The organization and folding of chromatin within the nucleus can determine the outcome of gene expression. Recent technological advancements have enabled us to study chromatin interactions in a genome-wide manner at high resolution. These studies have increased our understanding of the hierarchy and dynamics of chromatin domains that facilitate cognate enhancer–promoter looping, defining the transcriptional program of different cell types. In this review, we focus on vertebrate chromatin long-range interactions as they relate to transcriptional regulation. In addition, we describe how the alteration of boundaries that mark discrete regions in the genome with high interaction frequencies within them, called topological associated domains (TADs), could lead to various phenotypes, including human diseases, which we term as “TADopathies.” DNA is bound by a variety of histone proteins, noncoding RNAs, and transcription factors, collectively called chromatin. Packaging of chromatin within a eukaryotic nucleus can bring distant loci together, which may affect their transcriptional state. Numerous experiments have shown that the juxtaposition of two distant loci is not random, and their functional outcome depends upon the nature of interacting loci and the histone modifications they harbor. This information is encoded in the sequence of the loci that determines the transcription factors that bind to the DNA. Histone-modifying enzymes and complexes play a crucial role in regulating chromatin accessibility . UndeMuch of our understanding of eukaryotic gene expression has been gained by characterizing gene regulatory elements. Apart from the promoters that are quintessential for gene expression, distal regulatory elements control gene expression in a spatiotemporal manner. These elements include the following: “repressors,” which can inhibit gene promoters; “insulators,” which obliterate enhancer–promoter interaction when present between them, thus preventing non-cognate enhancer–promoter crosstalk; “barriers,” which can also be considered as another type of insulator, which stop heterochromatin spreading and maintain borders between euchromatin and heterochromatin regions ; and “enHow an enhancer identifies its target promoter in three-dimensional nuclear space still remains largely unknown. Several mechanisms have been proposed that explain enhancer–promoter interactions based on direct contact and non-contact models: (1) juxtaposition of enhancer and promoter by looping out the intervening region; (2) enhancer tracking over the intervening region to identify its target promoter; (3) chromatin modifications over large regions regulated through chromatin modifiers that act as a “link” between the enhancer and promoter ,7. To daSHH) limb enhancer, which resides over 900 kb away from SHH, was shown to physically interact with its promoter in developing mouse limbs using DNA-FISH .,26.25,26Chromatin condensation is directly linked to transcription, with closed chromatin representing transcriptionally repressed regions and open chromatin having an active transcription state. DNA regions that are tethered to inner nuclear periphery via interactions with the lamin B1 protein are called lamina-associated domains (LADs) . These aPtn), sex-determining region Y (SRY)-box 6 (Sox6), and neuropilin1 (Nrp1) genes show the largest loss of laminB1 association as they reposition toward nuclear interiors for transcriptional upregulation. Subsequently, the replication timing of these loci also switches from late to early upon differentiation . On. On53]. 7 (Bmp7) . Mouse rEnhancers often transcribe into RNA, termed eRNAs . StudiesFoxA1). Knockdown of FoxA1 reduced androgen receptor binding and eRNA transcription. This also resulted in the recruitment of the mediator subunit 12 (Med12) that facilitated enhancer looping interaction with a new set of promoter targets [In an enhancer–promoter looping model, eRNAs could play a role in loop stabilization . Support targets ,62, indi targets . HoweverSHH locus in a patient with features of a holoprosencephaly spectrum caused SHH to adopt a different limb enhancer in its new location, leading to its ectopic expression and subsequently causing various limb malformations [GATA2) and ecotopic viral integration site 1 (EVI1) repositions a GATA2 enhancer near EVI1 leading to its ectopic expression while reducing GATA2 expression [Translocations or inversions of genes or enhancers can lead to abnormal enhancer–promoter interactions and subsequent phenotypes, including human disease. For example, an inversion of the rmations . Taking pression , thus acOCA2) gene. Using 3C, a strong interaction between the enhancer and the OCA2 promoter was observed for the T pigmentation-associated allele versus a weak interaction for the C unassociated allele (SHH) limb enhancer, in which mutations in humans, mice, dogs, cats, and chickens were shown to lead to various limb malformations [Nucleotide changes in enhancers or promoters that prevent them from interacting could potentially also lead to human disease and other phenotypes. One such example is a human pigmentation-associated single nucleotide polymorphism (SNP), rs12913832, which is located in a postulated enhancer of oculocutaneous albinism II rmations ,70. Intermations . This obLMNB1) now lead to its misexpression and, subsequently, ADLD . This deletion leads to a loss of a TAD  and causly, ADLD .WNT6, IHH, EPHA4, and PAX3 revealed that it is structurally divided into three independent TADs: WNT6/IHH-TAD, EPHA4-TAD, and PAX3-TAD. Chromosomal aberrations that include deletions, inversions, and duplications that alter the TAD boundaries were shown to cause a variety of limb malformation phenotypes in humans. Analysis using 4C-seq of both patient-derived fibroblasts and mice engineered to model these aberrations showed that the deletions, duplications, and inversions encompassing the TAD boundaries of this locus lead to ectopic expression of surrounding genes. Deletions designed to spare the TAD boundaries but that remove the majority of the sequence that is affected in the patients did not result in any overt limb phenotype. This suggests that the loss of spacing or distance between enhancer and promoter does not cause the limb phenotype, but rather, the loss of TAD boundaries does.Another example of TAD boundary disruption that leads to human disease is the human chromosome 2q35-36 locus, which is associated with several different limb malformations in humans . InvestiThese results provide strong evidence that disruption of TAD boundaries as a result of chromosomal aberrations could be a cause of human disease, termed here as TADopathies. The functional components that make up these TAD boundaries are still not well understood. TADs are likely to be maintained by a variety of nuclear proteins. Mutations in these proteins that affect their binding could also result in altered gene expression and various human diseases.Despite numerous studies and technological advancements, we still do not have a comprehensive understanding of the factors that mediate chromatin interactions between loci. Techniques investigating structural organization of chromatin need to be integrated with finite transcriptional measurements. Imaging studies probing long-range interactions yield only a subset of nuclei where co-localization can be observed. Biochemical methods such as Hi-C generate genome-wide interactions on the basis of pairwise enrichment in a population of cells. Recently, single-cell analytical approaches have been developed to bridge this gap between microscopic and biochemical methods ,74. A siThere could be several additional enhancer–promoter interaction-associated factors that have yet to be identified. Numerous additional structural proteins, gene regulatory elements, or even DNA sequences that are involved in these interactions could exist. For example, recent computational work suggests that DNA G-quadruplexes (a motif of three to four consecutive guanines) could be involved in enhancer–promoter interactions . Studies


These epigenetic aberrations can be readily reversible and responsive to both synthetic agents and natural components of diet. A source of one of such diet components are cruciferous vegetables, which contain high levels of a number of glucosinolates and deliver, after enzymatic hydrolysis, sulforaphane and other bioactive isothiocyanates, that are involved in effective up-regulation of transcriptional activity of certain genes and also in restoration of active chromatin structure. Thus a consumption of cruciferous vegetables, treated as a source of isothiocyanates, seems to be potentially useful as an effective cancer preventive factor or as a source of nutrients improving efficacy of standard chemotherapies. In this review an attempt is made to elucidate the role of sulforaphane in regulation of gene promoter activity through a direct down-regulation of histone deacetylase activity and alteration of gene promoter methylation in indirect ways, but the sulforaphane influence on non-coding micro-RNA will not be a subject of this review.Carcinogenesis as well as cancer progression result from genetic and epigenetic changes of the genome that leads to dysregulation of transcriptional activity of genes. Epigenetic mechanisms in cancer cells comprise (i) post-translation histone modification ( Epigenetic aberrations can be relatively readily reversible and responsive to environmental factors, including diet, they have been identified as auspicious targets for new, additional strategies of carcinogenesis prevention or for improvement of efficacy of current standard chemotherapy. Many natural dietary agents, consisting of bioactive compounds, have been shown to be effective nutraceuticals in cancer prevention due to mediation between favorable epigenetic changes .,56.PTEN egative) .hTERT (telomerase reverse transcriptase) promoter, which leads to transcriptional repression of the gene in breast cancer cell lines [hTERT is connected with increased expression of the gene, whereas hypomethylation of this regulatory region of hTERT decreases its transcription. This character of hTERT gene is in contrast to the common model of transcriptional gene activity regulation in which the methylation of cytosine in gene promoters results in gene silencing. The hTERT gene is frequently regulated in an epigenetic manner and is expressed in over 90% of human cancers, but not in normal somatic cells [Results of other studies have shown that SFN suppresses methylation in the ll lines . This faic cells .DNMTs mRNA expression or protein may depend on the type of cancer cells, dose and time of exposure to the compound delivered from crucifers. For example, in LnCaP prostate cancer cells (androgen–dependent) SFN significantly decreases expression of DNMT1 and DNMT3b on mRNA and protein level but the plant HDI has slight effect on DNMT1 protein level in PC3 and BPH-1 