Differential introgression reveals candidate genes for selection across a spruce (<i><scp>P</scp>icea sitchensis </i>×<i> <scp>P</scp>. glauca</i>) hybrid zone
Bibliographic record
Abstract
Differential patterns of introgression between species across ecological gradients provide a fine-scale depiction of extrinsic and intrinsic factors that contribute to the maintenance of species barriers and adaptation across heterogeneous environments. Introgression was examined for 721 individuals collected from the ecological transition zone spanning maritime to continental climates within the Picea sitchensis-Picea glauca contact zone using a panel of 268 candidate gene single nucleotide polymorphisms. Geographic clines showed a strong spatial relationship between allele frequencies and both distance from the ocean along major rivers and mean annual precipitation, indicating a strong role for environmental selection. Interspecific patterns of differentiation using outlier tests revealed three candidate genes that may be targets of long-term divergent selection between the parental species, although contemporary genomic clines within the hybrid zone suggested neutral patterns of introgression for these genes. This study provides a fine-scale analysis of locus-specific introgression, identifying a suite of candidate loci that may be targets of extrinsic or intrinsic selection, with broad application in understanding local adaptation to climate.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".