Evidence map›Paper›PMID 20211838›Full record

ArticleNucleic acids research2010

Tuning and controlling gene expression noise in synthetic gene networks.

Kevin F Murphy, Rhys M Adams, Xiao Wang, Gábor Balázsi, James J Collins

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 1 synthesis or guideline pooled it, 148 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. The switch-liker's guide to plant synthetic gene circuits.The Plant journal : for cell and molecular biology · 2025
    Review
  4. Article
  5. Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Reduction in gene expression noise by targeted increase in accessibility at gene loci.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  14. Article
  15. 3Genome biology · 2021
    Article
  16. Article
  17. Article
  18. Making Sense of Computational Psychiatry.The international journal of neuropsychopharmacology · 2020
    Review
  19. Article
  20. Article

20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Kevin F MurphyDepartment of Biomedical Engineering, Howard Hughes Medical Institute, Center for BioDynamics & Center for Advanced Biotechnology, Department of Biology, Boston University, Boston, MA 02215, USA.
Rhys M Adams
Xiao Wang
Gábor Balázsi
James J Collins
Harvard University · USHoward Hughes Medical Institute · USThe University of Texas MD Anderson Cancer Center · US

Funding

Connecting the selection of noisy gene expression deviants to genetic evolutionDP2OD006481 · OD · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI BALAZSI, GABOR · 2009 to 2009
$2.3M
Howard Hughes Medical InstituteNIH HHS 1DP2 OD006481-01NIH HHS DP1 OD00344
6 · The paper itself

Abstract

Synthetic gene networks can be used to control gene expression and cellular phenotypes in a variety of applications. In many instances, however, such networks can behave unreliably due to gene expression noise. Accordingly, there is a need to develop systematic means to tune gene expression noise, so that it can be suppressed in some cases and harnessed in others, e.g. in cellular differentiation to create population-wide heterogeneity. Here, we present a method for controlling noise in synthetic eukaryotic gene expression systems, utilizing reduction of noise levels by TATA box mutations and noise propagation in transcriptional cascades. Specifically, we introduce TATA box mutations into promoters driving TetR expression and show that these mutations can be used to effectively tune the noise of a target gene while decoupling it from the mean, with negligible effects on the dynamic range and basal expression. We apply mathematical and computational modeling to explain the experimentally observed effects of TATA box mutations. This work, which highlights some important aspects of noise propagation in gene regulatory cascades, has practical implications for implementing gene expression control in synthetic gene networks.

Indexed as

Gene Expression RegulationGene Regulatory NetworksGenes, SyntheticTranscription, GeneticMutationSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsTATA BoxTrans-ActivatorsGAL10 protein, S cerevisiaeSaccharomyces cerevisiae ProteinsTrans-Activators

Identifiers

PMID20211838
PMCPMC2860118
OpenAlexW2111165959

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.