1932

Abstract

Comprehensive annotations of genetic and noncoding regions and corresponding accurate variant classification for Mendelian diseases are the next big challenge in the new genomic era of personalized medicine. Progress in the development of faster and more accurate pipelines for genome annotation and variant classification will lead to the discovery of more novel disease associations and candidate therapeutic targets. This ultimately will facilitate better patient recruitment in clinical trials. In this review, we describe the trends in research at the intersection of basic and clinical genomics that aims to increase understanding of overall genomic complexity, complex inheritance patterns of disease, and patient-phenotype-specific genomic associations. We describe the emerging field of translational functional genomics, which integrates other functional “-omics” approaches that support next-generation sequencing genomic data in order to facilitate personalized diagnostics, disease management, biomarker discovery, and medicine. We also discuss the utility of this integrated approach for diagnostic clinics and medical databases and its role in the future of personalized medicine.

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2017-08-31
2024-06-18
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Literature Cited

  1. 1. 1000 Genomes Proj. Consort. 2010. A map of human genome variation from population-scale sequencing. Nature 467:1061–73 [Google Scholar]
  2. 2. 1000 Genomes Proj. Consort. 2015. A global reference for human genetic variation. Nature 526:68–74 [Google Scholar]
  3. Acuna-Hidalgo R, Bo T, Kwint MP, van de Vorst M, Pinelli M. 3.  et al. 2015. Post-zygotic point mutations are an underrecognized source of de novo genomic variation. Am. J. Hum. Genet. 97:67–74 [Google Scholar]
  4. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S. 4.  et al. 2013. Signatures of mutational processes in human cancer. Nature 500:415–21 [Google Scholar]
  5. Alexandrov LB, Nik-Zainal S, Wedge DC, Campbell PJ, Stratton MR. 5.  2013. Deciphering signatures of mutational processes operative in human cancer. Cell Rep 3:246–59 [Google Scholar]
  6. 6. AllSeq. 2017. Complete Genomics http://allseq.com/knowledge-bank/sequencing-platforms/complete-genomics [Google Scholar]
  7. Amendola LM, Dorschner MO, Robertson PD, Salama JS, Hart R. 7.  et al. 2015. Actionable exonic incidental findings in 6503 participants: challenges of variant classifications. Genome Res 25:305–15 [Google Scholar]
  8. Angermueller C, Clark SJ, Lee HJ, Macaulay IC, Teng MJ. 8.  et al. 2016. Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat. Methods 13:229–32 [Google Scholar]
  9. Araujo PR, Yoon K, Ko D, Smith AD, Qiao M. 9.  et al. 2012. Before it gets started: regulating translation at the 5′ UTR. Comp. Funct. Genom 2012:475731 [Google Scholar]
  10. Arrowsmith J, Miller P. 10.  2013. Trial watch: phase II and phase III attrition rates 2011–2012. Nat. Rev. Drug Discov. 12:569 [Google Scholar]
  11. Ashley EA, Butte AJ, Wheeler MT, Chen R, Klein TE. 11.  et al. 2010. Clinical assessment incorporating a personal genome. Lancet 375:1525–35 [Google Scholar]
  12. Au CH, Wa A, Ho DN, Chan TL, Ma ES. 12.  2016. Clinical evaluation of panel testing by next-generation sequencing (NGS) for gene mutations in myeloid neoplasms. Diagn. Pathol. 11:11 [Google Scholar]
  13. Au KF, Underwood JG, Lee L, Wong WH. 13.  2012. Improving PacBio long read accuracy by short read alignment. PLOS ONE 7:e46679 [Google Scholar]
  14. Batut P, Gingeras TR. 14.  2013. RAMPAGE: promoter activity profiling by paired-end sequencing of 5′-complete cDNAs. Curr. Protoc. Mol. Biol. 104:25B.11.1–16 [Google Scholar]
  15. Bauters M, Frints SG, Van Esch H, Spruijt L, Baldewijns MM. 15.  et al. 2014. Evidence for increased SOX3 dosage as a risk factor for X-linked hypopituitarism and neural tube defects. Am. J. Med. Genet. A 164A1947–52 [Google Scholar]
  16. Bell CJ, Dinwiddie DL, Miller NA, Hateley SL, Ganusova EE. 16.  et al. 2011. Carrier testing for severe childhood recessive diseases by next-generation sequencing. Sci. Transl. Med. 3:65ra4 [Google Scholar]
  17. Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J. 17.  et al. 2008. Accurate whole human genome sequencing using reversible terminator chemistry. Nature 456:53–59 [Google Scholar]
  18. 18. BGI. 2015. Revolocitywhole genome sequencing service http://www.bgi.com/wp-content/uploads/2015/10/Global-WGSRevolocity-ENG-10-15.pdf [Google Scholar]
  19. 19. BGI. 2017. BGISEQ-500: a BGI sequencer http://seq500.com/en/portal/Sequencer.shtml [Google Scholar]
  20. Blomen VA, Majek P, Jae LT, Bigenzahn JW, Nieuwenhuis J. 20.  et al. 2015. Gene essentiality and synthetic lethality in haploid human cells. Science 350:1092–96 [Google Scholar]
  21. Boutz PL, Bhutkar A, Sharp PA. 21.  2015. Detained introns are a novel, widespread class of post-transcriptionally spliced introns. Genes Dev 29:63–80 [Google Scholar]
  22. Brunner AL, Johnson DS, Kim SW, Valouev A, Reddy TE. 22.  et al. 2009. Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal liver. Genome Res 19:1044–56 [Google Scholar]
  23. Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ. 23.  2013. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10:1213–18 [Google Scholar]
  24. Caberlotto L, Lauria M. 24.  2015. Systems biology meets -omic technologies: novel approaches to biomarker discovery and companion diagnostic development. Expert Rev. Mol. Diagn. 15:255–65 [Google Scholar]
  25. Campbell PJ, Stephens PJ, Pleasance ED, O'Meara S, Li H. 25.  et al. 2008. Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing. Nat. Genet. 40:722–29 [Google Scholar]
  26. Chan M, Ji SM, Yeo ZX, Gan L, Yap E. 26.  et al. 2012. Development of a next-generation sequencing method for BRCA mutation screening: a comparison between a high-throughput and a benchtop platform. J. Mol. Diagn. 14:602–12 [Google Scholar]
  27. Chiocchetti AG, Kopp M, Waltes R, Haslinger D, Duketis E. 27.  et al. 2015. Variants of the CNTNAP2 5′ promoter as risk factors for autism spectrum disorders: a genetic and functional approach. Mol. Psychiatr. 20:839–49 [Google Scholar]
  28. Choi M, Scholl UI, Ji W, Liu T, Tikhonova IR. 28.  et al. 2009. Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. PNAS 106:19096–101 [Google Scholar]
  29. Church DM, Schneider VA, Steinberg KM, Schatz MC, Quinlan AR. 29.  et al. 2015. Extending reference assembly models. Genome Biol 16:13 [Google Scholar]
  30. Church GM, Gao Y, Kosuri S. 30.  2012. Next-generation digital information storage in DNA. Science 337:1628 [Google Scholar]
  31. Cirulli ET, Goldstein DB. 31.  2010. Uncovering the roles of rare variants in common disease through whole-genome sequencing. Nat. Rev. Genet. 11:415–25 [Google Scholar]
  32. Clarke J, Wu HC, Jayasinghe L, Patel A, Reid S, Bayley H. 32.  2009. Continuous base identification for single-molecule nanopore DNA sequencing. Nat. Nanotechnol. 4:265–70 [Google Scholar]
  33. Colombo M, Blok MJ, Whiley P, Santamariña M, Gutiérrez-Enriquez S. 33.  et al. 2014. Comprehensive annotation of splice junctions support pervasive alternative splicing at the BRCA1 locus: a report from the ENIGMA consortium. Hum. Mol. Genet. 23:3666–80 [Google Scholar]
  34. Compeau PE, Pevzner PA, Tesler G. 34.  2011. How to apply de Bruijn graphs to genome assembly. Nat. Biotechnol. 29:987–91 [Google Scholar]
  35. Coon EA, Ahlskog JE, Patterson MC, Niu Z, Milone M. 35.  2016. Expanding phenotypic spectrum of NKX2-1-related disorders—mitochondrial and immunologic dysfunction. JAMA Neurol 73:237–38 [Google Scholar]
  36. de Ligt J, Willemsen MH, van Bon BW, Kleefstra T, Yntema HG. 36.  et al. 2012. Diagnostic exome sequencing in persons with severe intellectual disability. N. Engl. J. Med. 367:1921–29 [Google Scholar]
  37. Deans ZC, Costa JL, Cree I, Dequeker E, Edsjo A. 37.  et al. 2017. Integration of next-generation sequencing in clinical diagnostic molecular pathology laboratories for analysis of solid tumours; an expert opinion on behalf of IQN Path ASBL. Virchows Arch 470:5–20 [Google Scholar]
  38. 38. Deciphering Dev. Disord. Study. 2015. Large-scale discovery of novel genetic causes of developmental disorders. Nature 519:223–28 [Google Scholar]
  39. Delaney SK, Hultner ML, Jacob HJ, Ledbetter DH, McCarthy JJ. 39.  et al. 2016. Toward clinical genomics in everyday medicine: perspectives and recommendations. Expert Rev. Mol. Diagn. 16:521–32 [Google Scholar]
  40. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR. 40.  et al. 2011. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43:491–98 [Google Scholar]
  41. Derti A, Garrett-Engele P, MacIsaac KD, Stevens RC, Sriram S. 41.  et al. 2012. A quantitative atlas of polyadenylation in five mammals. Genome Res 22:1173–83 [Google Scholar]
  42. Dewey FE, Grove ME, Pan C, Goldstein BA, Bernstein JA. 42.  et al. 2014. Clinical interpretation and implications of whole-genome sequencing. JAMA 311:1035–45 [Google Scholar]
  43. Dorschner MO, Amendola LM, Turner EH, Robertson PD, Shirts BH. 43.  et al. 2013. Actionable, pathogenic incidental findings in 1,000 participants’ exomes. Am. J. Hum Genet. 93:631–40 [Google Scholar]
  44. Dressman D, Yan H, Traverso G, Kinzler KW, Vogelstein B. 44.  2003. Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. PNAS 100:8817–22 [Google Scholar]
  45. Drmanac R, Sparks AB, Callow MJ, Halpern AL, Burns NL. 45.  et al. 2010. Human genome sequencing using unchained base reads on self-assembling DNA nanoarrays. Science 327:78–81 [Google Scholar]
  46. Elkon R, Ugalde AP, Agami R. 46.  2013. Alternative cleavage and polyadenylation: extent, regulation and function. Nat. Rev. Genet. 14:496–506 [Google Scholar]
  47. English AC, Salerno WJ, Hampton OA, Gonzaga-Jauregui C, Ambreth S. 47.  et al. 2015. Assessing structural variation in a personal genome—towards a human reference diploid genome. BMC Genom 16:286 [Google Scholar]
  48. Esposito MV, Nunziato M, Starnone F, Telese A, Calabrese A. 48.  et al. 2016. A novel pathogenic BRCA1 splicing variant produces partial intron retention in the mature messenger RNA. Int. J. Mol. Sci. 17:2145 [Google Scholar]
