CRISPR screening with single-cell transcriptome readout establishes a high-throughput method for dissecting gene-regulatory mechanisms
1Vienna, Austria; 2Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
3Max Planck Institute for Informatics, Saarbrücken, Germany
International consortia have mapped the human genome, epigenome, and transcriptome in hundreds of cells types. These maps are being refined by ongoing single-cell sequencing projects, which will eventually give rise to a comprehensive catalog of all cells in the human body. However, we are lagging behind with our ability to assign biological functions to the observed gene regulatory patterns.
CRISPR-based genetic screens have the potential to accelerate functional studies, but current methods have inherent limitations. Widely used pooled screens are restricted to simple readouts including cell proliferation and sortable marker proteins. Arrayed screens allow for comprehensive molecular readouts such as transcriptome profiling, but at much lower throughput.
We combined pooled CRISPR screening with single-cell RNA sequencing into a broadly applicable workflow, directly linking guide RNA expression to transcriptome responses in thousands of individual cells (Dalinger et al., Nature Methods, in press). Our method for CRISPR droplet sequencing (CROP-seq) enables pooled CRISPR screens with single-cell transcriptome resolution.
We expect CROP-seq to be broadly useful for studying biological mechanisms that are difficult to re-duce to a simple readout needed for classical pooled screens. Applied to heterogeneous cell populations and in vivo tissue (e.g., in combination with Cas9-expressing mice), CROP-seq can localize cell-type-specific changes in complex organs and cellular differentiation hierarchies.
Given the increasing throughput of single-cell transcriptomics and the advent of single-cell multi-omics technology (reviewed in: Bock et al. 2016 Trends in Biotechnology), CROP-seq has the potential to provide comprehensive characterization of large CRISPR libraries and constitutes a powerful method for dissecting cellular regulation at scale.
C.B. is supported by an ERC Starting Grant (n° 679146).
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