Recently, super-enhancers (SEs) have been identified as a unique type of transcriptional regulation involved in cancer development. SEs exhibit a size, high transcription factor density, and strong binding to the transcriptional machinery compared with typical enhancers. SEs play an essential role in cell growth, differentiation, and disease initiation and progression including tumorigenesis. In particular, cancer-specific SEs have been proven to be key oncogenic drivers types of tumor cells. Furthermore, it has been confirmed that cancer-specific SEs can mediate the dysregulation of signaling pathways and promote cancer cell growth. Additionally, therapeutic strategies directly targeting SE components, for example, by disrupting SE structure or inhibiting SE cofactors, have shown a good curative effect on various cancers. Additionally, there are some DNA sequences located near or far from promoter regions that contain multiple transcription factor binding sites. These DNA sequences are referred to as “enhancers”, and they increase gene expression.3 Recently, with the development of high throughput sequencing, increasing numbers of enhancers have been detected on a genome-wide scale. A coactivator that was proven to be an enhancer increases target gene expression.4 The coactivator does not bind DNA, but it pairs with TFs, to further activate gene transcription. The coactivator has general activation domains that facilitate its interaction with the basal transcription or chromatin remodeling machinery.5 Additionally, the histone modification of H3K4 trimethylation has been found to be associated with active promoters.6 DNase hypersensitive sites partially overlap with enhancer regions, and enhancer activation coincides with the DNase I hypersensitivity of these regions, which is often associated with specific posttranslational modifications of adjacent nucleosomes.10 Direct interaction or looping between enhancers and promoters has been observed and might be critical for enhancer function.12 Super-enhancers (SEs) defined as clusters of enhancers in close genomic proximity are flanked by CTCF (CCCTC-binding factor) binding sites, and are involved in regulating the expression of key genes.13In eukaryotic cells, transcription begins with RNA polymerase binding to the promoters of DNA molecules, and transcription is regulated by transcription factors (TFs) through binding to specific DNA sequences to recruit RNA polymerase II initiation or elongation factors.14 involves in noncoding regulatory elements, including TFs, promoters, enhancers, SEs, and RNA polymerase II (Pol II).15 In particular, SEs have been found to play core roles in promoting oncogenic transcription to accelerate cancer progression.17 Herein, we introduce the concept, function and identification of SEs, and summarize the contribution of oncogenic SEs to cancer and the challenges of SEs in therapy. This will assist us to in achieving a profound understanding of the functional mechanism by which SEs regulate target gene expression.Gene transcriptional dysregulation, which is one of the core tenets of cancer development,18 TFs bind to and activate enhancers to initiate gene transcription.19 Enhancers are defined as short (~100–1000 bp) noncoding DNA sequences, composed of concentrated clusters of TF recognition motifs. Enhancers drive gene transcription independent of their distance, location or orientation relative to their cognate promoter.20 SEs are a large cluster of transcriptional enhancers that have been proposed to consist of a long genomic domain composed of an enhancer cluster occupied by high levels of H3K4me1, H3K27ac, p300 or master TFs. SEs span a range of more than 20 kb on average. They differ from classical enhancers in their size, transcription factor density and content, sensitivity of binding to perturbation, and active transcription , histone modification markers (such as H3K27ac and H3K4me1), and chromatin modification molecules (such as p300)  1, the enrichment of histone H3K27 acetylation (H3K27ac), or binding with cell-type-specific TFs.25 SEs are predicted to be located in bioinformatic stitching regions within 12.5 kb in the linear genome. As a result, SEs are longer than traditional enhancers, and often contain more than one separate region that is bound by multiple TFs.22Recently, “stretch-enhancers” were similar to SEs; stretch-enhancers induce high expression levels of target genes.22 a number of publications have referred to “super-enhancers”, although SE identification has been inconsistent. In some reports, the definition of “super-enhancer” deviates from specific properties of SEs such as chromatin marks and cofactors bound to these regions. In other studies, enhancers and SEs are not defined functionally, and enhancer stitching is an algorithmic step, not a selection criterion. The only defining feature of a “super-enhancer” is an exceptionally high degree of enrichment of transcriptional activators or chromatin marks, as determined by chromatin immunoprecipitation sequencing (ChIP-seq).26 Use of the term “enhancer” has also shifted from a functional definition of a DNA element that activates gene transcription to a looser definition based on chromatin profiles, characterized by DNAse I hypersensitivity, p300 binding, or H3K4me, or H3K27ac marks. The recent explosion of large-scale genomic data has led many researchers to carefully revisit these concepts.There are still some controversies about SE characterization. Since SEs were initially characterized by Whyte and Loven in 2013,21; “constituent” enhancers were identified as a class of regulatory regions with unusually strong enrichment, all of which were merged into a large region , the active enhancer site was identified, and the binding sites of key TFs, Oct4, Sox2 and Nanog (OSN) binding sites were then sequenced via ChIP-seq analysis13 SEs in mESCs were identified using key TFs such as PU.1, MyoD, T-bet, and C/EBPα from myotube cells, pro-B cells, Th cells and macrophages, and master TFs in these cells were found to be associated with SEs.13 SEs have been defined in many cells and tissues by tissue-specific master TFs; however, the master TFs constituting SEs are still not known, and genome-wide binding data are still limited. The various surrogate marks of typical enhancers include H3K27ac, H3K4me1, p300 and DNase, and the histone H3K27ac modification is superior to the others in mESC.31 A catalog of super-enhancers has been generated for 86 human cell and tissue types, and these SEs have been associated with genes based on cell-type-specific TFs. Thus, candidate master TFs have been identified in many cell types, which has proven to be useful for better understanding the transcriptional control of the cell state and reprogramming.21 SEs and their potential applications are increasingly being recognized and cited, and these findings have been widely used for the exploration of disease mechanisms, such as those of tumors.35 Additionally, human H1 embryonic stem (H1ES) cells were found to contain 6426 stretch-enhancers (with a mean size of 4434 bp)23 and 684 SEs.21 Among the 684 SEs, 505 overlap with a stretch-enhancer. According to the common definitions of SEs, the number of stretch-enhancers exceeds that of SEs by an order of magnitude. Thus, SEs are a subset of stretch-enhancers, and the two entities are not interchangeable as defined.A total of 8794 enhancers were identified in ESCs by using ChIP-seq data sets. In the differentiated cells, lineage-specific master regulators were used to generate binding plots of the OSN master TFs.13 Some researchers have cloned DNA fragments from SE elements into luciferase reporter vector, and then transfected the vector into ESCs to determine SE functionality. Constituent enhancer segments within SEs are defined as 600–1400 bp regions with a single peak of OSN occupancy, that generate higher luciferase activity than typical enhancer segments (3.8-fold high). SEs show a stronger ability to drive target gene transcription than typical enhancers.36 Interestingly, the functional interactions of SE constituents are neither superimposed nor synergistic, indicating that one component has complex effects on the activity of another component. Some SEs show increased effects on transcriptional activity, and some have inhibitory effects.36 SEs exhibit complicated interdependence on each other’s activity, following optimal transcriptional activity. SEs also present master transcription factor-dependent characteristics, exhibiting cell-type-specific functions and producing strong responses. In ESCs, a reduction in Oct4 leads to the loss of ESC-specific gene expression and differentiation. If SE-associated genes are more sensitive to the loss of master TFs than other genes, a reduction in Oct4 level should cause preferential loss of SE-associated gene expression. Upon knockdown of the transcription factor Oct4 in mESCs, the cells lose their pluripotent state.13 In this process, the expression of SE-correlated genes is decreased, and their expression is lower than that of typical enhancer related genes. These results indicate that SEs exhibit a higher interference sensitivity than TEs.37 When mediator levels are reduced using small hairpin RNAs (shRNAs), the greatest effects on gene expression were observed for SE-associated genes.38 If SE-associated genes are more sensitive to coactivator loss than other genes, a reduction in the levels of mediator subunits should preferentially affect the expression of SE-associated genes. Reduced levels of mediators and cohesins have the same effect on the key characteristics of the ES cell state as the loss of Oct4 itself.38Compared with other enhancers, SEs exhibit stronger transcriptional activation and a stronger regulatory ability for the genes that they control.30 The cohesin-mediated substructure of gene loops, such as cohesin-associated enhancer−promoter loops and cohesin-associated CTCF loops, regulates gene expression  that are transcribed and synthesized from the enhancer regions of genome. eRNA plays a stimulatory role in the transcription of related genes, and exhibits a genome-wide character.43 eRNAs serve as a “linker” between SEs and their target genes. The coordinated regulation of transcripts by eRNA can be plotted in active RNA Pol II global nuclear run-on sequencing (GRO-seq) experiments. The transcriptional and synthetic eRNAs of enhancers are conducive to the function of enhancers, and their transcriptional levels are correlated with high activity of enhancer.45 eRNA has been studied in various cell types including neurons, macrophages, T cells and cancer cells,48 and approximately 30.6% of typical enhancers and 93.3% of SEs overlap with eRNAs in intergenic regions. In response to Toll-like receptor signaling in macrophages, SE-related genes and eRNA show coordinated changes. However, these signal-dependent SEs, which are associated with innate immunity and inflammation, are different from the ones identified on the basis of cellular characteristics.45SEs drive the expression of cell-specific genes, and are densely occupied by the transcription apparatus and its cofactors including cohesins.36 Oncogenic SEs promote tumorigenesis and malignancy by upregulating oncogene transcription.21 Mechanistically, oncogenic SEs may activate the MAPK signaling pathway to inhibit apoptosis and promote the proliferation of cancer cells.49 SEs also induce overexpression of the v-ets erythroblastosis virus E26 oncogene homolog (ERG), leading to the overexpression of target genes driving the development of cancer.50 Additionally, oncogenic SEs upregulate