Identification and evaluation of PCR reference genes for host and pathogen in sugarcane-Sporisorium scitamineum interaction system
Bibliographic record
Abstract
BACKGROUND: Sugarcane (Saccharum L. plant) is an important crop for sugar and bio-energy production around the world. Among sugarcane diseases, smut caused by Sporisorium scitamineum is one of the major fungal diseases causing severe losses to the sugarcane industry. The use of PCR reference genes is essential to the normalization of data on gene expression involving the sugarcane-S. scitamineum interaction system; however, no report that addresses criteria in selecting these reference genes has been published to date. RESULTS: In this study, 10 sugarcane genes and eight S. scitamineum genes were selected as candidate PCR reference genes in the sugarcane-S. scitamineum interaction system. The stability and reliability of these 18 candidate genes were analyzed in smut-resistant (NCo376) and -susceptible (YC71-374) genotypes using the statistical algorithms geNorm, NormFinder, BestKeeper, and deltaCt method. Subsequently, the relative expression levels of the sugarcane chitinase I-3 gene and S. scitamineum chorismate mutase gene were determined to validate the applicability of these sugarcane and S. scitamineum PCR reference genes, respectively. We finally found that the acyl-CoA dehydrogenase gene (ACAD), serine/arginine repetitive matrix protein 1 gene (SARMp1), or their combination (ACAD + SARMp1) could be utilized as the most suitable reference genes for normalization of sugarcane gene expression in sugarcane bud tissues after S. scitamineum infection. Similarly, the inosine 5'-monophosphate dehydrogenase gene (S10), the SEC65-signal recognition particle subunit gene (S11), or their combination (S10 + S11) were suitable for normalization of S. scitamineum gene expression in sugarcane bud tissues. CONCLUSIONS: The PCR reference genes ACAD, SARMp1, S10, and S11 may be employed in gene transcriptional studies involving the sugarcane-S. scitamineum interaction system.
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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".