FIREWACh: high-throughput functional detection of transcriptional regulatory modules in mammalian cells

Hold out the genome: a roadmap to solving the cis-regulatory code

Gene expression is regulated by transcription factors that work together to read cis-regulatory DNA sequences. The 'cis-regulatory code' - how cells interpret DNA sequences to determine when, where and how much genes should be expressed - has proven to be exceedingly complex. Recently, advances in the scale and resolution of functional genomics assays and machine learning have enabled substantial progress towards deciphering this code. However, the cis-regulatory code will probably never be solved if models are trained only on genomic sequences; regions of homology can easily lead to overestimation of predictive performance, and our genome is too short and has insufficient sequence diversity to learn all relevant parameters. Fortunately, randomly synthesized DNA sequences enable testing a far larger sequence space than exists in our genomes, and designed DNA sequences enable targeted queries to maximally improve the models. As the same biochemical principles are used to interpret DNA regardless of its source, models trained on these synthetic data can predict genomic activity, often better than genome-trained models. Here we provide an outlook on the field, and propose a roadmap towards solving the cis-regulatory code by a combination of machine learning and massively parallel assays using synthetic DNA.

MPRAbase: A Massively Parallel Reporter Assay Database

Massively parallel reporter assays (MPRAs) represent a set of high-throughput technologies that measure the functional effects of thousands of sequences/variants on gene regulatory activity. There are several different variations of MPRA technology and they are used for numerous applications, including regulatory element discovery, variant effect measurement, saturation mutagenesis, synthetic regulatory element generation or characterization of evolutionary gene regulatory differences. Despite their many designs and uses, there is no comprehensive database that incorporates the results of these experiments. To address this, we developed MPRAbase, a manually curated database that currently harbors 129 experiments, encompassing 17,718,677 elements tested across 35 cell types and 4 organisms. The MPRAbase web interface ( http://www.mprabase.com ) serves as a centralized user-friendly repository to download existing MPRA data for independent analysis and is designed with the ability to allow researchers to share their published data for rapid dissemination to the community.

GATA transcription factors drive initial Xist upregulation after fertilization through direct activation of long-range enhancers

X-chromosome inactivation (XCI) balances gene expression between the sexes in female mammals. Shortly after fertilization, upregulation of Xist RNA from one X chromosome initiates XCI, leading to chromosome-wide gene silencing. XCI is maintained in all cell types, except the germ line and the pluripotent state where XCI is reversed. The mechanisms triggering Xist upregulation have remained elusive. Here we identify GATA transcription factors as potent activators of Xist. Through a pooled CRISPR activation screen in murine embryonic stem cells, we demonstrate that GATA1, as well as other GATA transcription factors can drive ectopic Xist expression. Moreover, we describe GATA-responsive regulatory elements in the Xist locus bound by different GATA factors. Finally, we show that GATA factors are essential for XCI induction in mouse preimplantation embryos. Deletion of GATA1/4/6 or GATA-responsive Xist enhancers in mouse zygotes effectively prevents Xist upregulation. We propose that the activity or complete absence of various GATA family members controls initial Xist upregulation, XCI maintenance in extra-embryonic lineages and XCI reversal in the epiblast.

Genome-wide enhancer identification by massively parallel reporter assay in Arabidopsis

Enhancers are critical cis-regulatory elements controlling gene expression during cell development and differentiation. However, genome-wide enhancer characterization has been challenging due to the lack of a well-defined relationship between enhancers and genes. Function-based methods are the gold standard for determining the biological function of cis-regulatory elements; however, these methods have not been widely applied to plants. Here, we applied a massively parallel reporter assay on Arabidopsis to measure enhancer activities across the genome. We identified 4327 enhancers with various combinations of epigenetic modifications distinctively different from animal enhancers. Furthermore, we showed that enhancers differ from promoters in their preference for transcription factors. Although some enhancers are not conserved and overlap with transposable elements forming clusters, enhancers are generally conserved across thousand Arabidopsis accessions, suggesting they are selected under evolution pressure and could play critical roles in the regulation of important genes. Moreover, comparison analysis reveals that enhancers identified by different strategies do not overlap, suggesting these methods are complementary in nature. In sum, we systematically investigated the features of enhancers identified by functional assay in A. thaliana, which lays the foundation for further investigation into enhancers' functional mechanisms in plants.

Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation

Despite the recent explosion in genome-wide studies in chromatin and gene regulation, we are still far from extracting a set of genetic rules that can predict the function of the regulatory genome. One major reason for this deficiency is that gene regulation is a multi-layered process that involves an enormous variable space, which cannot be fully explored using native genomes. This problem can be partially solved by introducing synthetic DNA libraries into cells, a method that can test the regulatory roles of thousands to millions of sequences with limited variables. Here, we review recent applications of this method to study transcription factor (TF) binding, nucleosome positioning, and transcriptional activity. We discuss the design principles, experimental procedures, and major findings from these studies and compare the pros and cons of different approaches.

Systematic mapping and modeling of 3D enhancer-promoter interactions in early mouse embryonic lineages reveal regulatory principles that determine the levels and cell-type specificity of gene expression

Mammalian embryogenesis commences with two pivotal and binary cell fate decisions that give rise to three essential lineages, the trophectoderm (TE), the epiblast (EPI) and the primitive endoderm (PrE). Although key signaling pathways and transcription factors that control these early embryonic decisions have been identified, the non-coding regulatory elements via which transcriptional regulators enact these fates remain understudied. To address this gap, we have characterized, at a genome-wide scale, enhancer activity and 3D connectivity in embryo-derived stem cell lines that represent each of the early developmental fates. We observed extensive enhancer remodeling and fine-scale 3D chromatin rewiring among the three lineages, which strongly associate with transcriptional changes, although there are distinct groups of genes that are irresponsive to topological changes. In each lineage, a high degree of connectivity or "hubness" positively correlates with levels of gene expression and enriches for cell-type specific and essential genes. Genes within 3D hubs also show a significantly stronger probability of coregulation across lineages, compared to genes in linear proximity or within the same contact domains. By incorporating 3D chromatin features, we build a novel predictive model for transcriptional regulation (3D-HiChAT), which outperformed models that use only 1D promoter or proximal variables in predicting levels and cell-type specificity of gene expression. Using 3D-HiChAT, we performed genome-wide in silico perturbations to nominate candidate functional enhancers and hubs in each cell lineage, and with CRISPRi experiments we validated several novel enhancers that control expression of one or more genes in their respective lineages. Our study comprehensively identifies 3D regulatory hubs associated with the earliest mammalian lineages and describes their relationship to gene expression and cell identity, providing a framework to understand lineage-specific transcriptional behaviors.

