Altered gene expression of epigenetic modifying enzymes in response to dietary supplementation with linseed oil
Bibliographic record
Abstract
Recently we showed that 5% linseed oil (LSO) and 5% safflower oil (SFO) supplementation of cow's diets reduced milk fat yield by 30·38 and 32·42% respectively, accompanied by differential expression of genes and regulation by microRNAs (miRNA). This research communication addresses the hypothesis that epigenetic regulation could be involved in the observed milk fat reduction. Thus, this study investigated the gene expression pattern of major epigenetic modifying enzymes in response to dietary supplementation with LSO or SFO. Twenty-six Canadian Holstein cows in mid lactation were randomly assigned to two groups (13/group) and fed a control diet for 28 d (day -28 to -1) (control period- CP) followed by a treatment period (TP) (control diet supplemented with 5% LSO (LSO treatment) or 5% SFO (SFO treatment) of 28 d (day +1 to +28). After treatment, cows in the two groups were returned to the control diet for another 28 d (day +29 to +56) (post treatment period-PTP). Milk samples were collected on day -1 (CP), +7, +28 (TP) and +56 (PTP) for RNA isolation and measurement of the expression of thirteen epigenetic modifying genes including two DNA methytrasferases (DNMT1, DNMT3A), four histone acetylases (HAT1, KAT2A, KAT5 and CREBBP), five histone deacetylases (HDAC1, HDAC2, HDAC3, SIRT1 and SIRT2) and two histone methytransferases (EHMT2 and PRMT1) by qPCR. Linseed oil supplementation significantly repressed the expression of EHMT2, HDAC2 and HDAC3 on day +7 (P < 0·05) and KAT2A and SIRT2 on day +28 (P < 0·05) as compared with the control period (day -1) while SFO had no effect. When LSO was withdrawn, the expression of some of the genes increased slightly but did not reach control (day -1) levels at the end of the PTP. Our study demonstrated a significant role of LSO in the epigenetic regulation of fatty acid synthesis as compared to SFO. The effect of LSO may be related to its higher degree of unsaturation and might represent a different regulatory mechanism which needs further investigation.
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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".