Skip to main content
SpringerLink
Log in

Rapid High-Resolution Typing of Class I HLA Genes by Nanopore Sequencing

  • Protocol
  • First Online:
Bioinformatics for Cancer Immunotherapy

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2120))

Abstract

Nanopore sequencing, enabled initially by the MinION device from Oxford Nanopore Technologies (ONT), is the only technology that offers portable, single-molecule sequencing and ultralong reads. The technology is ideal for the typing of human leukocyte antigen (HLA) genes for transplantation and cancer immunotherapy. However, such applications have been hindered by the high error rate of nanopore sequencing reads. We developed the workflow and bioinformatic pipeline, Athlon (accurate typing of human leukocyte antigen by Oxford Nanopore), to perform high-resolution typing of Class I HLA genes by nanopore sequencing. The method features a novel algorithm for candidate allele selection, followed by error correction through consensus building. Here, we describe the protocol of using Athlon packaged in a VirtualBox image for the above application.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Edgerly CH, Weimer ET (2018) The past, present, and future of HLA typing in transplantation. Methods Mol Biol 1802:1–10. https://doi.org/10.1007/978-1-4939-8546-3_1

    Article  CAS  PubMed  Google Scholar 

  2. Chen F, Zou Z, Du J, Su S, Shao J, Meng F, Yang J, Xu Q, Ding N, Yang Y, Liu Q, Wang Q, Sun Z, Zhou S, Du S, Wei J, Liu B (2019) Neoantigen identification strategies enable personalized immunotherapy in refractory solid tumors. J Clin Invest 130:2056–2070. https://doi.org/10.1172/jci99538

    Article  Google Scholar 

  3. Chowell D, Morris LGT, Grigg CM, Weber JK, Samstein RM, Makarov V, Kuo F, Kendall SM, Requena D, Riaz N, Greenbaum B, Carroll J, Garon E, Hyman DM, Zehir A, Solit D, Berger M, Zhou R, Rizvi NA, Chan TA (2018) Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 359(6375):582–587. https://doi.org/10.1126/science.aao4572

    Article  CAS  PubMed  Google Scholar 

  4. Allen ES, Yang B, Garrett J, Ball ED, Maiers M, Morris GP (2018) Improved accuracy of clinical HLA genotyping by next-generation DNA sequencing affects unrelated donor search results for hematopoietic stem cell transplantation. Hum Immunol 79(12):848–854. https://doi.org/10.1016/j.humimm.2018.10.008

    Article  CAS  PubMed  Google Scholar 

  5. Barone JC, Saito K, Beutner K, Campo M, Dong W, Goswami CP, Johnson ES, Wang ZX, Hsu S (2015) HLA-genotyping of clinical specimens using ion torrent-based NGS. Hum Immunol 76(12):903–909. https://doi.org/10.1016/j.humimm.2015.09.014

    Article  CAS  PubMed  Google Scholar 

  6. Mayor NP, Robinson J, McWhinnie AJ, Ranade S, Eng K, Midwinter W, Bultitude WP, Chin CS, Bowman B, Marks P, Braund H, Madrigal JA, Latham K, Marsh SG (2015) HLA typing for the next generation. PLoS One 10(5):e0127153. https://doi.org/10.1371/journal.pone.0127153

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Mayor NP, Hayhurst JD, Turner TR, Szydlo RM, Shaw BE, Bultitude WP, Sayno J, Tavarozzi F, Latham K, Anthias C, Braund H, Danby R, Perry JR, Wilson MC, Bloor AJ, Clark A, MacKinnon S, Marks DI, Pagliuca A, Potter MN, Russell NH, Thomason KJ, Madrigal JA, Marsh SGE (2018) Better HLA matching as revealed only by next generation sequencing technology results in superior overall survival post-allogeneic haematopoietic cell transplantation with unrelated donors. Biol Blood Marrow Transplant 24(3):S46

