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The Impact of Next-Generation Sequencing on the Diagnosis, Treatment, and Prevention of Hereditary Neuromuscular Disorders

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Abstract

The impact of high-throughput sequencing in genetic neuromuscular disorders cannot be overstated. The ability to rapidly and affordably sequence multiple genes simultaneously has enabled a second golden age of Mendelian disease gene discovery, with flow-on impacts for rapid genetic diagnosis, evidence-based treatment, tailored therapy development, carrier-screening, and prevention of disease recurrence in families. However, there are likely many more neuromuscular disease genes and mechanisms to be discovered. Many patients and families remain without a molecular diagnosis following targeted panel sequencing, clinical exome sequencing, or even genome sequencing. Here we review how massively parallel, or next-generation, sequencing has changed the field of genetic neuromuscular disorders, and anticipate future benefits of recent technological innovations such as RNA-seq implementation and detection of tandem repeat expansions from short-read sequencing.

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References

  1. Ozsarlak O, Schepens E, Parizel PM, Van Goethem JW, Vanhoenacker F, De Schepper AM, et al. Hereditary neuromuscular diseases. Eur J Radiol [Internet]. 2001;40:184–97 [cited 2016 Sep 26]. https://www.ncbi.nlm.nih.gov/pubmed/11731207.

  2. Laing NG. Genetics of neuromuscular disorders. Crit Rev Clin Lab Sci [Internet]. Taylor & Francis; 2012;49:33–48 [cited 2017 Jan 10]. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84859251280&doi=10.3109%2F10408363.2012.658906&partnerID=40&md5=6c6fd4503fc4fd70f1b7d1fedfbda51d.

  3. Beecroft SJ, Lombard M, Mowat D, McLean C, Cairns A, Davis M, et al. Genetics of neuromuscular fetal akinesia in the genomics era. J Med Genet [Internet]. 2018;55:505–14. https://doi.org/10.1136/jmedgenet-2018-105266.

    Article  CAS  PubMed  Google Scholar 

  4. Dharmadasa T, Henderson RD, Talman PS, Macdonell RA, Mathers S, Schultz DW, et al. Motor neurone disease: progress and challenges. Med J Aust. 2017;206:357–62.

    PubMed  Google Scholar 

  5. Szmulewicz DJ, Waterston JA, MacDougall HG, Mossman S, Chancellor AM, McLean CA, et al. Cerebellar ataxia, neuropathy, vestibular areflexia syndrome (CANVAS): a review of the clinical features and video-oculographic diagnosis. Ann N Y Acad Sci [Internet]. 2011;1233:139–47. https://doi.org/10.1111/j.1749-6632.2011.06158.x(cited 2016 Sep 26).

    Article  PubMed  Google Scholar 

  6. Martinez-Carrera LA, Wirth B. Dominant spinal muscular atrophy is caused by mutations in BICD2, an important golgin protein [Internet]. Front. Neurosci. Frontiers Media SA; 2015. p. 401 [cited 2016 Dec 13]. https://www.ncbi.nlm.nih.gov/pubmed/26594138.

  7. Biancalana V, Laporte J. Diagnostic use of massively parallel sequencing in neuromuscular diseases: towards an integrated diagnosis. J Neuromuscul Dis [Internet]. 2015;2:193–203. https://doi.org/10.3233/JND-150092(cited 2016 Sep 23).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Gonorazky H, Liang M, Cummings B, Lek M, Micallef J, Hawkins C, et al. RNAseq analysis for the diagnosis of muscular dystrophy. Ann Clin Transl Neurol [Internet]. 2016;3:55–60. https://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4704476&tool=pmcentrez&rendertype=abstract.

  9. Chong JX, Buckingham KJ, Jhangiani SN, Boehm C, Sobreira N, Smith JD, et al. The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities. Am J Hum Genet [Internet]. 2015;97:199–215. https://www.sciencedirect.com/science/article/pii/S0002929715002451.

  10. Access Economics (Firm) and Muscular Dystrophy Association. The cost of Muscular Dystrophy. Canberra: Access Economics; 2007.

  11. Angelis A, Tordrup D, Kanavos P. Socio-economic burden of rare diseases: a systematic review of cost of illness evidence. Health Policy (New York) [Internet]. 2015;119:964–79. https://doi.org/10.1016/j.healthpol.2014.12.016.

    Article  Google Scholar 

  12. Haskell GT, Adams MC, Fan Z, Amin K, Guzman Badillo RJ, Zhou L, et al. Diagnostic utility of exome sequencing in the evaluation of neuromuscular disorders. Neurol Genet [Internet]. 2018;4:e212. https://doi.org/10.1212/NXG.0000000000000212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Rare Diseases Europe E. Survey of the delay in diagnosis for 8 rare diseases in Europe (EurordisCare2) [Internet]. Eurodis fact sheet. 2007. https://www.eurordis.org/IMG/pdf/Fact_Sheet_Eurordiscare2.pdf.

