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Abstract:
Genomic DNA methylation profiles exhibit substantial variation within the human
population, with important functional implications for gene regulation. So far
little is known about the characteristics and determinants of DNA methylation
variation among healthy individuals. We performed bioinformatic analysis of
high-resolution methylation profiles from multiple individuals, uncovering
complex patterns of inter-individual variation that are strongly correlated
with the local DNA sequence. CpG-rich regions exhibit low and relatively
similar levels of DNA methylation in all individuals, but the sequential order
of the (few) methylated among the (many) unmethylated CpGs differs randomly
across individuals. In contrast, CpG-poor regions exhibit substantially
elevated levels of inter-individual variation, but also significant
conservation of specific DNA methylation patterns between unrelated
individuals. This observation has important implications for experimental
analysis of DNA methylation, e.g. in the context of epigenome projects. First,
DNA methylation mapping at single-CpG resolution is expected to uncover
informative DNA methylation patterns for the CpG-poor bulk of the human genome.
Second, for CpG-rich regions it will be sufficient to measure average
methylation levels rather than assaying every single CpG. We substantiate these
conclusions by an in silico benchmarking study of six widely used methods for
DNA methylation mapping. Based on our findings, we propose a cost-optimized
two-track strategy for mammalian methylome projects.
