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Prevalence and architecture of de novo mutations in developmental disorders

Nature volume 542, pages 433–438 (2017)Cite this article

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Abstract

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year.

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Figure 1: Association of phenotypes with the presence of DNMs that are probably pathogenic.
Figure 2: Genes exceeding genome-wide significance.
Figure 3: Excess of DNMs.
Figure 4: Prevalence of live births with DDs caused by dominant DNMs.

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Acknowledgements

We thank the families for their participation and patience. We are grateful to the Exome Aggregation Consortium for making their data available. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the UK Department of Health, and the Wellcome Trust Sanger Institute (grant WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of the Wellcome Trust or the UK Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South Research Ethics Committee and GEN/284/12, granted by the Republic of Ireland Research Ethics Committee). The research team acknowledges the support of the National Institutes for Health Research, through the Comprehensive Clinical Research Network. We thank the Sanger Human Genome Informatics team, the Sample Management team, the Illumina High-Throughput team, the New Pipeline Group team, the DNA pipelines team and the Core Sequencing team for their support in generating and processing the data. D.R.F. is funded through an MRC Human Genetics Unit program grant to the University of Edinburgh. Finally we acknowledge the contribution of two esteemed DDD clinical collaborators, J. Tolmie and L. Brueton, who died during the course of the study.

Author information

Author notes

  1. Helen V. Firth, Caroline F. Wright, David R. FitzPatrick, Jeffrey C. Barrett and Matthew E. Hurles: These authors jointly supervised this work.

Authors and Affiliations

  1. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, Cambridge, UK

    Jeremy F. McRae, Stephen Clayton, Tomas W. Fitzgerald, Joanna Kaplanis, Elena Prigmore, Diana Rajan, Alejandro Sifrim, Nadia Akawi, Kirsty Ambridge, Daniel M. Barrett, Tanya Bayzetinova, Philip Jones, Wendy D. Jones, Daniel King, Netravathi Krishnappa, Laura E. Mason, Tarjinder Singh, Adrian R. Tivey, Jana Awada, A. Paul Bevan, Simon Brent, Elena Chatzimichali, Irina Colgiu, Dylan de Vries, Emma Gray, Susan Gribble, Liu He, Lucy Hildyard, Ben Hutton, Rosemary Kelsell, Anna Middleton, Daniel Perrett, Martin Pollard, Raheleh Rahbari, Josh Randall, Ganesh Jawahar Swaminathan, Parthiban Vijayarangakannan, Sara Widaa, Emily Wilkinson, Helen V. Firth, Caroline F. Wright, David R. FitzPatrick, Jeffrey C. Barrett & Matthew E. Hurles

  2. MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK

    Stuart Aitken, Philip Greene, Andrew Jackson, Wayne Lam, Anne Lampe, Eddy Maher, David Moore & David R. FitzPatrick

  3. Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK

    Mohsan Alvi

  4. Wessex Clinical Genetics Service, University Hospital Southampton, Princess Anne Hospital, Coxford Road, Southampton, SO16 5YA, UK

    Munaza Ahmed, Diana Baralle, David J. Bunyan, Amanda Collins, Morag N. Collinson, Nicola Foulds, Lucy Harrison, Victoria Harrison, Katherine Lachlan, I. Karen Temple, Audrey Torokwa & Diana Wellesley

  5. Wessex Regional Genetics Laboratory, Salisbury NHS Foundation Trust, Salisbury District Hospital, Odstock Road, Salisbury, SP2 8BJ, Wiltshire, UK

    Munaza Ahmed, Diana Baralle, David J. Bunyan, Amanda Collins, Morag N. Collinson, Nicola Foulds, Lucy Harrison, Victoria Harrison, Katherine Lachlan, I. Karen Temple, Audrey Torokwa & Diana Wellesley

  6. Faculty of Medicine, University of Southampton, Building 85, Life Sciences Building, Highfield Campus, Southampton, SO17 1BJ, UK

    Munaza Ahmed, Diana Baralle, David J. Bunyan, Amanda Collins, Morag N. Collinson, Nicola Foulds, Lucy Harrison, Victoria Harrison, Katherine Lachlan, I. Karen Temple, Audrey Torokwa & Diana Wellesley

  7. South West Thames Regional Genetics Centre, St George’s Healthcare NHS Trust, St George’s, University of London, Cranmer Terrace, SW17 0RE, London, UK

