Over time analysis of the codon usage of SARS-CoV-2 and its variants

As viruses evolve over time with their host, they adapt to multiple cellular functions to ensure efficient long-term transmission. Their ability to survive and function efficiently depends on optimizing their genetic code to effectively recruit the host's gene expression machinery, particularly the translation machinery. Codon usage bias (CUB) measures the level of adaptation at the codon level, considering multiple factors such as the host's tRNA pool.By estimating the adaptation scores of viruses to their host, we can gain insight into the changes that occur on the genomic level throughout their evolution. In our study, we propose tracking the viral evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using CUB to estimate adaptation. By comparing different strains and analyzing changes over time, we demonstrate an increased adaptation of the Omicron SARS-COV-2 variant. In addition, we observe fluctuations in CUB scores, with periods of decreased and then increased adaptation over time, offering detailed insights at a fine temporal resolution. This analysis further contributes to understanding how different mutations influence viral adaptation, as well as the evolution of other human-infecting viruses.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2025-01-01
DOI
https://doi.org/10.1016/j.csbj.2025.05.021
Citations
2
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
2.79

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article

Over time analysis of the codon usage of SARS-CoV-2 and its variants

Tamir Tuller, Alexander Churkin, Danny Barash, Franziska Totzeck et al.
2 citations
Computational and Structural Biotechnology Journal
SARS-CoV-2 and COVID-19 Research
2.79
article

Over time analysis of the codon usage of SARS-CoV-2 and its variants

Tamir Tuller, Alexander Churkin, Danny Barash, Franziska Totzeck, Dmitrij Frishman, Marina Parr, Alma Davidson
article en
2 citations

Abstract

As viruses evolve over time with their host, they adapt to multiple cellular functions to ensure efficient long-term transmission. Their ability to survive and function efficiently depends on optimizing their genetic code to effectively recruit the host's gene expression machinery, particularly the translation machinery. Codon usage bias (CUB) measures the level of adaptation at the codon level, considering multiple factors such as the host's tRNA pool.By estimating the adaptation scores of viruses to their host, we can gain insight into the changes that occur on the genomic level throughout their evolution. In our study, we propose tracking the viral evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using CUB to estimate adaptation. By comparing different strains and analyzing changes over time, we demonstrate an increased adaptation of the Omicron SARS-COV-2 variant. In addition, we observe fluctuations in CUB scores, with periods of decreased and then increased adaptation over time, offering detailed insights at a fine temporal resolution. This analysis further contributes to understanding how different mutations influence viral adaptation, as well as the evolution of other human-infecting viruses.

Computational and Structural Biotechnology JournalVol. 27
Ben-Gurion University of the Negev (IL), Tel Aviv University (IL), Sami Shamoon College of Engineering (IL), Technical University of Munich (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 11%
SARS-CoV-2 and COVID-19 Research
2.79
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Over time analysis of the codon usage of SARS-CoV-2 and its variants — Tamir Tuller, Alexander Churkin, et al. · Computational and Structural Biotechnology Journal (2025) | TGRS Research Map | TGRS