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Reply to ‘Errors in long-read assemblies can critically affect protein prediction’

Nature Biotechnology volume 37, pages 127–128 (2019)Cite this article

Koren et al. reply — Warr and Watson1 describe the impact of insertion/deletion (indel) errors in long-read assemblies that confound protein sequence prediction as a result of erroneous frameshifts. Although this problem is well known in the sequencing community and has affected numerous sequencing platforms2, the authors are concerned that naive use of these techniques may contribute to a degradation in the quality of sequences in GenBank. We share their concern. However, we believe that a more nuanced discussion of the issue is warranted because rapidly evolving sequencing and bioinformatics methods are driving ever increasing read lengths and base call accuracy. In particular, Oxford Nanopore Technology (ONT) has undergone rapid technological improvements over the past two years.

Warr and Watson1 incorrectly focus on a single assembly from our previous paper3, using the now obsolete ONT-supplied cloud base caller, which used an early recurrent neural network (RNN) algorithm. In that study, we demonstrated that assembly quality identities are substantially affected by the choice of base caller2. We used Scrappie, an improved RNN base caller developed by ONT that incorporates dwell time information to improve the assembly quality of chromosome 20 (see the first table in ref. 3). This approach improves homopolymer length calls, thereby reducing a major source of error.

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Fig. 1: Probability of a perfect 1-kilobase-pair sequence.

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Author notes

  1. These authors contributed equally: Sergey Koren, Adam M. Phillippy.

Authors and Affiliations

  1. Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, USA

    Sergey Koren & Adam M. Phillippy

  2. Ontario Institute for Cancer Research, Toronto, Ontario, Canada

    Jared T. Simpson

  3. Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Birmingham, UK

    Nicholas J. Loman

  4. School of Life Sciences, University of Nottingham, Nottingham, UK

    Matthew Loose

Authors
  1. Sergey Koren
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  2. Adam M. Phillippy
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  3. Jared T. Simpson
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  4. Nicholas J. Loman
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Corresponding authors

Correspondence to Nicholas J. Loman or Matthew Loose.

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Competing interests

M.L., N.L. and J.T.S. were members of the MinION Access Program (MAP) and have received free-of-charge flow cells and kits for nanopore sequencing for this and other studies, and travel and accommodation expenses to speak at Oxford Nanopore Technologies conferences. N.J.L. has received an honorarium to speak at an Oxford Nanopore company meeting. S.K. has received travel and accommodation expenses to speak at Oxford Nanopore Technologies conferences. J.T.S. and M.L. have received research funding from Oxford Nanopore Technologies.

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Koren, S., Phillippy, A.M., Simpson, J.T. et al. Reply to ‘Errors in long-read assemblies can critically affect protein prediction’. Nat Biotechnol 37, 127–128 (2019). https://doi.org/10.1038/s41587-018-0005-y

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