Genetic diversity of the major histocompatibility complex region in commercial and noncommercial chicken flocks using the LEI0258 microsatellite marker
Bibliographic record
Abstract
Microsatellite marker LEI0258 was used as an indicator to examine the variability of the major histocompatibility complex (MHC) region in 2 commercial layer flocks, 1 experimental layer cross, and 5 noncommercial flocks (used for free-run and free-range meat and egg production). We hypothesized that the populations from noncommercial sources may have more diversity in MHC genes than that in the commercial-source populations. Two related parameters, heterozygosity and the number of alleles harbored by a population, were used to assess the genetic variability. The different combinations of the 22 alleles created 66 genotypes in the 8 chicken populations that were studied. The noncommercial populations, except for the Silkies (SK), harbored more alleles than those in the 2 commercial populations, Lohmann Brown and Lohmann White. The observed heterozygosity of the MHC region was high in all of the populations, except for SK. Considering the 2 parameters we have examined, we can generalize that the intensively selected commercial egg-layer varieties seem to have less genetic variability in their MHC regions compared with that of the noncommercial flocks, which are less intensively selected. The LEI0258 variants can be used as markers to detect most of the MHC haplotypes, but in the different populations the same allele size may not always be associated with the same serologically defined haplotype. The information obtained from this study will be useful for genetic resource conservation and the development of breeding stocks that are suitable for free-range production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".