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Updated: Nov 15, 2025

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
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Different selection dynamics of S and RdRp between SARS-CoV-2 genomes with and without the dominant mutations
Necla Koçhan1, Doğa Eskier2, Aslı Suner3
1Izmir Biomedicine and Genome Center (IBG), Izmir, Turkey.
Summary
Understanding SARS-CoV-2 mutations is key for COVID-19 research. This study reveals contrasting selection dynamics between the S gene and RNA-dependent RNA polymerase (RdRp) in mutant isolates.
Area of Science:
- Virology
- Molecular Biology
- Genetics
Background:
- Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) drives the ongoing COVID-19 pandemic.
- Genomic and peptide sequences are vital for developing diagnostics and therapeutics.
- Understanding viral mutation rates is critical for tracking viral evolution and fitness.
Purpose of the Study:
- To investigate the selection dynamics and mutation rates of SARS-CoV-2 genes.
- To compare these dynamics between isolates with specific common mutations (14408C>T in RdRp, 23403A>G in S gene) and those without.
- To elucidate the roles of the S gene and RdRp in viral fitness and infectivity.
Main Methods:
- Comparative genomic analysis of SARS-CoV-2 isolates.
- Analysis of mutation rates and selection pressures on specific genes (S gene, RdRp coding region).
- Stratification of isolates based on the presence or absence of key mutations (14408C>T and 23403A>G).
Main Results:
- The S gene and RdRp coding region exhibit the highest genetic variance between genotypes.
- Contrasting selection dynamics were observed: the S gene showed early positive selection followed by increasing negative selection in mutant isolates.
- The RdRp region in mutant isolates demonstrated consistent strong negative selection throughout the pandemic.
Conclusions:
- The S gene and RdRp coding region are hotspots for genetic variation in SARS-CoV-2.
- Specific mutations influence the selection pressures on these key viral genes.
- Understanding these dynamics is crucial for predicting viral evolution and informing public health strategies.
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