Summary Most human transcription factors bind a small subset of potential genomic sites and often use different subsets in different cell types. To identify mechanisms that govern cell type-specific transcription factor binding, we used an integrative approach to study estrogen receptor α (ER). We found that ER exhibits two distinct modes of binding. Shared sites, bound in multiple cell types, are characterized by high affinity estrogen response elements (EREs), inaccessible chromatin and a lack of DNA methylation, while cell-specific sites are characterized by a lack of EREs, co-occurrence with other transcription factors and cell type-specific chromatin accessibility and DNA methylation. These observations enabled accurate quantitative models of ER binding that suggest tethering of ER to one-third of cell-specific sites. The distinct properties of cell-specific binding were also observed with glucocorticoid receptor and for ER in primary mouse tissues, representing an elegant genomic encoding scheme for generating cell type-specific gene regulation.

Genome-wide association studies (GWAS) have consistently implicated noncoding variation within the TCF7L2 locus with type 2 diabetes (T2D) risk. While this locus represents the strongest genetic determinant for T2D risk in humans, it remains unclear how these noncoding variants affect disease etiology. To test the hypothesis that the T2D-associated interval harbors cis-regulatory elements controlling TCF7L2 expression, we conducted in vivo transgenic reporter assays to characterize the TCF7L2 regulatory landscape. We found that the 92-kb genomic interval associated with T2D harbors longrange enhancers regulating various aspects of the spatial-temporal expression patterns of TCF7L2, including expression in tissues involved in the control of glucose homeostasis. By selectively deleting this interval, we establish a critical role for these enhancers in robust TCF7L2 expression. To further determine whether variation in Tcf7l2 expression may lead to diabetes, we developed a Tcf7l2 copy-number allelic series in mice. We show that a null Tcf7l2 allele leads, in a dosedependent manner, to lower glycemic profiles. Tcf7l2 null mice also display enhanced glucose tolerance coupled to significantly lowered insulin levels, suggesting that these mice are protected against T2D. Confirming these observations, transgenic mice harboring multiple Tcf7l2 copies and overexpressing this gene display reciprocal phenotypes, including glucose intolerance. These results directly demonstrate that Tcf7l2 plays a role in regulating glucose tolerance, suggesting that overexpression of this gene is associated with increased risk of T2D. These data highlight the role of enhancer elements as mediators of T2D risk in humans, strengthening the evidence that variation in cis-regulatory elements may be a paradigm for genetic predispositions to common disease.[Supplemental material is available for this article.]Recent GWAS have uncovered a number of loci affecting risk of T2D (Voight et al. 2010). While some of these loci include genes known to play a role in glucose metabolism and diabetes pathogenesis (PPARG, KCNJ11) (Willson et al. 2001;Gloyn et al. 2006), others represent genomic regions with unknown functional roles in disease etiology. Among these, a set of single nucleotide polymorphisms (SNPs) on chromosome 10q25.2 shows strong and consistent association with T2D in virtually every population tested, constituting the greatest effect on risk identified to date, with a cumulative allelic odds ratio of 1.46 (Grant et al. 2006;Cauchi et al. 2007;Lyssenko 2008). These SNPs map to a 92-kb interval within TCF7L2, a gene encoding a transcription factor of the canonical Wnt signaling pathway known to have developmental roles in determining cell fate, survival, proliferation, and movement (Moon et al. 2004;Clevers 2006;MacDonald et al. 2009). Given the complexity of this pathway, establishing a definitive role for TCF7L2 in the etiology of T2D has been challenging (Pearson 2009).While the TCF7L2 T2D-associated interval spans coding sequence, exonic v...

Glucocorticoids are universally used in the treatment of acute lymphoblastic leukemia (ALL), and leukemia cell resistant to glucocorticoids confers a poor prognosis. To elucidate mechanisms of glucocorticoid resistance, we determined the sensitivity to prednisolone of primary leukemia cells from 444 newly diagnosed ALL patients, revealing significantly higher expression of caspase 1 (CASP1) and its activator NLRP3 in glucocorticoid resistant leukemia cells, due to significantly lower somatic methylation of CASP1 and NLRP3 promoters. Over-expression of CASP1 resulted in cleavage of the glucocorticoid receptor, diminished glucocorticoid-induced transcriptional response and increased glucocorticoid resistance. Knockdown or inhibition of CASP1 significantly increased glucocorticoid receptor levels and mitigated glucocorticoid resistance in CASP1 overexpressing ALL. Our findings establish a new mechanism by which the NLRP3/CASP1 inflammasome modulates cellular levels of the glucocorticoid receptor and diminishes cell sensitivity to glucocorticoids. The broad impact on glucocorticoid transcriptional response suggests this mechanism could also modify glucocorticoid effects in other diseases.

