1932
0
  1. Home
  2. A-Z Publications
  3. Annual Review of Genomics and Human Genetics
  4. Volume 22, 2021
  5. Article

Annual Review of Genomics and Human Genetics

Volume 22, 2021

The Need for a Human Pangenome Reference Sequence

Abstract

The reference human genome sequence is inarguably the most important and widely used resource in the fields of human genetics and genomics. It has transformed the conduct of biomedical sciences and brought invaluable benefits to the understanding and improvement of human health. However, the commonly used reference sequence has profound limitations, because across much of its span, it represents the sequence of just one human haplotype. This single, monoploid reference structure presents a critical barrier to representing the broad genomic diversity in the human population. In this review, we discuss the modernization of the reference human genome sequence to a more complete reference of human genomic diversity, known as a human pangenome.

Keyword(s): clinical genomics, diversity, Human Genome Project, pangenome
Loading

Article metrics loading...

/content/journals/10.1146/annurev-genom-120120-081921
2021-08-31
2024-04-16
Loading full text...

Full text loading...

/deliver/fulltext/genom/22/1/annurev-genom-120120-081921.html?itemId=/content/journals/10.1146/annurev-genom-120120-081921&mimeType=html&fmt=ahah

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 2012. An integrated map of genetic variation from 1,092 human genomes. Nature 491:56–65
     [Google Scholar]
  3. 3. 
    1000 Genomes Proj. Consort 2015. A global reference for human genetic variation. Nature 526:68–74
     [Google Scholar]
  4. 4. 
    Abe M, Ishikawa O, Miyachi Y. 1998. Lupoid sycosis successfully treated with minocycline. Br. J. Dermatol. 138:199–200
     [Google Scholar]
  5. 5. 
    Abel HJ, Larson DE, Regier AA, Chiang C, Das I et al. 2020. Mapping and characterization of structural variation in 17,795 human genomes. Nature 583:83–89
     [Google Scholar]
  6. 6. 
    Abul-Husn NS, Kenny EE 2019. Personalized medicine and the power of electronic health records. Cell 177:58–69
     [Google Scholar]
  7. 7. 
    After Havasupai litigation, Native Americans wary of genetic research; 2010. Am. J. Med. Genet. A 152A: ix:
     [Google Scholar]
  8. 8. 
    Alkan C, Coe BP, Eichler EE. 2011. Genome structural variation discovery and genotyping. Nat. Rev. Genet. 12:363–76
     [Google Scholar]
  9. 9. 
    Amendola LM, Berg JS, Horowitz CR, Angelo F, Bensen JT et al. 2018. The Clinical Sequencing Evidence-Generating Research Consortium: integrating genomic sequencing in diverse and medically underserved populations. Am. J. Hum. Genet. 103:319–27
     [Google Scholar]
  10. 10. 
    Audano PA, Sulovari A, Graves-Lindsay TA, Cantsilieris S, Sorensen M et al. 2019. Characterizing the major structural variant alleles of the human genome. Cell 176:663–75.e19
     [Google Scholar]
  11. 11. 
    Belbin GM, Odgis J, Sorokin EP, Yee M-C, Kohli S et al. 2017. Genetic identification of a common collagen disease in Puerto Ricans via identity-by-descent mapping in a health system. eLife 6:e25060
     [Google Scholar]
  12. 12. 
    Belton J-M, McCord RP, Gibcus JH, Naumova N, Zhan Y, Dekker J. 2012. Hi-C: a comprehensive technique to capture the conformation of genomes. Methods 58:268–76
     [Google Scholar]
  13. 13. 
    Bentley AR, Callier SL, Rotimi CN. 2020. Evaluating the promise of inclusion of African ancestry populations in genomics. npj Genom. Med. 5:5
     [Google Scholar]
  14. 14. 
    Bergström A, McCarthy SA, Hui R, Almarri MA, Ayub Q et al. 2020. Insights into human genetic variation and population history from 929 diverse genomes. Science 367:eaay5012
     [Google Scholar]
  15. 15. 
