Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq

A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (pooled CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells and present a framework to power biological discovery with the resulting genotype-phenotype map. We use transcriptional phenotypes to predict the function of poorly-characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena - from RNA processing to differentiation. We leverage this ability to systematically identify the genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene function and cellular behavior.

遗传学的核心目标之一是阐明基因型与表型之间的关联关系。高内涵表型筛选技术如Perturb-seq（基于混合CRISPR筛选且搭载单细胞RNA测序读长的技术）可实现大规模并行功能基因组作图，但截至目前其应用规模仍较为有限。本研究开展了全基因组规模的Perturb-seq实验，借助CRISPR干扰（CRISPRi）靶向覆盖所有表达基因，实验样本量超过250万个人类细胞，并基于所得的基因型-表型图谱构建了可助力生物学发现的分析框架。我们利用转录组表型预测功能注释不足的基因的功能，揭示了核糖体生物发生（含CCDC86、ZNF236与SPATA5L1）、转录过程（含C7orf26）以及线粒体呼吸（含TMEM242）的新型调控因子。除注释基因功能外，单细胞转录组表型还可用于深入解析从RNA加工到细胞分化的复杂细胞现象。我们借此系统鉴定了非整倍体的遗传驱动因子与调控后果，并发现了线粒体基因组应激特异性调控的未曾预料到的层级调控机制。本研究构建的信息丰富的基因型-表型图谱，展现了基因功能与细胞行为的多维特征图景。