Codon Preference analysis and Codon Adaptive Index measure d

Codon Preference analysis and Codon Adaptive Index measure distinct patterns/statistics regarding codon usage or bias, measuring different aspects of reading frames. How they are different? Be sure to include a specific description of the different information content contained in the reference tables that you generate for each method, and what each of these two algorithms measure as a result of this unique information in reading frames. Which algorithm is best for finding new reading frames in a partially sequenced new organism, and why?

Solution

The Codon Adaptation Index (CAI) is based on the measurement of Codon Usage Bias by a reference set for analysis. This measurement is opposite to Effective Number of Codons in respective of measurement based on Uniform Bias. The reference for CAI is set by highly expressed genes because they would compete with other genes at most for their expression sites.

On other hand the Codon Preference analysis uses three different reading frames for highly expressed genes, low expressed genes and non coding regions. The plot is relied on both codon frequency table and reading frames. This technique has three advantages: independent form of codon preference statistics, analysis is based on one table for on organism and also based on protein expression level. This technique reveals about highly and moderate express genes both.

So Codon Preference analysis is good for finding new reading frames in a partially sequenced new organism in compare to CAI. Codon Preference analysis is also a more developed technique than CAI.