top of page

Sequencing metabolically labeled transcripts in single cells reveals mRNA turnover strategies
Battich, Nico; Beumer, Joep; Barbanson, Buys de; Krenning, Lenno; Baron, ChloƩ S.; Tanenbaum, Marvin E.; Clevers, Hans; Oudenaarden, Alexander van
Abstract:
RNA life span at single-cell resolution RNA transcripts are an easily accessed representation of gene expression, but we lack a comprehensive view of the life span of RNA within the single cell. Battich et al. developed a method to sequence messenger RNA labeled with 5-ethynyl-uridine (EU) in single cells (scEU-seq), which allows estimation of RNA transcription and degradation rates. When examining intestinal organoid cells, scEU-seq data can be used to discern between transcription and degradation during development, indicating that this method can be applied to better understand the relationship between gene expression and RNA degradation during development. Science, this issue p. 1151 The regulation of messenger RNA levels in mammalian cells can be achieved by the modulation of synthesis and degradation rates. Metabolic RNA-labeling experiments in bulk have quantified these rates using relatively homogeneous cell populations. However, to determine these rates during complex dynamical processes, for instance during cellular differentiation, single-cell resolution is required. Therefore, we developed a method that simultaneously quantifies metabolically labeled and preexisting unlabeled transcripts in thousands of individual cells. We determined synthesis and degradation rates during the cell cycle and during differentiation of intestinal stem cells, revealing major regulatory strategies. These strategies have distinct consequences for controlling the dynamic range and precision of gene expression. These findings advance our understanding of how individual cells in heterogeneous populations shape their gene expression dynamics. Single-cell studies show how individual cells in heterogeneous populations shape their gene expression dynamics. Single-cell studies show how individual cells in heterogeneous populations shape their gene expression dynamics.
Automatic Tags
bottom of page