The human genome contains regulatory elements, such as enhancers, that are often rewired by cancer cells for the activation of genes that promote tumorigenesis and resistance to therapy. This is especially true for cancers that have little or no known driver mutations within protein coding genes, such as ovarian cancer. Herein, we utilize an integrated set of genomic and epigenomic datasets to identify clinically relevant super-enhancers that are preferentially amplified in ovarian cancer patients. We systematically probe the top 86 super-enhancers, using CRISPR-interference and CRISPR-deletion assays coupled to RNA-sequencing, to nominate two salient super-enhancers that drive proliferation and migration of cancer cells. Utilizing Hi-C, we construct chromatin interaction maps that enable the annotation of direct target genes for these super-enhancers and confirm their activity specifically within the cancer cell compartment of human tumors using single-cell genomics data. Together, our multi-omic approach examines a number of fundamental questions about how regulatory information encoded into super-enhancers drives gene expression networks that underlie the biology of ovarian cancer.

The genetic, epigenetic, and gene regulatory mechanisms underlying how hormone signal transduction influences erythroid gene expression remains only partly understood. A detailed understanding of these molecular pathways and how they intersect with one another will provide the basis for novel strategies to treat anemia and potentially other hematological diseases. As new regulators and signal transducers of EPO-signaling continue to emerge, new clinically relevant targets may be identified that improve the specificity and effectiveness of EPO therapy.

The hormone erythropoietin (Epo) is required for erythropoiesis, yet its molecular mechanism of action remains poorly understood, particularly with respect to chromatin dynamics. To investigate how Epo modulates the erythroid epigenome, we performed epigenetic profiling using an ex vivo murine cell system that undergoes synchronous erythroid maturation in response to Epo stimulation. Our findings define the repertoire of Epo-modulated enhancers, illuminating a new facet of Epo signaling. First, a large number of enhancers rapidly responded to Epo stimulation, revealing a cis-regulatory network of Epo-responsive enhancers. In contrast, most of the other identified enhancers remained in an active acetylated state during Epo signaling, suggesting that most erythroid enhancers are established at an earlier precursor stage. Second, we identified several hundred super-enhancers that were linked to key erythroid genes, such as Tal1, Bcl11a, and Mir144/451. Third, experimental and computational validation revealed that many predicted enhancer regions were occupied by TAL1 and enriched with DNA-binding motifs for GATA1, KLF1, TAL1/E-box, and STAT5. Additionally, many of these cis-regulatory regions were conserved evolutionarily and displayed correlated enhancer:promoter acetylation. Together, these findings define a cis-regulatory enhancer network for Epo signaling during erythropoiesis, and provide the framework for future studies involving the interplay of epigenetics and Epo signaling.

The human HCC1806 cell line is frequently used as a preclinical model for triple negative breast cancer (TNBC). Given that dysregulated epigenetic mechanisms are involved in cancer pathogenesis, emerging therapeutic strategies target chromatin regulators, such as histone deacetylases. A comprehensive understanding of the epigenome and transcription profiling in HCC1806 provides the framework for evaluating efficacy and molecular mechanisms of epigenetic therapies. Thus, to study the interplay of transcription and chromatin in the HCC1806 preclinical model, we performed nascent transcription profiling using Precision Run-On coupled to sequencing (PRO-seq). Additionally, we mapped the genome-wide locations for RNA polymerase II (Pol II), the histone variant H2A.Z, seven histone modifications, and CTCF using ChIP-exo. ChIP-exonuclease (ChIP-exo) is a refined version of ChIP-seq with near base pair precision mapping of protein-DNA interactions. In this Data Descriptor, we present detailed information on experimental design, data generation, quality control analysis, and data validation. We discuss how these data lay the foundation for future analysis to understand the relationship between the nascent transcription and chromatin.

The human K562 chronic myeloid leukemia cell line has long served as an experimental paradigm for functional genomic studies. To systematically and functionally annotate the human genome, the ENCODE consortium generated hundreds of functional genomic data sets, such as chromatin immunoprecipitation coupled to sequencing (ChIP-seq). While ChIP-seq analyses have provided tremendous insights into gene regulation, spatiotemporal insights were limited by a resolution of several hundred base pairs. ChIP-exonuclease (ChIP-exo) is a refined version of ChIP-seq that overcomes this limitation by providing higher precision mapping of protein-DNA interactions. To study the interplay of transcription initiation and chromatin, we profiled the genome-wide locations for RNA polymerase II (Pol II), the histone variant H2A.Z, and the histone modification H3K4me3 using ChIP-seq and ChIP-exo. In this Data Descriptor, we present detailed information on parallel experimental design, data generation, quality control analysis, and data validation. We discuss how these data lay the foundation for future analysis to understand the relationship between the occupancy of Pol II and nucleosome positions at near base pair resolution.