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Basic Characteristics of Mutations
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Mutation Site
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D614G |
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Mutation Site Sentence
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The D614G substitution was then maintained in all subsequent variants in this study without a decline in the variation frequency over the 3-year period sampled (Supplementary Fig. S2). |
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Mutation Level
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Amino acid level |
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Mutation Type
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Nonsynonymous substitution |
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Gene/Protein/Region
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S |
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Standardized Encoding Gene
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S
|
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Genotype/Subtype
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- |
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Viral Reference
|
NC_045512.2
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Functional Impact and Mechanisms
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Disease
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COVID-19
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Immune
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- |
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Target Gene
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-
|
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Clinical and Epidemiological Correlations
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Clinical Information
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- |
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Treatment
|
- |
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Location
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UK |
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Literature Information
|
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PMID
|
39970290
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Title
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Using minor variant genomes and machine learning to study the genome biology of SARS-CoV-2 over time
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Author
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Dong X,Matthews DA,Gallo G,Darby A,Donovan-Banfield I,Goldswain H,MacGill T,Myers T,Orr R,Bailey D,Carroll MW,Hiscox JA
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Journal
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Nucleic acids research
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Journal Info
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2025 Feb 8;53(4):gkaf077
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Abstract
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In infected individuals, viruses are present as a population consisting of dominant and minor variant genomes. Most databases contain information on the dominant genome sequence. Since the emergence of SARS-CoV-2 in late 2019, variants have been selected that are more transmissible and capable of partial immune escape. Currently, models for projecting the evolution of SARS-CoV-2 are based on using dominant genome sequences to forecast whether a known mutation will be prevalent in the future. However, novel variants of SARS-CoV-2 (and other viruses) are driven by evolutionary pressure acting on minor variant genomes, which then become dominant and form a potential next wave of infection. In this study, sequencing data from 96 209 patients, sampled over a 3-year period, were used to analyse patterns of minor variant genomes. These data were used to develop unsupervised machine learning clusters to identify amino acids that had a greater potential for mutation than others in the Spike protein. Being able to identify amino acids that may be present in future variants would better inform the design of longer-lived medical countermeasures and allow a risk-based evaluation of viral properties, including assessment of transmissibility and immune escape, thus providing candidates with early warning signals for when a new variant of SARS-CoV-2 emerges.
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Sequence Data
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-
|
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