The genetic architecture of embryonic developmental rate and genetic covariation with age at maturation in rainbow trout <i>Oncorhynchus mykiss</i>
Bibliographic record
Abstract
The genetic architecture underlying variation in embryonic developmental rate (DR) and genetic covariation with age of maturation (MAT) was investigated in rainbow trout Oncorhynchus mykiss. Highly significant additive parental effects and more limited evidence of epistatic effects on progeny hatching time were detected in three diallel sets of families. Genome scans with an average of 142 microsatellite loci from all 29 linkage groups in two families detected significant quantitative trait loci (QTL) for developmental rate on RT-8 and RT-30 with genome-wide and chromosome-wide effects, respectively. The QTL on linkage group RT-8 explained 23·7% of the phenotypic variation and supports results from previous studies. The co-localization of QTL for both DR and MAT to several linkage groups and the observation that alleles associated with faster developmental rate were found significantly more often in early maturing rather than typical and later maturing male ancestors supports the hypothesis of genetic covariation between DR and MAT. The maturation background and schedule of additional sires, however, did not have a consistent association with their progeny hatching times, suggesting that other genetic, environmental and physiological effects contribute to variation in these life-history traits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".