Candidate genes and biological pathways associated with carcass quality traits in beef cattle
Bibliographic record
Abstract
Karisa, B. K., Thomson, J., Wang, Z., Bruce, H. L., Plastow, G. S. and Moore, S. S. 2013. Candidate genes and biological pathways associated with carcass quality traits in beef cattle. Can. J. Anim. Sci. 93: 295-306. The objective of this study was to use the candidate gene approach to identify the genes associated with carcass quality traits in beef cattle steers at the University of Alberta Ranch at Kinsella, Canada. This approach involved identifying positional candidate genes and prioritizing them according to their functions into functional candidate genes before performing statistical association analysis. The positional candidate genes and single nucleotide polymorphisms (SNP) were identified from previously reported quantitative trait loci for component traits including body weight, average daily gain, metabolic weight, feed efficiency and energy balance. Positional candidate genes were then prioritized into functional candidate genes according to the associated gene ontology terms and their functions. A total of 116 genes were considered functional candidate genes and 117 functional SNPs were genotyped and used for multiple marker association analysis using ASReml®. Seven SNPs were significantly associated with various carcass quality traits (P=0.005). The significant genes were associated with biological processes such as fat, glucose, protein and steroid metabolism, growth, energy utilization and DNA transcription and translation as inferred from the protein knowledgebase (UniprotKB). Gene network analysis indicated significant involvement of biological processes related to fat and steroid metabolism and regulation of transcription and translation of DNA.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".