To study the interplay between spatial nuclear architecture and transcriptional activity during viral infections, I employed a genome-wide chromosome conformation capture approach (Hi-C) on infected murine and human cells and further enriched those libraries for genomic loci of interest and the viral genomes with biotinylated RNA baits. In parallel, I profiled newly transcribed RNA throughout the entire kinetic of murine cytomegalovirus (mCMV) infection in mice. Host genome rearrangement is a well-known phenomenon of mCMV infection but the underlying mechanisms are largely unknown. Furthermore, HPV infection can lead to cervical cancers in humans, with genomic instability and re-arrangements, leading to dysregulation of gene expression. Thus studying changes in genome architecture at early stages of HPV induced carcinogenesis can further our understanding on how certain integration events can provide a growth advantage. In this study, I identified clusters of genes characterized by distinct kinetic profiles upon CMV infection in the mouse, which were associated with distinct functional terms. ATAC-Seq uncovered proximal promoter regions (PPR) that showed an over-representation of specific transcription factor binding sites in each of the clusters. These correlated well with the annotated functions of the associated clusters. Further, I found that lytic mCMV infection is accompanied by local and global changes of chromosomal interactions in the host cell genome. Notably, chromatin properties, such as gene density, GC content and the association with the nuclear lamina, predict the structural dynamics upon infection and correlate well with transcriptional activity and changes thereof. High-resolution interaction profiles for TSSs of highly induced or repressed genes, suggest that in general, enhancer-promoter interactions already form in untreated cells; and these pre- existing DNA-structures are not significantly altered but function through transient activation or repression of enhancers. Finally, the viral genome showed a distinct pattern of open and closed chromatin late in infection. We found that the 7.2 kb viral intron displays the most open chromatin, and is highly enriched for chromosomal contacts with the host genome. Hi-C and capture Hi-C revealed that both short- (~50 kb) and long-range (~1 Mb) interactions occur during the early stages of HPV induced carcinogenesis between the host and the integrated HPV16 genomes. Integration and direct interactions between the viral genome and the host DNA were shown to be associated with changes in host gene expression. In addition, insertion of the virus can disrupt normal host architecture. In summary, this project pioneers the study of changes in nuclear architecture upon viral infection in man and mice. I uncover numerous structural features and changes of both the viral genomes and the infected host cellular genomes, and I demonstrate that these changes correlate with transcriptional activity.

Rheumatoid arthritis (RA) is a complex autoimmune disease affecting approximately 1% of the population. Multiple factors contribute to the development of RA, with genetic factors accounting for around 60% of the disease risk. Over the last few years, genome-wide association studies (GWAS) have successfully been used to identify regions of the genome predisposing to complex disease. There are now 101 confirmed RA risk loci, but for the vast majority of these loci the causal gene and causal variant remain unidentified and therefore, their function in disease is unexplored. The majority of genetic variants, or single nucleotide polymorphisms (SNPs), associated with disease map to non-coding enhancer regions, which may regulate transcription through long-range interactions with their target genes. The aims of this project were to identify the causal genes within an RA locus, pinpoint the causal variants and elucidate the mechanisms by which the variants modify gene function. Capture Hi-C (CHi-C) was carried out with the aim of identifying long range interactions between disease-associated SNPs and genes in four related autoimmune diseases. Many long-range interactions were identified which implicated novel candidate genes, interactions involving multiple genetic loci which had a common target, and interactions with loci which had previously been implicated in disease. Complex interaction patterns were observed in many of the disease associated loci, particularly in the 6q23 locus which is associated with a number of autoimmune diseases and is the focus of the present thesis. Within the 6q23 locus, associated SNPs lie a large distance from any gene (>180kb) making it difficult to pinpoint the exact causal gene. Results from CHi-C and chromosome conformation capture (3C-qPCR) experiments indicated that restriction fragments containing disease associated intergenic SNPs could display genotype-specific interactions with genes associated with autoimmunity (IL20RA and IFNGR1). Interactions could also be detected with long non-coding RNAs (lncRNAs), The lead SNP in the 6q23 region is in tight LD with eight other SNPs which are equally likely to be causal. Bioinformatics analysis suggested that the most plausible causal SNP in the 6q23 intergenic region was rs6927172, as it maps to an enhancer in both B-cells and T-cells, is in a DNaseI hypersensitivity cluster, shows transcription factor binding and is in a conserved region. Chromatin immunoprecipitation (ChIP) demonstrated binding of chromatin marks of active enhancers (H3K4me1 and H3K27ac) and the transcription factors BCL3 and NF-κB to the rs6927172 SNP target site in Jurkat T-cells and GM12878 B-cells, suggesting the risk allele could be associated with increased regulatory activity. In conclusion, these results show that CHi-C can help identify novel GWAS causal genes with the potential to suggest novel therapeutic targets. For example IL20RA is already a target for a monoclonal antibody which has been shown to be effective in treating RA in clinical trials. This project has also provided compelling evidence that the autoimmune risk variant in the 6q23 locus, rs6927172, is within a complex gene regulatory region, involving multiple immune genes and regulatory elements, such as lncRNAs.