    Besenbacher S, Liu S, Izarzugaza JMG, Grove J, Belling K et al. 2015. Novel variation and de novo mutation rates in population-wide de novo assembled Danish trios. Nat. Commun. 6:5969
     [Google Scholar]
  16. 16. 
    Beskow LM. 2016. Lessons from HeLa cells: the ethics and policy of biospecimens. Annu. Rev. Genom. Hum. Genet. 17:395–417
     [Google Scholar]
  17. 17. 
    Bocklandt S, Hastie A, Cao H. 2019. Bionano genome mapping: high-throughput, ultra-long molecule genome analysis system for precision genome assembly and haploid-resolved structural variation discovery. Adv. Exp. Med. Biol. 1129:97–118
     [Google Scholar]
  18. 18. 
    Bradbury KE, Murphy N, Key TJ. 2020. Diet and colorectal cancer in UK Biobank: a prospective study. Int. J. Epidemiol. 49:246–58
     [Google Scholar]
  19. 19. 
    Brandt DYC, Aguiar VRC, Bitarello BD, Nunes K, Goudet J, Meyer D. 2015. Mapping bias overestimates reference allele frequencies at the HLA genes in the 1000 Genomes Project phase I data. G3 5:931–41
     [Google Scholar]
  20. 20. 
    Buenrostro JD, Wu B, Chang HY, Greenleaf WJ. 2015. ATAC-seq: a method for assaying chromatin accessibility genome-wide. Curr. Protoc. Mol. Biol. 109:21.29.1–9
     [Google Scholar]
  21. 21. 
    Burke W, Appelbaum P, Dame L, Marshall P, Press N et al. 2015. The translational potential of research on the ethical, legal, and social implications of genomics. Genet. Med. 17:12–20
     [Google Scholar]
  22. 22. 
    Bycroft C, Freeman C, Petkova D, Band G, Elliott LT et al. 2018. The UK Biobank resource with deep phenotyping and genomic data. Nature 562:203–9
     [Google Scholar]
  23. 23. 
    Bzikadze AV, Pevzner PA. 2020. Automated assembly of centromeres from ultra-long error-prone reads. Nat. Biotechnol. 38:1309–16
     [Google Scholar]
  24. 24. 
    Carlson CS, Matise TC, North KE, Haiman CA, Fesinmeyer MD et al. 2013. Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study. PLOS Biol 11:e1001661
     [Google Scholar]
  25. 25. 
    Cavalli-Sforza LL. 2005. The Human Genome Diversity Project: past, present and future. Nat. Rev. Genet. 6:333–40
     [Google Scholar]
  26. 26. 
    Chaisson MJP, Sanders AD, Zhao X, Malhotra A, Porubsky D et al. 2019. Multi-platform discovery of haplotype-resolved structural variation in human genomes. Nat. Commun. 10:1784
     [Google Scholar]
  27. 27. 
    Cheng H, Concepcion GT, Feng X, Zhang H, Li H. 2020. Haplotype-resolved de novo assembly with phased assembly graphs. arXiv:2008.01237 [q-bio.GN]
    [Google Scholar]
  28. 28. 
    Chiang C, Scott AJ, Davis JR, Tsang EK, Li X et al. 2017. The impact of structural variation on human gene expression. Nat. Genet. 49:692–99
     [Google Scholar]
  29. 29. 
    Choudhury A, Aron S, Botigué LR, Sengupta D, Botha G et al. 2020. High-depth African genomes inform human migration and health. Nature 586:741–48
     [Google Scholar]
  30. 30. 
    Church DM, Schneider VA, Graves T, Auger K, Cunningham F et al. 2011. Modernizing reference genome assemblies. PLOS Biol 9:e1001091
     [Google Scholar]
  31. 31. 
    Collins FS, Galas D. 1993. A new five-year plan for the U.S. Human Genome Project. Science 262:43–46
     [Google Scholar]
  32. 32. 
    Collins FS, Morgan M, Patrinos A. 2003. The Human Genome Project: lessons from large-scale biology. Science 300:286–90
     [Google Scholar]
  33. 33. 
    Collins FS, Varmus H. 2015. A new initiative on precision medicine. N. Engl. J. Med. 372:793–95
     [Google Scholar]
  34. 34. 
