Journal
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
Volume 18, Issue -, Pages 306-313Publisher
ELSEVIER
DOI: 10.1016/j.csbj.2020.01.012
Keywords
Homorepeat; polyQ; Glutamine; Sequence context; Codon usage
Funding
- Deutsche Forschungsgemeinschaft [AN735/4-1]
- European Research Councilunder the European Union's H2020 Framework Programme (2014-2020)/ERC Grant [648030]
- Labex EpiGenMed, an Investissements d'avenir program [ANR-10-LABX-12-01]
- French National Research Agency [ANR-10-INBS-04-01, ANR-10-INBS-05]
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Polyglutamine (polyQ) regions are one of the most prevalent homorepeats in eukaryotes. It is however difficult to evaluate their prevalence because various studies claim different results. The reason is the lack of a consensus to define what is indeed a polyQ region. We have tackled this issue by studying how the use of different thresholds (i.e., minimum number of glutamines required in a protein region of a given size), to detect polyQ regions in the human proteome influences not only their prevalence but also their general features and sequence context. Threshold definition shapes the length distribution of the polyQ dataset, and changes the observed number and position of impurities (amino acids other than glutamine) within polyQ regions. Irrespective of the chosen threshold, leucine and proline residues are enriched both within and around polyQ. While leucine is enriched at the N-terminus of polyQ and specially at position -1 (amino acid preceding the polyQ), proline is prevalent in the C-terminus (positions +1 to +5, that is, the first five amino acids after the polyQ). We also checked the suitability of these thresholds for other species, and compared their polyQ features with those found in humans. As the sequence context and features of polyQ regions are threshold-dependent, we propose a method to quickly scan the polyQ landscape of a proteome. We complement our results with a summarized overview about which biases are to be expected per threshold when studying polyQ regions. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
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