Indiana University-Purdue University Indianapolis (IUPUI) / About 50 million years ago, an Hsmar1 transposon invaded an early primate genome and inserted itself downstream of a SET methyltransferase gene, leading to the birth of a new chimeric protein now called SETMAR. While all other Hsmar1 sequences in the human genome have suffered inactivating mutational damage, the transposase domain of SETMAR has remained remarkably intact, suggesting that it has gained a novel, evolutionarily advantageous function. While SETMAR can no longer transpose itself throughout the genome, it has retained its ancestral sequence-specific DNA binding activity, the importance of which is currently unknown. To investigate this, we performed ChIP-seq to examine SETMAR binding in the human genome. We also utilized RNA-sequencing to assess SETMAR overexpression as well as SETMAR deletion on the human transcriptome. Additionally, we explored SETMAR’s transposase-derived chromatin-looping ability using chromosome-conformation-capture-on-ChIP (4C) in the presence of SETMAR overexpression and performed genome-wide Hi-C to assess the impact of complete SETMAR silencing on global chromatin interactions. ChIP-seq revealed that SETMAR amassed 7,332 unique binding sites, 69% of which included a TIR motif. RNA-sequencing in cells overexpressing SETMAR indicated 177 differentially regulated transcripts, including repression of 17 histone transcripts, suggesting a possible role in chromatin dynamics. RNA-sequencing of parental and SETMAR knockout clones highlighted an average of 5,000 altered transcripts in each cell line, with 343 transcripts significantly differentially expressed in all three knockout clones, many of which participate in embryonic development pathways. 4C analysis in the presence of SETMAR overexpression discovered multiple intrachromosomal looping interactions, and Hi-C analysis of SETMAR knockout cell lines uncovered genome-wide loss of chromatin interactions and disruption of TAD boundaries. The prevalence of SETMAR binding in the human genome combined with its chromatin looping capability and its dramatic effects on the transcriptome suggest a previously undiscovered role for SETMAR as a novel chromatin organizing factor. / 2022-08-17

La structure de l'ADN, des chromosomes et l'organisation du génome sont des sujets fascinants du monde de la biologie. La plupart de la recherche s'est concentrée sur la structure unidimensionnelle du génome, étudiant comment les gènes et les chromosomes sont organisés, et le lien entre l'organisation unidimensionnelle et la régulation des gènes, l'épissage, la méthylation… Cependant, le génome est avant tout organisé dans un espace euclidien tridimensionnel, et cette structure 3D, bien que moins étudiée, joue elle aussi un rôle important dans la fonction génomique de la cellule. La capture de la conformation des chromosomes (3C) et les méthodes qui en sont dérivées, associées au séquençage à haut débit (NGS) mesurent désormais en une seule expérience des interactions physiques entre paire de loci sur tout le génome, permettant ainsi aux chercheurs de découvrir les secrets de l'organisation des génomes. Ces nouvelles technologies ouvrent la voie à des études systématiques et globales sur le repliement de l'ADN dans le noyau. Cependant, ces nouvelles méthodes 3C, comme toute nouvelle technologie, sont accompagnées de nombreux défis computationnels et théoriques. Le premier chapitre est dédié au développement d'une méthode robuste et précise pour inférer un modèle tridimensionnel à partir de données Hi-C. Notre méthode modélise les fréquences d'interaction comme une distribution de Poisson dont l'intensité est une fonction de la distance euclidienne entre paires de loci : nous formulons ainsi l'inférence de la structure 3D comme un problème de maximum de vraisemblance. Nous montrons que notre méthode infère des modèles plus robustes et plus stables selon les données et les résolutions de celles-ci. Le deuxième chapitre est consacré à l'étude de l'architecture du P. falciparum, un petit parasite responsable de la forme la plus virulente et mortelle de la malaria. Ce projet, dont l'objectif était avant tout de répondre à une question biologique, cherchait à comprendre comment l'architecture 3D du génome du P. falciparum est liée à l'expression et la régulation des gènes à différent moments du cycle cellulaire du parasite. En collaboration avec les équipes de K. Le Roch et de W. Noble, spécialisées respectivement dans l'étude du P. falciparum, et dans le développement de méthode computationnelle pour étudier, entre autre, la structure 3D du génome, nous avons construit des modèles de l'organisation du génome à trois moments du cycle cellulaire du parasite. Ceux-ci révèlent que le génome est replié dans le noyau dans une structure complexe, où de nombreux éléments génomiques colocalisent : centromères, télomères… Cette architecture