Variation in the strength of selected codon usage bias among bacteria.
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ABSTRACT:
SUBMITTER: Sharp PM
PROVIDER: S-EPMC549432 | biostudies-literature | 2005
REPOSITORIES: biostudies-literature
Publications
Variation in the strength of selected codon usage bias among bacteria.
Sharp Paul M PM Bailes Elizabeth E Grocock Russell J RJ Peden John F JF Sockett R Elizabeth RE
Nucleic acids research 20050223 4
Among bacteria, many species have synonymous codon usage patterns that have been influenced by natural selection for those codons that are translated more accurately and/or efficiently. However, in other species selection appears to have been ineffective. Here, we introduce a population genetics-based model for quantifying the extent to which selection has been effective. The approach is applied to 80 phylogenetically diverse bacterial species for which whole genome sequences are available. The ...[more]
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Project description:Codon usage bias is the preferential or non-random use of synonymous codons, a ubiquitous phenomenon observed in bacteria, plants and animals. Different species have consistent and characteristic codon biases. Codon bias varies not only with species, family or group within kingdom, but also between the genes within an organism. Codon usage bias has evolved through mutation, natural selection, and genetic drift in various organisms. Genome composition, GC content, expression level and length of genes, position and context of codons in the genes, recombination rates, mRNA folding, and tRNA abundance and interactions are some factors influencing codon bias. The factors shaping codon bias may also be involved in evolution of the universal genetic code. Codon-usage bias is critical factor determining gene expression and cellular function by influencing diverse processes such as RNA processing, protein translation and protein folding. Codon usage bias reflects the origin, mutation patterns and evolution of the species or genes. Investigations of codon bias patterns in genomes can reveal phylogenetic relationships between organisms, horizontal gene transfers, molecular evolution of genes and identify selective forces that drive their evolution. Most important application of codon bias analysis is in the design of transgenes, to increase gene expression levels through codon optimization, for development of transgenic crops. The review gives an overview of deviations of genetic code, factors influencing codon usage or bias, codon usage bias of nuclear and organellar genes, computational methods to determine codon usage and the significance as well as applications of codon usage analysis in biological research, with emphasis on plants.
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Project description:Codon usage is biased between lowly and highly expressed genes in a genome-specific manner. This universal bias has been well assessed in some unicellular species, but remains problematic to assess in more complex species. We propose a new method to compute codon usage bias based on genome wide translational data. A new technique based on sequencing of ribosome protected mRNA fragments (Ribo-seq) allowed us to rank genes and compute codon usage bias with high precision for a great variety of species, including mammals. Genes ranking using Ribo-Seq data confirms the influence of the tRNA pool on codon usage bias and shows a decreasing bias in multicellular species. Ribo-Seq analysis also makes possible to detect preferred codons without information on genes function.
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Project description:Severe acute respiratory syndrome has spread quickly throughout the world and was declared a pandemic by the World Health Organization (WHO). The pathogenic agent is a new coronavirus (SARS-CoV-2) that infects pulmonary cells with great effectiveness. In this study we focus on the codon composition for the viral protein synthesis and its relationship with the protein synthesis of the host. Our analysis reveals that SARS-CoV-2 preferred codons have poor representation of G or C nucleotides in the third position, a characteristic which could result in an unbalance in the tRNAs pools of the infected cells with serious implications in host protein synthesis. By integrating this observation with proteomic data from infected cells, we observe a reduced translation rate of host proteins associated with highly expressed genes and that they share the codon usage bias of the virus. The functional analysis of these genes suggests that this mechanism of epistasis can contribute to understanding how this virus evades the immune response and the etiology of some deleterious collateral effect as a result of the viral replication. In this manner, our finding contributes to the understanding of the SARS-CoV-2 pathogeny and could be useful for the design of a vaccine based on the live attenuated strategy.
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Project description:We propose a simple, sensitive measure of synonymous codon usage bias, the Relative Codon Adaptation Index (rCAI), as a way to discriminate better between highly biased and unbiased regions, compared with the widely used Codon Adaptation Index (CAI). CAI is a geometric mean of the relative usage of codons in a gene, and is calculated using the codon usage table trained with a set of highly expressed genes. In contrast, rCAI is computed by subtracting the background codon usage trained with two noncoding frames of highly expressed genes from the codon usage in the coding frame. rCAI has higher signal-to-noise ratio than CAI, considering that noncoding frames would not show codon bias. Translation efficiency and protein abundance correlates comparably or better with rCAI than CAI or other measures such as 'effective number of codons' and 'SCUMBLE offsets'. Within overlapping coding regions, one of the two coding frames dominates in codon usage bias according to rCAI. Presumably, rCAI could substitute CAI in diverse applications.
| S-EPMC2880845 | biostudies-literature