Cell fate decisions are driven through the integration of inductive signals and tissue-specific transcription factors (TFs), although the details on how this information converges in cis remain unclear. Here, we demonstrate that the five genetic components essential for cardiac specification in Drosophila, including the effectors of Wg and Dpp signaling, act as a collective unit to cooperatively regulate heart enhancer activity, both in vivo and in vitro. Their combinatorial binding does not require any specific motif orientation or spacing, suggesting an alternative mode of enhancer function whereby cooperative activity occurs with extensive motif flexibility. A fraction of enhancers co-occupied by cardiogenic TFs had unexpected activity in the neighboring visceral mesoderm but could be rendered active in heart through single-site mutations. Given that cardiac and visceral cells are both derived from the dorsal mesoderm, this "dormant" TF binding signature may represent a molecular footprint of these cells' developmental lineage.

Chromatin modifications are associated with many aspects of gene expression, yet their role in cellular transitions during development remains elusive. Here, we use a new approach to obtain cell type-specific information on chromatin state and RNA polymerase II (Pol II) occupancy within the multicellular Drosophila melanogaster embryo. We directly assessed the relationship between chromatin modifications and the spatio-temporal activity of enhancers. Rather than having a unique chromatin state, active developmental enhancers show heterogeneous histone modifications and Pol II occupancy. Despite this complexity, combined chromatin signatures and Pol II presence are sufficient to predict enhancer activity de novo. Pol II recruitment is highly predictive of the timing of enhancer activity and seems dependent on the timing and location of transcription factor binding. Chromatin modifications typically demarcate large regulatory regions encompassing multiple enhancers, whereas local changes in nucleosome positioning and Pol II occupancy delineate single active enhancers. This cell type-specific view identifies dynamic enhancer usage, an essential step in deciphering developmental networks.

We present a computational method for identifying potential targets of a transcription factor (TF) using wild-type gene expression time series data. For each putative target gene we fit a simple differential equation model of transcriptional regulation, and the model likelihood serves as a score to rank targets. The expression profile of the TF is modeled as a sample from a Gaussian process prior distribution that is integrated out using a nonparametric Bayesian procedure. This results in a parsimonious model with relatively few parameters that can be applied to short time series datasets without noticeable overfitting. We assess our method using genome-wide chromatin immunoprecipitation (ChIP-chip) and loss-of-function mutant expression data for two TFs, Twist, and Mef2, controlling mesoderm development in Drosophila. Lists of top-ranked genes identified by our method are significantly enriched for genes close to bound regions identified in the ChIP-chip data and for genes that are differentially expressed in loss-of-function mutants. Targets of Twist display diverse expression profiles, and in this case a model-based approach performs significantly better than scoring based on correlation with TF expression. Our approach is found to be comparable or superior to ranking based on mutant differential expression scores. Also, we show how integrating complementary wild-type spatial expression data can further improve target ranking performance.

Development requires the establishment of precise patterns of gene expression, which are primarily controlled by transcription factors binding to cis-regulatory modules. Although transcription factor occupancy can now be identified at genome-wide scales, decoding this regulatory landscape remains a daunting challenge. Here we used a novel approach to predict spatio-temporal cis-regulatory activity based only on in vivo transcription factor binding and enhancer activity data. We generated a high-resolution atlas of cis-regulatory modules describing their temporal and combinatorial occupancy during Drosophila mesoderm development. The binding profiles of cis-regulatory modules with characterized expression were used to train support vector machines to predict five spatio-temporal expression patterns. In vivo transgenic reporter assays demonstrate the high accuracy of these predictions and reveal an unanticipated plasticity in transcription factor binding leading to similar expression. This data-driven approach does not require previous knowledge of transcription factor sequence affinity, function or expression, making it widely applicable.

