2022
DOI: 10.1073/pnas.2207392119
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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 transcri… Show more

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Cited by 23 publications
(24 citation statements)
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References 108 publications
(133 reference statements)
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“…These observations are consistent with a model of active regulation of multiple related genes each controlled by cis regulatory elements for the same transcription factors with "on" and "off" states [9]. Until recently, studying the distribution of gene expression, in particular the joint distribution of multiple genes, has been technologically challenging and has been mostly pursued in model organisms that can be genetically modified [10,11].…”
Section: Introductionsupporting
confidence: 80%
“…These observations are consistent with a model of active regulation of multiple related genes each controlled by cis regulatory elements for the same transcription factors with "on" and "off" states [9]. Until recently, studying the distribution of gene expression, in particular the joint distribution of multiple genes, has been technologically challenging and has been mostly pursued in model organisms that can be genetically modified [10,11].…”
Section: Introductionsupporting
confidence: 80%
“…This feature makes GM18278 the only few available cell types for us to investigate large-scale regulatory mechanisms in burst kinetics. Studies with similar ideas have been performed in K562 (Gupta et al, 2022). Secondly, even though our study requires isogenic cell types, it is still applicable for other single-cell RNA-seq data by isolating individual cell types.…”
Section: Discussionmentioning
confidence: 99%
“…In addition, despite multiple studies that have investigated how gene regulatory factors (transcriptional factors, histone acetylation, DNA methylation, etc.) modulate transcriptional burst, the results are inconsistent among different cell lines and species, probably due to both cell type-specific effects and technical variation (Sánchez and Kondev 2008; Singh et al 2010; Dar et al 2012; Fukaya et al 2016; Faure et al 2017; Nicolas et al 2018; Li et al 2018; Larsson et al 2019; Bartman et al 2019; Dobrinic et al 2021; Gupta et al 2022). Therefore, a transcriptome-wide and unbiased investigation of how regulatory factors modulate transcriptional bursts in human cells is needed to understand how it influences gene expression at the cell population level and further propagates to tissue or organism-level phenotypes.…”
Section: Introductionmentioning
confidence: 99%
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