  14. Aartsma-Rus A, Ginjaar IB, Bushby K. The importance of genetic diagnosis for Duchenne muscular dystrophy. J Med Genet [Internet]. 2016;53:145–51. https://doi.org/10.1136/jmedgenet-2015-103387.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Tian X, Liang WC, Feng Y, Wang J, Zhang VW, Chou CH, et al. Expanding genotype/phenotype of neuromuscular diseases by comprehensive target capture/NGS. Neurol Genet. 2015;1–14.

  16. Posey JE, O’Donnell-Luria AH, Chong JX, Harel T, Jhangiani SN, Coban Akdemir ZH, et al. Insights into genetics, human biology and disease gleaned from family based genomic studies. Genet Med [Internet]. 2019;21:798–812. https://doi.org/10.1038/s41436-018-0408-7.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature. 2005;437:376–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Mardis ER, Next-Generation DNA. Sequencing methods. Annu Rev Genom Hum Genet. 2008;9:387–402.

    CAS  Google Scholar 

  19. Shendure J, Findlay GM, Snyder MW. Genomic medicine—progress, pitfalls, and promise. Cell [Internet]. 2019;177:45–57. https://doi.org/10.1016/j.cell.2019.02.003.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. McCarthy MI, MacArthur DG. Human disease genomics: from variants to biology. Genome Biol Genome Biol. 2017;18:18–20.

    Google Scholar 

  21. Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, et al. Targeted capture and massively parallel sequencing of 12 human exomes. Nature. 2009;461:272–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Choi M, Scholl UI, Ji W, Liu T, Tikhonova IR, Zumbo P, et al. Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc Natl Acad Sci USA [Internet]. 2009/10/27. National Academy of Sciences; 2009;106:19096–101. https://www.ncbi.nlm.nih.gov/pubmed/19861545.

  23. Hoischen A, van Bon BWM, Gilissen C, Arts P, van Lier B, Steehouwer M, et al. De novo mutations of SETBP1 cause Schinzel-Giedion syndrome. Nat Genet [Internet]. 2010;42:483–5. https://www.nature.com/articles/ng.581.

  24. Eldomery MK, Coban-Akdemir Z, Harel T, Rosenfeld JA, Gambin T, Stray-Pedersen A, et al. Lessons learned from additional research analyses of unsolved clinical exome cases. Genome Med Genome Med. 2017;9:1–15.

    Google Scholar 

  25. Beecroft SJ, Yau KS, Allcock RJN, Mina K, Gooding R, Faiz F, et al. Targeted gene panel use in 2249 neuromuscular patients: the Australasian referral center experience. Ann Clin Transl Neurol [Internet]. 2020;7:353–62. https://doi.org/10.1002/acn3.51002.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Ravenscroft G, Davis MR, Lamont P, Forrest A, Laing NG. New era in genetics of early onset muscle disease: Breakthroughs and challenges. Semin Cell Dev Biol [Internet]. Elsevier Ltd; 2016. https://www.ncbi.nlm.nih.gov/pubmed/27519468

  27. Klein C, Chuang R, Marras C, Lang AE. The curious case of phenocopies in families with genetic Parkinson’s disease. Mov Disord United States. 2011;26:1793–802.

    Google Scholar 

  28. Posey JE. Genome sequencing and implications for rare disorders. Orphanet J Rare Dis. 2019;14:1–10.

    Google Scholar 

  29. Sobreira NL, Valle D. Lessons learned from the search for genes responsible for rare Mendelian disorders. Mol Genet Genomic Med. 2016;4:371–5.

    PubMed  PubMed Central  Google Scholar 

  30. Lek M, Macarthur D. The challenge of next generation sequencing in the context of neuromuscular diseases. J Neuromuscul Dis. 2014;1:135–49.

    PubMed  Google Scholar 

  31. Boycott KM, Hartley T, Biesecker LG, Gibbs RA, Innes AM, Riess O, et al. A diagnosis for all rare genetic diseases: the horizon and the next frontiers. Cell [Internet]. 2019;177:32–7. https://doi.org/10.1016/j.cell.2019.02.040.

    Article  CAS  PubMed  Google Scholar 

  32. Alfares A, Aloraini T, Subaie LA, Alissa A, Qudsi AA, Alahmad A, et al. Whole-genome sequencing offers additional but limited clinical utility compared with reanalysis of whole-exome sequencing. Genet Med. 2018;20:1328–33.

    CAS  PubMed  Google Scholar 

  33. Karakaya M, Storbeck M, Strathmann EA, Delle Vedove A, Hölker I, Altmueller J, et al. Targeted sequencing with expanded gene profile enables high diagnostic yield in non-5q-spinal muscular atrophies. Hum Mutat [Internet]. 2018;39:1284–98. https://doi.org/10.1002/humu.23560.