    Uruj Anjum, Frances Elmslie, Tessa Homfray, Sahar Mansour, Karen Marks, Meriel McEntagart, Anand Saggar, Kate Tatton-Brown & Rohan Taylor

  8. Institute of Medical Genetics, University Hospital of Wales, Heath Park, CF14 4XW, Cardiff, UK

    Hayley Archer, Angus Clarke, Sally Davies, Karenza Evans, Andrew Fry, Dhavendra Kumar, Sian Morgan, Hood Mugalaasi, Annie Procter, Julian Sampson & Vinod Varghese

  9. Department of Clinical Genetics, Block 12, Glan Clwyd Hospital, Rhyl, LL18 5UJ, Denbighshire, UK

    Hayley Archer, Angus Clarke, Sally Davies, Karenza Evans, Andrew Fry, Dhavendra Kumar, Sian Morgan, Hood Mugalaasi, Annie Procter, Julian Sampson & Vinod Varghese

  10. East Anglian Medical Genetics Service, Box 134, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK

    Ruth Armstrong, Simon Holden, Sarju Mehta, Soo-Mi Park, Joan Paterson, Lucy Raymond, Jonathan Roberts, Richard Sandford, Ingrid Simonic, Marc Tischkowitz, Becky Treacy, Sarah Wallwark, Sarah Wilcox, Geoff Woods & Helen V. Firth

  11. Sheffield Regional Genetics Services, Sheffield Children’s NHS Trust, Western Bank, Sheffield, S10 2TH, UK

    Meena Balasubramanian, Stuart Ingram, Diana Johnson, Louise Nevitt, Michael J. Parker, Oliver Quarrell, Emma Shearing, Kath Smith & Cat Taylor

  12. Manchester Centre for Genomic Medicine, St Mary’s Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, M13 9WL, UK

    Siddharth Banka, Kate Chandler, Jill Clayton-Smith, Yanick Crow, Dian Donnai, Carina Donnelly, Sofia Douzgou, Lorraine Gaunt, Elizabeth Jones, Bronwyn Kerr, Helen Kingston, Kay Metcalfe, Emma Miles, Helen Murphy & Zara Skitt

  13. North East Thames Regional Genetics Service, Great Ormond Street Hospital for Children NHS Foundation Trust, Great Ormond Street Hospital, Great Ormond Street, London, WC1N 3JH, UK

    Angela Barnicoat, Maria Bitner-Glindzicz, Kate Brunstrom, Georgina Hollingsworth, Jane Hurst, Lucy Jenkins, V. K. Ajith Kumar, Melissa Lees, Alison Male, Elisabeth Rosser, Richard Scott, Jonathon Waters & Louise Wilson

  14. Department of Medical Genetics Medical School, North of Scotland Regional Genetics Service, NHS Grampian, Foresterhill, AB25 2ZD, Aberdeen, UK

    Paul Batstone, Mariella D’Alessandro, John Dean, Ruth McGowan, Catherine McWilliam, Zosia Miedzybrodzka, Alison Ross & Shalaka Samant

  15. Pathology Department, East of Scotland Regional Genetics Service, Human Genetics Unit, NHS Tayside, Ninewells Hospital, Dundee, DD1 9SY, UK

    David Baty, Jonathan Berg, David Goudie, Norman Pratt, Debbie Rice & Susann Schweiger

  16. Department of Clinical Genetics, Yorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Chapel Allerton Hospital, Chapeltown Road, Leeds, LS7 4SA, UK

    Chris Bennett, Moira Blyth, Andrea Coates, Angus Dobbie, Sarah Hewitt, Emma Hobson, Alison Kraus, Katrina Prescott, Paul Roberts, Eamonn Sheridan, Audrey Smith, Miranda Squires & Jenny Thomson

  17. North West Thames Regional Genetics Centre, North West London Hospitals NHS Trust, The Kennedy Galton Centre, Northwick Park and St Mark’s NHS Trust Watford Road, Harrow, HA1 3UJ, UK

    Birgitta Bernhard, Louise Bourdon, Angela Brady, Natalie Canham, Virginia Clowes, Neeti Ghali, Muriel Holder, Susan Holder, Stewart Payne, Cheryl Sequeira, Roldan Singzon, Anthony Vandersteen & Emma Wakeling

