Acute depletion of CTCF directly affects MYC regulation through loss of enhancer-promoter looping.
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Abstract
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Acute depletion of CTCF directly affects MYC regulation through loss of enhancer–promoter looping
Numerous pieces of evidence support the complex, 3D spatial organization of the genome dictates gene expression. CTCF is essential to define topologically associated domain boundaries and to facilitate the formation of insulated chromatin loop structures. To understand CTCF’s direct role in global transcriptional regulation, we integrated the miniAID-mClover3 cassette to the endogenous CTCF locus in a human pediatric B-ALL cell line, SEM, and an immortal erythroid precursor cell line, HUDEP-2, to allow for acute depletion of CTCF protein by the auxin-inducible degron system. In SEM cells, CTCF loss notably disrupted intra-TAD loops and TAD integrity in concurrence with a reduction in CTCF-binding affinity, while showing no perturbation to nuclear compartment integrity. Strikingly, the overall effect of CTCF’s loss on transcription was minimal. Whole transcriptome analysis showed hundreds of genes differentially expressed in CTCF-depleted cells, among which MYC and a number of MYC target genes were specifically downregulated. Mechanically, acute depletion of CTCF disrupted the direct interaction between the MYC promoter and its distal enhancer cluster residing ~1.8 Mb downstream. Notably, MYC expression was not profoundly affected upon CTCF loss in HUDEP-2 cells suggesting that CTCF could play a B-ALL cell line specific role in maintaining MYC expression.
CCCTC-binding factor (CTCF) is a transcription factor with 11 zinc finger domains ubiquitously expressed in cells of eukaryotes. Initially identified as a transcriptional repressor of chick c-myc (1,2), CTCF has since been shown to be a multi-functional gene necessary for survival and differentiation in mammals. Mouse genetic studies have revealed that Ctcf is required during early embryogenesis, with homozygous Ctcf knock-out mice survival limited to 5.5 days post coitum (dpc) (3,4). Although heterozygous Ctcf mice were viable and fertile, they exhibited a notably increased cancer incidence in aged animals (5). In addition, conditional knock-out mouse studies using Ctcfflox/flox mice crossed with various tissue-specific Cre-expressing strains confirmed the requirement of Ctcf during organ development (6–9).
CTCF is an important regulator of the 3D chromatin architecture of interphase chromosomes, which guides gene expression (10–13). However, the complex and dynamic organization of the genome within the nucleus is not fully understood. At the broadest level of organization, chromosomes are spatially arranged into non-random chromosomal territories generally defined by nuclear localization, and these territories are organized at the multi-Megabase (Mb) scale into either open, active A compartments or closed, inactive B compartments (14–17). Compartment structures are further organized into various sized topologically associated domains (TADs), which provide an insulated neighborhood that maintains transcriptional regulation in vivo (18). CTCF is well-characterized as a transcription factor that binds to insulator elements to define TAD boundaries, and along with cohesin proteins, promote the formation of CTCF–CTCF insulated chromatin loop structures. These structures spatially compartmentalize interacting promoters and enhancers into regulatory domains that allow for dynamic gene transcriptional regulation through proximal and distal intra-TAD chromatin looping (11,18–20). Intra-TAD DNA loops between enhancer and promoter regions have also been shown to be facilitated by CTCF (18,21). Significantly, meta-analysis of CTCF-mediated chromatin loops identified the unique pattern that two CTCF-binding sites must be oriented in a convergent manner to favor direct DNA contact and binding by cohesin proteins (21).
Previous attempts to address CTCF’s role in genome organization and transcriptional regulation in human cell lines have relied on either targeted disruption of CTCF-binding sites at specific TAD boundaries (22–24) or global RNA depletion by siRNA and antisense oligos (25,26), none of which are reversible. While these studies offered valuable insights into CTCF’s involvement in TAD boundary insulation and chromatin looping maintenance, the studies were not sensitive enough to fully deplete CTCF in an acute manner. In addition, accumulated secondary transcriptional responses might occur during the long-term establishment of knockdown cell lines. More recently, the auxin-induced degron (AID) system was utilized in a mouse embryonic stem (ES) cell model to integrate a miniAID epitope tag fused to the mClover3 fluorescent reporter gene to the endogenous Ctcf locus by clustered regularly interspaced short palindromic repeats (CRISPR/Cas9) genome editing. In the presence of doxycycline and auxin, enforced expression of OsTIR1 combines with Skp1/Culin/F-box (SCF) ubiquitin ligase components in the cell to form a functional SCF/OsTIR1 E3 ubiquitin ligase complex that rapidly degrades Ctcf protein in minutes, which was reversible after doxycycline and auxin were completely removed (27–29). Results from the study showed that loss of Ctcf did not abrogate genomic organization at the larger, compartmental scale, but did disrupt TAD insulation and chromatin looping between boundaries, resulting in a 10-fold increase in differentially expressed genes over a 4-day time course. Compared with previous functional studies of CTCF utilizing mRNA knockdown by shRNA, antisense oligo or Cre/LoxP induced Ctcf+/− tissues (4,5,30), AID system allowed for complete depletion of Ctcf in an acute and reversible manner, and greatly improved the investigation to identify Ctcf’s direct effect on chromatin organization and transcriptional regulation.
In human cells, CTCF’s role in genomic organization and global transcription regulation is less clearly defined due to the lack of available tools to efficiently deplete CTCF. Here, we used an AID system to conditionally deplete CTCF in a human B-cell lymphoblastic leukemia (B-ALL) cell line, SEM (31), and an immortal human erythroid precursor cell line, HUDEP-2 (32). To create the reporter cell lines, we developed a novel knock-in strategy termed CHASE-knock-in that combined homology-mediated end joining (HMEJ)-based (33) donor design with flow cytometry based serial sorting to improve knock-in efficiency in hard to target human cell lines. Our data supported the recent reported data that acute loss of Ctcf does not affect nuclear compartmentalization on the multi-Mb scale, but does significantly disrupt TAD boundary integrity and enhancer–promoter looping (29,34). Notably, even though chromatin organization was altered, the impact on global transcription was minimal suggesting the direct targets of CTCF were limited. Longer depletion of CTCF may be necessary for chromatin architectural changes to affect gene regulation of indirect targets. Here, we present evidence supporting that MYC was highly susceptible to CTCF depletion, and that the transcriptional regulation of MYC was mediated through a long-distance CTCF dependent enhancer–promoter interaction.
