Expressed sequence tags for the chicken genome from a normalized 10-day-old white leghorn whole-embryo cDNA library. 3. DNA sequence analysis of genetic variation in commercial chicken populations
Bibliographic record
Abstract
Single nucleotide polymorphisms (SNPs) have emerged as a major class of DNA markers with the advantage of permitting the development of high-density genetic maps adequate for quantitative trait loci (QTL) identification by linkage-disequilibrium analysis. Here we describe results of a relatively high-depth survey of chicken broiler and layer populations for SNPs in targeted genomic regions of chicken expressed sequence tag (EST) sites. The sequences scanned, representing the composite sequence of 12 amplified fragments for a total of 6489 bp, were randomly distributed, occurring on six different chromosomes or linkage groups in the chicken genome. Although one of the genomic DNA sequences did not match the reference cDNA sequence, another contained an intron that separated two putative exons. The number of SNPs observed within each of the 12 EST-targeted genomic regions ranged from 0 to 10 for a total of 44 and a frequency of 0.7%. About 70% of the polymorphisms were shared between layer and broiler populations. The average heterozygosity within the populations ranged from 0.15 to 0.48, with the layer populations showing the higher heterozygosity. SNPs and oligonucleotides described will provide a resource for genetic analysis in commercial chicken populations. The data appear to indicate that the relative frequency of SNPs in the targeted regions scanned is higher than the frequency reported for any of the other regions scanned to date in other eukaryotic genomes. Additionally, the results suggest that the use of DNA pools may offer an efficient approach to SNP detection in chickens, as has been shown in other vertebrates.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.024 |
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".