Promoter-proximal pausing of RNA polymerase II (Pol II) is a key regulatory step during transcription. Despite the central role of pausing in gene regulation, we do not understand the evolutionary processes that led to the emergence of Pol II pausing or its transition to a rate-limiting step actively controlled by transcription factors. Here we analyzed transcription in species across the tree of life. We found that unicellular eukaryotes display a slow acceleration of Pol II near transcription start sites. This proto-paused-like state transitioned to a longer, focused pause in derived metazoans which coincided with the evolution of new subunits in the NELF and 7SK complexes. Depletion of NELF reverts the mammalian focal pause to a proto-pause-like state and compromises transcriptional activation for a set of heat shock genes. Collectively, this work details the evolutionary history of Pol II pausing and sheds light on how new transcriptional regulatory mechanisms evolve. Drosophila and mammals, disrupting the continuous flow of transcription . Pol II transiently “pauses” 20–60 bases downstream of the transcription start site (TSS) at all genes in cription 1–4. The 11 to study transcription in 20 extant organisms that represent two billion years of evolution , and single-celled eukaryotes including the social amoeba (Dictyostelium discoideum), two ichthyosporeans , and a filasterean (Capsaspora owczarzaki). We also included a number of metazoan organisms representing major taxa, including the cnidarian (Nematostella vectensis), the sea urchin (Strongylocentrotus purpuratus), the water flea (Daphnia pulex), the butterfly (Dryas iulia), and the cyclostome (Petromyzon marinus). Finally, we have augmented our PRO-seq atlas by integrating published data from a fly (Drosophyla melanogaster11), a nematode (Caenorhabditis elegans12), yeast (Saccharomyces cerevisiae and Schizosaccharomyces pombe10), model plants , and mammals (Homo sapiens and Mus musculus16). These species occupy key positions along the phylogenetic tree, allowing us to investigate most major transitions in the animal lineage.We used Precision Run-On and Sequencing (PRO-seq)volution , includiZ. mays showed a focused peak, while the plant O. sativa and the yeast S. pombe displayed a more dispersed peak downstream of the TSS. The plant A. thaliana and yeast S. cerevisiae showed no evidence of pausing. To reveal more subtle differences in the dynamics and gene-by-gene variation at the pause site than observed in meta profiles, we computed pausing indexes which quantify the duration Pol II spends in a promoter-proximal paused state17. Pausing indexes revealed that the residence time of Pol II at the pause site is, on average, 1–2 orders of magnitude higher in metazoans than unicellular eukaryotes or plants (fig. S1). Consistent with the meta plots, we also noted wide variation in pausing indices in unicellular eukaryotes and plants. Taken together, our results suggest that an ancestral slowdown in Pol II transcription near the TSS may have arisen in unicellular eukaryotes and became longer in duration and more focused during the early evolution of metazoans.As expected, most metazoan organisms exhibited a pileup of RNA polymerase 30–100 base pairs downstream of the TSS indicative of Pol II promoter-proximal pausing . Convers19. Of these proteins, the NELF complex can establish pausing both in vitro and in vivo20. The NELF complex consists of multiple subunits, including NELF-A, -B, -C (or its isoform -D), and -E. CryoEM studies revealed that NELF-B and -E form a sub-complex, while NELF-C/-D and -A form a separate subcomplex. NELF-B and -C/-D interact with one another forming a core structure that holds the entire NELF complex together , and the negative elongation factor (NELF) complextogether 21–23.fig. S2; fig. S3). We found that NELF-B and -C/-D are widely distributed in eukaryotes, suggesting that the core NELF subunits were present in a shared common ancestor of all eukaryotes. Both subunits were secondarily lost in yeast, S. pombe and S. cerevisiae, as well as in the nematode C. elegans and in land plants. NELF-A is present in some unicellular eukaryotes; a strong match to the metazoan protein first appeared in a common ancestor of Ichthyosporea and metazoans. We only found strong evidence for NELF-E in metazoans, and the most parsimonious model is that NELF-E evolved early in Metazoa or just before the transition to multicellularity. Collectively, these findings demonstrate a strong association between the evolution of NELF proteins and paused polymerase near TSSs.We hypothesized that the evolution of NELF proteins was associated with the gain of pausing in eukaryotes. To test this hypothesis, we used BLASTp to identify potential orthologs of the human NELF subunits among a group of 30 organisms representative of key eukaryotic taxa , with some structural conservation extending back to archaea24. Thus, proteins responsible for the release from pause in metazoans  were part of the ancestral eukaryotic transcription complex, and evolved before the high pausing indices found in metazoans. The sole exceptions were the HEXIM proteins (HEXIM1 and HEXIM2), which are part of the 7SK complex that works in preventing P-TEFb-mediated pause release25. The most parsimonious model is that HEXIM proteins evolved in a common ancestor of Metazoa, perhaps coincident with NELF-E, as an additional checkpoint to increase the residence time of paused Pol II or to regulate pausing in metazoans.To test whether other factors besides NELF were associated with the evolution of paused Pol II, we examined the evolutionary conservation of other proteins linked to pausing. Most other proteins implicated in the early steps of transcription elongation, including PAF1, DSIF , the positive transcription elongation factor , and 7SK  are deeply conserved among eukaryotes . The addition of NELF-A increased pausing indexes to the same order of magnitude observed in metazoan model organisms . Thus, NELF-B and -C/-D are sufficient for pausing, but the addition of NELF-A, NELF-E, and HEXIM proteins correlates with higher pausing indexes and suggests the derived proteins may act together with the core NELF complex to fine-tune the function of paused RNA polymerase .Our finding that NELF and HEXIM protein evolution were uniquely associated with polymerase pausing led us to suspect that gains of specific NELF and HEXIM protein subunits may have resulted in incremental alteration of the residence time of paused Pol II along the animal stem lineage. To determine how the addition of multiple NELF subunits affected the strength of pausing, we compared pausing indexes between species with a different complement of NELF or HEXIM subunits. Species containing NELF-B and -C/-D (which we refer to as the “core” NELF complex) have higher pausing indexes than species without any NELF subunits ; Fig S4.Z. mays, S. pombe, and O. sativa all display an accumulation of Pol II near the TSS, despite having lost both NELF-B and NELF-C/D. This extreme example of a proto-pause appears in a similar location as a canonical pause (or just downstream), but does not have the same magnitude of pausing index . Conversely, the DNA sequence motif of the TATA box and Initiator were not correlated with pausing index (fig. S5G-H). Altogether, our data support the idea that a pause sequence motif, featuring a C (or possibly G) in the Pol II active site at the pause position, serves as an ancestral step limiting the rate of transcription after initiation and can be linked to the formation of a proto-pause. This pause-associated DNA sequence alongside other chromatin factors, such as the position of the +1 nucleosome and the rate at which the P-TEFb subunit CDK9 phosphorylates the early elongating Pol II complex, may then be sufficient to explain much of proto-pause formation in species such as S. pombe9.To determine whether the pause motif was associated with pausing index variation across all 20 species, we examined the enrichment of the human pause motif near the pause position . Despite31). The NELF-B dTAG was reported and validated in a recent paper7, while the NELF-E dTAG cell line is novel here. We verified that the FKBP12-tagged NELF-E protein was properly localized and that NELF-E was nearly undetectable within 30 min after the addition of 500 nM dTAG . We also verified that the rapid depletion of both NELF subunits decreased Pol II levels at the pause site following 30–60 min of dTAG-13 treatment, as measured by PRO-seq (fig. S8A). We hypothesized that loss of NELF-B would have a greater impact on NELF complex assembly on chromatin than loss of NELF-E due to the central role of NELF-B in the complex (21). Consistent with our hypothesis, we observed that loss of NELF-B led to a decrease of the entire NELF-B/E sub-complex from chromatin, while a loss of NELF-E resulted in only a moderate reduction of 40% in NELF-B protein levels . These findings confirm that the functions of NELF-B and -E in mESCs mirror the structure and evolutionary history of these NELF subunits.Our analysis of NELF evolution shows that the core NELF subunits, NELF-B and -C/D, evolved earlier than the ancillary subunits, NELF-A and -E. To test the functional impact of core and ancillary subunits in mammalian cells, we generated FKBP12-homozygously tagged mouse embryonic stem cell (mESC) lines that rapidly degrade either NELF-B (13) or NELF-E after treatment with the small molecule dTAG-13 –B7,31. TB complex 21. Consifig. S8B-C). To investigate the observed Pol II signal recovery, we first clustered genes based on their changes in Pol II loading between 30 and 60 min of dTAG treatment (fig. S9A). And, cluster 3 exhibited a recovery of Pol II further into the gene body in a similar position as the slowdown of Pol II observed in S. pombe and O. sativa, potentially near the location of the +1 nucleosome, as reported by a previous study32.Our PRO-seq data in the NELF-B cell line showed that many genes partially recovered Pol II at the pause site following 60 min of treatment (fig. 9B). Interestingly, the main difference between clusters 1 and 3 was that genes in cluster 3 had higher initiation rates, as determined by both TT-seq33 and a computational modeling approach analyzing steady-state PRO-seq data17 (fig. S9C). Genes in cluster 3 also had much higher binding of some components of the pre-initiation complex and more clearly defined DNA sequence motifs that specify transcription initiation34 (fig. S9D-E), potentially consistent with higher initiation rates. Based on these results, we propose that clusters 1 and 3 partially recover Pol II near the pause due to a combination of DNA sequence and interactions with well-positioned nucleosomes. We also speculate that genes in cluster 3 recover in a