Next-generation sequencing in Charcot–Marie–Tooth disease: opportunities and challenges

Abstract

Charcot–Marie–Tooth disease and the related disorders hereditary motor neuropathy and hereditary sensory neuropathy, collectively termed CMT, are the commonest group of inherited neuromuscular diseases, and they exhibit wide phenotypic and genetic heterogeneity. CMT is usually characterized by distal muscle atrophy, often with foot deformity, weakness and sensory loss. In the past decade, next-generation sequencing (NGS) technologies have revolutionized genomic medicine and, as these technologies are being applied to clinical practice, they are changing our diagnostic approach to CMT. In this Review, we discuss the application of NGS technologies, including disease-specific gene panels, whole-exome sequencing, whole-genome sequencing (WGS), mitochondrial sequencing and high-throughput transcriptome sequencing, to the diagnosis of CMT. We discuss the growing challenge of variant interpretation and consider how the clinical phenotype can be combined with genetic, bioinformatic and functional evidence to assess the pathogenicity of genetic variants in patients with CMT. WGS has several advantages over the other techniques that we discuss, which include unparalleled coverage of coding, non-coding and intergenic areas of both nuclear and mitochondrial genomes, the ability to identify structural variants and the opportunity to perform genome-wide dense homozygosity mapping. We propose an algorithm for incorporating WGS into the CMT diagnostic pathway.

Key points

  • In Charcot–Marie–Tooth disease (CMT), next-generation sequencing (NGS) technologies are applied in the form of specific CMT-associated gene panels, whole-exome sequencing, whole-genome sequencing (WGS), mitochondrial sequencing and high-throughput transcriptome sequencing.

  • Interpretation of NGS-derived variants is challenging owing to the high volume of returned variants and the phenotypic and genetic heterogeneity of CMT.

  • Setting a maximum credible population allele frequency for pathogenic variants in dominant and recessive CMT-associated genes is crucial for efficiently filtering NGS-derived variants.

  • A genome-first approach utilizing WGS has multiple advantages over other genetic tests for the diagnosis of CMT and should be combined with virtual gene panels to achieve the optimum balance between improved diagnostic yield and burden of variant analysis.

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Fig. 1: Venn diagrams showing CMT-associated genes by broad CMT phenotype.
Fig. 2: Deep CMT phenotype–genotype correlations.
Fig. 3: Proposed CMT diagnostic pathway integrating whole-genome sequencing.

References

  1. 1.

    Skre, H. Genetic and clinical aspects of Charcot-Marie-Tooth’s disease. Clin. Genet. 6, 98–118 (1974).

    CAS  PubMed  Google Scholar 

  2. 2.

    Barreto, C. L. S. et al. Epidemiologic study of Charcot-Marie-Tooth disease: a systematic review. Neuroepidemiology 46, 157–165 (2016).

    PubMed  Google Scholar 

  3. 3.

    Reilly, M. M., Murphy, S. M. & Laura, M. Charcot-Marie-Tooth disease. J. Peripher. Nerv. Syst. 16, 1–14 (2011).

    PubMed  Google Scholar 

  4. 4.

    Feely, S. M. E. et al. MFN2 mutations cause severe phenotypes in most patients with CMT2A. Neurology 76, 1690–1696 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Harding, A. E. & Thomas, P. K. The clinical features of hereditary motor and sensory neuropathy types I and II. Brain 103, 259–280 (1980).

    CAS  PubMed  Google Scholar 

  6. 6.

    Mathis, S. et al. Charcot-Marie-Tooth diseases: an update and some new proposals for the classification. J. Med. Genet. 52, 681–690 (2015).

    PubMed  Google Scholar 

  7. 7.

    Rossor, A. M. et al. Peripheral neuropathy in complex inherited diseases: an approach to diagnosis. J. Neurol. Neurosurg. Psychiatry 88, 846–863 (2017).

    PubMed  Google Scholar 

  8. 8.

    Fridman, V. et al. CMT subtypes and disease burden in patients enrolled in the Inherited Neuropathies Consortium Natural History study: a cross-sectional analysis. J. Neurol. Neurosurg. Psychiatry 86, 873–878 (2015).

    CAS  PubMed  Google Scholar 

  9. 9.