CYP24A1, GJA5, SLAMF7, and ETV1 in squamous cell carcinoma.51 The translocation of SEs upregulates MYB expression in adenoid cystic carcinoma (ACC), and SEs promote the expression of TERT in pheochromocytomas and paragangliomas.52Compared with TEs, SEs are enriched in one or more binding sites for the terminal TFs of signaling pathways and signaling modules, and function in the maintenance of stemness and pluripotency. Extending this principle, oncogenic SEs are rich in TF binding sites, and associated with specific signaling pathways upon which cancer cells depend.53 Colorectal cancer (CRC) is driven by various oncogenic pathways,14 and CRC-associated SEs are enriched in transcription factor 4 (TCF4) binding sites.36 CRC-associated SEs are found in CRC cells but not in normal colon cells, indicating that these SEs are specific to CRC tumorigenesis. The analysis of the ChIP-seq binding profile of CRC cells shows that TCF4 is a terminal TF of the Wnt pathway and occupies at the c-MYC locus -positive McF-7 cells indicate that the SE of the ESR1 gene only encodes estrogen receptor alpha (ERa) in tumor cells. Furthermore, oncogenic transcription can distinguish cancer subtypes relying on distinct signaling pathways  can selectively repress MYC expression by decreasing bromodomain-containing protein 4 (BRD4) binding to c-MYC SE regions.63 BRD4 is a member of the bromodomain and extraterminal (BET) subfamily of human bromodomain proteins, which is associated with acetylated chromatin and involved in transcriptional activation.65 It recruits positive transcription elongation factor b (P-TEFb) to regulate transcriptional elongation by RNA Pol II.67 BRD4 displays similar binding patterns to mediators, localizing to regulatory regions of the actively transcribed genes, especially at SEs. Its inhibition mediates the preferential loss of BRD4, which results in a corresponding decrease in MED1 (mediator of RNA polymerase II transcription subunit 1) binding and transcription  in a subset of acute lymphoblastic leukemia (ALL) is associated with SE formation. TAL1 upstream of an SE contains a short heterozygous somatic mutation that creates one SE and introduces binding motifs for the MYB transcription factor in noncoding sites35  expression, which leads to the concomitant loss of GATA2 transcription.40 The loss of GATA2 is associated with acute myeloid leukemia (AML), and GATA2 haploid in sufficiency might provide the precise context for EVI1-mediated oncogenic transformation73  disrupts GATA3 binding, and leads to reduced recruitment of H3K27Ac, which is negatively associated with the LMO1 SE in neuroblastoma cells34 , Burkitt’s lymphoma (BL), AML, and ALL80  of RNA Pol II and hinders promoter proximal pausing.84 Because SEs are enriched at the paused RNA Pol II, THZ1-induced deficiency at the pause sites leads to the decreased occupancy of Pol II at these enhancers, culminating in transcriptional inhibition86  cells and sensitizes NB cells to the inhibition of CDK7. When a covalent inhibitor of CDK7 is used to disrupt the transcription of amplified MYCN in NB cells, the oncoproteins are downregulated with the consequent strong suppression of MYCN. THZ1 selectively targets MYCN-amplified NB cells, and THZ1 target treatment leads to the preferential downregulation of SE-associated genes and significantly represses MYCN-dependent transcriptional amplification68  selectively kill cancer cells by inhibiting SE-driven oncogene transcription. However, transcription is a fundamental biological process shared by all living cells, and targeting transcription may therefore have dire consequences for global gene expression. Along with the development of SE research, there may be novel ideas about therapeutic techniques for diseases such as cancer and other complex diseases.SEs are large clusters of transcriptional enhancers that drive gene expression to control cell identity. Compared with normal enhancers, SEs display a unique structure and strong functional properties. Although there is still a lack of uniform rules for the definition of SEs, the differences in transcription factor density and content, binding sensitivity, and active transcription are used to distinguish SEs from ordinary enhancer,


In contrast, deleting mst2+, or other members of Mst2C, fully restores silencing in Set2-deficient cells. Suppression of the silencing defect in set2Δ cells is specific for pericentromeres and subtelomeres, which are marked by H3K9me, but is not seen for loci that lack genuine heterochromatin. Mst2 is known to acetylate histone H3K14 redundantly with the HAT Gnc5. Further, it is involved in the acetylation of the non-histone substrate and E3 ubiquitin ligase Brl1, resulting in increased H2B-K119 ubiquitylation at euchromatin. However, we reveal that none of these mechanisms are responsible for the Set2-dependent silencing pathway, implying that Mst2 targets another, unknown substrate critical for heterochromatin silencing. Our findings demonstrate that maintenance of chromatin states requires spatial constraint of opposing chromatin activities.Maintaining the identity of chromatin states requires mechanisms that ensure their structural integrity through the concerted actions of histone modifiers, readers, and erasers. Histone H3K9me and H3K27me are hallmarks of repressed heterochromatin, whereas H3K4me and H3K36me are associated with actively transcribed euchromatin. Paradoxically, several studies have reported that loss of Set2, the methyltransferase responsible for H3K36me, causes de-repression of heterochromatin. Here we show that unconstrained activity of the acetyltransferase complex Mst2C, which antagonizes heterochromatin, is the main cause of the silencing defects observed in Set2-deficient cells. As previously shown, Mst2C is sequestered to actively transcribed chromatin via binding to H3K36me3 that is recognized by the PWWP domain protein Pdp3. We demonstrate that combining deletions of  The nucleus of eukaryotic cells is organized into topologically distinct chromatin domains, known as eu- and heterochromatin. Both are controlled through various post-translational histone modifications, nucleosome remodeling and RNA-related processes. Euchromatin is associated with active transcription and histone hyperacetylation, contributing to an open chromatin structure. In contrast, heterochromatin is associated with gene repression and histone hypoacetylation, often adopting a compact chromatin structure that restricts transcription and genomic recombination. Whereas constitutive heterochromatin is present at repeat-rich sequences like centromeres and telomeres, facultative heterochromatin can also form at gene-rich regions, e.g. during cellular differentiation and adaptation to environmental changes. Responding to these changes and maintaining the structural integrity of heterochromatin domains requires the concerted actions of histone modifiers, readers, and erasers –3.Schizosaccharomyces pombe, distinct heterochromatin domains are present at pericentromeres, subtelomeres and the silent mating type locus. H3K9me is deposited by the sole histone methyltransferase Clr4 that is present in a complex known as CLRC (Clr4 methyltransferase complex) and catalyzes all three steps of methylation [A conserved type of heterochromatin is characterized by the presence of methylated lysine 9 of histone H3 (H3K9me) . In Schihylation . The rephylation  and membhylation , 9. Amonhylation –12.S. pombe [Heterochromatin assembly is guided by several targeting mechanisms among which the RNA interference machinery plays a prominent role in S. pombe , 14. ConS. pombe –17 and pS. pombe . Epe1 isS. pombe –21. HeteS. pombe –24. Paf1S. pombe , 26. FurS. pombe .paf1 mutant is drastically increased when Mst2 is absent [Saccharomyces cerevisiae NuA3b, which contains the PWWP domain protein Pdp3 [pdp3Δ cells) remains unknown.Histone acetyltransferases (HATs) also counteract heterochromatin by altering the charge and structure of nucleosomes, and also through the recruitment of factors to acetylated histones. The lysine acetytltransferase (KAT) Mst2 mediates H3K14 acetylation redundantly with the HAT Gcn5, which is part of the SAGA (Spt-Ada-Gcn5 acetyltransferase) complex . Loss ofs absent . Mst2 isein Pdp3 , 32. Pdpein Pdp3 , 32. Notein Pdp3 . Howeverein Pdp3 , 31. Proset2Δ cells are mediated directly through a local loss of H3K36me or an alternative mechanism remains unclear.H3K36 methylation is associated with actively transcribed chromatin. In budding and fission yeast, all three methylation states are mediated by a single enzyme, Set2 . Set2 biset2Δ cells at canonical heterochromatin can be fully reversed by concomitant deletion of mst2+. Full suppression of the silencing defect is also seen in the absence of other Mst2C members, which are critical for proper complex assembly, but not for Pdp3 that recruits Mst2C to actively transcribed regions via H3K36me3. Together, our findings implicate that the silencing defect of set2Δ cells is caused by the global mislocalization of Mst2C and its encroachment on heterochromatic regions.Here we demonstrate that the silencing defects in imr1L::ura4+ reporter gene and various subtelomeric genes, which are suppressed when mst2+ is concomitantly deleted [set2Δ at various pericentromeric and subtelomeric heterochromatic loci [set2Δ cells, analogous to mst2+ deletion in a pdp3Δ strain . Silencing can be monitored in vivo using the ura4+ reporter gene inserted into a heterochromatic region. Presence of the nucleotide analog 5-FOA (5′-fluoroorotic acid) inhibits cell growth due to the conversion of 5-FOA into a toxic metabolite by the gene product of ura4+ but allows growth when ura4+ transcription is repressed. By examining pericentromeric silencing in the imr1L::ura4+ reporter strain used previously [set2Δ cells on 5-FOA is impaired, similar to pdp3Δ cells and consistent with other studies that have reported silencing defects for set2Δ [mst2+ was deleted in a set2Δ background . We confirmed the findings of the reporter assay by reverse transcriptase assays combined with quantitative PCR (RT-qPCR). Deletion of set2+ causes a reproducible upregulation of the imr1L::ura4+ reporter gene (4-fold) and two endogenous transcripts from the outer dg and dh repeats . In contrast, transcript levels in the set2Δ mst2Δ double mutant resemble those of wild-type (WT) cells. In addition, we examined expression levels of transcripts derived from a subtelomeric region that is marked with high levels of H3K9me2 . De-repression of the subtelomeric genes tlh1+/tlh2+, SPAC212.09c and SPAC212.08c in set2Δ cells is even more pronounced  than what we found at pericentromeres. Nonetheless, transcriptional upregulation at these loci is completely suppressed when mst2+ is concomitantly deleted in set2Δ cells.We previously showed that loss of the PWWP subunit Pdp3 causes moderate silencing defects of the pericentromeric  deleted . Since P deleted , we testtic loci , 41–44 ceviously , we founor set2Δ , 41–43. S. pombe is marked by high levels of H3K9me but largely devoid of euchromatic histone modifications  [set2Δ cells for several heterochromatic loci that display intermediate H3K9me2 levels . Conversely, mst2Δ and set2Δ mst2Δ cells showed elevated H3K9me2 levels at those loci, suggesting that Mst2 counteracts H3K9me2 in a chromatin context-dependent manner. This notion was further supported by a comprehensive analysis of H3K9me2 using tiling oligonucleotides covering pericentromeric and subtelomeric heterochromatin, and a facultative heterochromatin island at the mei4+ locus . Especially at telomere-distal heterochromatin (30-50 kb downstream