Transcriptome divergence between introduced and native populations of Canada thistle, <i>Cirsium arvense</i>
Bibliographic record
Abstract
Introduced plants may quickly evolve new adaptive traits upon their introduction. Canada thistle (Cirsium arvense - Cardueae, Asteraceae) is one of the worst invasive weeds worldwide. The goal of this study is to compare gene expression profiles of native (European) and introduced (North American) populations of this species, to elucidate the genetic mechanisms that may underlie such rapid adaptation. We explored the transcriptome of ten populations (five per range) of C. arvense in response to three treatments (control, nutrient deficiency and shading) using a customized microarray chip containing 63 690 expressed sequence tags (ESTs), and verified the expression level of 13 loci through real-time quantitative PCR. Only 2116 ESTs (3.5%) were found to be differentially expressed between the ranges, and 4458 ESTs (7.1%) exhibited a significant treatment-by-range effect. Among them was an overrepresentation of loci involved in stimulus and stress responses. Cirsium arvense has evolved different life history strategies on each continent. The two ranges notably differ with regard to R-protein mediated defence, sensitivity to abiotic stresses, and developmental timing. The fact that genotypes from the Midwest exhibit different expression kinetics than remaining North American samples further corroborates the hypothesis that the New World has been colonized twice, independently.
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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".