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Detection of structural mosaicism from targeted and whole-genome sequencing data

Daniel A. King, Alejandro Sifrim, Tomas W. Fitzgerald, Raheleh Rahbari, Emma Hobson, Tessa Homfray, Sahar Mansour, Sarju G. Mehta, Mohammed Shehla, Susan E. Tomkins, Pradeep C. Vasudevan, Matthew E. Hurles, The Deciphering Developmental Disorders Study
doi: https://doi.org/10.1101/062620
Daniel A. King
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
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Alejandro Sifrim
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
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Tomas W. Fitzgerald
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
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Raheleh Rahbari
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
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Emma Hobson
2Department of Clinical Genetics, Chapel Allerton Hospital, Leeds, United Kingdom
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Tessa Homfray
3Southwest Thames Regional Genetics Centre, St George’s Healthcare NHS Trust, London, United Kingdom
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Sahar Mansour
3Southwest Thames Regional Genetics Centre, St George’s Healthcare NHS Trust, London, United Kingdom
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Sarju G. Mehta
4East Anglian Regional Genetics Service, Addenbrookes Hospital, Cambridge, United Kingdom
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Mohammed Shehla
5Guy’s Hospital, London, United Kingdom
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Susan E. Tomkins
6Department of Clinical Genetics, St Michael’s Hospital, Bristol, United Kingdom
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Pradeep C. Vasudevan
7Leicester Royal Infirmary, Leicester, United Kingdom
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Matthew E. Hurles
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom
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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.

Footnotes

  • Daniel A. King: dk6{at}sanger.ac.uk, Alejandro Sifrim: as33{at}sanger.ac.uk Tomas W. Fitzgerald: tomas{at}ebi.ac.uk, Raheleh Rahbari: rr11{at}sanger.ac.uk Emma.hobson: emma.hobson{at}nhs.net Tessa Homfray: thomfray{at}sgul.ac.uk Sahar Mansour: smansour{at}sgul.ac.uk Sarju G Mehta: sarju.mehta{at}addenbrookes.nhs.uk Mohammed Shehla: Shehla.Mohammed{at}gstt.nhs.uk Susan E. Tomkins: Susan.Tomkins{at}UHBristol.nhs.uk Pradeep C. Vasudevan: pradeep.vasudevan{at}uhl-tr.nhs.uk Matthew E. Hurles: meh{at}sanger.ac.uk

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 07, 2016.
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Detection of structural mosaicism from targeted and whole-genome sequencing data
Daniel A. King, Alejandro Sifrim, Tomas W. Fitzgerald, Raheleh Rahbari, Emma Hobson, Tessa Homfray, Sahar Mansour, Sarju G. Mehta, Mohammed Shehla, Susan E. Tomkins, Pradeep C. Vasudevan, Matthew E. Hurles, The Deciphering Developmental Disorders Study
bioRxiv 062620; doi: https://doi.org/10.1101/062620
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Detection of structural mosaicism from targeted and whole-genome sequencing data
Daniel A. King, Alejandro Sifrim, Tomas W. Fitzgerald, Raheleh Rahbari, Emma Hobson, Tessa Homfray, Sahar Mansour, Sarju G. Mehta, Mohammed Shehla, Susan E. Tomkins, Pradeep C. Vasudevan, Matthew E. Hurles, The Deciphering Developmental Disorders Study
bioRxiv 062620; doi: https://doi.org/10.1101/062620

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