Data from: Genome-wide SNP data revealed the extent of linkage disequilibrium, persistence of phase and effective population size in purebred and crossbred buffalo populations
Bibliographic record
Abstract
Linkage disequilibrium (LD) is a useful parameter for guiding the accuracy and power of both genome-wide association studies (GWAS) and genomic selection (GS) among different livestock species. The present study evaluated the extent of LD, persistence of phase and effective population size (Ne) for the purebred (Mediterranean buffalo; n=411) and crossbred [Mediterranean × Jianghan × Nili-Ravi buffalo, n=9; Murrah × Nili-Ravi × local (Xilin or Fuzhong) buffalo, n=36] buffalo populations using the 90K Buffalo SNP genotyping array. The results showed that the average square of correlation coefficient (r2) between adjacent SNP was 0.13 ± 0.19 across all autosomes for purebred and 0.09 ± 0.13 for crossbred, and the most rapid decline in LD was observed over the first 200 kb. Estimated r2 ≥ 0.2 extended up to approximately 50 kb in crossbred and 170 kb in purebred populations, while average r2 values ≥ 0.3 were respectively observed in the approximately 10 kb and 60 kb in the crossbred and purebred populations. The largest phase correlation (RP,C = 0.47) was observed at the distance of 100 kb, suggesting that this phase was not actively preserved between the two populations. Estimated Ne for the purebred and crossbred population at the current generation was 387 and 113 individuals, respectively. These findings may provide useful information to guide the GS and GWAS in buffaloes.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.007 | 0.015 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".