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Rapid, raw-read reference and identification (R4IDs): A flexible platform for rapid generic species ID using long-read sequencing technology

View ORCID ProfileJoe Parker, View ORCID ProfileAndrew Helmstetter, James Crowe, John Iacona, Dion Devey, View ORCID ProfileAlexander S. T. Papadopulos
doi: https://doi.org/10.1101/281048
Joe Parker
1The Jodrell Laboratory, Royal Botanic Gardens, Kew, TW9 3AA UK
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  • For correspondence: a.papadopulos@bangor.ac.uk joe.parker@kew.org
Andrew Helmstetter
2CNRS Montpellier, France
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James Crowe
1The Jodrell Laboratory, Royal Botanic Gardens, Kew, TW9 3AA UK
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John Iacona
1The Jodrell Laboratory, Royal Botanic Gardens, Kew, TW9 3AA UK
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Dion Devey
1The Jodrell Laboratory, Royal Botanic Gardens, Kew, TW9 3AA UK
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Alexander S. T. Papadopulos
3Molecular Ecology and Fisheries GeneticsLaboratory, Environment Centre Wales, School of Biological Sciences, University of Bangor, Wales
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  • ORCID record for Alexander S. T. Papadopulos
  • For correspondence: a.papadopulos@bangor.ac.uk joe.parker@kew.org
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Abstract

The versatility of the current DNA sequencing platforms and the development of portable, nanopore sequencers means that it has never been easier to collect genetic data for unknown sample ID. DNA barcoding and meta-barcoding have become increasingly popular and barcode databases continue to grow at an impressive rate. However, the number of canonical genome assemblies (reference or draft) that are publically available is relatively tiny, hindering the more widespread use of genome scale DNA sequencing technology for accurate species identification and discovery. Here, we show that rapid raw-read reference datasets, or R4IDs for short, generated in a matter of hours on the Oxford Nanopore MinION, can bridge this gap and accelerate the generation of useable reference sequence data. By exploiting the long read length of this technology, shotgun genomic sequencing of a small portion of an organism’s genome can act as a suitable reference database despite the low sequencing coverage. These R4IDs can then be used for accurate species identification with minimal amounts of re-sequencing effort (1000s of reads). We demonstrated the capabilities of this approach with six vascular plant species for which we created R4IDs in the laboratory and then re-sequenced, live at the Kew Science Festival 2016. We further validated our method using simulations to determine the broader applicability of the approach. Our data analysis pipeline has been made available as a Dockerised workflow for simple, scalable deployment for a range of uses.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 13, 2018.
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Rapid, raw-read reference and identification (R4IDs): A flexible platform for rapid generic species ID using long-read sequencing technology
Joe Parker, Andrew Helmstetter, James Crowe, John Iacona, Dion Devey, Alexander S. T. Papadopulos
bioRxiv 281048; doi: https://doi.org/10.1101/281048
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Rapid, raw-read reference and identification (R4IDs): A flexible platform for rapid generic species ID using long-read sequencing technology
Joe Parker, Andrew Helmstetter, James Crowe, John Iacona, Dion Devey, Alexander S. T. Papadopulos
bioRxiv 281048; doi: https://doi.org/10.1101/281048

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