1. Chromosomes and Gene Expression
Download icon

Live-cell imaging reveals enhancer-dependent Sox2 transcription in the absence of enhancer proximity

  1. Jeffrey M Alexander
  2. Juan Guan
  3. Bingkun Li
  4. Lenka Maliskova
  5. Michael Song
  6. Yin Shen
  7. Bo Huang
  8. Stavros Lomvardas
  9. Orion D Weiner  Is a corresponding author
  1. University of California, San Francisco, United States
  2. Chan Zuckerberg Biohub, United States
  3. Columbia University, United States
Research Article
  • Cited 0
  • Views 2,353
  • Annotations
Cite this article as: eLife 2019;8:e41769 doi: 10.7554/eLife.41769

Abstract

Enhancers are important regulatory elements that can control gene activity across vast genetic distances. However, the underlying nature of this regulation remains obscured because it has been difficult to observe in living cells. Here, we visualize the spatial organization and transcriptional output of the key pluripotency regulator Sox2 and its essential enhancer Sox2 Control Region (SCR) in living embryonic stem cells (ESCs). We find that Sox2 and SCR show no evidence of enhanced spatial proximity and that spatial dynamics of this pair is limited over tens of minutes. Sox2 transcription occurs in short, intermittent bursts in ESCs and, intriguingly, we find this activity demonstrates no association with enhancer proximity, suggesting that direct enhancer-promoter contacts do not drive contemporaneous Sox2 transcription. Our study establishes a framework for interrogation of enhancer function in living cells and supports an unexpected mechanism for enhancer control of Sox2 expression that uncouples transcription from enhancer proximity.

https://doi.org/10.7554/eLife.41769.001

Introduction

Chromosomes are packaged and organized non-randomly within the mammalian nucleus. Emerging evidence suggests that 3D genome topology plays a fundamental role in genome control, including the regulation of gene expression programs (Bickmore, 2013; Krijger and de Laat, 2016; Schwarzer and Spitz, 2014). Within the nucleus, each chromosome occupies discrete chromosomal territories (Cremer et al., 2006). These territories are further structured into distinct compartments that separate active and repressive chromatin (Lieberman-Aiden et al., 2009; Sexton et al., 2012). At finer scales, chromosomes are partitioned into largely-invariant, sub-megabase sized topologically-associated domains (TADs), which break up the linear genome into interactive neighborhoods (Dixon et al., 2012; Nora et al., 2012). Chromosomal contacts are disfavored across TAD boundaries. Thus, most cell-type specific contacts occur within TAD boundaries, and disruption of TAD architecture leads to dysregulation of gene expression (Dowen et al., 2014; Gröschel et al., 2014; Guo et al., 2015; Lupiáñez et al., 2015; Narendra et al., 2015; Nora et al., 2017).

Within this 3D framework, gene expression programs are established by non-coding regulatory enhancer elements. First discovered within a metazoan genome over three decades ago (Banerji et al., 1983), it is now predicted that greater than 300,000 enhancers are encoded in the human genome (ENCODE Project Consortium, 2012; Zhu et al., 2013). Enhancers demonstrate unique epigenetic markings, enriched for H3K4me1 and H3K27ac (Creyghton et al., 2010; Heintzman et al., 2007; Rada-Iglesias et al., 2011), and are highly accessible, as demonstrated by elevated DNase sensitivity and transposition susceptibility (Boyle et al., 2008; Buenrostro et al., 2013; Thurman et al., 2012). These features facilitate transcription factor occupancy, enrichment of co-activators such as p300 and Mediator, and transcription of non-coding enhancer RNAs (eRNAs), all of which play important roles in modulation of target gene expression (Kim et al., 2015; Long et al., 2016). Importantly, enhancer activity is highly specific across cell types (Heintzman et al., 2009; ENCODE Project Consortium, 2012; Zhu et al., 2013) and modulated during cellular differentiation (Blum et al., 2012; Buecker et al., 2014; Huang et al., 2016; Wamstad et al., 2012), and this activity correlates with nearby gene expression. Thus, enhancers are fundamental to achieving gene expression programs that orchestrate embryonic development and drive disease pathogenesis. Understanding the mechanism by which enhancers influence target genes is crucial to decode gene regulation.

The textbook model proposes that enhancers influence target gene promoters through protein-protein complexes and physical interaction mediated by a DNA loop (Alberts et al., 2014). Experimental support for this model comes primarily from numerous chromosome conformation capture (3C)-based studies that have identified enriched contacts between enhancer and promoter elements (Jin et al., 2013; Li et al., 2012; Rao et al., 2014; Sanyal et al., 2012; Weintraub et al., 2017) and recent observations that driving contacts between an enhancer-promoter pair is sufficient to augment gene expression (Bartman et al., 2016; Deng et al., 2012; Deng et al., 2014; Morgan et al., 2017). However, other observations fit this model poorly. For example, sonic hedgehog (Shh) enhancers that drive expression in the brain move further, rather than closer, to the Shh gene when activated (Benabdallah et al., 2017). Furthermore, in Drosophila, coupled reporter genes regulated by a shared enhancer nevertheless show coordinated transcriptional bursting, suggesting either that an enhancer can contact multiple genes at once or that contact can be decoupled from transcription (Fukaya et al., 2016; Lim et al., 2018). Super enhancers -- clusters of enhancers that are highly enriched for coactivators like Mediator and BRD4 (Lovén et al., 2013; Whyte et al., 2013) -- have been proposed to activate transcription through nucleation of activator droplets rather than stepwise assembly of transcription complexes (Hnisz et al., 2017), providing a possible mechanism for enhancer action at a distance, and recent imaging has provided support for this idea (Cho et al., 2018; Sabari et al., 2018). Thus, how distal elements communicate with and regulate gene promoters in living cells remains an open question.

Live-cell imaging represents a powerful approach to dissect chromatin architecture and gene regulation in the context of single cells to address these questions (Chen et al., 2013; Chen et al., 2018; Germier et al., 2017; Gu et al., 2018; Lucas et al., 2014). However, interrogation of both enhancer-gene spatial organization and real-time transcriptional activity of the regulated gene has not yet been realized in living mammalian cells. Here, we investigate the dynamic 3D organization and transcriptional activity of the Sox2 gene and its distal enhancer Sox2 Control Region (SCR) in mouse embryonic stem cells (ESCs) using live-cell microscopy.

We find that the Sox2 promoter and SCR demonstrate similar spatial characteristics to non-regulatory regions in ESCs, while differentiation of ESCs leads to significant compaction throughout the Sox2 region. Time-lapse microscopy revealed that individual loci explore only a fraction of their potential spatial range during the ~25 min imaging window, driving high cell-to-cell variability in Sox2 locus conformation and Sox2/SCR encounters. Incorporation of an MS2 transcriptional reporter into the Sox2 gene demonstrated that transcription occurs in intermittent bursts in ESCs but, surprisingly, showed no correlation with spatial proximity between the enhancer-promoter pair. Together, our findings establish the spatial and transcriptional characteristics of an essential pluripotency gene and suggest an unconventional mechanism for enhancer control of Sox2 expression that uncouples transcription from enhancer proximity.

Results

Engineering the endogenous Sox2 locus to visualize locus organization in living Embryonic Stem Cells

To visualize discrete loci within the mammalian genome, we turned to the well-established genetic labeling method of incorporating repetitive arrays of exogenous operator sequences, an approach that has been extensively used to visualize chromosomal loci (Belmont and Straight, 1998; Lucas et al., 2014; Marshall et al., 1997; Masui et al., 2011; Michaelis et al., 1997; Robinett et al., 1996; Roukos et al., 2013). To independently visualize two regions of interest, we utilized the tetO/TetR system to visualize one chromosomal location. For the other chromosomal location, because of the reported issues using lacO/lacI in ESCs (Lucas et al., 2014; Masui et al., 2011), we developed a new tool based on the cuO/CymR pair. This is a repressor system from the bacteria Pseudomonas putida that is involved in cumate metabolism and has been previously used as a tool for inducible gene expression (Mullick et al., 2006). We opted to target these arrays to the mouse genome using a two-step genetic engineering strategy with bacteriophage integrases for two reasons (Figure 1A, see Supplementary file 1 for protocol). First, repetitive sequences can be unstable during vector construction, making it advantageous to use generic targeting vectors portable between genomic loci. Second, we worried the repetitive arrays might recombine during genomic targeting using homologous recombination. To target the tetO/TetR and cuO/CymR labels to specific loci within the mouse genome, we first placed attP landing sites for the PhiC31 (Raymond and Soriano, 2007; Thyagarajan et al., 2001) and Bxb1 (Xu et al., 2013) integrase systems using CRISPR/Cas9 homology directed repair. We then integrated generic PhiC31 or Bxb1 targeting vectors bearing either the tetO array (224 repeats) or cuO array (144 repeats), respectively, at the corresponding landing sites through transient expression of the PhiC31 and Bxb1 integrases. This strategy was both modular in design and portable between genomic loci. To target two regions on the same chromosome, we used 129/Cast F1 hybrid ESCs, derived from crossing the 129 mouse strain to the divergent subspecies Mus musculus castaneus. This allowed us to limit editing to the 129 allele by using genetic polymorphisms between the two parental genomes to design allele-specific CRISPR guide RNAs.

Figure 1 with 3 supplements see all
The Sox2 Locus As a Model for Visualization of Enhancer-Promoter Regulation in Mouse Embryonic Stem Cells.

(A) To visualize chromosome loci in living cells, we have used tetO/TetR and cuO/CymR genetic labels. Our pipeline for insertion of these labels into the mouse genome is shown. First, CRISPR-Cas9 is used to place an attP integrase landing site. Second, a targeting plasmid bearing the compatible attB sequence, the tetO or cuO array, and a selection cassette is introduced along the integrase (Int) to mediate site-specific integration. The selection cassette can then be subsequently removed by Cre/Flp recombinase. (B) The Sox2 locus in mouse ESCs. Genomic browser tracks of epigenomic and expression data demonstrate high levels of histone acetylation, RNA polymerase II, and transcription factor (OCT4, SOX2, NANOG, CTCF) and cohesin (RAD21) occupancy at Sox2 and the distal Sox2 Control Region enhancer (tan boxes). Data from 4C and HiC experiments demonstrate chromosomal contacts at the Sox2 locus. For 4C data, read density indicates contact frequency with a fixed position near the Sox2 promoter (red triangle). Y-axis for browser tracks is reads per million. For HiC, all pairwise contact frequencies are shown using a heatmap. The intensity of each pixel represents the normalized number of contacts detected between a pair of loci. The maximum intensity is indicated in red square. At bottom, locations of the cuO- and tetO-arrays for the three cell lines utilized for this study. Sox2-8CcuO/+; Sox2-117TtetO/+ (Sox2-SCR) ESCs were used to track Sox2/SCR location. Two control lines, Sox2-43TtetO/+; Sox2-164TcuO/+ (Control-Control) and Sox2-117TtetO/+; Sox2-242TcuO/+ (SCR-Control) were analyzed for comparison. H3K27ac, RNA polymerase II (RNAP), and RNAseq data from GSE47949 (Wamstad et al., 2012); DNase data from GSE51336 (Vierstra et al., 2014); SOX2, OCT4, NANOG, CTCF data from GSE11431 (Chen et al., 2008b), and RAD21 data from GSE90994 (Hansen et al., 2017); 4C data from GSE72539 (de Wit et al., 2015); and HiChIP data from GSE96107 (Bonev et al., 2017).

