Saccharomyces cerevisiae or metazoan cultured cell lines. Here, we adapted native elongating transcript sequencing technology (NET-seq) to measure cotranscriptional splicing dynamics during the early developmental stages of Drosophila melanogaster embryos. Our results reveal the position of RNA polymerase II (Pol II) when both canonical and recursive splicing occur. We found heterogeneity in splicing dynamics, with some RNAs spliced immediately after intron transcription, whereas for other transcripts no splicing was observed over the first 100 nt of the downstream exon. Introns that show splicing completion before Pol II has reached the end of the downstream exon are necessarily intron-defined. We studied the splicing dynamics of both nascent pre-mRNAs transcribed in the early embryo, which have few and short introns, as well as pre-mRNAs transcribed later in embryonic development, which contain multiple long introns. As expected, we found a relationship between the proportion of spliced reads and intron size. However, intron definition was observed at all intron sizes. We further observed that genes transcribed in the early embryo tend to be isolated in the genome whereas genes transcribed later are often overlapped by a neighboring convergent gene. In isolated genes, transcription termination occurred soon after the polyadenylation site, while in overlapped genes, Pol II persisted associated with the DNA template after cleavage and polyadenylation of the nascent transcript. Taken together, our data unravel novel dynamic features of Pol II transcription and splicing in the developing Drosophila embryo.Widespread cotranscriptional splicing has been demonstrated from yeast to human. However, most studies to date addressing the kinetics of splicing relative to transcription used either  It is by now largely accepted that splicing can happen, and often does happen, while transcription is still in progress . It is aSaccharomyces cerevisiae, splicing could occur as soon as the 3′ splice site had emerged from the transcription machinery, suggesting that splicing may be completed immediately after intron transcription. Previous attempts to determine the duration of splicing in vivo had returned estimates ranging from a few seconds to several minutes  , whereas genes transcribed later contain multiple long introns (more similar to human genes). An additional feature of Drosophila is the presence of many genes with exceptionally long introns that are subdivided by a noncanonical mechanism termed recursive splicing  . An adva compact  and thussplicing . For allDrosophila early development is characterized by rapid mitotic cycles that lack cytokinesis, resulting in nuclear proliferation in a syncytial cytoplasm . The NET-seq technique involves isolation of transcription complexes formed by Pol II, the DNA template and the nascent RNA by immunoprecipitation, without crosslinking (Our first task was to adapt the NET-seq technology for use in slinking . After sslinking .We collected embryos at 2–3 h after fertilization (referred to as early embryos) and 4–6 h after fertilization (referred to as late embryos) A. AnalysDrosophila embryos, we optimized buffers and washing conditions to purify the chromatin fraction from manually sorted embryos, solubilize the transcription complexes with MNase digestion and immunoprecipitate Pol II with antibodies. We used rabbit polyclonal antibodies raised against synthetic peptides of the YSPTSPS repeat of the CTD of the largest Pol II subunit in Saccharomyces cerevisiae, phosphorylated at either S5 (ab5131 Abcam) or S2 (ab5095 Abcam). Both antibodies have been extensively used for chromatin immunoprecipitation experiments in Drosophila melanogaster  generated by MNase digestion of RNA was first converted to a 5′ phosphate by T4 polynucleotide kinase D. RNA wadNET-seq libraries were independently prepared from early and late embryos using S5P antibody; three additional libraries were prepared from late embryos using S2P antibody. Each library was sequenced to a high coverage with a read length of 150 bp . Experimental reproducibility was demonstrated by strong agreement of uniquely aligned read density between biological replicates prepared with antibodies raised against the CTD phosphorylated on either serine 5 (S5P) or serine 2 (S2P) positions . This suggests that both S5P and S2P antibodies recognize the CTD of elongating Pol II in Drosophila embryos.Two to three Drosophila embryos, we indeed observed large peaks of dNET-seq/S5P reads mapping to the last nucleotide of spliced exons, as shown for the kuk gene , contrasting with a lack of peak observed in mammalian cells  nucleotide of nascent RNA but also the 3′ OH end of RNAs that associate with the Pol II elongation complex . Notablyan cells . This isyl group .dNET-seq peaks at the end, we applied an algorithm that finds nucleotides where the NET-seq read density is at least three standard deviations above the transcript mean in a local region defined by 100 bp upstream and downstream , we classified the exons into four groups (quartiles) based on the dNET-seq read density of the corresponding gene and restricted the analysis to exons in the fourth quartile, that is, from genes with the highest read density. The results show that splicing intermediate peaks are detected in ∼80% of all constitutively spliced exons. We further analyzed the so-called pre-MBT (mid-blastula transition) genes, which are the first zygotic genes to become transcriptionally active in early embryos , gurken , and Rab32  were detected by RNA-seq in embryos collected 2–3 h after fertilization, but the dNET-seq signal over these genes was negligible. However, a robust dNET-seq/S5P signal was found at the pumilio gene  and odd skipped . Altogether, we examined 117 previously identified pre-MBT genes and 35 maternal mRNAs . The finding that a robust dNET-seq/S5P signal was recovered from zygotically but not from maternally expressed transcripts indicates that dNET-seq is specifically targeting the nascent transcriptome.The stage at which the embryo switches from relying on maternally deposited mRNAs and proteins to undergoing its own transcription is termed the mid-blastula transition (MBT). However, a few genes (known as pre-MBT genes) become transcriptionally active before MBT . A stronas snail D, fushi dNET-seq was capturing nascent RNA, we next investigated the distribution of Pol II density over transcript regions in early and late embryos. dNET-seq/S5P profiles  do not show the characteristic higher read density near the promoter, as previously described in mammalian cells ; thus, we only record the position of polymerases that have transcribed at least 60 bp past the TSS.Having confirmed that an cells . This isan cells  and in odNET-seq signal around the polyadenylation (pA) site. We found that in pre-MBT genes such as snail (tailless (tll) , and nullo , the dNET-seq/S5P signal ends soon after the pA site. In contrast, genes expressed in late embryos such as Akap200  and tsr , have a widespread dNET-seq/S5P signal on introns and regions downstream from the pA site. Analysis of RNA-seq data sets revealed that mRNAs encoded by these genes are efficiently spliced and 3′-end processed . Thus, dNET-seq/S5P is capturing newly synthesized transcripts that have not yet been spliced, as well as RNAs synthesized by Pol II complexes that continued to transcribe the DNA template after the mRNA was cleaved and polyadenylated at the pA site. We further noted that the 3′-UTR of genes with a dNET-seq signal extending past the pA site is overlapped by another gene , which is transcribed in the opposite direction.We then turned our attention to the as snail D, taille Akap200 E, His3.3dNET-seq metaprofiles for pre-MBT and late genes. Metagene analysis of the dNET-seq/S5P signal on pre-MBT genes expressed in early embryos confirmed that in this group of genes, the dNET-seq signal is sharply reduced past the pA site (tailless (tll) . Another 26 pre-MBT genes are embedded in larger genes, as shown for nullo, which is located within a long intron of the CG12541 gene . A smaller group of pre-MBT genes (21) have neighboring genes located on either strand within a region of 500 bp downstream from the pA site, as shown for Elba2 . We