prostate cancer cells [DNMT1. This fact has been confirmed by studies in which changes in methylation and expression of selected tumour suppressor genes in MCF-7 breast cancer cells exposed to SFN at 10 μM concentration for 96 h have not been associated with any relevant effects on DNMT1 mRNA level [Some authors point out that decreases in er cells . SimultaNA level .p21 expression. It is possible that activation of the p21 gene also depends on the methylation level of the STAT-binding site at the promoter, because hypermethylation of the p21 gene at the proximal STAT-binding site correlates with decreases in p21 expression [p21 gene mRNA level is associated with no change of DNMT1 mRNA level, in contrast to the effect of 5-Aza-dCyt [Results of studies with mammalian cells treated with SFN indicate, that reduction of DNMT1 can run in indirect pathways and seems to be modulated by p21 after HDAC inhibition . It is npression . MoreoveAza-dCyt ,42.DNMT1 expression and from cross-talk between histone modification and DNA methylation. This cooperation can lead to new arrangement of chromatin structure, favorable towards factors enhancing the transcriptional process. It has been confirmed in studies showing that DNMT1 interact physically with HDAC1 or 2, and that DNMTs recruit class I HDACs to function as co-repressors in the transcription of tumour suppressor genes [p21 at the mRNA and protein level. The reactivated p21 protein competes DNMT1 out from the replication complex [DNMT1 expression created probably either by reactivation of RARβ2 due to HDAC inhibition, or by reactivation of PTEN blocking the intracellular signaling pathways MAPK/AP-1, or by other hitherto unknown mechanism. It seems that DNA hypomethylation is an effect subsequent to SFN action, where crucial roles are played by the DNMT1, p21, RARβ and PTEN proteins as illustrated in In summary, most authors suggest that a downregulation of promoter methylation of certain genes, after treatment with SFN, results from decrease in or genes . On the  complex ,46. ThisThe above-mentioned findings provide additional insight into the mechanisms by which SFN may act as a direct and/or indirect epigenetic modulator of gene transcriptional activity. The sulforaphane effect on regulation of gene promoter activity probably acts through a direct downregulation of its histone deacetylase activity followed by alternation in the gene promoter methylation in indirect ways.in vivo and in vitro studies are necessary to fully elucidate chemopreventive and anticancer properties of SFN and other isothiocyanates.Thus a consumption of cruciferous vegetables, treated as a source of bioactive isothiocyanate, such as sulforapane, seems to be potentially useful as an effective preventive factor reducing risk of cancer, or as a supply of nutrients slowing down cancer development or improving efficacy of standard chemotherapies. What should be noted, however, is that a critical determinant of SFN and other isothiocyanates efficacy is their bioavailability from dietary sources. A crucial factor in isothiocyanates absorption is release of isothiocyanates from their glucosinolate precursors by myrosinase. This process might be intensified by chopping or chewing of cruciferous vegetables, but on the other hand the enzyme can be inactivated by heat. In dietary supplements containing extracts of broccoli or other cruciferous vegetables the myrosinase is often inactivated and bioavailability of isothiocyanates from these supplements is limited. Results of studies devoted to evaluation of SFN absorption in healthy humans following consumption of broccoli sprouts and myrosinase-treated broccoli sprout extract indicate higher bioavailability of SFN from fresh broccoli sprouts. The determined levels of total SFN metabolites in plasma and urine have been significantly (3–5 times) higher in broccoli sprouts consumers compared to myrosinase-treated broccoli sprout extract consumers but neither of the two SFN forms has caused a significant decrease in HDAC activity. These observations indicate that the hydrolysis of glucosinolates to isothiocyanates is not the only factor influencing their absorption and, as authors suggest, food matrix and meal composition could also affect isothiocyanate absorption . Further


BU-1 locus in REV1-deficient cells, despite its location 3.5 kb from the transcription start site (TSS). The effect of the G4 is dependent on it residing on the leading strand template, but is independent of its in vitro thermal stability. Moving the motif to more than 4 kb from the TSS stabilises expression of the gene. However, loss of histone modifications (H3K4me3 and H3K9/14ac) around the transcription start site correlates with the position of the G4 motif, expression being lost only when the promoter is affected. This supports the idea that processive replication is required to maintain the histone modification pattern and full transcription of this model locus.REV1-deficient chicken DT40 cells are compromised in replicating G quadruplex (G4)-forming DNA. This results in localised, stochastic loss of parental chromatin marks and changes in gene expression. We previously proposed that this epigenetic instability arises from G4-induced replication fork stalls disrupting the accurate propagation of chromatin structure through replication. Here, we test this model by showing that a single G4 motif is responsible for the epigenetic instability of the  However, evidence is mounting from studies using specific antibody or small molecule-mediated detection methods to support their formation in vivo  Is epigenetic instability induced by G4 motifs on both the leading and lagging strand? (ii) How do the in vitro biophysical characteristics of G4 motifs relate to their ability to cause epigenetic instability in REV1-deficient cells? and (iii) How does the distance of the G4 motif from the TSS influence the histone modification pattern and stability of expression of the BU-1 locus? Together, the answers help build a picture of the interplay between the replication fork, the G4 motif and the epigenetic landscape of the locus. Our data also provide direct evidence of a link between loss of histone modifications due to interruption of DNA replication and inability to maintain high-level gene expression.Here, we explore some predictions of this model by expanding our study of an actively expressed locus, BU-1  locus . The locus lies within a short (c. 50 kb) early constant timing region and is surrounded by two stretches replicated just before it , by expanding individual Bu-1ahighrev1:BU-1AΔG4 cells for 20 generations and then measuring the proportion of each clone that had become Bu-1alow by flow cytometry. We have previously shown that loss of Bu-1a protein expression is explained by loss of Bu-1a transcript and that there is a direct correlation between Bu-1a transcript and the percentage of Bu-1a loss variants in a population  or chromatin accessibility  also supporting there being no increase in chromatin compaction. Moving the G4 motif 1 kb further away from the TSS, to +4.5 kb, results in loss of H3K4me3 and H3K9/14ac in the body of the gene (+0.5 to +1.0 kb) but, surprisingly, not 5′ of the TSS (−0.5 kb)  Fig A and B, ants Fig . Moving ants Fig A and B aants Fig . In neitin vivo.In this study, we have exploited a genetically tractable system to explore the relationship between G4 motifs and replication-dependent instability of gene expression. In doing so, we have simultaneously gained insight into the role of processive replication in maintaining transcriptional states and created a sensitive assay that monitors problems with the replication of G4-forming DNA sequences BU-1 locus in REV1-deficient cells is dependent on the presence of a single G4 motif located at a considerable distance (3.5 kb) from the transcriptional start site. Although some G4 motifs have been linked with the regulation of gene expression  suggests that the frequency of events that lead to loss of Bu-1a expression is low, in the order of 0.02, and, despite employing a variety of approaches, we have not been able, thus far, to detect directly an enrichment of single-stranded DNA in the BU-1 locus of rev1 cells. It is possible that it has a relatively short half-life. The fact that Bu-1a is likely to be replicated bidirectionally would mean that a single-stranded region formed by a fork from the 3′ end of the locus arresting at the +3.5 G4 may be rapidly replicated by a fork arriving from the 5′ end of the locus, but with the parental nucleosomes already displaced, thereby ‘fixing’ the mark loss.We have suggested that a key consequence of the delayed replication of the +3.5 G4 motif in et al, et al, et al, Our data confirm the prediction of our model that epigenetic instability is dependent on interrupting leading strand replication. While we have previously argued that REV1 may act preferentially on the leading strand , suggesting that loss of Bu-1a expression is not a consequence of active heterochromatinisation.How could maintaining a pre-existing transcriptional state depend on processive replication? Fork arrest at tight protein–DNA complexes in 9me3 Fig C or incrBU-1 locus is sensitive to the position of the G4 motif relative to the TSS, consistent with a fixed zone in which histone marks are disrupted and that is defined by the position of the G4 motif . Thus, when the G4 motif is placed +4.5 kb from the TSS, we observe loss of H3K4me3 and H3K9/14ac within the body of the gene, despite expression indistinguishable from wild-type cells. This result is consistent with the pattern of histone modifications being directly influenced by the position of the replication stall rather than by transcription. It also suggests that the presence of a ‘wild-type’ level of H3K4me3 and H3K9/14ac within the body of the gene is not essential for its full and stable expression. Interestingly, H3K36me3 is diminished only when the G4 motif is in the +3.5 kb position and H3K4me3 is lost at the promoter and expression of Bu-1a is unstable, suggesting that H3K36me3 is indeed likely to correlate with transcriptional activity. Together, these data suggest that H3K4me3 at the promoter of BU-1 may be required to maintain fully active gene expression. Experiments in Dictyostelium and Xenopus have also provided evidence that H3K4me3 is required to maintain fully active transcription through cell division . The PCR product was cloned into pBluescript and the region between HindIII and SacI  at a 1:10 dilution and anti-Bu-1b directly conjugated to FITC . Cells were analysed by flow cytometry using an LSRII cytometer (Becton-Dickinson). To carry out fluctuation analysis, single cells staining positive for Bu-1a were sorted using a MOFLO (Dako-Cytomation) sorting cytometer and grown for 20 generations before staining and analysis using flow cytometry as above .Cells from cultures whose confluency was between 0.4 × 10et al, et