Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position

A novel method for predicting activity of cis-regulatory modules, based on a diverse training set

MOTIVATION

With the rapid emergence of technologies for locating cis-regulatory modules (CRMs) genome-wide, the next pressing challenge is to assign precise functions to each CRM, i.e. to determine the spatiotemporal domains or cell-types where it drives expression. A popular approach to this task is to model the typical k-mer composition of a set of CRMs known to drive a common expression pattern, and assign that pattern to other CRMs exhibiting a similar k-mer composition. This approach does not rely on prior knowledge of transcription factors relevant to the CRM or their binding motifs, and is thus more widely applicable than motif-based methods for predicting CRM activity, but is also prone to false positive predictions.

RESULTS

We present a novel strategy to improve the above-mentioned approach: to predict if a CRM drives a specific gene expression pattern, assess not only how similar the CRM is to other CRMs with similar activity but also to CRMs with distinct activities. We use a state-of-the-art statistical method to quantify a CRM's sequence similarity to many different training sets of CRMs, and employ a classification algorithm to integrate these similarity scores into a single prediction of the CRM's activity. This strategy is shown to significantly improve CRM activity prediction over current approaches.

AVAILABILITY AND IMPLEMENTATION

Our implementation of the new method, called IMMBoost, is freely available as source code, at https://github.com/weiyangedward/IMMBoost CONTACT: sinhas@illinois.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Authentication and characterisation of a new oesophageal adenocarcinoma cell line: MFD-1

New biological tools are required to understand the functional significance of genetic events revealed by whole genome sequencing (WGS) studies in oesophageal adenocarcinoma (OAC). The MFD-1 cell line was isolated from a 55-year-old male with OAC without recombinant-DNA transformation. Somatic genetic variations from MFD-1, tumour, normal oesophagus, and leucocytes were analysed with SNP6. WGS was performed in tumour and leucocytes. RNAseq was performed in MFD-1, and two classic OAC cell lines FLO1 and OE33. Transposase-accessible chromatin sequencing (ATAC-seq) was performed in MFD-1, OE33, and non-neoplastic HET1A cells. Functional studies were performed. MFD-1 had a high SNP genotype concordance with matched germline/tumour. Parental tumour and MFD-1 carried four somatically acquired mutations in three recurrent mutated genes in OAC: TP53, ABCB1 and SEMA5A, not present in FLO-1 or OE33. MFD-1 displayed high expression of epithelial and glandular markers and a unique fingerprint of open chromatin. MFD-1 was tumorigenic in SCID mouse and proliferative and invasive in 3D cultures. The clinical utility of whole genome sequencing projects will be delivered using accurate model systems to develop molecular-phenotype therapeutics. We have described the first such system to arise from the oesophageal International Cancer Genome Consortium project.

Conserved Noncoding Elements in the Most Distant Genera of Cephalochordates: The Goldilocks Principle

Cephalochordates, the sister group of vertebrates + tunicates, are evolving particularly slowly. Therefore, genome comparisons between two congeners of Branchiostoma revealed so many conserved noncoding elements (CNEs), that it was not clear how many are functional regulatory elements. To more effectively identify CNEs with potential regulatory functions, we compared noncoding sequences of genomes of the most phylogenetically distant cephalochordate genera, Asymmetron and Branchiostoma, which diverged approximately 120-160 million years ago. We found 113,070 noncoding elements conserved between the two species, amounting to 3.3% of the genome. The genomic distribution, target gene ontology, and enriched motifs of these CNEs all suggest that many of them are probably cis-regulatory elements. More than 90% of previously verified amphioxus regulatory elements were re-captured in this study. A search of the cephalochordate CNEs around 50 developmental genes in several vertebrate genomes revealed eight CNEs conserved between cephalochordates and vertebrates, indicating sequence conservation over >500 million years of divergence. The function of five CNEs was tested in reporter assays in zebrafish, and one was also tested in amphioxus. All five CNEs proved to be tissue-specific enhancers. Taken together, these findings indicate that even though Branchiostoma and Asymmetron are distantly related, as they are evolving slowly, comparisons between them are likely optimal for identifying most of their tissue-specific cis-regulatory elements laying the foundation for functional characterizations and a better understanding of the evolution of developmental regulation in cephalochordates.

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Population and family-based genetic studies typically result in the identification of genetic variants that are statistically associated with a clinical disease or phenotype. For many diseases and traits, most variants are non-coding, and are thus likely to act by impacting subtle, comparatively hard to predict mechanisms controlling gene expression. Here, we describe a general strategic approach to prioritize non-coding variants, and screen them for their function. This approach involves computational prioritization using functional genomic databases followed by experimental analysis of differential binding of transcription factors (TFs) to risk and non-risk alleles. For both electrophoretic mobility shift assay (EMSA) and DNA affinity precipitation assay (DAPA) analysis of genetic variants, a synthetic DNA oligonucleotide (oligo) is used to identify factors in the nuclear lysate of disease or phenotype-relevant cells. For EMSA, the oligonucleotides with or without bound nuclear factors (often TFs) are analyzed by non-denaturing electrophoresis on a tris-borate-EDTA (TBE) polyacrylamide gel. For DAPA, the oligonucleotides are bound to a magnetic column and the nuclear factors that specifically bind the DNA sequence are eluted and analyzed through mass spectrometry or with a reducing sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) followed by Western blot analysis. This general approach can be widely used to study the function of non-coding genetic variants associated with any disease, trait, or phenotype.

The Spectrum and Regulatory Landscape of Intestinal Innate Lymphoid Cells Are Shaped by the Microbiome

Innate lymphoid cells (ILCs) are critical modulators of mucosal immunity, inflammation, and tissue homeostasis, but their full spectrum of cellular states and regulatory landscapes remains elusive. Here, we combine genome-wide RNA-seq, ChIP-seq, and ATAC-seq to compare the transcriptional and epigenetic identity of small intestinal ILCs, identifying thousands of distinct gene profiles and regulatory elements. Single-cell RNA-seq and flow and mass cytometry analyses reveal compartmentalization of cytokine expression and metabolic activity within the three classical ILC subtypes and highlight transcriptional states beyond the current canonical classification. In addition, using antibiotic intervention and germ-free mice, we characterize the effect of the microbiome on the ILC regulatory landscape and determine the response of ILCs to microbial colonization at the single-cell level. Together, our work characterizes the spectrum of transcriptional identities of small intestinal ILCs and describes how ILCs differentially integrate signals from the microbial microenvironment to generate phenotypic and functional plasticity.

Network pharmacology of JAK inhibitors

Small-molecule inhibitors of the Janus kinase family (JAKis) are clinically efficacious in multiple autoimmune diseases, albeit with increased risk of certain infections. Their precise mechanism of action is unclear, with JAKs being signaling hubs for several cytokines. We assessed the in vivo impact of pan- and isoform-specific JAKi in mice by immunologic and genomic profiling. Effects were broad across the immunogenomic network, with overlap between inhibitors. Natural killer (NK) cell and macrophage homeostasis were most immediately perturbed, with network-level analysis revealing a rewiring of coregulated modules of NK cell transcripts. The repression of IFN signature genes after repeated JAKi treatment continued even after drug clearance, with persistent changes in chromatin accessibility and phospho-STAT responsiveness to IFN. Thus, clinical use and future development of JAKi might need to balance effects on immunological networks, rather than expect that JAKis affect a particular cytokine response and be cued to long-lasting epigenomic modifications rather than by short-term pharmacokinetics.

Mutant IDH1 Downregulates ATM and Alters DNA Repair and Sensitivity to DNA Damage Independent of TET2

Mutations in the isocitrate dehydrogenase-1 gene (IDH1) are common drivers of acute myeloid leukemia (AML) but their mechanism is not fully understood. It is thought that IDH1 mutants act by inhibiting TET2 to alter DNA methylation, but there are significant unexplained clinical differences between IDH1- and TET2-mutant diseases. We have discovered that mice expressing endogenous mutant IDH1 have reduced numbers of hematopoietic stem cells (HSCs), in contrast to Tet2 knockout (TET2-KO) mice. Mutant IDH1 downregulates the DNA damage (DD) sensor ATM by altering histone methylation, leading to impaired DNA repair, increased sensitivity to DD, and reduced HSC self-renewal, independent of TET2. ATM expression is also decreased in human IDH1-mutated AML. These findings may have implications for treatment of IDH-mutant leukemia.

Memory of Inflammation in Regulatory T Cells

Eukaryotic cells can "remember" transient encounters with a wide range of stimuli, inducing lasting states of altered responsiveness. Regulatory T (Treg) cells are a specialized lineage of suppressive CD4 T cells that act as critical negative regulators of inflammation in various biological contexts. Treg cells exposed to inflammatory conditions acquire strongly enhanced suppressive function. Using inducible genetic tracing, we analyzed the long-term stability of activation-induced transcriptional, epigenomic, and functional changes in Treg cells. We found that the inflammation-experienced Treg cell population reversed many activation-induced changes and lost its enhanced suppressive function over time. The "memory-less" potentiation of Treg suppressor function may help avoid a state of generalized immunosuppression that could otherwise result from repeated activation.

The Transcriptional Repressor Polycomb Group Factor 6, PCGF6, Negatively Regulates Dendritic Cell Activation and Promotes Quiescence

Pro-inflammatory signals provided by the microenvironment are critical to activate dendritic cells (DCs), components of the innate immune system that shape both innate and adaptive immunity. However, to prevent inappropriate immune activation, mechanisms must be in place to restrain DC activation to ensure DCs are activated only once sufficient stimuli have been received. Here, we report that DC activation and immunogenicity are regulated by the transcriptional repressor Polycomb group factor 6 (PCGF6). Pcgf6 is rapidly downregulated upon stimulation, and this downregulation is necessary to permit full DC activation. Silencing PCGF6 expression enhanced both spontaneous and stimulated DC activation. We show that PCGF6 associates with the H3K4me3 demethylase JARID1c, and together, they negatively regulate H3K4me3 levels in DCs. Our results identify two key regulators, PCGF6 and JARID1c that temper DC activation and implicate active transcriptional silencing via histone demethylation as a previously unappreciated mechanism for regulating DC activation and quiescence.

Genetic dissection of the α-globin super-enhancer in vivo

Many genes determining cell identity are regulated by clusters of Mediator-bound enhancer elements collectively referred to as super-enhancers. These super-enhancers have been proposed to manifest higher-order properties important in development and disease. Here we report a comprehensive functional dissection of one of the strongest putative super-enhancers in erythroid cells. By generating a series of mouse models, deleting each of the five regulatory elements of the α-globin super-enhancer individually and in informative combinations, we demonstrate that each constituent enhancer seems to act independently and in an additive fashion with respect to hematological phenotype, gene expression, chromatin structure and chromosome conformation, without clear evidence of synergistic or higher-order effects. Our study highlights the importance of functional genetic analyses for the identification of new concepts in transcriptional regulation.

A Highly Sensitive and Robust Method for Genome-wide 5hmC Profiling of Rare Cell Populations

We present a highly sensitive and selective chemical labeling and capture approach for genome-wide profiling of 5-hydroxylmethylcytosine (5hmC) using DNA isolated from ∼1,000 cells (nano-hmC-Seal). Using this technology, we assessed 5hmC occupancy and dynamics across different stages of hematopoietic differentiation. Nano-hmC-Seal profiling of purified Tet2-mutant acute myeloid leukemia (AML) murine stem cells allowed us to identify leukemia-specific, differentially hydroxymethylated regions that harbor known and candidate disease-specific target genes with differential 5hmC peaks compared to normal stem cells. The change of 5hmC patterns in AML strongly correlates with differential gene expression, demonstrating the importance of dynamic alterations of 5hmC in regulating transcription in AML. Together, covalent 5hmC labeling offers an effective approach to study and detect DNA methylation dynamics in in vivo disease models and in limited clinical samples.

