Sex-linked Quantitative Trait Loci for Thermotolerance and Length in the Rainbow Trout
Bibliographic record
Abstract
We hypothesized that correlation between growth traits and upper thermal tolerance (UTT) in rainbow trout (Oncorhynchus mykiss) might be explained by quantitative trait loci (QTL) localized to the same linkage groups. Microsatellites on three autosomal linkage groups carrying UTT QTL in rainbow trout were tested for associations with fork length (FL) and condition factor (K) in half-sib families of outbred rainbow trout and in backcrosses of trout lines selected on UTT. Additionally, we used a sex-linked microsatellite (OmyFGT19TUF) to test for marker-trait associations at the sex chromosomes. The sex-linked marker OmyFGT19TUF was significantly associated with FL and UTT, accounting for up to 9.6% and 9.7% of variance in these traits, respectively. Male advantages in FL (and, to a lesser extent, UTT) relative to their female sibs were dependent on the origin of the Y chromosome and thus varied among grandsire lines. However, males had higher K in a manner unrelated to Y chromosomal origin, suggesting a partially sex-limited expression of this trait. Omy325UoG was significantly associated with K in one of the outbred half-sib families, but no other significant autosomal marker-trait associations were detected. Our findings illustrate minor evidence that correlation between UTT and FL is partially determined by one or more sex-chromosomal QTL.
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 | 0.000 | 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".