Vector construction
The all-in-one CRISPR/Cas9-CTCF-gRNA (V6) construct was derived from a previous study (35). All target-specific single guide RNAs (gRNAs) were predicted by online software (http://crispr.mit.edu/) (36). Paired oligomers containing 20 bp of selected target sequence were synthesized from Thermo Fisher Scientific Company and cloned into the all-in-one vector between BsmBI sites. All oligo information were listed in Supplementary Table S1. Individual bacterial clones were screened and confirmed by Sanger sequencing with the U6-Forward sequencing primer: 5′GGGCAGGAAGAGGGCCTAT3′. A two-step in-fusion cloning protocol was performed to generate the CTCF-miniAID-mClover3 donor knock-in vector. Cloning primers were designed to amplify the 800 bp HA 5′ to the endogenous CTCF gRNA target. Overhangs of 23 bp including the target gRNA and PAM sequences (5′GCACAAGGCTCCGCCATCACCGG3′) were added to the 5′ end of the forward primer amplifying the 5′ HA sequence. The 3′ HA was generated with a similar design (reverse primer containing 23 bp including the target gRNA and PAM sequences), but also included an additional overhang for in-fusion cloning (Clontech). Both HAs were amplified from genomic DNA of SEM cells. The miniAID-mClover3 DNA fragment was amplified from pMK290 vector (Plasmid #72828, Addgene) (37). Snapgene software was used to design all primers used for in-fusion cloning. The PCR reactions were performed using CloneAmp polymerase (Clontech) and the cycling parameters were as follows for all cloning: 98°C for 5 min, followed by 40 cycles of 98°C for 15 s, 55°C for 20 s and 72°C for 20 s. First, the amplified 5′ HA was cloned into pCR-Blunt II-TOPO vector (Thermo Fisher Scientific). The DNA was purified from colonies and screened by Sanger sequencing with the primers M13F and M13R. The pCR-Blunt II-TOPO-gRNA-PAM-5′HA was then linearized by PacI digestion and ligated with miniAID-mClover3, and the 3′HA-gRNA-PAM through in-fusion cloning protocol (Clontech). Sanger sequencing was performed to ensure that the knock-in DNA was seamlessly cloned in-frame with the CTCF peptide. The doxycycline-regulated OsTIR1 expression plasmid (pMK243) was purchased from Addgene (Plasmid #72835, Addgene). The primers and sequences used for cloning vectors are listed in Supplementary Table S1.
Cell culture
The human B-ALL cell line SEM (DSMZ) was maintained in RPMI-1640 medium (Lonza) containing 10% fetal bovine serum (FBS) (Hyclone), 2 mM glutamine (Sigma) and 1% penicillin/streptomycin (Thermo Fisher Scientific). Immortal human erythroid precursor cell line HUDEP-2 was expanded in StemSpan SFEM (Stem Cell Technologies) supplemented with 1 μM dexamethasone, 1 μg/ml doxycycline, 50 ng/ml human SCF, 3 Units/ml EPO and 1% penicillin/streptomycin. All cells were maintained at 37°C in a 5% CO2 atmosphere and 95% humidity. All cells were tested negative for mycoplasma infection. Cell identity of SEM was confirmed by short tandem repeat (STR) analysis.
Electroporation
SEM and HUDEP-2 cells were electroporated by using the Nucleofector-2b device (Lonza) with the V-kit and program X-001. For CTCF-miniAID-mClover3 knock-in delivery, 2.5 μg of the donor plasmid and 2.5 μg of the CRISPR/Cas9-CTCF-gRNA plasmid were used for 5 million SEM cells. For the doxycycline-regulated OsTIR1 integration, 2.5 μg of pMK243 and 2.5 μg of the CRISPR/Cas9-AAVS1-gRNA plasmid were co-delivered into 5 million SEM cells.
Flow cytometry
To determine the percentage of cells that were mClover3-positive, suspension cultured SEM cells were collected by centrifugation at 800 g and filtered through a 70 μm cell filter before flow cytometry sorting. Fluorescence from mClover3 was detected by using the same FL1/FITC channel as GFP. DAPI was added to the cell suspension to exclude dead cells.
Characterization of on-target knock-in events by genomic PCR and Sanger sequencing
All cells stably integrated with knock-in cassettes were harvested for DNA extraction by PureLink Genomic DNA Mini Kit (Thermo Fisher Scientific) 5 weeks after co-electroporation with the CTCF-miniAID-mClover3 donor vector and CRISPR/Cas9-CTCF-gRNA plasmid. Specific primer sets designed to recognize the 5′ and 3′ knock-in boundaries were used with the following PCR cycling condition: 98°C for 5 min, followed by 40 cycles of 98°C for 15 s, 55°C for 20 s and 72°C for 20 s. The bands with expected size were cut out, purified and ligated to pCR-Blunt II-TOPO vector for Sanger sequencing by the M13F and M13R primers. Single cell-derived clones 27, 35 and 42 were genotyped for homozygous insertion of the miniAID-mClover3 cassette, and clone 36 for heterozygous knock-in.
Immunoblotting
Cells lysate was prepared by using RIPA buffer followed with SDS-PAGE (Thermo Fisher Scientific) and transferred to a PVDF membrane according to the manufacturer’s protocols (Bio-Rad) at constant 100 V for 1 h. After blocking incubation with 5% non-fat milk in TBS-T (10 mM Tris, pH 8.0, 150 mM NaCl, 0.5% Tween-20) for 1 h at room temperature, the membrane was incubated with antibodies against GAPDH (Thermo Fisher Scientific, AM4300, 1:10,000), AID (MBL, M3-214-3, 1:2,000), MYC (Cell Signaling Technology, #9402, 1:1,000), ACTIN (Sigma, MABT825, 1:5,000) and CTCF (abcam, ab70303, 1:1,000) at 4°C for 12 h with gentle shaking. Membranes were washed three times for 30 min and incubated with a 1:2,000 dilution of horseradish peroxidase-conjugated anti-mouse or anti-rabbit antibodies for 2 h at room temperature. Blots were washed with TBS-T three times for 30 min and developed with the ECL system (Amersham Biosciences) according to the manufacturer’s protocol.
Auxin-induced degradation
Successful knock-in clones were cultured in medium supplemented with doxycycline (1 μg/ml) to induce the expression of OsTIR1. Three single-cell derived clones were treated with culture medium supplemented with 500 μM IAA (natural auxin) (Sigma) for 24 or 48 h to induce degradation of CTCF. ‘Wash’ cells were prepared from treated cells that were centrifuged and resuspended by PBS three times followed with an additional culture for 48 h in regular medium.