The sound of silence: Transgene silencing in mammalian cell engineering

To elucidate principles operating in native biological systems and to develop novel biotechnologies, synthetic biology aims to build and integrate synthetic gene circuits within native transcriptional networks. The utility of synthetic gene circuits for cell engineering relies on the ability to control the expression of all constituent transgene components. Transgene silencing, defined as the loss of expression over time, persists as an obstacle for engineering primary cells and stem cells with transgenic cargos. In this review, we highlight the challenge that transgene silencing poses to the robust engineering of mammalian cells, outline potential molecular mechanisms of silencing, and present approaches for preventing transgene silencing. We conclude with a perspective identifying future research directions for improving the performance of synthetic gene circuits.

Efficient Selection of Enhancers and Promoters from MIA PaCa-2 Pancreatic Cancer Cells by ChIP-lentiMPRA

A library of active genome regulatory elements (putative promoters and enhancers) from MIA PaCa-2 pancreatic adenocarcinoma cells was constructed using a specially designed lentiviral vector and a massive parallel reporter assay (ChIP-lentiMPRA). Chromatin immunoprecipitation of the cell genomic DNA by H3K27ac antibodies was used for primary enrichment of the library for regulatory elements. Totally, 11,264 unique genome regions, many of which are capable of enhancing the expression of the CopGFP reporter gene from the minimal CMV promoter, were identified. The regions tend to be located near promoters. Based on the proximity assay, we found an enrichment of highly expressed genes among those associated with three or more mapped distal regions (2 kb distant from the 5'-ends of genes). It was shown significant enrichment of genes related to carcinogenesis or Mia PaCa-2 cell identity genes in this group. In contrast, genes associated with 1-2 distal regions or only with proximal regions (within 2 kbp of the 5'-ends of genes) are more often related to housekeeping functions. Thus, ChIP-lentiMPRA is a useful strategy for creating libraries of regulatory elements for the study of tumor-specific gene transcription.

Estrogen-related receptor alpha drives mitochondrial biogenesis and resistance to neoadjuvant chemoradiation in esophageal cancer

Neoadjuvant chemoradiotherapy (nCRT) improves outcomes in resectable esophageal adenocarcinoma (EAC), but acquired resistance precludes long-term efficacy. Here, we delineate these resistance mechanisms. RNA sequencing on matched patient samples obtained pre-and post-neoadjuvant treatment reveal that oxidative phosphorylation was the most upregulated of all biological programs following nCRT. Analysis of patient-derived models confirms that mitochondrial content and oxygen consumption strongly increase in response to nCRT and that ionizing radiation is the causative agent. Bioinformatics identifies estrogen-related receptor alpha (ESRRA) as the transcription factor responsible for reprogramming, and overexpression and silencing of ESRRA functionally confirm that its downstream metabolic rewiring contributes to resistance. Pharmacological inhibition of ESRRA successfully sensitizes EAC organoids and patient-derived xenografts to radiation. In conclusion, we report a profound metabolic rewiring following chemoradiation and demonstrate that its inhibition resensitizes EAC cells to radiation. These findings hold broader relevance for other cancer types treated with radiation as well.

Enhancer-gene specificity in development and disease

Enhancers control the establishment of spatiotemporal gene expression patterns throughout development. Over the past decade, the development of new technologies has improved our capacity to link enhancers with their target genes based on their colocalization within the same topological domains. However, the mechanisms that regulate how enhancers specifically activate some genes but not others within a given domain remain unclear. In this Review, we discuss recent insights into the factors controlling enhancer specificity, including the genetic composition of enhancers and promoters, the linear and 3D distance between enhancers and their target genes, and cell-type specific chromatin landscapes. We also discuss how elucidating the molecular principles of enhancer specificity might help us to better understand and predict the pathological consequences of human genetic, epigenetic and structural variants.

Molecular and experimental tools to design synthetic enhancers

Understanding the grammar of enhancers and how they regulate gene expression is key for both basic research and for the pharma and biotech industries. The design and characterization of synthetic enhancers can expand the known regulatory space. This is achieved by the utilization of DNA Oligo Libraries (OLs), which facilitates screening of as many as millions of synthetic enhancer variants simultaneously. This review includes the latest commercial DNA OL synthesis technology and its capabilities, and a general 'know-how' guide for the design, construction, and analysis of OL-based synthetic enhancer characterization experiments. Specifically, we focus on synthetic-enhancer-based massively parallel reporter assay, Sort-seq methodologies (e.g. flow cytometry, deep sequencing), and a brief description of machine learning-based attempts for OL-analysis and follow-up validation experiments.

