Evidence map›Paper›PMID 21444810›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2011

Exploring transcription regulation through cell-to-cell variability.

Ruty Rinott, Ariel Jaimovich, Nir Friedman

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

28 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
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  8. Chaperones, Canalization, and Evolution of Animal Forms.International journal of molecular sciences · 2018
    Review
  9. Redundancy, Feedback, and Robustness in theFrontiers in genetics · 2018
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Pervasive robustness in biological systems.Nature reviews. Genetics · 2015
    Review
  15. Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
  16. Article
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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

3 authors at 1 institution in 1 country.

Ruty RinottSchool of Computer Science and Engineering and Institute of Life Sciences, Hebrew University, Jerusalem 91904, Israel.
Ariel Jaimovich
Nir Friedman
Hebrew University of Jerusalem · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Gene Expression Regulation, FungalGenetic VariationTranscription, GeneticFlow CytometryGene DeletionLuminescent ProteinsPhenotypePromoter Regions, GeneticProtein BiosynthesisRed Fluorescent ProteinRibonucleasesRNA, TransferSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsLuminescent ProteinsPOP2 protein, S cerevisiaeRed Fluorescent ProteinRibonucleasesRNA, TransferSaccharomyces cerevisiae Proteins

Identifiers

PMID21444810
PMCPMC3076844
OpenAlexW2153866594

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.