Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells

7SK-BAF axis controls pervasive transcription at enhancers

RNA functions at enhancers remain mysterious. Here we show that the 7SK small nuclear RNA (snRNA) inhibits enhancer transcription by modulating nucleosome position. 7SK occupies enhancers and super enhancers genome-wide in mouse and human cells, and 7SK is required to limit eRNA initiation and synthesis in a manner distinct from promoter pausing. Clustered elements at super enhancers uniquely require 7SK to prevent convergent transcription and DNA damage signaling. 7SK physically interacts with the BAF chromatin remodeling complex, recruit BAF to enhancers, and inhibits enhancer transcription by modulating chromatin structure. In turn, 7SK occupancy at enhancers coincides with Brd4 and is exquisitely sensitive to the bromodomain inhibitor JQ1. Thus, 7SK employs distinct mechanisms to counteract diverse consequences of pervasive transcription that distinguish super enhancers, enhancers, and promoters.

Pioneer transcription factors, chromatin dynamics, and cell fate control

Among the diverse transcription factors that are necessary to elicit changes in cell fate, both in embryonic development and in cellular reprogramming, a subset of factors are capable of binding to their target sequences on nucleosomal DNA and initiating regulatory events in silent chromatin. Such 'pioneer transcription factors' initiate cooperative interactions with other regulatory proteins to elicit changes in local chromatin structure. As a consequence of pioneer factor binding, the local chromatin can either become open and competent for activation, closed and repressed, or transcriptionally active. Understanding how pioneer factors initiate chromatin dynamics and how such can be blocked at heterochromatic sites provides insights into controlling cell fate transitions at will.

Polycomb inhibits histone acetylation by CBP by binding directly to its catalytic domain

Drosophila Polycomb (PC), a subunit of Polycomb repressive complex 1 (PRC1), is well known for its role in maintaining repression of the homeotic genes and many others and for its binding to trimethylated histone H3 on Lys 27 (H3K27me3) via its chromodomain. Here, we identify a novel activity of PC: inhibition of the histone acetylation activity of CREB-binding protein (CBP). We show that PC and its mammalian CBX orthologs interact directly with the histone acetyltransferase (HAT) domain of CBP, binding to the previously identified autoregulatory loop, whose autoacetylation greatly enhances HAT activity. We identify a conserved PC motif adjacent to the chromodomain required for CBP binding and show that PC binding inhibits acetylation of histone H3. CBP autoacetylation impairs PC binding in vitro, and PC is preferentially associated with unacetylated CBP in vivo. PC knockdown elevates the acetylated H3K27 (H3K27ac) level globally and at promoter regions of some genes that are bound by both PC and CBP. Conversely, PC overexpression decreases the H3K27ac level in vivo and also suppresses CBP-dependent Polycomb phenotypes caused by overexpression of Trithorax, an antagonist of Polycomb silencing. We find that PC is physically associated with the initiating form of RNA polymerase II (Pol II) and that many promoters co-occupied by PC and CBP are associated with paused Pol II, suggesting that PC may play a role in Pol II pausing. These results suggest that PC/PRC1 inhibition of CBP HAT activity plays a role in regulating transcription of both repressed and active PC-regulated genes.

Genomic Views of Transcriptional Enhancers: Essential Determinants of Cellular Identity and Activity-Dependent Responses in the CNS

Sprinkled throughout the genome are a million regulatory sequences called transcriptional enhancers that activate gene promoters in the right cells, at the right time. Enhancers endow the brain with its incredible diversity of cell types and also translate neural activity into gene induction. Thanks to rapid advances in genomic technologies, it is now possible to identify thousands of enhancers rapidly, test their transcriptional function en masse, and address their neurobiological functions via genome editing. Enhancers also promise to be a great technological opportunity for neuroscience, offering the potential for cell-type-specific genetic labeling and manipulation without the need for transgenesis. The objective of this review and the accompanying 2015 SfN mini-symposium is to highlight the use of new and emerging genomic technologies to probe enhancer function in the nervous system.

SIGNIFICANCE STATEMENT

Transcriptional enhancers turn on genes in the right cells, at the right time. Enhancers are also the genomic sequences that encode the incredible diversity of cell types in the brain and enable the brain to turn genes on in response to new experiences. New technology enables enhancers to be found and manipulated. The study of enhancers promises to inform our understanding of brain development and function. The application of enhancer technology holds promise in accelerating basic neuroscience research and enabling gene therapies to be targeted to specific cell types in the brain.

[Epigenetic regulations and cerebral plasticity: towards new therapeutic options in neurodegenerative diseases?]

Although revealed in the 1950's, epigenetics is still a fast-growing field. Its delineations continuously evolve and become clarified. In particular, "neuroepigenetics", a notion that encompasses epigenetic regulations associated with neuronal processes, appears very promising. Indeed, the challenge to be undertaken in this sub-field is double. On the one hand, it should bring molecular comprehension of specific neuronal processes, some of them falling within the long term regulations, such as learning and memory. On the other hand, it could bring therapeutic options for brain diseases, e.g. neurodegenerative diseases such as Alzheimer's or Huntington's diseases.

