Statistical Inference of In Vivo Properties of Human DNA Methyltransferases from Double-Stranded Methylation Patterns

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 ( and ), and an autosomal locus (), where methylation densities are tissue-specific but moderate. We find strong evidence for a high level of processivity of DNMT1 at and , with the mean association tract length being a few hundred base pairs. Regardless of tissue types, methylation patterns at are dominated by DNMT1 maintenance events, similar to the two Xi-linked loci, but are insufficiently informative regarding processivity to draw any conclusions about processivity at that locus. At all three loci we find that DNMT1 shows a strong preference for adding methyl groups to hemi-methylated CpG sites over unmethylated sites. The data at all three loci also suggest low (possibly 0) association of the de novo methyltransferases, the DNMT3s, and are consequently uninformative about processivity or preference of these enzymes. We also extend our HMM to reanalyze published data on mouse DNMT1 activities in vitro. The results suggest shorter association tracts (and hence weaker processivity), and much longer non-association tracts than human DNMT1 in vivo

Asymmetric Strand Segregation: Epigenetic Costs of Genetic Fidelity?

Asymmetric strand segregation has been proposed as a mechanism to minimize effective mutation rates in epithelial tissues. Under asymmetric strand segregation, the double-stranded molecule that contains the oldest DNA strand is preferentially targeted to the somatic stem cell after each round of DNA replication. This oldest DNA strand is expected to have fewer errors than younger strands because some of the errors that arise on daughter strands during their synthesis fail to be repaired. Empirical findings suggest the possibility of asymmetric strand segregation in a subset of mammalian cell lineages, indicating that it may indeed function to increase genetic fidelity. However, the implications of asymmetric strand segregation for the fidelity of epigenetic information remain unexplored. Here, I explore the impact of strand-segregation dynamics on epigenetic fidelity using a mathematical-modelling approach that draws on the known molecular mechanisms of DNA methylation and existing rate estimates from empirical methylation data. I find that, for a wide range of starting methylation densities, asymmetric—but not symmetric—strand segregation leads to systematic increases in methylation levels if parent strands are subject to de novo methylation events. I found that epigenetic fidelity can be compromised when enhanced genetic fidelity is achieved through asymmetric strand segregation. Strand segregation dynamics could thus explain the increased DNA methylation densities that are observed in structured cellular populations during aging and in disease

The hypomethylating agent Decitabine causes a paradoxical increase in 5-hydroxymethylcytosine in human leukemia cells

The USFDA approved "epigenetic drug", Decitabine, exerts its effect by hypomethylating DNA, demonstrating the pivotal role aberrant genome-wide DNA methylation patterns play in cancer ontology. Using sensitive technologies in a cellular model of Acute Myeloid Leukemia, we demonstrate that while Decitabine reduces the global levels of 5-methylcytosine (5mC), it results in paradoxical increase of 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC) levels. Hitherto, the only biological mechanism known to generate 5hmC, 5fC and 5caC, involving oxidation of 5mC by members of Ten-Eleven-Translocation (TET) dioxygenase family, was not observed to undergo any alteration during DAC treatment. Using a multi-compartmental model of DNA methylation, we show that partial selectivity of TET enzymes for hemi-methylated CpG dinucleotides could lead to such alterations in 5hmC content. Furthermore, we investigated the binding of TET1-catalytic domain (CD)-GFP to DNA by Fluorescent Correlation Spectroscopy in live cells and detected the gradual increase of the DNA bound fraction of TET1-CD-GFP after treatment with Decitabine. Our study provides novel insights on the therapeutic activity of DAC in the backdrop of the newly discovered derivatives of 5mC and suggests that 5hmC has the potential to serve as a biomarker for monitoring the clinical success of patients receiving DAC

Comparative genomics of the class 4 histone deacetylase family indicates a complex evolutionary history

