Abstract
Genome expression is tightly controlled by different regulatory regions to provide a wide variety of cell types and functions. Identifying these regulatory regions, their characteristics and understand how they interact with each other in a tissue-specific manner is prime importance. This knowledge should help better understand the impact of genomic variants often located in non-coding regions. Besides, cancer development is invariably linked to deregulation of gene expression controls. To pave the way for targeted treatments and precision medicine, it is important to understand how all this machinery is orchestrated.To answer this question, several approaches were developed, most of them based on experimental data of histone modification, methylation and transcription factors (TFs). However, these data are limited to specific samples and cannot be generated for all the regulators and all the patients. First, my thesis research aimed at modeling gene expression based on DNA sequence only. We used a linear model with variable selection, equivalent in term of performances with non-parametric methods and easy to interpret. This model allowed me to compare several types of variables based on the DNA sequence, as TFs binding motifs and nucleotide composition. These variables are computed for various gene regions to estimate their regulatory power and contribution. Strikingly, introns, for which nucleotide composition reflects gene environment, appear to explain an important part of gene expression variation. Furthermore, we demonstrated that the topological domains (TADs), in which interactions are favored, share similar genomic compositions. Our prediction model presumably captures, for every individual, the composition of active TADs.A second aspect of my work studied the regulations occurring in introns. The international FANTOM consortium provided one of the most important transcription start sites (TSSs) atlas and we noticed that the majority of these TSSs are detected into non-coding regions, in particular introns. We thus investigated these intronic TSSs. To determine if these TSSs are functional, we searched for new potential regulatory motifs at the vicinity of these transcription signals. We found that a fraction of them is located 2 bases downstream of a repetition of Ts. Biochemical and genetic evidences suggest that at least part of these signals correspond to sense-intronic long non-coding RNAs, which are expressed in a tissue specific manner. The length of the T repetition also appears to govern the presence of a transcription signal at these loci and indirectly impact on host gene expression. These findings provide one possible molecular explanation for the effect of these short tandem repeats of Ts.