Non-coding RNAs: Classification, Biology and Functioning

One of the long-standing principles of molecular biology is that DNA acts as a template for transcription of messenger RNAs, which serve as blueprints for protein translation. A rapidly growing number of exceptions to this rule have been reported over the past decades: they include long known classes of RNAs involved in translation such as transfer RNAs and ribosomal RNAs, small nuclear RNAs involved in splicing events, and small nucleolar RNAs mainly involved in the modification of other small RNAs, such as ribosomal RNAs and transfer RNAs. More recently, several classes of short regulatory non-coding RNAs, including piwi-associated RNAs, endogenous short-interfering RNAs and microRNAs have been discovered in mammals, which act as key regulators of gene expression in many different cellular pathways and systems. Additionally, the human genome encodes several thousand long non-protein coding RNAs >200 nucleotides in length, some of which play crucial roles in a variety of biological processes such as epigenetic control of chromatin, promoter-specific gene regulation, mRNA stability, X-chromosome inactivation and imprinting. In this chapter, we will introduce several classes of short and long non-coding RNAs, describe their diverse roles in mammalian gene regulation and give examples for known modes of action.

Epigenomic Landscape of Human Fetal Brain, Heart, and Liver

The epigenetic regulation of spatiotemporal gene expression is crucial for human development. Here, we present whole-genome chromatin immunoprecipitation followed by high throughput DNA sequencing (ChIP-seq) analyses of a wide variety of histone markers in the brain, heart, and liver of early human embryos shortly after their formation. We identified 40,181 active enhancers, with a large portion showing tissue-specific and developmental stage-specific patterns, pointing to their roles in controlling the ordered spatiotemporal expression of the developmental genes in early human embryos. Moreover, using sequential ChIP-seq, we showed that all three organs have hundreds to thousands of bivalent domains that are marked by both H3K4me3 and H3K27me3, probably to keep the progenitor cells in these organs ready for immediate differentiation into diverse cell types during subsequent developmental processes. Our work illustrates the potentially critical roles of tissue-specific and developmental stage-specific epigenomes in regulating the spatiotemporal expression of developmental genes during early human embryonic development.

Application of Gene Expression Trajectories Initiated from ErbB Receptor Activation Highlights the Dynamics of Divergent Promoter Usage

Understanding how cells use complex transcriptional programs to alter their fate in response to specific stimuli is an important question in biology. For the MCF-7 human breast cancer cell line, we applied gene expression trajectory models to identify the genes involved in driving cell fate transitions. We modified trajectory models to account for the scenario where cells were exposed to different stimuli, in this case epidermal growth factor and heregulin, to arrive at different cell fates, i.e. proliferation and differentiation respectively. Using genome-wide CAGE time series data collected from the FANTOM5 consortium, we identified the sets of promoters that were involved in the transition of MCF-7 cells to their specific fates versus those with expression changes that were generic to both stimuli. Of the 1,552 promoters identified, 1,091 had stimulus-specific expression while 461 promoters had generic expression profiles over the time course surveyed. Many of these stimulus-specific promoters mapped to key regulators of the ERK (extracellular signal-regulated kinases) signaling pathway such as FHL2 (four and a half LIM domains 2). We observed that in general, generic promoters peaked in their expression early on in the time course, while stimulus-specific promoters tended to show activation of their expression at a later stage. The genes that mapped to stimulus-specific promoters were enriched for pathways that control focal adhesion, p53 signaling and MAPK signaling while generic promoters were enriched for cell death, transcription and the cell cycle. We identified 162 genes that were controlled by an alternative promoter during the time course where a subset of 37 genes had separate promoters that were classified as stimulus-specific and generic. The results of our study highlighted the degree of complexity involved in regulating a cell fate transition where multiple promoters mapping to the same gene can demonstrate quite divergent expression profiles.

Progress and challenges in bioinformatics approaches for enhancer identification

Enhancers are cis-acting DNA elements that play critical roles in distal regulation of gene expression. Identifying enhancers is an important step for understanding distinct gene expression programs that may reflect normal and pathogenic cellular conditions. Experimental identification of enhancers is constrained by the set of conditions used in the experiment. This requires multiple experiments to identify enhancers, as they can be active under specific cellular conditions but not in different cell types/tissues or cellular states. This has opened prospects for computational prediction methods that can be used for high-throughput identification of putative enhancers to complement experimental approaches. Potential functions and properties of predicted enhancers have been catalogued and summarized in several enhancer-oriented databases. Because the current methods for the computational prediction of enhancers produce significantly different enhancer predictions, it will be beneficial for the research community to have an overview of the strategies and solutions developed in this field. In this review, we focus on the identification and analysis of enhancers by bioinformatics approaches. First, we describe a general framework for computational identification of enhancers, present relevant data types and discuss possible computational solutions. Next, we cover over 30 existing computational enhancer identification methods that were developed since 2000. Our review highlights advantages, limitations and potentials, while suggesting pragmatic guidelines for development of more efficient computational enhancer prediction methods. Finally, we discuss challenges and open problems of this topic, which require further consideration.

