Abstract

CRISPR-Cas9 gene editing has transformed our ability to rapidly interrogate the functional impact of somatic mutations in human cancers. Droplet-based technology enables the analysis of Cas9-introduced gene edits in thousands of single cells. Using this technology, we analyze Ba/F3 cells engineered to express single or multiplexed loss-of-function mutations recurrent in chronic lymphocytic leukemia. Our approach reliably quantifies mutational co-occurrences, zygosity status, and the occurrence of Cas9 edits at single-cell resolution.

Highlights

  • Large-scale genetic sequencing studies of human cancers have identified a number of novel putative disease drivers, whose function is beginning to be understood partly as the result of advances in genetic engineering technologies

  • The genome alterations induced by single or multiple small-guide RNA (sgRNA) were assayed in thousands of individual cells using droplet-based sequestration of single cells, PCR generation of targeted sequencing libraries, and next-generation sequencing (NGS)

  • The Ba/F3 cell line was transduced to constitutively express Cas9, transduced with lentivirus expressing single mCherry-tagged sgRNAs targeting the loci of interest in the murine genome (i.e., Trp53, Atm, Chd2, Samhd1, Mga, Birc3) (Fig. 1a)

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Summary

Introduction

Large-scale genetic sequencing studies of human cancers have identified a number of novel putative disease drivers, whose function is beginning to be understood partly as the result of advances in genetic engineering technologies. In addition to advances in the interrogation of individual cancer drivers, rapidly evolving single-cell sequencing technologies [6,7,8] can be used to define tumor clonal architecture and mechanisms of clonal evolution of cancer cells, with better sensitivity and resolution than conventional bulk techniques. Despite these advances, tools to quantify the relative abundance of CRISPR-introduced disease drivers at the single-cell level, in the context of multiplexed gene editing, are currently lacking. As most cancers arise and propagate due to the complex interaction of multiple disease drivers, these tools would facilitate ten Hacken et al Genome Biology (2020) 21:266 the assessment of the contribution of individual genetic drivers to cellular fitness, their preferential co-occurrences, and the study of clonal evolutionary mechanisms both in cellular and mouse models

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