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 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  Through chromatin looping, these enhancer-bound transcriptional complexes can make physical contact with other enhancers and/or promoters, and dynamically regulate the transcriptional initiation and elongation of the target genes  consortium, the Roadmap Epigenetic Project and individual groups have generated chromatin immunoprecipitation followed by sequencing (ChIP-seq) data for hundreds of TFs in multiple widely-used cell lines. Comparative analysis of TF binding profiles within the same cell lines revealed that certain genomic loci, commonly referred to as high occupancy target (HOT) sites, are bound by dozens to hundreds of TFs and co-factors . While strans-acting high-occupancy enhancers considering of both the numbers of factors bound and the relative signal intensities for each factor. Our systematic analysis revealed that the re-defined high-occupancy enhancers, while physically distinct from the classic SE, exhibit all the expected functional characteristics of SEs. We further showed that even without chromatin-binding data from a large number of TF and co-factors, trans-acting high-occupancy enhancers can be reliably identified by ranking the signals from DNase-seq, and/or ChIP-seq of several commonly studied transcriptional co-activators. Based on the results of our analysis, we propose to expand the SE definition to include trans high-occupancy enhancers, and re-divide SE into three subclasses of cis, trans and dual SE, reflecting their distinct modes of actions.Through integrated analysis of >600 publicly available DNase-seq, ChIP-seq, Global nuclear run-on sequencing (GRO-seq) and three-dimensional (3D) chromatin interaction data from five commonly used cancer cell lines, we re-defined https://github.com/ENCODE-DCC/chip-seq-pipeline2) according to their recommended guidelines. Briefly, raw fastq files were aligned to GRCh38 using the Burrows Wheeler Aligner  algorithm (https://broadinstitute.github.io/picard/) to remove duplicates. Peak calling was then carried out using the SPP algorithm, where peak rankings and replicate consistency were determined using the irreproducible discovery rate (IDR) package  were downloaded from the ENCODE data portal see  was usedlgorithm . Post-allgorithm  to filte package ,38. The  were dowTo identify active enhancers in each cell line, we first subsetted DNase-seq peaks that overlapped with H3K27ac ChIP-seq peaks using findOverlapsOfPeaks from the ChIPpeakAnno R package ,40. The N is the number of factors, f, bound at enhancer, E. The calculated OS for each enhancer is dependent on the number of factors bound and the signal strength of each bound factor, as indicated by the sum of the factor signal values. By adapting the ROSE R script (https://bitbucket.org/young_computation/rose/src/master/), enhancers were ranked according to their OS values and plotted. The OS score at the curve's inflection point was deemed the cutoff and all enhancers with an OS score greater than the cutoff were classified as high occupancy enhancers.To assess the binding occupancy and strength of all TF, cofactors, and histone marks at all active enhancer regions, we used ChIPpeakAnno R package ,40 to ovThe ROSE algorithm ,10 was uTo identify high-confidence cell line-specific TF footprints, we filtered cell line-specific footprints  for footprints present in the ENCODE consensus footprint dataset, a high-confidence dataset identified by analyzing DNase-seq profiles across 243 human cell and tissue types . ConsensHomer (v4.11) software was used to calculate GC and CpG percentages for enhancer class peaks. Vertebrate phastCon scores for the GRCh38 genome were downloaded from UCSC table browser ,46. All To calculate the unrestricted peak width for all DNase-seq regions, we re-called DNase-seq peaks to permit peaks of variable widths using the findpeaks -region option from the Homer peak-calling software . The newHi-C or POLR2A ChIA-PET BED files containing significant 3D interactions loops from HepG2, A549 and MCF7 cells were downloaded from GEO . Left anmax – Signalmin)/# peaks, similar to the ROSE method but without stitching. Next, we calculated a local inflection point for the lower portion of the curve, using the global inflection point as the new maximum value. Using this newly-defined cutoff, the true positive and false positive rates were calculated for each indicated factor.To determine factor signals that best predict super-high-occupancy enhancers (aSEs and dSEs), we first ranked all active enhancer peaks according to the factor signal value (highest to lowest). For any active enhancers where factor peaks were not present, the signal value was assigned zero. Ranked enhancer peaks were then annotated based on their enhancer class and a receiver-operating characteristic (ROC) curve was plotted to evaluate the factor signal ranking for its predictive performance in identifying aSEs and dSEs. To calculate the optimal, factor-specific signal cutoff for predicting aSEs and dSEs, we implemented the following: Active enhancers were ranked according to the factor signal value at that peak (lowest to highest), with enhancers lacking overlapping factor peaks assigned a signal value of zero. The ranked signal value was plotted and the global inflection point was defined as the value where a line tangent to that point has a slope equal to the maximum signal value minus the minimum signal value divided by the total number of peaks:  by the sum of normalized peak signals of these factors (f). By ranking the active enhancers by their OS values, we identified a subset of enhancers with exceptionally high levels of factor binding, which represent between 5.7% and 11.3% of all active enhancers in the five cell lines examined  method , which id Figure .Notably, in the five cell lines examined only 14–34% of the newly defined super-high-occupancy enhancers identified by our algorithm qualify as classic SEs based on the standard ROSE method  Figure . We hypoNotably, compared to cSEs and rEhs, aSEs and dSEs are not only co-bound by significantly higher numbers of different factors, but the average signal values for most factors present at these sites are also significantly higher Figure , implyinP < 10–10 for all; Figure Classic SEs are known to exhibit exceptionally high levels of enrichment for P300, H3K27ac, BRD4, the mediator complex, and RNA Pol II . Indeed,P < 10–23 for all; Figure Another key feature associated with classic SEs is their heightened ability to transcribe bi-directional, short-lived eRNA, which can be detected by GRO-seq ,14. AnalP < 10–11 for all lines; dSE: 1.7–2.6-fold, P < 10–7 for all lines except HCT116; cSE: 0.8–1.0-fold, P = 0.9–0.03; Figure High-throughput reporter assays such as self-transcribing active regulatory region sequencing (STARR-seq) have enabled quantification of individual enhancer activities across the entire genome . CompariNext, we investigated potential mechanisms that could explain how individual aSEs are able to anchor such a large number of TFs and co-activators. Previous analysis of HOT loci in individual cell lines suggest that higher GC contents may contribute to the increase in TF binding affinity at these sites ,27,32. HTFs making direct contacts with DNA are known to protect their bound-motifs from DNase cleavage, leaving so-called footprints within DNase hypersensitive peaks ,52. TakiMaster lineage and oncogenic TF are known to be highly enriched at classic SEs ,9,15,16.To verify whether lineage-specific TFs are also responsible for anchoring aSEs and dSEs in other cell lines, we compared the frequency of DNASE footprints detected at each enhancer class in MCF7 and A549 cells. Similar to HepG2 cells, the C2H2 and NR motif families are the top most differentially enriched footprints at aSEs and dSEs compared to rEhs in MCF7 cells . In contIn light of the lineage-specific footprint enrichment signatures at the three SE subtypes, we compared the specificity of enhancer classification across cell lines. Consistent with previous reports , large fin trans  analysis revealed that signals from DNase-seq or ChIP-seq of P300 or MED1 achieved an AUC >0.89, corresponding to a >90% true positive rate for identifying aSEs and dSEs Figure . In contin trans. Among classic SEs identified by the ROSE method, we re-classified those that also met the criteria of aSEs as dSE, while renaming the rest as cSE. Notably, as dSEs represent overlaps between our newly identified super-high-occupancy enhancers and the classically defined SEs, they were considered a separate enhancer class for comparison purposes in this initial study. However, given that dSEs share most if not all the physical and functional characteristics of aSEs, they could be considered a subset of aSEs in future studies.First proposed in 2012, the concept of SE has become widely adopted into the scientific community, with roughly 400 publications and counting implicating SE in regulation of many important biological processes including embryonic development, cell differentiation, tumorigenesis, and therapy resistance. SE are classically defined as long stretches of active enhancers that are physically tethered together by multivalent, mega transcriptional complexes composed of numerous TFs and co-factors, which promote the transcription of distally localized lineage-specific genes through chromatin looping. Taking advantage of the large number of published ChIP-seq data from five commonly-used cancer cell of distinct lineages, we ranked enhancers based on both the numbers of factors bound and the relative signal intensities from each factor, and identified a set of enhancers meet all the functional criteria of SEs but are not captured by the widely adopted ROSE method. We termed these enhancers aSEs based on their ability to independently recruit many TFs and assemble mega transcriptional complexes et al. showed that the recruitment of HDACs to SE is necessary for preventing aberrant ‘spreading’ of H3K27ac to adjacent loci, which is critical for maintaining proper 3D chromatin architecture and enhancer-promoter contacts(Our in-depth analysis revealed that compared to cSEs and rEhs, aSEs and dSEs display dramatically higher levels of chromatin accessibility, as well as binding by TFs, MED1, P300 and other co-activators Figure . Among t contacts. Additio contacts. In part contacts. As cohe contacts. Moreove contacts, suggest contacts, implyin contacts, hintingin trans at specific chromatin ‘hot spot’ regions in response to certain stimuli (trans (Phase-separation has been increasingly recognized as a key mechanism in concentrating a large number of SE and co-factors and facilitating in long-distance interactions at classically defined SE sites ,66,78. T stimuli . The phei (trans . Given ti (trans , it is ri (trans ,66. Indei (trans ,80,82,83i (trans . It is wBy integrating 3D chromatin interaction data with RNAseq, we showed that similar to cSEs and dSEs, aSEs are involved in extensive, highly robust long-distance interactions with highly transcribed genes Figure . AdditioIn summary, this study provides evidentiary support for expanding the classification of SEs to include stand-alone aSE and exposes a number of unique traits associated with this newly defined SE subclass. We demonstrate that aSE can be reliably identified by ranking the signal levels from DNase-seq alone or in combination with ChIP-seq data for MED1 or p300 Figure . Moving All GEO and SRA datasets used throughout this paper can be found in gkab1105_Supplemental_FilesClick here for additional data file.


