Targeted Perturb-seq enables genome-scale genetic screens in single cells

被引:132
作者
Schraivogel, Daniel [1 ]
Gschwind, Andreas R. [2 ]
Milbank, Jennifer H. [1 ]
Leonce, Daniel R. [1 ]
Jakob, Petra [1 ]
Mathur, Lukas [1 ]
Korbel, Jan O. [1 ]
Merten, Christoph A. [1 ]
Velten, Lars [1 ,4 ]
Steinmetz, Lars M. [1 ,2 ,3 ]
机构
[1] European Mol Biol Lab EMBL, Genome Biol Unit, Heidelberg, Germany
[2] Stanford Univ, Dept Genet, Sch Med, Stanford, CA 94305 USA
[3] Stanford Genome Technol Ctr, Palo Alto, CA 94304 USA
[4] Barcelona Inst Sci & Technol, Ctr Genom Regulat, Barcelona, Spain
基金
瑞士国家科学基金会; 欧洲研究理事会;
关键词
ENHANCER; HETEROGENEITY; CIRCUITS; PLATFORM; ELEMENTS; PROGRAM; DESIGN; MAP;
D O I
10.1038/s41592-020-0837-5
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Targeted sequencing of perturbation effects offers a sensitive approach to capture genes of interest in CRISPR-mediated screens, enabling genome-scale screens at higher scale and lower cost than whole-transcriptome Perturb-seq. The transcriptome contains rich information on molecular, cellular and organismal phenotypes. However, experimental and statistical limitations constrain sensitivity and throughput of genetic screening with single-cell transcriptomics readout. To overcome these limitations, we introduce targeted Perturb-seq (TAP-seq), a sensitive, inexpensive and platform-independent method focusing single-cell RNA-seq coverage on genes of interest, thereby increasing the sensitivity and scale of genetic screens by orders of magnitude. TAP-seq permits routine analysis of thousands of CRISPR-mediated perturbations within a single experiment, detects weak effects and lowly expressed genes, and decreases sequencing requirements by up to 50-fold. We apply TAP-seq to generate perturbation-based enhancer-target gene maps for 1,778 enhancers within 2.5% of the human genome. We thereby show that enhancer-target association is jointly determined by three-dimensional contact frequency and epigenetic states, allowing accurate prediction of enhancer targets throughout the genome. In addition, we demonstrate that TAP-seq can identify cell subtypes with only 100 sequencing reads per cell.
引用
收藏
页码:629 / +
页数:20
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