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The term 'super enhancers' (SE) has been widely used to describe stretches of closely localized enhancers that are occupied collectively by large numbers of transcription factors (TFs) and co-factors, and control the transcription of highly-expressed genes. Through integrated analysis of >600 DNase-seq, ChIP-seq, GRO-seq, STARR-seq, RNA-seq, Hi-C and ChIA-PET data in five human cancer cell lines, we identified a new class of autonomous SEs (aSEs) that are excluded from classic SE calls by the widely used Rank Ordering of Super-Enhancers (ROSE) method. TF footprint analysis revealed that compared to classic SEs and regular enhancers, aSEs are tightly bound by a dense array of master lineage TFs, which serve as anchors to recruit additional TFs and co-factors in trans. In addition, aSEs are preferentially enriched for Cohesins, which likely involve in stabilizing long-distance interactions between aSEs and their distal target genes. Finally, we showed that aSEs can be reliably predicted using a single DNase-seq data or combined with Mediator and/or P300 ChIP-seq. Overall, our study demonstrates that aSEs represent a unique class of functionally important enhancer elements that distally regulate the transcription of highly expressed genes., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

SWI/SNF-type chromatin remodelers, such as BRAHMA (BRM), and H3K27 demethylases both have active roles in regulating gene expression at the chromatin level, but how they are recruited to specific genomic sites remains largely unknown. Here we show that RELATIVE OF EARLY FLOWERING 6 (REF6), a plant-unique H3K27 demethylase, targets genomic loci containing a CTCTGYTY motif via its zinc-finger (ZnF) domains and facilitates the recruitment of BRM. Genome-wide analyses showed that REF6 colocalizes with BRM at many genomic sites with the CTCTGYTY motif. Loss of REF6 results in decreased BRM occupancy at BRM-REF6 co-targets. Furthermore, REF6 directly binds to the CTCTGYTY motif in vitro, and deletion of the motif from a target gene renders it inaccessible to REF6 in vivo. Finally, we show that, when its ZnF domains are deleted, REF6 loses its genomic targeting ability. Thus, our work identifies a new genomic targeting mechanism for an H3K27 demethylase and demonstrates its key role in recruiting the BRM chromatin remodeler., Competing Interests: The authors declare no competing financial interests.

Pediatric tumors are relatively infrequent, but are often associated with significant lethality and lifelong morbidity. A major goal of pediatric cancer research has been to identify key drivers of tumorigenesis to eventually develop targeted therapies to enhance cure rate and minimize acute and long-term toxic effects. Here, we used genomic approaches to identify biomarkers and candidate drivers for fibrolamellar hepatocellular carcinoma (FL-HCC), a very rare subtype of pediatric liver cancer for which limited therapeutic options exist. In-depth genomic analyses of one tumor followed by immunohistochemistry validation on seven other tumors showed expression of neuroendocrine markers in FL-HCC. DNA and RNA sequencing data further showed that common cancer pathways are not visibly altered in FL-HCC but identified two novel structural variants, both resulting in fusion transcripts. The first, a 400 kb deletion, results in a DNAJB1-PRKCA fusion transcript, which leads to increased cAMP-dependent protein kinase (PKA) activity in the index tumor case and other FL-HCC cases compared with normal liver. This PKA fusion protein is oncogenic in HCC cells. The second gene fusion event, a translocation between the CLPTM1L and GLIS3 genes, generates a transcript whose product also promotes cancer phenotypes in HCC cell lines. These experiments further highlight the tumorigenic role of gene fusions in the etiology of pediatric solid tumors and identify both candidate biomarkers and possible therapeutic targets for this lethal pediatric disease., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

To broaden our understanding of the evolution of gene regulation mechanisms, we generated occupancy profiles for 34 orthologous transcription factors (TFs) in human-mouse erythroid progenitor, lymphoblast and embryonic stem-cell lines. By combining the genome-wide transcription factor occupancy repertoires, associated epigenetic signals, and co-association patterns, here we deduce several evolutionary principles of gene regulatory features operating since the mouse and human lineages diverged. The genomic distribution profiles, primary binding motifs, chromatin states, and DNA methylation preferences are well conserved for TF-occupied sequences. However, the extent to which orthologous DNA segments are bound by orthologous TFs varies both among TFs and with genomic location: binding at promoters is more highly conserved than binding at distal elements. Notably, occupancy-conserved TF-occupied sequences tend to be pleiotropic; they function in several tissues and also co-associate with many TFs. Single nucleotide variants at sites with potential regulatory functions are enriched in occupancy-conserved TF-occupied sequences.

Despite the large evolutionary distances between metazoan species, they can show remarkable commonalities in their biology, and this has helped to establish fly and worm as model organisms for human biology. Although studies of individual elements and factors have explored similarities in gene regulation, a large-scale comparative analysis of basic principles of transcriptional regulatory features is lacking. Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time. We find that structural properties of regulatory networks are remarkably conserved and that orthologous regulatory factor families recognize similar binding motifs in vivo and show some similar co-associations. Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections. The comparative maps of regulatory circuitry provided here will drive an improved understanding of the regulatory underpinnings of model organism biology and how these relate to human biology, development and disease.

Discovering the structure and dynamics of transcriptional regulatory events in the genome with cellular and temporal resolution is crucial to understanding the regulatory underpinnings of development and disease. We determined the genomic distribution of binding sites for 92 transcription factors and regulatory proteins across multiple stages of Caenorhabditis elegans development by performing 241 ChIP-seq (chromatin immunoprecipitation followed by sequencing) experiments. Integration of regulatory binding and cellular-resolution expression data produced a spatiotemporally resolved metazoan transcription factor binding map. Using this map, we explore developmental regulatory circuits that encode combinatorial logic at the levels of co-binding and co-expression of transcription factors, characterizing the genomic coverage and clustering of regulatory binding, the binding preferences of, and biological processes regulated by, transcription factors, the global transcription factor co-associations and genomic subdomains that suggest shared patterns of regulation, and identifying key transcription factors and transcription factor co-associations for fate specification of individual lineages and cell types.

Background: Steroidogenic acute regulatory protein (StAR)-related lipid transfer (START) domains were first identified from mammalian proteins that bind lipid/sterol ligands via a hydrophobic pocket. In plants, predicted START domains are predominantly found in homeodomain leucine zipper (HD-Zip) transcription factors that are master regulators of cell-type differentiation in development. Here we utilized studies of Arabidopsis in parallel with heterologous expression of START domains in yeast to investigate the hypothesis that START domains are versatile ligand-binding motifs that can modulate transcription factor activity., Results: Our results show that deletion of the START domain from Arabidopsis Glabra2 (GL2), a representative HD-Zip transcription factor involved in differentiation of the epidermis, results in a complete loss-of-function phenotype, although the protein is correctly localized to the nucleus. Despite low sequence similarly, the mammalian START domain from StAR can functionally replace the HD-Zip-derived START domain. Embedding the START domain within a synthetic transcription factor in yeast, we found that several mammalian START domains from StAR, MLN64 and PCTP stimulated transcription factor activity, as did START domains from two Arabidopsis HD-Zip transcription factors. Mutation of ligand-binding residues within StAR START reduced this activity, consistent with the yeast assay monitoring ligand-binding. The D182L missense mutation in StAR START was shown to affect GL2 transcription factor activity in maintenance of the leaf trichome cell fate. Analysis of in vivo protein-metabolite interactions by mass spectrometry provided direct evidence for analogous lipid-binding activity in mammalian and plant START domains in the yeast system. Structural modeling predicted similar sized ligand-binding cavities of a subset of plant START domains in comparison to mammalian counterparts., Conclusions: The START domain is required for transcription factor activity in HD-Zip proteins from plants, although it is not strictly necessary for the protein's nuclear localization. START domains from both mammals and plants are modular in that they can bind lipid ligands to regulate transcription factor function in a yeast system. The data provide evidence for an evolutionarily conserved mechanism by which lipid metabolites can orchestrate transcription. We propose a model in which the START domain is used by both plants and mammals to regulate transcription factor activity.

Transcription factors (TFs) are fundamental controllers of cellular regulation that function in a complex and combinatorial manner. Accurate identification of a transcription factor's targets is essential to understanding the role that factors play in disease biology. However, due to a high false positive rate, identifying coherent functional target sets is difficult. We have created an improved mapping of targets by integrating ChIP-Seq data with 423 functional modules derived from 9,395 human expression experiments. We identified 5,002 TF-module relationships, significantly improved TF target prediction, and found 30 high-confidence TF-TF associations, of which 14 are known. Importantly, we also connected TFs to diseases through these functional modules and identified 3,859 significant TF-disease relationships. As an example, we found a link between MEF2A and Crohn's disease, which we validated in an independent expression dataset. These results show the power of combining expression data and ChIP-Seq data to remove noise and better extract the associations between TFs, functional modules, and disease.

Transcription factors influence gene expression through their ability to bind DNA at specific regulatory elements. Specific DNA-protein interactions can be isolated through the chromatin immunoprecipitation (ChIP) procedure, in which DNA fragments bound by the protein of interest are recovered. ChIP is followed by high-throughput DNA sequencing (Seq) to determine the genomic provenance of ChIP DNA fragments and their relative abundance in the sample. This chapter describes a ChIP-Seq strategy adapted for budding yeast to enable the genome-wide characterization of binding sites of transcription factors (TFs) and other DNA-binding proteins in an efficient and cost-effective way.Yeast strains with epitope-tagged TFs are most commonly used for ChIP-Seq, along with their matching untagged control strains. The initial step of ChIP involves the cross-linking of DNA and proteins. Next, yeast cells are lysed and sonicated to shear chromatin into smaller fragments. An antibody against an epitope-tagged TF is used to pull down chromatin complexes containing DNA and the TF of interest. DNA is then purified and proteins degraded. Specific barcoded adapters for multiplex DNA sequencing are ligated to ChIP DNA. Short DNA sequence reads (28-36 base pairs) are parsed according to the barcode and aligned against the yeast reference genome, thus generating a nucleotide-resolution map of transcription factor-binding sites and their occupancy.

The global identification of transcription factor (TF) binding sites is a critical step in the elucidation of the functional elements of the genome. Several methods have been developed that map TF binding in human cells, yeast, and other model organisms. These methods make use of chromatin immunoprecipitation, or ChIP, and take advantage of the fact that formaldehyde fixation of living cells can be used to cross-link DNA sequences to the TFs that bind them in vivo. In ChIP, the cross-linked TF-DNA complexes are sheared by sonication, size fractionated, and incubated with antibody specific to the TF of interest to generate a library of TF-bound DNA sequences. ChIP-chip was the first technology developed to globally identify TF-bound DNA sequences and involves subsequent hybridization of the ChIP DNA to oligonucleotide microarrays. However, ChIP-chip proved to be costly, labor-intensive, and limited by the fixed number of probes available on the microarray chip. ChIP-Seq combines ChIP with massively parallel high-throughput sequencing (see Explanatory Chapter: Next Generation Sequencing) and has demonstrated vast improvement over ChIP-chip with respect to time and cost, signal-to-noise ratio, and resolution. In particular, multiplex sequencing can be used to achieve a higher throughput in ChIP-Seq analyses involving organisms with genomes of lower complexity than that of human (Lefrançois et al., 2009) and thereby reduce the cost and amount of time needed for each result. The multiplex ChIP-Seq method described in this section has been developed for Caenorhabditis elegans, but is easily adaptable for other organisms., (© 2014 Elsevier Inc. All rights reserved.)

Different trans-acting factors (TFs) collaborate and act in concert at distinct loci to perform accurate regulation of their target genes. To date, the cobinding of TF pairs has been investigated in a limited context both in terms of the number of factors within a cell type and across cell types and the extent of combinatorial colocalizations. Here, we use an approach to analyze TF colocalization within a cell type and across multiple cell lines at an unprecedented level. We extend this approach with large-scale mass spectrometry analysis of immunoprecipitations of 50 TFs. Our combined approach reveals large numbers of interesting TF-TF associations. We observe extensive change in TF colocalizations both within a cell type exposed to different conditions and across multiple cell types. We show distinct functional annotations and properties of different TF cobinding patterns and provide insights into the complex regulatory landscape of the cell., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Genome-wide association studies have discovered many genetic loci associated with disease traits, but the functional molecular basis of these associations is often unresolved. Genome-wide regulatory and gene expression profiles measured across individuals and diseases reflect downstream effects of genetic variation and may allow for functional assessment of disease-associated loci. Here, we present a unique approach for systematic integration of genetic disease associations, transcription factor binding among individuals, and gene expression data to assess the functional consequences of variants associated with hundreds of human diseases. In an analysis of genome-wide binding profiles of NFκB, we find that disease-associated SNPs are enriched in NFκB binding regions overall, and specifically for inflammatory-mediated diseases, such as asthma, rheumatoid arthritis, and coronary artery disease. Using genome-wide variation in transcription factor-binding data, we find that NFκB binding is often correlated with disease-associated variants in a genotype-specific and allele-specific manner. Furthermore, we show that this binding variation is often related to expression of nearby genes, which are also found to have altered expression in independent profiling of the variant-associated disease condition. Thus, using this integrative approach, we provide a unique means to assign putative function to many disease-associated SNPs.

Background: Transcription factors function by binding different classes of regulatory elements. The Encyclopedia of DNA Elements (ENCODE) project has recently produced binding data for more than 100 transcription factors from about 500 ChIP-seq experiments in multiple cell types. While this large amount of data creates a valuable resource, it is nonetheless overwhelmingly complex and simultaneously incomplete since it covers only a small fraction of all human transcription factors., Results: As part of the consortium effort in providing a concise abstraction of the data for facilitating various types of downstream analyses, we constructed statistical models that capture the genomic features of three paired types of regions by machine-learning methods: firstly, regions with active or inactive binding; secondly, those with extremely high or low degrees of co-binding, termed HOT and LOT regions; and finally, regulatory modules proximal or distal to genes. From the distal regulatory modules, we developed computational pipelines to identify potential enhancers, many of which were validated experimentally. We further associated the predicted enhancers with potential target transcripts and the transcription factors involved. For HOT regions, we found a significant fraction of transcription factor binding without clear sequence motifs and showed that this observation could be related to strong DNA accessibility of these regions., Conclusions: Overall, the three pairs of regions exhibit intricate differences in chromosomal locations, chromatin features, factors that bind them, and cell-type specificity. Our machine learning approach enables us to identify features potentially general to all transcription factors, including those not included in the data.

Chromatin-remodeling enzymes play essential roles in many biological processes, including gene expression, DNA replication and repair, and cell division. Although one such complex, SWI/SNF, has been extensively studied, new discoveries are still being made. Here, we review SWI/SNF biochemistry; highlight recent genomic and proteomic advances; and address the role of SWI/SNF in human diseases, including cancer and viral infections. These studies have greatly increased our understanding of complex nuclear processes.

Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.

Chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) has become the dominant technique for mapping transcription factor (TF) binding regions genome-wide. We performed an integrative analysis centered around 457 ChIP-seq data sets on 119 human TFs generated by the ENCODE Consortium. We identified highly enriched sequence motifs in most data sets, revealing new motifs and validating known ones. The motif sites (TF binding sites) are highly conserved evolutionarily and show distinct footprints upon DNase I digestion. We frequently detected secondary motifs in addition to the canonical motifs of the TFs, indicating tethered binding and cobinding between multiple TFs. We observed significant position and orientation preferences between many cobinding TFs. Genes specifically expressed in a cell line are often associated with a greater occurrence of nearby TF binding in that cell line. We observed cell-line-specific secondary motifs that mediate the binding of the histone deacetylase HDAC2 and the enhancer-binding protein EP300. TF binding sites are located in GC-rich, nucleosome-depleted, and DNase I sensitive regions, flanked by well-positioned nucleosomes, and many of these features show cell type specificity. The GC-richness may be beneficial for regulating TF binding because, when unoccupied by a TF, these regions are occupied by nucleosomes in vivo. We present the results of our analysis in a TF-centric web repository Factorbook (http://factorbook.org) and will continually update this repository as more ENCODE data are generated.

PPARGC1A is a transcriptional coactivator that binds to and coactivates a variety of transcription factors (TFs) to regulate the expression of target genes. PPARGC1A plays a pivotal role in regulating energy metabolism and has been implicated in several human diseases, most notably type II diabetes. Previous studies have focused on the interplay between PPARGC1A and individual TFs, but little is known about how PPARGC1A combines with all of its partners across the genome to regulate transcriptional dynamics. In this study, we describe a core PPARGC1A transcriptional regulatory network operating in HepG2 cells treated with forskolin. We first mapped the genome-wide binding sites of PPARGC1A using chromatin-IP followed by high-throughput sequencing (ChIP-seq) and uncovered overrepresented DNA sequence motifs corresponding to known and novel PPARGC1A network partners. We then profiled six of these site-specific TF partners using ChIP-seq and examined their network connectivity and combinatorial binding patterns with PPARGC1A. Our analysis revealed extensive overlap of targets including a novel link between PPARGC1A and HSF1, a TF regulating the conserved heat shock response pathway that is misregulated in diabetes. Importantly, we found that different combinations of TFs bound to distinct functional sets of genes, thereby helping to reveal the combinatorial regulatory code for metabolic and other cellular processes. In addition, the different TFs often bound near the promoters and coding regions of each other's genes suggesting an intricate network of interdependent regulation. Overall, our study provides an important framework for understanding the systems-level control of metabolic gene expression in humans.

Statistical models have been used to quantify the relationship between gene expression and transcription factor (TF) binding signals. Here we apply the models to the large-scale data generated by the ENCODE project to study transcriptional regulation by TFs. Our results reveal a notable difference in the prediction accuracy of expression levels of transcription start sites (TSSs) captured by different technologies and RNA extraction protocols. In general, the expression levels of TSSs with high CpG content are more predictable than those with low CpG content. For genes with alternative TSSs, the expression levels of downstream TSSs are more predictable than those of the upstream ones. Different TF categories and specific TFs vary substantially in their contributions to predicting expression. Between two cell lines, the differential expression of TSS can be precisely reflected by the difference of TF-binding signals in a quantitative manner, arguing against the conventional on-and-off model of TF binding. Finally, we explore the relationships between TF-binding signals and other chromatin features such as histone modifications and DNase hypersensitivity for determining expression. The models imply that these features regulate transcription in a highly coordinated manner.

Understanding the in vivo dynamics of protein localization and their physical interactions is important for many problems in biology. To enable systematic protein function interrogation in a multicellular context, we built a genome-scale transgenic platform for in vivo expression of fluorescent- and affinity-tagged proteins in Caenorhabditis elegans under endogenous cis regulatory control. The platform combines computer-assisted transgene design, massively parallel DNA engineering, and next-generation sequencing to generate a resource of 14,637 genomic DNA transgenes, which covers 73% of the proteome. The multipurpose tag used allows any protein of interest to be localized in vivo or affinity purified using standard tag-based assays. We illustrate the utility of the resource by systematic chromatin immunopurification and automated 4D imaging, which produced detailed DNA binding and cell/tissue distribution maps for key transcription factor proteins., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Gene duplication is a significant source of novel genes and the dynamics of gene duplicate retention vs loss are poorly understood, particularly in terms of the functional and regulatory specialization of their gene products. We compiled a comprehensive data set of S. cerevisiae phosphosites to study the role of phosphorylation in yeast paralog divergence. We found that proteins coded by duplicated genes created in the Whole Genome Duplication (WGD) event and in a period prior to the WGD are significantly more phosphorylated than other duplicates or singletons. Though the amino acid sequence of each paralog of a given pair tends to diverge fairly similarly from their common ortholog in a related species, the phosphorylated amino acids tend to diverge in sequence from the ortholog at different rates. We observed that transcription factors (TFs) are disproportionately present among the set of duplicate genes and among the set of proteins that are phosphorylated. Interestingly, TFs that occur on higher levels of the transcription network hierarchy (i.e., tend to regulate other TFs) tend to be more phosphorylated than lower-level TFs. We found that TF paralog divergence in expression, binding, and sequence correlates with the abundance of phosphosites. Overall, these studies have important implications for understanding divergence of gene function and regulation in eukaryotes.

There has been a recent surge in the use of genome-wide methodologies to identify and annotate the transcriptional regulatory elements in the human genome. Here we review some of these methodologies and the conceptual insights about transcription regulation that have been gained from the use of genome-wide studies. It has become clear that the binding of transcription factors is itself a highly regulated process, and binding does not always appear to have functional consequences. Numerous properties have now been associated with regulatory elements that may be useful in their identification. Several aspects of enhancer function have been shown to be more widespread than was previously appreciated, including the highly combinatorial nature of transcription factor binding, the postinitiation regulation of many target genes, and the binding of enhancers at early stages to maintain their competence during development. Going forward, the integration of multiple genome-wide data sets should become a standard approach to elucidate higher-order regulatory interactions.

Regulation of gene expression at the transcriptional level is achieved by complex interactions of transcription factors operating at their target genes. Dissecting the specific combination of factors that bind each target is a significant challenge. Here, we describe in detail the Allele Binding Cooperativity test, which uses variation in transcription factor binding among individuals to discover combinations of factors and their targets. We developed the ALPHABIT (a large-scale process to hunt for allele binding interacting transcription factors) pipeline, which includes statistical analysis of binding sites followed by experimental validation, and demonstrate that this method predicts transcription factors that associate with NFκB. Our method successfully identifies factors that have been known to work with NFκB (E2A, STAT1, IRF2), but whose global coassociation and sites of cooperative action were not known. In addition, we identify a unique coassociation (EBF1) that had not been reported previously. We present a general approach for discovering combinatorial models of regulation and advance our understanding of the genetic basis of variation in transcription factor binding.

An important mechanism for gene regulation involves chromatin changes via histone modification. One such modification is histone H3 lysine 4 trimethylation (H3K4me3), which requires histone methyltranferase complexes (HMT) containing the trithorax-group (trxG) protein ASH2. Mutations in ash2 cause a variety of pattern formation defects in the Drosophila wing. We have identified genome-wide binding of ASH2 in wing imaginal discs using chromatin immunoprecipitation combined with sequencing (ChIP-Seq). Our results show that genes with functions in development and transcriptional regulation are activated by ASH2 via H3K4 trimethylation in nearby nucleosomes. We have characterized the occupancy of phosphorylated forms of RNA Polymerase II and histone marks associated with activation and repression of transcription. ASH2 occupancy correlates with phosphorylated forms of RNA Polymerase II and histone activating marks in expressed genes. Additionally, RNA Polymerase II phosphorylation on serine 5 and H3K4me3 are reduced in ash2 mutants in comparison to wild-type flies. Finally, we have identified specific motifs associated with ASH2 binding in genes that are differentially expressed in ash2 mutants. Our data suggest that recruitment of the ASH2-containing HMT complexes is context specific and points to a function of ASH2 and H3K4me3 in transcriptional pausing control.

A systems understanding of nuclear organization and events is critical for determining how cells divide, differentiate, and respond to stimuli and for identifying the causes of diseases. Chromatin remodeling complexes such as SWI/SNF have been implicated in a wide variety of cellular processes including gene expression, nuclear organization, centromere function, and chromosomal stability, and mutations in SWI/SNF components have been linked to several types of cancer. To better understand the biological processes in which chromatin remodeling proteins participate, we globally mapped binding regions for several components of the SWI/SNF complex throughout the human genome using ChIP-Seq. SWI/SNF components were found to lie near regulatory elements integral to transcription (e.g. 5' ends, RNA Polymerases II and III, and enhancers) as well as regions critical for chromosome organization (e.g. CTCF, lamins, and DNA replication origins). Interestingly we also find that certain configurations of SWI/SNF subunits are associated with transcripts that have higher levels of expression, whereas other configurations of SWI/SNF factors are associated with transcripts that have lower levels of expression. To further elucidate the association of SWI/SNF subunits with each other as well as with other nuclear proteins, we also analyzed SWI/SNF immunoprecipitated complexes by mass spectrometry. Individual SWI/SNF factors are associated with their own family members, as well as with cellular constituents such as nuclear matrix proteins, key transcription factors, and centromere components, implying a ubiquitous role in gene regulation and nuclear function. We find an overrepresentation of both SWI/SNF-associated regions and proteins in cell cycle and chromosome organization. Taken together the results from our ChIP and immunoprecipitation experiments suggest that SWI/SNF facilitates gene regulation and genome function more broadly and through a greater diversity of interactions than previously appreciated., Competing Interests: The authors have declared that no competing interests exist.

Regulation of gene expression by sequence-specific transcription factors is central to developmental programs and depends on the binding of transcription factors with target sites in the genome. To date, most such analyses in Caenorhabditis elegans have focused on the interactions between a single transcription factor with one or a few select target genes. As part of the modENCODE Consortium, we have used chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-seq) to determine the genome-wide binding sites of 22 transcription factors (ALR-1, BLMP-1, CEH-14, CEH-30, EGL-27, EGL-5, ELT-3, EOR-1, GEI-11, HLH-1, LIN-11, LIN-13, LIN-15B, LIN-39, MAB-5, MDL-1, MEP-1, PES-1, PHA-4, PQM-1, SKN-1, and UNC-130) at diverse developmental stages. For each factor we determined candidate gene targets, both coding and non-coding. The typical binding sites of almost all factors are within a few hundred nucleotides of the transcript start site. Most factors target a mixture of coding and non-coding target genes, although one factor preferentially binds to non-coding RNA genes. We built a regulatory network among the 22 factors to determine their functional relationships to each other and found that some factors appear to act preferentially as regulators and others as target genes. Examination of the binding targets of three related HOX factors--LIN-39, MAB-5, and EGL-5--indicates that these factors regulate genes involved in cellular migration, neuronal function, and vulval differentiation, consistent with their known roles in these developmental processes. Ultimately, the comprehensive mapping of transcription factor binding sites will identify features of transcriptional networks that regulate C. elegans developmental processes.

Genome-wide occupancy profiles of five components of the RNA polymerase III (Pol III) machinery in human cells identified the expected tRNA and noncoding RNA targets and revealed many additional Pol III-associated loci, mostly near short interspersed elements (SINEs). Several genes are targets of an alternative transcription factor IIIB (TFIIIB) containing Brf2 instead of Brf1 and have extremely low levels of TFIIIC. Strikingly, expressed Pol III genes, unlike nonexpressed Pol III genes, are situated in regions with a pattern of histone modifications associated with functional Pol II promoters. TFIIIC alone associates with numerous ETC loci, via the B box or a novel motif. ETCs are often near CTCF binding sites, suggesting a potential role in chromosome organization. Our results suggest that human Pol III complexes associate preferentially with regions near functional Pol II promoters and that TFIIIC-mediated recruitment of TFIIIB is regulated in a locus-specific manner.

Variation in transcriptional regulation is thought to be a major cause of phenotypic diversity. Although widespread differences in gene expression among individuals of a species have been observed, studies to examine the variability of transcription factor binding on a global scale have not been performed, and thus the extent and underlying genetic basis of transcription factor binding diversity is unknown. By mapping differences in transcription factor binding among individuals, here we present the genetic basis of such variation on a genome-wide scale. Whole-genome Ste12-binding profiles were determined using chromatin immunoprecipitation coupled with DNA sequencing in pheromone-treated cells of 43 segregants of a cross between two highly diverged yeast strains and their parental lines. We identified extensive Ste12-binding variation among individuals, and mapped underlying cis- and trans-acting loci responsible for such variation. We showed that most transcription factor binding variation is cis-linked, and that many variations are associated with polymorphisms residing in the binding motifs of Ste12 as well as those of several proposed Ste12 cofactors. We also identified two trans-factors, AMN1 and FLO8, that modulate Ste12 binding to promoters of more than ten genes under alpha-factor treatment. Neither of these two genes was previously known to regulate Ste12, and we suggest that they may be mediators of gene activity and phenotypic diversity. Ste12 binding strongly correlates with gene expression for more than 200 genes, indicating that binding variation is functional. Many of the variable-bound genes are involved in cell wall organization and biogenesis. Overall, these studies identified genetic regulators of molecular diversity among individuals and provide new insights into mechanisms of gene regulation.

Transcription of the eukaryotic genomes is carried out by three distinct RNA polymerases I, II, and III, whereby each polymerase is thought to independently transcribe a distinct set of genes. To investigate a possible relationship of RNA polymerases II and III, we mapped their in vivo binding sites throughout the human genome by using ChIP-Seq in two different cell lines, GM12878 and K562 cells. Pol III was found to bind near many known genes as well as several previously unidentified target genes. RNA-Seq studies indicate that a majority of the bound genes are expressed, although a subset are not suggestive of stalling by RNA polymerase III. Pol II was found to bind near many known Pol III genes, including tRNA, U6, HVG, hY, 7SK and previously unidentified Pol III target genes. Similarly, in vivo binding studies also reveal that a number of transcription factors normally associated with Pol II transcription, including c-Fos, c-Jun and c-Myc, also tightly associate with most Pol III-transcribed genes. Inhibition of Pol II activity using alpha-amanitin reduced expression of a number of Pol III genes (e.g., U6, hY, HVG), suggesting that Pol II plays an important role in regulating their transcription. These results indicate that, contrary to previous expectations, polymerases can often work with one another to globally coordinate gene expression.

Much of eukaryotic gene regulation is mediated by binding of transcription factors near or within their target genes. Transcription factor binding sites (TFBS) are often identified globally using chromatin immunoprecipitation (ChIP) in which specific protein-DNA interactions are isolated using an antibody against the factor of interest. Coupling ChIP with high-throughput DNA sequencing allows identification of TFBS in a direct, unbiased fashion; this technique is termed ChIP-Sequencing (ChIP-Seq). In this chapter, we describe the yeast ChIP-Seq procedure, including the protocols for ChIP, input DNA preparation, and Illumina DNA sequencing library preparation. Descriptions of Illumina sequencing and data processing and analysis are also included. The use of multiplex short-read sequencing (i.e., barcoding) enables the analysis of many ChIP samples simultaneously, which is especially valuable for organisms with small genomes such as yeast., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Systems biology represents a paradigm shift from the study of individual genes, proteins or other components to that of the analysis of entire pathways, cellular, developmental, or organismal processes. Large scale studies, primarily initiated in Saccharomyces cerevisiae, have allowed the identification and characterization of components on an unprecedented level. Large scale interaction, transcription factor binding and phosphorylation data have enabled the elucidation of global regulatory networks. These studies have helped provide an understanding of cellular pathways and processes at a global and systems level.

Complex biological processes are often regulated, at least in part, by the binding of transcription factors to their targets. Recently, considerable effort has been made to analyze the binding of relevant factors to the suite of targets they regulate, thereby generating a regulatory circuit map. However, for most studies the dynamics of binding have not been analyzed, and thus the temporal order of events and mechanisms by which this occurs are poorly understood. We globally analyzed in detail the temporal order of binding of several key factors involved in the salt response of yeast to their target genes. Analysis of Yap4 and Sko1 binding to their target genes revealed multiple temporal classes of binding patterns: (1) constant binding, (2) rapid induction, (3) slow induction, and (4) transient induction. These results demonstrate that individual transcription factors can have multiple binding patterns and help define the different types of temporal binding patterns used in eukaryotic gene regulation. To investigate these binding patterns further, we also analyzed the binding of seven other key transcription factors implicated in osmotic regulation, including Hot1, Msn1, Msn2, Msn4, Skn7, and Yap6, and found significant coassociation among the different factors at their gene targets. Moreover, the binding of several key factors was correlated with distinct classes of Yap4- and Sko1-binding patterns and with distinct types of genes. Gene expression studies revealed association of Yap4, Sko1, and other transcription factor-binding patterns with different gene expression patterns. The integration and analysis of binding and expression information reveals a complex dynamic and hierarchical circuit in which specific combinations of transcription factors target distinct sets of genes at discrete times to coordinate a rapid and important biological response.

We characterized the relationship of H3K4me1 and H3K4me3 at distal and proximal regulatory elements by comparing ChIP-seq profiles for these histone modifications and for two functionally different transcription factors: STAT1 in the immortalized HeLa S3 cell line, with and without interferon-gamma (IFNG) stimulation; and FOXA2 in mouse adult liver tissue. In unstimulated and stimulated HeLa cells, respectively, we determined approximately 270,000 and approximately 301,000 H3K4me1-enriched regions, and approximately 54,500 and approximately 76,100 H3K4me3-enriched regions. In mouse adult liver, we determined approximately 227,000 and approximately 34,800 H3K4me1 and H3K4me3 regions. Seventy-five percent of the approximately 70,300 STAT1 binding sites in stimulated HeLa cells and 87% of the approximately 11,000 FOXA2 sites in mouse liver were distal to known gene TSS; in both cell types, approximately 83% of these distal sites were associated with at least one of the two histone modifications, and H3K4me1 was associated with over 96% of marked distal sites. After filtering against predicted transcription start sites, 50% of approximately 26,800 marked distal IFNG-stimulated STAT1 binding sites, but 95% of approximately 5800 marked distal FOXA2 sites, were associated with H3K4me1 only. Results for HeLa cells generated additional insights into transcriptional regulation involving STAT1. STAT1 binding was associated with 25% of all H3K4me1 regions in stimulated HeLa cells, suggesting that a single transcription factor can interact with an unexpectedly large fraction of regulatory regions. Strikingly, for a large majority of the locations of stimulated STAT1 binding, the dominant H3K4me1/me3 combinations were established before activation, suggesting mechanisms independent of IFNG stimulation and high-affinity STAT1 binding.

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale.

In recent years, techniques have been developed to map transcription factor binding sites using chromatin immunoprecipitation combined with DNA microarrays (chIP chip). Initially, polymerase chain reaction (PCR)-based DNA arrays were used for the chIP chip procedure, however, high-density oligonucleotide (HDO) arrays, which allow for the production of thousands more features per array, have emerged as a competing array platform. To compare the two platforms, data from chIP chip analysis performed for three factors (Tec1, Ste12, and Sok2) using both HDO and PCR arrays under identical experimental conditions were compared. HDO arrays provided increased reproducibility and sensitivity, detecting approximately three times more binding events than the PCR arrays while also showing increased accuracy. The increased resolution provided by the HDO arrays also allowed for the identification of multiple binding peaks in close proximity and of novel binding events such as binding within ORFs. The HDO array platform provides a far more robust array system by all measures than PCR-based arrays, all of which is directly attributable to the large number of probes available.