    Article  CAS  PubMed  Google Scholar 

  34. Savarese M, Torella A, Musumeci O, Angelini C, Astrea G, Bello L, et al. Targeted gene panel screening is an effective tool to identify undiagnosed late onset Pompe disease. Neuromuscul Disord [Internet]. England: Elsevier B.V.; 2018;28:586–91. https://linkinghub.elsevier.com/retrieve/pii/S096089661731489X.

  35. O’Grady GL, Lek M, Lamande SR, Waddell L, Oates EC, Punetha J, et al. Diagnosis and etiology of congenital muscular dystrophy: we are halfway there. Ann Neurol [Internet]. 2016;80:101–11. https://doi.org/10.1002/ana.24687.

    Article  CAS  PubMed  Google Scholar 

  36. Ghaoui R, Cooper ST, Lek M, Jones K, Corbett A, Reddel S, et al. Use of whole-exome sequencing for diagnosis of limb-girdle muscular dystrophy: outcomes and lessons learned. JAMA Neurol [Internet]. 2015;72:1424–32. https://doi.org/10.1001/jamaneurol.2015.2274.

    Article  PubMed  Google Scholar 

  37. Gilissen C, Hoischen A, Brunner HG, Veltman JA. Disease gene identification strategies for exome sequencing. Eur J Hum Genet [Internet]. Nature Publishing Group; 2012;20:490–7. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3330229/.

  38. Cooper DN, Chen JM, Ball EV, Howells K, Mort M, Phillips AD, et al. Genes, mutations, and human inherited disease at the dawn of the age of personalized genomics. Hum Mutat. 2010;31:631–55.

    CAS  PubMed  Google Scholar 

  39. Marchuk DS, Crooks K, Strande N, Kaiser-Rogers K, Milko LV, Brandt A, et al. Increasing the diagnostic yield of exome sequencing by copy number variant analysis. PLoS ONE. 2018;13:1–14.

    Google Scholar 

  40. Fernandez-Marmiesse A, Gouveia S, Couce ML. NGS Technologies as a Turning Point in Rare Disease Research , Diagnosis and Treatment. Curr Med Chem [Internet]. 2018;25:404–32. https://www.eurekaselect.com/154264/article.

  41. Antoniadi T, Buxton C, Dennis G, Forrester N, Smith D, Lunt P, 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 [Internet]. 2015;16:84. https://doi.org/10.1186/s12881-015-0224-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Hu X, Li N, Xu Y, Li G, Yu T, Yao R, et al. Proband-only medical exome sequencing as a cost-effective first-tier genetic diagnostic test for patients without prior molecular tests and clinical diagnosis in a developing country: the China experience. Genet Med. 2018;20:1045–53.

    CAS  PubMed  Google Scholar 

  43. Abdulwahab F, Abouelhoda M, Abouthuraya R, Abumansour I, Ahmed SO, Al Rubeaan K, et al. Comprehensive gene panels provide advantages over clinical exome sequencing for Mendelian diseases. Genome Biol [Internet]. 2015;16:226. https://genomebiology.com/2015/16/1/226.

  44. Montaut S, Tranchant C, Drouot N, Rudolf G, Guissart C, Tarabeux J, et al. Assessment of a targeted gene panel for identification of genes associated with movement disorders. JAMA Neurol [Internet]. 2018;75:1234–45. http://archneur.jamanetwork.com/article.aspx?10.1001/jamaneurol.2018.1478.

  45. Stark Z, Schofield D, Martyn M, Rynehart L, Shrestha R, Alam K, et al. Does genomic sequencing early in the diagnostic trajectory make a difference? A follow-up study of clinical outcomes and cost-effectiveness. Genet Med [Internet]. 2019;21:173–80. https://www.nature.com/articles/s41436-018-0006-8

  46. Schofield D, Alam K, Douglas L, Shrestha R, MacArthur DG, Davis M, et al. Cost-effectiveness of massively parallel sequencing for diagnosis of paediatric muscle diseases. npj Genomic Med [Internet]. [London]: Nature Publishing Group, published in partnership with Center of Excellence in Genomic Medicine Research; 2017;2:4. https://www.nature.com/articles/s41525-017-0006-7.

  47. Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, 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 [Internet]. American College of Medical Genetics and Genomics; 2015 [cited 2017 Mar 7];17:405–24. https://www.nature.com/gim/journal/v17/n5/pdf/gim201530a.pdf.

  48. Stals KL, Wakeling M, Baptista JJ, Caswell R, Parrish A, Rankin J, et al. Diagnosis of lethal or prenatal-onset autosomal recessive disorders by parental exome sequencing. Prenat Diagn [Internet]. 2017. https://doi.org/10.1002/pd.5175.

    Article  Google Scholar 

  49. Reid ES, Papandreou A, Drury S, Boustred C, Yue WW, Wedatilake Y, et al. Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes. Brain. 2016;139:2844–54.

