Evidence map›Paper›PMID 32452417›Full record

ArticleVirology2020

New insights into the evolutionary features of viral overlapping genes by discriminant analysis.

Angelo Pavesi

Open access · greenAbstract read
In one paragraph

Article in Virology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
5.6field-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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

  1. Pooled it
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  4. Creation of the HIV-1 antisense geneMicrobiology spectrum · 2024
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  19. The diagnostic and prognostic role of myocardial injury biomarkers in hospitalized patients with COVID-19.Clinica chimica acta; international journal of clinical chemistry · 2020
    Article
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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

1 author at 1 institution in 1 country.

Angelo PavesiDepartment of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area Delle Scienze 23/A, I-43124, Parma, Italy. Electronic address: angelo.pavesi@unipr.it.
University of Parma · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Overlapping genes originate by a mechanism of overprinting, in which nucleotide substitutions in a pre-existing frame induce the expression of a de novo protein from an alternative frame. In this study, I assembled a dataset of 319 viral overlapping genes, which included 82 overlaps whose expression is experimentally known and the respective 237 homologs. Principal component analysis revealed that overlapping genes have a common pattern of nucleotide and amino acid composition. Discriminant analysis separated overlapping from non-overlapping genes with an accuracy of 97%. When applied to overlapping genes with known genealogy, it separated ancestral from de novo frames with an accuracy close to 100%. This high discriminant power was crucial to computationally design variants of de novo viral proteins known to possess selective anticancer toxicity (apoptin) or protection against neurodegeneration (X protein), as well as to detect two new potential overlapping genes in the genome of the new coronavirus SARS-CoV-2.

Indexed as

Evolution, MolecularGenes, OverlappingGenes, ViralAlgorithmsAmino Acid SequenceBase SequenceBetacoronavirusComputational BiologyComputer SimulationDiscriminant AnalysisLeast-Squares AnalysisPrincipal Component AnalysisSARS-CoV-2Ancestral reading frameApoptinCodon usageComputer simulationDe novo reading FrameHomologsMultivariate statisticsSARS-CoV-2Therapeutic proteinsVirus evolution

Identifiers

PMID32452417
PMCPMC7157939
OpenAlexW3013726054

What OpenQuestion holds

Textmetadata
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.