DNA-binding transcriptional regulators interpret the genome's regulatory code by binding to specific sequences to induce or repress gene expression 1 . Comparative genomics has recently been used to identify potential cis-regulatory sequences within the yeast genome on the basis of phylogenetic conservation 2-6 , but this information alone does not reveal if or when transcriptional regulators occupy these binding sites. We have constructed an initial map of yeast's transcriptional regulatory code by identifying the sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species. The organization of regulatory elements in promoters and the environment-dependent use of these elements by regulators are discussed. We find that environment-specific use of regulatory elements predicts mechanistic models for the function of a large population of yeast's transcriptional regulators.We used genome-wide location analysis 7-10 to determine the genomic occupancy of 203 DNA-binding transcriptional regulators in rich media conditions and, for 84 of these regulators, in at least 1 of 12 other environmental conditions (Supplementary Table 1, Supplementary Fig. 1; http://web.wi.mit.edu/young/regulatory_code). These 203 proteins are likely to include nearly all of the DNA-binding transcriptional regulators encoded in the yeast genome. Regulators were selected for profiling in an additional environment if they were essential for growth in that environment or if there was other evidence implicating them in the regulation of gene expression in that environment. The genome-wide location data identified 11,000 unique interactions between regulators and promoter regions at high confidence (P ≤ 0.001).

We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.

The transcriptional regulatory networks that specify and maintain human tissue diversity are largely uncharted. To gain insight into this circuitry, we used chromatin immunoprecipitation combined with promoter microarrays to identify systematically the genes occupied by the transcriptional regulators HNF1alpha, HNF4alpha, and HNF6, together with RNA polymerase II, in human liver and pancreatic islets. We identified tissue-specific regulatory circuits formed by HNF1alpha, HNF4alpha, and HNF6 with other transcription factors, revealing how these factors function as master regulators of hepatocyte and islet transcription. Our results suggest how misregulation of HNF4alpha can contribute to type 2 diabetes.

Summary Current therapies for medulloblastoma (MB), a highly malignant childhood brain tumor, impose debilitating effects on the developing child, warranting deployment of molecularly targeted treatments with reduced toxicities. Prior studies failed to disclose the full spectrum of driver genes and molecular processes operative in MB subgroups. Herein, we detail the somatic landscape across 491 sequenced MBs and molecular heterogeneity amongst 1,256 epigenetically analyzed cases, identifying subgroup-specific driver alterations including previously unappreciated actionable targets. Driver mutations explained the majority of Group 3 and Group 4 patients, remarkably enhancing previous knowledge. Novel molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions targeting KBTBD4 and ‘enhancer hijacking’ driving PRDM6 activation. Thus, application of integrative genomics to an unprecedented cohort of clinical samples derived from a single childhood cancer entity disclosed a series of new cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for treating MB patients.

SUMMARY Heat-Shock Factor 1 (HSF1), master regulator of the heat-shock response, facilitates malignant transformation, cancer cell survival and proliferation in model systems. The common assumption is that these effects are mediated through regulation of heat-shock protein (HSP) expression. However, the transcriptional network that HSF1 coordinates directly in malignancy and its relationship to the heat-shock response have never been defined. By comparing cells with high and low malignant potential alongside their non-transformed counterparts, we identify an HSF1-regulated transcriptional program specific to highly malignant cells and distinct from heat shock. Cancer-specific genes in this program support oncogenic processes: cell-cycle regulation, signaling, metabolism, adhesion and translation. HSP genes are integral to this program, however, many are uniquely regulated in malignancy. This HSF1 cancer program is active in breast, colon and lung tumors isolated directly from human patients and is strongly associated with metastasis and death. Thus, HSF1 rewires the transcriptome in tumorigenesis, with prognostic and therapeutic implications.

BackgroundThe regulatory map of a genome consists of the binding sites for proteins that determine the transcription of nearby genes. An initial regulatory map for S. cerevisiae was recently published using six motif discovery programs to analyze genome-wide chromatin immunoprecipitation data for 203 transcription factors. The programs were used to identify sequence motifs that were likely to correspond to the DNA-binding specificity of the immunoprecipitated proteins. We report improved versions of two conservation-based motif discovery algorithms, PhyloCon and Converge. Using these programs, we create a refined regulatory map for S. cerevisiae by reanalyzing the same chromatin immunoprecipitation data.ResultsApplying the same conservative criteria that were applied in the original study, we find that PhyloCon and Converge each separately discover more known specificities than the combination of all six programs in the previous study. Combining the results of PhyloCon and Converge, we discover significant sequence motifs for 36 transcription factors that were previously missed. The new set of motifs identifies 636 more regulatory interactions than the previous one. The new network contains 28% more regulatory interactions among transcription factors, evidence of greater cross-talk between regulators.ConclusionCombining two complementary computational strategies for conservation-based motif discovery improves the ability to identify the specificity of transcriptional regulators from genome-wide chromatin immunoprecipitation data. The increased sensitivity of these methods significantly expands the map of yeast regulatory sites without the need to alter any of the thresholds for statistical significance. The new map of regulatory sites reveals a more elaborate and complex view of the yeast genetic regulatory network than was observed previously.

Foxp3 + CD4 + CD25 + regulatory T (T reg ) cells are essential for the prevention of autoimmunity 1,2 . T reg cells have an attenuated cytokine response to T-cell receptor stimulation, and can suppress the proliferation and effector function of neighbouring T cells 3,4 . The forkhead transcription factor Foxp3 (forkhead box P3) is selectively expressed in T reg cells, is required for T reg development and function, and is sufficient to induce a T reg phenotype in conventional CD4 + CD25 − T cells [5][6][7][8] . Mutations in Foxp3 cause severe, multi-organ autoimmunity in both human and mouse 9-11 . FOXP3 can cooperate in a DNA-binding complex with NFAT (nuclear factor of activated T cells) to regulate the transcription of several known target genes 12 . However, the global set of genes regulated directly by Foxp3 is not known and consequently, how this transcription factor controls the gene expression programme for T reg function is not understood. Here we identify Foxp3 target genes and report that many of these are key modulators of T-cell activation and function. Remarkably, the predominant, although not exclusive, effect of Foxp3 occupancy is to suppress

We demonstrate that the binding sites for highly conserved transcription factors vary extensively between human and mouse. We mapped the binding of four tissue-specific transcription factors (FOXA2, HNF1A, HNF4A, HNF6) to 4,000 orthologous gene pairs in hepatocytes purified from human and mouse livers. Despite the conserved function of these factors, from 41% to 89% of their binding events appear to be species-specific. When the same protein binds the promoters of orthologous genes, approximately two-thirds of the binding sites do not align.Elements of transcriptional regulation have central roles in evolution [1][2][3] . In many cases, conserved biological processes are controlled by evolutionarily conserved regulatory programs while evolving phenotypes are associated with cross-species variation in transcription regulation 4 . However, in the absence of suitable genome-wide data, it is unclear what fraction of all protein-DNA interactions are under either positive or negative selective pressure 1 . A preliminary effort to compare genome-wide binding sites for two stem cell-specific transcription factors in human and mouse has suggested that large differences exist between mouse and human 5, 6 yet because the data were obtained using different To compare systematically the binding of transcriptional regulators to promoter regions across species, we designed carefully matched ChIP-chip experiments 7 in human and mouse. We created custom DNA microarrays that array ten kilobases of sequence surrounding the known transcription start sites of over 4,000 orthologous pairs of mouse and human genes. These genes were selected because their orthology could be unambiguously assigned and oligonucleotides could be designed to represent the putative regulatory regions at high density ( Figure 1A, Supplementary Methods). Forty-seven hand-curated, tissuespecific genes were included in the array design as controls.Chromatin immunoprecipitations were performed independently in primary hepatocytes directly isolated from mouse and human liver using antibodies against four tissue-specific transcription factors (FOXA2, HNF1A, HNF4A, HNF6) involved in liver development and regulation ( Figure 1B, Table S1) 7 . Hepatocytes were chosen as a representative tissue for these experiments because (1) they are functionally and structurally conserved among mammals 8 ; (2) their gene expression programs are similar across species (Table S1); (3) their gene expression patterns are largely unperturbed by isolation procedures 9 ; and (4) the transcription factors responsible for hepatocyte development and function are highly conserved 8 . We amplified and fluorescently labeled the DNA from these binding experiments, hybridized it to the microarrays, and then scored binding events 10 .Several possible outcomes can be distinguished when comparing a binding event in one species with the data from the second species (Figure 1). First, one can determine if a particular transcription factor binds anywhere within the arrayed region of the human ...