HETEROGENEOUS GENOMIC DIFFERENTIATION BETWEEN WALKING-STICK ECOTYPES: "ISOLATION BY ADAPTATION" AND MULTIPLE ROLES FOR DIVERGENT SELECTION
Why this work is in the frame
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Bibliographic record
Abstract
Genetic differentiation can be highly variable across the genome. For example, loci under divergent selection and those tightly linked to them may exhibit elevated differentiation compared to neutral regions. These represent "outlier loci" whose differentiation exceeds neutral expectations. Adaptive divergence can also increase genome-wide differentiation by promoting general barriers to neutral gene flow, thereby facilitating genomic divergence via genetic drift. This latter process can yield a positive correlation between adaptive phenotypic divergence and neutral genetic differentiation (described here as "isolation-by-adaptation"). Here, we examine both these processes by combining an AFLP genome scan of two host plant ecotypes of Timema cristinae walking-sticks with existing data on adaptive phenotypic divergence and ecological speciation in these insects. We found that about 8% of loci are outliers in multiple population comparisons. Replicated comparisons between population-pairs using the same versus different host species revealed that 1-2% of loci are subject to host-related selection specifically. Locus-specific analyses revealed that up to 10% of putatively neutral (nonoutlier) AFLP loci exhibit significant isolation-by-adaptation. Our results suggest that selection may affect differentiation directly, via linkage, or by facilitating genetic drift. They thus illustrate the varied and sometimes nonintuitive contributions of selection to heterogeneous genomic differentiation.
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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