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

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 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.N.W. was supported by a Rosetrees and Stoneygate Imperial College Research Fellowship. This work was supported by the Wellcome Trust [107469/Z/15/Z; 200990/A/16/Z], Medical Research Council (UK), British Heart Foundation [RE/18/4/34215], National Institute for Health Research (NIHR) Royal Brompton Cardiovascular Biomedical Research Unit, and the NIHR Imperial College Biomedical Research Centre.published version, accepted version (12 month embargo), submitted versio