‘Good genes as heterozygosity’: the major histocompatibility complex and mate choice in Atlantic salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
According to the theory of mate choice based on heterozygosity, mates should choose each other in order to increase the heterozygosity of their offspring. In this study, we tested the 'good genes as heterozygosity' hypothesis of mate choice by documenting the mating patterns of wild Atlantic salmon (Salmo salar) using both major histocompatibility complex (MHC) and microsatellite loci. Specifically, we tested the null hypotheses that mate choice in Atlantic salmon is not dependent on the relatedness between potential partners or on the MHC similarity between mates. Three parameters were assessed: (i) the number of shared alleles between partners (x and y) at the MHC (M(xy)), (ii) the MHC amino-acid genotypic distance between mates' genotypes (AA(xy)), and (iii) genetic relatedness between mates (r(xy)). We found that Atlantic salmon choose their mates in order to increase the heterozygosity of their offspring at the MHC and, more specifically, at the peptide-binding region, presumably in order to provide them with better defence against parasites and pathogens. This was supported by a significant difference between the observed and expected AA(xy) (p = 0.0486). Furthermore, mate choice was not a mechanism of overall inbreeding avoidance as genetic relatedness supported a random mating scheme (p = 0.445). This study provides the first evidence that MHC genes influence mate choice in fish.
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 | 0.001 | 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) | 0.001 | 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".