Sci-fate characterizes the dynamics of gene expression in single cells

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • A549 Cells
  • Animals
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation
  • HEK293 Cells
  • Humans
  • Mice
  • NIH 3T3 Cells
  • Single-Cell Analysis / methods*
  • Transcriptome