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Beyond DNA sequence: Exploring and Exploiting Mammalian DNA Methylation

Abstract

Cytosine DNA methylation (mC) is a chemical modification prevalent in mammalian genome and it plays important roles in transcriptional regulation, development and cell differentiation. Recent studies reveal that mC affects how DNA is interpreted, like an additional information layer on top of the genetic code. Results of both in vitro and in vivo experiments demonstrate that mC is influential on the binding affinity of a number of transcription factors. Furthermore, targeted addition/removal of mC was shown to modulate gene transcription. In addition, while mC was thought to be a stable chemical decoration on DNA, it can be dynamically added or removed during biological processes such as cell differentiation, and its distribution is distinct in different cell types and tissues. Given mC's potential functional impact and cell/tissue specificity, systematically profiling mC across a variety of cell types and tissues is essential for understanding its biological significance. To fill this gap, I first worked with colleagues to dissect the mC landscape of 18 human tissue types from 4 individual. We systematically compared the mC distribution in these human tissues and identified over a million differentially methylated regions, which are strongly overlapped with tissue-specific regulatory DNA elements. The dataset serves as the mC state baseline of normal human tissues. In my second thesis project, I exploited the mC information and developed a computational approach called REPTILE to improve the identification of enhancers, the regulatory DNA elements that promote the transcription of their target genes. Finally, I worked with colleagues to investigate the temporal mC regulation in 12 developing mouse fetal tissues. Our results indicate that mC changes dramatically during development primarily at regulatory DNA elements and it shows a trend of demethylation at fetal stages followed by remethylation after birth. I applied REPTILE on this dataset and delineated hundreds of thousands of transcriptional regulatory DNA elements that are related to tissue development.

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