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 backg...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
The American Phytopathological Society
2023-06-01
|
| Series: | PhytoFrontiers |
| Subjects: | |
| Online Access: | https://apsjournals.apsnet.org/doi/10.1094/PHYTOFR-05-22-0047-FI |
| _version_ | 1827095642029162496 |
|---|---|
| author | Tyler Dang Huizi Wang Andres S. Espindola Josh Habiger Georgios Vidalakis Kitty Cardwell |
| author_facet | Tyler Dang Huizi Wang Andres S. Espindola Josh Habiger Georgios Vidalakis Kitty Cardwell |
| author_sort | Tyler Dang |
| collection | DOAJ |
| description | 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. [Figure: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license. |
| first_indexed | 2024-03-08T06:34:54Z |
| format | Article |
| id | doaj.art-07ffd848eac647adbcfd85e6088cb03a |
| institution | Directory Open Access Journal |
| issn | 2690-5442 |
| language | English |
| last_indexed | 2025-03-20T07:03:07Z |
| publishDate | 2023-06-01 |
| publisher | The American Phytopathological Society |
| record_format | Article |
| series | PhytoFrontiers |
| spelling | doaj.art-07ffd848eac647adbcfd85e6088cb03a2024-10-01T12:35:47ZengThe American Phytopathological SocietyPhytoFrontiers2690-54422023-06-013111312310.1094/PHYTOFR-05-22-0047-FIDevelopment and Statistical Validation of E-Probe Diagnostic Nucleic Acid Analysis (EDNA) Assays for the Detection of Citrus Pathogens from Raw High-Throughput Sequencing DataTyler Dang0Huizi Wang1Andres S. Espindola2Josh Habiger3Georgios Vidalakis4Kitty Cardwell5Department of Microbiology and Plant Pathology, University of California, Riverside, CA 92521Department of Statistics, Oklahoma State University, Stillwater, OK 74078Department of Entomology and Plant Pathology, Oklahoma State University, Stillwater, OK 74078Department of Statistics, Oklahoma State University, Stillwater, OK 74078Department of Microbiology and Plant Pathology, University of California, Riverside, CA 92521Department of Entomology and Plant Pathology, Oklahoma State University, Stillwater, OK 74078The 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. [Figure: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.https://apsjournals.apsnet.org/doi/10.1094/PHYTOFR-05-22-0047-FIassay validationhigh-throughput sequence (HTS) diagnosticslimit of detectionMiFinext-generation sequencing (NGS) |
| spellingShingle | Tyler Dang Huizi Wang Andres S. Espindola Josh Habiger Georgios Vidalakis Kitty Cardwell 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 PhytoFrontiers assay validation high-throughput sequence (HTS) diagnostics limit of detection MiFi next-generation sequencing (NGS) |
| 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 |
| title_full | 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_fullStr | 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_full_unstemmed | 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_short | 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_sort | 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 |
| topic | assay validation high-throughput sequence (HTS) diagnostics limit of detection MiFi next-generation sequencing (NGS) |
| url | https://apsjournals.apsnet.org/doi/10.1094/PHYTOFR-05-22-0047-FI |
| work_keys_str_mv | AT tylerdang developmentandstatisticalvalidationofeprobediagnosticnucleicacidanalysisednaassaysforthedetectionofcitruspathogensfromrawhighthroughputsequencingdata AT huiziwang developmentandstatisticalvalidationofeprobediagnosticnucleicacidanalysisednaassaysforthedetectionofcitruspathogensfromrawhighthroughputsequencingdata AT andressespindola developmentandstatisticalvalidationofeprobediagnosticnucleicacidanalysisednaassaysforthedetectionofcitruspathogensfromrawhighthroughputsequencingdata AT joshhabiger developmentandstatisticalvalidationofeprobediagnosticnucleicacidanalysisednaassaysforthedetectionofcitruspathogensfromrawhighthroughputsequencingdata AT georgiosvidalakis developmentandstatisticalvalidationofeprobediagnosticnucleicacidanalysisednaassaysforthedetectionofcitruspathogensfromrawhighthroughputsequencingdata AT kittycardwell developmentandstatisticalvalidationofeprobediagnosticnucleicacidanalysisednaassaysforthedetectionofcitruspathogensfromrawhighthroughputsequencingdata |