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

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 upre...

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Autores principales: Mellis, Ian A., Bodkin, Nicholas, Goyal, Yogesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462021/
https://www.ncbi.nlm.nih.gov/pubmed/37645989
http://dx.doi.org/10.1101/2023.08.14.553318
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author Mellis, Ian A.
Bodkin, Nicholas
Goyal, Yogesh
author_facet Mellis, Ian A.
Bodkin, Nicholas
Goyal, Yogesh
author_sort Mellis, Ian A.
collection PubMed
description 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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spelling pubmed-104620212023-08-29 Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells Mellis, Ian A. Bodkin, Nicholas Goyal, Yogesh bioRxiv Article 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. Cold Spring Harbor Laboratory 2023-08-14 /pmc/articles/PMC10462021/ /pubmed/37645989 http://dx.doi.org/10.1101/2023.08.14.553318 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Mellis, Ian A.
Bodkin, Nicholas
Goyal, Yogesh
Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells
title Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells
title_full Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells
title_fullStr Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells
title_full_unstemmed Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells
title_short Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells
title_sort prevalence of and gene regulatory constraints on transcriptional adaptation in single cells
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462021/
https://www.ncbi.nlm.nih.gov/pubmed/37645989
http://dx.doi.org/10.1101/2023.08.14.553318
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