Proteome-wide signatures of function in highly diverged intrinsically disordered regions
Abstract
Intrinsically disordered regions make up a large part of the proteome, but the sequence-to-function relationship in these regions is poorly understood, in part because the primary amino acid sequences of these regions are poorly conserved in alignments. Here we use an evolutionary approach to detect molecular features that are preserved in the amino acid sequences of orthologous intrinsically disordered regions. We find that most disordered regions contain multiple molecular features that are preserved, and we define these as 'evolutionary signatures' of disordered regions. We demonstrate that intrinsically disordered regions with similar evolutionary signatures can rescue function in vivo, and that groups of intrinsically disordered regions with similar evolutionary signatures are strongly enriched for functional annotations and phenotypes. We propose that evolutionary signatures can be used to predict function for many disordered regions from their amino acid sequences.
Data availability
The analysis is based on publically available sequence data from YGOB. Source data has been included as supplementary data.
Article and author information
Author details
Funding
National Sciences and Engineering Research Council (Alexander Graham Bell Scholarship)
- Taraneh Zarin
National Sciences and Engineering Research Council (Discovery Grant)
- Alan M Moses
Canadian Institutes of Health Research (PJT-148532)
- Julie Deborah Forman-Kay
- Alan M Moses
Canadian Institutes of Health Research (FDN-148375)
- Julie Deborah Forman-Kay
Canada Research Chairs
- Julie Deborah Forman-Kay
Canadian Foundation for Innovation
- Alan M Moses
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Zarin et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 8,406
- views
-
- 1,310
- downloads
-
- 169
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.