The most highly conserved noncoding elements (HCNEs) in mammalian genomes cluster within regions enriched for genes encoding developmentally important transcription factors (TFs). This suggests that HCNE-rich regions may contain key regulatory controls involved in development. We explored this by examining histone methylation in mouse embryonic stem (ES) cells across 56 large HCNE-rich loci. We identified a specific modification pattern, termed ‘‘bivalent domains,’ ’ consisting of large regions of H3 lysine 27 methylation harboring smaller regions of H3 lysine 4 methylation. Bivalent domains tend to coincide with TF genes expressed at low levels. We propose that bivalent domains silence developmental genes in ES cells while keeping them poised for activation. We also found striking correspondences between genome sequence and histone methylation in ES cells, which become notably weaker in differentiated cells. These results highlight the importance of DNA sequence in defining the initial epigenetic landscape and suggest a novel chromatin-based mechanism for maintaining pluripotency.

Accessing and analyzing the exponentially expanding genomic sequence and functional data pose a challenge for biomedical researchers. Here we describe an interactive system, Galaxy, that combines the power of existing genome annotation databases with a simple Web portal to enable users to search remote resources, combine data from independent queries, and visualize the results. The heart of Galaxy is a flexible history system that stores the queries from each user; performs operations such as intersections, unions, and subtractions; and links to other computational tools. Galaxy can be accessed at

Eukaryotic gene transcription is accompanied by acetylation and methylation of nucleosomes near promoters, but the locations and roles of histone modifications elsewhere in the genome remain unclear. We determined the chromatin modification states in high resolution along 30 Mb of the human genome and found that active promoters are marked by trimethylation of Lys4 of histone H3 (H3K4), whereas enhancers are marked by monomethylation, but not trimethylation, of H3K4. We developed computational algorithms using these distinct chromatin signatures to identify new regulatory elements, predicting over 200 promoters and 400 enhancers within the 30-Mb region. This approach accurately predicted the location and function of independently identified regulatory elements with high sensitivity and specificity and uncovered a novel functional enhancer for the carnitine transporter SLC22A5 (OCTN2). Our results give insight into the connections between chromatin modifications and transcriptional regulatory activity and provide a new tool for the functional annotation of the human genome. Activation of eukaryotic gene transcription involves the coordination of a multitude of transcription factors and cofactors on regulatory DNA sequences such as promoters and enhancers and on the chromatin structure containing these elements 1-3 . Promoters are located at the 5¢ ends of genes immediately surrounding the transcriptional start site (TSS) and serve as the point of assembly of the transcriptional machinery and initiation of transcription 4 . Enhancers contribute to the activation of their target genes from positions upstream, downstream or within a target or neighboring gene Recent investigations using chromatin immunoprecipitation (ChIP) and microarray (ChIP-chip) experiments have described the chromatin architecture of transcriptional promoters in yeast, fly and mammalian systems 9 . In a manner largely conserved across species, active promoters are marked by acetylation of various residues of histones H3 and H4 and methylation of H3K4, particularly trimethylation of this residue. Nucleosome depletion is also a general characteristic of active promoters in yeast and flies, although this feature remains to be thoroughly examined in mammalian systems. Although some studies suggest that distal regulatory elements like enhancers may be marked by similar histone modification patterns 10-13 , the distinguishing chromatin features of promoters and enhancers have yet to be determined, hindering our understanding of a predictive histone code for different classes of regulatory elements. Here, we present high-resolution maps of multiple histone modifications and transcriptional regulators in 30 Mb of the human genome, demonstrating that active promoters and enhancers are associated with distinct chromatin signatures that can be used to predict these regulatory elements in the human genome. RESULTS Chromatin architecture and transcription factor localization We performed ChIP-chip analysis 14 to determine the chromatin architecture along 44 human loci selected by the ENCODE consortium as common targets for genomic analysis 15 , totaling 30 Mb.

Noncoding RNAs (ncRNA) participate in epigenetic regulation but are poorly understood. Here we characterize the transcriptional landscape of the four human HOX loci at five base pair resolution in 11 anatomic sites and identify 231 HOX ncRNAs that extend known transcribed regions by more than 30 kilobases. HOX ncRNAs are spatially expressed along developmental axes and possess unique sequence motifs, and their expression demarcates broad chromosomal domains of differential histone methylation and RNA polymerase accessibility. We identified a 2.2 kilobase ncRNA residing in the HOXC locus, termed HOTAIR, which represses transcription in trans across 40 kilobases of the HOXD locus. HOTAIR interacts with Polycomb Repressive Complex 2 (PRC2) and is required for PRC2 occupancy and histone H3 lysine-27 trimethylation of HOXD locus. Thus, transcription of ncRNA may demarcate chromosomal domains of gene silencing at a distance; these results have broad implications for gene regulation in development and disease states.

