Gradients in nucleotide and codon usage along Escherichia coli genes

Hooper, Sean D.; Berg, Otto G.

doi:10.1093/nar/28.18.3517

Cited by 67 publications

(63 citation statements)

References 33 publications

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“…Nonsense errors have a number of different causes such as ribosome drop-off, improper translation of release factors, frameshifts, and even missense errors (Kurland 1992;Hooper and Berg 2000;Zaher and Green 2009). Direct estimates of the per codon nonsense error rates are rare, but those that do exist for Escherichia coli suggest that they are on the order of 10 À4 per codon (Manley 1978;Tsung et al 1989;Jorgensen and Kurland 1990).…”

mentioning

confidence: 99%

“…As a result, selection against nonsense errors leads to the unique prediction that CUB should increase intragenically with codon position. Numerous researchers have shown either directly or indirectly that CUB does indeed increase with codon position in E. coli and other microorganisms (Hooper and Berg 2000;Qin et al 2004;Gilchrist and Wagner 2006;Stoletzki and Eyre-Walker 2007).…”

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confidence: 99%

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Measuring and Detecting Molecular Adaptation in Codon Usage Against Nonsense Errors During Protein Translation

2009

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Codon usage bias (CUB) has been documented across a wide range of taxa and is the subject of numerous studies. While most explanations of CUB invoke some type of natural selection, most measures of CUB adaptation are heuristically defined. In contrast, we present a novel and mechanistic method for defining and contextualizing CUB adaptation to reduce the cost of nonsense errors during protein translation. Using a model of protein translation, we develop a general approach for measuring the protein production cost in the face of nonsense errors of a given allele as well as the mean and variance of these costs across its coding synonyms. We then use these results to define the nonsense error adaptation index (NAI) of the allele or a contiguous subset thereof. Conceptually, the NAI value of an allele is a relative measure of its elevation on a specific and well-defined adaptive landscape. To illustrate its utility, we calculate NAI values for the entire coding sequence and across a set of nonoverlapping windows for each gene in the Saccharomyces cerevisiae S288c genome. Our results provide clear evidence of adaptation to reduce the cost of nonsense errors and increasing adaptation with codon position and expression. The magnitude and nature of this adaptation are also largely consistent with simulation results in which nonsense errors are the only selective force driving CUB evolution. Because NAI is derived from mechanistic models, it is both easier to interpret and more amenable to future refinement than other commonly used measures of codon bias. Further, our approach can also be used as a starting point for developing other mechanistically derived measures of adaptation such as for translational accuracy.

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Measuring and Detecting Molecular Adaptation in Codon Usage Against Nonsense Errors During Protein Translation

2009

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“…We can see that the proteins could be preliminary separated into different subfamilies, i.e. Alpha herpesvirinae, Beta herpesvirinae and Gamma herpesvirinae (20,21 40), the codon usage bias in the UL31 -like genes of 49 reference species, especially the PRV is therefore, slightly high. If a specific gene is exposed to G + C compositional restriction for shaping the codon usage pattern, it will lie on a continuous curve, representing random codon usage (45).…”

Section: Molecular Phylogenetic Tree Of the Ul31-like Proteins In Prvmentioning

confidence: 99%

“…Further analysis found that synonymous codon usage pattern changed at distinct sites along a coding sequence (14), balances of strong versus weak base pair bonding (15,16), maintenance of DNA and RNA secondary structure (17), and translational efficiency and fidelity (6). Aujeszky's disease, which is provoked by the pathogenic factor of Pseudorabies virus (PRV) (also known as Suid herpesvirus 1,, is a regularly lethal disease with a global distribution that influences swine, mainly and other domestic and wild animals incidentally (18)(19)(20)(21)(22). PRV belongs to the genus Varicellovirus, subfamily alpha herpesvirinae, which is a swine alpha herpesvirus (20,(23)(24)(25)(26) …”