more downstream position as a result of a higher rate of initiation. Greater initiation rates at these genes may lead to an accumulation of Pol II at the start of the gene that causes polymerases to be pushed downstream due to interactions between newly incoming Pol II. In sum, we found that after NELF depletion, Pol II signal resembles the pattern found in proto-paused organisms that have lost the core NELF subunits. Furthermore, this proto-paused-like state is associated with the same DNA sequence features and the presence of strongly positioned nucleosomes.We hypothesized that after the depletion of NELF, DNA sequences associated with the proto-pause in organisms without NELF-B may be sufficient to re-establish some paused Pol II. We looked for enrichment of the DNA proto-pause motif at loci that exhibited recovery of the paused state after NELF depletion. We found both higher enrichment of the pause motif and better positioning of the +1 nucleosome in clusters 1 and 3 when compared to cluster 2 ; fig. 9B38. The factors that are responsible for pause release  are conserved in all eukaryotes , pointing to the critical role of release  in eukaryotic organisms10. After the depletion of NELF-B, we observed paused Pol II “creeping” across the first couple of kilobases of the gene body (fig. S10), similar to observations made in S. pombe, which has no NELF10. As a result, Pol II which needs to be released from pause by p-TEFb is no longer in a fixed location, in proximity to promoter-bound transcription factors.We speculate that the evolution of a focal pause was required for the evolution of a system that could control gene expression by releasing paused Pol II. In metazoans, sequence-specific transcription factors can modulate pause release and thereby tune the level of gene expression40. We asked whether HSF1 could release paused genes as efficiently following the depletion of NELF-B and -E in mESCs . Although many classical up-regulated genes were properly up-regulated following the depletion of NELF-B and NELF-E, heat shock (HS)-dependent genes on average had a lower induced fold-change following NELF-B depletion . Thus, Pol II redistribution after NELF-B depletion does prevent HSF1 from acting efficiently as a transcriptional activator.We hypothesized that the downstream redistribution of Pol II after NELF-B depletion would prevent the targeted regulation of gene expression by transcription factors acting to release paused Pol II into productive elongation. To test this hypothesis, we turned to the well-studied heat shock system, where the transcription factor heat shock factor 1 (HSF1) activates transcription of a core group of a few hundred genes following heat stress by the release of paused Pol IIin mESCs . We firs7, including the accumulation of Pol II trickling into the gene body (fig. S10), we focused our analysis on the gene body downstream from NELF-induced Pol II trickling regions. We also excluded genes with altered gene body density following dTAG-13 treatment in either cell line  and in a previous study32. The high rate of firing at these genes may be associated with a high concentration of p-TEFb, resulting in a higher probability of releasing Pol II in the right location before it trickles away from the promoter. In contrast, the more moderately induced and highly paused HS genes are firing less frequently and the trickling of paused Pol II to more downstream locations may prevent their proper activation (fig. S13). Altogether, these findings support our model in which the evolution of pausing facilitated the ability for transcription factors to act on pause-release, providing an additional step to more tightly control gene expression.To rule out the possibility that our observed differences in HSF1-dependent gene activation were driven by changes in gene expression following dTAG-13Our work offers mechanistic insights into how new regulatory complexity evolved by enabling targeted regulation of a preexisting step in the transcription cycle through the evolution of a focal promoter-proximal pause. We propose that the recruitment of P-TEFb and PAF1, which cause pause-release in metazoans, actually serve a more general role that is necessary at all genes in all eukaryotic organisms, regardless of whether the organism has a long-lived focal pause. The evolution of a “focal” pause collapsed the substrate for this step in transcription to a single location at each gene and increased the pause residence time. The degree to which Pol II slows down at the pause position, which progressively increased in the branches leading to metazoans, appears to be affected by the evolution of NELF-E, NELF-A, and HEXIM proteins. Together these evolutionary innovations collapsed a rate-limiting step in all eukaryotes into a single position in metazoans. A centralized location for paused Pol II allows transcription factors to catalyze the release of Pol II into productive elongation, by providing a focused and promoter-proximal target adjacent to transcription factor binding sites, as shown here in the case of HSF1. This innovation provided a new rate-limiting step in transcription that could be targeted for gene-specific regulation. The evolution of additional regulatory complexity may have helped to enable the evolution of complex, multicellular metazoan organisms.https://github.com/alexachivu/PauseEvolution_prjTables in CSV format can be downloaded from: Data generated in this study can be found in Gene Expression Omnibus at: GSE223913.https://github.com/alexachivu/PauseEvolution_prj/Custom code for analyzing sequencing data can be found on GitHub under: 44.An overnight culture of E. coli MG1655 was subcultured in 50 mL LB and grown at 37°C to OD 600 = 0.95. 5 mL aliquots were pelleted by centrifugation at 3000 × g. Pellets were permeabilized, washed, and flash-frozen as described in 44, and include: ATCC Medium 1176 recipe (1 L), 156 g NaCl, 13 g MgCl 2 × 6H 2 O, 20 g MgSO 4 × 7H 2 O, 1 g CaCl 2 × 2H 2 O, 4 g KCl, 0.2 g NaHCO 3, 0.5 g NaBr, 5 g yeast extract, 1 g glucose. After mixing components, the pH was adjusted to 7.0 and the buffer was autoclaved.ATCC 33500 was grown for 48 hours at 35 °C in ATCC Medium 1176. 12.5 mL culture was centrifuged, and the cell pellet was resuspended in 3 mL cold non-yeast permeabilization buffer. To increase permeabilization of archaeal cells, the cell suspension was split into 3 × 1 mL aliquots in screw-cap tubes and combined with 400 μL sterile 0.5 mm glass beads. Cells were subject to bead-beating for 3 cycles of 2 minutes vortexing, 2 minutes on ice. Supernatants were transferred to 1.5 mL tubes, centrifuged to collect cell contents, and washed twice by resuspension in 500 μL storage buffer. Cells were resuspended in a final volume of 50 μL storage buffer and snap-frozen. The permeabilization and storage buffers were the same as reported previously Sea Lampreys (Petromyzon marinus) were obtained from Lake Michigan via the Great Lakes Fisheries Commission and maintained under University of Kentucky IACUC protocol number 2011–0848 . For tissue sampling, animals were euthanized by immersion in buffered tricaine solution (1.0 g/l), dissected, and tissues were immediately frozen in liquid nitrogen. We analyzed muscle samples taken from the flank of one male and one female.45. Biological replicates of 20 hour blastula embryos were raised at 15°C in 0.2 um filtered sea water. The embryos were then spun down at 500 G and 0°C for 3 minutes and the pellets were flash-frozen in liquid nitrogen, stored at −80°C and shipped in dry ice.All of the animal rearing and downstream processing use the same protocols as 46 and 16). Wing tissues were dissected from pupae in cold PBS, after which nuclei were extracted in cold PBS using a dounce homogenizer. Nuclei were spun down and resuspended in nuclei storage buffer before flash freezing.Wing tissues were sampled from Day 3 pupae derived from Costa Rican stock following standard protocols (e.g. Capsaspora owczarzaki (strain ATCC 30864) was cultured axenically at 23°C in ATCC medium 1034 (modified PYNFH medium) in tissue culture-treated flat-bottomed polyethylene tissue culture flasks. Confluent cells were harvested by centrifugation , and the pellet flash-frozen and stored at −80°C. For the isolation of intact nuclei, cells were harvested as before; the pellet was washed twice with phosphate-buffered saline (PBS), resuspended in 1ml of 2x Lysis Buffer  and incubated on ice for 18 minutes. The resulting lysate was centrifuged , and the pellet containing nuclei was washed once with 1ml Wash Buffer . The nuclei were pelleted once more, resuspended in 1ml Storage Buffer , and stored at −80°C. For each buffer, 2 PhosStop™ phosphatase inhibitor tablets (Roche), 1mM PMSF, 50 μg Pepstatin A, 56 mg sodium butyrate, and 1 cOmplete™ Protease Inhibitor Cocktail tablet (Roche) per 50ml buffer were added immediately prior to use.Creolimax fragrantissima and Sphaeroforma arctica were cultured axenically in BD Difco™ Marine Broth 2216, in tissue culture-treated flat-bottomed polyethylene tissue culture flasks at 12°C; confluent cells were harvested by centrifugation, and the pellet flash-frozen and stored at −80°C.Dictyostelium discoideum AX3 wildtype cells were cultured axenically in HL-5 (Formedium) on untreated polystyrene petri dishes at 22°C. Confluent cells were resuspended in fresh media and centrifuged at 300×g for 5 min. The pellet was flash frozen and stored at −80°C.47. Adult males and females were induced to spawn in small glass bowls, and fertilized egg masses were removed and cultured in small glass bowls at 25°C. Swimming gastrula/early polyp stage animals were harvested for nuclei isolation.Adult Nematostella were reared in 1/3 strength artificial seawater at 18°C in dark conditions. Spawning was induced using the protocol described in E14 mESCs (ATTC) were cultured on 0.1% gelatin-coated (Millipore) tissue culture-grade plates in a humidified 37°C incubator with 5% CO2. The culture medium consisted of DMEM (Gibco) supplemented with 2 mM L-glutamine (Gibco), 1× MEM nonessential amino acids (Gibco), 1 mM sodium pyruvate (Gibco), 100 U/mL penicillin/100 U/mL streptomycin (Gibco), 0.1 mM 2-mercaptoethanol (Gibco), 15% fetal bovine serum (Gibco), and 1000 U/mL recombinant leukemia inhibitory factor (LIF). Genetic editing and experiments were performed using cells at passages 10–20.7.both cell lines were generated using an identical approach to endogenously and homozygously tag the C-terminus of each protein with FKBPF36V tag. The NELFB line has been previously described, and the NELFE line was generated for this study. The methods below describe the NELFE line generation, for more details of NELB line, please refer to nelf-e genes, two plasmid constructs were generated:Cas9 vector to target the C terminus of Nelfe gene: PX459 vector (Addgene 62988) was digested using BbsI-HF (NEB) and single guide RNA targeting Nelfe was annealed ..Homology-directed repair (HDR) vector containing the insert FKBPF36V tag, 2× HA tag, self-cleaving P2A sequence, and puromycin resistance, flanked by 1-kb Nelfe HDR sequences: The insert was obtained from pCRIS-PITCHv2-dTAG-Puro (Addgene 91796) . The plasmid backbone (pBluescript), Nelfe HDR sequences, and the insert were amplified using Q5 polymerase (NEB), and the plasmid was constructed using NEBuilder HiFi DNA assembly (NEB). All oligos used are available in the table below.To target the 3 million cells were transfected with 10 μg of PX459-Nelfe_sgRNA and 10 μg of Nelfe_left-FKBPF36V-2xHA-P2A-PURO-Nelfe_right using the Lonza P3 primary cell 4D-Nucleofector X 100-μL cuvettes. The transfected cells were plated on a 10-cm dish coated with mouse embryonic fibroblasts (MEFs). 