Epigenetic Variation between Human Induced Pluripotent Stem Cell Lines Is an Indicator of Differentiation Capacity

Variation in the differentiation capacity of induced pluripotent stem cells (iPSCs) to specific lineages is a significant concern for their use in clinical applications and disease modeling. To identify factors that affect differentiation capacity, we performed integration analyses between hematopoietic differentiation performance and molecular signatures such as gene expression, DNA methylation, and chromatin status, using 35 human iPSC lines and four ESC lines. Our analyses revealed that hematopoietic commitment of PSCs to hematopoietic precursors correlates with IGF2 expression level, which in turn depends on signaling-dependent chromatin accessibility at mesendodermal genes. Maturation capacity for conversion of PSC-derived hematopoietic precursors to mature blood associates with the amount and pattern of DNA methylation acquired during reprogramming. Our study therefore provides insight into the molecular features that determine the differential capacities seen among human iPSC lines and, through the predictive potential of this information, highlights a way to select optimal iPSCs for clinical applications.

Structural organization of the inactive X chromosome in the mouse

X-chromosome inactivation (XCI) involves major reorganization of the X chromosome as it becomes silent and heterochromatic. During female mammalian development, XCI is triggered by upregulation of the non-coding Xist RNA from one of the two X chromosomes. Xist coats the chromosome in cis and induces silencing of almost all genes via its A-repeat region, although some genes (constitutive escapees) avoid silencing in most cell types, and others (facultative escapees) escape XCI only in specific contexts. A role for Xist in organizing the inactive X (Xi) chromosome has been proposed. Recent chromosome conformation capture approaches have revealed global loss of local structure on the Xi chromosome and formation of large mega-domains, separated by a region containing the DXZ4 macrosatellite. However, the molecular architecture of the Xi chromosome, in both the silent and expressed regions,remains unclear. Here we investigate the structure, chromatin accessibility and expression status of the mouse Xi chromosome in highly polymorphic clonal neural progenitors (NPCs) and embryonic stem cells. We demonstrate a crucial role for Xist and the DXZ4-containing boundary in shaping Xi chromosome structure using allele-specific genome-wide chromosome conformation capture (Hi-C) analysis, an assay for transposase-accessible chromatin with high throughput sequencing (ATAC-seq) and RNA sequencing. Deletion of the boundary disrupts mega-domain formation, and induction of Xist RNA initiates formation of the boundary and the loss of DNA accessibility. We also show that in NPCs, the Xi chromosome lacks active/inactive compartments and topologically associating domains (TADs), except around genes that escape XCI. Escapee gene clusters display TAD-like structures and retain DNA accessibility at promoter-proximal and CTCF-binding sites. Furthermore, altered patterns of facultative escape genes indifferent neural progenitor clones are associated with the presence of different TAD-like structures after XCI. These findings suggest a key role for transcription and CTCF in the formation of TADs in the context of the Xi chromosome in neural progenitors.

Modeling cis-regulation with a compendium of genome-wide histone H3K27ac profiles

Model-based analysis of regulation of gene expression (MARGE) is a framework for interpreting the relationship between the H3K27ac chromatin environment and differentially expressed gene sets. The framework has three main functions: MARGE-potential, MARGE-express, and MARGE-cistrome. MARGE-potential defines a regulatory potential (RP) for each gene as the sum of H3K27ac ChIP-seq signals weighted by a function of genomic distance from the transcription start site. The MARGE framework includes a compendium of RPs derived from 365 human and 267 mouse H3K27ac ChIP-seq data sets. Relative RPs, scaled using this compendium, are superior to superenhancers in predicting BET (bromodomain and extraterminal domain) -inhibitor repressed genes. MARGE-express, which uses logistic regression to retrieve relevant H3K27ac profiles from the compendium to accurately model a query set of differentially expressed genes, was tested on 671 diverse gene sets from MSigDB. MARGE-cistrome adopts a novel semisupervised learning approach to identify cis-regulatory elements regulating a gene set. MARGE-cistrome exploits information from H3K27ac signal at DNase I hypersensitive sites identified from published human and mouse DNase-seq data. We tested the framework on newly generated RNA-seq and H3K27ac ChIP-seq profiles upon siRNA silencing of multiple transcriptional and epigenetic regulators in a prostate cancer cell line, LNCaP-abl. MARGE-cistrome can predict the binding sites of silenced transcription factors without matched H3K27ac ChIP-seq data. Even when the matching H3K27ac ChIP-seq profiles are available, MARGE leverages public H3K27ac profiles to enhance these data. This study demonstrates the advantage of integrating a large compendium of historical epigenetic data for genomic studies of transcriptional regulation.

A synergistic DNA logic predicts genome-wide chromatin accessibility

Enhancers and promoters commonly occur in accessible chromatin characterized by depleted nucleosome contact; however, it is unclear how chromatin accessibility is governed. We show that log-additive cis-acting DNA sequence features can predict chromatin accessibility at high spatial resolution. We develop a new type of high-dimensional machine learning model, the Synergistic Chromatin Model (SCM), which when trained with DNase-seq data for a cell type is capable of predicting expected read counts of genome-wide chromatin accessibility at every base from DNA sequence alone, with the highest accuracy at hypersensitive sites shared across cell types. We confirm that a SCM accurately predicts chromatin accessibility for thousands of synthetic DNA sequences using a novel CRISPR-based method of highly efficient site-specific DNA library integration. SCMs are directly interpretable and reveal that a logic based on local, nonspecific synergistic effects, largely among pioneer TFs, is sufficient to predict a large fraction of cellular chromatin accessibility in a wide variety of cell types.

