Short communication: Genetic association of variations in the osteopontin gene (SPP1) with lactation persistency in dairy cattle
Bibliographic record
Abstract
Improving lactation persistency (LP) in dairy cattle has a beneficial effect on animal health and fertility and herd productivity. A complex trait, LP not only reflects the cow's ability to maintain milk secretion activity after the lactation peak but is also a function of the postcalving development of the mammary gland and, later on, of tissue remodeling as lactation declines. This decline is a consequence of an imbalance between cell proliferation and cell removal. In a previous study, single nucleotide polymorphisms were identified in the osteopontin (OPN) gene, SPP1. Osteopontin is a multifaceted protein that plays an important role in immune regulation and tissue remodeling. Because OPN is involved in involution, it might also have an effect on LP. The objective of the present study was to evaluate whether LP could be influenced by genetic variations in the SPP1 gene. This association with LP was analyzed in the population of 578 bulls characterized in a previous study. The population mean of estimated breeding value (EBV) for LP was 100.95 ± 5.06 units. Allele and genotype association analyses were performed by comparing the frequencies of the different genotypes and alleles with EBV for LP for the respective lactation using logistic regression. The EBV for LP at the first lactation (LP1), second lactation (LP2), and third lactation (LP3) and for overall lactation (OLP) are reported for the genotypes SPP1c.-1301G>A, SPP1c.-1251C>T, SPP1c.-430G>A, and SPP1c.*40A>C. The first single nucleotide polymorphism, SPP1c.-1301G>A, affected LP1, LP2, LP3, and OLP. Analysis of the estimated average allele substitution effects also confirmed that G is a favorable allele for LP, given the gain observed over LP1, LP2, LP3, and OLP. Differences in EBV for LP were observed between animals with different haplotypes at LP1, LP2, LP3, and OLP. Contrast analysis for OLP revealed that mean EBV is greater for block H1 (101.34 ± 0.30) than for animals that do not have H1 (98.20 ± 0.77). The gain with block H1 (GCGA) suggests the presence of the favorable allele G (first position in the block: SPP1c.-1301G). The pleiotropic roles of OPN position it at the crossroads of immune regulation, tissue remodeling, and involution. From a genetic perspective, data from the present study suggest OPN as a candidate gene associated with LP for dairy cows.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.004 | 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".