Heterogeneity and Randomness of DNA Methylation Patterns in Human Embryonic Stem Cells

Abstract

DNA methylation has been proposed to be important in many biological processes and is the subject of intense study. Traditional bisulfite genomic sequencing allows detailed high-resolution methylation pattern analysis of each molecule with haplotype information across a few hundred bases at each locus, but lacks the capacity to gather voluminous data. Although recent technological developments are aimed at assessing DNA methylation patterns in a high-throughput manner across the genome, the haplotype information cannot be accurately assembled when the sequencing reads are short or when each hybridization target only includes one or two cytosine-phosphate-guanine (CpG) sites. Whether a distinct and nonrandom DNA methylation pattern is present at a given locus is difficult to discern without the haplotype information, and the DNA methylation patterns are much less apparent because the data are often obtained only as methylation frequencies at each CpG site with some of these methods. It would facilitate the interpretation of data obtained from high-throughput bisulfite sequencing if the loci with nonrandom DNA methylation patterns could be distinguished from those that are randomly methylated. In this study, we carried out traditional genomic bisulfite sequencing using the normal diploid human embryonic stem (hES) cell lines, and utilized Hamming distance analysis to evaluate the existence of a distinct and nonrandom DNA methylation pattern at each locus studied. Our findings suggest that Hamming distance is a simple, quick, and useful tool to identify loci with nonrandom DNA methylation patterns and may be utilized to discern links between biological changes and DNA methylation patterns in the high-throughput bisulfite sequencing data sets.