Drosophila, and human promoters. This element is observed in TATA-less promoters. Several studies have defined transcription factor requirements and additional cofactors that are needed for transcription initiation of initiator-containing promoters. However, those studies have been performed with additional core promoters in addition to the initiator. In this work, we have defined the pathway of preinitiation complex formation on the fission yeast nmt1 gene promoter, which contains a functional initiator with striking similarity to the initiator of the human dihydrofolate reductase (hDHFR) gene and to the factor requirement for transcription initiation of the nmt1 gene promoter. The results show that the nmt1 gene promoter possesses an initiator encompassing the transcription start site, and several conserved base positions are required for initiator function. A preinitiation complex formation on the nmt1 initiator can be started by TBP/TFIIA or TBP/TFIIB, but not TBP alone, and afterwards follows the same pathway as preinitiation complex formation on TATA-containing promoters. Transcription initiation is dependent on the general transcription factors TBP, TFIIB, TFIIE, TFIIF, TFIIH, RNA polymerase II, Mediator, and a cofactor identified as transcription cofactor for initiator function (TCIF), which is a high-molecular-weight protein complex of around 500 kDa. However, the TAF subunits of TFIID were not required for the nmt1 initiator transcription, as far as we tested. We also demonstrate that other initiators of the nmt1/hDHFR family can be transcribed in fission yeast whole-cell extracts.The initiator element is a core promoter element encompassing the transcription start site, which is found in yeast,  RNA polymerase II (RNAPII) is a multimeric enzyme that transcribes protein-coding genes, microRNAs, long non-coding RNAs, and small nuclear RNAs. Despite being a multimeric enzyme, RNAPII is unable to recognize gene promoters and start transcription initiation in the absence of additional factors. These set of additional factors are called general transcription factors (GTFs), and include TFIIA, TFIIB, TFIID (TBP + TAFs), TFIIE, TFIIF, and TFIIH, defined as the minimal set of GTFs required to in vitro transcribe a gene containing the TATA box promoter element. The GTFs are required for transcription of most, if not all, the genes transcribed by RNAPII, and they are evolutionarily well conserved from yeast to humans. On the other hand, RNAPII needs promoter elements for accurate start site selection and transcription initiation ,2. RNAPIThe Inr is a CPE that was discovered in an analysis of the gene promoter of lymphocyte-specific terminal transferase (TdT) . This CPSchizosaccharomyces pombe, DeepCAGE analysis has also been performed to find CPEs, which are present in gene promoters [S. cerevisiae Inr.In the fission yeast romoters . It was romoters . This seS. pombe is highly transcribed and completely repressed by thiamine [The nmt1 gene in thiamine . It possthiamine . The TSSthiamine ,18, and Recombinant GTFs  were expressed and purified as described in earlier studies ,20. TFIIMediator was depleted from a WCE of a TAP-tagged Med7 strain, by adjusting the WCE at 0.5 M potassium acetate and incubating two volumes of settled IgG-Sepharose with one volume of WCE. The mix was incubated by rocking for 30 min at room temperature, and then for 2 h at 4 °C. The mix was centrifugated and the supernatant used as depleted WCE (WCED). TAFs were depleted using a similar approach, except they were incubated with a column that contained 1 mg/mL of rabbit anti-TAF1 crosslinked to CNBr-activated Sepharose.32γATP was added to the assays, and the reaction mixes were incubated for 15 min at 30 °C. Inr-containing probe with single mutations was evaluated in the same manner as the wild-type probe. The DNA-protein complexes were evaluated in 5% acrylamide gels containing 10% glycerol, and run at 100 V at 4 °C for 2 h in 50 mM Tris-borate (pH 8.3) buffer. EMSA gels were prerun at 4 °C for 1 h. Detection of the complexes was performed using autoradiography analysis.EMSA assays were performed as described previously . Each biIn vitro transcription was performed as described previously ,20 usingTICF was purified from wild-type fission yeast whole-cell extracts. Extracts were fractionated on a phosphocellulose (Whatman P11) column equilibrated in buffer A . After loading, the column was washed with buffer A and sequentially eluted with 0.3, 0.5, and 1.0 M of KCl in buffer A. The fraction containing the transcription complementing activity (0.5 M) was dialysed against buffer A and loaded onto a heparin-agarose column and eluted as described for the P11 column. The fraction that contained the transcription complementing activity (0.5 M) was dialysed against 25 mM potassium phosphate buffer pH 7.9, 2.5 mM DTT, 10% glycerol, and 0.1 mM PMSF and loaded onto a hydroxyapatite column equilibrated in dialysis buffer. The column was washed and eluted with a potassium phosphate gradient (50–400 mM), and the transcription complementing activity eluted as a single peak at 100 mM phosphate, and separated from RNAPII and transcription factors. Subsequently, the fractions containing activity were pooled and dialysed against buffer A and loaded onto a Q-Sepharose column, washed and eluted with a gradient of KCl (50–400 mM) and the transcription complementing activity eluted as a single peak at 150 mM KCl. Active fractions were pooled and concentrated against buffer A containing 55% glycerol and loaded onto a AcA22 gel filtration column, then separated in buffer A containing 1 M KCl. The activity eluted as a single peak at approximately 500 kDa MW, and was devoid of GTFs, TAFs, Mediator, and CK2, as determined by Western blot analysis. These active fractions were stored at −80 °C and used in transcription assays.S. pombe has been described elsewhere [S. pombe in the new Eukaryotic Promoter Database (EPD) indicates that several TATA-less promoters contain a highly similar sequence, which we identify as the nmt1/hDHFR Inr family (S. pombe from the EPD (selecting from −30 to +20), with the consensus sequence TTCAACTT, produces a strong peak around the TSS, indicating that the sequence is highly represented in the EPD  and in vitro transcribed in fission yeast whole-cell extracts (WCE). The results obtained were compared with a similar template, in which a TATA box mutated nmt1 promoter (from −20 to +6) was used. The results of these experiments show that there was a concentration dependence of α-Amanitin on transcription inhibition of the evaluated promoters. In the case of wild-type TATA-containing promoter, this promoter was transcribed in WCE and inhibited by 4 μg/mL α-Amanitin, indicating that transcription is carried out by RNAPII . LikewisS. pombe WCE. The results obtained from these experiments are shown in To define the necessary region for nmt1 promoter transcription initiation, we mutated the region surrounding +1, including the +1 transcription start site. Mutations were performed according to the conserved positions in the nmt1 Inr family. The constructs carrying the mutant promoters were transcribed in vitro in Taken together, these results indicate that the nmtl promoter possesses a bona fide Inr around the TSS, which can direct transcription initiation in the absence of a TATA-box, as has been observed under in vivo conditions ,18.S. pombe WCE (WCED). TAFs were depleted using anti-TAF1 antibodies crosslinked to Sepharose beads, and Mediator was depleted from a TAP-tagged Med7 strain using IgG Sepharose beads. TAF-depletion did not affect the transcription from the nmt1 TATA-lacking Inr-containing promoter  from −20 to +6, and they were assayed and compared with nmt1 Inr and a mutated nmt1 Inr (+4) in transcription in a WCE. As expected, those promoters were able to direct transcription initiation in WCE , althougIn this work, we demonstrate that the nmtl gene possesses an Inr encompassing the transcription start site. This Inr is capable of directing PIC formation and transcription initiation. Nmtl Inr-directed transcription requires the GTFs, RNAPII, Med, PC4, and a high-molecular-weight protein fraction that we termed TICF. We have not yet identified any polypeptide from TICF, although we speculate that it contains protein kinases and transcriptional coactivators. However, we have determined, using Western blot analysis, that the fraction is free of GTFs, RNAPII, Med, TAF, and protein kinase CK2. It is well known that in vitro basal transcription from TATA-containing promoters requires RNAPII and GTFs, including TFIIA, TFIIB, TBP, TFIIE, TFIIF, and TFIIH ,22, althDrosophila, a trimeric TBP/TAF1/TAF2 can support Inr activity when added in place of TFIID [Drosophila. Indeed, a report from Conaway and colleagues has shown that the hDHFR promoter (a TATA-less promoter) can direct PIC formation and transcription initiation in a reconstituted system, and although transcription is highly dependent on TFIID, TBP can still direct low transcription levels [Despite the current knowledge of the factors required for TATA-box-mediated transcription, the requirement of protein factors for transcription initiation from TATA-lacking promoters remains poorly defined. Several studies that aimed to identify the minimal components used a TATA box in the context of an Inr to identify factors, which, together with GTFs and RNAPII, could allow Inr activity. Kaufmann et al. identified from HeLa nuclear extracts a protein fraction known as CIF (cofactor of Inr function), which can stimulate Inr activity in the presence of GTFs ,27. Thisof TFIID . Howeverof TFIID ,30. In aof TFIID  set out of TFIID , HMGA1 hof TFIID . In our n levels . It is pn levels ,34.Trichomonas vaginalis [T. vaginalis lack a TATA-box; however, they contain an Inr motif as the sole CPE. This element is bound by IBP39, which is an initiator-binding