48 hours after transfection, correctly targeted cells were selected for in 6 μg/mL Blasticidin for 5 days. Surviving cells were split into 1000 cells per 10-cm dish and maintained for 9 days under puromycin selection. Surviving clones were picked and expanded under a stereomicroscope and genotyped for the insert.https://www.bio-techne.com/p/small-molecules-peptides/dtag-13_6605) was reconstituted in DMSO (Sigma) to a final concentration of 5 mM. The dTAG-13 solution was diluted in culture medium to 500 nM and added to cells for the indicated time period during medium changes.The dTAG-13 reagent (Bio-Techne: Cells plated on u-Slide eight-well plates (Ibidi) were washed with PBS+/+ and fixed in 4% PFA (Electron Microscopy Sciences) in PBS+/+ for 10 min at room temperature. Cells were subsequently washed twice with PBS+/+, followed by wash buffer and 0.1% Triton X-100 (Sigma) in PBS+/+, and permeabilized in 0.5% Triton X-100 (Sigma) in PBS+/+ for 10 min. Then blocked with 3% donkey serum (Sigma) and 1% BSA (Sigma) for 1 h at room temperature. Cells were incubated with primary antibodies in blocking buffer overnight at 4°C . Then, they were washed three times in wash buffer and incubated with suitable donkey Alexa Fluor  for 1 h at room temperature. Finally, cells were washed three times with wash buffer, with the final wash containing 5 μg/mL Hoechst 33342 (Invitrogen), and imaged.Fixed immunostained samples were imaged using a Zeiss LSM880 laser scanning confocal microscope. An air plan-apochromat 20×/NA 0.75 objective was used. Images represent a 2D plane correlating to the monolayer of cells in culture. No further image processing was performed.Cells were harvested and lysed by adding 350 μL of lysis buffer containing 1× cell lysis buffer , 1 mM PMSF , and cOmplete Ultra protease inhibitor (Sigma) to a 90% confluent six-well dish  after washing with PBS−/−.The harvested cells were incubated on ice for 5 min, scraped and collected then sonicated for 15 sec to complete lysis and then spun down at 12,000g for 10 min at 4°C. The supernatant was collected, and protein concentration was measured using Pierce BCA protein assay kit (Thermo). Samples were prepared by mixing 10 to 20 μg of protein with Blue loading buffer  and 40 mM DTT , followed by boiling for 5 min at 95°C for denaturation. Cellular compartment fractions were prepared using subcellular protein fractionation kit (Thermo) following the manufacturer’s instructions.The samples were run on a Bio-Rad Protean system and transferred to a nitrocellulose membrane  using transblot semidry transfer cells (Bio-Rad) following the manufacturer’s instructions and reagents. The nitrocellulose membrane was briefly washed with ddH2O, stained with Ponceau S (Sigma) for 1 min, and washed three times with TBST (0.1% Tween 20 [Fisher] in TBS) to check for transfer quality and serve as a loading control. Then it got blocked with 4% BSA in TBST for 1 h at room temperature and incubated with primary antibodies diluted in blocking buffer overnight at 4°C. The membrane was then washed three times with TBST, incubated with secondary antibodies in blocking buffer for 1 h, and washed three times with TBST. Last, the nitrocellulose membrane was incubated with ECL reagent SignalFire for 1–2 min and imaged using a ChemiDoc (Bio-Rad).The following antibodies were used in this paper:40. We started the heat stress after 30 min of dTAG-13 treatment, which corresponds to the maximal depletion of paused Pol II based on PRO-seq data.Heat shock was administered as described in recent work from the Lis lab We performed the analysis of the HS data in two different ways:On a first analysis, by calling gene expression changes using DEseq  between a regular HS and NHS experiment. Then, we plotted log2 fold changes of (HS+dTAG)/(NH) and (HS+dTAG)/(NHS+dTAG) at these pre-defined HS up-regulated or down-regulated genes coordinates.fig. S13F). We confirmed a slight up-regulation of genes in the vicinity of the TSS after dTAG-13 treatment by plotting the correlation between the log2 fold change of dTAG-13 treatment after NELF-B degradation (fig. S10). We used deeptools to compute log2 fold change bigwigs and plot heat maps.For a second approach, we considered the effect that NELF-B depletion has on Pol II trickling into gene bodies. To eliminate any biases from increased PRO-seq signal downstream from the TSS due to the dTAG-13 treatment alone, we re-analyzed our data after removing the first 3 kb downstream from the TSS and we focused on genes that remain unchanged following dTAG-13 treatment, but are either up or down-regulated after HS . The same effect was also observed, though in far fewer genes in the absence of NELF-E . We noted no defect in down-regulated genes using this analysis approach.Both of these analyses confirmed a defect in up-regulation across many HS-dependent genes. In the second analysis, we observed that a significant number of genes that were meant to show HS-dependent upregulation failed to reach their full transcription potential in the absence of NELF-B .PRO-seq or ChRO-seq PRO-seq.*In this paper we refer to PRO-seq, GRO-seq, and ChRO-seq as https://github.com/Danko-Lab/proseq2.0) using the following parameters: -RNA5=R1_5prime --RNA3=R2_5prime --ADAPT1=GATCGTCGGACTGTAGAACTCTGAACG --ADAPT2=AGATCGGAAGAGCACACGTCTGAACTC --UMI1=4 --UMI2=4 --ADD_B1=6 --ADD_B2=0 --thread=8 --map5=FALSE. Library processing included adapter trimming using cutadapt, PCR deduplication (where UMIs are present) using printseq-lite.pl, followed by mapping to the reference genome using BWA. Mapped BAM files were then trimmed either to the 3’-end of the RNA (to map the location of RNA Pol II) or the 5’-end (to map the beginning of the RNA) and the 1bp position was converted to bedGraphs and BigWigs. PRO-seq libraries were also RPM normalized to account for differences in sequencing depth.Single and paired-end reads of PRO-seq data were aligned to its reference genome using the proseq2.0 pipeline from the Danko lab (Data was mapped to the following reference genomes:https://www.ncbi.nlm.nih.gov/nuccore/U00096.2)E.coli:escherichia_coli_mg1655_01312020 (https://www.ncbi.nlm.nih.gov/nuccore/NZ_CP039139.1) and the plasmids included here: https://www.ncbi.nlm.nih.gov/genome/?term=txid523841Haloferax: NZ_CP039139.1 (https://www.ebi.ac.uk/ena/browser/view/GCA_000004695.1)D.discoideum: dicty_2.7 Z.mays:GCF_902167145.1_Zm-B73-REFERENCE-NAM-5.0 (https://www.ncbi.nlm.nih.gov/assembly/GCF_001433935.1/)O.sativa:GCF_001433935.1_IRGSP-1.0_genomic.fna (C.owczarzaki: Capsaspora_owczarzaki_atcc_30864.C_owczarzaki_V2.dna.toplevelS.pombe: Schizosaccharomyces_pombe.ASM294v2.dna.toplevelS.cerevisiae: Saccharomyces_cerevisiae.R64-1-1.dna.toplevelhttps://www.ncbi.nlm.nih.gov/assembly/GCF_001186125.1/)S.arctica: Sphaeroforma_arctica_jp610.Spha_arctica_JP610_V1.dna.toplevel.fa.gz (ncbi.nlm.nih.gov/assembly/GCA_002024145.1/)C.fragmatissima: Creolimax_fragrantissima.genome (N.vectensis: nemVec1https://hgdownload.soe.ucsc.edu/goldenPath/ce6/chromosomes/)C.elegans: ce6 (http://wfleabase.org/prerelease/dpulex_jgi060905/genome-assembly/)D.pulex: dpulex_jgi060905 (46D.iulia: published assembly in http://genome.ucsc.edu/cgi-bin/hgTracks?db=dm3&chromInfoPage=)D.melanogaster:dm3 (https://www.ncbi.nlm.nih.gov/assembly/GCF_000002235.3/)S.purpuratus: Spur_3.1 (https://www.ncbi.nlm.nih.gov/assembly/GCA_000148955.1/)P.marinus: petMar2 (M.musculus: mm10 (GRCm38)https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.13/)H.sapiens: hg19 (https://github.com/Danko-Lab/RunOnBamToBigWig) to compute 5’prime mapped BigWigs . Then, we used published gene annotations in each species, resized them to a 1kb window centered on the gene annotation start site, and computed the total number of 5’-prime mapped PRO-seq reads that fall within this interval using 10bp sliding windows. Last, to reannotate gene start sites, we took the start position of the 10bp window with the maximum number of 5’-prime PRO-seq reads. We used these annotated TSSs for all further analyses.We took PRO-seq mapped BAM files and ran it through the RunOnBamToBigWig tool developed in the Danko lab . Genes shorter than 300bp were removed from the analysis.50.We use DeepTools to functions  to compute heatmaps and meta profiles of PRO-seq data. We also used DeepTools to cluster and compute correlations between the heat shock PRO-seq libraries as BAM files  Before running bigwigCompare, we generated combined BigWigs of the plus and minus PRO-seq data for each sample.bigwigCompare --bigwig1 HS_plus.minus.bw --bigwig2 NHS_plus.minus.bw -o HS.NHS_log2FC_plus.minus.bw --outFileFormat bigwig --pseudocount 0.1 --operation log2 --skipNAs -p max/2 &computeMatrix reference-point --referencePoint center -R regions.bed -S NHS_plus.minus.bw HS.NHS_log2FC_plus.minus.bw --samplesLabel “NHS” “HS / NHS”--sortUsingSamples 1 \-b 1000 -a 50000 \--binSize 1000 \--skipZeros -o Counts_GB.increase_log2FCs_NELF_B.gz -p max/2plotHeatmap -m Counts_GB.increase_log2FCs_NELF_B.gz \   -out Heatmap_Counts_GB.increase_log2FCs_NELF_B.pdf \   --colorList “blue,white,red” \   --heatmapHeight 10 \   --heatmapWidth 3 \   --zMin −2 --zMax 2 --missingDataColor 0 \   --averageTypeSummaryPlot “mean”plotProfile -m Counts_GB.increase_log2FCs_NELF_B.gz \   -out Metaplot_Counts_GB.increase_log2FCs_NELF_B.pdfmultiBamSummary bins \    --bamfiles ./*bam \    --minMappingQuality 10 \    -p max/2 \    -out allTSS_QC_readCount_corr.npz \    --outRawCounts allTSS_QC_readCount_corrRaw.tabplotCorrelation \    -in allTSS_Abood.PROseq_readCount_corr.npz \    --corMethod spearman --skipZeros \    --plotTitle “Spearman Correlation at annotated TSSs” \    --whatToPlot heatmap --colorMap seismic --plotNumbers \    -o allTSS_QC.Spearman.heatmap_readCounts.png \    --outFileCorMatrix allTSS_QC.PROseq_readCount_Spearman.tabfig. S2 and S3. For this analysis, we downloaded human protein