Characterization of interspecies differences in gene regulation is crucial for understanding the molecular basis of both phenotypic diversity and evolution. By means of chromatin immunoprecipitation and DNA microarray analysis, the divergence in the binding sites of the pseudohyphal regulators Ste12 and Tec1 was determined in the yeasts Saccharomyces cerevisiae, S. mikatae, and S. bayanus under pseudohyphal conditions. We have shown that most of these sites have diverged across these species, far exceeding the interspecies variation in orthologous genes. A group of Ste12 targets was shown to be bound only in S. mikatae and S. bayanus under pseudohyphal conditions. Many of these genes are targets of Ste12 during mating in S. cerevisiae, indicating that specialization between the two pathways has occurred in this species. Transcription factor binding sites have therefore diverged substantially faster than ortholog content. Thus, gene regulation resulting from transcription factor binding is likely to be a major cause of divergence between related species.

Motivation: Large-scale tiling array experiments are becoming increasingly common in genomics. In particular, the ENCODE project requires the consistent segmentation of many different tiling array datasets into 'active regions' (e.g. finding transfrags from transcriptional data and putative binding sites from ChIP-chip experiments). Previously, such segmentation was done in an unsupervised fashion mainly based on characteristics of the signal distribution in the tiling array data itself. Here we propose a supervised framework for doing this. It has the advantage of explicitly incorporating validated biological knowledge into the model and allowing for formal training and testing., Methodology: In particular, we use a hidden Markov model (HMM) framework, which is capable of explicitly modeling the dependency between neighboring probes and whose extended version (the generalized HMM) also allows explicit description of state duration density. We introduce a formal definition of the tiling-array analysis problem, and explain how we can use this to describe sampling small genomic regions for experimental validation to build up a gold-standard set for training and testing. We then describe various ideal and practical sampling strategies (e.g. maximizing signal entropy within a selected region versus using gene annotation or known promoters as positives for transcription or ChIP-chip data, respectively)., Results: For the practical sampling and training strategies, we show how the size and noise in the validated training data affects the performance of an HMM applied to the ENCODE transcriptional and ChIP-chip experiments. In particular, we show that the HMM framework is able to efficiently process tiling array data as well as or better than previous approaches. For the idealized sampling strategies, we show how we can assess their performance in a simulation framework and how a maximum entropy approach, which samples sub-regions with very different signal intensities, gives the maximally performing gold-standard. This latter result has strong implications for the optimum way medium-scale validation experiments should be carried out to verify the results of the genome-scale tiling array experiments.

Analyses of whole-genome sequences and experimental data sets have revealed a large number of DNA sequence motifs that are conserved in many species and may be functional. However, methods of sufficient scale to explore the roles of these elements are lacking. We describe the use of protein arrays to identify proteins that bind to DNA sequences of interest. A microarray of 282 known and potential yeast transcription factors was produced and probed with oligonucleotides of evolutionarily conserved sequences that are potentially functional. Transcription factors that bound to specific DNA sequences were identified. One previously uncharacterized DNA-binding protein, Yjl103, was characterized in detail. We defined the binding site for this protein and identified a number of its target genes, many of which are involved in stress response and oxidative phosphorylation. Protein microarrays offer a high-throughput method for determining DNA-protein interactions.

To understand the organization of the transcriptional networks that govern cell differentiation, we have investigated the transcriptional circuitry controlling pseudohyphal development in Saccharomyces cerevisiae. The binding targets of Ste12, Tec1, Sok2, Phd1, Mga1, and Flo8 were globally mapped across the yeast genome. The factors and their targets form a complex binding network, containing patterns characteristic of autoregulation, feedback and feed-forward loops, and cross-talk. Combinatorial binding to intergenic regions was commonly observed, which allowed for the identification of a novel binding association between Mga1 and Flo8, in which Mga1 requires Flo8 for binding to promoter regions. Further analysis of the network showed that the promoters of MGA1 and PHD1 were bound by all of the factors used in this study, identifying them as key target hubs. Overexpression of either of these two proteins specifically induced pseudohyphal growth under noninducing conditions, highlighting them as master regulators of the system. Our results indicate that target hubs can serve as master regulators whose activity is sufficient for the induction of complex developmental responses and therefore represent important regulatory nodes in biological networks.

Comprehensive mapping of transcription factor binding sites is essential in postgenomic biology. For this, we propose a mining approach combining noisy data from ChIP (chromatin immunoprecipitation)-chip experiments with known binding site patterns. Our method (BoCaTFBS) uses boosted cascades of classifiers for optimum efficiency, in which components are alternating decision trees; it exploits interpositional correlations; and it explicitly integrates massive negative information from ChIP-chip experiments. We applied BoCaTFBS within the ENCODE project and showed that it outperforms many traditional binding site identification methods (for instance, profiles).

We developed a new DNA microarray-based technology, called protein binding microarrays (PBMs), that allows rapid, high-throughput characterization of the in vitro DNA binding-site sequence specificities of transcription factors in a single day. Using PBMs, we identified the DNA binding-site sequence specificities of the yeast transcription factors Abf1, Rap1 and Mig1. Comparison of these proteins' in vitro binding sites with their in vivo binding sites indicates that PBM-derived sequence specificities can accurately reflect in vivo DNA sequence specificities. In addition to previously identified targets, Abf1, Rap1 and Mig1 bound to 107, 90 and 75 putative new target intergenic regions, respectively, many of which were upstream of previously uncharacterized open reading frames. Comparative sequence analysis indicated that many of these newly identified sites are highly conserved across five sequenced sensu stricto yeast species and, therefore, are probably functional in vivo binding sites that may be used in a condition-specific manner. Similar PBM experiments should be useful in identifying new cis regulatory elements and transcriptional regulatory networks in various genomes.