Methods of massive parallel reporter assays for investigation of enhancers

The correct deployment of genetic programs for development and differentiation relies on finely coordinated regulation of specific gene sets. Genomic regulatory elements play an exceptional role in this process. There are few types of gene regulatory elements, including promoters, enhancers, insulators and silencers. Alterations of gene regulatory elements may cause various pathologies, including cancer, congenital disorders and autoimmune diseases. The development of high-throughput genomic assays has made it possible to significantly accelerate the accumulation of information about the characteristic epigenetic properties of regulatory elements. In combination with high-throughput studies focused on the genome-wide distribution of epigenetic marks, regulatory proteins and the spatial structure of chromatin, this significantly expands the understanding of the principles of epigenetic regulation of genes and allows potential regulatory elements to be searched for in silico. However, common experimental approaches used to study the local characteristics of chromatin have a number of technical limitations that may reduce the reliability of computational identification of genomic regulatory sequences. Taking into account the variability of the functions of epigenetic determinants and complex multicomponent regulation of genomic elements activity, their functional verification is often required. A plethora of methods have been developed to study the functional role of regulatory elements on the genome scale. Common experimental approaches for in silico identification of regulatory elements and their inherent technical limitations will be described. The present review is focused on original high-throughput methods of enhancer activity reporter analysis that are currently used to validate predicted regulatory elements and to perform de novo searches. The methods described allow assessing the functional role of the nucleotide sequence of a regulatory element, to determine its exact boundaries and to assess the influence of the local state of chromatin on the activity of enhancers and gene expression. These approaches have contributed substantially to the understanding of the fundamental principles of gene regulation.

No Need to Stick Together to Be Connected: Multiple Types of Enhancers' Networking

Simple Summary

Transcription regulation programs require the functional interaction of distal and proximal regulatory regions, interacting by specific 3D chromatin configurations. Enhancers are cis-acting regulatory elements able to promote gene expression regardless their orientation and distance from the transcription starting site. Their systematic mapping by genome-wide chromatin profiling and chromosome conformation analysis, combined with the development of gene-editing approaches to modulate their function, revealed that many enhancers work together to fine-tune the expression of their target genes. This review aim to describe the functions of different types of enhancers and the modalities of enhancers’ interaction, focusing on their role in the regulation of complex biological processes like cancer development.

Abstract

The control of gene expression at a transcriptional level requires a widespread landscape of regulatory elements. Central to these regulatory circuits are enhancers (ENHs), which are defined as cis-acting DNA elements able to increase the transcription of a target gene in a distance- and orientation-independent manner. ENHs are not independent functional elements but work in a complex and dynamic cooperative network, constituting the building blocks of multimodular domains of gene expression regulation. The information from each of these elements converges on the target promoter, contributing to improving the precision and sharpness of gene modulation. ENHs’ interplay varies in its nature and extent, ranging from an additive to redundant effect depending on contexts. Moving from super-enhancers that drive the high expression levels of identity genes, to shadow-enhancers, whose redundant functions contribute to buffering the variation in gene expression, this review aims to describe the different modalities of ENHs’ interaction and their role in the regulation of complex biological processes like cancer development.

Annotating the Insect Regulatory Genome

An ever-growing number of insect genomes is being sequenced across the evolutionary spectrum. Comprehensive annotation of not only genes but also regulatory regions is critical for reaping the full benefits of this sequencing. Driven by developments in sequencing technologies and in both empirical and computational discovery strategies, the past few decades have witnessed dramatic progress in our ability to identify cis-regulatory modules (CRMs), sequences such as enhancers that play a major role in regulating transcription. Nevertheless, providing a timely and comprehensive regulatory annotation of newly sequenced insect genomes is an ongoing challenge. We review here the methods being used to identify CRMs in both model and non-model insect species, and focus on two tools that we have developed, REDfly and SCRMshaw. These resources can be paired together in a powerful combination to facilitate insect regulatory annotation over a broad range of species, with an accuracy equal to or better than that of other state-of-the-art methods.

A flexible repertoire of transcription factor binding sites and a diversity threshold determines enhancer activity in embryonic stem cells

Transcriptional enhancers are critical for development and phenotype evolution and are often mutated in disease contexts; however, even in well-studied cell types, the sequence code conferring enhancer activity remains unknown. To examine the enhancer regulatory code for pluripotent stem cells, we identified genomic regions with conserved binding of multiple transcription factors in mouse and human embryonic stem cells (ESCs). Examination of these regions revealed that they contain on average 12.6 conserved transcription factor binding site (TFBS) sequences. Enriched TFBSs are a diverse repertoire of 70 different sequences representing the binding sequences of both known and novel ESC regulators. Using a diverse set of TFBSs from this repertoire was sufficient to construct short synthetic enhancers with activity comparable to native enhancers. Site-directed mutagenesis of conserved TFBSs in endogenous enhancers or TFBS deletion from synthetic sequences revealed a requirement for 10 or more different TFBSs. Furthermore, specific TFBSs, including the POU5F1:SOX2 comotif, are dispensable, despite cobinding the POU5F1 (also known as OCT4), SOX2, and NANOG master regulators of pluripotency. These findings reveal that a TFBS sequence diversity threshold overrides the need for optimized regulatory grammar and individual TFBSs that recruit specific master regulators.

Transcriptional enhancers: from prediction to functional assessment on a genome-wide scale

Enhancers are cis-regulatory sequences located distally to target genes. These sequences consolidate developmental and environmental cues to coordinate gene expression in a tissue-specific manner. Enhancer function and tissue specificity depend on the expressed set of transcription factors, which recognize binding sites and recruit cofactors that regulate local chromatin organization and gene transcription. Unlike other genomic elements, enhancers are challenging to identify because they function independently of orientation, are often distant from their promoters, have poorly defined boundaries, and display no reading frame. In addition, there are no defined genetic or epigenetic features that are unambiguously associated with enhancer activity. Over recent years there have been developments in both empirical assays and computational methods for enhancer prediction. We review genome-wide tools, CRISPR advancements, and high-throughput screening approaches that have improved our ability to both observe and manipulate enhancers in vitro at the level of primary genetic sequences, chromatin states, and spatial interactions. We also highlight contemporary animal models and their importance to enhancer validation. Together, these experimental systems and techniques complement one another and broaden our understanding of enhancer function in development, evolution, and disease.