    Comput. Pan-Genomics Consort 2018. Computational pan-genomics: status, promises and challenges. Brief. Bioinform. 19:118–35
     [Google Scholar]
  35. 35. 
    Couzin-Frankel J. 2010. DNA returned to tribe, raising questions about consent. Science 328:558
     [Google Scholar]
  36. 36. 
    Dekker J, Belmont AS, Guttman M, Leshyk VO, Lis JT et al. 2017. The 4D nucleome project. Nature 549:219–26
     [Google Scholar]
  37. 37. 
    Devaney SA, Malerba L, Manson SM. 2020. The “All of Us” program and Indigenous peoples. N. Engl. J. Med. 383:1892–93
     [Google Scholar]
  38. 38. 
    Dilthey AT, Mentzer AJ, Carapito R, Cutland C, Cereb N et al. 2019. HLA*LA—HLA typing from linearly projected graph alignments. Bioinformatics 35:4394–96
     [Google Scholar]
  39. 39. 
    Dodson M, Williamson R. 1999. Indigenous peoples and the morality of the Human Genome Diversity Project. J. Med. Ethics 25:204–8
     [Google Scholar]
  40. 40. 
    Dolzhenko E, van Vugt JJFA, Shaw RJ, Bekritsky MA, van Blitterswijk M et al. 2017. Detection of long repeat expansions from PCR-free whole-genome sequence data. Genome Res 27:1895–903
     [Google Scholar]
  41. 41. 
    Duan Z, Qiao Y, Lu J, Lu H, Zhang W et al. 2019. HUPAN: a pan-genome analysis pipeline for human genomes. Genome Biol 20:149
     [Google Scholar]
  42. 42. 
    Dumitrescu L, Carty CL, Taylor K, Schumacher FR, Hindorff LA et al. 2011. Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study. PLOS Genet 7:e1002138
     [Google Scholar]
  43. 42a. 
    Ebert P, Audano PA, Zhu Q, Rodriguez-Martin B, Porubsky Det al 2021. Haplotype-resolved diverse human genomes and integrated analysis of structural variation. Science 372:eabf7117
     [Google Scholar]
  44. 43. 
    Ebler J, Clarke WE, Rausch T, Audano PA, Houwaart T et al. 2020. Pangenome-based genome inference. bioRxiv 2020.11.11.378133. https://doi.org/10.1101/2020.11.11.378133
    [Crossref] [Google Scholar]
  45. 44. 
    Eggertsson HP, Kristmundsdottir S, Beyter D, Jonsson H, Skuladottir A et al. 2019. GraphTyper2 enables population-scale genotyping of structural variation using pangenome graphs. Nat. Commun. 10:5402
     [Google Scholar]
  46. 45. 
    Eichler EE, Clark RA, She X. 2004. An assessment of the sequence gaps: unfinished business in a finished human genome. Nat. Rev. Genet. 5:345–54
     [Google Scholar]
  47. 46. 
    Eizenga JM, Novak AM, Sibbesen JA, Heumos S, Ghaffaari A et al. 2020. Pangenome graphs. Annu. Rev. Genom. Hum. Genet. 21:139–62
     [Google Scholar]
  48. 47. 
    ENCODE Proj. Consort 2004. The ENCODE (ENCyclopedia Of DNA Elements) Project. Science 306:636–40
     [Google Scholar]
  49. 48. 
    ENCODE Proj. Consort 2007. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 447:799–816
     [Google Scholar]
  50. 49. 
    ENCODE Proj. Consort 2012. An integrated encyclopedia of DNA elements in the human genome. Nature 489:57–74
     [Google Scholar]
  51. 50. 
    ENCODE Proj. Consortium, Moore JE, Purcaro MJ, Pratt HE, Epstein CB et al. 2020. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583:699–710
     [Google Scholar]
  52. 51. 
    Fiddes IT, Armstrong J, Diekhans M, Nachtweide S, Kronenberg ZN et al. 2018. Comparative Annotation Toolkit (CAT)—simultaneous clade and personal genome annotation. Genome Res 28:1029–38
     [Google Scholar]
  53. 52. 