RNA-sequencing
Total RNA was extracted by Trizol (Thermo Fisher Scientific, 15596026) from replicate samples of cells treated with or without IAA for 24 or 48 h. About 200 ng total RNA were treated using Kapa rRNA depletion reagents to remove ribosomal RNA, then converted into cDNA libraries using Kapa RNA HyperPrep Kit with RiboErase (HMR). After end repair, dA-tailing and adapter ligation, each cDNA library was purified and enriched by 11 cycles of PCR amplification. All RNA-seq libraries underwent 151-cycle paired-end sequencing on the Illumina NextSeq 500 system. FASTQ data of RNA-Seq were mapped to genome hg19. RNA-Seq reads from each species were aligned using Bowtie2 2.3.4 (38). Fragments per kilobase per million sequenced reads (FPKM) value were obtained using cufflinks v2.2.1 (39). Per-gene read counts were obtained using HTSeq v. 0.6.1 (40). Differentially expressed genes (DEGs) were identified using count data generated as described above and DESeq2 (version 1.14.0) (41). The log2(Fold change) of all genes from whole transcriptome comparison (CTCFAID-IAA versus CTCFAID+IAA) were uploaded for GSEA analysis (42). FPKM values of all genes were provided in Supplementary Table S2.
Quantitative real-time PCR
Reverse transcription was performed by using the High-Capacity cDNA Reverse Transcriptase Kit (Applied Biosystems, 4374966). Real-time PCR was performed using FAST SYBR Green Master Mix (Applied Biosystems, 4385612) based on manufacturer’s instructions with primers to detect CTCF, MYC and GAPDH (Supplementary Table S1). Relative gene expression was determined by using the ΔΔCT method (43).
Hi-C and data analysis
In situ Hi-C experiments were carried out as previously described (18). Briefly, five million CTCFAID SEM cells (clones 27 and 35) with or without IAA treatment were crosslinked with 1% formaldehyde for 10 min at room temperature, digested with 125 Units of MboI, labeled by biotinylated nucleotides and ligated for proximity ligation. After de-crosslinking, ligated DNA was purified and sheared to 300–500 bps. Ligation junctions were then pulled down with streptavidin beads and prepped as a standard Illumina library. Each library underwent 75-cycle paired-end sequencing on Illumina HiSeq 4000 system. About 100 million reads were obtained for each sample. Raw sequence data were mapped and processed using Juicer v1.5 (44) with default parameters. The Hi-C data and MboI cut sites were mapped to hg19. Replicates data were first processed separately. After confirmation of good reproducibility by HiC-Spector (Supplementary Figure S3C) (45), we merged the replicates and re-processed as combined results. The data were visualized with the Juicebox (46). Our Hi-C samples’ resolution was between 8 and 20 kb, and the median resolution of merged samples was ~18.5 kb. TADs and loops were called by Arrowhead and HiCCUPS from Juicer pipeline. We provide their annotated results in Supplementary Table S3. The Cis Eigenvector values were calculated by eigenvector function of Juicebox at 250 kb resolution.
Capture-C
Capture-C was performed on two CTCFAID knock-in clones 27, 35 and the CTCFAID heterozygous knock-in clone 36 following the protocol described by Davies JO et al. (47). To quantify interaction frequency between MYC promoter and distal enhancers, signal value from .bw file was analyzed by bigWigToBedGraph, then normalized by probe signal for each experiment (48). Capture-C oligo information was included in Supplementary Table S1.
Cut&Run assay
Cut&Run assay of CTCF was performed as previously described (44). Three million cells were collected for each sample. Cells were pelleted at 600 g for 3 min at room temperature. Cell pellets were washed twice with 1.5 ml room temperature wash buffer. Cell pellets were resuspended in 1 ml wash buffer at room temperature. While gently mixing, 100 μl concanavalin beads (BioMagAPlus Concanavalin A, Polysciences, 86057-3; prewashed and resuspended in 100 μl binding buffer) were added to the samples, followed with gentle rotation for 10 min at room temperature. Samples were placed on a magnetic stand and the supernatant was removed. Beads were resuspended in 200 μl AB buffer (Dig-wash buffer with 0.02% digitonin and 0.5 M EDTA) with 1.6 μg CTCF antibody (abcam, ab70303). Samples were rotated at 4°C for 2 h. Samples were placed on a magnetic stand and supernatant was removed. Beads were gently resuspended in 200 μl Dig-wash buffer with 0.02% digitonin, and 2 μl PA-MN (homemade reagent kindly provided by Dr Steven Henikoff) was added to each sample, followed by rotation at 4°C for 1 h. Samples were placed on a magnetic stand and supernatant was removed. Beads were washed for a total of three times in 1 ml Dig-wash buffer, pipetting gently. Following the final wash, beads were resuspended in 100 μl Dig-wash buffer by gentle mixing and transferred to a new tube. On ice, 2 μl 100 mM CaCl2 was added to the sample with gentle mixing. Afterward, samples were incubated on ice for 30 min. Then 100 μl stop buffer was added to the samples and samples were incubated for 10 min at 37°C followed by centrifugation at 4°C, 12,000 rpm. Samples were placed on a magnetic stand and the supernatant containing the Cut&Run fragments was collected. To the samples, 2 μl 10% SDS and 2.5 μl proteinase K were added and the samples were incubated at 50°C overnight. DNA was extracted by the phenol/chloroform/isopropanol protocol. Library construction was performed using the NEBNext UltraII DNA Library Prep Kit from NEB (E7645S). Indexed samples were sequenced using the Illumina MiSeq V3 600-cycle kit (MS-102-3003).
Analysis of Cut&Run data
Paired-end reads were trimmed for NEB index adapter by cutadapt (version 1.9, paired-end mode, default parameter with ‘-m 6 -O 20’) and aligned to human genome hg19 by BWA (version 0.7.12-r1039, default parameter) (49). Duplicated reads were then marked with Picard (version 2.6.0-SNAPSHOT) and only non-duplicated proper paired reads were kept by samtools (parameter ‘-q 1 -F 1804’ version 1.2) (50). To evaluate the Cut&Run assay quality, we first separated reads by fragment size <120 bp, or fragment size >150 bp and <2,000 bp and generated bigwig files for visualization. We observed a clear pattern that peaks in tracks with <120 bp were sharper and surrounded by peaks in tracks with >150 bp on IGV (version 2.4.13), which was consistent to the description from the original Cut&Run protocol paper (51). We then generated bigwig files using all reads that fragment size <2,000 bp. Our samples contained 4–11 million uniquely mapped reads that are comparable to published data. A R package ChIPseeker (version 1.18.0) was used for annotating Narrow peaks from MACS2 (52,53).
