Context-dependent substitution models for circular DNA.

Area of Science:

• Computational Biology
• Genetics
• Bioinformatics

Background:

• Markov substitution processes are fundamental to evolutionary sequence analysis.
• Existing models often simplify context dependencies, limiting interpretability.
• Circular DNA sequences offer a simplified framework for modeling substitution processes.

Purpose of the Study:

• To present the most general context-dependent Markov substitution process for DNA sequences.
• To classify and analyze special cases of context-dependent models.
• To propose a novel, interpretable codon model for DNA evolution.

Main Methods:

• Development of a general context-dependent Markov substitution process framework.
• Classification and review of existing context-dependent models (independent sites, nearest-neighbor, codon models).
• Analysis of mutation and selection processes within codon substitution models.

Main Results:

• A general context-dependent Markov substitution process is formally introduced.
• Existing models are categorized, revealing limitations in current codon models.
• Current codon models conflate mutation and selection, hindering rate interpretation.

Conclusions:

• A new, interpretable codon model is proposed, separating mutation and selection.
• This model can accommodate varying selection pressures in overlapping reading frames.
• The framework facilitates understanding of viral evolution and disease mechanisms.