    PubMed  PubMed Central  Google Scholar 

  50. Starita LM, Ahituv N, Dunham MJ, Kitzman JO, Roth FP, Seelig G, et al. Variant interpretation: functional assays to the rescue. Am J Hum Genet [Internet]. 2017;101:315–25. https://doi.org/10.1016/j.ajhg.2017.07.014.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. den Dunnen J. I.10Gene variant databases: driving research, diagnosis, treatment and interaction. Neuromuscul Disord. 2019;29:S121. https://doi.org/10.1016/j.nmd.2019.06.303

    Article  Google Scholar 

  52. Wenger AM, Guturu H, Bernstein JA, Bejerano G. Systematic reanalysis of clinical exome data yields additional diagnoses: implications for providers. Genet Med. 2017;19:209–14.

    PubMed  Google Scholar 

  53. Acuna-Hidalgo R, Bo T, Kwint MP, van de Vorst M, Pinelli M, Veltman JA, et al. Post-zygotic point mutations are an underrecognized source of de novo genomic variation. Am J Hum Genet [Internet]. 2015/06/06. Elsevier; 2015;97:67–74. https://www.ncbi.nlm.nih.gov/pubmed/26054435.

  54. Papenhausen P, Schwartz S, Risheg H, Keitges E, Gadi I, Burnside RD, et al. UPD detection using homozygosity profiling with a SNP genotyping microarray. Am J Med Genet A USA. 2011;155A:757–68.

    Google Scholar 

  55. Eggermann T, Mackay D, Tümer Z. Uniparental disomy and imprinting disorders. OBM Genet. 2018;2:1.

    Google Scholar 

  56. King DA, Fitzgerald TW, Miller R, Canham N, Clayton-Smith J, Johnson D, et al. A novel method for detecting uniparental disomy from trio genotypes identifies a significant excess in children with developmental disorders. Genome Res USA. 2014;24:673–87.

    CAS  Google Scholar 

  57. Bis DM, Schüle R, Reichbauer J, Synofzik M, Rattay TW, Soehn A, et al. Uniparental disomy determined by whole-exome sequencing in a spectrum of rare motoneuron diseases and ataxias. Mol Genet Genom Med. 2017;5:280–6.

    CAS  Google Scholar 

  58. Papadimitriou S, Gazzo A, Versbraegen N, Nachtegael C, Aerts J, Moreau Y, et al. Predicting disease-causing variant combinations. Proc Natl Acad Sci USA. 2019;116:11878–87.

    CAS  PubMed  Google Scholar 

  59. Posey JE, Harel T, Liu P, Rosenfeld JA, James RA, Coban Akdemir ZH, et al. Resolution of disease phenotypes resulting from multilocus genomic variation. N Engl J Med. 2017;376:21–31.

    CAS  PubMed  Google Scholar 

  60. Suter CM, Martin DIK. Inherited epimutation or a haplotypic basis for the propensity to silence? Nat Genet USA. 2007;39:573.

    CAS  Google Scholar 

  61. Martin DIK, Ward R, Suter CM. Germline epimutation: a basis for epigenetic disease in humans. Ann N Y Acad Sci USA. 2005;1054:68–77.

    Google Scholar 

  62. Aref-Eshghi E, Kerkhof J, Pedro VP, Barat-Houari M, Ruiz-Pallares N, Andrau J-C, et al. Evaluation of DNA Methylation Episignatures forDiagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders. Am J Hum Genet [Internet]. 2020;106:356–70.

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Ravenscroft G, Sollis E, Charles AK, North KN, Baynam G, Laing NG. Fetal akinesia: review of the genetics of the neuromuscular causes. J Med Genet [Internet]. 2011;48:793–801[cited 2016 Dec 18]. https://www.ncbi.nlm.nih.gov/pubmed/21984750.

  64. Beaulieu CL, Majewski J, Schwartzentruber J, Samuels ME, Fernandez BA, Bernier FP, et al. FORGE Canada consortium: Outcomes of a 2-year national rare-disease gene-discovery project. Am J Hum Genet. 2014;94:809–17.

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Ravenscroft G, Laing NG, Bönnemann CG. Pathophysiological concepts in the congenital myopathies: blurring the boundaries, sharpening the focus. Brain [Internet]. 2015;138:246–68. https://www.brain.oxfordjournals.org/content/brain/early/2014/12/31/brain.awu368.full.pdf.

  66. Oates EC, Jones KJ, Donkervoort S, Charlton A, Brammah S, Smith JE, et al. Congenital titinopathy: comprehensive characterization and pathogenic insights. Ann Neurol [Internet]. 2018;83:1105–24. https://doi.org/10.1002/ana.25241.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Hackman P, Udd B, Bonnemann CG, Ferreiro A. 219th ENMC International Workshop Titinopathies International database of titin mutations and phenotypes, Heemskerk, The Netherlands, 29 April-1 May 2016. Neuromuscul Disord Engl. 2017;27:396–407.

    Google Scholar 

  68. Jungbluth H, Dowling JJ, Ferreiro A, Muntoni F, Bönnemann C, Dirksen R, et al. 217th ENMC International Workshop: RYR1-related myopathies, Naarden, The Netherlands, 29–31 January 2016. Neuromuscul Disord [Internet]. 2016;26:624–33.

