Codon Adaptation Index (Cai)

Question

[martin.kavscek]

I am relativly new to the field and I am dealing now with the codon usage for different proteins in several pathways to see if there is corelation. Just to be sure about the metod - As I would like to compare two different organism I would like to set the reference codon usage table of the whole genome, and then calculate CAI for each gene in each organism. Will I be than able to relevantly compare CAI from homologous genes?

Thank you very much for your answers! Martin Kavšček

[Rm]

Look at these servers for CAI tools:

http://genomes.urv.es/CAIcal/

http://gcua.schoedl.de/sequential_v2.html

http://sysbio.cvm.msstate.edu/CodonO/

http://www.genscript.com/cgi-bin/tools/rare_codon_analysis

[Asaf]

You should make sure that the genomes you're testing have a codon bias, not every genome is biased. A simple test is to compare the codon frequencies between highly expressed genes and the rest of the genes in each genome.

[martin.kavscek]

I have additional question - if I will compute gCAI with this script the set reference (S) would again use genes that have high frequencies of highly used codons. What I would like to do is to have a set of genes that have average codon usage as a reference (and therefore average exspression) or to use a whole genome as a set of reference. In that way I would be able to compare expression values of homologous proteins in two different organism.

Am I thinking in the right direction or not ? :)

Thank you for your answers. Martin

[Rm]

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Answer 1

[Anthony Mathelier]

You should use CAIjava (http://www.ihes.fr/~carbone/materials/description.html) which introduces a correcting factor in the original formula proposed by Sharp and Li (Sharp and Li, 1987), compute the global codon adaptation index, (gCAI) and determine a set S of coding sequences with high gCAI values. Ultimately, CAI values can be computed on codon weights calculated on S.

Hence it refines the computation of CAI without using the starting set of highly expressed genes only to compute the codon biais. This method has been used successfully in many other papers.

http://www.ihes.fr/~carbone/papers/Bioinformatics.pdf .

[martin.kavscek]

Thank you very much for that. I will look into it. What I do not want is to use a reference set S that is based on some highly expressed genes, because I would like to compare the CAI of enzymes in glycolysis for 2 different organism.

[Anthony Mathelier]

Then you should definitely use this tool which computes the set S of interest directly from the genome.

Answer 2

[bioee]

For calculating CAI or RSCU mentioned in Sharp and Li (Sharp and Li, 1987), you can use the open source biopython, it is so easy to use.

Also, you should check another online tool http://www.biologicscorp.com/tools/CAICalculator which use a genomic codon usage or reference sequence for calculating.

Answer 3

[abdulwrs7]

Codon Adaptation Index (CAI) was first introduced by Sharp and Li to measure synonymous codon usage bias for a DNA or RNA sequence.It also measures the resemblance between the synonymous codon usage of a gene and the synonymous codon frequencies of a reference set.CAI was originally proposed to provide an estimate that can be used across genes and species, ranging from 0 to 1.

If a gene always uses the most frequently used synonymous codon in the reference set,then CAI=1. If a gene always uses the least frequently used synonymous codon in the reference set,then CAI=0.

Click on this link to explore more:Implementation Of Codon Adaptation Index (CAI) Using Biopython