Variation in the strength of selected codon usage bias among bacteria

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Variation in the strength of selected codon usage bias among bacteria

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 applie...

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Variation in the Correlation of G + C Composition with Synonymous Codon Usage Bias among Bacteria

G + C composition at the third codon position (GC3) is widely reported to be correlated with synonymous codon usage bias. However, no quantitative attempt has been made to compare the extent of this correlation among different genomes. Here, we applied Shannon entropy from information theory to measure the degree of GC3 bias and that of synonymous codon usage bias of each gene. The strength of ...

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

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 analysi...

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The influence of anticodon-codon interactions and modified bases on codon usage bias in bacteria.

Most transfer RNAs (tRNAs) can translate more than one synonymous codon, and most codons can be translated by more than one isoacceptor tRNA. The rates of translation of synonymous codons are dependent on the concentrations of the tRNAs and on the rates of pairing of each anticodon-codon combination. Translational selection causes a significant bias in codon frequencies in highly expressed gene...

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More Codon Usage Bias

χ measure. In statistics, the χ statstic computes how different the distribution of values is from a uniform distribution. Let d = c1 . . . cN be a DNA string in nucleotide alphabet, and let L be the total number of codons in d that are not Methinine or Tryptophan (the number does include the stop codons though). Let a be a k-degenerate amino acid, and let La be the total number of codons codin...

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ژورنال

عنوان ژورنال: Nucleic Acids Research

سال: 2005

ISSN: 1362-4962

DOI: 10.1093/nar/gki242