Allelic correlation is a marker of trade-offs between barriers to transmission of expression variability and signal responsiveness in genetic networks

Boe, Ryan H; Ayyappan, Vinay; Schuh, Lea; Raj, Arjun

doi:10.1016/j.cels.2022.10.008

Cited by 4 publications

(2 citation statements)

References 49 publications

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“…For a gene to respond quickly to a signal, it must be sensitized to incoming signals, which may inherently drive higher levels of noise. A noise-robustness tradeoff has been proposed previously when observing changes in gene expression over developmental time in drosophila (Sigalova et al, 2020) and in a mathematical framework that showed variations are necessary for a gene’s responsiveness (Boe et al, 2022). However, a regulatory mechanism has not been found.…”

Section: Discussionmentioning

confidence: 99%

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Ginley-Hidinger

Abewe

Osborne

et al. 2023

Preprint

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Cis-Regulatory Elements (CREs) control transcription levels, temporal dynamics, and cell-cell variation — often referred to as transcriptional noise. However, the combination of regulatory proteins and epigenetic features necessary to control different transcription attributes is not fully understood. Here, single-cell RNA-seq (scRNA-seq) is conducted during a time course of estrogen treatment to identify genomic predictors of expression timing and noise. We find that genes associated with multiple active enhancers exhibit faster temporal responses. Synthetic modulation of enhancer activity verifies that activating enhancers accelerates expression responses, while inhibiting enhancers results in a more gradual response. Noise is controlled by a balance of promoter and enhancer activity. Active promoters are found at genes with low noise levels, whereas active enhancers are associated with high noise. Finally, we observe that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise levels. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

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Section: Discussionmentioning

confidence: 99%

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Ginley-Hidinger

Abewe

Osborne

et al. 2023

Preprint

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“…In principle, our bioinformatic pipeline can be generalized to include other animal systems to reveal both species-specific and universal gene targets displaying transcriptional compensation 14,15 . Lastly, simulations of gene regulatory networks are inherently simplifying, and while we specified reactions and assumptions that have been shown to model small numbers of interacting genes well 59,60,70 , these models do not account for all regulatory interactions in a cell explicitly 32,54,71 .…”

Section: Discussionmentioning

confidence: 99%

Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells

Mellis

Bodkin²,

Goyal³

2023

Preprint

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Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene can trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, to date, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and contexts. Moreover, how the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear. Here we combine computational analysis of existing datasets with stochastic mathematical modeling and machine learning to uncover the widespread prevalence of transcriptional adaptation in mammalian systems and the diverse single-cell manifestations of minimal compensatory gene networks. Regulon gene expression analysis of a pooled single-cell genetic perturbation dataset recapitulates our model predictions. Our integrative approach uncovers several putative hits-genes demonstrating possible transcriptional adaptation-to follow up on experimentally, and provides a formal quantitative framework to test and refine models of transcriptional adaptation.

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Cis-regulatory control of transcriptional timing and noise in response to estrogen

Ginley-Hidinger,

Abewe,

Osborne

et al. 2024

Cell Genomics

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Allelic correlation is a marker of trade-offs between barriers to transmission of expression variability and signal responsiveness in genetic networks

Cited by 4 publications

References 49 publications

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells

Cis-regulatory control of transcriptional timing and noise in response to estrogen

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