Master transcription factors and mediator establish super-enhancers at key cell identity genes.

Master transcription factors Oct4, Sox2, and Nanog bind enhancer elements and recruit Mediator to activate much of the gene expression program of pluripotent embryonic stem cells (ESCs). We report here that the ESC master transcription factors form unusual enhancer domains at most genes that control the pluripotent state. These domains, which we call super-enhancers, consist of clusters of enhancers that are densely occupied by the master regulators and Mediator. Super-enhancers differ from typical enhancers in size, transcription factor density and content, ability to activate transcription, and sensitivity to perturbation. Reduced levels of Oct4 or Mediator cause preferential loss of expression of super-enhancer-associated genes relative to other genes, suggesting how changes in gene expression programs might be accomplished during development. In other more differentiated cells, super-enhancers containing cell-type-specific master transcription factors are also found at genes that define cell identity. Super-enhancers thus play key roles in the control of mammalian cell identity.

Selective inhibition of tumor oncogenes by disruption of super-enhancers.

Chromatin regulators have become attractive targets for cancer therapy, but it is unclear why inhibition of these ubiquitous regulators should have gene-specific effects in tumor cells. Here, we investigate how inhibition of the widely expressed transcriptional coactivator BRD4 leads to selective inhibition of the MYC oncogene in multiple myeloma (MM). BRD4 and Mediator were found to co-occupy thousands of enhancers associated with active genes. They also co-occupied a small set of exceptionally large super-enhancers associated with genes that feature prominently in MM biology, including the MYC oncogene. Treatment of MM tumor cells with the BET-bromodomain inhibitor JQ1 led to preferential loss of BRD4 at super-enhancers and consequent transcription elongation defects that preferentially impacted genes with super-enhancers, including MYC. Super-enhancers were found at key oncogenic drivers in many other tumor cells. These observations have implications for the discovery of cancer therapeutics directed at components of super-enhancers in diverse tumor types.

Revisiting global gene expression analysis.

Gene expression analysis is a widely used and powerful method for investigating the transcriptional behavior of biological systems, for classifying cell states in disease, and for many other purposes. Recent studies indicate that common assumptions currently embedded in experimental and analytical practices can lead to misinterpretation of global gene expression data. We discuss these assumptions and describe solutions that should minimize erroneous interpretation of gene expression data from multiple analysis platforms.

Master transcription factors determine cell-type-specific responses to TGF-ß signaling.

Transforming growth factor beta (TGF-ß) signaling, mediated through the transcription factors Smad2 and Smad3 (Smad2/3), directs different responses in different cell types. Here we report that Smad3 co-occupies the genome with cell-type-specific master transcription factors. Thus, Smad3 occupies the genome with Oct4 in embryonic stem cells (ESCs), Myod1 in myotubes, and PU.1 in pro-B cells. We find that these master transcription factors are required for Smad3 occupancy and that TGF-ß signaling largely affects the genes bound by the master transcription factors. Furthermore, we show that induction of Myod1 in nonmuscle cells is sufficient to redirect Smad3 to Myod1 sites. We conclude that cell-type-specific master transcription factors determine the genes bound by Smad2/3 and are thus responsible for orchestrating the cell-type-specific effects of TGF-ß signaling.

Author Correction: Enhancer decommissioning by LSD1 during embryonic stem cell differentiation.

In this Letter, the western blot for LSD1 in the right panel of Fig. 2b ('TCP +') was inadvertently duplicated from the tubulin blot immediately below. The actual tubulin western blot shows the same result, with no significant change to the levels of tubulin (see Fig. 1 of this Amendment). In addition, the western blots for LSD1 and HDAC1 of Fig. 3b and c have been corrected to include vertical black lines to delineate the juxtaposition of lanes that were non-adjacent in the original blotting experiment (see Fig. 2 of this Amendment). Supplementary Figs. 4a, 6b and 9b have also been corrected to delineate non-adjacent lanes with vertical black lines (see Supplementary Information of this Amendment). The complete raw data images from these western blotting experiments can also be found in the Supplementary Information of this Amendment. The original Letter has not been corrected.

