Literature DB >> 18719112

Information flow and optimization in transcriptional regulation.

Gasper Tkacik1, Curtis G Callan, William Bialek.   

Abstract

In the simplest view of transcriptional regulation, the expression of a gene is turned on or off by changes in the concentration of a transcription factor (TF). We use recent data on noise levels in gene expression to show that it should be possible to transmit much more than just one regulatory bit. Realizing this optimal information capacity would require that the dynamic range of TF concentrations used by the cell, the input/output relation of the regulatory module, and the noise in gene expression satisfy certain matching relations, which we derive. These results provide parameter-free, quantitative predictions connecting independently measurable quantities. Although we have considered only the simplified problem of a single gene responding to a single TF, we find that these predictions are in surprisingly good agreement with recent experiments on the Bicoid/Hunchback system in the early Drosophila embryo and that this system achieves approximately 90% of its theoretical maximum information transmission.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18719112      PMCID: PMC2527900          DOI: 10.1073/pnas.0806077105

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


  27 in total

1.  Adaptive rescaling maximizes information transmission.

Authors:  N Brenner; W Bialek; R de Ruyter van Steveninck
Journal:  Neuron       Date:  2000-06       Impact factor: 17.173

2.  Regulation of noise in the expression of a single gene.

Authors:  Ertugrul M Ozbudak; Mukund Thattai; Iren Kurtser; Alan D Grossman; Alexander van Oudenaarden
Journal:  Nat Genet       Date:  2002-04-22       Impact factor: 38.330

3.  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

4.  Stochastic gene expression in a single cell.

Authors:  Michael B Elowitz; Arnold J Levine; Eric D Siggia; Peter S Swain
Journal:  Science       Date:  2002-08-16       Impact factor: 47.728

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.  A gradient of bicoid protein in Drosophila embryos.

Authors:  W Driever; C Nüsslein-Volhard
Journal:  Cell       Date:  1988-07-01       Impact factor: 41.582

7.  Positional information and the spatial pattern of cellular differentiation.

Authors:  L Wolpert
Journal:  J Theor Biol       Date:  1969-10       Impact factor: 2.691

8.  A simple coding procedure enhances a neuron's information capacity.

Authors:  S Laughlin
Journal:  Z Naturforsch C Biosci       Date:  1981 Sep-Oct

9.  Information capacity of genetic regulatory elements.

Authors:  Gasper Tkacik; Curtis G Callan; William Bialek
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2008-07-21

10.  Detailed map of a cis-regulatory input function.

Authors:  Y Setty; A E Mayo; M G Surette; U Alon
Journal:  Proc Natl Acad Sci U S A       Date:  2003-06-12       Impact factor: 11.205

View more
  101 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.  Statistical method for revealing form-function relations in biological networks.

Authors:  Andrew Mugler; Boris Grinshpun; Riley Franks; Chris H Wiggins
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-23       Impact factor: 11.205

3.  Information-optimal transcriptional response to oscillatory driving.

Authors:  Andrew Mugler; Aleksandra M Walczak; Chris H Wiggins
Journal:  Phys Rev Lett       Date:  2010-07-29       Impact factor: 9.161

4.  Information processing in the adaptation of Saccharomyces cerevisiae to osmotic stress: an analysis of the phosphorelay system.

Authors:  Friedemann Uschner; Edda Klipp
Journal:  Syst Synth Biol       Date:  2014-04-19

5.  Comprehensive analysis reveals how single nucleotides contribute to noncoding RNA function in bacterial quorum sensing.

Authors:  Steven T Rutherford; Julie S Valastyan; Thibaud Taillefumier; Ned S Wingreen; Bonnie L Bassler
Journal:  Proc Natl Acad Sci U S A       Date:  2015-10-19       Impact factor: 11.205

6.  Information Thermodynamics for Time Series of Signal-Response Models.

Authors:  Andrea Auconi; Andrea Giansanti; Edda Klipp
Journal:  Entropy (Basel)       Date:  2019-02-14       Impact factor: 2.524

7.  A stochastic spectral analysis of transcriptional regulatory cascades.

Authors:  Aleksandra M Walczak; Andrew Mugler; Chris H Wiggins
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-07       Impact factor: 11.205

8.  Statistical mechanics of Monod-Wyman-Changeux (MWC) models.

Authors:  Sarah Marzen; Hernan G Garcia; Rob Phillips
Journal:  J Mol Biol       Date:  2013-03-14       Impact factor: 5.469

9.  Spectral solutions to stochastic models of gene expression with bursts and regulation.

Authors:  Andrew Mugler; Aleksandra M Walczak; Chris H Wiggins
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-10-20

10.  Optimizing information flow in small genetic networks.

Authors:  Gasper Tkacik; Aleksandra M Walczak; William Bialek
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-09-29
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.