Responses of the mammary transcriptome of dairy cows to altered photoperiod during late gestation
Bibliographic record
Abstract
Cows exposed to short day photoperiod (SD, 8L:16D) during the 60-day nonlactating period prior to parturition produce more milk in their subsequent lactation compared with cows exposed to long day photoperiod (LD, 16L:8D). Although this response is well established in dairy cows, the underlying mechanisms are not understood. We hypothesized that differential gene expression in cows exposed to SD or LD photoperiods during the dry period could be used to identify the functional basis for the subsequent increase in milk production during lactation. Pregnant, multiparous cows were maintained on an SD or LD photoperiod for 60 days prior to parturition. Mammary biopsies were obtained on days -24 and -9 relative to parturition and Affymetrix GeneChip Bovine Genome Arrays were used to quantify gene expression. Sixty-four genes were differentially expressed (P ≤ 0.05 and fold-change ≥ |1.5|) between SD and LD treatments. Many of these genes were associated with cell growth and proliferation, or immune function. Ingenuity Pathway Analysis predicted upstream regulators to include TNF, TGF-β1, interferon-γ, and several interleukins. In addition, expression of 125 genes was significantly different between day -24 and day -9; those genes were associated with milk component metabolism and immune function. The interaction of photoperiod and time affected 32 genes associated with insulin-like growth factor I signaling. Genes differentially expressed in response to photoperiod were associated with mammary development and immune function consistent with the enhancement of milk yield in the ensuing lactation. Our results provide insight into the mechanisms by which photoperiod affects the mammary gland and subsequently lactation.
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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 | 0.000 |
| 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) | 0.001 | 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".