Literature DB >> 18689455

Quantifying origins of cell-to-cell variations in gene expression.

Julia Rausenberger1, Markus Kollmann.   

Abstract

A general dynamic description of protein synthesis was employed to quantify different sources of gene expression noise in cellular systems. To test our approach, we use time-resolved expression data of individual human cells and, from this information, predict the stationary cell-to-cell variation in protein levels in a clonal population. For three of the four human genes investigated, the cellular variations in expression level are not due to fluctuations in promoter activity or transcript copy number, but are almost exclusively a consequence of long-term variations of gene regulatory factors or the global cellular state. Moreover, we show that a dynamic description is much more reliable to discriminate extrinsic and intrinsic sources of noise than it is on grounds of cell-cycle averaged descriptions. The excellent agreement between the theoretical predictions and the experimentally measured noise strengths shows that a quantitative description of gene expression noise is indeed possible on the basis of idealized stochastic processes.

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Year:  2008        PMID: 18689455      PMCID: PMC2576406          DOI: 10.1529/biophysj.107.127035

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  21 in total

1.  Intrinsic noise in gene regulatory networks.

Authors:  M Thattai; A van Oudenaarden
Journal:  Proc Natl Acad Sci U S A       Date:  2001-07-03       Impact factor: 11.205

2.  Noise in eukaryotic gene expression.

Authors:  William J Blake; Mads KAErn; Charles R Cantor; J J Collins
Journal:  Nature       Date:  2003-04-10       Impact factor: 49.962

3.  Summing up the noise in gene networks.

Authors:  Johan Paulsson
Journal:  Nature       Date:  2004-01-29       Impact factor: 49.962

4.  Intrinsic and extrinsic contributions to stochasticity in gene expression.

Authors:  Peter S Swain; Michael B Elowitz; Eric D Siggia
Journal:  Proc Natl Acad Sci U S A       Date:  2002-09-17       Impact factor: 11.205

5.  Control of stochasticity in eukaryotic gene expression.

Authors:  Jonathan M Raser; Erin K O'Shea
Journal:  Science       Date:  2004-05-27       Impact factor: 47.728

6.  Efficient attenuation of stochasticity in gene expression through post-transcriptional control.

Authors:  Peter S Swain
Journal:  J Mol Biol       Date:  2004-12-03       Impact factor: 5.469

Review 7.  Stochasticity in gene expression: from theories to phenotypes.

Authors:  Mads Kaern; Timothy C Elston; William J Blake; James J Collins
Journal:  Nat Rev Genet       Date:  2005-06       Impact factor: 53.242

8.  Linking stochastic dynamics to population distribution: an analytical framework of gene expression.

Authors:  Nir Friedman; Long Cai; X Sunney Xie
Journal:  Phys Rev Lett       Date:  2006-10-19       Impact factor: 9.161

9.  Gene regulation at the single-cell level.

Authors:  Nitzan Rosenfeld; Jonathan W Young; Uri Alon; Peter S Swain; Michael B Elowitz
Journal:  Science       Date:  2005-03-25       Impact factor: 47.728

10.  Noise propagation in gene networks.

Authors:  Juan M Pedraza; Alexander van Oudenaarden
Journal:  Science       Date:  2005-03-25       Impact factor: 47.728

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  16 in total

1.  Identifying sources of variation and the flow of information in biochemical networks.

Authors:  Clive G Bowsher; Peter S Swain
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-23       Impact factor: 11.205

2.  Using a single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression.

Authors:  Michał Komorowski; Bärbel Finkenstädt; David Rand
Journal:  Biophys J       Date:  2010-06-16       Impact factor: 4.033

3.  Stochastic variation: from single cells to superorganisms.

Authors:  Maria L Kilfoil; Paul Lasko; Ehab Abouheif
Journal:  HFSP J       Date:  2009-10-09

4.  Defining cooperativity in gene regulation locally through intrinsic noise.

Authors:  M Maienschein-Cline; A Warmflash; A R Dinner
Journal:  IET Syst Biol       Date:  2010-11       Impact factor: 1.615

5.  Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

Authors:  Andreas Hilfinger; Johan Paulsson
Journal:  Proc Natl Acad Sci U S A       Date:  2011-07-05       Impact factor: 11.205

6.  Random partitioning of molecules at cell division.

Authors:  Dann Huh; Johan Paulsson
Journal:  Proc Natl Acad Sci U S A       Date:  2011-08-22       Impact factor: 11.205

7.  Stochastic modelling, Bayesian inference, and new in vivo measurements elucidate the debated mtDNA bottleneck mechanism.

Authors:  Iain G Johnston; Joerg P Burgstaller; Vitezslav Havlicek; Thomas Kolbe; Thomas Rülicke; Gottfried Brem; Jo Poulton; Nick S Jones
Journal:  Elife       Date:  2015-06-02       Impact factor: 8.140

8.  Decomposing noise in biochemical signaling systems highlights the role of protein degradation.

Authors:  Michał Komorowski; Jacek Miękisz; Michael P H Stumpf
Journal:  Biophys J       Date:  2013-04-16       Impact factor: 4.033

9.  Contributions of cell growth and biochemical reactions to nongenetic variability of cells.

Authors:  Anne Schwabe; Frank J Bruggeman
Journal:  Biophys J       Date:  2014-07-15       Impact factor: 4.033

10.  Estimating intrinsic and extrinsic noise from single-cell gene expression measurements.

Authors:  Audrey Qiuyan Fu; Lior Pachter
Journal:  Stat Appl Genet Mol Biol       Date:  2016-12-01
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