Relative Codon Adaptation Index, a Sensitive Measure of Codon Usage Bias

Abstract

Abstract:We propose a simple, sensitive measure of synonymous codon usage bias, the Relative Codon Adaptation Index (rCAI), as a way to discriminate better between highly biased and unbiased regions, compared with the widely used Codon Adaptation Index (CAI). CAI is a geometric mean of the relative usage of codons in a gene, and is calculated using the codon usage table trained with a set of highly expressed genes. In contrast, rCAI is computed by subtracting the background codon usage trained with two noncoding frames of highly expressed genes from the codon usage in the coding frame. rCAI has higher signal-to-noise ratio than CAI, considering that noncoding frames would not show codon bias. Translation efficiency and protein abundance correlates comparably or better with rCAI than CAI or other measures such as 'effective number of codons' and 'SCUMBLE offsets'. Within overlapping coding regions, one of the two coding frames dominates in codon usage bias according to rCAI. Presumably, rCAI could substitute CAI in diverse applications.

Effective population size does not predict codon usage bias in mammals

“…We calculated ENC and ENCp using Novembre's ENCprime software, which quantifies the significance of observed versus expected codon usage via Pearson's χ 2 statistics (Novembre 2002). Alternative methods, such as the “frequency of preferred codons” (Ikemura 1981) or the “codon adaptation index” (Sharp and Li 1987; Lee et al 2010), require a priori definition of “preferred codons,” which may not be conserved across species (Hershberg and Petrov 2009; Rao 2011). Furthermore, selection may favor an overall balanced combination of preferred and unpreferred codons at the genomic scale so that genes vary in their preferred and unpreferred codons (Shah and Gilchrist 2011; Qian et al 2012; Agashe et al 2013; Yang et al 2014).…”

Viral Proteins Originated De Novo by Overprinting Can Be Identified by Codon Usage: Application to the “Gene Nursery” of Deltaretroviruses

“…Consequently, the de novo frame is expected to have a codon usage less similar to that of the viral genome than the ancestral frame (Figure 1). This approach has been empirically used to try and identify the de novo frame in a number of cases, as have been related methods which rely on the frequency on nucleotides at some or all codon positions [10], [22]–[29]. However, the reliability or accuracy of these methods has never been tested.…”

COUSIN (COdon Usage Similarity INdex): A normalized measure of Codon Usage Preferences

“…A variety of indices have been developed since the 1980s to evaluate the CUPrefs of a sequence (Ikemura, 1981; Freire-Picos et al , 1994; Urrutia and Hurst, 2001). Most of them compare the CUPrefs of a query against a reference set or against a Null Hypothesis chosen by the user (Shields et al , 1988; Lee et al , 2010). New indices are still developed (Zhang et al , 2012) but the “Codon Adaptation Index” (CAI) (Sharp and Li, 1987) and the “Effective Number of Codons” (ENC) (Wright, 1990) remain the most popular ones and are still being improved (Lee et al , 2010; Satapathy et al , 2017).…”

“…Most of them compare the CUPrefs of a query against a reference set or against a Null Hypothesis chosen by the user (Shields et al , 1988; Lee et al , 2010). New indices are still developed (Zhang et al , 2012) but the “Codon Adaptation Index” (CAI) (Sharp and Li, 1987) and the “Effective Number of Codons” (ENC) (Wright, 1990) remain the most popular ones and are still being improved (Lee et al , 2010; Satapathy et al , 2017). Problematically, most CUPrefs indices have little reliability when analyzing sequences with either short length, strong GC content or strong amino acid composition bias (Roth et al , 2012).…”