https://doi.org/10.7554/eLife.41769.002

We chose the murine Sox2 locus as our genetic model. Sox2 encodes a high-mobility group (HMG) DNA-binding transcription factor with important roles in embryonic development (Kamachi and Kondoh, 2013; Lefebvre et al., 2007; Sarkar and Hochedlinger, 2013), embryonic and adult neural progenitors (Pevny and Nicolis, 2010), and the progression of many forms of cancer (Weina and Utikal, 2014; Wuebben and Rizzino, 2017). Sox2 also functions as an essential regulator of pluripotency, where it cooperates with other transcriptional regulators to maintain the pluripotency transcriptional program and keep embryonic stem cells in the undifferentiated state (Chen et al., 2008a; Young, 2011). Sox2 resides in an isolated neighborhood on chromosome 3, as the sole protein-coding gene in a ~ 1.6 Mb region. Numerous regulatory elements that modulate Sox2 expression have been identified in this neighborhood across amniotes (Okamoto et al., 2015; Tomioka et al., 2002; Uchikawa et al., 2003; Zappone et al., 2000). However, Sox2 expression in mouse ESCs is controlled by a single, strong distal enhancer called the Sox2 Control Region (Li et al., 2014; Zhou et al., 2014), which is robustly enriched with H3K27ac, DNase hypersensitivity, RNA Polymerase II (RNAP), CTCF, the cohesion subunit RAD21, and transcription factor occupancy (herein referred to as SCR, Figure 1B). Genetic ablation of SCR in ESCs leads to loss of Sox2 expression in cis. Moreover, SCR maintains Sox2 expression levels in the context of compound deletion of alternative Sox2 enhancers, suggesting SCR is sufficient for Sox2 regulation in ESCs (Zhou et al., 2014). Publicly available circularized chromosome conformation capture (4C) and HiC datasets reveal enriched contacts between SCR and the Sox2 promoter region, suggesting that these enhancer-promoter interactions may play an important role in SCR function (Figure 1B).

We generated three distinct modified cell lines in 129/Cast F1 hybrid ESCs (Figure 1B, bottom) First, we labeled the Sox2 promoter region and SCR by integrating the cuO array 8 kb centromeric to the Sox2 TSS (Sox2-8C) and the tetO array approximately 5 kb telomeric to the SCR boundary (i.e. 117 kb telomeric to Sox2 TSS, Sox2-117T). We refer to this pair as Sox2-SCR. Secondly, we created two control ESC lines: one with two arbitrary loci labeled with cuO and tetO (Sox2-43TtetO/+; Sox2-164TcuO/+ or Control-Control) and a second where we labeled SCR along with a non-specific telomeric locus (Sox2-117TtetO/+; Sox2-242TcuO/+ or SCR-Control). In both cases, the genetic distance between labels was similar to that of Sox2-SCR. Both control pairs show low contact propensity in chromosome conformation capture data (Figure 1B). We verified the correct placement of the cuO and tetO labels for each locus using PCR with primers that span the unique recombination arms generated after plasmid integration (Figure 1—figure supplement 1, Supplementary file 2,3). We detected a similar Sox2 expression ratio (129/Cast) using an allele-specific qPCR assay for modified cell lines compared to the parental ESCs, suggesting Sox2 regulation is intact despite genetic alteration of the locus (Analysis of Variance, p=0.215, Figure 1—figure supplement 2). Furthermore, we found insertion of the cuO and tetO arrays within the Sox2 locus did not disrupt Sox2-SCR contacts on the modified allele (Figure 1—figure supplement 3).

Visualization of the Sox2 region in ESCs reveals minimal evidence for Sox2/SCR Interactions

We were first interested in measuring the 3D distance between Sox2 and the SCR enhancer in living ESCs. To this end, we stably coexpressed CymR-GFP and TetR-tdTomato (TetR-tdTom) fusion proteins in Sox2-SCR ESCs using ePiggyBac transposon-based gene delivery (Lacoste et al., 2009). This allowed for visualization of both the cuO and tetO arrays within the nucleus using live-cell fluorescence confocal microscopy. We confirmed that coexpression of CymR-GFP and TetR-tdTom did not significantly alter Sox2 expression from the modified 129 allele by qPCR (Figure 1—figure supplement 2) and did not alter Sox2-SCR contacts by 4C (Figure 1—figure supplement 3). 3D time series of proliferating ESCs showed the majority of cells demonstrated a single, bright focus of CymR-GFP and TetR-tdTom in the ESC nucleus in close proximity. Many of these foci revealed the presence of two juxtaposed sister chromatids (Video 1). Because the overlapping signal from adjacent, identical arrays would degrade the resolution of our localization, we excluded these loci from our analysis and focused on cells demonstrating single, diffraction-limited spots for cuO and tetO, likely representing cells in the G1/early S phase of the cell cycle.

Video 1
Visualization of Sister Chromatids at Sox2 Locus.

Maximum-intensity Z projection of 3D confocal Z-stacks of cuO/CymR-GFP (left) and tetO/TetR-tdTom (middle) labeling the Sox2 promoter region and SCR, respectively demonstrate two clear spots for the SCR label, suggesting cells in S/G2. These cells were excluded from analysis. Scale bar is 1 µm.

https://doi.org/10.7554/eLife.41769.006

To investigate the distribution of Sox2/SCR distances, we determined the 3D position of cuO and tetO for each locus, assembled 3D tracks, and calculated 3D separation distances between the labels across time (Figure 2A, Supplementary file 4). 84% and 62% of our assembled tracks span the full time series (>75 frames) for cuO and tetO, respectively (Figure 2—figure supplement 1). By localization of fluorescent beads at a comparable signal-to-noise ratio, we estimate our localization precision in the X, Y, and Z dimensions to be 12 nm, 10 nm, and 36 nm, respectively, for cuO/CymR and 16 nm, 16 nm, 50 nm for tetO/TetR (Figure 2—figure supplement 2). Using fixed cells as an alternative method to estimate cuO/tetO localization precision supported precision of at least this great. These precision estimates translate to an uncertainty in measured 3D distance between cuO/CymR and tetO/TetR of between 40–50 nm (Figure 2—figure supplement 3). This localization uncertainty degrades the accuracy of very small distance measurements; distances below 55 nm are dominated by the noise component (i.e. >50% error, Figure 2—figure supplement 3). Thus, our experiments are likely to inaccurately describe the 3D separate distance of structures below this value.

Figure 2 with 3 supplements see all
Visualization of the Sox2 Region in ESCs Reveals Minimal Evidence for Sox2/SCR Interactions.

(A) Top, confocal Z slices of CymR-GFP and TetR-tdTom in Sox2-SCR ESCs, labeling the Sox2 promoter and SCR region with bright puncta, respectively. Middle, 3D surface rendering of the ESC nucleus shown above. A single fluorescence channel was rendered white and transparent to outline the nucleus, and GFP and tdTom surfaces were rendered with high threshold to highlight the cuO and tetO arrays, respectively. Bottom, tracking data is rendered for the nucleus shown above. Inset shows example of calculated 3D separation distance between the two labels. Scale bar is 1 µm. (B) Normalized histogram of 3D separation distance for Sox2-SCR ESCs demonstrates a single peak (Hartigan’s Dip Test for multimodality, p=1). Schematic for an hypothetical looping enhancer-promoter pair is shown as an inset, with two peaks. Tan box indicates regime where distance measurement error is expected to be greater than 50%. (C) Cumulative density of 3D separation distance for Sox2-SCR versus control comparisons. Mean distance for each sample shown on bottom right. (D) Mean 3D separation distance per cell for each label pair. Population means and standard deviations are shown for each sample. Mann-Whitney, *p<0.05, **p<0.01, ***p<0.001.

https://doi.org/10.7554/eLife.41769.007

Importantly, the cuO and tetO labels are located kilobases away from the Sox2 promoter and SCR. Hence, these labels imperfectly report on the true locations of the Sox2 promoter and SCR and may be influenced by other confounding factors, such as the degree of local chromatin compaction. Other potential sources of error include position blurring caused by locus movement during the 30 ms exposure and possible non-diffraction limited behavior of the cuO/tetO arrays. Due to these factors, we expect greater uncertainty regarding how measured distances between cuO/tetO translate to the underlying positions of Sox2/SCR than is predicted solely by our localization precision3C data demonstrate enriched contacts between Sox2 and SCR (Beagan et al., 2017; Bonev et al., 2017; de Wit et al., 2015; Kieffer-Kwon et al., 2013; Mumbach et al., 2016; Phillips-Cremins et al., 2013; Zhou et al., 2014), supporting the possibility of a looped locus configuration with Sox2 and SCR juxtaposed in 3D space. A mixture of looped and unlooped configurations across the population might be expected to produce a multimodal distance distribution with short and large distance peaks representing looped and unlooped states, respectively, as was recently observed for an enhancer system in Drosophila (Chen et al., 2018). We visualized the measured distances between cuO and tetO in the Sox2-SCR configuration as a histogram. This analysis revealed a unimodal distribution with positive skew (Hartigan’s Dip Test for multimodality, p=1). On average, Sox2/SCR labels are separated by a few hundred nanometers in the ESC nucleus (mean = 339 nm, Figure 2B). Infrequently, we observed the Sox2 region adopt an extended conformation, leading to considerable Sox2/SCR separation distance (2.1% of measurements > 750 nm, 0.35% of measurements > 1 µm).

One possible interpretation of a unimodal distance distribution is that the Sox2/SCR pair exists predominantly in an interacting state. To investigate this possibility, we repeated this analysis with our two control locus pairs. We found that, while one control pair (Control-Control) did show increased separation distance as compared to Sox2/SCR, our other control set (SCR-Control), consisting of the SCR paired with a non-specific partner, showed a similar distribution to Sox2/SCR (Figure 2C). Indeed, no significant differences between Sox2-SCR and SCR –Control were found when comparing the mean distance per cell, while Control-Control demonstrated significantly increased distances (Figure 2D). Reinspection of chromosomal contact maps revealed evidence for a topological boundary, potentially established by the SCR element, separating the two labeled regions in the Control-Control configuration (Figure 1A), which could account for the elevated 3D distances measured for Control-Control, as has been observed for genomic loci separated by TAD boundaries (Dixon et al., 2012; Nora et al., 2012). These results suggest that SCR does not show greater proximity to the Sox2 gene than to a non-specific control.

To further exclude the possibility that our measurements reflected a constitutive interaction state, we sought to estimate the distance profile for a static Sox2/SCR interaction. To this end, we used CRISPR/Cas9 to delete a ~ 111 kb fragment between the cuO and tetO labels in the Sox2-SCR configuration, leaving a 14 kb tether between the labels (Figure 1—figure supplement 1). This is similar in length to the effective tether (~17 kb) between labels expected during a direct interaction between the Sox2 TSS and the center of the SCR. Visualization of this label configuration in living ESCs demonstrated a significant shift to more proximal distance values (Figure 2C,D). These results are consistent with our expectation that a direct Sox2/SCR interaction would be confined shorter 3D distances than those observed for the Sox2-SCR pair and validate our experimental capacity to measure these differences. Taken together, these data demonstrate no unique spatial characteristics for the Sox2-SCR pair in ESCs. While these observations could suggest very infrequent interaction events, they also may allude to fundamental differences between spatial proximity and the features captured by proximity ligation using 3C approaches (see DISCUSSION).

