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Gene expression variations are predictive for stochastic noise
Fluctuations in protein abundance among single cells are primarily due to the inherent stochasticity in transcription and translation processes, such stochasticity can often confer phenotypic heterogeneity among isogenic cells. It has been proposed that expression noise can be triggered as an adapta...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3025572/ https://www.ncbi.nlm.nih.gov/pubmed/20860999 http://dx.doi.org/10.1093/nar/gkq844 |
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author | Dong, Dong Shao, Xiaojian Deng, Naiyang Zhang, Zhaolei |
author_facet | Dong, Dong Shao, Xiaojian Deng, Naiyang Zhang, Zhaolei |
author_sort | Dong, Dong |
collection | PubMed |
description | Fluctuations in protein abundance among single cells are primarily due to the inherent stochasticity in transcription and translation processes, such stochasticity can often confer phenotypic heterogeneity among isogenic cells. It has been proposed that expression noise can be triggered as an adaptation to environmental stresses and genetic perturbations, and as a mechanism to facilitate gene expression evolution. Thus, elucidating the relationship between expression noise, measured at the single-cell level, and expression variation, measured on population of cells, can improve our understanding on the variability and evolvability of gene expression. Here, we showed that noise levels are significantly correlated with conditional expression variations. We further demonstrated that expression variations are highly predictive for noise level, especially in TATA-box containing genes. Our results suggest that expression variabilities can serve as a proxy for noise level, suggesting that these two properties share the same underlining mechanism, e.g. chromatin regulation. Our work paves the way for the study of stochastic noise in other single-cell organisms. |
format | Text |
id | pubmed-3025572 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-30255722011-01-24 Gene expression variations are predictive for stochastic noise Dong, Dong Shao, Xiaojian Deng, Naiyang Zhang, Zhaolei Nucleic Acids Res Computational Biology Fluctuations in protein abundance among single cells are primarily due to the inherent stochasticity in transcription and translation processes, such stochasticity can often confer phenotypic heterogeneity among isogenic cells. It has been proposed that expression noise can be triggered as an adaptation to environmental stresses and genetic perturbations, and as a mechanism to facilitate gene expression evolution. Thus, elucidating the relationship between expression noise, measured at the single-cell level, and expression variation, measured on population of cells, can improve our understanding on the variability and evolvability of gene expression. Here, we showed that noise levels are significantly correlated with conditional expression variations. We further demonstrated that expression variations are highly predictive for noise level, especially in TATA-box containing genes. Our results suggest that expression variabilities can serve as a proxy for noise level, suggesting that these two properties share the same underlining mechanism, e.g. chromatin regulation. Our work paves the way for the study of stochastic noise in other single-cell organisms. Oxford University Press 2011-01 2010-09-21 /pmc/articles/PMC3025572/ /pubmed/20860999 http://dx.doi.org/10.1093/nar/gkq844 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Dong, Dong Shao, Xiaojian Deng, Naiyang Zhang, Zhaolei Gene expression variations are predictive for stochastic noise |
title | Gene expression variations are predictive for stochastic noise |
title_full | Gene expression variations are predictive for stochastic noise |
title_fullStr | Gene expression variations are predictive for stochastic noise |
title_full_unstemmed | Gene expression variations are predictive for stochastic noise |
title_short | Gene expression variations are predictive for stochastic noise |
title_sort | gene expression variations are predictive for stochastic noise |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3025572/ https://www.ncbi.nlm.nih.gov/pubmed/20860999 http://dx.doi.org/10.1093/nar/gkq844 |
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