Sellers, Graham S., Jeffares, Daniel C. orcid.org/0000-0001-7320-0706, Lawson, Bex et al. (2 more authors) (2021) Identification of individual root-knot nematodes using low coverage long-read sequencing. PLOS one. e0253248. ISSN 1932-6203
Abstract
Root-knot nematodes (RKN; genus Meloidogyne) are polyphagous plant pathogens of great economic importance to agriculturalists globally. These species are small, diverse, and can be challenging for accurate taxonomic identification. Many of the most important crop pests confound analysis with simple genetic marker loci as they are polyploids of likely hybrid origin. Here we take a low-coverage, long-read genome sequencing approach to characterisation of individual root-knot nematodes. We demonstrate library preparation for Oxford Nanopore Technologies Flongle sequencing of low input DNA from individual juveniles and immature females, multiplexing up to twelve samples per flow cell. Taxonomic identification with Kraken 2 (a k-mer-based taxonomic assignment tool) is shown to reliably identify individual nematodes to species level, even within the very closely related Meloidogyne incognita group. Our approach forms a robust, low-cost, and scalable method for accurate RKN species diagnostics.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Publisher Copyright: © 2021 Sellers et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Biology (York) |
Depositing User: | Pure (York) |
Date Deposited: | 10 Dec 2021 16:20 |
Last Modified: | 23 Jan 2025 00:27 |
Published Version: | https://doi.org/10.1371/journal.pone.0253248 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1371/journal.pone.0253248 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:181462 |