A genetic linkage map for Arctic char (<i>Salvelinus alpinus</i>): evidence for higher recombination rates and segregation distortion in hybrid versus pure strain mapping parents
Bibliographic record
Abstract
We constructed a genetic linkage map for Arctic char (Salvelinus alpinus) using two backcrosses between genetically divergent strains. Forty-six linkage groups (expected = 39-41) and 19 homeologous affinities (expected = 25) were identified using 184 microsatellites, 129 amplified fragment length polymorphisms (AFLPs), 13 type I gene markers, and one phenotypic marker, SEX. Twenty-six markers remain unlinked. Female map distance (9.92 Morgans) was substantially higher than male map distance (3.90 Morgans) based on the most complete parental information (i.e., the F1 hybrids). Female recombination rates were often significantly higher than those of males across all pairwise comparisons within homologous chromosomal segments (average female to male ratios within families was 1.69:1). The female hybrid parent had significantly higher recombination rates than the pure strain female parent. Segregation distortion was detected in four linkage groups (4, 8, 13, 20) for both families. In family 3, only the largest fish were sampled for genotyping, suggesting that segregation distortion may represent regions possessing influences on growth. In family 2, almost all cases showing segregation distortion involved markers in the female hybrid parent.
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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 | 0.001 | 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) | 0.001 | 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".