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 developed PolyA-seq, a strand-specific and quantitative method for high-throughput sequencing of 39 ends of polyadenylated transcripts, and used it to globally map polyadenylation (polyA) sites in 24 matched tissues in human, rhesus, dog, mouse, and rat. We show that PolyA-seq is as accurate as existing RNA sequencing (RNA-seq) approaches for digital gene expression (DGE), enabling simultaneous mapping of polyA sites and quantitative measurement of their usage. In human, we confirmed 158,533 known sites and discovered 280,857 novel sites (FDR < 2.5%). On average 10% of novel human sites were also detected in matched tissues in other species. Most novel sites represent uncharacterized alternative polyA events and extensions of known transcripts in human and mouse, but primarily delineate novel transcripts in the other three species. A total of 69.1% of known human genes that we detected have multiple polyA sites in their 39UTRs, with 49.3% having three or more. We also detected polyadenylation of noncoding and antisense transcripts, including constitutive and tissue-specific primary microRNAs. The canonical polyA signal was strongly enriched and positionally conserved in all species. In general, usage of polyA sites is more similar within the same tissues across different species than within a species. These quantitative maps of polyA usage in evolutionarily and functionally related samples constitute a resource for understanding the regulatory mechanisms underlying alternative polyadenylation.[Supplemental material is available for this article.]Sequencing of mRNA and noncoding RNA has made important contributions to our understanding of biology and disease, with numerous implications for diagnostics and therapeutics. As an outcome of rapidly expanding sequencing capabilities, recently described methods produce comprehensive representations of the transcriptome (Mortazavi et al. 2008;Armour et al. 2009;Wang et al. 2009;Levin et al. 2010) and have been used to discover and monitor alternative splicing (Sultan et al. 2008;Wang et al. 2008;Wilhelm et al. 2008), as well as gene expression (Marioni et al. 2008) and its underlying regulatory genetic variation (Montgomery et al. 2010;Pickrell et al. 2010). While transcriptome sequencing studies continue to focus on gene expression and RNA processing, mapping of polyA sites has received considerably less attention, despite evidence suggesting that alternative polyadenylation is common in metazoans (Lee et al. 2007;Ozsolak et al. 2010) and contributes to phenotypic variation and disease. Avoidance of microRNA regulation via alternative polyA sites, for example, plays a role in development (Mangone et al. 2010;Thomsen et al. 2010;Jan et al. 2011) and cancer Mayr and Bartel 2009). Furthermore, extensive usage of tissue-specific sites, some of which are associated with cis-regulatory elements, suggests that alternative polyadenylation is tightly regulated (Proudfoot et al. 2002) and has important physiological implications. Lastly, the 39UTRs of some genes are expressed ...

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 ...

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SUMMARYThe Wilms' tumor suppressor 1 (WT1) gene encodes a DNA-and RNA-binding protein that plays an essential role in nephron progenitor differentiation during renal development. To identify WT1 target genes that might regulate nephron progenitor differentiation in vivo, we performed chromatin immunoprecipitation (ChIP) coupled to mouse promoter microarray (ChIP-chip) using chromatin prepared from embryonic mouse kidney tissue. We identified 1663 genes bound by WT1, 86% of which contain a previously identified, conserved, high-affinity WT1 binding site. To investigate functional interactions between WT1 and candidate target genes in nephron progenitors, we used a novel, modified WT1 morpholino loss-of-function model in embryonic mouse kidney explants to knock down WT1 expression in nephron progenitors ex vivo. Low doses of WT1 morpholino resulted in reduced WT1 target gene expression specifically in nephron progenitors, whereas high doses of WT1 morpholino arrested kidney explant development and were associated with increased nephron progenitor cell apoptosis, reminiscent of the phenotype observed in Wt1 -/-embryos. Collectively, our results provide a comprehensive description of endogenous WT1 target genes in nephron progenitor cells in vivo, as well as insights into the transcriptional signaling networks controlled by WT1 that might direct nephron progenitor fate during renal development.