  A transversal topic of my research has been the development and application
of computational methods for DNA sequence analysis. The methods I have been
developing aim at improving our understanding of the regulation processes
happening in normal and cancer cells. This topic connects together the projects
presented in this thesis. Two chapters of the thesis represent major areas of
my research interests: (1) methods for deciphering transcriptional regulation
and their application to answer specific biological questions, and (2) methods
to study the genome structure and their application in cancer studies. The
first chapter predominantly focuses on transcriptional regulation. Here I
describe my contribution to the development of methodology for the discovery of
transcription factor binding sites and the positioning of histone proteins. I
also explain how sequence analysis, in combination with gene expression data,
can allow the identification of direct target genes of a transcription factor
under study, as well as the physical mechanisms of its action. As two examples,
I provide the results of my study of transcriptional regulation by (i)
oncogenic protein EWS-FLI1 in Ewing sarcoma and (ii) oncogenic transcription
factor Spi-1/PU.1 in erythroleukemia. In the second chapter, I describe the
sequence analysis methods aimed at the identification of the genomic
rearrangements in species with existing reference genome. I explain how the
developed methodology can be applied to detect the structure of cancer genomes.
I provide an example of how such an analysis of tumor genomes can result in a
discovery of a new phenomenon: chromothripsis, when hundreds of rearrangements
occur in a single cellular catastrophe. The thesis is concluded by listing the
major challenges in high-throughput sequencing analysis. I also discuss the
current top questions demanding the integration of sequencing data.

Genomics