further identified 5 pre-MBT genes that have the 3′-UTR overlapped by an antisense convergent gene, as shown for spook (spo) . Notably, in these genes, the dNET-seq/S5P signal extended past the pA site .Next, we generated  pA site G. The maSupplemental Fig. S4E). Genes with dNET-seq signal over the gene body (in RPKM) above the 90th percentile of read density for all intergenic regions analyzed were considered to be transcriptionally active . We identified ∼7000 active genes, with similar results obtained from dNET-seq/S5P and dNET-seq/S2P data sets . This set of active genes includes over 85% of the 3500 genes previously identified as actively transcribed after the mid-blastula transition (MBT) based on ChIP-seq experiments , as expected assuming that when Pol II reaches this site, the nascent transcript is cleaved and polyadenylated and therefore there is no RNA left attached to the polymerase to be sequenced. However, in the case of late genes that have the 3′-UTR overlapped by an antisense (convergent) gene, the dNET-seq/S5P and dNET-seq/S2P signals increase again after the pA site . Using the methodology described above to identify transcribed genes, we found that the vast majority (>80%) of overlapping convergent genes were transcriptionally active and only 219 genes were silent. The metagene analysis shown in dNET-seq/S5P signal past the pA site is independent from transcription of the convergent overlapping gene.To identify all the genes that are transcriptionally active in late embryos, we used a strategy adapted from GRO-seq analysis  that releriments . Next, wdNET-seq/S5P and dNET-seq/S2P reads around the pA site suggest distinct patterns of transcription termination for genes that are either isolated in the genome or overlapped by another convergent gene. However, we cannot exclude the possibility that specifically in isolated genes, the lack of dNET-seq signal results from loss of CTD phosphorylation as Pol II transcribes past the pA site.In conclusion, the distribution profiles of dNET-seq reads on exons and introns. The number of nascent RNA reads whose 3′ ends map at a particular genomic position is proportional to the number of Pol II molecules at that position. Thus, Pol II pause sites can be detected as local peaks in NET-seq read density  in order to analyze only reads whose 3′ ends associate with the Pol II active site. We analyzed both S5P and S2P data. However, we were particularly interested in exploring the multiple peaks of dNET-seq/S5P signal observed on both exons and introns   B. This i points)  and Drosla cells . In addila cells C. This cice site C. A verydata set D.Supplemental Methods). We concluded that MNase biases are unlikely to explain either the enrichment of peaks in exons or the general profile of peak densities past the 3′ splice site.A potential caveat of read density analysis is that nucleotide composition varies systematically across exons and introns. For example, exons tend to have a higher GC content than introns . This coDrosophila embryos, we asked when splicing takes place relative to transcription. We first looked at recursive splicing of long introns because this process involves the formation of inherently unstable intermediates that are more likely to be formed soon after the transcription of each intronic splice site . Focusing on previously identified Drosophila ratchet points  internal to the downstream intron, as shown for the second intron of the Megalin gene .To capture recursive splicing intermediates using nd reads E, we wert points , we founlin gene B. Reads lin gene B. OveraldNET-seq profiles around a RP reveals an enrichment of reads in a region located a few nucleotides downstream from the RP, as shown for RP2 in the first intron of the Tenascin major gene  was calculated by dividing the number of spliced reads by the sum of the number of spliced and unspliced reads  and genes expressed in late embryos , indicating that a subset of junctions were always spliced immediately after transcription (SR = 1), while others remained unspliced (SR = 0). Notably, differences in SR distribution were found between dNET-seq/S5P and dNET-seq/S2P data sets . Significantly lower SR values were detected for S2P compared to S5P . This clearly points to a preferential association between cotranscriptional splicing and S5 phosphorylation of Pol II CTD, as previously proposed in human cells . However, this difference between pre-MBT genes and genes expressed in late embryos disappeared once the higher read density of pre-MBT genes had been controlled for (We observed that only ∼5% of splice junctions in pre-MBT genes were devoid of S5P reads spanning ligated exons and thus presented an SR of 0 (∼5.10% replicate 1/∼4.35% replicate 2), whereas in genes expressed in late embryos this proportion was ∼20% (∼19.72% replicate 1/∼18.55% replicate 2)   . A switce place) . It is udNET-seq splicing ratio and exon length . Regarding intron size, we found that introns with SR = 0 (and thus no evidence for intron definition) were, on average, indeed larger than other introns . However, more careful examination revealed a more complex picture, with a lower proportion of introns with SR = 0 both for introns of intermediate size  and for very large introns (>1000 nt) .We found no relationship between the 1000 nt) F. These Taken together, these results suggest that although fast splicing (implying intron definition) is indeed skewed toward small introns flanked by large exons, there is also frequent and efficient intron definition for large introns. Our results are inconsistent with a threshold model, where splicing would systematically switch to exon definition after a given intron size is reached.Supplemental Fig. S6K,L). A similar effect is observed as the ratio of the downstream exon GC content to intron GC content increases . Thus, the most efficient immediate splicing is observed when the GC content is low in both exons and introns but higher in exons than introns. Secondly, as 3′ splice site strength increases, the proportion of introns with SR = 0 decreases . We found no significant relationship between SR and 5′ splice site strength . However, we replicated previous observations . Thirdly, similarly to previous reports .We also investigated the relationship between SR and several other gene architecture parameters. Firstly, as the GC content in exons and introns decreases, the proportion of introns with SR = 1 increases and the proportion with SR = 0 decreases, showing more efficient immediate splicing . When such filtering is not done, a sharp peak is observed around the 3′ splice site, notably when SR values are low . It appears that intron lariat reads are primarily captured for introns with low splicing ratios . This contrasts with splicing intermediate reads from the end of the upstream exon, which are associated to higher splicing ratios instead .We next performed a meta-analysis of Supplemental Fig. S7A–C,G,H). The first is a region of increased peak density located roughly 10–20 nt after the 3′ splice site. This peak is independent of the presence of putative intron lariat reads , and is more prominent when the SR is higher .The peak density profile downstream from the 3′ splice site contains two primary regions of interest . We found no evidence that this increase in peak density could be a result of MNase digestion biases . As discussed above, this pattern of increased dNET-seq/S5P density could result from either a local enrichment of CTD S5 phosphorylation or from an accumulation of Pol II due to a decreased elongation rate. In the latter case, one possible explanation for such a slow-down over exonic regions could be their relatively higher GC content when compared to intronic sequences. The peak is indeed more prominent in introns where the ratio of exonic to intronic GC content is higher . However, when SR = 1, then even exons where this ratio is high do not display the peak . Moreover, introns with higher SR tend to have higher exonic to intronic GC ratios . Hence, the covariation with SR cannot be explained simply through the correlation between SR and GC content patterns. This suggests that there is an effect of the SR beyond any GC content effect. Potentially, this region could correspond to where delayed