Differentiation of ESCs to diverse lineages correlates with Sox2 locus compaction

We next differentiated our modified cell lines in order to determine how Sox2 locus organization is altered upon cellular differentiation (Figure 3A). To this end, we derived neural precursor cells (NPCs), a cell-type that maintains Sox2 expression despite inactivation of the SCR and reduced Sox2/SCR contacts by chromosome conformation capture carbon copy (5C) (Figure 3B) (Beagan et al., 2017). We validated that our NPC lines expressed NPC marker genes and demonstrated their ability to differentiate into both neurons and astrocytes (Figure 3—figure supplement 1). As an additional comparison, we differentiated our ESC lines into FLK1+/PDGFRα+ mesodermal precursors (MES), a cell type which downregulates Sox2 expression and inactivates the SCR element (Figure 3B). Interestingly, we observed that all label pairs embedded in the Sox2 locus showed greater proximity in differentiated cells compared to ESCs (Figure 3C). These changes were significant when comparing mean distances per cell between label pairs in NPCs or MES with ESCs (Figure 3D). These data suggest the entire Sox2 locus adopts a more compact conformation upon ESC differentiation, regardless of transcriptional status of Sox2.

Figure 3 with 2 supplements see all
Sox2 Locus Compacts upon ESC Differentiation.

(A) ESCs were differentiated into neural progenitor cells (NPCs), which maintain expression of Sox2 but inactivate the SCR, and cardiogenic mesodermal precursors (MES), which inactivate both Sox2 and the SCR. (B) Browser tracks of H3K27ac and RNA-seq data from ESCs, NPCs, and MES demonstrate the activation status of Sox2 and SCR in each cell type. Y-axis is 0–5 reads per million for H3K27ac data and 0–10 reads per million for RNA-seq data. (C) Cumulative density of 3D separation distance for Sox2-SCR and two control pairs for NPCs (left) and MES (right). ESC data are shown for comparison as solid lines on each graph and reproduced from Figure 2C. Tan box indicates regime where distance measurement error is expected to be greater than 50%. (D) Mean 3D separation distance per cell for each label pair, organized by cell type. Statistical analysis is for each matched pair-wise comparison between cell types. All p-values are below reported value. Mann-Whitney (**p<0.01, ***p<0.001). H3K27ac data from GSE47949 (Wamstad et al., 2012) and GSE24164 (Creyghton et al., 2010). RNAseq data from GSE47949 and GSE44067 (Zhang et al., 2013).

https://doi.org/10.7554/eLife.41769.011

To explore if compaction of the Sox2 locus conformation might be driven by inactivation of the SCR element (which occurs in both NPCs and MES) or could be driven by other factors related to cellular differentiation, we generated a heterozygous genetic deletion of the SCR element on the 129 allele in ESCs using CRISPR/Cas9 (Figure 1—figure supplement 1, Figure 3—figure supplement 2). These cells show no signs of differentiation and maintained naive ESC morphology, consistent with previous studies (Zhou et al., 2014). Moreover, SCR deletion led to reduction of Sox2 expression from the cis allele to undetectable levels by qPCR (Figure 1—figure supplement 2). Live-cell visualization of the cuO and tetO labels in these cells demonstrated a slight shift in 3D distances towards greater proximity; however, this shift was small compared to that seen after differentiation to NPCs or MES (Figure 3—figure supplement 2). Hierarchical clustering analysis of the similarity between distance histograms revealed that SCR-deleted ESCs were most similar to other ESC lines (Figure 3—figure supplement 2). These observations suggest that Sox2 locus organization is significantly altered with ESC differentiation but largely robust to changes in Sox2 or SCR activity.

Slow Sox2 locus conformation dynamics lead to limited exploration and variable enhancer encounters

We next investigated the dynamics of Sox2 spatial organization and focused our analysis of the ESC state. While all three label pairs showed comparable distance profiles across the cell population, we observed striking variation in locus organization between individual cells (Figure 4A,B, Video 2). We observed label pairs in prolonged compact or extended conformations as well as gradual or sharp transitions between the two (Figure 4A). However, few label pairs explored their entire range – the distance spread observed across our cell population -- during our imaging window (~25 min), demonstrating that Sox2 locus conformation dynamics are slow over tens of minutes.

Figure 4 with 1 supplement see all
Slow Sox2 Locus Conformation Dynamics Lead to Limited Exploration and Variable Encounters.

(A) Maximum-intensity projection images (top) centered on the Sox2 locus and associated 3D distance measurements (bottom) highlight distinct conformations and dynamics of the Sox2 locus across cells. Scale bar is 1 µm. (B) 3D separation distance measurements for individual cells for Sox2-SCR, Control-Control, and SCR-Control highlight the heterogeneity of Sox2 locus organization across the cell population. The three cells depicted in A are boxed. (C) Cartoon description of autocorrelation analysis. Distance measurement between two time points are correlated using population statistics, revealing the time scale over which local measurements diverge from the population mean. A cell with low autocorrelation will randomly fluctuate around the population mean, leading the autocorrelation function to quickly decay to zero. A cell with high autocorrelation will deviate substantially from the expected value, only slowly relaxing back to the population mean. In this case, the autocorrelation function will stay significantly above zero for large lag times. (D) Autocorrelation function for Sox2-SCR, Control-Control, and SCR-Control pairs demonstrates significant autocorrelation at large lag times, indicating significant memory in 3D conformation across a 20 min window. The plotted values are mean ± 95% CI. E) Percent of cells with an encounter between tetO and cuO labels shown as a function of the initial separation distance measured for the cell. Likelihood of an encounter depends on the initial conformation of the locus across all label pairs and encounter thresholds.

https://doi.org/10.7554/eLife.41769.014
Video 2
Variability in Sox2 Locus Organization Across Cells.

Maximum-intensity Z projection of 3D confocal Z-stacks of cuO/CymR (green) and tetO/TetR (magenta) labeling the Sox2 promoter region and SCR, respectively for three individual cells highlighted in Figure 3. The distance range explored by Cell1 and Cell2 is limited, while Cell3 shows large, abrupt changes in distance. Scale bar is 1 µm.

https://doi.org/10.7554/eLife.41769.016

To better understand this phenomenon, we investigated the dynamic properties of our Sox2-SCR label pair, as well as both control pairs. Both relative step sizes (defined as the 3D displacement of the cuO label between frames if the tetO location is fixed) and the change in 3D separation distance between frames were significant (e.g.180 nm and 79 nm, respectively, for the Sox2-SCR pair, 20 s per frame, Figure 4—figure supplement 1). We also computed the autocorrelation function. The autocorrelation function describes the correlation between measurements separated by various lag times and can be utilized to quantify memory or inertia in single cell quantities (e.g. protein levels) compared to the population average (Sigal et al., 2006) (Figure 4C). Autocorrelation values near one are expected between closely spaced measurements, decaying towards zero for larger lag times. An autocorrelation coefficient of zero indicates that the underlying process has randomized during the time lag between the relevant measurements. Computation of the autocorrelation function for each label pair revealed a monotonic decay with increasing lag times (Figure 4D). We observe an initial rapid reduction in autocorrelation in the small time lag regime, driven by a period of effective local exploration. As our probes begin to oversample the local environment (1–2 mins), the autocorrelation decay slows, reflecting the constraint on locus diffusion within the nuclear environment. Interestingly, at long time lags (>10 mins), the autocorrelation function for both control pairs appears to flatten to a slope of zero, suggesting that conformational memory for some loci may be quite long-lived. These data suggest oversampling of the local environment by individual loci within the Sox2 region and are consistent with current physical models of chromatin (Dekker and Mirny, 2016) and the viscoelastic nature of the nucleoplasm (Lucas et al., 2014).

An important implication of this behavior of chromatin is that encounters between loci are highly dependent on the initial configuration of the genomic region (Figure 4E). This can be seen by investigating the proportion of cells where the cuO and tetO labels have at least one encounter (defined by a separation distance below a proximity threshold). For instance, while 73% of Sox2-SCR pairs that start within 200 nm of each other are observed to have at least one encounter below 100 nm over the 25 min imaging window, this drops to 18% for pairs that start greater than 600 nm away. This trend is observed across label pairs and is robust to threshold value (Figure 4E). Such behavior could have important consequences for gene regulation by enhancer-promoter interactions. Given the observed inertia in locus conformation, enhancer proximity, and therefore the capacity for direct enhancer-promoter contact, is likely to be highly variable across time within a cell and between cells within a population.

Visualization of Sox2 transcriptional bursts in living ESCs

We next explored the temporal relation between 3D organization of the Sox2 locus and transcription. To this end, we utilized the well-established MS2 reporter system to directly visualize nascent transcription in single living ESCs (Bertrand et al., 1998). Using CRISPR/Cas9 genome engineering, we replaced the endogenous 129 Sox2 allele with a modified version that includes a P2A-puromycin resistance gene fusion and 24 MS2 stem loops inserted into the 3’ UTR of the Sox2 gene (Figure 5—figure supplement 1). We generated this MS2 reporter allele in our Sox2-SCR labeled cell line to generate Sox2-8CcuO/+, Sox2-117TtetO/+, Sox2MS2/WT ESCs (or simply Sox2-MS2 ESCs). Transcription levels derived from the Sox2-MS2 reporter allele were 35% of those from the untargeted 129 allele (Figure 1—figure supplement 2), potentially due to reduced stability of transcripts labeled with MS2 stem loops (Ochiai et al., 2014). Western blotting of Sox2-MS2 lysate revealed a SOX2 doublet as expected, suggesting proper expression of both wild-type SOX2 and the SOX-P2A fusion (Figure 5—figure supplement 1).

We first characterized the transcriptional activity of Sox2-MS2 reporter allele. We co-expressed a tandem-dimer of the MS2 coat protein fused with 2 copies of tagRFP-T (tdMS2cp-tagRFP-Tx2), TetR fused with 2 copies of GFP (TetR-GFPx2), and CymR fused with 2 copies of Halo tag (CymR-Halox2) in Sox2-MS2 ESCs. These ESCs enabled simultaneous visualization of the labels adjacent to the Sox2 promoter and SCR, as well as nascent Sox2 transcription in living ESCs when imaged in the presence of the Halo-tag ligand JF646 (Grimm et al., 2015) (Figure 5A). Time-lapse confocal microscopy revealed bright flashes of MS2cp signal in the ESC nucleus, which occurred in spatial proximity to the cuO and tetO labels, and were similar to the MS2 transcriptional bursts observed elsewhere (Bothma et al., 2014; Chubb et al., 2006; Lionnet et al., 2011; Martin et al., 2013; Ochiai et al., 2014). These results suggested the Sox2 MS2 reporter allele enables visualization of Sox2 transcription.

Figure 5 with 1 supplement see all
Visualizing Sox2 Expression in Single Living ESCs Reveals Intermittent Bursts of Transcription.