GO-FAANG meeting: a Gathering On Functional Annotation of Animal Genomes

The Functional Annotation of Animal Genomes (FAANG) Consortium recently held a Gathering On FAANG (GO‐FAANG) Workshop in Washington, DC on October 7–8, 2015. This consortium is a grass‐roots organization formed to advance the annotation of newly assembled genomes of domesticated and non‐model organisms (www.faang.org). The workshop gathered together from around the world a group of 100+ genome scientists, administrators, representatives of funding agencies and commodity groups to discuss the latest advancements of the consortium, new perspectives, next steps and implementation plans. The workshop was streamed live and recorded, and all talks, along with speaker slide presentations, are available at www.faang.org. In this report, we describe the major activities and outcomes of this meeting. We also provide updates on ongoing efforts to implement discussions and decisions taken at GO‐FAANG to guide future FAANG activities. In summary, reference datasets are being established under pilot projects; plans for tissue sets, morphological classification and methods of sample collection for different tissues were organized; and core assays and data and meta‐data analysis standards were established.

Identification of multi-loci hubs from 4C-seq demonstrates the functional importance of simultaneous interactions

Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that associations involving regulatory elements act in isolation of other interacting partners that also influence their impact. Indeed, the influence of multi-loci interactions remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise and novel tri-loci interactions involving the Tcrb and Igk antigen receptor enhancers. We further show that the three Igk enhancers, MiEκ, 3′Eκ and Edκ, interact simultaneously in this super-enhancer cluster, which add to our previous findings showing that loss of one element decreases interactions between all three elements as well as reducing their transcriptional output. These findings underscore the functional importance of simultaneous interactions and provide new insight into the relationship between enhancer elements. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings.

RAG1 targeting in the genome is dominated by chromatin interactions mediated by the non-core regions of RAG1 and RAG2

The RAG1/RAG2 endonuclease initiates V(D)J recombination at antigen receptor loci but also binds to thousands of places outside of these loci. RAG2 localizes directly to lysine 4 trimethylated histone 3 (H3K4me3) through a plant homeodomain (PHD) finger. The relative contribution of RAG2-dependent and RAG1-intrinsic mechanisms in determining RAG1 binding patterns is not known. Through analysis of deep RAG1 ChIP-seq data, we provide a quantitative description of the forces underlying genome-wide targeting of RAG1. Surprisingly, sequence-specific DNA binding contributes minimally to RAG1 targeting outside of antigen receptor loci. Instead, RAG1 binding is driven by two distinct modes of interaction with chromatin: the first is driven by H3K4me3, promoter-focused and dependent on the RAG2 PHD, and the second is defined by H3K27Ac, enhancer-focused and dependent on ‘non-core’ portions of RAG1. Based on this and additional chromatin and genomic features, we formulated a predictive model of RAG1 targeting to the genome. RAG1 binding sites predicted by our model correlate well with observed patterns of RAG1-mediated breaks in human pro-B acute lymphoblastic leukemia. Overall, this study provides an integrative model for RAG1 genome-wide binding and off-target activity and reveals a novel role for the RAG1 non-core region in RAG1 targeting.

fluff: exploratory analysis and visualization of high-throughput sequencing data

Summary. In this article we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available at http://fluff.readthedocs.org.

Availability. fluff is implemented in Python and runs on Linux. The source code is freely available for download at https://github.com/simonvh/fluff.

Piwi Modulates Chromatin Accessibility by Regulating Multiple Factors Including Histone H1 to Repress Transposons

PIWI-interacting RNAs (piRNAs) mediate transcriptional and post-transcriptional silencing of transposable element (TE) in animal gonads. In Drosophila ovaries, Piwi-piRNA complexes (Piwi-piRISCs) repress TE transcription by modifying the chromatin state, such as by H3K9 trimethylation. Here, we demonstrate that Piwi physically interacts with linker histone H1. Depletion of Piwi decreases H1 density at a subset of TEs, leading to their derepression. Silencing at these loci separately requires H1 and H3K9me3 and heterochromatin protein 1a (HP1a). Loss of H1 increases target loci chromatin accessibility without affecting H3K9me3 density at these loci, while loss of HP1a does not impact H1 density. Thus, Piwi-piRISCs require both H1 and HP1a to repress TEs, and the silencing is correlated with the chromatin state rather than H3K9me3 marks. These findings suggest that Piwi-piRISCs regulate the interaction of chromatin components with target loci to maintain silencing of TEs through the modulation of chromatin accessibility.

Nfib Promotes Metastasis through a Widespread Increase in Chromatin Accessibility

Metastases are the main cause of cancer deaths, but the mechanisms underlying metastatic progression remain poorly understood. We isolated pure populations of cancer cells from primary tumors and metastases from a genetically engineered mouse model of human small cell lung cancer (SCLC) to investigate the mechanisms that drive the metastatic spread of this lethal cancer. Genome-wide characterization of chromatin accessibility revealed the opening of large numbers of distal regulatory elements across the genome during metastatic progression. These changes correlate with copy number amplification of the Nfib locus, and differentially accessible sites were highly enriched for Nfib transcription factor binding sites. Nfib is necessary and sufficient to increase chromatin accessibility at a large subset of the intergenic regions. Nfib promotes pro-metastatic neuronal gene expression programs and drives the metastatic ability of SCLC cells. The identification of widespread chromatin changes during SCLC progression reveals an unexpected global reprogramming during metastatic progression.

