The activities of MYC, the androgen receptor, and its associated pioneer factors demonstrate substantial reprogramming between early and advanced prostate cancer. Although previous studies have shown a shift in cellular metabolic requirements associated with prostate cancer progression, the epigenetic regulation of these processes is incompletely described. Here, we have integrated chromatin immunoprecipitation sequencing (ChIP-seq) and whole-transcriptome sequencing to identify novel regulators of metabolism in advanced prostate tumors characterized by elevated MYC activity.MYC expression. In a cohort of 177 laser-capture microdissected foci of prostate tumors, KMT2A expression was positively correlated with MYC activity, AR activity, and HOXB13 expression, but decreased with tumor grade severity. However, KMT2A expression was negatively correlated with these factors in 25 LuCaP patient-derived xenograft models of advanced prostate cancer and 99 laser-capture microdissected foci of metastatic castration-resistant prostate cancer. Stratified by KMT2A expression, ChIP-seq against AR and HOXB13 in 15 LuCaP patient-derived xenografts showed an inverse association with sites involving genes implicated in lipid metabolism, including the arachidonic acid metabolic enzyme PLA2G4F. LuCaP patient-derived xenograft models grown as organoids recapitulated the inverse association between KMT2A expression and fluorine-18 labeled arachidonic acid uptake in vitro.Using ChIP-seq against MYC, HOXB13, and AR in LNCaP cells, we observed redistribution of co-bound sites suggestive of differential KMT2A activity as a function of Our study demonstrates that the epigenetic activity of transcription factor oncogenes exhibits a shift during prostate cancer progression with distinctive phenotypic effects on metabolism. These epigenetically driven changes in lipid metabolism may serve as novel targets for the development of novel imaging agents and therapeutics.The online version contains supplementary material available at 10.1007/s12672-022-00565-3. MYC proto-oncogene reactivates and opposes the antiproliferative functions of AR to drive continued cell growth ArA) over a two-hour time course in LuCaP PDX’s grown as organoids. As presented in Fig. 18F]ArA uptake varied across LuCaPs, ranging from 6 to 88% per million cells in KMT2A-high LuCaP models and 27–154% per million cells in the KMT2A-low LuCaP models. Overall, KMT2A-low models demonstrated greater median [18F]ArA uptake at two hours (54%) than the KMT2A-high models (22%)  isoform were specific.This current study has two important limitations. First, we observed a switch in the association between Despite these limitations, we have demonstrated concordance between transcriptional and chromatin readouts of TF activity within the same panel of PDX models, with further qualification of potential lipid metabolic differences using the PDXs in an in vitro functional assay. Our findings indicate that ArA metabolism is specifically sensitive to AR and MYC activity during PCa progression.KMT2A-low prostate cancers.We have reported that ArA metabolism and uptake are enriched in MYC-high prostate tumors. This finding has implications for the subset of treatment resistant prostate cancers that maintain high MYC activity and develop resistance to both hormonal and cytotoxic chemotherapies. Future studies are needed to validate these findings in larger cohorts, assess the viability of targeting ArA metabolism therapeutically, and determine whether ArA-based imaging agents demonstrate specific uptake in MYC-high/MYC expression as described in ArA uptake assays.LuCaP xenografts were processed and cultured as organoids as described previously . Organoi18F]ArA was prepared following as previously described with minor modifications [18F]TBAF in acetonitrile at 120 °C for 20 min followed by hydrolysis with potassium hydroxide (120 °C for 10 min) to produce 20-[18F]ArA. The overall radiochemical yields were 15–24%  with a molar activity of 59–163 GBq/µmol (n > 6).[ications . Briefly18F]ArA in BMCM for 120 min at 37 °C/5% CO2, washed twice with PBS to remove residual unincorporated [18F]ArA, and resuspended in 1 mL trypsin as a single-cell suspension. Cells were counted using acridine orange/propidium iodide cell counting dye. [18F]ArA uptake was determined by PerkinElmer 2480 Wizard3 Gamma Counter. For each sample, percent uptake per 106 live cells was calculated as follows:Organoid cultures were radiolabeled with 2 μCi [U tests.Statistical analyses were performed with GraphPad Prism version 9 (GraphPad Software) for Mac. Associations between factors were measured using Pearson or Spearman correlations. Comparisons of single factors between dichotomized samples was performed using Mann–Whitney Supplementary file 1 (XLSX 21 KB)Supplementary file 2 (XLSX 112 KB)Supplementary file 3 (PDF 1537 KB)Below is the link to the electronic supplementary material.


Insl3 gene expression in Leydig cells is not hormonally regulated but rather is constitutively expressed. The regulatory region of the Insl3 gene has been described in various species; moreover, functional studies have revealed that the Insl3 promoter is regulated by various transcription factors that include the nuclear receptors AR, NUR77, COUP-TFII, LRH1, and SF1, as well as the Krüppel-like factor KLF6. However, these transcription factors are also found in several tissues that do not express Insl3, indicating that other, yet unidentified factors, must be involved to drive Insl3 expression specifically in Leydig cells. Through a fine functional promoter analysis, we have identified a 35-bp region that is responsible for conferring 70% of the activity of the mouse Insl3 promoter in Leydig cells. All tri- and dinucleotide mutations introduced dramatically reduced Insl3 promoter activity, indicating that the entire 35-bp sequence is required. Nuclear proteins from MA-10 Leydig cells bound specifically to the 35-bp region. The 35-bp sequence contains GC- and GA-rich motifs as well as potential binding elements for members of the CREB, C/EBP, AP1, AP2, and NF-κB families. The Insl3 promoter was indeed activated 2-fold by NF-κB p50 but not by other transcription factors tested. These results help to further define the regulation of Insl3 gene transcription in Leydig cells.The peptide hormone insulin-like 3 (INSL3) is produced almost exclusively by Leydig cells of the male gonad. INSL3 has several functions such as fetal testis descent and bone metabolism in adults.  Leydig cells located in the testis produce testosterone and insulin-like 3 (INSL3), two hormones essential for male sex differentiation and reproductive function. More specifically, testosterone is required to masculinize the male embryo during fetal life, and postnatally to complete internal and external male organ development as well as for the initiation and maintenance of spermatogenesis . INSL3 rInsl3 gene is composed of two exons (219 and 404 bp) separated by a 739-bp intron. The Insl3 gene is atypically located entirely within the last intron of the Jak3 gene [Insl3 gene expression in Leydig cells are believed to be located within a short promoter region of about 1000 bp. The genomic region corresponding to the Insl3 promoter has been isolated from rat [Insl3 promoter activity in Leydig cells. These include the Krüppel-like factor KLF6 [Insl3 promoter has also been reported. However, most of these transcription factors are also found in cell types that do not express the Insl3 gene, such as Sertoli and adrenal cells, indicating that additional transcription factors are likely involved in directing Insl3 expression in Leydig cells. In the present study, we have identified a 35-bp regulatory region bound by nuclear proteins that is essential for mouse Insl3 promoter activity in MA-10 Leydig cells. The ak3 gene ,13,14. Cfrom rat ,15, humafrom rat , dog [17from rat . Functiotor KLF6  as well tor KLF6 , LRH1 ) was used to determine if protein(s) from Leydig cell nuclear extracts can bind to the 35-bp region. As shown in Insl3 promoter region and that the nucleotides mutated in mutants M1, M3, M4, and to a lesser extent M6, are important for this binding.The linker-scanning site-directed mutagenesis data  establisInsl3 promoter.The 35-bp nucleotide sequence (5′- AAT GTT GGG GAG CGG CTC CTG GCA CAG CGC CGC AC) contains potential binding sites for zinc finger-containing transcription factors known to bind GC- and GA-rich motifs. These include RBP2 (retinoblastoma-binding protein 2), GLI (GLI-Krüppel family zinc finger), IKZF1 (IKAROS family zinc finger 1), SP1 (specificity protein 1), KLF6 (Krüppel-like factor 6), HLTF (helicase-like transcription factor), ZEB1 (zinc finger E-box binding homeobox 1), and HAND1 . We, therefore, used oligonucleotides containing a consensus binding sequence for each of these transcription factors in EMSAs. As shown in Insl3 promoter in MA-10 Leydig cells. As shown in Insl3 promoter was activated by SF1 and COUP-TFII as previously reported [Insl3 promoter construct . We, threported ,20,25,26onstruct A,B. In tobserved B. Combinobserved A,B. Howeobserved A, and byobserved B, was abInsl3 promoter deletion constructs. As shown in Next, to locate the NF-κB p50 responsive region, MA-10 Leydig cells were transfected with Insl3 gene expression in Leydig cells, most are also present in cells that do not express Insl3 indicating that additional, yet unidentified transcription factors are also required to direct Insl3 expression in Leydig cells. In the present study, we have located and characterized new regulatory elements important for Insl3 promoter activity in Leydig cells. The peptide hormone INSL3 produced by Leydig cells plays important roles in male reproductive development and function (reviewed in ). AlthouInsl3 [Insl3 gene transcription [In our study, we made use of the mouse MA-10 Leydig cell line , which aInsl3 ,37,38,39cription .Insl3 transcription start site. Because the entire Insl3 gene is located within the last intron of the Jak3 gene [Jak3 gene. Our 5′ progressive deletion analysis of the mouse Insl3 −1082 bp regulatory region revealed that deletion of up to −186 bp did not significantly affect Insl3 promoter activity in MA-10 Leydig cells. This is similar to a previous study performed in another Leydig cell line, the MLTC-1 cells, where a construct of −188 bp retained all mouse Insl3 promoter activity [Insl3 promoter contained within −157 bp was required for Leydig-specific transcription [INSL3 promoter also showed that truncation to −132 bp still maintained full promoter activity in both MA-10 and MLTC-1 Leydig cells but not non-steroidogenic cells [Insl3 promoter from various rodents contains an additional ~50 bp compared to the INSL3 promoter from primates, as revealed by the alignment of the INSL3 promoter sequence from various species  strongly supports the involvement of bHLH family members. In addition, mutations that target GC/GA-rich motifs reduce