splicing starts (because these events have low immediate splicing ratios). Note that we obtained qualitatively similar meta-profiles when considering read rather than peak densities . Our results therefore cannot be explained through any biases introduced by the peak calling approach.The second feature of interest is a rapid increase in peak density ∼60 nt into the exon. Contrary to the first region of interest, the peak density in this region is higher when SR is Drosophila embryo. As shown in dNET-seq reads that span the junction to the downstream exon either directly on nascent transcripts or indirectly on splicing intermediates formed by cleavage at the 5′ splice site of the downstream exon  than among late genes  . Possibly, pre-MBT genes in the Drosophila genome may be under selection to avoid overlaps with other genes, thereby minimizing potential transcriptional interference problems such as collisions involving DNA polymerase complexes or Pol II transcribing opposite template strands  . These avia intron definition at least part of the time, allowing us to test long-held assumptions in the field. Notably, in vitro and reporter gene work suggested that Drosophila uses intron definition for introns smaller than ∼200–250 nt and exon definition for larger introns , the proportion with SR > 0 increases again, suggesting that specific mechanisms may have evolved for the intron-defined splicing of very large introns. The tendency for faster splicing kinetics with average intron sizes has also been reported using metabolic labeling in both Drosophila .We propose that the tethering of the upstream exon to Pol II  could be−12). Further work is thus needed to distinguish between causative and merely correlative factors. In addition, it must be determined how the GC content effect relates to patterns of nucleosome density  of Drosophila embryos can be completed soon after transcription of the 3′ splice site, as previously reported in other cellular models , many introns remained unspliced in our analysis. In agreement with these observations, a recent single-molecule study of nascent RNA dynamics in live cells found large kinetic variation in intron removal for single introns in single cells  were raised at 25°C, in polypropylene vials containing standard enriched culture medium . Three-day-old flies (counting from pupae eclosion) were fattened in culture medium supplemented with fresh yeast for 2 d. Embryos were collected into apple juice-agar plates supplemented with fresh yeast using appropriate cages containing ∼200 flies each. To avoid female retention of older embryos, three precollections of 30 min each were made before the first collection of embryos. To maximize egg laying, and avoid larvae contamination, adult flies were transferred to clean embryo collection cages every day over 5 d. For early stage embryos (2–3 h after egg-laying), adult females were allowed to lay eggs for 1 h in apple juice-agar plates. Plates were subsequently collected and embryos were aged at 25°C for 90 min. During the following 30 min, embryos were harvested from the plates, dechorionated in 50% bleach solution for 2 min, and washed once in Phosphate Buffered Saline supplemented with 0.1% Tween-20 (PBT) and twice in deionized water. In order to discard older embryos (stage 6 and older), manual staging of collected embryos was performed with the help of forceps and under a magnifier scope. Embryos were then resuspended in a solution containing 120 mM NaCl and 0.04% Triton, and washed twice with 120 mM NaCl solution. At the end of the 3 h collection, the solution was removed and embryos were frozen in liquid nitrogen and stored at −80°C. For the late stage (4–6 h), eggs were laid for 2 h and aged at 25°C for 3.5 h. Embryo collection and processing was similar to the early stage embryos, but in this case, no manual staging was performed.For each embryo collection, and after dechorionation, a representative embryo sample was collected from the total pool and fixed in a scintillation flask, using a solution containing one volume of 4% formaldehyde in PBT and four volumes of heptane, for 20 min at 100 rpm. The lower aqueous phase solution was subsequently removed, 4 mL of methanol was added and embryos were shaken vigorously for 1 min. Embryos were then collected from the bottom of the scintillation flask, washed twice with methanol, and frozen at −20°C in methanol. To rehydrate the embryos, they were washed for 5 min each, with 3:1, 1:1, and 1:3 mix solutions of methanol:PBT. Embryos were subsequently washed twice in PBT and incubated with 1:5000 Sytox green (Invitrogen), supplemented with 5 µg/mL RNase A (Sigma-Aldrich) in PBT for 15 min. After washing with PBT, embryos were mounted in fluorescence mounting medium (Dako) and examined in a Zeiss AxioZoom V16 Fluorescence Stereo Microscope for image acquisition and embryo staging. Images were processed using ImageJ software (NIH).dNET-seq protocol was adapted from mNET-seq . Embryos were homogenized in a Dounce homogenizer with 11× strokes using a tight pestle on ice. The suspension was centrifuged at 7700g for 15 min at 4°C, the supernatant was discarded, and the white pellet containing the nuclei was resuspended in 500 µL of Buffer B1. The suspension was again homogenized in the Dounce with 4× strokes and loaded without mixing on the top of buffer B2 . The suspension was centrifuged at 1310g for 30 min at 4°C, and the pellet was resuspended with 125 µL of NUN1 buffer . An amount of 1.2 mL of Buffer NUN2  was mixed with the nuclei and incubated on ice for 15 min preforming a short vortex every 3 min. Chromatin was then centrifuged at 10,000g for 10 min at 4°C, washed with 100 µL of 1× MNase Buffer, and incubated in 100 µL of MNase reaction mixing (1× MNase buffer and 30 gel unit/µL MNase [New England Biolabs]) for 3 min at 37°C with mixing at 1400 rpm. The reaction was stopped with 10 µL of 250 mM EGTA, centrifuged at 10,000g for 5 min at 4°C, and the supernatant containing the solubilized chromatin was recovered. For the early embryos sample, 2 × 300 µL of embryos were prepared in parallel and pooled together after the chromatin solubilization. Immunoprecipitation of Pol II–RNA complexes was performed using 50 µL of Protein G Dynabeads (Thermo Fisher Scientific), preincubated overnight with 5 µg of the correspondent antibody: anti-Pol II CTD S5P (ab5131 Abcam) or anti-Pol II CTD S2P (ab5095 Abcam) in 100 µL NET2  and washed three times with NET2. Beads were incubated with the solubilized chromatin in 1 mL total volume of NET2 for 1 h at 4°C, washed seven times with 500 µL of NET2 and once with 100 µL of PNKT (1× PNK buffer and 0.1% tween) before incubation for 6 min in 50 µL of PNK reaction mix : 300 µL of RNA Lysis Buffer in 33% EtOH was mixed to the beads by pipetting. Beads were discarded and the suspension was loaded into a Zymo spin column that was centrifuged at 10,000g for 30 sec. The column was washed once with 400 µL RNA prep buffer and twice with 700 µL and 400 µL RNA wash buffer, respectively. RNA was then eluted in 15 µL of DNase/RNase-free water (Zymo) and stored at −80°C. An amount of 100 ng of RNA was used to prepare each library, following the standard protocol of the TruSeq Small RNA Library Prep kit (Illumina). After adapter ligation and reverse transcription, the libraries were PCR amplified using 16 PCR cycles, and cDNA libraries were fractionated in the gel between 130 to 300 bp. The libraries were sequenced using PE-150 on the Illumina HiSeq X platform by Novogene Co., Ltd.The mNET-seq . BrieflydNET-seq paired-end samples using Cutadapt (version 1.18)    with theon 1.18)  with theease 95)  using STease 95)  with –chease 95)  with -q n script  with then script  was usedn script E.Drosophila embryonic transcriptome sequencing data [Poly(A) RNA-seq], performed in developmental stages similar to the dNET-seq early and late samples, were used in this study. RNA-seq data sets corresponding to cycle 14B . Data sets from modENCODE and GEO were aligned to the dm6 Drosophila reference genome (Ensembl release 95) (dm6 (Ensembl release 95) GTF file. Genes with TPM values above 2 were considered to be expressed.Adapters were removed from all data sets using Trim Galore (version 0.4.4) (ease 95)  using STease 95)  with –chease 95)  was useddNET-seq read densities were calculated by dividing the read counts in each window by the window length (in bp). Read counts per window were obtained with bedtools genome coverage (version 2.27.1-1-gb87c465) . Transcripts whose gene body dNETseq read density exceeded this threshold were considered to be transcriptionally active . For all of the analyses performed on late genes, only transcriptionally active genes were considered. In addition, only one isoform per gene was considered for all analysis, selected as the isoform with the highest RPKM value in the RNA-seq data set for the corresponding developmental stage.Similar to a previous GRO-seq analysis , we usedb87c465) , and an dm6 coordinates using the liftOver tool (https://genome.ucsc.edu/cgi-bin/hgLiftOver). The most representative isoform for each gene was manually selected through visualization of individual profiles.The coordinates of previously identified pre-MBT genes were obtained from dNET-seq read density of the corresponding gene. Only exons from the highest quartile  were considered in dNET-seq Late analysis.Exons containing splicing intermediates or introns containing lariats were identified using a peak finder algorithm (NET_snrPeakFinder)  that detdNET-seq data sets were calculated in the following manner:4 normalizes for gene length and 106 normalizes for sequencing depth. Queries of gene 3′UTR overlaps  . Strand-Wig tool  and uploWig tool .The read density metagene plots in Supplemental Figures S3G, S7A–G, and S7E–J were prepared using custom Python and R scripts (https://github.com/rosinaSav/dNETseq_code). The peak density value represents the proportion of introns/exons that overlap with a peak at that position. Only internal fully coding exons that were at least 100 nt long were included. In addition, the intron just upstream of the exon had to be at least 50 nt long. For Supplemental Figures S7A–G and S7E–H, further filtering based on read coverage was performed (see below). Note that exons shorter than 150 nucleotides contribute both to the upstream and downstream exonic proportion of the plot.The peak or read density metagene plots in Supplemental Fig. S6O–Q, the 3′ most coding exon was also analyzed). Finally, we performed filtering to remove exons where the read coverage was too low to allow for robust estimation of the splicing ratio. The relevant threshold was calculated for each data set separately. We calculated the total proportion of spliced reads out of all spliced/unspliced reads for the data set to obtain the expected splicing ratio. We then performed a binomial test to know the probability of sampling only spliced/unspliced reads by chance under the null that the true splicing ratio equaled this expectation. We set the threshold as the lowest number of reads that had to be sampled for the probability to be below 0.01. Through this procedure, the threshold was set at ≥10 reads for replicate 1 and 2 of the late data set , at ≥11/10 reads for replicate 1/2 of the late data set including terminal coding exons, and at ≥14/9 reads for replicate 1/2 of the early data set .The immediate splicing analysis was performed solely on the S5P data sets. Only the 117 previously annotated pre-MBT genes  were anaP-value was <0.05, Dunn's test was performed on the pairwise comparisons using R package dunn.test  under accession number GSE152585. The Python code used is available at https://github.com/rosinaSav/dNETseq_code and https://github.com/kennyrebelo.All raw and processed sequencing data generated in this study have been submitted to the NCBI Gene Expression Omnibus (GEO; Supplemental material is available for this article.


Studies of nanoscale nucleosomal chromatin organization benefited from a variety of electron microscopy techniques. Recent breakthroughs in the investigation of mesoscale chromatin structures have emerged from chromatin conformation capture methods (C-methods). Chromatin has been found to form hierarchical domains with high frequency of local interactions from loop domains to topologically associating domains and compartments. During the last decade, advances in super-resolution light microscopy made these levels of chromatin folding amenable for microscopic examination. Here we are reviewing recent developments in FISH-based approaches for detection, quantitative measurements, and validation of contact chromatin domains deduced from C-based data. We specifically focus on the design and application of Oligopaint probes, which marked the latest progress in the imaging of chromatin domains. Vivid examples of chromatin domain FISH-visualization by means of conventional, super-resolution light and electron microscopy in different model organisms are provided.The intimate relationships between genome structure and function direct efforts toward deciphering three-dimensional chromatin organization within the interphase nuclei at different genomic length scales. For decades, major insights into chromatin structure at the level of large-scale euchromatin and heterochromatin compartments, chromosome territories, and subchromosomal regions resulted from the evolution of light microscopy and fluorescence  The term “chromatin” was coined by Walther Flemming at the end of the 19th century to designate structures stained by aniline dyes and confined within the cell nucleus . TogetheAt the beginning of the journey toward understanding the chromatin structure, conventional light microscopy was the only way to directly observe chromatin and chromosomes both in the nucleus and in spread . InterphChromatin ultrastructure at a nanometer scale has been intensively investigated by electron microscopy, which achieved a resolution three orders of magnitude higher than light microscopy . It was Absence of underlying genetic sequence information remains a main obstacle for detailed investigation of the mesoscale chromatin domains, identified by electron microscopy. Indeed, when examining the ultrastructural image of chromatin, specific chromosomal regions are unidentifiable . Nowadayin situ hybridization , when hapten (or dye)-modified nucleotides and fluorescent streptavidin or antibody detection had been widely applied instead of radioisotope labeled probes  technique in the first decade of the 21st century on the basis of nuclear ligation assay  and the Color-coded heatmaps of pairwise interactions of genomic loci, a common form of data presentation in high-throughput C-methods, provide information on intra- and interchromosomal interactions at different genomic length scales from dozens of megabases down to ∼200 bp . ResolutDrosophila genomes, TADs were defined as diagonal domains of variable size , where genomic loci belonging to the same TAD show higher interaction frequency than loci assigned to neighboring TADs  10–50 kb of linear genomic distance is required to discriminate regions as individual signals within the interphase nucleus to allow accurate 3D-distance measurements . Thus, tWhile, theoretically, many probes could be used for simultaneous hybridization, due to the limited number of detection fluorochromes and the architecture of imaging systems, most often 1–3 genomic targets are visualized at one round of hybridization during FISH experiment. This major limitation of FISH is partly solved by applying combinatorial fluorochrome schemes for probe detection resulting in mixed colors or repeated sequential hybridization of samples with probes of interest . The curFor verification of medium to low resolution Hi-C-derived data within and between megabase-sized contact domains, the resolution of conventional laser-scanning confocal microscopy is sufficient . HoweverA microscopic image is the main source of information for imaging-based methods; therefore the requirements for image acquisition, equipment settings and image analysis pipelines should be particularly strict . To obtaProbes, based on cloned sequences  are the most common FISH probes and have been intensively used in interphase cytogenetics and genome architecture studies from the 1980th . The enz1 for some they are sparse or absent. Moreover, in poorly assembled genomes BAC-contigs could be placed incorrectly leading to the need for additional verification of chromosomal position for any