<i>TaCER1‐1A</i> is involved in cuticular wax alkane biosynthesis in hexaploid wheat and responds to plant abiotic stresses
Bibliographic record
Abstract
Abstract To protect above‐ground plant organs from excessive water loss, their surfaces are coated by waxes. The genes involved in wax formation have been investigated in detail in Arabidopsis but scarcely in crop species. Here, we aimed to isolate and characterize a CER1 enzyme responsible for formation of the very long‐chain alkanes present in high concentrations especially during late stages of wheat development. On the basis of comparative wax and transcriptome analyses of various wheat organs, we selected TaCER1‐1A as a primary candidate and demonstrated that it was located to the endoplasmic reticulum, the subcellular compartment for wax biosynthesis. A wheat nullisomic‐tetrasomic substitution line lacking TaCER1‐1A had significantly reduced amounts of C33 alkane, whereas rice plants overexpressing TaCER1‐1A showed substantial increases of C25–C33 alkanes relative to wild type control. Similarly, heterologous expression of TaCER1‐1A in Arabidopsis wild type and the cer1 mutant resulted in increased levels of unbranched alkanes, iso‐branched alkanes and alkenes. Finally, the expression of TaCER1‐1A was found activated by abiotic stresses and abscisic acid treatment, resulting in increased production of alkanes in wheat. Taken together, our results demonstrate that TaCER1‐1A plays an important role in wheat wax alkane biosynthesis and involved in responding to drought and other environmental stresses.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".