Skip to main content Accessibility help
×
Hostname: page-component-77c89778f8-9q27g Total loading time: 0 Render date: 2024-07-18T00:59:18.784Z Has data issue: false hasContentIssue false

15 - Next-generation sequencing for rare diseases

from Part IV - Next-generation sequencing technology and pharmaco-genomics

Published online by Cambridge University Press:  18 December 2015

Elena Bosch
Affiliation:
Universitat Pompeu Fabra
Ferran Casals
Affiliation:
Universitat Pompeu Fabra
Krishnarao Appasani
Affiliation:
GeneExpression Systems, Inc., Massachusetts
Stephen W. Scherer
Affiliation:
University of Toronto
Peter M. Visscher
Affiliation:
University of Queensland
Get access

Summary

Introduction

Most rare diseases have a genetic base, and are inherited in a Mendelian fashion. They are usually monogenic disorders segregating in families, or are sporadic, being autosomal or sex-linked and dominant or recessive. Before the advent of the new next-generation sequencing (NGS) technologies, positional cloning was the most commonly used technique for the analysis of the genetic basis of Mendelian diseases. Usually the first step of such studies was linkage analysis in pedigrees with multiples cases. In 1986, the genes underlying chronic granulomatous disease, Duchenne muscular dystrophy, and retinoblastoma were mapped using the linkage approach assisted by the identification of patients with structural changes or cytogenetically detectable deletions (Collins, 1995). Three years later, cystic fibrosis represented the first case where the gene of a Mendelian disease was mapped based only on linkage analysis and positional cloning (Kerem et al., 1989; Riordan et al., 1989). Another classical example is Huntington's disease, although in this case the gene was identified 10 years after the disease was mapped in 1983 (Gusella et al., 1983; Huntington et al., 1993). Cystic fibrosis and Huntington's disease are examples that fulfilled the most important requisites for successful linkage studies: a set of families with the disease segregating and minimal ambiguity of the cohort member status. On the other hand, misdiagnosis, incomplete penetrances, or allelic heterogeneity have often hindered linkage studies (Botstein and Risch, 2003). Very rare diseases, with the availability of only a few affected individuals from different pedigrees, have also remained unapproachable following this methodology. Another extensively used tool for recessive diseases is homozygosity mapping (Lander and Botstein, 1987), which is based on the location of the disease gene in tracks of homozygosity in the affected consanguineous children. These regions are expected to be homozygous across all the patients, and not in the unaffected relatives. Linkage and homozygosity mapping have benefitted from the increasing densities of genetic and physical mapping, improving their power with the availability of more complete human genetic variation maps. Paradoxically, the discovery rate of new genes related to Mendelian diseases did not increase after the release of the human genome sequence, and genetic research efforts shifted preferentially to the genetics of complex disorders (Antonarakis and Beckmann, 2006).

Type
Chapter
Information
Genome-Wide Association Studies
From Polymorphism to Personalized Medicine
, pp. 231 - 242
Publisher: Cambridge University Press
Print publication year: 2016