    Garrison E, Sirén J, Novak AM, Hickey G, Eizenga JM et al. 2018. Variation graph toolkit improves read mapping by representing genetic variation in the reference. Nat. Biotechnol. 36:875–79
     [Google Scholar]
  54. 53. 
    Genome 10K Community Sci 2009. Genome 10K: a proposal to obtain whole-genome sequence for 10,000 vertebrate species. J. Hered. 100:659–74
     [Google Scholar]
  55. 54. 
    Gerstein MB, Rozowsky J, Yan K-K, Wang D, Cheng C et al. 2014. Comparative analysis of the transcriptome across distant species. Nature 512:445–48
     [Google Scholar]
  56. 55. 
    Gibbs RA. 2020. The Human Genome Project changed everything. Nat. Rev. Genet. 21:575–76
     [Google Scholar]
  57. 56. 
    Ginsburg GS, Horowitz CR, Orlando LA. 2019. What will it take to implement genomics in practice? Lessons from the IGNITE Network. Pers. Med. 16:259–61
     [Google Scholar]
  58. 57. 
    Giresi PG, Kim J, McDaniell RM, Iyer VR, Lieb JD. 2007. FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements) isolates active regulatory elements from human chromatin. Genome Res 17:877–85
     [Google Scholar]
  59. 58. 
    Glob. Alliance Genom. Health 2016. A federated ecosystem for sharing genomic, clinical data. Science 352:1278–80
     [Google Scholar]
  60. 59. 
    Greely HT. 2007. The uneasy ethical and legal underpinnings of large-scale genomic biobanks. Annu. Rev. Genom. Hum. Genet. 8:343–64
     [Google Scholar]
  61. 60. 
    Green ED, Watson JD, Collins FS. 2015. Human Genome Project: twenty-five years of big biology. Nature 526:29–31
     [Google Scholar]
  62. 61. 
    Green RE, Krause J, Briggs AW, Maricic T, Stenzel U et al. 2010. A draft sequence of the Neandertal genome. Science 328:710–22
     [Google Scholar]
  63. 62. 
    Groza C, Kwan T, Soranzo N, Pastinen T, Bourque G. 2020. Personalized and graph genomes reveal missing signal in epigenomic data. Genome Biol 21:124
     [Google Scholar]
  64. 63. 
    Guan D. 2020. Asset. Github https://github.com/dfguan/asset
    [Google Scholar]
  65. 64. 
    Günther T, Nettelblad C. 2019. The presence and impact of reference bias on population genomic studies of prehistoric human populations. PLOS Genet 15:e1008302
     [Google Scholar]
  66. 65. 
    Hehir-Kwa JY, Marschall T, Kloosterman WP, Francioli LC, Baaijens JA et al. 2016. A high-quality human reference panel reveals the complexity and distribution of genomic structural variants. Nat. Commun. 7:12989
     [Google Scholar]
  67. 66. 
    Henikoff JG, Belsky JA, Krassovsky K, MacAlpine DM, Henikoff S. 2011. Epigenome characterization at single base-pair resolution. PNAS 108:18318–23
     [Google Scholar]
  68. 67. 
    Hickey G, Heller D, Monlong J, Sibbesen JA, Sirén J et al. 2020. Genotyping structural variants in pangenome graphs using the vg toolkit. Genome Biol 21:35
     [Google Scholar]
  69. 68. 
    Hindorff LA, Bonham VL, Ohno-Machado L. 2018. Enhancing diversity to reduce health information disparities and build an evidence base for genomic medicine. Pers. Med. 15:403–12
     [Google Scholar]
  70. 69. 
    Ho JWK, Jung YL, Liu T, Alver BH, Lee S et al. 2014. Comparative analysis of metazoan chromatin organization. Nature 512:449–52
     [Google Scholar]
  71. 70. 
    Huddleston J, Chaisson MJP, Steinberg KM, Warren W, Hoekzema K et al. 2017. Discovery and genotyping of structural variation from long-read haploid genome sequence data. Genome Res 27:677–85
     [Google Scholar]
  72. 71. 
    ICGC/TCGA Pan-Cancer Anal. Whole Genomes Consort 2020. Pan-cancer analysis of whole genomes. Nature 578:82–93
     [Google Scholar]
  73. 72. 
