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

Author

King, DA, Sifrim, A, Fitzgerald, TW, Rahbari, R, Hobson, E, Homfray, T, Mansour, S, Mehta, SG, Shehla, M, Tomkins, SE, Vasudevan, PC, Hurles, ME, and Deciphering Developmental Disorders Study

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 4911 patients with undiagnosed developmental disorders, and 11 events among nine patients were detected. For eight of these 11 events, mosaicism was observed in saliva but not blood, suggesting that assaying blood alone would miss a large fraction, possibly >50%, of mosaic diagnostic chromosomal rearrangements.

Published
2017

2. Prevalence and architecture of de novo mutations in developmental disorders

Author

McRae, JF, Clayton, S, Fitzgerald, TW, Kaplanis, J, Prigmore, E, Rajan, D, Sifrim, A, Aitken, S, Akawi, N, Alvi, M, Ambridge, K, Barrett, DM, Bayzetinova, T, Jones, P, Jones, WD, King, D, Krishnappa, N, Mason, LE, Singh, T, Tivey, AR, Ahmed, M, Anjum, U, Archer, H, Armstrong, R, Awada, J, Balasubramanian, M, Banka, S, Baralle, D, Barnicoat, A, Batstone, P, Baty, D, Bennett, C, Berg, J, Bernhard, B, Bevan, AP, Bitner-Glindzicz, M, Blair, E, Blyth, M, Bohanna, D, Bourdon, L, Bourn, D, Bradley, L, Brady, A, Brent, S, Brewer, C, Brunstrom, K, Bunyan, DJ, Burn, J, Canham, N, Castle, B, Chandler, K, Chatzimichali, E, Cilliers, D, Clarke, A, Clasper, S, Clayton-Smith, J, Clowes, V, Coates, A, Cole, T, Colgiu, I, Collins, A, Collinson, MN, Connell, F, Cooper, N, Cox, H, Cresswell, L, Cross, G, Crow, Y, D’Alessandro, M, Dabir, T, Davidson, R, Davies, S, de Vries, D, Dean, J, Deshpande, C, Devlin, G, Dixit, A, Dobbie, A, Donaldson, A, Donnai, D, Donnelly, D, Donnelly, C, Douglas, A, Douzgou, S, Duncan, A, Eason, J, Ellard, S, Ellis, I, Elmslie, F, Evans, K, Everest, S, Fendick, T, Fisher, R, Flinter, F, Foulds, N, Fry, A, Fryer, A, Gardiner, C, Gaunt, L, Ghali, N, Gibbons, R, Gill, H, Goodship, J, Goudie, D, Gray, E, Green, A, Greene, P, Greenhalgh, L, Gribble, S, Harrison, R, Harrison, L, Harrison, V, Hawkins, R, He, L, Hellens, S, Henderson, A, Hewitt, S, Hildyard, L, Hobson, E, Holden, S, Holder, M, Holder, S, Hollingsworth, G, Homfray, T, Humphreys, M, Hurst, J, Hutton, B, Ingram, S, Irving, M, Islam, L, Jackson, A, Jarvis, J, Jenkins, L, Johnson, D, Jones, E, Josifova, D, Joss, S, Kaemba, B, Kazembe, S, Kelsell, R, Kerr, B, Kingston, H, Kini, U, Kinning, E, Kirby, G, Kirk, C, Kivuva, E, Kraus, A, Kumar, D, Kumar, VKA, Lachlan, K, Lam, W, Lampe, A, Langman, C, Lees, M, Lim, D, Longman, C, Lowther, G, Lynch, SA, Magee, A, Maher, E, Male, A, Mansour, S, Marks, K, Martin, K, Maye, U, McCann, E, McConnell, V, McEntagart, M, McGowan, R, McKay, K, McKee, S, McMullan, DJ, McNerlan, S, McWilliam, C, Mehta, S, Metcalfe, K, Middleton, A, Miedzybrodzka, Z, Miles, E, Mohammed, S, Montgomery, T, Moore, D, Morgan, S, Morton, J, Mugalaasi, H, Murday, V, Murphy, H, Naik, S, Nemeth, A, Nevitt, L, Newbury-Ecob, R, Norman, A, O’Shea, R, Ogilvie, C, Ong, K-R, Park, S-M, Parker, MJ, Patel, C, Paterson, J, Payne, S, Perrett, D, Phipps, J, Pilz, DT, Pollard, M, Pottinger, C, Poulton, J, Pratt, N, Prescott, K, Price, S, Pridham, A, Procter, A, Purnell, H, Quarrell, O, Ragge, N, Rahbari, R, Randall, J, Rankin, J, Raymond, L, Rice, D, Robert, L, Roberts, E, Roberts, J, Roberts, P, Roberts, G, Ross, A, Rosser, E, Saggar, A, Samant, S, Sampson, J, Sandford, R, Sarkar, A, Schweiger, S, Scott, R, Scurr, I, Selby, A, Seller, A, Sequeira, C, Shannon, N, Sharif, S, Shaw-Smith, C, Shearing, E, Shears, D, Sheridan, E, Simonic, I, Singzon, R, Skitt, Z, Smith, A, Smith, K, Smithson, S, Sneddon, L, Splitt, M, Squires, M, Stewart, F, Stewart, H, Straub, V, Suri, M, Sutton, V, Swaminathan, GJ, Sweeney, E, Tatton-Brown, K, Taylor, C, Taylor, R, Tein, M, Temple, IK, Thomson, J, Tischkowitz, M, Tomkins, S, Torokwa, A, Treacy, B, Turner, C, Turnpenny, P, Tysoe, C, Vandersteen, A, Varghese, V, Vasudevan, P, Vijayarangakannan, P, Vogt, J, Wakeling, E, Wallwark, S, Waters, J, Weber, A, Wellesley, D, Whiteford, M, Widaa, S, Wilcox, S, Wilkinson, E, Williams, D, Williams, N, Wilson, L, Woods, G, Wragg, C, Wright, M, Yates, L, Yau, M, Nellåker, C, Parker, M, Firth, HV, Wright, CF, FitzPatrick, DR, Barrett, JC, and Hurles, ME