Polycomb group (PcG) proteins form conserved regulatory complexes that modify chromatin to repress transcription. Here, we report genome-wide binding profiles of PhoRC, the Drosophila PcG protein complex containing the DNA-binding factor Pho/dYY1 and dSfmbt. PhoRC constitutively occupies short Polycomb response elements (PREs) of a large set of developmental regulator genes in both embryos and larvae. The majority of these PREs are co-occupied by the PcG complexes PRC1 and PRC2. Analysis of PcG mutants shows that the PcG system represses genes required for anteroposterior, dorsoventral, and proximodistal patterning of imaginal discs and that it also represses cell cycle regulator genes. Many of these genes are regulated in a dynamic manner, and our results suggest that the PcG system restricts signaling-mediated activation of target genes to appropriate cells. Analysis of cell cycle regulators indicates that the PcG system also dynamically modulates the expression levels of certain genes, providing a possible explanation for the tumor phenotype of PcG mutants.

In the major animal model species like mouse, fish or fly, detailed spatial information on gene expression over time can be acquired through whole mount in situ hybridization experiments. In these species, expression patterns of many genes have been studied and data has been integrated into dedicated model organism databases like ZFIN for zebrafish, MEPD for medaka, BDGP for Drosophila or GXD for mouse. However, a central repository that allows users to query and compare gene expression patterns across different species has not yet been established. Therefore, we have integrated expression patterns for zebrafish, Drosophila, medaka and mouse into a central public repository called 4DXpress (expression database in four dimensions). Users can query anatomy ontology-based expression annotations across species and quickly jump from one gene to the orthologues in other species. Genes are linked to public microarray data in ArrayExpress. We have mapped developmental stages between the species to be able to compare developmental time phases. We store the largest collection of gene expression patterns available to date in an individual resource, reflecting 16 505 annotated genes. 4DXpress will be an invaluable tool for developmental as well as for computational biologists interested in gene regulation and evolution. 4DXpress is available at http://ani.embl.de/4DXpress.

Two new fluorene derivatized 1,10-phenanthroline ligands and related tris-chelate Ru(ii) or Zn(ii) coordination complexes have been synthesised. The linear and nonlinear (two-photon induced fluorescence) photophysical measurements have contributed to highlight the possibility to tune the absorption spectral range and excited lifetime, depending on ligand substitution and nature of the metal. More significantly, the observation of two-photon absorption (TPA) associated with long-lived metal-to-ligand charge-transfer (MLCT) excited states in the Ru(ii)-based chromophores, opens a wide range of applications in the near infrared.

Embryogenesis is controlled by large gene-regulatory networks, which generate spatially and temporally refined patterns of gene expression. Here, we report the characteristics of the regulatory network orchestrating early mesodermal development in the fruitfly Drosophila, where the transcription factor Twist is both necessary and sufficient to drive development. Through the integration of chromatin immunoprecipitation followed by microarray analysis (ChIP-on-chip) experiments during discrete time periods with computational approaches, we identified >2000 Twist-bound cis-regulatory modules (CRMs) and almost 500 direct target genes. Unexpectedly, Twist regulates an almost complete cassette of genes required for cell proliferation in addition to genes essential for morophogenesis and cell migration. Twist targets almost 25% of all annotated Drosophila transcription factors, which may represent the entire set of regulators necessary for the early development of this system. By combining in vivo binding data from Twist, Mef2, Tinman, and Dorsal we have constructed an initial transcriptional network of early mesoderm development. The network topology reveals extensive combinatorial binding, feed-forward regulation, and complex logical outputs as prevalent features. In addition to binary activation and repression, we suggest that Twist binds to almost all mesodermal CRMs to provide the competence to integrate inputs from more specialized transcription factors.

MOTIVATION: CoCo, ChIP-On-Chip Online, is an open-source web application that supports the annotation and curation of regulatory regions and associated target genes discovered in ChIP-on-chip experiments. CoCo integrates ChIP-on-chip results with diverse types of gene expression data (expression profiling, in situ hybridisation) and displays them within a genomic context. Regulatory relationships between the transcription factor-bound regions and putative target genes can be stored and expanded throughout different sessions. AVAILABILITY: http://furlonglab.embl.de/methods/tools/coco.