Supervised enhancer prediction with epigenetic pattern recognition and targeted validation

Enhancers are important noncoding elements, but they have been traditionally hard to characterize experimentally. The development of massively parallel assays allows the characterization of large numbers of enhancers for the first time. Here, we developed a framework using Drosophila STARR-seq to create shape-matching filters based on meta-profiles of epigenetic features. We integrated these features with supervised machine-learning algorithms to predict enhancers. We further demonstrated our model could be transferred to predict enhancers in mammals. We comprehensively validated the predictions using a combination of in vivo and in vitro approaches, involving transgenic assays in mouse and transduction-based reporter assays in human cell lines (153 enhancers in total). The results confirmed our model can accurately predict enhancers in different species without re-parameterization. Finally, we examined the transcription-factor binding patterns at predicted enhancers versus promoters. We demonstrated that these patterns enable the construction of a secondary model effectively discriminating between enhancers and promoters.

Gene regulatory networks STARR-ing B cells

A genome-wide screening of functionally active enhancers, combined with analyses of chromatin features, transcription factor binding and gene expression, reveals general principles of gene regulatory networks in activated B cells.

The Leukemogenic TCF3-HLF Complex Rewires Enhancers Driving Cellular Identity and Self-Renewal Conferring EP300 Vulnerability

The chimeric transcription factor TCF3-HLF defines an incurable acute lymphoblastic leukemia subtype. Here we decipher the regulome of endogenous TCF3-HLF and dissect its essential transcriptional components and targets by functional genomics. We demonstrate that TCF3-HLF recruits HLF binding sites at hematopoietic stem cell/myeloid lineage associated (super-) enhancers to drive lineage identity and self-renewal. Among direct targets, hijacking an HLF binding site in a MYC enhancer cluster by TCF3-HLF activates a conserved MYC-driven transformation program crucial for leukemia propagation in vivo. TCF3-HLF pioneers the cooperation with ERG and recruits histone acetyltransferase p300 (EP300), conferring susceptibility to EP300 inhibition. Our study provides a framework for targeting driving transcriptional dependencies in this fatal leukemia.

Massively parallel RNA device engineering in mammalian cells with RNA-Seq

Synthetic RNA-based genetic devices dynamically control a wide range of gene-regulatory processes across diverse cell types. However, the limited throughput of quantitative assays in mammalian cells has hindered fast iteration and interrogation of sequence space needed to identify new RNA devices. Here we report developing a quantitative, rapid and high-throughput mammalian cell-based RNA-Seq assay to efficiently engineer RNA devices. We identify new ribozyme-based RNA devices that respond to theophylline, hypoxanthine, cyclic-di-GMP, and folinic acid from libraries of ~22,700 sequences in total. The small molecule responsive devices exhibit low basal expression and high activation ratios, significantly expanding our toolset of highly functional ribozyme switches. The large datasets obtained further provide conserved sequence and structure motifs that may be used for rationally guided design. The RNA-Seq approach offers a generally applicable strategy for developing broad classes of RNA devices, thereby advancing the engineering of genetic devices for mammalian systems.

A scalable platform for the development of cell-type-specific viral drivers

Enhancers are the primary DNA regulatory elements that confer cell type specificity of gene expression. Recent studies characterizing individual enhancers have revealed their potential to direct heterologous gene expression in a highly cell-type-specific manner. However, it has not yet been possible to systematically identify and test the function of enhancers for each of the many cell types in an organism. We have developed PESCA, a scalable and generalizable method that leverages ATAC- and single-cell RNA-sequencing protocols, to characterize cell-type-specific enhancers that should enable genetic access and perturbation of gene function across mammalian cell types. Focusing on the highly heterogeneous mammalian cerebral cortex, we apply PESCA to find enhancers and generate viral reagents capable of accessing and manipulating a subset of somatostatin-expressing cortical interneurons with high specificity. This study demonstrates the utility of this platform for developing new cell-type-specific viral reagents, with significant implications for both basic and translational research.

Genetic Variation in Long-Range Enhancers

Cis-regulatory elements (CREs), including insulators, promoters, and enhancers, play critical roles in the establishment and maintenance of normal cellular function. Within each cell, the 3D structure of chromatin is arranged in specific patterns to expose the CREs required for optimal spatiotemporal regulation of gene expression. CREs can act over large distances along the linear genome, facilitated by looping of the intervening chromatin to allow direct interaction between distal regulatory elements and their target genes. A number of pathologies are associated with dysregulation of CRE function, including developmental disorders, cancers, and neuropsychiatric disease. A majority of known neuropsychiatric disease risk loci are noncoding, and increasing evidence suggests that they contribute to disease through disruption of CREs. As such, rather than directly altering the amino acid content of proteins, these variants are instead thought to affect where, when, and to what extent a given gene is expressed. The distances over which CREs can operate often render their target genes difficult to identify. Furthermore, as many risk loci contain multiple variants in high linkage disequilibrium, identification of the causative single nucleotide polymorphism(s) therein is not straightforward. Thus, deciphering the genetic etiology of complex neuropsychiatric disorders presents a significant challenge.

Bayesian estimation of genetic regulatory effects in high-throughput reporter assays

MOTIVATION

High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA.

RESULTS

We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters.

AVAILABILITY AND IMPLEMENTATION

The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Beyond the Exome: The Non-coding Genome and Enhancers in Neurodevelopmental Disorders and Malformations of Cortical Development

The development of the human cerebral cortex is a complex and dynamic process, in which neural stem cell proliferation, neuronal migration, and post-migratory neuronal organization need to occur in a well-organized fashion. Alterations at any of these crucial stages can result in malformations of cortical development (MCDs), a group of genetically heterogeneous neurodevelopmental disorders that present with developmental delay, intellectual disability and epilepsy. Recent progress in genetic technologies, such as next generation sequencing, most often focusing on all protein-coding exons (e.g., whole exome sequencing), allowed the discovery of more than a 100 genes associated with various types of MCDs. Although this has considerably increased the diagnostic yield, most MCD cases remain unexplained. As Whole Exome Sequencing investigates only a minor part of the human genome (1-2%), it is likely that patients, in which no disease-causing mutation has been identified, could harbor mutations in genomic regions beyond the exome. Even though functional annotation of non-coding regions is still lagging behind that of protein-coding genes, tremendous progress has been made in the field of gene regulation. One group of non-coding regulatory regions are enhancers, which can be distantly located upstream or downstream of genes and which can mediate temporal and tissue-specific transcriptional control via long-distance interactions with promoter regions. Although some examples exist in literature that link alterations of enhancers to genetic disorders, a widespread appreciation of the putative roles of these sequences in MCDs is still lacking. Here, we summarize the current state of knowledge on cis-regulatory regions and discuss novel technologies such as massively-parallel reporter assay systems, CRISPR-Cas9-based screens and computational approaches that help to further elucidate the emerging role of the non-coding genome in disease. Moreover, we discuss existing literature on mutations or copy number alterations of regulatory regions involved in brain development. We foresee that the future implementation of the knowledge obtained through ongoing gene regulation studies will benefit patients and will provide an explanation to part of the missing heritability of MCDs and other genetic disorders.