Cyclin-dependent kinases are regulators and effectors of oscillations driven by a transcription factor network.

During embryonic cell cycles, B-cyclin-CDKs function as the core component of an autonomous oscillator. Current models for the cell-cycle oscillator in nonembryonic cells are slightly more complex, incorporating multiple G1, S phase, and mitotic cyclin-CDK complexes. However, periodic events persist in yeast cells lacking all S phase and mitotic B-cyclin genes, challenging the assertion that cyclin-CDK complexes are essential for oscillations. These and other results led to the proposal that a network of sequentially activated transcription factors functions as an underlying cell-cycle oscillator. Here we examine the individual contributions of a transcription factor network and cyclin-CDKs to the maintenance of cell-cycle oscillations. Our findings suggest that while cyclin-CDKs are not required for oscillations, they do contribute to oscillation robustness. A model emerges in which cyclin expression (thereby, CDK activity) is entrained to an autonomous transcriptional oscillator. CDKs then modulate oscillator function and serve as effectors of the oscillator.

Enhancer decommissioning by LSD1 during embryonic stem cell differentiation.

Transcription factors and chromatin modifiers are important in the programming and reprogramming of cellular states during development. Transcription factors bind to enhancer elements and recruit coactivators and chromatin-modifying enzymes to facilitate transcription initiation. During differentiation a subset of these enhancers must be silenced, but the mechanisms underlying enhancer silencing are poorly understood. Here we show that the histone demethylase lysine-specific demethylase 1 (LSD1; ref. 5), which demethylates histone H3 on Lys 4 or Lys 9 (H3K4/K9), is essential in decommissioning enhancers during the differentiation of mouse embryonic stem cells (ESCs). LSD1 occupies enhancers of active genes that are critical for control of the state of ESCs. However, LSD1 is not essential for the maintenance of ESC identity. Instead, ESCs lacking LSD1 activity fail to differentiate fully, and ESC-specific enhancers fail to undergo the histone demethylation events associated with differentiation. At active enhancers, LSD1 is a component of the NuRD (nucleosome remodelling and histone deacetylase) complex, which contains additional subunits that are necessary for ESC differentiation. We propose that the LSD1-NuRD complex decommissions enhancers of the pluripotency program during differentiation, which is essential for the complete shutdown of the ESC gene expression program and the transition to new cell states.

The histone methyltransferase SETDB1 is recurrently amplified in melanoma and accelerates its onset.

The most common mutation in human melanoma, BRAF(V600E), activates the serine/threonine kinase BRAF and causes excessive activity in the mitogen-activated protein kinase pathway. BRAF(V600E) mutations are also present in benign melanocytic naevi, highlighting the importance of additional genetic alterations in the genesis of malignant tumours. Such changes include recurrent copy number variations that result in the amplification of oncogenes. For certain amplifications, the large number of genes in the interval has precluded an understanding of the cooperating oncogenic events. Here we have used a zebrafish melanoma model to test genes in a recurrently amplified region of chromosome 1 for the ability to cooperate with BRAF(V600E) and accelerate melanoma. SETDB1, an enzyme that methylates histone H3 on lysine 9 (H3K9), was found to accelerate melanoma formation significantly in zebrafish. Chromatin immunoprecipitation coupled with massively parallel DNA sequencing and gene expression analyses uncovered genes, including HOX genes, that are transcriptionally dysregulated in response to increased levels of SETDB1. Our studies establish SETDB1 as an oncogene in melanoma and underscore the role of chromatin factors in regulating tumorigenesis.

Mediator and cohesin connect gene expression and chromatin architecture.

Transcription factors control cell-specific gene expression programs through interactions with diverse coactivators and the transcription apparatus. Gene activation may involve DNA loop formation between enhancer-bound transcription factors and the transcription apparatus at the core promoter, but this process is not well understood. Here we report that mediator and cohesin physically and functionally connect the enhancers and core promoters of active genes in murine embryonic stem cells. Mediator, a transcriptional coactivator, forms a complex with cohesin, which can form rings that connect two DNA segments. The cohesin-loading factor Nipbl is associated with mediator-cohesin complexes, providing a means to load cohesin at promoters. DNA looping is observed between the enhancers and promoters occupied by mediator and cohesin. Mediator and cohesin co-occupy different promoters in different cells, thus generating cell-type-specific DNA loops linked to the gene expression program of each cell.