al, Chromatin immunoprecipitation (ChIP) was performed as previously described  containing 1 mM of EDTA and 100 mM of either LiCl or KCl. The samples were annealed by being heated at 95°C for 10 min and slowly cooled to room temperature. Scans were performed over the range of 200–320 nm at 20°C. Each trace is the result of the average of three scans taken with a step size of 1 nm, a time per point of 1 s and a bandwidth of 1 nm. A blank sample containing only buffer was treated in the same manner and subtracted from the collected data. The data were finally zero-corrected at 320 nm.m) values were obtained from the minimum of the first derivative of the melting curve.UV melting curves were collected using a Varian Cary 400 Scan UV-visible spectrophotometer by following the absorbance at 295 nm. Oligonucleotides solutions were prepared at a final concentration of 4 μM in 10 mM lithium cacodylate (pH 7.2) containing 1 mM EDTA and 100 mM KCl. The samples were annealed by heating to 95°C for 10 min and then slowly cooled to room temperature. Each sample was transferred to a 1-cm path-length quartz cuvette, covered with a layer of mineral oil, placed in the spectrophotometer and equilibrated at 5°C for 10 min. Samples were then heated to 95°C and cooled to 5°C at a rate of 0.5°C/min, with data collection every 1°C. Melting temperature  for DNA microarrays studies. Nascent strands were isolated by BrdU-immunoprecipitation and quantified by qPCR. For DNA microarrays, in order to obtain sufficient DNA, immunoprecipitated nascent strands were amplified by whole-genome amplification  and then hybridised on Agilent Chicken Genome CGH Microarrays 4X180K, custom microarray design with genome reference Gallus gallus V3 May 2006 (Hassan-Zadeh


Silent chromatin in budding yeast is propagated from one generation to the next, even though ‘silenced’ genes are occasionally expressed. Related research article Dodson AE, Rine J. 2015. Heritable capture of heterochromatin dynamics in Saccharomyces cerevisiae. eLife4:e05007. doi: 10.7554/eLife.05007Image A new assay employs a permanent switch from red to green fluorescence to mark yeast cells that ‘derepress’ silenced genesIf a tree falls in a forest and no one is there to hear it, does it make a sound? While questions about the perception and generation of sound can be debated endlessly, one thing is certain: a tree did fall. If a tree only swayed in a forest, how would we know? Sometimes events transpire that leave no evidence of their occurrence.eLife, Anne Dodson and Jasper Rine—from the University of California, Berkeley—report that budding yeast occasionally breaks this wall of silence (DNA in eukaryotic cells is wrapped around histone proteins to form a structure called chromatin. Heterochromatin is a more condensed form of chromatin that silences the genes encoded in the DNA, and is inherited by new cells via a code of chemical marks on the histones and sometimes the DNA. Female mammals convert one of their two X chromosomes into heterochromatin, which stops them from expressing a double dose of all X-linked genes for a lifetime. Likewise, a heterochromatin-like structure in budding yeast, termed ‘silent chromatin’, controls the yeast's sexual identity via faithful gene silencing. Now, in  silence .Saccharomyces cerevisiae, cells of opposite mating-types fuse with one another. A yeast cell's mating type can be MATα or MATa, depending on which pair of genes is at the MAT locus in its genome (MAT loci’ as templates to replace the genes at the MAT locus when switching between mating types. The hidden MAT loci have been studied for decades to understand how chromatin shuts off genes.During mating of the budding yeast, s genome . IdenticMAT loci from all other locations in the yeast genome (Nearby sections of DNA, termed silencers, distinguish the hidden t genome . Proteint genome . An addiTo the casual observer, silent chromatin might thus seem inert and unchanging. Two previous observations, however, suggested that this is not the case. First, silencing proteins constantly move onto, and off of, heterochromatin . Second,MAT loci (Do the dynamic properties of silent chromatin ever permit silenced mating-type genes to be expressed? To address the question, Dodson and Rine developed an elegant assay that means even a rare event—a momentary loss of silencing in this case—is marked in a way that persists and is easily detectable. They introduced the coding sequence of an enzyme called Cre recombinase into the hidden MAT loci . On a diMAT loci .MAT loci. Mutants without the gene for Hst3 develop seven times as many green sectors as wild-type yeast, but fail to register derepression in conventional assays (This assay revealed that ‘silenced’ yeast genes are expressed, or ‘derepressed’, in wild-type cells, as Dodson and Rine observed green fluorescent sectors within otherwise red fluorescent yeast colonies. Each green sector marks when silencing was briefly lost, and looking at how often these sectors appeared suggests that such events are rare, occurring roughly once out of every 1000 cell divisions. The assay was used to reveal that Hst3, an enzyme closely related to Sir2 that also modifies histones, also contributes to silencing of the hidden l assays . This ilDodson and Rine also looked at how often they could detect the expression of Cre recombinase within individual cells using a technique called ‘single-molecule RNA FISH’ . In mostSilencing is viewed as the culmination of three steps: a silent state is first established, then maintained and finally passed on to the cell's descendants. Sir2, Sir3 and Sir4 participate in all three steps, but Sir1 is different. In mutant yeast without Sir1, silencing is lost and not restored efficiently in some cells, whereas in other cells silencing is propagated from generation to generation. This suggests that silencing cannot be established well without Sir1 . Dodson MAT loci that is dynamic and permits breaks in the silence that had never been heard before now.Evolution has not selected for a more durable silent chromatin, most likely because of a need to balance silencing with other cellular processes. Silent chromatin must be flexible enough to permit the passage of the DNA replication machinery and allow mating-type switches. Moreover, if the Sir protein complex could associate with histones tightly enough to block all gene expression, then non-specific binding by the complex might silence the wrong genes elsewhere in the genome. Instead, evolution settled upon a heterochromatin-like structure at the hidden


The human genome is tightly packaged into chromatin whose functional output depends on both one-dimensional (1D) local chromatin states and three-dimensional (3D) genome organization. Currently, chromatin modifications and 3D genome organization are measured by distinct assays. An emerging question is whether it is possible to deduce 3D interactions by integrative analysis of 1D epigenomic data and associate 3D contacts to functionality of the interacting loci. Here we present EpiTensor, an algorithm to identify 3D spatial associations within topologically associating domains (TADs) from 1D maps of histone modifications, chromatin accessibility and RNA-seq. We demonstrate that active promoter–promoter, promoter–enhancer and enhancer–enhancer associations identified by EpiTensor are highly concordant with those detected by Hi-C, ChIA-PET and eQTL analyses at 200 bp resolution. Moreover, EpiTensor has identified a set of interaction hotspots, characterized by higher chromatin and transcriptional activity as well as enriched TF and ncRNA binding across diverse cell types, which may be critical for stabilizing the local 3D interactions. The human genome is highly organized, with one-dimensional chromatin states packaged into higher level three-dimensional architecture. Here, the authors present EpiTensor that can identify 3D spatial associations from 1D epigenetic information. Epigenomic modifications and 3D genomic interactions are tightly associated but currently they are measured by distinct technologies and an integrative interpretation is still lacking56On the other hand, epigenomic assays, including chromatin modification ChIP-seq, RNA-seq and DNaseI-seq, map chromatin features along the linear genome. The current state-of-the-art analyses focus on interpreting the epigenomic data in a 1D space along the linear genome. For example, the epigenomic state of a specific locus is defined by the combination of epigenomic signals, which leads to linear segmentation of the genome; sequencing reads of epigenomic modifications are typically visualized as different tracks in a genome browser8111213Here, we present EpiTensor, a novel unsupervised computational method to derive 3D interactions between distal genomic loci from 1D epigenomic data. EpiTensor provides a resolution significantly higher than that provided by Hi-C experiments. The current implementation provides a resolution of 200 bp, which can be further extended to even higher resolution. This work represents a systematic and unbiased attempt to infer 3D spatial patterns from 1D epigenomic data, which provides a new method complementary to Hi-C and ChIA-PET. As most of the interactions are within topologically associating domains (TAD), we constrain our analysis within TADs and show that promoter–enhancer, promoter–promoter and enhancer–enhancer associations within identified from EpiTensor are highly concordant with those from Hi-C, ChIA-PET and eQTL experiments. Furthermore, EpiTensor identified a set of interaction hotspots that have many interacting partners. We demonstrate these hotspots having higher chromatin and transcriptional activity across cell types are preferably bound by TFs and lncRNAs, and are enriched with TF motifs.mnk to model multi-dimensional epigenomic data, where m, n, k are the indices of cell types, assays and genomic loci, respectively  is shown in Ulocus represent spatial association patterns and peaks on the eigenvectors correspond to the associated regions  Peak pairs were chosen with a false discovery rate ≤0.05 based on the Qrandom distribution.To identify spatially associated pairs, we repeated the following four steps for each eigenlocus: (1) We called peaks in each eigenlocus using MACS2 software packageTo characterize the spatial associations identified by EpiTensor, we categorized them into groups that contain promoters, enhancers, exons, introns and intergenic regions . Promoteet al. studyet al. paper521To examine whether these five groups of associations are resulted from physical interactions, we first compared them with interactions detected by Hi-C experiments. We downloaded the Hi-C data in IMR90 cells from Jin To further illuminate the success of EpiTensor in identifying the spatial associations resulted from physical interactions, we compared its performance on predicting promoter–enhancer interactions with two other commonly used