sequences from UniProt, along with complete proteomes  of all species analyzed in this study from NCBI or Ensembl (only for C. fragrantissima and D. iulia).To determine if human orthologs of key transcription machinery proteins  were present in other species, we performed a reciprocal BLAST using the rBLAST library (version 0.99.2). First, given a human protein, H, a BLASTp was performed against the protein database of a different organism (X). Sequences in species X that produced a BLASTp E-value lower than 1e-6, were considered candidates for a second BLASTp run. On the second BLASTp run, we performed a reciprocal BLAST search using the candidates in species X relative to the human proteome. If this reciprocal search yielded any valid hits passing the scoring same threshold of E-value < 1e-6, the protein was considered present in species X. This approach was repeated for all protein sequences in https://github.com/alexachivu/PauseEvolution_prj/blob/main/Protein%20BLAST%20(BLASTp)) the human homologs of those proteins to the entire proteome of all species in this study. We provide the human protein sequences used in this reciprocal BLAST search here: https://github.com/alexachivu/PauseEvolution_prj/blob/main/Human.orthologs_sequences.faThen, we used the following script to compare  bedtools getfasta -s -fi mm10.fa.gz -bed ./M.musculus_Pause.20bp.bed -fo M.musculus_Pause.20bp.outWe then run the MotifDicovery pipeline  to discover DNA sequences associated with the pause site#2. R --vanilla --slave --args $(pwd) M.musculus_Pause.20bp.outM.musculus_Pause.20bp_SeqLogo.pdf < MotifDicovery.Rhttps://github.com/alexachivu/PauseEvolution_prj/blob/main/MotifEnrichment) to compare the DNA sequences in each species with a human pause motif described in 28.#3. For the motif enrichment analysis, we used a different script  as scaling factors.51 based on relationships depicted in 52 and edited in InkScape and Illustrator.We used BioRender to draw all of the illustrations and cartoons in this paper, with the exception of the schematic representing the relationships between species. The latter was prepared using Interactive Tree of Life (iTOL) v.6.7 An inventory of all functions used to process the PRO-seq data is deposited on GitHub at:https://github.com/alexachivu/PauseEvolution_prj/tree/main


A recent study from Yan et al.  providesHTT gene located in the 4th chromosome of the human genome  is a devastating monogenetic neurodegenerative disorder that is caused by an expanded CAG repeat in the exon 1 of the n genome . The pren genome . Thus, HHTT) or its transcript has been considered as promising strategies for HD treatment. For example, anti-sense oligonucleotides (ASOs) that suppress the HTT mRNA have been investigated in the HD mouse models and then entered the clinical trials  to navigate a nuclease (Cas9) to the target genome site and cleave it, triggering genome editing by generating double-stranded breaks (DSBs) and the subsequent DNA repair. CRISPR has been applied in both plants and animals, including rodents and non-human primates (NHP)  . Importaes (NHP) . Recentles (NHP) .HTT correction. They applied the AAVs to the striatum of HD KI pigs by stereotaxic injection, and the injected AAVs successfully “hunt out” the CAG repeat expansion with remarkably high efficiency and corrected it with a normal 20×CAG by homology directed repair (HDR) following CRISPR-mediated DNA cleavage. This genetic correction led to unprecedented phenotypic rescue that has never been observed in HD animal models previously. At the molecular level, the authors detected a correction of the transcriptome towards the wild-type (WT) after AAV injection, and the expression of mutant HTT protein (mHTT) was also drastically decreased. At the cellular level, the in vivo neurodegeneration and glia activation were significantly ameliorated. At the whole animal level, the injected pigs exhibited alleviated HD-relevant symptoms such as gait abnormalities and shortened lifespan. Overall, the study demonstrates that CRIPSR-mediated gene correction is an extremely promising new approach to fundamentally treat HD.In the Yan et al. study, the authors used their previous established HD KI pig model harboring 150×CAG repeats to test the potential therapeutic effects of genome editing by the CRISPR-mediated knock-in approach. They used the adeno-associated virus (AAV) to package the CRISPR elements, including Cas9, gRNAs, and the homologous recombination template for mMore specifically, there are several highlights of this study: (i) The gene therapy of HD in large animal models. Almost all the HD gene therapy studies were performed in mouse model, which typically lacked obvious neurodegeneration to mimic human HD. The pig models exhibit HD-like phenotypes with higher fidelity and are much closer to the patient’s symptoms, providing an ideal tool for HD therapeutic studies; (ii) Remarkable therapeutic effects after the gene editing by a single intracranial or intravenous injection of AAVs. Unlike the ASO-based gene therapy approaches that require multiple intrathecal injections per year, this study showed that a single peripheral injection could potentially treat HD, providing a much more desirable scenario for potential clinical application; (iii) Potential safety issues were systematically evaluated, including deep-sequencing and whole-genome sequencing that reveal minimal off-target effects and strong animal safety data that encourages further clinical trials.p53 activation (Scientists have been seeking for a fundamental HD therapy for decades without a final success. The Yan et al. study provides a great new hope for the HD patients by leading a new orientation of HD treatment approach. This promising study also inspires many future studies. The CAG repeat replacement is very promising but its efficiency remains to be improved. Besides potential clinical trials utilizing the reported approach, other genome-editing technologies could be considered to tackle HD or further improve the current approach. In light of the recent study showing that CRISPR may lead to endogenous DNA damage response arising from aberrant tivation , inactivtivation  are also


Sox2 gene and its enhancer, in response to a battery of perturbations. We find a close link between chromatin mobility and transcriptional status: active elements display more constrained mobility, consistent with confinement within specialized nuclear sites, and alterations in enhancer mobility distinguish poised from transcribing alleles. Strikingly, we find that whereas loop extrusion and transcription factor-mediated clustering contribute to promoter-enhancer proximity, they have antagonistic effects on chromatin dynamics. This provides an experimental framework for the underappreciated role of chromatin dynamics in genome regulation.The spatiotemporal configuration of genes with distal regulatory elements, and the impact of chromatin mobility on transcription, remain unclear. Loop extrusion is an attractive model for bringing genetic elements together, but how this functionally interacts with transcription is also largely unknown. We combine live tracking of genomic loci and nascent transcripts with molecular dynamics simulations to assess the spatiotemporal arrangement of the  For example, most chromosome conformation capture-based experiments support a model where distal enhancers require close spatial proximity to target genes to confer activation5, often presumed via chromatin “looping”, and engineered promoter-enhancer contacts have been shown to stimulate expression6. However, recent imaging experiments at different loci have shown clear physical separation of enhancers and active genes (often in the order of ~ 200–300 nm), with conflicting results as to whether their separation decreases8, stays the same9 or may actually increase10 on transcriptional activation. The identification of nuclear clusters of lineage-specific transcription factors12, RNA polymerase II (PolII)14, and genes and regulatory elements themselves19 has led to the proposal that transcription is organized into specialized nuclear microenvironments or “hubs”20. In this model, high local concentrations of regulatory factors accumulate near genomic sequences that are loosely co-associated; the shared location of regulatory elements within this microenvironment is more important for transcriptional regulation than their direct physical juxtaposition. These hubs are potentially built up through specific protein-protein interactions and/or phase-separated condensate formation between intrinsically disordered domains found on many transcription factors21. How genes and distal regulatory elements locate or nucleate such hubs, and how the different regulatory inputs are coordinated into a transcriptional decision within, remain open questions.Metazoan gene expression is finely controlled by regulatory inputs from promoter sequences and distal regulatory elements, such as enhancers. How these dispersed elements are spatiotemporally coordinated to determine transcriptional output has been a topic of intense study, but key questions remain unresolved22, the large polymeric chromatin fiber has more constrained movement, due to a crowded environment and elastic interactions with neighboring segments of the polymer23. This is often characterized as sub-diffusive movement, whereby the mean squared displacement (MSD) of the genomic element follows the relationship with time, 24, but we recently reported significant locus-specific differences in chromatin diffusive properties at euchromatic regions in mouse embryonic stem cells (ESCs), suggesting finer-scale modulation of chromatin dynamics, potentially linked to underlying function25. As methods for tracking specific genomic regions in vivo has recently become available, researchers have asked whether the transcriptional activity of genes affects their mobility. We previously showed that an estrogen-inducible transgene could only explore a much smaller nuclear volume on acute induction, and that this constraint was dependent on transcriptional initiation26, consistent with a model whereby the activated gene becomes confined within a transcriptional hub. This is supported by analogous studies showing slowed movement of the pluripotency gene Nanog when transcriptionally active27 and global enhanced chromatin mobility on treatment with transcriptional inhibitors29. However, mobility of the Oct4 gene was found to be insensitive to transcriptional status27, and a different study of transition between ESCs and epiblast-like cells reported acceleration of both promoters and enhancer-proximal sequences specific to the cell state where the elements are active30. A clear understanding of how transcriptional events modulate chromatin dynamics (or