    Rossor, A. M., Tomaselli, P. J. & Reilly, M. M. Recent advances in the genetic neuropathies. Curr. Opin. Neurol. 29, 537–548 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Murphy, S. M. et al. Charcot-Marie-Tooth disease: frequency of genetic subtypes and guidelines for genetic testing. J. Neurol. Neurosurg. Psychiatry 83, 706–710 (2012).

    PubMed  PubMed Central  Google Scholar 

  11. 11.

    Saporta, A. S. D. et al. Charcot-Marie-Tooth disease subtypes and genetic testing strategies. Ann. Neurol. 69, 22–33 (2011).

    PubMed  PubMed Central  Google Scholar 

  12. 12.

    Rossor, A. M., Polke, J. M., Houlden, H. & Reilly, M. M. Clinical implications of genetic advances in Charcot-Marie-Tooth disease. Nat. Rev. Neurol. 9, 562–571 (2013).

    CAS  PubMed  Google Scholar 

  13. 13.

    Landrum, M. J. et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46, D1062–D1067 (2018).

    CAS  PubMed  Google Scholar 

  14. 14.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Zuk, O. et al. Searching for missing heritability: designing rare variant association studies. Proc. Natl Acad. Sci. USA 111, E455–E464 (2014).

    CAS  PubMed  Google Scholar 

  16. 16.

    Marttila, M. et al. Molecular epidemiology of Charcot-Marie-Tooth disease in Northern Ostrobothnia, Finland: a population-based study. Neuroepidemiology 49, 34–39 (2017).

    PubMed  Google Scholar 

  17. 17.

    Gabrikova, D. et al. Founder mutations in NDRG1 and HK1 genes are common causes of inherited neuropathies among Roma/Gypsies in Slovakia. J. Appl. Genet. 54, 455–460 (2013).

    CAS  PubMed  Google Scholar 

  18. 18.

    Lupo, V. et al. Characterising the phenotype and mode of inheritance of patients with inherited peripheral neuropathies carrying MME mutations. J. Med. Genet. 55, 814–823 (2018).

    CAS  PubMed  Google Scholar 

  19. 19.

    Higuchi, Y. et al. Mutations in MME cause an autosomal-recessive Charcot-Marie-Tooth disease type 2. Ann. Neurol. 79, 659–672 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Gilissen, C. et al. Genome sequencing identifies major causes of severe intellectual disability. Nature 511, 344–347 (2014).

    CAS  PubMed  Google Scholar 

  21. 21.

    Antoniadi, T. et al. Application of targeted multi-gene panel testing for the diagnosis of inherited peripheral neuropathy provides a high diagnostic yield with unexpected phenotype-genotype variability. BMC Med. Genet. 16, 84 (2015).

    PubMed  PubMed Central  Google Scholar 

  22. 22.

    Nam, S. H. et al. Identification of genetic causes of inherited peripheral neuropathies by targeted gene panel sequencing. Mol. Cells 39, 382–388 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Lupo, V. et al. Assessment of targeted next-generation sequencing as a tool for the diagnosis of Charcot-Marie-Tooth disease and hereditary motor neuropathy. J. Mol. Diagn. 18, 225–234 (2016).

    CAS  PubMed  Google Scholar 

  24. 24.

    Yoshimura, A. et al. Genetic profile and onset features of 1005 patients with Charcot-Marie-Tooth disease in Japan. J. Neurol. Neurosurg. Psychiatry 90, 195–202 (2018).

    PubMed  PubMed Central  Google Scholar 

  25. 25.

    Wang, W. et al. Target-enrichment sequencing and copy number evaluation in inherited polyneuropathy. Neurology 86, 1762–1771 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Meienberg, J., Bruggmann, R., Oexle, K. & Matyas, G. Clinical sequencing: is WGS the better WES? Hum. Genet. 135, 359–362 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Choi, B. O. et al. Exome sequencing is an efficient tool for genetic screening of Charcot-Marie-Tooth disease. Hum. Mutat. 33, 1610–1615 (2012).

    CAS  PubMed  Google Scholar 

  28. 28.

    Drew, A. P. et al. Improved inherited peripheral neuropathy genetic diagnosis by whole-exome sequencing. Mol. Genet. Genomic Med. 3, 143–154 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Gonzaga-Jauregui, C. et al. Exome sequence analysis suggests that genetic burden contributes to phenotypic variability and complex neuropathy. Cell Rep. 12, 1169–1183 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Hartley, T. et al. Whole-exome sequencing is a valuable diagnostic tool for inherited peripheral neuropathies: outcomes from a cohort of 50 families. Clin. Genet. 93, 301–309 (2018).

