Genetic architecture of quantitative traits in beef cattle revealed by genome wide association studies of imputed whole genome sequence variants: II: carcass merit traits
Bibliographic record
Abstract
BACKGROUND: Genome wide association studies (GWAS) were conducted on 7,853,211 imputed whole genome sequence variants in a population of 3354 to 3984 animals from multiple beef cattle breeds for five carcass merit traits including hot carcass weight (HCW), average backfat thickness (AFAT), rib eye area (REA), lean meat yield (LMY) and carcass marbling score (CMAR). Based on the GWAS results, genetic architectures of the carcass merit traits in beef cattle were elucidated. RESULTS: , 51, 33, 46, 40, and 38 lead DNA variants on multiple chromosomes were significantly associated with HCW, AFAT, REA, LMY, and CMAR, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on HCW, AFAT, REA, and LMY were found on chromosome 6. On average, missense variants, 3'UTR variants, 5'UTR variants, and other regulatory region variants exhibited larger allele substitution effects on the traits in comparison to other functional classes. The amounts of additive genetic variance explained per DNA variant were smaller for intergenic and intron variants on all the traits whereas synonymous variants, missense variants, 3'UTR variants, 5'UTR variants, downstream and upstream gene variants, and other regulatory region variants captured a greater amount of additive genetic variance per sequence variant for one or more carcass merit traits investigated. In total, 26 enriched cellular and molecular functions were identified with lipid metabolisms, small molecular biochemistry, and carbohydrate metabolism being the most significant for the carcass merit traits. CONCLUSIONS: The GWAS results have shown that the carcass merit traits are controlled by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory, synonymous, and missense functional classes have relatively larger impacts per sequence variant on the variation of carcass merit traits. The genetic architecture as revealed by the GWAS will improve our understanding on genetic controls of carcass merit traits in beef cattle.
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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 | 0.001 |
| 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".