Dna Methylation Dynamics And Human Diseases PDF Download

T helper cells play a central role in orchestrating immune responses in humans. Upon encountering a foreign antigen, T helper cells are activated followed by a differentiation process where the cells are specialised to help combating the infection. Dysregulation of T helper cell activation, differentiation and function has been implicated in numerous diseases, including autoimmunity and cancer. Whereas gene-regulatory networks help drive T-cell differentiation, acquisition of stable cell states require heritable epigenetic signals, such as DNA methylation. Indeed, the establishment of DNA methylation patterns is a key part of appropriate T-cell differentiation but how this is regulated over time remains unknown. Methylation can be directly attached to cytosine residues in DNA to form 5-methylcytosine (5mC) but the removal of DNA methylation requires multiple enzymatic reactions, commonly initiated by the conversion into 5-hydroxymethylcytosine (5hmC), thus creating a highly complex regulatory system. This thesis aimed to investigate how DNA methylation is dynamically regulated during T-cell differentiation. To this end, we employed large-scale profiling techniques combining gene expression as well as genome-wide 5mC and 5hmC measurements to construct a time-series model of epigenetic regulation of differentiation. This revealed that early T-cell activation was accompanied by extensive genome-wide deposition of 5hmC which resulted in demethylation upon proliferation. Early DNA methylation remodelling through 5hmC was not only indicative of demethylation events during T-cell differentiation but also marked changes persisting longterm in memory T-cell subsets. These results suggest that priming of epigenetic landscapes in T-cells is initiated during early activation events, preceding any establishment of a stable lineage, which are then maintained throughout the cells lifespan. The regions undergoing remodelling were also highly enriched for genetic variants in autoimmune diseases which we show to be functional through disruption of protein binding. These variants could potentially disrupt gene-regulatory networks and the establishment of epigenetic priming, highlighting the complex interplay between genetic and epigenetic layers. In the course of this work, we discovered that a commonly used technique to study genome-wide DNA modifications, DNA immunoprecipitation (DIP)-seq, had a false discovery rate between 50-99% depending on the modification and cell type being assayed. This represented inherent technical errors related to the use of antibodies resulting in off-target binding of repetitive sequences lacking any DNA modifications. These sequences are common in mammalian genomes making robust detection of rare DNA modifications very difficult due to the high background signals. However, offtarget binding could easily be controlled for using a non-specific antibody control which greatly improved data quality and biological insight of the data. Although future studies are advised to use alternative methods where available, error correction is an acceptable alternative which will help fuel new discoveries through the removal of extensive background signals. Taken together, this thesis shows how integrative use of high-resolution epigenomic data can be used to study complex biological systems over time as well as how these techniques can be systematically characterised to identify and correct errors resulting in improved detection.