The recombination landscape in wild house mice inferred using population genomic data
Bibliographic record
Abstract
Abstract Characterizing variation in the rate of recombination across the genome is important for understanding many evolutionary processes. The landscape of recombination has been studied previously in the house mouse, Mus musculus, and it is known that the different subspecies exhibit different suites of recombination hotspots. However, it is not established whether broad-scale variation in the rate of recombination is conserved between the subspecies. In this study, we construct a fine-scale recombination map for the Eastern house mouse subspecies, M. m. castaneus, using 10 individuals sampled from its ancestral range. After inferring phase, we use LDhelmet to construct recombination maps for each autosome. We find that the spatial distribution of recombination rate is strongly positively between our castaneus map and a map constructed using inbred lines of mice derived predominantly from M. m. domesticus. We also find that levels of genetic diversity in M. m. castaneus are positively correlated with the rate of recombination, consistent with pervasive natural selection acting in the genome. Our study suggests that recombination rate variation is conserved at broad scales between M. musculus subspecies .
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".