  49. Farooq M, Fatima A, Mang Y, Hansen L, Kjaer KW. 49.  et al. 2016. A novel splice site mutation in CEP135 is associated with primary microcephaly in a Pakistani family. J. Hum. Genet. 61:271–73 [Google Scholar]
  50. Fu W, O'Connor TD, Jun G, Kang HM, Abecasis G. 50.  et al. 2013. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 493:216–20 [Google Scholar]
  51. Fullwood MJ, Ruan Y. 51.  2009. ChIP-based methods for the identification of long-range chromatin interactions. J. Cell. Biochem. 107:30–39 [Google Scholar]
  52. Gargis AS, Kalman L, Berry MW, Bick DP, Dimmock DP. 52.  et al. 2012. Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat. Biotechnol. 30:1033–36 [Google Scholar]
  53. Gargis AS, Kalman L, Bick DP, da Silva C, Dimmock DP. 53.  et al. 2015. Good laboratory practice for clinical next-generation sequencing informatics pipelines. Nat. Biotechnol. 33:689–93 [Google Scholar]
  54. Gargis AS, Kalman L, Lubin IM. 54.  2016. Assuring the quality of next-generation sequencing in clinical microbiology and public health laboratories. J. Clin. Microbiol. 54:2857–65 [Google Scholar]
  55. Garnett MJ, McDermott U. 55.  2014. The evolving role of cancer cell line-based screens to define the impact of cancer genomes on drug response. Curr. Opin. Genet. Dev. 24:114–19 [Google Scholar]
  56. 56. Genome Ref. Consort. 2017. Human genome overview https://www.ncbi.nlm.nih.gov/grc/human [Google Scholar]
  57. 57. GenomeWeb Staff Report. 2016. White House announces efforts to accelerate Precision Medicine Initiative. GenomeWeb Feb. 25. https://www.genomeweb.com/molecular-diagnostics/white-house-announces-efforts-accelerate-precision-medicine-initiative [Google Scholar]
  58. Gilissen C, Hoischen A, Brunner HG, Veltman JA. 58.  2012. Disease gene identification strategies for exome sequencing. Eur. J. Hum. Genet. 20:490–97 [Google Scholar]
  59. Goodwin S, McPherson JD, McCombie WR. 59.  2016. Coming of age: ten years of next-generation sequencing technologies. Nat. Rev. Genet. 17:333–51 [Google Scholar]
  60. Green RC, Berg JS, Grody WW, Kalia SS, Korf BR. 60.  et al. 2013. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet. Med. 15:565–74 [Google Scholar]
  61. Gudbjartsson DF, Helgason H, Gudjonsson SA, Zink F, Oddson A. 61.  et al. 2015. Large-scale whole-genome sequencing of the Icelandic population. Nat. Genet. 47:435–44 [Google Scholar]
  62. Gundersen S, Kalas M, Abul O, Frigessi A, Hovig E, Sandve GK. 62.  2011. Identifying elemental genomic track types and representing them uniformly. BMC Bioinform 12:494 [Google Scholar]
  63. Gunel M, Awad IA, Finberg K, Anson JA, Steinberg GK. 63.  et al. 1996. A founder mutation as a cause of cerebral cavernous malformation in Hispanic Americans. N. Engl. J. Med. 334:946–51 [Google Scholar]
  64. Guo J, Xu N, Li Z, Zhang S, Wu J. 64.  et al. 2008. Four-color DNA sequencing with 3′-O-modified nucleotide reversible terminators and chemically cleavable fluorescent dideoxynucleotides. PNAS 105:9145–50 [Google Scholar]
  65. Harismendy O, Ng PC, Strausberg RL, Wang X, Stockwell TB. 65.  et al. 2009. Evaluation of next generation sequencing platforms for population targeted sequencing studies. Genome Biol 10:R32 [Google Scholar]
  66. Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M. 66.  et al. 2012. GENCODE: the reference human genome annotation for the ENCODE Project. Genome Res 22:1760–74 [Google Scholar]
  67. Hayes DF, Schott AF. 67.  2015. Personalized medicine: genomics trials in oncology. Trans. Am. Clin. Climatol. Assoc. 126:133–43 [Google Scholar]
  68. Hegde M, Bale S, Bayrak-Toydemir P, Gibson J, Bone Jeng LJ. 68.  et al. 2015. Reporting incidental findings in genomic scale clinical sequencing—a clinical laboratory perspective: a report of the Association for Molecular Pathology. J. Mol. Diagn. 17:107–17 [Google Scholar]
  69. Hehir-Kwa JY, Marschall T, Kloosterman WP, Francioli LC, Baaijens JA. 69.  et al. 2016. A high-quality human reference panel reveals the complexity and distribution of genomic structural variants. Nat. Commun. 7:12989 [Google Scholar]
  70. Helleday T, Eshtad S, Nik-Zainal S. 70.  2014. Mechanisms underlying mutational signatures in human cancers. Nat. Rev. Genet. 15:585–98 [Google Scholar]
  71. Henshall DC. 71.  2014. MicroRNA and epilepsy: profiling, functions and potential clinical applications. Curr. Opin. Neurol. 27:199–205 [Google Scholar]
  72. Henshall DC, Kobow K. 72.  2015. Epigenetics and epilepsy. Cold Spring Harb. Perspect. Med. 5:a022731 [Google Scholar]
  73. Hodges E, Xuan Z, Balija V, Kramer M, Molla MN. 73.  et al. 2007. Genome-wide in situ exon capture for selective resequencing. Nat. Genet. 39:1522–27 [Google Scholar]
  74. Hussin JG, Hodgkinson A, Idaghdour Y, Grenier JC, Goulet JP. 74.  et al. 2015. Recombination affects accumulation of damaging and disease-associated mutations in human populations. Nat. Genet. 47:400–4 [Google Scholar]
  75. 75. Int. Hum. Genome Seq. Consort. 2004. Finishing the euchromatic sequence of the human genome. Nature 431:931–45 [Google Scholar]