Chromatin immunoprecipitation followed by next-generation DNA sequencing (ChIP-seq) is a widely used technique for identifying transcription factor (TF) binding events throughout an entire genome. However, ChIP-seq is limited by the availability of suitable ChIP-seq grade antibodies, and the vast majority of commercially available antibodies fail to generate usable data sets. To ameliorate these technical obstacles, we present a robust methodological approach for performing ChIPseq through epitope tagging of endogenous TFs. We used clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-based genome editing technology to develop CRISPR epitope tagging ChIP-seq (CETCh-seq) of DNA-binding proteins. We assessed the feasibility of CETCh-seq by tagging several DNA-binding proteins spanning a wide range of endogenous expression levels in the hepatocellular carcinoma cell line HepG2. Our data exhibit strong correlations between both replicate types as well as with standard ChIP-seq approaches that use TF antibodies. Notably, we also observed minimal changes to the cellular transcriptome and to the expression of the tagged TF. To examine the robustness of our technique, we further performed CETCh-seq in the breast adenocarcinoma cell line MCF7 as well as mouse embryonic stem cells and observed similarly high correlations. Collectively, these data highlight the applicability of CETCh-seq to accurately define the genome-wide binding profiles of DNA-binding proteins, allowing for a straightforward methodology to potentially assay the complete repertoire of TFs, including the large fraction for which ChIP-quality antibodies are not available.

Distal transcription enhancers are cis-regulatory elements that promote gene expression, enabling spatiotemporal control of genetic programs such as those required in metazoan developmental processes. Because of their importance, their disruption can lead to disease.

Despite considerable research connecting cellular metabolism with differentiation decisions, the underlying mechanisms that translate metabolite-sensitive activities into unique gene programs are still unclear. We found that aspects of the interleukin-2 (IL-2)-sensitive effector gene program in CD4+ and CD8+ T cells in type 1 conditions (Th1) were regulated by glutamine and alpha-ketoglutarate (αKG)-induced events, in part through changes in DNA and histone methylation states. We further identified a mechanism by which IL-2- and αKG-sensitive metabolic changes regulated the association of CCCTC-binding factor (CTCF) with select genomic sites. αKG-sensitive CTCF sites were often associated with loci containing IL-2- and αKG-sensitive genome organization patterns and gene expression in T cells. IL-2- and αKG-sensitive CTCF sites in T cells were also associated with genes from developmental pathways that had αKG-sensitive expression in embryonic stem cells. The data collectively support a mechanism wherein CTCF serves to translate αKG-sensitive metabolic changes into context-dependent differentiation gene programs.

Transcription factors are DNA-binding proteins that have key roles in gene regulation 1,2. Genome-wide occupancy maps of transcriptional regulators are important for understanding gene regulation and its effects on diverse biological processes 3-6. However, only a minority of the more than 1,600 transcription factors encoded in the human genome has been assayed. Here we present, as part of the ENCODE (Encyclopedia of DNA Elements) project, data and analyses from chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experiments using the human HepG2 cell line for 208 chromatinassociated proteins (CAPs). These comprise 171 transcription factors and 37 transcriptional cofactors and chromatin regulator proteins, and represent nearly one-quarter of CAPs expressed in HepG2 cells. The binding profiles of these CAPs form major groups associated predominantly with promoters or enhancers, or with both. We confirm and expand the current catalogue of DNA sequence motifs for transcription factors, and describe motifs that correspond to other transcription factors that are co-enriched with the primary ChIP target. For example, FOX family motifs are enriched in ChIP-seq peaks of 37 other CAPs. We show that motif content and occupancy patterns can distinguish between promoters and enhancers. This catalogue reveals high-occupancy target regions at which many CAPs associate, although each contains motifs for only a minority of the numerous associated transcription factors. These analyses provide a more complete overview of the gene regulatory networks that define this cell type, and demonstrate the usefulness of the large-scale production efforts of the ENCODE Consortium. There are an estimated 1,639 transcription factors (TFs) in the human genome 2 , and up to 2,500 CAPs when we include transcriptional cofactors, RNA polymerase-associated proteins, histone-binding regulators, and chromatin-modifying enzymes 1,7. A typical TF binds to a short DNA sequence motif, and, in vivo, some TFs exhibit additional chromosomal occupancy mediated by their interactions with other CAPs 8-10. CAPs are vital for orchestrating cell type-and cell state-specific gene regulation, including the temporal coordination of gene expression in developmental processes, environmental responses, and disease states 3-6,11-13. Identifying genomic regions with which a TF is physically associated, referred to as TF binding sites (TFBSs), is an important step towards understanding its biological roles. The most common genome-wide assay for identifying TFBSs is ChIP-seq 14-16. In addition to highlighting potentially active regulatory DNA elements by direct measurement, ChIP-seq data can define DNA sequence motifs that can be used, often in conjunction with expression data and chromatin accessibility maps, to infer likely binding events in other cellular contexts without performing direct assays. Although motifs identified by ChIP-seq are often representative of direct binding, this is not always the case, as co-occurrence of other TFs could ...

ENCODE 3 (2012-2017) expanded production and added new types of assays 8 (Fig. 1, Extended Data Fig. 1), which revealed landscapes of RNA binding and the 3D organization of chromatin via methods such as chromatin interaction analysis by paired-end tagging (ChIA-PET) and Hi-C chromosome conformation capture. Phases 2 and 3 delivered 9,239 experiments (7,495 in human and 1,744 in mouse) in more than 500 cell types and tissues, including mapping of transcribed regions and transcript isoforms, regions of transcripts recognized by RNA-binding proteins, transcription factor binding regions, and regions that harbour specific histone modifications, open chromatin, and 3D chromatin interactions. The results of all of these experiments are available at the ENCODE portal (http://www.encodeproject.org). These efforts, combined with those of related projects and many other laboratories, have produced a greatly enhanced view of the human genome (Fig. 2), identifying 20,225 protein-coding and 37,595 noncoding genes