protein in Trichomonas [Trichomonas, since it can interact with the CTD of the largest subunit of Trichomonas RNAPII [T. vaginalis are strikingly related to the nmt1/hDHFR Inr family (pol II: TATCAAAATAAT and TVCA1: TCTCAAATTTT) [Trichomonas genus. Furthermore, two TBPs have been identified, one of which binds to T. vaginalis gene promoter regions, and the other (TvTBP1) interacts with IBP39, suggesting that they might be part of a PIC at RNAPII core promoters [The Inr seems to be a widespread CPE, found in fission yeast, humans, insects, and many other metazoan organisms ,36. Indeaginalis . RNAPII chomonas . It is bAAATTTT) ,36. IBP3romoters .S. pombe, although in metazoan TATA-less promoters, such as in humans and insects, TAFs seem to be essential for transcription initiation [From our present study of Inr-directed transcription in fission yeast, it is clear that TAFs do not play a role in transcription initiation from Inr-containing TATA-lacking promoters in itiation ,28,29,30itiation ,42,43, aThe mechanism by which RNAPII is recruited into the TATA-less promoter has not yet been definitively elucidated. Our results support a model in which RNAPII is recruited at TATA-less promoters through interactions with TFIIB and TFIIF, as well as in the classic PIC formation on TATA-containing promoters; however, despite the PIC formation containing TBP-TFIIB-RNAPII/TFIIF-TFIIE-TFIIH, full-length transcripts have not been obtained. Perhaps that complex can polymerize the first 7–8 nucleotides and then a TICF is necessary to synthetize a longer RNA chain.The requirement of PC4 in this in vitro system is not completely understood, although it acts as a positive cofactor through the Med and TFIIA in fission yeast . PC4 canDrosophila, there are different patterns of transcription initiation, which are referred to as focused  and dispersed  [In mammals and s broad) ,13,14. Fs broad) ,18.In conclusion, we found a promoter element in a subset of fission yeast gene promoters that is highly homologous to the initiator of the hDHFR promoter. This element is found in the nmt1 TATA-containing promoter, and it is able, in isolation, to direct complex formation and transcription initiation in a fission yeast WCE and in a reconstituted system. However, transcription initiation in the reconstituted system requires, in addition to the GTFs and RNAPII, PC4, Mediator, and TCIF, indicating that transcription initiation in vitro from initiator-containing promoters is more complex than transcription of TATA-containing promoters. Furthermore, a stable PIC on the initiator is formed by the GTFs and RNAPII, and the first step is the binding of TBP in association with either TFIIA or TFIIB. We did not find any TAF requirement, either for PIC formation or transcription initiation, which is different from the results of previous studies on metazoans. Our results suggest that TATA-containing and Inr-containing promoters use the same universal pathway for the assembly of the PIC.


Chromatin architecture mapping in 3D formats has increased our understanding of how regulatory sequences and gene expression are connected and regulated in a genome. The 3D chromatin genome shows extensive remodeling during embryonic development, and although the cleavage-stage embryos of most species lack structure before zygotic genome activation (pre-ZGA), zebrafish has been reported to have structure. Here, we aimed to determine the chromosomal architecture in paternal/sperm zebrafish gamete cells to discern whether it either resembles or informs early pre-ZGA zebrafish embryo chromatin architecture. First, we assessed the higher-order architecture through advanced low-cell in situ Hi-C. The structure of zebrafish sperm, packaged by histones, lacks topological associated domains and instead displays “hinge-like” domains of ∼150 kb that repeat every 1–2 Mbs, suggesting a condensed repeating structure resembling mitotic chromosomes. The pre-ZGA embryos lacked chromosomal structure, in contrast to prior work, and only developed structure post-ZGA. During post-ZGA, we find chromatin architecture beginning to form at small contact domains of a median length of ∼90 kb. These small contact domains are established at enhancers, including super-enhancers, and chemical inhibition of Ep300a (p300) and Crebbpa (CBP) activity, lowering histone H3K27ac, but not transcription inhibition, diminishes these contacts. Together, this study reveals hinge-like domains in histone-packaged zebrafish sperm chromatin and determines that the initial formation of high-order chromatin architecture in zebrafish embryos occurs after ZGA primarily at enhancers bearing high H3K27ac. The folding of chromatin inside the nucleus helps regulate enhancer–promoter interactions and the formation of chromatin compartments, which impacts gene regulation and development. Chromatin is organized at multiple scales, the largest of which involves megabase-scale active or inactive regions called A or B compartments, respectively . It is fDanio rerio (zebrafish) has been reported to display both A/B compartments and TAD structures in the early cleavage-stage embryo before ZGA (pre-ZGA). Curiously, both A/B compartments and TADs are lost during ZGA  and the establishment of the chromatin organization. These issues have been explored in a number of vertebrate and invertebrate species, which have generally revealed that chromatin lacks extensive higher-order structure before ZGA, can form independently of transcription, and largely forms after ZGA . Conversring ZGA . This apOur work here also addresses zebrafish sperm chromatin architecture. In mammalian species, the vast majority of the paternal genome is packaged in protamine . HoweverOur initial goals were to use Hi-C to provide a better understanding of the connections between chromatin architecture and transcription initiation. We aimed to determine the 3D chromatin conformation of histone-packaged zebrafish sperm and to test if that architecture is transmitted to the next generation and either resembles or guides the structure of pre-ZGA zebrafish embryo chromatin. Notably, our characterization of the sperm genome reveals an architectural feature distinct from TADs and distinct from architecture in embryos. Within embryos, our results at pre-ZGA differed greatly from prior work, prompting a detailed Hi-C and ChIP-seq analysis of post-ZGA samples to identify the locations in the genome where chromatin architecture initially forms.Supplemental Fig. S1A). To ensure clear interpretation, we generated Hi-C contact maps of higher resolution than prior work .To better understand the nucleation of chromatin architecture in the developing embryo, our time course focused on time points that flank and include ZGA. To these ends, we modified previously published low-cell input Hi-C methods to the early zebrafish embryo Methods;  and deteSupplemental Table S1). First, we observed differences in contact probability over genomic distance for each embryo time point , suggesting that the overall chromatin architecture in the developing zebrafish embryo varies between time points. Consistent with prior work . We then generated metaplots of aggregate TAD insulation signal, using boundaries established at 24 hpf, and this approach also showed a lack of negative insulation score in sperm and pre-ZGA samples . Thus, our initial premise that sperm architecture might resemble the reported structure in pre-ZGA embryos was not supported, prompting instead an exploration of why the pre-ZGA samples lacked both A/B compartments and TAD boundaries, where and when structure initially forms in zebrafish, and the characterization of the unique structures observed in sperm.Visual inspection of normalized contact probability maps for all samples at 25 kb resolution revealed considerable differences in structure within the zebrafish developmental stages examined . We took two measures to determine whether the observed lack of structure in pre-ZGA samples was biological or instead a technical artifact. First, to minimize the confounding effects of highly condensed mitotic chromatin, we took advantage of the cell cycle synchrony of pre-ZGA embryos to enrich for embryo batches that were largely outside metaphase by including only embryo batches with <30% metaphase contribution in our pre-ZGA samples . Second, to address whether the lack of structure during pre-ZGA was technical or biological, we examined Hi-C contact maps and contact probability with genomic distance plots of the Drosophila spike-in . For all time points, the spike-in positive controls looked identical, which suggests a biological rather than a technical basis for the absence of structure during pre-ZGA. Taken together, these results suggest that zebrafish early embryos lack a defined 3D architecture. Independent work of our collaborators, working in both Oryzias latipes (medaka) and zebrafish, came to similar conclusions  genome essentially void of boundaries and TAD-like chromatin interactions . First, 5.3 hpf (post-ZGA) and 24 hpf stages displayed chromatin architecture interactions at similar locations, although stronger at 24 hpf than at 5.3 hpf, a trend noted in previous work and confirmed through our reanalysis of that prior data . However, examination of our data and prior data revealed chromosomal domains and boundary-like structures at 4 hpf that were not detected in prior work and a higher overlap between time points . By measuring negative insulation scores across each time point, we observed a limited number of structural boundaries emerging at 4 hpf, and that those established at 4 hpf are largely maintained at 5.3 and 24 hpf . The clarity of TADs in 24 hpf embryos, which are diverse in cell types, shows that zebrafish share with other species a consistency in TAD organization between cell types . We next addressed whether the loss of productive Pol II elongation