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The advent of single-cell sequencing has been revolutionary to the field of cancer genomics. Perfectly suited to capture cancer's heterogeneous nature, single-cell analyses provide information bulk sequencing could never hope to uncover. Many mechanisms of cancer have yet to be fully understood, and single-cell approaches are showing promise in their abilities to uncover these mysteries. Here we focus on the most recent single-cell methods for cancer genomics, and how they are not only providing insights into the inner workings of cancer, but are also transforming individualized therapy and non-invasive monitoring and diagnosis., (Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Invariant natural killer T cells (iNKT cells) are innate-like lymphocytes that protect against infection, autoimmune disease and cancer. However, little is known about the epigenetic regulation of iNKT cell development. Here we found that the H3K27me3 histone demethylase UTX was an essential cell-intrinsic factor that controlled an iNKT-cell lineage-specific gene-expression program and epigenetic landscape in a demethylase-activity-dependent manner. UTX-deficient iNKT cells exhibited impaired expression of iNKT cell signature genes due to a decrease in activation-associated H3K4me3 marks and an increase in repressive H3K27me3 marks within the promoters occupied by UTX. We found that JunB regulated iNKT cell development and that the expression of genes that were targets of both JunB and the iNKT cell master transcription factor PLZF was UTX dependent. We identified iNKT cell super-enhancers and demonstrated that UTX-mediated regulation of super-enhancer accessibility was a key mechanism for commitment to the iNKT cell lineage. Our findings reveal how UTX regulates the development of iNKT cells through multiple epigenetic mechanisms.

Recently, long non-coding RNAs (lncRNAs) have emerged as an important class of molecules involved in many cellular processes. One of their primary functions is to shape epigenetic landscape through interactions with chromatin modifying proteins. However, mechanisms contributing to the specificity of such interactions remain poorly understood. Here we took the human and mouse lncRNAs that were experimentally determined to have physical interactions with Polycomb repressive complex 2 (PRC2), and systematically investigated the sequence features of these lncRNAs by developing a new computational pipeline for sequences composition analysis, in which each sequence is considered as a series of transitions between adjacent nucleotides. Through that, PRC2-binding lncRNAs were found to be associated with a set of distinctive and evolutionarily conserved sequence features, which can be utilized to distinguish them from the others with considerable accuracy. We further identified fragments of PRC2-binding lncRNAs that are enriched with these sequence features, and found they show strong PRC2-binding signals and are more highly conserved across species than the other parts, implying their functional importance., Competing Interests: The authors declare no competing financial interests.

Recent work has shown that RNA polymerase II-mediated transcription at distal cis-regulatory elements serves as a mark of highly active enhancers. Production of noncoding RNAs at enhancers, termed eRNAs, correlates with higher expression of genes that the enhancer interacts with; hence, eRNAs provide a new tool to model gene activity in normal and disease tissues. Moreover, this unique class of noncoding RNA has diverse roles in transcriptional regulation. Transcribed enhancers can be identified by a common signature of epigenetic marks by overlaying a series of genome-wide chromatin immunoprecipitation and RNA sequencing datasets. A computational approach to filter non-enhancer elements and other classes of noncoding RNAs is essential to not cloud downstream analysis. Here we present a protocol that combines wet and dry bench methods to accurately identify transcribed enhancers genome-wide as well as an experimental procedure to validate these datasets.

BACKGROUND. Immune checkpoint blockade improves survival in a subset of patients with non-small-cell lung cancer (NSCLC), but robust biomarkers that predict response to PD-1 pathway inhibitors are lacking. Furthermore, our understanding of the diversity of the NSCLC tumor immune microenvironment remains limited. METHODS. We performed comprehensive flow cytometric immunoprofiling on both tumor and immune cells from 51 NSCLCs and integrated this analysis with clinical and histopathologic characteristics, next-generation sequencing, mRNA expression, and PD-L1 immunohistochemistry (IHC). RESULTS. Cytometric profiling identified an immunologically "hot" cluster with abundant CD8 + T cells expressing high levels of PD-1 and TIM-3 and an immunologically "cold" cluster with lower relative abundance of CD8 + T cells and expression of inhibitory markers. The "hot" cluster was highly enriched for expression of genes associated with T cell trafficking and cytotoxic function and high PD-L1 expression by IHC. There was no correlation between immunophenotype and KRAS or EGFR mutation, or patient smoking history, but we did observe an enrichment of squamous subtype and tumors with higher mutation burden in the "hot" cluster. Additionally, approximately 20% of cases had high B cell infiltrates with a subset producing IL-10. CONCLUSIONS. Our results support the use of immune-based metrics to study response and resistance to immunotherapy in lung cancer. FUNDING. The Robert A. and Renée E. Belfer Family Foundation, Expect Miracles Foundation, Starr Cancer Consortium, Stand Up to Cancer Foundation, Conquer Cancer Foundation, International Association for the Study of Lung Cancer, National Cancer Institute (R01 CA205150), and the Damon Runyon Cancer Research Foundation.

Lgr5(+) intestinal stem cells (ISCs) drive epithelial self-renewal, and their immediate progeny-intestinal bipotential progenitors-produce absorptive and secretory lineages via lateral inhibition. To define features of early transit from the ISC compartment, we used a microfluidics approach to measure selected stem- and lineage-specific transcripts in single Lgr5(+) cells. We identified two distinct cell populations, one that expresses known ISC markers and a second, abundant population that simultaneously expresses markers of stem and mature absorptive and secretory cells. Single-molecule mRNA in situ hybridization and immunofluorescence verified expression of lineage-restricted genes in a subset of Lgr5(+) cells in vivo. Transcriptional network analysis revealed that one group of Lgr5(+) cells arises from the other and displays characteristics expected of bipotential progenitors, including activation of Notch ligand and cell-cycle-inhibitor genes. These findings define the earliest steps in ISC differentiation and reveal multilineage gene priming as a fundamental property of the process., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.)

Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR (Ensemble Cell Lineage Analysis with Improved Robustness), a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Brain metastases represent the greatest clinical challenge in treating HER2-positive breast cancer. We report the development of orthotopic patient-derived xenografts (PDXs) of HER2-expressing breast cancer brain metastases (BCBM), and their use for the identification of targeted combination therapies. Combined inhibition of PI3K and mTOR resulted in durable tumor regressions in three of five PDXs, and therapeutic response was correlated with a reduction in the phosphorylation of 4EBP1, an mTORC1 effector. The two nonresponding PDXs showed hypermutated genomes with enrichment of mutations in DNA-repair genes, which suggests an association of genomic instability with therapeutic resistance. These findings suggest that a biomarker-driven clinical trial of PI3K inhibitor in combination with an mTOR inhibitor should be conducted for patients with HER2-positive BCBM.

High-throughput single-cell technologies have great potential to discover new cell types; however, it remains challenging to detect rare cell types that are distinct from a large population. We present a novel computational method, called GiniClust, to overcome this challenge. Validation against a benchmark dataset indicates that GiniClust achieves high sensitivity and specificity. Application of GiniClust to public single-cell RNA-seq datasets uncovers previously unrecognized rare cell types, including Zscan4-expressing cells within mouse embryonic stem cells and hemoglobin-expressing cells in the mouse cortex and hippocampus. GiniClust also correctly detects a small number of normal cells that are mixed in a cancer cell population.

Bivalent promoters in embryonic stem cells (ESCs) carry methylation marks on two lysine residues, K4 and K27, in histone3 (H3). K4me2/3 is generally considered to promote transcription, and Polycomb Repressive Complex 2 (PRC2) places K27me3, which is erased at lineage-restricted genes when ESCs differentiate in culture. Molecular defects in various PRC2 null adult tissues lack a unifying explanation. We found that epigenomes in adult mouse intestine and other self-renewing tissues show fewer and distinct bivalent promoters compared to ESCs. Groups of tissue-specific genes that carry bivalent marks are repressed, despite the presence of promoter H3K4me2/3. These are the predominant genes de-repressed in PRC2-deficient adult cells, where aberrant expression is proportional to the H3K4me2/3 levels observed at their promoters in wild-type cells. Thus, in adult animals, PRC2 specifically represses genes with acquired, tissue-restricted promoter bivalency. These findings provide new insights into specificity in chromatin-based gene regulation., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: The cohesin complex consists of multiple core subunits that play critical roles in mitosis and transcriptional regulation. The cohesin-associated protein Wapal plays a central role in off-loading cohesin to facilitate sister chromatid separation, but its role in regulating mammalian gene expression is not understood. We used embryonic stem cells as a model, given that the well-defined transcriptional regulatory circuits were established through master transcription factors and epigenetic pathways that regulate their ability to maintain a pluripotent state., Results: RNAi-mediated depletion of Wapal causes a loss of pluripotency, phenocopying loss of core cohesin subunits. Using chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq), we determine that Wapal occupies genomic sites distal to genes in combination with CTCF and core cohesin subunits such as Rad21. Interestingly, genomic sites occupied by Wapal appear enriched for cohesin, implying that Wapal does not off-load cohesin at regions it occupies. Wapal depletion induces derepression of Polycomb group (PcG) target genes without altering total levels of Polycomb-mediated histone modifications, implying that PcG enzymatic activity is preserved. By integrating ChIP-seq and gene expression changes data, we identify that Wapal binding is enriched at the promoters of PcG-silenced genes and is required for proper Polycomb repressive complex 2 (PRC2) recruitment. Lastly, we demonstrate that Wapal is required for the interaction of a distal cis-regulatory element (CRE) with the c-Fos promoter., Conclusions: Collectively, this work indicates that Wapal plays a critical role in silencing of PcG target genes through the interaction of distal CREs with promoters.

Little is known about how pro-obesity diets regulate tissue stem and progenitor cell function. Here we show that high-fat diet (HFD)-induced obesity augments the numbers and function of Lgr5(+) intestinal stem cells of the mammalian intestine. Mechanistically, a HFD induces a robust peroxisome proliferator-activated receptor delta (PPAR-δ) signature in intestinal stem cells and progenitor cells (non-intestinal stem cells), and pharmacological activation of PPAR-δ recapitulates the effects of a HFD on these cells. Like a HFD, ex vivo treatment of intestinal organoid cultures with fatty acid constituents of the HFD enhances the self-renewal potential of these organoid bodies in a PPAR-δ-dependent manner. Notably, HFD- and agonist-activated PPAR-δ signalling endow organoid-initiating capacity to progenitors, and enforced PPAR-δ signalling permits these progenitors to form in vivo tumours after loss of the tumour suppressor Apc. These findings highlight how diet-modulated PPAR-δ activation alters not only the function of intestinal stem and progenitor cells, but also their capacity to initiate tumours.

