• 1.

    Biesecker, L. G. & Spinner, N. B. A genomic view of mosaicism and human disease. Nat. Rev. Genet. 14, 307–320 (2013).

  • 2.

    Lupski, J. R. Genome mosaicism–one human, multiple genomes. Science 341, 358–359 (2013).

  • 3.

    Acuna-Hidalgo, R. et al. Post-zygotic point mutations are an underrecognized source of de novo genomic variation. Am. J. Hum. Genet. 97, 67–74 (2015).

  • 4.

    Campbell, I. M. et al. Parental somatic mosaicism is underrecognized and influences recurrence risk of genomic disorders. Am. J. Hum. Genet. 95, 173–182 (2014).

  • 5.

    Halvorsen, M. et al. Mosaic mutations in early-onset genetic diseases. Genet. Med. 18, 746–749 (2016).

  • 6.

    Myers, C. T. et al. Parental mosaicism in “de novo” epileptic encephalopathies. N. Engl. J. Med. 378, 1646–1648 (2018).

  • 7.

    Campbell, I. M. et al. Parent of origin, mosaicism, and recurrence risk: probabilistic modeling explains the broken symmetry of transmission genetics. Am. J. Hum. Genet. 95, 345–359 (2014).

  • 8.

    Breuss, M. et al. Quantification of autism recurrence risk by direct assessment of paternal sperm mosaicism. BioRxiv. https://doi.org/10.1101/208165 (2017)

  • 9.

    Jonsson, H. et al. Recurrence of de novo mutations in families. BioRxiv. https://doi.org/10.1101/221259 (2017)

  • 10.

    Rahbari, R. et al. Timing, rates and spectra of human germline mutation. Nat. Genet. 48, 126–133 (2016).

  • 11.

    Poduri, A., Evrony, G. D., Cai, X. & Walsh, C. A. Somatic mutation, genomic variation, and neurological disease. Science 341, 1237758 (2013).

  • 12.

    Nathan, N., Keppler-Noreuil, K. M., Biesecker, L. G., Moss, J. & Darling, T. N. Mosaic disorders of the pi3k/pten/akt/tsc/mtorc1 signaling pathway. Dermatol Clin. 35, 51–60 (2017).

  • 13.

    Ansari, M. et al. Genetic heterogeneity in Cornelia de Lange syndrome (CdLS) and CdLS-like phenotypes with observed and predicted levels of mosaicism. J. Med. Genet. 51, 659–668 (2014).

  • 14.

    Goriely, A. et al. Germline and somatic mosaicism for FGFR2 mutation in the mother of a child with Crouzon syndrome: Implications for genetic testing in “paternal age-effect” syndromes. Am. J. Med. Genet. A 152A, 2067–2073 (2010).

  • 15.

    Xin, B. et al. Novel DNMT3A germline mutations are associated with inherited Tatton-Brown-Rahman syndrome. Clin. Genet. 91, 623–628 (2017).

  • 16.

    Stosser, M. B. et al. High frequency of mosaic pathogenic variants in genes causing epilepsy-related neurodevelopmental disorders. Genet. Med. https://doi.org/10.1038/gim.2017.114 (2017)

  • 17.

    King, D. A. et al. Detection of structural mosaicism from targeted and whole-genome sequencing data. Genome Res. 27, 1704–1714 (2017).

  • 18.

    King, D. A. et al. Mosaic structural variation in children with developmental disorders. Hum. Mol. Genet. 24, 2733–2745 (2015).

  • 19.

    Papavassiliou, P., Charalsawadi, C., Rafferty, K. & Jackson-Cook, C. Mosaicism for trisomy 21: a review. Am. J. Med. Genet. A 167A, 26–39 (2015).

  • 20.

    Delhanty, J. D. A. Inherited aneuploidy: germline mosaicism. Cytogenet Genome Res 133, 136–140 (2011).

  • 21.

    Conlin, L. K. et al. Mechanisms of mosaicism, chimerism and uniparental disomy identified by single nucleotide polymorphism array analysis. Hum. Mol. Genet. 19, 1263–1275 (2010).

  • 22.

    Krupp, D. R. et al. Exonic mosaic mutations contribute risk for autism spectrum disorder. Am. J. Hum. Genet. 101, 369–390 (2017).

  • 23.

    Lim, E. T. et al. Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder. Nat. Neurosci. 20, 1217–1224 (2017).

  • 24.

    Huisman, S. A., Redeker, E. J. W., Maas, S. M., Mannens, M. M. & Hennekam, R. C. M. High rate of mosaicism in individuals with Cornelia de Lange syndrome. J. Med. Genet. 50, 339–344 (2013).

  • 25.

    Qin, L. et al. Detection and quantification of mosaic mutations in disease genes by next-generation sequencing. J. Mol. Diagn. 18, 446–453 (2016).

  • 26.

    Gajecka, M. Unrevealed mosaicism in the next-generation sequencing era. Mol. Genet. Genom. 291, 513–530 (2016).

  • 27.

    Metzker, M. L. Sequencing technologies—the next generation. Nat. Rev. Genet. 11, 31–46 (2010).

  • 28.