    Int. HapMap Consort 2003. The International HapMap Project. Nature 426:789–96
     [Google Scholar]
  74. 73. 
    Int. HapMap Consort 2005. A haplotype map of the human genome. Nature 437:1299–320
     [Google Scholar]
  75. 74. 
    Int. HapMap Consort 2007. A second generation human haplotype map of over 3.1 million SNPs. Nature 449:851–61
     [Google Scholar]
  76. 75. 
    Int. Hum. Genome Seq. Consort 2004. Finishing the euchromatic sequence of the human genome. Nature 431:931–45
     [Google Scholar]
  77. 76. 
    Iqbal Z, Caccamo M, Turner I, Flicek P, McVean G. 2012. De novo assembly and genotyping of variants using colored de Bruijn graphs. Nat. Genet. 44:226–32
     [Google Scholar]
  78. 77. 
    Jäger M, Schubach M, Zemojtel T, Reinert K, Church DM, Robinson PN. 2016. Alternate-locus aware variant calling in whole genome sequencing. Genome Med 8:130
     [Google Scholar]
  79. 78. 
    Jain M, Koren S, Miga KH, Quick J, Rand AC et al. 2018. Nanopore sequencing and assembly of a human genome with ultra-long reads. Nat. Biotechnol. 36:338–45
     [Google Scholar]
  80. 79. 
    Jain M, Olsen HE, Turner DJ, Stoddart D, Bulazel KV et al. 2018. Linear assembly of a human centromere on the Y chromosome. Nat. Biotechnol. 36:321–23
     [Google Scholar]
  81. 80. 
    Kaye J, Meslin EM, Knoppers BM, Juengst ET, Deschênes M et al. 2012. ELSI 2.0 for genomics and society. Science 336:673–74
     [Google Scholar]
  82. 81. 
    Kim D, Lee J-Y, Yang J-S, Kim JW, Kim VN, Chang H 2020. The architecture of SARS-CoV-2 transcriptome. Cell 181:914–21.e10
     [Google Scholar]
  83. 82. 
    Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. 2019. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37:907–15
     [Google Scholar]
  84. 83. 
    Knoppers BM, Zawati MH, Kirby ES. 2012. Sampling populations of humans across the world: ELSI issues. Annu. Rev. Genom. Hum. Genet. 13:395–413
     [Google Scholar]
  85. 84. 
    Knowler WC, Williams RC, Pettitt DJ, Steinberg AG. 1988. Gm3;5,13,14 and type 2 diabetes mellitus: an association in American Indians with genetic admixture. Am. J. Hum. Genet. 43:520–26
     [Google Scholar]
  86. 85. 
    Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC et al. 2001. Initial sequencing and analysis of the human genome. Nature 409:860–921
     [Google Scholar]
  87. 86. 
    Li H, Feng X, Chu C. 2020. The design and construction of reference pangenome graphs with minigraph. Genome Biol. 21:265
     [Google Scholar]
  88. 87. 
    Li JZ, Absher DM, Tang H, Southwick AM, Casto AM et al. 2008. Worldwide human relationships inferred from genome-wide patterns of variation. Science 319:1100–4
     [Google Scholar]
  89. 88. 
    Li R, Li Y, Zheng H, Luo R, Zhu H et al. 2010. Building the sequence map of the human pan-genome. Nat. Biotechnol. 28:57–63
     [Google Scholar]
  90. 89. 
    Logsdon GA, Vollger MR, Eichler EE. 2020. Long-read human genome sequencing and its applications. Nat. Rev. Genet. 21:597–614
     [Google Scholar]
  91. 90. 
    Logsdon GA, Vollger MR, Hsieh P, Mao Y, Liskovykh MA et al. 2021. The structure, function and evolution of a complete human chromosome 8. Nature 593:101–7
     [Google Scholar]
  92. 91. 
    Loos RJF. 2020. 15 years of genome-wide association studies and no signs of slowing down. Nat. Commun. 11:5900
     [Google Scholar]
  93. 92. 
    Mallick S, Li H, Lipson M, Mathieson I, Gymrek M et al. 2016. The Simons Genome Diversity Project: 300 genomes from 142 diverse populations. Nature 538:201–6
     [Google Scholar]
  94. 93. 