  76. 76. Ion Torrent. 2011. Ion semiconductor sequencing uniquely enables both accurate long reads and paired-end sequencing https://www3.appliedbiosystems.com/cms/groups/applied_markets_marketing/documents/generaldocuments/cms_098680.pdf [Google Scholar]
  77. Irizarry RA, Ladd-Acosta C, Carvalho B, Wu H, Brandenburg SA. 77.  et al. 2008. Comprehensive high-throughput arrays for relative methylation (CHARM). Genome Res 18:780–90 [Google Scholar]
  78. Jaeken J, Matthijs G. 78.  2007. Congenital disorders of glycosylation: a rapidly expanding disease family. Annu. Rev. Genom. Hum. Genet. 8:261–78 [Google Scholar]
  79. Jakovcevski M, Akbarian S. 79.  2012. Epigenetic mechanisms in neurological disease. Nat. Med. 18:1194–204 [Google Scholar]
  80. Jiang Y, Oldridge DA, Diskin SJ, Zhang NR. 80.  2015. CODEX: a normalization and copy number variation detection method for whole exome sequencing. Nucleic Acids Res 43:e39 [Google Scholar]
  81. Jimenez-Sanchez G, Childs B, Valle D. 81.  2001. Human disease genes. Nature 409:853–55 [Google Scholar]
  82. Johnston JJ, Rubinstein WS, Facio FM, Ng D, Singh LN. 82.  et al. 2012. Secondary variants in individuals undergoing exome sequencing: screening of 572 individuals identifies high-penetrance mutations in cancer-susceptibility genes. Am. J. Hum. Genet. 91:97–108 [Google Scholar]
  83. Jongmans MC, Admiraal RJ, van der Donk KP, Vissers LE, Baas AF. 83.  et al. 2006. CHARGE syndrome: the phenotypic spectrum of mutations in the CHD7 gene. J. Med. Genet 43306–14 [Google Scholar]
  84. Jørgensen JT. 84.  2015. Clinical application of companion diagnostics. Trends Mol. Med. 21:405–7 [Google Scholar]
  85. Jørgensen JT. 85.  2015. Companion diagnostics: the key to personalized medicine. Expert Rev. Mol. Diagn. 15:153–56 [Google Scholar]
  86. Ju J, Kim DH, Bi L, Meng Q, Bai X. 86.  et al. 2006. Four-color DNA sequencing by synthesis using cleavable fluorescent nucleotide reversible terminators. PNAS 103:19635–40 [Google Scholar]
  87. Kalia SS, Adelman K, Bale SJ, Chung WK, Eng C. 87.  et al. 2017. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet. Med. 19:249–55 [Google Scholar]
  88. Karow J. 88.  2015. Qiagen launches GeneReader NGS system at AMP; presents performance evaluation by Broad. GenomeWeb Nov. 4. https://www.genomeweb.com/molecular-diagnostics/qiagen-launches-genereader-ngs-system-amp-presents-performance-evaluation [Google Scholar]
  89. Khurana E, Fu Y, Chen J, Gerstein M. 89.  2013. Interpretation of genomic variants using a unified biological network approach. PLOS Comput. Biol. 9:e1002886 [Google Scholar]
  90. Kim JB, Porreca GJ, Song L, Greenway SC, Gorham JM. 90.  et al. 2007. Polony multiplex analysis of gene expression (PMAGE) in mouse hypertrophic cardiomyopathy. Science 316:1481–84 [Google Scholar]
  91. Kircher M, Kelso J. 91.  2010. High-throughput DNA sequencing—concepts and limitations. BioEssays 32:524–36 [Google Scholar]
  92. Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J. 92.  2014. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 46:310–15 [Google Scholar]
  93. Koren S, Schatz MC, Walenz BP, Martin J, Howard JT. 93.  et al. 2012. Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nat. Biotechnol. 30:693–700 [Google Scholar]
  94. Krumm N, Sudmant PH, Ko A, O'Roak BJ, Malig M. 94.  et al. 2012. Copy number variation detection and genotyping from exome sequence data. Genome Res 22:1525–32 [Google Scholar]
  95. Ku CS, Polychronakos C, Tan EK, Naidoo N, Pawitan Y. 95.  et al. 2013. A new paradigm emerges from the study of de novo mutations in the context of neurodevelopmental disease. Mol. Psychiatr. 18:141–53 [Google Scholar]
  96. Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC. 96.  et al. 2001. Initial sequencing and analysis of the human genome. Nature 409:860–921 [Google Scholar]
  97. Lapin V, Mighion LC, da Silva CP, Cuperus Y, Bean LJ, Hegde MR. 97.  2016. Regulating whole exome sequencing as a diagnostic test. Hum. Genet. 135:655–73 [Google Scholar]
  98. Leamon JH, Lee WL, Tartaro KR, Lanza JR, Sarkis GJ. 98.  et al. 2003. A massively parallel PicoTiterPlate based platform for discrete picoliter-scale polymerase chain reactions. Electrophoresis 24:3769–77 [Google Scholar]
  99. Lee D, Gorkin DU, Baker M, Strober BJ, Asoni AL. 99.  et al. 2015. A method to predict the impact of regulatory variants from DNA sequence. Nat. Genet. 47:955–61 [Google Scholar]
  100. Leen WG, Klepper J, Verbeek MM, Leferink M, Hofste T. 100.  et al. 2010. Glucose transporter-1 deficiency syndrome: the expanding clinical and genetic spectrum of a treatable disorder. Brain 133:655–70 [Google Scholar]
  101. Lelieveld SH, Spielmann M, Mundlos S, Veltman JA, Gilissen C. 101.  2015. Comparison of exome and genome sequencing technologies for the complete capture of protein-coding regions. Hum. Mutat. 36:815–22 [Google Scholar]
  102. Lelieveld SH, Veltman JA, Gilissen C. 102.  2016. Novel bioinformatic developments for exome sequencing. Hum. Genet. 135:603–14 [Google Scholar]
  103. Leslie EJ, O'Sullivan J, Cunningham ML, Singh A, Goudy SL. 103.  et al. 2015. Expanding the genetic and phenotypic spectrum of popliteal pterygium disorders. Am. J. Med. Genet. A 167A545–52 [Google Scholar]
