Evidence map›Paper›PMID 35801104›Full record

ArticleFrontiers in microbiology2022

Codon Usage of Hepatitis E Viruses: A Comprehensive Analysis.

Bingzhe Li, Han Wu, Ziping Miao, Linjie Hu, Lu Zhou, Yihan Lu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
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  4. Comprehensive analysis of codon bias in 13Frontiers in microbiology · 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

6 authors at 2 institutions in 1 country.

Bingzhe LiDepartment of Epidemiology, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Han WuDepartment of Epidemiology, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Ziping MiaoInstitute of Communicable Diseases Prevention and Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
Linjie HuDepartment of Epidemiology, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Lu ZhouDepartment of Epidemiology, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Yihan LuDepartment of Epidemiology, Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
Fudan University · CNZhejiang Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatitis E virus (HEV) is an emerging zoonotic pathogen with multiple species and genotypes, which may be classified into human, animal, and zoonotic HEV. Codon usage bias of HEV remained unclear. This study aims to characterize the codon usage of HEV and elucidate the main drivers influencing the codon usage bias. A total of seven HEV genotypes, HEV-1 (human HEV), HEV-3 and HEV-4 (zoonotic HEV), HEV-8, HEV-B, HEV-C1, and HEV-C2 (emerging animal HEV), were included in the study. Complete coding sequences, ORF1, ORF2, and ORF3, were accordingly obtained in the GenBank. Except for HEV-8, the other six genotypes tended to use codons ending in G/C. Based on the analysis of relatively synonymous codon usage (RSCU) and principal component analysis (PCA), codon usage bias was determined for HEV genotypes. Codon usage bias differed widely across human, zoonotic, and animal HEV genotypes; furthermore, it varied within certain genotypes such as HEV-4, HEV-8, and HEV-C1. In addition, dinucleotide abundance revealed that HEV was affected by translation selection to form a unique dinucleotide usage pattern. Moreover, parity rule 2 analysis (PR2), effective codon number (ENC)-plot, and neutrality analysis were jointly performed. Natural selection played a leading role in forming HEV codon usage bias, which was predominant in HEV-1, HEV-3, HEV-B and HEV-C1, while affected HEV-4, HEV-8, and HEV-C2 in combination with mutation pressure. Our findings may provide insights into HEV evolution and codon usage bias.

Indexed as

codon usageeffective codon numberhepatitis E virusrelatively synonymous codon usagezoonotic pathogen

Identifiers

PMID35801104
PMCPMC9253588
OpenAlexW4283215576

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.