of telomeric repeats) and mei4+, loss of Mst2 resulted in a large H3K9me2 increase, suggesting that those chromatin regions are particularly prone to heterochromatin assembly.Constitutive heterochromatin in H3K36me) , 45. By Figure 1D, middle panels; note that the absolute level might even be lower, since the anti-H3K36me3 antibody used here shows limited cross-reactivity with H3K9me2; Figure S2). Importantly, H3K36me3 levels changed only marginally in set2Δ and mst2Δ single mutants at most heterochromatin loci examined and, as expected, remained low in cells lacking both Set2 and Mst2, despite of silencing being restored in the double mutant. We also analyzed nucleosome abundance by examining  histone H3. While H3 ChIP enrichments tend to be lower for some loci in these mutants, most changes were not significant and did not reflect transcriptional upregulation or changes in histone modifications . Together, these findings suggest that the silencing defects at pericentromeric and subtelomeric heterochromatin are not primarily caused by local changes of H3K36me3 within heterochromatin . Rather, our results imply that they are triggered by the uncontrolled activity of Mst2, which in the absence of Set2 is no longer tethered to euchromatin and gains promiscuous genome-wide access to chromatin, including the heterochromatic regions [While H3K4me is completely absent at constitutive heterochromatin , residua regions .Figure 2A, left panel) [pdp3Δ than in set2Δ . Combining both deficiencies did not result in an additive increase; we rather observed a mild suppressive phenotype for set2Δ pdp3Δ when compared to the set2Δ single mutant. Although the nature of the partial suppression remains unclear (see discussion), the non-additive phenotype of the double mutant suggests that Pdp3 and Set2 act in the same pathway.We previously demonstrated that the Mst2C subunit Pdp3 mediates Mst2 recruitment via its PWWP domain that binds to H3K36me3 (t panel) . Since St panel) , cells lmst2+ elimination, suppresses the silencing defect of set2Δ . Similar to mst2Δ, eliminating nto1+, eaf3+ and ptf2+ alone did not increase gene repression but in combination with set2Δ completely suppressed the silencing defect . In contrast, deletion of ptf1+ rather resembled the phenotype of pdp3Δ, showing a moderate upregulation and partial suppression in combination with set2Δ, suggesting that Ptf1 also contributes to the recruitment of Mst2C to H3K36me3 . We refrained from examining the tfg3+, as its presence in multiple complexes likely causes pleiotropic effects that may be difficult to interpret. From these data we conclude that an intact Mst2 complex is required to trigger the silencing defect at heterochromatin.Besides Mst2 and Pdp3, Mst2C contains five additional subunits: Nto1, Eaf6, Tfg3, Ptf1 and Ptf2. Eaf6 is also present in the NuA4 acetyltransferase complex, while Tfg3 is shared with Ino80, SWI/SNF and the TFIID and TFIIF complexes. The functions of these subunits within Mst2C are not well understood, but Nto1 and Ptf2 are essential for the integrity and assembly of the complex, and mutants lacking either of these subunits phenocopy the loss of Mst2 . We therset2Δ cells . By ChIP, we confirmed previous reports [Figure 3B). Interestingly, H2B-K119ub was significantly reduced in the absence of Set2 at several of euchromatic genes but not at act1+ , which we used as an internal control for normalization in the subsequent ChIP experiments. We found that cells expressing the brl1-K242R mutant that inhibits Brl1 acetylation also showed decreased H2B-K119ub at several euchromatic genes  yet less distinct than seen in set2Δ cells. The set2Δ brl1-K242R double mutant displayed a slightly enhanced decrease, whereas the brl1-K242Q mimicking Brl1 acetylation did neither alter H2B-K119ub in WT nor in set2Δ cells. Together, these data imply that mutations affecting Brl1 acetylation regulate H2B ubiquitylation in euchromatin, which is in agreement with our previous observation for total H2B-K119ub [We previously showed that Mst2 is involved in the acetylation of the non-histone substrate Brl1, a conserved ubiquitin E3 ligase that mono-ubiquitylates histone H2B at lysine 119 . Acetyla reports , 47 thatB-K119ub  . Moreover, in stark contrast to set2Δ mst2Δ cells , we found that silencing at pericentromeres and subtelomeres was not reinstated in the set2Δ brl1-K242R double mutant . Hence, preventing Brl1 acetylation is not sufficient to block the anti-silencing activity of Mst2. Instead, we observed transcriptional upregulation even in the single brl1-K242R mutant for some heterochromatic loci, suggesting that the loss of its acetylation target Brl1 (in euchromatin) renders Mst2 more active (in heterochromatin). From this we conclude that Mst2's euchromatin-protective role via Brl1-K242ac differs from its role in counteracting gene silencing at heterochromatin. This further implies that Mst2 targets at least one other substrate that is critical for heterochromatin silencing.However, when examining heterochromatin, we found hardly any change in these mutants for H2B-K119ub, which was 5-10 times lower than euchromatin in WT cells and remained low in set2+ does not only affect gene repression at chromatin regions with high levels of H3K9me2 but also other subtelomeric loci. These include the telomere-proximal region , as well as a region 50 kb downstream of the telomeric repeats, which is characterized by highly condensed chromatin bodies dubbed ‘knobs' [Figure 4A and B). Transcription of the non-coding RNA TERRA (telomeric repeat-containing non-coding RNA) from the TAS is repressed by heterochromatin and members of shelterin, the telomere-end protecting complex [Figure 4C and D). Similarly, subtelomeric ‘knob' genes are decorated with a low amount of H3K9me2 and display reduced H3K36me3 compared to euchromatin .Loss of  ‘knobs'  . In agreement with previous studies, we also detected a 2 to 10-fold upregulation for several ‘knob' genes [mst2+ did not restore silencing of these loci in set2Δ . Nonetheless, disruption of mst2+ promoted the establishment of H3K9me2 at several knob genes (particularly SPAC977.15), corroborating the notion of Mst2C playing a global role in antagonizing heterochromatin [When we examined gene expression at the TAS, we found a subtle but reproducible upregulation (2 to 3-fold) of b' genes , 44. Addhromatin , 31, 51.mst2 restores silencing in cells lacking the H3K36me3 reader Pdp3 [Figure 1 and 2). Reinstatement of silencing is not only seen at the level of transcription but also at the level of heterochromatin structure (H3K9me2) at loci where loss of Set2 affects both . In contrast, H3K36me3 is low at these heterochromatin regions even in WT cells and also not affected upon deletion of mst2+. This suggests that defective silencing is not caused directly by the loss of H3K36me within heterochromatin but rather indirectly through the promiscuous activity of Mst2C. Although Set2 is implicated in various cellular functions, pleiotropic defects appear to be less likely the cause of impaired silencing. Instead, the fact that silencing is completely restored at constitutive heterochromatin implies that Set2 exclusively controls gene repression through sequestration of Mst2 by H3K36me3. It is worth mentioning that although Mst2 is not detected by ChIP at transcribed chromatin in pdp3Δ cells, it has still access to chromatin, as we previously demonstrated by DamID experiments [Transcriptionally active and repressed chromatin regions are marked by different posttranslational modifications. H3K36me3 in particular is deposited co-transcriptionally through the recruitment of Set2 by transcribing RNAPII and likely other elongating factors . Yet parder Pdp3 . Here, weriments .pdp3Δ is less pronounced than in set2Δ , despite the fact that silencing can be fully restored in the absence of Mst2 . A possible explanation would be that Mst2 recruitment involves another H3K36me3-binding factor that acts redundantly with Pdp3. Indeed, the Mst2C subunit Nto1 contains two PHD (plant homeodomain) fingers, and the S. cerevisiae homolog shows affinity for H3K36me3 [pdp3Δ and nto1Δ mutants. Alternatively, Pdp3 may also contribute to the stability or activity of the complex (at least in part), in addition to its function in H3K36me3 anchoring. This could explain the intermediate phenotype of pdp3Δ cells compared to set2Δ on one hand, and mst2Δ on the other. More work will be needed to better understand the functions of the individual subunits of Mst2C.Recruitment of Mst2 to euchromatin is mediated by the Mst2C subunit Pdp3, which binds to H3K36me3 via its PWWP domain. Consistently, lack of Pdp3, or a point mutation within its PWWP domain, also produces a defect in heterochromatin silencing . HoweverH3K36me3 . Howeverin vitro and in vivo and acts redundantly with the SAGA member Gcn5 [Mst2 acetylates H3K14 ber Gcn5 . H3K14acber Gcn5 . H3K14acber Gcn5 , 53. Morber Gcn5 . At firsber Gcn5 , 34. Secber Gcn5 . Third, ber Gcn5 . Togethebrl1+ with an acetylation-deficient mutant (brl1-K242R) phenocopied the deletion of mst2+, whereas mimicking acetylation (brl1-K242Q) bypassed the need for Mst2 in protecting euchromatin. In agreement with this finding, deletion mutants of brl1+ or other components of HULC display more robust heterochromatin silencing than WT cells [mst2Δ, we found that introducing the brl1-K424R mutant was not sufficient to suppress the silencing defect of set2Δ. While initially we did not expect a Brl1-independent Mst2 function at heterochromatin, several lines of evidence support the idea that Mst2 acts through different pathways at eu- and heterochromatin. First, whereas Mst2 antagonizes heterochromatin even when not recruited by H3K36me3, Brl1 acetylation and euchromatin protection requires stable chromatin binding of Mst2 via Pdp3 [Figure 3C and D). Second, at heterochromatin, loss of Pdp3 or Set2 causes de-repression and H3K9me decrease, whereas lack of Mst2 results in enhanced repression and increased H3K9me. However, at euchromatin and facultative heterochromatin, the lack of either Pdp3 or Mst2 causes ectopic heterochromatin assembly . We therefore speculate that besides H3K14 and Brl1-K242 Mst2C targets at least one other substrate that is important for heterochromatin maintenance . Previous proteomics failed so far to identify additional substrates besides Brl1 that involve acetylation by Mst2 [We previously showed that the euchromatin-protective role of Mst2 is mediated through acetylation of the non-histone substrate Brl1, a subunit of HULC . In partWT cells . Thus, avia Pdp3 . Consistgure S1; ). Finall by Mst2 . Howeverset2+ results in the transcriptional upregulation of other genes that are part of repressed chromatin regions but largely devoid of H3K9me2. These include the non-coding RNA TERRA expressed from the telomere-proximal TAS region as well as various other genes expressed from the telomere-distal ‘knob' region, which is characterized by high chromatin condensation and the absence of most post-transcriptional histone modifications [TERRA, we still detect some H3K36me3 at these chromatin regions, albeit reduced compared to euchromatin . Transcriptional upregulation of these loci is moderate in set2Δ and not suppressed by concomitant Mst2 elimination. Nonetheless, Mst2 may still gain access to these loci and antagonize heterochromatin formation, as seen by increased levels of H3K9me2 upon mst2+ deletion. Nonetheless, the lack of suppression suggests the involvement of a Set2-dependent but Mst2-independent pathway that is critical for gene repression.Besides defects at constitutive heterochromatin, deletion