Structural and expressional divergence of genes encoding <i>O</i>-methyltransferase in wheat
Bibliographic record
Abstract
Enzymatic methylation, which is catalyzed by the large number of O-methyltransferases (OMTs), is one of the important reactions in the flow of primary and (or) secondary metabolism. In a previous study, the gene TaOMT1 was induced by Hessian fly infestation of a wheat-rye translocation line. In this study we considered other wheat OMT genes - TaOMT3, TaOMT4, and TaOMT5 - using a bioinformatics approach and examined the TaOMT genes for their genomic organization, tissue-specific expression, responses to abiotic stresses and hormones, and cis-elements. There appeared to be a homoeologous relationship between TaOMT4 (6DS) and TaOMT5 (6BS), whereas TaOMT1 and TaOMT3 were placed on chromosome arms 7BL and 5DL, respectively. Differences in the tissue-specific, constitutive, and stress-inducible expression patterns among the TaOMT genes were found in both healthy and stressed plants. A number of cis-elements, which are potentially correlated with the responses of the TaOMT genes, were detected in the analysis of the TaOMT promoter sequences. In addition, evolutionary perspectives of the TaOMT genes are discussed. The nucleotide sequences have been deposited in the GenBank database under accession Nos. AAP23942 (TaCOMT1), EF423610 (TaOMT5), EF423611 (TaOMT4), EF423612 (TaOMT3), EU831287 (5' upstream of TaOMT1), EU831288 (5' upstream of TaOMT3), EU831289 (5' upstream of TaOMT4), and EU831290 (5' upstream of TaOMT5).
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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 | 0.000 | 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) | 0.001 | 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 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".