Variation in gene expression is an important feature of mouse embryonic stem cells (ESCs). However, the mechanisms responsible for global gene expression variation in ESCs are not fully understood. We performed single-cell mRNA-seq analysis of mouse ESCs and uncovered significant heterogeneity in ESCs cultured in serum. We define highly variable gene clusters with distinct chromatin states and show that bivalent genes are prone to expression variation. At the same time, we identify an ESC-priming pathway that initiates the exit from the naive ESC state. Finally, we provide evidence that a large proportion of intracellular network variability is due to the extracellular culture environment. Serum-free culture reduces cellular heterogeneity and transcriptome variation in ESCs., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Chronic obstructive pulmonary disease (COPD) is linked to both cigarette smoking and genetic determinants. We have previously identified iron-responsive element-binding protein 2 (IRP2) as an important COPD susceptibility gene and have shown that IRP2 protein is increased in the lungs of individuals with COPD. Here we demonstrate that mice deficient in Irp2 were protected from cigarette smoke (CS)-induced experimental COPD. By integrating RNA immunoprecipitation followed by sequencing (RIP-seq), RNA sequencing (RNA-seq), and gene expression and functional enrichment clustering analysis, we identified Irp2 as a regulator of mitochondrial function in the lungs of mice. Irp2 increased mitochondrial iron loading and levels of cytochrome c oxidase (COX), which led to mitochondrial dysfunction and subsequent experimental COPD. Frataxin-deficient mice, which had higher mitochondrial iron loading, showed impaired airway mucociliary clearance (MCC) and higher pulmonary inflammation at baseline, whereas mice deficient in the synthesis of cytochrome c oxidase, which have reduced COX, were protected from CS-induced pulmonary inflammation and impairment of MCC. Mice treated with a mitochondrial iron chelator or mice fed a low-iron diet were protected from CS-induced COPD. Mitochondrial iron chelation also alleviated CS-induced impairment of MCC, CS-induced pulmonary inflammation and CS-associated lung injury in mice with established COPD, suggesting a critical functional role and potential therapeutic intervention for the mitochondrial-iron axis in COPD.

Enhancers are the primary determinants of cell identity, but the regulatory components controlling enhancer turnover during lineage commitment remain largely unknown. Here we compare the enhancer landscape, transcriptional factor occupancy, and transcriptomic changes in human fetal and adult hematopoietic stem/progenitor cells and committed erythroid progenitors. We find that enhancers are modulated pervasively and direct lineage- and stage-specific transcription. GATA2-to-GATA1 switch is prevalent at dynamic enhancers and drives erythroid enhancer commissioning. Examination of lineage-specific enhancers identifies transcription factors and their combinatorial patterns in enhancer turnover. Importantly, by CRISPR/Cas9-mediated genomic editing, we uncover functional hierarchy of constituent enhancers within the SLC25A37 super-enhancer. Despite indistinguishable chromatin features, we reveal through genomic editing the functional diversity of several GATA switch enhancers in which enhancers with opposing functions cooperate to coordinate transcription. Thus, genome-wide enhancer profiling coupled with in situ enhancer editing provide critical insights into the functional complexity of enhancers during development., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Precise nucleosome positioning is an increasingly recognized feature of promoters and enhancers, reflecting complex contributions of DNA sequence, nucleosome positioning, histone modification and transcription factor binding to enhancer activity and regulation of gene expression. Changes in nucleosome position and occupancy, histone variants and modifications, and chromatin remodeling are also critical elements of dynamic transcriptional regulation, but poorly understood at enhancers. We investigated glucocorticoid receptor-associated (GR) nucleosome dynamics at enhancers in acute lymphoblastic leukemia., Results: For the first time, we demonstrate functionally distinct modes of nucleosome remodeling upon chromatin binding by GR, which we term central, non-central, phased, and minimal. Central and non-central remodeling reflect nucleosome eviction by GR and cofactors, respectively. Phased remodeling involves nucleosome repositioning and is associated with rapidly activated enhancers and induction of gene expression. Minimal remodeling sites initially have low levels of enhancer-associated histone modification, but the majority of these regions gain H3K4me2 or H3K27Ac to become de novo enhancers. Minimal remodeling regions are associated with gene ontologies specific to decreased B cell number and mTOR inhibition and may make unique contributions to glucocorticoid-induced leukemia cell death., Conclusions: Our findings form a novel framework for understanding the dynamic interplay between transcription factor binding, nucleosome remodeling, enhancer function, and gene expression in the leukemia response to glucocorticoids.

Enhancers, critical determinants of cellular identity, are commonly recognized by correlative chromatin marks and gain-of-function potential, although only loss-of-function studies can demonstrate their requirement in the native genomic context. Previously, we identified an erythroid enhancer of human BCL11A, subject to common genetic variation associated with the fetal haemoglobin level, the mouse orthologue of which is necessary for erythroid BCL11A expression. Here we develop pooled clustered regularly interspaced palindromic repeat (CRISPR)-Cas9 guide RNA libraries to perform in situ saturating mutagenesis of the human and mouse enhancers. This approach reveals critical minimal features and discrete vulnerabilities of these enhancers. Despite conserved function of the composite enhancers, their architecture diverges. The crucial human sequences appear to be primate-specific. Through editing of primary human progenitors and mouse transgenesis, we validate the BCL11A erythroid enhancer as a target for fetal haemoglobin reinduction. The detailed enhancer map will inform therapeutic genome editing, and the screening approach described here is generally applicable to functional interrogation of non-coding genomic elements.

Genetic changes and environmental differences result in cellular heterogeneity among cancer cells within the same tumor, thereby complicating treatment outcomes. Recent advances in single-cell technologies have opened new avenues to characterize the intra-tumor cellular heterogeneity, identify rare cell types, measure mutation rates, and, ultimately, guide diagnosis and treatment. In this paper we review the recent single-cell technological and computational advances at the genomic, transcriptomic, and proteomic levels, and discuss their applications in cancer research., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The transcription factor STAT3 is constitutively active in many cancers, where it mediates important biological effects, including cell proliferation, differentiation, survival, and angiogenesis. The N-terminal domain (NTD) of STAT3 performs multiple functions, such as cooperative DNA binding, nuclear translocation, and protein-protein interactions. However, it is unclear which subsets of STAT3 target genes depend on the NTD for transcriptional regulation. To identify such genes, we compared gene expression in STAT3-null mouse embryonic fibroblasts (MEFs) stably expressing wild-type STAT3 or STAT3 from which NTD was deleted. NTD deletion reduced the cytokine-induced expression of specific STAT3 target genes by decreasing STAT3 binding to their regulatory regions. To better understand the potential mechanisms of this effect, we determined the crystal structure of the STAT3 NTD and identified a dimer interface responsible for cooperative DNA binding in vitro. We also observed an Ni(2+)-mediated oligomer with an as yet unknown biological function. Mutations on both dimer and Ni(2+)-mediated interfaces affected the cytokine induction of STAT3 target genes. These studies shed light on the role of the NTD in transcriptional regulation by STAT3 and provide a structural template with which to design STAT3 NTD inhibitors with potential therapeutic value., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Genome-wide mapping of three dimensional chromatin organization is an important yet technically challenging task. To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries. Our model accurately and robustly predicts these features across datasets and cell types. Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries. Our predictions provide a useful guide for the exploration of chromatin organization.

