Profiling Walnut Fungal Pathobiome Associated with Walnut Dieback Using Community-Targeted DNA Metabarcoding

Area of Science:

• Plant Pathology
• Mycology
• Molecular Biology

Background:

• Walnut dieback presents complex symptoms, challenging the single pathogen-disease model.
• Accurate identification of the fungal pathobiome is essential for effective disease management.
• DNA metabarcoding offers a powerful tool for comprehensive fungal community analysis.

Purpose of the Study:

• Evaluate primer pair performance for fungal DNA amplification in walnuts.
• Assess taxonomic resolution and abundance estimation using different DNA metabarcoding pipelines.
• Determine the optimal bioinformatic pipeline for studying the walnut fungal pathobiome.

Main Methods:

• Tested five primer pairs targeting the ITS region using mock communities.
• Analyzed DNA metabarcoding data with phylogenetic trees for taxonomic resolution.
• Applied optimized pipelines to DNA from symptomatic walnut husks and twigs.
• Compared ITS1, ITS, and ITS2 regions for their efficacy as fungal barcodes.

Main Results:

• The ITS2 region demonstrated superior sensitivity and compositional similarity compared to ITS1 and ITS.
• The ITS3/ITS4_KYO1 primer set provided broader coverage of fungal diversity than other ITS2 primers.
• Extraction steps impacted taxonomic resolution variably depending on the primer pair.
• The Kyo set without ITS2 extraction yielded the most accurate fungal diversity assessment.

Conclusions:

• The ITS2 region is a more effective barcode for fungal identification in walnut dieback studies.
• The ITS3/ITS4_KYO1 primer set is recommended for comprehensive fungal diversity analysis.
• The optimal DNA metabarcoding pipeline involves the Kyo set without an ITS2 extraction step for accurate walnut pathobiome characterization.