(A) Sox2 locus with cuO-labeled Sox2 promoter and tetO-labeled SCR was further modified to introduce an MS2 transcriptional reporter cassette into the Sox2 gene. Transcription of Sox2 leads to visible spot at the Sox2 gene due to binding and clustering of MS2 coat protein to the MS2 hairpin sequence. (B) Maximum-intensity projection images centered on the Sox2 promoter (cuO) show intermittent bursts of MS2 signal, which are quantified on the right. Scale bar is 1 µm. (C) Single cell trajectories of Sox2 transcriptional bursts as representatively shown in B. (D) Aligned Sox2 transcriptional bursts. Randomly selected Sox2 bursts are shown as color traces (n = 50). Black line is mean MS2 signal for all annotated bursts. (E) Percent time Sox2 transcriptional bursting for various experimental conditions. Bars are mean ± standard error of ≥3 independent experiments. Sox2MS2/+ indicates cell line harbors the Sox2-MS2 reporter allele. SCRdel/+ indicates presence of an SCR deletion in cis with the Sox2-MS2 reporter. DRB indicates treatment with the transcriptional inhibitor 5,6-Dichloro-1-β-D-ribofuranosylbenzimidazole (DRB).

https://doi.org/10.7554/eLife.41769.017

Using our pipeline, we identified a total of 603 individual bursts across 1,208 cells (Figure 5B, Supplementary files 5,6, Video 3). We found Sox2 transcriptional activity to be sporadic both between cells and within individual cells across time (Figure 5C). Nearly two-thirds (66.1%) of nuclei lacked detectable Sox2 transcription during our 30 min imaging window, with the majority of remaining cells demonstrating transcriptional activity in less than 20% of frames (29.3%, Figure 5—figure supplement 1). However, we did observe rare cells that demonstrated robust transcriptional activity in greater than half the observed frames (0.25% of cells, Video 4). We also found substantial variability in the intensity of transcriptional bursts and their duration (Figure 5D). As a population, we found Sox2-MS2 ESCs spent 4% of their time with a detectable MS2 burst (Figure 5E). Thus, our live-cell measurements of Sox2transcription suggest short, intermittent transcriptional activity in ESCs.

Video 3
Identification of Sox2 Transcriptional Bursts in mESCs.

Maximum-intensity Z projection of 3D confocal Z-stacks of a tandem dimer of MS2 coat protein fused with two copies of tagRFP-T. The dashed yellow box highlights the ROI used for burst detection in our automated analysis pipeline, centered on the location of the Sox2 promoter (cuO/CymR location, not shown). Detected bursts are highlighted by red circles centered on the burst location, with color intensity indicating burst intensity. Scale bar is 1 µm.

https://doi.org/10.7554/eLife.41769.019
Video 4
High Transcriptional Output from Sox2 Locus.

Maximum-intensity Z projection of 3D confocal Z-stacks of a tandem dimer of MS2 coat protein fused with two copies of tagRFP-T demonstrate a period of high transcriptional activity for the highlighted Sox2 gene. The dashed yellow box highlights the ROI used for burst detection in our automated analysis pipeline, centered on the location of the Sox2 promoter (cuO/CymR location, not shown). Detected bursts are highlighted by red circles centered on the burst location, with color intensity indicating burst intensity. Scale bar is 1 µm.

https://doi.org/10.7554/eLife.41769.020

To ensure that our MS2 analysis identified bona fide transcriptional activity, we repeated our analysis in a number of control contexts. First, we measured bursting frequency in ESCs that expressed the MS2 coat protein but lacked the Sox2-MS2 reporter allele(Sox2-8CcuO/+, Sox2-117TtetO/+, Sox2WT/WT). Second, we measured bursting frequency in Sox2-MS2 ESCs that harbored an SCR deletion in cis (Sox2-8CcuO/+, Sox2-117TtetO/+, Sox2MS/WT, SCRdel/+). Third, we measured bursting frequency in Sox2-MS2 ESCs that were treated with the transcriptional inhibitor 5,6-Dichloro-1-β-D-ribofuranosylbenzimidazole (DRB). In each case, we observed a significant drop in Sox2 burst frequency (Figure 5E). Taken together, these data demonstrate our ability to accurately identify Sox2 transcriptional events using our MS2 reporter cell line.

Sox2 transcription is not associated with SCR proximity

Assuming SCR regulates Sox2 transcription via the conventional enhancer looping model, we would expect Sox2 transcriptional activity to occur during interactions or periods of Sox2/SCR proximity (Figure 6A), given that Sox2 depends of SCR for its ESC expression. To investigate this prediction, we restricted our analysis to nuclei with single, diffraction-limited spots for the cuO and tetO labels in our Sox2-MS2 ESC dataset. We calculated 3D distances between the cuO/tetO and compared single cell distance traces with matched MS2 signal traces. We identified some transcriptionally active cells that showed prolonged proximity of the Sox2/SCR labels. However, we also observed cells which showed robust transcriptional bursting despite a prolonged extended conformation of the Sox2 region, driving Sox2/SCR distance above the population average for the duration of our 30 min imaging window (Figure 6B, Video 5). We binned time points according to the measured distance between Sox2 and SCR and calculated the percent time spent bursting for each bin and found that all bins showed similar transcriptional activity (Figure 6C). Furthermore, segregating time points into bursting and non-bursting frames for each cell demonstrated no significant differences between the two groups (Figure 6D, Mann-Whitney, p=0.68).

Figure 6 with 1 supplement see all
Sox2 Transcription Is Not Associated with SCR Proximity.

(A) Schematic illustrating the expected relation between Sox2/SCR distance and MS2 transcription for a looping enhancer model. (B) Maximum-intensity projection images centered on the Sox2 promoter (cuO) show transcriptional activity without correlation to Sox2/SCR distance changes. The measured distance and MS2 signal are shown at bottom. The mean separation distance across the cell population is shown as a dotted red line. Scale bar is 1 µm. (C) Percent time with Sox2 transcriptional burst as a function of Sox2/SCR distance. Weighted mean + SE for seven experiments are shown. Weights were determined based on the proportion of frames in each bin contributed by individual experiments. (D) Mean separation distance per cell, separated into bursting and non-bursting frames. (Mann-Whitney, p=0.68). (E) Mean separation distance across a 25 min window for all transcriptional bursts (black) or randomly select time points (red), aligned according the burst initiation frame. Values plotted are mean ± 95% CI. (F) Single cell trajectories of Sox2 transcriptional bursts ranked by number of bursting frames per cell. At right, matched mean separation distances for each cell shown at left. Spearman’s correlation coefficient for each is shown. (G) Mean separation distance per cell for transcribing and non-transcribing cells. (Mann-Whitney, p=0.15). (H) Potential models of SCR regulation of Sox2 that would uncouple Sox2/SCR proximity from transcriptional activity. Above, SCR leads to long-lived activation of the Sox2 promoter that can persist long after Sox2/SCR contact is disassembled. Below, SCR nucleates a large hub of activator proteins that can modify the Sox2 promoter environment despite large distances between Sox2 and SCR.

https://doi.org/10.7554/eLife.41769.021
Video 5
Sox2 Transcriptional Bursts in the Absence of SCR Proximity.

Maximum-intensity Z projection of 3D confocal Z-stacks of cuO/CymR (green) and tetO/TetR (magenta) labeling the Sox2 promoter region and SCR, respectively (left), and MS2 coat protein highlighting Sox2 transcriptional activity (right). We detect clear Sox2 transcriptional bursts despite no colocalization of the Sox2/SCR labels. Scale bar is 1 µm.

https://doi.org/10.7554/eLife.41769.023

We next considered the possibility that Sox2/SCR proximity might precede transcriptional bursting by a characteristic time. This might be expected if there are characteristic delays for transcription complex assembly or to allow for elongation to the 3’ MS2 sequence (based on an estimated elongation rate of 30–100 nt/sec [Fuchs et al., 2014], it would require ~ 0.5–2 min for polymerase to reach the 3’ end of the MS2 array). We identified the initiation point for all bursts in our dataset and considered a 25 min window centered at each burst initiation event. Alignment and meta-analysis of these bursts showed little change in Sox2/SCR distance across the time window. To determine if Sox2/SCR distance significantly deviated from expected values across transcriptional bursts, we compared aligned bursts to a randomly shuffled control dataset and found no significant differences between the burst-centered and random-centered analysis (Figure 6E, Supplementary file 7). This analysis suggests Sox2/SCR proximity and Sox2 transcription is not separated by a characteristic lag within the time frame considered.

Finally, given the high degree of cell-to-cell variability in Sox2 locus organization, we investigated whether cells with greater average Sox2-SCR proximity, which would enable more frequent Sox2/SCR encounters, demonstrated higher transcriptional activity. We rank ordered cells based on cumulative transcriptional activity (i.e. number of transcriptionally active frames) and compared mean Sox2/SCR distance per cell (Figure 6F). As expected, non-transcribing cells showed no correlation between order and distance, given the ordering within this group was essentially random (Spearman’s ρ = −0.01). However, transcribing cells also showed no correlation between transcriptional activity and distance (Spearman’s ρ = 0.06). As a group, transcribing cells demonstrated no significant difference in mean Sox2/SCR separation distance compared to non-transcribing cells (Figure 6G, Mann-Whitney, p=0.15). These data suggest little relation between the 3D conformation of Sox2 relative to the SCR enhancer and its transcriptional output. Thus, our data indicate SCR is unlikely to directly activate Sox2 transcription through contact with its promoter.

Discussion

We have investigated the dynamic 3D organization and underlying transcriptional activity of the established enhancer-gene pair Sox2 and SCR. Interestingly, we observe few unique spatial characteristics for Sox2/SCR in ESCs; observed distance distributions and their spatial dynamics for SCR and the Sox2 promoter region are similar to those observed between SCR and an equally-spaced non-specific region. In contrast, 3C-based assays have identified enriched contacts between Sox2/SCR as compared to the surrounding neighborhood. We note that these results need not be incompatible. Proximity ligation (3C) and separation distance (microscopy) are distinct measures of chromatin structure with unique biases, assumptions, and limitations, and thus provide snapshots of chromatin architecture that may differ (Dekker, 2016; Fudenberg and Imakaev, 2017; Giorgetti and Heard, 2016). 3C-based assays often utilize millions of cells and so may capture rare conformations in the cell population; these rare conformations would have minimal impact on overall distance distributions constructed using microscopy. Moreover, it remains unclear what spatial proximity is required to enable ligation events during 3C, and this property may differ for distinct genomic regions. Indeed, enrichment of Sox2/SCR contacts in 3C assays may reflect only subtle differences in very proximal conformations (e.g. < 50 nm), conformations unlikely to be accurately represented by our microscopy measurements due to technical limitations in localization precision and uncertainty. Alternatively, large macromolecular bridges or hubs may enable crosslinking and ligation over larger distances that need not demonstrate pronounced spatial proximity, as recently demonstrated (Quinodoz et al., 2018). Moreover, chromatin composition and accessibility are likely to influence key features for 3C and microscopy experiments, such as crosslinkability, distances permissive for proximity ligation, and the scaling of spatial distances with genomic distance. All of these sources of uncertainty raise questions regarding how features from 3C and microscopy translate between assays and to the underlying chromatin structure. While a comprehensive picture of Sox2 locus organization remains out of view, our study provides guidance as to what structures are unlikely. For instance, the absence of enhanced proximity between the Sox2 and SCR pair suggests a prolonged, proximal conformation established by stable, direct pairing of the Sox2 promoter with SCR is unlikely to be the predominant structure in ESCs.