vice versa) is thus still lacking.An often-overlooked aspect determining how regulatory chromatin architectures are built or maintained is the underlying mobility (and freedom of movement) of the component factors. Whereas non-histone chromatin proteins, including transcription factors, are highly mobile in the nucleoplasm32, which have been proposed to prevent inappropriate promoter-enhancer communication across TAD borders, and/or to reduce the effective search space for enhancers to co-associate with target genes35. The major mechanism believed to organize TAD architecture is loop extrusion by SMC protein complexes, particularly cohesin : cohesin ablation eliminates TADs, but appears to strengthen compartments48. The exact mechanisms promoting chromosome compartmentation genome-wide are unclear, but since co-association of active domains appears to depend on transcription itself49 and transcription co-factors like BRD250, it is reasonable to hypothesize that these could be the same biochemical principles involved in clustering transcription factors and active elements at proposed transcriptional hubs, raising the curious possibility that loop extrusion may sometimes antagonize such nuclear microenvironments.At a larger scale, promoter-enhancer communication takes place within the context of topologically associated domains (TADs), regions of enhanced intra-domain chromatin contacts identified in population-average Hi-C mapsSox2 control region) of the pluripotency gene Sox2 in mouse ESCs, in combination with detection of nascent transcription from the same allele, for their tracking at high temporal resolution. With a battery of genetic and other experimental perturbations, we confirmed the decoupling of transcription and promoter-enhancer proximity that was previously described at this locus46, and also found a hitherto unappreciated localized effect of transcription on chromatin dynamics. Promoter kinetics are disrupted on severe transcriptional inhibition, but when comparing transcriptionally bursting and “poised” Sox2 alleles, it is the enhancer which specifically becomes less mobile on gene firing. Most strikingly, we observed that deleting either CTCF or transcription factor binding sites induced opposing effects on localized chromatin mobility. In addition, molecular dynamics simulations were able to recapitulate these experimental findings only when competition between loop extrusion and transcription-linked enhancer-promoter communication was reinforced, suggesting they may be antagonistic processes on chromatin dynamics, even though from a population-average viewpoint they are assumed to mediate the same interaction. These findings unify some of the seemingly conflicting results from previous studies and highlight the pitfalls of relying solely on population-averaged experiments on fixed cells to draw conclusions about a dynamic process such as spatiotemporal gene regulation.To assess more closely the interplay of enhancer activity, transcription and cohesin-mediated loop extrusion on the spatiotemporal organization of gene regulation, we tagged the promoter and major enhancer  in the musculus allele of F1 (Mus musculus129 × Mus castaneus) hybrid ESCs (we term this line WTSox2-SCR), enabling their visualization on transfection with plasmids encoding fluorescently labeled ParB proteins51. The small size (~ 1 kb) of the parS sequences allowed us to place the tags very close to the promoter (5.5 kb upstream of the TSS) and actually inside the SCR, in between the elements known to control Sox2 transcription44, facilitating direct imaging of the promoter and enhancer themselves. As a control, we also generated an ESC line (Inter-Down) with parS integration sites shifted by ~ 60 kb, allowing visualization of non-regulatory loci with equivalent genomic separation . Further, allele-specific 4C-seq showed that Sox2-SCR interaction strength was also unaltered by parS integration and ParB binding . Over the short periods over which images were acquired, separation distances were relatively stable . As may be expected from ESC Hi-C maps, the median distance between Sox2 and the SCR is significantly smaller than the control regions of equivalent genomic separation . Although this implies that the parS/ParB system does not perturb endogenous chromosomal locus configurations within the nucleus, the ANCHOR1-tagged control region downstream of the SCR was not included in the multiplexed DNA FISH design. We therefore performed 3D DNA FISH in wild-type F1 and ANCHOR-labeled WTSox2-SCR ESCs, using fosmid probes covering the locations of each of the parS integration sites, further confirming that average Sox2-SCR separation distances are smaller than the control regions . We note that a previous study using Tet- and Cu-repeat operators to label regions a little further upstream of the Sox2 promoter and downstream of the SCR measured significantly larger distances . This suggests that, at least for this locus, the repetitive operator system may artificially inflate physical separation of tagged loci compared to untagged counterparts.For these two ESC lines, we imaged the labeled loci at high temporal resolution (500 ms per frame) in 2D with spinning disk confocal microscopy, using a set of optimized affine transformations to correct for chromatic aberrations and control for camera misalignmentSox2-SCR interaction in the early stages of ESC differentiation to neuronal precursors when Sox2 expression is shut down54. We recapitulated this finding when differentiating the labeled WTSox2-SCR cells, observing a significant increase in average Sox2-SCR distance . However, recent studies, including those at the murine Sox2 locus, have brought this into question44. To directly test the effect of transcription on promoter-enhancer proximity, we also measured Sox2-SCR distances upon either global inhibition of transcription by treatment of the WTSox2-SCR cells with the drug triptolide , or specific inhibition of Sox2 expression in cis by the allele-specific deletion of two critical elements of the SCR (SRR107 and SRR111)44 to create the line ΔSRR107+111Sox2-SCR. In both cases, despite efficient loss of total or musculus-specific Sox2 expression, respectively, observed with qRT-PCR and single-molecule RNA FISH , average Sox2-SCR (and control region) distances remained small and were non-significantly altered . In none of the conditions tested did we find evidence for a multimodal distribution of inter-probe distances  model and extract their apparent diffusion coefficients, 25. As previously, we confirmed that the trajectories approximated to self-similar Gaussian-distributed displacements and an FBM velocity autocorrelation function over the time scale in which measurements are taken , affirming the suitability of the model used. The experimental MSD profiles were non-linear when plotted on double-logarithmic scales, suggesting that their properties cannot be explained by one regime, likely due in the main part to the confounding effects of nuclear and cellular movement and rotation. When analyzing cross-correlations of co-measured trajectories to estimate global movements of the cell/nuclear substrate25, the experimental MSD curves fit very well as the sum of the component locus and substrate FBM regimes . We stress that GPTool, apart from assuming proximity to a global FBM regime, is actually agnostic to any specific polymer model, and obtains estimates of diffusive parameters for individual trajectories which can vary quite a lot from the average (Sox2 promoter (median Table S1). We note that these measured values correspond well with the α ~ 0.2 determined from fits to radial MSD curves for lac/TetO-tagged CTCF-mediated interacting sites with a similar genomic separation of ~ 150 kb40. Analogous radial MSD analysis for the WTSox2-SCR and Inter-Down trajectories revealed similarly constrained motion, with the promoter and enhancer significantly more constrained than the neutral sequences . However, the nature of this analysis, by comparing the motion of one locus relative to the “fixed” second locus, does not allow any mobility differences between the two loci to be discerned. Using substrate-corrected GP-FBM, we further found that the promoter exhibited significantly more constrained motion than the enhancer .We previously reported that seemingly neutral elements within the HoxA locus exhibit different and locus-specific diffusive properties of labeled chromatin regions ,b. Note imes see ; Fig S5a average . As such26. To explore these properties further, we modeled the 800 kb of ESC chromatin around the Sox2 locus as a self-avoiding polymer chain of 1 kb beads, classed as either “neutral”, binding PolII ), transcribed genic regions (Sox2 gene body), or binding CTCF (determined by ChIP-seq peaks and with motif orientation information included). As we previously did for a theoretical locus to explain chromatin conformation changes on acute loss of PolII57, we performed molecular dynamics simulations using Langevin equations to model thermal motion of the chromatin and its binding factors, with the following additions to account for biological processes: PolII molecules have affinity for promoters and enhancers, and traverse the gene body to simulate transcription; PolII molecules also have affinity to each other to simulate potential for condensate or hub formation; cohesin complexes can bind anywhere on the polymer and extrude loops, but has preference to load at promoters and enhancers, and is unable to process past a CTCF-bound site when the motif is oriented towards the extruding loop . Collecting the trajectories of the beads corresponding to the parS-tagged loci, we derived simulation MSD curves indicating a clear reduced mobility of Sox2 and SCR compared to control sequences (These results are in line with our previous observations in a transgenic system that genes explore a more restricted nuclear volume when they are inducedloop see . The ensequences . In accorection) . This reSox2 promoter did not change when the gene was silenced by either onset of differentiation or deletion of SRR107/SRR111 . On the other hand, the SCR became significantly less constrained at the onset of ESC differentiation , combining ANCHOR tags at the SCR and Sox2 promoter with musculus-specific incorporation of MS2 repeats into the 3’UTR of the intronless Sox2 gene59, and subsequent PiggyBac-mediated transposition of constructs for both fluorescently-labeled ParB proteins and MCP. This setup allows for simultaneous tracking of promoter, enhancer and nascent RNA  of total protein levels or estimated transcription rates in our assayed cell line, despite an apparent destabilization of the MS2-tagged mRNA when bound by MCP . Imaging transcription bursts over two-hour windows, we measure an