Bioinformatics Vol. 19 no. 16 2003
pages 2005-2015
© 2003 Oxford University Press
Codon adaptation index as a measure of dominating codon bias
1 Institut des Hautes Études Scientifiques, 35, route de Chartres, 91440 Bures-sur-Yvette, France and 2 ATelier de Génomique Cognitive, CNRS ESA 8071/Genopole, 523 Terrasses de l’Agora, 91000 Evry, France
Received on February 6, 2003
; revised on April 15, 2003
; accepted on April 25, 2003
We propose a simple algorithm to detect dominating synonymous codon usage bias in genomes. The algorithm is based on a precise mathematical formulation of the problem that lead us to use the Codon Adaptation Index (CAI) as a ‘universal’ measure of codon bias. This measure has been previously employed in the specific context of translational bias. With the set of coding sequences as a sole source of biological information, the algorithm provides a reference set of genes which is highly representative of the bias. This set can be used to compute the CAI of genes of prokaryotic and eukaryotic organisms, including those whose functional annotation is not yet available. An important application concerns the detection of a reference set characterizing translational bias which is known to correlate to expression levels; in this case, the algorithm becomes a key tool to predict gene expression levels, to guide regulatory circuit reconstruction, and to compare species. The algorithm detects also leading–lagging strands bias, GC-content bias, GC3 bias, and horizontal gene transfer. The approach is validated on 12 slow-growing and fast-growing bacteria, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster.
Availability: http://www.ihes.fr/~materials.
Contact: carbone{at}ihes.fr
* To whom correspondence should be addressed.
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