Leukaemia cell of origin identified by chromatin landscape of bulk tumour cells

The precise identity of a tumour's cell of origin can influence disease prognosis and outcome. Methods to reliably define tumour cell of origin from primary, bulk tumour cell samples has been a challenge. Here we use a well-defined model of MLL-rearranged acute myeloid leukaemia (AML) to demonstrate that transforming haematopoietic stem cells (HSCs) and multipotent progenitors results in more aggressive AML than transforming committed progenitor cells. Transcriptome profiling reveals a gene expression signature broadly distinguishing stem cell-derived versus progenitor cell-derived AML, including genes involved in immune escape, extravasation and small GTPase signal transduction. However, whole-genome profiling of open chromatin reveals precise and robust biomarkers reflecting each cell of origin tested, from bulk AML tumour cell sampling. We find that bulk AML tumour cells exhibit distinct open chromatin loci that reflect the transformed cell of origin and suggest that open chromatin patterns may be leveraged as prognostic signatures in human AML.

A tumour's cell of origin may influence tumour progression and response to therapy. Here, the authors demonstrate that the cell of origin determines the aggressiveness of AML in a mouse model and identify unique biomarkers of the specific leukaemia cell of origin by profiling open chromatin regions of AML samples.

Genomic approaches for understanding the genetics of complex disease

There are thousands of known associations between genetic variants and complex human phenotypes, and the rate of novel discoveries is rapidly increasing. Translating those associations into knowledge of disease mechanisms remains a fundamental challenge because the associated variants are overwhelmingly in noncoding regions of the genome where we have few guiding principles to predict their function. Intersecting the compendium of identified genetic associations with maps of regulatory activity across the human genome has revealed that phenotype-associated variants are highly enriched in candidate regulatory elements. Allele-specific analyses of gene regulation can further prioritize variants that likely have a functional effect on disease mechanisms; and emerging high-throughput assays to quantify the activity of candidate regulatory elements are a promising next step in that direction. Together, these technologies have created the ability to systematically and empirically test hypotheses about the function of noncoding variants and haplotypes at the scale needed for comprehensive and systematic follow-up of genetic association studies. Major coordinated efforts to quantify regulatory mechanisms across genetically diverse populations in increasingly realistic cell models would be highly beneficial to realize that potential.

Defining cell types and states with single-cell genomics

A revolution in cellular measurement technology is under way: For the first time, we have the ability to monitor global gene regulation in thousands of individual cells in a single experiment. Such experiments will allow us to discover new cell types and states and trace their developmental origins. They overcome fundamental limitations inherent in measurements of bulk cell population that have frustrated efforts to resolve cellular states. Single-cell genomics and proteomics enable not only precise characterization of cell state, but also provide a stunningly high-resolution view of transitions between states. These measurements may finally make explicit the metaphor that C.H. Waddington posed nearly 60 years ago to explain cellular plasticity: Cells are residents of a vast “landscape” of possible states, over which they travel during development and in disease. Single-cell technology helps not only locate cells on this landscape, but illuminates the molecular mechanisms that shape the landscape itself. However, single-cell genomics is a field in its infancy, with many experimental and computational advances needed to fully realize its full potential.

Epigenomics and the structure of the living genome

Eukaryotic genomes are packaged into an extensively folded state known as chromatin. Analysis of the structure of eukaryotic chromosomes has been revolutionized by development of a suite of genome-wide measurement technologies, collectively termed “epigenomics.” We review major advances in epigenomic analysis of eukaryotic genomes, covering aspects of genome folding at scales ranging from whole chromosome folding down to nucleotide-resolution assays that provide structural insights into protein-DNA interactions. We then briefly outline several challenges remaining and highlight new developments such as single-cell epigenomic assays that will help provide us with a high-resolution structural understanding of eukaryotic genomes.

Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci

Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies have identified >150 loci associated with CAD and myocardial infarction susceptibility in humans. A majority of these variants reside in non-coding regions and are co-inherited with hundreds of candidate regulatory variants, presenting a challenge to elucidate their functions. Herein, we use integrative genomic, epigenomic and transcriptomic profiling of perturbed human coronary artery smooth muscle cells and tissues to begin to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps, we prioritize 64 candidate variants and perform allele-specific binding and expression analyses at seven top candidate loci: 9p21.3, SMAD3, PDGFD, IL6R, BMP1, CCDC97/TGFB1 and LMOD1. We validate our findings in expression quantitative trait loci cohorts, which together reveal new links between CAD associations and regulatory function in the appropriate disease context.

Coronary heart disease is the leading cause of death worldwide with multiple environmental and genetic risk factors. Here the authors integrate genomic, epigenomic and transcriptomic mapping to elucidate causal variation and mechanisms of known genetic associations.

Hormone-induced repression of genes requires BRG1-mediated H1.2 deposition at target promoters

Eukaryotic gene regulation is associated with changes in chromatin compaction that modulate access to DNA regulatory sequences relevant for transcriptional activation or repression. Although much is known about the mechanism of chromatin remodeling in hormonal gene activation, how repression is accomplished is much less understood. Here we report that in breast cancer cells, ligand-activated progesterone receptor (PR) is directly recruited to transcriptionally repressed genes involved in cell proliferation along with the kinases ERK1/2 and MSK1. PR recruits BRG1 associated with the HP1γ-LSD1 complex repressor complex, which is further anchored via binding of HP1γ to the H3K9me3 signal deposited by SUV39H2. In contrast to what is observed during gene activation, only BRG1 and not the BAF complex is recruited to repressed promoters, likely due to local enrichment of the pioneer factor FOXA1. BRG1 participates in gene repression by interacting with H1.2, facilitating its deposition and stabilizing nucleosome positioning around the transcription start site. Our results uncover a mechanism of hormone-dependent transcriptional repression and a novel role for BRG1 in progestin regulation of breast cancer cell growth.

Genome-wide footprinting: ready for prime time?