methods: nearest-gene assignment and a correlation-based methodNext, we compared EpiTensor prediction with another set of high-resolution Hi-C data reported in ref. P value <10−14 by binomial test) than those from random pairs . Promoter–enhancer interactions from EpiTensor were significantly enriched for SNPs correlated with gene expression levels  on 14 randomly selected pairs from EpiTensor. We achieved a 93% validation rate (13 out of 14), compared with a detection rate of 50% by Hi-C  and DNaseI-seq profiles between hotspots and non-hotspots in each of the five cell types (non-hotspots are promoters/enhancers other than hotspots). Hotspots showed slightly stronger enrichment of H3K4me1, H3K4me3, H3K27ac and DNaseI-seq in comparison with non-hotspots , suggestP value <2.2 × 10−16, Wilcoxon test). These results indicate that hotpots have higher chromatin activity than non-hotspots across cell types.However, much more significant difference was observed when we pooled together the DNaseI-seq and the six core histone mark ChIP-seq data in 82–125 cell types; including cell lines, primary cells and tissue see . We overP value <2.2 × 10−16, Wilcoxon test).Second, hotspot promoters are associated with highly expressed genes across cell types. We collected Reads Per Kilobase of transcript per Million mapped reads (RPKM) values from RNA-seq data in 57 cell types see  and counP value <2.2 × 10−16, Wilcoxon test). Previous studies have shown that TF bindings are not uniformly distributed but occupy specific loci referred as high occurrence target regions3738394142Third, hotspots are enriched for TF binding sites. We collected the ChIP-seq data for 49, 98 and 77 TFs mapped by the ENCODE consortiumThese hotspots are also enriched for TF motifs. As ChIP-seq data are available only for a limited number of TFs, we collected a comprehensive set of sequence motifs known to be recognized by TFs and other DNA binding proteins from five databases (see ‘Methods' section). We computed the score of each motif in hotspots and non-hotspots. NEAT1 and MALAT1. Both NEAT1 and MALAT1 were shown to bind to active chromatin sitesMALAT1 localizes to nuclear speckles (interchromatin nuclear domains enriched for serine/arginine splicing factors)NEAT1 is required for formation of paraspeckles (nuclear bodies close to nuclear speckles)P value <9.2 × 10−5, hypergeometric test). This significant difference suggests preferred binding of these two lncRNAs to the hotspots. Both NEAT1 and MALAT1 are important for transcription and the enrichment of their binding sites in hotspots is consistent with the observation that hotspots are associated with active chromatin structure across cell types.Fourth, hotspots have significant overlap with lncRNA binding sites. As lncRNAs have been shown to be important for chromatin structure organization4445Fifth, hotspots have significant overlap with super enhancers. We collected super enhancers in 96 human cell types/tissues. We overlapped them with each hotspot/non-hotspot and counted the number of cell types with overlapping super enhancers . Our resLast, hotspots are involved in important biological functions. In the promoter–promoter association category, the hotspot promoters are enriched with ‘chromatin organization' and ‘chromosome organization' , suggest53In summary, interaction hotspots are associated with higher chromatin and transcriptional activity across cell types. They are preferred for TF binding and are enriched with TF motifs. Furthermore, these loci are also preferably bound by lncRNAs. Interaction hotspots are linked to multiple partners and provide a topological framework for coordinated transcription or regulation of the associated regions.Our study presents the first attempt to deduce 3D spatial epigenomic patterns from 1D assays that provides a new method complementary to Hi-C and ChIA-PET. EpiTensor decodes the complex co-variation patterns of epigenomic patterns across cell types and genomic locations, which paves the way towards directly linking epigenomic state and chromosomal topology. Such co-variation relationships have previously been used to identify spatial associations but limited to promoter–enhancer interactions using specific marks232425262728Complementary to the Hi-C assays that detect physical contacts with a resolution of about 20,000–50,000 bp, EpiTensor analysis can be easily performed at a 200 bp resolution that is sufficient to pinpoint regulatory elements and their associated chromatin states . ConstraPrevious studies have shown that topological structures may exist before the modification of histones; these interactions can be captured by EpiTensor. In the integrated analysis across cell types, as long as a locus is marked by a variation in epigenetic modifications in some cell types, its interactions with other loci can be detected by EpiTensor. For example, physical contacts can exist before enhancers become active and such interactions can be naturally captured by EpiTensor because the poised or inactive enhancers are marked by H3K27me3 and this mark is removed when the enhancers become active in other cell types to regulate the target genes. In this study, we focused on identifying interactions between active promoters or enhancers that are critical for transcriptional regulation. An intriguing observation is that the EpiTensor interactions showed high concordance with active promoter–promoter, promoter–enhancer, enhancer–enhancer interactions from Hi-C data of two independent studies in 6 human cell lines and ChIA-PET data in K562 cells, indicating the power of EpiTensor to identify biologically important interactions.The interaction hotspots of promoters and enhancers are located in genomic regions with significantly higher chromatin and transcriptional activities across cell types. These hotspots are also enriched with TF and lncRNA binding as well as TF motif presence. The spatial interactions of these hotspots are highly concordant with the Hi-C, ChIA-PET and eQTL data, and the biological functions are highly relevant to chromosomal organization. Taken together, these observations indicate that the interaction hotspots identified by EpiTensor are important in linking 3D genome structure to functional activity. It is worth noting that the hotspots have little overlap with the loci that are involved in many 3D contact detected by Hi-C experiments, which is not surprising as the 3D contact loci are buried inside chromosome and the hotspots are functional sites exposed on the surface of chromosome structure. It is tempting to speculate that these hotspots are critical for stabilizing the genomes 3D topology; however, this hypothesis awaits experimental test.http://www.roadmapepigenomics.org/). The downloaded data were in BED format. The spp softwareGenome-wide maps of 16 chromatin modifications , RNA-seq and DNaseI-seq in hESCs, TBL cells, MSCs, NPCs and human lung fibroblast cells (IMR90) were downloaded from the website of NIH Roadmap Epigenomics project approximationUcell)TUcell=I, (Uassay)TUassay=I, and (Ulocus)TUlocus=I . In eQTL evaluation, each SNP that fell within an active enhancer in HepG2/GM12878 cells and was associated with an active gene in HepG2/GM12878 cells was considered eligible for evaluation. We compared the percentage of eQTLs that were predicted by EpiTensor with the percentage from random interaction.The eQTL data in HepG2 and GM12878 cells were obtained from the University of Chicago QTL browser (3C (chromosome conformation capture) libraries from IMR-90 cells were generated according to standard protocols as described previously in refs http://epigenomeatlas.org. As in ref. http://genome.ucsc.edu/encode. Uniform peaks of ChIP-seq data for 49, 98 and 77 TFs in hESC, GM12878 and K562 cells, respectively, were downloaded from the ENCODE website.The core set of six histone modifications  were downloaded from NIH Roadmap Epigenomics Project website P values.For histone modification ChIP-seq, DNaseI-seq and TF ChIP-seq data, their peaks were overlapped onto hotspots and non-hotspots, and the number of cell types with overlapping peaks was counted for each hotspot and non-hotspot. Distributions of the number of cell types were compared between hotspots and non-hotspots and Wilcoxon test was used to compute http://epigenomeatlas.org. A cut-off of 5 was used to classify each gene into expressed or un-expressed category in each cell type, and the number of cell types with expressed genes was counted for each hotspot and non-hotspot. Distributions of the number of cell types were compared between hotspots and non-hotspots, and Wilcoxon test was used to compute P values.For RNA-seq data, processed RPKM values for RNA-seq data in 57 cell types were downloaded from the NIH Roadmap Epigenomics Project data portal P values.For motif-enrichment analysis, a library of 292 non-redundant motifs were assembled by combining the DNA binding motifs in TransfacNEAT1 and MALAT1 were downloaded from ref. P value.For lncRNA binding enrichment analysis, the binding peaks of http://bioinfo.au.tsinghua.edu.cn/dbsuper/index.php). These super enhancers were overlapped onto hotspots and non-hotspots, and the number of cell types with overlapping super enhancers was counted for each hotspot and non-hotspot. Distributions of the number of cell types were compared between hotspots and non-hotpots and Wilcoxon test was used to compare the P values.For super enhancer data, we downloaded super enhancers in 96 human cell types/tissues from the dbSUPER website .Supplementary Figures 1-14, Supplementary Tables 1-4, Supplementary Note 1 and Supplementary References


