Detection and identification of selected cereal rust pathogens by TaqMan<sup>®</sup>real-time PCR
Bibliographic record
Abstract
The rust species Puccinia graminis and P. striiformis sensu stricto are important cereal pathogens, most well-known for causing the diseases stem rust and stripe rust on wheat and generating significant yield losses. Early and accurate detection of the pathogens would facilitate effective control of the diseases. In the present study, we developed real-time PCR assays to detect the specific lineages that include the wheat pathogens for each species complex, as identified using multi-gene DNA sequence analyses. Four DNA loci, for a comprehensive set of target and closely related fungi collected from diverse hosts and geographic regions, were explored to search for suitable lineage-specific probes: β-tubulin (BT), cytochrome c oxidase subunit 1 (COI), rDNA internal transcribed spacer (ITS), and RNA polymerase II second largest subunit (RPB2). Four TaqMan® real-time PCR assays were designed based on either the BT or RPB2 genes: one targeting Puccinia Series Striiformis (PSBT), one targeting P. striiformis sensu stricto (PSstrRPB2), and two targeting the P. graminis lineages on wheat (Pg2+BT and Pg2RPB2). Sensitivities of the assays were determined to be 0.65 pg µL−1 (Pg2) and 5 pg µL−1 (PS). Specificity of each assay was confirmed using a broad diversity of rusts and other selected wheat-associated fungi. The ITS and COI loci were found to be unsuitable for diagnostic assay development but contributed phylogenetic signal to the multi-gene analyses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".