Comprehensive Analysis and Comparison on the Codon Usage Pattern of Whole Mycobacterium tuberculosis Coding Genome
Li Gun1, Ren Yumiao1, Pan Haixian1
1Department of Biomedical Engineering, School of Electronic Information Engineering, Xi'an Technological University, Xi'an, China.
Biomed Research International
|June 2, 2018
Summary
Codon usage bias is prevalent in Mycobacterium tuberculosis genomes, impacting gene expression and translation efficiency. This bias offers insights into the bacterium's evolution and genetic characteristics.
Area of Science:
- Microbiology
- Genomics
- Evolutionary Biology
Background:
- Unequal usage of synonymous codons, known as codon usage bias, is a common phenomenon in Mycobacterium tuberculosis.
- This bias significantly influences gene expression regulation, translation accuracy, and efficiency.
- Understanding codon usage patterns is crucial for interpreting the evolutionary history of Mycobacterium tuberculosis.
Purpose of the Study:
- To investigate the codon usage patterns across 12 different Mycobacterium tuberculosis genomes.
- To analyze the correlations between various genomic metrics and codon usage bias.
- To explore the relationship between codon bias and evolutionary characteristics.
Main Methods:
- Downloaded 12 Mycobacterium tuberculosis genomes from GeneBank.
- Calculated correlations between G3, GC12, whole GC content, codon adaptation index (CAI), and codon bias index (CBI).
- Utilized ENC-plot, nucleotide composition plots (GC12 vs GC3), and relative synonymous codon usage (RSCU) analysis.
Main Results:
- Codon usage bias was confirmed in all 12 analyzed Mycobacterium tuberculosis genomes.
- A strong negative correlation was observed between the codon bias index (CBI) and the equalization of effective number of codons (ENC).
- Shorter proteins exhibited more pronounced differences in GC content (GC3 and GC12).
Conclusions:
- The study confirms the existence and significance of codon usage bias in Mycobacterium tuberculosis.
- Codon usage patterns provide valuable data for further research into the evolutionary dynamics of Mycobacterium tuberculosis.
- These findings contribute to a deeper understanding of Mycobacterium tuberculosis genomics and evolution.
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