BACKGROUND: Histone deacetylases are enzymes that modify core histones and play key roles in transcriptional regulation, chromatin assembly, DNA repair, and recombination in eukaryotes. Three types of related histone deacetylases (classes 1, 2, and 4) are widely found in eukaryotes, and structurally related proteins have also been found in some prokaryotes. Here we focus on the evolutionary history of the class 4 histone deacetylase family. RESULTS: Through sequence similarity searches against sequenced genomes and expressed sequence tag data, we identified members of the class 4 histone deacetylase family in 45 eukaryotic and 37 eubacterial species representative of very distant evolutionary lineages. Multiple phylogenetic analyses indicate that the phylogeny of these proteins is, in many respects, at odds with the phylogeny of the species in which they are found. In addition, the eukaryotic members of the class 4 histone deacetylase family clearly display an anomalous phyletic distribution. CONCLUSION: The unexpected phylogenetic relationships within the class 4 histone deacetylase family and the anomalous phyletic distribution of these proteins within eukaryotes might be explained by two mechanisms: ancient gene duplication followed by differential gene losses and/or horizontal gene transfer. We discuss both possibilities in this report, and suggest that the evolutionary history of the class 4 histone deacetylase family may have been shaped by horizontal gene transfers

Runoff sources and land cover change in the Amazon : an end-member mixing analysis from small watersheds

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Biogeochemistry 105 (2011): 7-18, doi:10.1007/s10533-011-9597-8.The flowpaths by which water moves from watersheds to streams has important consequences for the runoff dynamics and biogeochemistry of surface waters in the Amazon Basin. The clearing of Amazon forest to cattle pasture has the potential to change runoff sources to streams by shifting runoff to more surficial flow pathways. We applied end member mixing analysis (EMMA) to ten small watersheds throughout the Amazon in which solute composition of streamwater and groundwater, overland flow, soil solution, throughfall and rainwater were measured, largely as part of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia. We found a range in the extent to which streamwater samples fell within the mixing space determined by potential flowpath end members, suggesting that some water sources to streams were not sampled. The contribution of overland flow as a source of stream flow was greater in pasture watersheds than in forest watersheds of comparable size. Increases in overland flow contribution to pasture streams ranged in some cases from 0% in forest to 27 to 28% in pasture and were broadly consistent with results from hydrometric sampling of Amazon forest and pasture watersheds that indicate 17- to 18-fold increase in the overland flow contribution to stream flow in pastures. In forest, overland flow was an important contribution to stream flow (45 to 57%) in ephemeral streams where flows were dominated by stormflow. Overland flow contribution to stream flow decreased in importance with increasing watershed area, from 21 to 57% in forest and 60 to 89% in pasture watersheds 100 ha. Soil solution contributions to stream flow were similar across watershed area and groundwater inputs generally increased in proportion to decreases in overland flow. Application of EMMA across multiple watersheds indicated patterns across gradients of stream size and land cover that were consistent with patterns determined by detailed hydrometric sampling.This work was supported by National Science Foundation (DEB-0315656, DEB-0640661), the NASA LBA Program (NCC5-686, NCC5-69, NCC5-705, NNG066E88A) and by grants from Brazilian agencies FAPESP (03/13172-2) and CNPq (20199/2005-5)

In Vivo Control of CpG and Non-CpG DNA Methylation by DNA Methyltransferases

The enzymatic control of the setting and maintenance of symmetric and non-symmetric DNA methylation patterns in a particular genome context is not well understood. Here, we describe a comprehensive analysis of DNA methylation patterns generated by high resolution sequencing of hairpin-bisulfite amplicons of selected single copy genes and repetitive elements (LINE1, B1, IAP-LTR-retrotransposons, and major satellites). The analysis unambiguously identifies a substantial amount of regional incomplete methylation maintenance, i.e. hemimethylated CpG positions, with variant degrees among cell types. Moreover, non-CpG cytosine methylation is confined to ESCs and exclusively catalysed by Dnmt3a and Dnmt3b. This sequence position–, cell type–, and region-dependent non-CpG methylation is strongly linked to neighboring CpG methylation and requires the presence of Dnmt3L. The generation of a comprehensive data set of 146,000 CpG dyads was used to apply and develop parameter estimated hidden Markov models (HMM) to calculate the relative contribution of DNA methyltransferases (Dnmts) for de novo and maintenance DNA methylation. The comparative modelling included wild-type ESCs and mutant ESCs deficient for Dnmt1, Dnmt3a, Dnmt3b, or Dnmt3a/3b, respectively. The HMM analysis identifies a considerable de novo methylation activity for Dnmt1 at certain repetitive elements and single copy sequences. Dnmt3a and Dnmt3b contribute de novo function. However, both enzymes are also essential to maintain symmetrical CpG methylation at distinct repetitive and single copy sequences in ESCs