Large-scale genome-wide study reveals climate adaptive variability in a cosmopolitan pest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding the genetic basis of climatic adaptation is essential for predicting species' responses to climate change. However, intraspecific variation of these responses arising from local adaptation remains ambiguous for most species. Here, we analyze genomic data from diamondback moth (Plutella xylostella) collected from 75 sites spanning six continents to reveal that climate-associated adaptive variation exhibits a roughly latitudinal pattern. By developing an eco-genetic index that combines genetic variation and physiological responses, we predict that most P. xylostella populations have high tolerance to projected future climates. Using genome editing, a key gene, PxCad, emerged from our analysis as functionally temperature responsive. Our results demonstrate that P. xylostella is largely capable of tolerating future climates in most of the world and will remain a global pest beyond 2050. This work improves our understanding of adaptive variation along environmental gradients, and advances pest forecasting by highlighting the genetic basis for local climate adaptation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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