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Related Experiment Video

Updated: Feb 19, 2026

Optimizing the Genetic Incorporation of Chemical Probes into GPCRs for Photo-crosslinking Mapping and Bioorthogonal Chemistry in Live Mammalian Cells
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A content-centric organization of the genetic code.

Jun Yu1

  • 1Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 101300, China. junyu@genomics.org.cn

Genomics, Proteomics & Bioinformatics
|June 19, 2007
PubMed
Summary

This study rearranges the genetic codon table based on GC and purine content, revealing how genomic composition influences amino acid selection and mutation tolerance in prokaryotes.

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • The canonical genetic code dictates amino acid translation from codons.
  • Genomic composition, particularly GC content, varies across prokaryotic genomes.
  • Understanding the relationship between genomic features and amino acid usage is crucial.

Purpose of the Study:

  • To explore a rearranged codon table based on GC and purine content variability.
  • To investigate how genomic GC content influences amino acid composition and codon usage in prokaryotes.
  • To explain the relationship between protein coding sequences and amino acid content.

Main Methods:

  • Rearrangement of the canonical genetic codon table into four quarters and two halves based on GC and purine content.

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  • Analysis of codon usage patterns in prokaryotic genomes with varying GC content.
  • Correlation of codon features with amino acid properties and mutation tolerance.

    • Main Results:

    • Genomic GC content correlates with shifts in codon usage towards GC-rich or AU-rich quarters.
    • Prokaryotic genomes with high GC content favor mutation-tolerant, GC-rich codons.
    • Genomes with low GC content utilize AU-rich codons, encoding diverse amino acids sensitive to transversions.
    • Sixfold-degenerate codons are strategically placed for mutation robustness.

    Conclusions:

    • The rearranged codon table elucidates the link between genomic information content and functional amino acid composition.
    • This framework aids in predicting amino acid abundance and understanding physico-chemical property distributions.
    • The findings offer insights into the evolutionary pressures shaping genetic codes.