Transcriptome adaptation of the bovine mammary gland to diets rich in unsaturated fatty acids shows greater impact of linseed oil over safflower oil on gene expression and metabolic pathways
Bibliographic record
Abstract
BACKGROUND: Nutritional strategies can decrease saturated fatty acids (SFAs) and increase health beneficial fatty acids (FAs) in bovine milk. The pathways/genes involved in these processes are not properly defined. Next-generation RNA-sequencing was used to investigate the bovine mammary gland transcriptome following supplemental feeding with 5% linseed oil (LSO) or 5% safflower oil (SFO). Holstein cows in mid-lactation were fed a control diet for 28 days (control period) followed by supplementation with 5% LSO (12 cows) or 5% SFO (12 cows) for 28 days (treatment period). Milk and mammary gland biopsies were sampled on days-14 (control period), +7 and +28 (treatment period). Milk was used to measure fat(FP)/protein(PP) percentages and individual FAs while RNA was subjected to sequencing. RESULTS: Milk FP was decreased by 30.38% (LSO) or 32.42% (SFO) while PP was unaffected (LSO) or increased (SFO). Several beneficial FAs were increased by LSO (C18:1n11t, CLA:10t12c, CLA:9c11t, C20:3n3, C20:5n3, C22:5n3) and SFO (C18:1n11t, CLA:10t12c, C20:1c11, C20:2, C20:3n3) while several SFAs (C4:0, C6:0, C8:0, C14:0, C16:0, C17:0, C24:0) were decreased by both treatments (P < 0.05). 1006 (460 up- and 546 down-regulated) and 199 (127 up- and 72 down-regulated) genes were significantly differentially regulated (DE) by LSO and SFO, respectively. Top regulated genes (≥ 2 fold change) by both treatments (FBP2, UCP2, TIEG2, ANGPTL4, ALDH1L2) are potential candidate genes for milk fat traits. Involvement of SCP2, PDK4, NQO1, F2RL1, DBI, CPT1A, CNTFR, CALB1, ACADVL, SPTLC3, PIK3CG, PIGZ, ADORA2B, TRIB3, HPGD, IGFBP2 and TXN in FA/lipid metabolism in dairy cows is being reported for the first time. Functional analysis indicated similar and different top enriched functions for DE genes. DE genes were predicted to significantly decrease synthesis of FA/lipid by both treatments and FA metabolism by LSO. Top canonical pathways associated with DE genes of both treatments might be involved in lipid/cholesterol metabolism. CONCLUSION: This study shows that rich α-linolenic acid LSO has a greater impact on mammary gland transcriptome by affecting more genes, pathways and processes as compared to SFO, rich in linoleic acid. Our study suggest that decrease in milk SFAs was due to down-regulation of genes in the FA/lipid synthesis and lipid metabolism pathways while increase in PUFAs was due to increased availability of ruminal biohydrogenation metabolites that were up taken and incorporated into milk or used as substrate for the synthesis of PUFAs.
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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 | 0.000 |
| 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) | 0.000 | 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".