High throughput sequencing(HTS) technologies have the potential to become one of the most significant advances in molecular diagnostics. Their use by researchers to detect and characterize plant pathogens and pests has been growing steadily for more than a decade and they are now envisioned as a routine diagnostic test to be deployed by plant pest diagnostics laboratories. Nevertheless, HTS technologies and downstream bioinformatics analysis of the generated datasets represent a complex process including many steps whose reliability must be ensured. The aim of the present guidelines is to provide recommendations for researchers and diagnosticians aiming to reliably use HTS technologies to detect plant pathogens and pests. These guidelines are generic and do not depend on the sequencing technology or platform. They cover all the adoption processes of HTS technologies from test selection to test validation as well as their routine implementation. A special emphasis is given to key elements to be considered: undertaking a risk analysis, designing sample panels for validation, using proper controls, evaluating performance criteria, confirming and interpreting results. These guidelines cover any HTS test used for the detection and identification of any plant pest (viroid, virus, bacteria, phytoplasma, fungi and fungus-like protists, nematodes, arthropods, plants) from any type of matrix. Overall, their adoption by diagnosticians and researchers should greatly improve the reliability of pathogens and pest diagnostics and foster the use of HTS technologies in plant heal
Massart S., Adams I., Al Rwahnih M., Baeyen S., Bilodeau G. J., Blouin A., Boonham N., Candresse T., Chandellier A., De Jonghe K., Fox A., Gaafar Y. Z. A., Gentit P., Haegeman A., Ho W., Hurtado-Gonzales O., Jonkers W., Kreuze J., Kutjnak D., Landa B. B.
Guidelines for the reliable use of high throughput sequencing technologies to detect plant pathogens and pests.
Peer Community Journal, 2, 2022, 1-35.
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ISSN Online: 2804-3871
Digital Object Identifier (DOI): https://doi.org/10.24072/pcjournal.181
Publikations-ID (Webcode): 50724
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