Annotating high-impact 5’untranslated region variants with the UTRannotator
Author(s)
Zhang, Xiaolei
Wakeling, Matthew
Ware, James
Whiffin, Nicola
Type
Working Paper
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 (uORFs). We investigate the utility of this tool using the ClinVar database, providing an annotation for 30.8% 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 UTR annotator as we gain new knowledge on the impact of variants in UTRs.
Date Issued
2020-06-04
Citation
2020
Publisher
Cold Spring Harbor Laboratory
Copyright Statement
© 2021 The Author(s). It is made available under a CC-BY-NC-ND 4.0 International license.
Identifier
https://www.biorxiv.org/content/10.1101/2020.06.03.132266v1
Publication Status
Published