Surprisingly, we also observe no association between Sox2/SCR proximity and Sox2 transcription in real time. Indeed, we detect no correlation between transcriptional activity and instantaneous Sox2/SCR distances, no reduction in Sox2/SCR distances prior to transcriptional bursts, and no tendency for transcriptionally active cells to display reduced Sox2/SCR distance. It is important to note that we cannot exclude the importance of direct Sox2/SCR contacts in Sox2 activation. If these events lead to a complex, multi-step activation process with stochastic delays between steps, it is plausible that enhancer-promoter contact and transcriptional output could be temporally decoupled and demonstrate the poor correlation between Sox2/SCR proximity and transcriptional activity that we observe. Furthermore, SCR contacts could be important for long-lived activation of the Sox2 promoter, which could persist after disassembly of these interactions (Figure 6H, top). This mechanism might be achieved through delivery of durable factors (e.g. chromatin modifiers) to the Sox2 promoter during contact, and might explain why disruption of DNA loops genome-wide through acute RAD21 degradation leads to only modest changes in nascent transcription after 6 hr (Rao et al., 2017).

The Sox2 locus displays distinct behavior from an enhancer reporter recently used to explore the regulatory logic of the even-skipped (eve) enhancers in Drosophila embryos. In this study, the authors integrated an enhancer reporter ~ 142 kb upstream of eve locus and promoted pairing between the two loci by including an ectopic insulator sequence, which pairs with a similar sequence embedded near the eve enhancers. In this system, the authors observe both bimodality in distance measurements as well as clear correlation between enhancer-reporter proximity and reporter transcription. While it is not yet clear why these systems behave so differently, we note the considerable differences in the 3D distances we report for Sox2 (339 nm for Sox2/SCR) and those reported for the even-skipped reporter (709 nm for unpaired and 353 nm for paired). It seems plausible that the more extended conformation of the Drosophila chromosome necessitates pairing in order to bring the eve enhancer sufficiently close the reporter, particularly for enhancers evolved to function within 10 kb of their target gene. Our analysis suggests that most Sox2/SCR loci reside within this distance range, perhaps lowering the importance of locus conformation for SCR function. Indeed, SCR transcriptional control does demonstrate proximity dependence on some scale, as SCR ablation is not compensated for by a normal copy located on the homologous chromosome (Li et al., 2014; Zhou et al., 2014). In other contexts, such as during olfactory receptor gene choice or transvection in Drosophila, regulation can occur over very large distances in cis (~80 Mb) or in trans, and transcriptional activity may be more closely tied to pairing events that promote spatial proximity, as recently demonstrated for the latter (Horta et al., 2018; Lim et al., 2018; Markenscoff-Papadimitriou et al., 2014). Hence, genomic interactions and other features of genome topology may differ in importance depending of the spatial distances navigated by enhancer-gene pairs.

Our observations also open the possibility that direct contacts between Sox2 and SCR are dispensable for SCR function. Numerous mechanisms for long-range communication between enhancers and promoters have been proposed (Bulger and Groudine, 2010). For example, SCR may play a critical role in the nucleation and spreading of important epigenetic activators and chromatin accessibility, establishing a permissive environment of Sox2 transcription. An intriguing mechanism for action at a distance comes from recent observations that super-enhancers are capable of nucleating large (>300 nm), phase-separated condensates of coactivators, chromatin regulators, and transcription complexes (Cho et al., 2018; Sabari et al., 2018). SCR is a bona fide super-enhancer in ESCs (Whyte et al., 2013). Thus, SCR may deliver activation factors over hundreds of nanometers through inclusion of the Sox2 promoter into an activator hub or condensate (Figure 6H, bottom). Such a mechanism would present a number of challenges for achieving precise transcriptional control, most notably how SCR selectivity for Sox2 activation is achieved. Nevertheless, future studies that couple visualization of the Sox2 locus with that of important molecular components of transcriptional activation are likely to be essential in decoding how the SCR element achieves tight expression control of this essential pluripotency gene.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or referenceIdentifiersAdditional information
Cell line
(M. musculus)
129/Cast F1 ESCsPMID: 9298902
Cell line
(M. musculus)
E14 ESCsPMID: 3821905RRID:CVCL_C320
Cell line
(M. musculus)
Sox2-SCR ESCsthis paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2
TSS on the 129 allele
Cell line
(M. musculus)
Sox2-SCR ESCs;
CymR-GFP;
TetR-tdTom
this paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2
TSS on the 129 allele. Cells
stably express ePiggyBac
vectors epB-UbC-CymRV5
-nls-GFP-DEx2 and epB-
CAG-TetRFlag-nls-tdTom-DEx4
Cell line
(M. musculus)
Control-Control ESCsthis paper129/Cast F1 ESCs with
tetO array inserted 43 kb
telomeric to Sox2 TSS and
cuO array inserted 164 kb
telomeric to Sox2 TSS on
the 129 allele
Cell line
(M. musculus)
Control-Control ESCsthis paper129/Cast F1 ESCs with
tetO array inserted 43 kb
telomeric to Sox2 TSS and
cuO array inserted 164 kb
telomeric to Sox2 TSS on
the 129 allele. Cells stably
express ePiggyBac vectors
epB-UbC-CymRV5-nls-GFP-DEx2
and epB-CAG-TetRFlag-nls-
tdTom-DEx4
Cell line
(M. musculus)
SCR-Control ESCsthis paper129/Cast F1 ESCs with
tetO array inserted 117 kb
telomeric to Sox2 TSS and
cuO array inserted 242 kb
telomeric to Sox2 TSS on
the 129 allele
Cell line
(M. musculus)
SCR-Control ESCsthis paper129/Cast F1 ESCs with
tetO array inserted 117 kb
telomeric to Sox2 TSS and
cuO array inserted 242 kb
telomeric to Sox2 TSS on
the 129 allele. Cells stably
express ePiggyBac vectors
epB-UbC-CymRV5-nls-GFP-DEx2
and epB-CAG-TetRFlag-nls-td
Tom-DEx4
Cell line
(M. musculus)
SCR deletion ESCsthis paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2
TSS on the 129 allele.
SCR deletion (104 kb-112kb
from Sox2 TSS) is present
on 129 allele
Cell line
(M. musculus)
SCR deletion ESCsthis paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2
TSS on the 129 allele. SCR
deletion (104 kb-112kb
from Sox2 TSS) is present
on 129 allele. Cells stably
express ePiggyBac vectors
epB-UbC-CymRV5-nls-GFP-DEx2
and epB-CAG-TetRFlag-nls
-tdTom-DEx4
Cell line
(M. musculus)
Sox2-MS2 ESCsthis paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2
TSS on the 129 allele.
129 Sox2 allele has been
replaced with Sox2-P2A-
puro-24xMS2.
Cell line
(M. musculus)
Sox2-MS2 ESCsthis paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted 117 kb
telomeric to Sox2 TSS on the
129 allele. 129 Sox2 allele
has been replaced with
Sox2-P2A-puro-24xMS2. Cells
stably express ePiggyBac
vectors epB-UbC-CymRV5-
nls-Halox2-DEx4, epB-CAG-
TetRFlag-nls-GFPx2, and
epB-UbC-tdMS2cp-tagRFP-Tx2
Cell line
(M. musculus)
Sox2-MS2; SCR
deletion ESCs
this paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2 TSS
on the 129 allele. 129 Sox2
allele has been replaced
with Sox2-P2A-puro-24xMS2.
SCR deletion (104 kb-112kb
from Sox2 TSS) is present
on 129 allele
Cell line
(M. musculus)
Sox2-MS2; SCR
deletion ESCs
this paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2
TSS on the 129 allele.
129 Sox2 allele has been
replaced with Sox2-P2A-
puro-24xMS2. SCR deletion
(104 kb-112kb from Sox2 TSS)
is present on 129 allele.
Cells stably express
ePiggyBac vectors epB-UbC
-CymRV5-nls-Halox2-DEx4,
epB-CAG-TetRFlag-nls-GFPx2,
and epB-UbC-tdMS2cp-
tagRFP-Tx2
Cell line
(M. musculus)
Sox2-del-SCR ESCsthis paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2 TSS
on the 129 allele. Large
deletion (1 kb-112kb from
Sox2 TSS) is present on 129
allele. All genetic distances
based on reference genome.
Cell line
(M. musculus)
Sox2-del-SCR ESCsthis paper129/Cast F1 ESCs with
cuO array inserted 8 kb
centromeric to Sox2 TSS
and tetO array inserted
117 kb telomeric to Sox2
TSS on the 129 allele.
Large deletion (1 kb-112kb
from Sox2 TSS) is present
on 129 allele. All genetic
distances based on
reference genome. Cells
stably express ePiggyBac
vectors epB-UbC-CymRV5
-nls-GFP-DEx2 and epB-CAG
-TetRFlag-nls-tdTom-DEx4.
Cell line
(M. musculus)
Sox2-SCR NPCsthis paperNeural progenitor cells
derived from Sox2-SCR
ESCs. Cells stably express
ePiggyBac vectors epB-UbC
-CymRV5-nls-GFP-DEx2
and epB-CAG-TetRFlag-nls
-tdTom-DEx4.
Cell line
(M. musculus)
Sox2-SCR NPCsthis paperNeural progenitor cells
derived from Sox2-SCR
ESCs
Cell line
(M. musculus)
Control-Control NPCsthis paperNeural progenitor cells
derived from
Control-Control ESCs.
Cells stably express
ePiggyBac vectors
epB-UbC-CymRV5-nls-GFP-DEx2
and epB-CAG-TetRFlag-
nls-tdTom-DEx4.
Cell line
(M. musculus)
SCR-Control NPCsthis paperNeural progenitor cells
derived from SCR-Control
ESCs
Cell line
(M. musculus)
SCR-Control NPCsthis paperNeural progenitor cells
derived from SCR-Control
ESCs. epB-UbC-CymRV5
-nls-GFP-DEx2 and
epB-CAG-TetRFlag-nls-td
Tom-DEx4.
Antibodyrat monoclonal
PE-conjugated
anti-PDGFRα
Thermo Fisher12-1401-81;
RRID:AB_657615
Flow 1:400
Antibodymouse monoclonal
anti-SOX2
Santa Cruzsc-365823;
RRID:AB_10842165
WB 1:1000, IF 1:100
Antibodyrabbit polyclonal
anti-PAX6
Biolegend901301;
RRID:AB_2565003
IF 1:100
Antibodymouse monoclonal
anti-TUBB3
Biolegend801201;
RRID:AB_2313773
IF 1:100
Antibodymouse monoclonal
anti-GFAP
SigmaG3893;
RRID:AB_477010
IF 1:400
Antibodyrabbit polyclonal
anti-βactin
Abcamab8227;
RRID:AB_2305186
WB 1:2000
Antibodyanti-Flk1 biotinPMID: 17084363Hybridoma clone
D218 Flow 1:100
Recombinant
DNA reagent
pCAGGS-Bxb1o-nlsFlagthis paperAddgene: 119901Expresses Bxb1
integrase in mammalian
cells
Recombinant
DNA reagent
pDEST-tetOx224
_PhiC31attB_loxP-
PGKpuro-loxP
this paperAddgene: 119902PhiC31 integration
plasmid for tetO
array with Neo
selection cassette
Recombinant
DNA reagent
pDEST-cuOx144
_Bxb1attB_loxP-
PGKpuro-loxP
this paperAddgene: 119903Bxb1 integration plasmid
for cuO array with Puro
selection cassette
Recombinant
DNA reagent
pDEST-tetOx224
_PhiC31attB_FRT-
EF1a-GFP-FRT
this paperAddgene: 119904PhiC31 integration
plasmid for tetO array
with GFP expression
cassette
Recombinant
DNA reagent
pDEST-cuOx144_
Bxb1attB_loxP-
EF1a-tagRFP-T-loxP
this paperAddgene: 119905Bxb1 integration plasmid
for cuO array with
RFP expression cassette
Recombinant
DNA reagent
epB-UbC_CymRV5
-nls-GFP-DEx2
this paperAddgene: 119906ePiggyBac mammalian
expression plasmid for
CymR-GFP fusion
Recombinant
DNA reagent
epB-UbC_CymRV5
-nls-Halox2_DEx4
this paperAddgene: 119907ePiggyBac mammalian
expression plasmid
for CymR-Halo fusion
Recombinant
DNA reagent
epB-UbC_tdMS2cp
-tagRFP-Tx2
this paperAddgene: 119908ePiggyBac mammalian
expression plasmid for
tandem dimer
MS2cp-tagRFP-T fusion
Recombinant
DNA reagent
epB_CAG_TetRFlag-
nls-tdTom-DEx4
this paperAddgene: 119909ePiggyBac mammalian
expression plasmid for
TetR-tdTom fusion
Recombinant
DNA reagent
epB_CAG_TetRFlag-nls_GFPx2_DEx2this paperAddgene: 119910ePiggyBac mammalian
expression plasmid for
TetR-GFP fusion
Recombinant
DNA reagent
ePiggyBac-Transposasethis paperAddgene: 119911Mammalian expression
plasmid for the ePiggy
Bac transposes
Recombinant
DNA reagent
pKS_Sox2-P2A-puro-
24xMS_targeting_
vector_NoPAM
this paperTargeting vector for
generating Sox2-MS2
allele
Recombinant
DNA reagent
pX330-Sox2_3'
UTR_gRNA
this paperCas9/sgRNA expression
vector with gRNA that
targets the Sox2 3' UTR
Recombinant
DNA reagent
pX330-Sox2-
8C_gRNA
this paperCas9/sgRNA expression
vector with gRNA that
targets 8 kb centromeric
to Sox2 TSS
Recombinant
DNA reagent
pX330-Sox2-
43T_gRNA
this paperCas9/sgRNA expression
vector with gRNA that
targets 43 kb telomeric
to Sox2 TSS
Recombinant
DNA reagent
pX330-Sox2-
117T_gRNA
this paperCas9/sgRNA expression
vector with gRNA that
targets 117 kb telomeric
to Sox2 TSS
Recombinant
DNA reagent
pX330-Sox2-
164T_gRNA
this paperCas9/sgRNA expression
vector with gRNA that
targets 164 kb telomeric
to Sox2 TSS
Recombinant
DNA reagent
pX330-Sox2-
104T_gRNA
this paperCas9/sgRNA expression
vector with gRNA that
targets 104 kb telomeric
to Sox2 TSS
Recombinant
DNA reagent
pX330-Sox2-
112T_gRNA
this paperCas9/sgRNA expression
vector with gRNA that
targets 112 kb telomeric
to Sox2 TSS
Recombinant
DNA reagent
pX330-Sox2-
242T_gRNA
this paperCas9/sgRNA expression
vector with gRNA that
targets 242 kb telomeric
to Sox2 TSS
Sequence-based
reagent
Sox2 qPCR
Forward Primer
this paper5'-CTACGCGCACATGAACGG-3'
Sequence-based
reagent
Sox2 qPCR
Reverse Primer
this paper5'-CGAGCTGGTCATGGAGTTGT-3'
Sequence-based
reagent
Sox2 qPCR 129
allele Probe
this paper5'-/56-FAM/CAACCGATG
/ZEN/CACCGCTACGA/
3IABkFQ/−3'
Sequence-based
reagent
Sox2 qPCR
Cast allele Probe
this paper5'-/56-FAM/CAGCCGATG
/ZEN/CACCGATACGA/
3IABkFQ/−3'
Sequence-based
reagent
Tbp qPCR
Forward Primer
this paper5'-ACACTCAGTTACAGGTGGCA-3'
Sequence-based
reagent
Tbp qPCR
Reverse Primer
this paper5'-AGTAGTGCTGCAGGGTGATT-3'
Sequence-based
reagent
Tbp qPCR Pan
allele Probe
this paper5'-/56-FAM/ACACTGTGT/
ZEN/GTCCTACTGCA/3IABkFQ/−3'
Sequence-based
reagent
Genotyping
PCR Primers
this papersee Supplementary file 1
Sequence-based
reagent
CRISPR guide
sequences
this papersee Supplementary file 2
Peptide, recombinant
protein
Leukemia inhibitory
factor (Lif)
Peprotech250–02
Peptide, recombinant
protein
APC-StreptavidinBD-Biosciences554067;
RRID:AB_10050396
Flow 1:200
Peptide, recombinant
protein
InsulinSigmaI6634
Peptide, recombinant
protein
Epidermal growth
factor (EGF)
Peprotech315–09
Peptide, recombinant
protein
Fibroblast growth
factor basic (Fgfb)
R and D Systems233-FB
Peptide, recombinant
protein
Natural mouse lamininThermo Fisher23017015
Peptide, recombinant
protein
Bone morphogenetic
protein 4 (BMP4)
R and D Systems314 BP
Peptide, recombinant
protein
Vascular endothelial
growth factor (VEGF)
R and D Systems293-VE
Peptide, recombinant
protein
Activin AR and D Systems338-AC
peptide, recombinant
protein
Fibroblast growth
factor 10 (Fgf10)
R and D Systems345-FG
Peptide, recombinant
protein
Laminin-511iWaichemN-892011
Chemical
compound,
drug
Prolong Live
Antifade Reagent
Thermo FisherP36975
Chemical
compound,
drug
ascorbic acidSigmaA45-44
Chemical
compound,
drug
1-thioglycerolSigmaM6145
Chemical
compound,
drug
PD03259010SelleckchemS1036
Chemical
compound,
drug
CHIR99021SelleckchemS2924
Chemical
compound,
drug
5,6-Dichlorobenzimidazole
1-β-D-ribofuranoside
SigmaD1916
Chemical
compound,
drug
JF646PMID: 28869757
Software,
algorithm
MS2Reporter
AnalysisPipeline_knn
Model.py
this paperPython scripts can
be accessed on
github (Alexander, 2018; copy archived at https://github.com/elifesciences-publications/2018_eLife_Alexander_et_al)
OtherTetraspeck
fluorescent beads
Thermo FisherT7279
Commerical
assay, kit
KAPA Library
Quantification Kit
RocheKK4854
Commerical
assay, kit
SPRIselectBeckman CoulterB23319

