Abstract
Genetic mosaicism is the result of the accumulation of somatic mutations in the human genome starting from the first postzygotic cell generation and continuing throughout the whole life of an individual. The rapid development of next-generation and single-cell sequencing technologies is now allowing the study of genetic mosaicism in normal tissues, revealing unprecedented insights into their clonal architecture and physiology. The somatic variant repertoire of an adult human neuron is the result of somatic mutations that accumulate in the brain by different mechanisms and at different rates during development and ageing. Non-pathogenic developmental mutations function as natural barcodes that once identified in deep bulk or single-cell sequencing can be used to retrospectively reconstruct human lineages. This approach has revealed novel insights into the clonal structure of the human brain, which is a mosaic of clones traceable to the early embryo that contribute differentially to the brain and distinct areas of the cortex. Some of the mutations happening during development, however, have a pathogenic effect and can contribute to some epileptic malformations of cortical development and autism spectrum disorder. In this Review, we discuss recent findings in the context of genetic mosaicism and their implications for brain development and disease.
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
$32.99 / 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
References
International HapMap 3 Consortium. Integrating common and rare genetic variation in diverse human populations. Nature 467, 52–58 (2010).
Ludwig, L. S. et al. Lineage tracing in humans enabled by mitochondrial mutations and single-cell genomics. Cell 176, 1325–1339 (2019).
Spits, C. et al. Whole-genome multiple displacement amplification from single cells. Nat. Protoc. 1, 1965–1970 (2006).
Gonzalez-Pena, V. et al. Accurate genomic variant detection in single cells with primary template-directed amplification. Proc. Natl Acad. Sci. USA 118, e2024176118 (2021). This work presents one of the most advanced methods currently used for whole-genome amplification and genomic variant detection in single cells.
Xing, D., Tan, L., Chang, C. H., Li, H. & Xie, X. S. Accurate SNV detection in single cells by transposon-based whole-genome amplification of complementary strands. Proc. Natl Acad. Sci. USA 118, 676–690 (2021).
Abascal, F. et al. Somatic mutation landscapes at single-molecule resolution. Nature 593, 405–410 (2021).
Bohrson, C. L. et al. Linked-read analysis identifies mutations in single-cell DNA-sequencing data. Nat. Genet. 51, 749–754 (2019).
Huang, A. Y. et al. MosaicHunter: accurate detection of postzygotic single-nucleotide mosaicism through next-generation sequencing of unpaired, trio, and paired samples. Nucleic Acids Res. 45, e76 (2017).
Dou, Y. et al. Accurate detection of mosaic variants in sequencing data without matched controls. Nat. Biotechnol. 38, 314–319 (2020).
Luquette, L. J., Bohrson, C. L., Sherman, M. A. & Park, P. J. Identification of somatic mutations in single cell DNA-seq using a spatial model of allelic imbalance. Nat. Commun. 10, 3908 (2019).
Tu, K., Lu, K., Zhang, Q., Huang, W. & Xie, D. Accurate single-cell genotyping utilizing information from the local genome territory. Nucleic Acids Res. 49, e57 (2021).
Wang, Y. et al. Comprehensive identification of somatic nucleotide variants in human brain tissue. Genome Biol. 22, 92 (2021). This work explains best practices for somatic variant detection in the human brain defined by the Brain Somatic Mosaicism Network.
Luquette, L. J. et al. Ultraspecific somatic SNV and indel detection in single neurons using primary template-directed amplification. Preprint at bioRxiv https://doi.org/10.1101/2021.04.30.442032 (2021).
Maury, E. A. & Walsh, C. A. Somatic copy number variants in neuropsychiatric disorders. Curr. Opin. Genet. Dev. 68, 9–17 (2021).
Sherman, M. A. et al. Large mosaic copy number variations confer autism risk. Nat. Neurosci. 24, 197–203 (2021).
Evrony, G. D. et al. Cell lineage analysis in human brain using endogenous retroelements. Neuron 85, 49–59 (2015).
Evrony, G. D., Lee, E., Park, P. J. & Walsh, C. A. Resolving rates of mutation in the brain using single-neuron genomics. eLife 5, e12966 (2016).
Ebert, P. et al. Haplotype-resolved diverse human genomes and integrated analysis of structural variation. Science 372, eabf7117 (2021).
Mallory, X. F., Edrisi, M., Navin, N. & Nakhleh, L. Methods for copy number aberration detection from single-cell DNA-sequencing data. Genome Biol. 21, 208 (2020).
McKerrow, W. et al. Human transposon insertion profiling by sequencing (TIPseq) to map LINE-1 insertions in single cells. Phil. Trans. R. Soc. B 375, 20190335 (2020).
Zhu, X. et al. Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia. Nat. Neurosci. 24, 186–196 (2021).
Loh, P.-R. et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat. Genet. 48, 1443–1448 (2016).
Grossmann, S. et al. Development, maturation, and maintenance of human prostate inferred from somatic mutations. Cell Stem Cell 7, 1262–1274.e5 (2021).
Lawson, A. R. J. et al. Extensive heterogeneity in somatic mutation and selection in the human bladder. Science 370, 75–82 (2020).
Martincorena, I. et al. Somatic mutant clones colonize the human esophagus with age. Science 362, 911–917 (2018).
Welch, J. S. et al. The origin and evolution of mutations in acute myeloid leukemia. Cell 150, 264–278 (2012).
Osorio, F. G. et al. Somatic mutations reveal lineage relationships and age-related mutagenesis in human hematopoiesis. Cell Rep. 25, 2308–2316.e4 (2018).
Martincorena, I. et al. Tumor evolution. High burden and pervasive positive selection of somatic mutations in normal human skin. Science 348, 880–886 (2015).
Suda, K. et al. Clonal expansion and diversification of cancer-associated mutations in endometriosis and normal endometrium. Cell Rep. 24, 1777–1789 (2018).
Roerink, S. F. et al. Intra-tumour diversification in colorectal cancer at the single-cell level. Nature 556, 457–462 (2018).
Lee-Six, H. et al. The landscape of somatic mutation in normal colorectal epithelial cells. Nature 574, 532–537 (2019).
Brunner, S. F. et al. Somatic mutations and clonal dynamics in healthy and cirrhotic human liver. Nature 574, 538–542 (2019).
Brazhnik, K. et al. Single-cell analysis reveals different age-related somatic mutation profiles between stem and differentiated cells in human liver. Sci. Adv. 6, eaax2659 (2020).
Lodato, M. A. et al. Aging and neurodegeneration are associated with increased mutations in single human neurons. Science 359, 555–559 (2018). This work presents rates and mechanisms of somatic variant accumulation in postmitotic single human neurons during ageing.
Coorens, T. H. H. et al. Inherent mosaicism and extensive mutation of human placentas. Nature 592, 80–85 (2021).
Yoshida, K. et al. Tobacco smoking and somatic mutations in human bronchial epithelium. Nature 578, 266–272 (2020).
Moore, L. et al. The mutational landscape of human somatic and germline cells. Nature 597, 381–386 (2021).
Coorens, T. H. H. et al. Extensive phylogenies of human development inferred from somatic mutations. Nature 597, 387–392 (2021).
Bizzotto, S. et al. Landmarks of human embryonic development inscribed in somatic mutations. Science 371, 1249–1253 (2021). This work tracks lineages of human development from the first postzygotic cell generation to brain-specific clones using somatic mutations and shows asymmetries of clonal contributions to the human brain.
Spencer Chapman, M. et al. Lineage tracing of human development through somatic mutations. Nature 695, 85–90 (2021).
Lodato, M. A. et al. Somatic mutation in single human neurons tracks developmental and transcriptional history. Science 350, 94–98 (2015).
Fasching, L. et al. Early developmental asymmetries in cell lineage trees in living individuals. Science 371, 1245–1248 (2021).
Lee-Six, H. et al. Population dynamics of normal human blood inferred from somatic mutations. Nature 561, 473–478 (2018).
Ju, Y. S. et al. Somatic mutations reveal asymmetric cellular dynamics in the early human embryo. Nature 543, 714–718 (2017).
Jonsson, H. et al. Differences between germline genomes of monozygotic twins. Nat. Genet. 53, 27–34 (2021).
Rodin, R. E. 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).
Park, S. et al. Clonal dynamics in early human embryogenesis inferred from somatic mutation. Nature 597, 393–397 (2021).
Volkova, N. V. et al. Mutational signatures are jointly shaped by DNA damage and repair. Nat. Commun. 11, 2169 (2020).
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).
Bae, T. et al. Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis. Science 359, 550–555 (2018). This article presents rates and mechanisms of somatic mutation accumulation in human neuronal progenitors.