Background: We recently identified two robust ovarian cancer subtypes, defined by the expression of genes involved in angiogenesis, with significant differences in clinical outcome. To identify potential regulatory mechanisms that distinguish the subtypes we applied PANDA, a method that uses an integrative approach to model information flow in gene regulatory networks., Results: We find distinct differences between networks that are active in the angiogenic and non-angiogenic subtypes, largely defined by a set of key transcription factors that, although previously reported to play a role in angiogenesis, are not strongly differentially-expressed between the subtypes. Our network analysis indicates that these factors are involved in the activation (or repression) of different genes in the two subtypes, resulting in differential expression of their network targets. Mechanisms mediating differences between subtypes include a previously unrecognized pro-angiogenic role for increased genome-wide DNA methylation and complex patterns of combinatorial regulation., Conclusions: The models we develop require a shift in our interpretation of the driving factors in biological networks away from the genes themselves and toward their interactions. The observed regulatory changes between subtypes suggest therapeutic interventions that may help in the treatment of ovarian cancer.

Background: The HHIP gene, encoding Hedgehog interacting protein, has been implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS), and our subsequent studies identified a functional upstream genetic variant that decreased HHIP transcription. However, little is known about how HHIP contributes to COPD pathogenesis., Methods: We exposed Hhip haploinsufficient mice (Hhip (+/-) ) to cigarette smoke (CS) for 6 months to model the biological consequences caused by CS in human COPD risk-allele carriers at the HHIP locus. Gene expression profiling in murine lungs was performed followed by an integrative network inference analysis, PANDA (Passing Attributes between Networks for Data Assimilation) analysis., Results: We detected more severe airspace enlargement in Hhip (+/-) mice vs. wild-type littermates (Hhip (+/+) ) exposed to CS. Gene expression profiling in murine lungs suggested enhanced lymphocyte activation pathways in CS-exposed Hhip (+/-) vs. Hhip (+/+) mice, which was supported by increased numbers of lymphoid aggregates and enhanced activation of CD8+ T cells after CS-exposure in the lungs of Hhip (+/-) mice compared to Hhip (+/+) mice. Mechanistically, results from PANDA network analysis suggested a rewired and dampened Klf4 signaling network in Hhip (+/-) mice after CS exposure., Conclusions: In summary, HHIP haploinsufficiency exaggerated CS-induced airspace enlargement, which models CS-induced emphysema in human smokers carrying COPD risk alleles at the HHIP locus. Network modeling suggested rewired lymphocyte activation signaling circuits in the HHIP haploinsufficiency state.

Polycomb repressive complex 2 (PRC2) plays crucial roles in transcriptional regulation and stem cell development. However, the context-specific functions associated with alternative subunits remain largely unexplored. Here we show that the related enzymatic subunits EZH1 and EZH2 undergo an expression switch during blood cell development. An erythroid-specific enhancer mediates transcriptional activation of EZH1, and a switch from GATA2 to GATA1 controls the developmental EZH1/2 switch by differential association with EZH1 enhancers. We further examine the in vivo stoichiometry of the PRC2 complexes by quantitative proteomics and reveal the existence of an EZH1-SUZ12 subcomplex lacking EED. EZH1 together with SUZ12 form a non-canonical PRC2 complex, occupy active chromatin, and positively regulate gene expression. Loss of EZH2 expression leads to repositioning of EZH1 to EZH2 targets. Thus, the lineage- and developmental stage-specific regulation of PRC2 subunit composition leads to a switch from canonical silencing to non-canonical functions during blood stem cell specification., (Copyright © 2015 Elsevier Inc. All rights reserved.)

We present single-cell clustering using bifurcation analysis (SCUBA), a novel computational method for extracting lineage relationships from single-cell gene expression data and modeling the dynamic changes associated with cell differentiation. SCUBA draws techniques from nonlinear dynamics and stochastic differential equation theories, providing a systematic framework for modeling complex processes involving multilineage specifications. By applying SCUBA to analyze two complementary, publicly available datasets we successfully reconstructed the cellular hierarchy during early development of mouse embryos, modeled the dynamic changes in gene expression patterns, and predicted the effects of perturbing key transcriptional regulators on inducing lineage biases. The results were robust with respect to experimental platform differences between RT-PCR and RNA sequencing. We selectively tested our predictions in Nanog mutants and found good agreement between SCUBA predictions and the experimental data. We further extended the utility of SCUBA by developing a method to reconstruct missing temporal-order information from a typical single-cell dataset. Analysis of a hematopoietic dataset suggests that our method is effective for reconstructing gene expression dynamics during human B-cell development. In summary, SCUBA provides a useful single-cell data analysis tool that is well-suited for the investigation of developmental processes.

