Molecular analysis of poplar defense against herbivory: comparison of wound‐ and insect elicitor‐induced gene expression
Bibliographic record
Abstract
In order to characterize defense responses of hybrid poplar (Populus trichocarpax P. deltoides), we profiled leaf transcript patterns elicited by wounding and by regurgitant from forest tent caterpillar (FTC; Malacosoma disstria), a Lepidopteran defoliator of poplars. Macroarrays were used to compare transcript profiles. Both FTC-regurgitant (FTC-R) and mechanical wounding with pliers elicited expression of a variety of genes, and for these genes our analysis indicated that these treatments induced qualitatively similar responses. Similarly, a comparison of responses of directly treated and systemically induced leaves indicated extensive overlap in the sets of induced genes. FTC-R was found to contain the insect-derived elicitor volicitin. The simulated herbivory treatments resulted in the induction of genes involved in poplar defense and secondary metabolism. We also identified wound-responsive genes with roles in primary metabolism, including a putative invertase, lipase, and acyl-activating enzyme; some of these genes may have roles in defense signaling. In addition, we found three unknown genes containing a ZIM motif which may represent novel transcription factors.
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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".