Gene expression regulation is dynamic and specific to various factors such as developmental stages, environmental conditions, and stimulation of pathogens. Nowadays, a tremendous amount of transcriptome data sets are available from diverse species. This trend enables us to perform comparative transcriptome analysis that identifies conserved or diverged gene expression responses across species using transcriptome data. The goal of this dissertation is to develop and apply approaches of comparative transcriptomics to transfer knowledge from model species to non-model species with the hope that such an approach can contribute to the improvement of crop yield and human health. First, we presented a comprehensive method to identify cross-species modules between two plant species. We adapted the unsupervised network-based module finding method to identify conserved patterns of co-expression and functional conservation between Arabidopsis, a model species, and soybean, a crop species. Second, we compared drought-responsive genes across Arabidopsis, soybean, rice, corn, and Populus in order to explore the genomic characteristics that are conserved under drought stress across species. We identified hundreds of common gene families and conserved regulatory motifs between monocots and dicots. We also presented a BLS-based clustering method which takes into account evolutionary relationships among species to identify conserved co-expression genes. Last, we analyzed single-cell RNA-seq data from monocytes to attempt to understand regulatory mechanism of innate immune system under low-grade inflammation. We identified novel subpopulations of cells treated with lipopolysaccharide (LPS), that show distinct expression patterns from pro-inflammatory genes. The data revealed that a promising therapeutic reagent, sodium 4-phenylbutyrate, masked the effect of LPS. We inferred the existence of specific cellular transitions under different treatments and prioritized important motifs that modulate the transitions using feature selection by a random forest method. There has been a transition in genomics research from bulk RNA-seq to single-cell RNA-seq, and scRNA-seq has become a widely used approach for transcriptome analysis. With the experience we gained by analyzing scRNA-seq data, we plan to conduct comparative single-cell transcriptome analysis across multiple species. / Doctor of Philosophy / All cells in an organism have the same set of genes, but there are different cell types, tissues, organs with different functions as the organism ages or under different conditions. Gene expression regulation is one mechanism that modulates complex, dynamic, and specific changes in tissues or cell types for any living organisms. Understanding gene regulation is of fundamental importance in biology. With the rapid advancement of sequencing technologies, there is a tremendous amount of gene expression data (transcriptome) from individual species in public repositories. However, major studies have been reported from several model species and research on non-model species have relied on comparison results with a few model species. Comparative transcriptome analysis across species will help us to transform knowledge from model species to non-model species and such knowledge transfer can contribute to the improvement of crop yields and human health. The focus of my dissertation is to develop and apply approaches for comparative transcriptome analysis that can help us better understand what makes each species unique or special, and what kinds of common functions across species have been passed down from ancestors (evolutionarily conserved functions). Three research chapters are presented in this dissertation. First, we developed a method to identify groups of genes that are commonly co-expressed in two species. We chose seed development data from soybean with the hope to contribute to crop improvement. Second, we compared gene expression data across five plant species including soybean, rice, and corn to provide new perspectives about crop plants. We chose drought stress to identify conserved functions and regulatory factors across species since drought stress is one of the major stresses that negatively impact agricultural production. We also proposed a method that groups genes with evolutionary relationships from an unlimited number of species. Third, we analyzed single-cell RNA-seq data from mouse monocytes to understand the regulatory mechanism of the innate immune system under low-grade inflammation. We observed how innate immune cells respond to inflammation that could cause no symptoms but persist for a long period of time. Also, we reported an effect of a promising therapeutic reagent (sodium 4-phenylbutyrate) on chronic inflammatory diseases. The third project will be extended to comparative single-cell transcriptome analysis with multiple species.