Section: Introductionmentioning

confidence: 99%

Identification of Synonymous Codon Usage Bias in the Pseudorabies Virus UL31 Gene

et al. 2013

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Background: Little knowledge of synonymous codon usage pattern of pseudorabies virus (PRV) genome, especially the UL31 gene in the process for its evolution is available. Objectives: In the present study, the codon usage bias between PRV UL31 sequence and the UL31-like sequences was identified. Materials and Methods:We used a comprehensive analysis on codon usage pattern in the PRV UL31 gene and the UL31-like genes of 48 reference herpesviruses by calculating codon adaptation index, ENc, RSCU and EMBOSS assays. Results: Cluster analysis demonstrated that the codon usage bias of UL31-like genes of 49 herpesviruses had a very close relation to their gene functions. In addition, comparison of codon preferences in the UL31 gene of PRV with those of E. coli, yeast and human showed that there were 33 codons showing discrete usage differences between PRV and yeast, 24 between PRV and E. coli, but 22 between PRV and human. Although there were slightly fewer differences in codon usages between PRV and human, the difference is unlikely to be statistically significant, and experimental studies are necessary to establish the most suitable expression system for PRV UL31. Conclusions: These results may further our comprehending of the evolution, pathogenesis and functional studies of PRV.

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“…Several hypotheses attempt to explain how codon use mediates this effect, including but not limited to facilitating ribosomal pausing early in translation to optimize protein folding (13); adjusting mRNA secondary structure to optimize translation initiation or to modulate mRNA degradation; preventing ribosome stalling by coevolving with tRNA levels (6); providing a "translational ramp" for proper ribosome spacing and effective translation (14); and providing a layer of translational regulation for independent control of each gene in an operon (15). Additionally, codon use may impact translational fidelity (16), and the proteome may be tuned by fine control of the decoding tRNA pools (17). Although Quax et al (18) provide an excellent review of how biology chooses codons, systematic and exhaustive studies of codon choice in whole genomes are lacking.…”

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confidence: 99%

Emergent rules for codon choice elucidated by editing rare arginine codons in Escherichia coli

Napolitano

Landon

Gregg

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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The degeneracy of the genetic code allows nucleic acids to encode amino acid identity as well as noncoding information for gene regulation and genome maintenance. The rare arginine codons AGA and AGG (AGR) present a case study in codon choice, with AGRs encoding important transcriptional and translational properties distinct from the other synonymous alternatives (CGN). We created a strain of Escherichia coli with all 123 instances of AGR codons removed from all essential genes. We readily replaced 110 AGR codons with the synonymous CGU codons, but the remaining 13 "recalcitrant" AGRs required diversification to identify viable alternatives. Successful replacement codons tended to conserve local ribosomal binding site-like motifs and local mRNA secondary structure, sometimes at the expense of amino acid identity. Based on these observations, we empirically defined metrics for a multidimensional "safe replacement zone" (SRZ) within which alternative codons are more likely to be viable. To evaluate synonymous and nonsynonymous alternatives to essential AGRs further, we implemented a CRISPR/Cas9-based method to deplete a diversified population of a wild-type allele, allowing us to evaluate exhaustively the fitness impact of all 64 codon alternatives. Using this method, we confirmed the relevance of the SRZ by tracking codon fitness over time in 14 different genes, finding that codons that fall outside the SRZ are rapidly depleted from a growing population. Our unbiased and systematic strategy for identifying unpredicted design flaws in synthetic genomes and for elucidating rules governing codon choice will be crucial for designing genomes exhibiting radically altered genetic codes.codon choice | genome editing | recoded genomes

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Gradients in nucleotide and codon usage along Escherichia coli genes

Cited by 67 publications

References 33 publications

Measuring and Detecting Molecular Adaptation in Codon Usage Against Nonsense Errors During Protein Translation

Measuring and Detecting Molecular Adaptation in Codon Usage Against Nonsense Errors During Protein Translation

Identification of Synonymous Codon Usage Bias in the Pseudorabies Virus UL31 Gene

Emergent rules for codon choice elucidated by editing rare arginine codons in Escherichia coli

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