low efficiency of accurate editing and the isolation of these cells from a pool of cells with other editing outcomes. We present data from 85 transfections of induced pluripotent stem cells and an immortalised cell line, comparing the effects of altering CRISPR/Cas9 design and experimental conditions on rates of single nucleotide substitution. We targeted variants in TP53, which predispose to several cancers, and in TBXT which is implicated in the pathogenesis of the bone cancer, chordoma. We describe a scalable and adaptable workflow for single nucleotide editing that incorporates contemporary techniques including Illumina MiSeq sequencing, TaqMan qPCR and digital droplet PCR for screening transfected cells as well as quality control steps to mitigate against common pitfalls. This workflow can be applied to CRISPR/Cas9 and other genome editing systems to maximise experimental efficiency. Simple SummaryCRISPR/Cas9 has revolutionised genetic research. Cas9 generates a double strand break with high efficiency which is repaired by a cells pathways. If a genetic template is provided, the damage can be accurately repaired to introduce a desired genetic alteration. However, accurate repair occurs at a low efficiency and in a small proportion of edited cells, representing the main obstacles in harnessing CRISPRs full potential. Using data from 85 CRISPR experiments for single nucleotide editing, targeting three locations in the human genome that are implicated in predisposition to cancer, we report the effect of different experimental conditions on editing efficiency. We describe current technologies that can be used to streamline the identification of accurately edited cells and synthesise these into an adaptable workflow that can be applied to CRISPR/Cas9 experiments to achieve single nucleotide editing in disease-relevant cell models.