  69. Philippakis AA, Azzariti DR, Beltran S, Brookes AJ, Brownstein CA, Brudno M, et al. The matchmaker exchange: a platform for rare disease gene discovery. Hum Mutat [Internet]. 2015;36:915–21. https://doi.org/10.1002/humu.22858(cited 2016 Sep 26).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Lochmüller H, TorrentFarnell J, Le Cam Y, Jonker AH, Lau LP, Baynam G, et al. The International Rare Diseases Research Consortium: policies and guidelines to maximize impact. Eur J Hum Genet [Internet]. 2017;25:1293–302. https://doi.org/10.1038/s41431-017-0008-z.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, et al. Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of-function intolerance across human protein-coding genes. bioRxiv [Interenet]. 2019. https://doi.org/10.1101/531210v2.

    Article  Google Scholar 

  72. Lek M, Karczewski KJ, Samocha KE, Banks E, Fennell T, O’Donnell-Luria AH, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature [Internet]. 2016;536:285–92. https://doi.org/10.1038/nature19057(cited 2016 Dec 14).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Scott EM, Halees A, Itan Y, Spencer EG, He Y, Azab MA, et al. Characterization of greater middle Eastern genetic variation for enhanced disease gene discovery. Nat Genet [Internet]. 2016;48:1071–6. https://www.ncbi.nlm.nih.gov/pubmed/27428751%5Cn. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5019950/pdf/nihms788970.pdf

  74. Walsh R, Thomson KL, Ware JS, Funke BH, Woodley J, McGuire KJ, et al. Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples. Genet Med [Internet]. United States; 2017;19:192–203. https://biorxiv.org/content/early/2016/02/24/041111.abstract.

  75. Monies D, Abouelhoda M, AlSayed M, Alhassnan Z, Alotaibi M, Kayyali H, et al. The landscape of genetic diseases in Saudi Arabia based on the first 1000 diagnostic panels and exomes. Hum Genet. 2017;136:921–39.

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Monies D, Abouelhoda M, Assoum M, Moghrabi N, Rafiullah R, Almontashiri N, et al. Lessons learned from large-scale, first-tier clinical exome sequencing in a highly consanguineous population. Am J Hum Genet [Internet]. ElsevierCompany; 2019;1–20. https://linkinghub.elsevier.com/retrieve/pii/S0002929719301594.

  77. Saleheen D, Natarajan P, Armean IM, Zhao W, Rasheed A, Khetarpal SA, et al. Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity. Nature [Internet]. 2017;544:235–9. https://doi.org/10.1038/nature22034.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Bentley AR, Callier S, Rotimi CN. Diversity and inclusion in genomic research: why the uneven progress? J Community Genet [Internet]. 2017;8:255–66. https://doi.org/10.1007/s12687-017-0316-6.

    Article  PubMed  PubMed Central  Google Scholar 

  79. Chaudhary R, Garg J, Shah N, Sumner A. PCSK9 inhibitors: a new era of lipid lowering therapy. World J Cardiol. 2017;9:76.

    PubMed  PubMed Central  Google Scholar 

  80. Delatycki MB, Alkuraya F, Archibald A, Castellani C, Cornel M, Grody WW, et al. International perspectives on the implementation of reproductive carrier screening. Prenat Diagn. 2019.

  81. Delatycki MB, Laing N, Kirk E. Expanded reproductive carrier screening—how can we do the most good and cause the least harm? Eur J Hum Genet [Internet]. 2019;27:669–70. https://doi.org/10.1038/s41431-019-0356-y.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Langlois S, Benn P, Wilkins-Haug L. Current controversies in prenatal diagnosis 4: pre-conception expanded carrier screening should replace all current prenatal screening for specific single gene disorders. Prenat Diagn. 2015;35:23–8.

    PubMed  Google Scholar 

  83. American College of Obstetricians and Gynecologists (ACOG). Carrier screening for genetic conditions. Committee Opinion No. 691. Obstet Gynecol [Internet]. 2017;129:1–15. 10.1542/neo.5-7-e290%0A. http://www.ncbi.nlm.nih.gov/pubmed/28225426.

  84. Stark Z, Tan TY, Chong B, Brett GR, Yap P, Walsh M, et al. A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. Genet Med [Internet]. 2016;18:1090–6. https://www.nature.com/articles/gim20161.

  85. Hooker GW, Ormond KE, Sweet K, Biesecker BB. Teaching genomic counseling: preparing the genetic counseling workforce for the genomic era. J Genet Couns. 2014;23:445–51.

    PubMed  PubMed Central  Google Scholar 

  86. Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013;15:565–74.

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Grove ME, Wolpert MN, Cho MK, Lee SSJ, Ormond KE. Views of genetics health professionals on the return of genomic results. J Genet Couns. 2014;23:531–8.

