Abstract
We characterize the landscape of somatic mutations—mutations occurring after fertilization—in the human brain using ultra-deep (~250×) whole-genome sequencing of prefrontal cortex from 59 donors with autism spectrum disorder (ASD) and 15 control donors. We observe a mean of 26 somatic single-nucleotide variants per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2–3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 somatic single-nucleotide variants present in ≥2% of cells—comparable to the number of de novo germline mutations per generation—with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared with controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
Whole-genome sequencing data are available from the National Institute of Mental Health Data Archive (https://doi.org/10.15154/1503337).
Code availability
Custom code is available from the authors by request.
Change history
29 August 2023
A Correction to this paper has been published: https://doi.org/10.1038/s41593-023-01437-x
22 March 2021
A Correction to this paper has been published: https://doi.org/10.1038/s41593-021-00830-8
References
Lynch, M. Rate, molecular spectrum, and consequences of human mutation. Proc. Natl Acad. Sci. USA 107, 961–968 (2010).
D’Gama, A. M. et al. Mammalian target of rapamycin pathway mutations cause hemimegalencephaly and focal cortical dysplasia. Ann. Neurol. 77, 720–725 (2015).
Lim, J. S. et al. Somatic mutations in TSC1 and TSC2 cause focal cortical dysplasia. Am. J. Hum. Genet. 100, 454–472 (2017).
Nakashima, M. et al. Somatic mutations in the MTOR gene cause focal cortical dysplasia type IIb. Ann. Neurol. 78, 375–386 (2015).
Erickson, R. P. Recent advances in the study of somatic mosaicism and diseases other than cancer. Curr. Opin. Genet. Dev. 26, 73–78 (2014).
Insel, T. R. Brain somatic mutations: the dark matter of psychiatric genetics? Mol. Psychiatry 19, 156–158 (2014).
McConnell, M. J. et al. Intersection of diverse neuronal genomes and neuropsychiatric disease: the brain somatic mosaicism network. Science https://doi.org/10.1126/science.aal1641 (2017).
Lodato, M. A. et al. Aging and neurodegeneration are associated with increased mutations in single human neurons. Science 359, 555–559 (2018).
Keogh, M. J. et al. High prevalence of focal and multi-focal somatic genetic variants in the human brain. Nat. Commun. 9, 4257 (2018).
Wei, W. et al. Frequency and signature of somatic variants in 1461 human brain exomes. Genet. Med. 21, 904–912 (2019).
Dou, Y. et al. Postzygotic single-nucleotide mosaicisms contribute to the etiology of autism spectrum disorder and autistic traits and the origin of mutations. Hum. Mutat. 38, 1002–1013 (2017).
Freed, D. & Pevsner, J. The contribution of mosaic variants to autism spectrum disorder. PLoS Genet. 12, e1006245 (2016).
Lim, E. T. et al. Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder. Nat. Neurosci. 20, 1217–1224 (2017).
Krupp, D. R. et al. Exonic mosaic mutations contribute risk for autism spectrum disorder. Am. J. Hum. Genet. 101, 369–390 (2017).
D’Gama, A. M. et al. Targeted DNA sequencing from autism spectrum disorder brains implicates multiple genetic mechanisms. Neuron 88, 910–917 (2015).
Dou, Y. et al. Accurate detection of mosaic variants in sequencing data without matched controls. Nat. Biotechnol. 38, 314–319 (2020).
Lodato, M. A. et al. Somatic mutation in single human neurons tracks developmental and transcriptional history. Science 350, 94–98 (2015).
Doan, R. N. et al. Recessive gene disruptions in autism spectrum disorder. Nat. Genet. 51, 1092–1098 (2019).
Damaj, L. et al. CACNA1A haploinsufficiency causes cognitive impairment, autism and epileptic encephalopathy with mild cerebellar symptoms. Eur. J. Hum. Genet. 23, 1505–1512 (2015).
Epi4K Consortium De novo mutations in SLC1A2 and CACNA1A are important causes of epileptic encephalopathies. Am. J. Hum. Genet. 99, 287–298 (2016).
Satterstrom, F. K. et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell 180, 568–584.e523 (2020).
Mercer, T. R. et al. DNase I-hypersensitive exons colocalize with promoters and distal regulatory elements. Nat. Genet. 45, 852–859 (2013).
Thurman, R. E. et al. The accessible chromatin landscape of the human genome. Nature 489, 75–82 (2012).
Polak, P. et al. Reduced local mutation density in regulatory DNA of cancer genomes is linked to DNA repair. Nat. Biotechnol. 32, 71–75 (2014).
