Genome-Wide Patterns of Genetic Variation within and among Alternative Selective Regimes
Bibliographic record
Abstract
Environmental heterogeneity has been hypothesized to influence levels of genetic variation but the effect of heterogeneity depends on (i) the form of heterogeneity, (ii) whether ecologically relevant or neutral loci are being considered, and (iii) the genetic basis of ecological adaptation. We surveyed genome-wide SNP diversity in replicate experimental Drosophila melanogaster populations with equal census sizes that evolved for 42 generations under one of four selection regimes: (i) salt-enriched environment (Salt), (ii) cadmium-enriched environment (Cad), (iii) temporally (Temp) or (iv) spatially (Spatial) variable environments. There was significant differentiation between all pairs of treatments but the greatest differentiation occurred between the two homogenous treatments (Cad and Salt). For sites likely under differential ecological selection (and those closely linked to them), the pattern of within-population diversity π followed the expectation from classic antagonistic selection theory: Spatial > Temp >S alt ≈ Cad. However, neutral diversity unlinked to selected sites followed a different pattern: Spatial>Salt ≈ Cad > Temp. As implicated by the latter result, measures of FST among replicate populations within treatments are consistent with differences in effective population sizes among selective regimes despite equal census sizes. Though there are clear changes in the rank order of treatments when contrasting selected and neutral sites with respect to π, the rank ordering of treatments with respect to FST appears reasonably consistent between site categories. These results demonstrate that alternative selective regimes affect within- and among-population diversity differently for different site types.
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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 | 0.001 | 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".