Controlling for conservation in genome-wide DNA methylation studies

Meromit Singer, Lior Pachter

A commonplace analysis in high-throughput DNA methylation studies is the comparison of methylation extent between different functional regions, computed by averaging methylation states within region types and then comparing averages between regions. For example, it has been reported that methylation is more prevalent in coding regions as compared to their neighboring introns or UTRs, leading to hypotheses about novel forms of epigenetic regulation. We have identified and characterized a bias present in these seemingly straightforward comparisons that results in the false detection of differences in methylation intensities across region types. This bias arises due to differences in conservation rates, rather than methylation rates, and is broadly present in the published literature. When controlling for conservation at coding start sites the differences in DNA methylation rates disappear. Moreover, a re-evaluation of methylation rates at intronexon junctions reveals that the magnitude of previously reported differences is greatly exaggerated. We introduce two correction methods to address this bias, an inferencebased matrix completion algorithm and an averaging approach, tailored to address different underlying biological questions. We evaluate how analysis using these corrections affects the detection of differences in DNA methylation across functional boundaries. We report here on a bias in DNA methylation comparative studies that originates in conservation rate differences and manifests itself in the false discovery of differences in DNA methylation intensities and their extents. We have characterized this bias and its broad implications, and show how to control for it so as to enable the study of a variety of biological questions.