  18. Oxford Regional Genetics Service, Oxford Radcliffe Hospitals NHS Trust, The Churchill Old Road, Oxford, OX3 7LJ, UK

    Edward Blair, Deirdre Cilliers, Susan Clasper, Richard Gibbons, Usha Kini, Andrea Nemeth, Julie Phipps, Joanna Poulton, Sue Price, Abigail Pridham, Hellen Purnell, Anneke Seller, Debbie Shears & Helen Stewart

  19. West Midlands Regional Genetics Service, Birmingham Women’s NHS Foundation Trust, Birmingham Women’s Hospital, Edgbaston, B15 2TG, Birmingham, UK

    David Bohanna, Trevor Cole, Nicola Cooper, Helen Cox, Lily Islam, Joanna Jarvis, Gail Kirby, Derek Lim, Kirsten McKay, Dominic J. McMullan, Jenny Morton, Swati Naik, Andrew Norman, Kai-Ren Ong, Chirag Patel, Nicola Ragge, Saba Sharif, Mark Tein, Julie Vogt & Denise Williams

  20. Northern Genetics Service, Newcastle upon Tyne Hospitals NHS Foundation Trust, Institute of Human Genetics, International Centre for Life, Central Parkway, Newcastle upon Tyne, NE1 3BZ, UK

    David Bourn, John Burn, Richard Fisher, Judith Goodship, Stephen Hellens, Alex Henderson, Tara Montgomery, Linda Sneddon, Miranda Splitt, Volker Straub, Michael Wright & Laura Yates

  21. Northern Ireland Regional Genetics Centre, Belfast Health and Social Care Trust, Belfast City Hospital, Lisburn Road, Belfast, BT9 7AB, UK

    Lisa Bradley, Tabib Dabir, Deirdre Donnelly, Mervyn Humphreys, Claire Kirk, Alex Magee, Vivienne McConnell, Shane McKee, Susan McNerlan & Fiona Stewart

  22. Clinical Genetics Department, Peninsula Clinical Genetics Service, Royal Devon and Exeter NHS Foundation Trust, Royal Devon & Exeter Hospital (Heavitree), Gladstone Road, Exeter, EX1 2ED, UK

    Carole Brewer, Bruce Castle, Gemma Devlin, Sian Ellard, Sarah Everest, Emma Kivuva, Julia Rankin, Charles Shaw-Smith, Claire Turner, Peter Turnpenny & Carolyn Tysoe

  23. South East Thames Regional Genetics Centre, Guy’s and St Thomas’ NHS Foundation Trust, Guy’s Hospital, Great Maze Pond, London, SE1 9RT, UK

    Fiona Connell, Charu Deshpande, Tina Fendick, Frances Flinter, Melita Irving, Dragana Josifova, Caroline Langman, Shehla Mohammed, Caroline Ogilvie, Leema Robert & Michael Yau

  24. Leicestershire Genetics Centre, University Hospitals of Leicester NHS Trust, Leicester Royal Infirmary (NHS Trust), Leicester, LE1 5WW, UK

    Lara Cresswell, Beckie Kaemba, Sandra Kazembe & Pradeep Vasudevan

  25. Nottingham Regional Genetics Service, City Hospital Campus, Nottingham University Hospitals NHS Trust, The Gables, Hucknall Road, Nottingham, NG5 1PB, UK

    Gareth Cross, Abhijit Dixit, Jacqueline Eason, Rachel Harrison, Katherine Martin, Ajoy Sarkar, Ann Selby, Nora Shannon & Mohnish Suri

  26. West of Scotland Regional Genetics Service, NHS Greater Glasgow and Clyde, Institute of Medical Genetics, Yorkhill Hospital, Glasgow, G3 8SJ, UK

    Rosemarie Davidson, Alexis Duncan, Carol Gardiner, Shelagh Joss, Esther Kinning, Cheryl Longman, Gordon Lowther, Victoria Murday, Daniela T. Pilz, Margo Whiteford & Nicola Williams

  27. Bristol Genetics Service (Avon, Somerset, Gloucs and West Wilts), University Hospitals Bristol NHS Foundation Trust, St Michael’s Hospital, St Michael’s Hill, Bristol, BS2 8DT, UK

    Alan Donaldson, Rose Hawkins, Ruth Newbury-Ecob, Eileen Roberts, Ingrid Scurr, Sarah Smithson, Susan Tomkins & Christopher Wragg