indique une forte association entre l'organisation spatiale du génome et l'expression des gènes. Le dernier chapitre répond à une question très différente, mais aussi liée à l'étude des données 3C. Celles-ci, initialement développées pour étudier la structure tridimensionnelle du génome, ont été récemment utilisées pour des applications très diverses : l'assemblage de génomes de novo, la déconvolution d'échantillons métagénomiques et l'annotation de génomes. Nous décrivons dans ce chapitre une nouvelle méthode, Centurion, qui infère conjointement la position de tous les centromères d'un organisme, en utilisant la propriété qu'ont les centromères à colocaliser dans le noyau. Cette méthode est donc une alternative aux méthodes de détection de centromères classiques, qui, malgré des années de recherche et un enjeu économique certain, n'ont pu identifier la position des centromères dans un certain nombre d'espèces de levure. / The structure of DNA, chromosomes and genome organization is a topic that has fascinated the field of biology for many years. Most research focused on the one-dimensional structure of the genome, studying the linear organizations of genes and genomes and their link with gene expression and regulation, splicing, DNA methylation… Yet, spatial and temporal three-dimensional genome architecture is also thought to play an important role in many genomic functions. Chromosome conformation capture (3C) based methods, coupled with next generation sequencing (NGS), allow the measurement, in a single experiment, of genome wide physical interactions between pairs of loci, thus enabling to unravel the secrets behind 3D organization of genomes. These new technologies have paved the way towards a systematic and genome wide analysis of how DNA folds into the nucleus and opened new avenues to understanding many biological processes, such as gene regulation, DNA replication and repair, somatic copy number alterations and epigenetic changes. Yet, 3C technologies, as any new biotechnology, now poses important computational and theoretical challenges for which mathematically well grounded methods need to be developped. The first chapter is dedicated to developping a robust and accurate method to infer a 3D model of the genome from Hi-C data. Previous methods often formulated the inference as an optimization problem akin to multidimensional scaling (MDS) based on an ad hoc conversion of contact counts into euclidean wish distances. Chromosomes are modeled with a beads-on-a-string model, and the methods attempt to place the beads in a 3D euclidean space to fullfill a number of, often non convex, constraints and such that the pairwise distances between beads are as close as possible to the corresponding wish distances. These approaches rely on dubious hypotheses to convert contact counts into wish distances, challenging the accuracy of the final 3D model. Another limitation is the MDS formulation which is only intuitively motivated, and not grounded on a clear statistical model. To alleviate these problems, our method models contact counts as a Poisson distribution where the intensity is a decreasing function of the spatial distance between elements interacting. We then formulate the 3D structure inference as a maximum likelihood problem. We demonstrate that our method infers robust and stable models across resolutions and datasets. The second chapter focuses on the genome architecture of the P. falciparum, a small parasite responsible for the deadliest and most virulent form of human malaria. This project was biologically driven and aimed at understanding whether and how the 3D structure of the genome related to gene expression and regulation at different time points in the complex life cycle of the parasite. In collaboration with the Le Roch lab and the Noble lab, we built 3D models of the genome at three time points which resulted in a complex genome architecture indicative of a strong association between the spatial genome and gene expression. The last chapter tackles a very different question, also based on 3C-based data. Initially developped to probe the 3D architecture of the chromosomes, Hi-C and related techniques have recently been re-purposed for diverse applications: de novo genome assembly, deconvolution of metagenomic samples and genome annotations. We describe in this chapter a novel method, Centurion, that jointly infers the locations of all centromeres in a single yeast genome from Hi-C data, using the centromeres' tendency to strongly colocalize in the nucleus. Indeed, centromeres are essential for proper chromosome segregation, yet, despite extensive research, centromere locations are unknown for many yeast species. We demonstrate the robustness of our approach on datasets with low and high coverage on well annotated organisms. We then predict centromere coordinates for 6 yeast species that currently lack those annotations.