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1000 Genomes Project Consortium. (2010). A map of human genome variation from population-scale sequencing. Nature, 467(7319), 1061–1073.
Abecasis, G.R., Auton, A., Brooks, L.D., et al. (2012). An integrated map of genetic variation from 1,092 human genomes. Nature, 491(7422), 56–65.Google ScholarPubMed
Adzhubei, I.A., Schmidt, S., Peshkin, L., et al. (2010). A method and server for predicting damaging missense mutations. Nature Meth., 7(4), 248–249.CrossRefGoogle ScholarPubMed
Alexander, R.P., Fang, G., Rozowsky, J., et al. (2010). Annotating non-coding regions of the genome. Nature Rev. Genet., 11(8), 559–571.CrossRefGoogle ScholarPubMed
Antonarakis, S.E. and Beckmann, J.S. (2006). Mendelian disorders deserve more attention. Nature Rev. Genet., 7(4), 277–282.CrossRefGoogle ScholarPubMed
Awadalla, P., Gauthier, J., Myers, R.A., et al. (2010). Direct measure of the de novo mutation rate in autism and schizophrenia cohorts. Am. J. Hum. Genet., 87(3), 316–324.CrossRefGoogle Scholar
Bamshad, M.J., Ng, S.B., Bigham, A.W., et al. (2011). Exome sequencing as a tool for Mendelian disease gene discovery. Nature Rev. Genet., 12(11), 745–755.CrossRefGoogle ScholarPubMed
Bolze, A., Byun, M., McDonald, D., et al. (2010). Whole-exome-sequencing-based discovery of human FADD deficiency. Am. J. Hum. Genet., 87(6), 873–881.CrossRefGoogle ScholarPubMed
Botstein, D. and Risch, N. (2003). Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nature Genet., 33(Suppl.), 228–237.CrossRefGoogle ScholarPubMed
Boycott, K.M., Vanstone, M.R., Bulman, D.E., et al. (2013). Rare-disease genetics in the era of next-generation sequencing: discovery to translation. Nature Rev. Genet., 14(10), 681–691.CrossRefGoogle Scholar
Bustamante, C.D., Burchard, E.G. and De la Vega, F.M. (2011). Genomics for the world. Nature, 475(7355), 163–165.CrossRefGoogle Scholar
Choi, M., Scholl, U.I., Ji, W., et al. (2009). Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc. Natl Acad. Sci. USA, 106(45), 19096–19101.CrossRefGoogle ScholarPubMed
Collins, F.S. (1995). Positional cloning moves from perditional to traditional. Nature Genet., 9(4), 347–350.CrossRefGoogle ScholarPubMed
Conrad, D.F., Keebler, J.E., Depristo, M.A., et al. (2011). Variation in genome-wide mutation rates within and between human families. Nature Genet., 43(7), 712–714.CrossRefGoogle ScholarPubMed
Cooper, G.M. and Shendure, J. (2011). Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data. Nature Rev. Genet., 12(9),628–640.CrossRefGoogle Scholar
Doolittle, W.F. (2013). Is junk DNA bunk? A critique of ENCODE. Proc. Natl Acad. Sci. USA, 110(14), 5294–5300.CrossRefGoogle Scholar
Dunham, I., Kundaje, A., Aldred, S.F., et al. (2012). An integrated encyclopedia of DNA elements in the human genome. Nature, 489(7414), 57–74.Google Scholar
Gilissen, C., Hoischen, A., Brunner, H.G., et al. (2011). Unlocking Mendelian disease using exome sequencing. Genome Biol., 12(9), 228.CrossRefGoogle ScholarPubMed
Girard, S.L., Gauthier, J., Noreau, A., et al. (2011.) Increased exonic de novo mutation rate in individuals with schizophrenia. Nature Genet., 43(9), 860–863.CrossRefGoogle ScholarPubMed
González-Pérez, A. and López-Bigas, N. (2011). Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel. Am. J. Hum. Genet., 88(4), 440–449.CrossRefGoogle ScholarPubMed
Gravel, S., Henn, B.M., Gutenkunst, R.N., et al. (2011). Demographic history and rare allele sharing among human populations. Proc. Natl Acad. Sci. USA, 108(29), 11983–11988.CrossRefGoogle ScholarPubMed
Gusella, J., Wexler, N., Conneally, P., et al. (1983) A polymorphic DNA marker genetically linked to Huntington's disease. Nature, 306, 234–238.CrossRefGoogle ScholarPubMed
Hoischen, A., van Bon, B.W.M, Gilissen, C., et al. (2010). De novo mutations of SETBP1 cause Schinzel–Giedion syndrome. Nature Genet., 42(6), 483–485.CrossRefGoogle ScholarPubMed
Huntington, T., Macdonald, M.E., Ambrose, C.M., et al. (1993). A novel gene containing a trinucleotide that is expanded and unstable on Huntington's disease chromosomes. Cell, 72, 971–983.Google Scholar
International HapMap Consortium. (2003). The International HapMap Project. Nature, 426(6968), 789–796.
Itsara, A., Wu, H., Smith, J.D., et al. (2010). De novo rates and selection of large copy number variation. Genome Res., 20(11), 1469–1481.CrossRefGoogle ScholarPubMed
Jones, M., Bhide, S., Chin, E., et al. (2011). Targeted PCR-based enrichment and next generation sequencing for diagnostic testing of congenital disorders of glycosylation (CDG). Genet. Med., 13(11), 921–932.CrossRefGoogle Scholar
Keinan, A. and Clark, A.G. (2012). Recent explosive human population growth has resulted in an excess of rare genetic variants. Science, 336(6082), 740–743.CrossRefGoogle Scholar
Kerem, A.B., Rommens, J.M., Buchanan, J.A., et al. (1989). Identification of the cystic fibrosis gene: genetic analysis. Science, 245(4922), 1073–1080.CrossRefGoogle ScholarPubMed
Khurana, E., Fu, Y., Chen, J., et al. (2013). Interpretation of genomic variants using a unified biological network approach. PLoS Comput. Biol., 9(3), e1002886.CrossRefGoogle ScholarPubMed
