Exploring the potential of gametic reconstruction of parental genotypes by F<sub>1</sub> hybrids as a bridge for rapid introgression
Bibliographic record
Abstract
Interspecific hybridization and genetic introgression are commonly observed in natural populations of many species, especially trees. Among oaks, gene flow between closely related species has been well documented. And yet, hybridization does not lead to a “melting pot”, i.e., the homogenization of phenotypic traits. Here, we explore how the combination of several common reproductive and genomic traits could create an avenue for interspecific gene flow that partially explains this apparent paradox. During meiosis, F1 hybrids will produce approximately (½)n “reconstructed” parental gametes, where n equals the number of chromosomes. Crossing over would introduce a small amount of introgressive material. The resulting parental-type gametophytes would probably possess a similar fertilization advantage as conspecific pollen. The resulting “backcross” would actually be the genetic equivalent of a conspecific out-cross, with a small amount of heterospecific DNA captured through crossing over. Even with detailed genomic analysis, the resulting offspring would not appear to be a backcross. This avenue for rapid introgression between species through the F1 hybrid will be viable for organisms that meet certain conditions: low base chromosome number, conserved genomic structure and size, production of billions of gametes/gametophytes during each reproductive event, and conspecific fertilization advantage.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".