    Maretty L, Jensen JM, Petersen B, Sibbesen JA, Liu S et al. 2017. Sequencing and de novo assembly of 150 genomes from Denmark as a population reference. Nature 548:87–91
     [Google Scholar]
  95. 94. 
    Martiniano R, Garrison E, Jones ER, Manica A, Durbin R. 2020. Removing reference bias and improving indel calling in ancient DNA data analysis by mapping to a sequence variation graph. Genome Biol 21:250
     [Google Scholar]
  96. 95. 
    Matise TC, Ambite JL, Buyske S, Carlson CS, Cole SA et al. 2011. The next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study. Am. J. Epidemiol. 174:849–59
     [Google Scholar]
  97. 96. 
    McEwen JE, Boyer JT, Sun KY, Rothenberg KH, Lockhart NC, Guyer MS. 2014. The Ethical, Legal, and Social Implications Program of the National Human Genome Research Institute: reflections on an ongoing experiment. Annu. Rev. Genom. Hum. Genet. 15:481–505
     [Google Scholar]
  98. 97. 
    Meyer M, Kircher M, Gansauge M-T, Li H, Racimo F et al. 2012. A high-coverage genome sequence from an archaic Denisovan individual. Science 338:222–26
     [Google Scholar]
  99. 98. 
    Miga KH, Koren S, Rhie A, Vollger MR, Gershman A et al. 2020. Telomere-to-telomere assembly of a complete human X chromosome. Nature 585:79–84
     [Google Scholar]
  100. 99. 
    Moodley K, Kleinsmidt A. 2020. Allegations of misuse of African DNA in the UK: Will data protection legislation in South Africa be sufficient to prevent a recurrence?. Dev. World Bioeth. https://doi.org/10.1111/dewb.12277
    [Crossref] [Google Scholar]
  101. 100. 
    Morales J, Welter D, Bowler EH, Cerezo M, Harris LW et al. 2018. A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog. Genome Biol 19:21
     [Google Scholar]
  102. 101. 
    Nagai A, Hirata M, Kamatani Y, Muto K, Matsuda K et al. 2017. Overview of the BioBank Japan Project: study design and profile. J. Epidemiol. 27:S2–8
     [Google Scholar]
  103. 102. 
    Nègre N, Brown CD, Ma L, Bristow CA, Miller SW et al. 2011. A cis-regulatory map of the Drosophila genome. Nature 471:527–31
     [Google Scholar]
  104. 103. 
    Nurk S, Walenz BP, Rhie A, Vollger MR, Logsdon GA et al. 2020. HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads. Genome Res 30:1291–305
     [Google Scholar]
  105. 104. 
    O'Connor BD, Yuen D, Chung V, Duncan AG, Liu XK et al. 2017. The Dockstore: enabling modular, community-focused sharing of Docker-based genomics tools and workflows. F1000Research 6:52
     [Google Scholar]
  106. 105. 
    Park PJ. 2009. ChIP-seq: advantages and challenges of a maturing technology. Nat. Rev. Genet. 10:669–80
     [Google Scholar]
  107. 106. 
    Paten B, Novak AM, Eizenga JM, Garrison E. 2017. Genome graphs and the evolution of genome inference. Genome Res 27:665–76
     [Google Scholar]
  108. 107. 
    Payne A, Holmes N, Rakyan V, Loose M. 2019. BulkVis: a graphical viewer for Oxford nanopore bulk FAST5 files. Bioinformatics 35:2193–98
     [Google Scholar]
  109. 108. 
    Petersen A. 2005. Securing our genetic health: engendering trust in UK Biobank. Sociol. Health Illn. 27:271–92
     [Google Scholar]
  110. 109. 
    Putnam NH, O'Connell BL, Stites JC, Rice BJ, Blanchette M et al. 2016. Chromosome-scale shotgun assembly using an in vitro method for long-range linkage. Genome Res 26:342–50
     [Google Scholar]
  111. 110. 
    Rakocevic G, Semenyuk V, Lee W-P, Spencer J, Browning J et al. 2019. Fast and accurate genomic analyses using genome graphs. Nat. Genet. 51:354–62
     [Google Scholar]
  112. 111. 