particular BAC-clone. In summary, clone-based probes remain the probes of choice for imaging of relatively large genomic regions by both conventional microscopy and super-resolution microscopy due to the probe robustness, relatively low cost, versatile labeling and detection protocols.Being originated from relatively large genomic fragments, clone-based probes may exhibit moderate specificity due to the presence of repetitive sequences . When thWhen the sequence of the DNA region to be visualized by FISH is known, FISH probes could be produced directly from genomic DNA via PCR with specific primers . One of Oligonucleotides arrived on the FISH scene with the development of automated oligonucleotide synthesis. However, their use was limited to identifying repetitive sequences, spanning large genomic regions and usually found within the centromere, telomere, and nucleolus organizer regions of chromosomes . PresentDuring the last decade, the development of cost-effective techniques for massive parallel oligo synthesis and accumulation of genome sequencing data have boosted the application of oligonucleotide-based FISH-probes and culminated in the development of Oligopaint technique . Oligopain vitro, and then reverse-transcribed with specific labeled primers  and differentiating erythroblasts showed that distinct domain shapes and specific cis-contacts are established before transcriptional activation  occurred preferentially between genomic loci belonging to B-compartments. Multiple loci imaging also confirmed earlier observations on enrichment of genomic loci belonging to B-compartments near the nuclear lamina and nucleolus, and enrichment of genomic loci belonging to A-compartment in proximity to nuclear speckles (Recent coupling of the chromatin tracing technology with RNA-multiplexed error-robust FISH (RNA-MERFISH) and immunofluorescence staining made it possible to simultaneously visualize chromosomal loci, RNA and nuclear domains  in mouse embryonic liver cells  and humaspeckles .Taking into account the almost decade-long extremely intense investigation of genome architecture by C-methods, possibly the most relevant question to ask is whether TADs could be captured by microscopy as chromatin domains somehow insulated from neighboring chromatin? Several recent studies involving chromatin tracing of 5–50 kb regions and both super-resolution and diffraction-limited fluorescent microscopy succeeded in quantitative imaging of chromatin conformation at the level of TADs and other contact domains . TAD-likHighly similar results were obtained in an independent study that addressed the internal organization of TADs and utilized Oligopaint-based super-resolution imaging of individual TADs in mESCs . The autNevertheless, chromatin domain profiles, essentially corresponding to TAD profiles in Hi-C maps, emerged after averaging spatial distance (or proximity frequency) matrices between hundreds of cells . FurtherHeterogeneity of chromatin-folding structures within distinct loop domains has also been demonstrated in human cell line by ISH combined with serial block-face scanning electron microscopy (3D-EMISH) , FISH wiMyc locus), confirmed some conclusions from a loop extrusion model of TAD formation , occupied by smaller contact domains   . A colleartments .Drosophila genome and TADs/compartment domains themselves, efficient visualization of chromatin domains in the interphase nucleus has been achieved by super-resolution microscopy. In correspondence with the emerging picture of epigenetically specified compartment domains, microscopic observations identified repressed TADs as distinct nanometer-sized domains and active regions as extended chains of dotted subdomains  in several differentiating cell types of Drosophila embryos, discriminated by simultaneous mapping of 30 RNA species. This approach allowed to track cell type specific changes in the microscopically identified TAD patterns in BX-C locus and to correlate them with changes in epigenetic status accompanied by transcription activation. Upon sequential activation of BX-C genes, the inactive TAD substantially contracted and its boundary moved to the right, separating the still inactive H2K27Me3 and PcG-rich chromatin from the active regions. Importantly, smaller TADs appeared within the active region, bounding distinct genes and their regulatory regions. The borders of these TADs were independent of PcG activity, but contained CTCF and CP190, indicating that CTCF may also play a role as an insulator of contact interactions at least in some of the chromatin domains in Drosophila (Two cognate approaches to chromatin tracing combined with RNA detection (Hi-M and ORCA) allowed to visualize several adjacent TADs in  embryos . Multipl embryos . In anotosophila .Drosophila. Early light and electron microscopy observations of polytene chromosomes from salivary glands and other tissues demonstrated that dense (black and gray) bands and more diffuse interbands alternate along the length of these extended interphase chromosomes     , amphibipicalis)  and bird gallus) , compart gallus) . Moreovetructure . FISH-batructure .Saccharomyces cerevisiae, Schizosaccharomyces pombe), worms (Caenorhabditis elegans), plants and even prokaryotes , a condensin placed on rex sites megabase-sized euchromatic loops , and maize (Zea mays) interphase chromatin, revealed an important role of repeat content in shaping local chromatin domains  or KNOT engaged Elements (KEEs). FISH with probes to IHIs confirmed that KNOT is formed by IHIs that could belong to different chromosomes  demonstrated the potential for imaging more targets in fewer rounds of sequencing and with higher resolution, than chromatin tracing and DNA-MERFISH , generally based on the operator-repressor methods , ANCHOR/ParB system, transcription activator-like effectors (TALEs) or clustered regularly interspaced short palindromic repeats (CRISPR)/nuclease-deactivated CRISPR-associated protein 9 (dCas9) technology (reviewed by Tracing of individual chromatin contact domains Rapid advances in chromatin imaging and the spreading of these “hi-end” techniques within the scientific community hold promise for decoding the mesoscale spatial and temporal organization of the genome and its multifaceted regulatory capacity in the near future.AM wrote the original draft, prepared the figures, and edited the manuscript. AK suggested concept of the article, critically revised the manuscript, and the figures. Both authors approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


SOX2 oncogene represent a hallmark of squamous cancers originating from diverse tissue types. Here, we find that squamous cancers selectively amplify a 3’ noncoding region together with SOX2, which harbors squamous cancer-specific chromatin accessible regions. We identify a single enhancer e1 that predominantly drives SOX2 expression. Repression of e1 in SOX2-high cells causes collapse of the surrounding enhancers, remarkable reduction in SOX2 expression, and a global transcriptional change reminiscent of SOX2 knockout. The e1 enhancer is driven by a combination of transcription factors including SOX2 itself and the AP-1 complex, which facilitates recruitment of the co-activator BRD4. CRISPR-mediated activation of e1 in SOX2-low cells is sufficient to rebuild the e1-SOX2 loop and activate SOX2 expression. Our study shows that squamous cancers selectively amplify a predominant enhancer to drive SOX2 overexpression, uncovering functional links among enhancer activation, chromatin looping, and lineage-specific copy number amplifications of oncogenes.Amplification and overexpression of the  SOX2 amplification and overexpression represents a hallmark of squamous cancers with distinct distribution of chromatin accessible regions depending on cancer type. Here, the authors identify a single enhancer e1 that predominantly drives SOX2 expression in squamous cancer. SOX2, a member of the SRY-box transcription factor family, is well known for its role in the pluripotency of embryonic stem cells (ESCs)6. SOX2 is also essential in maintaining the self-renewal ability of basal cells7, which have been reported as the cell of origin for squamous cancers, the most common type of solid tumors8. Squamous cancer can originate from