Evidence map›Paper›PMID 20444877›Full record

ArticleNucleic acids research2010

Decoding accuracy in eRF1 mutants and its correlation with pleiotropic quantitative traits in yeast.

Gloria H Merritt, Wesley R Naemi, Pierre Mugnier, Helen M Webb, Mick F Tuite, Tobias von der Haar

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 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

24 citing papers in PubMed, 43 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Gloria H MerrittKent Fungal Group and Protein Science Group, School of Biosciences, University of Kent, Canterbury, CT2 7NJ, UK.
Wesley R Naemi
Pierre Mugnier
Helen M Webb
Mick F Tuite
Tobias von der Haar
University of Kent · GB

Funding

Biotechnology and Biological Sciences Research Council 96/G06869Wellcome Trust 075438
6 · The paper itself

Abstract

Translation termination in eukaryotes typically requires the decoding of one of three stop codons UAA, UAG or UGA by the eukaryotic release factor eRF1. The molecular mechanisms that allow eRF1 to decode either A or G in the second nucleotide, but to exclude UGG as a stop codon, are currently not well understood. Several models of stop codon recognition have been developed on the basis of evidence from mutagenesis studies, as well as studies on the evolutionary sequence conservation of eRF1. We show here that point mutants of Saccharomyces cerevisiae eRF1 display significant variability in their stop codon read-through phenotypes depending on the background genotype of the strain used, and that evolutionary conservation of amino acids in eRF1 is only a poor indicator of the functional importance of individual residues in translation termination. We further show that many phenotypes associated with eRF1 mutants are quantitatively unlinked with translation termination defects, suggesting that the evolutionary history of eRF1 was shaped by a complex set of molecular functions in addition to translation termination. We reassess current models of stop-codon recognition by eRF1 in the light of these new data.

Indexed as

Codon, TerminatorPeptide Chain Termination, TranslationalPeptide Termination FactorsPhenotypePoint MutationQuantitative Trait, HeritableSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsCodon, Terminatorpeptide-chain-release factor 3Peptide Termination FactorsSaccharomyces cerevisiae ProteinsSUP45 protein, S cerevisiae

Identifiers

PMID20444877
PMCPMC2938225
OpenAlexW2052010589

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.