CSF1 Restores Innate Immunity After Liver Injury in Mice and Serum Levels Indicate Outcomes of Patients With Acute Liver Failure

BACKGROUND & AIMS

Liver regeneration requires functional liver macrophages, which provide an immune barrier that is compromised after liver injury. The numbers of liver macrophages are controlled by macrophage colony-stimulating factor (CSF1). We examined the prognostic significance of the serum level of CSF1 in patients with acute liver injury and studied its effects in mice.

METHODS

We measured levels of CSF1 in serum samples collected from 55 patients who underwent partial hepatectomy at the Royal Infirmary Edinburgh between December 2012 and October 2013, as well as from 78 patients with acetaminophen-induced acute liver failure admitted to the Royal Infirmary Edinburgh or the University of Kansas Medical Centre. We studied the effects of increased levels of CSF1 in uninjured mice that express wild-type CSF1 receptor or a constitutive or inducible CSF1-receptor reporter, as well as in chemokine receptor 2 (Ccr2)-/- mice; we performed fate-tracing experiments using bone marrow chimeras. We administered CSF1-Fc (fragment, crystallizable) to mice after partial hepatectomy and acetaminophen intoxication, and measured regenerative parameters and innate immunity by clearance of fluorescent microbeads and bacterial particles.

RESULTS

Serum levels of CSF1 increased in patients undergoing liver surgery in proportion to the extent of liver resected. In patients with acetaminophen-induced acute liver failure, a low serum level of CSF1 was associated with increased mortality. In mice, administration of CSF1-Fc promoted hepatic macrophage accumulation via proliferation of resident macrophages and recruitment of monocytes. CSF1-Fc also promoted transdifferentiation of infiltrating monocytes into cells with a hepatic macrophage phenotype. CSF1-Fc increased innate immunity in mice after partial hepatectomy or acetaminophen-induced injury, with resident hepatic macrophage as the main effector cells.

CONCLUSIONS

Serum CSF1 appears to be a prognostic marker for patients with acute liver injury. CSF1 might be developed as a therapeutic agent to restore innate immune function after liver injury.

Architectural and Functional Commonalities between Enhancers and Promoters

With the explosion of genome-wide studies of regulated transcription, it has become clear that traditional definitions of enhancers and promoters need to be revisited. These control elements can now be characterized in terms of their local and regional architecture, their regulatory components, including histone modifications and associated binding factors, and their functional contribution to transcription. This Review discusses unifying themes between promoters and enhancers in transcriptional regulatory mechanisms.

Stimulus-specific combinatorial functionality of neuronal c-fos enhancers

The c-fos gene is induced by a broad range of stimuli, and has been commonly used as a reliable marker for neural activity. Its induction mechanism and available reporter mouse lines are exclusively based on the c-fos promoter activity. Here, we demonstrate that multiple enhancers surrounding the c-fos gene are critical for ensuring robust c-fos response to various stimuli. Membrane depolarization, brain-derived neurotrophic factor (BDNF), and Forskolin activate distinct subsets of the enhancers to induce c-fos transcription in neurons, suggesting that stimulus-specific combinatorial activation of multiple enhancers underlies the broad inducibility of the c-fos gene. Accordingly, the functional requirement of key transcription factors varies depending on the type of stimulation. Combinatorial enhancer activation also occurs in the brain. Providing a comprehensive picture of the c-fos induction mechanism beyond the minimal promoter, our study should help in understanding the physiological nature of c-fos induction in relation to neural activity and plasticity.

In the loop: promoter-enhancer interactions and bioinformatics

Enhancer-promoter regulation is a fundamental mechanism underlying differential transcriptional regulation. Spatial chromatin organization brings remote enhancers in contact with target promoters in cis to regulate gene expression. There is considerable evidence for promoter-enhancer interactions (PEIs). In the recent years, genome-wide analyses have identified signatures and mapped novel enhancers; however, being able to precisely identify their target gene(s) requires massive biological and bioinformatics efforts. In this review, we give a short overview of the chromatin landscape and transcriptional regulation. We discuss some key concepts and problems related to chromatin interaction detection technologies, and emerging knowledge from genome-wide chromatin interaction data sets. Then, we critically review different types of bioinformatics analysis methods and tools related to representation and visualization of PEI data, raw data processing and PEI prediction. Lastly, we provide specific examples of how PEIs have been used to elucidate a functional role of non-coding single-nucleotide polymorphisms. The topic is at the forefront of epigenetic research, and by highlighting some future bioinformatics challenges in the field, this review provides a comprehensive background for future PEI studies.