of ications . HoweverS. cerevisiae; MORF4 in humans) [S. cerevisiae, Rpd3S, prevents cryptic transcription through deacetylation of histones in coding regions marked with H3K36me2/3 via Eaf3 [S. cerevisiae homolog, S. pombe Set2 does not contribute to deacetylation of bulk histones and only moderately affects antisense transcription; in addition, the set2Δ alp13Δ double mutant displays an additive defect, thus arguing for parallel pathways [Another histone-modifying complex potentially involved in Set2-dependent silencing is the HDAC Clr6C-II, which contains the chromodomain protein Alp13 (Eaf3 in  humans) , 55. Thevia Eaf3 . Similarvia Eaf3 . In addivia Eaf3 . Howeverpathways . Moreovepathways , heterocpathways , 34. Togcec-4-null larvae identified the chromodomain protein MRG-1 as a critical factor for perinuclear heterochromatin organization [S. cerevisiae) and Clr6C-II subunit Alp13 (S. pombe). In addition, MRG-1 may associate with the HAT CBP-1/p300 analogous to other organisms. Although MRG-1/CBP-1 and Pdp3/Mst2C are not homologous to each other, there are still striking parallels [mrg-1-null is phenocopied by the double mutant lacking the H3K36 methyltransferases MET-1 and MES-4. Reducing CBP-1 restores silencing in mrg-1-null larvae, whereas overexpression of cbp-1 is sufficient to release heterochromatin from the nuclear periphery in the absence of CEC-4. Moreover, the authors detected increased CBP-1 binding at several heterochromatic genes in mrg-1-null larvae. This was accompanied by elevated histone acetylation (H3K27ac), providing a direct link to gene expression.In worm embryos, perinuclear heterochromatin is established through two methyltransferases  and the nuclear membrane-associated chromodomain protein CEC-4, which tethers H3K9me-marked chromatin to the nuclear periphery , 58. Hownization . MRG-1 iarallels : Like PdAltogether, this demonstrates that the principle of heterochromatin maintenance through internal sequestration of KATs is conserved between fission yeast and worms, despite some apparent differences regarding the molecular mechanisms (i.e. the nature of the KAT enzymes and their substrates). It further unveils that the pathways partition in eu- and heterochromatin are remarkably entwined, requiring spatial constraint of opposing chromatin activities to maintain the identity of chromatin states. Recent observations have reinforced the notion that repressive histone marks contribute to epigenetic inheritance of chromatin domains , 27, 60.Important reagents and assays used are listed in Table S5. Further information and requests for resources and reagents should be directed to and will be fulfilled by Sigurd Braun (sigurd.braun@bmc.med.lmu.de).ura4+ reporter assay in Figure 1B cells were plated on EMM or EMM containing 1 mg/mL FOA. The strains were grown at 30°C for three  and four days (5-FOA), respectively. Cultures were grown at 30°C in liquid YES media  or at 30°C on solid YES agarose plates (for 3 days). The brl1-K242R point mutant was provided by M. Bühler . Strains used in this study are listed in Table S1.Standard media and genome engineering methods were used . For theact1+ normalized data sets from independent experiments were standardized to the mean of all samples from each experiment . These sample pool-normalized results were shown relative to the mean value of the sample pool-normalized WT data from all (n) experiments (eq 1.2).RT-qPCR experiments were carried out as previously described . The datExperimental normalization:Mean WT normalization:Using the average from a collection (sample pool) instead of a single strain (e.g. WT) reduces bias, especially when transcripts levels are low in the repressed state and therefore more prone to noise.600): anti-H3K9me2 (15 OD600) anti-H3K36me3 (5 OD600), anti-H3 (5 OD600) and anti-H2B-K120ub (20 OD600). Antibodies are listed in Table S4. Immunoprecipitated DNA was quantified by qPCR using the primaQUANT CYBR Master Mix (Steinbrenner Laborsysteme) and a QuantStudio 5 Real-Time PCR System (Applied Biosystems). Primers are listed in Table S2. Unless otherwise noted, the median was calculated from three independent experiments. qPCR signals were normalized against the input samples for each primer position as internal control. For ChIP experiments with anti-H3K9me2, the input-normalized values were corrected for variation by normalizing against the mean of cen-dg and cen-dh as the otr is the region with the highest and most stable H3K9me2 enrichment . For ChIP experiments with anti-H3K36me3 and H3, input-normalized qPCR signals were normalized to the mean of 3 euchromatic loci  as an internal control, which was set to 1 . ChIP results with anti-H2B-K119ub were analyzed analogously, except that ChIP signals were normalized to input  or act1+ as an internal control .ChIP experiments were performed essentially as described . Cross-lInternal ChIP normalization H3K9me2:Internal ChIP normalization H3K6me3 and H3:act1+) reduces bias coming from variations in ChIP experiments, especially when doing IP experiments with bulk histones.Using the mean of multiple euchromatic loci (‘EC') instead of single locus (e.g. PRG and SB designed the study. PRG generated yeast strains and performed RT-qPCR experiments with assistance by SFB. PRG and MC performed ChIP-qPCR experiments with assistance by SFB. MC performed silencing reporter assays. PRG and SB analyzed all data. SB wrote the manuscript, and PRG and MC contributed to editing.Click here for supplemental data file.http://www.microbialcell.com/researcharticles/2020a-georgescu-microbial-cell/.All supplemental data for this article are available online at


In this study, we synthesized series of l-thymidine (l-T)-modified DNA strands and evaluated the processivity of nucleotide incorporation for transcription by T7 RNA polymerase (RNAP) with an l-T-containing template. When single l-T was introduced into the transcribed region, transcription proceeded to afford the full-length transcript with different efficiencies. However, introduction of l-T into the non-transcribed region did not exhibit a noticeable change in the transcription efficiency. Surprisingly, when two consecutive or internal l-Ts were introduced into the transcribed region, no transcripts were detected. Compared to natural template, significant lags in NTP incorporation into the template T+4/N and T+7/N  were detected by kinetic analysis. Furthermore, affinity of template T+4/N was almost the same with T/N, whereas affinity of T+7/N was apparently increased. Furthermore, no mismatch opposite to l-T in the template was detected in transcription reactions via gel fidelity analysis. These results demonstrate the effects of chiral l-T in DNA on the efficiency and fidelity of RNA transcription mediated by T7 RNAP, which provides important knowledge about how mirror-image thymidine perturbs the flow of genetic information during RNA transcription and development of diseases caused by gene mutation.Due to highly enzymatic   l-T was introduced into templates. When two consecutive or internal l-Ts were introduced into the transcribed region, no transcripts were detected. No mismatch opposite to l-T in the template was detected.Transcription proceeded to afford the full-length transcript with different efficiencies when single  However, recent investigations report that the non-natural nucleobase pairs in duplex DNA can be efficiently duplicated in PCR reactions,,,Chirality of the repeating units of polymers is an essential factor for the formation of the higher-order structure and function of diverse living organisms.l-nucleoside analogs  in living cells as a new class of antiviral drugs.,d-stereoselectivity,l-thymidine (l-T) unit in the DNA template by B family DNA polymerases  and elongate the primer with self-repair.Possibly, damage of chirality of DNA occurs owing to the presence of −6 error rate).,,Transcription is a continuous process of synthesis of an RNA copy from the DNA templates, catalyzed by RNA polymerase (RNAP) with high fidelity.l-T insertion,l-T into different sites of template strands and non-template strands, and then examined the processivity of transcription with the modified templates catalyzed by T7 RNAP. Upon introduction of l-T into non-transcribed regions of template or non-template, transcription was able to efficiently achieve full-length transcripts. When l-T was introduced into a transcribed region of templates, T7 RNAP incorporated NTP with distinct catalytic efficiencies. Notably, transcription catalyzed by T7 RNAP was aborted when two consecutive or internal l-Ts were introduced into a transcribed region. In addition, T7 RNAP incorporated NTP with high catalytic efficiency along the mirror-image-containing template with no mismatch. Moreover, structural insights into the NTP incorporation clarified the detailed mechanism by combining with their transcriptional activities and kinetic analysis.Although DNA replication studies with A and B family DNA polymerases have been carried out for ,l-T-containing templates by T7 RNAP, we synthesized the l-T phosphoramidite to introduce the l-T unit into either the non-template strand (N) or the template strand (T) at different sites as shown in T7 promoter includes two functional regions, that is, an RNAP recognition region and an unwinding region.l-T on the efficiency of transcription catalyzed by T7 RNAP, a transcription reaction with template containing l-T at positions +4, +7, +8, +10, and +12 of the transcribed region  was performed. A transcription reaction was carried out in the presence of all four natural NTPs. As shown in l-T was introduced into the transcribed region . The transcription products from template T+7/N were analyzed on denaturing gel. Full-length products as well as aborted transcripts could be visualized in the gel, indicating that transcription of the template T+7/N was less efficient than for other templates. These data suggest that T7 RNAP possessed almost the same catalytic properties during RNA synthesis with these l-T-containing templates except for T-7/N.To evaluate the effect of l-T in the T7 promoter was conducted. Several transcription experiments were performed using the templates modified with l-T at position −3 and −10 (template T−3/N and T−10/N) in the T7 promoter in the presence of T7 RNAP. As shown in l-T into a non-transcribed region of template strand has no impact on the process of transcription.Therefore, an investigation of transcription reaction with templates containing l-T in transcription, templates T associated with non-template N strand containing l-T units at positions −2, −8, and +11 were utilized to test the regulation of transcription in the presence of T7 RNAP. Strikingly, similar results were obtained for introduction of l-T in the non-template strand by comparing it with natural DNA template. In the case of template T associated with the non-template strand containing l-T at positions −2, −8 and +11 , the same amounts of 17-nt transcripts were detected, indicating that the introduction of l-T at different sites of non-template strand did not result in a sharp decrease or increase in the yields of transcripts  and two interval l-Ts (T+8+10/N). Extraordinarily, with modification of two consecutive l-Ts at positions +7 and +8 in the transcribed region, no noticeable bands of any transcriptional products were detected, indicating that incorporation of NTP was suppressed in the synthesis. Similarly, transcription with templates containing two interval l-Ts (T+8+10/N) was unable to proceed, and no detectable transcription products were found in the gel  in the presence of all four