at these boundaries impacts chromatin organization. To test, we treated zebrafish embryos with either vehicle (DMSO) or the Pol II inhibitor Flavopiridol (FLAV), starting at the one-cell stage and continuing through ZGA, and collected embryos at 4 hpf for examination by in situ Hi-C . Treatment with FLAV led to a loss of Pol II ser5 phosphorylation signal, by immunofluorescence, suggesting effective Pol II inhibition and loss of transcription in the 4 hpf embryo . However, the chromatin Hi-C contact maps obtained after Pol II inhibition appeared largely unaffected . TAD boundary insulation present at Pol II–bound loci in the 4 hpf (untreated) and vehicle-treated (DMSO) embryos was only slightly reduced upon treatment with FLAV. These results suggest that the lack of transcription elongation is not sufficient to markedly disrupt chromatin architecture boundaries, a result supported by similar experiments (We next investigated the relationship of TAD boundaries to transcription. We first determined the association of RNA Polymerase II (Pol II) during TAD boundary establishment by evaluating the insulation score across the top 1000 peaks of Pol II loci ChIP-seq at 4 hpf embryos. Pol II–bound loci at 4 hpf displayed negative insulation scores, suggesting that Pol II–bound loci are associated with TAD boundaries forming/formed at 4 hpf . In contrast, at locations where Rad21 binds independent of the presence of Ctcf binding sites, the opposite behavior was observed—an increase in interactions , especially at 5.3 hpf . These observations suggest that small contact domains (median size 90 kb) occur in the early embryo at locations where cohesin is present, but not where Ctcf is predicted to be co-occupied with cohesin.Although TAD structures are rare and weak at ZGA, we sought to address instead whether smaller contact domains might be established in early zebrafish embryos, and by virtue of their small size, form in spite of replication/cell cycle time constraints. Prior work in other systems suggested that early enhancer/promoter loops might form independent of cohesin and Ctcf (CTCF ortholog) co-occupied sites and can form faster than structural loops , promptiWe next explored possible chromatin interactions at enhancers and their relationships to cohesin, Ctcf, and other DNA-binding proteins. First, we defined candidate enhancers at 4 hpf using the standard ROSE algorithms  and publSupplemental Fig. S5B). Taken together, enhancers constitute the primary regions of the genome where structural interactions initially form, and their insulation score strength scales with their levels of H3K27ac and H3K4me1.To determine whether enhancers are the primary location where structure is initially established, we examined all regions of chromosomal interaction/structure (measured by positive insulation score) and determined the proportion of those regions that contain enhancers. First, we captured and stratified regions with positive insulation signal at 5.3 hpf genome-wide and determined the number of enhancer types within each positive insulation region. Enhancers constituted the majority of regions above the threshold positive insulation score 0.1, and the regions with the highest positive insulation scores consisted mainly of Group 3 or SE enhancers D. Only aSupplemental Fig. S5A). We then intersected the enhancer regions with the ATAC-seq signal and used HOMER Motif Analysis  in the 4 hpf embryo. The ATAC-seq signal had the strongest peak across potential SE and Group 3 enhancers . First, histone H3K27ac and H3K4me1 were expectedly coincident, and H3K4me3 and H3K27me3 were low or lacking at the strongest enhancers—those with highest histone H3K4me1 and H3K27ac (SE and Group 3) . Additionally, cohesin, Pol II, and H3K36me3 were detected across regions within SE and Group 3 putative enhancers . Although these heatmaps appear to convey a direct overlap of Pol II and histone H3K36me3 at enhancers, our limited resolution (>10-kb bins) cannot reveal enhancer/promoter looping. Next, to distinguish from maternally deposited mRNAs from actively transcribed mRNAs (and enhancer-derived RNAs [eRNAs]) from the zygotic genome, we analyzed published zebrafish embryo Click-iT-seq  for chromatin insulation score, centered on enhancer regions A. Again,Supplemental Fig. S3B; Supplemental Table S1). We verified inhibition of Crebbp/Ep300a activity by the approximately twofold bulk reduction of histone H3K27ac by quantitating loss of H3K27ac on a western blot analysis . We further verified a strong (four- to sixfold) focal reduction of histone H3K27ac at several SE regions, as assessed by ChIP-qPCR , compared to the vehicle control. Upon treatment with SGC, we observed a loss of chromatin interactions (reduction of insulation score) across the putative SE and Group 3 enhancers compared to the vehicle control, whereas there was little impact on Group 1 and Group 2 insulation . Additionally, by reanalyzing published Click-iT-seq data, upon SGC treatment the SE and Group 3 regions displayed a loss of transcription compared to control samples , which in somatic cells has been interpreted as signifying chromosome condensation . The flare feature is consistent with a large region displaying increased interactions primarily between locations equidistant from a fixed pivot/hinge point. This raises the possibility of periodic self-associating “hinge-like” chromosome domains occurring throughout the sperm genome  to extract them, yielding a total of 333 flares across the zebrafish sperm genome. These flares range in size, although in aggregate generate a unimodal peak centered at ∼150 kb A. After Supplemental Fig. S7B), as expected owing to the variety of spermatogenesis-specific cohesin complexes . Furthermore, we found no enrichment of repetitive elements at flares, nor an increase in GC percent distribution . Evolutionary breakpoints have overlap with 24 hpf boundaries . Last, we analyzed available genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) data, derived from sperm and 24 hpf samples. Histone H3K27ac , but the Smc3 subunit was detectable  of many developmental genes. The initial transcription at ZGA could  benefit from the utilization of chromatin architectural elements such as A/B compartments, TADs, and enhancer–promoter loops, and these elements in the embryo could (in principle) derive from states inherited from the parental gametes. However, zebrafish ZGA occurs during cleavage stage, which is characterized by rapid replication and about 10 synchronous cell division cycles that average ∼15 min. The major wave of ZGA occurs at ∼3–4 hpf, as cell cycles begin to lengthen and lose their synchrony . Thus, tFirst, we do not observe higher-order structure elements, such as A/B compartments or TADs, in pre-ZGA and ZGA embryos B,C. Our Drosophila, another species with fast cycling cells during early embryogenesis , but the presence of apparent A/B compartments in sperm  as the most prominent proteins for packaging the genome in a condensed manner . Our worin sperm C, 5A. Wein sperm B, 5B, whin sperm E. We hypAdditional topological constraints are needed to favor equidistant interactions, and we propose two speculative models to achieve this: an “intra-loop model” favors interactions between regions equidistant from point D, although solely within the loop E, left, Danio rerio strains were maintained under accordance with approved institutional protocols at the University of Utah (Zebrafish  of Utah . All expD. melanogaster were cultured in Gibco Schneider's Drosophila medium (Thermo Fisher Scientific 21720024) supplemented with 10% FBS (Omega Scientific FB-11) and penicillin/streptomycin. Cells were grown at room temperature and split as the dish became confluent.Schneider S2 cells derived from Supplemental Methods.Pre-ZGA samples were dechorionated with pronase  at one-cell stage shortly after mating. For full details, see Supplemental Methods for more details.Embryos at pre-ZGA, 4, 5.3, and 24 hpf were dechorionated with pronase at the time of collection as described above. After the 4–5 washes, the embryos were transferred carefully to a 1.5 mL eppendorf tube with a transfer pipette to not disrupt the embryos. The embryos were then deyolked because the yolk proteins interfere with digestion steps later in the Hi-C protocol. See Sperm samples were collected with standard methods as previously described  and fixeSupplemental Methods for more details.For spike-in preparation, standard fixation methods were used. See Flavopiridol  and SGC-CBP30  were prepared in DMSO. Embryos were incubated at indicated concentrations in E3 embryo water  for 4 h Drosophila S2 cells were added to each sample to equal 1/5 of the zebrafish cell count.Aliquots of enough cells at each time point were pulled out of the freezer; 2.25 hpf , 4 hpf , 5.3 hpf , and 24 hpf . Cells were thawed on ice and recounted to verify accurate spike-in amount. Zebrafish cells were washed one time with Hi-C lysis buffer  followed by a 15-min lysis incubation on ice. During the lysis step, the Drosophila S2 cells were added to each sample to equal one-fifth of the zebrafish cell count.An aliquot of cells was thawed on ice and recounted to verify accurate spike-in amount. Approximately 4 million cells were used per sample. Cells were washed one time with Hi-C lysis buffer followed by a 15-min lysis incubation on ice. During the lysis step, the Supplemental Table S1 for all replicates where S2 cells were included.Aliquots of cells were thawed on ice and recounted to verify accurate spike-in amount. No more than 5 million cells were lysed at one time using 500 µL Hi-C lysis buffer on ice. Once the S2 cells were resuspended in lysis buffer, they were added to the zebrafish cells undergoing lysis at the same time. See Supplemental Methods.Following nuclei isolation, the standard operating practices of the 4DN in situ Hi-C protocol