Saturation genome editing of DDX3X clarifies pathogenicity of germline and somatic variation

Elizabeth J. Radford, Hong-Kee Tan, Malin H. L. Andersson, James D. Stephenson, Eugene J. Gardner, Holly Ironfield, Andrew J. Waters, Daniel Gitterman, Sarah Lindsay, Federico Abascal, Iñigo Martincorena, Anna Kolesnik-Taylor, Elise Ng-Cordell, Helen V. Firth, Kate Baker, John R. B. Perry, David J. Adams, Sebastian S. Gerety and Matthew E. Hurles ()
Additional contact information
Elizabeth J. Radford: Wellcome Sanger Institute
Hong-Kee Tan: Wellcome Sanger Institute
Malin H. L. Andersson: Wellcome Sanger Institute
James D. Stephenson: EMBL-EBI, Wellcome Genome Campus
Eugene J. Gardner: MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus
Holly Ironfield: Wellcome Sanger Institute
Andrew J. Waters: Wellcome Sanger Institute
Daniel Gitterman: Wellcome Sanger Institute
Sarah Lindsay: Wellcome Sanger Institute
Federico Abascal: Wellcome Sanger Institute
Iñigo Martincorena: Wellcome Sanger Institute
Anna Kolesnik-Taylor: University of Cambridge
Elise Ng-Cordell: University of Cambridge
Helen V. Firth: Wellcome Sanger Institute
Kate Baker: University of Cambridge
John R. B. Perry: MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus
David J. Adams: Wellcome Sanger Institute
Sebastian S. Gerety: Wellcome Sanger Institute
Matthew E. Hurles: Wellcome Sanger Institute

Nature Communications, 2023, vol. 14, issue 1, 1-17

Abstract: Abstract Loss-of-function of DDX3X is a leading cause of neurodevelopmental disorders (NDD) in females. DDX3X is also a somatically mutated cancer driver gene proposed to have tumour promoting and suppressing effects. We perform saturation genome editing of DDX3X, testing in vitro the functional impact of 12,776 nucleotide variants. We identify 3432 functionally abnormal variants, in three distinct classes. We train a machine learning classifier to identify functionally abnormal variants of NDD-relevance. This classifier has at least 97% sensitivity and 99% specificity to detect variants pathogenic for NDD, substantially out-performing in silico predictors, and resolving up to 93% of variants of uncertain significance. Moreover, functionally-abnormal variants can account for almost all of the excess nonsynonymous DDX3X somatic mutations seen in DDX3X-driven cancers. Systematic maps of variant effects generated in experimentally tractable cell types have the potential to transform clinical interpretation of both germline and somatic disease-associated variation.

Date: 2023
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DOI: 10.1038/s41467-023-43041-4

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