Functional evaluation of transposable elements as enhancers in mouse embryonic and trophoblast stem cells

Transposable elements (TEs) are thought to have helped establish gene regulatory networks. Both the embryonic and extraembryonic lineages of the early mouse embryo have seemingly co-opted TEs as enhancers, but there is little evidence that they play significant roles in gene regulation. Here we tested a set of long terminal repeat TE families for roles as enhancers in mouse embryonic and trophoblast stem cells. Epigenomic and transcriptomic data suggested that a large number of TEs helped to establish tissue-specific gene expression programmes. Genetic editing of individual TEs confirmed a subset of these regulatory relationships. However, a wider survey via CRISPR interference of RLTR13D6 elements in embryonic stem cells revealed that only a minority play significant roles in gene regulation. Our results suggest that a subset of TEs are important for gene regulation in early mouse development, and highlight the importance of functional experiments when evaluating gene regulatory roles of TEs.

High-resolution genome-wide functional dissection of transcriptional regulatory regions and nucleotides in human

Genome-wide epigenomic maps have revealed millions of putative enhancers and promoters, but experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited. Here, we present HiDRA (High-resolution Dissection of Regulatory Activity), a combined experimental and computational method for high-resolution genome-wide testing and dissection of putative regulatory regions. We test ~7 million accessible DNA fragments in a single experiment, by coupling accessible chromatin extraction with self-transcribing episomal reporters (ATAC-STARR-seq). By design, fragments are highly overlapping in densely-sampled accessible regions, enabling us to pinpoint driver regulatory nucleotides by exploiting differences in activity between partially-overlapping fragments using a machine learning model (SHARPR-RE). In GM12878 lymphoblastoid cells, we find ~65,000 regions showing enhancer function, and pinpoint ~13,000 high-resolution driver elements. These are enriched for regulatory motifs, evolutionarily-conserved nucleotides, and disease-associated genetic variants from genome-wide association studies. Overall, HiDRA provides a high-throughput, high-resolution approach for dissecting regulatory regions and driver nucleotides.

Millions of enhancers are predicted, but their validation remains challenging. Here, the authors report genome-wide enhancer function quantification and high-resolution dissection for millions of accessible DNA fragments, revealing driver nucleotides and helping interpret non-coding disease variants.

Enhancer and super-enhancer: Positive regulators in gene transcription

Enhancer is a positive regulator for spatiotemporal development in eukaryotes. As a cluster, super-enhancer is closely related to cell identity- and fate-determined processes. Both of them function tightly depending on their targeted transcription factors, cofactors, and genes through distal genomic interactions. They have been recognized as critical components and played positive roles in transcriptional regulatory network or factory. Recent advances of next-generation sequencing have dramatically expanded our ability and knowledge to interrogate the molecular mechanism of enhancer and super-enhancer for transcription. Here, we review the history, importance, advances and challenges on enhancer and super-enhancer field. This will benefit our understanding of their function mechanism for transcription underlying precise gene expression.

Functional Dissection of the Enhancer Repertoire in Human Embryonic Stem Cells

Enhancers are genetic elements that regulate spatiotemporal gene expression. Enhancer function requires transcription factor (TF) binding and correlates with histone modifications. However, the extent to which TF binding and histone modifications functionally define active enhancers remains unclear. Here, we combine chromatin immunoprecipitation with a massively parallel reporter assay (ChIP-STARR-seq) to identify functional enhancers in human embryonic stem cells (ESCs) genome-wide in a quantitative unbiased manner. Although active enhancers associate with TFs, only a minority of regions marked by NANOG, OCT4, H3K27ac, and H3K4me1 function as enhancers, with activity markedly changing under naive versus primed culture conditions. We identify an enhancer set associated with functions extending to non-ESC-specific processes. Moreover, although transposable elements associate with putative enhancers, only some exhibit activity. Similarly, within super-enhancers, large tracts are non-functional, with activity restricted to small sub-domains. This catalog of validated enhancers provides a valuable resource for further functional dissection of the regulatory genome.

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Massively parallel reporter assay assessed over 350,000 genome regions

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ChIP-STARR-seq catalogs functional enhancers in primed and naive hESCs

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Identification of transcription factors and transposable elements linked to enhancers

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ChIP-STARR-seq dissects super-enhancers into small functional units

High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing

Functional characterization of disease-causing variants at risk loci has been a significant challenge. Here we report a high-throughput single-nucleotide polymorphisms sequencing (SNPs-seq) technology to simultaneously screen hundreds to thousands of SNPs for their allele-dependent protein-binding differences. This technology takes advantage of higher retention rate of protein-bound DNA oligos in protein purification column to quantitatively sequence these SNP-containing oligos. We apply this technology to test prostate cancer-risk loci and observe differential allelic protein binding in a significant number of selected SNPs. We also test a unique application of self-transcribing active regulatory region sequencing (STARR-seq) in characterizing allele-dependent transcriptional regulation and provide detailed functional analysis at two risk loci (RGS17 and ASCL2). Together, we introduce a powerful high-throughput pipeline for large-scale screening of functional SNPs at disease risk loci.

