Dataset Information

Codon usage pattern and its influencing factors in different genomes of hepadnaviruses.

ABSTRACT: Codon usage bias (CUB) arises from the preference for a codon over codons for the same amino acid. The major factors contributing to CUB are evolutionary forces, compositional properties, gene expression, and protein properties. The present analysis was performed to investigate the compositional properties and the extent of CUB across the genomes of members of the family Hepadnaviridae, as previously no work using bioinformatic tools has been reported. The viral genes were found to be AT rich with low CUB. Analysis of relative synonymous codon usage (RSCU) was used to identify overrepresented and underrepresented codons for each amino acid. Correlation analysis of overall nucleotide composition and its composition at the third codon position suggested that mutation pressure might influence the CUB. A highly significant correlation was observed between GC12 and GC3 (r = 0.910, p < 0.01), indicating that directional mutation affected all three codon positions across the genome. Translational selection (P2) and mutational responsive index (MRI) values of genes suggested that mutation plays a more important role than translational selection in members of the family Hepadnaviridae.

SUBMITTER: Deb B

PROVIDER: S-EPMC7086886 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Codon usage pattern and its influencing factors in different genomes of hepadnaviruses.

Deb Bornali B Uddin Arif A Chakraborty Supriyo S

Archives of virology 20200208 3

Codon usage bias (CUB) arises from the preference for a codon over codons for the same amino acid. The major factors contributing to CUB are evolutionary forces, compositional properties, gene expression, and protein properties. The present analysis was performed to investigate the compositional properties and the extent of CUB across the genomes of members of the family Hepadnaviridae, as previously no work using bioinformatic tools has been reported. The viral genes were found to be AT rich wi ...[more]

PMID: 32036428

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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.

Dataset Information

Codon usage pattern and its influencing factors in different genomes of hepadnaviruses.

Publications

Codon usage pattern and its influencing factors in different genomes of hepadnaviruses.

Similar Datasets

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