PSVIII-B-15 Potential Involvement of DNA Methylation of First Intron in Transcriptional Regulation During Bovine Subclinical Mastitis Caused by Staphylococcus Aureus
Bibliographic record
Abstract
Abstract DNA methylation involvement in the regulation of mammary gland inflammatory defense against pathogens, including Staphylococcus aureus(SA) has been documented. However, the mechanisms are not clear. The possible influence of DNA methylation of first introns (DNA-MeFI) on transcriptional activities during subclinical mastitis was studied by profiling the methylome (whole genome methylation sequencing) and transcriptome (RNA-sequencing) of milk somatic cells from cows(n=15) with SA subclinical mastitis (SACs) and healthy cows (HCs)(n=13), followed by bioinformatics processing with standard tools. The DNA-MeFI was calculated, for each of 19411 genes found as expressed in the samples, by averaging the methylation levels of all CpG sites in the first intron. At genome-wide, the DNA-MeFIs was inversely correlated with gene expression (GE) (Pearson’s r=-0.173, p=1.60×10-122)(Figure 1-A). Similarly, the difference in the DNA-MeFI and GE between SACs and HCs was also inversely correlated (Pearson’s r=-0.149, p=4.25×10-97)(Figure 1-B). Application of machine learning by Gaussian Mixed model (GMM) using scikit-learn in python to the changes of DNA-MeFI and GE between SACs and HCs revealed 2866 outliers (GMM’s p< 0.005) that showed significant changes in the DNA-MeFI and/or GE. 644 genes with >10% difference in DNA-MeFI and |log2FC| >1 in GE were selected and referred to as differentially methylated and expressed genes (DME-genes). 644 DME-genes were significantly enriched in 5 GO terms and 11 KEGG pathways related to diseases and immune functions, including Staphylococcus aureus infection and Natural killer cell mediated cytotoxicity (Table 1). Furthermore, 74.84% DME-genes showed inverse changes in DNA-MeFI and GE. Besides, the DNA-MeFI of 264 DME-genes were found to correlate significantly with their GE (|rho| >0.3, FDR<0.05), including 225 DME-genes(85.23%) with inverse correlations(rho< -0.3, FDR< 0.05). 39 DME-genes with positive correlations were significantly enriched in 21 GO terms mainly related to metabolic processes. In conclusion, the DNA-MeFI possibly participate in the regulation of gene expression during bovine subclinical mastitis caused by SA.
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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) | 0.002 | 0.001 |
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".