Subjects
Male, Parents, Heredity, Developmental Disabilities, GRIN2B, POGZ, Autoantigens, SMAD4, CASK, GATAD2B, 0302 clinical medicine, TRIO, SMARCA2, KCNH1, Average Faces, CTNNB1, SCN1A, Young adult, Casein Kinase II, Child, AUTS2, MEF2C, Exome, ADNP, Exome sequencing, EP300, KCNQ2, KCNQ3, EHMT1, CNKSR2, CREBBP, MYT1L, MED13L, CSNK2A1, Protein Phosphatase 2C, PPP2R1A, ZBTB18, CDKL5, WAC, HNRNPU, Cohort, STXBP1, Medical genetics, SYNGAP1, Mi-2 Nucleosome Remodeling and Deacetylase Complex, Sex characteristics, AHDC1, SCN8A, medicine.medical_specialty, SLC6A1, FOXP1, USP9X, Article, ANKRD11, PUF60, BRAF, 03 medical and health sciences, SATB2, SMC1A, Intellectual Disability, BCL11A, GABRB3, IQSEC2, Humans, TBL1XR1, TCF4, MSL3, TCF20, DNM1, EEF1A2, SUV420H1, DYRK1A, SETD5, COL4A3BP, CTCF, CHD2, R1, CHD4, 030104 developmental biology, NAA10, HDAC8, Mutation, KDM5B, CHAMP1, PhenIcons, 030217 neurology & neurosurgery, Transcription Factors, 0301 basic medicine, ZMYND11, PTEN, De novo mutation, Chromosomal Proteins, Non-Histone, PTPN11, ASXL1, Bioinformatics, medicine.disease_cause, ASXL3, Cohort Studies, DEAD-box RNA Helicases, CHD8, Prevalence, QRICH1, KIF1A, Genetics, Sex Characteristics, GNAI1, Multidisciplinary, WDR45, Middle Aged, KMT2A, PPM1D, MECP2, DNA-Binding Proteins, PPP2R5D, Phenotype, PACS1, ras GTPase-Activating Proteins, DDX3X, Female, FOXG1, SET, Myeloid-Lymphoid Leukemia Protein, Developmental Disease, Adult, KANSL1, Adolescent, NFIX, Nerve Tissue Proteins, PURA, Biology, KAT6B, KAT6A, NSD1, PDHA1, ALG13, Young Adult, Seizures, CDC2 Protein Kinase, medicine, Journal Article, QH426, Homeodomain Proteins, ITPR1, DYNC1H1, GNAO1, Histone-Lysine N-Methyltransferase, Sequence Analysis, DNA, ZC4H2, ARID1B, Repressor Proteins, CNOT3, SCN2A, SLC35A2, CDK13
Abstract

Children with severe, undiagnosed developmental disorders (DDs) are enriched for damaging de novo mutations (DNMs) in developmentally important genes. We exome sequenced 4,294 families with children with DDs, and meta-analysed these data with published data on 3,287 children with similar disorders. We show that the most significant factors influencing the diagnostic yield of de novo mutations are the sex of the child, the relatedness of their parents and the age of both father and mother. We identified 95 genes enriched for damaging de novo mutation at genome-wide significance (P < 5 x 10-7), including fourteen genes for which compelling data for causation was previously lacking. The large number of genome-wide significant findings allow us to demonstrate that, at current cost differentials, exome sequencing has much greater power than genome sequencing for novel gene discovery in genetically heterogeneous disorders. We estimate that 42.5% of our cohort likely carry pathogenic de novo single nucleotide variants (SNVs) and indels in coding sequences, with approximately half operating by a loss-of-function mechanism, and the remainder being gain-of-function. We established that most haploinsufficient developmental disorders have already been identified, but that many gain-of-function disorders remain to be discovered. Extrapolating from the DDD cohort to the general population, we estimate that de novo dominant developmental disorders have an average birth prevalence of 1 in 168 to 1 in 377, depending on parental age.

Published
2017

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