Kleinjan, D.A. and van Heyningen, V. (2005). Long-range control of gene expression: emerging mechanisms and disruption in disease. Am. J. Hum. Genet., 76(1), 8–32.CrossRefGoogle Scholar
Krumm, N., Sudmant, P.H., Ko, A., et al. (2012). Copy number variation detection and genotyping from exome sequence data. Genome Res., 22(8), 1525–1532.CrossRefGoogle ScholarPubMed
Ku, C.S., Naidoo, N. and Pawitan, Y. (2011). Revisiting Mendelian disorders through exome sequencing. Hum. Genet., 129(4), 351–370.CrossRefGoogle ScholarPubMed
Ku, C.-.S, Cooper, D.N., Polychronakos, C., et al. (2012). Exome sequencing: dual role as a discovery and diagnostic tool. Ann. Neurol., 71(1), 5–14.CrossRefGoogle ScholarPubMed
Lander, E. and Botstein, D. (1987). Homozygosity mapping: a way to map human recessive traits with the DNA of inbred children. Science, 236, 1567–1570.CrossRefGoogle ScholarPubMed
Lindhurst, M.J., Sapp, J.C., Teer, J.K., et al. (2011) A mosaic activating mutation in AKT1 associated with the Proteus syndrome. New Engl. J. Med., 365(7), 611–619.CrossRefGoogle ScholarPubMed
Lo, Y.M.D., Corbetta, N., Chamberlain, P.F., et al. (1997). Presence of fetal DNA in maternal plasma and serum. Lancet, 350, 485–487.CrossRefGoogle ScholarPubMed
MacArthur, D.G., Balasubramanian, S., Frankish, A., et al. (2012). A systematic survey of loss-of-function variants in human protein-coding genes. Science (New York, N.Y.), 335(6070), 823–828.CrossRefGoogle ScholarPubMed
Malhotra, D., McCarthy, S., Michaelson, J.J., et al. (2011). High frequencies of de novo CNVs in bipolar disorder and schizophrenia. Neuron, 72(6), 951–963.CrossRefGoogle Scholar
Nelson, M.R., Wegmann, D., Ehm, M.G., et al. (2012). An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people. Science, 337(6090), 100–104.CrossRefGoogle ScholarPubMed
Ng, S.B., Buckingham, K.J., Lee, C., et al. (2009). Exome sequencing identifies the cause of a mendelian disorder. Nature Genet., 42(1), 30–35.Google ScholarPubMed
Ng, S.B., Bigham, A.W., Buckingham, K.J., et al. (2010). Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome. Nature Genet., 42(9), 790–793.Google ScholarPubMed
Nielsen, R., Paul, J.S., Albrechtsen, A., et al. (2011). Genotype and SNP calling from next-generation sequencing data. Nature Rev. Genet., 12(6), 443–451.CrossRefGoogle ScholarPubMed
O'Roak, B.J., Deriziotis, P., Lee, C., et al. (2011). Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations. Nature Genet., 43(6), 585–589.CrossRefGoogle ScholarPubMed
Riordan, J.R., Rommens, J.M., Kerem, B., et al. (1989). Identification of the cystic fibrosis gene: cloning and characterization of complementary DNA. Science (New York, N.Y.), 245(4922), 1066–1073.CrossRefGoogle ScholarPubMed
Sanders, S.J., Ercan-Sencicek, A.G., Hus, V., et al. (2011). Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism. Neuron, 70(5), 863–885.CrossRefGoogle ScholarPubMed
Sherry, S.T., Ward, M.H., Kholodov, M., et al. (2001) dbSNP: the NCBI database of genetic variation. Nucleic Acids Res., 29(1), 308–311.CrossRefGoogle ScholarPubMed
Snyder, M.W., Simmons, L.E., Kitzman, J.O., et al. (2013). Noninvasive fetal genome sequencing: a primer. Prenat. Diagn., 33(6), 547–554.CrossRefGoogle ScholarPubMed
Stumm, M., Entezami, M., Trunk, N., et al. (2012). Noninvasive prenatal detection of chromosomal aneuploidies using different next generation sequencing strategies and algorithms. Prenat. Diagn., 32(6), 569–577.CrossRefGoogle ScholarPubMed
Tennessen, J.A., Bigham, A.W., O'Connor, T.D., et al. (2012). Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science, 337(6090), 64–69.CrossRefGoogle ScholarPubMed
Treangen, T.J. and Salzberg, S.L. (2012). Repetitive DNA and next-generation sequencing: computational challenges and solutions. Nature Rev. Genet., 13(1), 36–46.Google Scholar
Veltman, J.A. and Brunner, H.G. (2012). De novo mutations in human genetic disease. Nature Rev. Genet., 13(8), 565–575.CrossRefGoogle ScholarPubMed
Vissers, L.E., de Ligt, J., Gilissen, C., et al. (2010). A de novo paradigm for mental retardation. Nature Genet., 42(12), 1109–1112.CrossRefGoogle Scholar
Walsh, T., Shahin, H., Elkan-Miller, T., et al. (2010). Whole exome sequencing and homozygosity mapping identify mutation in the cell polarity protein GPSM2 as the cause of nonsyndromic hearing loss DFNB82. Am. J. Hum. Genet., 87(1), 90–94.CrossRefGoogle ScholarPubMed
Wang, J.L., Yang, X., Xia, K., et al. (2010). TGM6 identified as a novel causative gene of spinocerebellar ataxias using exome sequencing. Brain, 133(Pt 12), 3510–3518.CrossRefGoogle ScholarPubMed
Worthey, E.A., Mayer, A.N., Syverson, G.D., et al. (2011). Making a definitive diagnosis: successful clinical application of whole exome sequencing in a child with intractable inflammatory bowel disease. Genet. Med., 13(3), 255–262.CrossRefGoogle Scholar
Yang, Y., Muzny, D.M., Reid, J.G., et al. (2013). Clinical whole-exome sequencing for the diagnosis of mendelian disorders. New Engl. J. Med., 369(16), 1502–1511.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×