  28. Department of Clinical Genetics, Merseyside and Cheshire Genetics Service, Liverpool Women’s NHS Foundation Trust, Royal Liverpool Children’s Hospital Alder Hey, Eaton Road, Liverpool, L12 2AP, UK

    Angela Douglas, Ian Ellis, Alan Fryer, Lynn Greenhalgh, Una Maye, Gillian Roberts, Vivienne Sutton, Elizabeth Sweeney & Astrid Weber

  29. National Centre for Medical Genetics, Our Lady’s Children’s Hospital, Crumlin, 12, Dublin, Ireland

    Harinder Gill, Andrew Green, Sally A. Lynch & Rosie O’Shea

  30. Department of Clinical Genetics, Block 12, Glan Clwyd Hospital, Rhyl, Denbighshire, LL18 5UJ, Wales, UK

    Emma McCann & Caroline Pottinger

  31. Nuffield Department of Obstetrics & Gynaecology, University of Oxford, Level 3, Women’s Centre, John Radcliffe Hospital, Oxford, OX3 9DU, UK

    Chris Nellåker

  32. Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK

    Chris Nellåker

  33. Big Data Institute, University of Oxford, Roosevelt drive, Oxford, OX3 7LF, UK

    Chris Nellåker

  34. Nuffield Department of Population Health, The Ethox Centre, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK

    Michael Parker

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Deciphering Developmental Disorders Study

  • Jeremy F. McRae
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  • , Tomas W. Fitzgerald
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  •  & Matthew E. Hurles

Contributions

Patient recruitment and phenotyping: M.Ah., U.A., H.A., R.A., M.Ba., S.Ba., D.Bar., A.Ba., P.B., D.Bat., C.Be., J.Be., B.B., M.B.-G., E.B., M.Bl., D.Boh., L.Bo., D.Bou., L.Br., A.Br., C.Br., K.B., D.J.B., J.Bu., N.Ca., B.C., K.C., D.C., A.Cl., S.Clas., J.C.-S., V.C., A.Coa., T.C., A.Col., M.N.C., F.C., N.Co., H.C., L.C., G.C., Y.C., M.D., T.D., R.D., S.Da., J.D., C.De., G.D., A.Di., A.Dob., A.Don., D.Donna., D.Donne., C.Do., A.Dou., S.Do., A.Du., J.E., S.El., I.E., F.E., K.E., S.Ev., T.F., R.F., F.F., N.F., A.Fry, A.Frye., C.G., L.Ga., N.G., R.G., H.G., J.G., D.G., A.G., P.G., L.Gr., R.Har., L.Ha., V.H., R.Haw., S.Hel., A.H., S.Hew., E.H., S.Holden, M.Ho., S.Holder, G.H., T.H., M.Hu., J.H., S.I., M.I., L.I., A.J., J.J., L.J., D.Joh., E.J., D.Jos., S.J., B.Ka., S.K., B.Ke., H.K., U.K., E.Kin., G.K., C.K., E.Kiv., A.K., D.Ku., V.K.A.K., K.L., W.L., A.L., C.La., M.L., D.L., C.Lo., G.L., S.A.L., A.Mag., E.Ma., A.Mal., S.Ma., K.Mark., K.Mart., U.M., E.Mc., V.Mc., M.M., R.M., K.Mc., S.McK., D.J.M., S.McN., C.M., S.Me., K.Me., Z.M., A.Mi., E.Mi., S.Moh., T.M., D.M., S.Mor., J.M., H.Mug., V.Mu., H.Mur., S.N., A.Ne., L.N., R.N.-E., A.No., R.O., C.O., K.-R.O., S.-M.P., M. J.P., C.Pa., J.Pa., S.Pa., J.Ph., D.T.P., C.Po., J.Po., N.P., K.P., S.Pr., A.Pri., A.Pro., H.P., O.Q., N.R., J.Rank., L.Ra., D.Ri., L.Ro., E.Rob., J.Ro., P.R., G.R., A.R., E.Ros., A.Sag., S.Sa., J.S., R.Sa., A.Sar., S.Sc., R.Sc., I.Sc., A.Selb., A.Sell., C.S., N.S., S.Sh., C.S.-S., E.Shea., D.S., E.Sher., I.Si., R.Si., Z.S., A.Sm., K.S., S.Sm., L.S., M.Sp., M.Sq., F.S., H.S., V.St., M.Su., V.Su., E.Sw., K.T.-B., C.Ta., R.T., M.Tein, I.K.T., J.T., M.Ti., S.T., A.T., B.T., C.Tu., P.T., C.Ty., A.V., V.V., P.Va., J.V., E.Wa., S.Wa., J.W., A.W., D.We., M.Wh., S.Wil., D.Wi., N.W., L.W., G.W., C.W., M.Wr., L.Y., M.Y., H.V.F. and D.R.F. Sample and data processing: S.Clay., T.W.F., E.P., D.Ra., K.A., D.M.B., T.B., P.J., N.K., L.E.M., A.R.T., A.P.B., S.Br., E.C., I.C., E.G., S.G., L.Hi., B.H., R.K., D.P., M.Po., J.Rand., G.J.S., S.Wid. and E.Wi. Validation experiments: J.F.M., E.P., D.Ra., A.Si., N.K. and C.F.W. Study design: M.Pa., H.V.F., C.F.W., D.R.F., J.C.B. and M.E.H. Method development and data analysis: J.F.M., S.Clay., T.W.F., J.K., E.P., D.Ra., A.Si., S.A., N.A., M.Al., P.J., W.D.J., D.Ki., T.S., J.A., D.d.V., L.He, R.R., G.J.S., P.Vi., C.N., H.V.F., C.F.W., D.R.F., J.C.B. and M.E.H. Data interpretation: J.F.M., H.V.F., C.F.W., D.R.F., J.C.B. and M.E.H. Writing: J.F.M., C.F.W., D.R.F. and M.E.H. Experimental and analytical supervision: M.Pa., H.V.F., C.F.W., D.R.F., J.C.B. and M.E.H. Project Supervision: M.E.H.