Les cellules souches somatiques présentent habituellement un comportement très différent des cellules souches pluripotentes. Les bases moléculaires de l’auto-renouvellement des cellules souches embryonnaires ont été récemment déchiffrées grâce à la facilité avec laquelle nous pouvons maintenant les purifier et les maintenir en culture durant de longues périodes de temps. Par contre, il en va tout autrement pour les cellules souches hématopoïétiques. Dans le but d’en apprendre davantage sur le fonctionnement moléculaire de l’auto-renouvellement des cellules souches hématopoïétiques, j’ai d’abord conçu une nouvelle méthode de criblage gain-de-fonction qui répond aux caprices particuliers de ces cellules. Partant d’une liste de plus de 700 facteurs nucléaires et facteurs de division asymétrique candidats, j’ai identifié 24 nouveaux facteurs qui augmentent l’activité des cellules souches hématopoïétiques lorsqu’ils sont surexprimés. J’ai par la suite démontré que neuf de ces facteurs agissent de manière extrinsèque aux cellules souches hématopoïétiques, c’est-à-dire que l’effet provient des cellules nourricières modifiées en co-culture. J’ai également mis à jour un nouveau réseau de régulation de transcription qui implique cinq des facteurs identifiés, c’est-à-dire PRDM16, SPI1, KLF10, FOS et TFEC. Ce réseau ressemble étrangement à celui soutenant l’ostéoclastogénèse. Ces résultats soulèvent l’hypothèse selon laquelle les ostéoclastes pourraient aussi faire partie de la niche fonctionnelle des cellules souches hématopoïétiques dans la moelle osseuse. De plus, j’ai identifié un second réseau de régulation impliquant SOX4, SMARCC1 et plusieurs facteurs identifiés précédemment dans le laboratoire, c’est-à-dire BMI1, MSI2 et KDM5B. D’autre part, plusieurs indices accumulés tendent à démontrer qu’il existe des différences fondamentales entre le fonctionnement des cellules souches hématopoïétiques murines et humaines. / Somatic stem cells usually exhibit a very different behavior compared to pluripotent stem cells. The molecular basis of embryonic stem cell self-renewal was recently decrypted by the relative straightforwardness with which we can now purify and maintain these cells in culture for long periods of time. However, this is not the case with hematopoietic stem cells. In order to elucidate the molecular mechanisms of hematopoietic stem cell self-renewal, I developed a novel gain-of-function screening strategy, which bypasses some constraints found with these cells. Starting from a list of more than 700 candidate nuclear factors and asymmetric division factors, I have identified 24 new factors that increase hematopoietic stem cell activity when overexpressed. I have also found that nine of these factors act extrinsically to hematopoietic stem cells, i.e., the effect comes from the engineered feeder cells in co-culture. Moreover, I have revealed a new transcriptional regulatory network including five of the factors identified, i.e., PRDM16, SPI1, KLF10, FOS and TFEC. This network is particularly similar to that involved in osteoclastogenesis. These results raise the hypothesis that osteoclasts might also be part of the functional hematopoietic stem cell niche in the bone marrow. Furthermore, I have identified a second regulatory network involving SOX4, SMARCC1 and several factors previously identified in the laboratory, i.e., BMI1, MSI2 and KDM5B. Besides, several lines of evidence tend to show that there are fundamental differences between mouse and human hematopoietic stem cells.

