A high-density SNP-based linkage map of the chicken genome reveals sequence features correlated with recombination rate
Bibliographic record
Abstract
The resolution of the chicken consensus linkage map has been dramatically improved in this study by genotyping 12,945 single nucleotide polymorphisms (SNPs) on three existing mapping populations in chicken: the Wageningen (WU), East Lansing (EL), and Uppsala (UPP) mapping populations. As many as 8599 SNPs could be included, bringing the total number of markers in the current consensus linkage map to 9268. The total length of the sex average map is 3228 cM, considerably smaller than previous estimates using the WU and EL populations, reflecting the higher quality of the new map. The current map consists of 34 linkage groups and covers at least 29 of the 38 autosomes. Sex-specific analysis and comparisons of the maps based on the three individual populations showed prominent heterogeneity in recombination rates between populations, but no significant heterogeneity between sexes. The recombination rates in the F(1) Red Jungle fowl/White Leghorn males and females were significantly lower compared with those in the WU broiler population, consistent with a higher recombination rate in purebred domestic animals under strong artificial selection. The recombination rate varied considerably among chromosomes as well as along individual chromosomes. An analysis of the sequence composition at recombination hot and cold spots revealed a strong positive correlation between GC-rich sequences and high recombination rates. The GC-rich cohesin binding sites in particular stood out from other GC-rich sequences with a 3.4-fold higher density at recombination hot spots versus cold spots, suggesting a functional relationship between recombination frequency and cohesin binding.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".