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Three-dimensional eukaryotic genomic organization is strongly correlated with codon usage expression and function

Author

Listed:
  • Alon Diament

    (Tel Aviv University)

  • Ron Y. Pinter

    (Technion—Israel Institute of Technology)

  • Tamir Tuller

    (Tel Aviv University
    The Sagol School of Neuroscience, Tel Aviv University)

Abstract

It has been shown that the distribution of genes in eukaryotic genomes is not random; however, formerly reported relations between gene function and genomic organization were relatively weak. Previous studies have demonstrated that codon usage bias is related to all stages of gene expression and to protein function. Here we apply a novel tool for assessing functional relatedness, codon usage frequency similarity (CUFS), which measures similarity between genes in terms of codon and amino acid usage. By analyzing chromosome conformation capture data, describing the three-dimensional (3D) conformation of the DNA, we show that the functional similarity between genes captured by CUFS is directly and very strongly correlated with their 3D distance in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, mouse and human. This emphasizes the importance of three-dimensional genomic localization in eukaryotes and indicates that codon usage is tightly linked to genome architecture.

Suggested Citation

  • Alon Diament & Ron Y. Pinter & Tamir Tuller, 2014. "Three-dimensional eukaryotic genomic organization is strongly correlated with codon usage expression and function," Nature Communications, Nature, vol. 5(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6876
    DOI: 10.1038/ncomms6876
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    Cited by:

    1. Alon Diament & Tamir Tuller, 2015. "Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-22, May.
    2. Behrouz Eslami-Mossallam & Raoul D Schram & Marco Tompitak & John van Noort & Helmut Schiessel, 2016. "Multiplexing Genetic and Nucleosome Positioning Codes: A Computational Approach," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-14, June.

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