ReviewMedical review (2021)2022
Evolutionary dynamics of the severe acute respiratory syndrome coronavirus 2 genomes.
Review in Medical review (2021), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Convergent Evolution and Host-Limiting Impacts of SARS-CoV-2 Revealed by Cellular Experiments.Molecular biology and evolution · 2025Article
- Article
- Identification of the critical residues of TMPRSS2 for entry and host range of human coronavirus HKU1.Journal of virology · 2024Article
- Molecular Evolution of Protein Sequences and Codon Usage in Monkeypox Viruses.Genomics, proteomics & bioinformatics · 2024Article
- Optimization and Deoptimization of Codons in SARS-CoV-2 and Related Implications for Vaccine Development.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Host susceptibility and structural and immunological insight of S proteins of two SARS-CoV-2 closely related bat coronaviruses.Cell discovery · 2023Article
- High-throughput screening of spike variants uncovers the key residues that alter the affinity and antigenicity of SARS-CoV-2.Cell discovery · 2023Article
- Adaptive Evolution of the Spike Protein in Coronaviruses.Molecular biology and evolution · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has caused immense losses in human lives and the global economy and posed significant challenges for global public health. As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, has evolved, thousands of single nucleotide variants (SNVs) have been identified across the viral genome. The roles of individual SNVs in the zoonotic origin, evolution, and transmission of SARS-CoV-2 have become the focus of many studies. This review summarizes recent comparative genomic analyses of SARS-CoV-2 and related coronaviruses (SC2r-CoVs) found in non-human animals, including delineation of SARS-CoV-2 lineages based on characteristic SNVs. We also discuss the current understanding of receptor-binding domain (RBD) evolution and characteristic mutations in variants of concern (VOCs) of SARS-CoV-2, as well as possible co-evolution between RBD and its receptor, angiotensin-converting enzyme 2 (ACE2). We propose that the interplay between SARS-CoV-2 and host RNA editing mechanisms might have partially resulted in the bias in nucleotide changes during SARS-CoV-2 evolution. Finally, we outline some current challenges, including difficulty in deciphering the complicated relationship between viral pathogenicity and infectivity of different variants, and monitoring transmission of SARS-CoV-2 between humans and animals as the pandemic progresses.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.