L’organisation nucléaire de la chromatine n’est pas aléatoire. Sa structure est parfaitement contrôlée, suivant un modèle hiérarchique avec différents niveaux d’organisation et de compaction. A large échelle, chaque chromosome occupe son propre espace au sein du noyau. A plus fine résolution, un chromosome est subdivisé en compartiments actifs ou répressifs, caractérisés par un état de la chromatine plus ou moins compact. A l’échelle du méga-base, cette organisation hiérarchique peut encore être divisée en domaines topologiques (ou TADs), jusqu’à la caractérisation de boucle d’ADN facilitant les interactions entre promoteurs et régions régulatrices. Très brièvement, et bien que les méchanismes exactes restent à déterminer, il a récemment été démontré que l’organisation spatiale de la chromatine dans une cellule normale joue un rôle primordial dans la régulation et l’expression des gènes. L’organisation en domaines topologiques implique la présence de complexes protéiques insulateurs tel que CTCF/cohésine. Ces facteurs jouent un rôle de barrière en restreignant et favorisant les interactions entre éléments régulateurs et gènes à l’intérieur d’un domaine, tout en limitant les interactions entre domaines. De cette façon, deux régions appartenant au même domaine topologique pourront fréquemment interagir, alors que deux régions appartenant à des domaines distincts auront une très faible probabilité d’interaction. Dans la cellule cancéreuse, l’implication de l’épigénome et de l’organisation spatiale de la chromatine dans la progression tumorale reste à ce jour largement inexplorée. Certaines études récentes ont toutefois démontré qu’une altération de la conformation de l’ADN pouvait être associée à l’activation de certains oncogènes. Même si les mécanismes exacts ne sont pas encore connus, cela démontre que l’organisation de la chromatine est un facteur important de la tumorigenèse, permettant, dans certains cas, d’expliquer les méchanismes moléculaires à l’origine de la dérégulation de certains gènes. Parmi les cas rapportés, une alération des régions insulatrices (ou frontières) entre domaines topologiques permettrait à des régions normalement éloignées spatialement de se retrouver en contact, favorisant ainsi l’activation de certains gènes. Une caractérisation systématique de la conformation spatiale des génomes cancéreux pourrait donc permettre d’améliorer nos connaissances de la biologie des cancers. Les techniques haut-débit d’analyse de la conformation de la chromatine sont actuellement largement utilisées pour caractériser les interactions physiques entre régions du génome. Brièvement, ces techniques consistent à fixer, digérer, puis liguer ensemble deux régions du génome spatialement proches. Les fragments d’ADN chimériques ainsi générés peuvent alors être séquencés par leurs extrémités, afin de quantifier le nombre de fois où ces régions ont été trouvées en contact. Parmi les différentes variantes de ces techniques, le Hi-C associé à un séquençage profond permet l’exploration systématique de ces interactions à l’échelle du génome, offrant ainsi une vue détaillée de l’organisation tri-dimensionnelle de la chromatine d’une population cellulaire. / The chromatin is not randomly arranged into the nucleus. Instead, the nuclear organization is tightly controlled following different organization levels. Recent studies have explored how the genome is organized to ensure proper gene regulation within a constrained nuclear space. However, the impact of the epigenome, and in particular the three-dimensional topology of chromatin and its implication in cancer progression remain largely unexplored. As an example, recent studies have started to demonstrate that defects in the folding of the genome can be associated with oncogenes activation. Although the exact mechanisms are not yet fully understood, it demonstrates that the chromatin organization is an important factor of tumorigenesis, and that a systematic exploration of the three-dimensional cancer genomes could improve our knowledge of cancer biology in a near future. High-throughput chromosome conformation capture methods are now widely used to map chromatin interaction within regions of interest or across the genome. The Hi-C technique empowered by next generation sequencing was designed to explore intra and inter-chromosomal contacts at the whole genome scale and therefore offers detailed insights into the spatial arrangement of complete genomes. The aim of this project was to develop computational methods and tools, that can extract relevant information from Hi-C data, and in particular, in a cancer specific context. The presented work is divided in three parts. First, as many sequencing applications, the Hi-C technique generates a huge amount of data. Managing these data requires optimized bioinformatics workflows able to process them in reasonable time and space. To answer this need, we developped HiC-Pro, an optimized and flexible pipeline to process Hi-C data from raw sequencing reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, generates and normalizes intra- and inter-chromosomal contact maps. In addition, HiC-Pro is compatible with all current Hi-C-based protocols.

