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  • Development and Statistical Validation of E-Probe Diagnostic Nucleic Acid Analysis (EDNA) Assays for the Detection of Citrus Pathogens from Raw High-Throughput Sequencing Data
Title: Development and Statistical Validation of E-Probe Diagnostic Nucleic Acid Analysis (EDNA) Assays for the Detection of Citrus Pathogens from Raw High-Throughput Sequencing Data
The cost for high-throughput sequencing (HTS) has decreased significantly and has made it possible for the application of this technology for routine plant diagnostics. There are constraints to the use of HTS as a diagnostic tool, including the need for dedicated personnel with a bioinformatic background for data analysis and the lack of a standardized analysis pipeline that makes evaluating and validating results generated at different HTS laboratories difficult. E-probe diagnostic nucleic acid analysis (EDNA) is an in-silico bioinformatic tool that utilizes short curated electronic probes (e-probes) designed from pathogen-specific sequences that allow users to detect and identify single or multiple pathogens of interest in raw HTS data sets. This platform streamlines the bioinformatic data analysis into a graphical user interface as a plant diagnostic tool used by diagnosticians. In this study, we describe the process for the development, validation, and use of e-probes for detection and identification of a wide range of taxonomically unique citrus pathogens that include citrus exocortis viroid, citrus tristeza virus, ‘ Candidatus Liberibacter asiaticus’, and Spiroplasma citri. We demonstrate the process for evaluating the analytical and diagnostic sensitivity and specificity metrics of the in-silico EDNA assays. In addition, we show the importance of including background noise (internal controls) to generate variance in noninfected samples for a valid statistical test using the quadratic discriminant analysis. The fully validated EDNA assays from this study can be readily integrated into existing citrus testing programs that utilize HTS. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .  more » « less
Award ID(s):
2122686
PAR ID:
10507727
Author(s) / Creator(s):
; ; ; ; ;
Editor(s):
Cardwell, K.F.; Harmon, C.L; Stack, J.; Sharma, P.
Publisher / Repository:
American Phytopathological Society
Date Published:
Journal Name:
PhytoFrontiers™
Edition / Version:
2
Volume:
3
Issue:
1
ISSN:
2690-5442
Page Range / eLocation ID:
113 to 123
Subject(s) / Keyword(s):
Citrus disease diagnostics high-throughput sequencing assay validation limit of detection Microbe Finder (MiFi)
Format(s):
Medium: X Size: 2MB Other: cxv
Size(s):
2MB
Sponsoring Org:
National Science Foundation
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