Dataset Information

Gaussian-Distributed Codon Frequencies of Genomes.

ABSTRACT: DNA encodes protein primary structure using 64 different codons to specify 20 different amino acids and a stop signal. Frequencies of codon occurrence when ordered in descending sequence provide a global characterization of a genome's preference (bias) for using the different codons of the redundant genetic code. Whereas frequency/rank relations have been described by empirical expressions, here we propose a statistical model in which two different forms of codon usage co-exist in a genome. We investigate whether such a model can account for the range of codon usages observed in a large set of genomes from different taxa. The differences in frequency/rank relations across these genomes can be expressed in a single parameter, the proportion of the two codon compartments. One compartment uses different codons with weak bias according to a Gaussian distribution of frequency, the other uses different codons with strong bias. In prokaryotic genomes both compartments appear to be present in a wide range of proportions, whereas in eukaryotic genomes the compartment with Gaussian distribution tends to dominate. Codon frequencies that are Gaussian-distributed suggest that many evolutionary conditions are involved in shaping weakly-biased codon usage, whereas strong bias in codon usage suggests dominance of few evolutionary conditions.

SUBMITTER: Khomtchouk BB

PROVIDER: S-EPMC6505138 | biostudies-other | 2019 May

REPOSITORIES: biostudies-other

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Gaussian-Distributed Codon Frequencies of Genomes.

Khomtchouk Bohdan B BB Nonner Wolfgang W

G3 (Bethesda, Md.) 20190507 5

DNA encodes protein primary structure using 64 different codons to specify 20 different amino acids and a stop signal. Frequencies of codon occurrence when ordered in descending sequence provide a global characterization of a genome's preference (bias) for using the different codons of the redundant genetic code. Whereas frequency/rank relations have been described by empirical expressions, here we propose a statistical model in which two different forms of codon usage co-exist in a genome. We i ...[more]

PMID: 30808691

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Project description:Background and Aims:Studies on codon usage in monocots have focused on grasses, and observed patterns of this taxon were generalized to all monocot species. Here, non-grass monocot species were analysed to investigate the differences between grass and non-grass monocots. Methods:First, studies of codon usage in monocots were reviewed. The current information was then extended regarding codon usage, as well as codon-pair context bias, using four completely sequenced non-grass monocot genomes (Musa acuminata, Musa balbisiana, Phoenix dactylifera and Spirodela polyrhiza) for which comparable transcriptome datasets are available. Measurements were taken regarding relative synonymous codon usage, effective number of codons, derived optimal codon and GC content and then the relationships investigated to infer the underlying evolutionary forces. Key Results:The research identified optimal codons, rare codons and preferred codon-pair context in the non-grass monocot species studied. In contrast to the bimodal distribution of GC3 (GC content in third codon position) in grasses, non-grass monocots showed a unimodal distribution. Disproportionate use of G and C (and of A and T) in two- and four-codon amino acids detected in the analysis rules out the mutational bias hypothesis as an explanation of genomic variation in GC content. There was found to be a positive relationship between CAI (codon adaptation index; predicts the level of expression of a gene) and GC3. In addition, a strong correlation was observed between coding and genomic GC content and negative correlation of GC3 with gene length, indicating a strong impact of GC-biased gene conversion (gBGC) in shaping codon usage and nucleotide composition in non-grass monocots. Conclusion:Optimal codons in these non-grass monocots show a preference for G/C in the third codon position. These results support the concept that codon usage and nucleotide composition in non-grass monocots are mainly driven by gBGC.

Project description:BACKGROUND: Natural selection has traditionally been understood as a force responsible for pushing genes to states of higher translational efficiency, whereas lower translational efficiency has been explained by neutral mutation and genetic drift. We looked for evidence of directional selection resulting in increased unpreferred codon usage (and presumably reduced translational efficiency) in three divergent clusters of eukaryotic genomes using a simple optimal-codon-based metric (Kp/Ku). RESULTS: Here we show that for some genes natural selection is indeed responsible for causing accelerated unpreferred codon substitution, and document the scope of this selection. In Cryptococcus and to a lesser extent Drosophila, we find many genes showing a statistically significant signal of selection for unpreferred codon usage in one or more lineages. We did not find evidence for this type of selection in Saccharomyces. The signal of positive selection observed from unpreferred synonymous codon substitutions is coincident in Cryptococcus and Drosophila with the distribution of upstream open reading frames (uORFs), another genic feature known to reduce translational efficiency. Functional enrichment analysis of genes exhibiting low Kp/Ku ratios reveals that genes in regulatory roles are particularly subject to this type of selection. CONCLUSION: Through genome-wide scans, we find recent selection for unpreferred codon usage at approximately 1% of genetic loci in a Cryptococcus and several genes in Drosophila. Unpreferred codons can impede translation efficiency, and we find that genes with translation-impeding uORFs are enriched for this selection signal. We find that regulatory genes are particularly likely to be subject to selection for unpreferred codon usage. Given that expression noise can propagate through regulatory cascades, and that low translational efficiency can reduce expression noise, this finding supports the hypothesis that translational efficiency may be suppressed in some cases to reduce stochastic noise in gene expression.

Dataset Information

Gaussian-Distributed Codon Frequencies of Genomes.

Publications

Gaussian-Distributed Codon Frequencies of Genomes.

Similar Datasets

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