The development of chromatin conformation capture technology has opened new avenues of study into the 3D structure and function of the genome. Chromatin structure is known to influence gene regulation, and differences in structure are now emerging as a mechanism of regulation between, e.g., cell differentiation and disease vs. normal states. Hi-C sequencing technology now provides a way to study the 3D interactions of the chromatin over the whole genome. However, like all sequencing technologies, Hi-C suffers from several forms of bias stemming from both the technology and the DNA sequence itself. Several normalization methods have been developed for normalizing individual Hi-C datasets, but little work has been done on developing joint normalization methods for comparing two or more Hi-C datasets. To make full use of Hi-C data, joint normalization and statistical comparison techniques are needed to carry out experiments to identify regions where chromatin structure differs between conditions. We develop methods for the joint normalization and comparison of two Hi-C datasets, which we then extended to more complex experimental designs. Our normalization method is novel in that it makes use of the distance-dependent nature of chromatin interactions. Our modification of the Minus vs. Average (MA) plot to the Minus vs. Distance (MD) plot allows for a nonparametric data-driven normalization technique using loess smoothing. Additionally, we present a simple statistical method using Z-scores for detecting differentially interacting regions between two datasets. Our initial method was published as the Bioconductor R package HiCcompare [http://bioconductor.org/packages/HiCcompare/](http://bioconductor.org/packages/HiCcompare/). We then further extended our normalization and comparison method for use in complex Hi-C experiments with more than two datasets and optional covariates. We extended the normalization method to jointly normalize any number of Hi-C datasets by using a cyclic loess procedure on the MD plot. The cyclic loess normalization technique can remove between dataset biases efficiently and effectively even when several datasets are analyzed at one time. Our comparison method implements a generalized linear model-based approach for comparing complex Hi-C experiments, which may have more than two groups and additional covariates. The extended methods are also available as a Bioconductor R package [http://bioconductor.org/packages/multiHiCcompare/](http://bioconductor.org/packages/multiHiCcompare/). Finally, we demonstrate the use of HiCcompare and multiHiCcompare in several test cases on real data in addition to comparing them to other similar methods (https://doi.org/10.1002/cpbi.76).

Development and application of genomic approaches based on 3C methods combined with increasingly powerful imaging approaches have enabled high-resolution genome-wide analysis of the spatial organization of chromosomes in genome function. In this thesis, I first describe an updated protocol for Hi-C (Hi-C 2.0), integrating recent improvements that significantly contribute to the efficient and high-resolution capture of chromatin interactions. Secondly, I present an assessment of the epigenetic landscape and chromosome conformation around the MYC gene in acute myeloid leukemia (AML) cells before and after small molecule, AI-10-49, treatment. MYC is up-regulated upon inhibition of the RUNX1 repressor by the fusion oncoprotein CBFβ-SMMHC. Treatment of AML cells with AI-10-49 blocks the RUNX1-CBFβ-SMMHC interaction, restoring RUNX1 at MYC regulatory elements. We demonstrate that the established loop is maintained and exchange between activating and repressive chromatin complexes at the regulatory elements, rather than altered chromatin topology, mediates disruption of target gene expression. Finally, Hi-C interaction maps represent the population-averaged steady-states. To understand the forces that promote and maintain the association of loci with specific sub-nuclear structures genome-wide, we developed liquid chromatin Hi-C. Detection of intrinsic locus-locus interaction stabilities and chromatin mobility are enabled by fragmenting chromosomes prior to fixation and Hi-C, thus removing strong polymeric constraints. Nuclear compartmentalization was found to be stable for average fragment lengths are 10-25 kb while fragmentation below 6kb led to a gradual loss of spatial genome organization. Dissolution kinetics of chromatin interactions vary widely for different domains and are analyzed in detail in the final chapter of this thesis., with lamin-associated domains being most stable, and speckle-associated loci most dynamic.

