Computational Analysis of DNA-Methylation and Application to Human Embryonic Stem Cells

Methylation of cytosines is a reversible and dynamic epigenetic DNA modification emerging during differentiation of human embryonic stem cells (hESCs) and throughout mammalian development. Crucial advancements in sequencing technologies have enabled the analysis of DNA methylation on a full genome level. Several studies recently examined the methylomes of hESCs, and investigated genetic and epigenetic dependencies during early differentiation. Methylated DNA immunoprecipitation (MeDIP) followed by high-throughput sequencing (MeDIP-seq) has become a cost-efficient experimental approach for genome wide epigenetic studies. However, it has been shown that MeDIP-seq data has to be corrected for a DNA sequence composition dependent bias in order to produce valid methylation profiles. Therefore, the development and implementation of time-efficient computational methods able to process large amounts of sequencing data with respect to its inherent complexity, is crucial for reducing the imbalance of sequencing data generation and analysis. This chapter introduces to different experimental techniques available for full genome methylation analysis. Subsequently, time efficient algorithms for processing MeDIP-seq data as well as different concepts for normalization are presented. Finally, recent findings of genetic and epigenetic dependencies in hESCs are summarized.

Keywords: DNA methylation, CpG islands, transcription factor binding sites, immunoprecipitation, epigenetics, differentiation, MeDIP, MeDIP-seq, next generation sequencing, linear model, MEDIPS, regulation, transcriptional regulation, pluripotency, normalization.