    PubMed  Google Scholar 

  88. Mills R, Haga SB. Genomic counseling: next generation counseling. J Genet Couns. 2014;23:689–92.

    PubMed  Google Scholar 

  89. Krabbenborg L, Vissers LELM, Schieving J, Kleefstra T, Kamsteeg EJ, Veltman JA, et al. Understanding the psychosocial effects of WES test results on parents of children with rare diseases. J Genet Couns. 2016;25:1207–14.

    PubMed  PubMed Central  Google Scholar 

  90. Han PKJ, Klein WMP, Arora NK. Varieties of uncertainty in health care: a conceptual taxonomy. Med Decis Mak. 2011;31:828–38.

    Google Scholar 

  91. Finsterer J, Stöllberger C, Brandau O, Laccone F, Bichler K, Laing NG. Novel MYH7 mutation associated with mild myopathy but life-threatening ventricular arrhythmias and noncompaction. Int J Cardiol [Internet]. 2014;173:532–5. https://doi.org/10.1016/j.ijcard.2014.03.025.

    Article  PubMed  Google Scholar 

  92. Farnaes L, Hildreth A, Sweeney NM, Clark MM, Chowdhury S, Nahas S, et al. Rapid whole-genome sequencing decreases infant morbidity and cost of hospitalization. npj Genom Med [Internet]. 2018. https://doi.org/10.1038/s41525-018-0049-4.

    Article  Google Scholar 

  93. Stark Z, Marum JE, Elliott J, Riseley JR, Jarmolowicz A, Prawer Y, et al. Meeting the challenges of implementing rapid genomic testing in acute pediatric care. Genet Med. 2018;20:1554–633.

    PubMed  Google Scholar 

  94. Kang PB, Morrison L, Iannaccone ST, Graham RJ, Bonnemann CG, Rutkowski A, et al. Evidence-based guideline summary: Evaluation, diagnosis, and management of congenital muscular dystrophy: report of the guideline development subcommittee of the American Academy of Neurology and the Practice Issues Review Panel of the American Association. Neurology. 2015;84:1369–78.

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Wurster CD, Ludolph AC. Nusinersen for spinal muscular atrophy. Ther Adv Neurol Disord [Internet]. 2018;11:175628561875445. https://doi.org/10.1177/1756285618754459.

    Article  Google Scholar 

  96. Laing NG, Davis MR, Bayley K, Fletcher S, Wilton SD. Molecular diagnosis of Duchenne muscular dystrophy: Past, present and future in relation to implementing therapies [Internet]. Clin. Biochem. Rev. The Australian Association of Clinical Biochemists; 2011. p. 129–34 [cited 2016 Sep 26]. https://www.ncbi.nlm.nih.gov/pubmed/21912442.

  97. Long C, Li H, Tiburcy M, Rodriguez-Caycedo C, Kyrychenko V, Zhou H, et al. Correction of diverse muscular dystrophy mutations in human engineered heart muscle by single-site genome editing. Sci Adv [Internet]. 2018;4:eaap9004. https://advances.sciencemag.org/content/4/1/eaap9004.abstract.

  98. Rabai A, Reisser L, Reina-San-Martin B, Mamchaoui K, Cowling BS, Nicot AS, et al. Allele-specific CRISPR/Cas9 correction of a heterozygous DNM2 mutation rescues centronuclear myopathy cell phenotypes. Mol Ther Nucleic Acids [Internet]. 2019;16:246–56. https://doi.org/10.1016/j.omtn.2019.02.019.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Bolduc V, Foley AR, Solomon-Degefa H, Sarathy A, Donkervoort S, Hu Y, et al. A recurrent COL6A1 pseudoexon insertion causes muscular dystrophy and is effectively targeted by splice-correction therapies. JCI Insight. 2019;4:1–19.

    Google Scholar 

  100. Gina Kolata. Drug designed for one raises many questions. New York Times [Internet]. New York; 2019;3. https://www.nytimes.com/2019/10/09/health/mila-makovec-drug.html.

  101. Kim J, Hu C, Moufawad El Achkar C, Black LE, Douville J, Larson A, et al. Patient-customized oligonucleotide therapy for a rare genetic disease. N Engl J Med [Internet]. 2019;381:1644–52. https://doi.org/10.1056/NEJMoa1813279.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Regier AA, Farjoun Y, Larson DE, Krasheninina O, Kang HM, Howrigan DP, et al. Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects. Nat Commun [Internet]. 2018;9:1–8. https://doi.org/10.1038/s41467-018-06159-4.

    Article  CAS  Google Scholar 

  103. Gymrek M. A genomic view of short tandem repeats. Curr Opin Genet Dev [Internet]. 2017;44:9–16. https://doi.org/10.1016/j.gde.2017.01.012.

    Article  CAS  PubMed  Google Scholar 

  104. Ravenscroft G, Bryson-Richardson RJ, Nowak KJ, Laing NG. Recent advances in understanding congenital myopathies. F1000 Research [Internet]. 2018;7:1921. https://doi.org/10.12688/f1000research.16422.1.

