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利用低覆盖度长读测序鉴定单个根结线虫。

Identification of individual root-knot nematodes using low coverage long-read sequencing.

机构信息

Department of Biological and Marine Sciences, Energy and Environment Institute, University of Hull, Hull, United Kingdom.

Department of Biology and York Biomedical Research Institute, University of York, York, United Kingdom.

出版信息

PLoS One. 2021 Dec 1;16(12):e0253248. doi: 10.1371/journal.pone.0253248. eCollection 2021.

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.

摘要

根结线虫(RKN;属 Meloidogyne)是一种具有广泛食性的植物病原物,对全球农业学家具有重要的经济意义。这些物种体型小、种类繁多,准确的分类鉴定具有挑战性。许多最重要的作物害虫通过简单的遗传标记基因座进行分析,因为它们可能是杂种起源的多倍体。在这里,我们采用低覆盖度、长读长基因组测序方法来描述单个根结线虫。我们展示了从单个幼虫和未成熟雌虫的低输入 DNA 制备 Oxford Nanopore Technologies Flongle 测序文库的方法,每个流动池可最多混合 12 个样本。使用 Kraken 2(一种基于 k-mer 的分类分配工具)进行的分类鉴定可可靠地将单个线虫鉴定到种水平,即使在非常密切相关的 Meloidogyne incognita 组内也是如此。我们的方法形成了一种强大、低成本且可扩展的准确 RKN 物种诊断方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/620a/8635404/4e41f8f4479c/pone.0253248.g001.jpg

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