To check whether our reduced CTCF sites upon CTCF loss demonstrated bias toward 2XCTSes compared with CTCF only sites (1XCTSes), we first called peaks individually from each of the three clones (clones 27, 35 and 42 with or without IAA) by MACS2 (version 2.1.1.20160309, ‘-f BAMPE –extsize 200 –nomodel’) twice using high confidence cutoff FDR correct P-value ≤0.05; or low confidence cutoff FDR correct P-value ≤0.5, respectively. To obtain reproducible peaks, we only kept peaks called at least once in high confidence cutoff and in either high or low confidence cutoff for the other two replicates. After merging reproducible peaks from samples with or without IAA and removing overlapped peaks (blacklist) (54), we counted reads from three single cell derived clones with overlapped peaks, calculated FPKM and compared between +IAA versus -IAA groups. To further define CTCF peaks with high stringency, we scanned genome-wide CTCF motif predicted by TRANSFAC (55) and JASPAR (56) using FIMO from MEME suite (57) (version 4.11.3, ‘–motif-pseudo 0.0001 –thresh 1e-4’) and kept peaks carrying CTSes annotated by ‘TRANSFAC_CTCF_M01259’ (Figure (Figure2D2D--EE and Supplementary Figure S2H). The ratio calculated by log2fold change (CTCFAID+IAA/-IAA) was utilized to define reduced (log2fold change≤-1), retained (-1<log2fold change≤1) and gained (log2 fold change>1) CTSes.
CTCF degradation disrupted global CTCF occupancy. (A) CTCF Cut&Run tracks shown at the selective viewpoint of TP53 locus where significant reduction of CTCF binding following 48 h IAA treatment was observed from clones 35 and 42. (B) CTCF Cut&Run tracks shown at the selective viewpoint of EIF5A locus where minimal reduction of CTCF binding following 48 h IAA treatment was observed from clones 35 and 42. (C) Genomic distribution of all CTCF binding peaks carrying CTSes were analyzed by ChIPseeker for all peaks (13,287), reduced peaks (6,394), retained peaks (6,740) and gained peaks (153) collected from clones 27, 35 and 42 with and without IAA treatment for 48 h. (D) Global reduction of CTCF binding affinity was demonstrated by MA plot for 1XCTSes, 2XCTSes and 3XCTSes. The X-axis indicated mean CTCF binding read density calculated by FPKM from Cut&Run analysis, while Y-axis indicated log2fold change (+IAA/-IAA) of CTCF binding read density. (E) Statistical analysis of CTCF binding reduction among 1XCTSes, 2XCTSes and 3XCTSes groups was performed by showing Wilcox P value.
Statistical analysis
Statistical analysis was performed by GraphPad Prism 6.0. P-values in Q-PCR, RNA-seq and quantification of Capture-C results were calculated by performing a two-tailed t-test from two or three independent biological replicates.
The miniAID cassette knock-in to the endogenous CTCF locus
We developed an optimized CRISPR/Cas9 with homology arm and sorting enrichment knock-in protocol, so called CHASE-knock-in, which combined HMEJ donor design (33) with flow cytometry based serial sorting to efficiently deliver the miniAID-mClover3 cassette to the endogenous CTCF locus in a human B-ALL cell line, SEM (31), and an immortal human erythroid precursor cell line, HUDEP-2 (32), each with doxycycline inducible OsTIR1 integration (Figure (Figure1A1A and Supplementary Figure S1A). Briefly, CHASE-knock-in requires co-delivering to cells the previously described CRISPR/Cas9 all-in-one vector (58) along with a knock-in cassette vector to generate CRISPR mediated double-cut nuclease cleavage and release of the knock-in cassette along with endogenous gRNA targeting to facilitate knock-in events, which were enriched by serial sorting for knock-in cassette fluorescence. In this study, a gRNA targeting the stop codon of CTCF was cloned into the CRISPR/Cas9 all-in-one vector, called CRISPR/Cas9-CTCF-gRNA. The knock-in cassette vector, called CTCF-miniAID-mClover3, was designed to flank a miniAID-mClover3 cassette with homology arms (HAs) 800-bp upstream (5′ HA) and 800-bp downstream (3′ HA) from the CTCF gRNA target sequence. The ends of the HAs in the knock-in cassette were equipped with the CTCF gRNA and PAM sequence, which allowed for the knock-in cassette to be released from the vector in the presence of CRISPR/Cas9-CTCF-gRNA (Figure (Figure1A).1A). Twenty-four hours after co-delivery of CRISPR/Cas9-CTCF-gRNA plasmid and CTCF-miniAID-mClover3 donor vector by electroporation, cells were sorted for fluorescence of CRISPR/Cas9-CTCF-gRNA (mCherry). The sorted population recovered for 3 weeks in culture, followed by a second sort to detect the proportion of cells expressing the knock-in reporter fluorescence, mClover3. In SEM cells, we detected ~0.1% of the cells carried the mClover3 knock-in cassette following the second sorting. The cells containing the knock-in reporter were cultured for an additional 2 weeks and sorted a third time to expand the knock-in population. While initial knock-in efficiency was low, serial sorting led to an enriched knock-in population with 98.9% of the cells containing the mClover3 cassette following the third sort (Supplementary Figure S1B–D). High fluorescence density populations were selected to confirm successful knock-in events (Supplementary Figure S1E).
miniAID cassette knock-in to the endogenous CTCF locus. (A) Schematic diagram of the donor vector design for miniAID-mClover3 knock-in to the C-terminus of human CTCF before the stop codon. HA: homology arm; Endo-gRNA-PAM: CTCF endogenous guide RNA sequence and PAM sequences added to each end of the HAs. (B) A pair of primers residing outside the HAs was used for genomic PCR. Single-cell derived clones (Clones 27, 28, 34, 35, 39, 40, 42, 46 and 48) were identified to only carry the knock-in (KI) allele. Clone 36 was recognized as a mono-allelic knock-in clone (labeled blue). Clones 27, 35 and 42 were selected for subsequent studies (labeled red). (C) Multiple single cell-derived clones were expanded and treated with IAA and doxycycline for 48 h to degrade the CTCF-miniAID-mClover3 fusion protein. Knock-in clones 27, 35 and 42 demonstrated complete protein degradation after IAA treatment, as detected by immunoblotting. Mono-allelic knock-in clone 36 demonstrated specific degradation of the fusion protein translated from the knock-in allele and retained endogenous protein expression. The fusion protein was 35 KD larger than endogenous CTCF. GAPDH was included as loading control. (D) Q-PCR assessment of CTCF mRNA in response to CTCF protein depletion from three biological replicates treated with IAA for 48 h; knock-in clones 27, 35 and 42 (N = 3). (E) Clone 27 cells were treated with doxycycline and IAA for 0, 24, 48 and 72 h and assessed for viability with trypan blue staining.
