NatureGenomicsPeer-reviewed journal article
Whole-genome sequencing of rare disease patients in a national healthcare system
Ernest TurroiD, William J. Astle, Karyn MégyiD, Stefan GräfiD, Daniel Greene, Olga ShamardinaiD, Hana Lango AlleniD, Alba Sanchis‐JuaniD, Mattia FrontiniiD, Chantal Thys, Jonathan C. StephensiD, Rutendo P. Mapeta, Oliver S. BurreniD, Kate DownesiD, Matthias HaimeliD, Salih TunaiD, Sri V. V. DeeviiD, Timothy J. AitmaniD, David BennettiD, Paul Calleja, Keren CarssiD, Mark J. CaulfieldiD, Patrick Francis ChinneryiD, Peter H. DixoniD, Daniel Philip GaleiD, , Rachel J. BuchaniD
Abstract
Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and mediating genes for more than half such disorders remain to be discovered. We implemented whole-genome sequencing (WGS) in a national healthcare system to streamline diagnosis and to discover unknown aetiological variants, in the coding and non-coding regions of the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed aetiological. Using WGS of UK Biobank1, we showed that rare alleles can explain the presence of some individuals in the tails of a quantitative red blood cell (RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 570
- FWCI
- 48.65
- Field percentile
- top 1%
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