Inheritance and expression in diploid and triploid Chinook salmon (Oncorhynchus tshawytscha): Segregation distortion at the major histocompatibility complex (MHC) and microsatellite loci.
Bibliographic record
Abstract
In order to investigate the influence of triploidy on genetic inheritance and expression, DNA and mRNA were extracted from diploid and triploid offspring of a single breeding pair of Chinook salmon. Neutral (microsatellite) and a functional markers (class I major histocompability complex (MHC)) were used to analyze the DNA samples for meiotic bias. Significant segregation distortion (P<0.02) was found in the distribution of maternal-origin alleles in the triploid samples at two microsatellite loci and at the MHC locus. No bias was found in the diploid samples, indicating that the distortion was due to maternal dosage effects. This could be the result of a biochemical imbalance caused by dilution of the paternally-derived gene product, or to gene dosage effects of functional, deleterious, maternally-derived proteins. MRNA, converted to cDNA, was also used as a template for MHC amplification and, as expected, the MHC expression in the triploid offspring displayed a dosage effect pattern.Dept. of Biological Sciences. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .J36. Source: Masters Abstracts International, Volume: 45-01, page: 0224. Thesis (M.Sc.)--University of Windsor (Canada), 2006.
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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 | 0.000 | 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".