Open AccessIdentification of individual root-knot nematodes using low coverage long-read sequencing
Author(s) -
Graham S. Sellers,
Daniel Jeffares,
Bex Lawson,
Thomas Prior,
David H. Lunt
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0253248
Subject(s) - biology , nanopore sequencing , dna sequencing , meloidogyne incognita , phylogenetic tree , root knot nematode , identification (biology) , genome , computational biology , evolutionary biology , genetics , botany , dna , nematode , ecology , gene
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.