McConnell, M. J. et al. Mosaic copy number variation in human neurons. Science 342, 632–637 (2013).
Knouse, K. A., Wu, J. & Amon, A. Assessment of megabase-scale somatic copy number variation using single-cell sequencing. Genome Res. 26, 376–384 (2016).
Cai, X. et al. Single-cell, genome-wide sequencing identifies clonal somatic copy-number variation in the human brain. Cell Rep. 8, 1280–1289 (2014).
Evrony, G. D. et al. Single-neuron sequencing analysis of L1 retrotransposition and somatic mutation in the human brain. Cell 151, 483–496 (2012).
Erwin, J. A. et al. L1-associated genomic regions are deleted in somatic cells of the healthy human brain. Nat. Neurosci. 19, 1583–1591 (2016).
Ganz, J. et al. Rates and patterns of clonal oncogenic mutations in the normal human brain. Cancer Discov. 12, 172–185 (2022).
Tomkova, M., Tomek, J., Kriaucionis, S. & Schuster-Bockler, B. Mutational signature distribution varies with DNA replication timing and strand asymmetry. Genome Biol. 19, 129 (2018).
Tate, J. G. et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Res. 47, D941–D947 (2019).
Huang, A. Y. et al. Distinctive types of postzygotic single-nucleotide mosaicisms in healthy individuals revealed by genome-wide profiling of multiple organs. PLoS Genet. 14, e1007395 (2018).
Wu, W. et al. Neuronal enhancers are hotspots for DNA single-strand break repair. Nature 593, 440–444 (2021).
Reid, D. A. et al. Incorporation of a nucleoside analog maps genome repair sites in postmitotic human neurons. Science 372, 91–94 (2021).
Raj, B. et al. Simultaneous single-cell profiling of lineages and cell types in the vertebrate brain. Nat. Biotechnol. 36, 442–450 (2018).
Alemany, A., Florescu, M., Baron, C. S., Peterson-Maduro, J. & van Oudenaarden, A. Whole-organism clone tracing using single-cell sequencing. Nature 556, 108–112 (2018).
Rodriguez-Fraticelli, A. E. et al. Clonal analysis of lineage fate in native haematopoiesis. Nature 553, 212–216 (2018).
Wagner, D. E. et al. Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo. Science 360, 981–987 (2018).
Leeper, K. et al. Lineage barcoding in mice with homing CRISPR. Nat. Protoc. 16, 2088–2108 (2021).
Spanjaard, B. et al. Simultaneous lineage tracing and cell-type identification using CRISPR-Cas9-induced genetic scars. Nat. Biotechnol. 36, 469–473 (2018).
McKenna, A. et al. Whole-organism lineage tracing by combinatorial and cumulative genome editing. Science 353, aaf7907 (2016).
Kalhor, R. et al. Developmental barcoding of whole mouse via homing CRISPR. Science 361, eaat9804 (2018). This article is a very nice example of prospective lineage tracing in a model organism using genome editing to introduce cell barcodes.
Chan, M. M. et al. Molecular recording of mammalian embryogenesis. Nature 570, 77–82 (2019).
Llorca, A. et al. A stochastic framework of neurogenesis underlies the assembly of neocortical cytoarchitecture. eLife 8, e51381 (2019).
Hansen, D. V., Lui, J. H., Parker, P. R. & Kriegstein, A. R. Neurogenic radial glia in the outer subventricular zone of human neocortex. Nature 464, 554–561 (2010).
Xiang, L. et al. A developmental landscape of 3D-cultured human pre-gastrulation embryos. Nature 577, 537–542 (2020).
Rakic, P. Radial versus tangential migration of neuronal clones in the developing cerebral cortex. Proc. Natl Acad. Sci. USA 92, 11323–11327 (1995).
Price, J., Turner, D. & Cepko, C. Lineage analysis in the vertebrate nervous system by retrovirus-mediated gene transfer. Proc. Natl Acad. Sci. USA 84, 156–160 (1987).
Cepko, C. Retrovirus vectors and their applications in neurobiology. Neuron 1, 345–353 (1988).
Huang, Z. J. & Zeng, H. Genetic approaches to neural circuits in the mouse. Annu. Rev. Neurosci. 36, 183–215 (2013).
Joyner, A. L. & Zervas, M. Genetic inducible fate mapping in mouse: establishing genetic lineages and defining genetic neuroanatomy in the nervous system. Dev. Dyn. 235, 2376–2385 (2006).
He, M. et al. Strategies and tools for combinatorial targeting of GABAergic neurons in mouse cerebral cortex. Neuron 92, 555 (2016).
Livet, J. et al. Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature 450, 56–62 (2007).
Lee, T. & Luo, L. Mosaic analysis with a repressible cell marker for studies of gene function in neuronal morphogenesis. Neuron 22, 451–461 (1999).
Zong, H., Espinosa, J. S., Su, H. H., Muzumdar, M. D. & Luo, L. Mosaic analysis with double markers in mice. Cell 121, 479–492 (2005).
Tasic, B. et al. Extensions of MADM (mosaic analysis with double markers) in mice. PLoS ONE 7, e33332 (2012).
Gao, P. et al. Deterministic progenitor behavior and unitary production of neurons in the neocortex. Cell 159, 775–788 (2014).
Beattie, R. et al. Mosaic analysis with double markers reveals distinct sequential functions of Lgl1 in neural stem cells. Neuron 94, 517–533.e3 (2017).
Bonaguidi, M. A. et al. In vivo clonal analysis reveals self-renewing and multipotent adult neural stem cell characteristics. Cell 145, 1142–1155 (2011).
Ma, J., Shen, Z., Yu, Y. C. & Shi, S. H. Neural lineage tracing in the mammalian brain. Curr. Opin. Neurobiol. 50, 7–16 (2018).
Reid, C. B., Tavazoie, S. F. & Walsh, C. A. Clonal dispersion and evidence for asymmetric cell division in ferret cortex. Development 124, 2441–2450 (1997).
Ware, M. L., Tavazoie, S. F., Reid, C. B. & Walsh, C. A. Coexistence of widespread clones and large radial clones in early embryonic ferret cortex. Cereb. Cortex 9, 636–645 (1999).
Kornack, D. R. & Rakic, P. Radial and horizontal deployment of clonally related cells in the primate neocortex: relationship to distinct mitotic lineages. Neuron 15, 311–321 (1995).
Betizeau, M. et al. Precursor diversity and complexity of lineage relationships in the outer subventricular zone of the primate. Neuron 80, 442–457 (2013).
Gertz, C. C., Lui, J. H., LaMonica, B. E., Wang, X. & Kriegstein, A. R. Diverse behaviors of outer radial glia in developing ferret and human cortex. J. Neurosci. 34, 2559–2570 (2014).
Lin, Y. et al. Behavior and lineage progression of neural progenitors in the mammalian cortex. Curr. Opin. Neurobiol. 66, 144–157 (2021). This is a nice recent review of what is known about mammalian cortical progenitors and their lineage output, including differences between lissencephalic and gyrencephalic species such as humans.
Huang, A. Y. et al. Parallel RNA and DNA analysis after deep sequencing (PRDD-seq) reveals cell type-specific lineage patterns in human brain. Proc. Natl Acad. Sci. USA 117, 13886–13895 (2020). This work presents a recently developed method to detect clonal somatic variants and expression of cell type-specific gene markers in the same single cell to couple lineage tracing with cell type information in the human brain.
Delgado, R. N. et al. Individual human cortical progenitors can produce excitatory and inhibitory neurons. Nature 601, 397–403 (2021).
Hansen, D. V. et al. Non-epithelial stem cells and cortical interneuron production in the human ganglionic eminences. Nat. Neurosci. 16, 1576–1587 (2013).
Rudy, B., Fishell, G., Lee, S. & Hjerling-Leffler, J. Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons. Dev. Neurobiol. 71, 45–61 (2011).
Nigro, M. J., Hashikawa-Yamasaki, Y. & Rudy, B. Diversity and connectivity of layer 5 somatostatin-expressing interneurons in the mouse barrel cortex. J. Neurosci. 38, 1622–1633 (2018).
Hodge, R. D. et al. Conserved cell types with divergent features in human versus mouse cortex. Nature 573, 61–68 (2019). This work presents one of the most updated classifications of human brain cell types obtained from single-cell transcriptomics.
Ang, E. S. Jr., Haydar, T. F., Gluncic, V. & Rakic, P. Four-dimensional migratory coordinates of GABAergic interneurons in the developing mouse cortex. J. Neurosci. 23, 5805–5815 (2003).
Rymar, V. V. & Sadikot, A. F. Laminar fate of cortical GABAergic interneurons is dependent on both birthdate and phenotype. J. Comp. Neurol. 501, 369–380 (2007).
