Evidence map›Paper›PMID 39261582›Full record

ArticleScientific reports2024

Genetic analysis of tomato brown rugose fruit virus reveals evolutionary adaptation and codon usage bias patterns.

Abozar Ghorbani

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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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

14 citing papers in PubMed.

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  14. An advanced 10K SNP panel for genotyping tomato (Frontiers in plant science · 2025
    Article
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.

Abozar GhorbaniNuclear Agriculture Research School, Nuclear Science and Technology Research Institute (NSTRI), Karaj, Iran. abghorbany@aeoi.org.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tomato brown rugose fruit virus (ToBRFV) poses a significant threat to tomato production worldwide, prompting extensive research into its genetic diversity, evolutionary dynamics, and adaptive strategies. In this study, we conducted a comprehensive analysis of ToBRFV at the codon level, focusing on codon usage bias, selection pressures, and evolutionary patterns across multiple genes. Our analysis revealed distinct patterns of codon usage bias and selection pressures within the ToBRFV genome, with varying levels of genetic diversity and evolutionary constraints among different genes. We observed a transition/transversion bias of 2.07 across the entire ToBRFV genome, with the movement protein (MP) gene exhibiting the highest transition/transversion bias and SNP density, suggesting potential evolutionary pressures or a higher mutation rate in this gene. Furthermore, our study identified episodic positive selection primarily in the MP gene, highlighting specific codons subject to adaptive changes in response to host immune pressures or environmental factors. Comparative analysis of codon usage bias in the coat protein (CP) and RNA-dependent RNA polymerase (RdRp) genes revealed gene-specific patterns reflecting functional constraints and adaptation to the host's translational machinery. Our findings provide valuable insights into the molecular mechanisms driving ToBRFV evolution and adaptation, with implications for understanding viral pathogenesis, host-virus interactions, and the development of control strategies. Future research directions include further elucidating the functional significance of codon usage biases, exploring the role of episodic positive selection in viral adaptation, and leveraging these insights to inform the development of effective antiviral strategies and crop protection measures.

Indexed as

Codon UsageEvolution, MolecularGenome, ViralSolanum lycopersicumAdaptation, PhysiologicalCodonGenetic VariationPlant DiseasesSelection, GeneticCodonCodon usage biasEvolutionary dynamicsMolecular adaptationSelection pressuresTomato brown rugose fruit virus

Identifiers

PMID39261582
PMCPMC11390899

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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.