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 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 implementationUTRannotator is freely available on Github: https://github.com/ImperialCardioGenetics/UTRannotator.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
Upstream open reading frames are short sequences within 50untranslated regions (50UTR) that regulate the rate at which the downstream coding sequence is translated into protein
We have developed a plugin to the Ensembl Variant Effect Predictor, the UTRannotator, that annotates variants in 50untranslated regions (50UTR) 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 50UTR pathogenic variants, and highlighting 31 variants of uncertain significance as candidates for further follow-up
Summary
Upstream open reading frames (uORFs) are short sequences within 50UTRs that regulate the rate at which the downstream coding sequence is translated into protein. We recently used data from the Genome Aggregation Database (gnomAD) to systematically characterize the deleteriousness of different categories of uORF-perturbing variants and prioritize those that are more likely to be disease causing (Whiffin et al, 2020). To aid the assessment of high-impact uORF-perturbing variants, we have developed a plugin for VEP to identify 50UTR variants that create upstream start sites (uAUGs), disrupt the start or stop codon of existing uORFs, create a new stop codon within existing uORFs, or shift the frame of an existing uORF. The tool outputs detailed annotations that allow the user to predict the likely impact of the variant on protein translation
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