Following CHASE-knock-in, clones derived from a targeted bulk population of cells exhibiting high mClover3 levels were characterized for successful knock-in integration by genomic PCR and validated by Sanger Sequencing (Figure (Figure1B).1B). Auxin-inducible protein degradation was possible when CTCF was tagged with miniAID-mClover3 in SEM and HUDEP-2 cells with doxycycline inducible OsTIR1 integration. To test the efficient depletion of the CTCF-miniAID-mClover3 fusion protein, multiple knock-in clones were exposed to IAA (auxin) and doxycycline for 48 h in culture, and then harvested for immunoblotting using antibodies against CTCF and AID. Protein degradation was consistent between immunoblotting and flow cytometric analysis (Figure (Figure1C;1C; Supplementary Figure S1F–G). Parental wild-type SEM cells demonstrated no change to CTCF’s expression when treated with IAA and doxycycline (Supplementary Figure S1H). Thereafter, three knock-in SEM clones (27, 35 and 42) showing complete depletion of CTCF were selected for subsequent experiments. Additionally, three knock-in HUDEP-2 clones (C3, C16 and C41; Supplementary Figure S8A–D) were characterized and used to compare findings observed from experiments in the SEM clones 27, 35 and 42. In the mono-allelic knock-in SEM clone 36, when the CTCF-miniAID-mClover3 was degraded, CTCF protein translation from the wild-type allele notably increased, suggesting compensation occurred in response to CTCF disruption. We also investigated the mRNA expression of CTCF in the knock-in SEM clones 27, 35 and 42 by Q-PCR. After CTCF protein depletion, the mRNA level was significantly induced suggesting that CTCF protein might repress its own transcription (Figure (Figure1D).1D). Consistent with previous observations in mouse embryonic stem cells (33), loss of CTCF in SEM cells resulted in time-dependent cell death (Figure (Figure1E)1E) limiting the length of time cells could be treated and studied. Therefore, our human CTCFAID cellular model was used as a tool to investigate early changes to genomic organization and global transcriptional regulation upon CTCF loss.
CTCF degradation disrupted global CTCF binding affinity
To assess the genome-wide CTCF-binding profile in CTCF depleted cells, we investigated CTCF binding occupancy using in situ chromatin immunoprecipitation followed by high-throughput sequencing (Cut&Run assay) (51). We identified 15,583, 33,059 and 21,669 peaks occupied by CTCF in clones 27, 35 and 42 without IAA treatment, respectively (Supplementary Figure S2A–C). Among these three clones, CTCF bound peaks were evenly distributed in promoters (21.4–30.4%), introns (30.8–35.32%), and distal intergenic regions (33.23–37.66%) (Supplementary Figure S2D and G). Global reduction of CTCF-binding affinity and minimal CTCF retention at certain loci were evident in all three clones following 48 h of IAA treatment (Figure (Figure2A2A and B; Supplementary Figure S2A–C, Supplementary Table S4).
Given the variation of peak numbers called from different clones, a more stringent analysis of the CTCF-binding signature was conducted by combining peaks called between the three replicates and using only those peaks containing CTCF target sites (CTSes) as well as high confidence reproducibility (see method of ‘Analysis of Cut&Run data’). The ChIPseeker analysis tool (53) was used to detect bias in genomic distribution of CTSes upon IAA treatment for 48 h. From the combined analysis, there were 13, 287 total CTSes assigned to three categories; reduced (6394), gained (153) and retained (6740). Among the reduced CTCF-binding peaks, 31.48% were located at promoter regions within 1 kb of a transcription start site (TSS), and 30.84% were located at distal intergenic regions. In contrast, retained peaks were mostly located at promoters within 1 kb distance of a TSS (75.77%), with less retention at distal intergenic regions (10.98%). Gained CTCF binding peaks shared a similar pattern to retained peaks (75.82% at promoters within 1 kb distance to TSS and 9.8% at distal intergenic regions) (Figure (Figure2C2C and Supplementary Table S4).
Previously (59), it was observed that CTCF and BORIS (CTCFL) could co-occupy a specific subset of regulatory elements consisting of clustered CTCF-binding motifs (termed 2XCTSes) mainly located at active promoters and enhancers. To separate CTCF peaks with either 1XCTSes or 2XCTSes, we identified the number of CTCF motifs in the SEM genome located within 40-bp of each other and grouped them by counts. For instance, 1XCTSes indicated one CTCF-binding motif with no others counted within 40- bp, while 2XCTSes have 2 CTCF motifs and 3XCTSes have ≥ 3 CTCF motifs. Next, we assigned CTCF peaks identified by Cut&Run to these three groups. Overall, we observed peak density of 2XCTSes and 3XCTSes was generally stronger than 1XCTSes. Upon CTCF loss, the CTCF-binding affinity against 2XCTSes and 3XCTSes was more significantly reduced than 1XCTSes as indicated by the log2fold change (CTCFAID+IAA/-IAA) (Figure (Figure2D2D and E, P = 2.2e-16, Wilcox test). However, there is no significant difference between loss of binding between 2XCTSes and 3XCTSes (Figure (Figure2E,2E, P = 0.51, Wilcox test).
CTCF depletion reduced global TAD insulation and intra-TAD chromatin loops
To explore global chromatin architecture changes in response to CTCF loss, we utilized in situ Hi-C to quantify the genome-wide DNA contacts based on proximity ligation and next-generation sequencing in the SEM clones 27 and 35 after 48 h IAA treatment achieving ~20 kb resolution. As a quality control, we detected the translocation breakpoint of AFF1/MLL fusion gene, which was initially identified as a driver mutation during leukemogenesis of SEM cells (Supplementary Figure S3A–B). We found that high-order chromosome folding at the resolution of compartments was normally maintained after 48 h of CTCF depletion in SEM cells (R2 = 0.9751) (Figure (Figure3A3A and B), which was also supported by other cellular models (29). Next, based on the sequencing depth and resolution of our Hi-C data, we called 63 and 176 TADs in untreated clone 27 and 35, respectively. However, after CTCF depletion 12 and 9 TADs remained, correspondingly. Reproducibility of Hi-C data from each biological replicate was consistently high (Supplementary Figure S3C) enabling compilation of Hi-C data for analysis. When we combined raw Hi-C data collected from both clones and re-called TADs, 890 TADs were discovered in untreated cells and 131 TADs in cells treated with IAA for 48 h (Figure (Figure3C).3C). Additionally, quantification and comparison of the impact of CTCF loss on DNA loops within TAD boundaries showed a 97.5% decrease in intra-TAD looping following 48 h of IAA treatment (Figure (Figure3D).3D). These data suggest that CTCF is essential for maintenance of intra-TAD DNA interactions and delineating TAD boundaries, but dispensable for higher order compartment integrity.
