Genomics of systemic induced defense responses to insect herbivory in hybrid poplar
Bibliographic record
Abstract
The availability of a poplar (Populus trichocarpa Torr & A. Gray, black cottonwood) genome sequence is enabling new research approaches in angiosperm tree biology. Much of the recent genomics research in poplars has been on wood formation, growth and development, and abiotic stress tolerance, motivated, at least in part, by the fact that poplars provide an important system for large scale, short-rotation plantation forestry in the Northern Hemisphere. Given their widespread distribution and long lifespan, poplar trees are threatened by a large variety of insect herbivore pests, and must deal with their attacks with a successful defense response. To sustain productivity and ecosystem health of natural and planted poplar forests, it is of critical importance to develop a better understanding of the molecular mechanisms of defense and resistance of poplars against insect pests. Previous research has established a solid foundation of the chemical ecology of poplar defense against insects. In this study, I buiLd on this base with large-scale profiling of transcriptome responses of poplar trees to insect herbivory. A 15,496-clone cDNA microarray was developed and used to analyse transcriptome responses through time to a variety of insect, mechanical, and chemical elicitor treatments in treated source leaves, as well as in undamaged systemic source and sink leaves of hybrid poplar (Populus trichocarpa x deltoides). Comparing mechanical wounding with insect feeding and chemical eLicitor treatment with methyl jasmonate demonstrated that qualitatively similar profiles of transcriptome response were eLicited with differences in the timing of induction. Transcriptome analysis in undamaged systemic leaves of treated trees uncovered distinct early changes in primary metabolism (e.g. sugar metabolism) and general stress responses (e.g. heat shock proteins) prior to the activation of insect herbivory response genes (e.g. Kunitz-type protease inhibitors). Source-sink relationships are maintained and strengthened by insect damage on source leaves, emphasizing changes in resource allocation patterns as being important for poplar defense. Overall, a model of poplar defense begins to emerge where a cascade of transcriptome profiles through space and time lead to reorganization of metabolism for tolerance and induction of defense.
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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".