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ARS Home » Pacific West Area » Salinas, California » Crop Improvement and Protection Research » Research » Publications at this Location » Publication #388404
Research Project: Management of Pathogens for Strawberry and Vegetable Production Systems

Location: Crop Improvement and Protection Research

Title: A step towards validation of high-throughput sequencing for the identification of plant pathogenic oomycetes

Author
item ESPINDOLA, ANDRES - Oklahoma State University
item CARDWELL, KITTY - Oklahoma State University
item Martin, Frank
item HOYT, PETER - Oklahoma State University
item MAREK, STEPHEN - Oklahoma State University
item SCHNEIDER, WILLIAM - F1k9
item GARZON, CARLA - Oklahoma State University

Submitted to: Phytopathology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/23/2022
Publication Date: 3/29/2022
Citation: Espindola, A.S., Cardwell, K., Martin, F.N., Hoyt, P.R., Marek, S.M., Schneider, W., Garzon, C.D. 2022. A step towards validation of high-throughput sequencing for the identification of plant pathogenic oomycetes. Phytopathology. 112(9):1859-1866. https://doi.org/10.1094/PHYTO-11-21-0454-R.
DOI: https://doi.org/10.1094/PHYTO-11-21-0454-R

Interpretive Summary: This manuscript describes the use of whole genome sequencing and bioinformatic tools for identifying unique sequences that can be useful for rapid identification of plant pathogens from infected plant samples.

Technical Abstract: Precise plant pathogen identification is essential for deployment of suitable disease control and management strategies. The advancement in high-throughput sequencing (HTS) technology allows the detection of pathogens without the need for isolation or template amplification. Plant regulatory agencies worldwide are adopting HTS as a pre-screening tool for plant pathogens in imported plant germplasm. The technique is a multipronged process, and often the bioinformatic analysis complicates detection. Previously we developed an approach for HTS data analysis called e-probe Diagnostic Nucleic acid Analysis (EDNA) to resolve the time-consuming bioinformatic data management and to conclusively detect pathogens in HTS data. EDNA uses custom databases (e-probes) to reduce computational effort and subjectivity when determining pathogen presence in a sample. EDNA was developed as a theoretical approach for all pathogens, but it requires in vitro validation for each pathosystem. Here we validated e-probes in vitro for two oomycete plant pathogens using HTS data of Pythium ultimum (Trow) and Phytophthora ramorum (Werres, De Cock & Man in’t Veld). E-probe length was found to be a determinant of diagnostic sensitivity and specificity. Eighty nucleotide e-probe sequencelength increased the diagnostic specificity to 100%. Curating e-probes to increase specificity affected diagnostic sensitivity in 80 nt P. ultimum e-probes. Finally, alternative bioinformatic tools were evaluated to detect pathogen sequence reads in HTS data as a comparison of traditional approaches with EDNA; while pathogen sequence reads were detected it took a longer time compared with EDNA.