    CAS  PubMed  Google Scholar 

  31. 31.

    Yang, Y. et al. Clinical whole-exome sequencing for the diagnosis of mendelian disorders. N. Engl. J. Med. 369, 1502–1511 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Bansagi, B. et al. Genetic heterogeneity of motor neuropathies. Neurology 88, 1226–1234 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Jo, H. Y. et al. Application of whole-exome sequencing for detecting copy number variants in CMT1A/HNPP. Clin. Genet. 90, 177–181 (2016).

    CAS  PubMed  Google Scholar 

  34. 34.

    Belkadi, A. et al. Whole-genome sequencing is more powerful than whole-exome sequencing for detecting exome variants. Proc. Natl Acad. Sci. USA 112, 5473–5478 (2015).

    CAS  PubMed  Google Scholar 

  35. 35.

    Lelieveld, S. H., Spielmann, M., Mundlos, S., Veltman, J. A. & Gilissen, C. Comparison of exome and genome sequencing technologies for the complete capture of protein-coding regions. Hum. Mutat. 36, 815–822 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Dewey, F. E. et al. Clinical interpretation and implications of whole-genome sequencing. JAMA 311, 1035–1045 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Carss, K. J. et al. Comprehensive rare variant analysis via whole-genome sequencing to determine the molecular pathology of inherited retinal disease. Am. J. Hum. Genet. 100, 75–90 (2017).

    CAS  PubMed  Google Scholar 

  38. 38.

    Wright, C. F., FitzPatrick, D. R. & Firth, H. V. Paediatric genomics: diagnosing rare disease in children. Nat. Rev. Genet. 19, 253–268 (2018).

    CAS  PubMed  Google Scholar 

  39. 39.

    Taylor, J. C. et al. Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat. Genet. 47, 717–726 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Lupski, J. R. et al. Whole-genome sequencing in a patient with Charcot-Marie-Tooth neuropathy. N. Engl. J. Med. 362, 1181–1191 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Brewer, M. H. et al. Whole genome sequencing identifies a 78kb insertion from chromosome 8 as the cause of Charcot-Marie-Tooth neuropathy CMTX3. PLOS Genet. 12, e1006177 (2016).

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    Drew, A. P., Cutrupi, A. N., Brewer, M. H., Nicholson, G. A. & Kennerson, M. L. A 1.35Mb DNA fragment is inserted into the DHMN1 locus on chromosome 7q34–q36.2. Hum. Genet. 135, 1269–1278 (2016).

    CAS  PubMed  Google Scholar 

  43. 43.

    Raymond, F. L., Horvath, R. & Chinnery, P. F. First-line genomic diagnosis of mitochondrial disorders. Nat. Rev. Genet. 19, 399–400 (2018).

    CAS  PubMed  Google Scholar 

  44. 44.

    Minoche, A. E. et al. Genome sequencing as a first-line genetic test in familial dilated cardiomyopathy. Genet. Med. 21, 650–662 (2018).

    PubMed  Google Scholar 

  45. 45.

    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).

    PubMed  PubMed Central  Google Scholar 

  46. 46.

    Turnbull, C. et al. The 100 000 Genomes Project: bringing whole genome sequencing to the NHS. BMJ 361, k1687 (2018).

    PubMed  Google Scholar 

  47. 47.

    Gonzalez, M. et al. Innovative genomic collaboration using the GENESIS (GEM.app) platform. Hum. Mutat. 36, 950–956 (2015).

    PubMed  PubMed Central  Google Scholar 

  48. 48.

    Nadeau, J. H. Modifier genes in mice and humans. Nat. Rev. Genet. 2, 165–174 (2001).

    CAS  PubMed  Google Scholar 

  49. 49.

    Barnett, I. J., Lee, S. & Lin, X. Detecting rare variant effects using extreme phenotype sampling in sequencing association studies. Genet. Epidemiol. 37, 142–151 (2013).

    PubMed  Google Scholar 

  50. 50.

    Tao, F. et al. Variation in SIPA1L2 is correlated with phenotype modification in Charcot-Marie-Tooth disease type 1A. Ann. Neurol. 85, 316–330 (2019).