NTPs (0.5 mM) and T7 RNAP (5 U/μL) for various times, respectively. Evidently, transcripts directed by a natural template were comparatively more abundant than those of template T+4/N. In addition, nucleotide incorporation into RNA products directed by template T+4/N became relatively slow. Similar to template T+4/N, transcription directed by template T+7/N showed a more serious lag in incorporating NTPs compared to a natural DNA template. Moreover, abortive and intermediate products were also observed with template T+7/N.Because T7 RNAP can incorporate NTPs into transcripts directed by templates containing a single l-T, bypass %) versus reaction time (obs]) of transcription were obtained by A(1 − e−kobst) (where A is the amplitude of the reaction and t is the time in seconds), and kobs values for nucleotide insertions opposite l-T for template T+4/N and T+7/N were 1.05 × 10−2 s−1 and 0.5 × 10−2 s−1, respectively, versus 1.19 × 10−2 s−1 for d-T. The least efficient transcription (T+7/N) led to synthesis of a 2.38-fold (1.19 × 10−2/0.5 × 10−2) lower amount of runoff RNA than for the most efficient transcription (T/N).Quantitative analyses of running start assays were determined by full-length production formation  were performed with T+4/N and T+7/N as well as the natural template at various NTP concentrations, and the gel analyses are shown in −1) was plotted as a function of NTP concentration, and the data were fit by Michaelis-Menten plots of transcription rate as a function of the concentration of NTP (OriginLab).,l-T into templates T+4/N and T+7/N played a different role in transcription. From these plots, Km and kcat of the two templates could be calculated as listed in m for T+4/N was almost the same with that for T/N , whereas Km for T+7/N was 0.214 mM, demonstrating that introduction of l-T at position +7 of the transcribed region strongly interfered with the binding affinity of RNAP. Moreover, compared with templates T/N and T+4/N, the Km did not change, but the kcat significantly changed. In contrast, kcat values of transcription with T+7/N as the template were remarkably dropped compared to that of the normal template (1.12 versus 12.46 min−1), suggesting a noticeable decrease in the transcript formation rate with template T+7/N. Considering that changes in kinetic parameters are affected by structural changes of template, substrate, or the polymerase,As described above, transcription activity was higher with normal templates than with the −6 in elongation,,l-nucleotide residue in heterochiral duplexes retains its selectivity toward the complementary d-nucleotide residue.,l-T in the templates into transcripts with different efficiency, we therefore checked the fidelity of the T7 RNAP when it encountered l-T-containing templates.In the RNA synthesis, the selection of nucleotide substrate is based on the Watson-Crick base pairing between a template DNA nucleotide and the incoming NTP with the aid of RNAP.2/N2 or l-T-modified template T2+7/N2. As described in 2/N2 can obtain the full-length transcription product, and the transcription was terminated when encountering the d-T in the templates. Similarly, the band of full-length transcripts was clearly observed in the gel in the presence of GTP+ATP with T2+7/N2 as template. However, compared to T2/N2, the amounts of products were remarkably smaller, although an obvious band of aborted products (6 nt) was detected, indicating the much lower transcription efficiency for T2+7/N2. When GTP, GTP+CTP, or GTP+UTP was added into the reaction system, only the aborted transcripts were detected and full-length products were not found in the gel, suggesting that the T7 RNAP cannot incorporate GTP, CTP, or UTP opposite l-T in the template to continue the RNA synthesis process by T7 RNAP. Only ATP could be incorporated efficiently with the complementary nucleotides (d-T or l-T) on the template, without significant mismatch having been observed.Considering that T7 RNAP exhibits a strong bias for guanosine triphosphate (GTP) as the initiating nucleotide,l-T in transcription reactions by T7 RNAP, and our results led to several important findings. First, we observed that single l-T can be bypassed in all transcription reactions to afford the full-length transcript with different efficiencies. Introduction of l-T into the non-transcribed region of template or non-template does not result in remarkable change in transcription efficiency. However, l-T at the +4 and +7 positions of the transcription region inhibited RNA transcriptions, and the incorporation inhibited at position +7 was much stronger than that at position +4, suggesting that the l-Ts at the +7 position were not much better tolerated in RNAP transcription elongation. According to our results from Gaussian calculations, the Gibbs free energy for template T+7/N (l-T) binding with RNAP  is higher than that for template T+7/N (d-T)  (l-Ts (T+8+10/N) is suppressed by T7 RNAP. Third, our results demonstrated that the nucleotide insertion opposite l-Ts is specific, where only the T-A base pair was formed for T7 RNAP.We systematically investigated the compatibility and fidelity of cal/mol) . Second,in vitro.,,T7 RNAP exhibits powerful transcription efficiency Extensive studies have been devoted to analysis of the 3D structure of the T7 RNAP transcribing or initiation complex. Thus, insights into NTP addition from 3D structure may provide useful information for understanding our results. T7 RNAP resembles a canonical “right hand” with thumb, palm, and fingers domains.d-T) or T+4/N (l-T) as template, Y639 is able to contact with the complex in the entrance and induce conformational changes of ATP to obtain a correct orientation for base pairing. However, ATP at pre-insertion associates closely with Y639 for template T+7/N (d-T) (l-T) (l-T) as template, which is unlikely to be further inserted. Thus, an off-path pre-insertion configuration sterically blocks the rotation of Y639 to some extent and prohibits it from nucleotide insertion. No significant change in Km and an obvious decrease in kcat for T+4/N indicate that only the rate of product formation was decreased , the slight steric constraint does not hinder the rotation of Y639 and the release of promoter. In consequence, there is no remarkable alteration in the transcription efficiencies of template T+8/N, T+10/N, and T+12/N  E but staT) (l-T) F. Conseqecreased . This mad region  and S2. d T+12/N .l-T and d-T have identical functional groups, substitution of d-T with l-T in the promoter region  and non-template strand (T/N+11) causes relatively small steric hindrance when T7 RNAP binds to the promoter. With no significant steric clashes, introduction of l-T into the promoter region  and non-template strand (T/N+11) does not much affect the binding or dissociation of T7 RNAP from the promoter. Thus, transcription efficiencies had no significant changes compared with normal template (l-Ts into the transcribed region (T+7+8/N) significantly disorders the template duplex, and thus binding of RNAP will be strongly interfered with because of its strict recognition. In addition, due to the accumulated steric hindrance, the rotation of Y639 is suppressed. In this case, insertion of NTP is sterically impossible, and thus transcription would be strongly interfered with  on the template.Since the template  and S4. red with . In addil-T was from Hanwei BioTechnologies . Normal deoxynucleotide phosphoramidites for automated DNA synthesis were obtained from Anhui WuhuHuaren Biotechnique.T7 RNAP was purchased from Beijing Biolink Biotechnology . RNase inhibitor was bought from Vazyme Biotech. The NTP mixtures were from Shenggong Co. . DTT was obtained from Solarbio Life Sciences, and l-T phosphoramidite was synthesized from l-T via 4,4'-dimethoxytrityl (DMT) deprotection of one hydroxyl group and following the reaction of the other hydroxyl group with phosphine reagent, and 1H nuclear magnetic resonance (NMR), 13C NMR, and 31P NMR (l-T phosphoramidite was introduced to the oligonucleotides using a 3400 DNA synthesizer (Applied Biosystems) with standard reagents and program. After incubation with concentrated ammonium hydroxide for 10 h at 50°C, the oligonucleotides were cleaved from solid supports. Then, the oligonucleotides were purified by reversed phase high-pressure liquid chromatography (RP-HPLC) with a Waters reverse phase C18 column . Oligonucleotide concentrations were determined by UV absorbance at 260 nm using a NanoDrop spectrophotometer (Thermo Scientific). Electrospray ionization mass spectrometry (ESI-MS) was used to identify the oligonucleotides , 6 mM MgCl2, 2 mM spermidine, 1 μM DNA template, 1 mM NTP mixtures, 5 mM DTT, and 1 U/μL RNA inhibitor. After the addition of T7 RNAP (50 U/μL), the reaction mixtures were gently vortexed and incubated at 37°C for 4 h to achieve transcripts. Then, the mixtures were mixed with an equal volume of 2× loading buffer  and incubated at 90°C for 5 min. A 10-μL aliquot of the mixture was subjected to electrophoresis on a 20% denaturing polyacrylamide gel containing 7 M urea at 100 V for 2 h in the presence of a 1× Tris/borate/EDTA (TBE) buffer. DNA templates and RNA products separated on the gel were stained with SYBR Gold  and visualized by the ChemiDoc XRS system (Bio-Rad).Double-stranded DNA templates were prepared by independently combining equimolar ratios of template and non-template strands in 10 mM NaCl, 40 mM Tris (pH 7.8), 6 mM MgCll-T triphosphate bypass %) as a function of reaction time. All reactions were performed in triplicate.For single time points, the transcription reactions were done as described above. The reaction mixtures were incubated for different time intervals  and stopped with an equal volume of 2× loading buffer . After incubation at 90°C for 5 min, products of transcription were resolved by denaturing gel electrophoresis  and visualized by the ChemiDoc XRS system (Bio-Rad). Quantitative analysis of the running start assays was performed by determining the relative lesion bypass efficiencies  of polymerase and were run at 37°C. Aliquots (10 μL) were taken at 4 h, mixed with an equal volume of 2× loading buffer used above, and electrophoresed on 20% denaturing polyacrylamide gel containing 7 M urea. Transcripts bands were quantitated using the ChemiDoc XRS system (Bio-Rad). Percent incorporation was translated into the rate of transcript synthesis as a function of [NTP], and rate data were fit by nonlinear least squares using the Michaelis-Menten equation to derive Km and kcat values.For the determination of kinetic parameters, transcription was carried out by changing the concentration of NTP mixtures according to previous reports.The mismatch was analyzed by a gel fidelity assay. After annealing at 95°C for 5 min, 2 μL of template-non-template complexes (10 μM), 2 μL of RNAP reaction buffer, 2 μL of T7 RNAP (50 U/μL), 2 μL of 50 mM DTT, 4 μL of GTP (2.5 mM), and 4 μL of diethyl pyrocarbonate (DEPC) water were mixed. Transcription was initiated by adding 4 μL of 2.5 mM CTP, ATP, or UTP, respectively. The mixtures were incubated at 37°C for 8 h. The polymerase reactions were quenched by the addition of 20 μL of loading buffer . After heating at 90°C for 5 min, the products were analyzed as described above.Q.L. performed the experiments and wrote the manuscript. Y. Ke helped with statistical analysis. Y.Kan helped conduct the gel fidelity analysis. X.T. helped with the synthesis of templates. X.L. helped analyze the data. Y.H. helped to conceive the research. L.W. conceived the research, analyze the data, and corrected the manuscript.The authors declare no competing interests.