ESC Culture

129/CastEiJ F1 hybrid mouse embryonic stem cells were maintained in 2i + Lif media, composed of a 1:1 mixture of DMEM/F12 (Thermo Fisher Waltham, MA, #11320–033) and Neurobasal (Thermo Fisher #21103–049) supplemented with N2 supplement (Thermo Fisher #17502–048), B27 with retinoid acid (Thermo Fisher #17504–044), 0.05% BSA (Thermo Fisher #15260–037), 2 mM GlutaMax (Thermo Fisher #35050–061), 150 µM 1-thioglycerol (Sigma St. Louis, MO, M6145), 1 µM PD03259010 (Selleckchem Houston, TX, #1036), 3 µM CHIR99021 (Selleckchem #S2924) and 106 U/L leukemia inhibitory factor (Peprotech Rocky Hill, NJ, #250–02). Media was changed daily and cells were passaged every 2 days.129/CastEiJ ESCs were genetically verified by PCR amplification and Sanger sequencing of regions within the Sox2 locus to identify predicted SNPs between the parental genomes. These cells tested negatively for mycoplasma using MycoAlert Detect Kit (Lonza Basal, Switzerland #LT07-318).

ESC genome modification

For insertion of PhiC31 and Bxb1 attP sequences, 150,000 cells were electroporated with 1 µM of single-stranded oligonucleotide donor containing the attP sequence and 400 ng of the sgRNA/Cas9 dual expression plasmid pX330 (a gift from Feng Zhang, Addgene Plasmid #42230) using the Neon Transfection System (Thermo Fisher). Neon settings for the electroporation were as follows: 1400V, 10 ms pulse width, three pulses. Electroporated ESCs were given 3 days to recover, followed by seeding approximately 5000 cells on a 10 cm dish for clone isolation (see Clone Isolation).

For integration of the tetO and cuO array, 150,000 cells were electroporated with 300 ng each of (1) a tetOx224 repeat plasmid bearing a PhiC31 attB sequence and a FRT-flanked neomycin resistance cassette, (2) a cuOx144 repeat plasmid bearing a Bxb1 attB sequence and a floxed puromycin or blasticidin resistance cassette, (3) an expression plasmid for the PhiC31 integrase (a gift from Philippe Soriano, Addgene Plasmid #13795), and (4) an expression plasmid for the Bxb1 integrase using the Neon Transfection System. Electroporated ESCs were allowed to recover for 3 days, followed by 7 days of drug selection using 500 µg/mL G418 and either 1 µg/mL puromycin or 8 µg/mL blasticidin in antibiotic-free media. After drug selection, cells were electroporated again with 400 ng each of Cre and Flpo expression plasmids to remove the resistance cassettes. 3 days after electroporation, approximately 5000 cells were seeded on a 10 cm plate for clone isolation (see Clone Isolation).

For targeting of the MS2 reporter construct into the endogenous Sox2 allele, we generated a targeting plasmid that inserted a P2A sequence followed by the puromycin resistance gene upstream of the endogenous Sox2 stop codon with 1 kb homolog arms on either side. We next mutated the PAM sequence for our sgRNA in the 3’ homology arm by site-directed mutagenesis. 24 repeats of the MS2 hairpin sequence were inserted into an EcoRI restriction site located just 3’ of the puromycin stop codon. 150,000 cells were electroporated with 400 ng of targeting plasmid and 400 ng of pX330 expressing the appropriate sgRNA. Electroporated ESCs were given 3 days to recover, followed by 5 days of puromycin selection. Approximately 5000 cells were subsequently seeded on a 10 cm dish for clone isolation (see Clone Isolation). A positive clone was identified by PCR. DNA sequencing confirmed no mutations in the Sox2-P2A-puror cassette and identified a single bp deletion in the 3’ UTR of the non-targeted CastEiJ allele due to residual targeting of a non-canonical NAG PAM.

For deletion of the Sox2 Control Region or the Sox2-1-112T fragment, 150,000 cells were electroporated with 400 ng each of pX330 expressing sgRNAs targeting genomic regions centromeric and telomeric to the deletion fragment. 3 days after electroporation, approximately 5000 cells were seeded on a 10 cm plate for clone isolation (see Clone Isolation).

ESC clone isolation

After 5–6 days of growth at low density (~5000 cells per 10 cm dish), individual colonies were picked and transferred to a 96-well plate. Briefly, colonies were aspirated and transferred to a well with trypsin, followed by quenching and dissociation with 2i + Lif + 5% FBS. Once the 96-well plate had grown to confluency, we split the clones into 2 identical 96-well plates. One plate was frozen at −80°C by resuspending the clones in 80% FBS/20% DMSO freezing media. The second plate was used for DNA extraction. All wells were washed once with PBS and subsequently lysed overnight at 55°C in a humidified chamber with 50 µL lysis buffer (10 mM Tris-HCl, pH 8.3, 50 mM KCl, 1.5 mM MgCl2, 0.45% NP40, 0.45% Tween 20, 100 µg/mL Proteinase K). Genomic DNA was concentrated by ethanol precipitation and resuspended in 100 µL of double distilled water. 1 µL of suspension was used for subsequent PCR screening reactions using GoTaq Master Mix (Promega Madison, WI, #M7123).