    Rios, J. J. & Delgado, M. R. Using whole-exome sequencing to identify variants inherited from mosaic parents. Eur. J. Hum. Genet. 23, 547–550 (2015).

  • 29.

    Contini, E. et al. A systematic assessment of accuracy in detecting somatic mosaic variants by deep amplicon sequencing: application to NF2 gene. PLoS ONE 10, e0129099 (2015).

  • 30.

    de Lange, I. M. et al. Mosaicism of de novo pathogenic SCN1A variants in epilepsy is a frequent phenomenon that correlates with variable phenotypes. Epilepsia 59, 690–703 (2018).

  • 31.

    Deciphering Developmental Disorders Study. Prevalence and architecture of de novo mutations in developmental disorders. Nature 542, 433–438 (2017).

  • 32.

    Wright, C. F. et al. Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. Lancet 385, 1305–1314 (2015).

  • 33.

    Wright, C. F. et al. Making new genetic diagnoses with old data: iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders. Genet. Med. 20, 1216–1223 (2018).

  • 34.

    Firth, H. V. & Wright, C. F., DDD Study. The deciphering developmental disorders (DDD) study. Dev. Med. Child Neurol. 53, 702–703 (2011).

  • 35.

    Marini, C., Mei, D., Helen Cross, J. & Guerrini, R. Mosaic SCN1A mutation in familial severe myoclonic epilepsy of infancy. Epilepsia 47, 1737–1740 (2006).

  • 36.

    Nakayama, T. et al. Somatic mosaic deletions involving SCN1A cause Dravet syndrome. Am. J. Med. Genet. A 176, 657–662 (2018).

  • 37.

    Meisler, M. H. et al. SCN8A encephalopathy: research progress and prospects. Epilepsia 57, 1027–1035 (2016).

  • 38.

    Wall, J. D. et al. Estimating genotype error rates from high-coverage next-generation sequence data. Genome Res. 24, 1734–1739 (2014).

  • 39.

    Jónsson, H. et al. Parental influence on human germline de novo mutations in 1,548 trios from Iceland. Nature 549, 519–522 (2017).

  • 40.

    Snape, K. et al. Mutations in CEP57 cause mosaic variegated aneuploidy syndrome. Nat. Genet. 43, 527–529 (2011).

  • 41.

    Hochstenbach, R. et al. Monosomy 20 mosaicism revealed by extensive karyotyping in blood and skin cells: case report and review of the literature. Cytogenet Genome Res 144, 155–162 (2014).

  • 42.

    Choufani, S. et al. NSD1 mutations generate a genome-wide DNA methylation signature. Nat. Commun. 6, 10207 (2015).

  • 43.

    Brzezinski, J. et al. Wilms tumour in Beckwith-Wiedemann Syndrome and loss of methylation at imprinting centre 2: revisiting tumour surveillance guidelines. Eur. J. Hum. Genet. 25, 1031–1039 (2017).

  • 44.

    Butcher, D. T. et al. CHARGE and Kabuki Syndromes: gene-specific dna methylation signatures identify epigenetic mechanisms linking these clinically overlapping conditions. Am. J. Hum. Genet. 100, 773–788 (2017).

  • 45.

    Jamuar, S. S. et al. Somatic mutations in cerebral cortical malformations. N. Engl. J. Med. 371, 733–743 (2014).

  • 46.

    Hiatt, J. B., Pritchard, C. C., Salipante, S. J., O’Roak, B. J. & Shendure, J. Single molecule molecular inversion probes for targeted, high-accuracy detection of low-frequency variation. Genome Res. 23, 843–854 (2013).

  • 47.

    Kennedy, S. R. et al. Detecting ultralow-frequency mutations by duplex sequencing. Nat. Protoc. 9, 2586–2606 (2014).

  • 48.

    Yang, X. et al. Genomic mosaicism in paternal sperm and multiple parental tissues in a Dravet syndrome cohort. Sci. Rep. 7, 15677 (2017).

  • 49.

    Bragin, E. et al. DECIPHER: database for the interpretation of phenotype-linked plausibly pathogenic sequence and copy-number variation. Nucleic Acids Res. 42, D993–D1000 (2014).

  • 50.

    Köhler, S. et al. The human phenotype ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res. 42, D966–D974 (2014).

  • 51.

    Deciphering Developmental Disorders Study. Large-scale discovery of novel genetic causes of developmental disorders. Nature 519, 223–228 (2015).

  • 52.

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

  • 53.

    McKenna, A. et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

  • 54.

    Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

  • 55.

    Ramu, A. et al. DeNovoGear: de novo indel and point mutation discovery and phasing. Nat. Methods 10, 985–987 (2013).

  • 56.

    1000 Genomes Project Consortium. et al. An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65 (2012).

  • 57.

    UK10K Consortium. et al. The UK10K project identifies rare variants in health and disease. Nature 526, 82–90 (2015).

  • 58.

    Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).

  • 59.

    McLaren, W. et al. The ensembl variant effect predictor. Genome Biol. 17, 122 (2016).

  • 60.

    Samocha, K. E. et al. A framework for the interpretation of de novo mutation in human disease. Nat. Genet. 46, 944–950 (2014).

  • 61.

    Thorvaldsdóttir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).

  • Source