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.

转录组包含有关分子、细胞和有机体表型的丰富信息。然而，实验和统计限制限制了单细胞转录组学读数遗传筛查的灵敏度和通量。为了克服这些限制，我们引入了靶向 Perturb-seq (TAP-seq)，这是一种敏感、廉价且独立于平台的方法，重点关注感兴趣基因的单细胞 RNA-seq 覆盖范围，从而按顺序提高遗传筛选的灵敏度和规模的数量级。 TAP-seq 允许在单个实验中对数千个 CRISPR 介导的扰动进行常规分析，检测微弱效应和低表达基因，并将测序要求降低多达 50 倍。我们应用 TAP-seq 为人类基因组 2.5% 内的 1,778 个增强子生成基于扰动的增强子-靶基因图谱。因此，我们表明增强子-靶标关联是由三维接触频率和表观遗传状态共同决定的，从而可以准确预测整个基因组的增强子靶标。此外，我们证明 TAP-seq 可以识别每个细胞仅 100 个测序读数的细胞亚型。