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Published on: September 26, 2011
Variable rates of SARS-CoV-2 evolution in chronic infections
Ewan W Smith1, William L Hamilton2,3,4, Ben Warne2,3
1MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, United Kingdom.
Chronic SARS-CoV-2 infections can drive virus evolution within a host, leading to distinct viral subpopulations. A new statistical method reveals this complex within-host evolution, often underestimated by standard approaches.
Area of Science:
- Virology
- Evolutionary Biology
- Statistical Modeling
Background:
- Emergence of highly mutated SARS-CoV-2 variants is a significant evolutionary concern.
- Chronic viral infections are hypothesized to accelerate viral evolution and genetic novelty.
- Within-host viral population structure (compartmentalization) complicates the measurement of evolution rates.
Purpose of the Study:
- To develop and apply a novel statistical method for analyzing within-host virus evolution.
- To identify the minimum number of viral subpopulations within chronic infections.
- To infer accurate rates of within-host viral evolution.
Main Methods:
- Application of a novel statistical method to sequence data from chronic SARS-CoV-2 infections.
- Identification of minimum subpopulations required to explain observed sequence data.
- Inference of viral evolution rates within individual hosts.
Main Results:
- Non-trivial viral population structure was common in five out of nine chronic SARS-CoV-2 infections.
- Detection of multiple subpopulations was more frequent in severely immunocompromised individuals.
- Within-host evolution rates varied significantly, with some faster and some slower than the global SARS-CoV-2 population.
- Population structure was linked to high within-host evolution rates, often underestimated by standard methods.
Conclusions:
- Within-host viral evolution is complex and influenced by population structure.
- Novel statistical methods are crucial for accurately characterizing viral evolution in chronic infections.
- Understanding within-host dynamics is essential for tracking the evolution of novel viral variants.
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