Candidate genes associated with fatty acid compositions in north American Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
Abstract Fatty acids are a requirement for normal development, however, since humans are unable to de novo produce essential fatty acids, they must be obtained from diet. Atlantic salmon is a major dietary source of nutritious and digestible fatty acids. Here, we set out to uncover the genomic basis of individual fatty acids and indices (saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, n-3, and n-6) in 208 North American Atlantic salmon, to understand selection potential toward increasing relative quantities of essential fatty acids and to identify candidate genes for future research. Total n-6 (pro-inflammatory) was higher than total n-3 (anti-inflammatory) fatty acids with a ratio of 1 : 1.31 (n-3 : n-6). Heritability of fatty acids ranged from 0 to 0.99, however, most fatty acids and indices had moderate to high heritabilities (ranged from 0.20 to 0.88), implying that selection for improvement of traits could be possible. We found the same significant markers on chromosome 23 (based on false discovery rate thresholds of 2.0e-6 and suggestive significant thresholds of 2.0e-5 in Manhattan plots) in four fatty acids (γ-linoleic acid, stearidonic acid, dihimo-γ-linolenic acid, and eicosatrienoic acid), where three genes (sin3b, acbd6, and fads2) are known to be involved in lipid metabolism. These genes, fads2 in particular, would all make ideal candidates for future functional studies. In addition, there were four fatty acids with loci over the suggestive significant threshold with a variety of markers on different chromosomes (lauric acid, stearic acid, eicosatetraenoic acid (ETA), and docosadienoic acid), with associated genes that had relevant functions to fatty acids or adipose cells in general.
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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 | 0.001 |
| 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".