Evidence map›Paper›PMID 34751397›Full record

ArticleMolecular biology and evolution2022

Variation in Release Factor Abundance Is Not Needed to Explain Trends in Bacterial Stop Codon Usage.

Alexander T Ho, Laurence D Hurst

Open access · goldAbstract read
In one paragraph

Article in Molecular biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 46% 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

4 citing papers in PubMed, 5 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

2 authors at 1 institution in 1 country.

Alexander T HoMilner Centre for Evolution, University of Bath, Bath, United Kingdom.ORCID 0000-0001-7824-8709
Laurence D HurstMilner Centre for Evolution, University of Bath, Bath, United Kingdom.ORCID 0000-0002-1002-1054
University of Bath · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In bacteria stop codons are recognized by one of two class I release factors (RF1) recognizing TAG, RF2 recognizing TGA, and TAA being recognized by both. Variation across bacteria in the relative abundance of RF1 and RF2 is thus hypothesized to select for different TGA/TAG usage. This has been supported by correlations between TAG:TGA ratios and RF1:RF2 ratios across multiple bacterial species, potentially also explaining why TAG usage is approximately constant despite extensive variation in GC content. It is, however, possible that stop codon trends are determined by other forces and that RF ratios adapt to stop codon usage, rather than vice versa. Here, we determine which direction of the causal arrow is the more parsimonious. Our results support the notion that RF1/RF2 ratios become adapted to stop codon usage as the same trends, notably the anomalous TAG behavior, are seen in contexts where RF1:RF2 ratios cannot be, or are unlikely to be, causative, that is, at 3'untranslated sites never used for translation termination, in intragenomic analyses, and across archaeal species (that possess only one RF1). We conclude that specifics of RF biology are unlikely to fully explain TGA/TAG relative usage. We discuss why the causal relationships for the evolution of synonymous stop codon usage might be different from those affecting synonymous sense codon usage, noting that transitions between TGA and TAG require two-point mutations one of which is likely to be deleterious.

Indexed as

BacteriaCodon, TerminatorCodon UsagePeptide Termination FactorsBase CompositionCodon, TerminatorPeptide Termination Factorsmolecular evolutionrelease factorstop codonstranslation termination

Identifiers

PMID34751397
PMCPMC8789281
OpenAlexW3212616219

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.