Identification of quantitative trait loci for milk protein percentage in Murrah buffaloes
Bibliographic record
Abstract
Milk protein is an important constituent of milk in buffaloes and is moderately heritable. The milk protein percentage varies significantly between breeds/herds/species. Buffaloes can be selected for higher milk protein percentage and this paper provides QTLs for marker assisted selection in buffaloes. The milk protein percentage records on 2,028 daughters belonging to 12 half sib families were analyzed for the identification of QTLs on 8 chromosomes in buffaloes using chromosome scans. The single marker analysis revealed 74 markers to be associated with milk protein percentage in 12 sire families. When common markers were removed from the analysis, 51 markers remained. The Interval mapping using R/qtl identified 69 QTLs in 12 half sib families on 8 chromosomes of buffalo. The meta QTL analysis defined 25 consensus QTL regions in buffaloes for milk protein percentage. Most of the QTLs identified have been reported for cattle however few new chromosomal locations were also identified to be associated with milk protein percentage in buffaloes. Comparative genomics revealed 1117 genes underlying the QTL regions associated with milk protein percentage. Among these, 109 genes were directly associated with protein metabolism. The protein-protein interaction among the genes and gene ontology analysis and pathways have been identified. These 109 genes have potential to be candidate genes for milk protein percentage 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 | 0.001 | 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 | 0.000 |
| 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 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".