Functional characterization of disease-causing variants at risk loci in cancer is challenging. Here, in prostate cancer the authors report a pipeline for high-throughput single-nucleotide polymorphisms sequencing (SNPs-seq) for large scale screening of functional SNPs at disease risk loci.

Enhancer Logic and Mechanics in Development and Disease

Enhancers are distally located genomic cis-regulatory elements that integrate spatiotemporal cues to coordinate gene expression in a tissue-specific manner during metazoan development. Enhancer function depends on a combination of bound transcription factors and cofactors that regulate local chromatin structure, as well as on the topological interactions that are necessary for their activity. Numerous genome-wide studies concur that the vast majority of disease-associated variations occur within non-coding genomic sequences, in other words the 'cis-regulome', and this underscores their relevance for human health. Advances in DNA sequencing and genome-editing technologies have dramatically expanded our ability to identify enhancers and investigate their properties in vivo, revealing an extraordinary level of interconnectivity underlying cis-regulatory networks. We discuss here these recently developed methodologies, as well as emerging trends and remaining questions in the field of enhancer biology, and how perturbation of enhancer activities/functions results in enhanceropathies.

Integrative Approaches to Understanding the Pathogenic Role of Genetic Variation in Rheumatic Diseases

The use of high-throughput omics may help to understand the contribution of genetic variants to the pathogenesis of rheumatic diseases. We discuss the concept of missing heritability: that genetic variants do not explain the heritability of rheumatoid arthritis and related rheumatologic conditions. In addition to an overview of how integrative data analysis can lead to novel insights into mechanisms of rheumatic diseases, we describe statistical approaches to prioritizing genetic variants for future functional analyses. We illustrate how analyses of large datasets provide hope for improved approaches to the diagnosis, treatment, and prevention of rheumatic diseases.

Widespread Enhancer Activity from Core Promoters

Gene expression in higher eukaryotes is precisely regulated in time and space through the interplay between promoters and gene-distal regulatory regions, known as enhancers. The original definition of enhancers implies the ability to activate gene expression remotely, while promoters entail the capability to locally induce gene expression. Despite the conventional distinction between them, promoters and enhancers share many genomic and epigenomic features. One intriguing finding in the gene regulation field comes from the observation that many core promoter regions display enhancer activity. Recent high-throughput reporter assays along with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-related approaches have indicated that this phenomenon is common and might have a strong impact on our global understanding of genome organisation and gene expression regulation.

Assessing sufficiency and necessity of enhancer activities for gene expression and the mechanisms of transcription activation

Enhancers are important genomic regulatory elements directing cell type-specific transcription. They assume a key role during development and disease, and their identification and functional characterization have long been the focus of scientific interest. The advent of next-generation sequencing and clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9-based genome editing has revolutionized the means by which we study enhancer biology. In this review, we cover recent developments in the prediction of enhancers based on chromatin characteristics and their identification by functional reporter assays and endogenous DNA perturbations. We discuss that the two latter approaches provide different and complementary insights, especially in assessing enhancer sufficiency and necessity for transcription activation. Furthermore, we discuss recent insights into mechanistic aspects of enhancer function, including findings about cofactor requirements and the role of post-translational histone modifications such as monomethylation of histone H3 Lys4 (H3K4me1). Finally, we survey how these approaches advance our understanding of transcription regulation with respect to promoter specificity and transcriptional bursting and provide an outlook covering open questions and promising developments.

Mammalian Synthetic Biology: Engineering Biological Systems

The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

Functional assessment of human enhancer activities using whole-genome STARR-sequencing

BACKGROUND

Genome-wide quantification of enhancer activity in the human genome has proven to be a challenging problem. Recent efforts have led to the development of powerful tools for enhancer quantification. However, because of genome size and complexity, these tools have yet to be applied to the whole human genome.

RESULTS

 In the current study, we use a human prostate cancer cell line, LNCaP as a model to perform whole human genome STARR-seq (WHG-STARR-seq) to reliably obtain an assessment of enhancer activity. This approach builds upon previously developed STARR-seq in the fly genome and CapSTARR-seq techniques in targeted human genomic regions. With an improved library preparation strategy, our approach greatly increases the library complexity per unit of starting material, which makes it feasible and cost-effective to explore the landscape of regulatory activity in the much larger human genome. In addition to our ability to identify active, accessible enhancers located in open chromatin regions, we can also detect sequences with the potential for enhancer activity that are located in inaccessible, closed chromatin regions. When treated with the histone deacetylase inhibitor, Trichostatin A, genes nearby this latter class of enhancers are up-regulated, demonstrating the potential for endogenous functionality of these regulatory elements.

CONCLUSION

WHG-STARR-seq provides an improved approach to current pipelines for analysis of high complexity genomes to gain a better understanding of the intricacies of transcriptional regulation.

Functional assessment of human enhancer activities using whole-genome STARR-sequencing

Background

Genome-wide quantification of enhancer activity in the human genome has proven to be a challenging problem. Recent efforts have led to the development of powerful tools for enhancer quantification. However, because of genome size and complexity, these tools have yet to be applied to the whole human genome.

Results

 In the current study, we use a human prostate cancer cell line, LNCaP as a model to perform whole human genome STARR-seq (WHG-STARR-seq) to reliably obtain an assessment of enhancer activity. This approach builds upon previously developed STARR-seq in the fly genome and CapSTARR-seq techniques in targeted human genomic regions. With an improved library preparation strategy, our approach greatly increases the library complexity per unit of starting material, which makes it feasible and cost-effective to explore the landscape of regulatory activity in the much larger human genome. In addition to our ability to identify active, accessible enhancers located in open chromatin regions, we can also detect sequences with the potential for enhancer activity that are located in inaccessible, closed chromatin regions. When treated with the histone deacetylase inhibitor, Trichostatin A, genes nearby this latter class of enhancers are up-regulated, demonstrating the potential for endogenous functionality of these regulatory elements.

Conclusion

WHG-STARR-seq provides an improved approach to current pipelines for analysis of high complexity genomes to gain a better understanding of the intricacies of transcriptional regulation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1345-5) contains supplementary material, which is available to authorized users.