  104. Levy SE, Myers RM. 104.  2016. Advancements in next-generation sequencing. Annu. Rev. Genom. Hum. Genet. 17:95–115 [Google Scholar]
  105. Li H. 105.  2014. On the graphical representation of sequences. Heng Li's Blog July 25. http://lh3.github.io/2014/07/25/on-the-graphical-representation-of-sequences [Google Scholar]
  106. Li S, Tighe SW, Nicolet CM, Grove D, Levy S. 106.  et al. 2014. Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study. Nat. Biotechnol. 32:915–25 [Google Scholar]
  107. Lieberman-Aiden E, van Berkum NL, Williams L, Imakaev M, Ragoczy T. 107.  et al. 2009. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326:289–93 [Google Scholar]
  108. Lin E, Chien J, Ong FS, Fan JB. 108.  2015. Challenges and opportunities for next-generation sequencing in companion diagnostics. Expert Rev. Mol. Diagn. 15:193–209 [Google Scholar]
  109. Liu L, Li Y, Li S, Hu N, He Y. 109.  et al. 2012. Comparison of next-generation sequencing systems. J. Biomed. Biotechnol. 2012:251364 [Google Scholar]
  110. Lohmueller KE, Sparsø T, Li Q, Andersson E, Korneliussen T. 110.  et al. 2013. Whole-exome sequencing of 2,000 Danish individuals and the role of rare coding variants in type 2 diabetes. Am. J. Hum. Genet. 93:1072–86 [Google Scholar]
  111. MacArthur DG, Tyler-Smith C. 111.  2010. Loss-of-function variants in the genomes of healthy humans. Hum. Mol. Genet. 19:R125–30 [Google Scholar]
  112. Macaulay IC, Teng MJ, Haerty W, Kumar P, Ponting CP, Voet T. 112.  2016. Separation and parallel sequencing of the genomes and transcriptomes of single cells using G&T-seq. Nat. Protoc. 11:2081–103 [Google Scholar]
  113. Majewski J, Schwartzentruber J, Lalonde E, Montpetit A, Jabado N. 113.  2011. What can exome sequencing do for you?. J. Med. Genet 48580–89 [Google Scholar]
  114. Malapelle U, Vigliar E, Sgariglia R, Bellevicine C, Colarossi L. 114.  et al. 2015. Ion Torrent next-generation sequencing for routine identification of clinically relevant mutations in colorectal cancer patients. J. Clin. Pathol. 68:64–68 [Google Scholar]
  115. Mandelker D, Schmidt RJ, Ankala A, McDonald Gibson K, Bowser M. 115.  et al. 2016. Navigating highly homologous genes in a molecular diagnostic setting: a resource for clinical next-generation sequencing. Genet. Med. 18:1282–89 [Google Scholar]
  116. McCarroll SA, Altshuler DM. 116.  2007. Copy-number variation and association studies of human disease. Nat. Genet. 39:S37–42 [Google Scholar]
  117. Meissner A, Gnirke A, Bell GW, Ramsahoye B, Lander ES, Jaenisch R. 117.  2005. Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res 33:5868–77 [Google Scholar]
  118. Metzker ML. 118.  2010. Sequencing technologies—the next generation. Nat. Rev. Genet. 11:31–46 [Google Scholar]
  119. Meynert AM, Ansari M, FitzPatrick DR, Taylor MS. 119.  2014. Variant detection sensitivity and biases in whole genome and exome sequencing. BMC Bioinform 15:247 [Google Scholar]
  120. Mirkin SM. 120.  2007. Expandable DNA repeats and human disease. Nature 447:932–40 [Google Scholar]
  121. Morey M, Fernandez-Marmiesse A, Castineiras D, Fraga JM, Couce ML, Cocho JA. 121.  2013. A glimpse into past, present, and future DNA sequencing. Mol. Genet. Metab. 110:3–24 [Google Scholar]
  122. Myers EW. 122.  2005. The fragment assembly string graph. Bioinformatics 21:Suppl. 2ii79–85 [Google Scholar]
  123. Nagy E, Maquat LE. 123.  1998. A rule for termination-codon position within intron-containing genes: when nonsense affects RNA abundance. Trends Biochem. Sci. 23:198–99 [Google Scholar]
  124. Narravula A, Garber KB, Askree SH, Hegde M, Hall PL. 124.  2017. Variants of uncertain significance in newborn screening disorders: implications for large-scale genomic sequencing. Genet. Med. 19:77–82 [Google Scholar]
  125. 125. Natl. Hum. Genome Res. Inst. 2016. The cost of sequencing a human genome Updated July 16. https://www.genome.gov/sequencingcosts [Google Scholar]
  126. Neale BM, Kou Y, Liu L, Ma'ayan A, Samocha KE. 126.  et al. 2012. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature 485:242–45 [Google Scholar]
  127. Ng SB, Bigham AW, Buckingham KJ, Hannibal MC, McMillin MJ. 127.  et al. 2010. Exome sequencing identifies MLL2 mutations as a cause of Kabuki syndrome. Nat. Genet. 42:790–93 [Google Scholar]
  128. Ng SB, Buckingham KJ, Lee C, Bigham AW, Tabor HK. 128.  et al. 2010. Exome sequencing identifies the cause of a Mendelian disorder. Nat. Genet. 42:30–35 [Google Scholar]
  129. Nguyen LS, Jolly L, Shoubridge C, Chan WK, Huang L. 129.  et al. 2012. Transcriptome profiling of UPF3B/NMD-deficient lymphoblastoid cells from patients with various forms of intellectual disability. Mol. Psychiatr. 17:1103–15 [Google Scholar]
  130. Niesler B, Flohr T, Nöthen MM, Fischer C, Rietschel M. 130.  et al. 2001. Association between the 5′ UTR variant C178T of the serotonin receptor gene HTR3A and bipolar affective disorder. Pharmacogenetics 11:471–75 [Google Scholar]
  131. Nothnagel M, Herrmann A, Wolf A, Schreiber S, Platzer M. 131.  et al. 2011. Technology-specific error signatures in the 1000 Genomes Project data. Hum. Genet. 130:505–16 [Google Scholar]
