Natural Variation in Gene Expression Between Wild and Weedy Populations of <i>Helianthus annuus</i>
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Bibliographic record
Abstract
The molecular genetic changes underlying the transformation of wild plants into agricultural weeds are poorly understood. Here we use a sunflower cDNA microarray to detect variation in gene expression between two wild (non-weedy) Helianthus annuus populations from Utah and Kansas and four weedy H. annuus populations collected from agricultural fields in Utah, Kansas, Indiana, and California. When grown in a common growth chamber environment, populations differed substantially in their gene expression patterns, indicating extensive genetic differentiation. Overall, 165 uni-genes, representing approximately 5% of total genes on the array, showed significant differential expression in one or more weedy populations when compared to both wild populations. This subset of genes is enriched for abiotic/biotic stimulus and stress response proteins, which may underlie niche transitions from the natural sites to agricultural fields for H. annuus. However, only a small proportion of the differentially expressed genes overlapped in multiple wild vs. weedy comparisons, indicating that most of the observed expression changes are due to local adaptation or neutral processes, as opposed to parallel genotypic adaptation to agricultural fields. These results are consistent with an earlier phylogeographic study suggesting that weedy sunflowers have evolved multiple times in different regions of the United States and further indicate that the evolution of weedy sunflowers has been accompanied by substantial gene expression divergence in different weedy populations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it