    Rautiainen M, Marschall T. 2020. GraphAligner: rapid and versatile sequence-to-graph alignment. Genome Biol 21:253
     [Google Scholar]
  113. 112. 
    Reardon J. 2009. Race to the Finish: Identity and Governance in an Age of Genomics Princeton, NJ: Princeton Univ. Press
  114. 113. 
    Rheinbay E, Nielsen MM, Abascal F, Wala JA, Shapira O et al. 2020. Analyses of non-coding somatic drivers in 2,658 cancer whole genomes. Nature 578:102–11
     [Google Scholar]
  115. 114. 
    Rhie A, Walenz BP, Koren S, Phillippy AM. 2020. Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies. Genome Biol 21:245
     [Google Scholar]
  116. 115. 
    Roadmap Epigenom. Consort., Kundaje A, Meuleman W, Ernst J, Bilenky M et al. 2015. Integrative analysis of 111 reference human epigenomes. Nature 518:317–30
     [Google Scholar]
  117. 116. 
    Rockwell DH, Yobs AR, Moore MB Jr. 1964. The Tuskegee Study of Untreated Syphilis: the 30th year of observation. Arch. Intern. Med. 114:792–98
     [Google Scholar]
  118. 117. 
    Rosen Y, Eizenga J, Paten B 2017. Modelling haplotypes with respect to reference cohort variation graphs. Bioinformatics 33:i118–23
     [Google Scholar]
  119. 118. 
    Rozenblatt-Rosen O, Stubbington MJT, Regev A, Teichmann SA. 2017. The Human Cell Atlas: from vision to reality. Nature 550:451–53
     [Google Scholar]
  120. 119. 
    Said MA, Verweij N, van der Harst P. 2018. Associations of combined genetic and lifestyle risks with incident cardiovascular disease and diabetes in the UK Biobank study. JAMA Cardiol 3:693–702
     [Google Scholar]
  121. 120. 
    Sankar PL, Parker LS. 2017. The Precision Medicine Initiative's All of Us Research Program: an agenda for research on its ethical, legal, and social issues. Genet. Med. 19:743–50
     [Google Scholar]
  122. 121. 
    Schneider VA, Graves-Lindsay T, Howe K, Bouk N, Chen H-C et al. 2017. Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly. Genome Res 27:849–64
     [Google Scholar]
  123. 122. 
    Schones DE, Cui K, Cuddapah S, Roh T-Y, Barski A et al. 2008. Dynamic regulation of nucleosome positioning in the human genome. Cell 132:887–98
     [Google Scholar]
  124. 123. 
    Scott CT, Caulfield T, Borgelt E, Illes J. 2012. Personal medicine—the new banking crisis. Nat. Biotechnol. 30:141–47
     [Google Scholar]
  125. 124. 
    Sedlazeck FJ, Lee H, Darby CA, Schatz MC. 2018. Piercing the dark matter: bioinformatics of long-range sequencing and mapping. Nat. Rev. Genet. 19:329–46
     [Google Scholar]
  126. 125. 
    Shafin K, Pesout T, Lorig-Roach R, Haukness M, Olsen HE et al. 2020. Nanopore sequencing and the Shasta toolkit enable efficient de novo assembly of eleven human genomes. Nat. Biotechnol. 38:1044–53
     [Google Scholar]
  127. 126. 
    Sherman RM, Forman J, Antonescu V, Puiu D, Daya M et al. 2019. Assembly of a pan-genome from deep sequencing of 910 humans of African descent. Nat. Genet. 51:30–35
     [Google Scholar]
  128. 127. 
    Sherman RM, Salzberg SL. 2020. Pan-genomics in the human genome era. Nat. Rev. Genet. 21:243–54
     [Google Scholar]
  129. 128. 
    Sherry ST, Ward MH, Kholodov M, Baker J, Phan L et al. 2001. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 29:308–11
     [Google Scholar]
  130. 129. 
    Skirton H, Goldsmith L, Jackson L, O'Connor A. 2012. Direct to consumer genetic testing: a systematic review of position statements, policies and recommendations. Clin. Genet. 82:210–18
     [Google Scholar]
  131. 130. 