the activity of both the mouse (present work) and human [INSL3 promoter in Leydig cells. This prompted us to assess whether proteins known to bind to GC/GA-rich motifs could bind to the 35-bp region of the mouse Insl3 promoter. Although a protein complex from MA-10 Leydig cells specifically bound to the 35-bp region as identified by EMSA, competition experiments using several oligonucleotides containing binding sites for various transcription factors known to bind GC/GA-rich sequences such as RBP2, GLI, IKZF1, SP1, KLF6, HLTF, ZEB1, and HAND1, failed to displace the binding. This indicates that the protein complex binding to the 35-bp region does not contain members of these transcription factor families. Through fine promoter deletions, we identified a 35-bp region located between −186 and −151 bp that is essential for maximal  species . In addiOur protein–DNA interaction assays indicated that the protein(s) responsible for the activity of the 35-bp region might not be zinc finger-containing transcription factors recognizing GC/GA-rich motifs. Of all the mutations introduced in the 35-bp region and tested by EMSA, mutants M1, M3, M4, and M6 failed displace the binding complex. This indicates that the integrity of these sequences is essential for protein binding, and thus, provides clues regarding the nature of the transcription factor that could bind to these sequences. Insl3 promoter, either by themselves or in combination with other transcription factors. On the other hand, activity of the −1082 bp Insl3 promoter was increased by 2-fold in the presence of NF-κB p50, supporting a role for this transcription factor in Insl3 gene transcription in Leydig cells. Furthermore, the NF-κB p50-dependent activation of the Insl3 promoter required the 35-bp region as a deletion construct lacking this region was no longer activated by NF-κB p50. Additional work such as performing EMSAs and competition assays using a consensus NF-κB p50 motif, using mutated Insl3 promoter constructs, as well as testing other potential partners, would be needed to fully understand the mechanism of NF-κB p50 action in the regulation of Insl3 promoter activity in Leydig cells.In silico analysis of the sequence surrounding mutant M1 identified potential binding sites for members of the CREB, C/EBP, and NF-κB families of transcription factors, which are expressed in Leydig cells where they regulate gene expression ,43,44,45Insl3 promoter in MA-10 Leydig cells was the sequence 5′-TCCTGGCACA-3′ located between −170 and −161 bp. Mutation of this sequence (mutants M3 and M4) prevented protein binding and reduced Insl3 promoter activity by 70%. In silico analysis of this sequence predicted that it could be recognized by members of the AP1 and AP2 families. Several AP1 members are known to be expressed in Leydig cells, including cJUN, a well-characterized activator of several genes . AP2 faiewed in . DespiteInsl3 promoter activity in Leydig cells.In conclusion, although our present work has identified a key 35-bp regulatory region, additional work is needed to fully decipher the transcription factors acting via this 35-bp element responsible for 70% of Insl3 promoter constructs −1082 to +5 bp and −186 to +5 bp were previously described [Insl3 promoter deletions to −973 bp, −791 bp, −591 bp, −151 bp, −141 bp, −131 bp, −120 bp, −111 bp, and −79 bp were obtained by PCR using the −1082 bp Insl3 promoter as a template, along the primers listed in The mouse escribed ,25. MousVarious trinucleotide and dinucleotide mutant constructs in the context of the −1082 bp reporter were generated using the QuikChange XL mutagenesis kit , as recommended by the manufacturer, along with the oligonucleotides listed in All the deletion and mutation reporter constructs were confirmed by sequencing . The following expression plasmids were obtained from different research groups: SF1/NR5A1 , cJUN 5, CREB 5, C/EBPβ 2 in a humidified incubator. MA-10 Leydig cells were validated by morphology and by quantifying steroidogenic output, as previously described [Insl3 promoter construct fused to the Firefly luciferase reporter gene, 20 ng of phRL-TK Renilla luciferase expression vector used as an internal control for transfection efficiency, and pSP64 as carrier DNA up to 1.5 μg/well. For transactivation assays, cells were transfected with 400 ng of the mouse Insl3 −1082/+5 bp reporter vector along with 100 ng of an empty expression vector (pcDNA3.1 as control), or expression vectors for the various transcription factors (50 ng) individually , or the combination of transcription factors (50 ng each). The culture media were renewed 3 h before and 16 h after the transfection. Two days after the transfection, MA-10 Leydig cells were harvested and luciferase activities were measured using the Dual Luciferase Assay System  and the Luminoskan Ascent luminometer . The data reported represent the average of at least four experiments, using different DNA preparations, and each performed in duplicate.Mouse MA-10 Leydig cells  were grown in DMEM/F12 medium supplemented with 2.438 g/L sodium bicarbonate, 3.57 g/L HEPES, and 15% horse serum on gelatin-coated plates. Penicillin and streptomycin sulphate were added to the cell culture media to a final concentration of 50 mg/L, and cells were kept at 37 °C, 5% COescribed ,60,61,62escribed ,64, or tescribed ,35,48,65Nuclear extracts from MA-10 Leydig cells were prepared using the method described by Schreiber , with th2, 100 ng BSA, 10% glycerol, and 500 ng poly(dI-dC) for 1 h on ice. A 32P-labeled 42-bp double-stranded oligonucleotide containing the 35 bp (−186/−151 bp) region of the mouse Insl3 promoter was used as a probe (5′- GTT GGG GAG CGG CTC CTG GCA CAG CGC CGC ACC TGG GAG AGG -3′). Competition experiments were performed using 5× and 25× (molar excess) of unlabeled double-stranded oligonucleotides corresponding to the probe or harboring various mutations (shown in lowercase) in the 35-bp (−186/−151 bp) region of the mouse Insl3 promoter (Electromobility shift assays (EMSAs) were performed as previously described ,69,70,71promoter . Competipromoter .Insl3 promoter was analyzed using the bioinformatic tools TFbind  [http://alggen.lsi.upc.es/cgi-bin/promo_v3/promo/promoinit.cgi?dirDB=TF_8.3) [https://www.ebi.ac.uk/Tools/msa/clustalo/) [To identify binding sites for potential transcription factors, the 35-bp region of the mouse er 2022)  and PROM=TF_8.3) ,82. Multustalo/) .https://www.statskingdom.com/kruskal-wallis-calculator.html, accessed on 7 October 2022). To identify significant differences between multiple groups, statistical analyses were carried out using a nonparametric Kruskal–Wallis one-way ANOVA on ranks followed by a Mann–Whitney U test to detect differences between pairs. For all statistical analyses, p < 0.05 was considered significant.Statistical analyses were carried out using Statistics Calculators (Statistics Kingdom, Melbourne, Australia, November 2017,


Here, Taylor et al. investigated how distal regulatory elements control gene transcription and chromatin topology in lineage specification during development. Through allele-specific genome editing and chromatin interaction analyses of the Sox2 locus in mouse embryonic stem cells, they found a striking disconnection between transcriptional control and chromatin architecture, and traced nearly all Sox2 transcriptional activation to a small number of key transcription factor binding sites, whose deletions have no effect on promoter–enhancer interaction frequencies or topological domain organization. Sox2 locus in mouse embryonic stem cells, we found a striking disconnection between transcriptional control and chromatin architecture. We traced nearly all Sox2 transcriptional activation to a small number of key transcription factor binding sites, whose deletions have no effect on promoter–enhancer interaction frequencies or topological domain organization. Local chromatin architecture maintenance, including at the topologically associating domain (TAD) boundary downstream from the Sox2 enhancer, is widely distributed over multiple transcription factor-bound regions and maintained in a CTCF-independent manner. Furthermore, partial disruption of promoter–enhancer interactions by ectopic chromatin loop formation has no effect on Sox2 transcription. These findings indicate that many transcription factors are involved in modulating chromatin architecture independently of CTCF.How distal regulatory elements control gene transcription and chromatin topology is not clearly defined, yet these processes are closely linked in lineage specification during development. Through allele-specific genome editing and chromatin interaction analyses of the  Enhancer sequences are critical positive regulators of gene transcription that ensure appropriate spatiotemporal control of gene expression during development and in adult tissues . EnhanceEnhancers and regulated genes are often spatially configured by chromatin–chromatin interactions, whereby gene enhancer groups, which are linearly distant on the 2D chromosome fiber, may be brought into close proximity in 3D nuclear space . GrowingSox2 (sex-determining region Y-box 2) gene encodes a transcription factor necessary for pluripotency and self-renewal in mouse embryonic stem cells (ESCs) and embryonic development (Sox2 transcription in mouse ESCs and the developing epiblast is regulated by the Sox2 control region (SCR), a 7.3-kb cluster of transcription factor-bound regions located >100 kb downstream from Sox2  107 and 111 , are responsible for the majority of Sox2 transcription in ESCs; however, the deletion of these regions had no effect on interaction frequency between the SCR and the Sox2 gene. These data show a stark uncoupling of transcription enhancement from chromatin–chromatin interaction maintenance. Furthermore, removal of the sole CTCF-bound site within the SCR had no effect on either chromatin topology or Sox2 transcription. Significant perturbation of chromatin interaction frequencies and TAD border insulation function required deletion of the entire SCR, comprising multiple transcription factor-bound sites beyond those responsible for gene activation. On the other hand, insertion of CTCF motifs between Sox2 and the SCR was able to partially insulate these sites from each other from a topological standpoint, but with no effect on transcription. Thus, whereas enhancer function is mediated by a small number of key transcription factor-bound regions, chromatin–chromatin interaction is independent from transcriptional control and maintained in a distributed manner by many elements within the Sox2 TAD.To identify the sequences required for Sox2 transcription in ESCs (Sox2 locus. To establish a locus-wide view of the chromatin contacts in both wild-type F1 ESCs (Mus musculus129 × Mus castaneus) and ESCs containing a homozygous deletion of the SCR (ΔSCR/ΔSCR), we subjected fixed chromatin from both lines to an allele-specific 4C-seq approach . The