Hallmarks of therapeutic management of the cystic fibrosis functional landscape

The cystic fibrosis (CF) transmembrane conductance regulator (CFTR) protein does not operate in isolation, rather in a dynamic network of interacting components that impact its synthesis, folding, stability, intracellular location and function, referred to herein as the 'CFTR Functional Landscape (CFFL)'. For the prominent F508del mutation, many of these interactors are deeply connected to a protein fold management system, the proteostasis network (PN). However, CF encompasses an additional 2000 CFTR variants distributed along its entire coding sequence (referred to as CFTR2), and each variant contributes a differential liability to PN management of CFTR and to a protein 'social network' (SN) that directs the probability of the (patho)physiologic events that impact ion transport in each cell, tissue and patient in health and disease. Recognition of the importance of the PN and SN in driving the unique patient CFFL leading to disease highlights the importance of precision medicine in therapeutic management of disease progression. We take the view herein that it is not CFTR, rather the PN/SN, and their impact on the CFFL, that are the key physiologic forces driving onset and clinical progression of CF. We posit that a deep understanding of each patients PN/SN gained by merging genomic, proteomic (mass spectrometry (MS)), and high-content microscopy (HCM) technologies in the context of novel network learning algorithms will lead to a paradigm shift in CF clinical management. This should allow for generation of new classes of patient specific PN/SN directed therapeutics for personalized management of the CFFL in the clinic.

Long non-coding RNAs in corticogenesis: deciphering the non-coding code of the brain

Evidence on the role of long non-coding (lnc) RNAs has been accumulating over decades, but it has been only recently that advances in sequencing technologies have allowed the field to fully appreciate their abundance and diversity. Despite this, only a handful of lncRNAs have been phenotypically or mechanistically studied. Moreover, novel lncRNAs and new classes of RNAs are being discovered at growing pace, suggesting that this class of molecules may have functions as diverse as protein-coding genes. Interestingly, the brain is the organ where lncRNAs have the most peculiar features including the highest number of lncRNAs that are expressed, proportion of tissue-specific lncRNAs and highest signals of evolutionary conservation. In this work, we critically review the current knowledge about the steps that have led to the identification of the non-coding transcriptome including the general features of lncRNAs in different contexts in terms of both their genomic organisation, evolutionary origin, patterns of expression, and function in the developing and adult mammalian brain.

Detecting shifts in gene regulatory networks during time-course experiments at single-time-point temporal resolution

Comprehensively understanding the dynamics of biological systems is one of the greatest challenges in biology. Vastly improved biological technologies have provided vast amounts of information that must be understood by bioinformatics and systems biology researchers. Gene regulations have been frequently modeled by ordinary differential equations or graphical models based on time-course gene expression profiles. The state-of-the-art computational approaches for analyzing gene regulations assume that their models are same throughout time-course experiments. However, these approaches cannot easily analyze transient changes at a time point, such as diauxic shift. We propose a score that analyzes the gene regulations at each time point. The score is based on the information gains of information criterion values. The method detects the shifts in gene regulatory networks (GRNs) during time-course experiments with single-time-point resolution. The effectiveness of the method is evaluated on the diauxic shift from glucose to lactose in Escherichia coli. Gene regulation shifts were detected at two time points: the first corresponding to the time at which the growth of E. coli ceased and the second corresponding to the end of the experiment, when the nutrient sources (glucose and lactose) had become exhausted. According to these results, the proposed score and method can appropriately detect the time of gene regulation shifts. The method based on the proposed score provides a new tool for analyzing dynamic biological systems. Because the score value indicates the strength of gene regulation at each time point in a gene expression profile, it can potentially infer hidden GRNs from time-course experiments.

Public data and open source tools for multi-assay genomic investigation of disease

Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods.

Paradigm shifts in genomics through the FANTOM projects

Big leaps in science happen when scientists from different backgrounds interact. In the past 15 years, the FANTOM Consortium has brought together scientists from different fields to analyze and interpret genomic data produced with novel technologies, including mouse full-length cDNAs and, more recently, expression profiling at single-nucleotide resolution by cap-analysis gene expression. The FANTOM Consortium has provided the most comprehensive mouse cDNA collection for functional studies and extensive maps of the human and mouse transcriptome comprising promoters, enhancers, as well as the network of their regulatory interactions. More importantly, serendipitous observations of the FANTOM dataset led us to realize that the mammalian genome is pervasively transcribed, even from retrotransposon elements, which were previously considered junk DNA. The majority of products from the mammalian genome are long non-coding RNAs (lncRNAs), including sense-antisense, intergenic, and enhancer RNAs. While the biological function has been elucidated for some lncRNAs, more than 98 % of them remain without a known function. We argue that large-scale studies are urgently needed to address the functional role of lncRNAs.

Topologically Associating Domains: An invariant framework or a dynamic scaffold?

