Quantitative Trait Loci Affecting Rous Sarcoma Virus Induced Tumor Regression Trait in F2 Intercross Chickens
Bibliographic record
Abstract
We performed a genome-wide linkage and quantitative trait locus (QTL) analysis to confirm the existence of QTL affecting Rous Sarcoma Virus (RSV) induced tumor regression, and to estimate their effects on phenotypic variance in an F2 resource population.The F2 population comprised 158 chickens obtained by crossing tumor regressive White Leghorn (WL) and tumor progressive Rhode Island Red (RIR) lines was measured for tumor formation after RSV inoculation.Forty-three tumor progressive and 28 tumor regressive chickens were then used for genome-wide linkage and QTL analysis using a total of 186 microsatellite markers.Microsatellite markers were mapped on 20 autosomal chromosomes.A significant QTL was detected with marker LEI0258 located within the MHC B region on chromosome 16.This QTL had the highest F ratio (9.8) and accounted for 20.1% of the phenotypic variation.Suggestive QTL were also detected on chromosomes 4, 7 and 10.The QTL on chromosome 4 were detected at the 1% chromosome-wide level explaining 17.5% of the phenotypic variation, and the QTLs on chromosome 7 and 10 were detected at the 5% chromosome-wide level and explained 11.1% and 10.5% of the phenotypic variation, respectively.These results indicate that the QTLs in the non-MHC regions play a significant role in RSV-induced tumor regression.The present study constitutes one of the first preliminary reports in domestic chickens for QTLs affecting RSV-induced tumor regression outside the MHC region.(
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".