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here--particularly the large-scale topological changes and hub transience--will apply to other biological networks, including complex sub-systems in higher eukaryotes.

Successful mating of MATa Saccharomyces cerevisiae cells is dependent on Ste2p, the alpha-factor receptor. Besides receiving the pheromone signal and transducing it through the G-protein coupled MAP kinase pathway, Ste2p is active in the establishment and orientation of the mating projection. We investigated the role of the carboxyl terminus of the receptor in mating projection formation and orientation using a spatial gradient assay. Cells carrying the ste2-T326 mutation, truncating 105 of the 135 amino acids in the receptor tail including a motif necessary for its ligand-mediated internalization, display slow onset of projection formation, abnormal shmoo morphology, and reduced ability to orient the mating projection toward a pheromone source. This reduction was due to the increased loss of mating projection orientation in a pheromone gradient. Cells with a mutated endocytosis motif were defective in reorientation in a pheromone gradient. ste2-Delta296 cells, which carry a complete truncation of the Ste2p tail, exhibit a severe defect in projection formation, and those projections that do form are unable to orient in a pheromone gradient. These results suggest a complex role for the Ste2p carboxy-terminal tail in the formation, orientation, and directional adjustment of the mating projection, and that endocytosis of the receptor is important for this process. In addition, mutations in RSR1/BUD1 and SPA2, genes necessary for budding polarity, exhibited little or no defect in formation or orientation of mating projections. We conclude that mating projection orientation depends upon the carboxyl terminus of the pheromone receptor and not the directional machinery used in budding., (Copyright 2002 Wiley-Liss, Inc.)

The expression of the beta-like globin genes is intricately regulated by a series of both general and tissue-restricted transcription factors. The hemapoietic lineage-specific transcription factor GATA-1 is important for erythroid differentiation and has been implicated in regulating the expression of the erythroid-specific genes including the genes of the beta-globin locus. In the human erythroleukemic K562 cell line, only one DNA region has been identified previously as a putative site of GATA-1 interaction by in vivo footprinting studies. We mapped GATA-1 binding throughout the beta-globin locus by using chIp-chip analysis of K562 cells. We found that GATA-1 binds in a region encompassing the HS2 core element, as was previously identified, and an additional region of GATA-1 binding upstream of the gammaG gene. This approach will be of general utility for mapping transcription factor binding sites within the beta-globin locus and throughout the genome.

The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.

ENCODE comprises thousands of functional genomics datasets, and the encyclopedia covers hundreds of cell types, providing a universal annotation for genome interpretation. However, for particular applications, it may be advantageous to use a customized annotation. Here, we develop such a custom annotation by leveraging advanced assays, such as eCLIP, Hi-C, and whole-genome STARR-seq on a number of data-rich ENCODE cell types. A key aspect of this annotation is comprehensive and experimentally derived networks of both transcription factors and RNA-binding proteins (TFs and RBPs). Cancer, a disease of system-wide dysregulation, is an ideal application for such a network-based annotation. Specifically, for cancer-associated cell types, we put regulators into hierarchies and measure their network change (rewiring) during oncogenesis. We also extensively survey TF-RBP crosstalk, highlighting how SUB1, a previously uncharacterized RBP, drives aberrant tumor expression and amplifies the effect of MYC, a well-known oncogenic TF. Furthermore, we show how our annotation allows us to place oncogenic transformations in the context of a broad cell space; here, many normal-to-tumor transitions move towards a stem-like state, while oncogene knockdowns show an opposing trend. Finally, we organize the resource into a coherent workflow to prioritize key elements and variants, in addition to regulators. We showcase the application of this prioritization to somatic burdening, cancer differential expression and GWAS. Targeted validations of the prioritized regulators, elements and variants using siRNA knockdowns, CRISPR-based editing, and luciferase assays demonstrate the value of the ENCODE resource.

The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.

In breast cancer, the increased stiffness of the extracellular matrix is a key driver of malignancy. Yet little is known about the epigenomic changes that underlie the tumorigenic impact of extracellular matrix mechanics. Here, we show in a three-dimensional culture model of breast cancer that stiff extracellular matrix induces a tumorigenic phenotype through changes in chromatin state. We found that increased stiffness yielded cells with more wrinkled nuclei and with increased lamina-associated chromatin, that cells cultured in stiff matrices displayed more accessible chromatin sites, which exhibited footprints of Sp1 binding, and that this transcription factor acts along with the histone deacetylases 3 and 8 to regulate the induction of stiffness-mediated tumorigenicity. Just as cell culture on soft environments or in them rather than on tissue-culture plastic better recapitulates the acinar morphology observed in mammary epithelium in vivo, mammary epithelial cells cultured on soft microenvironments or in them also more closely replicate the in vivo chromatin state. Our results emphasize the importance of culture conditions for epigenomic studies, and reveal that chromatin state is a critical mediator of mechanotransduction.

The AIRE gene plays a key role in the development of central immune tolerance by promoting thymic presentation of tissue-specific molecules. Patients with AIRE-deficiency develop multiple autoimmune manifestations and display autoantibodies against the affected tissues. In 2016 it was reported that: i) the spectrum of autoantibodies in patients with AIRE-deficiency is much broader than previously appreciated; ii) neutralizing autoantibodies to type I interferons (IFNs) could provide protection against type 1 diabetes in these patients (Meyer et al., 2016). We attempted to replicate these new findings using a similar experimental approach in an independent patient cohort, and found no evidence for either conclusion.