Moreover, by RPC6-knockdown, we showed a direct functional link between RNAPIII transcription and BLV miRNAs expression. Furthermore, both the tumor- and the quiescent-related isoforms of RPC7 subunits were recruited to the miRNA cluster. We showed that the BLV miRNA cluster was enriched in positive epigenetic marks. Interestingly, we demonstrated the in vivo recruitment of RNAPII at the 3′LTR/host genomic junction, associated with positive epigenetic marks. Functionally, we showed that the BLV LTR exhibited a strong antisense promoter activity and identified cis-acting elements of an RNAPII-dependent promoter. Finally, we provided evidence for an in vivo collision between RNAPIII and RNAPII convergent transcriptions. Our results provide new insights into alternative ways used by BLV to counteract silencing of the viral 5′LTR promoter.Bovine leukemia virus latency is a viral strategy used to escape from the host immune system and contribute to tumor development. However, a highly expressed BLV micro-RNA cluster has been reported, suggesting that the BLV silencing is not complete. Here, we demonstrate the  Bovine leukemia virus (BLV) is a B-lymphotropic oncogenic deltaretrovirus infecting cattle that shares common biological and structural features with the human T-cell leukemia virus I and II (HTLV-I and II)  and is regulated by cellular transcription factors for which several binding sites have been identified in the LTR9101112131415161718Recent publications from two independent laboratories have identified, by bioinformatics analysis and deep sequencing, a cluster of 10 micro-RNAs (miRNAs) encoded by the BLV genome26in vivo recruitment of the RNAPII and RNAPIII complexes to the BLV genome. We demonstrated the recruitment of a bona fide RNA polymerase III at the BLV miRNA cluster through a canonical type 2 RNAPIII promoter similar to the one responsible for transfer RNA (tRNA) transcription. We also established a direct functional link between BLV miRNAs expression and RNAPIII transcriptional activity. Next, we showed that both tumor- and quiescent-related isoforms of RNAPIII were recruited to the miRNA cluster and that the miRNA cluster exhibited a profile of positive epigenetic marks (histone acetylation and DNA hypomethylation). Interestingly, in addition to the RNAPIII recruitment, we demonstrated an RNAPII recruitment at the junction between the 3′LTR and the host genome which was also associated with positive epigenetic marks typical of transcriptionally active promoters. Therefore, we tested the potential promoter activity of the LTR and demonstrated that this region was able to drive transcription in the antisense orientation in the nucleosomal context of episomally replicating constructs through a new RNAPII-dependent promoter. Importantly, ChIP-seq experiments performed in a BLV-infected cell line confirmed the high RNAPIII recruitment to the BLV miRNA cluster and the RNAPII occupancy just downstream of this region, suggesting a collision phenomenon between these two polymerase machineries and stalling of RNAPII.In the present report, we investigated the et al. have identified by bioinformatics analyses RNAPIII initiation cis-elements in the BLV miRNA clustercis-regulatory elements are functional in the context of 293T cells transformed with plasmids coding for BLV miRNA2627in vivo recruitment to the BLV provirus of RNAPIII by performing chromatin immunoprecipitation (ChIP) assays. For this purpose, we prepared chromatin from the latently BLV-infected L267 cell line and immunoprecipitated the largest RNAPIII subunit (RPC1) using a specific antibody. As controls, we performed ChIP assays with a purified IgG to measure the aspecific background and with an antibody directed against the largest RNAPII subunit (RPB1). Next, purified DNA was amplified by real-time quantitative PCR with oligonucleotide primers hybridizing to thirteen specific regions along the BLV genome and its host environment  isolated from a BLV-infected sheep that developed leukemia. We demonstrated recruitment of RPC1 to the BLV miRNA cluster . Forty-eight hours post-transfection, cells were harvested and lysed. Total RNA and protein extracts were used in RT-qPCR and western blot experiments to measure BLV miRNAs expression levels and RPC6 protein levels, respectively.To avoid off-target effects of the shRNAs, we used two different shRNAs recognizing distinct target sites in the RPC6 mRNA. We first attempted to deplete RPC6 by transfecting or transducing latently BLV-infected L267 and YR2 cell lines. Unfortunately, due to the low transfection or transduction efficiencies in these cell lines, we were unable to show a decrease either in RPC6 protein level or in BLV miRNA transcripts level. Therefore, we performed transduction experiments in the 293T cell line, using lentiviral particles containing shRNAs against RPC6 or a non-targeting shRNA as control. Transduced cells were then transfected with a plasmid expressing the entire miRNA cluster (pmiR). As an internal control for transfection efficiency, cells were cotransfected with a plasmid expressing the Firefly luciferase mRNA level  have been found to encode two isoforms of RPC7  defining two different RNAPIII complexesFollowing a duplication event in an ancestor of vertebrates, 2 genes . As shown in As positive controls, we amplified immunopurified DNA by real-time quantitative PCR with oligonucleotide primers hybridizing in three known RNAPIII-dependent genes  to identify putative CpG islands in the region of the miRNA cluster. The three prediction tools identified a CpG island containing the BLV miRNA cluster and spanning a region from nucleotide (nt) + 6342 to nt + 6833 (nt + 1 defined as the first nucleotide of the 5′LTR after retrotranscription). Then, we evaluated the DNA methylation status of each CpG dinucleotide of the BLV miRNA cluster in the context of integrated proviruses present in L267 and YR2 cells by treating genomic DNA with sodium bisulfite. Our results showed that, except for the third and the fourth CpG located upstream of the first BLV pre-miR, the miRNA cluster was not methylated in both the L267  of the BLV LTR sequence in the antisense orientation to identify specific cis-regulatory elements present in RNAPII-dependent promotersTo further characterize this newly identified promoter, we performed cis-regulatory motifs, we introduced individually or in combination point mutations known to abolish the motif’s function52In order to functionally characterize these hbz geneTaken together, our results demonstrate the presence of a transcriptionally active RNAPII promoter in the BLV 3′LTR, associated with positive epigenetic marks and responsible for antisense transcription, a situation reminiscent of the previously reported HTLV-I 3′LTR antisense promoter activity responsible for transcription of the viral As presented in As shown in 44Altogether, our data are further confirming RNAPII recruitment to the transcriptional promoter located at the end of the 3′LTR  and indienv gene and the pX region. Some evidence support the notion that the miRNA cluster is transcribed by the RNA polymerase III, although a direct functional link between RNAPIII transcriptional activity and BLV miRNAs expression has not been reported to date. Indeed, the algorithm used by Kincaid and coworkers has been designed to find RNAPIII-specific initiation cis-regulatory elements that have been functionally characterizedcis-regulatory elements2627in vivo, and at epigenetically and functionally characterizing its promoter. To this end, we performed chromatin immunoprecipitation assays in two BLV latently-infected ovine cell lines and in BLV-infected primary B cells.One of the major features of BLV infection is the absence of viremia due to the RNA polymerase II 5′LTR-driven transcriptional repression. Nevertheless, recent reports using bioinformatics analysisin vivo (bona fide RNAPIII at this genomic region in the context of a complete BLV provirus and confirming previous evidence2627BLV (L267LTaxSN cell line) or by PMA/ionomycin treatment .L267 is a clonal lymphoma-derived B-cell line established from a BLV-infected sheep (S267) injected with naked proviral DNA of an infectious BLV variant23The eukaryotic expression vectors pTax is a gift from Drs. Luc Willems and Richard KettmannTo construct the plasmid expressing the BLV miRNAs, genomic DNA from the L267 cell line was firstly extracted using the DNeasy Blood and Tissue kit (Qiagen) according to the protocol of the manufacturer. The miRNA cluster was then amplified by PCR using specific primers  and 125 6 cells (1 106 from the epigenetic modifications) and 5 μg of antibodies (see e of the immunoprecipitated DNA and the PerfeCTa SYBRgreen SuperMix (Quanta BioSciences). Relative quantification using standard curve method was performed for each primer pair and 96-well Optical Reaction plates were read in a StepOnePlus PCR instrument (Applied Biosystem). Fold enrichments were calculated as percentages of input values or as fold inductions relative to the values measured with IgG. Primer sequences used for quantification (see ChIP assays were performed as previously describeddies see . Quantittion see  were desChIP assays were performed as described above. Recovered DNA (~100 ng) was then used for library preparation using the TruSeq ChIP Sample Preparation protocol following Manufacter’s instructions (Illumina Technologies). Paired-end sequencing was then performed with the Illumina HiSeq 2000 instrument. More than 20 millions of single reads were obtained for RPC1 and RPB1 libraries and 10 millions of single reads for IgG library. The single-matched reads were mapped to an hybrid ovine genome (OAR v3.1) containing the BLV provirus sequence (GenBank: KT122858.1) at the L267 integration site (chr10:86299813) using bowtie2 software (-N 1 and -k 5 parameters). Finally, our results were visualized using IGV program. Reads spanning LTR-host and LTR-BLV boundaries were extracted from the alignment file using an in-house R script and ggplot2 was used to plot the ChIP-seq coverage.Genomic DNA was isolated from L267 and YR2 cell lines using the DNeasy Blood and Tissue kit (Qiagen) according to the protocol of the manufacturer. One microgram of genomic DNA was treated with bisulfite with EpiTect Bisulfite kit (Qiagen). The miRNA cluster region of BLV provirus was amplified by two successive PCR reactions (primer sequences are in the 6 cells was extracted using TRIzol (Life Technologies) followed by treatment with turbo DNAse (Life Technologies) according to the manufacturer’s protocol. Retrotranscription reactions were performed with PrimeScript RT-PCR Kit (TaKaRa) either using 200 ng of RNA and random hexamer oligonucleotides (for luciferase and GAPDH genes) or specific stemloop oligonucleotides for miRNA quantificationTotal RNA from 3 106 /10 cm dish), with the different shRNAs-containing plasmids (9 μg), the pVSV-G (2.25 μg) and the psPAX2 (6.75 μg) packaging vectors by the calcium phosphate transfection method according to the manufacturer’s protocol (Promega). 72 hours post-transfection, viral stocks were collected.VSV-G pseudotyped lentiviral particles were produced by transfection of 293T cells (5 105) were transduced in 6-well plates by 1 mL of undiluted viral stock supplemented by Polybrene at the final concentration of 8 μg/mL. 6 hours post-transduction, the medium was removed and replaced by 2 mL of complete DMEM.293T cells (4.5 105) were transfected with 3 μg of DNA (pmiR and pTK-luc) using FuGENE 6 reagent (Promega) according to the manufacturer’s protocol in 6-well plates. Raji cells (3 106) were transfected with 750 ng of DNA  as internal control) using the DEAE-dextran procedure as described previously293T cells . Data sets from RNA quantifications were analyzed using a two-tailed unpaired T test comparisons between samples and the cells transfected with the non-targeting shRNA. The threshold of statistical significance α was set at 0.05. Analyses were performed using Prism version 6.0 (GraphPad software).How to cite this article: Van Driessche, B. et al. Characterization of new RNA polymerase III and RNA polymerase II transcriptional promoters in the Bovine Leukemia Virus genome. Sci. Rep.6, 31125; doi: 10.1038/srep31125 (2016).


