An integrative ChIP-chip and gene expression profiling to model SMAD regulatory modules

<p>Abstract</p> <p>Background</p> <p>The TGF-β/SMAD pathway is part of a broader signaling network in which crosstalk between pathways occurs. While the molecular mechanisms of TGF-β/SMAD signaling pathway have been studied in detail, the global networks downstream of SMAD remain largely unknown. The regulatory effect of SMAD complex likely depends on transcriptional modules, in which the SMAD binding elements and partner transcription factor binding sites (SMAD modules) are present in specific context.</p> <p>Results</p> <p>To address this question and develop a computational model for SMAD modules, we simultaneously performed chromatin immunoprecipitation followed by microarray analysis (ChIP-chip) and mRNA expression profiling to identify TGF-β/SMAD regulated and synchronously coexpressed gene sets in ovarian surface epithelium. Intersecting the ChIP-chip and gene expression data yielded 150 direct targets, of which 141 were grouped into 3 co-expressed gene sets (sustained up-regulated, transient up-regulated and down-regulated), based on their temporal changes in expression after TGF-β activation. We developed a data-mining method driven by the Random Forest algorithm to model SMAD transcriptional modules in the target sequences. The predicted SMAD modules contain SMAD binding element and up to 2 of 7 other transcription factor binding sites (E2F, P53, LEF1, ELK1, COUPTF, PAX4 and DR1).</p> <p>Conclusion</p> <p>Together, the computational results further the understanding of the interactions between SMAD and other transcription factors at specific target promoters, and provide the basis for more targeted experimental verification of the co-regulatory modules.</p

ChIP-seq Defined Genome-Wide Map of TGFβ/SMAD4 Targets: Implications with Clinical Outcome of Ovarian Cancer

Deregulation of the transforming growth factor-β (TGFβ) signaling pathway in epithelial ovarian cancer has been reported, but the precise mechanism underlying disrupted TGFβ signaling in the disease remains unclear. We performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate genome-wide screening of TGFβ-induced SMAD4 binding in epithelial ovarian cancer. Following TGFβ stimulation of the A2780 epithelial ovarian cancer cell line, we identified 2,362 SMAD4 binding loci and 318 differentially expressed SMAD4 target genes. Comprehensive examination of SMAD4-bound loci, revealed four distinct binding patterns: 1) Basal; 2) Shift; 3) Stimulated Only; 4) Unstimulated Only. TGFβ stimulated SMAD4-bound loci were primarily classified as either Stimulated only (74%) or Shift (25%), indicating that TGFβ-stimulation alters SMAD4 binding patterns in epithelial ovarian cancer cells. Furthermore, based on gene regulatory network analysis, we determined that the TGFβ-induced, SMAD4-dependent regulatory network was strikingly different in ovarian cancer compared to normal cells. Importantly, the TGFβ/SMAD4 target genes identified in the A2780 epithelial ovarian cancer cell line were predictive of patient survival, based on in silico mining of publically available patient data bases. In conclusion, our data highlight the utility of next generation sequencing technology to identify genome-wide SMAD4 target genes in epithelial ovarian cancer and link aberrant TGFβ/SMAD signaling to ovarian tumorigenesis. Furthermore, the identified SMAD4 binding loci, combined with gene expression profiling and in silico data mining of patient cohorts, may provide a powerful approach to determine potential gene signatures with biological and future translational research in ovarian and other cancers

Computational Characterization of Genome-wide DNA-binding Pro les

The work and data that is presented in this thesis is part of a collaborative project that is funded by the Berlin Center for Regenerative Therapies. A number of people have contributed to this work and for clarity I will now mention the individual contributions. Stefan Mundlos, Peter N. Robinson and Jochen Hecht designed this project with the purpose of studying bone development using ChIP-seq in a chicken model. Jochen Hecht and Asita Stiege established the ChIP-seq protocol and together with Daniel Ibrahim, Hendrikje Hein, and Catrin Janetzky carried out the immunoprecipitations and sequencing. Peter Krawitz was responsible for the data processing that involved base calling and basic quality control. Daniel Ibrahim contributed to the analysis on the Hox proteins identifying the Q317K mutant to be related to Pitx1 and Obox family members. Sebastian Kohler and Sebastian Bauer carried out the computation of the Gene Ontology similarity data and random walk distances that I used for the target gene assignments in chapter 5. The results for the EMSA experiments that are shown in chapter three has been carried out by Asita Stiege. The work on target gene assignment that is presented in chapter 5 has been published in Nucleic Acids Research [1]. All the remaining methods, data and the experimental results will be partially be included in future publications by Ibrahim et al. and Hein et al.

Tgif1 Counterbalances The Activity Of Core Pluripotency Factors In Mouse Embryonic Stem Cells

Core pluripotency factors, such as Oct4, Sox2, and Nanog, play important roles in maintaining embryonic stem cell (ESC) identity by autoregulatory feedforward loops. Nevertheless, the mechanism that provides precise control of the levels of the ESC core factors without indefinite amplification has remained elusive. Here, we report the direct repression of core pluripotency factors by Tgif1, a previously known terminal repressor of TGF beta/activin/nodal signaling. Overexpression of Tgif1 reduces the levels of ESC core factors, whereas its depletion leads to the induction of the pluripotency factors. We confirm the existence of physical associations between Tgif1 and Oct4, Nanog, and HDAC1/2 and further show the level of Tgif1 is not significantly altered by treatment with an activator/inhibitor of the TGF beta/activin/nodal signaling. Collectively, our findings establish Tgif1 as an integral member of the core regulatory circuitry of mouse ESCs that counterbalances the levels of the core pluripotency factors in a TGF beta/activin/nodal-independent manner.Cancer Prevention Research Institute of Texas (CPRIT) R1106Molecular Bioscience

Integrative and perturbation-based analysis of the transcriptional dynamics of TGFβ/BMP system components in transition from embryonic stem cells to neural progenitors

Cooperative actions of extrinsic signals and cell-intrinsic transcription factors alter gene regulatory networks enabling cells to respond appropriately to environmental cues. Signaling by transforming growth factor type β (TGFβ) family ligands (eg, bone morphogenetic proteins [BMPs] and Activin/Nodal) exerts cell-type specific and context-dependent transcriptional changes, thereby steering cellular transitions throughout embryogenesis. Little is known about coordinated regulation and transcriptional interplay of the TGFβ system. To understand intrafamily transcriptional regulation as part of this system's actions during development, we selected 95 of its components and investigated their mRNA-expression dynamics, gene-gene interactions, and single-cell expression heterogeneity in mouse embryonic stem cells transiting to neural progenitors. Interrogation at 24 hour intervals identified four types of temporal gene transcription profiles that capture all stages, that is, pluripotency, epiblast formation, and neural commitment. Then, between each stage we performed esiRNA-based perturbation of each individual component and documented the effect on steady-state mRNA levels of the remaining 94 components. This exposed an intricate system of multilevel regulation whereby the majority of gene-gene interactions display a marked cell-stage specific behavior. Furthermore, single-cell RNA-profiling at individual stages demonstrated the presence of detailed co-expression modules and subpopulations showing stable co-expression modules such as that of the core pluripotency genes at all stages. Our combinatorial experimental approach demonstrates how intrinsically complex transcriptional regulation within a given pathway is during cell fate/state transitions

SMAD4: a multifunctional regulator of limb bud initiation and outgrowth

During mouse embryonic development, the spatio-temporal expression of genes is controlled by both interlinked signalling pathways and interactions between transcription factors and their target cis-regulatory modules. To gain global insights into the roles of a trans-acting transcriptional regulator in a specific tissue, the genome-wide profiling of its target regulatory regions and their association with the putative target genes are essential. Therefore, I have combined several types of genome-wide analyses such as ChIP-seq using epitope-tagged transcription factors with ATAC-seq and RNA-seq to study the functions of HAND2 and SMAD4 during heart and limb bud development, respectively. In Hand2-deficient embryos, we observed that cells of the atrioventricular canal do not undergo the endothelial-mesenchymal transition that underlies cardiac cushion development. By combining HAND23xF ChIP-seq and RNA-seq analysis, we have identified the HAND2 gene regulatory network involved in these processes and show that HAND2 is a key regulator of heart valve development. Limb bud outgrowth and patterning are regulated by a self-regulatory feedback signalling system operating between the SHH and FGF signalling pathways that critically depends on the BMP antagonist GREMLIN1. However, the establishment of these signalling feedback loops requires initiation of Gremlin1 expression by high BMP activity. For my PhD research, I have investigated the roles of the BMP signalling pathway during limb bud initiation by studying the functions of the BMP signal transducer SMAD4. By combining genome-wide SMAD43xF ChIP-seq, ATAC-seq and RNA-seq analyses, I am able to show that SMAD4 participates in activation of Gremlin1 expression by interacting with Grem1 coding exon 2 (a putative regulatory region). Furthermore, the identification of the SMAD4 gene regulatory network reveals multiple functions of SMAD4 during the onset of limb bud development. Especially, SMAD4 directly regulates target genes involved in limb bud outgrowth and patterning. Rather unexpected, my analysis reveals that SMAD4 directly regulates cholesterol homeostasis and controls the gradient and activity of the SHH signalling pathway during early limb bud development

Vitamin D and the RNA transcriptome: more than mRNA regulation

The GRCh37.p13 primary assembly of the human genome contains 20805 protein coding mRNA, and 37147 non-protein coding genes and pseudogenes that as a result of RNA processing and editing generate 196501 gene transcripts. Given the size and diversity of the human transcriptome, it is timely to revisit what is known of VDR function in the regulation and targeting of transcription.Early transcriptomic studies using microarray approaches focused on the protein coding mRNA that were regulated by the VDR, usually following treatment with ligand. These studies quickly established the approxamte size, and surprising diversity of the VDR transcriptome, revealing it to be highly heterogenous and cell type and time dependent. With the discovery of microRNA, investigators also considered VDR regulation of these non-protein coding RNA. Again, cell and time dependency has emerged. Attempts to integrate mRNA and miRNA regulation patterns are beginning to reveal patterns of co-regulation and interaction that allow for greater control of mRNA expression, and the capacity to govern more complex cellular events. As the awareness of the diversity of non-coding RNA increases, it is evident that VDR actions are mediated through these molecules also. Key knowledge gaps remain over the VDR transcriptome. The causes for the cell and type dependent transcriptional heterogenetiy remain enigmatic. ChIP-Seq approaches have confirmed that VDR binding choices differ very significantly by cell type, but as yet the underlying causes distilling VDR binding choices are unclear. Similarly, it is clear that many of the VDR binding sites are non-canonical in nature but again the mechanisms underlying these interactions are unclear. Finally, although alternative splicing is clearly a very significant process in cellular transcriptional control, the lack of RNA-Seq data centered on VDR function are currently limiting the global assessment of the VDR transcriptome. VDR focused research that complement

Multifaceted enrichment analysis of RNA-RNA crosstalk reveals cooperating micro-societies in human colorectal cancer

Alterations in the balance of mRNA and microRNA (miRNA) expression profiles contribute to the onset and development of colorectal cancer. The regulatory functions of individual miRNA-gene pairs are widely acknowledged, but group effects are largely unexplored. We performed an integrative analysis of mRNA–miRNA and miRNA–miRNA interactions using high-throughput mRNA and miRNA expression profiles obtained from matched specimens of human colorectal cancer tissue and adjacent non- tumorous mucosa. This investigation resulted in a hypernetwork-based model, whose functional back- bone was fulfilled by tight micro-societies of miR- NAs. These proved to modulate several genes that are known to control a set of significantly enriched cancer-enhancer and cancer-protection biological processes, and that an array of upstream regulatory analyses demonstrated to be dependent on miR-145, a cell cycle and MAPK signalling cascade master regulator. In conclusion, we reveal miRNA-gene clusters and gene families with close functional relationships and highlight the role of miR-145 as potent upstream regulator of a complex RNA–RNA crosstalk, which mechanistically modulates several signalling path- ways and regulatory circuits that when deranged are relevant to the changes occurring in colorectal carcinogenesis

The proto-oncogenic protein TAL1 controls TGF-β1 signaling through interaction with SMAD3

AbstractTGF-β1 is involved in many aspects of tissue development and homeostasis including hematopoiesis. The TAL1 transcription factor is also an important player of this latter process and is expressed very early in the myeloid and erythroid lineages. We previously established a link between TGF-β1 signaling and TAL1 by showing that the cytokine was able to induce its proteolytic degradation by the ubiquitin proteasome pathway. In this manuscript we show that TAL1 interacts with SMAD3 that acts in the pathway downstream of TGF-β1 association with its receptor. TAL1 expression strengthens the positive or negative effect of SMAD3 on various genes. Both transcription factors activate the inhibitory SMAD7 factor through the E box motif present in its transcriptional promoter. DNA precipitation assays showed that TAL1 present in Jurkat or K562 cells binds to this SMAD binding element in a SMAD3 dependent manner. SMAD3 and TAL1 also inhibit several genes including ID1, hTERT and TGF-β1 itself. In this latter case TAL1 and SMAD3 can impair the positive effect exerted by E47. Our results indicate that TAL1 expression can modulate TGF-β1 signaling by interacting with SMAD3 and by increasing its transcriptional properties. They also suggest the existence of a negative feedback loop between TAL1 expression and TGF-β1 signaling

Deep Sequencing of MYC DNA-Binding Sites in Burkitt Lymphoma

BACKGROUND: MYC is a key transcription factor involved in central cellular processes such as regulation of the cell cycle, histone acetylation and ribosomal biogenesis. It is overexpressed in the majority of human tumors including aggressive B-cell lymphoma. Especially Burkitt lymphoma (BL) is a highlight example for MYC overexpression due to a chromosomal translocation involving the c-MYC gene. However, no genome-wide analysis of MYC-binding sites by chromatin immunoprecipitation (ChIP) followed by next generation sequencing (ChIP-Seq) has been conducted in BL so far. METHODOLOGY/PRINCIPAL FINDINGS: ChIP-Seq was performed on 5 BL cell lines with a MYC-specific antibody giving rise to 7,054 MYC-binding sites after bioinformatics analysis of a total of approx. 19 million sequence reads. In line with previous findings, binding sites accumulate in gene sets known to be involved in the cell cycle, ribosomal biogenesis, histone acetyltransferase and methyltransferase complexes demonstrating a regulatory role of MYC in these processes. Unexpectedly, MYC-binding sites also accumulate in many B-cell relevant genes. To assess the functional consequences of MYC binding, the ChIP-Seq data were supplemented with siRNA- mediated knock-downs of MYC in BL cell lines followed by gene expression profiling. Interestingly, amongst others, genes involved in the B-cell function were up-regulated in response to MYC silencing. CONCLUSION/SIGNIFICANCE: The 7,054 MYC-binding sites identified by our ChIP-Seq approach greatly extend the knowledge regarding MYC binding in BL and shed further light on the enormous complexity of the MYC regulatory network. Especially our observations that (i) many B-cell relevant genes are targeted by MYC and (ii) that MYC down-regulation leads to an up-regulation of B-cell genes highlight an interesting aspect of BL biology