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, University of Washington researchers 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. The researchers used sci-fate to study the cortisol response in >6,000 single cultured cells. From these data, they quantified the dynamics of the cell cycle and glucocorticoid receptor activation, and explored their intersection. Finally, they developed software to infer and analyze cell-state transitions. The researchers anticipate that sci-fate will be broadly applicable to quantitatively characterize transcriptional dynamics in diverse systems.
Availability – Scripts for processing sci-fate sequencing were written in Python and R with code available at https://github.com/JunyueC/sci-fate_analysis.