apparent large increase in interaction just downstream from the SCR in the deletion line . The Sox2-spanning region, which forms an interaction with the SCR-proximal region in all wild-type 4C replicates, was used for quantitative interaction comparisons with all other tested clonal cell lines. Relative to wild-type cells, ΔSCR/ΔSCR cells showed a significant 28% decrease (P = 0.02) in relative contact frequency between the SCR-proximal bait and Sox2 , whereas the relative Sox2–SCR contact frequency of the allele with the deletion was reduced by 24%  compared with wild-type levels. This loss is not significantly different from the reduction observed in cells containing homozygous deletion of the SCR (P = 0.74) . These results thus indicate that the loss of the SCR in cis directly accounts for reduced interactions with the Sox2 gene. Interestingly, the majority of the interaction is apparently maintained with complete loss of the SCR, which confers >80% of Sox2 transcriptional activity. These data suggest that genome architecture and expression control may be decoupled at this locus, and that additional cis elements are required to maintain local chromatin structure.Deletion of the SCR abrogates the majority of  in ESCs ; howeverhe locus B. Regionhe locus  were caland Sox2 C. This fn levels . We thern levels . The all = 0.74) C. When cSox2 transcription. We previously established that, of the four transcription factor-bound regions within the SCR  . Allele-specific Sox2 transcript-level quantification analysis   (Sox2 expression (ΔSRR107+111/+)  A, only S SRR111) . To examanalysis  allowed RR107/+) B. RemovaRR111/+) B. A comp7+111/+) B. Furthe/+ cells B. These Sox2 transcription was shown to be significantly reduced upon deletion of both SRR107 and SRR111 on the same allele, these enhancers were investigated for the presence of core ESC transcription factor binding motifs that may promote the activity of these regions. Using the JASPAR GeneReg database tool . Overlapping of ChIP-seq data sets extracted from the CODEX database . Because of the partially redundant functions of the two enhancers, we targeted each of these motifs for removal in clones carrying only one intact enhancer (in which the motif of interest resided) with the other SRR deleted on the same allele. Clones carrying microdeletions of the targeted motifs  were subjected to allele-specific expression analyses. We found that deletion of the high-scoring OCT4:SOX2 motif in SRR107 (ΔOS_SRR107+111/+) resulted in a transcript reduction level close to that of the loss of the entire SRR107 in an SRR111 deletion-carrying background (Sox2 transcript levels (ΔOS_SRR107+111/+ [OS intact]). Allele-specific ChIP analysis of OCT4:SOX2 motif-deleted cells revealed a disruption in the association of OCT4 and RNA polymerase II at the altered SRR . Similar to previous heterozygous deletions of the SCR, heterozygous deletions of SCR subregions did not cause a reduction in SOX2 protein levels , and subjected these clones to allele-specific 4C-seq and expression analysis. In line with previous perturbations of the SRR109 CTCF site (Sox2 expression levels (ΔSRR109/+) (P = 0.4)   B, indicaP = 0.4) A, suggesP = 0.6) B. These Sox2 promoter. To test this hypothesis, we used ΔSRR107–111/+ ESCs, which lacked both enhancers and the CTCF-bound region on the same allele . Here, we did observe a reduction (17%) in the chromatin interaction profile between the SCR-proximal region and the Sox2 gene on the SRR107–SRR111 deletion-carrying allele compared with the corresponding wild-type allele. However, this observation did not meet the critical value for statistical significance in our analysis (P = 0.08)  of the interaction. Overall, our results indicate a striking decoupling at this locus between genetic elements responsible for transcriptional activation (key transcription factor motifs within SRR107 and SRR111) and those influencing chromatin architecture, where the sole CTCF-bound site within the SCR appears to have only a minor contribution.We next considered that SRR109 might cooperate with the two enhancer components of the SCR to support its interaction with the  = 0.08) C. This fSox2 gene, we searched for other candidate regions surrounding the SCR that might support the bulk of the remaining interactions. We postulated that a CTCF-bound region  downstream from the SCR may be involved in stabilizing the interaction between the SCR-proximal region and Sox2 when the SCR is deleted. Cobound by CTCF, RAD21, and SMC1A  cooperates to reinforce TAD and intra-TAD loops . We extended the distal deletion to include the SCR and the downstream CTCF-bound region (ΔSCR-dCTCF/+), thus removing both CTCF-bound sites. However, these deletions demonstrated only a marginally increased loss of chromatin interaction (36%) compared with that observed with deletion of the SCR alone (28%), a variation in interaction frequencies that was not significantly different (P = 0.5)  B.Sox2 promoter (SRR85 and SRR95) . These regions were previously shown to lack enhancer activity in a reporter assay . We tested whether these elements may play more of an architectural role in stabilizing a transcription factor-bound “hub” instead. Upon producing the compound deletion ΔSRR85–95+SCR-dCTCF/+, which removes all major CTCF and transcription factor-bound regions in and around the SCR, we surprisingly noted only a subtle further reduction (36%) in interaction frequency compared with deletion of the SCR alone (28%)  C. The ex5 region C, arrow.Sox2 locus was only achieved by deletion of the entire SCR; the combined deletion of SRR109 (and its resident CTCF site) and the two principal enhancer elements (ΔSRR107–111/+)  (Sox2 decreased by 43% in ΔSRR85–95+107-dCTCF/+ cells compared with wild-type cells (P = 0.01), yet this chromatin contact profile is quantitatively similar to and not different statistically from the reduction caused by deletion of the SCR (P = 0.3) , chromatin architecture supporting interactions between SCR-proximal regions and the Sox2 gene is widely distributed over many contributing elements. Much of the chromatin contact profile (>50% of wild-type levels) was maintained in the absence of Sox2 transcription and persisted even in cells with the most extreme deletions generated in this study .When comparing all the locus deletions discussed thus far, we noted that the significant reduction in chromatin contacts at the 7–111/+)  caused odCTCF/+) D. DistalP = 0.3) D. Thus, Sox2 gene and the SCR each reside near a TAD boundary, thereby restricting interactions with flanking chromatin outside the ESC-specific Sox2 TAD . When we evaluated interaction frequencies between the SCR-proximal bait region and genomic regions outside its resident TAD, we noted that removal of the SCR did not generate any specific ectopic interactions upstream of or downstream from the TAD borders, but did cause a general increase in 4C signal downstream from the SCR beyond the directly contiguous sequence , suggesting that local chromatin architecture is indeed CTCF-independent.Since the CTCF binding sites within the ESC pression . In lineSox2 expression and locus topology; however, these data did not indicate whether Sox2 TAD architecture is in fact important for transcriptional control. All ESC lines harboring deletions that perturbed chromatin interactions had removed the SRR107 and SRR111 elements required for efficient Sox2 expression. To assess the functional significance of the chromatin interactions at the Sox2 locus, we chose to disrupt these endogenous Sox2–SCR interactions while keeping the SCR intact. We engineered an FRT/F3 cassette at a site located between the Sox2 gene and the SCR in the 129 allele of F1 ESCs . We were thus able to site-specifically insert putative insulator sequences of interest by recombinase-mediated cassette exchange and assess their effect on allele-specific chromatin topology and Sox2 expression levels  required the insertion of tandem copies of CTCF motifs and flanking sequences  to alter endogenous Sox2–SCR interactions. In a parallel study to ours, Sox2 expression in mouse blastocysts when tandem copies of CTCF motifs were homozygously inserted. However, these studies only assessed chromatin topology for insertions where significant transcriptional inhibition had been observed. Whether structural perturbations could occur in the absence of an effect on transcription had not been investigated.The deletion experiments described thus far have allowed for the fine functional dissection of the SCR and SCR-proximal elements to evaluate the role these regions have in regulating n levels A. This aSOX9 gene), which could be used as a unique 4C bait. We introduced this insertion, with or without two copies of the core 19-bp CTCF motif within SRR109, into the landing site between Sox2 and the SCR; the motifs were either both in convergent orientation with SRR109/SCR or with the CTCF site at the Sox2 promoter . With this setup, we were able to perform allele-specific 4C-seq using either the SCR , but not with the SCR, from either the SCR or insertion site bait viewpoint . The endogenous Sox2–SCR interaction was unaffected (P = 0.1).We engineered a short human sequence insertion (352-bp DpnII–Csp6I fragment upstream of the promoter A. By ChI the SCR B or the  the SCR C as the  in ESCs A. As mayP = 0.02), which was clearly detected from both SCR and insertion site bait perspectives  and quantitatively very similar to the interaction loss caused by deletion of the SCR. Surprisingly, the ectopic CTCF site also formed a strong and significant interaction with the Sox2 promoter (P = 0.02), which would not have been expected from a loop extrusion model due to the incompatible motif orientations at these regions. Contrary to other studies showing an effect on Sox2 expression on insertion of larger CTCF-bound sequences ; a significant reduction upon loss of the entire SCR; and weak further losses of interaction frequencies when also removing transcription factor-bound regions at SRR85–SRR95 and/or an extension of the SCR deletion to a distal CTCF site. These data support the notion of a distribution of chromatin architecture maintenance over many genomic elements (presumably transcription factor-bound regions), within the Sox2 TAD, each individually posing a weak effect but one that collectively builds up the domain. Since the cohesin complex subunit SMC1A is enriched at each of these contributing regions, the possibility is raised that cohesin is involved in Sox2 locus topology maintenance. Alternatively, such a result is consistent with previous findings that distal regulatory elements can coassociate in nuclear “hubs” , may be similarly coordinated  in the M. musculus129 × M. castaneus; female cells obtained from Barbara Panning) were cultured on 0.1% gelatin-coated plates in ES medium , which maintains ESCs in a pluripotent state in the absence of a feeder layer . For select cases of allele-specific targeting, gRNA