Evidence map›Paper›PMID 26963725›Full record

ArticlePLoS genetics2016

The Selective Advantage of Synonymous Codon Usage Bias in Salmonella.

Gerrit Brandis, Diarmaid Hughes

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

43 citing papers in PubMed, 69 citations in OpenAlex.

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  20. Comprehensive analysis of coding sequence architecture features and gene expression inPhysiology and molecular biology of plants : an international journal of functional plant biology · 2021
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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.

Gerrit BrandisDepartment of Medical Biochemistry and Microbiology, Uppsala University, Biomedical Center, Uppsala, Sweden.
Diarmaid HughesDepartment of Medical Biochemistry and Microbiology, Uppsala University, Biomedical Center, Uppsala, Sweden.
Uppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The genetic code in mRNA is redundant, with 61 sense codons translated into 20 different amino acids. Individual amino acids are encoded by up to six different codons but within codon families some are used more frequently than others. This phenomenon is referred to as synonymous codon usage bias. The genomes of free-living unicellular organisms such as bacteria have an extreme codon usage bias and the degree of bias differs between genes within the same genome. The strong positive correlation between codon usage bias and gene expression levels in many microorganisms is attributed to selection for translational efficiency. However, this putative selective advantage has never been measured in bacteria and theoretical estimates vary widely. By systematically exchanging optimal codons for synonymous codons in the tuf genes we quantified the selective advantage of biased codon usage in highly expressed genes to be in the range 0.2-4.2 x 10-4 per codon per generation. These data quantify for the first time the potential for selection on synonymous codon choice to drive genome-wide sequence evolution in bacteria, and in particular to optimize the sequences of highly expressed genes. This quantification may have predictive applications in the design of synthetic genes and for heterologous gene expression in biotechnology.

Indexed as

Evolution, MolecularSelection, GeneticAmino AcidsAmino Acid SubstitutionCodonProtein BiosynthesisSalmonellaAmino AcidsCodon

Identifiers

PMID26963725
PMCPMC4786093
OpenAlexW2295737414

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.