Metazoan genomes are organized into regions of topologically associating domains (TADs). TADs are demarcated by border elements, which are enriched for active genes and high occupancy architectural protein binding sites. We recently demonstrated that 3D chromatin architecture is dynamic in response to heat shock, a physiological stress that downregulates transcription and causes a global redistribution of architectural proteins. We utilized a quantitative measure of border strength after heat shock, transcriptional inhibition, and architectural protein knockdown to demonstrate that changes in both transcription and architectural protein occupancy contribute to heat shock-induced TAD dynamics. Notably, architectural proteins appear to play a more important role in altering 3D chromatin architecture. Here, we discuss the implications of our findings on previous studies evaluating the dynamics of TAD structure during cellular differentiation. We propose that the subset of variable TADs observed after differentiation are representative of cell-type specific gene expression and are biologically significant.

Long Noncoding RNA Expression during Human B-Cell Development

Long noncoding RNAs (lncRNAs) have emerged as important regulators of diverse cellular processes, but their roles in the developing immune system are poorly understood. In this study, we analysed lncRNA expression during human B-cell development by array-based expression profiling of eleven distinct flow-sorted B-cell subsets, comprising pre-B1, pre-B2, immature, naive, memory, and plasma cells from bone marrow biopsies (n = 7), and naive, centroblast, centrocyte, memory, and plasmablast cells from tonsil tissue samples (n = 6), respectively. A remapping strategy was used to assign the array probes to 37630 gene-level probe sets, reflecting recent updates in genomic and transcriptomic databases, which enabled expression profiling of 19579 long noncoding RNAs, comprising 3947 antisense RNAs, 5277 lincRNAs, 7625 pseudogenes, and 2730 additional lncRNAs. As a first step towards inferring the functions of the identified lncRNAs in developing B-cells, we analysed their co-expression with well-characterized protein-coding genes, a method known as “guilt by association”. By using weighted gene co-expression network analysis, we identified 272 lincRNAs, 471 antisense RNAs, 376 pseudogene RNAs, and 64 lncRNAs within seven sub-networks associated with distinct stages of B-cell development, such as early B-cell development, B-cell proliferation, affinity maturation of antibody, and terminal differentiation. These data provide an important resource for future studies on the functions of lncRNAs in development of the adaptive immune response, and the pathogenesis of B-cell malignancies that originate from distinct B-cell subpopulations.

Genomic approaches to studying human-specific developmental traits

Changes in developmental regulatory programs drive both disease and phenotypic differences among species. Linking human-specific traits to alterations in development is challenging, because we have lacked the tools to assay and manipulate regulatory networks in human and primate embryonic cells. This field was transformed by the sequencing of hundreds of genomes – human and non-human – that can be compared to discover the regulatory machinery of genes involved in human development. This approach has identified thousands of human-specific genome alterations in developmental genes and their regulatory regions. With recent advances in stem cell techniques, genome engineering, and genomics, we can now test these sequences for effects on developmental gene regulation and downstream phenotypes in human cells and tissues.

Transcriptional Enhancers in the Regulation of T Cell Differentiation

The changes in phenotype and function that characterize the differentiation of naïve T cells to effector and memory states are underscored by large-scale, coordinated, and stable changes in gene expression. In turn, these changes are choreographed by the interplay between transcription factors and epigenetic regulators that act to restructure the genome, ultimately ensuring lineage-appropriate gene expression. Here, we focus on the mechanisms that control T cell differentiation, with a particular focus on the role of regulatory elements encoded within the genome, known as transcriptional enhancers (TEs). We discuss the central role of TEs in regulating T cell differentiation, both in health and disease.

Exploiting the multiplexing capabilities of tandem mass tags for high-throughput estimation of cellular protein abundances by mass spectrometry

The generation of dynamic models of biological processes critically depends on the determination of precise cellular concentrations of biomolecules. Measurements of system-wide absolute protein levels are particularly valuable information in systems biology. Recently, mass spectrometry based proteomics approaches have been developed to estimate protein concentrations on a proteome-wide scale. However, for very complex proteomes, fractionation steps are required, increasing samples number and instrument analysis time. As a result, the number of full proteomes that can be routinely analyzed is limited. Here we combined absolute quantification strategies with the multiplexing capabilities of isobaric tandem mass tags to determine cellular protein abundances in a high throughput and proteome-wide scale even for highly complex biological systems, such as a whole human cell line. We generated two independent data sets to demonstrate the power of the approach regarding sample throughput, dynamic range, quantitative precision and accuracy as well as proteome coverage in comparison to existing mass spectrometry based strategies.

Review: High-performance computing to detect epistasis in genome scale data sets

It is becoming clear that most human diseases have a complex etiology that cannot be explained by single nucleotide polymorphisms (SNPs) or simple additive combinations; the general consensus is that they are caused by combinations of multiple genetic variations. The limited success of some genome-wide association studies is partly a result of this focus on single genetic markers. A more promising approach is to take into account epistasis, by considering the association of multiple SNP interactions with disease. However, as genomic data continues to grow in resolution, and genome and exome sequencing become more established, the number of combinations of variants to consider increases rapidly. Two potential solutions should be considered: the use of high-performance computing, which allows us to consider a larger number of variables, and heuristics to make the solution more tractable, essential in the case of genome sequencing. In this review, we look at different computational methods to analyse epistatic interactions within disease-related genetic data sets created by microarray technology. We also review efforts to use epistatic analysis results to produce biomarkers for diagnostic tests and give our views on future directions in this field in light of advances in sequencing technology and variants in non-coding regions.