Branching process deconvolution algorithm reveals a detailed cell-cycle transcription program.

Due to cell-to-cell variability and asymmetric cell division, cells in a synchronized population lose synchrony over time. As a result, time-series measurements from synchronized cell populations do not reflect the underlying dynamics of cell-cycle processes. Here, we present a branching process deconvolution algorithm that learns a more accurate view of dynamic cell-cycle processes, free from the convolution effects associated with imperfect cell synchronization. Through wavelet-basis regularization, our method sharpens signal without sharpening noise and can remarkably increase both the dynamic range and the temporal resolution of time-series data. Although applicable to any such data, we demonstrate the utility of our method by applying it to a recent cell-cycle transcription time course in the eukaryote Saccharomyces cerevisiae. Our method more sensitively detects cell-cycle-regulated transcription and reveals subtle timing differences that are masked in the original population measurements. Our algorithm also explicitly learns distinct transcription programs for mother and daughter cells, enabling us to identify 82 genes transcribed almost entirely in early G1 in a daughter-specific manner.

Divergent transcription of long noncoding RNA/mRNA gene pairs in embryonic stem cells.

Many long noncoding RNA (lncRNA) species have been identified in mammalian cells, but the genomic origin and regulation of these molecules in individual cell types is poorly understood. We have generated catalogs of lncRNA species expressed in human and murine embryonic stem cells and mapped their genomic origin. A surprisingly large fraction of these transcripts (>60%) originate from divergent transcription at promoters of active protein-coding genes. The divergently transcribed lncRNA/mRNA gene pairs exhibit coordinated changes in transcription when embryonic stem cells are differentiated into endoderm. Our results reveal that transcription of most lncRNA genes is coordinated with transcription of protein-coding genes.

Global control of cell-cycle transcription by coupled CDK and network oscillators.

A significant fraction of the Saccharomyces cerevisiae genome is transcribed periodically during the cell division cycle, indicating that properly timed gene expression is important for regulating cell-cycle events. Genomic analyses of the localization and expression dynamics of transcription factors suggest that a network of sequentially expressed transcription factors could control the temporal programme of transcription during the cell cycle. However, directed studies interrogating small numbers of genes indicate that their periodic transcription is governed by the activity of cyclin-dependent kinases (CDKs). To determine the extent to which the global cell-cycle transcription programme is controlled by cyclin-CDK complexes, we examined genome-wide transcription dynamics in budding yeast mutant cells that do not express S-phase and mitotic cyclins. Here we show that a significant fraction of periodic genes are aberrantly expressed in the cyclin mutant. Although cells lacking cyclins are blocked at the G1/S border, nearly 70% of periodic genes continued to be expressed periodically and on schedule. Our findings reveal that although CDKs have a function in the regulation of cell-cycle transcription, they are not solely responsible for establishing the global periodic transcription programme. We propose that periodic transcription is an emergent property of a transcription factor network that can function as a cell-cycle oscillator independently of, and in tandem with, the CDK oscillator.

CpG island structure and trithorax/polycomb chromatin domains in human cells.

TrxG and PcG complexes play key roles in the epigenetic regulation of development through H3K4me3 and H3K27me3 modification at specific sites throughout the human genome, but how these sites are selected is poorly understood. We find that in pluripotent cells, clustered CpG-islands at genes predict occupancy of H3K4me3 and H3K27me3, and these "bivalent" chromatin domains precisely span the boundaries of CpG-island clusters. These relationships are specific to pluripotent stem cells and are not retained at H3K4me3 and H3K27me3 sites unique to differentiated cells. We show that putative transcripts from clustered CpG-islands predict stem-loop structures characteristic of those bound by PcG complexes, consistent with the possibility that RNA facilitates PcG recruitment or maintenance at these sites. These studies suggest that CpG-island structure plays a fundamental role in establishing developmentally important chromatin structures in the pluripotent genome, and a subordinate role in establishing TrxG/PcG chromatin structure at sites unique to differentiated cells.

Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons.

Investigating the cell cycle often depends on synchronizing cell populations to measure various parameters in a time series as the cells traverse the cell cycle. However, even under similar conditions, replicate experiments display differences in the time required to recover from synchrony and to traverse the cell cycle, thus preventing direct comparisons at each time point. The problem of comparing dynamic measurements across experiments is exacerbated in mutant populations or in alternative growth conditions that affect the synchrony recovery time and/or the cell-cycle period. We have previously published a parametric mathematical model named Characterizing Loss of Cell Cycle Synchrony (CLOCCS) that monitors how synchronous populations of cells release from synchrony and progress through the cell cycle. The learned parameters from the model can then be used to convert experimental time points from synchronized time-series experiments into a normalized time scale (lifeline points). Rather than representing the elapsed time in minutes from the start of the experiment, the lifeline scale represents the progression from synchrony to cell-cycle entry and then through the phases of the cell cycle. Since lifeline points correspond to the phase of the average cell within the synchronized population, this normalized time scale allows for direct comparisons between experiments, including those with varying periods and recovery times. Furthermore, the model has been used to align cell-cycle experiments between different species (e.g., Saccharomyces cerevisiae and Schizosaccharomyces pombe), thus enabling direct comparison of cell-cycle measurements, which may reveal evolutionary similarities and differences.

Detecting separate time scales in genetic expression data.

BACKGROUND: Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. RESULTS: We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. CONCLUSIONS: The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.

Reconstructing spatiotemporal gene expression data from partial observations.

MOTIVATION: Developmental transcriptional networks in plants and animals operate in both space and time. To understand these transcriptional networks it is essential to obtain whole-genome expression data at high spatiotemporal resolution. Substantial amounts of spatial and temporal microarray expression data previously have been obtained for the Arabidopsis root; however, these two dimensions of data have not been integrated thoroughly. Complicating this integration is the fact that these data are heterogeneous and incomplete, with observed expression levels representing complex spatial or temporal mixtures. RESULTS: Given these partial observations, we present a novel method for reconstructing integrated high-resolution spatiotemporal data. Our method is based on a new iterative algorithm for finding approximate roots to systems of bilinear equations. AVAILABILITY: Source code for solving bilinear equations is available at http://math.berkeley.edu/ approximately dustin/bilinear/. Visualizations of reconstructed patterns on a schematic Arabidopsis root are available at http://www.arexdb.org/.

Protonophore- and pH-insensitive glucose and sucrose accumulation detected by FRET nanosensors in Arabidopsis root tips.

Although soil contains only traces of soluble carbohydrates, plant roots take up glucose and sucrose efficiently when supplied in artificial media. Soluble carbohydrates and other small metabolites found in soil are in part products from exudation from plant roots. The molecular nature of the transporters for uptake and exudation is unknown. Here, fluorescence resonance energy transfer (FRET) glucose and sucrose sensors were used to characterize accumulation and elimination of glucose and sucrose in Arabidopsis roots tips. Using an improved image acquisition set-up, FRET responses to perfusion with carbohydrates were detectable in roots within less than 10 sec and over a wide concentration range. Accumulation was fully reversible within 10-180 sec after glucose or sucrose had been withdrawn; elimination may be caused by metabolism and/or efflux. The rate of elimination was unaffected by pre-incubation with high concentrations of glucose, suggesting that elimination is not due to accumulation in a short-term buffer such as the vacuole. Glucose and sucrose accumulation was insensitive to protonophores, was comparable in media differing in potassium levels, and was similar at pH 5.8, 6.8 and 7.8, suggesting that both influx and efflux may be mediated by proton-independent transport systems. High-resolution expression mapping in root tips showed that only a few proton-dependent transport of the STP (Sugar Transport Protein) and SUT/SUC (Sucrose Transporter/Carrier) families are expressed in the external cell layers of root tips. The root expression maps may help to pinpoint candidate genes for uptake and release of carbohydrates from roots.

Discovery and Characterization of SY-1365, a Selective, Covalent Inhibitor of CDK7.

