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- Title
Annotating high-impact 5′untranslated region variants with the UTRannotator.
- Authors
Zhang, Xiaolei; Wakeling, Matthew; Ware, James; Whiffin, Nicola
- Abstract
Summary Current tools to annotate the predicted effect of genetic variants are heavily biased towards protein-coding sequence. Variants outside of these regions may have a large impact on protein expression and/or structure and can lead to disease, but this effect can be challenging to predict. Consequently, these variants are poorly annotated using standard tools. We have developed a plugin to the Ensembl Variant Effect Predictor, the UTRannotator, that annotates variants in 5 ′ untranslated regions (5 ′ UTR) that create or disrupt upstream open reading frames. We investigate the utility of this tool using the ClinVar database, providing an annotation for 31.9% of all 5 ′ UTR (likely) pathogenic variants, and highlighting 31 variants of uncertain significance as candidates for further follow-up. We will continue to update the UTRannotator as we gain new knowledge on the impact of variants in UTRs. Availability and implementation UTRannotator is freely available on Github: https://github.com/ImperialCardioGenetics/UTRannotator. Supplementary information Supplementary data are available at Bioinformatics online.
- Subjects
PROTEIN expression; OPEN reading frames (Genetics); FORECASTING
- Publication
Bioinformatics, 2021, Vol 37, Issue 8, p1171
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/btaa783