Systematic Development of<i>Phytophthora</i>Species-Specific Mitochondrial Diagnostic Markers for Economically Important Members of the Genus
Bibliographic record
Abstract
The genus Phytophthora contains many invasive species to the U.S.A. that have the potential to cause significant damage to agriculture and native ecosystems. A genus and species-specific diagnostic assay was previously reported based on mitochondrial gene order differences that allowed for the systematic development of 14 species-specific TaqMan probes for pathogen detection ( Bilodeau et al. 2014 ). In this study, an additional 32 species-specific TaqMan probes for detection of primarily invasive species have been validated against 145 Phytophthora taxa as well as a range of Pythium and plant DNA samples. All validated probes were found to be species-specific and could be multiplexed with a genus-specific probe. The lower limit of linear detection using purified genomic DNA ranged from 1 to 100 fg in all assays. In addition, 124 unique TaqMan probes for Phytophthora spp. developed in silico are presented, which, if testing confirms they are species-specific, will provide diagnostic capabilities for approximately 89% of the genus. To enhance sensitivity of detection for several species that contained a single nucleotide polymorphism (SNP) in the reverse primer, a second primer was developed that is added in a small amount to the master mix. Furthermore, a PCR-RFLP system was developed that could be used to identify individual species when multiple species are present in a sample, without requiring cloning or sequencing. Several experiments were also conducted to compare various qPCR thermal cyclers and independent validation experiments with another research laboratory to identify possible limitations when the assays are used on a range of equipment in different labs. This system represents a comprehensive, hierarchal approach to increase the detection capability and provide tools to help prevent the introduction of invasive Phytophthora species.
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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 | 0.001 | 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".