Le projet international de synthèse des chromosomes de S. cerevisiae (projet Sc2.0) a débuté il y a une dizaine d'années en suivant des principes établis par le Pr. Jef Boeke. Les chromosomes synthétiques ont été conçus pour augmenter la stabilité du génome en supprimant toutes les séquences répétées (ARNt, éléments transposables...), tout en y ajoutant un système d'évolution inductible dépendant du système Cré/LoxP (système SCRaMbLE), permettant de générer rapidement des réarrangements chromosomiques. Bien que le design du projet Sc2.0 soit très conservateur en ce qui concerne le contenu des gènes, la suppression de plusieurs classes de séquences répétées peut affecter l'organisation du génome et potentiellement altérer les fonctions cellulaires. En utilisant la méthode de capture de conformation de chromosome couplée au séquençage de seconde génération (Hi-C), mon objectif a été de caractériser l'organisation 3D des génomes des souches synthétiques et évoluées. À ce jour, huit chromosomes (syn I, II, III, V, VI, IX-R, X et XII) ont été entièrement assemblés séparément. En utilisant les souches contenant un ou plusieurs de ces chromosomes, nous avons pu montrer que leur organisation génomique n'est globalement pas affectée par leur présence. Quelques exceptions subsistent, avec synIII dont les cassettes HML et HMR ont été retirées, et synXII d'où l'ADNr a été déplacé sur un autre chromosome. À ce stade, nous concluons que l'ADN répétitif dispersé ne conduit pas la conformation moyenne globale du génome de S. cerevisiae. Nous avons aussi exploité les cartes de contacts pour identifier les réarrangements dans les souches SCRaMbLE. / The international project Sc2.0 started 10 years ago by the Pr. Jef Boeke aims to build a fully synthetic genome of S. cerevisiae which increases the genome stability by removing all repeated sequences (tRNA, transposable elements, etc.), and implements SCRaMbLE (for Synthetic Chromosome Rearrangement and Modification by LoxP-mediated Evolution), an inducible, high-throughput chromosome rearrangement system. This design is highly conservative with respect to gene content, the deletion of several classes of repeated sequences and the introduction of thousands of designer changes. However, it may affect genome organization and potentially alter cellular functions. To determine wether those modifications affected the three-dimensional conformation of synthetic chromosmes, we investigated it using chromosomes conformation capture coupled to second generation sequencing method (Hi-C). Currently, eight synthetic chromosomes (synI, synII, synIII, synV, synVI, synIX-R, synX et synXII) have been fully assembled. Using these strains we observed that the large-scale genomic organization is globally unaffected by the presence of synthetic chromosome(s). Two exceptions are synIII, which lacks the silent mating-type cassettes, and synXII, specifically when the ribosomal DNA is moved to another chromosome. We also exploited the contact maps to detect rearrangements induced in these SCRaMbLE strains.

Le programme de réplication d’environ la moitié du génome des mammifères est caractérisé par des U/N-domaines de réplication de l’ordre du méga-base en taille. Ces domaines sont bordés par des origines de réplication maitresses (MaOris) correspondantes à des régions (~200 kb) de chromatine ouverte favorables à l’initiation précoce de la réplication et de la transcription. Grâce au développement récent de technologies à haut débit de capture de conformations des chromosomes (Hi-C), des matrices de fréquences de co-localisation 3D entre toutes les paires de loci sont désormais déterminées expérimentalement. Il est apparu que les U/N-domaines sont reliés à l’organisation du génome en unités structurelles. Dans cette thèse, nous avons effectué une analyse combinée de données de Hi-C de lignées cellulaires humaines et de profils de temps de réplication pour explorer davantage les relations structure/fonction dans le noyau. Cela nous a conduit à décrire de nouveaux domaines de réplication de grande tailles (>3 Mb) : les split-U-domaines aussi bordés par des MaOris; à démontrer que la vague de réplication initiée aux MaOris ne dépend que du temps pendant la phase S et de montrer que le repliement de la chromatine est compatible avec un modèle d’équilibre 3D pour les régions euchromatiniennes à réplication précoces et un modèle d’équilibre 2D pour les régions heterochromatiniennes à réplication tardives associées à la lamina nucléaire. En représentant les matrices de co-localisation issues du Hi-C en réseaux d’interactions structurelles et en déployant des outils de la théorie des graphes, nous avons aussi démontré que les MaOris sont des hubs interconnectés à longue portée dans le réseau structurel, fondamentaux pour l’organisation 3D du génome et nous avons développé une méthodologie multi-échelle basée sur les ondelettes sur graphes pour délimiter objectivement