average bursting time of ~ 200 s and an average time between bursts of ~ 630 s. As a population, the observed cells spent ~ 36% of their time with a detected burst of transcription, nearly ten times more frequently than what was observed in the previous study using a cell line with more extensively perturbed Sox2 expression9. To measure chromatin dynamics at maximum temporal resolution, we then used this line for triple-label tracking over five-minute windows. Over this timeframe, the majority of movies were either always transcribing or always silent, but transition points were occasionally observed . Strikingly, however, we found that the enhancer is specifically more constrained on average when transcriptionally active . This is more pronounced for SCR dynamics, but the Sox2 promoter also shows similar behavior, suggesting that both elements are effectively confined within a defined volume during transcription. It is interesting to speculate that this locus restriction is a consequence of transcription taking place in very specified nuclear foci15 and/or condensates21, although chromatin dynamics will need to be traced over longer time periods, spanning several transcription bursts, to determine whether any volume restriction is exclusive to active states. Overall, this direct observation of chromatin dynamics relative to ongoing transcription shows an expectedly high cell-to-cell variability26, with the recurrent trend that in wild-type ESCs, the highly expressed Sox2 gene appears to have high constraints to local mobility that are not altered by transcriptional state. On the other hand, the SCR, while maintaining relative proximity (but not necessarily complete juxtaposition) to the target gene, has greater freedom of movement when the gene is transcriptionally poised yet inactive, but becomes constrained to levels comparable with the gene itself on transcriptional firing.The experiments performed so far have relied on perturbations, such as cell differentiation, cent RNA ,b. Previobserved . When coWT cells , there i60. Furthermore, acute ablation of cohesin has already been shown to generally increase chromatin mobility40. Differentiation to neural precursors causes loss of the ESC-specific TAD border at the SCR, whereas the strong TAD border just upstream of the Sox2 promoter is maintained61 . This loss of “anchoring” to distal regions could thus be responsible for the previously observed reduced mobility constraints at the SCR  or within the SCR (ΔCTCF_SCRSox2-SCR) . Both lines maintained high expression of pluripotency marker genes , and Sox2 expression was only mildly (and non-significantly) reduced in the Sox2-SCRΔCTCF_SCR line, in agreement with previous findings for homozygous deletions of this element62, although expression was reduced to ~ 60% of wild-type levels in the Sox2-SCRΔCTCF_Sox2 line . In agreement with previous studies of the respective roles of these CTCF sites on Sox2-SCR interaction62, allele-specific 4C-seq and ANCHOR inter-probe distance measurements showed negligible topological changes when the SCR CTCF site is deleted and a mild reduced interaction on homozygous deletion of the Sox2 CTCF site . Despite these somewhat limited phenotypic effects, both lines demonstrated a significantly reduced local constraint on chromatin mobility when CTCF binding was abrogated: the median apparent anomalous exponent was increased at the Sox2 promoter in ΔCTCF_Sox2Sox2-SCR cells  on deletion of multiple transcription factor binding sites at SRR107 and SRR111   and S7b. binding –e. TheseΔSRR107,111Sox2-SCR line by deleting the corresponding beads, and abolishing PolII binding at the inactivated Sox2 promoter. The original model did not recapitulate the chromatin dynamics changes observed in the experiments . In particular, the model predicted that transcription factor site deletions at the SCR would increase mobility at the enhancer, instead of placing greater constraints as we had observed. Strikingly, better agreement to experimental observations was accomplished by increasing RNA polymerase stability at bound enhancers, effectively reinforcing the competition between transcription-linked compartmentation and loop extrusion 43, in combination with visualization of any transcriptional hubs themselves, will be required to formally address these questions.By combining live imaging of labeled endogenous loci with a battery of perturbation experiments and molecular dynamics simulations, we have teased apart some of the spatiotemporal complexities of enhancer-promoter communication. The ANCHOR system employs relatively small tags that can be placed extremely close to genomic loci of interest with negligible observable effects on transcription, nuclear organization and cell state, so is a valuable tool for such studies. The first question we addressed was whether promoters and enhancers need to directly juxtapose for transcriptional firing, since conventional C-method and light microscopy approaches have given rather different viewpoints alleles , stronglcision in diffusive property measurements of single trajectories, both on simulations25 and in complex and noisy experimental data . A limitation of this approach, which is also shared by radial MSD analysis, is the requirement to use cross-correlations of co-measured trajectories to correct for global nuclear movements and rotations, which can be quite large in ESCs . There is the possibility that a perturbation could affect the coupling of the two labeled loci more than the individual particle dynamics in themselves, which could be missed by GPTool measurements, but this does not seem to be the case, since most perturbations were found to have localized effects on only SCR or Sox2, and not both together.Whereas average inter-probe distances only demonstrated subtle differences at best in this study, MSD plots revealed more dramatic locus- and condition-specific differences in chromatin dynamics, with the most obvious being the greater relative freedom of movement of control sequences compared to the constrained promoter and enhancer. Conventional fits to ensemble log-transformed MSD curves are not precise and only robustly identify very flagrant differences in dynamics; our previously developed GP-FBM framework demonstrably gives greater preSox2 locus, we found clear links between chromatin dynamics and gene expression: the constrained promoter, but not the SCR, was sensitive to strong transcriptional inhibition by either enhancer element deletion or triptolide treatment, becoming even less mobile. Furthermore, when directly comparing transcribing and non-transcribing alleles within minimally perturbed cells, Sox2 promoter dynamics were relatively unaltered, whereas the SCR became more constrained upon transcriptional firing of its partner gene. A model that may explain these findings are that there are (at least) two distinct processes linking transcriptional control and local chromatin mobility: entry into a transcriptional hub/microenvironment, and transcription itself  on transcriptional activation. Although the SCR is itself transcribed58, this is at much lower levels than Sox2, so may not feature significantly in the measurements. While explaining our results, and coherent with results from different prior studies, this hypothesis requires experiments beyond current technological capabilities to formally test, simultaneously tagging transcriptional “hub” components, nascent RNA and the promoter and enhancer over sufficiently long time periods to cover multiple transcription cycles while maintaining high temporal resolution. However, the results of our study alone are highly evocative in suggesting that some loci may be able to nucleate their own transcription-competent microenvironments, whereas others need to “find” them, raising questions about whether and how such a “hierarchy” is formed, and the mechanisms influencing the search time to access transcriptional environments.The major question we wished to address was how chromatin mobility is affected by transcription. For the n itself . In the Sox2 and the SCR are strong TAD borders in ESCs, and cohesin-mediated loop extrusion has recently been shown to affect chromatin mobility40, much of their local constraints could perhaps be explained by mechanisms independent of transcription. Indeed, abrogation of CTCF binding caused localized increases in chromatin mobility, which was particularly noteworthy at the SCR, considering that deletion of this site had negligible changes on global chromatin conformation (as determined by population-average 4C-seq) or Sox2 expression. We also note that identifying the localized changes in chromatin dynamics is only possible by the analytical framework that we have developed, and not by conventional radial MSD. Even more striking was the finding that deletion of transcription factor binding sites had opposing effects on local dynamics to CTCF site deletion. Assuming that transcription factor clustering is one aspect of chromosome compartmentation50, this is reminiscent of the known antagonism between loop extrusion and compartments in defining chromosome conformations enhancer ~ 150 kb from the promoter, comprising clusters of binding sites for tissue-specific transcription factors oriented around one major CTCF site facing the gene, and with no other confounding genes within the locus, was a convenient model for the studies presented here. Although many of the organizational principles uncovered here likely apply to many genes, more systematic studies will be required to formally test this. For example, the limited deletion studies performed so far have already shown large differences in robustness of TAD structures to loss of specific CTCF sites68, which could also play out in their dynamics. The ANCHOR system and its derivatives, coupled to orthogonal systems to track nuclear hubs and loop extrusion processes, will open new avenues to understanding the spatiotemporal regulation of transcription.The M. musculus129 × M. castaneus female cells obtained from Barbara Panning) were cultured on 0.1% gelatin-coated plates in ES medium , which maintains ESCs in a pluripotent state in the absence of a feeder layer70. The WTSox2-SCR and Inter-Down lines were generated by allele-specific CRISPR/Cas9-mediated knock-in of ANCH1 sequence51 into the SCR or downstream control region, and ANCH3 sequence26 into the Sox2 promoter-proximal region or intervening control region, respectively. Flanking homology arms were first introduced by PCR amplification and Gibson assembly into vectors containing the ANCH1 or ANCH3 sequence, and 1 μg of each vector were co-transfected with 3 μg of plasmid containing Cas9-GFP, a puromycin resistance marker and a scaffold to encode the two gRNAs specific to the two insertion sites (generated by the IGBMC molecular biology platform) in 1 million F1 ESCs with Lipofectamine-2000. SNPs remove the NGG PAM sequence at the castaneus allele, assuring allele-specific knock-in (sequences given in Table S3). Two days after transfection, the cells were cultured for 24 h with 3 μg/mL, then 48 h with 1 μg/mL puromycin to enrich for transfected cells, before sorting individual GFP-positive cells into 96-well plates and amplification of individual clones. Heterozygous clones with the correct sequences inserted in the musculus allele were screened by PCR and sequencing.Mouse F1 ESCs .