Background: A fundamental challenge for cancer therapy is that each tumor contains a highly heterogeneous cell population whose structure and mechanistic underpinnings remain incompletely understood. Recent advances in single-cell gene expression profiling have created new possibilities to characterize this heterogeneity and to dissect the potential intra-cancer cellular hierarchy., Results: Here, we apply single-cell analysis to systematically characterize the heterogeneity within leukemic cells using the MLL-AF9 driven mouse model of acute myeloid leukemia. We start with fluorescence-activated cell sorting analysis with seven surface markers, and extend by using a multiplexing quantitative polymerase chain reaction approach to assay the transcriptional profile of a panel of 175 carefully selected genes in leukemic cells at the single-cell level. By employing a set of computational tools we find striking heterogeneity within leukemic cells. Mapping to the normal hematopoietic cellular hierarchy identifies two distinct subtypes of leukemic cells; one similar to granulocyte/monocyte progenitors and the other to macrophage and dendritic cells. Further functional experiments suggest that these subtypes differ in proliferation rates and clonal phenotypes. Finally, co-expression network analysis reveals similarities as well as organizational differences between leukemia and normal granulocyte/monocyte progenitor networks., Conclusions: Overall, our single-cell analysis pinpoints previously uncharacterized heterogeneity within leukemic cells and provides new insights into the molecular signatures of acute myeloid leukemia.

Background: There is growing evidence that many diseases develop, progress, and respond to therapy differently in men and women. This variability may manifest as a result of sex-specific structures in gene regulatory networks that influence how those networks operate. However, there are few methods to identify and characterize differences in network structure, slowing progress in understanding mechanisms driving sexual dimorphism., Results: Here we apply an integrative network inference method, PANDA (Passing Attributes between Networks for Data Assimilation), to model sex-specific networks in blood and sputum samples from subjects with Chronic Obstructive Pulmonary Disease (COPD). We used a jack-knifing approach to build an ensemble of likely networks for each sex. By adapting statistical methods to compare these network ensembles, we were able to identify strong differential-targeting patterns associated with functionally-related sets of genes, including those involved in mitochondrial function and energy metabolism. Network analysis also identified several potential sex- and disease-specific transcriptional regulators of these pathways., Conclusions: Network analysis yielded insight into potential mechanisms driving sexual dimorphism in COPD that were not evident from gene expression analysis alone. We believe our ensemble approach to network analysis provides a principled way to capture sex-specific regulatory relationships and could be applied to identify differences in gene regulatory patterns in a wide variety of diseases and contexts.

The MYC oncoproteins are thought to stimulate tumor cell growth and proliferation through amplification of gene transcription, a mechanism that has thwarted most efforts to inhibit MYC function as potential cancer therapy. Using a covalent inhibitor of cyclin-dependent kinase 7 (CDK7) to disrupt the transcription of amplified MYCN in neuroblastoma cells, we demonstrate downregulation of the oncoprotein with consequent massive suppression of MYCN-driven global transcriptional amplification. This response translated to significant tumor regression in a mouse model of high-risk neuroblastoma, without the introduction of systemic toxicity. The striking treatment selectivity of MYCN-overexpressing cells correlated with preferential downregulation of super-enhancer-associated genes, including MYCN and other known oncogenic drivers in neuroblastoma. These results indicate that CDK7 inhibition, by selectively targeting the mechanisms that promote global transcriptional amplification in tumor cells, may be useful therapy for cancers that are driven by MYC family oncoproteins.

Background: Long noncoding RNAs (lncRNAs) have recently been implicated in many biological processes and diseases. Atherosclerosis is a major risk factor for cardiovascular disease. However, the functional role of lncRNAs in atherosclerosis is largely unknown., Methods and Results: We identified lincRNA-p21 as a key regulator of cell proliferation and apoptosis during atherosclerosis. The expression of lincRNA-p21 was dramatically downregulated in atherosclerotic plaques of ApoE(-/-) mice, an animal model for atherosclerosis. Through loss- and gain-of-function approaches, we showed that lincRNA-p21 represses cell proliferation and induces apoptosis in vascular smooth muscle cells and mouse mononuclear macrophage cells in vitro. Moreover, we found that inhibition of lincRNA-p21 results in neointimal hyperplasia in vivo in a carotid artery injury model. Genome-wide analysis revealed that lincRNA-p21 inhibition dysregulated many p53 targets. Furthermore, lincRNA-p21, a transcriptional target of p53, feeds back to enhance p53 transcriptional activity, at least in part, via binding to mouse double minute 2 (MDM2), an E3 ubiquitin-protein ligase. The association of lincRNA-p21 and MDM2 releases MDM2 repression of p53, enabling p53 to interact with p300 and to bind to the promoters/enhancers of its target genes. Finally, we show that lincRNA-p21 expression is decreased in patients with coronary artery disease., Conclusions: Our studies identify lincRNA-p21 as a novel regulator of cell proliferation and apoptosis and suggest that this lncRNA could serve as a therapeutic target to treat atherosclerosis and related cardiovascular disorders., (© 2014 American Heart Association, Inc.)

Epigenetic mechanisms play an important role in the regulation of cell type-specific gene activities, yet how epigenetic patterns are established and maintained remains poorly understood. Recent studies have supported a role of DNA sequences in recruitment of epigenetic regulators. Alignment-free methods have been applied to identify distinct sequence features that are associated with epigenetic patterns and to predict epigenomic profiles. Here, we review recent advances in such applications, including the methods to map DNA sequence to feature space, sequence comparison and prediction models. Computational studies using these methods have provided important insights into the epigenetic regulatory mechanisms.

Hematopoietic stem cells (HSCs) sustain blood formation throughout life and are the functional units of bone marrow transplantation. We show that transient expression of six transcription factors Run1t1, Hlf, Lmo2, Prdm5, Pbx1, and Zfp37 imparts multilineage transplantation potential onto otherwise committed lymphoid and myeloid progenitors and myeloid effector cells. Inclusion of Mycn and Meis1 and use of polycistronic viruses increase reprogramming efficacy. The reprogrammed cells, designated induced-HSCs (iHSCs), possess clonal multilineage differentiation potential, reconstitute stem/progenitor compartments, and are serially transplantable. Single-cell analysis revealed that iHSCs derived under optimal conditions exhibit a gene expression profile that is highly similar to endogenous HSCs. These findings demonstrate that expression of a set of defined factors is sufficient to activate the gene networks governing HSC functional identity in committed blood cells. Our results raise the prospect that blood cell reprogramming may be a strategy for derivation of transplantable stem cells for clinical application., (Copyright © 2014 Elsevier Inc. All rights reserved.)

