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

Area of Science:

• Genomics and Bioinformatics
• Plant Pathology
• Agricultural Entomology

Background:

• Root-knot nematodes (RKN; genus Meloidogyne) are significant global agricultural pests.
• Accurate taxonomic identification of RKN species is challenging due to their diversity and polyploid nature.
• Existing genetic markers often fail for complex RKN populations.

Purpose of the Study:

• To develop a robust, low-cost, and scalable method for accurate RKN species identification.
• To characterize individual root-knot nematodes using a novel genomic sequencing approach.

Main Methods:

• Utilized low-coverage, long-read genome sequencing with Oxford Nanopore Technologies Flongle.
• Developed library preparation for low DNA input from individual juvenile and immature female nematodes.
• Employed multiplexing of up to twelve samples per flow cell and Kraken 2 for taxonomic assignment.

Main Results:

• Successfully sequenced and identified individual RKNs to the species level.
• Demonstrated reliable species identification even within the complex Meloidogyne incognita group.
• Validated a scalable method for RKN diagnostics using multiplexed sequencing.

Conclusions:

• The developed genomic sequencing approach provides accurate and efficient RKN species diagnostics.
• This method offers a cost-effective and scalable solution for agricultural pest management.
• Enables precise identification crucial for targeted control strategies against economically important nematodes.