Evidence map›Paper›PMID 22974057›Full record

ArticleBiology direct2012

Stop codons in bacteria are not selectively equivalent.

Inna S Povolotskaya, Fyodor A Kondrashov, Alice Ledda, Peter K Vlasov

Open access · goldAbstract read
In one paragraph

Article in Biology direct, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

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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

20 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Review
  3. StORF-Reporter: finding genes between genes.Nucleic acids research · 2023
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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

4 authors at 2 institutions in 2 countries.

Inna S PovolotskayaBioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG) and UPF, 88 Dr, Aiguader, Barcelona 08003, Spain.
Fyodor A Kondrashov
Alice Ledda
Peter K Vlasov
Centre for Genomic Regulation · ESInserm · FR

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

backgroundThe evolution and genomic stop codon frequencies have not been rigorously studied with the exception of coding of non-canonical amino acids. Here we study the rate of evolution and frequency distribution of stop codons in bacterial genomes.

resultsWe show that in bacteria stop codons evolve slower than synonymous sites, suggesting the action of weak negative selection. However, the frequency of stop codons relative to genomic nucleotide content indicated that this selection regime is not straightforward. The frequency of TAA and TGA stop codons is GC-content dependent, with TAA decreasing and TGA increasing with GC-content, while TAG frequency is independent of GC-content. Applying a formal, analytical model to these data we found that the relationship between stop codon frequencies and nucleotide content cannot be explained by mutational biases or selection on nucleotide content. However, with weak nucleotide content-dependent selection on TAG, -0.5 < Nes < 1.5, the model fits all of the data and recapitulates the relationship between TAG and nucleotide content. For biologically plausible rates of mutations we show that, in bacteria, TAG stop codon is universally associated with lower fitness, with TAA being the optimal for G-content < 16% while for G-content > 16% TGA has a higher fitness than TAG.

conclusionsOur data indicate that TAG codon is universally suboptimal in the bacterial lineage, such that TAA is likely to be the preferred stop codon for low GC content while the TGA is the preferred stop codon for high GC content. The optimization of stop codon usage may therefore be useful in genome engineering or gene expression optimization applications.

Indexed as

Evolution, MolecularGene Expression Regulation, BacterialGenome, BacterialBacteriaBase CompositionCodon, TerminatorModels, GeneticMutationCodon, Terminator

Identifiers

PMID22974057
PMCPMC3549826
OpenAlexW2129452435

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.