Here, we review the role of sucrose nonfermenting (SNF2) family enzymes in blood cell development. The SNF2 family comprises helicase-like ATPases, originally discovered in yeast, that can remodel chromatin by changing chromatin structure and composition. The human genome encodes 30 different SNF2 enzymes. SNF2 family enzymes are often part of multisubunit chromatin remodeling complexes (CRCs), which consist of noncatalytic/auxiliary subunit along with the ATPase subunit. However, blood cells express a limited set of SNF2 ATPases that are necessary to maintain the pool of hematopoietic stem cells (HSCs) and drive normal blood cell development and differentiation. The composition of CRCs can be altered by the association of specific auxiliary subunits. Several auxiliary CRC subunits have specific functions in hematopoiesis. Aberrant expressions of SNF2 ATPases and/or auxiliary CRC subunit(s) are often observed in hematological malignancies. Using large-scale data from the International Cancer Genome Consortium (ICGC) we observed frequent mutations in genes encoding SNF2 helicase-like enzymes and auxiliary CRC subunits in leukemia. Hence, orderly function of SNF2 family enzymes is crucial for the execution of normal blood cell developmental program, and defects in chromatin remodeling caused by mutations or aberrant expression of these proteins may contribute to leukemogenesis. SNF2) and mating-type switching mutant (SWI2). Analysis of chromatin from these mutants in vivo suggested that the gene products affected chromatin structure [ in vitro and to affect the binding of the transcription factor GAL4 [ SNF2 gene name (http://www.yeastgenome.org/), and we use this nomenclature in this review article.The gene encoding the first SNF2/SWI2 enzyme was discovered by the yeast geneticists Ira Herskowitz and Marian Carlson in the 1980s. These researchers named the gene two different names depending on the genetic screen used for their identification [tructure . Approxi in vitro in an ATP-dependent manner, and several enzymes remain to be tested.A SNF2 protein is an enzyme that belongs to the SF2 helicase-like superfamily, and it is the founding member of a subfamily of enzymes called SNF2-like helicases, which all harbor a conserved helicase-related motifs similar to SNF2 . The SNFBecause SNF2 enzymes regulate DNA accessibility in chromatin fibers, they are important regulators of gene expression and genome stability. SNF2 enzymes are key players in epigenetic control. They affect several epigenetic modification processes, including DNA methylation, histone modification, histone variant exchange, noncoding RNA, and higher order chromatin structure . SNF2 en in vivo and biochemical studies have been employed using different model organisms to address the detailed effects of SNF2 enzymes on chromatin. The chromatin remodeling reaction can lead to nucleosome sliding, histone exchange, histone eviction (disassembly), and nucleosome spacing to form regular arrays or nucleosome assembly depending on both which SNF2 enzyme is used and whether other cofactors, such as histone chaperones, are added to the experiments (recently reviewed in [Numerousiewed in ). The diThe hematopoietic system consists of two main cell lineages, the myeloid and the lymphoid, which both originate from hematopoietic stem cells (HSCs) . BrieflyLineage choice and blood cell differentiation are tightly regulated at several levels. Different transcription factors (TFs) have been identified that together form a regulatory network for hematopoiesis (reviewed in ). SeveraHow alterations in chromatin structure allow for temporal control of gene expression to orchestrate the different developmental programs is just now beginning to unfold. A recent study in Zebrafish by Huang et al. found several chromatin modulators, including CRCs such as BAF, ISWI, and NuRD, to be key regulators of hematopoiesis . Here, w Brg1−/− mouse embryos die at the preimplantation stage, whereas Brm−/− mice develop normally [The SWI/SNF complex has been extensively studied in model organisms, where it both activates and represses gene expression . In mammnormally . This pinormally , 19. Baf155−/− mutation die at the preimplantation stage, similar to Brg1−/− null mutation [ Baf155−/+ show defects in brain organization [ Baf155−/− homozygous mutant mice harboring a transgene expressing BAF155/SMARCC1 show a defect in blood vessel formation [BAF complexes are implicated in HSC maintenance  and regumutation . Mice henization , whereasormation . These formation . We receormation . Krastevormation .β-globin genes. This mechanism was discovered by Bultman et al. using a hypomorph point mutation (E1083G) located in the ATPase domain of SMARCA4. This mutation does not affect BAF complex integrity, ATP hydrolysis, or recruitment of the complex to the adult β-globin genes. However, this mutation does compromise the chromatin remodeling activity of SMARCA4 and leads to a closed chromatin confirmation, thereby inhibiting the transcription of β-globin genes for definitive erythropoiesis [ Brg1−/− conditional null mutation affects the expression of the α-globin locus and, hence, primitive erythropoiesis [β-globin gene expression.In the erythroid lineage, a SMARCA4-containing BAF complex is essential for both primitive and definitive erythropoiesis , 30. Eryopoiesis . However Brg1 blocks T-cell differentiation [κB-dependent remodeling of a single nucleosome in the GM-CSF promoter upon T-cell activation [The T-cells that migrate to thymocytes from bone marrow do not possess CD4 or CD8 antigen coreceptors and are thus described as double negative (DN) cells. During subsequent stages of T-cell differentiation in the thymus, the CD8 receptor is activated, followed by depression of the CD4 marker or vice versa. Once the T-cells become CD4+ or CD8+, they undergo a final maturation . The BRGntiation , 31, andntiation , 31. Mecntiation . Interesntiation . In a rentiation . Hollowativation . Baf155 and Brg1 show defects in early B-cell development. Furthermore, Baf155 deficiency results in low levels of B-cell-specific gene expression, loss of IL-7 signaling, lack of V(D)J rearrangements, and lack of activation of the TF EBF1 [Only a few studies have explored the role of BAF complexes in B-cell development. Mice deficient in TF EBF1 . Our rec TF EBF1 . Howeverβ, interacts with the BAF complex via its N-terminal activating domain to activate myeloid specific genes [Several TFs have been implicated in myeloid development and maturation. The CCAAT/enhancer binding protein (C/EBP) family of proteins participate in cell proliferation and terminal differentiation . C/EBP aic genes . Vradii ic genes .The ISWI subfamily of CRCs has a highly conserved ATPase catalytic core along with 1–3 auxiliary cofactors. In mammals, as many as seven different ISWI complexes have been described, including ACF (ATP-utilizing chromatin assembly and remodeling factor), CHRAC (chromatin remodeling and assembly complex), RSF (remodeling and spacing factor), WICH (WSTF-ISWI chromatin remodeling complex), NoRC (nucleolar remodeling complex), CERF (CECR2-containing remodeling factor), and NURF (nucleosome remodeling factor) , 43. ACF Bptf, the largest subunit of the NURF complex, displayed a significant reduction in single positive CD4+ and CD8+ T-cells. Furthermore, they observed that this defect in T-cell maturation was due to a change in the chromatin landscape as measured by DNase I hypersensitivity [Unlike the BAF complex, which is essential for T-cell development, the ISWI complex NURF is required for T-cell maturation only after the CD4+/CD8+ selection stage . Landry sitivity . Thus, t in vivo and in vitro [ in vivo to study the biological role of CHD1, its function in hematopoiesis remains elusive. However, a study by Chen et al. hints at a potential role for CHD1 in bone marrow hematopoiesis and myeloid transformation through its function at Hox genes [ Chd2 mice have a defect in HSC differentiation into the erythroid lineage and that heterozygous mutant mice develop T-cell lymphomas [Mammals harbor nine different CHD proteins, which are characterized by the presence of tandem chromodomains and a SNF2 helicase domain. CHDs are further classified into three subfamilies depending on the presence of additional domains. CHD1-2 has an additional DNA-binding domain, CHD3–5 has a dual PHD domain, and CHD6–9 has a BRK domain. They are classified into subfamilies I, II, and III, respectively . The sigin vitro , 56. Altox genes . Nagarajymphomas .α/CHD3 and Mi-2β/CHD4 as SNF2 ATPase subunits and two histone deacetylases, HDAC1 and HDAC2, and several auxiliary subunits [α), and GATAD2B (p66β) [The nucleosome remodeling and deacetylase (NuRD) complex consists of Mi-2subunits . The NuRB (p66β) , 60. TheB (p66β) , which eB (p66β) . FurtherB (p66β) . Cd79a gene encodes Igα, which is essential for immunoglobulin assembly and intracellular signaling when the B-cell receptor interacts with an antigen. The activation of the gene encoding Cd79a is regulated not only by several TFs but also via different epigenetic mechanisms [α, as the knock-down of CHD4 increases transcription, accessibility of chromatin, and DNA demethylation [ Cd79a promoter element in the presence of EBF and Pax5 TFs by binding to it, and the knock-down of SMARCA4/SMARCA2 reduces chromatin accessibility. The opposing function of NuRD and BAF complexes defines a delicate Cd79a expression balance [The B-cellschanisms . The CHDhylation . Interes balance . Similar balance .The differentiation and maturation of DN to DP T-cells are also regulated by the NuRD complex predominantly through its interaction with CHD4 ATPase. Conditional inactivation of CHD4 abrogates the expression of CD4 and reduces single positive CD4+ T-cells . FurtherWe also surveyed the existing evidence for roles of other SNF2 ATPases in hematopoiesis as follows. (1) The helicase lymphoid-specific enzyme (HELLS), also known as the lymphoid-specific helicase (LSH), is a member of the SNF2 helicase family. Loss of HELLS in mice results in a modest reduction in the transition of T-cells from the DN stage CD4−CD8− to the DP stage CD4+CD8+ . (2) EP4http://fantom.gsc.riken.jp/) [Genome-wide methodologies to study gene expression provide a holistic picture of promoter usage, levels of mRNA, and proteins within cells/tissues. To construct a comprehensive picture of the levels of expression of genes encoding epigenetic factors in various blood cells, we exploited the Cap Analysis of Gene Expression (CAGE) technique as a part of the Fantom 5 collaborative project (ken.jp/) . To bettken.jp/) , 73. Thiken.jp/) . Thus, gWe also included several leukemic cell lines in our epigenetic transcriptome analysis and found that the leukemic cell lines clustered together with progenitor cells based on their expression profiles . This fi in vivo functional data are now available, which explains the specific