The luminescence spectra of InGaN/GaN multiple quantum wells light-emitting diodes under low level injection current (<4 mA) during aging process was investigated for the first time. Comparing the electroluminescence (EL) spectra of LEDs before and after aging time it was found that the peak wavelength and the full width at half maximum (FWHM) decreased with stress time and the changes of EL spectrum had two different stages-drastic decrease at the early stress stage and slow decrease later showing the same trend with the output optical power of LEDs, which indicates that the effective polarization electric field of LEDs becomes weak during the aging process and the change has a clear correlation with the increase of the defects in the multiple quantum wells of LEDs. Electrical measurement revealed that junction capacitance (C(j)) under the same junction voltage (V(j) = 1.8 V) and the junction voltage (V(j)) with the same injection current 1 mA calculated by ac small-signal IV method increased along with aging time, which explicates that the carrier density under the same low injection increases as the aging time increases. Analyses indicate that the polarization field in the quantum well is more seriously screened by the increased carriers captured by defects activated during stress time, the weaker effective polarization electric field makes the tilt of the energy band smaller, the energy radiated through the band edge and the density of energy states of the band edge increase which leads to the behaviors of peak wavelength and the FWHM of InGaN/GaN multiple quantum wells LEDs under low level injection current.

Chromatin states are highly cell-type-specific, but the underlying mechanisms for the establishment and maintenance of their genome-wide patterns remain poorly understood. Here we present a computational approach for investigation of chromatin-state plasticity. We applied this approach to investigate an ENCODE ChIP-seq dataset profiling the genome-wide distributions of the H3K27me3 mark in 19 human cell lines. We found that the high plasticity regions (HPRs) can be divided into two functionally and mechanistically distinct subsets, which correspond to CpG island (CGI) proximal or distal regions, respectively. Although the CGI proximal HPRs are typically associated with continuous variation across different cell-types, the distal HPRs are associated with binary-like variations. We developed a computational approach to predict putative cell-type-specific modulators of H3K27me3 patterns and validated the predictions by comparing with public ChIP-seq data. Furthermore, we applied this approach to investigate mechanisms for poised enhancer establishment in primary human erythroid precursors. Importantly, we predicted and experimentally validated that the principal hematopoietic regulator T-cell acute lymphocytic leukemia-1 (TAL1) is involved in regulating H3K27me3 variations in collaboration with the transcription factor growth factor independent 1B (GFI1B), providing fresh insights into the context-specific role of TAL1 in erythropoiesis. Our approach is generally applicable to investigate the regulatory mechanisms of epigenetic pathways in establishing cellular identity.

Self-renewal and pluripotency of embryonic stem cells (ESCs) are established by multiple regulatory pathways operating at several levels. The roles of histone demethylases (HDMs) in these programs are incompletely defined. We conducted a functional RNAi screen for HDMs and identified five potential HDMs essential for mouse ESC identity. In-depth analyses demonstrate that the closely related HDMs Jmjd2b and Jmjd2c are necessary for self-renewal of ESCs and induced pluripotent stem cell generation. Genome-wide occupancy studies reveal that Jmjd2b unique, Jmjd2c unique, and Jmjd2b-Jmjd2c common target sites belong to functionally separable Core, Polycomb repressive complex (PRC), and Myc regulatory modules, respectively. Jmjd2b and Nanog act through an interconnected regulatory loop, whereas Jmjd2c assists PRC2 in transcriptional repression. Thus, two HDMs of the same subclass exhibit distinct and combinatorial functions in control of the ESC state. Such complexity of HDM function reveals an aspect of multilayered transcriptional control., (Copyright © 2014 Elsevier Inc. All rights reserved.)

In mammals, numerous autosomal genes are subject to mitotically stable monoallelic expression (MAE), including genes that play critical roles in a variety of human diseases. Due to challenges posed by the clonal nature of MAE, very little is known about its regulation; in particular, no molecular features have been specifically linked to MAE. In this study, we report an approach that distinguishes MAE genes in human cells with great accuracy: a chromatin signature consisting of chromatin marks associated with active transcription (H3K36me3) and silencing (H3K27me3) simultaneously occurring in the gene body. The MAE signature is present in ∼20% of ubiquitously expressed genes and over 30% of tissue-specific genes across cell types. Notably, it is enriched among key developmental genes that have bivalent chromatin structure in pluripotent cells. Our results open a new approach to the study of MAE that is independent of polymorphisms, and suggest that MAE is linked to cell differentiation. DOI: http://dx.doi.org/10.7554/eLife.01256.001.

Enhancers are cis-acting elements capable of regulating transcription in a distance and orientation-independent manner. A subset of enhancers are occupied by RNA polymerase II (RNAP II) and transcribed to produce long non-coding RNAs termed eRNAs. We thoroughly investigated the association between eRNA productivity and various chromatin marks and transcriptional regulators in mouse embryonic stem cells (ESCs) through an integrative approach. We found that eRNA-producing enhancers exhibited elevated levels of the active mark H3K27Ac, decreased DNA methylation, and enrichment for the DNA hydroxylase Tet1. Many eRNA-producing enhancers have recently been characterized as "super-enhancers," suggesting an important role in the maintenance of pluripotency. Using experimental methods, we focally investigated a well-characterized enhancer linked to the Nanog locus and confirmed its exclusive eRNA productivity in ESCs. We further demonstrate that the binding of Sall4 and Tet family proteins were required for eRNA productivity at this locus. Collectively, we demonstrate that Tet1 binding and DNA hypomethylation are hallmarks of eRNA production.