Why the activity of a gene depends on its neighbors

Sixty years ago, the position of a gene on a chromosome was seen to be a major determinant of gene activity; however, position effects are rarely central to current discussions of gene expression. We describe a comprehensive and simplifying view of how position in 1D sequence and 3D nuclear space underlies expression. We suggest that apparently-different regulatory motifs including enhancers, silencers, insulators, barriers, and boundaries act similarly - they are active promoters that tether target genes close to, or distant from, appropriate transcription sites or 'factories'. We also suggest that any active transcription unit regulates the firing of its neighbors - and thus can be categorized as one or other type of motif; this is consistent with expression quantitative trait loci (eQTLs) being widely dispersed.

THZ1 Reveals Roles for Cdk7 in Co-transcriptional Capping and Pausing

The Cdk7 subunit of TFIIH phosphorylates RNA polymerase II (Pol II) during initiation, and, while recent studies show that inhibition of human Cdk7 negatively influences transcription, the mechanisms involved are unclear. Using in vitro transcription with nuclear extract, we demonstrate that THZ1, a covalent Cdk7 inhibitor, causes defects in Pol II phosphorylation, co-transcriptional capping, promoter proximal pausing, and productive elongation. THZ1 does not affect initiation but blocks essentially all Pol II large subunit C-terminal domain (CTD) phosphorylation. We found that guanylylation of nascent RNAs is length dependent and modulated by a THZ1-sensitive factor present in nuclear extract. THZ1 impacts pausing through a capping-independent block of DSIF and NELF loading. The P-TEFb-dependent transition into productive elongation was also inhibited by THZ1, likely due to loss of DSIF. Capping and pausing were also reduced in THZ1-treated cells. Our results provide mechanistic insights into THZ1 action and how Cdk7 broadly influences transcription and capping.

Temporal Dissection of Rate Limiting Transcriptional Events Using Pol II ChIP and RNA Analysis of Adrenergic Stress Gene Activation

In mammals, increasing evidence supports mechanisms of co-transcriptional gene regulation and the generality of genetic control subsequent to RNA polymerase II (Pol II) recruitment. In this report, we use Pol II Chromatin Immunoprecipitation to investigate relationships between the mechanistic events controlling immediate early gene (IEG) activation following stimulation of the α_1a-Adrenergic Receptor expressed in rat-1 fibroblasts. We validate our Pol II ChIP assay by comparison to major transcriptional events assessable by microarray and PCR analysis of precursor and mature mRNA. Temporal analysis of Pol II density suggests that reduced proximal pausing often enhances gene expression and was essential for Nr4a3 expression. Nevertheless, for Nr4a3 and several other genes, proximal pausing delayed the time required for initiation of productive elongation, consistent with a role in ensuring transcriptional fidelity. Arrival of Pol II at the 3’ cleavage site usually correlated with increased polyadenylated mRNA; however, for Nfil3 and probably Gprc5a expression was delayed and accompanied by apparent pre-mRNA degradation. Intragenic pausing not associated with polyadenylation was also found to regulate and delay Gprc5a expression. Temporal analysis of Nr4a3, Dusp5 and Nfil3 shows that transcription of native IEG genes can proceed at velocities of 3.5 to 4 kilobases/min immediately after activation. Of note, all of the genes studied here also used increased Pol II recruitment as an important regulator of expression. Nevertheless, the generality of co-transcriptional regulation during IEG activation suggests temporal and integrated analysis will often be necessary to distinguish causative from potential rate limiting mechanisms.

Kruppel-Like Factor 4 Regulates Granule Cell Pax6 Expression and Cell Proliferation in Early Cerebellar Development

Kruppel-like factor 4 (Klf4) is a transcription factor that regulates many important cellular processes in stem cell biology, cancer, and development. We used histological and molecular methods to study the expression of Klf4 in embryonic development of the normal and Klf4 knockout cerebellum. We find that Klf4 is expressed strongly in early granule cell progenitor development but tails-off considerably by the end of embryonic development. Klf4 is also co-expressed with Pax6 in these cells. In the Klf4-null mouse, which is perinatal lethal, Klf4 positively regulates Pax6 expression and regulates the proliferation of neuronal progenitors in the rhombic lip, external granular layer and the neuroepithelium. This paper is the first to describe a role for Klf4 in the cerebellum and provides insight into this gene’s function in neuronal development.