High-throughput sequencing technologies have allowed many gene locus-level molecular biology assays to become genome-wide profiling methods. DNA-cleaving enzymes such as DNase I have been used to probe accessible chromatin. The accessible regions contain functional regulatory sites, including promoters, insulators and enhancers. Deep sequencing of DNase-seq libraries and computational analysis of the cut profiles have been used to infer protein occupancy in the genome at the nucleotide level, a method introduced as 'digital genomic footprinting'. The approach has been proposed as an attractive alternative to the analysis of transcription factors (TFs) by chromatin immunoprecipitation followed by sequencing (ChIP-seq), and in theory it should overcome antibody issues, poor resolution and batch effects. Recent reports point to limitations of the DNase-based genomic footprinting approach and call into question the scope of detectable protein occupancy, especially for TFs with short-lived chromatin binding. The genomics community is grappling with issues concerning the utility of genomic footprinting and is reassessing the proposed approaches in terms of robust deliverables. Here we summarize the consensus as well as different views emerging from recent reports, and we describe the remaining issues and hurdles for genomic footprinting.

Enhancers reside in a unique epigenetic environment during early zebrafish development

BACKGROUND

Enhancers, not promoters, are the most dynamic in their DNA methylation status throughout development and differentiation. Generally speaking, enhancers that are primed to or actually drive gene expression are characterized by relatively low levels of DNA methylation (hypo-methylation), while inactive enhancers display hyper-methylation of the underlying DNA. The direct functional significance of the DNA methylation state of enhancers is, however, unclear for most loci.

RESULTS

In contrast to conventional epigenetic interactions at enhancers, we find that DNA methylation status and enhancer activity during early zebrafish development display very unusual correlation characteristics: hypo-methylation is a unique feature of primed enhancers whereas active enhancers are generally hyper-methylated. The hypo-methylated enhancers that we identify (hypo-enhancers) are enriched close to important transcription factors that act later in development. Interestingly, hypo-enhancers are de-methylated shortly before the midblastula transition and reside in a unique epigenetic environment. Finally, we demonstrate that hypo-enhancers do become active at later developmental stages and that they are physically associated with the transcriptional start site of target genes, irrespective of target gene activity.

CONCLUSIONS

We demonstrate that early development in zebrafish embodies a time window characterized by non-canonical DNA methylation-enhancer relationships, including global DNA hypo-methylation of inactive enhancers and DNA hyper-methylation of active enhancers.

BACH2 regulates CD8(+) T cell differentiation by controlling access of AP-1 factors to enhancers

T cell antigen receptor (TCR) signaling drives distinct responses depending on the differentiation state and context of CD8(+) T cells. We hypothesized that access of signal-dependent transcription factors (TFs) to enhancers is dynamically regulated to shape transcriptional responses to TCR signaling. We found that the TF BACH2 restrains terminal differentiation to enable generation of long-lived memory cells and protective immunity after viral infection. BACH2 was recruited to enhancers, where it limited expression of TCR-driven genes by attenuating the availability of activator protein-1 (AP-1) sites to Jun family signal-dependent TFs. In naive cells, this prevented TCR-driven induction of genes associated with terminal differentiation. Upon effector differentiation, reduced expression of BACH2 and its phosphorylation enabled unrestrained induction of TCR-driven effector programs.

The genetic regulatory signature of type 2 diabetes in human skeletal muscle

Type 2 diabetes (T2D) results from the combined effects of genetic and environmental factors on multiple tissues over time. Of the >100 variants associated with T2D and related traits in genome-wide association studies (GWAS), >90% occur in non-coding regions, suggesting a strong regulatory component to T2D risk. Here to understand how T2D status, metabolic traits and genetic variation influence gene expression, we analyse skeletal muscle biopsies from 271 well-phenotyped Finnish participants with glucose tolerance ranging from normal to newly diagnosed T2D. We perform high-depth strand-specific mRNA-sequencing and dense genotyping. Computational integration of these data with epigenome data, including ATAC-seq on skeletal muscle, and transcriptome data across diverse tissues reveals that the tissue-specific genetic regulatory architecture of skeletal muscle is highly enriched in muscle stretch/super enhancers, including some that overlap T2D GWAS variants. In one such example, T2D risk alleles residing in a muscle stretch/super enhancer are linked to increased expression and alternative splicing of muscle-specific isoforms of ANK1.

From Loci to Biology: Functional Genomics of Genome-Wide Association for Coronary Disease

Genome-wide association studies have provided a rich collection of ≈ 58 coronary artery disease (CAD) loci that suggest the existence of previously unsuspected new biology relevant to atherosclerosis. However, these studies only identify genomic loci associated with CAD, and many questions remain even after a genomic locus is definitively implicated, including the nature of the causal variant(s) and the causal gene(s), as well as the directionality of effect. There are several tools that can be used for investigation of the functional genomics of these loci, and progress has been made on a limited number of novel CAD loci. New biology regarding atherosclerosis and CAD will be learned through the functional genomics of these loci, and the hope is that at least some of these new pathways relevant to CAD pathogenesis will yield new therapeutic targets for the prevention and treatment of CAD.

Gene regulation at a distance: From remote enhancers to 3D regulatory ensembles

Large-scale identification of elements associated with gene expression revealed that many of them are located extremely far from gene transcriptional start sites. We review here the growing evidence that show that distal cis-acting elements provide key instructions to genes, as genetic variation affecting them is growingly identified as an importance source of phenotypic diversity and disease. We discuss the different mechanisms that allow these elements to exert their regulatory functions, in a robust and specific manner, despite the large genomic distances separating them from their target genes. We particularly focus on the role of the structural organization of the genome in guiding such regulatory interactions.