Recent advances in high-throughput approaches to dissect enhancer function

The regulation of gene transcription in higher eukaryotes is accomplished through the involvement of transcription start site (TSS)-proximal (promoters) and -distal (enhancers) regulatory elements. It is now well acknowledged that enhancer elements play an essential role during development and cell differentiation, while genetic alterations in these elements are a major cause of human disease. Many strategies have been developed to identify and characterize enhancers. Here, we discuss recent advances in high-throughput approaches to assess enhancer activity, from the well-established massively parallel reporter assays to the recent clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-based technologies. We highlight how these approaches contribute toward a better understanding of enhancer function, eventually leading to the discovery of new types of regulatory sequences, and how the alteration of enhancers can affect transcriptional regulation.

Orphan CpG islands define a novel class of highly active enhancers

CpG islands (CGI) are critical genomic regulatory elements that support transcriptional initiation and are associated with the promoters of most human genes. CGI are distinguished from the bulk genome by their high CpG density, lack of DNA methylation, and euchromatic features. While CGI are canonically known as strong promoters, thousands of 'orphan' CGI lie far from any known transcript, leaving their function an open question. We undertook a comprehensive analysis of the epigenetic state of orphan CGI across over 100 cell types. Here we show that most orphan CGI display the chromatin features of active enhancers (H3K4me1, H3K27Ac) in at least one cell type. Relative to classical enhancers, these enhancer CGI (ECGI) are stronger, as gauged by chromatin state and in functional assays, are more broadly expressed, and are more highly conserved. Likewise, ECGI engage in more genomic contacts and are enriched for transcription factor binding relative to classical enhancers. In human cancers, these epigenetic differences between ECGI vs. classical enhancers manifest in distinct alterations in DNA methylation. Thus, ECGI define a class of highly active enhancers, strengthened by the broad transcriptional activity, CpG density, hypomethylation, and chromatin features they share with promoter CGI. In addition to indicating a role for thousands of orphan CGI, these findings suggests that enhancer activity may be an intrinsic function of CGI in general and provides new insights into the evolution of enhancers and their epigenetic regulation during development and tumorigenesis.

Gene Regulatory Elements, Major Drivers of Human Disease

Gene expression changes, the driving forces for cellular diversity in multicellular organisms, are regulated by a diverse set of gene regulatory elements that direct transcription in specific cells. Mutations in these elements, ranging from chromosomal aberrations to single-nucleotide polymorphisms, are a major cause of human disease. However, we currently have a very limited understanding of how regulatory element genotypes lead to specific phenotypes. In this review, we discuss the various methods of regulatory element identification, the different types of mutations they harbor, and their impact on human disease. We highlight how these variations can affect transcription of multiple genes in gene regulatory networks. In addition, we describe how novel technologies, such as massively parallel reporter assays and CRISPR/Cas9 genome editing, are beginning to provide a better understanding of the functional roles that these elements have and how their alteration can lead to specific phenotypes.

A genome-integrated massively parallel reporter assay reveals DNA sequence determinants of cis-regulatory activity in neural cells

Recent large-scale genomics efforts to characterize the cis-regulatory sequences that orchestrate genome-wide expression patterns have produced impressive catalogues of putative regulatory elements. Most of these sequences have not been functionally tested, and our limited understanding of the non-coding genome prevents us from predicting which sequences are bona fide cis-regulatory elements. Recently, massively parallel reporter assays (MPRAs) have been deployed to measure the activity of putative cis-regulatory sequences in several biological contexts, each with specific advantages and distinct limitations. We developed LV-MPRA, a novel lentiviral-based, massively parallel reporter gene assay, to study the function of genome-integrated regulatory elements in any mammalian cell type; thus, making it possible to apply MPRAs in more biologically relevant contexts. We measured the activity of 2,600 sequences in U87 glioblastoma cells and human neural progenitor cells (hNPCs) and explored how regulatory activity is encoded in DNA sequence. We demonstrate that LV-MPRA can be applied to estimate the effects of local DNA sequence and regional chromatin on regulatory activity. Our data reveal that primary DNA sequence features, such as GC content and dinucleotide composition, accurately distinguish sequences with high activity from sequences with low activity in a full chromosomal context, and may also function in combination with different transcription factor binding sites to determine cell type specificity. We conclude that LV-MPRA will be an important tool for identifying cis-regulatory elements and stimulating new understanding about how the non-coding genome encodes information.

Decoding transcriptional states in cancer

Gene regulatory networks determine cellular identity. In cancer, aberrations of gene networks are caused by driver mutations that often affect transcription factors and chromatin modifiers. Nevertheless, gene transcription in cancer follows the same cis-regulatory rules as normal cells, and cancer cells have served as convenient model systems to study transcriptional regulation. Tumours often show regulatory heterogeneity, with subpopulations of cells in different transcriptional states, which has important therapeutic implications. Here, we review recent experimental and computational techniques to reverse engineer cancer gene networks using transcriptome and epigenome data. New algorithms, data integration strategies, and increasing amounts of single cell genomics data provide exciting opportunities to model dynamic regulatory states at unprecedented resolution.

[High-throughput approaches to study cis-regulating elements]

Gene expression in higher eukaryotes is regulated through the involvement of transcription start site (TSS)-proximal (promoters) and -distal (enhancers) regulatory elements. Enhancer elements play an essential role during development and cell differentiation, while genetic alterations in these elements are a major cause of human disease. Here, we discuss recent advances in high-throughput approaches to identify and characterize enhancer elements, from the well-established massively parallel reporter assays to the recent clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-based technologies. We discuss how these approaches contribute toward a better understanding of enhancer function in normal and pathological conditions.

