Academic journal article Genetics

Measuring and Detecting Molecular Adaptation in Codon Usage against Nonsense Errors during Protein Translation

Academic journal article Genetics

Measuring and Detecting Molecular Adaptation in Codon Usage against Nonsense Errors during Protein Translation

Article excerpt

ABSTRACT

Codon usage bias (CUB) has been documented across a wide range of taxa and is the subject of numerous studies. While most explanations of CUB invoke some type of natural selection, most measures of CUB adaptation are heuristically defined. In contrast, we present a novel and mechanistic method for defining and contextualizing CUB adaptation to reduce the cost of nonsense errors during protein translation. Using a model of protein translation, we develop a general approach for measuring the protein production cost in the face of nonsense errors of a given allele as well as the mean and variance of these costs across its coding synonyms. We then use these results to define the nonsense error adaptation index (NAI) of the allele or a contiguous subset thereof. Conceptually, the NAI value of an allele is a relative measure of its elevation on a specific and well-defined adaptive landscape. To illustrate its utility, we calculate NAI values for the entire coding sequence and across a set of nonoverlapping windows for each gene in the Saccharomyces cerevisiae S288c genome. Our results provide clear evidence of adaptation to reduce the cost of nonsense errors and increasing adaptation with codon position and expression. The magnitude and nature of this adaptation are also largely consistent with simulation results in which nonsense errors are the only selective force driving CUB evolution. Because NAI is derived from mechanistic models, it is both easier to interpret and more amenable to future refinement than other commonly used measures of codon bias. Further, our approach can also be used as a starting point for developing other mechanistically derived measures of adaptation such as for translational accuracy.

(ProQuest: ... denotes formulae omitted.)

CODON usage bias (CUB) is defined as the nonuniform use of synonymous codons within a gene (IKEMURA 1981; BENNETZEN and HALL 1982; SHARP and LI 1987). CUB has been extensively documented across a wide range of organisms and varies greatly both within and between genomes (GRANTHAM et al. 1980; IKEMURA 1981, 1982, 1985; BENNETZEN and HALL 1982; SHARP and LI 1987; GHOSH et al. 2000; CARBONE et al. 2003; MOUGEL et al. 2004; SUBRAMANIAN 2008). Most explanations of CUB involve a mixture of factors including mutational bias, intron splicing, recombination, gene conversion, DNA packaging, and selection for increased translational efficiency or accuracy (BERNARDI and BERNARDI 1986; BULMER 1988, 1991; SHIELDS et al. 1988; KLIMAN and HEY 1993, 1994; AKASHI 1994, 2003; XIA 1996, 1998; AKASHI and EYRE-WALKER 1998;MUSTO et al. 1999, 2003; MCVEAN and CHARLESWORTH 1999; GHOSH et al. 2000; WAGNER 2000; BIRDSELL 2002; COMERON and KREITMAN 2002; ELF et al. 2003; CHEN et al. 2004; CHAMARY and HURST 2005a,b; COMERON 2006; LIN et al. 2006; WARNECKE and HURST 2007; DRUMMOND and WILKE 2008; WARNECKE et al. 2008). As a result, CUB has played an important role in the neutralist-selectionist debate (e.g., WOLFE and SHARP 1993; DURET and MOUCHIROUD 1999;MUSTO et al. 2001; URRUTIA and HURST 2003; PLOTKIN et al. 2004; SÉMON et al. 2005; CHAMARY et al. 2006; LYNCH 2007), interpretations of molecular clocks (e.g., LONG and GILLESPIE 1991; TAMURA et al. 2004; XIA 2009), and phylogenetics (e.g., GOLDMAN and YANG 1994; MOOERS and HOLMES 2000;NIELSEN et al. 2007a,b;ANISIMOVA and KOSIOL 2009).

Currently, multiple indexes are available for measuring the average CUB of a gene [e.g., Fop, codon bias index (CBI), relative synonymous codon usage (RCSU), codon adaptation index (CAI), Nc, E(g), CodonO, and relative codon bias (RCB) (IKEMURA 1981;BENNETZEN and HALL 1982; SHARP et al. 1986; SHARP and LI 1987; WRIGHT 1990; KARLIN and MRAZEK 2000; WAN et al. 2006; ROYMONDAL et al. 2009)]. However, directly relating any of these measures to a specific biological process is difficult. As a result, while certain measures of CUB are more popular in some circles than in others, there is no clear "correct" measure of codon bias. …

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