Corresponding author

Correspondence to Matthew E. Hurles.

Ethics declarations

Competing interests

M.E.H. is a co-founder of, consultant to, and holds shares in, Congenica Ltd, a genetics diagnostic company.

Additional information

Reviewer Information Nature thanks D. Goldstein, B. Neale and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Proportion of individuals with a DNM that is probably pathogenic.

Only individuals with protein-altering or protein-truncating DNMs in dominant or X-linked dominant DD-associated genes, or males with DNMs in hemizygous DD-associated genes were included. The proportions given are for those individuals with any DNMs rather than the total number of individuals in each subset. Cohorts included in the DNM meta-analyses are shaded blue.

Extended Data Figure 2 Phenotypic summary of genes without previous compelling evidence.

Phenotypes are grouped by type. The first group indicates numbers of individuals with DNMs per gene divided by sex (m, male; f, female), and by functional consequence (NSV, nonsynonymous variant; PTV, protein-truncating variant). The second group indicates mean values for growth parameters: birthweight (bw), height (ht), weight (wt) and occipitofrontal circumference (OFC). Values are given as standard deviations from the healthy population mean derived from ALSPAC (Avon longitudinal study of parents and children) data. The third group indicates the mean age for achieving developmental milestones: age of first social smile, age of first sitting unassisted, age of first walking unassisted and age of first speaking. Values are given in months. The final group summarizes HPO-coded phenotypes per gene, as number of HPO terms within different clinical categories.

Extended Data Figure 3 Phenotypic summary of individuals with DNMs in genes achieving genome-wide significance.

Phenotypes are grouped by type. The first group indicates numbers of individuals with DNMs per gene divided by sex (m, male; f, female), and by functional consequence (NSV, nonsynonymous variant; PTV, protein-truncating variant). The second group indicates mean values for growth parameters: birthweight (bw), height (ht), weight (wt) and occipitofrontal circumference (OFC). Values are given as standard deviations from the healthy population mean derived from ALSPAC data. The third group indicates the mean age for achieving developmental milestones: age of first social smile, age of first sitting unassisted, age of first walking unassisted and age of first speaking. Values are given in months. The final group summarizes HPO-coded phenotypes per gene, as number of HPO terms within different clinical categories.

Extended Data Figure 4 Dispersion of DNMs and domains for each novel gene.

a, CDK13. b, CHD4. c, CNOT3. d, CSNK2A1. e, GNAI1. f, KCNQ3. g, MSL3. h, PPM1D. i, PUF60. j, QRICH1. k, SET. l, KMT5B. m, TCF20. n, ZBTB18.

