Entropic Dynamics of Mutations in SARS-CoV-2 Genomic Sequences

Area of Science:

• Genomics
• Computational Biology
• Virology

Background:

• Genomic sequences evolve through mutations.
• Understanding mutation dynamics is crucial for viral evolution studies.
• SARS-CoV-2 presents a rich dataset for analyzing viral mutations.

Purpose of the Study:

• To investigate mutation patterns in genomic sequences.
• To analyze the evolution of entropy and relative entropy in base frequencies.
• To uncover novel aspects of SARS-CoV-2 mutation dynamics.

Main Methods:

• Studying entropy and relative entropy of base frequencies.
• Applying a model to random sequences, with a focus on SARS-CoV-2.
• Utilizing mean field approximation of Markov dynamics within stochastic thermodynamics.

Main Results:

• The model successfully tracks known mutation features like Cytosine-Thymine bias.
• New, previously uncharacterized features of virus mutation dynamics were revealed.
• The approach provides a framework for studying these new findings.

Conclusions:

• Entropy and relative entropy analysis offers insights into genomic sequence evolution.
• The developed model is effective for analyzing SARS-CoV-2 mutation dynamics.
• Stochastic thermodynamics provides a powerful lens for understanding viral evolution.