Evidence map›Paper›PMID 34209097›Full record

ArticleViruses2021

Mutation Profiles, Glycosylation Site Distribution and Codon Usage Bias of Human Papillomavirus Type 16.

Wei Liu, Junhua Li, Hongli Du, Zhihua Ou

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2021. 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
1.1field-weighted citation impact, top 23% 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, 10 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

4 authors at 2 institutions in 1 country.

Wei LiuSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou 510000, China.ORCID 0000-0002-5160-1768
Junhua LiSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou 510000, China.ORCID 0000-0001-6784-1873
Hongli DuSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou 510000, China.
Zhihua OuBGI-Shenzhen, Shenzhen 518083, China.ORCID 0000-0002-1479-9007
BGI Group (China) · CNSouth China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human papillomavirus type 16 (HPV16) is the most prevalent HPV type causing cervical cancers. Herein, using 1597 full genomes, we systemically investigated the mutation profiles, surface protein glycosylation sites and the codon usage bias (CUB) of HPV16 from different lineages and sublineages. Multiple lineage- or sublineage-conserved mutation sites were identified. Glycosylation analysis showed that HPV16 lineage D contained the highest number of different glycosylation sites from lineage A in both L1 and L2 capsid proteins, which might lead to their antigenic distances between the two lineages. CUB analysis showed that the HPV16 open reading frames (ORFs) preferred codons ending with A/T. The CUB of HPV16 ORFs was mainly affected by natural selection except for E1, E5 and L2. HPV16 only shared some of the preferred codons with humans, which might help reduce competition in translational resources. These findings increase our understanding of the heterogeneity between HPV16 lineages and sublineages, and the adaptation mechanism of HPV in human cells. In summary, this study might facilitate HPV classification and improve vaccine development and application.

Indexed as

Codon UsageGenome, ViralMutationDNA, ViralFemaleGlycosylationHuman papillomavirus 16HumansOpen Reading FramesPapillomavirus InfectionsVaccine DevelopmentDNA, Viralcodon usage biasglycosylationHPV16lineage and sublineagemutation

Identifiers

PMID34209097
PMCPMC8310365
OpenAlexW3174881356

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.