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The general stochastic model of nucleotide substitution
F Rodríguez1, J L Oliver, A Marín
1Departamento de Genética, Facultad de Biología, Universidad de Sevilla, Spain.
Journal of Theoretical Biology
|February 22, 1990
Summary
This study presents a Markov process model for DNA sequence evolution, correcting for multiple substitutions to measure evolutionary divergence. Simulation results indicate the general model slightly outperforms its specific cases for nucleotide substitution analysis.
Area of Science:
- Molecular Biology
- Evolutionary Biology
- Bioinformatics
Background:
- DNA sequence evolution can be modeled as a stationary Markov process.
- Nucleotide substitutions are fundamental to evolutionary divergence.
- Accurate measurement of evolutionary divergence requires correcting for multiple and parallel substitutions.
Purpose of the Study:
- To develop a formula correcting for multiple substitutions in DNA sequence divergence.
- To investigate the calculation of substitution rates using Markov models.
- To evaluate the effectiveness of a general DNA substitution model.
Main Methods:
- Utilized fundamental equations of a stationary Markov process for DNA sequence evolution.
- Developed a formula based on a general model with 12 independent substitution parameters.
- Employed simulation experiments to test the model's performance.
Main Results:
- A formula was derived to correct for multiple and parallel substitutions in evolutionary divergence.
- Only reversible Markov models (six parameters) allow for the calculation of substitution rates.
- Simulation experiments suggest the general model's effectiveness is questioned, yet it shows slight superiority over particular cases.
Conclusions:
- The derived formula effectively corrects for multiple substitutions in DNA sequence divergence.
- Reversible models are necessary for estimating substitution rates.
- While simulations raise questions, the general Markov model offers a robust framework for studying DNA evolution.