pairs were designed so that at least one gRNA overlapped a SNP to specifically target the M. musculus129 allele. On- and off-target specificities of the gRNAs were calculated as described in Cas9-mediated deletions were carried out as previously described . Cas9 taSupplemental Table S3).F1 ESCs were transfected with 5 µg of each of the 5′ gRNA(s), 3′ gRNA(s), and pCas9_GFP (Addgene 44719)  or pCas9Sox2 on the musculus allele of F1 ESCs by homologous recombination after Cas9-mediated DNA break at the 3′ end of Sox2. A plasmid containing a P2A-Venus cassette and one containing Cas9-mCherry, a puromycin resistance gene, and three gRNA cassettes were assembled by the Institute of Genetics and Molecular and Cellular Biology (IGBMC) molecular biology platform . One gRNA targeted a Cas9-mediated DNA break at the 3′ end of Sox2, and the other two targeted breaks flanking the P2A-Venus cassette on the plasmid to generate 8-bp microhomology with the Sox2 3′ site . Five micrograms of each plasmid was transfected into 1 million cells with Lipofectamine 2000, and Venus-positive cells were isolated by FACS after 5 d. Single clones were isolated, and incorporation of reporter into the musculus and/or castaneus allele was determined by allele-specific PCR. A musculus-incorporated heterozygous clone was further characterized by sequencing of PCR products. Expression of pluripotency markers, allelic Sox2 expression, and 4C chromatin interaction profiles were unperturbed by incorporation of the Venus reporter .A P2A-Venus reporter construct was inserted at musculus-specific insertion of an FRT/F3 cassette into a site between Sox2 and the SCR. One-kilobase homology arms were added to a plasmid containing a puromycin resistance–thymidine kinase positive selection marker within an FRT/F3 cassette  by restriction cloning . Five micrograms of this plasmid was cotransfected with 5 µg of Cas9-mCherry/sgRNA plasmid  into 1 million cells with Lipofectamine 2000. Only the musculus allele had a functional PAM at the gRNA target site due to a SNP. Cherry-positive cells were isolated by FACS after 3 d, and after 1 d of recovery, clones were selected with 3 µg/mL puromycin for 1 d, and then 1 µg/mL puromycin until individual resistant colonies were formed. Clones were screened by PCR and confirmed by sequencing. We noted a slight reduction in musculus-specific Sox2 transcription and SCR–Sox2 interaction from this founder line, which was rescued on removal of the positive–negative selection marker .This reporter line was then used for Supplemental Fig. S9), even though allelic balance of Sox2 expression was unaltered .The positive–negative selection marker was replaced with different inserts by FLP-mediated recombination. The donor vectors were constructed by restriction cloning of the initial FRT/F3 plasmid, annealed oligonucleotides (for CTCF motifs), and PCR products from human genomic DNA template (for SOX9 sequence). Five micrograms of donor vector was coelectroporated with 5 µg of FLP-expressing plasmid  with neon, and after 2 d of recovery, recombinant clones were selected with 6 µM ganciclovir. Clones were screened by PCR and confirmed by sequencing. Flow cytometry quantitation revealed a slight but equal reduction in Venus reporter expression in all clones compared with the founder line , and an additional DNase I step was used to remove genomic DNA. RNA was reverse-transcribed with random primers using the high-capacity cDNA synthesis kit (Thermo Fisher Scientific). Sox2 promoter bait), and aliquots of 5 million nuclei were further permeabilized by treatment with 0.4% SDS for 1 h at 37°C and then incubated with 3.33% Triton X-100 for 1 h at 37°C. Nuclei were digested overnight with 1500 U of DpnII at 37°C (300 U of NlaIII for Sox2 promoter bait) and then washed twice by centrifuging and resuspending in T4 DNA ligase buffer. In situ ligation was performed in 400 μL of T4 DNA ligase buffer with 20,000 U of T4 DNA ligase overnight at 23°C. DNA was purified by reverse cross-linking with an overnight incubation at 65°C with proteinase K, followed by RNase A digestion, phenol/chloroform extraction, and isopropanol precipitation. The DNA was digested with 5 U/μg Csp6I overnight at 37°C, and then repurified by phenol/chloroform extraction and isopropanol precipitation. The DNA was then circularized by ligation with 200 U/μg T4 DNA ligase under dilute conditions (3 ng/μL DNA) and purified by phenol/chloroform extraction and isopropanol precipitation. For allele-specific 4C from the SCR-proximal bait, samples of the DNA were digested with BveI or Alw26I, cutting specifically at the region between the DpnII site and the 4C reading primer annealing site on the 129 or castaneus allele, respectively. For 129-specific 4C from the SCR bait, the material was digested with AvaIII, cutting specifically at the region between the Csp6I site and the 4C nonreading primer annealing site on the castaneus allele. There were no SNPs allowing castaneus-specific 4C from this bait. No digestion was required for allele-specific 4C from the human insertion sequence, since this was only present on the 129 allele. 4C using the Sox2 promoter as bait was not allele-specific, and no extra digestion step was incorporated. One-hundred-nanogram aliquots of treated DNA were then used as template for PCR with bait-specific primers containing Illumina adapter termini . PCR reactions were pooled, and primers were removed by washing with 1.8× AMPure XP beads and then quantified on a Bioanalyzer (Agilent) before sequencing with a HiSeq 4000 (Illumina).Cells were fixed with 2% paraformaldehyde in 10% FBS in PBS for 10 min at 23°C. The fixation was quenched with cold glycine at a final concentration of 125 mM, and then cells were washed with PBS and permeabilized for 1 h on ice with 10 mM Tris-HCl (pH 8), 100 mM NaCl, 0.1% NP-40, and protease inhibitors. Nuclei were resuspended in DpnII restriction buffer at 10 million nuclei/mL concentration . Total protein samples were prepared in Laemmli buffer before being analyzed by SDS-PAGE . Blots were probed with primary antibodies for SOX2  or UBF (sc-13125), followed by horseradish peroxidase-conjugated secondary antibodies. Blots were visualized with enhanced chemiluminescence.Protein was extracted from 5 million cells using RIPA buffer  containing Halt protease inhibitor complete EDTA-free (Thermo Fisher Scientific), supplemented with 1 mM PMSF and 2 mM Nag for 5 min at 4°C before resuspending in ice-cold lysis buffer 2  for 10 min at 4°C. Nuclei were pelleted at 2000g for 5 min at 4°C before resuspending in ice-cold lysis buffer 3 . Sonication was performed using a probe sonicator at 20 A (15 sec on/30 sec off) for 4.5 min at 4°C. After cell lysis and sonication, Triton X-100 was added to the sonicated lysate to precipitate any debris. Fifty microliters of cell lysate was obtained as whole-cell extract (WCE), and the remaining lysate was used for two immunoprecipitations. Chromatin samples were incubated overnight with 5 μg of relevant antibodies at 4°C with rotation. Antibodies used for ChIP experiments were anti-OCT4A (CST 5677), anti-SOX2 (CST 23064), anti-RNA polymerase II (Abcam ab5131), and anti-CTCF (Millipore 07-729). One-hundred microliters of protein A magnetic Dynabeads (Invitrogen) was added to the antibody-bound chromatin and incubated overnight at 4°C with rotation. Lysates were washed six times at room temperature with RIPA buffer followed by a TBS buffer wash. Samples were eluted with an SDS-based elution buffer  for 30 min at 65°C before addition of 4 μL of 20 mg/mL proteinase K and overnight decross-linking at 65°C. ChIP DNA was purified using phenol/chloroform. Fold enrichment was calculated using the standard curve method with WCE used to generate the standard curve. For all ChIP experiments, except those pertaining to CTCF, allele-specific primers were used to specifically amplify either the musculus or castaneus allele as described , fixed with 4% paraformaldehyde for 10 min, and washed twice for 10 min in PBS. The cells were permeabilized with 70% ethanol overnight at 4°C. Coverslips were hybridized overnight at 37°C with hybridization buffer containing 10% dextran sulfate, 10% formamide, 2× SSC, and 5 pmol of fluorescent probes targeting Sox2 and labeled with Quasar670 dye (Biosearch Technologies). Coverslips were washed three times for 30 min with 10% formamide and 2× SSC at 37°C, once with 2× SSC, and once for 5 min with PBS at room temperature. Coverslips were mounted on microscope slides using ProLong Gold mounting medium containing DAPI (Thermo Fisher). Coverslips were dried for at least 24 h at room temperature in the dark before imaging. Imaging was performed on an inverted microscope (Zeiss AxioObserver), a plan-apochromat 40× 1.4 NA oil DIC UV objective, a 1.60× optovar, and an sCMOS camera (Hamamatsu Orca Flash 4v3). For Quasar670, a 660-nm longpass dichroic (Chroma T660lpxrxt), 697/60-nm emission filter (Chroma ET697/60 m), and 640/30-nm LED excitation at full power  were used. For DAPI, a 425-nm longpass dichroic (Chroma T425lpxr), a 460/50-nm emission filter (Chroma ET460/50 m), and LED excitation at 395/25 nm at 25% power  were used. For each sample and each channel, we used the Micro-Manager software to acquire at several fields of view, each consisting of a 45-z-stack (Δz 0.3 μm) at 25-msec exposure for DAPI and 750-msec exposure for Quasar670.Three-hundred-thousand cells were seeded onto poly-L-lysine-coated coverslips in culture medium and incubated for 2–3 h at 37°C and 5% COhttps://github.com/najoshi/sabre) and aligned to the mm10 genome with Bowtie  tested in this study . For statistical comparison of specific interactions, the 4C read counts within 1 Mb of the bait for all replicates and conditions (from the same bait) were quantile-normalized using the limma package . For the insertion site–SCR interaction, we used the minimal region spanning the SCR called as interacting in all replicates of the (CTCF insertion [SCR-convergent]) line . For quantifying inter-TAD interactions from the near-SCR bait, we used the 325-kb region  that contains nearly the entire downstream TAD. Since 4C-seq signal at the 5′ end of the downstream TAD is artificially inflated in various deletion lines because the genomic separation has been shortened by the deletion, the selected region started at a conservatively chosen place 3′ to 4C-seq local minima . As a control for the upstream TAD, the same size region was used .Sequencing read fastq files were demultiplexed with sabre . Cells and nuclei were segmented using Otsu thresholding and watershedding. Spots were localized by fitting a 3D Gaussian mask after local background subtraction (2 test.A custom Python script was used to detect, localize, and classify the spots (traction  and counESC ChIP-seq data sets and associated peak files were obtained from the CODEX database .All 4C-seq data from this study have been deposited on GEO with the accession GSE195906.


