Summary Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intra-genic, extra-genic and inter-genic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated non-coding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into the transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells.

We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor–binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor–binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.

Chromatin immunoprecipitation followed by tag sequencing (ChIP-Seq) using high-throughput next-generation instrumentation is replacing ChIP-chip for mapping of sites of transcription-factor binding and chromatin modification. To develop a scoring approach for this new technique, we produce two deeply sequenced datasets for human RNA polymerase II and STAT1 with matching input-DNA controls. In these, we observe that signal peaks corresponding to sites of potential binding are strongly correlated with peaks in the control, likely revealing features of open chromatin. Based on these observations, we develop a two-pass approach for scoring ChIP-Seq relative to controls. The first pass identifies putative binding sites and compensates for genomic variation in the mappability of sequences. The second pass filters sites not significantly enriched compared to the normalized control, computing precise enrichments and significances. Using our scoring we investigate optimal experimental design -i.e. depth of sequencing and value of replicas (showing marginal information gain beyond two).With the advent of new high-throughput sequencing technologies (Helicos HeliScope, Illumina Genome Analyzer, ABI SOLiD, Roche 454), most genome scale assays that previously could only be done cost-effectively using genomic tiling microarrays can now be performed using DNA sequencing. One of the most common uses of tiling microarrays is for performing ChIP-chip 1-3 . In ChIP-chip, DNA associated with a protein of interest is immunoprecipitated using an antibody specific to that protein (chromatin immunoprecipitation or ChIP) and the resulting DNA is labeled and hybridized to a genomic tiling microarray. Early adaptations of ChIP sequencing (e.g. STAGE 4 , ChIP-PET 5,6 ) used Sanger-based sequencing, which generally provided limited tags and/or was expensive. The

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