The Many Alternative Faces of Macrophage Activation

Monocytes and macrophages provide the first line of defense against pathogens. They also initiate acquired immunity by processing and presenting antigens and provide the downstream effector functions. Analysis of large gene expression datasets from multiple cells and tissues reveals sets of genes that are co-regulated with the transcription factors that regulate them. In macrophages, the gene clusters include lineage-specific genes, interferon-responsive genes, early inflammatory genes, and genes required for endocytosis and lysosome function. Macrophages enter tissues and alter their function to deal with a wide range of challenges related to development and organogenesis, tissue injury, malignancy, sterile, or pathogenic inflammatory stimuli. These stimuli alter the gene expression to produce "activated macrophages" that are better equipped to eliminate the cause of their influx and to restore homeostasis. Activation or polarization states of macrophages have been classified as "classical" and "alternative" or M1 and M2. These proposed states of cells are not supported by large-scale transcriptomic data, including macrophage-associated signatures from large cancer tissue datasets, where the supposed markers do not correlate with other. Individual macrophage cells differ markedly from each other, and change their functions in response to doses and combinations of agonists and time. The most studied macrophage activation response is the transcriptional cascade initiated by the TLR4 agonist lipopolysaccharide. This response is reviewed herein. The network topology is conserved across species, but genes within the transcriptional network evolve rapidly and differ between mouse and human. There is also considerable divergence in the sets of target genes between mouse strains, between individuals, and in other species such as pigs. The deluge of complex information related to macrophage activation can be accessed with new analytical tools and new databases that provide access for the non-expert.

Promoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ErbB receptors in breast cancer cells

The analysis of CAGE (Cap Analysis of Gene Expression) time-course has been proposed by the FANTOM5 Consortium to extend the understanding of the sequence of events facilitating cell state transition at the level of promoter regulation. To identify the most prominent transcriptional regulations induced by growth factors in human breast cancer, we apply here the Complexity Invariant Dynamic Time Warping motif EnRichment (CIDER) analysis approach to the CAGE time-course datasets of MCF-7 cells stimulated by epidermal growth factor (EGF) or heregulin (HRG). We identify a multi-level cascade of regulations rooted by the Serum Response Factor (SRF) transcription factor, connecting the MAPK-mediated transduction of the HRG stimulus to the negative regulation of the MAPK pathway by the members of the DUSP family phosphatases. The finding confirms the known primary role of FOS and FOSL1, members of AP-1 family, in shaping gene expression in response to HRG induction. Moreover, we identify a new potential regulation of DUSP5 and RARA (known to antagonize the transcriptional regulation induced by the estrogen receptors) by the activity of the AP-1 complex, specific to HRG response. The results indicate that a divergence in AP-1 regulation determines cellular changes of breast cancer cells stimulated by ErbB receptors.

Redefining the transcriptional regulatory dynamics of classically and alternatively activated macrophages by deepCAGE transcriptomics

Classically or alternatively activated macrophages (M1 and M2, respectively) play distinct and important roles for microbiocidal activity, regulation of inflammation and tissue homeostasis. Despite this, their transcriptional regulatory dynamics are poorly understood. Using promoter-level expression profiling by non-biased deepCAGE we have studied the transcriptional dynamics of classically and alternatively activated macrophages. Transcription factor (TF) binding motif activity analysis revealed four motifs, NFKB1_REL_RELA, IRF1,2, IRF7 and TBP that are commonly activated but have distinct activity dynamics in M1 and M2 activation. We observe matching changes in the expression profiles of the corresponding TFs and show that only a restricted set of TFs change expression. There is an overall drastic and transient up-regulation in M1 and a weaker and more sustainable up-regulation in M2. Novel TFs, such as Thap6, Maff, (M1) and Hivep1, Nfil3, Prdm1, (M2) among others, were suggested to be involved in the activation processes. Additionally, 52 (M1) and 67 (M2) novel differentially expressed genes and, for the first time, several differentially expressed long non-coding RNA (lncRNA) transcriptome markers were identified. In conclusion, the finding of novel motifs, TFs and protein-coding and lncRNA genes is an important step forward to fully understand the transcriptional machinery of macrophage activation.

Novel biological insights in T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive type of blood cancer that accounts for about 15% of pediatric and 25% of adult acute lymphoblastic leukemia (ALL) cases. It is considered as a paradigm for the multistep nature of cancer initiation and progression. Genetic and epigenetic reprogramming events, which transform T-cell precursors into malignant T-ALL lymphoblasts, have been extensively characterized over the past decade. Despite our comprehensive understanding of the genomic landscape of human T-ALL, leukemia patients are still treated by high-dose multiagent chemotherapy, potentially followed by hematopoietic stem cell transplantation. Even with such aggressive treatment regimens, which are often associated with considerable acute and long-term side effects, about 15% of pediatric and 40% of adult T-ALL patients still relapse, owing to acquired therapy resistance, and present with very dismal survival perspectives. Unfortunately, the molecular mechanisms by which residual T-ALL tumor cells survive chemotherapy and act as a reservoir for leukemic progression and hematologic relapse remain poorly understood. Nevertheless, it is expected that enhanced molecular understanding of T-ALL disease biology will ultimately facilitate a targeted therapy driven approach that can reduce chemotherapy-associated toxicities and improve survival of refractory T-ALL patients through personalized salvage therapy. In this review, we summarize recent biological insights into the molecular pathogenesis of T-ALL and speculate how the genetic landscape of T-ALL could trigger the development of novel therapeutic strategies for the treatment of human T-ALL.