CTCF depletion reduced global TAD insulation and intra-TAD chromatin loops. (A) Chromatin compartments evaluated by cis-Eigenvector 1 values were not significantly affected genome wide by CTCF protein depletion following 48 h IAA treatment. (B) A representative snapshot of chromatin compartment integrity of the entire chromosome 2 was shown in cells from Hi-C data combined from clones 27 and 35 without IAA treatment and following 48 h of IAA treatment. Red bars indicated compartment (A); blue bars indicated compartment (B). Scale bar indicated 20 MB. (C) Number of TADs called from clone 27 and 35 were shown in cells with or without 48 h IAA treatment. Reproducibility of Hi-C data from each biological replicate was high enabling compilation of raw Hi-C data for recalling of TADs (combined). (D) Number of intra-TAD DNA loops called from clone 27 and 35 were shown in cells with or without 48 h IAA treatment. Reproducibility of Hi-C data from each biological replicate was high enabling compilation of raw Hi-C data for recalling of intra-TAD loops (combined).
The global transcriptome is minimally altered upon acute depletion of CTCF
To comprehensively evaluate transcription alteration according to global looping disruption in CTCF-depleted cells, we conducted RNA-seq on SEM clones 27, 35 and 42. At a stringent cut-off (log2fold change≥1, adjust P ≤ 0.05, FPKM≥1), we identified 330 genes that were differentially expressed between CTCF wild-type (CTCFAID-IAA) versus depleted cells (CTCFAID+IAA). Overall, the global transcriptome profiling between CTCFAID-IAA and CTCFAID+IAA was highly correlated (Spearman’s r = 0.95), suggesting acute depletion of CTCF in the miniAID-mClover3 knock-in SEM clones did not significantly impact global transcription at an early time point (Figure (Figure4A).4A). As seen by Q-PCR, RNA-seq confirmed CTCF expression increased following IAA treatment (Supplementary Figure S5A). Although we observed a significant disruption to intra-TAD interactions and TAD boundary maintenance, transcriptional changes to genes located near abrogated interactions and disrupted TAD boundaries were mostly unaltered. When we compared our transcriptome data with 664 genes confirmed by Hi-C to have altered DNA looping following IAA treatment for 48 h, we only identified 10 genes with overlapping differential expression and abrogated looping (Figure (Figure4B).4B). These data suggest that while CTCF is necessary for many intra-TAD interactions, early loss of CTCF has a limited direct impact on transcription.
The oncogene MYC was directly susceptible to CTCF loss. (A) RNA-seq data were illustrated as log2 (normalized numbers of FPKM) averaged from three clones (clone 27, 35 and 42) with or without IAA treatment for 48 h. MYC was highlighted in red. (B) The Venn-diagram illustrated the overlapped gene number (yellow) between genes confirmed by Hi-C to have disrupted intra-TAD looping after CTCF depletion (gray) and genes identified as differentially expressed [Ilog2fold change (CTCFAID-IAA/+IAA)I≥1, adjust P ≤ 0.05 and FPKM≥1] following CTCF depletion (green) for 48 h. (C) Q-PCR of MYC confirmed the reduction of transcription in response to CTCF depletion for 48 h from three biological replicates; clone 27, 35 and 42 (N = 3). (D) Clones 27 and 35 were treated with IAA for 0.5, 1 and 24 h and collected for immunoblotting using specific antibodies against CTCF and MYC. GAPDH was used as loading control. (E) GSEA analysis was performed using fold change of all genes collected from RNA-seq and DESeq2 analysis by comparing CTCFAID-IAA versus CTCFAID+IAA, which revealed the top rank concordance of CTCF depletion with the differential expression of MYC target genes. (F) The gene expression level of the top 100 downregulated MYC target genes discovered by SLAM-seq (61) in MYCAID knock-in K562 cells was plotted to illustrate concordant downregulation in SEM CTCFAID cells after IAA treatment for 48 h. Six genes were not shown because of FPKM≤1. (G) The gene expression level of the top 100 downregulated MYC target genes discovered by SLAM-seq (61) in MYCAID knock-in HCT-116 cells was plotted to illustrate concordant downregulation in SEM CTCFAID cells after IAA treatment for 48 h. (H) Transcriptionally active genes with putative CTCF-mediated enhancer-docking in HCT-116 (red circle), K562 (purple circle) and Jurkat cells (orange circle) were identified from a previous study (62). The Venn-diagram demonstrated the number of overlapped genes between the above studies and genes identified as differentially expressed following CTCF depletion (green circle) [Ilog2 (fold change CTCFAID-IAA/+IAA)I≥1, adjust P ≤ 0.05 and FPKM≥1].
GSEA revealed the significant concordance of CTCF depletion with upregulation of the apoptosis pathway, while unsupervised hierarchical transcriptome analysis demonstrated the upregulation of apoptosis associated genes 48 h post IAA treatment (Supplementary Figure S9A and B). Upregulation of the apoptosis pathway upon CTCF depletion supported our observation that loss of CTCF in SEM cells resulted in time-dependent cell death. When IAA was removed from the culture medium, CTCF protein level was restored and cell viability was rescued (data not shown).
The oncogene MYC was most directly susceptible to CTCF loss
Notably, RNA-seq identified the oncogene MYC among the genes significantly downregulated by CTCF loss in SEM cells (Figure (Figure4A;4A; Supplementary Figure S4A–F). Global looping analysis additionally confirmed looped DNA interactions between MYC and its distal enhancers and TAD boundaries were significantly disrupted following IAA treatment (Supplementary Table S3). Q-PCR confirmed the notable reduction of MYC upon CTCF loss following 48 h of IAA treatment in SEM (Figure (Figure4C),4C), and immunoblotting validated the decrease of MYC and CTCF 24 h post IAA treatment (Figure (Figure4D).4D). Additionally, MYC expression was completely restored after IAA removal for 48 h (Supplementary Figure S9C). Among the genes located in the same TAD boundary with MYC, we observed significant transcriptional changes for the non-coding RNA PVT1 (Supplementary Figure S5B), which has been identified to share and compete for enhancer activity with MYC (60). Other genes in the MYC TAD including GSDMC, TMEM75 and FAM84B also appeared differentially regulated by altered CTCF-dependent higher order structure. However, the expression level of these genes was low resulting in poor reproducibility of transcription variation between the replicates (Supplementary Figure S5C–F). The transcription level of other B-ALL associated major oncogenes including MYB, RUNX1, EBF1, KRAS, NRAS and MEF2C remained unchanged (Supplementary Figure S6A–F).
