Optimized design and data analysis of tag-based cytosine methylation assays

Epigenetic mechanisms of transcriptional regulation are increasingly being studied for their potential influences in human disease pathogenesis. Much of this interest is based on the paradigm of neoplastic transformation, in which epigenetic changes appear to be universal, widespread throughout the genome, causative of critical transcriptional changes and predictive of disease prognosis (reviewed in [1]). Furthermore, these epigenetic changes represent potential pharmacological targets for reversal and amelioration of the disease process [2].Of the large number of regulatory processes referred to as epigenetic, there exist numerous assays to study chromatin component distribution, cytosine methylation and microRNA expression genome-wide. The chromatin components include a large number of post-translational modifications of histones, variant histones, DNA-binding proteins and associated complexes, all tested by chromatin immunoprecipitation (ChIP) approaches coupled with microarray hybridization or massively parallel sequencing (MPS). MicroRNAs can be identified and quantified by using microarrays and MPS, while cytosine methylation can be definitively studied by converting the DNA of the genome using sodium bisulfite, shotgun sequencing the product using MPS and mapping this back to the genome to count how frequently cytosines remain unconverted, indicating their methylation in the starting material, due to the resistance of methylcytosine to bisulfite conversion compared with unmethylated cytosines. This allows nucleotide resolution, strand-specific, quantitative assessment of cytosine methylation, with such studies performed in Arabidopsis [3-5] and human cells to date [6].While this approach represents the ideal means of testing cytosine methylation, the amount of sequencing necessary (for the human genome, over 1 billion sequences of ~75 bp each [6]) to generate quantitative information genome-wide remains prohibitive in terms of cost, limiting these studies to