In the middle of the 1990’s the microarray technology was introduced. The technology allowed for genome wide analysis of gene expression in one experiment. Since its introduction similar high through-put methods have been developed in other fields of molecular biology. These high through-put methods provide measurements for hundred up to millions of variables in a single experiment and a rigorous data analysis is necessary in order to answer the underlying biological questions. Further complications arise in data analysis as technological variation is introduced in the data, due to the complexity of the experimental procedures in these experiments. This technological variation needs to be removed in order to draw relevant biological conclusions from the data. The process of removing the technical variation is referred to as normalization or pre-processing. During the last decade a large number of normalization and data analysis methods have been proposed. In this thesis, data from two types of high through-put methods are used to evaluate the effect pre-processing methods have on further analyzes. In areas where problems in current methods are identified, novel normalization methods are proposed. The evaluations of known and novel methods are performed on simulated data, real data and data from an in-house produced spike-in experiment.

The human genome is a dynamic structure, recently recognized to present with significant large-scale structural variation. DNA-copy number changes represent one common type of such variation and is found both between individuals and within the somatic cells of the same individual, especially in disease states like cancer.  Apart from DNA-rearrangements, epigenomic changes are increasingly acknowledged as important events in the maintenance of genomic integrity. In this thesis, different array-based methods have been applied for global genomic and epigenomic profiling of both normal and cancer cells. In paper I, a genomic microarray was established and used to determine DNA-copy number variants (CNVs) in a cohort of 76 healthy individuals from three ethnic populations. We identified 315 CNV regions that in total encompassed ~3,5% of the genome. In paper II, the array was utilized to discover CNVs within several differentiated tissues from the same subject. Six variants were identified providing evidence for somatic mosaicism. In paper III and IV we studied pheochromocytomas and paragangliomas, rare endocrine tumours that most often present as benign and sporadic with unclear genetic/epigenetic cause. Genome-wide DNA-copy number analysis of 53 benign and malignant samples in paper III revealed numerous common and novel chromosomal regions of losses and gains. High frequencies of relatively small overlapping regions of deletions were detected on chromosome 1p arm, encompassing several candidate tumour suppressor genes. In paper IV, an epigenomic map for two histone modifications associated with silent (H3K27me3) or active (H3K4me3) gene transcription, was generated for one malignant pheochromocytoma. Integrated analysis of global histone methylation, copy number alterations and gene expression data aided in the identification of candidate tumour genes. In conclusion, the performed studies have contributed to gain knowledge of CNVs in healthy individuals, and identified regions and genes which are likely associated with the development and progression of pheochromocytoma/paraganglioma.

Gene activity is regulated at two separate layers. Through structural and chemical properties of DNA – the primary layer of encoding – local signatures may enable, or disable, the binding of proteins or complexes of them with regulatory potential to the DNA. At a higher level – the structural layer of encoding – gene activity is regulated through the properties of higher order DNA structure, chromatin, and chromosome organization. Cells with abnormal chromosome compaction or organization, e.g. cancer cells, may thus have perturbed regulatory activities resulting in abnormal gene activity. Hence, there is a great need to decode the transcriptional regulation encoded in both layers to further our understanding of the factors that control activity and life of a cell and, ultimately, an organism. Modern genome-wide studies with those aims rely on data-intense experiments requiring sophisticated computational and statistical methods for data handling and analyses. This thesis describes recent advances of analyzing experimental data from quantitative biological studies to decipher the structural layer of encoding in human cells. Adopting an integrative approach when possible, combining multiple sources of data, allowed us to study the influences of chromatin (Papers I and II) and chromosomal aberrations (Paper IV) on transcription. Combining chromatin data with chromosomal aberration data allowed us to identify putative driver oncogenes and tumor-suppressor genes in cancer (Paper IV). Bayesian approaches enabling the incorporation of background information in the models and the adaptability of such models to data have been very useful. Their usages yielded accurate and narrow detection of chromosomal breakpoints in cancer (Papers III and IV) and reliable positioning of nucleosomes and their dynamics during transcriptional regulation at functionally relevant regulatory elements (Paper II). Using massively parallel sequencing data, we explored the chromatin landscapes of human cells (Papers I and II) and concluded that there is a preferential and evolutionary conserved positioning at internal exons nearly unaffected by the transcriptional level. We also observed a strong association between certain histone modifications and the inclusion or exclusion of an exon in the mature gene transcript, suggesting a functional role in splicing.

The key to the complexity of higher organisms lies not in the number of protein coding genes they carry, but rather in the intrinsic complexity of the gene regulatory networks. The major effectors of transcriptional regulation are proteins called transcription factors, and in this thesis four papers describing genome-wide studies of seven such factors are presented, together with studies on components of the chromatin and transcriptome. In Paper I, we optimized a large-scale in vivo method, ChIP-chip, to study protein – DNA interactions using microarrays. The metabolic-disease related transcription factors USF1, HNF4a and FOXA2 were studied in 1 % of the genome, and a surprising number of binding sites were found, mostly far from annotated genes. In Paper II, a novel sequencing based method, ChIP-seq, was applied to FOXA2, HNF4a and GABPa, allowing a true genome-wide view of binding sites. A large overlap between the datasets were seen, and molecular interactions were verified in vivo. Using a ChIP-seq specific motif discovery method, we identified both the expected motifs and several for co-localized transcription factors. In Paper III, we identified and studied a novel transcription factor, ZBED6, using the ChIP-seq method. Here, we went from one known binding site to several hundred sites throughout the mouse genome. Finally, in Paper IV, we studied the chromatin landscape by deep sequencing of nucleosomal DNA, and further used RNA-sequencing to quantify expression levels, and extended the knowledge about the binding profiles for the transcription factors NFY and TCF7L2.

This dissertation research consists of two topics, population stochastics approximation Monte Carlo (Pop-SAMC) for Baysian model selection problems and ChIP-chip data analysis. The following two paragraphs give a brief introduction to each of the two topics, respectively. Although the reversible jump MCMC (RJMCMC) has the ability to traverse the space of possible models in Bayesian model selection problems, it is prone to becoming trapped into local mode, when the model space is complex. SAMC, proposed by Liang, Liu and Carroll, essentially overcomes the difficulty in dimension-jumping moves, by introducing a self-adjusting mechanism. However, this learning mechanism has not yet reached its maximum efficiency. In this dissertation, we propose a Pop-SAMC algorithm; it works on population chains of SAMC, which can provide a more efficient self-adjusting mechanism and make use of crossover operator from genetic algorithms to further increase its efficiency. Under mild conditions, the convergence of this algorithm is proved. The effectiveness of Pop-SAMC in Bayesian model selection problems is examined through a change-point identification example and a large-p linear regression variable selection example. The numerical results indicate that Pop- SAMC outperforms both the single chain SAMC and RJMCMC significantly. In the ChIP-chip data analysis study, we developed two methodologies to identify the transcription factor binding sites: Bayesian latent model and population-based test. The former models the neighboring dependence of probes by introducing a latent indicator vector; The later provides a nonparametric method for evaluation of test scores in a multiple hypothesis test by making use of population information of samples. Both methods are applied to real and simulated datasets. The numerical results indicate the Bayesian latent model can outperform the existing methods, especially when the data contain outliers, and the use of population information can significantly improve the power of multiple hypothesis tests.

La chromatine est un système de compaction de l’ADN jouant un rôle important dans la régulation de l’expression génique. L’acétylation de la chromatine provoque un relâchement de sa structure, facilitant le recrutement de facteurs de transcription. Inversement, des complexes histones déacétylases favorisent une structure compacte, réprimant l’expression de gènes. Un complexe HDAC, Rpd3S, est recruté par l’ARN polymérase II phosphorylée sur les régions codantes transcrites. Cette activité HDAC est stimulée par la déposition de la marque H3K36me générée par l’histone méthyltransférase Set2. Par approche génomique, en utilisant comme organisme modèle Saccharomyces cerevisiae, j’ai optimisé la méthode de ChIP-chip puis démontré que les sous unités Hos2 et Set3 d’un autre complexe HDAC, Set3C, étaient recrutées sur des régions codantes de gènes transcrits. De plus, Set3C est connu pour être recruté soit par H3K4me ou par la Pol II. La suite du projet portera sur le recrutement de Set3C qui semble similaire à Rpd3S. / Chromatin is a DNA compaction system and the main mecanism of gene expression regulation. Acetylation of histones loosens DNA compaction and thus facilitates the recruitment of transcription factors. By opposition, histone deacetylase (HDAC) complexes increase the compaction of chromatin and thus repress transcription. Rpd3S, a HDAC complex, is recruited to chromatin by interaction with a phosphorylated form of RNA polymerase II (Pol II) on actively transcribed genes and its activity is stimulated by the presence of the mark H3K36me mark. During my Master degree, I optimized ChIP-chip, using Saccharomyces cerevisiae as model organism, in order to investigate the localisation of two subunits (Hos2 and Set3) of another HDAC complex, Set3C. My datas demonstrate that Set3C subunits localized on actively transcribed genes, in a fashion similar to Rpd3S. Further, Set3C is known to be recruited either by Pol II or H3K4me suggesting that Set3C has a similar recruitment mechanism than Rpd3S. Future experiments in the laboratory will investigate the recruitment of Set3C.

Indiana University-Purdue University Indianapolis (IUPUI) / Immune response enables the body to resist foreign invasions. The Inflammatory response is an important aspect in the immune response which is articulated by elements such as cytokines, APC, T-cell and B-cell, effector cell or natural killer. Of these elements, T-cells especially T-helper cells; a sub class of T-cells plays a pivotal role in stimulating the immune response by participating in various biological reactions such as, the transcription regulatory network. Transcriptional regulatory mechanisms are mediated by a set of transcription factors (TFs), that bind to a specific region (motifs or transcription factor binding sites, TFBS), on the target gene(s) controlling the expression of genes that are involved in T-helper cell mediated immune response. Eukaryotic regulatory motifs, referred to as cis regulatory modules (CRMs) or cistrome, co-occur with the regulated gene’s transcription start site (TSS) thus, providing all the essential components for building the transcriptional regulatory networks that depends on the relevant TF-TFBS interactions. Here, we study IL-12 stimulated transcriptional regulators in STAT4 mediated T helper 1 (Th1) cell development by focusing on the identification of TFBS and CRMs using a set of Stat4 ChIP-on-chip target genes. A region containing 2000 bases of Mus musculus sequences with the Stat4 binding site, derived from the ChIP-on-chip data, has been characterized for enrichment of other motifs and, thus CRMs. Our experiments identify some potential motifs, (such as NF-κB and PPARγ/RXR) being enriched in the Stat4 binding sequences compared to neighboring background sequences. Furthermore, these predicted CRMs were observed to be associated with biologically relevant target genes in the ChIP-on-chip data set by meaningful gene ontology annotations. These analyses will enable us to comprehend the complicated transcription regulatory network and at the same time categorically analyze the IL-12 stimulated Stat4 mediated Th1 cell differentiation.

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La chromatine est essentielle au maintien de l’intégrité du génome, mais, ironiquement, constitue l’obstacle principal à la transcription des gènes. Plusieurs mécanismes ont été développés par la cellule pour pallier ce problème, dont l’acétylation des histones composant les nucléosomes. Cette acétylation, catalysée par des histones acétyl transférases (HATs), permet de réduire la force de l’interaction entre les nucléosomes et l’ADN, ce qui permet à la machinerie transcriptionnelle de faire son travail. Toutefois, on ne peut laisser la chromatine dans cet état permissif sans conséquence néfaste. Les histone déacétylases (HDACs) catalysent le clivage du groupement acétyle pour permettre à la chromatine de retrouver une conformation compacte. Cette thèse se penche sur la caractérisation de la fonction et du mécanisme de recrutement des complexes HDACs Rpd3S et Set3C. Le complexe Rpd3S est recruté aux régions transcrites par une interaction avec le domaine C-terminal hyperphosphorylé de Rpb1, une sous-unité de l’ARN polymérase II. Toutefois, le facteur d’élongation DSIF joue un rôle dans la régulation de cette association en limitant le recrutement de Rpd3S aux régions transcrites. L’activité HDAC de Rpd3S, quant à elle, dépend de la méthylation du résidu H3K36 par l’histone méthyltransférase Set2. La fonction du complexe Set3C n’est pas clairement définie. Ce complexe est recruté à la plupart de ses cibles par l’interaction entre le domaine PHD de Set3 et le résidu H3K4 di- ou triméthylé. Un mécanisme indépendant de cette méthylation, possiblement le même que pour Rpd3S, régit toutefois l’association de Set3C aux régions codantes des gènes les plus transcrits. La majorité de ces résultats ont été obtenus par la technique d’immunoprécipitation de la chromatine couplée aux biopuces (ChIP-chip). Le protocole technique et le design expérimental de ce type d’expérience fera aussi l’objet d’une discussion approfondie. / Chromatin is essential for the maintenance of genomic integrity but, ironically, is also the main barrier to gene transcription. Many mechanisms, such as histone acetylation, have evolved to overcome this problem. Histone acetylation, catalyzed by histone acetyltransferases (HATs), weakens the internucleosomal and nucleosome-DNA interactions, thus permitting the transcriptional machinery access to its template. However, this permissive chromatin state also allows for opportunistic DNA binding events. Histone deacetylases (HDACs) help restore a compact chromatin structure by catalyzing the removal of acetyl moieties from histones. This thesis focuses on the characterization of the function and of the recruitment mechanism of HDAC complexes Rpd3S and Set3C. The Rpd3S complex is recruited to actively transcribed coding regions through interactions with the hyperphosphorylated C-terminal domain of Rpb1, a subunit of RNA polymerase II, with the DSIF elongation factor playing a role in limiting this recruitment. However, the HDAC activity of Rpd3S depends on H3K36 methylation, which is catalyzed by the Set2 histone methyltransferase. The Set3C complex’ function is still not clearly defined. It is recruited to most of its targets through the interaction between the Set3 PHD domain and di- or trimethylated H3K4. However, Set3C recruitment to genes displaying high RNA polymerase II occupancy is independent of H3K4 methylation. The mechanism by which Set3C is recruited to this gene subset is under investigation. These results have mostly been obtained through chromatin immunoprecipitation coupled to tiling microarrays (ChIP-chip). The protocol and experimental design challenges inherent to this technique will also be discussed in depth.