Genetic architecture and genomic patterns of gene flow between hybridizing species of Picea
Bibliographic record
Abstract
Hybrid zones provide an opportunity to study the effects of selection and gene flow in natural settings. We employed nuclear microsatellites (single sequence repeat (SSR)) and candidate gene single-nucleotide polymorphism markers (SNPs) to characterize the genetic architecture and patterns of interspecific gene flow in the Picea glauca × P. engelmannii hybrid zone across a broad latitudinal (40-60 degrees) and elevational (350-3500 m) range in western North America. Our results revealed a wide and complex hybrid zone with broad ancestry levels and low interspecific heterozygosity, shaped by asymmetric advanced-generation introgression, and low reproductive barriers between parental species. The clinal variation based on geographic variables, lack of concordance in clines among loci and the width of the hybrid zone points towards the maintenance of species integrity through environmental selection. Congruency between geographic and genomic clines suggests that loci with narrow clines are under strong selection, favoring either one parental species (directional selection) or their hybrids (overdominance) as a result of strong associations with climatic variables such as precipitation as snow and mean annual temperature. Cline movement due to past demographic events (evidenced by allelic richness and heterozygosity shifts from the average cline center) may explain the asymmetry in introgression and predominance of P. engelmannii found in this study. These results provide insights into the genetic architecture and fine-scale patterns of admixture, and identify loci that may be involved in reproductive barriers between the species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".