Aster Yellows Phytoplasma, Aster Leafhopper And Canola: Development And Application Of Improved Molecular Methods For Pathogen Detection And Genetic Characterization Provide Increased Understanding Of Aster Yellows Disease
Notice bibliographique
Résumé
Phytoplasmas are insect-vectored, difficult-to-culture bacterial pathogens that infect a wide variety of plants. They are associated with diseases connected with severe yield losses in global agricultural production, including Aster Yellows (AY). Aster Yellows phytoplasma (AYp) is primarily transmitted by the aster leafhopper (ALH), Macrosteles quadrilineatus Forbes, and AY outbreaks in Western Canada tend to damage canola crops most severely. Even though there are several methods to control AYp spread, the most common method is insecticide spray, which can damage the environment if used unsustainably. \nTools that can rapidly diagnose phytoplasma infection and accurately identify phytoplasma strains are of critical importance for disease management. Currently, detecting AYp involves a time-consuming process of transporting insect samples and extracting DNA, and this method often delays the application of mitigative measures. A rapid and field-adaptable diagnostic method was developed, which uses Flinders Technology Associates (FTA) PlantSaver paper cards to extract insect DNA followed by a loop-mediated isothermal amplification (LAMP) assay. This approach successfully detected AYp in under an hour, and its application could be expanded to a wide range of insect-transmitted pathogens. Disease management can also be improved by identifying and understanding the various species, strains, groups, and subgroups of phytoplasma. PCR-based methods targeting universal taxonomic markers (e.g., 16S rRNA) are commonly used to identify phytoplasmas in plant and insect tissues; however, these methods provide limited resolution of phytoplasma strains. In response to these limitations, a PCR-independent, hybridization-based multilocus sequence typing (MLST) assay was developed to precisely characterize phytoplasmas through the concurrent sequencing of seven taxonomic markers. This novel approach could serve as a standardized method for phytoplasma identification and may inform the understanding of phytoplasma spread in crop plants worldwide. \nLittle is conclusively known about the long-distance dispersal patterns of ALH, but gaining a more comprehensive understanding of the species could positively influence the development of AY control strategies. A panel of 22 microsatellite markers for ALH was developed and used in multiplex format to explore the genetic makeup of Saskatchewan ALH populations. This initial investigation into ALH genetics indicated a wide range of genetic variation within populations. In addition, there was no correlation between genetic and geographic distances, suggesting that Western Canada is a melting pot for North American ALH populations. While this study is a pioneering work and cannot be compared to reference data, it is a critical step in furthering knowledge of ALH. In the context of Western Canada, while researchers explore knowledge gaps in AYp identification and ALH origins, this work has determined that the best approach to AY management is, and may remain, prompt detection of AYp using field-adaptable molecular diagnostic methods.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».