    Article  CAS  Google Scholar 

  105. Sagath L, Lehtokari V-L, Välipakka S, Udd B, Wallgren-Pettersson C, Pelin K, et al. An extended targeted copy number variation detection array including 187 genes for the diagnostics of neuromuscular disorders. J Neuromuscul Dis [Internet]. 2018;5:307–14. https://doi.org/10.3233/JND-170298.

    Article  PubMed  PubMed Central  Google Scholar 

  106. White J, Mazzeu JF, Hoischen A, Jhangiani SN, Gambin T, Alcino MC, et al. DVL1 frameshift mutations clustering in the penultimate exon cause autosomal-dominant robinow syndrome. Am J Hum Genet. 2015;96:612–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  107. Wang Z, Liu X, Yang BZ, Gelernter J. The role and challenges of exome sequencing in studies of human diseases. Front Genet. 2013;4:1–8.

    Google Scholar 

  108. Fromer M, Moran JL, Chambert K, Banks E, Bergen SE, Ruderfer DM, et al. Discovery and statistical genotyping of copy-number variation from whole-exome sequencing depth. Am J Hum Genet [Internet]. 2012;91:597–607. https://doi.org/10.1016/j.ajhg.2012.08.005.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Gambin T, Akdemir ZC, Yuan B, Gu S, Chiang T, Carvalho CMB, et al. Homozygous and hemizygous CNV detection from exome sequencing data in a Mendelian disease cohort. Nucleic Acids Res. 2017;45:1633–48.

    CAS  PubMed  Google Scholar 

  110. de Ligt J, Boone PM, Pfundt R, Vissers LELM, Richmond T, Geoghegan J, et al. Detection of clinically relevant copy number variants with whole-exome sequencing. Hum Mutat. 2013;34:1439–48.

    PubMed  Google Scholar 

  111. Salmon LB, Orenstein N, Markus-Bustani K, Ruhrman-Shahar N, Kilim Y, Magal N, et al. Improved diagnostics by exome sequencing following raw data reevaluation by clinical geneticists involved in the medical care of the individuals tested. Genet Med [Internet]. 2019;21:1443–511. https://doi.org/10.1038/s41436-018-0343-7.

    Article  Google Scholar 

  112. Cortese A, Simone R, Sullivan R, Vandrovcova J, Tariq H, Yan YW, et al. Biallelic expansion of an intronic repeat in RFC1 is a common cause of late-onset ataxia. Nat Genet [Internet]. Springer US; 2019;51:649–58. https://www.nature.com/articles/s41588-019-0372-4.

  113. Rafehi H, Szmulewicz DJ, Bennett MF, Sobreira NL, Pope K, Smith KR, et al. Bioinformatics-based identification of expanded repeats: a non-reference intronic pentamer expansion in RFC1 causes CANVAS. Am J Hum Genet. 2019;105:151–65.

    CAS  PubMed  PubMed Central  Google Scholar 

  114. Van Daele SH, Vermeer S, Van Eesbeeck A, Lannoo L, Race V, van Damme P, et al. Diagnostic yield of testing for RFC1 repeat expansions in patients with unexplained adult-onset cerebellar ataxia. J Neurol Neurosurg Psychiatry [Internet]. 2020;jnnp-2020-323998. Available from: http://jnnp.bmj.com/content/early/2020/07/30/jnnp-2020-323998.abstract

  115. Cortese A, Tozza S, Yau WY, Rossi S, Beecroft SJ, Jaunmuktane Z, et al. Cerebellar ataxia, neuropathy, vestibular areflexia syndrome due to RFC1 repeat expansion. Brain [Internet]. 2020;143:480–90. https://academic.oup.com/brain/article/143/2/480/5733001.

  116. Ruggieri A, Naumenko S, Smith MA, Iannibelli E, Blasevich F, Bragato C, et al. Multiomic elucidation of a coding 99-mer repeat-expansion skeletal muscle disease. Acta Neuropathol [Internet]. 2020;140:231–5. https://doi.org/10.1007/s00401-020-02164-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Ishiura H, Shibata S, Yoshimura J, Suzuki Y, Qu W, Doi K, et al. Noncoding CGG repeat expansions in neuronal intranuclear inclusion disease, oculopharyngodistal myopathy and an overlapping disease. Nat Genet [Internet]. 2019;51:1222–32. https://doi.org/10.1038/s41588-019-0458-z.

    Article  CAS  PubMed  Google Scholar 

  118. Cortese A, Zhu Y, Rebelo AP, Negri S, Courel S, Abreu L, et al. Biallelic mutations in SORD cause a common and potentially treatable hereditaryneuropathy with implications for diabetes. Nat Genet [Internet]. 2020;52:473–81.