Probing chromatin landscape reveals roles of endocardial TBX20 in septation

Mutations in the T-box transcription factor TBX20 are associated with multiple forms of congenital heart defects, including cardiac septal abnormalities, but our understanding of the contributions of endocardial TBX20 to heart development remains incomplete. Here, we investigated how TBX20 interacts with endocardial gene networks to drive the mesenchymal and myocardial movements that are essential for outflow tract and atrioventricular septation. Selective ablation of Tbx20 in murine endocardial lineages reduced the expression of extracellular matrix and cell migration genes that are critical for septation. Using the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), we identified accessible chromatin within endocardial lineages and intersected these data with TBX20 ChIP-seq and chromatin loop maps to determine that TBX20 binds a conserved long-range enhancer to regulate versican (Vcan) expression. We also observed reduced Vcan expression in Tbx20-deficient mice, supporting a direct role for TBX20 in Vcan regulation. Further, we show that the Vcan enhancer drove reporter gene expression in endocardial lineages in a TBX20-binding site-dependent manner. This work illuminates gene networks that interact with TBX20 to orchestrate cardiac septation and provides insight into the chromatin landscape of endocardial lineages during septation.

Chromatin accessibility maps of chronic lymphocytic leukaemia identify subtype-specific epigenome signatures and transcription regulatory networks

Chronic lymphocytic leukaemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, here we present genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients measured by the ATAC-seq assay. We also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting data set, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status-which distinguishes the two major subtypes of CLL-was accurately predicted by the chromatin profiles and gene regulatory networks inferred for IGHV-mutated versus IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukaemia and demonstrated the feasibility of large-scale chromatin accessibility mapping in cancer cohorts and clinical research.

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. AVAILABILITY: QuIN’s web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

Microglia development follows a stepwise program to regulate brain homeostasis

Microglia, the resident myeloid cells of the central nervous system, play important roles in life-long brain maintenance and in pathology. Despite their importance, their regulatory dynamics during brain development have not been fully elucidated. Using genome-wide chromatin and expression profiling coupled with single-cell transcriptomic analysis throughout development, we found that microglia undergo three temporal stages of development in synchrony with the brain--early, pre-, and adult microglia--which are under distinct regulatory circuits. Knockout of the gene encoding the adult microglia transcription factor MAFB and environmental perturbations, such as those affecting the microbiome or prenatal immune activation, led to disruption of developmental genes and immune response pathways. Together, our work identifies a stepwise microglia developmental program integrating immune response pathways that may be associated with several neurodevelopmental disorders.

Advancing haematopoietic stem and progenitor cell biology through single-cell profiling

Haematopoietic stem and progenitor cells (HSPCs) sit at the top of the haematopoietic hierarchy, and their fate choices need to be carefully controlled to ensure balanced production of all mature blood cell types. As cell fate decisions are made at the level of the individual cells, recent technological advances in measuring gene and protein expression in increasingly large numbers of single cells have been rapidly adopted to study both normal and pathological HSPC function. In this review we emphasise the importance of combining the correct computational models with single-cell experimental techniques, and illustrate how such integrated approaches have been used to resolve heterogeneities in populations, reconstruct lineage differentiation, identify regulatory relationships and link molecular profiling to cellular function.

Chromatin immunoprecipitation and an open chromatin assay in zebrafish erythrocytes

Zebrafish is an excellent genetic and developmental model for the study of vertebrate development and disease. Its ability to produce an abundance of transparent, externally developed embryos has facilitated large-scale genetic and chemical screens for the identification of critical genes and chemical factors that modulate developmental pathways. These studies can have profound implications for the diagnosis and treatment of a variety of human diseases. Recent advancements in molecular and genomic studies have provided valuable tools and resources for comprehensive and high-resolution analysis of epigenomes during cell specification and lineage differentiation throughout development. In this chapter, we describe two simple methods to evaluate protein-DNA interaction and chromatin architecture in erythrocytes from adult zebrafish. These are chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq) and an assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). These techniques, together with gene expression profiling, are useful for analyzing epigenomic regulation of cell specification, differentiation, and function during zebrafish development in both normal and disease models.

Enhancer regions show high histone H3.3 turnover that changes during differentiation

The organization of DNA into chromatin is dynamic; nucleosomes are frequently displaced to facilitate the ability of regulatory proteins to access specific DNA elements. To gain insight into nucleosome dynamics, and to follow how dynamics change during differentiation, we used a technique called time-ChIP to quantitatively assess histone H3.3 turnover genome-wide during differentiation of mouse ESCs. We found that, without prior assumptions, high turnover could be used to identify regions involved in gene regulation. High turnover was seen at enhancers, as observed previously, with particularly high turnover at super-enhancers. In contrast, regions associated with the repressive Polycomb-Group showed low turnover in ESCs. Turnover correlated with DNA accessibility. Upon differentiation, numerous changes in H3.3 turnover rates were observed, the majority of which occurred at enhancers. Thus, time-ChIP measurement of histone turnover shows that active enhancers are unusually dynamic in ESCs and changes in highly dynamic nucleosomes predominate at enhancers during differentiation.

Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well.

Parsing the Interferon Transcriptional Network and Its Disease Associations

Type 1 interferon (IFN) is a key mediator of organismal responses to pathogens, eliciting prototypical "interferon signature genes" that encode antiviral and inflammatory mediators. For a global view of IFN signatures and regulatory pathways, we performed gene expression and chromatin analyses of the IFN-induced response across a range of immunocyte lineages. These distinguished ISGs by cell-type specificity, kinetics, and sensitivity to tonic IFN and revealed underlying changes in chromatin configuration. We combined 1,398 human and mouse datasets to computationally infer ISG modules and their regulators, validated by genetic analysis in both species. Some ISGs are controlled by Stat1/2 and Irf9 and the ISRE DNA motif, but others appeared dependent on non-canonical factors. This regulatory framework helped to interpret JAK1 blockade pharmacology, different clusters being affected under tonic or IFN-stimulated conditions, and the IFN signatures previously associated with human diseases, revealing unrecognized subtleties in disease footprints, as affected by human ancestry.

