statistical inference of in vivo properties of human dna methyltransferases from double-stranded methylation patterns统计推断体内性质的人类从双链dna甲基转移酶甲基化模式.pdfVIP

Statistical Inference of In Vivo Properties of Human DNA Methyltransferases from Double-Stranded Methylation Patterns 1 ¤ 2 ¨ 3 2 2 Audrey Q. Fu * , Diane P. Genereux , Reinhard Stoger , Alice F. Burden , Charles D. Laird , Matthew Stephens4 1 Department of Physiology, Development and Neuroscience, Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom, 2 Department of Biology, University of Washington, Seattle, Washington, United States of America, 3 School of Biosciences, University of Nottingham, Sutton Bonington Campus, Leicestershire, United Kingdom, 4 Departments of Human Genetics and Statistics, University of Chicago, Chicago, Illinois, United States of America Abstract DNA methyltransferases establish methylation patterns in cells and transmit these patterns over cell generations, thereby influencing each cell’s epigenetic states. Three primary DNA methyltransferases have been identified in mammals: DNMT1, DNMT3A and DNMT3B. Extensive in vitro studies have investigated key properties of these enzymes, namely their substrate specificity and processivity. Here we study these properties in vivo, by applying novel statistical analysis methods to double- stranded DNA methylation patterns collected using hairpin-bisulfite PCR. Our analysis fits a novel Hidden Markov Model (HMM) to the observed data, allowing for potential bisulfite conversion errors, and yields statistical estimates of parameters that quantify enzyme processivity and substrate specificity. We apply this model to methylation patterns established in vivo at three loci in humans: two densely methylated inactive X (Xi)-linked loci (FMR 1 and G6PD), and an autosomal locus (LEP), where methylation densities are tissue-specific but moder