Gagliardi, Miriam (2016) Integrative analyses of multi-omic data applied to the study of a rare human disease, the ICF syndrome. [Tesi di dottorato]

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Application of the next-generation sequencing (NGS) technology has transformed epigenetic studies, generating large datasets that can be analyzed in different ways to answer a multitude of questions. Data integration is an essential step to understand intricate biological processes, such as the epigenetic control of gene regulation. Recent "multi-omic" studies proposed the intriguing possibility that the intragenic DNA methylation would play a role in processing of transcripts during transcription modulating the elongation or splicing. Indeed a kinetic model, in which epigenetic modifications affect the rate of transcriptional elongation, and/or a recruitment model, in which adaptor proteins bind to epigenetic modifications recruiting splicing factors have been proposed. Moreover, it was demonstrated that the intragenic methylation in highly transcribed genes is exclusively dependent on the DNMT3B function. However, whether a DNMT3B-dependent epigenetic regulatory network modulates exon usage and transcription of alternative isoforms remains to be determined. Through a large-scale integrative study we show that human DNMT3B germline mutations perturb its intragenic methyltransferase activity, affecting the relative abundance of transcript isoforms in the context of Immunodeficiency, Centromeric instability, Facial anomalies syndrome type-1 (ICF1). This correlates with changes of H3K4me3 and H3K27me3 at isoform-specific transcription start sites. Notably, the newly identified DNMT3B target genes might significantly contribute to ICF1 phenotype.

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