Literature DB >> 21444810

Exploring transcription regulation through cell-to-cell variability.

Ruty Rinott1, Ariel Jaimovich, Nir Friedman.   

Abstract

The regulation of cellular protein levels is a complex process involving many regulatory mechanisms, each introducing stochastic events, leading to variability of protein levels between isogenic cells. Previous studies have shown that perturbing genes involved in transcription regulation affects the amount of cell-to-cell variability in protein levels, but to date there has been no systematic characterization of variability in expression as a phenotype. In this research, we use single-cell expression levels of two fluorescent reporters driven by two different promoters under a wide range of genetic perturbations in Saccharomyces cerevisiae, to identify proteins that affect variability in the expression of these reporters. We introduce computational methodology to determine the variability caused by each perturbation and distinguish between global variability, which affects both reporters in a coordinated manner (e.g., due to cell size variability), and local variability, which affects the individual reporters independently (e.g., due to stochastic events in transcription initiation). Classifying genes by their variability phenotype (the effect of their deletion on reporter variability) identifies functionally coherent groups, which broadly correlate with the different stages of transcriptional regulation. Specifically, we find that most processes whose perturbation affects global variability are related to protein synthesis, protein transport, and cell morphology, whereas most processes whose perturbations affect local variability are related to DNA maintenance, chromatin regulation, and RNA synthesis. Moreover, we demonstrate that the variability phenotypes of different protein complexes provide insights into their cellular functions. Our results establish the utility of variability phenotype for dissecting the regulatory mechanisms involved in gene expression.

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Year:  2011        PMID: 21444810      PMCID: PMC3076844          DOI: 10.1073/pnas.1013148108

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  30 in total

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  24 in total

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Authors:  Clive G Bowsher; Peter S Swain
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3.  Analytical distribution and tunability of noise in a model of promoter progress.

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Review 4.  The developmental genetics of biological robustness.

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Review 5.  Using variability in gene expression as a tool for studying gene regulation.

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Review 6.  Pervasive robustness in biological systems.

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8.  Promoter-mediated transcriptional dynamics.

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10.  Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters.

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Journal:  Proc Natl Acad Sci U S A       Date:  2014-11-17       Impact factor: 11.205

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