Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Mycology and Nematology Genetic Diversity and Biology Laboratory » Research » Research Project #450380

Research Project: DNA Barcoding of Downy Mildew Specimens on Flowering Plants Present in the U.S. National Fungus Collection

Location: Mycology and Nematology Genetic Diversity and Biology Laboratory

Project Number: 8042-22000-323-016-I
Project Type: Interagency Reimbursable Agreement

Start Date: Aug 1, 2026
End Date: Jul 31, 2027

Objective:
This project aims to enhance pest identification technologies by generating high-quality DNA barcode sequences for downy mildew species (Peronosporaceae, Oomycota) affecting the floral and nursery crops in the U.S., using historical specimens from the U.S. National Fungus Collection (BPI). This project addresses long-standing taxonomic challenges caused by outdated morphological classifications, taxonomic synonymization errors, and lack of molecular data for many downy mildew species. Downy mildews cause significant economic losses in the floriculture industry, and accurate identification is critical for quarantine and diagnostic efforts.

Approach:
ARS will identify and select key specimens from the genera Hyaloperonospora, Peronospora, and Plasmopara present at the BPI’s collection, optimize DNA extraction protocols for degraded fungarium samples, test PCR reagents and procedure conditions to amplify barcode regions, generate and analyze DNA sequences to reconstruct phylogenetic relationships and deposit data in public repositories. This effort will improve the speed and precision of pathogen identification, supporting the development of diagnostic tools. The primary beneficiaries include USDA-APHIS, plant pathologists, and diagnostic laboratories nationwide. The outcomes will also contribute to biodiversity monitoring, biosecurity, and risk mitigation for the floral and nursery crops industry. ARS plans to release the data generated to APHIS PPQ personnel and public data repositories.