Evidence map›Paper›PMID 29385509›Full record

ArticleGenome biology and evolution2018

Translational Selection for Speed Is Not Sufficient to Explain Variation in Bacterial Codon Usage Bias.

Saurabh Mahajan, Deepa Agashe

Open access · goldAbstract read
In one paragraph

Article in Genome biology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 15 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.

Saurabh MahajanNational Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, Karnataka, India.
Deepa AgasheNational Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, Karnataka, India.
Tata Institute of Fundamental Research · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing growth rate across bacteria strengthens selection for faster translation, concomitantly increasing the total number of tRNA genes and codon usage bias (CUB: enrichment of specific synonymous codons in highly expressed genes). Typically, enriched codons are translated by tRNAs with higher gene copy numbers (GCN). A model of tRNA-CUB coevolution based on fast growth-associated selection on translational speed recapitulates these patterns. A key untested implication of the coevolution model is that translational selection should favor higher tRNA GCN for more frequently used amino acids, potentially weakening the effect of growth-associated selection on CUB. Surprisingly, we find that CUB saturates with increasing growth rate across γ-proteobacteria, even as the number of tRNA genes continues to increase. As predicted, amino acid-specific tRNA GCN is positively correlated with the usage of corresponding amino acids, but there is no correlation between growth rate associated changes in CUB and amino acid usage. Instead, we find that some amino acids-cysteine and those in the NNA/G codon family-show weak CUB that does not increase with growth rate, despite large variation in the corresponding tRNA GCN. We suggest that amino acid-specific variation in CUB is not explained by tRNA GCN because GCN does not influence the difference between translation times of synonymous codons as expected. Thus, selection on translational speed alone cannot fully explain quantitative variation in overall or amino acid-specific CUB, suggesting a significant role for other functional constraints and amino acid-specific codon features.

Indexed as

CodonProtein BiosynthesisAmino AcidsBacteriaEvolution, MolecularGene DosageGene Expression Regulation, BacterialRNA, BacterialRNA, RibosomalRNA, TransferSelection, GeneticAmino AcidsCodonRNA, BacterialRNA, RibosomalRNA, Transferamino acid usageeffective number of codonsgrowth raterRNA copy numbertRNA gene copy number

Identifiers

PMID29385509
PMCPMC5800062
OpenAlexW2790849690

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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.