Epigenetic modifications to histones may promote either activation or repression of the transcription of nearby genes. Recent experimental studies show that the promoters of many lineage-control genes in stem cells have "bivalent domains" in which the nucleosomes contain both active (H3K4me3) and repressive (H3K27me3) marks. It is generally agreed that bivalent domains play an important role in stem cell differentiation, but the underlying mechanisms remain unclear. Here we formulate a mathematical model to investigate the dynamic properties of histone modification patterns. We then illustrate that our modeling framework can be used to capture key features of experimentally observed combinatorial chromatin states.

Genome-wide association studies (GWASs) have ascertained numerous trait-associated common genetic variants, frequently localized to regulatory DNA. We found that common genetic variation at BCL11A associated with fetal hemoglobin (HbF) level lies in noncoding sequences decorated by an erythroid enhancer chromatin signature. Fine-mapping uncovers a motif-disrupting common variant associated with reduced transcription factor (TF) binding, modestly diminished BCL11A expression, and elevated HbF. The surrounding sequences function in vivo as a developmental stage-specific, lineage-restricted enhancer. Genome engineering reveals the enhancer is required in erythroid but not B-lymphoid cells for BCL11A expression. These findings illustrate how GWASs may expose functional variants of modest impact within causal elements essential for appropriate gene expression. We propose the GWAS-marked BCL11A enhancer represents an attractive target for therapeutic genome engineering for the β-hemoglobinopathies.

Stem cell differentiation pathways are most often studied at the population level, whereas critical decisions are executed at the level of single cells. We have established a highly multiplexed, quantitative PCR assay to profile in an unbiased manner a panel of all commonly used cell surface markers (280 genes) from individual cells. With this method, we analyzed over 1,500 single cells throughout the mouse hematopoietic system and illustrate its utility for revealing important biological insights. The comprehensive single cell data set permits mapping of the mouse hematopoietic stem cell differentiation hierarchy by computational lineage progression analysis. Further profiling of 180 intracellular regulators enabled construction of a genetic network to assign the earliest differentiation event during hematopoietic lineage specification. Analysis of acute myeloid leukemia elicited by MLL-AF9 uncovered a distinct cellular hierarchy containing two independent self-renewing lineages with different clonal activities. The strategy has broad applicability in other cellular systems., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Inappropriate activation of the transcription factors STAT3 and STAT5 has been shown to drive cancer pathogenesis through dysregulation of genes involved in cell survival, growth, and differentiation. Although STAT3 and STAT5 are structurally related, they can have opposite effects on key genes, including BCL6. BCL6, a transcriptional repressor, has been shown to be oncogenic in diffuse large B cell lymphoma. BCL6 also plays an important role in breast cancer pathogenesis, a disease in which STAT3 and STAT5 can be activated individually or concomitantly. To determine the mechanism by which these oncogenic transcription factors regulate BCL6 transcription, we analyzed their effects at the levels of chromatin and gene expression. We found that STAT3 increases expression of BCL6 and enhances recruitment of RNA polymerase II phosphorylated at a site associated with transcriptional initiation. STAT5, in contrast, represses BCL6 expression below basal levels and decreases the association of RNA polymerase II at the gene. Furthermore, the repression mediated by STAT5 is dominant over STAT3-mediated induction. STAT5 exerts this effect by displacing STAT3 from one of the two regulatory regions to which it binds. These findings may underlie the divergent biology of breast cancers containing activated STAT3 alone or in conjunction with activated STAT5.

Precise characterization of chromatin states is an important but difficult task for understanding the regulatory role of chromatin. A number of computational methods have been developed with varying levels of success. However, a remaining challenge is to model epigenomic patterns over multi-scales, as each histone mark is distributed with its own characteristic length scale. We developed a tiered hidden Markov model and applied it to analyze a ChIP-seq dataset in human embryonic stem cells. We identified a two-tier structure containing 15 distinct bin-level chromatin states grouped into three domain-level states. Whereas the bin-level states capture the local variation of histone marks, the domain-level states detect large-scale variations. Compared to bin-level states, the domain-level states are more robust and coherent. We also found active regions in intergenic regions that upon closer examination were expressed non-coding RNAs and pseudogenes. These results provide insights into an additional layer of complexity in chromatin organization., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net.

Distinguishing aggressive from indolent disease and developing effective therapy for advanced disease are the major challenges in prostate cancer research. Chromosomal rearrangements involving ETS transcription factors, such as ERG and ETV1, occur frequently in prostate cancer. How they contribute to tumorigenesis and whether they play similar or distinct in vivo roles remain elusive. Here we show that in mice with ERG or ETV1 targeted to the endogenous Tmprss2 locus, either factor cooperated with loss of a single copy of Pten, leading to localized cancer, but only ETV1 appeared to support development of invasive adenocarcinoma under the background of full Pten loss. Mechanistic studies demonstrated that ERG and ETV1 control a common transcriptional network but largely in an opposing fashion. In particular, while ERG negatively regulates the androgen receptor (AR) transcriptional program, ETV1 cooperates with AR signaling by favoring activation of the AR transcriptional program. Furthermore, we found that ETV1 expression, but not that of ERG, promotes autonomous testosterone production. Last, we confirmed the association of an ETV1 expression signature with aggressive disease and poorer outcome in patient data. The distinct biology of ETV1-associated prostate cancer suggests that this disease class may require new therapies directed to underlying programs controlled by ETV1.