Nemtsova, M. V. et al. Clinical relevance of somatic mutations in main driver genes detected in gastric cancer patients by next-generation DNA sequencing. Sci. Rep. 10, 504 (2020).
van Rooij, J. et al. Somatic TARDBP variants as a cause of semantic dementia. Brain 143, 3827–3841 (2020).
Mass, E. et al. A somatic mutation in erythro-myeloid progenitors causes neurodegenerative disease. Nature 549, 389–393 (2017).
Park, J. S. et al. Brain somatic mutations observed in Alzheimer’s disease associated with aging and dysregulation of tau phosphorylation. Nat. Commun. 10, 3090 (2019).
Lobon, I. et al. Somatic mutations in Parkinson disease are enriched in synaptic and neuronal processes. Preprint at medRxiv https://doi.org/10.1101/2020.09.14.20190538 (2020).
Miller, M. B., Reed, H. C. & Walsh, C. A. Brain somatic mutation in aging and Alzheimer’s disease. Annu. Rev. Genomics Hum. Genet. 22, 239–256 (2021).
Doan, R. N. et al. Mutations in human accelerated regions disrupt cognition and social behavior. Cell 167, 341–354.e12 (2016).
Lim, E. T. et al. Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder. Nat. Neurosci. 20, 1217–1224 (2017).
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).
Poduri, A. et al. Somatic activation of AKT3 causes hemispheric developmental brain malformations. Neuron 74, 41–48 (2012).
Conti, V. et al. Focal dysplasia of the cerebral cortex and infantile spasms associated with somatic 1q21.1-q44 duplication including the AKT3 gene. Clin. Genet. 88, 241–247 (2015).
Kobow, K. et al. Mosaic trisomy of chromosome 1q in human brain tissue associates with unilateral polymicrogyria, very early-onset focal epilepsy, and severe developmental delay. Acta Neuropathol. 140, 881–891 (2020).
Kim, M.-H. et al. Low-level brain somatic mutations are implicated in schizophrenia. Biol. Psychiatry 90, 35–46 (2021).
Fullard, J. F. et al. Assessment of somatic single-nucleotide variation in brain tissue of cases with schizophrenia. Transl. Psychiatry 9, 21 (2019).
Blümcke, I. et al. Toward a better definition of focal cortical dysplasia: an iterative histopathological and genetic agreement trial. Epilepsia 62, 1416–1428 (2021).
D’Gama, A. M. et al. Somatic mutations activating the mTOR pathway in dorsal telencephalic progenitors cause a continuum of cortical dysplasias. Cell Rep. 21, 3754–3766 (2017).
Jansen, L. A. et al. PI3K/AKT pathway mutations cause a spectrum of brain malformations from megalencephaly to focal cortical dysplasia. Brain 138, 1613–1628 (2015).
Lim, J. S. et al. Brain somatic mutations in MTOR cause focal cortical dysplasia type II leading to intractable epilepsy. Nat. Med. 21, 395–400 (2015).
Lee, W. S. et al. Gradient of brain mosaic RHEB variants causes a continuum of cortical dysplasia. Ann. Clin. Transl. Neurol. 8, 485–490 (2021).
Baldassari, S. et al. Dissecting the genetic basis of focal cortical dysplasia: a large cohort study. Acta Neuropathol. 138, 885–900 (2019). This article shows the role of pathogenic brain somatic mutations in a wide cohort of patients affected by epileptic FCD.
Lee, J. H. et al. De novo somatic mutations in components of the PI3K-AKT3-mTOR pathway cause hemimegalencephaly. Nat. Genet. 44, 941–945 (2012).
Lim, J. S. et al. Somatic mutations in TSC1 and TSC2 cause focal cortical dysplasia. Am. J. Hum. Genet. 100, 454–472 (2017).
Ribierre, T. et al. Second-hit mosaic mutation in mTORC1 repressor DEPDC5 causes focal cortical dysplasia-associated epilepsy. J. Clin. Invest. 128, 2452–2458 (2018).
Winawer, M. R. et al. Somatic SLC35A2 variants in the brain are associated with intractable neocortical epilepsy. Ann. Neurol. 83, 1133–1146 (2018).
Bonduelle, T. et al. Frequent SLC35A2 brain mosaicism in mild malformation of cortical development with oligodendroglial hyperplasia in epilepsy (MOGHE). Acta Neuropathol. Commun. 9, 3 (2021).
