First report of lingonberry stunted yellows disease of Vaccinium vitis-idaea L. associated with ‘ Candidatus Phytoplasma trifolii’-related phytoplasma strain in Lithuania /
Notice bibliographique
Résumé
Lingonberries (Vaccinium vitis-idaea L.) are low-growing, evergreen shrubs of cooler, northern regions of North America and Europe. These plants produce berries that are unique in flavor, bear high economic significance, and play a vital role in maintaining the diversity of the northern ecosystems (Kowalska, 2021). In October 2023 diseased plants of lingonberry were discovered in Labanoras Forest (55°14′N 25°42′E) (Lithuania). The plants expressed symptoms of stunting, yellowing, little leaf, shortened internodes, and stem distortions. Samples (leaves) were collected and tested from ten asymptomatic and ten symptomatic lingonberry plants. Total genomic DNAs of all samples were extracted by a CTAB protocol. Extracted DNAs were used as a template in direct and nested PCRs using the universal primer pairs P1/P7 and R16F2n/R2, respectively, to amplify phytoplasma 16S rRNA gene 1.2 kb fragments (Lee et al. 1998). The primer pairs SecAFor1/SecARev3 and SecAFor2/SecARev3 were used in direct and semi-nested PCRs, respectively, to amplify phytoplasma secA genes 0.5 kb fragment (Dickinson and Hodgetts, 2013). PCR amplicons of the 16S rRNA and secA genes specific for the phytoplasmas were only obtained from all sampled symptomatic plants. Three R16F2n/R2 and three SecAFor2/SecARev3 amplicons were cloned and submitted for Sanger sequencing (Nature Research Centre, Vilnius, Lithuania by 3500 Genetic Analyser). The three 16S rDNAs as well as the three secA gene fragments were identical. The BLAST analysis (NCBI) of the obtained sequences showed a similarity percentage, ranging from 99.75% to 100% (1247-1250 bp from 1250 bp) for 16SrRNA, and 98.13% to 99,15% (473-478 bp from 482 bp) for secA amplicons, with numerous strains of ‘Candidatus (Ca.) Phytoplasma (P.) trifolii’ (first hit MT674293 and KR906724, respectively). Additionally, 16S rDNA sequences by using iPhyClassifier were used to create virtual RFLP pattern (Zhao et al. 2009). The generated pattern was identical (similarity coefficient 1.00) to the reference pattern of 16Sr group VI, subgroup A. The phytoplasma strain detected in lingonberries was designated as lingonberry stunted yellows, LingbSY. Furthermore, the enzymatic RFLP analysis was performed with the 14 restriction enzymes (Lee et al., 1998), and obtained profiles were compared with virtually generated using iPhyClassifier. This yielded the same classification of detected phytoplasma to the 16SrVI-A phytoplasma subgroup. The phylogenetic analysis of both marker gene sequences revealed the same LingbSY phytoplasma classification. Selected sequences were deposited in GenBank (NCBI) with Accession No: PP237769 (16S rRNA gene) and No: PP238489 (secA gene). Phytoplasmas of 16SrI phytoplasma group were identified in lingonberries in Canada (Brochu et al. 2022). Strains of 16SrVI phytoplasma group were reported in Vaccinium myrtillus in Austria (Fernandez et al. 2007). This is the first report of ‘Ca. P. trifolii’ strain belonging to 16SrVI-A phytoplasma subgroup infecting lingonberry worldwide. Also, this is the first report of 16SrVI phytoplasma group in Lithuania. The presence of this phytoplasma poses a threat to the natural ecosystem and could eventually spread into agricultural settings in our country. Therefore, it’s crucial to conduct surveillance for insect vectors, and assess effective control methods. Without proactive action, long term sustainability of lingonberries and their ecosystems may be jeopardized.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».