roles of different CRC subunits in programming the development and differentiation of cells [CRCs are often multisubunit complexes containing one or two SNF2 ATPase subunits that are capable of hydrolyzing ATP along with several auxiliary subunits. Subsequently, they can convert energy released from ATP hydrolysis to mechanical energy for changing chromatin confirmations. However, such mechanical actions are not only performed by the ATPase subunit but also require the participation of the entire complex . Althougof cells , 44. Thiof cells , heart aof cells , 76, andof cells , 20. In of cells . Previouof cells . RecentlThe ATPase motors in the BAF complex with either SMARCA4/Brg1 or SMARCA2/Brm share significant identity in their amino acid composition and biochemical chromatin remodeling activities. However, notably, SMARCA4 is essential, whereas SMARCA2 is dispensable . Such diβ-globin gene promoter and activates its transcription [β-globin gene promoter in vitro [β-globin gene expression, indicating that E-RC1 has a specialized function [CRCs can also form subcomplexes with transcription factors to target specific genes. For example, the transcription factor EKLF (erythroid Krüppel-like factor) binds to the cription . Biochemin vitro . Interesfunction .The composition of the NuRD complex is dynamic and changes with its distinct roles in cell survival, differentiation, development, and homeostasis in various organisms . For exaThus, we can conclude that CRC composition is diverse in blood cells and that several different CRC isoforms exist for specialized function.Dysfunctional expression of CRC subunits has been associated with leukemia. Downregulation of the BAF complex subunits SMARCA4, ARID1A, and SMARCB1 has been associated with glucocorticoid-resistance in acute lymphoid leukemia (ALL) .α and AML1) (reviewed in [Acute myeloid leukemia (AML) is a heterogeneous disease that consists of several subtypes based on cytogenetic and genetic alterations, which form the basis for classification and prognosis. AML is characterized by disturbed transcriptional regulation, which leads to a differentiation block and increased proliferation. Several chromosomal translocations or mutations in AML involve epigenetic regulators  or transcription factors . Transciewed in . Althougiewed in   and the Cancer Genome Atlas (TCGA), have provided large datasets that enable systematic studies of mutations in epigenetic machinery in cancer. Genes encoding enzymes involved in basic epigenetic mechanisms, such as histone modification, chromatin remodeling, and DNA methylation, are frequently mutated in cancer, including a range of tissue types such as breast, brain, lung, ovarian, blood, kidney, colon, uterus, liver, and pancreas (reviewed in ). MutatiSMARCA4 is one of the catalytic subunits of the BAF complex. Subunits of BAF complex are mutated in a variety of cancers: loss of function of the auxiliary subunit SMARCB1 was detected in 98% of rhabdoid tumors and in 30–40% of familial Schwannomatosis; the subunit PBRM1 was mutated in 41% of renal carcinoma; the subunit ARID1A was mutated in 50% of ovarian clear cell carcinoma and in 35% of endometrial carcinoma; and SMARCA4 itself was mutated in 35% of nonsmall cell lung cancers . We usedThe subunits of the other CRC complexes were also mutated in patients with lymphoma, though at frequencies somewhat lower compared with SWI/SNF. For example, mutations in the NuRD complex subunits MTA3 (18%) and p66beta/GATAD28 (16%) were observed. The MRG15 subunit of the EP400 complex was mutated in 16% of patients with malignant lymphoma and in 5.3% of AML patients. CRC mutations were rare in the CLL cohort. Thus, in agreement with the central role for SNF2 enzymes and their CRC complexes in blood cell differentiation, mutations are often observed in patients with malignant lymphoma and AML, suggesting that disruptions in the function of these enzymes and complexes could contribute to these blood cancer phenotypes. in vitro assembled chromatin system revealed that all CRCs tested so far translocate on the nucleosomal DNA [ in vivo are more complex. Since CRCs lack motifs to recognize specific DNA sequences, other factors are required to recruit CRCs to their genomic targets. The interactions of CRCs with transcription factors and posttranslational histone modifications perform this function in cell/tissue specific manner.SNF2 family enzymes are key players in the epigenetic control of cell/tissue development, differentiation, and maturation. The question is how and by what mechanisms SNF2 enzymes and CRCs regulate epigenetic switches? Decades of research by several groups have shown that these enzymes change the accessibility of DNA by multiple chromatin remodeling mechanisms. Such mechanisms are critical for maintenance of genome integrity, regulation of transcription, and organization of chromatin into higher-order structures. Biochemical experiments to assess the functions of CRCs in a homogeneousomal DNA . This DNomal DNA , 43, 44.Recent studies have shown that the auxiliary subunit composition of CRCs is dynamic and variable during cellular development. Such diversification adds to another level of complexity to the current understanding of gene regulation by CRCs in heart, muscle, and neuronal development as discussed above. More recently, studies have shown that the multilineage hematopoietic system possesses a similar mode of regulation where subunit composition of CRCs such as BAF and NuRD changes during hematopoietic lineage choices. Our genome-wide expression data revealed several such differentially expressed CRC components . In an eDefects in chromatin remodeling caused by mutations in the genes encoding SNF2 ATPases and CRC auxiliary subunits are common in leukemia. Data mining from ICGC consortium shows that these mutations are common in genes encoding SNF2 family enzymes. We also observed aberrant expression of genes encoding SNF2 family enzymes and CRC subunits in acute myeloid leukemia (AML) using data from the Cancer Genome Atlas (TCGA). Mechanistic studies will clearly be important to understand the contribution of these mutations and expression changes to leukemogenesis and possibly to allow for the development of personalized therapies based on specific SNF2 or CRC targets. In this review, we have attempted to summarize the current knowledge of SNF2 and CRC functions in hematopoiesis and leukemia. Further studies are required to unfold multiple mechanisms of chromatin remodeling complexes by which hematopoietic cells can follow normal or malignant hematopoiesis.


A chromosomal translocation results in production of an oncogenic PAX8-PPARG fusion protein (PPFP) in thyroid carcinomas. PAX8 is a thyroid transcription factor, and PPARG is a transcription factor that plays important roles in adipocytes and macrophages. PPFP retains the DNA binding domains of both proteins; however, the genomic binding sites of PPFP have not been identified, and only limited data exist to characterize gene expression in PPFP thyroid carcinomas. Therefore, the oncogenic function of PPFP is poorly understood. We expressed PPFP in PCCL3 rat thyroid cells and used ChIP-seq to identify PPFP genomic binding sites (PPFP peaks) and RNA-seq to characterize PPFP-dependent gene expression. PPFP peaks  include known PAX8 and PPARG binding sites and are enriched with both motifs, indicating that both DNA binding domains are functional. PPFP binds to and regulates many genes involved in cancer-related processes. In PCCL3 thyroid cells, PPFP binds to adipocyte PPARG target genes in preference to macrophage PPARG target genes, consistent with the pro-adipogenic nature of PPFP and its ligand pioglitazone in thyroid cells. PPFP induces oxidative stress in thyroid cells, and pioglitazone increases susceptibility to further oxidative stress. Our data highlight the complexity of PPFP as a transcription factor and the numerous ways that it regulates thyroid oncogenesis. BRAF or RAS mutations, gene fusions involving RET, or gene fusions between PAX8 and PPARG (reviewed in [PAX8- peroxisome proliferator-activated receptor gamma (PPARG) gene fusion is a consequence of a translocation between chromosomes 2 and 3, and is found in ~30% of follicular thyroid carcinomas and ~5% of follicular variant papillary carcinomas. The resulting PAX8-PPARG fusion protein (PPFP) is unusual in that it is the fusion of two transcription factors and it retains the DNA binding domains (DBDs) of both parent proteins [Thyroid carcinoma is the most common endocrine malignancy, and its incidence has increased nearly 3-fold since 1990 . The majproteins . Thus, aproteins ).PAX8 is a member of the paired box family of transcription factors and is essential for thyroid gland development , 8. In tBRAF [RAS [RET gene fusions [There are no existing cell lines from PPFP thyroid carcinomas. However, PPFP has been stably expressed in the PCCL3 rat thyroid cell line at a level comparable to that in human thyroid cancers, herein denoted PPFP cells . PPFP exBRAF  and RAS RAF [RAS , and RET fusions .Here, we have used RNA deep sequencing (RNA-seq) to study the gene expression of PPFP cells versus control empty vector (EV) cells, cultured with and without pioglitazone. We also performed chromatin immunoprecipitation-deep sequencing (ChIP-seq) to identify the PPFP binding sites within the PCCL3 cell genome, and integrated the results with the gene expression data and publicly-available PAX8 and PPARG ChIP-seq data. The results provide novel insights into the transcriptional regulatory activity of PPFP, its oncogenic actions, and the response to pioglitazone.An RNA-seq analysis was performed on RNA from PPFP cells versus EV cells treated with or without pioglitazone. PPFP regulated the expression of 1541 genes  in the comparison of PPFP cells versus EV cells without pioglitazone (FDR <0.05 and fold change >2). When both cell lines were cultured with pioglitazone, slightly more genes were differentially expressed . In a comparison of PPFP cells cultured with versus without pioglitazone, 250 genes were differentially expressed . The differentially expressed genes in all of these comparisons are highly overlapping  were investigated further and were also found to be induced at the protein level by PPFP  terms and KEGG pathways , 17. We P Figure . ConsistAcaa2 and Plin1, at the protein level . Since induction by siPAX8 implies repression by PAX8 and vice versa, the data indicate that PAX8 and PPFP regulate gene expression in the same direction for ~2/3 of the genes, and in opposite directions for ~1/3.PAX8 induces thyroid-specific genes such as lication , siRNA kmitochondrial envelope, lipid particle, and cellular response to fatty acid , confirming that PPFP preferentially binds to the subset of PAX8 peaks that also contain a PPARG motif.Since PPFP contains DBDs from both PAX8 and PPARG, in principle it could bind to the DNA motifs