CALCA, is modulated by epigenetic modifications, including the DNA methylation, histone modification, and effects of micro RNAs (miRNAs), circular RNAs, and long-coding RNAs (lncRNAs). On the other hand, CGRP can change the epigenetic profile of neuronal and glial cells. The promoter of the CALCA gene has two CpG islands that may be specifically methylated in migraine patients. DNA methylation and lncRNAs were shown to play a role in the cell-specific alternative splicing of the CALCA primary transcript. CGRP may be involved in changes in neural cytoarchitecture that are controlled by histone deacetylase 6 (HDAC6) and can be related to migraine. Inhibition of HDAC6 results in reduced cortical-spreading depression and a blockade of the CGRP receptor. CGRP levels are associated with the expression of several miRNAs in plasma, making them useful peripheral markers of migraine. The fundamental role of CGRP in inflammatory pain transmission may be epigenetically regulated. In conclusion, epigenetic connections of CGRP should be further explored for efficient and safe antimigraine therapy. The calcitonin gene-related peptide (CGRP) is implicated in the pathogenesis of several pain-related syndromes, including migraine. Targeting CGRP and its receptor by their antagonists and antibodies was a breakthrough in migraine therapy, but the need to improve efficacy and limit the side effects of these drugs justify further studies on the regulation of CGRP in migraine. The expression of the CGRP encoding gene,  Molecular mechanisms of migraine pathogenesis are incompletely known. This is the main reason this disease remains undertreated despite significant therapeutic progress made by the application of drugs based on monoclonal antibodies against the calcitonin gene-related peptide (CGRP) and the antagonists of and antibodies against its receptor in migraine prevention and therapy ,2. IntroGenetics plays an important role in migraine susceptibility, symptoms, and comorbidity with other conditions, evidenced by studies associating genetic variants and migraine-related phenotypes (reviewed in ). HoweveIn 2013, Eising et al. pointed out epigenetics as a promising avenue in the study of migraine pathogenesis . Some reIn 2011, Park et al. presented results on the epigenetic regulation of CGRP signaling in trigeminal glia, suggesting their potential in migraine pathogenesis . FurtherIn this review, we present and update information on the role of epigenetics in CGRP regulation and their interaction with other proteins and regulatory RNAs in migraine and other pain-related syndromes. We also present some information on the role of epigenetics in CGRP effects in other diseases, including disorders of the cardiovascular system.CALCA) gene, located at 11p15. The gene has 5684 base pairs (GRCh38/hg38) and encodes the hormone calcitonin (CT) and CGRP alpha (CGRP-1) mediated by alternative mRNA processing [CALCA, and β-CGRP (CGRP-2), encoded by the calcitonin-related polypeptide beta (CALCB) gene. CGRP-1 is the predominant form of CGRP expressed in trigeminal ganglia and will be further referred to as CGRP unless otherwise stated [CGRP is encoded by the calcitonin-related polypeptide alpha  [The regulation of elements   . It is ate (TSS) .CGRP exerts biological action through the interaction with its complex heterotrimeric G-protein coupled receptor, composed of the calcitonin-like receptor (CLR), receptor activity-modifying protein 1 (RAMP1), and a small receptor component protein (RCP)  Figure . CLR is CALCA gene yields CGRP and CT primary transcripts resulting from the use of two distinct polyadenylation sites and different splicing patterns [CALCA gene has six exons, of which exons 1, 2, 3, and 4 are spliced together to produce CT mRNA and exons 1, 2, 3, 5, and 6 are spliced to yield CGRP-1 mRNA [CALCA gene transcript [The transcription of the patterns   . Domain CALCB gene, also located on the 11th chromosome but in a distinct site from CALCA [CALCB region has been identified as a migraine risk locus in a genome-wide association study (GWAS) with over a hundred thousand migraine cases [Another form of CGRP, CGRP-2, is encoded by the om CALCA . Human Com CALCA . Recentlne cases .The circulating plasma level of CGRP in healthy individuals is low, but CGRP is naturally increased in pregnancy to regulate uteroplacental blood flow and other vascular changes ,41. ChanThe most remarkable evidence of the involvement of CGRP in migraine pathogenesis is its elevated level in physiological fluids in migraine patients during headache attacks and the induction of delayed migraine-like headaches after CGRP infusion (reviewed in ). HoweveCGRP can be found in many areas of the brain, including the thalamus, the amygdala, periaqueductal grey, locus coeruleus, trigeminal nucleus caudalis (TNC), parabrachial nucleus, hypothalamus, the cerebellum as well as the meningeal vasculature . The triCGRP is stored in large, dense-core vesicles in the sensory nerve terminals . TrigemiCGRP is the most potent vasodilatory peptide, and its receptors are localized in the regions that are important in migraine pathogenesis . HoweverCALCA gene in trigeminal glia by a paracrine regulatory mechanism [The activation of the CGRP receptor mediates neurogenic inflammation and the sensitization of nociceptive neurons . Reactivechanism . It was In the CNS, CGRP and its receptor are involved in several signaling pathways that may play a role in migraine pathogenesis . The triCGRP can also act in the peripheral nervous system, where it targets mast cells, blood vessels, glial cells, trigeminal afferents in the meninges and neural cell bodies, and satellite glia in the trigeminal ganglia . AdditioApart from migraine and other pain-related neurological diseases, CGRP may be involved in the pathophysiology of several other disorders, including sepsis, hypertension, diabetes, obesity, atherosclerosis, and myocardial infarction (reviewed in ). TherefHuman DNA can be methylated in many ways, but DNA signaling methylation, which is a part of epigenetic regulation of gene expression, involves the transfer of a methyl group from S-adenosyl-methionine (SAM) to the carbon-5 of cytosine in DNA, changing it to 5-methyl cytosine (5 mC). This reaction is catalyzed by the DNA methyltransferases DNMT1, DNMT3A, and DNMT3B . In the Several studies report an association between DNA methylation and migraine occurrence . In the https://clinicaltrials.gov/ct2/show/record/NCT04503083, accessed on 10 May 2022). It is expected that the results of the project will be related to the epigenetic regulation of CGRP [The ongoing BIOmarkers of MIGrAine based on the stratification of responders to CGRP monoclonal antibodies (BIOMIGA) proof of concept study (NCT04503083) includes the assessment of DNA methylation levels in migraine subjects as compared to non-migraineur controls  and one encompassing the proximal promoter and exon 1 [CALCA-expressing human medullary thyroid carcinoma TT cell line but are hypermethylated in the CALCA non-expressing non-small-cell lung cancer NCI-H460 cell line. Hypermethylation was stronger in the 5′ upstream region than in the exon. Incubation of Rat2 cells with 5-aza-2-deoxycytidine (Aza-dC), a DNA methylation inhibitor, resulted in a detectable induction of CT mRNA, also observed when primers specific to both CT and CGRP mRNA were used. Two CpG islands in the human d exon 1 ,64. BothCALCA gene: one located in the distal promoter between −2762 and −2362 bp and the other situated in the proximal promoter between −1662 and −1028 bp , calcitonin receptor-like receptor (CALCRL), upstream stimulating factor 2 (USF2), and other genes in leukocytes and migraine-related tissues, including dura mater, trigeminal ganglion and trigeminal caudal nucleus. In addition, results obtained in the leukocytes of rats were compared with those in humans. There was no correlation between DNA methylation in rat leukocytes and samples from other tissues. On the other hand, DNA methylation patterns in human lymphocytes correlated with those of rats. This important work suggests two essential aspects of migraine-related research: (1) studies on peripheral tissue may not reflect effects occurring in target tissues, and (2) rats may be a good model to study the significance of DNA methylation in migraine in humans. Labruijere et al. studied DNA methylation in many migraine-related genes in different tissues of rats to check whether the results of research on DNA methylation in leukocytes can be extended to other cells more related to migraine . They deRAMP1 gene in leukocytes of migraineurs and controls were shown, but a low DNA methylation trend was observed in migraineurs [Infusion of CGRP in migraineurs provoked delayed migraine-like headaches, but such an effect was not observed in non-migraineurs . No diffraineurs . Howeverraineurs . Thereforaineurs ,71,72.In summary, results on the DNA methylation of genes encoding CGRP and its receptor in the periphery may suggest that this epigenetic modification may play a role in migraine pathogenesis, but no direct evidence has been presented so far. It is too early to conclude on the significance of DNA methylation patterns in some specific aspects of migraine, including sex difference in its prevalence and associated symptoms such as aura or comorbidity, but ongoing studies on large cohorts may contribute to our knowledge of the role of DNA methylation in migraine. The process of DNA methylation uses folate , an essential micronutrient that may link DNA methylation, migraine, and a migraine-preventive diet. However, this issue also needs further research to establish potential dietary recommendations .The ratio between the total length of the human nuclear DNA (ca. 2 m) and the average size of the nucleus in the human cells (6 µm) dictates packaging the human genome into a highly organized structure (chromatin) not only to fit DNA into the nucleus but also to enable the reading of the primary genetic information contained in DNA. Major protein components of chromatin are histones that are subjected to an array of post-translational covalent modifications, mainly in their N-terminal tails, which protrude from histone complexes and are accessible to histone-modifying enzymes. These modifications are an important part of the information carried by a fragment of DNA associated with histones, and their pattern is referred to as the histone code . It is aHistone deacetylase 6 (HDAC6) deacetylases not only histones but also non-histone proteins, including proteins important for steady and dynamic cellular structures . One of Abnormal histone modifications, including the trimethylation of histone H3 at lysine 27 (H3K27me3), are associated with the expression of proinflammatory mediators in neuroinflammation, which plays a role in migraine pathogenesis ,81. SuchCALCA gene and the antibodies against histone H3 acetylated at Lys9 (H3K9ac), resulted in the observation of a robust signal in neuronal-like rat CA77 cells expressing CALCA but not in the rat-embryo-derived Rat2 fibroblast cell line that did not express the CALCA gene [CALCA gene. However, the use of trichostatin A (TCA), a histone deacetylase inhibitor, did not change CALCA expression in Rat2 cells. Treatment with another HDAC inhibitor, sodium butyrate, had little or no effect either. Comparing these results with those obtained for Aza-dC, presented in the previous section, it was concluded that DNA methylation and not histone deacetylation was the major factor controlling CALCA expression in Rat2 cells. Treatment with Aza-dC increased about 30-fold the CT mRNA in glial cultures, but treatment with TSA singly did not change CALCA expression. However, the Aza-dC + TSA combination resulted in a synergistic, about 80-fold, increase in CT and a 3-fold increase in CGRP mRNA. The effect of histone acetylation needed DNA methylation to be manifested. This important study pointed at glial CALCA as an important element in migraine pathophysiology and a potential marker in this disease.The use of the ChIP assay, PCR amplification of the 18-bp enhancer in the promoter of the LCA gene . The sigCX3CR1), and interleukin 1 beta (IL1B) genes in the spinal dorsal horn. A CGRP receptor