Recommendations for clinical interpretation of variants found in non-coding regions of the genome
Jamie M. EllingfordiD, Joo Wook AhniD, Richard D. BagnalliD, Diana BaralleiD, Stephanie Barton, Chris Campbell, Kate DownesiD, Sian EllardiD, Celia R. A. Duff‐Farrier, David R FitzPatrickiD, John M. GreallyiD, Jodie InglesiD, Neesha Krishnan, Jenny LordiD, Hilary C. MartiniD, William G. NewmaniD, Anne O’Donnell‐LuriaiD, Simon Ramsden, Heidi L. RehmiD, Ebony RichardsoniD, Moriel Singer‐BerkiD, Jenny C. TayloriD, Maggie WilliamsiD, Jordan C. WoodiD, Caroline Fiona WrightiD, , Nicola WhiffiniD
Abstract
PurposeThe majority of clinical genetic testing focuses almost exclusively on regions of the genome that directly encode proteins. The important role of variants in non-coding regions in penetrant disease is, however, increasingly being demonstrated, and the use of whole genome sequencing in clinical diagnostic settings is rising across a large range of genetic disorders. Despite this, there is no existing guidance on how current guidelines designed primarily for variants in protein-coding regions should be adapted for variants identified in other genomic contexts. MethodsWe convened a panel of clinical and research scientists with wide-ranging expertise in clinical variant interpretation, with specific experience in variants within non-coding regions. This panel discussed and refined an initial draft of the guidelines which were then extensively tested and reviewed by external groups. ResultsWe discuss considerations specifically for variants in non-coding regions of the genome. We outline how to define candidate regulatory elements, highlight examples of mechanisms through which non-coding region variants can lead to penetrant monogenic disease, and outline how existing guidelines can be adapted for these variants. ConclusionThese recommendations aim to increase the number and range of non-coding region variants that can be clinically interpreted, which, together with a compatible phenotype, can lead to new diagnoses and catalyse the discovery of novel disease mechanisms.
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