Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA.
Nat Biotechnol. 2020 Aug;38(8):980-988. doi: 10.1038/s41587-020-0480-9. Epub 2020 Apr 13.
Gene expression programs change over time, differentiation and development, and in response to stimuli. However, nearly all techniques for profiling gene expression in single cells do not directly capture transcriptional dynamics. In the present study, we present a method for combined single-cell combinatorial indexing and messenger RNA labeling (sci-fate), which uses combinatorial cell indexing and 4-thiouridine labeling of newly synthesized mRNA to concurrently profile the whole and newly synthesized transcriptome in each of many single cells. We used sci-fate to study the cortisol response in >6,000 single cultured cells. From these data, we quantified the dynamics of the cell cycle and glucocorticoid receptor activation, and explored their intersection. Finally, we developed software to infer and analyze cell-state transitions. We anticipate that sci-fate will be broadly applicable to quantitatively characterize transcriptional dynamics in diverse systems.
基因表达程序随时间、分化和发育而变化,并对刺激作出反应。然而,几乎所有用于在单细胞中分析基因表达的技术都不能直接捕获转录动力学。在本研究中,我们提出了一种组合单细胞组合索引和信使 RNA 标记(sci-fate)的方法,该方法使用组合细胞索引和新合成的 mRNA 的 4-硫代尿苷标记,同时在许多单个细胞中的每个细胞中分析整个和新合成的转录组。我们使用 sci-fate 来研究>6000 个培养的单细胞中的皮质醇反应。从这些数据中,我们定量描述了细胞周期和糖皮质激素受体激活的动态,并探讨了它们的交集。最后,我们开发了软件来推断和分析细胞状态的转变。我们预计 sci-fate 将广泛适用于定量描述不同系统中的转录动力学。