Stable expression of fluorescent transgenes

To generate stable lines expressing CymR, TetR, and MS2cp fluorescent protein fusions, 150,000 cells were electroporated with 400 ng of an ePiggyBac Transposase expression plasmid (a gift from Ali Brivanlou) and 50 ng of expression plasmid bearing PiggyBac terminal repeats. 7 days after electroporation, fluorescent cells were resuspended in fluorescence-activated cell sorting (FACS) buffer (5% FBS in PBS) and purified via FACS using a FACSAria II (BD). To enrich cells expressing the CymR-Halox2 fusion protein, ESCs were incubated in 100 nM of Janeila Fluor 646 (a gift from Luke Lavis) for 30 min at room temperature, washed once in FACS Buffer, incubated for 30 min at room temperature in FACS Buffer, washed again, and sorted using a FACSAria II.

Isolation of Neural Progenitor Cells from ESCs

ESCs were passaged onto gelatinized 6 wells at 50,000–100,000 cells. The following day, these cultures were switched to N2B27 media (1:1 composition of DMEM/F12 and Neurobasal, N2 supplement, B27 with retinoic acid, 0.05% BSA, 2 mM GlutaMax, 150 µM 1-thioglycerol, 25 µg/mL insulin (Sigma #I6634)). After 4 days, we dissociated the cultures and seeded 1 million cells in an ungelatinized 10 cm dish in N2B27 with 10 ng/mL FGF basic (R and D Systems Minneapolis, MN, #233-FB) and 10 ng/mL EGF (Peprotech #315–09) to form neurospheres. After 3–4 days of outgrowth, neurospheres were collected by gentle centrifugation (180xg, 3 min) and plated onto a pre-gelatinized six well. Neural progenitor cell (NPCs) lines were established by passaging (4–6 passages). For maintainance of NPCs, cells were cultured on wells pre-treated with poly-D-lysine and 4 µg/mL natural mouse laminin (Thermo Fisher #23017015) in N2B27 with 10 ng/mL FGF basic and 10 ng/mL EGF and passaged every 4–5 days.

Differentiation of NPCs to neurons and astrocytes

To differentiate NPCs to astrocytes, 30,000 cells were plated onto coverglass within a 24 well pre-treated with poly-D-lysine and laminin. The following day, cells were switched to N2B27 with 10 ng/mL BMP4 (R and D Systems #314 BP) and allowed to differentiate for 12 days.

To differentiate NPCs to neurons, 30,000 cells were plated onto coverglass within a 24 well pre-treated with poly-D-lysine and laminin. The following day, cells were switched to N2B27 with 10 ng/mL FGF basic and allowed to differentiate for 6 days. Cells were then switched to N2B27 without additional factors and grown for 6 days.

Differentiation of cardiogenic mesodermal precursors from ESCs

ESCs were dissociated and seeded to form embryoid bodies at 1 million cells per dish in SFD media (3:1 composition of IMDM (Thermo Fisher #12440–053) and Ham’s F12 (Thermo Fisher #11765–054), N2 supplement, B27 without retinoic acid (Thermo Fisher #12587–010), 0.05% BSA, 2 mM GlutaMax, 50 µg/mL ascorbic acid (Sigma #A-4544), 450 µM 1-thioglycerol). After 2 days, EBs were dissociated and reaggregated at 1 million cells per dish in SFD media with 5 ng/mL VEGF (R and D Systems #293-VE), 5 ng/mL Activin A (R and D Systems #338-AC), and 0.75 ng/mL BMP4 to induce cardiogenic mesoderm. 40 hr after induction, cells were dissociated and stained for Flk1 and PDGFRα. Briefly, cells were washed four times in FACS Buffer, followed by incubation for 30 min with a biotinylated anti-FLK-1 antibody (Hybridoma Clone D218, 1:100). Cells were then washed three times with FACS Buffer and incubated with a PE-conjugated anti-PDGFRα (Thermo Fisher #12-1401-81, 1:400) and APC-Streptavidin (BD Biosciences Franklin Lakes, NJ, #554067, 1:200) for 30 min at room temperature. Cells were then washed two times with FACS Buffer and sorted for FLK1+/PDGFRα+ cells.

Immunofluorescence

NPCs or differentiated astrocytes/neurons on coverglass were fixed for 10 min at room temperature with 4% paraformaldehyde in PBS. After fixing, the coverglass were washed twice with PBS, permeabilized in PBS with 0.5% Triton X-100 for 10 min, and washed once in PBS with 0.1% Triton. Cells were then blocked for 1 hr at room temperature in PBS/0.1% Triton/4% goat serum. After blocking, coverglass were incubated in primary antibody in PBS/0.1% Triton/4% goat serum overnight at 4°C in a humidified chamber. Coverglass were subsequently washed three times with PBS/0.1% Triton and incubated in secondary antibody in PBS/0.1% Triton/4% goat serum at room temperature for 1 hr. After secondary incubation, coverglass were washed three times with PBS/0.1% Triton, stained with DAPI in PBS (1 µg/mL), and mounted on a slide for imaging in mounting medium (1x PBS, pH7.4, 90% glycerol, 5 mg/mL propyl gallate). Antibodies used were anti-SOX2 (Santa Cruz Biotechnology Dallas, TX, #sc-365823, Lot# K1414), anti-PAX6 (Biolegend San Diego, CA, #901301, Lot# B235967), anti-TUBB3 (Biolegend #801201, Lot# B199846), and anti-GFAP (Sigma #G3893, Lot# 105M4784V).

Western blotting

3 million cells were collected, washed once with PBS, and lysed in 4x Laemmli Buffer. Cell lysate was passed through a 30 gauge needle twenty times to shear the genomic DNA and the lysate was cleared by centrifugation at 13,000 RPM for 10 min at 4°C. Subsequently, lysate was supplemented with 100 mM DTT and boiled at 95°C for 10 min. 200,000 cells of protein lysate were loaded onto a Bis-Tris 4–12% polyacrylamide gel (ThermoFisher #NW04120BOX) and electrophoresis was carried out using the Bolt system (ThermoFisher). Protein was transferred to a PVDF membrane. Membranes were blocked for 1 hr at room temperature with 4% milk PBS Tween (PBST). Membrane was subsequently incubated in primary antibody overnight in 4% milk PBST at 4°C. Membranes were then washed four times 15 min at room temperature in PBST and incubated in secondary antibody in 4% milk PBST for 1 hr at room temperature. After secondary incubation, membranes were washed four times 15 min at room temperature in PBST, incubated in SuperSignal chemiluminescence HRP substrate (ThermoFisher #34075), and visualized by film exposure. Antibodies used were anti-SOX2 (Santa Cruz #sc-365823, Lot# K1414) and anti-β-actin (Abcam Cambridge, UK, ab8227, Lot# GR92448-1).

Quantitative PCR

RNA was extracted from 500,000 to 1,000,000 million cells using TRIzol and 200 ng of RNA was reversed transcribed using the QuantiTect Reverse Transcription kit (Qiagen Hilden, Germany). Quantitative PCR was performed on 8 ng cDNA in technical triplicates using TaqMan Gene Expression Master Mix (ThermoFisher #4369016) on a 790HT Fast Real-Time PCR System (ThermoFisher). The primer and probe sets used are as follows:

  • Sox2 Forward primer – 5’CTACGCGCACATGAACGG3’,

  • Sox2 Reverse primer – 5’CGAGCTGGTCATGGAGTTGT3’,

  • Sox2 129 allele probe –/56-FAM/CAACCGATG/ZEN/CACCGCTACGA/3IABkFQ/,

  • Sox2 CastEiJ allele probe –/56-FAM/CAGCCGATG/ZEN/CACCGATACGA/3IABkFQ/, Tbp Forward primer – 5’ACACTCAGTTACAGGTGGCA3’,

  • Tbp Reverse primer – 5’AGTAGTGCTGCAGGGTGATT3’,

  • Tbp probe -/56-FAM/ACACTGTGT/ZEN/GTCCTACTGCA/3IABkFQ.

  • 56-FAM = Fluorescein

  • ZEN = internal quencher (IDT)

  • 3IABkFQ = 3’ Iowa Black quencher

Circular chromosome conformation capture (4C) Sequencing

4C using the Sox2 promoter as a bait region was prepared as previously described (van de Werken et al., 2012). Primers used for 4C amplification are as follows:

  • Sox2 promoter Forward primer - CAAGCAGAAGACGGCATACGAGATACXXXXXXGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTGAATTAGGGGTTGAGGACAC

  • Sox2 promoter Reverse primer – AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTAGAGGGTAATTTTAGCCGATC

where XXXXXX stands for a barcode sequence and sequence complementary to the viewpoint fragment containing the Sox2 promoter is underlined.

Single cell suspensions of mouse embryonic stem cells were cross-linked with 1% formaldehyde in PBS for 10 min at room temperature. Nuclei were isolated in lysis buffer (10 mM Tris-HCl pH8.0, 10 mM NaCl, 0.2% Igepal CA630, 1X protease inhibitor),and cross-linked chromatin was digested with DpnII (0.4 U/µL, 100U total) overnight at 37°C. This was followed by proximity ligation with 2000 units of T4 DNA Ligase (NEB, #M0202, 2 U/µL) for 4 hr at room temperature. After ligation, samples were treated with 1 mg/mL Proteinase K, 10% SDS for 30 min at 55°C, followed by reverse crosslinking through addition of 5M NaCl and heating to 65°C overnight. Circularized DNA was then linearized by subsequent digestion with 50 units of NlaIII (0.1 U/µL) overnight at 37°C. Typically, 200 ng of the resulting 4C template was used for the subsequent PCR reaction. The 4C template was PCR amplified for 30 cycles and 3–4 reactions were pooled together. Primers were designed such that the single-end read would sequence the primer binding site of the bait region and read into the target region of interest. The primers were designed to include Illumina adaptor sequences as well as barcodes derived from Illumina’s TruSeq adaptors, which allowed for multiplexing of 4C-seq reactions. The PCR products were then purified using dual SPRI bead selection (Beckman Coulter, Indianapolis, IN Cat# B23319) to get template between 120–1000 bp according to the manufacturer’s instructions. The concentrations of each 4C library were calculated using the KAPA qPCR system (Roche Basal, Switzerland Cat# KK4854) and comparison to a standard curve. The libraries were then combined and sequenced on a HiSeq 4000 (Illumina San Diego, CA) with single-end 50 bp reads.

For generating near-cis plots, 4C reads were first trimmed using cutadapt (Martin, 2011, RRID:SCR_011841) to remove the reading primer sequences, then mapped to the mm9 genome using bwa (Li and Durbin, 2009, RRID:SCR_010910). Mapped reads were filtered for valid 4C fragments, normalized to reads per million, and visualized at the Sox2 genomic locus using Basic4CSeq (Walter et al., 2014, RRID:SCR_002836).

