Gatto, Sole (2013) Integrated bioinformatics analysis of epigenomic and transcriptomic data from ICF syndrome patient's cells. [Tesi di dottorato]


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Item Type: Tesi di dottorato
Resource language: English
Title: Integrated bioinformatics analysis of epigenomic and transcriptomic data from ICF syndrome patient's cells
Date: 1 April 2013
Number of Pages: 92
Institution: Università degli Studi di Napoli Federico II
Department: Biologia e patologia cellullare e molecolare "L. Califano"
Scuola di dottorato: Biotecnologie
Dottorato: Biologia computazionale e bioinformatica
Ciclo di dottorato: 25
Coordinatore del Corso di dottorato:
Date: 1 April 2013
Number of Pages: 92
Keywords: Bioinformatics, NGS, ICF syndrome, epigenetics
Settori scientifico-disciplinari del MIUR: Area 05 - Scienze biologiche > BIO/11 - Biologia molecolare
Date Deposited: 03 Apr 2013 10:18
Last Modified: 10 Jul 2014 13:28

Collection description

Immunodeficiency, Centromeric region instability, Facial anomalies (ICF) syndrome (OMIM 242860), is a human autosomic recessive disease due to mutations in the Dnmt3b gene, characterized by inheritance of aberrant patterns of DNA methylation and heterochromatin defects. How mutations in Dnmt3B and the resulting deficiency in DNA methyltransferase activity result mainly in immunodeficiency has not been clarified yet. It is already known that the expression of several genes and microRNAs is deregulated in ICF lymphoblastoid cell lines (LCLs), being both up- and down-regulated. Subltle and sporadic changes were observed in the epigenetic profile of those genes. It is clear that Dnmt3B mutations affect not only DNA methylation, but also several other expression regulators. The new Next Generation Sequencing (NGS) technologies had a very important role in assessing to what extent these mutations affect the epigenetic landscape of the whole genome. The global DNA methylation profile was generated (Heyn et al., 2011) and the genome-wide mapping of H3K4me3, H3K27me3 and H3K9me3 by chromatin immunoprecipitation-sequencing (ChIP-seq) and correlated those to mRNA transcriptome (obtained by RNA-seq) and to microRNA expression (Gatto et al., 2010) in ICF and control LCLs. Reliable pipelines for the analysis and the integration of these data were developed during this work. In this thesis are described in detail the performed analyses and also the biological results obtained.


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