PhytoFrontiers (Jun 2023)

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

  • Tyler Dang,
  • Huizi Wang,
  • Andres S. Espindola,
  • Josh Habiger,
  • Georgios Vidalakis,
  • Kitty Cardwell

DOI
https://doi.org/10.1094/PHYTOFR-05-22-0047-FI
Journal volume & issue
Vol. 3, no. 1
pp. 113 – 123

Abstract

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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. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

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