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Title: Reverse engieering gene regulatory networks : elucidation of trancriptome organization, gene function and gene regulation in mammalian systems
Author: Belcastro, Vincenzo
ISNI:       0000 0004 2704 9437
Awarding Body: Open University
Current Institution: Open University
Date of Award: 2011
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The main aim of this thesis was to infer mammalian gene regulatory networks from tens of thousands gene expression profiles via a new "reverse-engineering" approach. Human arid Mouse gene regulatory networks were both inferred and the results collected in a database that represents part of the non-written material that will support. the thesis (http: //rretview. tigem. it). Each gene regulatory network consists of a set of gene pairs (connections) and a score based on Mutual Information, which states their statistical dependence. The inferred connections are organized into a network that allows exploration of the global features of gene regulation in a mammalian cell. We collected a massive and heterogeneous dataset of 22,255 gene expression profiles from a variety of human samples and experimental conditions. We developed a new mutual-information (MI) reverse-engineering approach able to quantify the extent to which the mRNA levels of two genes are related to each other across such a complex dataset. The resulting network consists of 4,817,629 connections among 22,255 transcripts. The inferred connections were compared against known protein-protein and other regulatory interactions to assess their biological significance. We experimentally identified a subset of predicted protein-protein interactions not previously described in the literature. We discovered regulatory modules within the network, consisting of genes strongly connected to each other, which carry out specific biological functions. We found that these connected genes tend to be in physical proximity at the chromatin level in the nucleus. We show that the network can be used to predict the biological function and subcellular localization of a protein, and to elucidate the function of a disease-gene. Specifically we discovered that the gene granulin precursor GRN), whose mutations cause frontotemporal lobar degeneration, is involved in lysosome function. We have developed an online tool ( for querying and exploring the gene regulatory network.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral