Literature DB >> 31175370

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

Christopher J Oldfield1, Zhenling Peng2, Vladimir N Uversky3,4, Lukasz Kurgan5.   

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.

Entities:  

Keywords:  Amino acid composition; Codon selection; GC content; Intrinsically disordered proteins

Mesh:

Substances:

Year:  2019        PMID: 31175370     DOI: 10.1007/s00018-019-03166-6

Source DB:  PubMed          Journal:  Cell Mol Life Sci        ISSN: 1420-682X            Impact factor:   9.261


  55 in total

1.  Predicting Protein Disorder for N-, C-, and Internal Regions.

Authors: 
Journal:  Genome Inform Ser Workshop Genome Inform       Date:  1999

2.  Why are "natively unfolded" proteins unstructured under physiologic conditions?

Authors:  V N Uversky; J R Gillespie; A L Fink
Journal:  Proteins       Date:  2000-11-15

Review 3.  Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm.

Authors:  P E Wright; H J Dyson
Journal:  J Mol Biol       Date:  1999-10-22       Impact factor: 5.469

4.  The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins.

Authors:  Zsuzsanna Dosztányi; Veronika Csizmók; Péter Tompa; István Simon
Journal:  J Mol Biol       Date:  2005-04-08       Impact factor: 5.469

5.  Extensive lysine methylation in hyperthermophilic crenarchaea: potential implications for protein stability and recombinant enzymes.

Authors:  Catherine H Botting; Paul Talbot; Sonia Paytubi; Malcolm F White
Journal:  Archaea       Date:  2010-08-05       Impact factor: 3.273

6.  Codon selection in yeast.

Authors:  J L Bennetzen; B D Hall
Journal:  J Biol Chem       Date:  1982-03-25       Impact factor: 5.157

7.  Bioinformatics analysis of disordered proteins in prokaryotes.

Authors:  Gordana M Pavlović-Lažetić; Nenad S Mitić; Jovana J Kovačević; Zoran Obradović; Saša N Malkov; Miloš V Beljanski
Journal:  BMC Bioinformatics       Date:  2011-03-02       Impact factor: 3.169

8.  Reorganizing the protein space at the Universal Protein Resource (UniProt).

Authors: 
Journal:  Nucleic Acids Res       Date:  2011-11-18       Impact factor: 16.971

9.  Genetic recombination is associated with intrinsic disorder in plant proteomes.

Authors:  Inmaculada Yruela; Bruno Contreras-Moreira
Journal:  BMC Genomics       Date:  2013-11-09       Impact factor: 3.969

10.  What Signatures Dominantly Associate with Gene Age?

Authors:  Hongyan Yin; Guangyu Wang; Lina Ma; Soojin V Yi; Zhang Zhang
Journal:  Genome Biol Evol       Date:  2016-10-13       Impact factor: 3.416

View more
  1 in total

1.  Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19.

Authors:  Komi Nambou; Manawa Anakpa
Journal:  Infect Genet Evol       Date:  2020-07-22       Impact factor: 3.342

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.