Correlation of codon biases and potential secondary structures with mRNA translation efficiency in unicellular organisms

• Published in: Molecular biology (New York) Vol. 41; no. 5; pp. 843 - 850
• Main Authors: Vladimirov, N V, Likhoshvai, V A, Matushkin, YuG
• Format: Journal Article
• Language: English
• Published: New York Springer Nature B.V 01.10.2007
• Subjects: Archaea; Bacteria; codon bias; Codons; Data processing; Efficiency; Elongation; Evolution; Free energy; Gene expression; Genomes; Helicobacter pylori; Nucleotide sequence; Nucleotides; Open reading frames; Organisms; Protein structure; Proteins; Ribosomes; Saccharomyces cerevisiae; Secondary structure; Translation
• ISSN: 0026-8933; 1608-3245
• DOI: 10.1134/S0026893307050184

Gene expression is known to correlate with the degree of codon bias in many unicellular organisms. However, such a correlation is not observed in some organisms. It was demonstrated that inverted complementary repeats within coding DNA sequences (ORFs) should be considered for proper estimation of the translation efficiency because they can form secondary structures that obstruct ribosome movement. A program was developed for estimating the potential expression of ORFs in unicellular organisms on the basis of their genome sequences. The program computes the elongation efficiency index (EEI) and takes into account three key factors: codon bias, the average number of inverted complementary repeats, and the free energies of potential stem-loop structures formed by these repeats. The influence of these factors on translation was numerically estimated. Their optimal ratio was computed for each organism. EEIs of 384 unicellular organisms (351 bacteria, 28 archaea, and 5 eukaryotes) were computed using the annotated genomes available from GenBank. Five potential evolutionary strategies of translational optimization were determined in the organisms studied. A considerable difference in preferential translational strategies was observed between bacteria and archaea. Significant correlations between EEIs and gene expression levels were shown for two species (Saccharomyces cerevisiae and Helicobacter pylori), using the available microarray data. The method allows the numerical estimation of the translation efficiency of an ORF and optimization of the nucleotide composition of heterologous genes in specified unicellular organisms. The program is available at http://wwwmgs.bionet.nsc.ru/mgs/programs/eei-calculator.