  132. Oberhardt MA, Gianchandani EP. 132.  2014. Genome-scale modeling and human disease: an overview. Front. Physiol. 5:527 [Google Scholar]
  133. Oberhardt MA, Palsson , Papin JA. 133.  2009. Applications of genome-scale metabolic reconstructions. Mol. Syst. Biol. 5:320 [Google Scholar]
  134. Oda M, Glass JL, Thompson RF, Mo Y, Olivier EN. 134.  et al. 2009. High-resolution genome-wide cytosine methylation profiling with simultaneous copy number analysis and optimization for limited cell numbers. Nucleic Acids Res 37:3829–39 [Google Scholar]
  135. Offit K. 135.  2014. Decade in review—genomics: a decade of discovery in cancer genomics. Nat. Rev. Clin. Oncol. 11:632–34 [Google Scholar]
  136. Olson ND, Lund SP, Colman RE, Foster JT, Sahl JW. 136.  et al. 2015. Best practices for evaluating single nucleotide variant calling methods for microbial genomics. Front. Genet. 6:235 [Google Scholar]
  137. Oskoui M, Gazzellone MJ, Thiruvahindrapuram B, Zarrei M, Andersen J. 137.  et al. 2015. Clinically relevant copy number variations detected in cerebral palsy. Nat. Commun. 6:7949 [Google Scholar]
  138. 138. Pac. Biosci. 2012. Detecting DNA base modifications using single molecule, real-time sequencing http://www.pacb.com/wp-content/uploads/2015/09/WP_Detecting_DNA_Base_Modifications_Using_SMRT_Sequencing.pdf [Google Scholar]
  139. Panjwani N, Wilson MD, Addis L, Crosbie J, Wirrell E. 139.  et al. 2016. A microRNA-328 binding site in PAX6 is associated with centrotemporal spikes of rolandic epilepsy. Ann. Clin. Transl. Neurol. 3:512–22 [Google Scholar]
  140. Pant S, Weiner R, Marton MJ. 140.  2014. Navigating the rapids: the development of regulated next-generation sequencing-based clinical trial assays and companion diagnostics. Front. Oncol. 4:78 [Google Scholar]
  141. Parikh H, Mohiyuddin M, Lam HY, Iyer H, Chen D. 141.  et al. 2016. svclassify: a method to establish benchmark structural variant calls. BMC Genom 17:64 [Google Scholar]
  142. Park PJ. 142.  2009. ChIP-seq: advantages and challenges of a maturing technology. Nat. Rev. Genet. 10:669–80 [Google Scholar]
  143. Parla JS, Iossifov I, Grabill I, Spector MS, Kramer M, McCombie WR. 143.  2011. A comparative analysis of exome capture. Genome Biol 12:R97 [Google Scholar]
  144. Patwardhan A, Harris J, Leng N, Bartha G, Church DM. 144.  et al. 2015. Achieving high-sensitivity for clinical applications using augmented exome sequencing. Genome Med 7:71 [Google Scholar]
  145. Paul SM, Mytelka DS, Dunwiddie CT, Persinger CC, Munos BH. 145.  et al. 2010. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat. Rev. Drug Discov. 9:203–14 [Google Scholar]
  146. Pei B, Sisu C, Frankish A, Howald C, Habegger L. 146.  et al. 2012. The GENCODE pseudogene resource. Genome Biol 13:R51 [Google Scholar]
  147. Petrovski S, Wang Q, Heinzen EL, Allen AS, Goldstein DB. 147.  2013. Genic intolerance to functional variation and the interpretation of personal genomes. PLOS Genet 9:e1003709 [Google Scholar]
  148. Poliseno L, Haimovic A, Christos PJ, Vega Y Saenz de Miera EC, Shapiro R. 148.  et al. 2011. Deletion of PTENP1 pseudogene in human melanoma. J. Investig. Dermatol. 131:2497–500 [Google Scholar]
  149. Poliseno L, Salmena L, Zhang J, Carver B, Haveman WJ, Pandolfi PP. 149.  2010. A coding-independent function of gene and pseudogene mRNAs regulates tumour biology. Nature 465:1033–38 [Google Scholar]
  150. Posey JE, Rosenfeld JA, James RA, Bainbridge M, Niu Z. 150.  et al. 2016. Molecular diagnostic experience of whole-exome sequencing in adult patients. Genet. Med. 18:678–85 [Google Scholar]
  151. Qureshi IA, Mehler MF. 151.  2012. Emerging roles of non-coding RNAs in brain evolution, development, plasticity and disease. Nat. Rev. Neurosci. 13:528–41 [Google Scholar]
  152. Ramser J, Abidi FE, Burckle CA, Lenski C, Toriello H. 152.  et al. 2005. A unique exonic splice enhancer mutation in a family with X-linked mental retardation and epilepsy points to a novel role of the renin receptor. Hum. Mol. Genet. 14:1019–27 [Google Scholar]
  153. Rauch C, Trieb M, Wibowo FR, Wellenzohn B, Mayer E, Liedl KR. 153.  2005. Towards an understanding of DNA recognition by the methyl-CpG binding domain 1. J. Biomol. Struct. Dyn. 22:695–706 [Google Scholar]
  154. Regalado A. 154.  2015. U.S. to develop DNA study of one million people. MIT Technology Review Jan. 30. https://www.technologyreview.com/s/534591/us-to-develop-dna-study-of-one-million-people [Google Scholar]
  155. Rehm HL, Bale SJ, Bayrak-Toydemir P, Berg JS, Brown KK. 155.  et al. 2013. ACMG clinical laboratory standards for next-generation sequencing. Genet. Med. 15:733–47 [Google Scholar]
  156. Reimand J, Wagih O, Bader GD. 156.  2015. Evolutionary constraint and disease associations of post-translational modification sites in human genomes. PLOS Genet 11:e1004919 [Google Scholar]
  157. Ren L, Zhu R, Li X. 157.  2016. Silencing miR-181a produces neuroprotection against hippocampus neuron cell apoptosis post-status epilepticus in a rat model and in children with temporal lobe epilepsy. Genet. Mol. Res. 15:gmr.15017798 [Google Scholar]