Les facteurs de transcription sont des protéines spécialisées qui jouent un rôle important dans différents processus biologiques tel que la différenciation, le cycle cellulaire et la tumorigenèse. Ils régulent la transcription des gènes en se fixant sur des séquences d’ADN spécifiques (éléments cis-régulateurs). L’identification de ces éléments est une étape cruciale dans la compréhension des réseaux de régulation des gènes. Avec l’avènement des technologies de séquençage à haut débit, l’identification de tout les éléments fonctionnels dans les génomes, incluant gènes et éléments cis-régulateurs a connu une avancée considérable. Alors qu’on est arrivé à estimer le nombre de gènes chez différentes espèces, l’information sur les éléments qui contrôlent et orchestrent la régulation de ces gènes est encore mal définie. Grace aux techniques de ChIP-chip et de ChIP-séquençage il est possible d’identifier toutes les régions du génome qui sont liées par un facteur de transcription d’intérêt. Plusieurs approches computationnelles ont été développées pour prédire les sites fixés par les facteurs de transcription. Ces approches sont classées en deux catégories principales: les algorithmes énumératifs et probabilistes. Toutefois, plusieurs études ont montré que ces approches génèrent des taux élevés de faux négatifs et de faux positifs ce qui rend difficile l’interprétation des résultats et par conséquent leur validation expérimentale. Dans cette thèse, nous avons ciblé deux objectifs. Le premier objectif a été de développer une nouvelle approche pour la découverte des sites de fixation des facteurs de transcription à l’ADN (SAMD-ChIP) adaptée aux données de ChIP-chip et de ChIP-séquençage. Notre approche implémente un algorithme hybride qui combine les deux stratégies énumérative et probabiliste, afin d’exploiter les performances de chacune d’entre elles. Notre approche a montré ses performances, comparée aux outils de découvertes de motifs existants sur des jeux de données simulées et des jeux de données de ChIP-chip et de ChIP-séquençage. SAMD-ChIP présente aussi l’avantage d’exploiter les propriétés de distributions des sites liés par les facteurs de transcription autour du centre des régions liées afin de limiter la prédiction aux motifs qui sont enrichis dans une fenêtre de longueur fixe autour du centre de ces régions. Les facteurs de transcription agissent rarement seuls. Ils forment souvent des complexes pour interagir avec l’ADN pour réguler leurs gènes cibles. Ces interactions impliquent des facteurs de transcription dont les sites de fixation à l’ADN sont localisés proches les uns des autres ou bien médier par des boucles de chromatine. Notre deuxième objectif a été d’exploiter la proximité spatiale des sites liés par les facteurs de transcription dans les régions de ChIP-chip et de ChIP-séquençage pour développer une approche pour la prédiction des motifs composites (motifs composés par deux sites et séparés par un espacement de taille fixe). Nous avons testé ce module pour prédire la co-localisation entre les deux demi-sites ERE qui forment le site ERE, lié par le récepteur des œstrogènes ERα. Ce module a été incorporé à notre outil de découverte de motifs SAMD-ChIP. / Transcription factors (TF) play important roles in various biological processes such as differentiation, cell cycle progression and tumorigenesis. They regulate gene expression by binding to specific DNA sequences (TFBS). Identifying these cis-regulatory elements is a crucial step to understand gene regulatory networks. Technological developments have enhanced DNA sequencing at genomic scale. On the basis of the resulting sequences, computational biologists now attempt to localize the most important functional regions, starting with genes, but also importantly the whole genome characterization of transcription factor binding sites and allow the development of several computational DNA motif discovery tools. Although these various tools are widely used and have been successful at discovering novel motifs, they are not adapted to ChIP-chip and ChIP-sequencing data. The main drawback of these approaches is that most of the predicted motifs represent artifacts due to an inefficient assessment of their enrichment. This thesis is about transcription factor proteins and statistical analysis of their binding sites in ChIP-chip and ChIP-sequencing data. The first objective was to develop a new do novo DNA motif discovery tool adapted to ChIP-chip and ChIP-sequencing data. SAMD-ChIP combines enumerative and stochastic strategies to predict enriched motifs in the vicinity of the ChIP peak summits. Our approach is an automated pipeline that includes motif discovery, motif clustering, motif optimization and finally motif identification using transcription factor (TF) databases. SAMD-ChIP outperforms state-of-the-art motif discovery tools in term of the number of predicted motifs and the prediction of rare and degenerate motifs. In particular, SAMD-ChIP efficiently identifies gapped motifs such as inverted or direct repeats bound by nuclear receptors and composite motifs resulting from the association of different single TF binding sites. The underlying assumption of the second objective is that in regulatory regions, binding sites of interacting transcription factors co-occur more often than expected by chance in the vicinity of the ChIP-peak summits. We proposed an approach to predict transcription factor binding sites co-localization based on the prediction of single motifs by do novo motif discovery tools or by using TFBS models from TF data bases.

Die Etablierung von Hochdurchsatz-Technologien zur Durchführung von Genexpressionsmessungen führte in den letzten 20 Jahren zu einer stetig wachsende Menge an verfügbaren Daten. Sie ermöglichen durch Kombination einzelner Experimente neue Vergleichsstudien zu kombinieren oder Experimente aus verschiedenen Studien zu großen Datensätzen zu vereinen. Dieses Vorgehen wird als Meta-Analyse bezeichnet und in dieser Arbeit verwendet, um einen großen Genexpressionsdatensatz aus öffentlich zugänglichen T-Zell Experimenten zu erstellen. T-Zellen sind Immunzellen, die eine Vielzahl von unterschiedlichen Funktionen des Immunsystems inititiieren und steuern. Sie können in verschiedene Subtypen mit unterschiedlichen Funktionen differenzieren. Der mittels Meta-Analyse erstellte Datensatz beinhaltet nur Experimente zu einem T-Zell-Subtyp, den regulatorischen T-Zellen (Treg) bzw. der beiden Untergruppen, natürliche Treg (nTreg) und induzierte Treg (iTreg) Zellen. Eine bisher unbeantwortete Frage lautet, welche subtyp-spezifischen gen-regulatorische Mechanismen die T-Zell Differenzierung steuern. Dazu werden in dieser Arbeit zwei spezifische Herausforderungen der Treg Forschung behandelt: (i) die Identifikation von Zelloberflächenmarkern zur Unterscheidung und Charakterisierung der Subtypen, sowie (ii) die Rekonstruktion von Treg-Zell-spezifischen gen-regulatorischen Netzwerken (GRN), die die Differenzierungsmechanismen beschreiben. Die implementierte Meta-Analyse kombiniert mehr als 150 Microarray-Experimente aus über 30 Studien in einem Datensatz. Dieser wird benutzt, um mittels Machine Learning Zell-spezifische Oberflächenmarker an Hand ihres Expressionsprofils zu identifizieren. Mit der in dieser Arbeit entwickelten Methode wurden 41 Genen extrahiert, von denen sechs Oberflächenmarker sind. Zusätzliche Validierungsexperimente zeigten, dass diese sechs Gene die Experimenten beider T-Zell Subtypen sicher unterscheiden können. Zur Rekonstruktion von GRNs vergleichen wir unter Verwendung des erstellten Datensatzes 11 verschiedene Algorithmen und evaluieren die Ergebnisse mit Informationen aus Interaktionsdatenbanken. Die Evaluierung zeigt, dass die derzeit verfügbaren Methoden nicht in der Lage sind den Wissensstand Treg-spezifischer, regulatorsicher Mechanismen zu erweitern. Abschließend präsentieren wir eine Datenintegrationstrategie zur Rekonstruktion von GRN am Beispiel von Th2 Zellen. Aus Hochdurchsatzexperimenten wird ein Th2-spezifisches GRN bestehend aus 100 Genen rekonstruiert. Während 89 dieser Gene im Kontext der Th2-Zelldifferenzierung bekannt sind, wurden 11 neue Kandidatengene ohne bisherige Assoziation zur Th2-Differenzierung ermittelt. Die Ergebnisse zeigen, dass Datenintegration prinzipiell die GRN Rekonstruktion ermöglicht. Mit der Verfügbarkeit von mehr Daten mit besserer Qualität ist zu erwarten, dass Methoden zur Rekonstruktion maßgeblich zum besseren Verstehen der zellulären Differenzierung im Immunsystem und darüber hinaus beitragen können und so letztlich die Ursachenforschung von Dysfunktionen und Krankheiten des Immunsystems ermöglichen werden. / Within the last two decades high-throughput gene expression screening technologies have led to a rapid accumulation of experimental data. The amounts of information available have enabled researchers to contrast and combine multiple experiments by synthesis, one of such approaches is called meta-analysis. In this thesis, we build a large gene expression data set based on publicly available studies for further research on T cell subtype discrimination and the reconstruction of T cell specific gene regulatory events. T cells are immune cells which have the ability to differentiate into subtypes with distinct functions, initiating and contributing to a variety of immune processes. To date, an unsolved problem in understanding the immune system is how T cells obtain a specific subtype differentiation program, which relates to subtype-specific gene regulatory mechanisms. We present an assembled expression data set which describes a specific T cell subset, regulatory T (Treg) cells, which can be further categorized into natural Treg (nTreg) and induced Treg (iTreg) cells. In our analysis we have addressed specific challenges in regulatory T cell research: (i) discriminating between different Treg cell subtypes for characterization and functional analysis, and (ii) reconstructing T cell subtype specific gene regulatory mechanisms which determine the differences in subtype-specific roles for the immune system. Our meta-analysis strategy combines more than one hundred microarray experiments. This data set is applied to a machine learning based strategy of extracting surface protein markers to enable Treg cell subtype discrimination. We identified a set of 41 genes which distinguish between nTregs and iTregs based on gene expression profile only. Evaluation of six of these genes confirmed their discriminative power which indicates that our approach is suitable to extract candidates for robust discrimination between experiment classes. Next, we identify gene regulatory interactions using existing reconstruction algorithms aiming to extend the number of known gene-gene interactions for Treg cells. We applied eleven GRN reconstruction tools based on expression data only and compared their performance. Taken together, our results suggest that the available methods are not yet sufficient to extend the current knowledge by inferring so far unreported Treg specific interactions. Finally, we present an approach of integrating multiple data sets based on different high-throughput technologies to reconstruct a subtype-specific GRN. We constructed a Th2 cell specific gene regulatory network of 100 genes. While 89 of these are known to be related to Th2 cell differentiation, we were able to attribute 11 new candidate genes with a function in Th2 cell differentiation. We show that our approach to data integration does, in principle, allow for the reconstruction of a complex network. Future availability of more and more consistent data may enable the use of the concept of GRN reconstruction to improve understanding causes and mechanisms of cellular differentiation in the immune system and beyond and, ultimately, their dysfunctions and diseases.

Embryonic stem cells (ESCs) are characterized by their unlimited capacity for self-renewal and the ability to contribute to every lineage of the developing embryo. The promoters of developmentally regulated loci within these cells are marked by coincident epigenetic modifications of gene activation and repression, termed bivalent domains. Trithorax group (TrxG) and Polycomb Group (PcG) proteins respectively place these epigenetic marks on chromatin and extensively colocalize with Oct4 in ESCs. Although it appears that these cells are poised and ready for differentiation, the switch that permits this transition is critically held in check. The derepression of bivalent domains upon knockdown of Oct4 or PcG underscores their respective roles in maintaining the pluripotent state through epigenetic regulation of chromatin structure. The mechanisms that facilitate the recruitment and retention of Oct4, TrxG, and PcG proteins at developmentally regulated loci to maintain the pluripotent state, however, remain unknown. Oct4 may function as either a transcriptional activator or repressor. Prevailing thought holds that both of these activities are required to maintain the pluripotent state through activation of genes implicated in pluripotency and cell-cycle control with concomitant repression of genes required for differentiation and lineage-specific differentiation. More recent evidence however, suggests that the activator function of Oct4 may play a more critical role in maintaining the pluripotent state (Hammachi et al., 2012). The purpose of the studies described in this dissertation was to clarify the underlying mechanisms by which Oct4 functions in transcriptional activation and repression. By so doing, we wished to contextualize its role in pluripotent cells, and to provide insight into how changes in Oct4 function might account for its ability to facilitate cell fate transitions. As a result of our studies we find that Oct4 function is dependent upon post-translational modifications (PTMs). We find through a combination of experimental approaches, including genome-wide microarray analysis, bioinformatics, chromatin immunoprecipitation, functional molecular, and biochemical analyses, that in the pluripotent state Oct4, Akt, and Hmgb2 participate in a regulatory feedback loop. Akt-mediated phosphorylation of Oct4 facilitates interaction with PcG recruiter Hmgb2. Consequently, Hmgb2 functions as a context dependent modulator of Akt and Oct4 function, promoting transcriptional poise at Oct4 bound loci. Sumoylation of Oct4 is then required to maintain Hmgb2 enrichment at repressed loci and to transmit the H3K27me3 mark in daughter progeny. The expression of Oct4 phosphorylation mutants however, leads to Akt inactivation and initiates the DNA Damage Checkpoint response. Our results suggest that this may subsequently facilitate chromatin reorganization and cell fate transitions. In summary, our results suggest that controlled modulation of Oct4, Akt, and Hmgb2 function is required to maintain pluripotency and for the faithful induction of transcriptional programs required for lineage specific differentiation.