GSEA revealed the unique and significant concordance of CTCF depletion with downregulation of MYC target gene signatures (Figure (Figure4E).4E). Although MYC could potentially regulate thousands of target genes, a recent study by Muhar et al. using nascent mRNA sequencing by SLAM-seq identified only 100 direct targets downregulated upon MYC loss (61). When we compared these 100 genes from SLAM-seq to our RNA-seq dataset, 92 out of 100 genes showed decreased expression in CTCF depleted cells (Figure (Figure4F4F and G; Supplementary Figure S7A–F). To address whether the ‘MYC-signature’ was unique upon CTCF loss in B-ALL SEM cells, we performed RNA-seq on two well-characterized immortal HUDEP-2 CTCFAID knock-in clones (C3 and C16) (Supplementary Figure S8A–D). In total, 1216 genes were differentially expressed (log2fold change≥1, adjust P ≤ 0.05) between CTCF wild-type (CTCFAID-IAA) versus depleted cells (CTCFAID+IAA), with expression recovered in most genes when IAA was removed from the culture medium (Supplementary Figure S8E). However, MYC expression was minimally altered upon CTCF depletion (Supplementary Figure S8F). Additionally, MYC downstream targets remained unaffected. The only pathway modestly enriched from GSEA was hedgehog signaling. Collectively, these data support that MYC and its downstream targets were primarily affected by acute loss of CTCF in the B-ALL cell line SEM, and that CTCF affected transcriptional regulation in a cell type-specific manner.
Schuijers et al. identified a conserved CTCF-binding motif residing 2.5 kb upstream of the MYC promoter that provides an enhancer-docking site facilitating its interaction with the downstream MYC promoter (62). They go on to postulate that hundreds of putative enhancer-docking sites may be defined by CTCF binding within 2.5 kb of promoters of actively transcribed genes in HCT-116, K562 and Jurkat human cancer cell lines (63,64). When we analyzed our global looping analysis following CTCF depletion to identify disrupted interactions at putative enhancer-docking sites in HCT-116, K562 and Jurkat cells, we only observed abrogated looping in 15, 9 and 8 interactions, respectively. In addition, when we compared the 330 genes we identified as differentially expressed in response to CTCF depletion in SEM cells with the genes classified to contain putative enhancer-docking site interactions in HCT-116, K562 and Jurkat cells, we only identified 21, 15 and 11 overlapped genes, respectively. When we raised the cutoff of mRNA expression (FPKM≥10), the only shared gene between all cohorts was MYC (Figure (Figure4H4H).
CTCF regulated MYC through a long-distance chromatin interaction in SEM cells
MYC overexpression has been detected in 50–60% of human cancers and plays an essential role in cancer initiation and maintenance through multiple molecular mechanisms including gene amplification, aberrant transcription activation and enhancer hijacking. Previous studies have reported the MYC promoter is physically recruited to a variety of proximal and distal enhancers to enforce its high expression in different human cancer cells (60,62,65–70). The MYC TAD contains many conserved CTCF-binding sites in human cancer and normal somatic cell lines (Supplementary Figure S10). We hypothesized that MYC downregulation observed in CTCF-depleted cells was a result of a disrupted CTCF-dependent enhancer–promoter interaction. The Hi-C data collected from SEM clone 27 and 35 indicated dramatic loss of contacts from MYC to distal regions in cells treated for 48 h with IAA (Figure (Figure5A).5A). To more clearly identify abrogated interactions, next-generation Capture-C was performed on clones 27, 35 and the mono-allelic knock-in clone 36 with or without IAA treatment using specific DNA probes that hybridize to the MYC promoter. We detected frequent interactions between the MYC promoter and a distal enhancer cluster residing ~1.8 Mb downstream of the promoter in the absence of IAA treatment in all three clones. However, the interactions between the distal enhancer cluster and MYC promoter were notably disrupted in clone 27 and 35 after IAA treatment, and partially maintained in the heterozygous knock-in clone 36 (Figure (Figure5B5B and C) indicating CTCF was required to facilitate this specific enhancer–promoter interaction. The distal interacting region has been well supported by previous work to be an enhancer cluster that interacts with the MYC promoter. ChIA-PET studies in various cell lines have captured the looped interaction of the MYC promoter to the distal enhancer cluster (54). Additionally, the distal enhancer region exhibits hallmark enhancer features including open chromatin status as shown by ATAC-seq (unpublished, GSE129066), and H3K27ac binding as seen by ChIP-seq (71). The enhancer cluster also demonstrated high affinity binding for AFF1 (72). CTCF Cut&Run showed reduced CTCF-binding affinity at the MYC promoter and the distal enhancer following 48 h IAA treatment in SEM clones 27 and 35, further supporting MYC expression in SEM cells is regulated by a CTCF mediated long-distance chromatin interaction between the distal enhancer and the MYC promoter (Figure (Figure5B5B and D).
CTCF regulates MYC through a long-distance chromatin interaction. (A) Snapshots of 12.6 Mb of Hi-C data at 10 kb resolution were shown from CTCFAID SEM clone 27, 35 and Hi-C data combined from clones 27 and 35 without IAA treatment and following 48 h of IAA treatment. DNA interactions between MYC and the distal enhancers were highlighted by blue arrows in CTCFAID-IAA samples. (B) Next-generation Capture-C was performed on clones 27, 35, and the heterozygous knock-in clone 36 with and without 48 h IAA treatment using specific probes that hybridized to the MYC promoter (shown by orange box). The interaction profiles are shown at the indicated viewpoint in the hg19 human genome browser. Interactions to the distal enhancer cluster observed using the MYC probes are indicated by the highlighted purple box. Capture-C data were aligned with ATAC-seq, H3K27ac and AFF1 ChIP-seq tracks identified in previous studies (GSE129066, GSE76783 and GSE89485) to specify the functional regulatory elements. CTCF Cut&Run tracks were provided for clones 27 and 35 with or without 48 h IAA treatment. CTCF and PolII ChIA-PET data were obtained from K562 cells from a previous study (GSE39495). (C) ‘Relative interaction frequency’ was calculated by the quantification of Capture-C interaction reads from the MYC promoter to distal enhancer 1 (arrow 1 = Loop1) and 2 (arrow 2 = Loop 2). (N = 2). (D) Schematic diagram summary of the CTCF/MYC regulation axis in SEM cells.
MYC enhancer–promoter interactions identified in previous works including the enhancer-docking site located 2.5 kb away from the promoter were not detected in our Capture-C analysis (60,62,67,69,73–76). Additionally, Cut&Run assay showed strong CTCF binding at the MYC promoter and distal enhancer in untreated SEM clones, with weaker occupancy observed more proximal to the promoter. We conclude that residual expression of MYC after IAA treatment might be from basal promoter activity or interactions of the MYC promoter with proximal enhancers beyond the detection resolution of Capture-C.
