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Published on: April 26, 2019
Translation efficiency is determined by both codon bias and folding energy
Tamir Tuller1, Yedael Y Waldman, Martin Kupiec
1Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel. tamirtul@post.tau.ac.il
Summary
Codon bias significantly impacts translation efficiency in bacteria and yeast, contrary to previous hypotheses. mRNA folding energy also influences this process, particularly at the gene
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- Synonymous mutations can alter protein levels without changing the protein sequence.
- The mechanisms driving this phenomenon, such as codon bias and mRNA folding, are debated.
Purpose of the Study:
- To investigate the genome-wide determinants of translation efficiency in Escherichia coli and Saccharomyces cerevisiae.
- To clarify the relative importance of codon bias versus mRNA folding energy in regulating translation efficiency.
Main Methods:
- Genome-scale analysis of transcriptomes from E. coli and S. cerevisiae.
- Correlation analysis between codon bias, mRNA folding energy, and translation efficiency.
- Examination of ribosomal density profiles and selection pressures on mRNA folding at gene beginnings.
Main Results:
- A significant association was found between codon bias and translation efficiency across endogenous genes.
- No direct association was observed between folding energy and translation efficiency, but it modulates the codon bias effect.
- Lower folding energies correlate with decreased translation efficiency by slowing ribosome movement.
- Selection pressures favor reduced folding energy at the start of genes.
Conclusions:
- Codon bias is a key determinant of translation efficiency in E. coli and S. cerevisiae.
- mRNA folding energy influences translation efficiency globally, not just at translation initiation, and its effects are intertwined with codon bias.
- Previous studies may have overlooked the global role of folding energy due to its complex interaction with expression levels.
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