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

ABSTRACT: 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.

ORGANISM(S): Saccharomyces cerevisiae

PROVIDER: GSE242556 | GEO | 2023/09/21

REPOSITORIES: GEO

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