    CAS  PubMed  Google Scholar 

  51. 51.

    Nam, S. H. et al. Association of miR-149 polymorphism with onset age and severity in Charcot-Marie-Tooth disease type 1A. Neuromuscul. Disord. 28, 502–507 (2018).

    PubMed  Google Scholar 

  52. 52.

    Pitceathly, R. D. et al. Genetic dysfunction of MT-ATP6 causes axonal Charcot-Marie-Tooth disease. Neurology 79, 1145–1154 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Tang, S. et al. Transition to next generation analysis of the whole mitochondrial genome: a summary of molecular defects. Hum. Mutat. 34, 882–893 (2013).

    CAS  PubMed  Google Scholar 

  54. 54.

    Picardi, E. & Pesole, G. Mitochondrial genomes gleaned from human whole-exome sequencing. Nat. Methods 9, 523–524 (2012).

    CAS  PubMed  Google Scholar 

  55. 55.

    Tomaselli, P. J. et al. Mutations in noncoding regions of GJB1 are a major cause of X-linked CMT. Neurology 88, 1445–1453 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Chen, D. H. et al. An 8-generation family with X-linked Charcot-Marie-Tooth: confirmation of the pathogenicity of a 3′ untranslated region mutation in GJB1 and its clinical features. Muscle Nerve 57, 859–862 (2018).

    CAS  PubMed  Google Scholar 

  57. 57.

    Chatterjee, S. & Pal, J. K. Role of 5’- and 3’-untranslated regions of mRNAs in human diseases. Biol. Cell 101, 251–262 (2009).

    CAS  PubMed  Google Scholar 

  58. 58.

    Corrado, L. et al. A novel synonymous mutation in the MPZ gene causing an aberrant splicing pattern and Charcot-Marie-Tooth disease type 1b. Neuromuscul. Disord. 26, 516–520 (2016).

    CAS  PubMed  Google Scholar 

  59. 59.

    Crehalet, H. et al. U1 snRNA mis-binding: a new cause of CMT1B. Neurogenetics 11, 13–19 (2010).

    CAS  PubMed  Google Scholar 

  60. 60.

    Taioli, F. et al. Dejerine-Sottas syndrome with a silent nucleotide change of myelin protein zero gene. J. Peripher. Nerv. Syst. 16, 59–64 (2011).

    CAS  PubMed  Google Scholar 

  61. 61.

    Laššuthová, P. et al. High frequency of SH3TC2 mutations in Czech HMSN I patients. Clin. Genet. 80, 334–345 (2011).

    PubMed  Google Scholar 

  62. 62.

    Cummings, B. B. et al. Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Sci. Transl Med. 9, eaal5209 (2017).

    PubMed  PubMed Central  Google Scholar 

  63. 63.

    Sapio, M. R., Goswami, S. C., Gross, J. R., Mannes, A. J. & Iadarola, M. J. Transcriptomic analyses of genes and tissues in inherited sensory neuropathies. Exp. Neurol. 283, 375–395 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64.

    GTEx Consortium. The genotype-tissue expression (gtex) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).

    PubMed  PubMed Central  Google Scholar 

  65. 65.

    Li, J. et al. Skin biopsies in myelin-related neuropathies: bringing molecular pathology to the bedside. Brain 128, 1168–1177 (2005).

    PubMed  Google Scholar 

  66. 66.

    Kitani-Morii, F. et al. Analysis of neural crest cells from Charcot-Marie-Tooth disease patients demonstrates disease-relevant molecular signature. Neuroreport 28, 814–821 (2017).

    CAS  PubMed  Google Scholar 

  67. 67.

    MacArthur, D. G. et al. Guidelines for investigating causality of sequence variants in human disease. Nature 508, 469–476 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. 68.

    Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 17, 405–424 (2015).

    PubMed  PubMed Central  Google Scholar 

  69. 69.

    Whiffin, N. et al. Using high-resolution variant frequencies to empower clinical genome interpretation. Genet. Med. 19, 1151–1158 (2017).

    PubMed  PubMed Central  Google Scholar 

  70. 70.

    Panosyan, F. B. et al. Cross-sectional analysis of a large cohort with X-linked Charcot-Marie-Tooth disease (CMTX1). Neurology 89, 927–935 (2017).

    PubMed  PubMed Central  Google Scholar 

  71. 71.