Recent studies suggest that targeting transcriptional machinery can lead to potent and selective anticancer effects in cancers dependent on high and constant expression of certain transcription factors for growth and survival. Cyclin-dependent kinase 7 (CDK7) is the catalytic subunit of the CDK-activating kinase complex. Its function is required for both cell-cycle regulation and transcriptional control of gene expression. CDK7 has recently emerged as an attractive cancer target because its inhibition leads to decreased transcript levels of oncogenic transcription factors, especially those associated with super-enhancers. Here, we describe a selective CDK7 inhibitor SY-1365, which is currently in clinical trials in populations of patients with ovarian and breast cancer (NCT03134638). In vitro, SY-1365 inhibited cell growth of many different cancer types at nanomolar concentrations. SY-1365 treatment decreased MCL1 protein levels, and cancer cells with low BCL2L1 (BCL-XL) expression were found to be more sensitive to SY-1365. Transcriptional changes in acute myeloid leukemia (AML) cell lines were distinct from those following treatment with other transcriptional inhibitors. SY-1365 demonstrated substantial antitumor effects in multiple AML xenograft models as a single agent; SY-1365-induced growth inhibition was enhanced in combination with the BCL2 inhibitor venetoclax. Antitumor activity was also observed in xenograft models of ovarian cancer, suggesting the potential for exploring SY-1365 in the clinic in both hematologic and solid tumors. Our findings support targeting CDK7 as a new approach for treating transcriptionally addicted cancers. SIGNIFICANCE: These findings demonstrate the molecular mechanism of action and potent antitumor activity of SY-1365, the first selective CDK7 inhibitor to enter clinical investigation.

Superenhancer Analysis Defines Novel Epigenomic Subtypes of Non-APL AML, Including an RARα Dependency Targetable by SY-1425, a Potent and Selective RARα Agonist.

We characterized the enhancer landscape of 66 patients with acute myeloid leukemia (AML), identifying 6 novel subgroups and their associated regulatory loci. These subgroups are defined by their superenhancer (SE) maps, orthogonal to somatic mutations, and are associated with distinct leukemic cell states. Examination of transcriptional drivers for these epigenomic subtypes uncovers a subset of patients with a particularly strong SE at the retinoic acid receptor alpha (RARA) gene locus. The presence of a RARA SE and concomitant high levels of RARA mRNA predisposes cell lines and ex vivo models to exquisite sensitivity to a selective agonist of RARα, SY-1425 (tamibarotene). Furthermore, only AML patient-derived xenograft (PDX) models with high RARA mRNA were found to respond to SY-1425. Mechanistically, we show that the response to SY-1425 in RARA-high AML cells is similar to that of acute promyelocytic leukemia treated with retinoids, characterized by the induction of known retinoic acid response genes, increased differentiation, and loss of proliferation.Significance: We use the SE landscape of primary human AML to elucidate transcriptional circuitry and identify novel cancer vulnerabilities. A subset of patients were found to have an SE at RARA, which is predictive for response to SY-1425, a potent and selective RARα agonist, in preclinical models, forming the rationale for its clinical investigation in biomarker-selected patients. Cancer Discov; 7(10); 1136-53. ©2017 AACR.See related commentary by Wang and Aifantis, p. 1065.This article is highlighted in the In This Issue feature, p. 1047.

Quantitative ChIP-Seq normalization reveals global modulation of the epigenome.

Epigenomic profiling by chromatin immunoprecipitation coupled with massively parallel DNA sequencing (ChIP-seq) is a prevailing methodology used to investigate chromatin-based regulation in biological systems such as human disease, but the lack of an empirical methodology to enable normalization among experiments has limited the precision and usefulness of this technique. Here, we describe a method called ChIP with reference exogenous genome (ChIP-Rx) that allows one to perform genome-wide quantitative comparisons of histone modification status across cell populations using defined quantities of a reference epigenome. ChIP-Rx enables the discovery and quantification of dynamic epigenomic profiles across mammalian cells that would otherwise remain hidden using traditional normalization methods. We demonstrate the utility of this method for measuring epigenomic changes following chemical perturbations and show how reference normalization of ChIP-seq experiments enables the discovery of disease-relevant changes in histone modification occupancy.