Long non-coding RNA PVT1 residing ~58 kb away from MYC was also downregulated upon CTCF loss in B-ALL cells. Howard Chang’s group recently showed that targeted CRISPR interference at the PVT1 promoter enhanced breast cancer cell competition and growth in vivo due to the competition between PVT1 and MYC for engagement with four intragenic enhancers in the PVT1 locus (60). Since the physical distance between MYC and PVT1 is small, juxtaposition between MYC and its distal enhancer might also facilitate the interaction and regulation of this enhancer to PVT1. However, in our Capture-C data we did not detect any interactions between the MYC promoter and PVT1 or other alternative enhancers when CTCF was depleted. Therefore, PVT1 downregulation in CTCF depleted cells could be caused by loss of TAD integrity.
CTCF ChIP-seq data collected from different human cancer and normal somatic cells have identified thousands of CTCF-binding sites (40 000–80 000) across the genome with most CTCF-binding sites conserved in TAD boundaries. However, current characterization of chromatin loops discovered by high-resolution Hi-C, Hi-ChIP and ChIA-PET has to date only identified ~7000 CTCF-mediated loops (77–80) suggesting that most -binding sites are not involved in facilitating DNA interactions, but in other roles such as direct transcriptional regulation. However, we observed that acute depletion of CTCF in SEM and HUDEP-2 cells did not lead to severe genome-wide transcriptional dysregulation. Notably, RNA-seq analysis showed markedly different effects on global transcription in SEM and HUDEP-2 cell lines, again highlighting CTCF functions in a cell type-specific manner to regulate gene expression.
In B-ALL SEM cells, depletion of CTCF significantly disrupted TAD boundaries and intra-TAD DNA loops but had minimal effects on global transcription following 48 h of CTCF depletion. Surprisingly, even some genes located on or near disrupted TAD boundaries did not show transcriptional changes following CTCF depletion suggesting dramatic changes to chromatin architecture may not have an immediate impact on global transcription, and that transcriptional changes secondary to architectural disruption could be observed under continuous depletion of CTCF. However, CTCF depletion was lethal in B-ALL cells, limiting the scope of the experiment. Our findings supported the work by Nora et al. that showed loss of Ctcf by the AID system in mouse embryonic stem cells did not abrogate genomic organization on the larger, compartmental scale, but did disrupt TAD insulation and looping between boundaries. While Nora et al. carried out IAA treatment for 4 days showing a 10-fold increase in differentially expressed genes over time, we chose to analyze transcriptional changes at an earlier time point to identify genes directly affected by CTCF loss (29). We suspect continued depletion of CTCF over time would result in an accumulation of secondary transcriptional changes in response to dysregulation of genes impacted by early CTCF loss, as well as transcriptional changes brought about by apoptosis signaling.
The MYC promoter has been reported to loop to a spectrum of distal and proximal enhancers in different cancers to initiate and maintain tumorigenesis (62,65–67,70,75,76,81). In SEM cells, we showed MYC was specifically looped to an enhancer cluster that also resided on the right TAD neighborhood boundary. We hypothesize the transcriptional susceptibility of MYC to CTCF regulation is associated with its unique enhancer location, which demonstrated disrupted looping with the MYC promoter upon CTCF loss. Paradoxically, when MYC was defined to juxtapose both proximal and distal enhancers in myeloid leukemia K562 and WEHI231 B-cell lymphoma (62), ectopic expression of CTCF led to downregulation of MYC, growth retardation and promotion of differentiation into the erythroid lineage (25,26) underscoring the complexity of CTCF’s regulation of MYC across tissue types.
Survival data collected from a mixed C57BL6/129 strain of Ctcf+/− mice suggested that ~80% of heterozygous animals developed multiple tumors compared to 40% in wild-type littermates at ~100 weeks old. Although these data indicated Ctcf behaved as a tumor suppressor gene (4), which was also supported by somatic mutation burden of CTCF in a recent human pan-cancer study (82), contradictory results were seen in other models regarding the CTCF/MYC regulation axis (25,26,62). Results from this study suggest in B-ALL CTCF could behave indirectly as an oncogenic driver via its regulation of MYC. However, additional studies would be necessary to assess CTCF’s role in B-ALL tumorigenesis.
In summary, we developed a simplified, highly efficient knock-in protocol, CHASE-knock-in, to integrate the miniAID-mClover3 cassette to the endogenous human CTCF locus, which allowed for acute auxin-inducible degradation of the CTCF protein in human cells. We provide bona fide evidence that CTCF is an essential factor directly regulating the distal enhancer–promoter interactions of MYC, suggesting MYC and its downstream targets are uniquely affected by acute loss of CTCF in B-ALL SEM cells. The cell model and results collected from this study will expedite the investigation of CTCF’s impact on transcriptional regulation in cancers and other biological processes.
ChIP-seq data of human normal cell lines and cancer cell lines were obtained from ENCODE. RNA-seq, Capture-C and Cut&Run raw data generated from this study were deposited to GEO under the accession numbers: GSE120781, GSE121257 and GSE126619. SLAM-seq data were downloaded from GSE111463. Hi-C raw data are available at ProteinPaint portal (https://pecan.stjude.org/proteinpaint) upon request. Enhancer–promoter interaction data of HCT-116, K562 and Jurkat were downloaded from GSE92881. CTCF and PolII ChIA-PET data were obtained from GSE39495.
This study was initiated with the encouragement of Dr Charles J. Sherr and salary support to Judith Hyle and Shaela Wright was provided through his Howard Hughes Medical Institute laboratory. We are indebted to thank everyone in the Core Flow Cytometry, Cytogenetics and Cell Sorting Shared Resource facility at St. Jude Children’s Research Hospital. We appreciate Dr Ryo Kurita and Dr Yukio Nakamura for kindly providing HUDEP-2 cells. We also thank Dr Jun J. Yang, Dr Yong Cheng, Dr Jun Yang and Dr Yu Liu for providing advice and comments for this project. The authors declare no competing interests.
Author contributions: C.L. designed this project. J.H., Y.Z., S.W., Y.S., J.E., R.F., P.X. and C.L. conducted all experiments. Y.Z., B.S. and L.T. provided all the bioinformatic analysis. J.H., Y.Z., S.W. and C.L. wrote the manuscript with input from all co-authors. Project Administration and Funding Acquisition was from C.L.
Supplementary Data are available at NAR Online.
American Lebanese Syrian Associated Charities (ALSAC); Comprehensive Cancer Center-developmental fund from National Cancer Institute (NCI-5P30CA021765-37 to C.L.). Funding for open access charge: ALSAC.
Conflict of interest statement. None declared.
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