Dataset: Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression

External ID

GSE242556

Channels

1

Conditions

35

Description

Cells respond to environmental and developmental stimuli by changing their transcriptomes through both regulation of transcription rate and regulated mRNA decay. These biophysical properties determine the transcriptional state of a cell, but measuring them requires metabolic RNA labeling (e.g. 4-thiouracil pulse-chase) to separate RNA decay from synthesis rates. We approach this problem by sequencing individual Saccharomyces cerevisiae cell transcriptomes by continuously sampling from a population without metabolic labeling. Using this continuous-sampling system, we measure expression in 180,000 individual cells both prior to and in response to rapamycin treatment. The rates of change for each transcript can be calculated on a per-cell basis to give smooth, biologically relevant, estimates of RNA velocity. We then train deep learning models to use this transcriptomic and velocity information to make time-dependent predictions about RNA biophysics, and to infer causal regulatory relationships between transcription factors and their genes.

Categories

chemical stimulus, environmental-sensing

GEO