antagonist inhibited thermal and mechanical hyperalgesia in chronic construction injury rats. Many genes were affected by CGRP-induced changes in their epigenetic profile, including genes involved in proliferation, autophagy, and macrophage chemotaxis. In the context of the present review, that work signals a potential of astroglial cells in pain transmission and also in migraine and points to CGRP as an important modulator of this process through the regulation of the epigenetic profile of these cells. Astrocytes are essential for normal neuronal functions, and there is emerging evidence for their role in migraine pathogenesis ,86. So fSeveral studies not related to migraine or pain transmission have shown the involvement of CGRP in regulating epigenetic profiles in neuronal cells. Intracerebroventricular administration of CGRP disturbed traumatic fear memories in animal models of post-traumatic stress disorder . This efIn summary, CGRP may be involved in epigenetically regulated changes in neural cytoarchitecture that may be related to migraine and HDAC6 may control this process. Changes in histone methylation may result in changes in the production of proinflammatory molecules that may play a role in migraine. CGRP may be involved in neurogenic pain transmission through the methylation of H3 histone mediated by EZH2 in the spinal dorsal horn. Histone modifications associated with CGRP should be considered with changes in DNA methylation profile.Only a small proportion of the human genome encodes polypeptides, and the human transcriptome can be understood in at least two ways: as the total RNA content of the cell or the complete set of mRNAs. In general, the RNA content of the cell can be divided into coding  and non-coding  RNAs. The latter can be further divided into housekeeping ncRNAs, such as ribosomal RNA (rRNA) and transfer RNA (tRNA), and regulatory ncRNAs, which can be classified into short non-coding RNA  and long non-coding RNA (more than 200 nucleotides). This is not a subject of this review; detailed information on the classification and general properties of non-coding RNAs can be found elsewhere, e.g., ,91. We wMiRNAs are synthesized from a precursor that has a stem-loop structure by its cleavage to give molecules of miRNAs, typically 20–25 nucleotides in length . They arHigher levels of CGRP, miR-382-5p, and miR-34a-5p in the plasma of chronic migraine (CM) patients who overused medications compared with patients with episodic migraine (EM) were observed . After aCALCA gene is the target for miR-30a, and the overexpression of miR-30a caused the downregulation of CALCA, while the knockdown of miR-30 resulted in CALCA upregulation. A mechanistic study revealed that miR-30a might bind CALCA in its 3′-UTR to degrade it. In conclusion, miR-30a may act protectively against migraine to inhibit its progression through a mechanism involving CALCA silencing and a decrease in CGRP levels.A lower serum level of miR-30a in migraine patients than in non-migraine controls, with increased methylation in the promoter of the miR-30 gene, was reported . FurtherAn increased expression of miR-34a-5p in the serum of migraine patients during the disease attack but not in the pain-free period was observed . Then, aThe role of miR-155-5p in TNC in chronic migraine using an NTG-induced chronic migraine mouse model was determined . NTG cauCGRP was reported to interfere with the cellular epigenetic profile in effects not directly related to migraine. Li et al. showed that CGRP inhibited apoptosis and ROS production induced by isoprenaline in cultured rat cardiomyocytes through the regulation of miRNA-1 and miRNA-133a . The effCALCA gene to decrease CGRP levels. miR-125a-3p and miR-34a-5p may regulate CGRP in inflammatory pain pathways. CGRP may act in concert with miR-155-5p to induce the activation of microglial and central sensitization mediated by the downregulation of SIRT1.In summary, CGRP levels may positively correlate with the expression of some miRNAs, including miR-382-5p and miR-34a-5p, that are associated with migraine occurrence and CGRP plasma levels. The expression of some miRNAs correlated with CGRP levels may be a peripheral marker for migraine, stronger than CGRP. The expression of miR-30a is negatively correlated with migraine, and this miRNA may downregulate the CircRNA, due to its structure, with no free ends for exonuclease degradation, is more stable than linear RNA and can act as a sponge for miRNAs . CircRNAIt was shown that CGRP increased the expression of IL6 mRNA in RAW264.7 macrophages . This efIt was shown that CGRP regulated the expression of the FOS-like 2 AP-1 transcription factor subunit (FOSL2) in mouse bone marrow mesenchymal stem cells with the involvement of mmu_circRNA_003795 . FOSL2 iThe role of the interplay between circRNAs and miRNAs in CGRP regulation was confirmed by Wu et al., who observed an aberrant expression of mm9_circ_009056 circRNA in CGRP-induced MC3T3 cells . IncreasIn summary, CGRP regulation of pathways important in migraine pathogenesis can be assisted by the sponging of related miRNAs by circRNAs. LncRNAs are longer than 200 nucleotides, and they are usually divided into five categories: long intergenic ncRNA (lincRNA), long intronic ncRNA, sense lncRNAs, overlapping sense lncRNA, and bidirectional lncRNA. Some lncRNAs can be further processed to produce small ncRNAs, including miRNAs . The funXu et al. investigated the effect of the Gm14461 lncRNA on pain transmission in the trigeminal nerve of the mouse trigeminal neuralgia model . They obAlthough, generally, migraine is not considered a “classical” neuropathic pain syndrome, it has many features of it . To inveEpigenetic regulation of CGRP may play a role in its involvement in the mechanisms underlying cancer-induced pain (CIP). Sun et al. observed the overexpression of lncRNA-NONRATT021203.2 in rats with induced CIP . FurtherCALCA gene, a process essential for CGRP production, may be regulated by lncRNA MIAT.As mentioned, CGRP was reported to exert beneficial effects in cardiovascular disorders. It was shown that the regulation of CGRP by lncRNAs might be important in the treatment of acute myocardial infarction . That stIn a similar study, Hu et al. showed that the expression of lncRNA 1700020I14Rik and CGRP was downregulated in myocardial ischemia-reperfusion (I/R) injury and hypoxia/reoxygenation (H/R) injury in a myocardial cell culture model . OverexpCALCA gene, a process essential for CGRP production. CGRP, together with lncRNAs, may promote pain transmission in trigeminal neuralgia mouse models. lncRNAs may play an important role in the transmission of DNP by promoting the release of CGRP in the spinal cord. We speculate that lncRNA regulation of CGRP in cardiovascular diseases may share mechanism(s) with CGRP involvement in migraine pathogenesis.In summary, lncRNAs may regulate alternative splicing of the A short summary of epigenetic effects related to CGRP and its gene that may be associated with migraine is presented in CALCA gene and the involvement of lncRNAs in the alternative splicing of the CALCA primary transcript.Epigenetic regulation of gene expression has an essential impact on the expression of primary genetic information contained in DNA into functional proteins determining the phenotype. CGRP uses alternative RNA processing as a part of a developmental strategy of the brain to direct tissue-specific patterns of polypeptide synthesis . This prCALCA gene, including DNA methylation, histone modifications, and regulatory ncRNAs. On the other hand, CGRP may change the cellular epigenetic pattern modifying the expression of its components and its regulatory protein.CGRP is involved in pain transmission, essential for migraine and other pain-related syndromes, and this involvement can be featured by epigenetic modifications of the CALCA gene are important for its cell-specific expression not only in neuronal cells but also in cultured glia [CALCA in glial cells as a potential therapeutic target in migraine. The involvement of glial cells in migraine has been addressed in several studies and hypotheses ,132CALCAspective .CALCA and CGRP in the network of genes involved in migraine pathogenesis is equally important as the sole role of this peptide in migraine. As suggested by Andrew Russo, one way to do so would be a study of the epistasis relationships and epigenetic regulators of CGRP [CALCA gene, but, on the other hand, we also tried to show that CGRP may also evoke changes in the epigenetic profile of promoters of genes that are important in migraine pathogenesis.To position  of CGRP . We haveSeveral reports show the involvement of CGRP in cardiovascular diseases, underlined by epigenetic modifications of pathways that may be important in migraine pathogenesis. Therefore, checking these pathways in migraine seems to be an immediate perspective.Although this work focuses on the epigenetic aspects of the CGRP pathway, it is worth mentioning that recently, Zecca et. showed for the first time the suitability of the rs7590387 polymorphism of the RAMP1 (receptor activity-modifying protein 1) gene as a predictive marker of the efficacy of erenumab, the first monoclonal antibody against the CGRP receptor approved for migraine prevention . EarlierMany aspects of CGRP functioning require explanation. The apparently paradoxical observation that salmon CGRP is more efficient in humans than human CGRP is still not completely clear, especially how its administration affects pain perception ,137. The


The three-dimensional genomic structure plays a critical role in gene expression, cellular differentiation, and pathological conditions. It is pivotal to elucidate fine-scale chromatin architectures, especially interactions of regulatory elements, to understand the temporospatial regulation of gene expression. In this study, we report Hi-TrAC as a proximity ligation-free, robust, and sensitive technique to profile genome-wide chromatin interactions at high-resolution among regulatory elements. Hi-TrAC detects chromatin looping among accessible regions at single nucleosome resolution. With almost half-million identified loops, we reveal a comprehensive interaction network of regulatory elements across the genome. After integrating chromatin binding profiles of transcription factors, we discover that cohesin complex and CTCF are responsible for organizing long-range chromatin loops, related to domain formation; whereas ZNF143 and HCFC1 are involved in structuring short-range chromatin loops between regulatory elements, which directly regulate gene expression. Thus, we introduce a methodology to identify a delicate and comprehensive network of cis-regulatory elements, revealing the complexity and a division of labor of transcription factors in organizing chromatin loops for genome organization and gene expression. It is currently not clear how architectural proteins orchestrate chromatin looping at different scales of genome organisation. Here the authors report Hi-TrAC as a proximity ligation-free method to profile genome-wide chromatin interactions at single nucleosome resolution among regulatory elements. Each chromosome occupies a discrete territory in the nucleus7. Based on the spatial separation of active and inactive phases, the chromatin is partitioned into A and B compartments, respectively9. Self-associating chromatin assembles into ~1 Mb-sized topologically associating domains (TADs)12, which contain nested sub-TADs with the size of several hundred kb14. Chromatin domains are assembled by chromatin interaction loops, which are organized by CTCF and cohesin complex through a loop-extrusion process26. Interactions between transcriptional regulatory elements are important for orchestrating gene expression43. Knowledge of the detailed enhancer-promoter interaction network is important for understanding the fine-tuning of cell activities46. A sensitive and efficient technique is highly desired for elucidating genome-wide fine structures, particularly enhancer-promoter interactions. It is generally accepted that cohesin complex catalyzes chromatin folding into loops anchored by CTCF binding50, whereas several other chromatin factors, including ZNF143 and YY1, have been shown