Inferring gene regulation from stochastic transcriptional variation across single cells at steady state.

ABSTRACT: Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and te

SUBMITTER: Gupta A 

PROVIDER: S-EPMC9407670 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature