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Figure S1. Further dissection of TF site occupancy and spatial co-localization. Figure S2. The relationship between spatial density in mESC genome structures and sequence density for sites of different TFs. Figure S3. Differences in ChIP-seq SignalValue between sequence-paired TF sites in high and low co-localization groups. Figure S4. Enrichment in co-localization between heterotypic TF pairs. Figure S5. Enrichment in co-localization between heterotypic TF pairs in single cells. Figure S6. Additional analyses for TF network groups. Figure S7. Conservation of TF binding sites between human lymphoblastoid and ES cells. (PDF 4417 kb)

Figure S3. Estimated Îť distribution in relation to PWM motif length. Each color coded point represents a specific Îť value of a TF estimated by Eq. 6 for S. cerevisiae (green), D. melanogaster (red), and vertebrate (blue).There is a positive correlation between estimated Îť value and TF motif length with adjusted R 2 equals 0.33. (PDF 22.6KB)

Figure S2. Estimated λdistribution across major TF families. BBA-ZF represents the λdistribution for β- β- α zinc-finger family; NR is zinc-finger nuclear receptor family; L-zipper stands for the basic leucine-zipper family; HLH is helix-loop-helix family; Homeo is homeobox family; FK is fork-head family and HMG is high mobility group family. For each group, λ was calculated by Eq. 6. (PDF 5.33KB)

Figure S1. The relationship between maximum PWM score and information content of PWMs. Individual dots represents each PWM generated from the non-redundant PFM JASPAR-CORE database [5] after the filtering procedures specified in the Methods section. There is a strong positive correlation between the information content of the PWM and the maximum possible PWM score that could be generated by that PWM, with an adjusted R 2 value of 0.597. (PDF 25.9KB)

Figure S4. Comparison of Îť values calculated by using different pseudo-count values in PWMs. Subfigure A shows the comparison between the Îťvalues obtained by using PWMs with pseudocounts of 1 and 3 (the adjusted R 2 is 0.973), while subfigure B compares pseudocounts of 1 and 0.3 (the adjusted R 2 is 0.978). Each dot represents a TF from 100 randomly chosen vertebrate TFs in JASPAR database [5]. (PDF 31.2KB)

Figure S7. Heatmaps for λ conversion between different PWMs. These are additional examples of heatmaps of sequence-specific residence time that are used for λ conversion between different PWMs of the same TF. Alternative versions of PWMs are from BioConductor R package of PWMEnrich.Dmelanogaster.background [17]. Each column of the heatmaps represents a specific λ value and each row represents a specific binding site strength level. (PDF 25.5KB)

Figure S5. Correlation of λ rank obtained by using different top score thresholds in Eq. 6. We compare the λ rank for different TFs in each group of organisms (subfigure A, B for S. cerevisiae, C and D for D. melanogaster, E and F for vertebrate PWM motifs) by adopting a different top score threshold of top 0.01 % or 0.001 % instead of the default value of 0.1 % in Eq. 6. The adjusted R 2 for the λ rank correlation between 0.1 % and 0.01 % thresholds for S. cerevisiae, D. melanogaster, and vertebrate motifs are 0.94, 0.89 and 0.80, respectively, with p-values all less than 10−8. As for the λrank correlation between 0.1 % and 0.001 % thresholds, the adjusted R 2 are 0.87, 0.92 and 0.74, respectively (p-values all less than 10−6). (PDF 33.2KB)

The NK homeodomain factor Tinman is a crucial regulator of early mesoderm patterning and, together with the GATA factor Pannier and the Dorsocross T-box factors, serves as one of the key cardiogenic factors during specification and differentiation of heart cells. Although the basic framework of regulatory interactions driving heart development has been worked out, only about a dozen genes involved in heart development have been designated as direct Tinman target genes to date, and detailed information about the functional architectures of their cardiac enhancers is lacking. We have used immunoprecipitation of chromatin (ChIP) from embryos at two different stages of early cardiogenesis to obtain a global overview of the sequences bound by Tinman in vivo and their linked genes. Our data from the analysis of ∼50 sequences with high Tinman occupancy show that the majority of such sequences act as enhancers in various mesodermal tissues in which Tinman is active. All of the dorsal mesodermal and cardiac enhancers, but not some of the others, require tinman function. The cardiac enhancers feature diverse arrangements of binding motifs for Tinman, Pannier, and Dorsocross. By employing these cardiac and non-cardiac enhancers in machine learning approaches, we identify a novel motif, termed CEE, as a classifier for cardiac enhancers. In vivo assays for the requirement of the binding motifs of Tinman, Pannier, and Dorsocross, as well as the CEE motifs in a set of cardiac enhancers, show that the Tinman sites are essential in all but one of the tested enhancers; although on occasion they can be functionally redundant with Dorsocross sites. The enhancers differ widely with respect to their requirement for Pannier, Dorsocross, and CEE sites, which we ascribe to their different position in the regulatory circuitry, their distinct temporal and spatial activities during cardiogenesis, and functional redundancies among different factor binding sites., Author Summary The Drosophila homeodomain protein Tinman was the first transcription factor found to control the development and differentiation of the heart in any species. In spite of that, our knowledge of the number, identities, and mode of regulation of the downstream target genes of Tinman that are necessary to exert its cardiogenic functions is still very incomplete. To address these issues, we have performed a genome-wide analysis of DNA regions associated with Tinman-binding in embryos and the genes linked to them. The combined data from our in-depth in vivo assays of sequence elements with high Tinman occupancy allow the following general conclusions: (1) The majority of such sequences are active as regulatory elements (called enhancers) in mesodermal tissues that include Tinman-expressing cells. (2) The enhancers active in the heart progenitor cells and the heart generally are dependent on tinman gene activity, whereas those active in non-cardiac mesoderm are often bound neutrally by Tinman. (3) Tinman binding motifs in most cases are essential for cardiac enhancer activity, but in some cases they can be functionally-redundant with those of other cardiogenic factors. (4) Tinman-occupied cardiac enhancers are enriched for a newly discovered binding motif for an unknown factor that is functional in vivo.

Studienhintergrund: Plattenepithelkarzinome des Kopf-Hals-Bereiches (HNSCC) stellen mehr als 5% aller Tumorerkrankungen weltweit, sind schlecht therapierbar und haben eine ungünstige Prognose. Ziel dieser Studie war es Proteinbiomarker nachzuweisen, die sich in Tumorzellen von Plattenepithelkarzinomzellen[for full text, please go to the a.m. URL], 80. Jahresversammlung der Deutschen Gesellschaft für Hals-Nasen-Ohren-Heilkunde, Kopf- und Hals-Chirurgie

Die Embryonalentwicklung der Tracheen der Fruchtfliege Drosophila stellt ein Modell für genetische und molekulare Analysen der Verzweigungsmorphogenese dar. Durch die Arbeiten vieler Laboratorien konnten BRANCHLESS (BNL, ein Homolog des Fibroblastenwachstumsfaktors) und BREATHLESS (BTL, sein Rezeptor) als essentielle Faktoren für viele Schritte in der Entwicklung des Tracheensystems identifiziert werden. Die Zielgene der BNL/BTL-Signalkaskade waren bisher zumeist unbekannt. Für die vorliegende Arbeit wurden Embryonen nach Verlust von BNL-Aktivität als auch solche nach gewebespezifischer trachealer Überexpression von BNL morphologisch und physiologisch charakterisiert. Ebenso wurden Transkriptionsprofile für die funktionell-genomische Analyse erstellt. Durch im Rahmen der vorliegenden Arbeit neu entwickelte bioinformatische Methoden konnten bisher unbekannte Gene identifiziert werden, die von BNL abhängig sind und deren tracheale Expression durch in situ-Hybridisierung validiert werden konnte. Ebenso war es möglich, durch die Projektion der Messdaten auf genetische Interaktionsgraphen putative Wechselwirkungen der BNL/BTL-Signalkaskade mit anderen Signalwegen aufzuzeigen, und eventuelle Aktivierungsmechanismen beispielsweise für unter Überexpression von BNL auftretende Immunfaktoren zu erkennen. Es konnte gezeigt werden, dass der Signalweg über Stickstoffmonoxid von BNL unabhängig in den Tracheen agiert, wohingegen sich eine Interaktion mit der JAK/STAT-Signalkaskade andeutet., The embryonic development of the Drosophila tracheal system resembles a model for genetic and molecular analyses of branching morphogenesis. Efforts of many laboratories have identified BRANCHLESS (BNL, a homologue of the fibroblast growth factor) and BREATHLESS (BTL, its receptor) as essential factors for many steps in the development of the tracheal system. However, the transcriptional targets of the BNL/BTL signalling cascade remain mostly unkown. This thesis presents the characterisation of BNL gain- and loss-of-function on the level of morphology and physiology. Transcriptional profiles of wildtype, bnl mutant and bnl over-expressing embryos were obtained. Computational methods (projection of expression data onto chromosomal position, functional Gene Ontology-annotation and to graphs of protein or genetic interaction) were developed in order to identify novel BNL-dependent genes, which are expressed in the tracheal system. It was possible to suggest putative cross-talk between the BNL/BTL signalling cascade and other pathways, which may explain the expression of genes of the innate immune system in response to ectopic dosages of BNL. Signalling of nitric oxide in the trachea appears to be independent from BNL, whereas there is evidence for an interaction with the JAK/STAT signalling cascade.