    Rossor, A. M. et al. Phenotypic and molecular insights into spinal muscular atrophy due to mutations in BICD2. Brain 138, 293–310 (2015).

    PubMed  Google Scholar 

  72. 72.

    Scoto, M. et al. Novel mutations expand the clinical spectrum of DYNC1H1-associated spinal muscular atrophy. Neurology 84, 668–679 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73.

    Houlden, H., King, R. H., Wood, N. W., Thomas, P. K. & Reilly, M. M. Mutations in the 5′ region of the myotubularin-related protein 2 (MTMR2) gene in autosomal recessive hereditary neuropathy with focally folded myelin. Brain 124, 907–915 (2001).

    CAS  PubMed  Google Scholar 

  74. 74.

    Meggouh, F. et al. Early onset neuropathy in a compound form of Charcot-Marie-Tooth disease. Ann. Neurol. 57, 589–591 (2005).

    PubMed  Google Scholar 

  75. 75.

    Anghelescu, C. et al. Targeted exomes reveal simultaneous MFN2 and GDAP1 mutations in a severe Charcot-Marie-Tooth disease type 2 phenotype. Eur. J. Neurol. 24, e15–e16 (2017).

    CAS  PubMed  Google Scholar 

  76. 76.

    Posey, J. E. et al. Resolution of disease phenotypes resulting from multilocus genomic variation. N. Engl. J. Med. 376, 21–31 (2017).

    CAS  PubMed  Google Scholar 

  77. 77.

    Hodapp, J. A. et al. Double trouble in hereditary neuropathy: concomitant mutations in the PMP-22 gene and another gene produce novel phenotypes. Arch. Neurol. 63, 112–117 (2006).

    PubMed  Google Scholar 

  78. 78.

    Schreiber, O. et al. Facioscapulohumeral muscular dystrophy and Charcot-Marie-Tooth neuropathy 1A – evidence for “double trouble” overlapping syndromes. BMC Med. Genet. 14, 92 (2013).

    PubMed  PubMed Central  Google Scholar 

  79. 79.

    Besenbacher, S. et al. Novel variation and de novo mutation rates in population-wide de novo assembled Danish trios. Nat. Commun. 6, 5969 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. 80.

    Veltman, J. A. & Brunner, H. G. De novo mutations in human genetic disease. Nat. Rev. Genet. 13, 565–575 (2012).

    CAS  PubMed  Google Scholar 

  81. 81.

    Sevilla, T. et al. Mutations in the MORC2 gene cause axonal Charcot-Marie-Tooth disease. Brain 139, 62–72 (2016).

    PubMed  Google Scholar 

  82. 82.

    Verhoeven, K. et al. MFN2 mutation distribution and genotype/phenotype correlation in Charcot-Marie-Tooth type 2. Brain 129, 2093–2102 (2006).

    PubMed  Google Scholar 

  83. 83.

    MacArthur, D. G. et al. A systematic survey of loss-of-function variants in human protein-coding genes. Science 335, 823–828 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. 84.

    Sanmaneechai, O. et al. Genotype-phenotype characteristics and baseline natural history of heritable neuropathies caused by mutations in the MPZ gene. Brain 138, 3180–3192 (2015).

    PubMed  PubMed Central  Google Scholar 

  85. 85.

    Abe, A. et al. Neurofilament light chain polypeptide gene mutations in Charcot-Marie-Tooth disease: nonsense mutation probably causes a recessive phenotype. J. Hum. Genet. 54, 94–97 (2009).

    CAS  PubMed  Google Scholar 

  86. 86.

    Yum, S. W., Zhang, J., Mo, K., Li, J. & Scherer, S. S. A novel recessive Nefl mutation causes a severe, early-onset axonal neuropathy. Ann. Neurol. 66, 759–770 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. 87.

    Mu, W., Lu, H. M., Chen, J., Li, S. & Elliott, A. M. Sanger confirmation is required to achieve optimal sensitivity and specificity in next-generation sequencing panel testing. J. Mol. Diagn. 18, 923–932 (2016).

    CAS  PubMed  Google Scholar 

  88. 88.

    Rossor, A. M. et al. Pilot phenotype and natural history study of hereditary neuropathies caused by mutations in the HSPB1 gene. Neuromuscul. Disord. 27, 50–56 (2017).