    CAS  PubMed  Google Scholar 

  119. Schadt EE, Turner S, Kasarskis A. A window into third-generation sequencing. Hum Mol Genet. 2010;19:227–40.

    Google Scholar 

  120. Jain M, Olsen HE, Paten B, Akeson M. The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biol [Internet]. 2016;17:239. https://doi.org/10.1186/s13059-016-1103-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Marks P, Garcia S, Barrio AM, Belhocine K, Bernate J, Bharadwaj R, et al. Resolving the full spectrum of human genome variation using Linked-Reads. Genome Res. 2019;29:635–45.

    CAS  PubMed  PubMed Central  Google Scholar 

  122. Pollard MO, Gurdasani D, Mentzer AJ, Porter T, Sandhu MS. Long reads: their purpose and place. Hum Mol Genet [Internet]. 2018;27:R234–41. https://academic.oup.com/hmg/article/27/R2/R234/4996216.

  123. Bamshad MJ, Nickerson DA, Chong JX. Mendelian gene discovery: fast and furious with no end in sight [Internet]. Am J Hum Genet. 2019. https://doi.org/10.1016/j.ajhg.2019.07.011.

    Article  PubMed  PubMed Central  Google Scholar 

  124. Foley AR, Zou Y, Dunford JE, Rooney J, Chandra G, Xiong H, et al. GGPS1 mutations cause muscular dystrophy/hearing loss/ovarian insufficiency syndrome. Ann Neurol [Internet]. 2020;. https://doi.org/10.1002/ana.25772.

    Article  PubMed  PubMed Central  Google Scholar 

  125. Quang D, Chen Y, Xie X. DANN: A deep learning approach for annotating the pathogenicity of genetic variants. Bioinformatics. 2015;31:761–3.

    CAS  PubMed  Google Scholar 

  126. Lappalainen T, Scott AJ, Brandt M, Hall IM. Genomic analysis in the age of human genome sequencing. Cell [Internet]. 2019;177:70–84. https://doi.org/10.1016/j.cell.2019.02.032.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Foley KE. Model network: Canadian program aims to generate models for rare disease. Nat Med [Internet]. 2015;21:1242–3. https://doi.org/10.1038/nm1115-1242.

    Article  CAS  PubMed  Google Scholar 

  128. Starita LM, Young DL, Islam M, Kitzman JO, Gullingsrud J, Hause RJ, et al. Massively parallel functional analysis of BRCA1 RING domain variants. Genetics. 2015;200:413–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  129. Majithia AR, Tsuda B, Agostini M, Gnanapradeepan K, Rice R, Peloso G, et al. Prospective functional classification of all possible missense variants in PPARG. Nat Genet. 2016;48:1570–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  130. Cummings BB, Marshall JL, Tukiainen T, Lek M, Donkervoort S, Foley R, et al. Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Sci Transl Med [Internet]. Washington, DC : American Association for the Advancement of Science 2017;9:1–11.

  131. Spielmann M, Mundlos S. Looking beyond the genes: the role of non-coding variants in human disease. Hum Mol Genet [Internet]. 2016;0:ddw205. https://doi.org/10.1093/hmg/ddw205.

    Article  CAS  Google Scholar 

  132. Kremer LS, Bader DM, Mertes C, Kopajtich R, Pichler G, Iuso A, et al. Genetic diagnosis of Mendelian disorders via RNA sequencing. Nat Commun. 2017;8:1–11.

    Google Scholar 

  133. Fresard L, Smail C, Smith KS, Ferraro NM, Teran NA, Kernohan KD, et al. Identification of rare-disease genes in diverse undiagnosed cases using whole blood transcriptome sequencing and large control cohorts. bioRxiv [Internet]. 2018;25:408492. 10.1101/408492%0A. https://www.biorxiv.org/content/early/2018/09/04/408492.

  134. Cummings BB, Marshall JL, Tukiainen T, Lek M, Donkervoort S, Foley AR, et al. Improving genetic diagnosis in Mendelian disease with transcriptome sequencing. Sci Transl Med [Internet]. Washington, DC : American Association for the Advancement of Science; 2017;9:1–25. https://www.macarthurlab.org/2017/05/31/improving-genetic-diagnosis-in-mendelian-disease-with-transcriptome-sequencing-a-walk-through/.

  135. Gonorazky HD, Naumenko S, Ramani AK, Nelakuditi V, Mashouri P, Wang P, et al. Expanding the boundaries of RNA sequencing as a diagnostic tool for rare Mendelian disease. Am J Hum Genet [Internet]. 2019;0:1–18.

    Google Scholar 

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SJB is funded by The Fred Liuzzi Foundation (TFLF) (Melbourne, Australia). NGL (APP1117510) and GR (APP1122952) are supported by the Australian National Health and Medical Research Council (NHMRC).

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Beecroft, S.J., Lamont, P.J., Edwards, S. et al. The Impact of Next-Generation Sequencing on the Diagnosis, Treatment, and Prevention of Hereditary Neuromuscular Disorders. Mol Diagn Ther 24, 641–652 (2020). https://doi.org/10.1007/s40291-020-00495-2

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