Refining the genomic location of SNP variation affecting Atlantic salmon maturation timing at a key large-effect locus
Bibliographic record
Abstract
ABSTRACT Efforts to understand the genetic underpinnings of phenotypic variation are becoming more and more frequent in molecular ecology. Such efforts often lead to the identification of candidate regions showing signals of association and/or selection. These regions may contain multiple genes and therefore validation of which genes are actually responsible for the signal is required. In Atlantic salmon ( Salmo salar ), a large-effect locus for maturation timing, an ecologically important trait, occurs in a genomic region including two genes, vgll3 and akap11 , but data for clearly determining which of the genes (or both) contribute to the association have been lacking. Here, we take advantage of natural recombination events detected between the two candidate genes in a salmon broodstock to reduce linkage disequilibrium at the locus, and thus enabling delineation of the influence of variation at these two genes on maturation timing. By rearing 5895 males to maturation age, of which 81% had recombinant vgll3 / akap11 allelic combinations, we found that vgll3 SNP variation was strongly associated with maturation timing, whereas there was little or no association between akap11 SNP variation and maturation timing. These findings provide strong evidence supporting vgll3 as the primary candidate gene in the chromosome 25 locus for influencing maturation timing. This will help guide future research for understanding the genetic processes controlling maturation timing. This also exemplifies the utility of natural recombinants to more precisely map causal variation underlying ecologically important phenotypic diversity.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".