    PubMed  PubMed Central  Google Scholar 

  89. 89.

    Schon, K. et al. Mosaicism for a pathogenic MFN2 mutation causes minimal clinical features of CMT2A in the parent of a severely affected child. Neurogenetics 18, 49–55 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90.

    Lassuthova, P. et al. Mutations in ATP1A1 cause dominant Charcot-Marie-Tooth type 2. Am. J. Hum. Genet. 102, 505–514 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. 91.

    Rebelo, A. P. et al. SCO2 mutations cause early-onset axonal Charcot-Marie-Tooth disease associated with cellular copper deficiency. Brain 141, 662–672 (2018).

    PubMed  PubMed Central  Google Scholar 

  92. 92.

    Leal, A. et al. The polynucleotide kinase 3′-phosphatase gene (PNKP) is involved in Charcot-Marie-Tooth disease (CMT2B2) previously related to MED25. Neurogenetics 19, 215–225 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93.

    Kirin, M. et al. Genomic runs of homozygosity record population history and consanguinity. PLOS ONE 5, e13996 (2010).

    PubMed  PubMed Central  Google Scholar 

  94. 94.

    Ceballos, F. C., Joshi, P. K., Clark, D. W., Ramsay, M. & Wilson, J. F. Runs of homozygosity: windows into population history and trait architecture. Nat. Rev. Genet. 19, 220–234 (2018).

    CAS  Google Scholar 

  95. 95.

    Kancheva, D. et al. Novel mutations in genes causing hereditary spastic paraplegia and Charcot-Marie-Tooth neuropathy identified by an optimized protocol for homozygosity mapping based on whole-exome sequencing. Genet. Med. 18, 600–607 (2016).

    CAS  PubMed  Google Scholar 

  96. 96.

    Kukurba, K. R. & Montgomery, S. B. RNA sequencing and analysis. Cold Spring Harb. Protoc. 2015, 951–969 (2015).

    PubMed  PubMed Central  Google Scholar 

  97. 97.

    Uszczynska-Ratajczak, B., Lagarde, J., Frankish, A., Guigó, R. & Johnson, R. Towards a complete map of the human long non-coding RNA transcriptome. Nat. Rev. Genet. 19, 535–548 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  98. 98.

    Rivera, C. M. & Ren, B. Mapping human epigenomes. Cell 155, 39–55 (2013).

    CAS  Google Scholar 

  99. 99.

    Schwarze, K., Buchanan, J., Taylor, J. C. & Wordsworth, S. Are whole-exome and whole-genome sequencing approaches cost-effective? A systematic review of the literature. Genet. Med. 20, 1122–1130 (2018).

    Google Scholar 

  100. 100.

    Wetterstrand, K. A. DNA sequencing costs: data from the NHGRI Genome Sequencing Program (GSP). NHGRI https://www.genome.gov/sequencingcostsdata (2019).

  101. 101.

    Walsh, M. et al. Diagnostic and cost utility of whole exome sequencing in peripheral neuropathy. Ann. Clin. Transl Neurol. 4, 318–325 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

M.P. is funded by the NIH, the Office of Rare Diseases Research and the Inherited Neuropathy Consortium (INC; grant U54NS065712). A.M.R. is funded by a Wellcome Trust Postdoctoral Fellowship for Clinicians (grant 110043/Z/15/Z). M.M.R. is grateful to the National Institutes of Neurological Diseases and Stroke, the Office of Rare Diseases (grant U54NS065712) and the Muscular Dystrophy Association (grant MDA510281) for their support. The INC is a part of the National Center for Advancing Translational Services (NCATS) Rare Diseases Clinical Research Network (RDCRN). Work undertaken at University College London Hospitals and University College London was partly funded by the Department of Health’s National Institute for Health Research Biomedical Research Centres.

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Correspondence to Mary M. Reilly.

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Supplementary information

Glossary

Bottlenecked populations

Populations that at some point suffered a steep decline in size and subsequently recovered from a smaller pool of individuals.

Endogamy

Marriage within a community or restricted population.

Founder mutations

Mutations that occurred spontaneously in an ancestral allele at some point in the past and have been inherited by individuals in subsequent generations. In ethnically or geographically restricted populations that do not outbreed, the founder mutation will be observed at an increased frequency and might even occur only in that population.

Consanguinity

Mating of closely blood-related individuals such as first or second cousins.

