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Quantitative relationship between synonymous codon usage bias and GC composition across unicellular genomes.
Xiu-Feng Wan1, Dong Xu, Andris Kleinhofs
1Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. wanx@missouri.edu
BMC Evolutionary Biology
|June 30, 2004
Summary
This study quantifies codon usage bias in bacteria and archaea using GC composition. A simple model was developed to predict synonymous codon usage bias based on GC3 content, aiding genomic analysis.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Evolution
Background:
- Codon usage bias is known to correlate with GC composition.
- A quantitative relationship across species has not been previously established.
Purpose of the Study:
- To investigate the quantitative relationship between codon usage bias and GC composition across species.
- To develop a model for quantifying synonymous codon usage bias based on GC composition.
Main Methods:
- Utilized a previously developed informatics method (SCUO) based on Shannon informational theory and maximum entropy theory.
- Analyzed 70 bacterial and 16 archaeal genomes.
- Developed and validated an analytical model using regression and computational simulation.
Main Results:
- Established regression models for bacteria (SCUO = -2.06 * GC3 + 2.05*(GC3)2 + 0.65, r = 0.91) and archaea (SCUO = -1.79 * GC3 + 1.85*(GC3)2 + 0.56, r = 0.89).
- Developed a simplified analytical model quantifying synonymous codon usage bias using GC3 content.
- Validated the model through computational simulation.
Conclusions:
- Synonymous codon usage bias can be simply expressed as a function of GC3 content.
- The developed software 'codonO' for measuring SCUO is publicly available.