ArticleViruses2025
Neutral Impact of SARS-CoV-2 Coinfection on the Recombination-Driven Evolution of Endemic HCoV-OC43.
Article in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
8 authors.
Funding
Abstract
Knowledge gaps exist on whether SARS-CoV-2 co-infection alters recombination frequency or induces phylogenetic incongruities in endemic β-coronaviruses (HCoV-OC43, HCoV-HKU1), limiting our understanding of cross-species evolution. Among 7213 COVID-19 and 1590 non-COVID-19 acute respiratory cases (2021-2022) screened via multiplex PCR, β-coronavirus co-infections (SARS-CoV-2 + HCoV-OC43/HKU1) and single HCoV-OC43/HKU1 infections were identified. Whole-genome sequencing (Illumina NovaSeq) was performed. Phylogenies were reconstructed using Bayesian inference (MrBayes). Recombination was assessed via Bootscan analysis (SimPlot). Co-infection prevalence was low (0.51%, mainly HCoV-HKU1: 0.28%, HCoV-OC43: 0.11%). HCoV-OC43 diverged into lineage 1 (genotype K) and a novel recombinant lineage 2 (genotypes F/J/G/I segments), exhibiting accelerated evolution. HCoV-HKU1 remained genetically stable (genotype B). Co-infection status did not influence evolutionary outcomes. While SARS-CoV-2 co-infection may favor transmission of endemic HCoVs, their evolution appears driven by population-level selection, not co-infection. HCoV-OC43 underwent recombination-driven diversification, contrasting sharply with HCoV-HKU1's stasis, highlighting distinct evolutionary strategies. Integrated genomic and clinical surveillance is critical for tracking coronavirus adaptation.
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