to facilitate chromatin loop formation58. However, it is not clear how these architectural proteins orchestrate chromatin looping at different scales of genome organization.The genome is organized into higher-order chromatin structuresIn this study, we developed a highly sensitive technique termed as Hi-TrAC  and applied it to profiling chromatin loops at Tn5 accessible chromatin regions in three different mouse and human cell types. By integrating the regulatory interaction network from the Hi-TrAC data with hundreds of transcription factor ChIP-seq data, we found that while CTCF and cohesin are involved in long-range chromatin interactions, HCFC1 and ZNF143 are involved in short-range chromatin loop formation.59. Hi-TrAC takes advantage of DNA transposase Tn5’s ability of utilizing a specially designed bivalent linker to covalently bridge spatially proximal open chromatin regions, thus eliminating chromatin fragmentation and proximity ligation steps required for 3 C (chromosome conformation capture)-based techniques  method with substantial improvementsues Fig. , Methods62. Starting with 0.01, 0.1, and 1 million mouse embryonic stem cells (mESCs) , which produce high-resolution chromatin structure mapsles Fig. . To compsis Fig. . Moreovesis Fig. . With a sis Fig. . These rMyc . Globally, with at least 10 PETs supporting a loop, we called 91,042 high-confidence loops in GM12878 cells  in K562 cells 80. Accumulating evidence suggests that HCFC1 and ZNF143 may be involved in organizing chromatin structures85. The number of loops co-bound by HCFC1/ZNF143 but not CTCF or RAD21 was similar to the number of loops co-bound by CTCF/RAD21 but not HCFC1 or ZNF143 in GM12878  these different factors either individually or in combination in K562 cells  genes. This region exhibited strong promoter-promoter interactions, which is conserved between K562 and GM12878 cells. Multiple HCFC1 and ZNF143 binding peaks were detected at the loop anchors within this locus, whereas no strong CTCF and RAD21 binding was detected Fig. . The simZNF225 promoter is bound by HCFC1 and ZNF143 and interacts with other promoters in the region, while the non-expressed ZNF234 promoter has only very weak binding of HCFC1 and ZNF143 and does not interact with other promoters and thus serves as a negative control  with only 10% of PETs (223 M vs 2396 M); Hi-TrAC detected almost all the interactions between potential enhancers and their target promoters as detected by MCC. Comparing to other 3C-based techniques, Hi-TrAC also showed advantage in detecting much more chromatin loops at high resolution with less sequencing amount. Thus, Hi-TrAC can serve as an inexpensive, highly sensitive and robust alternative method for analyzing interactions among regulatory elements of chromatin and transcription.We present here Hi-TrAC as a sensitive technique for mapping chromatin loops among transcription and chromatin regulator elements in accessible genomic regions. This technique shares the basic concept with Trac-looping, which utilizes Tn5’s ability to integrate DNA bridge into accessible chromatin regions to covalently link physically-contacting chromatin loci, thereby avoiding the proximity ligation that is required for the 3C-derived techniquesThe bridging linker used in Hi-TrAC works like a ruler charting the genome map. To be bridged by the linker, the spatial distance between two interacting loci should be shorter than the length of the linker. We tested linkers with different lengths and found that a linker with a 30 bp spacer between the flanking Tn5 binding sites performed best. Longer linkers captured too many inter-chromatin interactions, whereas shorter linkers lost many distal interactions  and promoters of corresponding genes with the help of transcription factors87. To gain comprehensive information on the mechanisms of gene regulation genome-widely, it is important to identify the regulatory interaction networks of enhancers and promoters. However, even the most comprehensive 3D data in previous studies only provide limited information on genome-wide enhancer-promoter loops61. To our knowledge, we now have provided the most comprehensive interaction data among accessible chromatin regions in GM12878, K562 cells, and mESCs, reporting a total of about 500,000 chromatin loops. Further, our data also revealed shared chromatin loops and cell-specific loops that contribute to cell-specific expression of genes that are responsible for differentiation and cellular function. Even for genes showing similar expression levels in both cell types, the interactions of regulatory elements, especially of enhancers, exhibit different patterns, suggesting that gene expression could be differentially regulated in different cells.Enhancer-promoter interaction loops play a critical role in controlling the temporospatial expression of genes90 via an extrusion model23. Several specific transcription factors have been found to contribute to chromatin looping between enhancers and promoter58. YY1 facilitates the loop formation between enhancer and promoter and regulates gene expression, and ZNF143 was reported to act with CTCF to facilitate chromatin looping. However, in general, the mechanisms that regulate enhancer-promoter looping require much clarification. In this study, we found that in addition to CTCF and RAD21, ZNF143 and HCFC1 are also among the top enriched factors and shared among GM12878 and K562 cells, suggesting that these two factors may play a general role in chromatin looping. Interestingly, over 96% of the loop anchors co-bound by ZNF143 and HCFC1 in GM12878 cells involved enhancers and promoters, while only 38% of the loop anchors were co-bound by CTCF and RAD21 in GM12878 cells involved enhancers and promoters, suggesting that ZNF143 and HCFC1 play a general role in contributing to enhancer-promoter loops. The loops disrupted by knocking down HCFC1 and/or ZNF143 showed a median size of 20 kb, consistent with the size of enhancer and promoter interactions, while the loops disrupted by knocking down CTCF and/or RAD21 showed a median size of about 100 kb, consistent with the distance between domain boundaries.Chromatin loops can be roughly separated into three categories based on the location of loop anchors relative to chromatin domain organization: (1) in the TAD boundaries; (2) in the sub-TAD boundaries; and (3) within TADs and sub-TADs. They can also be categorized based on the functional annotation of the loop anchors: (1) promoters; (2) enhancers; and (3) others. While the loops linking enhancers and promoters are often found within TADs or sub-TADs, others are mapped to the boundaries of these chromatin domains. Generally, the loops originating from the domain boundaries are much longer (>100 kb) than those linking enhancers and promoters (<100 kb). Previous data have established that CTCF and cohesin complex play critical roles in maintaining the chromatin interaction of TADs93, direct data to support the hypothesis are needed. Here, we found that HCFC1 and ZNF143 bound to the anchors of promoter loops at the ZNF gene cluster locus; the simultaneous knocking down HCFC1 and ZNF143 disrupted promoter-promoter loops and decreased the expression of these target promoters and thus providing strong evidence that the promoter-promoter looping contributes to the gene expression. However, since chromatin accessibility is necessary for Hi-TrAC to detect chromatin interactions, the decreased interactions detected by Hi-TrAC could be derived from either decreased interaction alone or from decreased accessibility and interactions together, both of which could be regulated by HCFC1 and ZNF143. Based on these results, we propose that different architectural proteins show a division of labor for organizing chromatin looping: CTCF and RAD21 are responsible for building the outer frame of chromatin domains, whereas HCFC1 and ZNF143 decorate the inner structures by organizing looping between regulatory elements. With the development and completion of high-resolution genome structure and more chromatin binding datasets of transcription factors, more chromatin looping regulators will be identified, including general ones and cell type-specific ones. Our comprehensive data on the interaction network among accessible chromatin regions provide a rich resource to further explore the complex function and mechanisms in genome organization.Although it was previously suggested that promoter-promoter interactions may facilitate gene expression by bringing the target promoters in close proximityGM12878 cells were purchased from Coriell Institute; K562 (CCL-243), 293 T (CRL-3216), mES-E14TG2a (CRL-1821), and mES-R1 (SCRC-1011) cells were purchased from ATCC.2O for 12 cycles. The DNA fragments between 300 bp and 700 bp were excised for paired-end sequencing on Illumina platforms.Cells were fixed with 1% Formaldehyde in a culture medium at room temperature for 10 min. Wash the cells twice with 1 mL ice-cold PBS, then keep cells on ice. The Tnp complex was assembled by mixing 2 μL short adapter (50 μM), 2 μL bridging linker (25 μM) . shRNA targets are: Control-shRNA-1: GCGCGATAGCGCTAATAATTT, Control-shRNA-2: CAACAAGATGAAGAGCACCAA; CTCF-shRNA-1: GGAGAAACGAAGAAGAGTA, CTCF-shRNA-2: GTAGAAGTCAGCAAATTAA; RAD21-shRNA-1: AGAGTTGGATAGCAAGACA, RAD21-shRNA-2: GGAAGCTAATTGTTGACAGTGTCAA; HCFC1-shRNA-1: GCAACCACCATCGGAAATAAA, HCFC1-shRNA-2: AGAACAACATTCCAAGGTACCTGAA; ZNF143-shRNA-1: GCTACAAGAGTAACTGCTAAA, ZNF143-shRNA-2: GGACGACGTTGTTTCTACACAAGTA. Co-transfect 12 μg lentivector with packaging plasmids 9 μg psPAX2  and 3 μg pMD2.G  into 293 T cells cultured in 100 mm dish. Change with 12 mL fresh medium at 12 h after transfection, and medium supernatant containing virus was collected at 72 h after transfection. Add the medium to 3 million K562 cells to start transduction. Cells were harvested 72 h after infection. Protein expression was checked by western blotting. We used Invitrogen NuPAGE gel electrophoresis system following the owner’s manual, and proteins were transferred onto PVDF membrane. Primary antibodies used for detecting corresponding proteins are: anti-CTCF , anti-RAD21 , anti-HCFC1  and anti-ZNF143 .94.Total RNA from 5000 cells was extracted and purified with QIAzol Lysis Reagent (QIAGEN) and RNeasy mini kit (QIAGEN). RNA-seq library was constructed with purified RNA following the Smart-seq2 protocolCRISPR targeting sequences were designed and cloned into pSpCas9(BB)−2A-Puro vector (Addgene #62988). Following transfection of K562 cells with Cas9 and sgRNA expressing plasmids for 24 h, the cells were treated with 2 μg/mL Puromycin for 48 h to kill non-transfected cells. Surviving cells were sorted into 96-well plate at a density of one cell per well, cultured for two to three weeks, and genotyped using specific PCR primers for identification of loop anchor deletion clones. The targeting sequences used are following: CEMIP2-E2, 1-GATCGAGTTCTAGTTGACCC, 2-GTGCGTCTATGAATCTGCGC; CEMIP2-E3, 1-GTAAGCACATGGCCCGTCAG, 2-TCGAACAGGAACGTACTATC; CEMIP2-E5, 1-CTAACGCAATCCACCTAGAA, 2-TAAGGCTCTCTACTTAGCGG; ZNF225-promoter, 1-TGGCGCTTAACGACGAACCC, 2-TTTATGGGGCACGGCGACCA; ZNF234-promoter, 1-AAGGAGGATCCTATACGTGA, 2-TAAGCCGCAACGTGACTCTG.Public data used in this study, including Hi-C, HiChIP, ChIA-PET, capture Hi-C, MCC, Micro-C, RNA-seq, ATAC-seq, DNase-seq, and ChIP-seq, were summarized in 95 were used in any gene-related analysis. Human genome version hg38 and mouse genome version mm10 were used in this study. If human or mouse data are generated in other genome versions, they are always converted to hg38 or mm10 for analysis.Human (gencode.v30.basic.annotation.gtf) and mouse (gencode.vM21.basic.annotation.gtf) gene annotations from GENCODE96 and processed as following: 1) all regions annotated as “Enh” and “Tss” were collected; 2) overlapping regions were merged with BEDtools merge; 3) merged regions were further annotated by annotatePeaks.pl in HOMER package97 with gene annotation file downloaded from GENCODE95; if a region is within 2 kb either upstream or downstream of a TSS, it is defined as a promoter; otherwise it is defined as an enhancer. 