Genome-wide mapping of autonomous promoter activity in human cells

Previous methods to systematically characterize sequence-intrinsic activity of promoters have been limited by relatively low throughput and the length of the sequences that could be tested. Here we present 'survey of regulatory elements' (SuRE), a method that assays more than 10⁸ DNA fragments, each 0.2-2 kb in size, for their ability to drive transcription autonomously. In SuRE, a plasmid library of random genomic fragments upstream of a 20-bp barcode is constructed, and decoded by paired-end sequencing. This library is used to transfect cells, and barcodes in transcribed RNA are quantified by high-throughput sequencing. When applied to the human genome, we achieve 55-fold genome coverage, allowing us to map autonomous promoter activity genome-wide in K562 cells. By computational modeling we delineate subregions within promoters that are relevant for their activity. We show that antisense promoter transcription is generally dependent on the sense core promoter sequences, and that most enhancers and several families of repetitive elements act as autonomous transcription initiation sites.

Enhancers and super-enhancers have an equivalent regulatory role in embryonic stem cells through regulation of single or multiple genes

Transcriptional enhancers are critical for maintaining cell-type-specific gene expression and driving cell fate changes during development. Highly transcribed genes are often associated with a cluster of individual enhancers such as those found in locus control regions. Recently, these have been termed stretch enhancers or super-enhancers, which have been predicted to regulate critical cell identity genes. We employed a CRISPR/Cas9-mediated deletion approach to study the function of several enhancer clusters (ECs) and isolated enhancers in mouse embryonic stem (ES) cells. Our results reveal that the effect of deleting ECs, also classified as ES cell super-enhancers, is highly variable, resulting in target gene expression reductions ranging from 12% to as much as 92%. Partial deletions of these ECs which removed only one enhancer or a subcluster of enhancers revealed partially redundant control of the regulated gene by multiple enhancers within the larger cluster. Many highly transcribed genes in ES cells are not associated with a super-enhancer; furthermore, super-enhancer predictions ignore 81% of the potentially active regulatory elements predicted by cobinding of five or more pluripotency-associated transcription factors. Deletion of these additional enhancer regions revealed their robust regulatory role in gene transcription. In addition, select super-enhancers and enhancers were identified that regulated clusters of paralogous genes. We conclude that, whereas robust transcriptional output can be achieved by an isolated enhancer, clusters of enhancers acting on a common target gene act in a partially redundant manner to fine tune transcriptional output of their target genes.

Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

A systematic comparison reveals substantial differences in chromosomal versus episomal encoding of enhancer activity

Candidate enhancers can be identified on the basis of chromatin modifications, the binding of chromatin modifiers and transcription factors and cofactors, or chromatin accessibility. However, validating such candidates as bona fide enhancers requires functional characterization, typically achieved through reporter assays that test whether a sequence can increase expression of a transcriptional reporter via a minimal promoter. A longstanding concern is that reporter assays are mainly implemented on episomes, which are thought to lack physiological chromatin. However, the magnitude and determinants of differences in cis-regulation for regulatory sequences residing in episomes versus chromosomes remain almost completely unknown. To address this systematically, we developed and applied a novel lentivirus-based massively parallel reporter assay (lentiMPRA) to directly compare the functional activities of 2236 candidate liver enhancers in an episomal versus a chromosomally integrated context. We find that the activities of chromosomally integrated sequences are substantially different from the activities of the identical sequences assayed on episomes, and furthermore are correlated with different subsets of ENCODE annotations. The results of chromosomally based reporter assays are also more reproducible and more strongly predictable by both ENCODE annotations and sequence-based models. With a linear model that combines chromatin annotations and sequence information, we achieve a Pearson's R² of 0.362 for predicting the results of chromosomally integrated reporter assays. This level of prediction is better than with either chromatin annotations or sequence information alone and also outperforms predictive models of episomal assays. Our results have broad implications for how cis-regulatory elements are identified, prioritized and functionally validated.

Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions

Massively parallel reporter assays (MPRAs) enable nucleotide-resolution dissection of transcriptional regulatory regions, such as enhancers, but only few regions at a time. Here we present a combined experimental and computational approach, Systematic high-resolution activation and repression profiling with reporter tiling using MPRA (Sharpr-MPRA), that allows high-resolution analysis of thousands of regions simultaneously. Sharpr-MPRA combines dense tiling of overlapping MPRA constructs with a probabilistic graphical model to recognize functional regulatory nucleotides, and to distinguish activating and repressive nucleotides, using their inferred contribution to reporter gene expression. We used Sharpr-MPRA to test 4.6 million nucleotides spanning 15,000 putative regulatory regions tiled at 5-nucleotide resolution in two human cell types. Our results recovered known cell-type-specific regulatory motifs and evolutionarily conserved nucleotides, and distinguished known activating and repressive motifs. Our results also showed that endogenous chromatin state and DNA accessibility are both predictive of regulatory function in reporter assays, identified retroviral elements with activating roles, and uncovered 'attenuator' motifs with repressive roles in active chromatin.

Understanding the genetic liability to schizophrenia through the neuroepigenome

The Psychiatric Genomics Consortium-Schizophrenia Workgroup (PGC-SCZ) recently identified 108 loci associated with increased risk for schizophrenia (SCZ). The vast majority of these variants reside within non-coding sequences of the genome and are predicted to exert their effects by affecting the mechanism of action of cis regulatory elements (CREs), such as promoters and enhancers. Although a number of large-scale collaborative efforts (e.g. ENCODE) have achieved a comprehensive mapping of CREs in human cell lines or tissue homogenates, it is becoming increasingly evident that many risk-associated variants are enriched for expression Quantitative Trait Loci (eQTLs) and CREs in specific tissues or cells. As such, data derived from previous research endeavors may not capture fully cell-type and/or region specific changes associated with brain diseases. Coupling recent technological advances in genomics with cell-type specific methodologies, we are presented with an unprecedented opportunity to better understand the genetics of normal brain development and function and, in turn, the molecular basis of neuropsychiatric disorders. In this review, we will outline ongoing efforts towards this goal and will discuss approaches with the potential to shed light on the mechanism(s) of action of cell-type specific cis regulatory elements and their putative roles in disease, with particular emphasis on understanding the manner in which the epigenome and CREs influence the etiology of SCZ.