Detection of structural mosaicism from targeted and whole-genome sequencing data
- Daniel A King1,
- Alejandro Sifrim1,
- Tomas W. Fitzgerald1,
- Raheleh Rahbari1,
- Emma Hobson2,
- Tessa Homfray3,
- Sahar Mansour3,
- Sarju G. Mehta4,
- Mohammed Shehla5,
- Susan E. Tomkins6,
- Pradeep C. Vasudevan7,
- Matthew E. Hurles1,9,
- The Deciphering Developmental Disorders Study8
- 1 Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom;
- 2 Chapel Allerton Hospital, Leeds, United Kingdom;
- 3 Southwest Thames Regional Genetics Centre, St George's Healthcare NHS Trust, London, United Kingdom;
- 4 East Anglian Regional Genetics Service, Addenbrookes Hospital, Cambridge, United Kingdom;
- 5 South East Thames Regional Genetics Centre, Guys Hospital, London, United Kingdom;
- 6 St Michael ′s Hospital, Bristol, United Kingdom;
- 7 Leicester Royal Infirmary, Leicester, United Kingdom;
- 8 -
Abstract
Structural mosaic abnormalities are large post-zygotic mutations present in a subset of cells and have been implicated in developmental disorders and cancer. Such mutations have been conventionally assessed in clinical diagnostics using cytogenetic or microarray testing. Modern disease studies rely heavily on exome sequencing, yet an adequate method for the detection of structural mosaicism using targeted sequencing data is lacking. Here, we present a method, called MrMosaic, to detect structural mosaic abnormalities using deviations in allele fraction and read coverage from next generation sequencing data. Whole-exome sequencing (WES) and whole-genome sequencing (WGS) simulations were used to calculate detection performance across a range of mosaic event sizes, types, clonalities, and sequencing depths. The tool was applied to 4,911 patients with undiagnosed developmental disorders, and 11 events in 9 patients were detected. In 8 of 11 cases, mosaicism was observed in saliva but not blood, suggesting that assaying blood alone would miss a large fraction, possibly more than 50%, of mosaic diagnostic chromosomal rearrangements.
- Received July 7, 2016.
- Accepted July 18, 2017.
- Published by Cold Spring Harbor Laboratory Press
This manuscript is Open Access.
This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International license), as described at http://creativecommons.org/licenses/by/4.0/.











