Evidence map›Paper›PMID 26669443›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2015

Effects of DNA replication on mRNA noise.

Joseph R Peterson, John A Cole, Jingyi Fei, Taekjip Ha, Zaida A Luthey-Schulten

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
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

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Analytical distributions for detailed models of stochastic gene expression in eukaryotic cells.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
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.

Joseph R PetersonDepartment of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801;
John A ColeDepartment of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801;
Jingyi FeiCarl Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Carl Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801;
Taekjip HaDepartment of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Carl Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Howard Hughes Medical Institute, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Howard Hughes Medical Institute, University of Illinois at Urbana-Champaign, Urbana, IL 61801;
Zaida A Luthey-SchultenDepartment of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Carl Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, IL 61801; zan@illinois.edu.

Funding

WHOLE CELL SIMULATIONP41GM104601 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI TAJKHORSHID, EMAD · 2012 to 2021
$19.0M
Quantitative Imaging and Modeling of Regulation by Bacterial Small RNAR01GM112659 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI HA, TAEKJIP, LUTHEY-SCHULTEN, ZAIDA · 2015 to 2018
$1.1M
NIGMS NIH HHS 9 P41 GM104601-23NIGMS NIH HHS GM112659NIGMS NIH HHS P41 GM104601NIGMS NIH HHS R01 GM112659
6 · The paper itself

Abstract

There are several sources of fluctuations in gene expression. Here we study the effects of time-dependent DNA replication, itself a tightly controlled process, on noise in mRNA levels. Stochastic simulations of constitutive and regulated gene expression are used to analyze the time-averaged mean and variation in each case. The simulations demonstrate that to capture mRNA distributions correctly, chromosome replication must be realistically modeled. Slow relaxation of mRNA from the low copy number steady state before gene replication to the high steady state after replication is set by the transcript's half-life and contributes significantly to the shape of the mRNA distribution. Consequently both the intrinsic kinetics and the gene location play an important role in accounting for the mRNA average and variance. Exact analytic expressions for moments of the mRNA distributions that depend on the DNA copy number, gene location, cell doubling time, and the rates of transcription and degradation are derived for the case of constitutive expression and subsequently extended to provide approximate corrections for regulated expression and RNA polymerase variability. Comparisons of the simulated models and analytical expressions to experimentally measured mRNA distributions show that they better capture the physics of the system than previous theories.

Indexed as

AlgorithmsDNA ReplicationGene Expression RegulationModels, GeneticDNADNA-Directed RNA PolymerasesGene DosageKineticsRNA, MessengerStochastic ProcessesTime FactorsDNADNA-Directed RNA PolymerasesRNA, Messengeranalytical solutionschromosome replicationmaster equationstochastic gene expressionstochastic simulation

Identifiers

PMID26669443
PMCPMC4702981

What OpenQuestion holds

Textmetadata
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.