Penetrance

The frequency of individuals with an expressed phenotype among carriers of a genetic mutation. If some individuals with the genetic mutation never express a phenotype, the disease is described as having incomplete or reduced penetrance.

Sanger sequencing

Also referred to as first-generation sequencing, Sanger sequencing is the standard sequencing biochemistry described by Frederick Sanger’s group in 1977 and was used to sequence the reference human genome. The technique uses fluorescently labelled DNA chain terminators in the form of dideoxynucleotide triphosphates, which are randomly incorporated into chains of sequenced DNA during the polymerase chain reaction and arrest the elongation of the DNA sequence chain. These chains of DNA are subsequently aligned according to length and the fluorescent signal is read one nucleotide at a time, thus yielding a sequence read.

Multiple ligation-dependent probe amplification

A molecular genetic technique in which multiple pairs of oligonucleotide probes are used to hybridize to specific genomic sites. Each pair of probes is designed to hybridize to immediately adjacent sites and, once this is done, each pair of probes is ligated into a single fragment that is unique in length. Successfully ligated fragments are amplified by a polymerase chain reaction, separated according to size, detected and quantitatively analysed by comparison to reference values. Genomic sites with single nucleotide polymorphisms, point mutations and copy number variants would interfere with the ligation and/or proportional amplification of fragments and, therefore, will be highlighted during the fragment detection and analysis step.

Read depths

The number of times a specific nucleotide or base pair has been sequenced and read in a single sequencing experiment or series of experiments.

Phase

The position of two variants in a set of alleles in relation to one another. If the variants are on the same allele, they are in ‘cis phase’ and if they are on opposite alleles they are in ‘trans phase’.

Variant calling

The step in next-generation sequencing data analysis during which the sequenced data are reviewed or ‘queried’ for genetic variation compared with the reference genome, and variations at the nucleotide base level or over longer DNA sequences are identified and marked (or called).

Pleiotropy

A genetic principle describing the variety of phenotypic features in affected individuals with a specific gene mutation. A genetic modifier (which is different to the causal genetic mutation) can influence which phenotypic features manifest in the affected individual.

Haploinsufficiency

A phenomenon that occurs when the functional loss of one of two alleles of a specific gene causes a reduction in the amount of gene product, usually by 50%. Depending on the gene product and its function in the cell or tissue in which it is expressed, haploinsufficiency can lead to a disease state. If no disease ensues, the cell, tissue or organism harbouring the heterozygous allele loss is said to tolerate haploinsufficiency.

Coding synonymous variants

Single nucleotide changes in the protein-coding DNA that do not alter the amino acid in the translated protein.

Sequencing trace

The colour-coded peak chart, also known as the electropherogram, that is produced as a consequence of the readout of the fluorescent signal in a Sanger sequencing reaction.

Microsatellite array

An array-based molecular genetic technique that uses specific oligonucleotide probes to genotype specific short repetitive DNA sequences (referred to as microsatellites) that are present at particular loci across the genome. The number of repeats in these microsatellites varies between individuals, so the unique combination of a set of repeat sequences can be used as a genetic tracker.

Runs of homozygosity

Contiguous genomic regions that are homozygous across all base pairs in an individual. This phenomenon occurs when the transmitted maternal and paternal alleles are identical and would have been inherited from a common ancestor at some point in the past.

Uniparental disomy

A phenomenon that occurs when offspring inherit two copies of a chromosome or part of a chromosome from one parent and no copies from the other parent. Uniparental disomy usually occurs as a random event during the stage of meiosis in gametogenesis.

Microarray comparative genomic hybridization

An array-based molecular genetic technique that compares the genome of interest to the reference genome for duplications or deletions of genetic material, also known as copy number variants (CNVs). This technique can detect CNVs as small as 50 kb.

Secondary findings

Genetic variants which may be of significance, that are identified in a patient but are unrelated to the primary diagnostic question or the reason for which the sequencing data were generated. They may be discovered additionally (if there was intentional opportunistic screening, e.g. for variants in cancer genes) or incidentally (if they were not sought).

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Pipis, M., Rossor, A.M., Laura, M. et al. Next-generation sequencing in Charcot–Marie–Tooth disease: opportunities and challenges. Nat Rev Neurol 15, 644–656 (2019). https://doi.org/10.1038/s41582-019-0254-5

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