Extended Data Figure 5 Effect of clustering by phenotype on the ability to identify genome-wide significant genes.

a, Comparison of P values derived from genotypic information alone versus P values that incorporate genotypic information and phenotypic similarity. b, Comparison of P values from tests in the complete DDD cohort versus tests in the subset with seizures. Genes that were previously linked to seizures are shaded blue. c, Proportion of cohort with a DNM in a seizure-associated gene, stratified by seizure-affected status. Error bars, 95% CI. d, Comparison of power to identify genome-wide significant genes in probands with seizures, versus the unstratified cohort, at matched sample sizes.

Extended Data Figure 6 Power of genome versus exome sequencing to discover dominant genes associated with DDs.

a, The number of genes exceeding genome-wide significance was estimated at three different fixed budgets ($USD1, 2 or 3 million) and a range of relative sensitivities for genomes versus exomes to detect DNMs. The number of genes identifiable by exome sequencing are shaded blue, whereas the number of genes identifiable by genome sequencing are shaded green. The regions where exome sequencing costs 30–40% of genome sequencing are shaded with a grey background, which corresponds to the price differential in 2016. b, Simulated estimates of power to detect loss-of-function genes in the genome at different cohort sizes, given fixed budgets.

Extended Data Figure 7 Gene-wise significance of neurodevelopmental genes versus the expected number of mutations per gene.

Points are shaded by clinical recognizability classification (blue and brown points denote cryptic and distinctive disorders, respectively). Genes have been separated into two plots. Left, genes for cryptic disorders with low, mild or moderate clinical recognizability. Right, genes for distinctive disorders with high clinical recognizability.

Extended Data Figure 8 Stringency of DNM filtering.

a, Sensitivity and specificity of DNM validations within sets filtered using varying thresholds of DNM quality (posterior probability of DNM). The analysed DNMs were restricted to sites identified within the earlier 1,133 trios15, where all candidate DNMs underwent validation experiments. The labelled value is the quality threshold at which the number of candidate synonymous DNMs equals the number of expected synonymous mutations under a null germline mutation rate. b, Excess of missense and loss-of-function DNMs at varying DNM quality thresholds. The DNM excess is adjusted for the sensitivity and specificity at each threshold.

Extended Data Figure 9 Enrichment of DNMs by consequence type, across functional constraint quantiles for residual variation intolerance scores.

A comparison of enrichment for residual variation intolerance score (RVIS) values generated from ESP6500 data (ref. 31) versus ExAC data (obtained from http://genic-intolerance.org/) are provided.

Extended Data Table 1 Phenotypes tested for association with having a pathogenic DNM
Full size table

Supplementary information

Supplementary Information

This file contains a Supplementary Note and the Phenicons for the 94 genes exceeding genome-wide significance (see page 2 for details). (PDF 4196 kb)

Supplementary Tables

This file contains Supplementary Tables 1-4 comprising: (1) de novo mutations (DNM) in the 4,293 DDD individuals. It includes sex, chromosome, position, reference and alternate alleles, HGNC symbol, VEP consequence, posterior probability of DNM and validation status where available. Individual IDs are available on request. This list excludes the sites that failed validations, but includes sites that passed validation (confirmed), sites that were uncertain (uncertain), and sites that were not tested by secondary validation (NA). Genome positions are given as GRCh37 coordinates; (2) Details of cohorts used in meta-analyses. This includes numbers of individuals by sex and publication details; (3) Genes with genome-wide significant statistical evidence to be developmental disorder genes. The numbers of unrelated individuals with independent de novo mutations (DNMs) are given for protein truncating variants (PTV) and missense variants. If any additional individuals were in other cohorts, that number is given in brackets. The P-value reported is the minimum P-value from the testing of the DDD dataset or the meta-analysis dataset. The subset providing the P-value is also listed. Mutations are considered clustered if the P-value proximity clustering of DNMs is less than 0.01; (4) Comparison of known haploinsufficient (HI) neurodevelopment genes to HI and non-HI enrichment models. Genes are ranked by difference in the Akaike’s Information Criterion computed for models where the genes match either expected non-HI PTV enrichment (model 1), or expected HI protein-truncating variant (PTV) enrichment (model 2). (XLSX 629 kb)

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Deciphering Developmental Disorders Study. Prevalence and architecture of de novo mutations in developmental disorders. Nature 542, 433–438 (2017). https://doi.org/10.1038/nature21062

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