diverse tissues such as lung , cervix , skin, esophagus , and upper digestive tissues in the head and neck . Genomic analyses have revealed that the SOX2 gene is widely amplified and overexpressed in squamous cancers, nominating SOX2 as a lineage-specific oncogene16. Indeed, previous in vivo studies have shown that Sox2 overexpression, together with the inactivation of tumor suppressors such as Pten or Lkb1, drives the formation of mouse lung squamous cancers18. In addition to squamous cancer, SOX2 amplification and overexpression have also been reported in glioma19, a common type of brain tumor that includes low-grade glioma (LGG), glioblastoma (GBM), and several other subtypes.Lineage-specific oncogenes represent a class of genes that play important roles in the normal development of specific cell lineages, but drive tumorigenesis when dysregulated. Many lineage-specific oncogenes encode transcription factors such as MITF in melanomasSOX2 overexpression in cancer cells has been largely attributed to copy number amplifications of the SOX2 gene itself19. However, our understanding of oncogene copy number amplifications is evolving. We and others have recently shown that noncoding enhancers outside oncogenes such as MYC, MYCN, AR, KLF5, and EGFR are selectively amplified with or without their respective oncogenes28, demonstrating novel mechanisms that transcriptionally activate oncogenes in diverse cancer types. Therefore, we decided to revisit the SOX2 locus and its associated copy number changes.SOX2 locus between squamous cancers and gliomas, which corresponds to the distribution of lineage-specific potential regulatory elements. Focusing on the noncoding region that is selectively co-amplified with SOX2 in squamous cancers, we discover a single predominant enhancer that is necessary and sufficient for SOX2 activation. Furthermore, we delineate its relationship with the surrounding enhancers, identify its associated transcription factors, reveal its vulnerability to bromodomain protein degradation, and illustrate its impact on 3D chromatin architecture. Our study reveals the functional link among enhancer activation, enhancer–promoter interactions, and lineage-specific copy number amplifications in cancer.Here, we reveal distinct copy number profiles at the 29 to the single-nucleotide polymorphism (SNP)-array-based copy number data of combined squamous cancer samples  from The Cancer Genome Atlas (TCGA)31  covers SOX2 and a ~290 kb noncoding region 3′ to SOX2, while the glioma peak  covers SOX2 and a ~173 kb noncoding region 5′ to SOX2  > 0.1), which corresponds to 9% of squamous cancers and 4% of gliomas, we profiled the averaged copy number amplitude surrounding the SOX2 locus OX2 Fig. . Squamoucus Fig. . The copOX2 Fig. . TCGA sqene Fig. . We foun33. In squamous cancers, we found multiple chromatin-accessible regions within the 3′ noncoding region that is selectively amplified in squamous cancers  data from TCGA, which profiled genome-wide chromatin accessibility to identify potential regulatory elements in diverse types of human primary tumorsers Fig. . These rers Fig. . In conters Fig. . We thenity Fig. . Collectene Fig. .SOX2 gene and the potential regulatory elements. The human genome is organized into series of insulated neighborhoods or topologically associating domains demarcated by CCCTC-binding factor (CTCF) binding, which restrict promoter–enhancer interactions34. We found that the SOX2 promoter resides at the boundary of two adjacent insulated neighborhoods that were previously identified from CTCF chromatin interaction analysis with paired-end tag (ChIA-PET) sequencing analysis35, suggesting that the SOX2 promoter may have access to regulatory elements from both ends  data of H3K27ac, a marker for active regulatory elements, in esophageal squamous cancer cell lines KYSE140, TT, and TE10, and lung squamous cancer cell lines LK2 and NCI-H52038  < 0.05) of the candidate enhancers with the SOX2 promoter in SOX2-high esophageal squamous cancer cell lines KYSE140, KYSE70, and TT and lung squamous cancer cell lines LK2 and NCI-H520  system, which uses an inactivated Cas9 (dCas9) fused to two transcriptional repressors KRAB and MeCP245, to inhibit each of the five enhancers in SOX2-high squamous cancer cell lines KYSE140, LK2, and NCI-H520. ChIP-coupled with quantitative PCR (ChIP-qPCR) of dCas9 in KYSE140 cells validated the on-target effects of the single guide RNAs (sgRNAs)  across the six cell lines  and upregulated SOX2-repressed genes . Furthermore, expression of e1-regulated genes  is significantly correlated with SOX2 expression in TCGA squamous cancer samples, suggesting they are likely to be SOX2-target genes in human primary tumors . We identified four additional candidate coding and noncoding genes FXR1, ATP11B, SOX2-OT, and LINC01206—the promoter region of each gene interacts with at least one of the enhancer anchors in two or more of the five tested cell lines  data for 113 squamous cancers from the Pan-Cancer Atlas of Whole-Genome (PCAWG) dataset49. GISTIC analysis of the segment data validated the focal amplification of the SOX2-e1 locus  and the AP1 complex  identified DNA sequences recognized by multiple transcription factor families Fig. , most oflex Fig.  that wasSOX2 expression (76% for KYSE140 and 93% for LK2) as compared to individual motif disruptions, suggesting joint effects of the candidate transcription factors , AP1, RUNX, and STAT (2nd) motifs within the e1 enhancer in KYSE140 and SOX (2nd), AP1, SNAIL, and TCF motifs in LK2, which may either alter the nucleotides of the motif sequences or delete DNA fragments covering the motifs. We found that combinatorial cutting of the motifs resulted in more dramatic reductions in ors Fig. . Combinaors Fig. , which iors Fig. , suggestSOX2 overexpression may be sensitive to BRD4 perturbation. To test this hypothesis, we applied the proteolysis targeting chimera (PROTAC) molecule ARV-771 to recruit the E3 ligase cereblon to degrade BRD452. We found that 2 h of 0.5 µM ARV-771 treatment efficiently decreased the BRD4 protein level  to label the newly transcribed RNA, also known as nascent RNA, which was then captured by biotin pulldown and quantified by quantitative reverse transcription PCR (RT-qPCR). We showed that 2 h of ARV-771 treatments resulted in ~88% loss of the nascent SOX2 transcription, demonstrating an acute and remarkable response of SOX2 transcription to BRD4 degradation  or 0.5 µM ARV-771 treatment. H3K27ac serves as an ideal bait for the HiChIP capture in this experiment, as the enrichment of H3K27ac at the SOX2-e1 locus was barely affected by 2 h of ARV-771 treatment  across the tested cell lines, demonstrating that e1 is sufficient for SOX2 activation  in SKMES1 cells after e1 activation  and downregulated SOX2-repressed genes   Fig. . Finallyoop Fig. . We also28. Here, we show that this phenomenon extends to lineage-specific enhancers in a cancer type-specific manner. Squamous cancers and gliomas selectively amplify enhancers located 3′ and 5′ to the SOX2 gene, respectively, exhibiting a spatial switch of cancer type-specific copy number amplifications. The phenomenon is likely caused by the unique chromatin architecture surrounding the SOX2 gene: (1) glioma- and squamous cancer-specific enhancers are distributed in two adjacent insulated neighborhoods demarcated by CTCF binding; (2) SOX2 resides right at the boundary of the two neighborhoods so that it has access to both. A recent study showed that copy number amplifications of oncogenes including SOX2 may occur as different forms of structural events such as linear tandem duplications, chromosomal rearrangements, or extrachromosomal circular DNA54. We reveal that SOX2 and distal enhancers that are looped to the SOX2 promoter are often co-amplified in squamous cancers, suggesting a common transcriptional regulatory mechanism that may be shared by different structural forms of SOX2 amplifications.We and others have previously shown that overexpression of oncogenes can be driven by copy number amplifications of distal enhancers57, yet the hierarchical structures for most of these enhancer clusters remain largely unknown. We show that the enhancer cluster co-amplified with SOX2 in squamous cancer is predominantly