Defense by duplication: The relation between phenotypic glyphosate resistance and EPSPS gene copy number variation in <i>Amaranthus palmeri</i>
Bibliographic record
Abstract
Abstract Gene copy number variation (CNV) has been increasingly associated with organismal responses to environmental stress, but we know little about the quantitative relation between CNV and phenotypic variation. In this study we quantify variation in EPSPS (5-enolpyruvylshikimate-3-phosphate synthase) copy number using digital drop PCR and variation in phenotypic glyphosate resistance in 22 populations of Amaranthus palmeri (Palmer Amaranth), a range-expanding agricultural weed. Overall, we detected a significant positive relation between population mean copy number and mean resistance. The majority of populations exhibited high glyphosate resistance, yet maintained low-resistance individuals resulting in bimodality in many populations. We investigated linear and threshold models for the relation between copy number and resistance, and found evidence for a threshold of ~15 EPSPS copies: there was a steep increase in resistance before the threshold, followed by a much shallower slope. Moreover, as copy number increases, the range of variation in resistance decreases. This suggests a working hypothesis that as EPSPS copies and dosage increases, negative epistatic interactions may be compensated. We detected a quadratic relation between mean resistance and variation (s.d.) in resistance, consistent with the prediction that as phenotypic resistance increases in populations, stabilizing selection decreases variation in the trait. Finally, patterns of variation across the landscape are consistent with less variation among populations in mean copy number / resistance in Georgia where glyphosate resistance was first detected, and wider variation among populations in resistance and copy number in a more northern state where resistance evolution may be at a younger evolutionary state.
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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 | 0.001 |
| 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".