Translationally Optimal Codons Associate with Structurally Sensitive Sites in Proteins
- 6 April 2009
- journal article
- research article
- Published by Oxford University Press (OUP) in Molecular Biology and Evolution
- Vol. 26 (7) , 1571-1580
- https://doi.org/10.1093/molbev/msp070
Abstract
The mistranslation-induced protein misfolding hypothesis predicts that selection should prefer high-fidelity codons at sites at which translation errors are structurally disruptive and lead to protein misfolding and aggregation. To test this hypothesis, we analyzed the relationship between codon usage bias and protein structure in the genomes of four model organisms, Escherichia coli, yeast, fly, and mouse. Using both the Mantel-Haenszel procedure, which applies to categorical data, and a newly developed association test for continuous variables, we find that translationally optimal codons associate with buried residues and also with residues at sites where mutations lead to large changes in free energy (delta delta G). In each species, only a subset of all amino acids show this signal, but most amino acids show the signal in at least one species. By repeating the analysis on a reduced data set that excludes interdomain linkers, we show that our results are not caused by an association of rare codons with solvent-accessible linker regions. Finally, we find that our results depend weakly on expression level; the association between optimal codons and buried sites exists at all expression levels, but increases in strength as expression level increases.Keywords
This publication has 77 references indexed in Scilit:
- Mistranslation-Induced Protein Misfolding as a Dominant Constraint on Coding-Sequence EvolutionCell, 2008
- Structural Mapping of Protein Interactions Reveals Differences in Evolutionary Pressures Correlated to mRNA Level and Protein AbundanceStructure, 2007
- The selection of acceptable protein mutationsProceedings of the National Academy of Sciences, 2007
- The CATH domain structure database: new protocols and classification levels give a more comprehensive resource for exploring evolutionNucleic Acids Research, 2007
- Protein stability promotes evolvabilityProceedings of the National Academy of Sciences, 2006
- Integrating high-throughput and computational data elucidates bacterial networksNature, 2004
- A gene atlas of the mouse and human protein-encoding transcriptomesProceedings of the National Academy of Sciences, 2004
- MUSCLE: multiple sequence alignment with high accuracy and high throughputNucleic Acids Research, 2004
- CATH – a hierarchic classification of protein domain structuresPublished by Elsevier ,1997
- Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical featuresBiopolymers, 1983