ΔCTCF_Sox2Sox2-SCR and ΔCTCF_SCRSox2-SCR cells were derived from the WTSox2-SCR line, essentially as in ref Table S3) and 1 μg Alt-R homology-directed repair single-stranded DNA oligonucleotide  with Lipofectamine-2000. The repair oligonucleotides are designed to replace the CTCF motif with an EcoRI site to help screening knock-outs. Two days after transfection, the cells were cultured for 24 h with 3 μg/mL, then 48 h with 1 μg/mL puromycin to enrich for transfected cells, before sorting individual GFP-positive cells into 96-well plates and amplification of individual clones. Deletions were evaluated on agarose gel after PCR amplification of the region around the deletion and EcoRI digestion. Homozygous deletions were confirmed by sequencing.MS2Sox2-SCR cells were derived from the WTSox2-SCR line by co-transfecting 1 million cells with 2 μg plasmid containing Cas9 and the scaffold encoding a gRNA at the Sox2 3’UTR, and 2 μg targeting vector containing the MS2 cassette, comprising 24 copies of the v6 MS2 repeat59, a hygromycin resistance cassette flanked by loxP sites, and primer binding sites to facilitate screening for inserted clones, following the strategy of ref Fig S9), with Lipofectamine-2000. Three days after transfection, cells with integrated vector were selected with nine days of treatment with 200 μg/mL hygromycin. Individual cells were sorted into 96-well plates for clonal amplification, which were screened for heterozygous (musculus-specific) incorporation of full length 24xMS2 repeats by PCR and sequencing. To remove the selection marker, which may perturb Sox2 mRNA function, 1 million cells were transfected with 4 μg Cre-GFP vector with Lipofectamine-2000, and after three days were subjected to selection with 6 μM ganciclovir for ten days. Marker excision and maintenance of full-length MS2 construct were verified by PCR and sequencing in surviving colonies. Finally, 1 million cells were co-transfected with 1 μg ePiggyBac transposase expression plasmid (System Biosciences) and 1 μg each epB-MCP-mScarletI, epB-OR1-EGFP and epB-OR3-IRFP vectors (the OR vectors are derived from those used in ref MS2Sox2-SCR line) and imaged essentially as in ref 2 throughout the experiment. The system was controlled using Metamorph 7.10 software. For double-label experiments, EGFP and IRFP were excited by 491-nm and 635-nm lasers. Green and far-red fluorescence were detected with an emission filter using a 525/50 nm and 708/75 nm detection window, respectively. Time-lapse was performed in 2D, acquiring 241 time points at 0.5 s interval. For triple-label experiments, EGFP and IRFP were first imaged as for the double-label, then mScarletI was excited at an identical z-position with a 561-nm laser, and red fluorescence was detected with an emission filter using a 609/54 nm detection window. Time-lapse was performed in 2D, acquiring 301 time points at 1 s interval. For assessment of transcriptional bursting of MS2Sox2-SCR cells, mScarletI was excited with a 561-nm laser, and red fluorescence was detected with an emission filter using a 609/54 nm detection window. Ten positions were taken per acquisition session, obtaining 20 z-stacks of 0.5 μm interval for each position every 2 min, for a total of 2 hr. All time lapse was performed with Perfect focus system (PFS) of the microscope to avoid any focus drift.Cells were transiently transfected with OR vectors  supplemented with 2 mM GlutaMAX, 10% FBS, 0.1 mM MEM nonessential amino acids, 0.1 mM 2-mercaptoethanol without LIF or 2i inhibitors. After 24 h, the medium was changed daily and supplemented with 5 μM retinoic acid.Two days after transfection with OR vectors, as previously, cell medium was changed for fresh medium, supplemented with either 500 nM triptolide or 1:2000 dilution of DMSO and incubated for 4 h prior to image acquisition.SDHA (succinate dehydrogenase complex flavoprotein subunit A). SNPs allowed primer design to distinguish musculus and castaneus Sox2 expression44. Primer sequences are given in Table S5. Statistical comparisons were made by two-tailed t-tests.Total RNA was extracted using the Nucleospin RNA extraction kit (Macherey-Nagel) and reverse-transcribed using random hexamer primers and SuperScript IV (Invitrogen). qRT-PCR was performed on 10 ng cDNA aliquots in technical triplicates per biological replicate (three minimum) using QuantitTect SYBR Green PCR kit (Qiagen). Amplification was normalized to 1 million cells were fixed in 66% ethanol on ice for 2 h, washed with PBS, then resuspended in 750 μL 50 μg/mL propidium iodide and 2 μg/mL RNase A in PBS, before incubation at 37°C for 30 min. Analysis of propidium iodide staining with a FACS Fortesa (BD Biosciences) allowed cells to be gated to G1 (2n DNA content), S (2n < DNA content < 4n) and G2/M (4n DNA content) phases. Statistical comparisons were made by two-tailed t-tests.DpnII restriction buffer at 10 million nuclei/mL concentration, and 5 million nuclei aliquots were further permeabilized by treatment for 1 h with 0.4% SDS at 37°C, then incubating for a further 1 h with 3.33% Triton X-100 at 37°C. Nuclei were digested overnight with 1500 U DpnII at 37°C, then washed twice by centrifuging and resuspending in T4 DNA ligase buffer. In situ ligation was performed in 400 μL T4 DNA ligase buffer with 20,000 U T4 DNA ligase overnight at 23°C. DNA was purified by reverse cross-linking with an overnight incubation at 65°C with proteinase K, followed by RNase A digestion, phenol/chloroform extraction, and isopropanol precipitation. The DNA was digested with 5 U/μg Csp6I at 37°C overnight, then re-purified by phenol/chloroform extraction and isopropanol precipitation. The DNA was then circularized by ligation with 200 U/μg T4 DNA ligase under dilute conditions (3 ng/μL DNA), and purified by phenol/chloroform extraction and isopropanol precipitation. For musculus-specific 4C profiles, samples of the DNA were digested with AvaII, cutting specifically at the region between the Csp6I site and the non-reading primer annealing site on the castaneus allele. 100 ng aliquots of treated DNA were then used as template for PCR with bait-specific primers containing Illumina adapter termini (primer sequences in Table S6). PCR reactions were pooled, primers removed by washing with 1.8× AMPure XP beads, then quantified on a Bioanalyzer (Agilent) before sequencing with a HiSeq 4000 (Illumina). Sequencing read fastq files were demultiplexed with sabre (https://github.com/najoshi/sabre) and aligned to the mm10 genome with Bowtie73, and intrachromosomal reads were assigned to DpnII fragments by utility tools coming with the 4See package54. 4See was also used to visualize the 4C profiles. Interactions were called for each replicate with peakC74 with window size set to 21 fragments, and were then filtered to only include the regions called as interacting across all wild-type replicates. For statistical comparison of specific interactions, the 4C read counts within 1 Mb of the bait for all replicates and conditions (from the same bait) were quantile normalized using the limma package75. The means of summed normalized 4C scores over tested interacting regions were taken as “interaction scores”, and were compared across conditions by two-tailed t-tests.4C-seq was essentially carried out as in ref Sox2, WI1–788C1 for Inter, WI1–111C20 for SCR, WI1–156F5 for Down), labeling the DNA with dUTP conjugated to biotin (SCR and Down probes) or digoxigenin (Sox2 and Inter probes). For each hybridization experiment, 300 ng each probe was combined with 3 μg mouse C0t DNA and 20 μg yeast tRNA and resuspended in 5 μL hybridization mix (10% (w/v) dextran sulphate, 50% formamide, 1% Tween-20 in 2x SSC). Probe was denatured at 95°C for 5 min just before application to cells. FISH was performed as in ref FISH probes were generated by nick translation from fosmids centered on the ANCHOR insertion sites  microscope, using a x63/1.4 objective lens (C plan-Aprochromat 63x/1.4 Oil DIC UV-VIS-IT M27), under 2x zoom and line-averaging 4 settings. The interval between z-slices was 0.37 μm and the x- and y-pixel size was 132 nm. Nuclei were segmented and inter-probe 3D distances were measured by custom scripts in ImageJSox2 probes were designed with Stellaris Probe Designer and labeled with Cy3 and Cy5, respectively, on the 3’ ends. Glass coverslips were placed into a 12-well plate and coated overnight with Poly-d-lysine. 400,000 cells were seeded per well and allowed to attach for 3 h to 70–80% confluency at 37°C, 5% CO2. Cells were washed three times with pre-warmed HBSS buffer , before aspiration of buffer and cell fixation in 4% paraformaldehyde in PBS for 10 min at 23°C, then two washes in PBS for 10 min at 23°C. Cells were permeabilized overnight in 70% ethanol at 4°C, then washed for 5 min at 37°C with pre-warmed wash buffer (10% (v/v) formamide in 2x SSC). Coverslips were aspirated and dried for 5 min, before applying hybridization mix (50 nM each probe in 10% (w/v) dextran sulphate sodium salt, 10% (v/v) formamide, 2x SSC) and incubating overnight at 37°C in a humidified chamber. Coverslips were washed three times in wash buffer for 30 min at 37°C, then rinsed in 2x SSC and washed in PBS for 5 min at 23°C. Samples were mounted in Prolong Gold with DAPI (Invitrogen) on glass slides, and left to dry in the dark for 24 h before imaging on a Zeiss AxioObserver 7 inverted wide-field fluorescence microscope with LED illumination  and sCMOS ORCA Flash 4.0 V3 717 (Hamamatsu). A 40x oil objective lens (NA 1.4) with 1.6x Optovar was used. 27 z-stacks with 300 nm slices and 1×1 binning were taken with an exposure time of 500 ms for Cy3, 750 ms for Cy5 (100% LED power for both), and 25 ms for DAPI (10% LED power). Micromanager 1.4 software was used. A custom Python script was used to detect, localize and classify the spots . Cells and nuclei were segmented using Otsu thresholding and watershedding. Spots were localized by fitting a 3D Gaussian mask after local background subtraction78 and counted per cell.MS2v6 and SOX2, Santa Cruz #sc-365823; anti-histone H3, H31HH.3EI-IGBMC) at 1:1000 dilution in 4% milk/PBST overnight at 4°C. Membranes were washed four times for 5 min each at 23°C in PBST, then incubated with 1:10,000 goat anti-mouse-alkaline phosphatase (IGBMC) in 4% milk/PBST for 1 h at 23°C, before washing four times for 5 min each at 23°C in PBST and developing with Pierce ECL Western blotting substrate (Thermo Fisher). Image acquisition was performed on ImageQuant 800 (Amersham).