recognized by both transcription factors. This is what was observed, as we identified the PPARG and PAX8 motifs ng HOMER . Overallng HOMER . We firsTg promoter [Aqp7 promoter [PPFP peaks were found to encompass a number of known functional response elements in classic PAX8 and PPARG responsive genes. For example, PPFP peaks encompass the PAX8 response element in the promoter  and the promoter .q-values are related to immune function, development/differentiation, or lipid metabolism, and the GO terms in the full list include additional cancer-related concepts such as negative regulation of programmed cell death, regulation of cell migration, G1/S transition of mitotic cell cycle, and Wnt receptor signaling pathway.One hundred sixty eight GO terms were identified as enriched with PPFP peaks (FDR<0.05), after associating peaks with the gene having the nearest TSS . Nine ofPlin1. The one additional induced gene set, G1/S transition of mitotic cell cycle, includes genes such as Plk3 that promote progression through the cell cycle and cell division. The inductions of Plin1 and Plk3 were confirmed at the protein level, as noted previously , morphogenesis/development/differentiation (4 gene sets), and cell communication/extracellular matrix/adhesion (4 gene sets). The repressed genes in these gene sets include the thyroid development genes Fgfr2  and Hhexr2 [Hhex .We classified PPFP peaks as to whether they contain a PAX8 motif or a PPARG motif, and whether they are ≤10kb from a TSS or >10kb upstream from a TSS. We then performed gene set enrichment analyses on these 4 groups of PPFP peaks using ChIP-Enrich  and compmorphogenesis, development or organ formation . The fact that PPFP in the thyroid preferentially binds to adipocyte PPARG target genes likely underlies the observation that the pioglitazone response is adipocyte-like.When mice with PPFP thyroid carcinomas are treated with pioglitazone, metastatic disease is prevented and the primary thyroid tumors shrink markedly . The mosGlutathione metabolism (KEGG), peroxidase activity (GO) and arachidonic acid metabolism (KEGG). There are 49 unique, differentially expressed genes within these gene sets, including multiple glutathione peroxidases, glutathione reductase, glutathione synthase, glutathione S-transferases, and peroxiredoxins (We reasoned that genes or pathways regulated in opposite directions by PPFP without pioglitazone versus PPFP with pioglitazone may be involved in the therapeutic efficacy of this drug. We therefore identified GO or KEGG terms in our RNA-seq data that are both induced (or repressed) in PPFP cells versus EV cells without pioglitazone, and repressed (or induced) in PPFP cells with pioglitazone versus PPFP cells without pioglitazone. Only three gene sets qualified, and all were induced by PPFP without pioglitazone and repressed by pioglitazone. The 3 gene sets relate to oxidative stress: redoxins . Based oTo assess this, we evaluated oxidative stress in PPFP and EV cells by flow cytometry after treatment with the reactive oxygen species (ROS)-sensitive dye CellROX Deep Red. PPFP cells had greater ROS than EV cells, cultured in the absence of pioglitazone Figure . AnalysiANGPTL4 and AQP7, which were two of the six most highly induced genes in the human PPFP carcinomas. We also found that the set of 49 ROS-related genes described above is induced in the 7 PPFP follicular carcinomas versus the non-PPFP follicular carcinomas , as well as the fact that PPFP thyroid carcinomas are uncommon. Furthermore, the largest gene expression profiling study of human PPFP thyroid carcinomas included only 7 cases . This stPPFP is an unusual oncoprotein in that it is the fusion of two transcription factors, PAX8 and PPARG, and it retains the DBDs of both parent proteins. However, until now there were no studies to determine whether PPFP actively bound both PAX8 and PPARG target genes. Gene expression data in PPFP thyroid carcinomas also are very limited - the largest study included only 7 PPFP carcinomas , and givPparg has not been reported, but would provide a means to address this question.Here, we identified ~20,000 putative PPFP binding sites in the rat PCCL3 cell line genome, and found that these binding sites are enriched within −5 kb of transcription start sites and in first introns. PPFP peaks encompass known PAX8 and PPARG binding sites, indicating that both DBDs within PPFP are functional. Interestingly, PPFP preferentially binds to the subset of PAX8 peaks that also contain PPARG motifs, implying that the PPARG portion of PPFP is particularly important in directing PPFP to its target genes. The fact that many PAX8 binding sites have a nearby PPARG motif also suggests PPARG may play a role in normal thyroid biology. Thyroid-specific deletion of murine RNA-seq analysis shows that PPFP regulates the expression of ~1500 genes in the absence of pioglitazone and ~2000 genes in its presence. In general, pioglitazone reinforces PPFP-dependent gene expression, but in 17% of cases it reverses the effects of PPFP. PPFP regulates many genes known to be regulated by PAX8 in thyrocytes or PPARG in adipocytes. For the latter, the gene regulation by PPFP is particularly striking in the presence of pioglitazone. Although gene expression data in human PPFP thyroid carcinomas are very limited, there is excellent overlap between the human data and our data, including the induction of PPARG target genes.We identified an unusual dichotomy in the function of PPFP for genes with peaks containing PAX8 motifs. When such motifs are located >10kb upstream from the TSS, the functional consequence tends to be gene set repression, including processes related to morphogenesis and development. In contrast, when such peaks are close to the TSS, the consequence tends to be gene set induction. This dichotomy likely reflects the summed activity of transcriptional activators and repressors brought to the target gene, but the factors that determine these differences are unknown.clinicaltrials.gov identifier NCT01655719). A remarkable aspect of this response is that the drug trans-differentiated the surviving thyroid cancer cells into adipocyte-like cells. Our ChIP-seq data show that, in PCCL3 thyroid cells, PPFP binds to adipocyte PPARG target genes in preference to macrophage PPARG target genes, likely explaining why pioglitazone is specifically pro-adipogenic.The data are relevant to the biology of PPFP in human thyroid cancer. For example, PPFP induces gene sets related to the cell cycle, and represses gene sets related to differentiation. In a transgenic mouse model of PPFP thyroid carcinoma, pioglitazone was highly therapeutic , and thiin vivo to oxidative stressors, leading to increased cytotoxicity and cell death. Substantiation of this hypothesis could lead to approaches to further enhance the efficacy of this drug.It is plausible that the therapeutic efficacy of pioglitazone is at least in part due to its adipogenic pro-differentiation effects. However, our data uncovered another potential contributing factor. We found that PPFP cells have higher expression of ROS-related genes than EV cells, and this reflects higher levels of oxidative stress. Pioglitazone caused the PPFP cells to develop even greater levels of ROS when exposed to a low dose of the reactive peroxide TBHP, indicating that pioglitazone sensitizes PPFP cells to potential oxidant stressors. These data suggest pioglitazone might sensitize PPFP thyroid cancers PCCL3-PPFP cells stably express human PPFP with a 3xMyc tag at the amino terminus, and PCCL3-EV cells have been stably transfected with the empty vector . PPFP anAntibodies were obtained from the following sources as indicated: Cell Signaling Technology  - beta actin #8457, Ccnb1 #12231, Hes1 #11988, Myc tag #2276, Notch1 #3608 and Plk3 #4896; Proteintech  - Acaa2 #11111-1-AP and Icam5 #12759-1-AP; Sigma  - Foxe1 #SAB2100840; and Life Technologies  - Cdk1 #MA5-11472 and Plin1 #PA1-1051.DNA content was analyzed by propidium iodide staining and oxidative stress was analyzed with CellROX Deep Red per the vendor's protocols (Life Technologies). For the oxidative stress experiments, the cells were cultured ±1 μM pioglitazone for 2 days and ±50 μM TBHP for the final hour. Approximately 10,000 cells per condition were analyzed in the University of Michigan Comprehensive Cancer Center Flow Cytometry Core on a MACSQuant cytometer.PPFP cells were cultured with pioglitazone for 16 hours, crosslinked with formaldehyde, sonicated to an average DNA size of 300 to 500 bp, and immunoprecipitated with anti-Myc antibody at 1:500 overnight at 4C using the protocol of Upstate Biotechnology , except that immunoprecipitation was performed with Dynabeads G (Life Technologies). ChIP and input DNA were used for next generation library construction and DNA sequencing on an Illumina HiSeq 2000 per the manufacturer's protocol using 50 nt single-end reads, performed by the University of Michigan DNA Sequencing Core. Four samples were barcoded and run on one lane, obtaining an average of 31 million reads per sample.PPFP and EV cells were treated with 1 μM pioglitazone or vehicle for 16 hours. Total RNA was prepared using an RNeasy Mini Kit (Qiagen). Three independent experiments were performed. Library construction (Illumina TruSeq RNA) and sequencing on an Illumina HiSeq2000 using 50 nt paired end reads were per the manufacturer's protocols, performed by the University of Michigan DNA Sequencing Core. The samples were barcoded and loaded onto the same run, with all samples from each experiment run on the same two lanes; an average of 88 million reads were obtained per sample.PPFP ChIP-seq and RNA-seq data were deposited in Gene Expression Omnibus (GEO) with the accession ID GSE70354.q-value < 0.05 cutoff [The quality of reads were assessed using FastQC . There w5 cutoff . Peaks w5 cutoff  to remov5 cutoff , 29, 33 5 cutoff , as the Peaks were annotated to the genome with respect to gene features using an adapted HOMER script. If a peak had two or more annotations, a priority was assigned based on the order from left to right in Figure PAX8 ChIP-seq raw read data (GSE26871) were downloaded and analyzed as described above. The PAX8 motif .edgeR (3.2.4) Bioconductor package [Quality checks were performed on RNA-seq reads with RSeQC (2.3.9) . The rea package . Differe package .P-values from differential expression analysis from edgeR using the RNA-seq data were input into LRpath [p-values). We used the directional test option in LRpath, and tested GO terms and KEGG pathways with each pairwise comparison of PPFP cells or EV cells treated with and without pioglitazone. Gene sets satisfying FDR≤0.05 were considered to be significant.o LRpath , 17 for Gene set enrichment testing of the ChIP-seq data was performed with ChIP-Enrich, a logistic-regression-based method that uses a smoothing spline to empirically adjust for gene locus length and mappability . Gene se