Blumcke, I. et al. The clinicopathologic spectrum of focal cortical dysplasias: a consensus classification proposed by an ad hoc task force of the ILAE Diagnostic Methods Commission. Epilepsia 52, 158–174 (2011).
Cepeda, C. et al. Epileptogenesis in pediatric cortical dysplasia: the dysmature cerebral developmental hypothesis. Epilepsy Behav. 9, 219–235 (2006).
Koh, H. Y. et al. BRAF somatic mutation contributes to intrinsic epileptogenicity in pediatric brain tumors. Nat. Med. 24, 1662–1668 (2018).
Koh, H. Y. et al. Non-cell autonomous epileptogenesis in focal cortical dysplasia. Ann. Neurol. 90, 285–299 (2021). This article presents a mouse model of FCD due to brain mTOR activating somatic mutations and nicely explains the cell-autonomous versus non-cell-autonomous effects in mosaic brain disorders.
Nguyen, L. H. et al. Genetic expression of 4E-BP1 in juvenile mice alleviates mTOR-induced neuronal dysfunction and epilepsy. Brain https://doi.org/10.1093/brain/awab390 (2021).
Weiner, D. J. et al. Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders. Nat. Genet. 49, 978–985 (2017).
Krumm, N. et al. Excess of rare, inherited truncating mutations in autism. Nat. Genet. 47, 582–588 (2015).
Sanders, S. J. et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature 485, 237–241 (2012).
Mitra, I. et al. Patterns of de novo tandem repeat mutations and their role in autism. Nature 589, 246–250 (2021).
Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014).
Doan, R. N. et al. Recessive gene disruptions in autism spectrum disorder. Nat. Genet. 51, 1092–1098 (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). This work analyses whole-exome sequencing data to show the contribution of somatic mosaic mutations to ASDs.
Krupp, D. R. et al. Exonic mosaic mutations contribute risk for autism spectrum disorder. Am. J. Hum. Genet. 101, 369–390 (2017).
Yin, Y. et al. High-throughput single-cell sequencing with linear amplification. Mol. Cell 76, 676–690.e10 (2019). This article presents one of the most high-throughput single-cell sequencing methods now available.
Chen, C. et al. Single-cell whole-genome analyses by linear amplification via transposon insertion (LIANTI). Science 356, 189–194 (2017).
Lareau, C. A. et al. Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling. Nat. Biotechnol. 39, 451–461 (2020).
Xu, J. et al. Single-cell lineage tracing by endogenous mutations enriched in transposase accessible mitochondrial DNA. eLife 8, e45105 (2019).
Zhong, S. et al. A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex. Nature 555, 524–528 (2018).
Chow, K.-H. K. et al. Imaging cell lineage with a synthetic digital recording system. Science 372, eabb3099 (2021).
Liao, J., Lu, X., Shao, X., Zhu, L. & Fan, X. Uncovering an organ’s molecular architecture at single-cell resolution by spatially resolved transcriptomics. Trends Biotechnol. 39, 43–58 (2021).
Pollen, A. A. et al. Molecular identity of human outer radial glia during cortical development. Cell 163, 55–67 (2015).
Martincorena, I. et al. Universal patterns of selection in cancer and somatic tissues. Cell 173, 1823 (2018).
Kakiuchi, N. & Ogawa, S. Clonal expansion in non-cancer tissues. Nat. Rev. Cancer 21, 239–256 (2021).
Acknowledgements
The authors thank K. Probst (Xavier Studio) for valuable assistance with figure assembly and design. They also thank all their colleagues at Boston Children’s Hospital and Harvard Medical School for discussions that helped formulate and clarify ideas included in this Review. C.A.W. is an investigator of the Howard Hughes Medical Institute, supported by the Allen Frontiers Group through the Allen Discovery Center for Human Brain Evolution and by NINDS grants R01NS32457 and R01NS35129. S.B. was supported by the Manton Center for Orphan Disease Research at Boston Children’s Hospital and is now supported by a European Commission’s Horizon 2020 Research and Innovation Programme Marie Skłodowska-Curie Actions Individual Fellowship (grant agreement no. 101026484 — CODICES).
Author information
Authors and Affiliations
Contributions
S.B. and C.A.W. wrote the Review and contributed substantially to discussion of the content.
