Solving the riddle of codon usage preferences: a test for translational selection

Abstract

Translational selection is responsible for the unequal usage of synonymous codons in protein coding genes in a wide variety of organisms. It is one of the most subtle and pervasive forces of molecular evolution, yet, establishing the underlying causes for its idiosyncratic behaviour across living kingdoms has proven elusive to researchers over the past 20 years. In this study, a statistical model for measuring translational selection in any given genome is developed, and the test is applied to 126 fully sequenced genomes, ranging from archaea to eukaryotes. It is shown that tRNA gene redundancy and genome size are interacting forces that ultimately determine the action of translational selection, and that an optimal genome size exists for which this kind of selection is maximal. Accordingly, genome size also presents upper and lower boundaries beyond which selection on codon usage is not possible. We propose a model where the coevolution of genome size and tRNA genes explains the observed patterns in translational selection in all living organisms. This model finally unifies our understanding of codon usage across prokaryotes and eukaryotes. Helicobacter pylori, Saccharomyces cerevisiae and Homo sapiens are codon usage paradigms that can be better understood under the proposed model.

Hepatitis A Virus Adaptation to Cellular Shutoff Is Driven by Dynamic Adjustments of Codon Usage and Results in the Selection of Populations with Altered Capsids

“…Codon and anticodon usages of each viral population were inferred through the analysis of the sequences of 50 molecular clones of two capsid genomic regions (comprising codons 1 to 123 of VP3 and 85 to 245 of VP1) and compared with codon and anticodon usage of the host cell as previously described (17,33). Anticodon usage variation was estimated through codon usage variation assuming a model based on the frequency of the codons, the anticodon degeneracy, and the codonanticodon match pairing preferences (17,33).…”

Automated Isolation of Translational Efficiency Bias That Resists the Confounding Effect of GC(AT)-Content

“…Others have investigated the effects of GC-content on expected bias scores [8], [39], [40], though these analyses did not explore whether measuring deviation from such expected values could enhance prediction of translational efficiency bias. The study by dos Reis et al [39] used a correlation between their transfer RNA adaptation index and deviation from expected effective number of codons to make a determination of whether the underlying bias was that of translational efficiency bias.…”

Transfer-RNA-mediated enhancement of ribosomal proteins S6 kinases signaling for cell proliferation

“…However, it is still debated whether tRNA abundance and codon usage are under concerted regulation of translation rate and efficiency. 18-20 In fact, several studies have suggested that preferentially used codons are not translated faster, and that tRNA variation might play an adaptive role in coping with environmental changes. Analysis of human tRNAs using microarrays have revealed that tRNAs could be biasedly induced toward different cell programs such as proliferation and differentiation.…”