The impact of spatial correlation on methylation entropy with application to mouse brain methylome

With the advance of bisulfite sequencing technologies, massive amount of methylation data have been generated, which provide unprecedented opportunities to study the epigenetic mechanism and its relationship to other biological processes. A commonly seen feature of the methylation data is the correlation between nearby CpG sites. Although such a spatial correlation was utilized in several epigenetic studies, its interaction to other characteristics of the methylation data has not been fully investigated.

We filled this research gap from an information theoretic perspective, by exploring the impact of the spatial correlation on the methylation entropy (ME). With the spatial correlation taken into account, we derived the analytical relation between the ME and another key parameter, the methylation probability. By comparing it to the empirical relation between the two corresponding statistics, the observed ME and the mean methylation level, genomic loci under strong epigenetic control can be identified, which may serve as potential markers for cell-type specific methylation. The proposed method was validated by simulation studies, and applied to analyze a published dataset of mouse brain methylome.

Compared to other sophisticated methods developed in literature, the proposed method provides a simple but effective way to detect CpG segments under strong epigenetic control (e.g., with bipolar methylation pattern). Findings from this study shed light on the identification of cell-type specific genes/pathways based on methylation data from a mixed cell population.