CTCF plays a pivotal role in mediating chromatin interactions, but it does not do so alone. A number of factors have been reported to co-localize with CTCF and regulate CTCF loops, but no comprehensive analysis of binding partners has been performed. This prompted us to identify CTCF loop participants and regulators by co-localization analysis with CTCF. We screened all factors that had ChIP-seq data in humans by co-localization analysis with human super conserved CTCF (hscCTCF) binding sites, and identified many new factors that overlapped with hscCTCF binding sites. Combined with CTCF loop information, we observed that clustered factors could promote CTCF loops. After in-depth mining of each factor, we found that many factors might have the potential to promote CTCF loops. Our data further demonstrated that BHLHE40 affected CTCF loops by regulating CTCF binding. Together, this study revealed that many factors have the potential to participate in or regulate CTCF loops, and discovered a new role for BHLHE40 in modulating CTCF loop formation. The eukaryotic genome is organized into three dimensional topologies, which play an important role in gene regulation. It is becoming clear that factors exist to mediate chromosomal contacts, and CTCF has emerged as a leading mediator. CTCF is a ubiquitously expressed, highly conserved vertebrate nuclear protein ,2, whichWhile researchers have shown that CTCF can mediate chromatin interactions, how a molecular complex around CTCF is formed remains unclear. CTCF has been postulated to participate in chromatin loops in several ways, including forming sole CTCF–DNA interactions, but the best supported evidence indicates that CTCF forms multimeric complexes by interacting with other proteins . CTCF haHere, using a computational approach, we identified several well-known factors as well as many new factors that had a high overlap ratio with conserved CTCF binding sites. The more factors that colocalize with CTCF, the stronger loop intensity. These factors might be potential candidates to be involved in CTCF loops, and we go on to experimentally validate one of the novel CTCF binding partners, BHLHE40. Bioinformatics analysis and co-IP experiments indicated that BHLHE40 binding regions overlap with CTCF binding sites, and BHLHE40 forms a protein complex with CTCF. Furthermore, BHLHE40 loss-of-function reduces CTCF binding and disrupts CTCF-mediated long-range chromatin interactions. Taken together, we integrated multiple factor binding and chromatin open states to systemically analyze the features that are related to CTCF looping of DNA, and provide a new description of the organization of CTCF and its binding partners in cells.BHLHE40 were cloned into a pLKO.1-TRC vector. All the constructs were confirmed by Sanger sequencing, and the shRNA targeting sequences used in this study are described in Stable knockdown and overexpression cell lines were generated by using the lentiviral system. CTCF CDS (coding sequence) was cloned into a pSin-FLAG vector. shRNAs targeting HeLa-S3 and HEK293T cells were cultured in DMEM (Hyclone) supplemented with 10% fetal bovine serum. HeLa-S3 cells were infected with lentivirus. After 48 h infection, puromycin (2 μg/mL) was added to the medium to select positively infected cells.The following antibodies were used in this study: mouse anti-ACTIN antibody , rabbit anti-CTCF antibody , anti-BIOTIN HRP-linked antibody  for western blot, rabbit anti-BHLHE40 antibody  for western blot and ChIP experiments, Flag M2 beads  for Flag co-IP, Dynabeads M-280 Streptavidin  for BIOTIN ChIP-seq, rabbit anti-CTCF antibody  for CTCF HiChIP.The cells were resuspended and sonicated in RIPA buffer . Total soluble proteins were obtained by centrifugation at 12 000 rpm for 10 min. Samples were separated on SDS-PAGE gel and transferred onto a PVDF membrane (Millipore). The PVDF membrane was blocked with 5% milk in TBS-T (TBS with 0.05% Tween-20). Immunoblot analysis was performed with the indicated antibodies.2, 1 mM PMSF and 1 × protease inhibitor cocktails) for 10 min on ice followed by homogenization eight times with a loose pestle. Nuclei were centrifuged at 2000 × g for 10 min at 4°C, then the supernatant was discarded. Nuclear pellets were resuspended in 0.5 volume low salt buffer  and homogenized six times with a loose pestle. High salt buffer  was slowly added. Nuclei were rotated for 30 min and centrifuged at 14 000 × g for 15 min at 4°C. After that, the supernatant was collected. The insoluble material was re-suspended in 0.5 volume TGME buffer , homogenized with a loose pestle at least 20 times. Supernatant was collected after centrifugation at 14 000 × g for 15 min at 4°C and combined with previous supernatant. Then nuclear extract was incubated with Flag M2 or Dynabeads M-280 Streptavidin beads with rotation at 4°C overnight. After three washes with IP wash buffer , proteins bound on the M2 or Dynabeads M-280 Streptavidin beads were boiled with 1× SDS loading buffer for 10 min. And the eluted bound proteins were analyzed by western blot.To verify the interaction between CTCF and BHLHE40, nuclear extract (NE) of HeLa-S3 cells overexpressing FLAG tagged CTCF or BIOTIN tagged BHLHE40 was used. To make soluble nuclear extract, cells were washed once and swollen in hypotonic buffer . Quantitative real-time PCR was performed with SYBR green mixture (Genstar) on a CFX Real-Time System (Bio-Rad). The primers used in the RT-qPCR assays are listed in CTCF ChIA-PET data was downloaded from GEO database and analyzed with ChIA-PET2 software  using thConserved peaks from four ChIA-PET data were overlapped with ENCODE CTCF peaks, which were extracted from wgEncodeRegTfbsCellsV3.tab, peak overlapping was performed by bedtools intersect (v2.25)  to identAll ChIP-seq data collected from GEO database were first transformed to fastq files using fastq-dump (v2.8.2). Raw reads were subjected to Trim Galore (v0.4.4) to trim adaptors and low-quality reads. Trimmed reads were aligned to the hg19 human genome assembly using bowtie2 (v2.2.5)  with thePeaks from human protein factor ChIP-seq data, hscCTCF binding sites and genome-wide CTCF binding sites were all adjusted to 200 bp by extending 100 bp for each direction from the peak summit. Peak cobinding analysis has been performed by using bedtools intersect. By overlapping with hscCTCF binding sites, at most top 100,000 peaks were extracted to avoid false positive results.Candidate regulatory modules (CRMs) were generated by merging ChIP-seq peak data, similar to the procedure in a previous study . GeneralTo evaluate the correlation between ChIP enrichment and CTCF looping, CTCF loop anchor regions identified in CTCF ChIA-PET data were used, if two or more CTCF binding sites were contained in the same loop anchor region, these binding sites were filtered out, which ensured that each loop anchor corresponded to a unique CTCF binding site. CTCF loop strength mediated by each anchor was calculated by collecting all loop PET tags mediated by this anchor.2(coverage × 109/peak length × 106). CTCF loop strength was also transformed and expressed as log2. The Pearson correlation between them was calculated in R using the cor function. When the peak numbers were <1000 or the P-value from Pearson correlation was larger than 0.01, the correlation between them was considered as unreliable, and −log10 was set to zero. P-value is further adjusted for multiple comparisons with Bonferroni correction.The DNase signal, factor binding strength or ChIP enrichment of histone markers were calculated as below. The coverage of their peak regions was first extracted using bedtools coverage, then normalized as logSince each chromatin loop is connected with two chromatin anchor regions, we hypothesized that the factors binding at the two anchors of each loop might form a complex to promote loop formation. We combined any two factors from each paired loop anchor as a factor pair, representing all possible direct or indirect protein interactions, and then gave each pair a score, which was the original loop strength in the cells, and finally pooled all factor pairs together with the scores summed up for the same factor pair. Factor pairs with their scores were further integrated into a network in cytoscape software . The thi7 cells were crosslinked with 1% formaldehyde for 10 min at room temperature, then the reaction was stopped by adding glycine . Crosslinked cells were lysed in ChIP SDS lysis buffer  containing 1× protease