A PCR-RFLP assay for identification and detection of Pythium myriotylum, causal agent of the cocoyam root rot disease
Bibliographic record
Abstract
AIM: Development of a PCR-RFLP assay that could reliably distinguish strains of Pythium myriotylum that are pathogenic to cocoyam from nonpathogens, as well as in planta detection of the pathogen. METHODS AND RESULTS: Sequences of the internal transcribed spacer regions of nuclear ribosomal DNA (rDNA-ITS) containing ITS1 and ITS2 of P. myriotylum isolates from cocoyam and other hosts were aligned and a restriction map was generated. rDNA-ITS alignment report revealed a new single nucleotide polymorphism (SNP; thymine/cytosine) downstream to previously published SNP (guanine/adenine) between isolates of P. myriotylum that are pathogenic to cocoyam and nonpathogenic strains. This new SNP is within the restriction site of the endonuclease AarI. Based on this SNP, a PCR-RFLP assay was developed for specific detection of P. myriotylum. The PCR amplicons of all isolates of P. myriotylum that infect cocoyam were cleaved by AarI, resulting to two bands (600/400 bp); but those from other hosts showed a single band (1000 bp), confirming the presence and specificity of the AarI restriction site. Also, the assay was effective in in planta detection of the pathogen on infected cocoyam roots without prior isolation of a pure culture. CONCLUSION: A PCR-RFLP method was developed that differentiates isolates of P. myriotylum that are pathogenic to cocoyam from nonpathogens as well as from other fungi commonly found in the cocoyam rhizosphere. SIGNIFICANCE AND IMPACT OF THE STUDY: Early and rapid detection of the pathogen could be of great importance in certifying planting materials as disease-free, enhancing sustainable management practices and limiting economic losses.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".