A unified architecture of transcriptional regulatory elements

Gene expression is precisely controlled in time and space through the integration of signals that act at gene promoters and gene-distal enhancers. Classically, promoters and enhancers are considered separate classes of regulatory elements, often distinguished by histone modifications. However, recent studies have revealed broad similarities between enhancers and promoters, blurring the distinction: active enhancers often initiate transcription, and some gene promoters have the potential to enhance transcriptional output of other promoters. Here, we propose a model in which promoters and enhancers are considered a single class of functional element, with a unified architecture for transcription initiation. The context of interacting regulatory elements and the surrounding sequences determine local transcriptional output as well as the enhancer and promoter activities of individual elements.

Architectural proteins, transcription, and the three-dimensional organization of the genome

Architectural proteins mediate interactions between distant sequences in the genome. Two well-characterized functions of architectural protein interactions include the tethering of enhancers to promoters and bringing together Polycomb-containing sites to facilitate silencing. The nature of which sequences interact genome-wide appears to be determined by the orientation of the architectural protein binding sites as well as the number and identity of architectural proteins present. Ultimately, long range chromatin interactions result in the formation of loops within the chromatin fiber. In this review, we discuss data suggesting that architectural proteins mediate long range chromatin interactions that both facilitate and hinder neighboring interactions, compartmentalizing the genome into regions of highly interacting chromatin domains.

Genome-Wide Definition of Promoter and Enhancer Usage during Neural Induction of Human Embryonic Stem Cells

Genome-wide mapping of transcriptional regulatory elements is an essential tool for understanding the molecular events orchestrating self-renewal, commitment and differentiation of stem cells. We combined high-throughput identification of transcription start sites with genome-wide profiling of histones modifications to map active promoters and enhancers in embryonic stem cells (ESCs) induced to neuroepithelial-like stem cells (NESCs). Our analysis showed that most promoters are active in both cell types while approximately half of the enhancers are cell-specific and account for most of the epigenetic changes occurring during neural induction, and most likely for the modulation of the promoters to generate cell-specific gene expression programs. Interestingly, the majority of the promoters activated or up-regulated during neural induction have a “bivalent” histone modification signature in ESCs, suggesting that developmentally-regulated promoters are already poised for transcription in ESCs, which are apparently pre-committed to neuroectodermal differentiation. Overall, our study provides a collection of differentially used enhancers, promoters, transcription starts sites, protein-coding and non-coding RNAs in human ESCs and ESC-derived NESCs, and a broad, genome-wide description of promoter and enhancer usage and of gene expression programs characterizing the transition from a pluripotent to a neural-restricted cell fate.

Transcriptional dynamics reveal critical roles for non-coding RNAs in the immediate-early response

The immediate-early response mediates cell fate in response to a variety of extracellular stimuli and is dysregulated in many cancers. However, the specificity of the response across stimuli and cell types, and the roles of non-coding RNAs are not well understood. Using a large collection of densely-sampled time series expression data we have examined the induction of the immediate-early response in unparalleled detail, across cell types and stimuli. We exploit cap analysis of gene expression (CAGE) time series datasets to directly measure promoter activities over time. Using a novel analysis method for time series data we identify transcripts with expression patterns that closely resemble the dynamics of known immediate-early genes (IEGs) and this enables a comprehensive comparative study of these genes and their chromatin state. Surprisingly, these data suggest that the earliest transcriptional responses often involve promoters generating non-coding RNAs, many of which are produced in advance of canonical protein-coding IEGs. IEGs are known to be capable of induction without de novo protein synthesis. Consistent with this, we find that the response of both protein-coding and non-coding RNA IEGs can be explained by their transcriptionally poised, permissive chromatin state prior to stimulation. We also explore the function of non-coding RNAs in the attenuation of the immediate early response in a small RNA sequencing dataset matched to the CAGE data: We identify a novel set of microRNAs responsible for the attenuation of the IEG response in an estrogen receptor positive cancer cell line. Our computational statistical method is well suited to meta-analyses as there is no requirement for transcripts to pass thresholds for significant differential expression between time points, and it is agnostic to the number of time points per dataset.

Cells respond to stimuli through a set of genes that are primed for rapid activation. These genes, known as immediate-early genes (IEGs), are regulated at the level of transcription of the messenger RNA, and at subsequent RNA processing levels. These rapid responders are then rapidly switched off in normal cells. Immediate-early genes are involved in many cellular processes, including differentiation and proliferation, that are often dysregulated in cancer where they become continuously active. We characterise IEGs in a genome-wide sequencing dataset that captures their transcriptional response over time. Using a novel analysis technique, we identify both protein-coding and non-coding genes that are activated comparably to IEGs and investigate their properties. We examine how IEGs are switched off, including through microRNAs, small non-coding RNAs that act to control the level of key IEGs. We identify a novel set of microRNAs responsible for the attenuation of the IEG response in an estrogen receptor positive cancer cell line.