Gene-distal enhancers are critical for tissue-specific gene expression, but their genomic determinants within a specific lineage at different stages of development are unknown. Here we profile chromatin state maps, transcription factor occupancy, and gene expression profiles during human erythroid development at fetal and adult stages. Comparative analyses of human erythropoiesis identify developmental stage-specific enhancers as primary determinants of stage-specific gene expression programs. We find that erythroid master regulators GATA1 and TAL1 act cooperatively within active enhancers but confer little predictive value for stage specificity. Instead, a set of stage-specific coregulators collaborates with master regulators and contributes to differential gene expression. We further identify and validate IRF2, IRF6, and MYB as effectors of an adult-stage expression program. Thus, the combinatorial assembly of lineage-specific master regulators and transcriptional coregulators within developmental stage-specific enhancers determines gene expression programs and temporal regulation of transcriptional networks in a mammalian genome., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Recent epigenomic studies have identified significant differences between developmental stages and cell types. While the importance of epigenetic regulation has been increasingly recognized, it remains unclear how the global epigenetic patterns are established and maintained. Here I review a number of recent studies with the emphasis on the role of the genomic sequence in shaping the epigenetic landscape. These studies strongly suggest that the sequence information is important not just for controlling target specificity but for orchestrating the diversity of epigenetic patterns among different cell types. The epigenome is maintained by the complex network of a large number of interactions. Integrative approaches are needed to gain insights into these networks., (Copyright © 2012 Wiley Periodicals, Inc.)

ChIP-Seq is widely used to characterize genome-wide binding patterns of transcription factors and other chromatin-associated proteins. Although comparison of ChIP-Seq data sets is critical for understanding cell type-dependent and cell state-specific binding, and thus the study of cell-specific gene regulation, few quantitative approaches have been developed. Here, we present a simple and effective method, MAnorm, for quantitative comparison of ChIP-Seq data sets describing transcription factor binding sites and epigenetic modifications. The quantitative binding differences inferred by MAnorm showed strong correlation with both the changes in expression of target genes and the binding of cell type-specific regulators.

Gene expression is controlled by the concerted interactions between transcription factors and chromatin regulators. While recent studies have identified global chromatin state changes across cell-types, it remains unclear to what extent these changes are co-regulated during cell-differentiation. Here we present a comprehensive computational analysis by assembling a large dataset containing genome-wide occupancy information of 5 histone modifications in 27 human cell lines (including 24 normal and 3 cancer cell lines) obtained from the public domain, followed by independent analysis at three different representations. We classified the differentiation stage of a cell-type based on its genome-wide pattern of chromatin states, and found that our method was able to identify normal cell lines with nearly 100% accuracy. We then applied our model to classify the cancer cell lines and found that each can be unequivocally classified as differentiated cells. The differences can be in part explained by the differential activities of three regulatory modules associated with embryonic stem cells. We also found that the "hotspot" genes, whose chromatin states change dynamically in accordance to the differentiation stage, are not randomly distributed across the genome but tend to be embedded in multi-gene chromatin domains, and that specialized gene clusters tend to be embedded in stably occupied domains.

Background: Genome-wide mapping of protein-DNA interactions has been widely used to investigate biological functions of the genome. An important question is to what extent such interactions are regulated at the DNA sequence level. However, current investigation is hampered by the lack of computational methods for systematic evaluating sequence specificity., Results: We present a simple, unbiased quantitative measure for DNA sequence specificity called the Motif Independent Measure (MIM). By analyzing both simulated and real experimental data, we found that the MIM measure can be used to detect sequence specificity independent of presence of transcription factor (TF) binding motifs. We also found that the level of specificity associated with H3K4me1 target sequences is highly cell-type specific and highest in embryonic stem (ES) cells. We predicted H3K4me1 target sequences by using the N- score model and found that the prediction accuracy is indeed high in ES cells.The software to compute the MIM is freely available at: https://github.com/lucapinello/mim., Conclusions: Our method provides a unified framework for quantifying DNA sequence specificity and serves as a guide for development of sequence-based prediction models.

Chromatin-modifying enzymes play a fundamental role in regulating chromatin structure so that DNA replication is spatially and temporally coordinated. For example, the lysine demethylase 4A/Jumonji domain-containing 2A (KDM4A/JMJD2A) is tightly regulated during the cell cycle. Overexpression of JMJD2A leads to altered replication timing and faster S phase progression. In this study, we demonstrate that degradation of JMJD2A is regulated by the proteasome. JMJD2A turnover is coordinated through the SKP1-Cul1-F-box ubiquitin ligase complex that contains cullin 1 and the F-box and leucine-rich repeat protein 4 (FbxL4). This complex interacted with JMJD2A. Ubiquitin overexpression restored turnover and blocked the JMJD2A-dependent faster S phase progression in a cullin 1-dependent manner. Furthermore, increased ubiquitin levels decreased JMJD2A occupancy and BrdU incorporation at target sites. This study highlights a finely tuned mechanism for regulating histone demethylase levels and emphasizes the need to tightly regulate chromatin modifiers so that the cell cycle occurs properly.

Background: Epigenetics is an important layer of transcriptional control necessary for cell-type specific gene regulation. Recent studies have shown significant epigenetic patterns associated with developmental stages and diseases. However, previous studies have been mostly limited to focal epigenetic patterns, whereas methods for analyzing large-scale organizations are still lacking., Results: We developed a hidden Markov model (HMM) approach for detecting the types and locations of epigenetic domains from multiple histone modifications. We used this method to analyze a published ChIP-seq dataset of five histone modification marks (H3K4me2, H3K4me3, H3K27me3, H3K9me3, and H3K36me3) in mouse embryonic stem (ES) cells. We identified three types of domains, corresponding to active, non-active, and null states. In total, our three-state HMM identified 258 domains in the mouse genome containing 9.6 genes on average. These domains were validated by a number of criteria. The largest domains correspond to olfactory receptor (OR) gene clusters. Each Hox gene cluster also forms a separate epigenetic domain. We found that each type of domain is associated with distinct biological functions and structural changes during early cell differentiation., Conclusions: The HMM approach successfully detects domains of consistent epigenetic patterns from ChIP-seq data, providing new insights into the role of epigenetics in long-range gene regulation.