Trans‐species shared polymorphisms at orthologous nuclear gene loci among distant species in the conifer <i>Picea</i> (Pinaceae): implications for the long‐term maintenance of genetic diversity in trees
Bibliographic record
Abstract
For each of three nuclear gene loci, intraspecific- as well as trans-specific shared polymorphisms were detected in DNA among three distantly related species in the genus Picea. Few fixed interspecific polymorphisms were observed. Allele genealogies did not match species phylogenies, and species lineages were not reciprocally monophyletic. Based on molecular clocks and morphological evidence from the fossil record, the divergence time between species was estimated at 13-20 million years (my), and a mutation rate of 2.23 × 10(-10) to 3.42 × 10(-10) per site per year was estimated. Large historical population sizes in excess of 100 000 were inferred, which would have delayed the fixation of polymorphisms. These numbers translated into allele coalescence times in the order of 10 to 18 my, which implies the sharing of polymorphisms since common ancestry. These results suggest that trans-species shared polymorphisms might be frequent at plant nuclear gene loci, leading to high allelic diversity. Such a trend is more likely in trees and plants characterized by ecological and life-history determinants favoring large population sizes such as an outcrossing mating system, wind pollination, and a dominant position in ecosystem. These polymorphisms also call for caution in estimating congeneric species phylogenies from nuclear gene sequences in such plant groups.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".