Ye, A. Y. et al. A model for postzygotic mosaicisms quantifies the allele fraction drift, mutation rate, and contribution to de novo mutations. Genome Res. 28, 943–951 (2018).
Ju, Y. S. et al. Somatic mutations reveal asymmetric cellular dynamics in the early human embryo. Nature 543, 714–718 (2017).
Bae, T. et al. Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis. Science 359, 550–555 (2018).
Rahbari, R. et al. Timing, rates and spectra of human germline mutation. Nat. Genet. 48, 126–133 (2016).
Wong, C. C. et al. Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage. Nat. Biotechnol. 28, 1115–1121 (2010).
Kiessling, A. A. et al. Genome-wide microarray evidence that 8-cell human blastomeres over-express cell cycle drivers and under-express checkpoints. J. Assist. Reprod. Genet. 27, 265–276 (2010).
Gonzalez-Marin, C., Gosalvez, J. & Roy, R. Types, causes, detection and repair of DNA fragmentation in animal and human sperm cells. Int. J. Mol. Sci. 13, 14026–14052 (2012).
Russell, L. B. & Russell, W. L. Spontaneous mutations recovered as mosaics in the mouse specific-locus test. Proc. Natl Acad. Sci. USA 93, 13072–13077 (1996).
Turner, T. N. et al. Genome sequencing of autism-affected families reveals disruption of putative noncoding regulatory DNA. Am. J. Hum. Genet. 98, 58–74 (2016).
Neale, B. M. et al. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 485, 242–245 (2012).
Kryukov, G. V., Pennacchio, L. A. & Sunyaev, S. R. Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am. J. Hum. Genet. 80, 727–739 (2007).
Blokzijl, F. et al. Tissue-specific mutation accumulation in human adult stem cells during life. Nature 538, 260–264 (2016).
Chen, C. L. et al. Impact of replication timing on non-CpG and CpG substitution rates in mammalian genomes. Genome Res. 20, 447–457 (2010).
Koren, A. et al. Differential relationship of DNA replication timing to different forms of human mutation and variation. Am. J. Hum. Genet. 91, 1033–1040 (2012).
Seisenberger, S. et al. The dynamics of genome-wide DNA methylation reprogramming in mouse primordial germ cells. Mol. Cell 48, 849–862 (2012).
Short, P. J. et al. De novo mutations in regulatory elements in neurodevelopmental disorders. Nature 555, 611–616 (2018).
Williams, S. M. et al. An integrative analysis of non-coding regulatory DNA variations associated with autism spectrum disorder. Mol. Psychiatry 24, 1707–1719 (2019).
Zhou, J. et al. Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk. Nat. Genet. 51, 973–980 (2019).
An, J. Y. et al. Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder. Science https://doi.org/10.1126/science.aat6576 (2018).
Turner, T. N. et al. Genomic patterns of de novo mutation in simplex autism. Cell 171, 710–722.e712 (2017).
Consortium, G. T. Human genomics. The Genotype-Tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).
He, B., Chen, C., Teng, L. & Tan, K. Global view of enhancer–promoter interactome in human cells. Proc. Natl Acad. Sci. USA 111, E2191–E2199 (2014).
Jin, F. et al. A high-resolution map of the three-dimensional chromatin interactome in human cells. Nature 503, 290–294 (2013).
Li, G. et al. Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation. Cell 148, 84–98 (2012).
Evrony, G. D. et al. Single-neuron sequencing analysis of L1 retrotransposition and somatic mutation in the human brain. Cell 151, 483–496 (2012).
Miosge, L. A. et al. Comparison of predicted and actual consequences of missense mutations. Proc. Natl Acad. Sci. USA 112, E5189–E5198 (2015).
Genovese, G., Handsaker, R. E., Li, H., Kenny, E. E. & McCarroll, S. A. Mapping the human reference genome’s missing sequence by three-way admixture in Latino genomes. Am. J. Hum. Genet. 93, 411–421 (2013).
McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213–219 (2013).
Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).
Benson, G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573–580 (1999).
Yang, L. et al. Diverse mechanisms of somatic structural variations in human cancer genomes. Cell 153, 919–929 (2013).
Samocha, K. E. et al. A framework for the interpretation of de novo mutation in human disease. Nat. Genet. 46, 944–950 (2014).
Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).
MacArthur, D. G. et al. A systematic survey of loss-of-function variants in human protein-coding genes. Science 335, 823–828 (2012).
Samocha, K. E. et al. Regional missense constraint improves variant deleteriousness prediction. Preprint at bioRxiv https://doi.org/10.1101/148353v1 (2017).
Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).
