A single-cell approach to cancer mutation discovery and CRISPR phenotypic modelling

We developed a new single-cell approach to identify disease-related mutations from individual cells and then genome engineer these mutations into cellular experimental systems for further biological characterization. To identify mutations, we used a targeted, long-read sequencing approach on single cells to identify cancer somatic mutations and even gene fusion rearrangements. This involved leveraging nanopore long-read sequences that covered entire transcripts of cancer genes. Next, we used CRISPR based-editor technology to introduce specific cancer mutations into single cells on a large scale. We directly engineered cancer mutations among different single cells and then determined their transcriptional phenotype with integrated nanopore long- and short-read sequencing. In summary, our work demonstrates a direct and highly scalable method for identifying, modelling, and functionally assessing cancer mutation phenotype at single-cell resolution.
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