driven by a single enhancer e1, which aligns with previous findings of predominant enhancers in other enhancer clusters59. Within the SOX2 enhancer cluster, all the remaining enhancers physically interact with e1 and are dependent on the activity of e1, but individually have a minimal or modest impact on SOX2 expression. It is possible that some of the enhancers are redundant to each other in activating SOX2—repression of e1 collapses the entire enhancer cluster and thereby impairs the redundancy. Our work suggests that the predominant role of e1 may be driven by a series of squamous cancer-relevant transcription factors such as SOX2 itself, AP1, and potential family members of RUNX, STAT, SNAI, and TCF complexes. Identification of such predominant enhancers and their associated protein complexes will clarify mechanisms underlying the activation of lineage-specific oncogenes.Lineage-specific oncogenes are known to be driven by condensed clusters of enhancer elements, namely super-enhancers or stretch enhancersSOX2, TP63, and KLF560. While the encoded transcription factors are hard to be therapeutically targeted, enhancer activation may yield unique vulnerabilities for cancer cells driven by these oncogenes. We show that the activity of the SOX2 enhancer is dependent on the SOX2 transcription factor itself, its potential cofactor AP1, and the transcriptional coactivator BRD4, representing a self-regulatory circuit that is normally hypersensitive to transcriptional inhibitors—a unique vulnerability that has been reported for other oncogenic transcription factors61. We show that PROTAC-mediated BRD4 degradation leads to an acute and dramatic reduction of SOX2 transcription, suggesting an alternative strategy to target squamous cancers with SOX2 activation, although the efficacy and specificity of such treatments require further preclinical investigations.As transcription factors are difficult targets with small molecules, understanding the mechanisms underlying their transcriptional activation may imply alternative therapeutic strategies. This is particularly important for squamous cancers that are largely associated with copy number amplifications and the transcriptional activation of transcription factor genes such as SOX2 loop, suggesting that enhancer activation is a prerequisite for initiating enhancer–promoter loops. On the other hand, despite the remarkable impact of BRD4 degradation on SOX2 transcription, we find that it has little effect on maintaining the e1-SOX2 chromatin loop. The observation agrees with recent findings of the MYC and BCL2 loci in leukemia cells62. Similar findings have also been reported for the mediator complex, another important transcriptional coactivator64. These together suggest that enhancer activation may be dispensable for maintaining enhancer–promoter loops. Previous studies have shown that binding of several transcription factors such as CTCF, ZNF143, and YY1 to promoters or promoter-proximal regions is required for maintaining enhancer–promoter loops66. Indeed, we observed DNA recognition motifs of these transcription factors in the promoter-proximal region of SOX2. Future investigations are needed to determine whether and which enhancer-bound transcription factors play similar roles in promoter–enhancer interactions.It remains elusive how enhancer–promoter loops are initiated and maintained. We show that CRISPR-mediated activation of the e1 enhancer is sufficient to rebuild the e1-68. The esophageal squamous cancer cell line TT was obtained from the Japanese Collection of Research Bioresources Cell Bank. Cells were grown in RPMI-1640 media supplemented with 10% fetal bovine serum and 1% of penicillin–streptomycin and tested negative for mycoplasma using the Lonza MycoAlert Detection kit. Cell lines were used for experiments after <3 months of passages. Cell line identities were verified by either SNP-array-based fingerprinting as previously described in the CCLE project68 or short tandem repeat analysis.Squamous cancer cell lines KYSE140, KYSE70, LK2, NCI-H520, HSC4, TE1, TE10, SKMES1, and RERFLCAI were obtained from the Broad Institute Cancer Cell Line Encyclopedia (CCLE) projecthttps://gdc.cancer.gov/about-data/publications/pancanatlas). We performed GISTIC229 analysis using combined glioma data (LGG and GBM) and combined squamous cancer data  to call significantly focally amplified regions in the two cancer types. TCGA ATAC-seq data was published by Corces et al.33 and downloaded from the NCI Genomic Data Commons data portal (URL: https://gdc.cancer.gov/about-data/publications/ATACseq-AWG). We used the published bigWig data for Integrative Genomics Viewer presentation and the normalized ATAC-seq insertion counts across the identified pan-cancer peak set for calculating Z-scores for each cancer type. TCGA-processed RNA-seq data was downloaded from the Firehose GDAC data portal of the Broad Institute (URL: http://gdac.broadinstitute.org/). For RNA expression correlation of SOX2 and genes regulated by the e1 enhancer, we first calculated Z-scores for each tumor based on SOX2 expression level (log 2 (RSEM + 1)) or the sum of the expression level of e1-regulated genes. One thousand six hundred and thirty-four e1-activated and 1391 e1-repressed genes  were used for the analysis. We used the Z-scores for Spearman’s correlation analysis to examine the relationship between the expression of SOX2 versus e1-regulated genes. Squamous cancer WGS-based copy number segment data and structural variants data were downloaded from the PCAWG data portal (URL: https://dcc.icgc.org/releases/PCAWG/).TCGA pan-cancer copy number segment dataset was downloaded from the National Cancer Institute Genomic Data Commons data portal  to generate a lentiviral dCas9-KRAB-MeCP2 vector. We then infected cells with the vector to stably express the dCas9-KRAB-MeCP2 fusion. The infected cells were selected with blasticidin (10 µg/ml) for at least 5 days. Enhancer-targeting sgRNAs were designed close to the summits of ATAC-seq peaks within the SOX2 enhancer cluster. We then infected the dCas9-KRAB-MeCP2 cells with LentiGuide-Puro (Addgene: 52963) carrying either previously published sgRNAs that have no recognition sites in the genome28 or sgRNAs targeting the SOX2 enhancers. The infected cells were selected with puromycin (2 µg/ml) for at least 2 days before any molecular or cellular assays. For enhancer activation, cells were first infected with lenti-dCas9-VP64-Blast (Addgene: 61425) and selected with blasticidin (10 µg/ml) for at least 5 days. We then infected the dCas9-VP64 cells with pXPR502 (Addgene 96923) carrying either negative control or enhancer-targeting sgRNA, and selected the cells with puromycin (2 µg/ml) for at least 2 days. All sgRNA sequences are listed in Supplementary Table For enhancer repression, we first subcloned dCas9-KRAB-MeCP2  into For cell proliferation, infected and selected cells were seeded at the same number (0.025 or 0.05 million) in a 6-well plate and counted after 6 days. For phenotype-rescue experiment, we first cloned SOX2 complementary DNA (cDNA) into the doxycycline-inducible expression vector pCW57.1-Puro (Addgene: 41393) and infected dCas9-KRAB-MeCP2 KYSE140 cells with pCW57.1-SOX2-Puro. We then used LentiGuide-Zeo (to avoid overlap of selection markers) to express sgRNAs. Cells were selected with zeocin (800 µg/ml) for 3 days and the same number of cells were then seeded with or without 1 µg/ml doxycycline. The cell culture media were changed with fresh doxycycline every other day before counting.69, the coding region of SOX2, or the transcription factor DNA binding motifs identified in the e1 enhancer. The infected cells were selected with puromycin (2 µg/ml) for at least 2 days before any experiments. All sgRNA sequences are listed in Supplementary Table We first generated Cas9-expressing cells by infecting cells with lenti-Cas9-Blast (Addgene: 52962). The infected cells were selected with blasticidin (10 µg/ml) for at least 5 days. We then infected the Cas9-expressing cells with LentiGuide-Puro carrying previously published sgRNAs targeting negative control regions sgAAVS1 and sg-Chr.2-24. Briefly, five million cells were crosslinked with 1% formaldehyde ) and lysed with Lysis Buffer I  and then Lysis Buffer II  