Margaret Sweatmans novel, <i>When Alice Lay Down With Peter</i>, plays with the British Empires adventure story and its creation of manhood. Mimicking this creative process in the Canadian Northwest, Sweatman conceives and births a womans previously erased passion back into the adventure story in a playful, erotic, and politically-charged presentation of the performing female body. Although appreciating the magic realism element to the novel (157), Nicole Markotic suggests that Sweatmans characters, like the readers, become History Tourists and are mere backdrop for the last century or so of Current Events that take precedence over their stories (156). The McCormack women, Markotic argues, have few stories other than going to war, having one momentous sex scene, giving birth (156). Indeed, Sweatmans whirlwind tour through 109 years of well-documented, and already too many times rehashed, rebellions, labour strikes, and world wars, seems to reflect this sentiment, but to limit Sweatman and her characters to only the Empires gender performative is to miss the female body performing as its own Big Bang.<p>Since a womans contingency and agency within the Empires gender performative has been vigorously debated by post modern and cultural theorists, Sweatman chooses to birth her characters into a world of/as performance. Richard Schechner, a pioneer in the field of performance theory, argues in his earlier work, Essays on Performance Theory (1977), that performance is a very inclusive notion of action, in which the performance workshop and the performance strategy of play are much more important than previously imagined (1,61). Sweatman draws on this discovery in order to free her characters to explore passion beyond Imperial and textual constraints. Four generations of McCormack women mimic, mock, and sidewind their way into, around, and beyond the Empires warring narrative and its heterosexual imperative. They are savvy, sexy, and provocative, playing simultaneously as shameless voyeurs, plagiarists, and war artists.

Margaret Sweatmans novel, <i>When Alice Lay Down With Peter</i>, plays with the British Empires adventure story and its creation of manhood. Mimicking this creative process in the Canadian Northwest, Sweatman conceives and births a womans previously erased passion back into the adventure story in a playful, erotic, and politically-charged presentation of the performing female body. Although appreciating the magic realism element to the novel (157), Nicole Markotic suggests that Sweatmans characters, like the readers, become History Tourists and are mere backdrop for the last century or so of Current Events that take precedence over their stories (156). The McCormack women, Markotic argues, have few stories other than going to war, having one momentous sex scene, giving birth (156). Indeed, Sweatmans whirlwind tour through 109 years of well-documented, and already too many times rehashed, rebellions, labour strikes, and world wars, seems to reflect this sentiment, but to limit Sweatman and her characters to only the Empires gender performative is to miss the female body performing as its own Big Bang.<p>Since a womans contingency and agency within the Empires gender performative has been vigorously debated by post modern and cultural theorists, Sweatman chooses to birth her characters into a world of/as performance. Richard Schechner, a pioneer in the field of performance theory, argues in his earlier work, Essays on Performance Theory (1977), that performance is a very inclusive notion of action, in which the performance workshop and the performance strategy of play are much more important than previously imagined (1,61). Sweatman draws on this discovery in order to free her characters to explore passion beyond Imperial and textual constraints. Four generations of McCormack women mimic, mock, and sidewind their way into, around, and beyond the Empires warring narrative and its heterosexual imperative. They are savvy, sexy, and provocative, playing simultaneously as shameless voyeurs, plagiarists, and war artists.

Les cellules souches somatiques présentent habituellement un comportement très différent des cellules souches pluripotentes. Les bases moléculaires de l’auto-renouvellement des cellules souches embryonnaires ont été récemment déchiffrées grâce à la facilité avec laquelle nous pouvons maintenant les purifier et les maintenir en culture durant de longues périodes de temps. Par contre, il en va tout autrement pour les cellules souches hématopoïétiques. Dans le but d’en apprendre davantage sur le fonctionnement moléculaire de l’auto-renouvellement des cellules souches hématopoïétiques, j’ai d’abord conçu une nouvelle méthode de criblage gain-de-fonction qui répond aux caprices particuliers de ces cellules. Partant d’une liste de plus de 700 facteurs nucléaires et facteurs de division asymétrique candidats, j’ai identifié 24 nouveaux facteurs qui augmentent l’activité des cellules souches hématopoïétiques lorsqu’ils sont surexprimés. J’ai par la suite démontré que neuf de ces facteurs agissent de manière extrinsèque aux cellules souches hématopoïétiques, c’est-à-dire que l’effet provient des cellules nourricières modifiées en co-culture. J’ai également mis à jour un nouveau réseau de régulation de transcription qui implique cinq des facteurs identifiés, c’est-à-dire PRDM16, SPI1, KLF10, FOS et TFEC. Ce réseau ressemble étrangement à celui soutenant l’ostéoclastogénèse. Ces résultats soulèvent l’hypothèse selon laquelle les ostéoclastes pourraient aussi faire partie de la niche fonctionnelle des cellules souches hématopoïétiques dans la moelle osseuse. De plus, j’ai identifié un second réseau de régulation impliquant SOX4, SMARCC1 et plusieurs facteurs identifiés précédemment dans le laboratoire, c’est-à-dire BMI1, MSI2 et KDM5B. D’autre part, plusieurs indices accumulés tendent à démontrer qu’il existe des différences fondamentales entre le fonctionnement des cellules souches hématopoïétiques murines et humaines. / Somatic stem cells usually exhibit a very different behavior compared to pluripotent stem cells. The molecular basis of embryonic stem cell self-renewal was recently decrypted by the relative straightforwardness with which we can now purify and maintain these cells in culture for long periods of time. However, this is not the case with hematopoietic stem cells. In order to elucidate the molecular mechanisms of hematopoietic stem cell self-renewal, I developed a novel gain-of-function screening strategy, which bypasses some constraints found with these cells. Starting from a list of more than 700 candidate nuclear factors and asymmetric division factors, I have identified 24 new factors that increase hematopoietic stem cell activity when overexpressed. I have also found that nine of these factors act extrinsically to hematopoietic stem cells, i.e., the effect comes from the engineered feeder cells in co-culture. Moreover, I have revealed a new transcriptional regulatory network including five of the factors identified, i.e., PRDM16, SPI1, KLF10, FOS and TFEC. This network is particularly similar to that involved in osteoclastogenesis. These results raise the hypothesis that osteoclasts might also be part of the functional hematopoietic stem cell niche in the bone marrow. Furthermore, I have identified a second regulatory network involving SOX4, SMARCC1 and several factors previously identified in the laboratory, i.e., BMI1, MSI2 and KDM5B. Besides, several lines of evidence tend to show that there are fundamental differences between mouse and human hematopoietic stem cells.