inhibitor cocktail and PMSF, then sonicated to achieve a chromatin size of 200-400 bp. After sonication, the supernatant was diluted with IP buffer and then co-incubated with protein A and protein G dynabeads (1:1 mix) and the indicated antibodies at 4°C overnight with rotation. Antibody bound DNA was subsequently washed with low salt wash buffer , high salt wash buffer , LiCl wash buffer  once, respectively, and then TE wash buffer  twice. ChIPed DNA was reverse-crosslinked and purified for DNA library construction followed by sequencing or ChIP-qPCR analysis. Primers used for ChIP-qPCR were listed in ® V2. After PCR library amplification, size selection of adaptor-ligated DNA was performed using Agecourt AMPure XP Beads (Beckman Coulter). The libraries were diluted at a proper concentration for sequencing and finally sequenced on HiSeq X-Ten .ChIP experiments were performed as previously described . Briefly2(fold_change) >1 and P-value <0.01 were considered as significantly differential binding sites, which were used for further analysis. Results from DiffBind were listed in Raw reads are subjected to Trim Galore to remove adaptors and low-quality reads, then trimmed reads were mapped to female hg19 genome using bowtie2 with parameters “--very-sensitive --end-to-end --no-unal", proper aligned and high quality mapped (MAPQ >30) reads were selected and reads in blacklist region or chrM were further removed, duplicates were removed using Picard. For CTCF ChIP-seq in HeLa-S3 cells with control shRNA, BHLHE40-depleted cells, unique high-quality reads were uniformly subsampled to 20 million reads using set.seed (9999) and sample function in R. Peaks were called by MACS2 with the parameter “-q 0.01". For BHLHE40 and BIOTIN-BHLHE40 ChIP-seq data, peaks were called by MACS2 with default parameters “-q 0.05". For all data, normalized signal tracks were generated by using bamCoverage from deeptools with parameter “--normalizeUsing RPGC". Differential CTCF binding sites were identified using Diffbind package , bindingq-value <0.05) and with fold change >2. These differentially expressed genes were listed in All RNA-seq experiments have two biological replicates. Raw reads were firstly trimmed to remove the adaptors and low-quality reads by using Trim Galore, then mapped to human genome (hg19 sourced from UCSC genome browser) using STAR (v2.5.2a) , gene exMboI restriction enzyme  was added at 37°C for 2 h to digest the nuclei, and heat inactivated at 62°C for 20 min. After filling in the restriction fragment overhangs and marking the DNA ends with biotin, in situ contact was generated by proximity ligation. The nuclei with in situ generated contacts were pelleted at 2500 × g for 5 min at room temperature and the nuclear pellet was resuspended in nuclear lysis buffer  for sonication, and clarified by centrifugation at 16 100 × g at 4°C for 15 min. The clarified samples were transferred to a new tube and diluted with ChIP dilution buffer  for ChIP procedures. ChIPed DNA was quantified by Qubit (Thermo Fisher) to estimate the amount of Tn5 (Illumina) needed to generate libraries at the correct size distribution. 150 ng of ChIPed DNA was taken into the biotin capture step and tagmented with Tn5. Finally, the tagmented DNA containing beads was PCR amplified and size selected with AMPure XP beads (Beckman). After size selection, libraries were quantified with qPCR against Illumina primers and/or bioanalyzer. Libraries were paired-end sequenced with read lengths of 150 bp.The HiChIP protocol was performed as previously described ,44 with MboI restriction fragments. Valid reads from HiC-Pro results were further processed to call loops with hichipper  . Sra datTxDb.Hsapiens.UCSC.hg19.knownGene package has been used to extract ± 500 bp regions of the TSS of all transcripts as candidate promoter regions. Previous defined regions for EnhG1, EnhG2, EnhA1, EnhA2, EnhWk in HeLa-S3 cells . Raw datLoops were annotated to the promoter and enhancer regions with GenomicInteractions package , then prTo identify factors participating in CTCF-mediated chromatin interactions, we collected CTCF co-localized factors using ChIP-seq data for chromatin-associated proteins. CTCF ChIP-seq data from the ENCODE project, which contains 99 CTCF ChIP-seq datasets from 70 cell types or treatments, were utilized . We thenExcept the ChIP-seq data for the above explored factors, there is still a large amount of untapped ChIP-seq data , which mWe prepared conserved CTCF binding sites by integrating all CTCF ChIP-seq data from the ENCODE project with conserved CTCF ChIA-PET peaks from different cell lines  to ensure that the binding sites could mediate chromatin loops . In totaTo further explore the relationship between CTCF co-binding factors and CTCF loops, we defined CTCF candidate regulatory modules (CRMs) , similar to a previous study , which c10(FDR) <20 and analyzed the relationship between DNA binding and loop strength for the remaining co-factors. As expected, the cohesin subunit RAD21 emerged as the co-factor with the highest score, as it is critical for CTCF loops . This strategy does not depend on correlation analysis, which might be biased by the value of looping strength or CTCF binding strength. Our data showed that many factors such as CTCF, cohesin subunits, MAX, MAZ and BHLHE40 frequently existed at both of the two loop anchors Figure . These dTo validate our computational analysis for CTCF co-binding factors, we selected BHLHE40 for further study. We first knocked down BHLHE40 using specific shRNAs Figure , and theThe reduction of CTCF binding by loss of BHLHE40 might lead to changes in CTCF loops. To examine this, we performed CTCF HiChIP experiments in both control shRNA and BHLHE40-depleted cells. CTCF HiChIP data in control cells were first compared to our previously published HiChIP data, the results indicated that they were well correlated . FurtherThe DNA sequences of the eukaryotic genome form a complex three-dimensional architecture, and CTCF serves as a chromatin looping mediator to build the higher-order genome structure ,69. IdenIn addition to previously reported co-factors, such as RAD21 and SMARCA4, we identified many new factors that could overlap strongly with CTCF, and these factors provide a new opportunity to study the mechanism of CTCF loop dynamics. Among these factors, we found that the overlap ratio of cohesin subunits in different cells was relatively high and stable, but the overlap ratio of many other factors fluctuated in different cell types. This might be due to the different ChIP enrichment for each factor or CTCF, which resulted in different peak number and caused variation of the overlap ratio. Except for ChIP-seq data quality, context-dependent factor binding would also lead to large differences in CTCF co-localization. On the one hand, although there are many conserved CTCF binding sites, the cell-specific CTCF binding sites still have different fractions in different cell types ,70. On tIn addition to co-localization analysis, we explored information related to CTCF loops in four specific cell types. We found that factors clustered with CTCF in the loop anchor regions, and the anchor with more factors had a greater capacity to mediate stronger loops. And we also observed that many CTCF binding sites were located at gene promoter and enhancer regions with strong histone modifications, where chromatin loops were usually mediated by mediator complex. CTCF could mediate long-range chromatin interactions, and have long been known to have enhancer-blocking function to inactivate important genes . DiffereOverall, our study used the unique properties of CTCF to computationally predict co-factors for CTCF. We went on to experimentally validate BHLHE40 as a co-factor of CTCF, and showed that it did co-localize with CTCF and knockdown of BHLHE40 led to a reduction in CTCF binding, and a reduction in CTCF-mediated loop strength. Nonetheless, our identified co-factors for CTCF may both positively and negatively regulate CTCF-mediated functions and future research will reveal the roles of these multi-component CTCF complexes.Our sequencing data for ChIP-seq, RNA-seq and HiChIP have been deposited in the Gene Expression Omnibus and the accession numbers are: GSE137848, GSE137849, GSE137850, respectively. All other relevant data supporting the key findings of this study are available within the article and supplementary information files.gkaa705_Supplemental_FilesClick here for additional data file.


