Effect of codon adaptation on codon-level and gene-level translation efficiency in vivo

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Abstract

Background: There is a significant difference between synonymous codon usage in many organisms, and it is known that codons used more frequently generally showed efficient decoding rate. At the gene level, however, there are conflicting reports on the existence of a correlation between codon adaptation and translation efficiency, even in the same organism. Results: To resolve this issue, we cultured Escherichia coli under conditions designed to maintain constant levels of mRNA and protein and subjected the cells to ribosome profiling (RP) and mRNA-seq analyses. We showed that the RP results correlated more closely with protein levels generated under similar culture conditions than with the mRNA abundance from the mRNA-seq. Our result indicated that RP/mRNA ratio could be used as a measure of translation efficiency at gene level. On the other hand, the RP data showed that codon-specific ribosome density at the decoding site negatively correlated with codon usage, consistent with the hypothesis that preferred codons display lower ribosome densities due to their faster decoding rate. However, highly codon-adapted genes showed higher ribosome densities at the gene level, indicating that the efficiency of translation initiation, rather than higher elongation efficiency of preferred codons, exerted a greater effect on ribosome density and thus translation efficiency. Conclusions: These findings indicate that evolutionary pressure on highly expressed genes influenced both codon bias and translation initiation efficiency and therefore explains contradictory findings that codon usage bias correlates with translation efficiency of native genes, but not with the artificially created gene pool, which was not subjected to evolution pressure.

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APA

Nakahigashi, K., Takai, Y., Shiwa, Y., Wada, M., Honma, M., Yoshikawa, H., … Mori, H. (2014). Effect of codon adaptation on codon-level and gene-level translation efficiency in vivo. BMC Genomics, 15(1). https://doi.org/10.1186/1471-2164-15-1115

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