Roadmap Epigenomics, C. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Rimmer, A. et al. Integrating mapping-, assembly- and haplotype-based approaches for calling variants in clinical sequencing applications. Nat. Genet. 46, 912–918 (2014).
Yee, T. W. Vector Generalized Linear and Additive Models: with an Implementation in R (Springer-Verlag, 2015).
Alexandrov, L. et al. The repertoire of mutational signatures in human cancer. Nature 578, 94–101 (2020).
Rosenthal, R., McGranahan, N., Herrero, J., Taylor, B. S. & Swanton, C. DeconstructSigs: delineating mutational processes in single tumors distinguishes DNA repair deficiencies and patterns of carcinoma evolution. Genome Biol. 17, 31 (2016).
Alexandrov, L. B. et al. Signatures of mutational processes in human cancer. Nature 500, 415–4217 (2013).
Haradhvala, N. J. et al. Mutational strand asymmetries in cancer genomes reveal mechanisms of DNA damage and repair. Cell 164, 538–549 (2016).
Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2019).
Consortium, G. T. et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).
Chong, J. A. et al. REST: a mammalian silencer protein that restricts sodium channel gene expression to neurons. Cell 80, 949–957 (1995).
Acknowledgements
Human tissue was obtained from the NIH NeuroBioBank at the University of Maryland, the Lieber Institute for Brain Development, Oxford University Brain Bank and Autism BrainNet. Autism BrainNet is a resource of the Simons Foundation Autism Research Initiative (SFARI). Autism BrainNet also manages the Autism Tissue Program (ATP) collection previously funded by Autism Speaks. We thank the donors and their families for their invaluable contribution to the advancement of science. We also thank R.S. Hill, J. Partlow, W. Bainter and the Research Computing group at Harvard Medical School for assistance. R.E.R., A.M.D. and S.N.K. are supported by the Stuart H.Q. and Victoria Quan Fellowship in Neurobiology. R.E.R., A.M.D. and A.N. are also supported by the Harvard/MIT MD-PhD program (grant no. T32GM007753) from the National Institute of General Medical Sciences. Y.D., M.K., M.A.S., D.C.G. and P.J.P. are supported by grants from the NIMH (grant nos. U01MH106883 and P50MH106933) and the Harvard Ludwig Center. L.J.L. and C.L.B. are supported by the Bioinformatics and Integrative Genomics training grant (no. T32HG002295) from the National Human Genome Research Institute. C.A.W. is supported by the Manton Center for Orphan Disease Research, the Allen Discovery Center program through The Paul G. Allen Frontiers Group, grant no. R01NS032457 from the NINDS and grant no. U01MH106883 from the NIMH. C.A.W. is an Investigator of the Howard Hughes Medical Institute. Data were generated as part of the Brain Somatic Mosaicism Network (BSMN) Consortium, supported by grant nos.: U01MH106874, U01MH106876, U01MH106882, U01MH106883, U01MH106883, U01MH106884, U01MH106891, U01MH106891, U01MH106891, U01MH106892, U01MH106893 and U01MH108898 awarded to: N.S. (Yale University), F.M.V. (Yale University), F.H.G. (Salk Institute for Biological Studies), C.A.W. (Boston Children’s Hospital), P.J.P. (Harvard University), J.P. (Kennedy Krieger Institute), A.C. (Icahn School of Medicine at Mount Sinai), J.V.M. (University of Michigan), D.R.W. (Lieber Institute for Brain Development) and J.G.G. (University of California, San Diego). The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences or the National Institutes of Health.
Author information
Authors and Affiliations
Consortia
Contributions
R.E.R., Y.D., P.J.P. and C.A.W. conceptualized the study. R.E.R., A.M.D. and S.N.K. generated whole-genome sequencing data. Y.D. led bioinformatic analysis with assistance from M.K. for variant identification and from M.A.S., L.J.L., C.L.B. and D.C.G for technical issues. R.E.R., L.M.R. and R.N.D. performed targeted variant validation. L.M.R. and K.M.G. performed cloning and luciferase assay experiments. A.N. performed germline pathogenic variant analysis. R.E.R., Y.D., P.J.P. and C.A.W. wrote the manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Peer review information Nature Neuroscience thanks the anonymous reviewers for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Supplementary Figs. 1–16.
Supplementary Tables
Supplementary Tables 1–11.
Rights and permissions
About this article
Cite this article
Rodin, R.E., Dou, Y., Kwon, M. et al. The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing. Nat Neurosci 24, 176–185 (2021). https://doi.org/10.1038/s41593-020-00765-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41593-020-00765-6