Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR

Area of Science:

• Epigenetics and Genomics
• Bioinformatics and Computational Biology

Background:

• Cytosine methylation at CpG sites is a key epigenetic modification in vertebrates, often silencing gene promoters and linked to diseases like cancer.
• Bisulfite sequencing (BS-seq) is the gold standard for DNA methylation profiling, with Reduced Representation Bisulfite Sequencing (RRBS) offering a cost-efficient approach by targeting CpG-rich regions.

Purpose of the Study:

• To demonstrate the adaptation of RNA-sequencing (RNA-seq) analysis pipelines for differential methylation analysis of RRBS data.
• To apply this adapted pipeline to analyze RRBS profiles from mouse mammary gland cell populations.

Main Methods:

• Adaptation of RNA-seq analysis software (specifically the Bioconductor package edgeR) for RRBS data by incorporating read coverage into the design matrix.
• Differential methylation analysis of RRBS data from mouse mammary gland cell populations.
• Correlation analysis between DNA methylation and gene expression (RNA-seq) data.

Main Results:

• Lineage-committed cells exhibit hyper-methylation compared to progenitor cells across autosomes, but not sex chromosomes.
• A significant negative correlation was observed between promoter methylation and gene expression levels.
• The adapted RNA-seq pipeline proved effective for analyzing RRBS data, enabling access to advanced statistical tools.

Conclusions:

• The adapted RNA-seq pipeline provides a robust and versatile method for differential methylation analysis of RRBS data.
• DNA methylation acts as a regulatory mechanism in epithelial lineage commitment, evidenced by the negative correlation with gene expression.
• This approach facilitates deeper insights into epigenetic regulation and its role in cellular differentiation and disease.