Development and application of multiplex targeted-sequencing approaches to identify Phytophthora species associated with root rot and wilting complex of red raspberry
Bibliographic record
Abstract
Phytophthora species are primary causal agents of raspberry root rot and wilting complex (RRWC), a disease complex that is of major concern to raspberry producers worldwide. Accurate identification of the causal agents is a first step for effective disease management. Advancements in molecular diagnostics can facilitate the detection of multiple pathogen species associated with this disease complex. We developed multiplex targeted-sequencing methods using degenerate primers for heat shock protein 90, elongation factor 1α and β-tubulin genes to identify Phytophthora species causing RRWC. One hundred and twenty-eight isolates recovered during 2018 to 2020 from diverse fields in major raspberry growing areas of British Columbia (BC) were sequenced and identified by comparing with known reference sequences of 142 Phytophthora species, 111 Pythium species, and nine Phytopythium species in the NCBI database. This multiplex targeted-sequencing method was highly specific and identified two species of Phytophthora associated with RRWC. These were P. rubi (85% of isolates) and P. gonapodyides (15% of isolates). Phytophthora rubi was predominantly isolated from the cultivars 'Chemainus' (51%), 'Rudi' (27%) and 'Meeker' (15%), whereas P. gonapodyides was predominately isolated from the moderately resistant cultivar 'Cascade Bounty'. Pathogenicity studies on intact plants and detached leaves confirmed that P. rubi and P. gonapodyides can cause symptoms of RRWC on raspberry, thus fulfilling Koch's postulates. To our knowledge, this is the first report of P. gonapodyides as a causal agent of RRWC on raspberry in BC. This study provides novel insights into the identification and species composition of Phytophthora associated with RRWC in raspberry production systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".