was followed  adjustinSupplemental Methods.ChIP experiments were carried out as described previously , modifieSupplemental Methods.The original protocol  was modiSupplemental Methods.Standard protocol for immunohistochemistry was followed . For fulSupplemental Methods for the description for DAPI staining and cell cycle staging for the 2.25 hpf Hi-C embryo samples.Confocal images were acquired on a Leica SP8 White Light laser confocal. Image processing was completed using Nikon NIS-Elements multiplatform acquisition software with a 40×/1.10 Water objective. Fiji  was used to color DAPI channel to cyan, GFP color remained green. Confocal images are max projections of Z stacks taken 0.5 μm apart for a total of the embryo ∼7–12 μm. See http://bio-bwa.sourceforge.net/bwa.shtml) using the following options -A 1 -B 4 -E 50 -L 0. HiCExplorer  hicBuildMatrix was used to create matrix at 10, 25, and 50 kb resolutions, using the option –outBam . For full details of Hi-C data processing, see Supplemental Methods.Reads were aligned to a merged Zv10 (chromosomes were labeled 1–25) and dm6  genome using BWA-MEM . Flares/hinges were merged if within 50 kb of each other, and the first round of filtering was done to remove blacklisted regions as described previously. A second round of filtering was done by visually inspecting the positive flares and verifying they were not a false positive attributable to a genome assembly issue. Once flare/hinge list was filtered, the size of a flare was calculated by the width of the positive values in the bedGraph matrix. The distance between two flares was calculated by measuring the distance of one flare to the other. The distance between flares was excluded if there was a genome assembly gap creating a blacklisted region causing an inaccurate distance measurement.http://www.htslib.org/doc/samtools-merge.html)  . Data wiN = 411. For the 24 hpf potential enhancers, the enhancers list in To identify enhancers and super-enhancers (SEs), the ROSE algorithm version 0.1 was applied with default parameters performing TSS exclusion (–t 2000) . Using thttps://metacpan.org/release/Bio-ToolBox). The metaplots were visualized in R using standard methods. For full details, see Supplemental Methods.To generate metaregions plots of ChIP-seq, ATAC-seq, and Click-iT-seq, signal was averaged in 10-kb bins across the genome using get_datasets.pl from Biotoolbox (https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE152744. The Hi-C contact maps and raw data in this study have also been submitted to the 4D Nucleome data portal (https://data.4dnucleome.org/Cairns_zf_embryo_HiC).All raw and processed sequencing data generated in this study have been submitted to the NCBI Gene Expression Omnibus (GEO;


Four-stranded G-quadruplexes (G4s) are DNA secondary structures in the human genome that are primarily found in active promoters associated with elevated transcription. Here, we explore the relationship between the folding of promoter G4s, transcription and chromatin state.Transcriptional inhibition by DRB or by triptolide reveals that promoter G4 formation, as assessed by G4 ChIP-seq, does not depend on transcriptional activity. We then show that chromatin compaction can lead to loss of promoter G4s and is accompanied by a corresponding loss of RNA polymerase II (Pol II), thus establishing a link between G4 formation and chromatin accessibility. Furthermore, pre-treatment of cells with a G4-stabilising ligand mitigates the loss of Pol II at promoters induced by chromatin compaction.Overall, our findings show that G4 folding is coupled to the establishment of accessible chromatin and does not require active transcription.The online version contains supplementary material available at 10.1186/s13059-021-02346-7. Four-stranded G-quadruplex G4) structures form in DNA from stacked tetrads of Hoogsteen-bonded guanines . G4 sequ structurA central unanswered question is whether G4 formation at promoters of active genes is a cause or a consequence of increased transcriptional activity. Herein, we establish that the folding of G4s in promoters does not necessarily require active transcription but can be favoured by an accessible chromatin state. Moreover, we provide evidence that G4s are a genomic feature that enables the recruitment of Pol II to promoters.R > 0.96). The majority of the consensus G4 peaks (> 75%) comprise G4 sequence motifs that have been independently shown to fold into a G4 structure in vitro, by a DNA polymerase stalling assay  further revealed that the majority of all consensus G4s (88.2%) were located in NDRs , we observed significantly higher Pol II occupancy at promoters with an endogenous G4 compared to those without  to prevent paused Pol II release [p < 0.01; 5/4023, 0.1% up, 136/4023, 3.4% down; Fig. We directly evaluated whether active transcription is required for the formation of promoter G4s, as has been suggested , 16, by  release , 18. DRBp < 0.01; 11/4268 down, 0.3%; Fig. p < 0.01; 449/4268 up, 10.5%) of promoter G4s showed increased G4 signal after TPL treatment. This contrasts with experiments in human adenocarcinoma cells that showed no G4 alterations following TPL treatment [To evaluate whether inhibition of transcription initiation causes loss of promoter G4s, we used triptolide (TPL), which covalently inhibits the Pol II-associated helicase XPB . As seenreatment . Our obsreatment , 21. In reatment , our resGiven transcriptional inhibition does not remove promoter G4s in chromatin, and since chromatin relaxation by histone deacetylase inhibition can increase their formation , we hypo2) by ATAC-seq and found that G4-marked promoters (i.e. Pol II+ G4+) are located in more accessible chromatin compared to their active non-G4-marked (i.e. Pol II+ G4−) counterparts , showing that G4 stabilisation protects G4s from unfolding in hypoxia.To directly assay if G4 stabilisation impacts G4 formation in hypoxia, we visualised nuclear G4 foci  using U2+ G4+ promoters, we found that pyPDS treatment reduced the loss of Pol II by 10-fold in hypoxia compared to DMSO-treated cells  (Sigma), triptolide (Sigma) and pyPDS [2 in the presence of pyPDS for 1 h.K562 cells  were cultured in RPMI 1640  supplemented with 10% of foetal bovine serum . U2OS cells  were cultured in DMEM  supplemented with 10% of FBS. Cells were cultured at 37 °C in 21% Ond pyPDS , 32 wereCells were washed twice with ice-cold PBS and lysed in Pierce® RIPA buffer  by sonatication using a Bioruptor (Diagenode). The following primary antibodies were used for immunoblotting: RNA Pol II C-terminal domain (CTD) phospho Ser2 , RNA Pol II CTD phospho Ser5 , RNA Pol II CTD , HIF 1α , β-Actin  and APE1 . IRDye secondary antibodies (LiCor) were used, and the blot was visualised using a LiCor Odessey CLx instrument.2, 0.5% NP-40, fresh protease inhibitors + 1 mM DTT) at 4 °C for 10 min. Nuclei were pelleted by centrifugation at 1400×g for 5 min at 4 °C and washed once with lysis buffer. Samples were digested with 0.5 U MNase at 25 °C in digestion buffer  and the reaction stopped with an equal volume of MNase stop solution (40 mM EDTA + 0.5% SDS). DNA fragments were purified using QIAGEN MinElute kit. Equal amounts of DNA (300 ng) from each sample were then loaded and resolved on 2% E-Gel EX precast agarose gels .One million cells were washed in ice-cold PBS and incubated in lysis buffer  ChIP-seq was performed essentially with 5 biological replicates as previously described . FifteenATAC-seq was performed essentially with 3 biological replicates as previously described . BrieflyImmunofluorescence staining with BG4 was performed essentially as described previously . Digitalhgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz). Human annotations (gtf file) were downloaded from the Genecode project portal . Annotations for genomic regions  were extracted from the gtf file.Human genome hg38 was downloaded from UCSC (http://broadinstitute.github.io/picard) and removed. Fragment size distribution was estimated using uniquely mapped reads bams with Picard CollectInsertSizeMetric. To assess the amount of mitochondria contamination, reads mapping to chrM were identified and counted directly from the alignment bam files. For each library, regions with local accessibility were identified by calling peaks with macs2 with default options and excluding chrM. For each experimental condition, peak regions observed in 2 out the 3 biological replicates were selected as the consensus regions using bedtools multiIntersectBed (version 2.27.1) [Fastq reads were trimmed from adapters using cutatapt  (cutadap 2.27.1) .Fastq reads were trimmed from adapters using cutadapt (-m 10 -q 20 -O 3 -a CTGTCTCTTATACACATCT) and aligned to the human genome hg38 with bwa mem. Bam files were generated from alignment with samtools view, and duplicated reads were marked and removed using picard MarkDuplicates. The total number of unique reads was quantified for each library. Regions with local enrichments were obtained by calling peaks with macs2 for each individual pull-down library paired to the corresponding input control. For G4 ChIP-seq experiments, consensus regions of each biological replicate were obtained as those observed in 2 out of the 3 technical replicates (multiIntersectBed). The consensus by the experimental case  was obtained by selecting regions reproducibly observed in at least 2 of the 3 biological replicates. For Pol II ChIP-seq experiments, the consensus regions in each experimental condition were obtained as the regions observed in at least 3 of the 5 biological replicates.For both types of ChIP-seq, genome-wide reads per million (RPM) G4 signal was obtained by quantifying the read coverage across the genome and scaling it to a factor that reflected the individual library size , and the analysis was restricted to the human whitelist. The analysis generated the number of overlaps between the G4 consensus