Análises genômicas para composição predita de ácidos graxos do leite em bovinos leiteiros: uma perspectiva longitudinal
Bibliographic record
Abstract
Milk fat composition has important implications in the nutritional and processing properties of milk. In addition to nutritional and health aspects, milk fat composition can also be associated with cow physiological and health status. Milk fatty composition can be improved through various ways, including modification of the cow’s diet and genetic selection. The main objectives of this study were: 1) to estimate genetic parameters for five milk fatty acid (FA) groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted based on milk mid-infrared spectroscopy, for Canadian Ayrshire, Holstein and Jersey breeds; 2) to perform genomic prediction of breeding values using a longitudinal single-step GBLUP approach for these five traits; 3) to conduct a single-step genome-wide association study aiming to identify genomic regions, candidate genes and metabolic pathways associated with milk FA, and consequently, to understand the underlying biology of these traits. We used 31,709 test-day records of 9,648 Ayrshire cows from 268 herds, 629,769 records of 201,465 Holstein cows from 6,105 herds, and 34,341 records of 11,479 Jersey cows from 883 herds. The genomic database contained a total of 2,330 Ayrshire, 8,865 Holstein, and 1,019 Jersey animals. The average daily h2 ranged from 0.18 (long-chain FA) to 0.34 (medium-chain FA), from 0.24 (unsaturated FA) to 0.47 (medium-chain and saturated FAs) and from 0.25 (long-chain and unsaturated FAs) to 0.52 (medium-chain and saturated FAs) for Ayrshire, Holstein and Jersey, respectively. The reliability of the genomic prediction, when considering τ and ω equal to 1 (default), ranged from 0.540 (saturated) to 0.746 (unsaturated) in Ayrshire, and from 0.564 (long-chain) to 0.737 (medium-chain) in Holstein. When using the optimal τ and ω values, the Genomic Estimated Breeding Value’ reliability ranged from 0.528 (saturated) to 0.786 (unsaturated) in Ayrshire, and from 0.583 (long-chain) to 0.732 (short-chain) in Holstein. Important genomic regions were identified in the chromosomes BTA3, BTA5, BTA12, BTA13, BTA14, BTA16, BTA18, BTA20, and BTA21. The proportion of the variance explained by 20 adjacent SNPs ranged from 0.70% (SFA) to 1.12% (SCFA) in Ayrshire, from 0.71% (SFA) to 15.12% (LCFA) in Holstein, and from 0.70% (UFA) to 3.23% (MCFA) in Jersey. Important candidate genes with respective pathways were also identified. Important candidate genes and pathways were also identified. The results of this study contribute to better understand the genetic architecture of predicted milk FA in dairy cattle and will be of great value for the implementation of genomic selection for these traits.
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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 | 0.001 | 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".