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Comparative analysis of codon usage bias and codon context patterns between dipteran and hymenopteran sequenced
Susanta K Behura1, David W Severson
1Eck Institute for Global Health, Department of Biological Sciences. University of Notre Dame, Notre Dame, Indiana, United States of America. sbehura@nd.edu
Plos One
|August 23, 2012
Summary
Codon bias patterns differ between dipteran and hymenopteran insects, influenced by genome GC/AT content. Codon context also varies phylogenetically across these insect groups.
Area of Science:
- Genomics
- Bioinformatics
- Evolutionary Biology
Background:
- Codon bias describes non-uniform codon usage within genes.
- Codon context examines sequential codon pairs, offering insights into gene expression regulation.
- Limited analysis exists for codon usage bias in many dipteran and hymenopteran insects despite available genome data.
Purpose of the Study:
- To perform a genome-wide analysis of codon usage bias and codon context patterns in dipteran and hymenopteran insects.
- To compare codon usage bias and context patterns across species to identify evolutionary trends.
- To investigate the relationship between genomic composition (GC/AT content) and codon bias.
Main Methods:
- Bioinformatics approaches were employed for genome-wide analysis.
- Codon usage bias and codon context patterns were analyzed across 15 dipteran and 7 hymenopteran species.
- Comparative analysis included 30 one-to-one orthologous genes from 17 species.
Main Results:
- GAA was the most frequent codon in dipterans; GAG in hymenopterans.
- Dipteran genomes favored codons ending in C or G, while hymenopteran genomes favored codons ending in A or T.
- Drosophila willistoni exhibited the least codon bias, while Apis mellifera showed the highest; codon context near start/stop codons varied phylogenetically.
Conclusions:
- Distinct codon bias patterns exist between dipteran and hymenopteran insects, linked to GC and AT content, respectively.
- Codon context patterns correlate with species phylogeny.
- These findings provide insights into insect genome evolution and gene expression strategies.
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