Journal
BIOINFORMATICS
Volume 37, Issue 8, Pages 1171-1173Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa783
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Funding
- Rosetrees and Stoneygate Imperial College Research Fellowship
- 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
- NIHR Imperial College Biomedical Research Centre
- MRC [MC_UP_1102/20] Funding Source: UKRI
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Current tools for annotating genetic variants heavily focus on protein-coding sequences, rather than non-coding variants, which can be challenging to predict. Our UTRannotator plugin offers a new approach to annotate variants in 5'UTRs, providing insights into their impact.
A 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.
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