sites and the segments to query against , and the fold-enrichments were obtained after summarising results from randomisations.Fold enrichments for G4s over random chance were evaluated at various sites of interest whose genomic coordinates were stored into bed files. Fold enrichments were computed by using the Genomic Association Tester . Next, RPM signals were combined together by averaging replicates of the same cell and then generating a new matrix of signals. The difference of normalised summarised signals between two experimental conditions was obtained by subtracting the matrix of normalised signal in one condition to the matrix of the other condition under investigation. Heatmaps were produced using deeptools plotHeatmap (options: --averageTypeSummaryPlot median). Metagene density signal profile plots were obtained by plotting the average trend of the signal of interest .The metagene density signal profile at transcription start sites (TSSs) was produced similarly for G4, Pol II and ATAC-seq data. After creating bed files with the set/s of regions of interest, we employed the function glmLRT) with default parameters  was used to assess regions with a differential binding signal. For the differential test, batch information, biological and technical (when present) replicates were incorporated in the definition of the design matrix. The differential binding analysis compared pairs of experimental conditions: hypoxia vs normoxia ; all pairwise comparison among DMSO hypoxia, DMSO normoxia, pyPDS hypoxia and pyPDS normoxia. Regions with differential signal were identified as those with p value ≤ 0.05. The regions of interest used to test the effects of hypoxia plus pyPDS or hypoxia alone were defined as the G4 consensus regions overlapping Pol II consensus regions in normoxia at promoters (TSS ± 500 bp). In the case of DRB and TPL experiments, the regions used for the differential signal analysis were obtained as the merge of the regions observed in treatment and control case for each experimental condition, respectively. To illustrate the outcome of the differential analysis, Bland Altman (MA) plots showing the average CPM (x-axis) versus the log-fold change (y-axis) obtained comparing the 2 conditions of interest were used.All differential binding signal analyses were carried out with the R package edgeR. Initially, library size and read coverages at the regions of interest were computed. Prior differential testing, the average cpm (counts per millions) signal was estimated across all input libraries and a threshold value was defined as 2 times the 99th quantile of the average distribution of input cpm. Subsequently, regions for which at least one pull-down library exceeded the threshold value previously defined were kept for subsequent analysis. This step happened for each sequencing assay independently and only for the case when input libraries were available . A generalised linear model  staining for G4s in DMSO- or pyPDS-treated cells upon hypoxia treatment.Additional file 2. Uncropped Western blots.Additional file 3. Review history.


Viruses suppress immune recognition through diverse mechanisms. Epstein-Barr Virus (EBV) establishes latent infection in memory B-lymphocytes and B-cell malignancies where it impacts B-cell immune function. We show here that EBV primary infection of naïve B-cells results in a robust down-regulation of HLA genes. We found that the viral encoded transcriptional regulatory factor EBNA2 bound to multiple regulatory regions in the HLA locus. Conditional expression of EBNA2 correlated with the down regulation of HLA class II transcription. EBNA2 down-regulation of HLA transcription was found to be dependent on CIITA, the major transcriptional activator of HLA class II gene transcription. We identified a major EBNA2 binding site downstream of the CIITA gene and upstream of DEXI, a dexamethasone inducible gene that is oriented head-to-head with CIITA gene transcripts. CRISPR/Cas9 deletion of the EBNA2 site upstream of DEXI attenuated CIITA transcriptional repression. EBNA2 caused an increase in DEXI transcription and a graded change in histone modifications with activation mark H3K27ac near the DEXI locus, and a loss of activation marks at the CIITA locus. A prominent CTCF binding site between CIITA and DEXI enhancers was mutated and further diminished the effects of EBNA2 on CIITA. Analysis of HiC data indicate that DEXI and CIITA enhancers are situated in different chromosome topological associated domains (TADs). These findings suggest that EBNA2 down regulates HLA-II genes through the down regulation of CIITA, and that this down regulation is an indirect consequence of EBNA2 enhancer formation at a neighboring TAD. We propose that enhancer competition between these neighboring chromosome domains represents a novel mechanism for gene regulation demonstrated by EBNA2. in vivo.We describe a novel transcriptional mechanism through which EBV encoded EBNA2 down-regulates HLA class II gene expression. EBNA2 is known to be a potent transcriptional activator and strengthens enhancer formation at many sites in B-lymphocytes. We show that EBNA2 binds to an enhancer element at the DEXI gene that competes with CIITA gene promoter, leading to the down regulation of CIITA transcription. As CIITA is the master regulator of HLA class II gene expression, these findings reveal a novel, highly indirect mechanism for EBNA2 down-regulation of HLA II gene transcription. Down regulation of HLA class II gene expression by EBNA2 is functionally important for the attenuation of T-cell recognition of EBV infected cells, and likely to contribute to EBV persistence and lymphomagenesis  Virus down-regulation of HLA is a classic mechanism of immune evasion . EpsteinThe human leukocyte antigen (HLA) locus contains clusters of genes involved in antigen presentation and immune signaling ,12. It iEBV encodes several genes known to alter host immune function ,20. DuriEBNA2 is a potent transcriptional regulator essential for EBV primary infection and immortalization of B-cells –33. EBNAConversely, EBNA2 can also down-regulate some genes, such as BCL6 and TCL1 to restrict the germinal center phenotype . The mecHere, we show that EBV primary infection of B-lymphocytes results in a concerted down regulation of HLA II genes. We show that EBNA2 is sufficient to down regulation the HLA class II genes, and that this could be attributed largely to a down regulation of the master transcriptional regulator of HLA-class II CIITA . EBNA2 bFig 1A)  , anti-EBF1 , anti-PU.1 , anti-CTCF , anti-RNAPII , or anti-CIITA  overnight at 4°C. Preblocked protein A/G sepharose  was added to each IP reaction for additional 2 to 3 h incubation at 4°C. Each immune complex was washed five times (10 min each) in ChIP related wash buffer at 4°C, and eluted with 150 μl Elution buffer  at 65°C for 30 min. The elutes were then incubated at 65°C overnight to reverse cross-linking, and further treated with Proteinase K in a final concentration of 100 μg/ml at 50°C for 2 hrs. ChIP DNA was purified by Quick PCR Purification Kit (Life Technologies) following the manufacturer’s instruction. ChIP DNA was assayed by qPCR using primers specific for indicated regions and quantified as % input. Primers for ChIP-qPCR are listed in S2 Table.Cells were crosslinked in 1% formaldehyde for 15 min, followed by quenching for 5 min with 0.125 M glycine. 1 × 10pLKO.1 vector-based shRNA constructs for CIITA (TRCN0000019072) were obtained from Open Biosystems. Control shRNAs (shControl or shCtrl) were generated in the pLKO.1 vector with the target sequence 5′-TTATCGCGCATATCACGCG-3′. Lentiviruses were produced in 293T cells using envelope and packaging vectors pMD2.G and pSPAX2 as described previously. EREB2.5 cells were infected with lentiviruses carrying pLKO.1-puro vectors by spin infection at 450 × g for 90 min at room temperature. The cell pellets were resuspended and incubated in fresh RPMI medium (containing 1μM estradiol) and then treated with 2 μg/ml puromycin at 48 h after the infection. The RPMI medium with 2μg/ml puromycin was replaced every 2 to 3 days. The cells were collected after 7 days of puromycin selection and then subjected to further analyses, as indicated.https://tide.nki.nl) [gRNAs targeting CTCF binding motif or EBNA2 binding site were cloned into the lentiCRISPRv2 (Addgene 52961) using published protocols . Lentivi.nki.nl) .6 cells/ml in the same buffer. Cells were blocked with Fc block for 20 min on ice followed by staining of surface-expressed HLA-DR at room temperature for 30 min with anti-HLA-DR . Then the cells were washed three times with FACS buffer, incubated in the dark with secondary antibody  for additional 30 min at room temperature, washed three times and resuspended in ice cold FACS buffer. Then flow cytometric data were collected on an LSRII and analysis of flow cytometry data was conducted with FlowJo. The experiment was conducted in triplicate.Cells were harvested, washed twice with ice cold FACS buffer (PBS with 5% FBS and 0.1% NaN3), and resuspended at 2.5x10RNA-Seq and ATAC-Seq on EBV infected B-cells was described previously. HiC datS1 FigTo rule out the potential impact of estradiol on HLA transcription, LCL352 was treated with (+) or without (-) estradiol for 48 hrs and then assayed by RT-qPCR for HLA-II gene transcription.(TIF)Click here for additional data file.S2 FigA) Schematic diagram showing gRNA positions and location of EBF1 and PU.1 motifs. (B) After CRISPR deletion of EBNA2_BS, genomic DNA was PCR amplified and verified for deletion efficiency.((TIF)Click here for additional data file.S3 FigTo confirm the CTCF-BS mutation, PCR was performed to amplify the gRNA targeted region. The purified PCR fragments were Sanger sequenced (A) and analyzed using TIDE (B). The cutting efficiency were indicated top left.(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.


Hepatoblastoma is a kind of extreme malignancy frequently diagnosed in children. Although surgical resection is considered as the first-line treatment for hepatoblastoma, a relatively large population of patients have lost the preferred opportunity for surgery. Administration of locoregional ablation enables local tumor control but with the deficiency of insufficient ablation, residual tumor, and rapid progression. In this study, we integrated 219 hepatoblastoma and 121 non-cancer liver tissues to evaluate the expression of NR2F6, from which a higher NR2F6 level was found in hepatoblastoma compared with non-cancer livers with a standard mean difference (SMD) of 1.04 . The overexpression of NR2F6 also appeared to be an efficient indicator in distinguishing hepatoblastoma tissues from non-cancer liver tissues from the indication of a summarized AUC of 0.90, with a pooled sensitivity of 0.76 and a pooled specificity of 0.89. Interestingly, nude mouse xenografts provided direct evidence that overexpressed NR2F6 was also detected in residual tumor compared to untreated hepatoblastoma. Chromatin immunoprecipitation-binding data in HepG2 cells and transcriptome analysis of HepG2 xenografts were combined to identify target genes regulated by NR2F6. We finally selected 150 novel target genes of NR2F6 in residual tumor of incomplete ablation, and these genes appeared to be associated with the biological regulation of lipid metabolism-related pathway. Accordingly, targeting NR2F6 holds a therapeutic promise in treating residual recurrent hepatoblastoma after incomplete ablation.  HepatobIn recent years, ultrasound-guided tumor ablation has become the preferred clinical strategy for primary small liver tumors in adults because of the advantages of being minimally invasive with fewer complications compared to surgical resection ,8. But oTranscription factor nuclear receptor subfamily 2, group F, member 6 (NR2F6) is a member of a nuclear receptor superfamily that has been shown to be crucial for the regulation of biological events, such as metabolism, reproduction, and development . SeveralIn this study, we confirmed a higher expression of NR2F6 in 219 cases of hepatoblastoma than 121 cases of non-cancer child liver by combining high throughput RNA sequencing (RNA-seq) data. We therefore hypothesized that overexpressed NR2F6 might contribute to the carcinogenesis of hepatoblastoma. The aim of this paper is to investigate the role of NR2F6 in the progression of residual tumor. The nude mouse xenografts were performed, which indicated an upregulated NR2F6 level in the ablation xenografts after incomplete ablation. Furthermore, targets regulated by the transcription factor NR2F6 were identified by integrating ChIP-seq and nude mouse xenograft models. These findings supported that NR2F6 might be a prospective therapeutic target for recurrent residual hepatoblastoma after insufficient ablation.2.2.1To systematically evaluate the expression level of NR2F6 in hepatoblastoma, we tried to obtain available samples from several public databases  through the searching words of hepatoblastoma. The samples that met the following criteria would be included : NR2F6 e2.22 dishes containing Dulbecco’s Modified Eagle’s Medium  supplemented with 10% fetal bovine serum and 1% streptomycin-penicillin antibiotic mixture in an atmosphere of 5% CO2 at 37°C for 7 days. And specific pathogen-free BALB/c nude mice  were purchased from Shanghai SLAC Laboratory Animal Co., Ltd. Of note, the ove [In order to explore the underlying mechanisms of NR2F6 in residual hepatoblastoma, nude mouse xenograft experiments were performed to simulate incomplete ablation of human hepatoblastoma. Human hepatoblastoma (HepG2) cell line was provided by Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. HepG2 cells were cultured in 25 cm the ove . Followi2.42(x + 1) scale, and gene expression levels were calculated into mean ± SD. Students’ t-tests were used to examine expression differences between the two groups. And for systematic evaluation of the NR2F6 level in hepatoblastoma, evidence-based evaluation models, including a fixed-effects model and a random-effects model, were constructed using the Stata 12.0 software. When heterogeneity >50%, a random-effects model would be used; otherwise, a fixed-effects model would be the preferred option. Then, publication bias existing in evidence-based models was further assessed using Begg’s and Egger’s tests. Further, latent competence for NR2F6 to differentiate between hepatoblastoma and non-tumor liver tissues was also assessed by pooled sensitivity and specificity, together with a summarized receiver operating characteristic (ROC) curve [Statistical analysis was performed using Prismpad 8.0 and R language. All raw expression data were normalized into a log C) curve ,27.2.5Transcription factors usually exert a regulatory influence on gene expression by binding to promoter regions. Chromatin immunoprecipitation (ChIP) assay is a helpful technique to explore interactions of protein-DNA and to advance epigenetic modifications and genetic regulation. ChIP-seq technique can identify and relatively measure-specific interactions between protein and chromatin at multiple loci in the human genome. Based on CistromeDB, four ChIP-seq datasets of NR2F6  were obtained to screen latent targets regulated by NR2F6 in the hepatoblastoma HepG2 cells. The genes with interaction scores greater than 2 and repeated in at least two datasets among four ChIP-seq analyses were considered as potential targets for NR2F6 .2.6In this study, transcriptome analysis of incomplete ablation xenograft and NR2F6 ChIP-seq data were jointly used to detect the latent genes targeted by NR2F6 in residual hepatoblastoma. We selected the intersection genes appearing at upregulated DEGs following incomplete ablation and the targets of NR2F6 detected by ChIP-seq. To reveal the underlying mechanism of NR2F6 in recurrent residual hepatoblastoma, Gene Ontology (GO) annotation and pathway analysis including Reactome pathway and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were finally carried out using WebGestalt server .In this work, increased NR2F6 was determined from hepatoblastoma based on large-scale data including 440 samples. Subsequently, hepatoblastoma-derived HepG2 cells were inoculated under the right armpit of mice. Treatment of incomplete ablation was performed for HepG2 xenografts, from which a higher NR2F6 level was detected in residual hepatoblastoma untreated samples. A total of 150 targets regulated by NR2F6 in residual tumor were identified from experimentally verified ChIP-seq data and transcriptome analysis, and a molecular mechanism for these genes was disclosed utilizing GO annotation and pathway analysis, indicating NR2F6 along with its targets greatly contribute to the dysregulation of biological activity related to lipid metabolism.33.1In seven datasets among nine studies, NR2F6 exhibited clearly higher levels in hepatoblastoma tissues than non-cancer child livers  of eight studies indicated that NR2F6 had a relatively high ability to differentiate between hepatoblastoma and non-cancer child livers . Besides3.32FC = 1.590, p = 0.03), suggesting that NR2F6 might also play an important role in residual tumor. Besides, an upward trend of NR2F6 expression could still be observed in residual tumor when compared to an untreated group, although nonparametric t tests did not indicate a significantly statistical p-value . At the same time, the overexpression of NR2F6 appeared to be an efficient indicator in distinguishing hepatoblastoma tissues from non-cancer liver tissues from the indication of summarized AUC of 0.90, with a pooled sensitivity of 0.76 and a pooled specificity of 0.89, demonstrating that overexpressed NR2F6 might act as a promising biomarker in the diagnosis of hepatoblastoma. Nevertheless, whether serum NR2F6 could be used to diagnose NR2F6 in clinical practice needs an in-depth investigation. To further study the role of residual liver tumor, hepatoblastoma HepG2 cells were subcutaneously transplanted into nude mice. Interestingly, increased NR2F6 was also found in the group treated by incomplete ablation in comparison with the untreated group. This finding provides a shred of novel evidence to reveal the underlying mechanism of residual hepatoblastoma.To elucidate how NR2F6 functions as a transcription factor in residual hepatoblastoma, differentially expressed analyses were performed between incomplete ablation xenografts and an untreated group, from which we selected 1,060 upregulated genes through the threshold of a p-value < 0.05 and a log2FC > 1. Subsequently, genome-wide binding data (ChIP-seq) in HepG2 cells were combined to identify which genes could be bound by NR2F6. Finally, NR2F6 was found to clearly interact with the promoter region of 150 targets among 1,060 upregulated genes after incomplete ablation. According to the GO annotation and pathway analysis, these 150 genes targeted by NR2F6 in residual tumor are apparently related to the biological events of a metabolism-related pathway, especially lipid metabolism.Lipid metabolic reprogramming is an essential property of tumor cells and has recently drawn much attention from researchers. A growing number of studies have shown that nuclear receptors play a key role in the regulation of lipid metabolism reprogramming, such as NR4A1, which serves as a key transcriptional regulator of liposome and glucose homeostasis, as well as lipid metabolism . Lipid mDespite the aforementioned findings, some deficiencies should still be illustrated. First, the expression evaluation of NR2F6 is based only on microarrays and high throughput sequencing. An additional detection technique, such as qRT-PCR, needs to be performed. Besides, although increased levels of NR2F6 mRNA were detected in both hepatoblastoma and residual tumor, changes of NR2F6 protein should be further validated by Western blot or immunochemistry. In addition, the targets of NR2F6 in residual hepatoblastoma were significantly related to the regulation of lipid metabolism as indicated by GO annotation and pathway analysis. Therefore, we mainly focused on and mainly discussed the lipid metabolic regulation of NR2F6 in residual hepatoblastoma. However, whether these targets regulated by NR2F6 would be involved in cell-cycle progression, cell apoptosis, and angiogenesis needs to be experimentally verified by evidence in our further research.5.We are the first to confirm the overexpression of NR2F6 in hepatoblastoma tissues, utilizing large-sample evaluation from multi-region and multi-source samples. Besides, we are also the first to find the increased level in residual tumor received incomplete ablation compared with untreated xenografts. Through ChIP-seq data and transcriptome analysis, the targets and molecular mechanism for NR2F6 were disclosed by GO annotation and pathway analysis, indicating that the rapid progression of residual hepatoblastoma might result from dysregulation of lipid metabolism stimulated by overexpressed NR2F6 in residual hepatoblastoma. In the future, an in-depth investigation will be performed to validate our findings.Click here for additional data file.


Nature, Shen and colleagues characterized a peri-arteriolar niche in the bone marrow with highly proliferative, short-lived, leptin receptor- and osteolectin (Oln) positive stromal cells, which improved bone regeneration and supported bacterial clearance after fracture. By proving that maintenance of these cells critically required mechanical stimulation, which in turn was affected by age,1 the authors identified possible therapeutic targets for bone healing and regeneration.In a study recently published in + BMSCs, however, was dependent on the expression of Oln, also known as stem cell growth factor (SCGF) or C-type lectin domain family 11 member A (CLEC11A). Oln was previously shown to be expressed in hypertrophic chondrocytes, osteoblasts, and osteocytes. Oln-negative LEPR+Oln− BMSCs preferably differentiated into adipocytes, but retained their osteogenic potential. Oln-positive LEPR+Oln+ BMSCs were primed towards osteogenesis , also known as skeletal or mesenchymal stem cells, not only function as adipogenic, chondrogenic or osteogenic progenitors, but also provide cytokines critically required for maintenance and fate of hematopoietic stem cells (HSCs). These cytokines include, among others, stem cell factor (SCF), stromal cell-derived factor 1 and pleiotrophin. In other studies, it was shown that BMSCs producing these cytokines express leptin receptor (LEPR). In the here presented study, the authors showed that the differentiation potential of these LEPR+Oln+ and LEPR+Oln− BMSCs. LEPR+Oln− BMSCs localized in the periphery of sinusoidal vessels. In contrast, LEPR+Oln+ BMSCs were found in the periphery of arterioles, mainly in the diaphysis, the central bone marrow and near the endosteum, which defined the niche for these osteoprogenitor cells. Comparing the two cell types, LEPR+Oln+ BMSCs showed a significantly higher proliferation rate than LEPR+Oln− BMSCs. The rapid cell division of LEPR+Oln+ BMSCs was accompanied by a high recombination efficiency and a short live-span. Despite these differences, LEPR+Oln− and LEPR+Oln+ BMSCs both expressed SCF. Deletion of SCF in LEPR+Oln+ BMSCs, did not affect the frequencies of HSCs, multipotent-, granulocyte-macrophage-, megakaryocyte-erythrocyte- or common myeloid progenitors, but significantly reduced the frequency of common lymphoid progenitors (CLPs) in the bone marrow  decreased the number of LEPR+Oln+ BMSCs and thus CLPs in the bone marrow, which led to the conclusion that increasing bone volume alone was not sufficient to augment these two cell types in the bone marrow. However, the number of LEPR+Oln+ BMSCs in the peri-arteriolar niche rapidly increased after a bone fracture. Together with the Oln+ osteogenic cells within the callus at the fracture site, LEPR+Oln+ BMSCs formed most of the osteoblasts that contributed to the regeneration of the bone. Thus, LEPR+Oln+ BMSCs in the peri-arteriolar niche represent an interesting target to be addressed in delayed or non-union fracture healing, often accompanied by complications such as infections. As depletion of LEPR+Oln+ BMSCs was associated with a decline in CLPs, the authors also addressed this point. Mice with conditional knockdown of osteolectin, failed to increase B-cell and T-cell counts and clear bacteria from the spleen after oral administration of Listeria monocytogenesis. After intraperitoneal administration of Listeria, this effect was even more pronounced and also involved NK-cells, and cells of the thymus. Thus, cells of the peri-arteriolar niche seemed to be required not only for maintenance of normal numbers of CLPs, but also for augmentation of lymphopoiesis and for clearance of bacteria after acute infection. Therefore, these cells may also prospectively be addressed in the treatment of septic complications.The authors followed several approaches to better characterize the biological function of the peri-arteriolar LEPR+Oln+ BMSCs and CLPs in the weight-bearing bones. For the reverse experiments, the authors suspended hindlimbs of young mice to reduce the mechanical loading. After only 2 weeks, bone mineral density, cortical thickness, as well as LEPR+Oln+ BMSCs and CLPs were significantly reduced in the femurs of the suspended mice as compared to mice with normal activity. Gene-expression profiling and Western blotting identified the mechanosensitive ion channel PIEZO1 as possible regulator in this process. Applied pressure and pharmacological stimulation of PIEZO1 with Yoda1 both induced calcium influx into LEPR+Oln+ BMSCs. Deletion of PIEZO1 in LEPR+Oln+ BMSCs abolished this effect. Furthermore, the deletion of PIEZO1 was accompanied by a significant decline in CLPs substantiating the proposed regulatory role of PIEZO1 in the described peri-arteriolar niche. This mechano-dependence could not be shown for the LEPR+Oln− BMSCs in the peri-sinusoidal niche  mechanosensitive (PIEZO1+) BMSCs that control osteogenesis and lymphopoiesis. These specialized cells represent an interesting target to address clinical challenges, such as osteoporosis, delayed or non-union fracture healing, and associated septic complications. For example, transforming growth factor beta (TGF-β), which is well known to control adhesion, proliferation, migration and mechanosensation of osteoprogenitor cells during bone regeneration,3 was reported to maintain multipotency and to inhibit cell commitment and expression of Oln.4 Oln in turn was reported to suppress expression of fibroblast activation protein, also known as dipeptidyl peptidase-4 or CD26, actively inhibiting osteogenesis.5 These examples show that unraveling the underlying molecular mechanisms may provide novel therapeutic targets to support bone regeneration.In summary, the manuscript provides a detailed characterization of a novel peri-arteriolar niche in the bone, harboring specific (LEPR