Empirical optimization of stem cell differentiation protocols is time consuming, is laborintensive, and typically does not comprehensively interrogate all relevant signaling pathways. Here we describe barcodelet single-cell RNA sequencing (barRNA-seq), which enables systematic exploration of cellular perturbations by tagging individual cells with RNA “barcodelets” to identify them on the basis of the treatments they receive. We apply barRNA-seq to simultaneously manipulate up to seven developmental pathways and study effects on embryonic stem cell (ESC) germ layer specification and mesodermal specification, uncovering combinatorial effects of signaling pathway activation on gene expression. We further develop a data-driven framework for identifying combinatorial signaling perturbations that drive cells toward specific fates, including several annotated in an existing scRNA-seq gastrulation atlas, and use this approach to guide ESC differentiation into a notochord-like population. We expect that barRNA-seq will have broad utility for investigating and understanding how cooperative signaling pathways drive cell fate acquisition.

干细胞分化方案的经验优化是耗时的，费力的，并且通常不会全面询问所有相关的信号传导途径。在这里，我们描述了条形码单细胞RNA测序（barRNA-seq），它可以通过用RNA“条形码”标记单个细胞，从而根据其接受的治疗方法识别它们，从而对细胞扰动进行系统的探索。我们应用barRNA-seq来同时操纵多达7个发育途径，并研究对胚胎干细胞（ESC）胚层规格和中胚层规格的影响，揭示信号通路激活对基因表达的组合作用。我们进一步开发了一种数据驱动的框架，用于识别驱动细胞趋向特定命运的组合信号扰动，包括在现有的scRNA-seq胃气化图集中注释的数种，并使用这种方法指导ESC分化为脊索状种群。我们期望barRNA-seq在研究和了解协同信号通路如何驱动细胞命运获取方面具有广泛的用途。