Active and Inactive Enhancers Cooperate to Exert Localized and Long-Range Control of Gene Regulation

V(D)J recombination relies on the presence of proximal enhancers that activate the antigen receptor (AgR) loci in a lineage- and stage-specific manner. Unexpectedly, we find that both active and inactive AgR enhancers cooperate to disseminate their effects in a localized and long-range manner. Here, we demonstrate the importance of short-range contacts between active enhancers that constitute an Igk super-enhancer in B cells. Deletion of one element reduces the interaction frequency between other enhancers in the hub, which compromises the transcriptional output of each component. Furthermore, we establish that, in T cells, long-range contact and cooperation between the inactive Igk enhancer MiEκ and the active Tcrb enhancer Eβ alters enrichment of CBFβ binding in a manner that impacts Tcrb recombination. These findings underline the complexities of enhancer regulation and point to a role for localized and long-range enhancer-sharing between active and inactive elements in lineage- and stage-specific control.

Identifying peaks in *-seq data using shape information

Background

Peak calling is a fundamental step in the analysis of data generated by ChIP-seq or similar techniques to acquire epigenetics information. Current peak callers are often hard to parameterise and may therefore be difficult to use for non-bioinformaticians. In this paper, we present the ChIP-seq analysis tool available in CLC Genomics Workbench and CLC Genomics Server (version 7.5 and up), a user-friendly peak-caller designed to be not specific to a particular *-seq protocol.

Results

We illustrate the advantages of a shape-based approach and describe the algorithmic principles underlying the implementation. Thanks to the generality of the idea and the fact the algorithm is able to learn the peak shape from the data, the implementation requires only minimal user input, while still being applicable to a range of *-seq protocols. Using independently validated benchmark datasets, we compare our implementation to other state-of-the-art algorithms explicitly designed to analyse ChIP-seq data and provide an evaluation in terms of receiver-operator characteristic (ROC) plots. In order to show the applicability of the method to similar *-seq protocols, we also investigate algorithmic performances on DNase-seq data.

Conclusions

The results show that CLC shape-based peak caller ranks well among popular state-of-the-art peak callers while providing flexibility and ease-of-use.

Molecular functions of the transcription factors E2A and E2-2 in controlling germinal center B cell and plasma cell development

Busslinger et al. showed that the transcription factors E2A and E2-2 control the expression of genes required for the development of GC B cells and plasma cells.

E2A is an essential regulator of early B cell development. Here, we have demonstrated that E2A together with E2-2 controlled germinal center (GC) B cell and plasma cell development. As shown by the identification of regulated E2A,E2-2 target genes in activated B cells, these E-proteins directly activated genes with important functions in GC B cells and plasma cells by inducing and maintaining DNase I hypersensitive sites. Through binding to multiple enhancers in the Igh 3′ regulatory region and Aicda locus, E-proteins regulated class switch recombination by inducing both Igh germline transcription and AID expression. By regulating 3′ Igk and Igh enhancers and a distal element at the Prdm1 (Blimp1) locus, E-proteins contributed to Igk, Igh, and Prdm1 activation in plasmablasts. Together, these data identified E2A and E2-2 as central regulators of B cell immunity.

ATAC-seq on biobanked specimens defines a unique chromatin accessibility structure in naïve SLE B cells

Biobanking is a widespread practice for storing biological samples for future studies ranging from genotyping to RNA analysis. However, methods that probe the status of the epigenome are lacking. Here, the framework for applying the Assay for Transposase Accessible Sequencing (ATAC-seq) to biobanked specimens is described and was used to examine the accessibility landscape of naïve B cells from Systemic Lupus Erythematosus (SLE) patients undergoing disease flares. An SLE specific chromatin accessibility signature was identified. Changes in accessibility occurred at loci surrounding genes involved in B cell activation and contained motifs for transcription factors that regulate B cell activation and differentiation. These data provide evidence for an altered epigenetic programming in SLE B cells and identify loci and transcription factor networks that potentially impact disease. The ability to determine the chromatin accessibility landscape and identify cis-regulatory elements has broad application to studies using biorepositories and offers significant advantages to improve the molecular information obtained from biobanked samples.

An enduring role for quiescent stem cells

The intestine's ability to recover from catastrophic injury requires quiescent intestinal stem cells (q-ISCs). While rapidly cycling (Lgr5+) crypt base columnar (CBC) ISCs normally maintain the intestine, they are highly sensitive to pathological injuries (irradiation, inflammation) and must be restored by q-ISCs to sustain intestinal homeostasis. Despite clear relevance to human health, virtually nothing is known regarding the factors that regulate q-ISCs. A comprehensive understanding of these mechanisms would likely lead to targeted new therapies with profound therapeutic implications for patients with gastrointestinal conditions. We briefly review the current state of the literature, highlighting homeostatic mechanisms important for q-ISC regulation, listing key questions in the field, and offer strategies to address them. Developmental Dynamics 245:718-726, 2016. © 2016 Wiley Periodicals, Inc.

Transcriptomics in type 2 diabetes: Bridging the gap between genotype and phenotype

Type 2 diabetes (T2D) is a common, multifactorial disease that is influenced by genetic and environmental factors and their interactions. However, common variants identified by genome wide association studies (GWAS) explain only about 10% of the total trait variance for T2D and less than 5% of the variance for obesity, indicating that a large proportion of heritability is still unexplained. The transcriptomic approach described here uses quantitative gene expression and disease-related physiological data (deep phenotyping) to measure the direct correlation between the expression of specific genes and physiological traits. Transcriptomic analysis bridges the gulf between GWAS and physiological studies. Recent GWAS studies have utilized very large population samples, numbering in the tens of thousands (or even hundreds of thousands) of individuals, yet establishing causal functional relationships between strongly associated genetic variants and disease remains elusive. In light of the findings described below, it is appropriate to consider how and why transcriptomic approaches in small samples might be capable of identifying complex disease-related genes which are not apparent using GWAS in large samples.