    Song L, Crawford GE. 2010. DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. Cold Spring Harb. Protoc. 2010.db.prot5384
     [Google Scholar]
  132. 131. 
    Sperber NR, Carpenter JS, Cavallari LH, Damschroder LJ, Cooper-DeHoff RM et al. 2017. Challenges and strategies for implementing genomic services in diverse settings: experiences from the Implementing GeNomics In pracTicE (IGNITE) network. BMC Med. Genom. 10:35
     [Google Scholar]
  133. 132. 
    Stark Z, Dolman L, Manolio TA, Ozenberger B, Hill SL et al. 2019. Integrating genomics into healthcare: a global responsibility. Am. J. Hum. Genet. 104:13–20
     [Google Scholar]
  134. 133. 
    Sudmant PH, Rausch T, Gardner EJ, Handsaker RE, Abyzov A et al. 2015. An integrated map of structural variation in 2,504 human genomes. Nature 526:75–81
     [Google Scholar]
  135. 134. 
    Telenti A, Pierce LCT, Biggs WH, di Iulio J, Wong EHM et al. 2016. Deep sequencing of 10,000 human genomes. PNAS 113:11901–6
     [Google Scholar]
  136. 135. 
    Toh C, Brody JP. 2020. Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation. Hum. Genom. 14:36
     [Google Scholar]
  137. 136. 
    Tutton R, Kaye J, Hoeyer K. 2004. Governing UK Biobank: the importance of ensuring public trust. Trends Biotechnol 22:284–85
     [Google Scholar]
  138. 137. 
    Venter JC, Adams MD, Myers EW, Li PW, Mural RJ et al. 2001. The sequence of the human genome. Science 291:1304–51
     [Google Scholar]
  139. 138. 
    Vernikos G, Medini D, Riley DR, Tettelin H. 2015. Ten years of pan-genome analyses. Curr. Opin. Microbiol. 23:148–54
     [Google Scholar]
  140. 139. 
    Wainberg M, Mahajan A, Kundaje A, McCarthy MI, Ingelsson E et al. 2019. Homogeneity in the association of body mass index with type 2 diabetes across the UK Biobank: a Mendelian randomization study. PLOS Med 16:e1002982
     [Google Scholar]
  141. 140. 
    Wang Z, Gerstein M, Snyder M. 2009. RNA-Seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 10:57–63
     [Google Scholar]
  142. 141. 
    Wenger AM, Peluso P, Rowell WJ, Chang P-C, Hall RJ et al. 2019. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat. Biotechnol. 37:1155–62
     [Google Scholar]
  143. 142. 
    Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018
     [Google Scholar]
  144. 143. 
    Wong KHY, Ma W, Wei C-Y, Yeh E-C, Lin W-J et al. 2020. Towards a reference genome that captures global genetic diversity. Nat. Commun. 11:5482
     [Google Scholar]
  145. 144. 
    Yu Y, Wei C. 2020. A powerful HUPAN on a pan-genome study: significance and perspectives. Cancer Biol. Med. 17:1–5
     [Google Scholar]
  146. 145. 
    Yue F, Cheng Y, Breschi A, Vierstra J, Wu W et al. 2014. A comparative encyclopedia of DNA elements in the mouse genome. Nature 515:355–64
     [Google Scholar]
  147. 146. 
    Zeberg H, Pääbo S. 2020. The major genetic risk factor for severe COVID-19 is inherited from Neanderthals. Nature 587:610–12
     [Google Scholar]
  148. 147. 
    Zhou P, Yang X-L, Wang X-G, Hu B, Zhang L et al. 2020. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 579:270–73
     [Google Scholar]
/content/journals/10.1146/annurev-genom-120120-081921
Loading
The Need for a Human Pangenome Reference Sequence
Annual Review of Genomics and Human Genetics 22, 81 (2021); https://doi.org/10.1146/annurev-genom-120120-081921
/content/journals/10.1146/annurev-genom-120120-081921
/content/journals/10.1146/annurev-genom-120120-081921
Loading

Data & Media loading...

  • Article Type: Review Article

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error