Multiple studies have confirmed the contribution of rare de novo copy number variations to the risk for autism spectrum disorders1,2,3. But whereas de novo single nucleotide variants have been identified in affected individuals4, their contribution to risk has yet to be clarified. Specifically, the frequency and distribution of these mutations have not been well characterized in matched unaffected controls, and such data are vital to the interpretation of de novo coding mutations observed in probands. Here we show, using whole-exome sequencing of 928 individuals, including 200 phenotypically discordant sibling pairs, that highly disruptive (nonsense and splice-site) de novo mutations in brain-expressed genes are associated with autism spectrum disorders and carry large effects. On the basis of mutation rates in unaffected individuals, we demonstrate that multiple independent de novo single nucleotide variants in the same gene among unrelated probands reliably identifies risk alleles, providing a clear path forward for gene discovery. Among a total of 279 identified de novo coding mutations, there is a single instance in probands, and none in siblings, in which two independent nonsense variants disrupt the same gene, SCN2A (sodium channel, voltage-gated, type II, α subunit), a result that is highly unlikely by chance.

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Sequence Read Archive

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Sequence data from this study is available through the NCBI Sequence Read Archive (accession number SRP010920.1).


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We are grateful to all of the families participating in the Simons Foundation Autism Research Initiative (SFARI) Simplex Collection (SSC). This work was supported by a grant from the Simons Foundation. R.P.L. is an Investigator of the Howard Hughes Medical Institute. We thank the SSC principal investigators A. L. Beaudet, R. Bernier, J. Constantino, E. H. Cook Jr, E. Fombonne, D. Geschwind, D. E. Grice, A. Klin, D. H. Ledbetter, C. Lord, C. L. Martin, D. M. Martin, R. Maxim, J. Miles, O. Ousley, B. Peterson, J. Piggot, C. Saulnier, M. W. State, W. Stone, J. S. Sutcliffe, C. A. Walsh and E. Wijsman and the coordinators and staff at the SSC sites for the recruitment and comprehensive assessment of simplex families; the SFARI staff, in particular M. Benedetti, for facilitating access to the SSC; Prometheus Research for phenotypic data management and Prometheus Research and the Rutgers University Cell and DNA repository for accessing biomaterials; the Yale Center of Genomic Analysis, in particular M. Mahajan, S. Umlauf, I. Tikhonova and A. Lopez, for generating sequencing data; T. Brooks-Boone, N. Wright-Davis and M. Wojciechowski for their help in administering the project at Yale; I. Hart for support; G. D. Fischbach, A. Packer, J. Spiro, M. Benedetti and M. Carlson for their suggestions throughout; and B. Neale and M. Daly for discussions regarding de novo variation. We also acknowledge T. Lehner and the Autism Sequencing Consortium for providing an opportunity for pre-publication data exchange among the participating groups.

Author information

Author notes

    • Abha R. Gupta
    • , John D. Murdoch
    • , Melanie J. Raubeson
    • , A. Jeremy Willsey
    • , A. Gulhan Ercan-Sencicek
    •  & Nicholas M. DiLullo

    These authors contributed equally to this work.


  1. Program on Neurogenetics, Child Study Center, Department of Psychiatry, Department of Genetics, Yale University School of Medicine, 230 South Frontage Road, New Haven, Connecticut 06520, USA

    • Stephan J. Sanders
    • , Michael T. Murtha
    • , John D. Murdoch
    • , Melanie J. Raubeson
    • , A. Jeremy Willsey
    • , A. Gulhan Ercan-Sencicek
    • , Nicholas M. DiLullo
    • , Michael F. Walker
    • , Gordon T. Ober
    • , Nicole A. Teran
    • , Youeun Song
    • , Paul El-Fishawy
    • , Ryan C. Murtha
    •  & Matthew W. State
  2. Child Study Center, Department of Pediatrics, Yale University School of Medicine, 230 South Frontage Road, New Haven, Connecticut 06520, USA

    • Abha R. Gupta
  3. Neurogenetics Program, UCLA, 695 Charles E. Young Dr. South, Los Angeles, California 90095, USA

    • Neelroop N. Parikshak
    • , Jason L. Stein
    •  & Daniel H. Geschwind
  4. Department of Genetics, Howard Hughes Medical Institute, Yale University School of Medicine, New Haven, Connecticut 06510, USA

    • Murim Choi
    • , John D. Overton
    •  & Richard P. Lifton
  5. Department of Computer Science, Yale Center for Genome Analysis, Yale University, 51 Prospect Street, New Haven, Connecticut 06511, USA

    • Robert D. Bjornson
    •  & Nicholas J. Carriero
  6. Department of Neurobiology, Kavli Institute for Neuroscience, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA

    • Kyle A. Meyer
    •  & Nenad Šestan
  7. Department of Neurosurgery, Center for Human Genetics and Genomics, Program on Neurogenetics, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06520, USA

    • Kaya Bilguvar
    •  & Murat Günel
  8. Yale Center for Genome Analysis, 300 Heffernan Drive, West Haven, Connecticut 06516, USA

    • Shrikant M. Mane
  9. Department of Statistics, Carnegie Mellon University, 130 DeSoto Street, Pittsburgh, Pennsylvania 15213, USA

    • Kathryn Roeder
  10. Department of Psychiatry and Human Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15213, USA

    • Bernie Devlin


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S.J.S., M.T.M., R.P.L., M.G., D.H.G. and M.W.S. designed the study; M.T.M., A.R.G., J.M., M.R., A.G.E.-S., N.M.D., S.M., M.W., G.O., Y.S., P.E., R.M. and J.O. designed and performed high-throughput sequencing experiments and variant confirmations; S.J.S., M.C., K.B., R.B. and N.C. designed the exome-analysis bioinformatics pipeline; S.J.S., A.J.W., N.N.P., J.L.S., N.T., K.A.M., N.Š., K.R., D.H.G., B.D. and M.W.S. analysed the data; S.J.S., A.J.W., K.R., B.D. and M.W.S. wrote the paper; J.M., M.R., A.J.W., A.R.G., A.G.E.-S. and N.M.D. contributed equally to the study. All authors discussed the results and contributed to editing the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Daniel H. Geschwind or Bernie Devlin or Matthew W. State.

Supplementary information

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    Supplementary Information

    This file contains Supplementary Figures 1-12, Supplementary Methods, Supplementary Tables 1-7, Supplementary Equations, legends for Supplementary Data files 1 and 2 and additional references – See Table of contents for more details.

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  1. 1.

    Supplementary Data 1

    This file contains quality metrics and sample IDs - see Supplementary information file for full legend.

  2. 2.

    Supplementary Data 2

    This file contains a list of de novo variants - see Supplementary information file for full legend.

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