Corresponding authors
Ethics declarations
Competing interests
C.A.W. is a paid consultant (cash and no equity) for Third Rock Ventures and is on the Clinical Advisory Board (cash and equity) of Maze Therapeutics. No research support was received. These companies did not fund and had no role in the writing of this Review. S.B. declares no competing interests.
Peer review
Peer review information
Nature Reviews Neuroscience thanks B. Treutlein, J.H. Lee and the other, anonymous reviewers for their contribution to the peer review of this work.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Glossary
- Bulk variant allele frequency
-
Fraction of reads showing the mutant allele (compared with the reference human genome) calculated on the basis of the total number of reads covering the mutation position as obtained from deep bulk (non-single-cell) DNA sequencing.
- Allelic imbalance
-
Where two alleles of a given gene are represented at different levels in the DNA sample, which results from higher amplification of one allele over the other at the time of whole-genome amplification and/or library preparation and consequently across sequencing reads.
- Variant calling
-
The process of identifying in sequencing data the sequence changes such as single-nucleotide variants and indels that are present in a given genome compared with the reference genome.
- Indels
-
Genetic mutations described as insertions or deletions of one or more base pairs (typically fewer than 1,000) at a defined position compared with the reference human genome.
- Copy number variants
-
(CNVs). Genetic mutations defined as deletions or repetitions of sections of the human genome of variable size that lead to partial aneuploidy (one copy instead of two copies) or multiploidy (more than two copies), respectively.
- Inversions
-
Genetic mutations that consist of a section of the genome with the wrong (opposite) orientation, generated by a double break followed by change in the orientation of the DNA section and reinsertion in the same position.
- Translocations
-
Changes in the location of sections of the genome that occur when parts of one chromosome are transferred to another chromosome.
- Whole-chromosome gains or losses
-
Copy number variants of a type by which an entire chromosome is present in one copy instead of two copies (chromosome loss, aneuploidy) or alternatively when an entire chromosome is found in more than two copies (chromosome gain, multiploidy).
- Mobile genetic element insertions
-
Insertions in the genome of new copies of discrete segments of genomic DNA.
- Long-read sequencing
-
Also known as third-generation sequencing, a class of DNA sequencing methods that generate reads much longer (10–15 kb, up to 30 kb) than classical short-read next-generation sequencing methods (~150 bp).
- Retrotransposition events
-
Mobile genetic element insertions of a type involving class I transposable elements that are able to copy and paste themselves by generating an RNA intermediate.
- Gyrencephalic
-
Condition by which the surface of the cerebral cortex is characterized by the presence of convolutions made of alternating gyri and sulci, in contrast to the lissencephalic cerebral cortex, where the surface is smooth.
- Cytomegalic dysmorphic neurons
-
Abnormal neurons that represent a histopathological hallmark of focal cortical dysplasia type 2 and are characterized by a significantly enlarged cell body and nucleus, misorientation, abnormally distributed intracellular Nissl substance and cytoplasmic accumulation of neurofilament proteins.
- Balloon cells
-
Abnormal cells of unclear identity that represent a histopathological hallmark of focal cortical dysplasia type 2B and that are characterized by a large cell body, opalescent glassy eosinophilic cytoplasm (visible by haematoxylin and eosin staining) and absence of Nissl substance.
- Positive selection
-
The process by which a clone acquires a selective advantage and proliferates more with respect to surrounding clones, leading to an over-representation in the tissue.
- Epigenomics
-
Study of the ensemble of the epigenetic changes such as methylation and histone modifications present across the genome.
Rights and permissions
About this article
Cite this article
Bizzotto, S., Walsh, C.A. Genetic mosaicism in the human brain: from lineage tracing to neuropsychiatric disorders. Nat Rev Neurosci 23, 275–286 (2022). https://doi.org/10.1038/s41583-022-00572-x
Accepted:
Published:
Issue date:
DOI: https://doi.org/10.1038/s41583-022-00572-x
This article is cited by
-
Spatial transcriptomic imaging of an intact organism using volumetric DNA microscopy
Nature Biotechnology (2025)
-
The Principle of Cortical Development and Evolution
Neuroscience Bulletin (2025)
-
The Somatic Mosaicism across Human Tissues Network
Nature (2025)
-
Targeting pathological cells with senolytic drugs reduces seizures in neurodevelopmental mTOR-related epilepsy
Nature Neuroscience (2024)
-
Genetics of human brain development
Nature Reviews Genetics (2024)