  158. Reuter JA, Spacek DV, Snyder MP. 158.  2015. High-throughput sequencing technologies. Mol. Cell 58:586–97 [Google Scholar]
  159. Richards S, Aziz N, Bale S, Bick D, Das S. 159.  et al. 2015. 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. 17:405–24 [Google Scholar]
  160. Rieber N, Zapatka M, Lasitschka B, Jones D, Northcott P. 160.  et al. 2013. Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies. PLOS ONE 8:e66621 [Google Scholar]
  161. Robinson PN, Köhler S, Oellrich A. 161.  Sanger Mouse Genet. Proj., Wang K et al. 2014. Improved exome prioritization of disease genes through cross-species phenotype comparison. Genome Res. 24:340–48 [Google Scholar]
  162. Rogozhina Y, Mironovich S, Shestak A, Adyan T, Polyakov A. 162.  et al. 2016. New intronic splicing mutation in the LMNA gene causing progressive cardiac conduction defects and variable myopathy. Gene 595:202–6 [Google Scholar]
  163. Rothberg JM, Hinz W, Rearick TM, Schultz J, Mileski W. 163.  et al. 2011. An integrated semiconductor device enabling non-optical genome sequencing. Nature 475:348–52 [Google Scholar]
  164. Rydbeck H, Sandve GK, Ferkingstad E, Simovski B, Rye M, Hovig E. 164.  2015. ClusTrack: feature extraction and similarity measures for clustering of genome-wide data sets. PLOS ONE 10:e0123261 [Google Scholar]
  165. Samocha KE, Robinson EB, Sanders SJ, Stevens C, Sabo A. 165.  et al. 2014. A framework for the interpretation of de novo mutation in human disease. Nat. Genet. 46:944–50 [Google Scholar]
  166. Schatz MC, Delcher AL, Salzberg SL. 166.  2010. Assembly of large genomes using second-generation sequencing. Genome Res 20:1165–73 [Google Scholar]
  167. Sharon D, Tilgner H, Grubert F, Snyder M. 167.  2013. A single-molecule long-read survey of the human transcriptome. Nat. Biotechnol. 31:1009–14 [Google Scholar]
  168. Shen Y, Sarin S, Liu Y, Hobert O, Pe'er I. 168.  2008. Comparing platforms for C. elegans mutant identification using high-throughput whole-genome sequencing. PLOS ONE 3:e4012 [Google Scholar]
  169. Shendure J, Porreca GJ, Reppas NB, Lin X, McCutcheon JP. 169.  et al. 2005. Accurate multiplex polony sequencing of an evolved bacterial genome. Science 309:1728–32 [Google Scholar]
  170. Shiraki T, Kondo S, Katayama S, Waki K, Kasukawa T. 170.  et al. 2003. Cap analysis gene expression for high-throughput analysis of transcriptional starting point and identification of promoter usage. PNAS 100:15776–81 [Google Scholar]
  171. Simon R, Roychowdhury S. 171.  2013. Implementing personalized cancer genomics in clinical trials. Nat. Rev. Drug Discov. 12:358–69 [Google Scholar]
  172. Sinajon P, Verbaan D, So J. 172.  2016. The expanding phenotypic spectrum of female SLC9A6 mutation carriers: a case series and review of the literature. Hum. Genet. 135:841–50 [Google Scholar]
  173. Spielmann M, Mundlos S. 173.  2016. Looking beyond the genes: the role of non-coding variants in human disease. Hum. Mol. Genet. 25:R157–65 [Google Scholar]
  174. Stankiewicz P, Lupski JR. 174.  2010. Structural variation in the human genome and its role in disease. Annu. Rev. Med. 61:437–55 [Google Scholar]
  175. Steinberg KM, Schneider VA, Graves-Lindsay TA, Fulton RS, Agarwala R. 175.  et al. 2014. Single haplotype assembly of the human genome from a hydatidiform mole. Genome Res 24:2066–76 [Google Scholar]
  176. Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C. 176.  et al. 2015. Big data: astronomical or genomical?. PLOS Biol 13:e1002195 [Google Scholar]
  177. Stokman MF, Renkema KY, Giles RH, Schaefer F, Knoers NV, van Eerde AM. 177.  2016. The expanding phenotypic spectra of kidney diseases: insights from genetic studies. Nat. Rev. Nephrol. 12:472–83 [Google Scholar]
  178. Sudmant PH, Rausch T, Gardner EJ, Handsaker RE, Abyzov A. 178.  et al. 2015. An integrated map of structural variation in 2,504 human genomes. Nature 526:75–81 [Google Scholar]
  179. Tilgner H, Jahanbani F, Blauwkamp T, Moshrefi A, Jaeger E. 179.  et al. 2015. Comprehensive transcriptome analysis using synthetic long-read sequencing reveals molecular co-association of distant splicing events. Nat. Biotechnol. 33:736–42 [Google Scholar]
  180. Timmerman L. 180.  2015. DNA sequencing market will exceed $20 billion, says Illumina CEO Jay Flatley. Forbes Apr. 29. http://www.forbes.com/sites/luketimmerman/2015/04/29/qa-with-jay-flatley-ceo-of-illumina-the-genomics-company-pursuing-a-20b-market [Google Scholar]
  181. Treutlein B, Brownfield DG, Wu AR, Neff NF, Mantalas GL. 181.  et al. 2014. Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq. Nature 509:371–75 [Google Scholar]
  182. 182. UK10K Consort. 2015. The UK10K project identifies rare variants in health and disease. Nature 526:82–90 [Google Scholar]
  183. Ulitsky I, Bartel DP. 183.  2013. lincRNAs: genomics, evolution, and mechanisms. Cell 154:26–46 [Google Scholar]
  184. Valouev A, Ichikawa J, Tonthat T, Stuart J, Ranade S. 184.  et al. 2008. A high-resolution, nucleosome position map of C. elegans reveals a lack of universal sequence-dictated positioning. Genome Res 18:1051–63 [Google Scholar]
