Evidence map›Paper›PMID 21098719›Full record

ArticleGenetics2011

Inferences about the distribution of dominance drawn from yeast gene knockout data.

Aneil F Agrawal, Michael C Whitlock

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers.

0numbers the graph read from it
0cells of the map it votes in
118citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

118 citing papers in PubMed, 268 citations in OpenAlex.

  1. Article
  2. Dynamics of mutators of arbitrary dominance in humans.bioRxiv : the preprint server for biology · 2026
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  11. Review
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  13. Accessible, realistic genome simulation with selection using stdpopsim.bioRxiv : the preprint server for biology · 2025
    Article
  14. Whole-genome duplication increases genetic diversity and load in outcrossingProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  15. Article
  16. Article
  17. The distribution of highly deleterious variants across human ancestry groups.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  18. Article
  19. Article
  20. Article

58 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

2 authors at 2 institutions in 1 country.

Aneil F AgrawalDepartment of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario M5S 3B2, Canada. a.agrawal@utoronto.ca
Michael C Whitlock
University of British Columbia · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data from several thousand knockout mutations in yeast (Saccharomyces cerevisiae) were used to estimate the distribution of dominance coefficients. We propose a new unbiased likelihood approach to measuring dominance coefficients. On average, deleterious mutations are partially recessive, with a mean dominance coefficient ~0.2. Alleles with large homozygous effects are more likely to be more recessive than are alleles of weaker effect. Our approach allows us to quantify, for the first time, the substantial variance and skew in the distribution of dominance coefficients. This heterogeneity is so great that many population genetic processes analyses based on the mean dominance coefficient alone will be in substantial error. These results are applied to the debate about various mechanisms for the evolution of dominance, and we conclude that they are most consistent with models that depend on indirect selection on homeostatic gene expression or on the ability to perform well under periods of high demand for a protein.

Indexed as

Genes, DominantGene Knockout TechniquesGenetics, PopulationModels, GeneticMutationSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSaccharomyces cerevisiae Proteins

Identifiers

PMID21098719
PMCPMC3030496
OpenAlexW1980722139

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.