Variation in the Molecular Phenotype of <i>βglu‐1</i> , an Insect Defence‐Related Beta‐Glucosidase Gene, in Two Transcontinental <i>Picea</i> Species
Bibliographic record
Abstract
Forest trees face threats from many insect pest species, underscoring the importance of understanding their defence mechanisms for survival. In a North American conifer species, Picea glauca, gene expression of βglu-1 produces phenolic compounds (acetophenones) that defend against its insect defoliator, Choristoneura fumiferana. βglu-1 is also expressed in a Eurasian conifer species, Picea abies, although no major insect defoliators are present within the species' natural range. We compared the range-wide variation of βglu-1 transcript levels from foliage samples of P. glauca in North America and P. abies in Europe using RT-qPCR and targeted transcriptome sequencing. βglu-1 transcript levels were highly correlated between the two methods, with large transcript level variation being detected within and between populations in both species and one of the βglu-1 gene forms being significantly differentially expressed in P. glauca. Importantly, βglu-1 transcript levels in P. glauca varied longitudinally and were positively associated with mean annual precipitation and C. fumiferana outbreak class, which has historically higher outbreak frequency and severity in eastern compared to western populations. In P. abies, βglu-1 transcript levels were associated with annual temperature range. Overall, these results enhance our understanding of potential adaptive variation in acetophenone defences in P. glauca, while the factors influencing βglu-1 transcript variation in P. abies require further investigation.
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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 | 0.001 | 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".