des unités structurelles à partir des données Hi-C. Ce travail nous permet de discuter de la relation entre les domaines de réplication et les unités structurelles entre les différentes lignées cellulaires humaines. / The replication program of about one half of mammalian genomes is characterized by megabase-sized replication U/N-domains. These domains are bordered by master replication origins (MaOris) corresponding to ~200 kb regions of open chromatin favorable for early initiation of replication and transcription. Thanks to recent high-throughput chromosome conformation capture technologies (Hi-C), 3D co-localization frequency matrices between all genome loci are now experimentally determined. It appeared that U/N-domains were related to the organization of the genome into structural units. In this thesis, we performed a combined analysis of human Hi-C data and replication timing profiles to further explore the structure/function relationships in the nucleus. This led us to describe novel large (>3 Mb) replication timing split-U domains also bordered by MaOris, to demonstrate that the replication wave initiated at MaOris only depends of the time during S phase and to show that chromatin folding is compatible with a 3D equilibrium in early-replicating euchromatin regions turning to a 2D equilibrium in the late-replicating heterochromatin regions associated to nuclear lamina. Representing Hi-C co-localization matrices as structural networks and deploying graph theoretical tools, we also demonstrated that MaOris are long-range interconnected hubs in the structural network, central to the 3D organization of the genome and we developed a novel multi-scale methodology based on graph wavelets to objectively delineate structural units from Hi-C data. This work allows us to discuss the relationship between replication domains and structural units across different human cell lines.

L'ADN chromosomique des cellules eucaryotes est fortement condensé au sein d'un complexe nucléoprotéïque, la chromatine. Aussi bien l'organisation spatiale que la composition biochimique (état “épigénomique”) de la chromatine jouent un rôle fondamental dans la régulation des gènes. Grâce aux récents développements des techniques de séquençage à haut-débit, il est possible de déterminer l'état épigénomique local de la chromatine ainsi que la probabilité de contact entre deux sites génomiques (technique dite de “Hi-C”). Ces deux techniques ont permis de mettre en évidence l’existence de domaines d’interaction dont les positions corrèlent fortement avec la segmentation épigénomique de la chromatine. Cependant, les mécanismes responsables de ce couplage sont encore mal compris. L’objectif de cette thèse est de bâtir des modèles physiques permettant de valider l’hypothèse que l’épigénome est un acteur majeur dans le repliement 3D de la chromatine. Pour cela, nous avons tout d’abord développé “IC-Finder”, un algorithme permettant de segmenter les cartes Hi-C en domaines d’interaction. Nous avons alors pu quantifier précisément l’association entre épigénome et organisation de la chromatine. Les corrélations trouvées justifient l’idée de modéliser la chromatine par un copolymère par bloc dont les monomères ont chacun un état épigénomique. Dans ce cadre, nous avons développé une méthode d’inférence des potentiels d'interaction entre sites génomiques à partir des cartes Hi-C expérimentales. Ce travail permettra à plus long terme de prévoir l’organisation de la chromatine sous différentes conditions, ce qui permettra d’étudier en particulier les changements de structure résultant de l’altération de l’épigénome. / DNA of eukaryotes is highly condensed in a nucleoprotein complex called chromatin. Both the spatial organization and the biochemical composition (“epigenomic” state) of the chromatin are fundamental for gene regulation. Remarkably, recent studies indicate that1D epigenomic domains tend to fold into 3D topologically associated domains (TADs) forming specialized nuclear chromatin compartments. In this thesis, we address the question of the coupling between chromatin folding and epigenome. We first built a software called IC-finder to segment HiC maps into interacting domains. We next used it to quantify correlations between the TADs and epigenomic partitions of the genome. This led us to develop a physical model of the chromatin with the working hypothesis that chromatin organization is driven by physical interactions between epigenomic loci. We modeled chromatin as a block copolymer where each block corresponds to an epigenomic domain. With this framework, we developed a method to infer interaction parameters between chromatin loci from experimental Hi-C map. An outcome of such inference process would be a powerful tool to predict chromatin organization in various conditions, allowing investigating in silico changes in TAD formations and long-range contacts when altering the epigenome.