Methylome and transcriptome data integration reveals potential roles of DNA methylation and candidate biomarkers of cow Streptococcus uberis subclinical mastitis

Abstract

Abstract Background Mastitis caused by different pathogens including Streptococcus uberis (S. uberis) is responsible for huge economic losses to the dairy industry. In order to investigate the potential genetic and epigenetic regulatory mechanisms of subclinical mastitis due to S. uberis, the DNA methylome (whole genome DNA methylation sequencing) and transcriptome (RNA sequencing) of milk somatic cells from cows with naturally occurring S. uberis subclinical mastitis and healthy control cows (n = 3/group) were studied. Results Globally, the DNA methylation levels of CpG sites were low in the promoters and first exons but high in inner exons and introns. The DNA methylation levels at the promoter, first exon and first intron regions were negatively correlated with the expression level of genes at a whole-genome-wide scale. In general, DNA methylation level was lower in S. uberis-positive group (SUG) than in the control group (CTG). A total of 174,342 differentially methylated cytosines (DMCs) (FDR < 0.05) were identified between SUG and CTG, including 132,237, 7412 and 34,693 DMCs in the context of CpG, CHG and CHH (H = A or T or C), respectively. Besides, 101,612 methylation haplotype blocks (MHBs) were identified, including 451 MHBs that were significantly different (dMHB) between the two groups. A total of 2130 differentially expressed (DE) genes (1378 with up-regulated and 752 with down-regulated expression) were found in SUG. Integration of methylome and transcriptome data with MethGET program revealed 1623 genes with significant changes in their methylation levels and/or gene expression changes (MetGDE genes, MethGET P-value < 0.001). Functional enrichment of genes harboring ≥ 15 DMCs, DE genes and MetGDE genes suggest significant involvement of DNA methylation changes in the regulation of the host immune response to S. uberis infection, especially cytokine activities. Furthermore, discriminant correlation analysis with DIABLO method identified 26 candidate biomarkers, including 6 DE genes, 15 CpG-DMCs and 5 dMHBs that discriminated between SUG and CTG. Conclusion The integration of methylome and transcriptome of milk somatic cells suggests the possible involvement of DNA methylation changes in the regulation of the host immune response to subclinical mastitis due to S. uberis. The presented genetic and epigenetic biomarkers could contribute to the design of management strategies of subclinical mastitis and breeding for mastitis resistance.