BSCM2TDb

BSCM2TDb catalogs MeDIP-Seq DNA methylation and RNA-Seq transcriptome data to enable investigation of epigenetic regulation in subclinical mastitis (SCM) in water buffalo.

Key Features:

• Genome-Wide Methylation Profiling: MeDIP-Seq data from peripheral blood lymphocytes provide genome-wide DNA methylation information related to SCM.
• Gene Expression Analysis: RNA-Seq profiles from milk somatic cells compare transcriptional changes between healthy and SCM-infected buffaloes.
• Differentially Methylated Regions and Genes: Identification of 3,950 DMRs annotated to 370 DMGs with significant enrichment in promoter regions.
• Pathway Analysis: Hypomethylation-associated pathway activation includes Staphylococcus aureus infection, Th17 cell differentiation, and antigen processing and presentation among defense-response pathways.
• Integration with Transcriptome Data: Integrated methylome–transcriptome analysis links methylation to expression changes, reporting 4,778 significant DEGs of which 67 are also differentially methylated.
• Immune Response Genes: Highlighted downregulated immune-related genes include CSF2RB, LOC102408349, C3 and PZP like, and CPAMD8.
• Epigenetic Associations: Associations between DNA methylation and transposable elements, miRNAs, and lncRNAs are cataloged.

Scientific Applications:

• Host–Pathogen Interaction Analysis: Enables investigation of buffalo host responses to mastitis pathogens at epigenetic and transcriptional levels.
• Epigenetic Regulation Studies: Supports study of DNA methylation impacts on gene regulation in SCM.
• Biomarker Discovery: Facilitates identification of differentially methylated or expressed genes as candidate biomarkers for SCM.
• Pathway and Mechanism Inference: Allows analysis of affected pathways such as Th17 differentiation and antigen presentation in SCM contexts.

Methodology:

Data were generated using MeDIP-Seq for DNA methylation profiling and RNA-Seq for gene expression analysis and stored in a three-tier architecture relational database.