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Codon selection reduces GC content bias in nucleic acids encoding for intrinsically disordered proteins

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Abstract

Protein-coding nucleic acids exhibit composition and codon biases between sequences coding for intrinsically disordered regions (IDRs) and those coding for structured regions. IDRs are regions of proteins that are folding self-insufficient and which function without the prerequisite of folded structure. Several authors have investigated composition bias or codon selection in regions encoding for IDRs, primarily in Eukaryota, and concluded that elevated GC content is the result of the biased amino acid composition of IDRs. We substantively extend previous work by examining GC content in regions encoding IDRs, from 44 species in Eukaryota, Archaea, and Bacteria, spanning a wide range of GC content. We confirm that regions coding for IDRs show a significantly elevated GC content, even across all domains of life. Although this is largely attributable to the amino acid composition bias of IDRs, we show that this bias is independent of the overall GC content and, most importantly, we are the first to observe that GC content bias in IDRs is significantly different than expected from IDR amino acid composition alone. We empirically find compensatory codon selection that reduces the observed GC content bias in IDRs. This selection is dependent on the overall GC content of the organism. The codon selection bias manifests as use of infrequent, AT-rich codons in encoding IDRs. Further, we find these relationships to be independent of the intrinsic disorder prediction method used, and independent of estimated translation efficiency. These observations are consistent with the previous work, and we speculate on whether the observed biases are causal or symptomatic of other driving forces.

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Acknowledgements

This research was supported in part by the National Science Foundation Grant 1617369 and the Robert J. Mattauch Endowment from Virginia Commonwealth University to L.K.

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Authors and Affiliations

  1. Department of Computer Science, Virginia Commonwealth University, Richmond, VA, 23284, USA

    Christopher J. Oldfield & Lukasz Kurgan

  2. Center for Applied Mathematics, Tianjin University, Tianjin, 300072, China

    Zhenling Peng

  3. Department of Molecular Medicine and USF Health Byrd Alzheimer’s Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL, 33612, USA

    Vladimir N. Uversky

  4. Institute for Biological Instrumentation, Russian Academy of Sciences, 142290, Pushchino, Moscow Region, Russia

    Vladimir N. Uversky

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  1. Christopher J. Oldfield
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Correspondence to Christopher J. Oldfield or Lukasz Kurgan.

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Oldfield, C.J., Peng, Z., Uversky, V.N. et al. Codon selection reduces GC content bias in nucleic acids encoding for intrinsically disordered proteins. Cell. Mol. Life Sci. 77, 149–160 (2020). https://doi.org/10.1007/s00018-019-03166-6

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