  185. Vengoechea J, Parikh AS, Zhang S, Tassone F. 185.  2012. De novo microduplication of the FMR1 gene in a patient with developmental delay, epilepsy and hyperactivity. Eur. J. Hum. Genet. 20:1197–200 [Google Scholar]
  186. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ. 186.  et al. 2001. The sequence of the human genome. Science 291:1304–51 [Google Scholar]
  187. 187. VeritasGenetics. 2015. VeritasGenetics breaks $1,000 whole genome barrier Press Release, Sept. 29. https://www.veritasgenetics.com/documents/VG-PGP-Announcement-Final.pdf [Google Scholar]
  188. 188. VeritasGenetics. 2016. VeritasGenetics launches $999 whole genome and sets new standard for genetic testing Press Release, Mar. 4. https://www.veritasgenetics.com/documents/veritas-mygenome-final3-mar-9-2016.pdf [Google Scholar]
  189. Voelkerding KV, Dames SA, Durtschi JD. 189.  2009. Next-generation sequencing: from basic research to diagnostics. Clin. Chem. 55:641–58 [Google Scholar]
  190. Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr., Kinzler KW. 190.  2013. Cancer genome landscapes. Science 339:1546–58 [Google Scholar]
  191. Wall JD, Tang LF, Zerbe B, Kvale MN, Kwok PY. 191.  et al. 2014. Estimating genotype error rates from high-coverage next-generation sequence data. Genome Res 24:1734–39 [Google Scholar]
  192. Wang T, Birsoy K, Hughes NW, Krupczak KM, Post Y. 192.  et al. 2015. Identification and characterization of essential genes in the human genome. Science 350:1096–101 [Google Scholar]
  193. Wang Z, Gerstein M, Snyder M. 193.  2009. RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 10:57–63 [Google Scholar]
  194. Watson CM, Crinnion LA, Berry IR, Harrison SM, Lascelles C. 194.  et al. 2016. Enhanced diagnostic yield in Meckel-Gruber and Joubert syndrome through exome sequencing supplemented with split-read mapping. BMC Med. Genet 171 [Google Scholar]
  195. Watson CT, Steinberg KM, Huddleston J, Warren RL, Malig M. 195.  et al. 2013. Complete haplotype sequence of the human immunoglobulin heavy-chain variable, diversity, and joining genes and characterization of allelic and copy-number variation. Am. J. Hum. Genet. 92:530–46 [Google Scholar]
  196. Wheeler DA, Srinivasan M, Egholm M, Shen Y, Chen L. 196.  et al. 2008. The complete genome of an individual by massively parallel DNA sequencing. Nature 452:872–76 [Google Scholar]
  197. Wheeler DA, Wang L. 197.  2013. From human genome to cancer genome: the first decade. Genome Res 23:1054–62 [Google Scholar]
  198. Worthey EA, Mayer AN, Syverson GD, Helbling D, Bonacci BB. 198.  et al. 2011. Making a definitive diagnosis: successful clinical application of whole exome sequencing in a child with intractable inflammatory bowel disease. Genet. Med. 13:255–62 [Google Scholar]
  199. Xiong HY, Alipanahi B, Lee LJ, Bretschneider H, Merico D. 199.  et al. 2015. The human splicing code reveals new insights into the genetic determinants of disease. Science 347:1254806 [Google Scholar]
  200. Xu B, Roos JL, Dexheimer P, Boone B, Plummer B. 200.  et al. 2011. Exome sequencing supports a de novo mutational paradigm for schizophrenia. Nat. Genet. 43:864–68 [Google Scholar]
  201. Yang Y, Muzny DM, Reid JG, Bainbridge MN, Willis A. 201.  et al. 2013. Clinical whole-exome sequencing for the diagnosis of Mendelian disorders. N. Engl. J. Med. 369:1502–11 [Google Scholar]
  202. Yu G, Yao W, Gumireddy K, Li A, Wang J. 202.  et al. 2014. Pseudogene PTENP1 functions as a competing endogenous RNA to suppress clear-cell renal cell carcinoma progression. Mol. Cancer Ther. 13:3086–97 [Google Scholar]
  203. Zarrei M, MacDonald JR, Merico D, Scherer SW. 203.  2015. A copy number variation map of the human genome. Nat. Rev. Genet. 16:172–83 [Google Scholar]
  204. Zeng T, Dong ZF, Liu SJ, Wan RP, Tang LJ. 204.  et al. 2014. A novel variant in the 3′ UTR of human SCN1A gene from a patient with Dravet syndrome decreases mRNA stability mediated by GAPDH's binding. Hum. Genet. 133:801–11 [Google Scholar]
  205. Zhan T, Boutros M. 205.  2016. Towards a compendium of essential genes—from model organisms to synthetic lethality in cancer cells. Crit. Rev. Biochem. Mol. Biol. 51:74–85 [Google Scholar]
  206. Zhang J, Walsh MF, Wu G, Edmonson MN, Gruber TA. 206.  et al. 2015. Germline mutations in predisposition genes in pediatric cancer. N. Engl. J. Med. 373:2336–46 [Google Scholar]
  207. Zhang X, Weissman SM, Newburger PE. 207.  2014. Long intergenic non-coding RNA HOTAIRM1 regulates cell cycle progression during myeloid maturation in NB4 human promyelocytic leukemia cells. RNA Biol 11:777–87 [Google Scholar]
  208. Zhou J, Troyanskaya OG. 208.  2015. Predicting effects of noncoding variants with deep learning-based sequence model. Nat. Methods 12:931–34 [Google Scholar]
  209. Zook JM, Catoe D, McDaniel J, Vang L, Spies N. 209.  et al. 2016. Extensive sequencing of seven human genomes to characterize benchmark reference materials. Sci. Data 3:160025 [Google Scholar]
  210. Zook JM, Chapman B, Wang J, Mittelman D, Hofmann O. 210.  et al. 2014. Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls. Nat. Biotechnol. 32:246–51 [Google Scholar]
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