Method

A novel method for detecting uniparental disomy from trio genotypes identifies a significant excess in children with developmental disorders

    • 1Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1HH, United Kingdom;
    • 2North West Thames Regional Genetics Service, North West London Hospitals NHS Trust, Harrow, Middlesex HA1 3UJ, United Kingdom;
    • 3Centre for Genetic Medicine, Institute of Human Development, Faculty of Medical and Human Sciences, University of Manchester and Central Manchester University Hospitals NHS Foundation Trust, Manchester M13 9WU, United Kingdom;
    • 4Sheffield Genetics Service, Sheffield Children’s NHS Foundation Trust, Sheffield S10 2TH, United Kingdom;
    • 5South West Thames Regional Genetics Service, St. George’s Healthcare NHS Trust, London SW17 0QT, United Kingdom;
    • 6Northern Ireland Regional Genetics Centre, Belfast City Hospital, Belfast BT9 7AB, United Kingdom;
    • 7Leicestershire Genetics Centre, Leicester Royal Infirmary, University Hospitals of Leicester, NHS Trust Infirmary Square, Leicester LE1 5WW, United Kingdom
Published December 19, 2013. Vol 24 Issue 4, pp. 673-687. https://doi.org/10.1101/gr.160465.113
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Abstract

Exome sequencing of parent-offspring trios is a popular strategy for identifying causative genetic variants in children with rare diseases. This method owes its strength to the leveraging of inheritance information, which facilitates de novo variant calling, inference of compound heterozygosity, and the identification of inheritance anomalies. Uniparental disomy describes the inheritance of a homologous chromosome pair from only one parent. This aberration is important to detect in genetic disease studies because it can result in imprinting disorders and recessive diseases. We have developed a software tool to detect uniparental disomy from child–mother–father genotype data that uses a binomial test to identify chromosomes with a significant burden of uniparentally inherited genotypes. This tool is the first to read VCF-formatted genotypes, to perform integrated copy number filtering, and to use a statistical test inherently robust for use in platforms of varying genotyping density and noise characteristics. Simulations demonstrated superior accuracy compared with previously developed approaches. We implemented the method on 1057 trios from the Deciphering Developmental Disorders project, a trio-based rare disease study, and detected six validated events, a significant enrichment compared with the population prevalence of UPD (1 in 3500), suggesting that most of these events are pathogenic. One of these events represents a known imprinting disorder, and exome analyses have identified rare homozygous candidate variants, mainly in the isodisomic regions of UPD chromosomes, which, among other variants, provide targets for further genetic and functional evaluation.

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