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Abstract
CRISPR-based gene activation (CRISPRa) is a strategy for upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to a library of 493 gRNAs targeting candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically upregulating intended target genes and no other neighboring genes within 1 Mb, including gRNAs yielding upregulation of six autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes in neurons. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate genes in a cell type-specific manner.
Scalable CRISPRa screening of cis-regulatory elements in non-cancer cell lines has proved challenging. Here, the authors describe a scalable, CRISPR activation screening framework to identify regulatory element-gene pairs in diverse cell types including cancer cells and neurons.
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1 University of Washington, Department of Genome Sciences, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); Seattle Hub for Synthetic Biology, Seattle, USA (GRID:grid.34477.33)
2 University of California, San Francisco, Department of Psychiatry and Behavioral Sciences, Kavli Institute for Fundamental Neuroscience, Weill Institute for Neurosciences, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); University of California, San Francisco, Department of Bioengineering and Therapeutic Sciences, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); University of California, San Francisco, Institute for Human Genetics, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811)
3 University of Washington, Department of Genome Sciences, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657)
4 University of Washington, Department of Genome Sciences, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); Brotman Baty Institute for Precision Medicine, Seattle, USA (GRID:grid.507913.9)
5 University of California, San Francisco, Department of Psychiatry and Behavioral Sciences, Kavli Institute for Fundamental Neuroscience, Weill Institute for Neurosciences, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); University of California, San Francisco, Institute for Human Genetics, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); University of Oxford, Institute of Developmental and Regenerative Medicine, Department of Paediatrics, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)
6 University of California, San Francisco, Department of Bioengineering and Therapeutic Sciences, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); University of California, San Francisco, Institute for Human Genetics, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811)
7 University of Washington, Department of Genome Sciences, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); Seattle Hub for Synthetic Biology, Seattle, USA (GRID:grid.34477.33); Brotman Baty Institute for Precision Medicine, Seattle, USA (GRID:grid.507913.9); Howard Hughes Medical Institute, Seattle, USA (GRID:grid.413575.1) (ISNI:0000 0001 2167 1581); Allen Discovery Center for Cell Lineage Tracing, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657)