Embryonic stem cells (ESCs) are characterized by their unlimited capacity for self-renewal and the ability to contribute to every lineage of the developing embryo. The promoters of developmentally regulated loci within these cells are marked by coincident epigenetic modifications of gene activation and repression, termed bivalent domains. Trithorax group (TrxG) and Polycomb Group (PcG) proteins respectively place these epigenetic marks on chromatin and extensively colocalize with Oct4 in ESCs. Although it appears that these cells are poised and ready for differentiation, the switch that permits this transition is critically held in check. The derepression of bivalent domains upon knockdown of Oct4 or PcG underscores their respective roles in maintaining the pluripotent state through epigenetic regulation of chromatin structure. The mechanisms that facilitate the recruitment and retention of Oct4, TrxG, and PcG proteins at developmentally regulated loci to maintain the pluripotent state, however, remain unknown. Oct4 may function as either a transcriptional activator or repressor. Prevailing thought holds that both of these activities are required to maintain the pluripotent state through activation of genes implicated in pluripotency and cell-cycle control with concomitant repression of genes required for differentiation and lineage-specific differentiation. More recent evidence however, suggests that the activator function of Oct4 may play a more critical role in maintaining the pluripotent state (Hammachi et al., 2012). The purpose of the studies described in this dissertation was to clarify the underlying mechanisms by which Oct4 functions in transcriptional activation and repression. By so doing, we wished to contextualize its role in pluripotent cells, and to provide insight into how changes in Oct4 function might account for its ability to facilitate cell fate transitions. As a result of our studies we find that Oct4 function is dependent upon post-translational modifications (PTMs). We find through a combination of experimental approaches, including genome-wide microarray analysis, bioinformatics, chromatin immunoprecipitation, functional molecular, and biochemical analyses, that in the pluripotent state Oct4, Akt, and Hmgb2 participate in a regulatory feedback loop. Akt-mediated phosphorylation of Oct4 facilitates interaction with PcG recruiter Hmgb2. Consequently, Hmgb2 functions as a context dependent modulator of Akt and Oct4 function, promoting transcriptional poise at Oct4 bound loci. Sumoylation of Oct4 is then required to maintain Hmgb2 enrichment at repressed loci and to transmit the H3K27me3 mark in daughter progeny. The expression of Oct4 phosphorylation mutants however, leads to Akt inactivation and initiates the DNA Damage Checkpoint response. Our results suggest that this may subsequently facilitate chromatin reorganization and cell fate transitions. In summary, our results suggest that controlled modulation of Oct4, Akt, and Hmgb2 function is required to maintain pluripotency and for the faithful induction of transcriptional programs required for lineage specific differentiation.

Background Molecular data of histologically classified oligodendrogliomas are available offering the possibility to stratify these human brain tumors into clinically relevant molecular subtypes. Methods Gene copy number, mutation, and expression data of 193 histologically classified oligodendrogliomas from The Cancer Genome Atlas (TCGA) were analyzed by well-established computational approaches (unsupervised clustering, statistical testing, network inference). Results We applied hierarchical clustering to tumor gene copy number profiles and revealed three molecular subgroups within histologically classified oligodendrogliomas. We further screened these subgroups for molecular glioma markers (1p/19q co-deletion, IDH mutation, gain of chromosome 7 and loss of chromosome 10) and found that our subgroups largely resemble known molecular glioma subtypes. We excluded glioblastoma-like tumors (7a10d subgroup) and derived a gene expression signature distinguishing histologically classified oligodendrogliomas with concurrent 1p/19q co-deletion and IDH mutation (1p/19q subgroup) from those with predominant IDH mutation alone (IDHme subgroup). Interestingly, many signature genes were part of signaling pathways involved in the regulation of cell proliferation, differentiation, migration, and cell-cell contacts. We further learned a gene regulatory network associated with the gene expression signature revealing novel putative major regulators with functions in cytoskeleton remodeling (e.g. APBB1IP, VAV1, ARPC1B), apoptosis (CCNL2, CREB3L1), and neural development (e.g. MYTIL, SCRT1, MEF2C) potentially contributing to the manifestation of differences between both subgroups. Moreover, we revealed characteristic expression differences of several HOX and SOX transcription factors suggesting the activity of different glioma stemness programs in both subgroups. Conclusions We show that gene copy number profiles alone are sufficient to derive molecular subgroups of histologically classified oligodendrogliomas that are well-embedded into general glioma classification schemes. Moreover, our revealed novel putative major regulators and characteristic stemness signatures indicate that different developmental programs might be active in these subgroups, providing a basis for future studies.