    Article  Google Scholar 

  8. Turner TR, Hayhurst JD, Hayward DR, Bultitude WP, Barker DJ, Robinson J, Madrigal JA, Mayor NP, Marsh SGE (2018) Single molecule real-time DNA sequencing of HLA genes at ultra-high resolution from 126 international HLA and immunogenetics workshop cell lines. Hla 91(2):88–101. https://doi.org/10.1111/tan.13184

    Article  CAS  PubMed  Google Scholar 

  9. Lan JH, Yin Y, Reed EF, Moua K, Thomas K, Zhang Q (2015) Impact of three Illumina library construction methods on GC bias and HLA genotype calling. Hum Immunol 76(2-3):166–175. https://doi.org/10.1016/j.humimm.2014.12.016

    Article  CAS  PubMed  Google Scholar 

  10. Leggett RM, Clark MD (2017) A world of opportunities with nanopore sequencing. J Exp Bot 68(20):5419–5429. https://doi.org/10.1093/jxb/erx289

    Article  CAS  PubMed  Google Scholar 

  11. Rang FJ, Kloosterman WP, de Ridder J (2018) From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy. Genome Biol 19(1):90. https://doi.org/10.1186/s13059-018-1462-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Liu C, Xiao F, Hoisington-Lopez J, Lang K, Quenzel P, Duffy B, Mitra RD (2018) Accurate typing of human leukocyte antigen class I genes by Oxford nanopore sequencing. J Mol Diagn 20(4):428–435. https://doi.org/10.1016/j.jmoldx.2018.02.006

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Chaisson MJ, Tesler G (2012) Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory. BMC Bioinformatics 13:238. https://doi.org/10.1186/1471-2105-13-238

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Quinlan AR, Hall IM (2010) BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26(6):841–842. https://doi.org/10.1093/bioinformatics/btq033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Garrison E, Marth G (2012) Haplotype-based variant detection from short-read sequencing. arXiv. doi:arXiv:1207.3907

    Google Scholar 

  16. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL (2009) BLAST+: architecture and applications. BMC Bioinformatics 10:421. https://doi.org/10.1186/1471-2105-10-421

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Robinson JT, Thorvaldsdottir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP (2011) Integrative genomics viewer. Nat Biotechnol 29:24–26. https://doi.org/10.1038/nbt.1754

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Thorvaldsdottir H, Robinson JT, Mesirov JP (2013) Integrative genomics viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14(2):178–192. https://doi.org/10.1093/bib/bbs017

    Article  CAS  PubMed  Google Scholar 

  19. Hosomichi K, Jinam TA, Mitsunaga S, Nakaoka H, Inoue I (2013) Phase-defined complete sequencing of the HLA genes by next-generation sequencing. BMC Genomics 14:355. https://doi.org/10.1186/1471-2164-14-355

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Robinson J, Guethlein LA, Cereb N, Yang SY, Norman PJ, Marsh SGE, Parham P (2017) Distinguishing functional polymorphism from random variation in the sequences of >10,000 HLA-A, -B and -C alleles. PLoS Genet 13(6):e1006862. https://doi.org/10.1371/journal.pgen.1006862

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Klasberg S, Lang K, Gunther M, Schober G, Massalski C, Schmidt AH, Lange V, Schofl G (2019) Patterns of non-ARD variation in more than 300 full-length HLA-DPB1 alleles. Hum Immunol 80(1):44–52. https://doi.org/10.1016/j.humimm.2018.05.006

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA

    Chang Liu

  2. PlatformSTL, St. Louis, MO, USA

    Rick Berry

Authors
  1. Chang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rick Berry
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chang Liu .

Editor information

Editors and Affiliations

  1. Mainz, Germany

    Sebastian Boegel

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Liu, C., Berry, R. (2020). Rapid High-Resolution Typing of Class I HLA Genes by Nanopore Sequencing. In: Boegel, S. (eds) Bioinformatics for Cancer Immunotherapy. Methods in Molecular Biology, vol 2120. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0327-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-0327-7_6

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0326-0

  • Online ISBN: 978-1-0716-0327-7

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation