Importantly, YXS initiated biological process such as anti-apoptosis and DNA repair to protect cardiomyocytes from H2O2-induced damage. By using the integrated strategy, DNA-(apurinic or apyrimidinic site) lyase (Apex1), pre B-cell leukemia transcription factor 3 (Pbx3), and five other TFs with their functions involved in anti-oxidation, anti-apoptosis and DNA repair were identified. This study offers a new understanding of the mechanism underlying YXS-mediated protection against H2O2-induced oxidative stress in cardiomyocytes and reveals novel targets for oxidative stress-related diseases.Oxidative stress initiates harmful cellular responses, such as DNA damage and protein denaturation, triggering a series of cardiovascular disorders. Systematic investigations of the transcription factors (TFs) involved in oxidative stress can help reveal the underlying molecular mechanisms and facilitate the discovery of effective therapeutic targets in related diseases. In this study, an integrated strategy which integrated RNA-seq-based transcriptomics techniques and a newly developed concatenated tandem array of consensus TF response elements (catTFREs)-based proteomics approach and then combined with a network pharmacology analysis, was developed and this integrated strategy was used to investigate critical TFs in the protection of Yixin-shu (YXS), a standardized medical product used for ischaemic heart disease, against hydrogen peroxide (H During oxidative stress, ROS can induce a serious of biological changes such as DNA damage, lipid peroxidation and protein aggregation, which lead to cell death. Notably, oxidative stress-induced injury plays a vital role in myocardial ischaemia reperfusion (MI/R) injury by causing a series of complicated pathological changes such as DNA damage, mitochondrial dysfunction, and protein alteration, resulting in cell death and apoptosis3. Transcription factors (TFs) are proteins that bind to specific DNA sequences and regulate the transcription of DNA into RNA. Growing evidence has indicated that transcription factors act as critical regulators in many pathologic processes5. For example, sineoculis homeobox homolog 1 (Six1) decreased caspase-3 levels and inhibited tumor necrosis factor-related apoptosis6. Ring1 and YY1 binding protein (RYBP) induced tumour cell apoptosis by activating the activator protein 1 (AP-1) signalling pathway7. As an NF-κB family member, the transcription factor p65 (RELA) prevented JNK-mediated apoptosis in osteoclasts in response to the cytokine RANKL8. Recent studies have indicated that TFs may be critical regulators in oxidative stress injury10. The transcription factor GATA-4 (GATA4), a zinc finger-containing transcription factor, can protect cardiomyocytes from doxorubicin-induced apoptosis by recognizing the −266 GATA motif in the Bcl2 promoter11. Antioxidant and DNA repair genes could be activated by nuclear factor erythroid-derived-like 2 (Nrf-2) to promote cell survival when subjected to oxidative stress10. During ischaemia-reperfusion (IR), oxidative stress was enhanced by nuclear cardiac myosin light chain 2 (MYL2) through the up-regulation of NOX2 gene expression12.Reactive oxygen species (ROS) are a series of oxygen-based molecular species characterized by their high chemical reactivity, and the balance of the production and removal of ROS is vital in maintaining normal physiological processes14. However, the transcriptional activity of TFs cannot be directly inferred from mRNA profiling information. In addition, proteomics approaches can only detect a small portion of TFs, and their low abundance prevents the activity profiling of all TFs present in a cell, while the protein level of TFs is also insufficient to reflect their transcriptional activity14. Recently, a method for quantitatively evaluating the activity of TFs through large-scale profiling was established by building a DNA construct containing tandem transcription factor DNA response elements (catTFREs) with an affinity to specific TFs15. The catTFRE technology allows the direct identification and quantification of TF transcriptional activity in a high-throughput manner.Though TFs have been identified as important regulators in oxidative stress, direct large-scale profiling of TFs has remained a challenge, especially their quantitative evaluation. Currently, one method commonly used to estimate the abundance of TFs is the analysis of mRNA profiles17. Considering the binding activity of TFs to a specific DNA sequence and their downstream genes expression levels at the same time could reflect the activity and functions of the transcription factors more accurately and systematically. In this study, an integrated strategy which integrated TFs activity quantified by catTFRE method and their downstream genes by RNA-seq technology firstly and then combined with a network pharmacology analysis was developed and used to identify critical TFs in the protection of Yixin-shu (YXS), a Chinese standardized medical product used for the treatment of ischaemic heart disease, against H2O2-induced oxidative stress. YXS, containing seven herbs, Ginseng, Ophiopogon japonicus, Schisandra, Astragalus, Salvia, Chuanxiong, and Hawthorn, has been shown to maintain cardiac function by reducing mitochondrial-mediated apoptosis and oxidative stress injury18. However, the molecular mechanism by which YXS protects against oxidative stress remains unclear, especially on a TF level. Thus, an integrated strategy was developed in our research, and we hypothesized that this integrated strategy could be used to reveal critical TFs in the protection of YXS against H2O2-induced injury. Importantly, this integrated strategy could reduce the background interference to the minimum and find out the fundamental critical transcription factors in complicated biological process. Moreover, rather than focusing on a single or a few molecular pathways, a whole-transcriptome analysis and large-scale TF investigation, and then combined a network pharmacology approach help to ensure a comprehensive and accurate analysis.The catTFRE method provide a direct insight for the binding activity of transcription factors to a specific DNA sequence, which usually is the first step to activate downstream genes. The Illumina-based RNA-seq technology allows for a comprehensive examination of downstream gene expression2 0.10 g, CaCl2 0.20 g, NaHCO3 1.00 g, NaH2PO4 0.05 g, glucose 1.00 g, pH 7.4) was added to obtain YXS extraction solution . After maintained in fasting conditions for 12 h, the rats were sacrificed and the intestines were collected. Four segments of intestines of 14 cm segments were generated and ligated to form a sac at one end after turned inside-out in Tyrode buffer solution at 0 °C. The Tyrode buffer in the sac was then exchanged with YXS solution  at 37 °C with O2/CO2 (95%/5%). After 2 h, the solution in the sac was collected and filtered for the following experiments. The final concentration of YXS intestinal absorption liquid was 2 mg/mL, which was calculated according to the crude drug.Experimental Animal Center of Peking University Health Science Center, Beijing, China (certificate no. SCXK (Jing) 2009–0017) provided male Sprague Dawley rats weighting 220 ± 10 g. The experiment was approved by Committee on Animal Care and Use of Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, and performed according to the approved guidelines. YXS capsule  was provided by Guizhou Xinbang Pharmaceutical Co., Ltd. The powder of YXS capsule was dissolved in the ethanol  and extracted for 2 hours under reflux. After filtered, the solution was rotary evaporated to dryness at 65 °C. Tyrode buffer solution 19 and cultured according to its recommended procedures. The purchased hiPS-CMs cells were thawed and then cultured on the culture plates, which were pre-coated with 50 μL matrigel solutions  at 4 °C for 24 h. Then the cells were cultured in the incubator at 37 °C in 5% CO2 atmospheres. The medium was changed every 2 days. After nearly 5–7days, the hiPS-CM cells reached a stable cell status and used for the following experiment.Cell Resource Center of Peking Union Medical College in China offered H9c2 cells. The cells were cultured with culture medium containing penicillin (100 μg/ml), and streptomycin (100 μg/ml), high-glucose DMEM , and 10% v/v fetal bovine serum , at 37 °C in 5% CO2O2 treatment for 1 hour. The safe concentration of YXS was investigated by treating H9c2 cells only with YXS for 24 hour. Trimetazidine  with 10 μM was used as positive control. Then MTT solution was added to incubate for 3 hours and then treated with dimethyl sulfoxide (DMSO) before detected at 570 nm with a microplate reader . As for the analysis of the total-antioxygen capacity (T-AOC), the total superoxide dismutase (T-SOD), and Glutaric dialdehyde (MDA), the treated cells were collected and then crushed through ultrasonic wave. Then investigation of T-AOC, T-SOD and MDA were performed according to the instruction of the detection kit with a microplate reader , which were purchased from Nanjing Jiancheng (China).The cell viability was performed by using 3--2, 5-diphenyl-2H-tetrazolium bromide  assay. For the therapeutic effect, the cells were pre-treated with YXS intestinal absorption liquid of various concentrations  for 24 hours before HμL binding buffer was added and then 5 μL Annexin V and 5 μL propidium iodide was loaded in the dark at room temperature for 10 min. Photos were taken under a confocal microscope.Intracellular reactive oxygen species (ROS) was assessed with the DCFH-DA probe . Briefly, 10 μM DCFH-DA was incubated with cell suspensions for 30 min and then residual probe was removed by washing with PBS. The cellular fluorescence intensities were measured on a fluorescence microplate reader  with excitation and emission wavelengths set at 488 nm and 525 nm, respectively. Cell apoptosis was analyzed through annexin V-PI staining and JC-1 assay. After treatment, cell precipitate was collected through trypsinization and centrifugation. JC-1 dye  diluted with culture medium were added to the precipitation at 37 °C for 20 min. After washed twice, the cell suspension was detected with a FACStar Plus flow cytometer . The mitochondrial membrane potential could be reflected by the Mean FL2 fluorescence intensity. Annexin V-FITC and PI staining was applied to investigate the cell apoptotic rate by using an Annexin V-FITC Apoptosis Detection Kit. Briefly, after treatment, 500 For the immunofluorescence staining, 10% polyformaldehyde was applied to fix the samples, followed by permeabilizing with 0.5% Triton X-100 for 30 min. After washed with PBS, the samples were treated with 10% donkey serum to block background for 60 min. Next, the primary antibody including cleaved Caspase-3 , APEX1 , PBX3 , was loaded at 4 °C for 24 h, followed by rhodamine phalloidin  and a secondary anti-body  incubation in the dark at 37 °C for 60 min. Finally, the samples were treated with 4,6-diamidino-2-phenylindole  for 5 min before photos were taken under the confocal microscope .https://www.ncbi.nlm.nih.gov/bioproject/PRJNA361184.Three biological replicates were used for the RNA-seq experiment. After treatment, total RNA was extracted using TRIzol Reagent  according to the manufacturer’s instructions. An RNA Nano 6000 Assay Kit was used to detect the RNA integrity on a Bioanalyzer 2100 system . Then, 1 μg of RNA was used to construct a cDNA library with a NEBNext® Ultra™ RNA Library Prep Kit for Illumina® . Briefly, poly-T oligo-conjugated magnetic beads were used to purify mRNA, and then the purified mRNA was cleaved into fragments by divalent cations before the synthesis of first-strand cDNA. Next, second-strand cDNA was synthesized using DNA Polymerase I and RNase H. Ligation of the adapters and adenylation of the 3′ ends of DNA fragments was completed before PCR was used to amplify the cDNA template. A TruSeq PE150 Cluster Kit v3-cBot-HS (Illumina) was used to perform the clustering of the index-coded samples on a cBot Cluster Generation System. An Illumina HiSeq. 4000 platform was used to sequence the library, and 150 bp paired-end reads were produced. The library construction and Illumina sequencing were performed at Novogene Bioinformatics Technology Co., Ltd. , and the raw-sequence read data of the whole experiment were uploaded to 20. FDR correction for multiple testing was applied to discover differentially expressed genes (FDR < 0.05). ClueGO21 was used for the functional annotation of the RNA-seq data, which was further visualized with Cytoscape v3.4.022.The rat reference genome (ensemble release 83) was used for read mapping for the subsequent transcript assembly and quantification, and HTseq v0.6.1 was used to count the number of reads mapped to each gene. To estimate gene expression levels, FPKM was calculated and represented as the number of fragments per kilobase of transcript sequence per millions of base pairs sequenced. The differential expression analysis was performed using edgeR softwareNuclear extracts of the samples were obtained using nuclear extract prep kits (Thermo Fisher) according to the manufacturer’s protocol. Biotinylated DNA was pre-immobilized on Dynabeads before the nuclear extract was added and incubated with the Dynabeads. EDTA/EGTA and NaCl were then added to this mixture to obtain a final concentration of 1 mM and 200–250 mM, respectively, and the mixture was incubated at 4 °C for 2 h. The supernatant was removed, and the Dynabeads were washed with NETN  twice before the beads were digested overnight with trypsin. The tryptic peptides were analysed by an LTQ-Orbitrap Velos instrument (Thermo) after separation on a C18 column , with the flow rate set at 350 nL/min. The MS conditions were set as follows: A nano-spray ion source with a spray voltage of 1800 V, with no sheath gas flow and with the ion transfer tube at 350 °C, was used. A data-dependent mode was used in the mass spectrometer with a survey scan from m/z 375 to 1600 with a resolution of 60,000 at m/z 400. Collision-induced dissociation with normalized collision energy of 35% and an activation time of 5 ms was applied to acquire the 50 most intense peaks with a charge state no less than 2.LC-MS/MS analyses were conducted on an Easy-nLC 1000 liquid chromatography system (Thermo), which was coupled to an Orbitrap Fusion through a nano-electrospray ion source (Thermo). The obtained tryptic peptides were isolated on a homemade 100 µm ID × 10 cm column  at 500 nL/min with a linear 5–35% acetonitrile gradient after being eluted from a 360-um ID × 2 cm, C18 trap column. Survey scans were acquired after the accumulation of 5e5 ions in the Orbitrap for m/z 300–1400 using a resolution of 120,000 at m/z 200. After the fragmentation was conducted in top-speed data-dependent mode at normalized collision energy of 32% in the HCD cell, the fragmented ions were transferred into the ion trap analyser with the AGC target at 5e3 and maximum injection time at 35 ms. The dynamic exclusion of previously acquired precursor ions was set to be 18 s.The rat protein RefSeq database in Proteome Discoverer 1.4.0.288 was used to analyse the spectral data. Mascot  was used to ensure a false discovery rate lower than 1%. The mass tolerance for the precursor was set to be 20 ppm, while the tolerance for product ions was set at 0.5 Da. Specifically, acetyl (N terminus) and oxidation (Met) were set as variable modifications and carbamidomethyl (Cys) as a fixed modification, and 2 missed cleavage sites for trypsin were permitted. An intensity-based absolute quantification method was applied to analyse the protein level. Briefly, the number of theoretical peptides was calculated by in silico protein digestion with a PERL script, and the numbers of peptides between 6 and 30 amino acids were added, while the missed cleavages were ignored. The iBAQ intensities were acquired by normalizing the protein intensities to the number of theoretical peptides23. Critical TFs and their downstream target genes regulatory relationships were used to construct TF-target regulatory network. Among target genes, only differentially expressed gene were included. Co-occurring TFs and target were colored as pink node by comparing regulatory network of model (model vs control) and after YXS pretreatment (YXS vs model).Based on expression level and regulatory relationships of TFs and target genes, critical TFs were identified as TFs whose target genes expression level was differentially expressed accordingly. According to consistency of transcriptional activity of TF and expression level of downstream targets, critical TFs were classified into two categories: activators and repressors; in two conditions, change of transcription activity of former and downstream target gene expression is consistent which suggested activator may activated transcription of targets, and change of the latter is inconsistent which suggested repressors may repressed target transcription. Permutation test was applied to test whether there is statistically significant change of target genes expression using whole transcriptome as null distribution to compare, and only the TFs with significantly differential expressing of target genes were considered as critical TFs. For a group of targets, T is a vector which includes fold change of each target expression in two conditions (e.g. model vs. control or YXS vs. model). G is a vector which presents fold change of all genes expression in two conditions. Permutation test is applied to test whether there is significant difference between means of T and G (null distribution). A group of targets was significantly up-regulated, if mean of T is larger than G with significant difference; otherwise this group of targets was significantly down-regulated. Gene regulatory relationships were retrieved from the mouse gene regulatory network of CellNet by vertebrate homology mapping to rat24 and then were submitted to BATMAN-TCM25 to discover TCM therapeutic mechanism. The potential targets of 83 chemical compounds were obtained by the retrieval in the integrated known drug-target interaction dataset and the similarity-based target prediction method which ranks potential drug-target interactions based on their similarity to the known drug-target interactions, respectively26.Chemical compounds of YXS were obtained from a published literature#P < 0.05 versus model.The data obtained in this research was analyzed with SPSS V17.0  and the results are shown as mean ± standard deviation (SD). The significant difference was set at P values, *P < 0.05 versus control, 2O2-induced damage, cell viability, antioxidant enzymes, ROS levels and cell apoptosis were examined accordingly  approach. As shown in Table 2O2, with 57 activated TFs (fold change > 2) and 51 repressed TFs (fold change < 0.5) identified in the H2O2-treated group compared with the control group  terms were determined Fig. . When corms Fig. . Specifirms Fig. . In addi2O2-induced injury model, an algorithm was developed based on the transcriptional activity of TFs and the expression level of target genes. The critical TFs were divided into two classes, activators and repressors, based on the direction of TF regulation and the expression of target genes. The correlations between critical TFs and their target genes in response to H2O2 are shown in Fig. 2O2 treatment, which was in agreement with the global repressed gene expression profile in the model group  and constituent chemical compounds (15 compounds) was constructed to demonstrate the connection between these critical TFs in oxidative stress and YXS. This network revealed that 24 transcriptional co-activators were co-expressed with their interacting critical TFs after YXS treatment Fig. . Among t29. Pbx3 belongs to a family of TALE (three amino acid loop extension) class homeodomain transcription factors, which are involved in developmental gene expression30. To further verify the transcriptional activity of Apex1 and Pbx3, immunofluorescence staining was performed. The transcriptional activity of Apex1 and Pbx3 was suppressed, as indicated by a decrease in the nuclear staining of Apex1 and Pbx3 in the H2O2-treated group  and PI staining to 259 ± 47% (p < 0.05) of the control group, whereas YXS treatment significantly reduced the staining to 135 ± 30% and 112 ± 27% of the control, respectively. In addition, increased cleaved caspase-3 staining  was observed after H2O2 treatment, and this was decreased by YXS   Fig. , indicatdel Fig. .Figure 82. However, the mechanisms involved in oxidative stress remain unclear. Due to low TF abundance, large-scale quantitative analysis of TFs remains a challenge, and it is important to reveal the underlying mechanisms in regards to the activity of transcription factors in oxidative stress. In this study, an integrated strategy was developed to find critical transcription factors through integrating TFs activity and their downstream genes and then combined with a network pharmacology analysis. By using the integrated strategy, Apex1, Pbx3, and along with other 5 TFs with their functions involved in anti-oxidation, anti-apoptosis and DNA repair might be important transcription factors that mediate YXS’s protection against H2O2-induced oxidative stress. Moreover, YXS initiated biological process such as anti-apoptosis and DNA repair to protect cardiomyocytes against H2O2-induced damage. The findings offer novel insights into the underlying mechanisms of YXS for the treatment of heart disease.Oxidative stress plays a vital role in the pathogenesis of many complicated diseases such as diabetes, ageing and cardiovascular diseases2O2-induced injury as shown in Fig. 15. Then 10 critical TFs were initially screened out by integrating TFs activity and their downstream genes based on their gene expression and regulatory directions. Integrating the data from the RNA-seq transcriptome and catTFRE proteome could reduce the background interference to the minimum and find out the fundamental critical transcription factors in complicated biological process. Finally, 7 critical TFs were further identified through a network of chemical components of YXS and their potential targets via a network pharmacology analysis. Need to notice, up-regulation of Apex1 could inhibit oxidative stress and enhanced antioxidant ability through regulating Nrf2 which was consistent with our result31. Meis1 deficiency resulted in increased oxidative stress and cell apoptosis32. Arnt could reduce ROS levels, and the deficiency of Arnt in the mouse hearts resulted in cardiomyopathy33. All these findings indicated that the integrated strategy was effective to discover critical transcription factors in the protection of YXS against H2O2-induced oxidative stress.An integrated strategy was successfully constructed to reveal critical TFs in the protection of YXS against H2O2-induced injury. ROS play vital roles in oxidative stress-mediated cardiac injury, as they can attack biological molecules such as lipids, proteins, nucleic acids and enzymes and induce a series of damaging processes including DNA crosslinking, enzyme deactivation, and protein degradation, resulting in eventual cell death. Among the responses, cell apoptosis was a typical phenomenon that occurs in response to oxidative stress. In this study, typical apoptotic characteristics of cardiomyocytes were observed, such as increased cleaved casapase-3 and an increase in the loss of mitochondria membrane potential, and these outcomes were obviously rescued by YXS  enhances apoptosis resistance during oxidative stress by targeting FOXO134. Among identified seven TFs, anti-apoptotic TFs such as Apex135, Pbx337, Tfcp238, and Arnt33 were obviously repressed, and their target anti-apoptotic genes such as Asxl139, Bcl940, Fat141 and Arhgef1242 were also down-regulated, indicating that cell apoptosis occurred at the molecular level after H2O2 treatment. By contrast, YXS activated anti-apoptotic TFs such as Apex1, Pbx3, Tfcp2, and Arnt, and increased anti-apoptosis genes such as Asxl1, Arhgef1242 and Cenpf43, demonstrating a vital protective role in H2O2-induced injury. Moreover, the DNA repair process was also activated by YXS, as indicated by the results from the RNA-seq data  class homeodomain transcription factors consisting of Pbx-1, 2, 3, 4, which function as Hox cofactors in developmental gene expression30. Recent studies revealed that Pbx3 could serve as a cofactor of HOXA9 to inhibit leukaemic cell apoptosis in leukaemogenesis37. To further reveal the role of Pbx3, its downstream genes were extensively analysed. The pro-survival genes Bcl940, Fat141 and Arhgef1242 were all significantly decreased, indicating that serious damage was caused by H2O2. Importantly, an increase in anti-apoptotic genes such as Arhgef1242, and Cenpf43 and a decrease in pro-apoptotic genes such as Pbx152 was observed after YXS treatment, suggesting a potential protective role of Pbx3 in H2O2-induced injury. Thus, Pbx3 might played a role in anti-apoptotic effect as indicated by the increased anti-apoptotic genes expression such as Arhgef12 and Cenpf and decreased pro-apoptotic genes such as Pbx1 after YXS treatment.In this study, Apex1 and Pbx3 were identified as critical TFs in the protection of YXS against H2O2-induced injury. Alpha-globin transcription factor CP2 (Tfcp2), also known as LSF, belongs to the LSF/CP2 family, which is related to the Grainyhead family of proteins, and the activity of Tfcp2 is essential for cell cycle progression54. The transcriptional activity of Tfcp2 is regulated through phosphorylation by both Erk and cyclin C/Cdk2 during G1 phase. Phosphorylation by Erk on Ser-291 and by cyclin C/Cdk2 on Ser-309 results in Tfcp2 suppression, and the dephosphorylation of both sites activates Tfcp2 and facilitates the transition of cells into late G1 phase, prior to the activation of Tyms at the G1/S transition56. Recent studies have indicated that the suppression of Tfcp2 transcriptional activity results in either apoptosis during S phase or cell cycle arrest at the G1/S transition by down-regulating thymidylate synthase (Tyms)38. Dnmt1-associated protein 1 (Dmap1), a component of the NuA4 histone acetyltransferase complex, plays a role in DNA repair and the maintenance of genome integrity58, and Dmap1 loss results in DNA damage and causes growth arrest due to the activation of cell cycle checkpoints via p53 in mouse embryonic fibroblasts58. Meis1, which is a member of the 3-amino-acid loop extension homeodomain-containing family, acts as a vital regulator in the development of the cardiovascular and haematopoietic system59. Recent studies have indicated that Meis1 controls ROS production via Hif-1α and Hif-2α59 and increases oxidative stress, and apoptosis is caused by Meis1 loss32. Aryl hydrocarbon receptor nuclear translocator (Arnt), a member of the basic helix-loop-helix Per-ARNT-Sim family, binds to hypoxia response elements (HREs) and HIF1/2α for xenobiotic and hypoxic responses60. Arnt has been shown to demonstrate an antioxidant effect by reducing ROS levels, and the deletion of Arnt in the hearts of adult mice resulted in cardiomyopathy33. As a member of the HOXD gene family, HOXD13 plays a critical role in tumour development and progression in cancers such as breast cancer and melanoma61, and a mutation in HOXD13 was shown to lead to synpolydactyly62.Apart from Apex1 and Pbx3, five other TFs, alpha-globin transcription factor CP2 (Tfcp2), homeobox protein Hox-D13 (Hoxd13), DNA methyltransferase 1-associated protein 1 (Dmap1), aryl hydrocarbon receptor nuclear translocator (Arnt), and homeobox protein Meis1 (Meis1) were also identified as important TFs in the YXS-mediated protection against H2O2-induced damage in cardiomyocytes. The high-throughput and deep coverage characteristics of this integrated strategy allows it reveal the fundamental alterations occurring and decrease the background interference observed in these types of analyses. YXS initiated biological process such as anti-apoptosis and DNA repair to protect cardiomyocytes against H2O2-induced damage. By using this integrated strategy, DNA-(apurinic or apyrimidinic site) lyase (Apex1), pre B-cell leukemia transcription factor 3 (Pbx3), and five other TFs were identified as important TFs with their functions involved in anti-oxidation, anti-apoptosis and DNA repair. This study offers a new understanding of the mechanism of YXS-mediated protection against oxidative stress in cardiomyocytes and reveals novel targets for related diseases.In this study, an integrated strategy which integrated RNA-seq-based transcriptomics techniques and a newly developed concatenated tandem array of consensus TF response elements (catTFREs)-based proteomics approach and then combined with a network pharmacology analysis, and this integrated strategy was used to investigate critical TFs in the protection of YXS against HSupplementary materialsSupplementary TableS1Supplementary TableS2


Endothelial cells (ECs) are critical determinants of vascular homeostasis and inflammation, but transcriptional mechanisms specifying their identities and functional states remain poorly understood. Here, we report a genome-wide assessment of regulatory landscapes of primary human aortic endothelial cells (HAECs) under basal and activated conditions, enabling inference of transcription factor networks that direct homeostatic and pro-inflammatory programs. We demonstrate that 43% of detected enhancers are EC-specific and contain SNPs associated to cardiovascular disease and hypertension. We provide evidence that AP1, ETS, and GATA transcription factors play key roles in HAEC transcription by co-binding enhancers associated with EC-specific genes. We further demonstrate that exposure of HAECs to oxidized phospholipids or pro-inflammatory cytokines results in signal-specific alterations in enhancer landscapes and associate with coordinated binding of CEBPD, IRF1, and NFκB. Collectively, these findings identify cis-regulatory elements and corresponding trans-acting factors that contribute to EC identity and their specific responses to pro-inflammatory stimuli.DOI:http://dx.doi.org/10.7554/eLife.22536.001 Atherosclerosis is an inflammatory disease of large arteries mediated by the accumulation of plaque within the vessel wall. Through sequelae such as heart attack, stroke, and peripheral vascular disease, it is responsible for an immense burden of morbidity and mortality. The pathogenesis of atherosclerosis involves several cell types and environmental risk factors . One of enhancers, yet a given cell type only utilizes on the order of tens of thousands of active enhancers (Genome-wide association studies have identified more than 50 loci that predispose humans to cardiovascular disease (CVD) , of whicnhancers . This manhancers .An important insight into enhancer biology is the observation that unique combinations of a few transcription factors (TFs) together activate cell-type-specific enhancers. Enhancer priming by TFs is both collaborative, (such that one TF will not bind its DNA motif if the motif for a collaborating TF is mutated ), and hiIn the current study, we take a genome-wide approach using DNA variation, epigenetic, and transcriptomic data to identify the major TF families that coordinate human aortic endothelial cell (HAEC) gene expression in homeostasis and upon exposure to prototypic inflammatory stimuli characteristic of atherosclerosis. Using a combination of experimental and computational approaches, we find that members of the ETS and AP1 TF families bind EC enhancers and that removing ETS member ERG elicits an inflammatory profile. We demonstrate that many enhancers identified in ECs are cell type-specific and several enhancers overlap with SNPs that have been associated to coronary artery disease (CAD) and hypertension. In addition, we demonstrate that TFs NRF2, NFκB, CEBD, and IRF1 are signal-dependent TFs that mediate the EC response to inflammatory stimuli.A total of 16,929 high-confidence enhancer-like elements were mapped in HAECs  using chWe hypothesized that the major TFs that select and maintain enhancers in HAECs would be evident via enrichment of binding motifs in enhancer DNA sequences. Thus, we performed de novo motif enrichment analysis and discovered that AP1, ETS, SOX and GATA motifs were significantly enriched  in HAEC enhancers compared to random GC-matched genomic background sequence . Based oTens of genes encode proteins of the AP1, ETS, SOX and GATA TF families. Within each family different members share nearly identical DNA-binding domains and thus bind the same motif. In addition, AP1 protein members bind AP1 motifs as homo- and hetero-dimers. These sources of redundancy make it challenging to identify the functional family member(s) without additional information. To narrow the search in HAECs, we hypothesized that the operational TFs would be highly expressed and that their genetic loci would contain super-enhancers (SEs), or unusually dense clusters of highly decorated enhancers . CharactTo investigate which enhancer-like elements discovered in HAECs were specific to ECs, we analyzed public H3K27ac ChIP-seq datasets from ENCODE  and RoadTo investigate whether EC enhancers have utility to prioritize non-coding functional variants for the cardiovascular diseases CAD and hypertension, we overlapped physical coordinates of the 16,929 enhancers from We next questioned how AP1, ETS, SOX, and GATA TFs were expressed in artery ECs across the human population. We postulated that the most prominent actors would be highly expressed with modest variation between people. By leveraging global transcript levels collected across 97 genetically distinct HAECs from healthy human donors , we founTo gain insight into the behavior of the TF members with respect to each other, we measured co-variation in TF gene expression profiles across the human population. Co-variation, or co-expression, of TFs could result from one TF (in)directly regulating another, both (in)directly regulating each other, or from each being regulated by a common third mechanism. By clustering pair-wide correlation coefficients across all TFs of interest, we identified three main groups with similar co-expressed profiles: group 1 (in orange) with members FOSL1 and ETS1; group 2 (in green) with GATA2 and GATA6; and group 3 (in yellow) with the remaining factors . The degTo test whether the nominated TFs indeed bound HAEC enhancers, we performed the first chromatin immunoprecipitation sequencing (ChIP-seq) experiments for JUNB, JUN, and ERG in HAECs and analyzed GATA2 and ETS1One approach to study collaborative binding between TFs is to knock-down/out a TF of interest and observe a shift in binding or activity at the regulatory element. To avoid complications in interpretability caused by potential redundancy of TF members, we took an alternative approach. As applied in inbred mouse strains previously , we util-10) such that binding was predominant on the chromosome lacking AP1 motif mutations and diminished on chromosomes containing the mutation (-3). We would expect to observe the reciprocal relationship, in which AP1 motif mutations alter ERG binding, but the ERG ChIP-seq experiment in the sequenced HAEC donor yielded less than ten thousand peaks and more information is necessary for this analysis. Taken together, these data support a collaborative relationship between AP1 and ETS factors at endothelial enhancers.Results showed that JUN binding was significantly affected by mutations in the AP1 motif , epidermal growth factor-like protein 7 (EGFL7), von Willebrand Factor (VWF), endothelial nitric oxide synthase (NOS3), and TEK receptor tyrosine kinase , exhibited between three and seven ERG/JUN co-bound enhancers across their genetic loci . By cros-4 to 1e-17, To test the functional importance of ERG on target gene expression, we knocked-down ERG using siRNA in HAECs and measured gene expression changes with RNA-seq and RT-qPCR  and 2. EAmong the most up-regulated genes caused by ERG knockdown were cytokines interleukin one alpha , interleukin one beta , leukemia inhibitory factor , interleukin 6 , granulocyte colony stimulating factor , transforming growth factor beta 2  and other pro-inflammatory molecules including tissue factor   and 2. I-13), and the ‘unfolded protein response’ . Genes regulated by 4 hr exposures to TNFα and IL1β were highly enriched in the same pathways including, ‘TNF receptor signaling’ , ‘granulocyte adhesion and diapedesis’ , and ‘macrophage, fibroblast and EC roles in rheumatoid arthritis’ .To identify regulatory factors that instruct gene expression responses to inflammatory environments of atherosclerosis, we exposed HAECs to three pro-inflammatory treatments: (i) the oxidized products of 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine (oxPAPC) that are components of oxidized low-density lipoproteins (oxLDL) , (ii) tu-6), consistent with the model that the predominant AP1 and ETS endothelial factors collaborate with newly activated SDTFs to activate responsive enhancers and direct dynamic gene expression  play a critical role in the enhancer activation process and, in this study, were used in this study to identify SDTFs. We identified between 266 and 3199 de novo enhancers across treatments , Table 2pression . Enrichmpression . Likewispression .10.7554/To directly test the hypothesis that NRF2 and NFκB were in fact SDTFs responsible for inflammatory gene responses, we measured the NRF2 cistrome upon oxPAPC treatment and the NFκB cistrome (using ChIP-seq with κB-component p65) in TNFα and IL1β 4-hr-treated ECs. NRF2 and p65 binding were associated with increases in H3K27ac on adjacent nucleosomes consistent with a role for NRF2 and NFκB as activators of target gene expression  and 3. GFor NFκB, we identified tens of thousands of bound loci after TNFα and IL1β treatment . Upon cytokine treatment, 52–63% of the elements that gained p65 were pre-bound in untreated HAECs by ERG or JUN , consistIn addition, we analyzed allele-specific NFκB binding as a function of motif mutations in the κB motif itself as well as mutations in the AP1 and ETS motif. Interestingly, we observed that NFκB binding was diminished at loci where κB, ETS, or AP1 motifs were mutated . These dThe transcriptional signature resulting from ERG knockdown in aortic ECs  is evideTo examine the genome-wide relationship between ERG and NFκB occupancy upon inflammatory signaling, we compared binding profiles. Twenty-nine percent of ERG binding sites in untreated ECs gained p65 binding upon 4-hr treatment with TNFα, and conversely, 25% of TNFα-elicited p65 binding occurred at loci pre-bound by ERG . All co-The result that CEBP and IRF motifs were preferentially enriched in TNFα and IL1β-induced enhancers suggested that TFs in these families direct the EC response to cytokines . To idenNext, we measured binding of IRF1 and CEBPD genome-wide after cytokine treatment . For IRFNotably, ERG and NFκB bind to elements at the CEBPD locus and ERG knockdown induces CEBPD expression . These dLastly, we tested whether reducing CEBPD and IRF1 levels with siRNA would dampen the endothelial response to cytokines. As hypothesized, CEBPD knockdown to less than 20% control RNA levels resulted in dampened fold-change ratios for genes up-regulated by TNFα  with Lipofectamine 2000 (ThermoFisher Scientific). Transfections were performed in serum-free media for 4 hr, then cells were grown in full growth media for 48 hr. All siRNAs and qPCR primers used in this study are listed in HAECs were resuspended in RNA Lysis Buffer and RNA was extracted from cells using the Quick-RNA Micro Prep kit from ZymoResearch , including optional DNase I treatment. mRNA was selected through poly-A isolation using Oligo d(T)25 beads . Selected RNA was fragmented, followed by single strand cDNA synthesis using a SuperScript III First-Strand Synthesis System (ThermoFisher Scientific # 18080051), followed by second strand synthesis using DNA Polymerase I . dsDNA ends were repaired with T4 DNA Polymerase (Enzymatics #P7080L). Barcode adapters  were ligated onto the ends of sequences using T4 DNA Ligase (Enzymatics #L-6030-HC-L) and samples were treated with Uracil DNA Glycosylase (UDG) (Enzymatics #G5010L). Libraries were then amplified by PCR  and purified (Zymo #D5205) for high-throughput sequencing.ChIP-seq was performed as previously described . BrieflyATAC-seq was performed on 50,000 HAEC nuclei according to the original published protocol  with theLibraries were sequenced on an Illumina HiSeq 4000 according to manufacturer’s specifications at the University California San Diego and at the University of Chicago. Public data was downloaded from public repositories and processed exactly as new data in this study (see below). Reads from ChIP-seq and ATAC-seq were mapped to the hg19 build of the human genome with Bowtie2  and RNA-ATAC-seq and RNA-seq experiments that measured accessibility and expression in different treatment stimuli  were all conducted at least twice. ERG knockdown was performed in three different HAEC donors. CEBPD and IRF knockdowns were performed in one HAEC donor. The Benjamini-Hochberg false discovery rate (FDR) method was used to correct for all multiple testing in this study. No explicit power analysis was used to compute sample size. Instead, genome-wide features such as enhancer elements served as the replicates for motif analysis and duplicate ChIP-seq experiments confirmed that binding peaks were consistent. With the exception of CEBPD and JUNB that were performed one time, all ChIP-seq experiments were performed in biological duplicate, meaning separate cell expansion and collection.For quantification, RNA-seq was normalized using Reads Per Kilobase of transcript per Million mapped reads (RPKM) procedure in HOMER . RNA seqChIP-seq and ATAC peaks were identified using un-immunoprecipitated chromain, or ‘input’, as a negative control. Inputs from the corresponding crosslinking condition were used for each ChIP. No input was used to call ATAC peaks. Peaks were identified in HOMER with the findPeaks program according to the data type. Transcription factor peaks were called using the ‘findPeaks -style factor –size 200’ option and histone peaks called using the ‘findPeaks -style histone’ option. ATAC-seq peaks were called using findPeaks with ‘-L 8 F 8 -style histone -size 75 -minDist 75 -minTagThreshold 6’ options. Differential peaks between experiments were determined using the ‘getDifferentialPeaks program with default parameters’ .Peak merging was performed in HOMER using the ‘mergePeaks’ program. For enhancers defined in De novo enhancers were defined as loci that gained ATAC-seq and H3K27ac ChIP-seq in the same cell simulation. Individual gained peak sets was determined by ‘getDifferentialPeaks’, explained above, and significant sets were intersected using ‘mergePeaks’ where the ATAC-seq gained peaks were listed first to maintain centering on accessibility.Super-enhancers were defined in HOMER from H3K27ac ChIP-seq experiments and corresponding inputs using ‘findPeaks -style super -L 0’. This procedure follows the same logic as the original definition proposed by the Young laboratory . BrieflyMotif enrichment analysis was performed on peak sets using HOMER’s ‘findMotifsGenome.pl’ program. As a background control, this program selects a set of sequences from the same genome build that are matched in size and GC content to the peak set of interest. In Analysis of motif distances in For the HAEC line sequenced for analysis as in Allele-specific binding of JUN and NFκB/p65 was quantified using the WASP pipeline . To avoiAllele-specific motif mutations were identified with the same method as reported previously  with sliFor visualization, plots as in Heatmap-syle histograms of sequencing tags e.g. , were geCoronary artery disease, hypertension, and related traits were downloaded from the NHGRI-EBI Catalog of published genome-wide association studies . SNPs inWith the exception of data used to generate Data generated in this study is available under GEO accession GSE89970 and WGS via NCBI SRA Archive, BioProject PRJNA381088.The HAECs used in this study were primary isolates of ECs from aortic trimmings collected from trimmings of donor hearts transplanted through the UCLA heart transplant program as previously described . No tran In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Harry Dietz as the Senior Editor. The following individual involved in review of your submission has agreed to reveal her identity: Lynn Butler (Reviewer #2).Thank you for submitting your article "Transcriptional networks specifying homeostatic and inflammatory expression programs in human aortic endothelial cells" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:Hogan et al. performed an extensive analyses of transcriptional regulation in human aortic endothelial cells (HAECs). They authors provide a comprehensive map of the gene regulatory landscape of HAEC cells under basal (part1) and inflammatory conditions (part2). Using a combination of enhancer annotation, in-silico motif analysis and transcription factor ChIP the authors find that a Jun (an AP1 factor) and ERG (an ETS factor) cooperate to establish much of the cell enhancer landscape. In the second part, the authors study the transcriptional network in response to inflammatory stimulus.Essential revisions:1) It is unclear why the focus is only on JUNB. The reviewers felt there the authors should explain why JUND is not pursued further.2) Two reviewers, one of them from prior experience, are worried that some of the observed effects are due to the transfection itself, or other off-target effects. The authors should carefully establish this before they conclude that ERG, or any other siRNA knock-down is the cause of the (observed) inflammatory response. The reviewers strongly suggest a combination of appropriate controls and replication with different siRNAs to ensure that the result is not due to secondary effects not related to the result of the ERG and all other knock-down experiments.3) The collaborative nature of JUNB and ERG function would be strengthen by showing the effect of loss of function of JUNB.eLife. Your revised article has been favorably evaluated by Harry Dietz (Senior editor) and a Reviewing editor.Thank you for resubmitting your work entitled "Transcriptional networks specifying homeostatic and inflammatory expression programs in human aortic endothelial cells" for further consideration at The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:There is one remaining point you may want to discuss. While the AP1 factors are highly expressed, the ETS factors are not. eLife. Your revised article has been favorably evaluated by Harry Dietz (Senior editor), a Reviewing editor, and two reviewers.Thank you for resubmitting your work entitled "Transcriptional networks specifying homeostatic and inflammatory expression programs in human aortic endothelial cells" for further consideration at The manuscript has been improved but there is one remaining issue that need to be addressed before acceptance, as outlined below:While the methods for quantification of RNA-Seq data have been clearly improved since the original submission, there was consensus that these methods are not adequately described in the revised manuscript. Please expand and refine this description in the Materials and methods section. Essential revisions:1) It is unclear why the focus is only on JUNB. The reviewers felt there the authors should explain why JUND is not pursued further.We agree that JUND is likely to be one of the important AP-1 family members involved in regulating endothelial transcription. This is evident from motif analysis of the 17 thousand HAEC enhancers that revealed a prominent role in AP1 transcription factors , high leResults section: “Tens of genes encode proteins of the AP1, ETS, SOX and GATA TF families. Within each family different members share nearly identical DNA binding domains and thus bind the same motif. In addition, AP1 protein members bind AP1 motifs as homo- and hetero-dimers. These sources of redundancy make it challenging to identify the functional family member(s) without additional information.”Results section: “AP1 family members JUND, JUN, and JUNB were also in the top 4%. RNA-seq from other HAEC donors and replicate samples confirmed these findings . Next, wResults section: “The JUND cistrome would also be informative in these studies; however, we proceeded with JUN and JUNB because the heterodimeric binding of AP1 factors makes it likely that JUN and JUNB profiles encompass a major portion of the overall AP1 landscape. Consistent with this, the JUN and JUNB cistromes are highly concordant .”2) Two reviewers, one of them from prior experience, are worried that some of the observed effects are due to the transfection itself, or other off-target effects. The authors should carefully establish this before they conclude that ERG, or any other siRNA knock-down is the cause of the (observed) inflammatory response. The reviewers strongly suggest a combination of appropriate controls and replication with different siRNAs to ensure that the result is not due to secondary effects not related to the result of the ERG and all other knock-down experiments.This point is well taken. Additional experiments were performed refer to  by each Results section: “To ensure that the inflammatory gene profile elicited by ERG knock-down was not a consequence of transfection itself or off-target effects, the profile resulting from six individual siERG oligos was measured along with two non-targeting scrambled siRNA controls and non-transfection controls . These d3) The collaborative nature of JUNB and ERG function would be strengthen by showing the effect of loss of function of JUNB.We agree that an implication of collaborative TF binding is that loss-of-function of a participating TF would decrease the ability of the other factor to bind target elements. The expectation to observe this effect genome-wide is complicated, however, by other TFs in the same families that can bind the same DNA-binding motif and provide a surrogate collaborative role. Considering that we observe multiple AP1 and ETS members with high expression in HAECs, we decided to undertake an alternative approach to test for collaborative interactions.This approach stems from our previous work in genetically diverse inbred mouse strains where millions of naturally occurring SNPs between strains were considered nature’s mutagenesis experiment . The current study is the first to implement this approach in human cells. The approach is as follows: SNPs are identified across the genome within a single individual. We achieved this using whole-genome sequencing (40X average depth) in one aortic endothelial cell donor. Next, we identified loci where the alleles of the SNPs mutated a canonical DNA binding motif for a TF of interest  only on one homologous chromosome. These are the potential functional SNPs that are used to test for effects on TF binding. Next, we developed an analytical pipeline using a combination of public tools  to quantify allele-specific TF binding for JUN and NFkB/p65 that takes into account personal genome sequence and avoids caveats of mapping bias .Results show that allele-specific mutations in AP-1 motifs genome-wide (n = 237) are coincident with reduced JUN binding in the expected allele-specific manner  = 5e-10.Results:“Allele-specific binding to chromosomes lacking motif mutations supports collaborative binding between AP1 and ETS factors […] Taken together, these data support a collaborative relationship between AP1 and ETS factors at endothelial enhancers.”Results: “In addition, we analyzed allele-specific NFkB binding as a function of motif mutations in the kB motif itself as well as mutations in the AP1 and ETS motif. […]Furthermore, these data demonstrate that allele-specific binding in heterogeneous human cells is a useful means to reveal collaborative interactions between transcription factors.”Materials and methods:“Whole-Genome Sequencing (WGS), Motif Mutation Analysis and Allele-Specific Factor Binding For the HAEC line sequenced for analysis as in The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:There is one remaining point you may want to discuss. While the AP1 factors are highly expressed, the ETS factors are not. When quantifying gene expression from RNA-seq data as all tags between the transcription start site to the termination site, the expression levels between ETS and AP-1 factors are different. This is largely because ETS factors tend to have multiple large introns . This revision is reflected in While our study highlights a collaborative role for ERG and JUN specifically, we acknowledge that this combination is not likely the sole modulating combination. In fact, other collaborative interactions involving other AP-1 and ETS factors almost certainly regulate EC gene expression, and the cistromes of these factors and their functional effects remain a target of future investigation.We have now revised our manuscript to reflect these changes in the following ways:Discussion:“While we focus on ERG and JUN in particular, other combinatorial interactions between other ETS and AP-1 members almost certainly play prominent roles in endothelial regulation.”Clearly, at their mRNA levels ERG and JUN are at very different, is there evidence that ERG is a more stable protein? A related point: In We believe this comment refers to loci shown for TEK and CDH5. PECAM1, what was more significantly affected by siERG, is now included  that disThe manuscript has been improved but there is one remaining issue that need to be addressed before acceptance, as outlined below:While the methods for quantification of RNA-Seq data have been clearly improved since the original submission, there was consensus that these methods are not adequately described in the revised manuscript. Please expand and refine this description in the methods section.We now present a more detailed description of the RNA-seq analysis that reflects the precise options used to quantify gene expression and determine differential expression. This change can be found in subsection “RNA-seq Analysis” as follows:“RNA-seq Analysis For quantification, RNA-seq was normalized using Reads Per Kilobase of transcript per Million mapped reads (RPKM) procedure in HOMER[…] Pathway enrichment analysis was performed using Ingenuity Pathway Analysis software (Qiagen).”


ESC lines with chimeric BACs, in which two TERT promoters were swapped, were also generated. Using these chromatinized BACs, we showed that hTERT silencing during differentiation to embryoid bodies (EBs) and to fibroblast-like cells was driven by the human-specific genomic context and accompanied by increases of repressive epigenetic marks, H3K9me3 and H3K27me3, near its promoter. Conversely, the mouse genomic context did not repress TERT transcription until late during differentiation. The hTERT promoter was more active than its mouse counterpart when compared in the same genomic contexts. Mutations of E-box and E2F consensus sites at the promoter had little effect on hTERT transcription in ESCs. However, the mutant promoters were rapidly silenced upon EB differentiation, indicating that transcription factors (TFs) bound to these sites were critical in maintaining hTERT transcription during differentiation. Together, our study revealed a dynamic hTERT regulation by chromatin environment and promoter-bound TFs during ESC differentiation.Differential regulation of telomerase reverse transcriptase (TERT) genes contribute to distinct aging and tumorigenic processes in humans and mice. To study TERT regulation, we generated mouse embryonic stem cell (ESC) lines containing single-copy bacterial artificial chromosome (BAC) reporters, covering  Telomere DNA sequences are replenished by telomerase2, a reverse transcriptase complex containing a catalytic subunit (TERT), an RNA template (TERC), and accessory proteins4. Without telomerase, telomeres shorten upon successive cell divisions, leading to cell death or senescence6. Mutations in human telomerase genes  lead to dyskeratosis congenita, a multi-system disorder with a broad spectrum of clinical manifestations7. Moreover, ectopic hTERT expression in many cell types resulted in telomere elongation and cellular immortalization, indicating that hTERT is a limiting component of telomerase in human cells10.Telomeres are protective caps of chromosomal ends that are critical for genomic stability13. In humans, while alternative mRNA splicing and post-translational modifications play roles in regulating hTERT expression12, the dominant event of hTERT regulation is its repression during development and differentiation14. Indeed, the level of hTERT mRNA is very low in most somatic tissues, with the exception of testis, ovary, thymus, and skin15. On the other hand, the mTERT gene is widely expressed in the majority of adult mouse tissues16. This broad expression is accompanied by very long telomeres in mouse cells and tissues17. Consequently, proliferative senescence of human cells, but not mouse cells, is telomere-dependent.Telomerase is highly expressed during early embryonic development, as well as in pluripotent stem cells, such as embryonic stem cells and germline cells18. To study its regulation in a relevant genomic context, we initially constructed BAC reporter H(wt), which contained a 160-kb human genomic sequence encompassing the entire hTERT locus, and its upstream and downstream neighboring loci, CRR9 , and Xtrp2 (or SLC6A18) loci. Previously, we showed that the hTERT promoter in randomly integrated H(wt) was highly active in mouse embryonic stem cells, and was efficiently repressed upon in vitro differentiation19. This was in contrast with the endogenous mTERT mRNA, which was only moderately down regulated during the same differentiation process and widely expressed in mouse tissues, indicating the significant differences in the regulation of TERT genes in human and mice16.hTERT transcription is a primary step of telomerase regulation in many cell typeshTERT locus was determined by the distal genomic sequences, not the promoter per se. Mutations of two E-boxes and three E2F consensus sites at the proximal hTERT promoter region did not affect hTERT transcription in ESCs, but led to a stronger repression of the promoter during EB differentiation, indicating their roles in maintaining telomerase expression during differentiation. Thus, we demonstrated that the RMBT system in ESCs should facilitate the study of species-specific developmental regulation of human and mouse TERT genes.To study the species-specific TERT regulation during differentiation, we developed a new recombinase-mediated BAC targeting (RMBT) protocol to integrate H(wt) and M(wt), a BAC reporter containing a mouse genomic region equivalent to that in H(wt), into a chromosomal acceptor site in mouse ESCs. We showed that the hTERT promoter in H(wt), but not the mTERT promoter in M(wt), was progressively down-regulated during EB differentiation and further silenced upon differentiation into osteogenic and fibroblast-like cells. Furthermore, by using chimera BACs, in which the TERT promoters were swapped between H(wt) and M(wt), we showed that the repression of 20. To integrate BAC reporters in ESCs, we constructed a lentiviral vector pLentiPreT2 because the previously reported retroviral acceptor was silenced in pluripotent stem cells. The resulting proviral acceptor locus contained a tkNeo expression cassette, encoding a fusion protein of the HSV thymidine kinase and neomycin resistance genes  and M(wt), which contained genomic sequences encompassing the consecutive CRR9, TERT, and Xtrp2 loci of the 160-bp human and 135-bp mouse genomic regions, respectively21, into T2-5 cells. Circular BAC DNAs and pCBM were co-transfected into T2-5 cells. Cre-mediated recombination between lox511/loxP sites on BACs and those of proviral LentiPreT2 resulted in the replacement of the tkNeo cassette by the entire BAC inserts. Individual clones were isolated following consecutive selection using puromycin and ganciclovir (GCV). Southern blot analyses were performed to determine the integrity of integrated BACs. For example, correct integration of H(wt) resulted in the loss of 3.9 kb DraI band and the gain of a 1.4-kb and a 2.3-kb band at the lox511 and loxP site, respectively  and Renilla (Rluc) luciferase probes, respectively. In addition to H(wt) and M(wt), we also generated ESC clones containing H(mPro) and M(hPro). H(mPro) and M(hPro) were resulted from swapping of the hTERT and mTERT promoters  between H(wt) and M(wt)21. Thus, all these single-copy BAC reporters were integrated at the same chromosomal site and analyzed in the same chromatin environment.To directly compare ely Fig. . The intTo determine the activities of TERT promoters in undifferentiated mouse ESCs, two independent ESC clones containing each BAC construct were analyzed Fig. . Compari15. As an attempt to understand how hTERT and mTERT genes were regulated during development, ESCs were induced to differentiate into EBs for up to two weeks, and luciferase activities were determined during differentiation. As shown in Fig. Telomerase is expressed at very low levels in most human adult somatic tissues, but is readily detectable in most mouse tissues13. Thus, EBs were induced to differentiate into the osteogenic lineage, and the resulting cells were subsequently cultured in 10% fetal bovine serum and became morphologically fibroblast-like cells  and quantitative PCR analysis  and H(mPro) contained little H3K9me3 and H3K27me3. These marks dramatically increased in differentiated cells. However, no H3K9me3 and H3K27me3 were detected at M(wt) and M(hPro) in either ESCs or their differentiated derivatives. These results suggested that the human genomic context conferred a repressive chromatin environment and led to a stronger repression of the 21. To verify that HDACs were also involved in hTERT repression during ESC differentiation, differentiated mouse cells containing H(wt) were treated with chemical inhibitors, trichostatin A , MS-275 (a specific inhibitor of class I HDACs), and MC-1568 (an inhibitor of class II HDACs). As shown in Fig. Recently, we reported that hTERT repression in immortal human fibroblasts involved multiple HDAC1-containing corepressor complexes (CRCs)22. As shown in Fig. 23. The binding of USF1, also an E-box binding TF, and Sp1 was relatively weak at the TERT promoters. Finally, the presence of PolII at the TERT promoters correlated with their activities in ESCs and this association decreased in all BAC reporters in differentiated cells. Overall, the association of TFs was consistent with the regulation of TERT promoters in both ESCs and differentiated cells.Next, we assessed the binding of several TFs to the TERT promoters. Proto-oncogene product c-Myc and its heterodimer partner Max were known to bind to the E-boxes at the hTERT promoter and activate hTERT transcription in cancer cells26. However, most previous studies were done in the contexts of transiently transfected small reporter plasmids. To determine how these TFs regulated hTERT transcription in ESCs and during differentiation, point mutations were introduced to several TF sites in the BAC reporter H(wt). These sites were two E-boxes, three E2F consensus sites, and five GC-boxes at the hTERT promoter  into an acceptor site and allows the studies of distal elements in correct genomic contexts. Since BACs are not integrated at the endogenous locus, the mTERT gene in ESCs remains intact and its regulation is unlikely affected by manipulation of the reporters. This technique should also be applicable for studying genes essential for stem cell proliferation and differentiation. Second, because human and mouse genomic sequences bear little resemblance outside of their coding regions, the endogenous mTERT locus does not interfere with the epigenetic studies of the human sequences, such as ChIP-qPCR. Third, BAC recombineering allows more precise and complex manipulation of BAC DNA sequences than the genomic editing techniques using the CRISPR-Cas930. Hence, the RMBT method combined with BAC recombineering will still provide a useful tool for analysis of genomic elements in the foreseeable future. Fourth, the use of sensitive bioluminescent reporters allows the detection of relatively small changes in transcriptional regulation. Finally, the RMBT technique is used to analyze human genes in mouse ESCs which are easier to culture and manipulate than human pluripotent stem cells31.Previously, we used the RMBT technique to study hTERT regulation in immortal human fibroblastshTERT and mTERT genes were highly expressed and not repressed in undifferentiated ESCs27. We also showed that the repressive chromatin of the hTERT gene was set up progressively starting early EB differentiation. A significant decrease of hTERT transcription was readily detected within 3 days after the initiation of differentiation. The repression was accompanied by marked increases of both H3K9me3 and H3K27me3 at the hTERT promoter. In contrast, the mTERT promoter in M(wt) remained active throughout EB differentiation, and its activity reduced moderately only following osteogenic differentiation. No detectable H3K9me3 and H3K27me3 marks were found at the mTERT promoter in ESCs or differentiated cells. Importantly, the human-specific repression during differentiation was determined by distal genomic sequences, not the promoters, as indicated by data from chimera BACs H(mPro) and M(hPro). This result was also consistent with our previous report that hTERT repression in human fibroblasts required the human genomic context using the same set of BAC reporters21. Determination of sequence requirement for the hTERT repression should help to identify cis elements required for repression. These distal elements likely recruit class I HDACs CRCs to the promoter and mediated the repression.In this first study using RMBT in ESCs, our results corroborated previous reports that the hTERT, but not mTERT, gene also contains five minisatellites , in introns 2, 6, and 12. It is conceivable that these repetitive elements help to create a repressive chromatin environment at the hTERT locus. Based on published studies, it is tempting to speculate that two mechanisms contribute to transcriptional repression. First, these elements may function as silencers by binding to repressors. For example, TEs have been shown to recruit polycomb group (PcG) repressor complexes32 and KAP1/NuRD repressor complexes via KRAB family zinc finger proteins (KRAB-ZNFs)33, leading to the accumulation of H3K27me3 and H3K9me3, respectively. Second, although contradictory, transcription may occur in non-coding regions containing repetitive sequences34. The resulting transcripts may be aberrantly processed and recognized through base-pairing by small interfering RNAs, which recruit complexes containing Argonaute proteins, leading to histone modifications and the formation of heterochromatin36. The RNAi-mediated transcriptional gene silencing has been well studied in model organisms, but its mechanisms in mammals are only beginning to be understood38.Comparing human and mouse sequences, one notable difference is that human 5′ intergenic region  is much larger than its mouse counterpart (7-kb) Fig. . This di39. How this expression is maintained in these cells remains to be elucidated. Our data showed that elimination of E-boxes and E2F consensus sites, binding sites for two critical TF families, had little effect on hTERT transcription in ESCs, indicating that these TFs were not required for hTERT promoter activity in these cells. It was possible that redundant TFs activated the hTERT promoter in ESCs. Alternatively, the chromatin of hTERT locus might be wide-open in ESCs40 and transcriptional machineries could be easily loaded onto the promoter without the facilitation by TFs. Interestingly, the mutant BAC reporters lacking either E-boxes or E2F sites underwent rapid down-regulation during EB differentiation, more quickly than H(wt), suggesting that TF bound to these sites played important roles in maintaining hTERT transcription in differentiating cells. Upon differentiation, the chromatin around the hTERT promoter began to condense and it was critical for TFs to bind to the promoter and maintain its expression during differentiation. Based on this result, it would be interesting to determine whether these TFs were required for hTERT transcription in adult stem cells and progenitor cells.The highest hTERT transcription is found in pluripotent stem cellshTERT gene is very complex. It was recently reported that the hTERT gene might also be regulated by telomeric position effect via telomere looping at the end of chromosome 5p43. The 160-kb human sequence in H(wt) did not contain any interstitial telomeric sequence of (TTAGGG)2 or longer and the reporter nonetheless recapitulated endogenous hTERT regulation in an integration site-independent manner in both ESCs cells and transgenic mice20. These results suggested that H(wt) contained sufficient regulatory sequence for hTERT regulation. In addition to transcriptional regulation, hTERT mRNA was also subjected to alternative splicing45. In H(wt), a Renilla luciferase cassette was inserted at the ATG codon in the first hTERT exon, and the reporter was unlikely affected by splicing. Despite of these potential shortcomings, H(wt) recapitulated endogenous hTERT regulation during mouse development and ESC differentiation15 and should provide valuable insights into the mechanisms of its regulation.The regulation of hTERT gene in mouse ESCs. Whereas epigenetic mechanisms have been linked to gene silencing, relatively little is known about how epigenetic memories are directed to target DNA sequences during development and in response to extracellular environment. The identification of cis elements is important for elucidating the mechanisms of not only hTERT repression in most somatic cells, but also its tissue-specific expression in thymus, skin, testis, and ovary, where telomerase is critical for T cell functions, skin regeneration, and germ cell proliferation and maintenance. Finally, this technical platform should also be applicable to the investigation of other genes and genomic regions.In summary, we have developed a system to study the transcriptional regulation of 21. The two E-box sites , three E2F sites , and five GC-boxes  at hTERT core promoter in H(wt) were mutated via BAC recombineering28, resulting in H(EboxDM), H(E2F*3), and H(GC*5), respectively. H(EboxDM) and H(GC*5) were reported previously22. The E2F consensus sites in H(E2F*3) were mutated as (−174)CGCGC→CATGC, (−98)CGCGC→CATGC, and (−10)GCGCG→GCATA. All mutations were verified by sequencing.BAC reporters H(wt), M(wt), H(mPro), and M(hPro) were described previously46 was cultured as previous described19. TC1 cells were infected with a low titer lentivirus LentiPreT2 and neomycin-resistant clones were isolated. T2–5, a clone with a single-copy provirus, was cotransfected with BAC reporters and a Cre-expressing plasmid pCBM20. Following consecutive selections with puromycin and GCV, clones with both Fluc and Rluc activities were isolated and analyzed. Southern analysis of RMBT clones was performed20 using probes listed in Table Mouse ESC line TC113. On days 0, 3, 6, 10 and 14, individual EBs were harvested for luciferase assay. Differentiated osteogenic cells were analyzed by Alizarin red staining47. To promote fibroblast-like differentiation, passaged cells were treated with 0.15 µM retinoic acid  for 2 days. Fibroblast-like cells were characterized by Immunofluorescence staining using vimentin antibody .Differentiation of ESCs into EBs and osteogenic cultures were described previously48, Rluc activities from the TERT promoters were normalized to Fluc activity from the CRR9 promoters. Moreover, all data were verified by normalizing Rluc activity to the number of cells, as determined by thiazolyl blue tetrazolium bromide (MTT) assays (data not shown). To induce hTERT transcription, differentiated cells were treated with HDAC inhibitors TSA, MS-275, or MC-1568 for 24 h and luciferase activities were determined. All reporter assays were performed in triplicate and repeated at least once.Luciferase activities were measured using Dual-Luciferase® Reporter Assay System . As both hCRR9 and mCRR9 genes were constitutively expressed and their expression did not change during differentiation22. The precipitated chromatin DNA fragments were analyzed by quantitative PCR. Antibodies are listed in Tables ChIP assay was done as in previous publicationsThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable requests.Supplementary Information


Genes encoding subunits of SWI/SNF (BAF) chromatin remodelling complexes are collectively altered in over 20% of human malignancies, but the mechanisms by which these complexes alter chromatin to modulate transcription and cell fate are poorly understood. Utilizing mouse embryonic fibroblast and cancer cell line models, here we show via ChIP-seq and biochemical assays that SWI/SNF complexes are preferentially targeted to distal lineage specific enhancers and interact with p300 to modulate histone H3 lysine 27 acetylation. We identify a greater requirement for SWI/SNF at typical enhancers than at most super-enhancers and at enhancers in untranscribed regions than in transcribed regions. Our data further demonstrate that SWI/SNF-dependent distal enhancers are essential for controlling expression of genes linked to developmental processes. Our findings thus establish SWI/SNF complexes as regulators of the enhancer landscape and provide insight into the roles of SWI/SNF in cellular fate control. SWI/SNF chromatin remodelling complex is a major regulator of chromatin structure and of transcription. Here, using mouse embryonic fibroblasts and human rhabdoid tumour cells, the authors provide evidence that SWI/SNF functions as a regulator of enhancers. ARID1A, ARID1B, ARID2, PBRM1, SMARCA4 and SMARCB1) collectively occurring in ∼20% of all tumours whose genomes have been characterized to date, SWI/SNF complexes are the most commonly mutated chromatin modulators in human cancerSWI/SNF (BAF) chromatin remodellers are large ∼2 MDa), evolutionarily conserved complexes, each composed of approximately 15 protein subunits MDa, evo456Although SWI/SNF complexes have been found to serve key roles in transcriptional regulation1213141516Enhancers are DNA sequences consisting of binding sites of transcription factors (TFs) that facilitate the activation of target genes. In addition to various cell type-specific TFs such as master regulators, enhancers are also bound by general factors such as the mediator complex, cohesion complex and various coactivators192324cis-regulatory elements that are affected by the loss of different SWI/SNF subunits, we observe that enhancers have a greater requirement for the SWI/SNF complex than promoters. Surprisingly, we find that typical enhancers are more strongly affected than super-enhancers. Mechanistically, we show that the regulation of H3K27ac at enhancers by SWI/SNF happens via its interaction with the p300/CBP histone acetyltranfrase. Furthermore, we show that enhancers regulated by the SWI/SNF complex are essential in controlling genes important for lineage specification.In the work presented here, we set out to build on our previous work and evaluate the role of SWI/SNF in control of methylation of H3K27 by EZH2. This leads to our observation that the SWI/SNF complex plays a major role in regulating H3K27 acetylation (H3K27ac) in both loss-of-function mouse embryonic fibroblast (MEF) and gain-of-function rhabdoid tumour (RT) systems. By characterizing the Smarca4, Smarcb1 or Arid1a SWI/SNF subunit genes could be conditionally deleted, as well as Ezh2 conditional knockout MEFs to gauge PRC2 function (Methods). Although we noted a subtle increase in global H3K27me3 levels upon SWI/SNF subunit inactivation in western blots, surprisingly a much greater effect of decreased global levels of H3K27ac was observed (We utilized a mouse embryonic fibroblast (MEF) system in which the observed . In contobserved .Smarca4 or Smarcb1 conditional knockout MEFs. We identified regions enriched for H3K27ac and classified them based on their proximity to active transcription start sites (TSS) marked by H3K4me3. A total of 11,531 sites proximal to active TSSs and 21,772 sites distal to active TSSs were identified as putative promoters and enhancers, respectively. We validated that the enhancer set defined in this work is consistent with enhancers identified in MEFs by the Mouse Encyclopedia of DNA Elements (ENCODE) consortiumSmarcb1 or Smarca4, we observed little change in H3K27ac levels at promoters, but a marked reduction at many enhancers  for H3K27ac in wild-type MEFs and in nhancers . This renhancers . Furthernhancers . Howeversubunit. .Given that the effects of SWI/SNF subunit loss appeared to be localized specifically at enhancers, we next evaluated whether deletion of SWI/SNF subunits also affected H3K4me1, a histone modification associated with both active and poised enhancers. We observed that H3K4me1 levels at enhancers also showed a decrease at enhancers, but to a lesser extent than the decrease in H3K27ac levels , This fiSmarcb1-deficient cells. Because the genome-wide binding profiles of these two subunits were very similar , are more sensitive to BRD4 inhibition than typical enhancersSmarcb1 deletion. Surprisingly, we found that the opposite was true: super-enhancers were more refractory to Smarcb1 deletion, both in terms of SWI/SNF binding and H3K27ac levels . In enhancers with H3K27ac loss, the most highly overrepresented motifs corresponded to the recognition sequence for the oncogenic heterodimer activator protein-1 (AP-1) TFs  TFs . The samRT cells . The samRT cells . This fi in MEFs . On the cb1 loss .Smarca4 or Smarcb1 deletion, we performed RNA-seq analysis in wild-type MEFs and in MEFs lacking Smarca4 or Smarcb1. We observed a significant correlation between the loss of H3K27ac at enhancers and reduced expression of the nearest gene , animal welfare insurance number A3023-01, using DFCI protocol 12-017. The Smarcb1loxP-flanked allele and hemizygous/heterozygous for the cre transgene, a homozygous loxP-flanked mouse of the target subunit was mated to a cre transgenic mouse. This yields ∼50% of the offspring as heterozygous for the loxP allele and hemizygous/heterozygous for the cre transgene. Then, these mice were mated back to the homozygous loxP-flanked mice. Approximately 25% of the progeny from this mating are homozygous for the loxP-flanked allele and hemizygous/heterozygous for the cre transgene. We checked the genotype for each target subunit gene as well as Cre by PCR.To generate mice that are heterozygous for a fl/fl or Smarca4fl/fl or Arid1afl/fl or Ezh2fl/fl and hemizygous/heterozygous for the cre transgene. The cells were transduced with pBabe-Cre-puro retrovirus and selected in puromycin (4 μg ml−1) for 72 h post infection. G401 cell line was purchased from American Type Culture Collection (ATCC) and BT16 cell line was maintained in the lab. Rhabdoid cell lines were culture in DMEM with 10% FBS at 37 °C with 5% CO2. SMARCB1 doxycycline inducible cell lines were first transduced with lentiviral pInducer21-SMARCB1 plasmid. After 72 h post to transduction, cells were sorted by GFP expression and maintained in Tet-System Approved FBS (Clonetech). SMARCB1 was re-expressed with doxycycline (1 μg ml−1) for indicated time.Primary MEFs were prepared from E13.5 embryos of B6/129 strain wild-type mice or mice that were homozygous for Smarcb12, 0.34 M sucrose, 10% glycerol, 1 mM dithiothritol and protease inhibitor cocktail) containing 0.2% Triton X-100. Nuclei were pelleted by centrifugation at 1,000g, resuspended in buffer A without Triton X-100. Next, nuclei were collected and incubated in Buffer B  for 30 min and centrifuged at 2,000g to remove nuclear debris. After washing once with Buffer B, the samples were resuspended in SDS sample buffer and chromatin associated proteins were analysed by western Blot analysis.72 h post transduction, MEFs and G401 cells were harvested and lysed with buffer A  were extracted with Trizol reagent (Invitrogen) and and further purified using RNeasy MinElute Cleanup Kit (Qiagen). Two microgram of total RNA was used to make the RNA-Seq library using TruSeq Total RNA Sample Prep Kit (Illumina) and sequenced with the Hi-Seq Illumina genome analyser.7 MEFs per experiment. Briefly, cells were crosslinked with 1% formaldehyde for 10 min at room temperature and the reaction was quenched by glycine at a final concentration of 0.125 M. Chromatin was digested with MNase to an average size of 1–2 kb. A total of 5 ug of antibody against H3K27ac , H3K4me1 , H3K4me3  or PolII  was added to the digested chromatin  and incubated overnight at 4 °C.ChIP assays for histone modifications and PolII were performed from 10For the ChIP-seq of SWI/SNF complex subunits, the protocol was slightly modified. In particular, dual crosslinking and sonication were utilized. Cells were first crosslinked in 2 mM disuccinimidyl glutarate  for 30 min then in 1% formaldehyde for 10 min, quenched with glycine for 5 min. Cells were washed with PBS three times then used to generate nuclear extract. Chromatin was fragmented using sonication based the adaptive focused acoustics technology developed by Covaris. Solubilized chromatin was immunoprecipitated with antibodies against SMARCA4/BRG1 , SMARCC1/BAF155 .For both, protein G Dynal magnetic beads were added to the ChIP reactions and incubated for 4–6 h at 4 °C. Magnetic beads were washed and chromatin was eluted. After crosslinking reversal, RNase A, and proteinase K treatment, ChIP DNA was extracted with the Min-Elute PCR purification kit (Qiagen). ChIP DNA was quantified with Quant-it PicoGreen dsDNA Assay Kit (Life Technologies). 10 ng of ChIP DNA per sample was used to prepare sequencing libraries, and ChIP DNA and input controls were sequenced with the Hi-Seq Illumina genome analyser.Cre-retrovirus induced MEFs and doxycycline treated rhabdoid cells were washed twice with 1 × PBS and whole cell lysates were prepared using lysis buffer . The cell lysates were mixed with Dynabeads conjugated with anti-SMARCC1 , anti-SMARCB1 , anti-SMARCA4  antibodies and rotated at 4 °C overnight before removal of the supernatant. The resulting samples were suspended SDS gel loading buffer and analysed by western blot analysis using anti-SMARCC1 , anti-SMARCB1 , anti-SMARCA4 , anti-EZH2 , anti-CBP  and anti-P300  antibodies. The raw blot images are shown in Unmodified full-length recombinant histone H3 was mixed with Acetyl-CoA (Active Motif) in 1 × Assay Buffer in a final volume of 50 uL and incubated at 30 °C for 1 h. Recombinant p300 catalytic domain (Active Motif) was used as a positive control.The sequenced reads were aligned to the mm9 genome assembly using Bowtie 0.12.6 ref. , allowinReads on the 19 assembled autosomes excluding the 280 kb blacklist region were kept for downstream analysis. The typical fragment size for the different samples ranged between 140 and 180 bp. Each read was considered to represent a signal at half typical fragment size from the 5′-end. Library complexity was calculated for each sample as the number of unique bp positions mapped on each strand, divided by the total number of mapped reads. For batches of experiments where the typical library complexity was below 90% , only one read mapping to each position was kept.Smarcb1 or Smarca4 loss, we repeated the H3K27ac ChIP-seq experiments on indepedently derived MEFs. In the main text and figures, we show the average of results from the two replicate sets. In this section, we demonstrate the reproducibility of the observations. Genome-wide correlations for ChIP-experiments are shown in To validate the observations of H3K27ac loss at TSS-distal sites upon find.binding.positions function) and regions of enrichment (RoE) with a search window of 400 bp (get.broad.enrichment.clusters function). For TFs, only the former calls are made. For both histone marks and TFs, reproducibility is evaluated using the irreproducible discovery rate (IDR) measure on point binding calls from replicate experiments39To systematically assess the reproducibility of experiments, we follow guidelines determined by the ENCODE consortiumcis-regulatory elements, since histone marks are not found at fixed single bp resolution binding positions like TFs. However, to obtain IDR values, we have called point binding sites for H3K27ac samples (find.binding.positions function) with a loose threshold of false discovery rate<0.05. Peaks from two replicates were considered to be the same peaks if they were within 90 bp of each other. Peak signal values, y, from the two replicates were used to determine IDR using the est.IDR function from R package IDR. If a peak in one sample did not match any peaks in the replicate sample, a signal signal value of y=0 was assigned in the replicate. We have also performed an IDR comparison between two pseudoreplicates generated by randomly partitioning the reads from the two replicates. ENCODE guidelines require that the number of peaks with IDR<0.01 for true replicates (Nt) should be more than 50% of the number of peaks for pseudoreplicates (Np)cis-regulatory elements, defined below. As expected, we observed that the replicates show a high degree of correlation in terms of the signal at promoters and enhancers  was quantified as ‘number of reads in region per million mapped reads+pseudocount of 1'. ChIP-seq signal enrichment was then defined as signal in IP sample divided by signal in input signal. ChIP-seq signal fold-change is defined as IP signal in a given sample divided by IP signal in a control sample. Input signal was not taken into account in the calculation of differences between conditions, because little systematic difference was observed between input samples in different conditions; and the statistical variability gets large if ratios of ratios are calculated.cis-regulatory elements between replicates in y=x, but rather appear to be off by a constant factor. We expect two ChIP-seq libraries that are normalized in this fashion to be comparable if two assumptions hold:The factor that is being pulled down has a similar level of binding to DNA for the two samples.The IP efficiency was similar in the two experiments, that is, the libraries contain similar ratio of pulled down to background fragments.While we saw a high degree of correlation between H3K27ac signal as In particular, for replicate experiments of the same condition, the first assumption is known to hold and the validity of the second assumption can be directly assessed. The constant offset we observe for replicate experiments is consistent with variability in the efficacy of IP pulldown between different ChIP-seq experiments.y=x line with a different offset .For each mutant, one of the replicates shows a distribution of fold-differences around 1  show higher H3K27ac signal at promoters upon SWI/SNF subunit inactivation. This is the opposite trend to what is seen for global H3K27ac levels in western blots  the signal change mutant/WT was below 1 for each replicate set; and (ii) the geometric mean of the signal change for the two replicate comparisons was below ½. P values for gene set enrichment for genes associated to sensitive enhancers were calculated relative to genes associated with any enhancer using hypergeometric test. q values were obtained based on Benjamini–Hochberg procedure.Each enhancer was associated to the closest active TSS within 100 kb. Enhancers sensitive to σ=100 bp after library size normalization  are highlighted on the figures.TF motif maps for hg19 for 4,095 motifs  were downloaded from P value was set such that the number of matches to mm9 was barely as many as the number of matches to the hg19 map. Any matches for the motif below this threshold was discarded.To perform the same analysis for MEFs, we first sought to create a corresponding motif map for the mouse genome build mm9. For each motif, we utilized the p.w.m. calculated above based on the provided hg19 map. The locations of motif matches were determined using the MEME suite tool mast with default parametersThe experiments on the human samples were performed once, whereas the experiments for the MEF samples were in replicates. The same approach as used for human cell lines was applied for MEFs, taking advantage of the replicate pairs, to compare highly sensitive enhancers  and insensitive enhancers .The sequenced reads from each sample were aligned to the mouse genome+transcriptome assembly NCBIM37.67 using TopHat v2.0.8 with default parameters except turning off novel junction search (‘-G <gtf> --no-novel-juncs' options)Each enhancer was associated to the closest active TSS, as defined above. The ratio of IP signal for mutant divided by WT MEFs was used to categorize enhancers to four groups: more than 3-fold signal loss, between 1.5- and 3-fold signal loss, less than 1.5-fold-change, and more than 1.5-fold signal increase. The change in RNA-seq was quantified as log2. Only enhancers for which the closest active TSS was 5–100 kb away, and the corresponding gene had cuffdiff status ‘OK' were retained.http://geneontology.org on 29 April 2014. P value for GO term enrichment in downregulated genes versus all (status=OK) genes was calculated using hypergeometric test. Multiple-hypothesis correction was applied using Benjamini–Hochberg procedure. Selected terms are displayed in the figures.Gene level comparisons output by cufffdiff (gene_exp.diff) were used for GO analysis. For each mutant / WT comparison, only genes with status=OK were retained. Downregulated genes were selected as those reported by cuffdiff as significantly different  and with a greater than 2-fold reduction in gene expression when comparing mutant versus WT. GO databases were downloaded from All sequencing data have been submitted to the GEO database with accession number GSE71509. All other data are available from authors upon reasonable request.How to cite this article: Alver, B. H. et al. The SWI/SNF chromatin remodelling complex is required for maintenance of lineage specific enhancers. Nat. Commun.8, 14648 doi: 10.1038/ncomms14648 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary Figures and Supplementary Table


Gene expression is regulated by the dynamic nature of DNA modification, histone modification, and recruitment of activating and repressing protein complexes at specific loci. Chromatin itself is further organized structurally into regions of varying accessibility, an aspect of which includes transient or sustained redistribution of portions of the genome from the nucleoplasm to the nuclear periphery. Targeting of genes to the nuclear membrane, frequently via association with components of the nuclear pore complex (NPC), has both positive and negative effects on the timing and magnitude of gene expression Saccharomyces cerevisiae, where precise manipulation of environmental conditions can be coupled with state of the art single-cell imaging and genetics. For example, genes have been found to localize to the nuclear periphery in response to nutrient shift  and heat shock   in the promoter INO1 locus remains associated with the nuclear periphery for multiple generations, conferring transcriptional memory via stabilization of a poised RNA polymerase II complex 6The mechanisms underlying these various phenomena are beginning to be understood at the molecular level, perhaps best exemplified by studies in the baker’s yeast ock HSP10, TSA2  and Tet (TetO) Operator elements integrated at loci of interest paired with fluorescent protein-DNA binding protein fusions. Cells bearing these endogenous and/or ectopic constructs can then be visualized with confocal microscopy and intra-nuclear distances measured  for individual cells within a population. A key observation derived from these analyses was that two copies of the same locus, for example Microbial Cell, Brickner and co-workers reveal that clustering also occurs during transcriptional memory INO1 memory clustering differentiate this phenomenon from that observed upon gene activation. Transcriptional memory at the GAL1-10 locus requires the nuclear basket protein Mlp1, in contrast to INO1 which targets to the NPC through Nup100 6GAL1 and INO1, when differentially labeled, were found not to cluster after shift to repressing conditions, indicating specificity In the article published in this issue of INO1, GAL1 and HSP104 transit back into the nucleoplasm (as defined by average locus-periphery distances) during S phase, only to re-localize at the periphery before mitosis et al. categorized clustering with respect to bud stage, they found that while un-budded or small-budded cells (G1/S) maintained memory-based clustering, large-budded cells (G2/M) did not, even though both INO1 loci remained associated with the nuclear periphery One of the less well understood features of gene localization at the nuclear periphery is that localization is dynamic during the cell cycle. Stress-activated genes such as This work further illuminates the complex and dynamic architecture of control of gene expression by chromatin localization, but raises even more interesting questions as it does so. Chief among these is the role of clustering with respect to targeting to the nuclear periphery. Because loci with the same DNA zip code will both cluster and target to the periphery, they appear to be localizing to the same location - possibly a specific NPC. However, clustering is retained after disengagement from the membrane, suggesting that it is not the targeted location that is specific but rather the association of different portions of chromatin. What is the fate of the nuclear pore proteins involved in nuclear membrane targeting? Do they release from the NPC with the chromatin, or release from the chromatin and remain with the NPC? The fact that clustering during gene activation is a prerequisite for clustering during transcriptional memory, while utilizing distinct DNA elements  implicates a functional transfer of chromatin oversight from one system to another. It also suggests that the memory system is incapable of initiating clustering through the MRS zip code on its own. Identification of the as yet unknown MRS-binding protein (in addition to Nup100 within the NPC) may shed light on the molecular mechanisms that promote memory, defined by the rapid reinstatement of active transcription at a locus. This is thought to be achieved by stabilization of a pre-initiation transcriptional complex and a poised polymerase at the promoter, events that may be facilitated by insertion of the histone variant H2A.Z into flanking nucleosomes 6As with other epigenetic regulatory mechanisms, clustering and sub-nuclear localization of specific loci allow transient or sustained modulation of gene expression in the absence of permanent nucleotide changes in the genome. Such layers of control provide an attractive target for adaptive selection - organisms capable of re-activating stress response genes faster than their neighbors are likely to gain competitive advantage, without the possible trade-offs that arise with spontaneous mutation. Moreover, the trans-generational nature of transcriptional memory satisfies the tenet that selection can only act on heritable traits. Thus, cellular memory becomes organismal memory. Unraveling the complex language of control of gene expression via sub-nuclear positioning in yeast and other model systems such as Drosophila may have broader impacts to human health.Potentially, thousands of human genes exhibit association with nuclear pore proteins 1410