Evidence map›Paper›PMID 27536275›Full record

ArticleFrontiers in microbiology2016

Pangenome Evidence for Higher Codon Usage Bias and Stronger Translational Selection in Core Genes of Escherichia coli.

Shixiang Sun, Jingfa Xiao, Huiyong Zhang, Zhang Zhang

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2016. 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
–field-weighted citation impact
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

8 citing papers in PubMed.

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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.

Shixiang SunCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China; University of Chinese Academy of SciencesBeijing, China.
Jingfa XiaoCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.
Huiyong ZhangCollege of Life Sciences, Henan Agricultural University Zhengzhou, China.
Zhang ZhangCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China; BIG Data Center, Beijing Institute of Genomics, Chinese Academy of SciencesBeijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Codon usage bias, as a combined interplay from mutation and selection, has been intensively studied in Escherichia coli. However, codon usage analysis in an E. coli pangenome remains unexplored and the relative importance of mutation and selection acting on core genes and strain-specific genes is unknown. Here we perform comprehensive codon usage analyses based on a collection of multiple complete genome sequences of E. coli. Our results show that core genes that are present in all strains have higher codon usage bias than strain-specific genes that are unique to single strains. We further explore the forces in influencing codon usage and investigate the difference of the major force between core and strain-specific genes. Our results demonstrate that although mutation may exert genome-wide influences on codon usage acting similarly in different gene sets, selection dominates as an important force to shape biased codon usage as genes are present in an increased number of strains. Together, our results provide important insights for better understanding genome plasticity and complexity as well as evolutionary mechanisms behind codon usage bias.

Indexed as

codon usage biascore genesmutationpangenomestrain-specific genestranslational selection

Identifiers

PMID27536275
PMCPMC4971109

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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.