Deciphering the molecular mechanisms underpinning myoblast differentiation is a critical step in developing the best strategy to promote muscle regeneration in patients suffering from muscle-related diseases. We have previously established that a rexinoid x receptor (RXR)-selective agonist, bexarotene, enhances the differentiation and fusion of myoblasts through a direct regulation of MyoD expression, coupled with an augmentation of myogenin protein. Here, we found that RXR signaling associates with the distribution of myogenin at poised enhancers and a distinct E-box motif. We also found an association of myogenin with rexinoid-responsive gene expression and identified an epigenetic signature related to histone acetyltransferase p300. Moreover, RXR signaling augments residue-specific histone acetylation at enhancers co-occupied by p300 and myogenin. Thus, genomic distribution of transcriptional regulators is an important designate for identifying novel targets as well as developing therapeutics that modulate epigenetic landscape in a selective manner to promote muscle regeneration. Khilji et al analyse how myogenin distribution changes in differentiating C2C12 myoblasts using ChIP-sequencing. They find that rexinoid x receptor signalling promotes myogenin localisation to poised enhancers and the association of myogenin with p300-mediated histone acetylation, providing insights into epigenetic mechanism of myogenic differentiation. Histone acetylation is one form of epigenetic regulation that affects DNA accessibility for lineage-specific transcription factors to direct the differentiation of stem cells into distinct lineages, including skeletal myoblasts2. Amongst the MRFs, Myf5 and MyoD are considered as determination factors since they regulate the proliferation and early differentiation of myoblasts, while myogenin functions downstream of MyoD to activate muscle gene expression and is critical for the differentiation and fusion of myoblasts into multinucleated myotubes3. While Myf5 and MyoD collaborate with partial redundancy in the development of open chromatin formation at muscle-specific loci, myogenin has a unique role in transcription from genes that have been primed4. At the structural level, MRFs are a family of basic helix-loop-helix (bHLH) transcription factors that bind to a conserved core hexanucleotide motif (CANNTG) known as E-box5. MRF binding is modulated by E-box accessibility, central dinucleotide pair and flanking sequences, which may vary between biological systems and conditions8. As such, the myogenic program is genetically governed by E-box components, whereas E-box accessibility is controlled epigenetically9.The formation of skeletal muscle requires temporal-spatial expression of myogenic regulatory factors (MRFs) that overlap in their ability to convert stem cells into the myoblast lineage10. During myoblast differentiation, an overall decrease in acetylation of H3K9, H3K18, and H3K2712 is accompanied by an increase in H4 acetylation, specifically at MyoD targets12. Overexpression of myogenin in differentiating C2C12 myoblasts correlates to hyperacetylation of H4, which is associated specifically to late muscle genes13. The global decrease in histone acetylation during myoblast differentiation likely reflects a downregulation of proliferation genes, whereas histone acetylation increases at loci important for differentiation. For example, the regulatory regions of Myod and Myf5 are associated with an increase in H3K18 and H3K27 acetylation, connected specifically to the histone acetyl-transferase (HAT) activity of p30015.Genome-wide profiling of histone marks has allowed segmentation of the myoblast genome into distinct chromatin states characterized by a combination of histone modification patterns present in those regions16, p300 is a critical transcriptional co-activator of a myriad of transcription factors involved in many cellular processes including proliferation and differentiation17. It instigates chromatin remodeling as a HAT, but acts also as a molecular scaffold, bridging different DNA-binding proteins and activators with the basal transcriptional machinery20. Particularly, H3K18 and H3K27 are the acetylation targets of p300 prior to RNA polymerase II recruitment21. While p300 can be found at the promoter regions22, its occupancy is regarded as the best chromatin signature of enhancers24 which can be further categorized as poised, marked by H3K4me1/2, or active, signified by H3K27ac in addition to H3K4me1/226. In contrast, H3K27me3 is tightly associated with inactive genes and has a predictive nature of gene silencing27. We have recently utilized different histone marks within the proliferating myoblasts to generate a 14-state chromatin state model to characterize loci-specific histone acetylation at p3000-associated enhancers in early myoblast differentiation, particularly when it is recruited by MyoD12. Our data presents a model of histone acetylation increases at distinct genomic loci despite a global decrease in histone acetylation as myoblasts differentiate12.Initially identified as an E1A-associated protein28. As a member of this family, retinoid X receptor (RXR) binds to DNA either as a homodimer or heterodimer with other family members, making it a partaker of a large array of signaling pathways and a significant modulator of drug targets. We have previously reported that a RXR-selective agonist, bexarotene, enhances the differentiation and fusion of myoblasts through the function of RXR as a transcription factor29. In addition, this enhancement is mediated largely through a direct regulation of MyoD gene expression and coupled with an augmentation of myogenin protein10. While MyoD is required for early myogenic differentiation, the activation of a subset of late muscle-specific genes occurs most efficiently in the presence of myogenin that amplifies the expression of genes previously primed by MyoD30.Nuclear receptor superfamily of transcription factors regulate gene expression in response to steroids, lipids, and other small molecule ligandsNonetheless, the molecular pathways of transcription partners, co-activators and chromatin state dynamics underlying myogenin-mediated myoblast differentiation in response to RXR signaling remain an important but poorly understood issue. Here, we delineate how RXR-selective signaling affects genome-wide myogenin binding characteristics and dissect the molecular pathways through which RXR-selective signaling promotes myoblast differentiation.29. To study the molecular pathways underlying myogenin-mediated myoblast differentiation in the context of RXR signaling, we examined genome-wide myogenin localization using chromatin immunoprecipitation coupled with deep-sequencing (ChIP-seq), in the well-established myoblast model32. As shown in Supplementary Fig. We have previously reported that a RXR-selective agonist, bexarotene, enhances the differentiation and fusion of skeletal myoblasts into mature myotubes, while augmenting the protein level of myogenin, a terminal differentiation factor33 of myogenin read signals displayed a distinct enrichment at myogenic loci . Comparing to 40% of myogenin loci unique to control, only 15% of loci unique to bexarotene were found to be within 1 kb of a promoter  harbor the E-box motif as differentiation proceeds from 24 h to 7 day, similar to myoblasts differentiated with bexarotene for 24 h Fig. . We also4 h Fig. . In addi4 h Fig. .Next, we quantified the number of E-box motifs per myogenin peak, and found that 47% of myogenin loci in myoblasts differentiated with bexarotene for 24 h contained 2 or more E-boxes similar to 58% and 43% of myogenin loci in 7-day C2C12 and 24-h primary myoblast differentiation respectively Fig. . In cont38. However, among myogenin loci unique to bexarotene, we identified a double-E-box, two canonical E-boxes, separated by 4 or 6 bp . A thorough understanding of the epigenetic mechanisms that regulate myogenic fate transitions will allow the development of novel therapeutics to treat muscle-related diseases, as the ability to control endogenous epigenetic modifiers will enable specific changes in transcriptional activity of genes important for myogenesis.2. To induce differentiation, cells at 70–80% confluence were switched to differentiation medium (DM), DMEM supplemented with 2% horse serum, and cultured for 24 h. Bexarotene (LC Laboratories) was added to DM at a final concentration of 50 nm for treatment.C2C12 mouse myoblasts (ATCC) were maintained in growth medium (GM), consisting of Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% fetal bovine serum, 100 units/ml penicillin and 100 μg/ml streptomycin, at 37 °C with 5% CO67. Protein concentrations were determined by the Bradford Method (Bio-Rad). The proteins were then separated by SDS-PAGE and transferred to an Immun-Blot PVDF membrane. Bio-Rad ChemiDoc MP System was used to capture chemiluminescent images, and the protein bands were quantified using Scion Image (Scion Corporation). The primary antibodies used for western analysis were from hybridoma E7 for β-tubulin and hybridoma F5D for myogenin.Cells were lysed in whole cell extract buffer , at 4 °C for 30 min with rotation. Cell extracts were prepared as previously described–ΔΔCT. Experiments were repeated at least three times. The following primers were used: myomixer primer forward, GTTAGAACTGGTGAGCAGGAG and reverse, CCATCGGGAGCAATGGAA; Mybph primer forward, ACTTAGCCACCACCACCAAG and reverse, GGAGTGGAGGTATGGTCAGC; TBP primer forward, TCATGGACCAGAACAACAGC, and reverse, GCTGTGGAGTAAGTCCTGTGC.Total RNA from C2C12 cells was isolated by using the GeneJET RNA Purification Kit (ThermoFisher Scientific) and quantified by Nanodrop (ND-1000). An equal amount of RNA was reverse transcribed into cDNA by using a High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) in accordance with the manufacturer’s instructions. SYBR® Green PCR Master Mix and HotStarTaq DNA polymerase (Qiagen) were used for qPCR on a CFX96 Touch Real-Time PCR Detection System (BioRad). The data was analyzed by using the threshold cycle comparative method, normalized to the expression of TATA-Binding Protein (TBP), using the formula 268. Chromatin immunoprecipitation was performed with antibodies obtained from Santa Cruz against myogenin (sc-12732) and p300 (sc-584). The immunoprecipitants were purified using a MiniElute PCR Purification kit (Qiagen). ChIP-seq libraries were prepared and sequenced on an Illumina HiSeq 2000 (p300 and H3K27me3) or Illumina HiSeq 4000 (myogenin) as single-end 50 bp reads. For p300 and H3K27me3, reads were mapped to the mm9 genome using Bowtie69 v0.12.7 allowing for three mismatches and reporting the single best alignment per 50 bp read. For myogenin, sequence reads were aligned to the mouse mm9 reference genome build using BWA-Mem70 v0.7.10 with default parameters. Duplicate reads were removed utilizing the Picard package v2.6.0. Genome-wide read coverage and enrichment was assessed using deepTOOLS71 fingerprint plots where the corresponding x- and y-axes for a point of intersection, denote the percentage of genome coverage and the percentage of all uniquely aligned reads, respectively. Peak calling was performed with HOMER72 v4.10 with -style factor and FDR of 1.0 × 10−4. The approximate IP efficiency calculated by HOMER describes the fraction of tags found in peaks compared with the genomic background and is utilized as one measure of ChIP efficacy.Following 24 h of differentiation, cells were fixed, crosslinked, and sonicated with a Bioruptor as previously describedDe novo motif discovery was performed with MEME using the “meme-pal” option with input sequences of 500 bps surrounding the peak center. The mergePeaks tool from HOMER was utilized for co-localization of peaks (-d given) and the findMotifsGenome tool for de novo motif discovery on the 200 bp surrounding the peak centers. The annotatePeaks.pl script was employed for quantification of motif enrichment and for peak annotation, where HOMER compares the distance from a peak to the RefSeq catalog of TSS of nearby genes, and reports the closest TSS as the associated gene.73 which calculates the coverage vectors for each query region based on specified alignment files. Coverage data is normalized for equal length and vectors are normalized against the corresponding library size, to allow comparisons of datasets with differences in sequencing depth. Default values for all analyses were used unless specified. IGV v2.3.97 was used for data browsing and representative snapshots.The enrichment of histone acetylation at specified loci or TSSs was calculated with ngs.plotmyomixer locus forward, GAACAGCTGTGTTCTGGCAC and reverse, TGGGGAATTCCTGCACATGG; Mybph locus forward, AGTGCCTGCTCAGCTAATCC and reverse, CTGAGCCTCCTAAGCAGCAA.Following ChIP, qPCR was performed in triplicate reactions using the SYBR green method with locus specific primers. A standard curve was created for each set of primers with input DNA, followed by quantification of the abundance of immunoprecipitated target DNA in relation to input chromatin DNA. Each qChIP was repeated at least three times. Antibodies against p300 and myogenin were the same as for Western. Primer pairs used for qPCR amplification were as follows: t-test. Non-normally distributed data were analyzed by non-parametric two-sided Wilcoxon rank sum tests. A p < 0.05 was considered statistically significant. Statistical details and number of replicates are indicated in the figure legends.All statistical analyses were performed using The R Project for Statistical Computing or Microsoft Excel. Normally distributed data were analyzed by a two-tailed Student’s Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Reporting SummaryPeer Review File