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Title: Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae

Abstract

Stochasticity is an inherent feature of complex systems with nanoscale structure. In such systems information is represented by small collections of elements (e.g. a few electrons on a quantum dot), and small variations in the populations of these elements may lead to big uncertainties in the information. Unfortunately, little is known about how to work within this inherently noisy environment to design robust functionality into complex nanoscale systems. Here, we look to the biological cell as an intriguing model system where evolution has mediated the trade-offs between fluctuations and function, and in particular we look at the relationships and trade-offs between stochastic and deterministic responses in the gene expression of budding yeast (Saccharomyces cerevisiae). We find gene regulatory arrangements that control the stochastic and deterministic components of expression, and show that genes that have evolved to respond to stimuli (stress) in the most strongly deterministic way exhibit the most noise in the absence of the stimuli. We show that this relationship is consistent with a bursty 2-state model of gene expression, and demonstrate that this regulatory motif generates the most uncertainty in gene expression when there is the greatest uncertainty in the optimal level of gene expression.

Authors:
 [1];  [1];  [2];  [1];  [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
  2. Univ. of Tennessee, Knoxville, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1076448
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Chaos: An Interdisciplinary Journal of Nonlinear Science
Additional Journal Information:
Journal Volume: 20; Journal Issue: 3; Journal ID: ISSN 1054-1500
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; SACCHAROMYCES CEREVISIAE; TRANSCRIPTIONAL PLASTICITY; GENE EXPRESSION NOISE; GENE CIRCUIT FLUCTUATION ANALYSIS; REGULATORY ARCHITECTURE; STRESS RESPONSE

Citation Formats

Dar, R. D., Karig, D. K., Cooke, J. F., Cox, C. D., and Simpson, M. L.. Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae. United States: N. p., 2010. Web. doi:10.1063/1.3486800.
Dar, R. D., Karig, D. K., Cooke, J. F., Cox, C. D., & Simpson, M. L.. Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae. United States. doi:10.1063/1.3486800.
Dar, R. D., Karig, D. K., Cooke, J. F., Cox, C. D., and Simpson, M. L.. Wed . "Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae". United States. doi:10.1063/1.3486800. https://www.osti.gov/servlets/purl/1076448.
@article{osti_1076448,
title = {Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae},
author = {Dar, R. D. and Karig, D. K. and Cooke, J. F. and Cox, C. D. and Simpson, M. L.},
abstractNote = {Stochasticity is an inherent feature of complex systems with nanoscale structure. In such systems information is represented by small collections of elements (e.g. a few electrons on a quantum dot), and small variations in the populations of these elements may lead to big uncertainties in the information. Unfortunately, little is known about how to work within this inherently noisy environment to design robust functionality into complex nanoscale systems. Here, we look to the biological cell as an intriguing model system where evolution has mediated the trade-offs between fluctuations and function, and in particular we look at the relationships and trade-offs between stochastic and deterministic responses in the gene expression of budding yeast (Saccharomyces cerevisiae). We find gene regulatory arrangements that control the stochastic and deterministic components of expression, and show that genes that have evolved to respond to stimuli (stress) in the most strongly deterministic way exhibit the most noise in the absence of the stimuli. We show that this relationship is consistent with a bursty 2-state model of gene expression, and demonstrate that this regulatory motif generates the most uncertainty in gene expression when there is the greatest uncertainty in the optimal level of gene expression.},
doi = {10.1063/1.3486800},
journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
number = 3,
volume = 20,
place = {United States},
year = {2010},
month = {9}
}

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