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BioinformaticsBioinformatics
Peer-reviewed journal article

Annotating high-impact 5'untranslated region variants with the UTRannotator

Xiaolei ZhangiD, Matthew Neil WakelingiD, James S. WareiD, Nicola WhiffiniD

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Abstract

SummaryCurrent 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 5untranslated regions (5UTR) 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 5UTR (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. Availability and implementationUTRannotator is freely available on Github: https://github.com/ImperialCardioGenetics/UTRannotator Supplementary informationSupplementary data are available at bioRxiv.

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