4) neighboring enhancers or promoters with gaps <100 bp were merged again by BEDtools merge.Putative enhancer and promoter annotations of human cells were obtained from NIH Roadmap Epigenomics ConsortiumPutative cis-regulatory elements of mouse embryonic stem cells were defined by ATAC-seq peaks. If a peak is within 2 kb either upstream or downstream of a TSS, it is defined as a promoter; otherwise, it is defined as an enhancer.98 with –end-to-end–very-sensitive parameter. Mapped PETs with MAPQ ≥ 10 were converted to BEDPE files. Mapped PETs with a distance shorter than 1 kb without linker sequence in any end were further filtered. PCR replicates of PETs were filtered if the locations of both ends were identical. Unique intra-chromosomal PETs (cis PETs) as BEDPE files were mainly used for downstream analysis. All the described processing steps were summarized as tracPre2.py in the cLoops2 package99. Quality control statistical results were also generated by tracPre2.py. BEDPE files were used to analyze PET level properties, and the cLoops2 pre-module processed them to cLoops2 data directories for other analyses such as domain-calling, loop-calling, and visualization.Raw paired-end reads in FASTQ files were first trimmed of the linker sequence CTGTCTCTTATACACATCT from both ends. Only paired-end tags (PETs) with both ends with a length ≥ 10 bp were kept. Trimmed PETs were mapped to hg38 using Bowtie299.Virtual 4 C signals were generated by only keeping the PETs with one end located within 1 kb either upstream or downstream of target TSSs. These PETs were then piled up as the 1D signal. The method is implemented in the cLoops2 plot module for visualization or the cLoops2 dump module for data extraction100 with parameter settings of –cpu –ignore-sparsity -r 2500 -f 0.1 -k KR -p 4 -i 8 -d 2 for the 2.6 billion PETs HIC file downloaded from GEO, according to the original paper as leading to the most of loops compared to other resolutions60. More loops were called from the Micro-C data than the original paper due to the upgrades of the HiCCUPS algorithm60. The loop-calling algorithm described in cLoops101 was slightly improved and implemented as the cLoops2 callLoops module99 for loop-calling with Hi-TrAC data. mESC Hi-TrAC loops were called by the cLoops2 callLoops module with parameters of -eps 200,500,1000,2000 -minPts 20 -p 30 -w -j -i -max_cut -cut 5000. For the overlapping analysis, loop anchors were extended to 5 kb, unique and overlapped loops were obtained by pairtopair subcommand in BEDTools (v2.29.2) package102 with -type notboth or -type both options.Micro-C loops were called by HiCCUPS in Juicer package (v1.22.01)The cLoops2 callLoops module with key parameters settings of -eps 200,500,1000,2000 -minPts 10 -max_cut was used to call loops from GM12878 Hi-TrAC data, requiring a loop supported by at least 10 PETs. For K562 Hi-TrAC data, loops were called by parameters settings of -eps 200,500,1000,2000 -minPts 10 -cut 5000 to filter PETs with distance short then 5 kb, by which the default parameters will automatically filter all loops short than 20 kb.An 11 × 11 contact matrix was constructed for a loop from interacting PETs, together with its five upstream and downstream windows of the same size. An individual enrichment score for a loop was calculated as the number of PETs in the 11 × 11 contact matrix center divided by the mean value of all others. The global enrichment score was the mean value of all enrichment scores for individual loops. The 11 × 11 contact matrix was further normalized by the total number of PETs in the matrix and z-score normalization. Heatmap was plotted of the average matrix for all normalized 11 × 11 matrices. The analysis was implemented in cLoops2 agg module with the option of -loops. Except for the parameters specifically mentioned, the default parameter with -loop_norm was used to generate visualization results.103 with CTCF motif recorded in CIS-BP database104.The whole-genome-wide CTCT motif orientations were annotated by FIMOLoops from samples under different conditions were combined and quantified in both conditions. The neighboring regions nearby loop anchors, which were the permutated nearby background regions defined in cLoops for estimation loops statistical test, were also quantified. The background data for the two conditions were fitted linearly. The fitted linear model was used to transform the PETs in loops of the treatment dataset to the control set, assuming there should be no difference in background data. False discovery rate (FDR) is a required parameter to find the cutoffs of average and fold change in the background data MA plot. The cutoffs were then applied to the transformed loops data. Poisson p-values were finally assigned to each loop as follows,99, and differentially enriched loops were called with key parameters of -fdr 0.05 for GM12878 vs. K562 Hi-TrAC data.This algorithm was implemented in the cLoops2 callDiffLoops module105  on 2020-08-09. For a loop, both the regions of three sizes upstream of its left anchor  and downstream of its right anchor (bigger coordinate in the genome) were linked as background data  for comparisons, to calculate the enrichment of TF binding sites on both anchors. Any background regions overlapping with true loop anchors were removed. The overlaps between anchors and background regions with transcription factor binding sites were compiled into the left anchors’ matrix and the right anchors’ matrix. Rows are anchors or backgrounds, and columns are factors in the binary matrix. In the binary matrix, 1 indicates the anchor is bound by the factor and 0 stands for no binding. With the two binary matrices, the following attributes were calculated and used to find enriched transcription factors: 1) anchors consistency: for a TF, a vector from the left anchor matrix and a vector from the right anchor matrix were used to calculate the Spearman correlation coefficient, indicating the co-binding consistency of a factor at both anchors. 2) anchors co-binding ratio: for a TF, the ratio of anchors bound by the TF. 3) TF peaks overlap ratio: for a TF, ratio of peaks overlapping with loop anchor regions. To filter TFs, the following cutoffs were used: 1) comparing to the background, ratio of consistency >2; 2) anchors co-binding ratio >0.1; 3) comparing to the background, the ratio of co-binding ratio >2; 4) comparing to the background, the ratio of TF peaks overlap ratio ≥ 1. Except for using the anchor flanking regions as background, we also implemented the random shuffling value 1000 times as background to ensure the observed attributes are higher than permutation background and require FDR < 0.001. The remaining TFs were sorted by consistency in descending order, by which known looping associated factors such as CTCF and cohesin are among the top-ranked factors.Integration of public ChIP-seq data and Hi-TrAC loops was intended to identify transcription factors associated with chromatin looping. We collected the binding sites for 162 transcription factors in GM12878 and 360 transcription factors in K562 from ReMap 2020P-value 0.001 was used to select significantly changed loops.Raw Hi-TrAC data were processed by tracPre2.py first to extract the unique cis PETs 107. Gene annotation file (v30) downloaded from GENCODE95 was used to quantify gene expression level by Cufflinks (v2.2.1)108. Further, significant differentially expressed genes (knocking down samples vs. control) were called by Cuffdiff (v2.2.1) in Cufflinks package, requiring P-value <0.001 and fold changes ≥1.Raw RNA-seq data reads were mapped to human reference genome hg38 by STAR (v2.7.3a)g for 10 min in a 4 °C microcentrifuge. 10% of the chromatin supernatant was saved as input. Mix 2 μg antibody with 20 μL Dynabeads Protein A beads  with rotation at room temperature for 1 h. Wash the beads once with 1× PBS, then add chromatin solution to beads, and incubate at 4 °C overnight with rotation. Wash the beads twice with RIPA buffer, then twice with RIPA buffer plus 300 mM NaCl, then twice with LiCl buffer , and finally twice with 1x TE buffer. Elute DNA and reverse crosslinking by protease K digestion and incubating at 65 °C for 6 h. Purify DNA with MinElute Reaction Cleanup Kit . Repair ends of DNA using End-It DNA End-Repair Kit , then perform A-tailing with Klenow Fragment (3’-> 5’ exo-)  provided with dATP, and then perform adapter ligation with T4 DNA ligase . Amplify the library and add index by PCR. DNA fragments between 200 bp and 600 bp were purified and sequenced on Illumina platforms.Control and TF knockdown K562 cells were fixed with 1% Formaldehyde in culture medium at room temperature for 10 min. Wash the cells twice with 1 mL ice-cold PBS, then keep cells on ice. 0.1 million fixed cells were used for CTCF and RAD21 ChIP-seq library preparation, and 0.5 million cells were used for HCFC1 and ZNF143 ChIP-seq library preparation. Resuspend cells with 1x TE buffer provided with 1 mM PMSF and 1x protease inhibitor cocktail. Chromatin shearing was performed on a Diagenode Bioruptor Pico sonication device at 4 °C for 6 cycles with 30 sec on and 30 sec off, resulting in 200–1000 bp fragments. Adjust chromatin solution to 1x RIPA buffer  plus 200 mM NaCl. Collect the chromatin supernatant after centrifugation at 15,000 × The following antibodies were used in the experiments: anti-CTCF , anti-RAD21 , anti-HCFC1  anti-ZNF143 .109.ATAC-seq was performed with 50,000 cells following the protocol as reported2O, 50 μL 10× CutSmart Buffer, 44 μL 1% SDS). Incubate at 65 °C for 10 min. Add 50 μL of 10% Triton X-100, then shake on a thermomixer at 37 °C for 1 h. Add 100 U selected restriction enzyme , then incubate at 37 °C overnight with shaking. Collect digested nuclei by centrifugation, then resuspend with 100 μL inactivation buffer , and incubate at 65 °C for 20 min. Add 895 μL diluted T4 ligation buffer  and mix well. Add 100 U T4 DNA ligase, and incubate at 16 °C overnight. Add 30 μL 10% SDS and 100 μg Protease K to stop the ligation reaction, then incubate at 65 °C to reverse crosslinking. Purify 3 C libraries by Phenol-Chloroform extraction. Design primers and probes according to the sequence of the interaction pair, then quantify the interaction frequency by qPCR. The promoter region of MYC gene was used as input control. Used primers and probes are: MYC promoter input, forward: CTCAGCAGCAGCTCCAAATA, probe: /56-FAM/AGAGTGCTG/ZEN/CTAGAGCAACAAGCA/3IABkFQ/, reverse: GACCATGGAAGTTGCCTTCT; MYC promoter-enhancer, forward: TCATTTCAGGGAGCAAACAAATC, probe: /56-FAM/ACGCTTCGA/ZEN/CTTAGCTAGTTGCCC/3IABkFQ/, reverser: TTACTCTGGAATAGGTTCCATGC; ZNF224-ZNF284, forward: GACTGGTGGTCTCTTCTTAGTG, probe: /56-FAM/ATTTCCCAC/ZEN/GAAGCCTGTCAGGTC/3IABkFQ/, reverse: TCGATCACCAGTTCTTTGAGG; ZNF225-ZNF235, forward: GTAGCTGGATCTCCTAGACTCA, probe: /56-FAM/AGGAGTTTC/ZEN/CAAACAACAGGCGTCT/3IABkFQ/, reverse: ATTAACATTGTATCAAATATTGCTCAACCA; MRPL24-PRCC, forward: GCCTGGCACATACTGAATACT, probe: /56-FAM/AAAGGATAG/ZEN/GCTCTTCCCGCACC/3IABkFQ/, reverse: GCGGAAAGTGGAGGTGAG; NDC1-TCEANC2, forward: AGACCGAGTCAAATGCTTCAG, probe: /56-FAM/TAGTCTAGG/ZEN/GCGTACAGGAGACCG/3IABkFQ/, reverse: GCCTTCCTGCCTTTGAACT.Resuspend 1 million fixed cells with 1 mL ice-cold lysis buffer , then incubate on ice for 20 min. Collect cells by centrifugation at 4 °C, then resuspend with diluted CutSmart buffer  as bigWig files by deepTools110 for visualization or aggregation analysis.Raw ChIP-seq and ATAC-seq data reads were mapped to human reference genome hg38 by Bowtie297. Only top-ranked significant known motifs were shown.Motif analysis for Hi-TrAC loop anchors or ChIP-seq peaks was performed by findMotifsGenome.pl in HOMER package97, requiring more than ten overlapping genes in the terms, and there are fewer than 1000 genes in the terms. Only top-enriched terms sorted by P-values were shown.GO terms enrichment analysis for genes was performed by script findGO.pl in HOMER package111. Other plots were generated by matplotlib112 and seaborn113.Most of 1D profile and heatmap visualizations were shown by the cLoops2 plot module. Networks were visualized and analyzed by NetworkXNo statistical method was used to predetermine sample size of Hi-TrAC libraries. No data were excluded from the analyses. The experiments were not randomized.Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Supplementary Data 11Reporting Summary