~ 3 million cells were collected by trypsinization, washed with PBS and lysed in 100 μL RIPA buffer  NP-40, 0.5% (w/v) sodium deoxycholate, 0.1% (w/v) SDS, 1 mM EDTA) for 30 min at 4°C. Cell lysate was sonicated with a Covaris E220 Bioruptor in AFA microtubes to shear genomic DNA , before addition of 100 U benzonase (Sigma) in 100 μL RIPA buffer and incubation for 30 min at 30°C. Lysate was cleared by centrifugation at 22,000 g for 20 min at 4°C and protein concentration was measured with a Bio-Rad protein assay. 30 μg protein extract was loaded onto a 15% Bis-Tris polyacrylamide gel for electrophoresis then transfer to a PVDF membrane using a Mini Trans Blot Cell (Bio-Rad). Membranes were blocked for 1 h at 23°C in 4% milk/PBST (0.1% Tween-20 in PBS), then incubated with primary antibody  for 15 min at 23°C. Eluate and input samples were decrosslinked by treatment overnight at 65°C, then DNA purified by RNase A digestion, proteinase K digestion, phenol/chloroform extraction and ethanol precipitation. qPCR was performed with QuantitTect SYBR Green PCR kit (Qiagen), using dilutions of the input material to generate the standard curve. Primer sequences are given in Table S7.For CTCF ChIP, 40 million ESCs were harvested with TrypLE (Invitrogen) and fixed for 10 min with 1% formaldehyde, then quenched with 125 mM glycine for 5 min at 23°C then 15 min at 4°C. Cells were washed with 10% FBS/125 mM glycine in 1x PBS, then lysed in 275 μL lysis buffer  on ice for 20 min. 320 μL lysate was transferred to a microtube 500 AFA and sonicated with a Covaris E220  for 25 min to shear chromatin to a 200–700 bp range. Cell debris was removed by centrifugation for 15 min at 20,000 g, 4°C. Equal volumes of protein A- and protein G-Dynabeads (Invitrogen) were mixed and prepared by washing in ChIP dilution buffer , then finally resuspending in an equivalent volume of ChIP dilution buffer. 100 μg chromatin aliquots were diluted eight-fold in ChIP dilution buffer and pre-cleared for 90 min with 30 μL prepared protein A/protein G-Dynabeads at 4°C on a rotating wheel. The pre-cleared chromatin was then incubated overnight at 4°C with 10 μL of either rabbit IgG  or rabbit anti-CTCF . Immunoprecipitated chromatin was then adsorbed to 100 μL prepared protein A/protein G-Dynabeads for 3.5 h at 4°C on a rotating wheel. The beads were then washed twice for 5 min at 4°C with low salt wash buffer , twice for 5 min at 4°C with high salt wash buffer , twice for 5 min at 4°C with LiCl wash buffer , then twice for 5 min at 4°C with TE buffer . The immunoprecipitated chromatin was eluted by two incubations with 250 μL elution buffer . Lysates were again centrifuged for 5 min at 2000 g, 4°C, before resuspending in ice-cold lysis buffer 3 . Chromatin was sonicated in a probe sonicator at 20 A (15 s on/30 s off) for 2.5 min at 4°C. Triton X-100 was added to the sonicated lysate to precipitate any remaining debris, and the cleared lysate was incubated overnight with 5 μg anti-Rad21 antibody (Abcam ab217678) at 4°C with rotation. 80 μL protein A/G Dynabeads (Invitrogen) was added to the antibody-bound chromatin and incubated overnight at 4°C with rotation. The immunoprecipitates were washed six times at 23°C with RIPA buffer followed by a TBS buffer wash, then bound chromatin was eluted by incubation for 30 min at 65°C with elution buffer , before addition of 4 μL 20 mg/mL proteinase K and reversal of crosslinks by incubating at 65°C overnight. DNA was purified with phenol/chloroform extraction and ethanol precipitation before qPCR quantification (primer sequences given in Table S7), using serial dilutions of pre-immunoprecipitated input material to generate the quantification standard curve. Quantification at the musculus and castaneus SRR109 (SCR CTCF site) was expressed as fold-enrichment over the amplification at a non-genic, negative control sequence, not bound by Rad21, CTCF or known pluripotency transcription factors.For Rad21 ChIP, 40 million ESCs were fixed for 45 min with 2 mM succinimidyl glurarate, then for 10 min with 1% formaldehyde at 23°C, before quenching with 125 mM glycine for 15 min at 23°C. Cell pellets were washed twice with ice-cold PBS, then resuspension and incubation in lysis buffer 1  for 10 min at 4°C. Lysates were centrifuged for 5 min at 2000 79, before localization precision enhancement in GPTool25. This assumes that the spots have the shape of a 2D Gaussian function, as follows,Sar2-SCRMS2, line, ICY was additionally used for spot detection and tracking of MCP (mScarletI). The majority of experiments had MCP detection for virtually all of none of the frames, and were categorized as “transcribing” and “non-transcribing” cells, respectively. The other experiments were only included in the analysis if they contained at least 75 contiguous frames with MCP signal (“transcribing”) and/or absence (“non-transcribing”). For these, the largest contiguous stretch of frames above this threshold was maintained for subsequent analysis.Live imaging experiments were treated essentially as in ref For inter-spot distance measurements, effects of camera misalignments and chromatic aberrations were corrected with a set of generic affine transformations, including translation, rotation and scaling, defined as,github.com/Lenstralab/livecell)80, maximal intensity projections were made of the 3D movies, followed by background subtraction and cell segmentation using Otsu thresholding and watershedding. Transcription bursts were detected and tracked using a 2D Gaussian fit followed by hysteresis filtering using 5 and 8 standard deviations of the background as low/high thresholds, respectively. Output data were manually checked to reject entonecus tracking or dividing cells.Using the LiveCell pipeline  and that the velocity autocorrelation function from experimental trajectories,Fig S4):Diffusive parameters for individual trajectories were estimated using GPToolTo measure and correct for substrate movement, GPTool builds a covariance model to handle the cross-correlation that substrate motion introduces into the two measured particles’ trajectories, generating the probability distribution:To generate the individual trajectory plots e.g. , the inf81. For each individual trajectory, the time-averaged MSD was computed . using either the trajectories uncorected or corrected by GPTool for substrate movement, as stated. Because some trajectories exhibited large deviations from the average, especially at long time, we chose to calculate the ensemble median of all individual MSD and the median absolute deviation as a measure of the variability. For testing the fit of GPTool-measured parameters to experimental data, theoretical 2D MSD curves were made from these measured parameters for each individual trajectory, giving eitherSox2-SCR and infer-Down radial MSD were assessed by ANCONA.MSD analysis was performed using the msdanalyzer utility in MatlabThe distributions of inferred apparent anomalous diffusion coefficients from different genomic loci or experimental conditions were compared by Wilcoxon rank sum test, with Benjamini-Hochberg multiple testing correction in cases where four or more statistical tests were combined. Since 82, as in ref 84. Langevin equations for all beads are simultaneously solved in EspressoMD using a standard Velocity-Verlet numerical algorithm. The potential connecting Molecular dynamics simulations were performed via the multipurpose EspressoMD package85), which encodes the association tendency of Polll with the Sox2 promoter (defined as the 1 kb bead containing the transcription start site within the modeled region) by means of the shifted, truncated Lennard-Jones (LJ) potential, allowing spontaneous co-localization of beads around a distance 84.From now on, any description of the formation of a bond means the introduction of the aforementioned harmonic bond between the particles involved. To regulate the lifetime of these harmonic interactions, mechanisms of bond formation and removal were introduced according to cutoff distance For PolII interactions and transcription, the polymerase is presented as a bead with LJ interaction with specific beads of the chromatin fiber representing the promoter, enhancers (defined as beads containing HBK27ac peaks) or gene body (beads containing sox 2 coding sequence) with energy −547. This allows cohesin to be affected by the surroundings during extrusion (e.g. presence of PolII close by or bound to adjacent sites). Cohesin detachment can occur independently at any step at a given rate 86). Polll and loop extrusion dynamics are performed using a python script driving the EspressoMD library. The polymer initializes as a random walk and its dynamics first evolves in the absence of extrusion and transcription to generate an equilibrium coil formation. Extrusion and transcription processes are then switched on, and the evolution of the bead positions are tracked. Across all simulations, standard values for the friction coefficient in silico space-time units with real distances and times, it is assumed that the concentration of DNA in the 3D simulation space is the same as that in a mammalian nucleus, giving a rough estimation of For CTCF binding, a single bead interacts vil Sox2 gene, 16 enhancer beads from the peaks of H3K27ac, and 6 CTCF binding regions with directionality determined by orientation of binding motifs. CTCF binding regions can be composed of up to 3 beads where CTCF occupancy signal is the highest (i.e. two regions upstream of Sox2), so giving a stronger anchoring function to such regions. Polymer models for ΔCTCF_Sox2Sox2-SCR and ΔCTCF_SCRSox2-SCR have the relevant CTCF sites converted into non-CTCF binding beads, so to remove the cohesin anchoring effect. The model for ΔSRR107,111Sox2-SCR has the two enhancer beads immediately flanking the SCR CTCF region completely removed from the polymer, and reduced PolII stability to the promoter (from 0.02 bonds lost per second to 0.2 bonds lost per second), to mimic inactivation of the gene.The region modeled  encompasses the The positions of the beads corresponding to the positions of ANCHOR labels were tracked across 40 simulations of 1000 timepoints, and these trajectories were subsequently fed into MSD fits and GPTool diffusive parameter estimations, as for the experimental trajectories.87. The differential Hi-C map was derived as in ref 89. For comparison of 2D Sox2-SCR distance distributions with analogous methods, results from oligoFISH were taken from ref ESC and NPC Hi-C data were taken from ref