The estrogen receptor is the master transcriptional regulator of breast cancer phenotype and the archetype of a molecular therapeutic target. We mapped all estrogen receptor and RNA polymerase II binding sites on a genome-wide scale, identifying the authentic cis binding sites and target genes, in breast cancer cells. Combining this unique resource with gene expression data demonstrates distinct temporal mechanisms of estrogen-mediated gene regulation, particularly in the case of estrogen-suppressed genes. Furthermore, this resource has allowed the identification of cis-regulatory sites in previously unexplored regions of the genome and the cooperating transcription factors underlying estrogen signaling in breast cancer. Recent work has focused on identifying gene expression signatures in breast cancer subtypes that predict response to specific treatment regimes and improved disease outcome Estrogen receptor-mediated transcription has been intensively studied on a small number of endogenous target promoters RESULTS The MCF-7 breast cancer cell line has been extensively used as a model of hormone-dependent breast cancer. We deprived MCF-7 cells of hormones for 3 d and then synchronously induced transcription by the addition of estrogen for a brief period of time (45 min) known to result in maximal estrogen receptor-chromatin binding

ABSTRACT In eukaryotes, the core promoter serves as a platform for the assembly of transcription preinitiation complex (PIC) that includes TFIIA, TFIIB,

The genome sequence framework provided by the human genome project allows us to precisely map human genetic variations in order to study their association with disease and their direct effects on gene function. Since the description of tumor suppressor genes and oncogenes several decades ago, both germ-line variations and somatic mutations have been established to be important in cancer—in terms of risk, oncogenesis, prognosis and response to therapy. The Cancer Genome Atlas initiative proposed by the NIH is poised to elucidate the contribution of somatic mutations to cancer development and progression through the re-sequencing of a substantial fraction of the total collection of human genes—in hundreds of individ-ual tumors and spanning several tumor types. We have developed the CancerGenes resource to simplify the process of gene selection and prioriti-zation in large collaborative projects. CancerGenes combines gene lists annotated by experts with information from key public databases. Each gene is annotated with gene name(s), functional descrip-tion, organism, chromosome number, location, Entrez Gene ID, GO terms, InterPro descriptions, gene structure, protein length, transcript count, and experimentally determined transcript control regions, as well as links to Entrez Gene, COSMIC, and iHOP gene pages and the UCSC and Ensembl genome browsers. The user-friendly interface pro-vides for searching, sorting and intersection of gene lists. Users may view tabulated results through a web browser or may dynamically download them as a spreadsheet table. CancerGenes is available at

The recent availability of high-density human genome tiling arrays enables biologists to conduct ChIP– chip experiments to locate the in vivo-binding sites of transcription factors in the human genome and explore the regulatory mechanisms. Once genomic regions enriched by transcription factor ChIP–chip are located, genome-scale downstream analyses are crucial but difficult for biologists without strong bioinformatics support. We designed and implemented the first web server to streamline the ChIP–chip downstream analyses. Given genome-scale ChIP regions, the cis-regulatory element annotation system (CEAS) retrieves repeat-masked genomic sequences, calculates GC content, plots evolutionary conservation, maps nearby genes and identifies enriched transcription factor-binding motifs. Biologists can utilize CEAS to retrieve useful information for ChIP–chip validation, assemble important knowledge to include in their publication and generate novel hypotheses (e.g. transcription factor cooperative partner) for further study. CEAS helps the adoption of ChIP–chip in mammalian systems and provides insights towards a more comprehensive understanding of transcriptional regulatory mechanisms. The

Recent studies have revealed that transcription of noncoding, intergenic DNA is abundant among eukaryotes. However, the functions of this transcription are poorly understood. We have previously shown that in Saccharomyces cerevisiae, expression of an intergenic transcript, SRG1, represses the transcription of the adjacent gene, SER3, by transcription interference. We now show that SRG1 transcription is regulated by serine, thereby conferring regulation of SER3, a serine biosynthetic gene. This regulation requires Cha4, a serine-dependent activator that binds to the SRG1 promoter and is required for SRG1 induction in the presence of serine. Furthermore, two coactivator complexes, SAGA and Swi/Snf, are also directly required for activation of SRG1 and transcription interference of SER3. Taken together, our results elucidate a physiological role for intergenic transcription in the regulation of SER3. Moreover, our results demonstrate a mechanism by which intergenic transcription allows activators to act indirectly as repressors. [Keywords: Intergenic transcription; noncoding RNA; transcription interference; transcription] Supplemental material is available at

A recent development in microarray construction entails the unbiased coverage, or tiling, of non-repetitive genomic DNA for the experimental identification of unannotated transcribed sequences and regulatory elements. A central issue in designing tiling arrays is one of sequence similarity, as significant experimental cross-hybridization can result from the incorporation of non-unique probe sequences. Many genomes contain thousands of repetitive elements that must also be identified and omitted from the array design. Due to the fragmentation introduced by repeats, the problem of obtaining adequate sequence coverage increases with the sizes of subsequence tiles that are to be included on the array. Here we describe the general problem of designing arrays with tiles of varying sizes, and discuss the issues that arise when tiling with shorter and longer sequences. The general problem of sequence tiling can be framed as finding an optimal partitioning of nonrepetitive subsequence fragments, or tiles, for a given range of sizes on a DNA sequence containing repetitive and non-repetitive regions. Exact solutions to the tiling problem can become computationally infeasible when applied to large genomes, but we develop