supplemented with protease inhibitors. Chromatin extract was sonicated with QSonica Q800R  and immunoprecipitated with antibodies premixed with Dynabeads A and G. Antibodies: H3K27ac , BRD4 , SOX2 , CTCF , FOSL1 , Cas9 . ChIP-seq libraries were prepared using NEBNext DNA Ultra II library prep kit and NEBNext Multiplex Oligos for Illumina , and sequenced by Illumina NovaSeq. For ChIP-qPCR assays, we designed primers targeting individual SOX2 enhancers and used sonicated genomic DNA to normalize primer efficiency variance. All the qPCR primers are listed in Supplementary Table ChIP-seq assays were performed as previously described70 to align sequencing reads to the hg19 human genome, Samtools71 to sort and index the aligned reads, and MACS272 to calculate signal per million reads (SPMR) and to call significant ChIP-seq peaks . For super-enhancer analysis, we used the Homer pipeline73 to identify super-enhancers based on H3K27ac ChIP-seq signal, and then used bedtools74 to intersect super-enhancers called from SOX2-high squamous cancer cell lines, which identified the shared super-enhancer region in the SOX2 locus. For enhancer comparison between human and mouse cells, we applied the UCSC LiftOver tool43 to identify mouse genomic regions that are conserved to human squamous cancer SOX2 enhancers and then compared these regions to mouse ESC Sox2 enhancers. For measuring the effect of e1 repression on global BRD4 ChIP-seq signal, we first categorized BRD4 binding sites (BRD4 ChIP-seq peaks identified in KYSE140 cells with sg-NC#1) into two groups based on whether or not they overlap with high-confidence SOX2 binding sites (SOX2 ChIP-seq peaks containing SOX motifs). We used deepTools75 to present averaged BRD4 ChIP-seq profile across these two groups of BRD4 sites in KYSE140 cells with and without e1 repression. To calculate the change of BRD4 ChIP-seq signal at individual enhancers in KYSE140 cells post ARV-771 treatment, we used the UCSC tool “bigWigAverageOverBed”76 to calculate the SPMR value for each BRD4 binding site (BRD4 ChIP-seq peaks identified in KYSE140 cells treated with DMSO) and then performed t tests to compare the values from cells with DMSO or ARV-771 treatments.We used Bowtie270. Expression level (read counts) for each GENCODE gene was quantified with RSEM77. We applied the edgeR package78 to normalize the read counts and to perform differential expression analysis. We applied the cut-off of FDR < 0.05 and fold change > 1.5 to identify genes that are significantly down- or upregulated after SOX2 knockout, e1 repression, or e1 activation. To compare gene expression changes caused by SOX2 knockouts versus e1 repression or activation, we ranked SOX2-regulated genes based on their edgeR FDR values and selected the top 1000 SOX2-activated or -repressed genes as “gene sets,” which we used for GSEA analysis to assess if they are down- or upregulated after e1 repression or activation. For RT-qPCR, the extracted RNA was first converted into cDNA with NEB LunaScript SuperMix kit and then processed with real-time PCR using the NEB Luna Universal qPCR Master Mix on a Bio-Rad CFX96 qPCR instrument. The signal of qPCR was normalized to the internal reference genes ACTB or HPRT1. Primers used for RT-qPCR were listed in Supplementary Table Total RNA was extracted using the Zymo Quick-RNA miniprep kit with on-column DNase treatments. mRNA was then purified using the NEBNext Poly-A mRNA Magnetic Isolation Module. RNA-seq libraries were prepared using NEBNext Ultra Directional RNA library prep kit and NEBNext Multiplex Oligos for Illumina , and then sequenced by Illumina NovaSeq. Sequencing reads were aligned to the hg19 human genome using Bowtie244 with several modifications as previously described4. Briefly, crosslinked chromatin was first digested with the MboI restriction enzyme, filled with dCTP, dGTP, dTTP, and biotin-labeled dATP, ligated with T4 DNA ligase, and sonicated to achieve an average fragment length of ~1 kb. Antibodies of H3K27ac  were used to capture DNA fragments with potential regulatory activity. The streptavidin C1 magnetic beads were used to enrich DNA fragments that were successfully ligated. HiChIP libraries were generated with the Illumina Tagment DNA Enzyme and Buffer kit and sequenced with Illumina NextSeq or NovaSeq.HiChIP was performed based on the previously published protocol79. For calling chromatin loops, we first generated a union of H3K27ac sites by merging H3K27ac ChIP-seq binding sites (broad peaks) identified in SOX2-high squamous cancer cell lines KYSE140, TT, TE10, LK2, and NCI-H520. We then used these sites as “anchors” and counted the number of PET spanning these anchors using the Hichipper pipeline80. For presentation, we selected the significant loops (PETs ≥ 5 and FDR < 0.05) that are connected to the anchor overlapping with the SOX2 transcription start site. For presenting HiChIP data from SKMES1 cells with and without CRISPR-mediated e1 activation, two biological replicates were merged.The sequencing reads were aligned to the hg19 human genome using the HiC-Pro pipelineSOX2 enhancer regions. We then used the FIMO software81 with a threshold of P value <10−4 to identify transcription factor binding motifs from the JASPAR motif database82 that are present in the SOX2 enhancers.We used ATAC-seq signal from TCGA squamous cancer samples and BRD4 ChIP-seq signal from KYSE140 cells to narrow down DNA coordinates of candidate 83 with minor modifications. Two million cells per 10 cm dish were seeded one day prior to labeling. Cells were first treated with 0.5 µM ARV-771 or the same volume of DMSO control for 2 h at 37 °C and then treated with 200 µM 4sU  or the same volume of DMSO for 20 min at 37 °C. Per condition, cells were harvested and processed with TRIzol and Zymo Quick-RNA miniprep purification. Twenty micrograms of purified RNA was mixed with 5 μg of MTSEA biotin-XX  in 400 μl of Biotinylation buffer  and incubated for 2 h with rotation in the dark. Free biotin was then removed with Zymo RNA Clean & Concentrator kit. One hundred microliters of Dynabeads MyOne Streptavidin C1 (Thermo Fisher) was added to RNA and incubated in 200 µl Biotin binding buffer  for 1 h with rotation. Beads were washed three times with the Biotin binding buffer. RNA was eluted sequentially with 5% β-mercaptoethanol for 15 min at room temperature and 100% β-mercaptoethanol for 5 min at 50 °C. The combined RNA elute was purified with Zymo RNA Clean & Concentrator kit. The abundance of SOX2 nascent transcription was quantified using RT-qPCR and normalized to HPRT1 nascent transcription. All the qPCR primers are listed in Supplementary Table 4sU labeling of nascent RNA was performed as previously describedSOX2 cDNA  supplemented with protease inhibitors and sonicated with QSonica Q800R . Protein extract was denatured with LDS sample buffer (Thermo Fisher) supplemented with 20 mM dithiothreitol, separated in 4–12% NuPage Bis-Tris gel (Thermo Fisher), and transferred to nitrocellulose membranes. For immunoblotting, we used primary antibodies of SOX2 , ACTIN , and BRD4 , and secondary antibodies of goat anti-rabbit IRDye 800CW , and goat anti-mouse IRDye 680CW . In this study, we independently validated the specificity of the SOX2 antibody by using cells with and without ectopic expression of 2) × 0.5.All animal experiments were conducted in accordance with procedures approved by the institutional Animal Care and Use Committee at the Dana-Farber Cancer Institute, in compliance with NIH guidelines. For subcutaneous implantation, 2.5 million LK2 cells with and without CRISPR-mediated e1 repression were resuspended in 200 μl mixture (1:1 Matrigel:media) and injected into the flanks of female nude mice . All the mice were housed in pathogen-free environment, with 12 h of light and 12 h of dark cycles, 18–21 °C, and 40–60% humidity. Mice were examined every 3–4 days, and tumor length and width were measured using calipers. The maximal tumor size permitted by our ethics committee is 2 cm (in any dimension). None of the tumors in our study exceeded the maximal limit. Tumor volume was calculated using the following formula: (length × widthFurther information on research design is available in the Supplementary InformationPeer Review FileReporting Summary