Global DNA methylation levels in bovine peripheral blood mononuclear cells and in milk somatic cells
Résumé
Epigenetic modifications such as DNA methylation play a role in regulating gene expression and consequently in biological processes like health and diseases. In human, studies provide evidences that the methylome in peripheral blood mononuclear cells (PBMC) can reflect disease susceptibility (Reinius et al, 2012). In dairy cows, the post calving period is characterized by changes associated with an immunosuppression increasing the susceptibility to mastitis as well as post-partum uterine diseases. This study aims to quantify the global DNA methylation levels at two lactation stages (J15 and J60) in PBMC and in milk leukocytes and epithelial cells purified as previously described (Boutinaud et al, 2013). 52 lactating Holstein were housed at two INRA’s experimental dairy farms. Parity, milk production and quality, health and diet were notified. Global DNA methylation (MeDNA) was analyzed by a global quantification using a LUminometric Methylation Assay targeting CpG rich regions. 94 samples of PBMC showed MeDNA variation from 72 to 86%. However, no significant difference in MeDNA was found between breeding, parity and lactation stages. In blood, the proportion of different cell types was determined by cytometry and was found stable during the lactation period. DNA methylation amount does not correlate with each cell population count. The analysis of 48 matched samples (milk leukocytes - epithelial cells – PBMC) demonstrated that MeDNA was cell type specific but not modified with the lactation period or the parity. Some cows exhibited diseases like mastitis or uterine post-partum disease. MeDNA in PBMC from these pathological cows was not significantly altered in comparison with MeDNA in PBMC from healthy individuals. This study highlights that MeDNA is cell type specific. However, the change does not be associated with breeding, parity or health in dairy cattle. Studies to identify of specific changes in DNA methylation using genome-wide analysis are in progress.