生物
仿形(计算机编程)
计算生物学
基因
遗传学
核糖核酸
RNA序列
转录组
基因表达谱
基因表达
计算机科学
操作系统
作者
Atray Dixit,Oren Parnas,Biyu Li,Jenny Chen,Charles P. Fulco,Livnat Jerby‐Arnon,Nemanja D. Marjanovic,Danielle Dionne,Tyler Burks,Raktima Raychowdhury,Britt Adamson,Thomas M. Norman,Eric S. Lander,Jonathan S. Weissman,Nir Friedman,Aviv Regev
出处
期刊:Cell
[Cell Press]
日期:2016-12-01
卷期号:167 (7): 1853-1866.e17
被引量:1469
标识
DOI:10.1016/j.cell.2016.11.038
摘要
Highlights•Pooled CRISPR screen with scRNA-seq readout•Integrated model of perturbations, single cell phenotypes, and epistatic interactions•Effect of TFs on genes, programs, and states in LPS response in immune cells•Downsampling assessment of feasibility of genome-wide or combinatorial screensSummaryGenetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes—such as transcriptional profiles—at scale. Here, we develop Perturb-seq, combining single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays.Graphical abstract
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