For allele-specific read assignments, 4C reads were trimmed using cutadapt. Reads were then mapped to a modified mm9 genome using bowtie2 (Langmead and Salzberg, 2012) with default settings, where base positions annotated as heterozygous in the F123 129/CastEiJ hybrid cell line were masked. Reads mapping within the SCR (mm9 genomic coordinates chr3: 34653927–34660927) were then assigned to the 129 or Cast allele using SNPsplit.

Live-Cell microscopy

We imaged all experiments on a Nikon Ti-E microscope and the following setup for live, spinning disk confocal microscopy: Yokogawa CSU-22 spinning disk, 150 mW Coherent OBIS 488 nm laser, 100 mW Coherent OBIS 561 nm laser, 100 mW Coherent OBIS 640 nm laser, a Yokogawa 405/491/561/640 dichroic, zET405/488/561/635 m quad pass emission filter, Piezo Z-drive, Okolab enclosure allowing for heating to 37°C, humidity control, and CO2 control, and a Plan Apo VC 100x/1.4 oil immersion objective. Image acquisition utilized either a Photometric Evolve Delta EMCCD or an Andor iXon Ultra EMCCD camera. Pixel size using this set up was 91 nm.

ESCs were plated one day prior to imaging on a 8-chambered coverglass (VWR Radnor, PA, #155409) pretreated for at least 2 hr with 3.1 µg/mL Laminin-511 (iWaichem Tokyo, Japan #N-892011) at 120,000 cells per chamber. Just prior to imaging, 2i + Lif media was pre-mixed with 50 µg/mL ascorbic acid and a 1:100 dilution of Prolong Live Antifade Reagent (ThermoFisher P36975). If the cells to be imaged also expressed CymRHalox2, 100 nM of JF646 was also added to the media. After a one hour incubation, we added this media to the ESCs to be imaged. When indicated, ESC media was supplemented with 75 µM DRB (Sigma D1916) and incubated for 1 hr prior to image acquisition.

NPCs were plated at least 8 hr prior to imaging on a 8-chambered coverglass pre-treated with poly-D-lysine and laminin at 120,000 cells per chamber. Prior to imaging, N2B27 with FGF basic and EGF was pre-mixed with 50 µg/mL ascorbic acid and a 1:100 dilution of Prolong Live Antifade Reagent. After a one hour incubation, we added this media to the NPCs to be imaged.

Cardiogenic mesodermal cells enriched by FACS for FLK1 and PDGFRα were plated on 8-chambered coverglass precoated with 0.1% gelatin in StemPro-34 (Thermo Fisher #10639–011) supplemented with 2 mM GlutaMax, 50 µg/mL ascorbic acid, 5 ng/mL VEGF, 10 ng/mL FGF basic, and 25 ng/mL FGF10 (R and D Systems #345-FG) and cultured for 24 hr. Just prior to imaging, StemPro-34 media (with the additives listed above) was supplemented with a 1:100 dilution of Prolong Live Antifade Reagent, incubated for one hour, and subsequently added to the cultures for imaging.

For imaging experiments using CymRGFP and TetRtdTom, we captured green and red images by toggling the 488 nm and 561 nm lasers with a zET405/488/561/635 m multi-band pass emission filter in place, respectively. All colors were collected per plane prior to moving to next the plane (i.e. Z1-C1, Z1-C2, Z2-C1, Z2-C2, etc.) Z-planes were spaced 300 nm apart and exposure times were 30 ms. Each z-stack was composed of 21–28 slices and spaced 20 s apart. A single z-stack using this protocol required approximately 1.6 s for completion. Examples of raw and denoised data stacks used for analysis can be found at doi: 10.5281/zenodo.2658814; https://zenodo.org/record/2658814#.XNDLAhNKjyw.

For imaging experiments using CymRHalox2-JF646, TetRGFPx2, abd tdMS2cp-tagRFP-Tx2, we imaged the green and far red channels as above except the the 488 nm and 640 nm lasers were used. After completion of the initial z-stack, a second z-stack was constructed at identical z-positions using the 561 nm laser and a ET525/50 m emission filter to capture tdMS2cp-tagRFP-Tx2 fluorescence. This eliminated bleed-through signal from the JF646 dye during 561 nm excitation allowed by the quad pass emission filter. Exposure times for this second z-stack were 50 ms.

All images were acquired using μManager (Edelstein et al., 2010, RRID:SCR_016865). Imaging data for each condition is composed of a minimum of three imaging sessions, except for cardiogenic mesodermal cultures, in which duplicate differentiations were performed.

Image processing

Images were background subtracted using a dark image, converted to 32-bit, and denoised using NDSafir (Carlton et al., 2010; Kervrann and Boulanger, 2006) with the following settings: ndsafir_priism input_image denoised_image -4d = zt -noise=”poisson’ -iter = 4 -p = 1 -sampling=-1 -adapt = 10 -island = 4 usetmp.

Denoised images were reverted back to 16-bit, fluorescence bleach corrected using exponential fitting and despeckled to remove high-frequency noise using ImageJ (Schindelin et al., 2012; Schneider et al., 2012, RRID:SCR_003070).

Image analysis

Tracking loci

Maximum Z-projections of 3D time series were manually analyzed to identify cuO/CymR and tetO/TetR spots in nuclei and annotate individual loci as doublets (likely two sister chromatids) or singlets. Loci that showed any frames with doublet spots for either channel were not included in downstream analysis. For each Sox2 locus with well-behaved singlets, an ROI was drawn that included the locus location throughout the timecourse (or if the locus became untrackable due to leaving the field of view, the duration of its visibility). In some cases (e.g. NPCs), multiple ROIs were needed to track a single loci because of large-scale movements of the cell nucleus. In these cases, location data were merged together after tracking. For each locus, the 3D location for the cuO/CymR spot and the tetO/TetR spot was tracked within the delimited ROI using TrackMate (Tinevez et al., 2017) and its Laplacian of Gaussian spot detector with a sparse LAP tracker. The following additional settings were used:

  • DO_SUBPIXEL_LOCALIZATION = true

  • RADIUS = 2.5 pixels

  • THRESHOLD = 0

  • DO_MEDIAN_FILTERING = false

  • ALLOW_TRACK_SPLITTING = false

  • ALLOW_TRACK_MERGING = false

  • LINKING_MAX_DISTANCE = 20 pixels for ESCs, MES/40 pixels for NPCs

  • GAP_CLOSING_MAX_DISTANCE = 30 pixels for ESCs, MES/60 pixels for NPCs

  • MAX_FRAME_GAP = 3 frames

  • LINKING_FEATURE_PENALTIES = (QUALITY: 1.0, POSITION_Z: 0.8)

  • GAP_CLOSING_FEATURE_PENALTIES = (QUALITY: 1.0, POSITION_Z: 0.8)

  • TRACK_FILTER = TRACK_DURATION: 10

A Spot Quality Filter was also applied to result in detection of 20% more spots than the number of frames in the time course. This threshold was found to minimize spurious spot detection while also minimizing the loss of bona-fide cuO/tetO localization. In the case where solely the location of the Sox2 promoter was of interest (i.e. for identifying and quantitating Sox2 transcriptional bursts across all cells), cuO/CymR-Halox2 spots were tracked as above except ALLOW_TRACK_MERGING was set to true. This facilitated recording a single track when the Sox2 locus showed two sister chromatids.

TrackMate tracks for each spot were manually inspected, and if multiple tracks existed (due to gaps in the tracking), these were merged through manual curation. Spot positions converted to physical distances using a 0.091 µm pixel size and a 0.3 µm z-step.

Correction for chromatic aberration

We corrected for chromatic aberration by collecting a single z-stack of TetraSpeck fluorescent beads (ThermoFisher #T7279) embedded in 2% agrose using the 488 nm, 561 nm, and 640 nm laser. Exposure time for was 50 ms. Positions of the beads were determined using TrackMate and its Laplacian of Gaussian spot detector with the following additional settings:

  • DO_SUBPIXEL_LOCALIZATION = true

  • RADIUS = 2.5 pixels

  • THRESHOLD = 0

  • DO_MEDIAN_FILTERING = false

  • SPOT_FILTER = QUALITY: 100

Differences between the position of each bead in the green and red as well as green and far-red channel were determined. Based on these data, we calculated linear models for chromatic aberration correction in X, Y, and Z based on position within the field of view. The following corrections were applied to the green channel when being compared to red:

Xcorrected=0.00027Xraw+0.00728
Ycorrected=0.00028Yraw0.00303
Zcorrected=0.00139Zraw0.1954

The following corrections were applied to the green channel when being compared to far-red:

Xcorrected=0.0005Xraw+0.02553
Ycorrected=0.00044Yraw+0.01949
Zcorrected=0.00325Zraw0.15869

Localization precision estimation

Tetraspeck (Thermo Fisher T7279) multicolor fluorescent beads were embedded in 2% agarose and a one hundred frame Z-stack time series was constructed at various laser intensities. The max spot intensity as well as the mean and standard deviation of the nuclear background was estimated from ten nuclei for both cuO/CymR and tetO/TetR using our raw time-lapse data. Bead time series were modified to add background noise using ImageJ to approximate the nuclear background and then denoised as described above. 9–15 beads that showed signal within one standard deviation of that observed for either the cuO/CymR or tetO/TetR spots were tracked using TrackMate and the following additional settings:

  • DO_SUBPIXEL_LOCALIZATION = true

  • RADIUS = 2.5 pixels

  • THRESHOLD = 0

  • DO_MEDIAN_FILTERING = false

A spot filter for spot quality was set manually to only include the top 100 detected spots. The standard deviation of position of each bead was computed in the X, Y, and Z dimensions using a five frame sliding window to generate a distribution of estimated uncertainties.

As an addition measure of localization precision, Sox2-SCR ESCs expressing CymR-GFP and TetR-tdTom were cultured on coverglass as described for live-cell imaging above. Prior to imaging, the growth medium was removed and cells were fixed using 4% PFA in PBS for 5 min at room temperature. Cells were washed once with PBS and imaged in PBS. Two color z-stacks were captured at 72 time points using settings that were identical to live-cell microscopy except that there was no time delay between frames. These images were then processed identically to that used for live-cell microscopy. Spots from 10 to 14 Sox2 loci were tracked across the time course using TrackMate and the following settings:

  • DO_SUBPIXEL_LOCALIZATION = true

  • RADIUS = 2.5 pixels

  • THRESHOLD = 0

  • DO_MEDIAN_FILTERING = false

A spot filter for spot quality was set manually to only include the top 72 detected spots. As with the fluorescent beads, the standard deviation of position for both the cuO and tetO label was computed in the X, Y, and Z dimensions using a five frame sliding window to generate a distribution of estimated uncertainties.

Simulation of 3D distance measurement bias and uncertainty

To estimate the measurement bias of distance measurements, 1000 X, Y, and Z positions were sampled from normal distributions with standard deviations equal to the median values of our localization precision estimates (X = 12 nm, Y = 10 nm, Z = 36 nm for cuO and X = 16 nm, Y = 16 nm, Z = 50 nm for tetO). The means of these distributions were fixed a 0 for cuO and varied over a range for tetO to simulate a range of separation distances. True distance was calculated as the Euclidean distance between points located at the center of the cuO and tetO distributions. Simulated measured distance was taken as the mean of the sampled Euclidean distances.

To estimate the uncertainty of distance measurements, we repeated the analysis above except the number of sampled positions was increased to 50,000. Simulated distance uncertainty was taken as the interquartile range of the simulated measured distances.

Euclidean distance

1D, 2D, and 3D euclidean distances were calculated using the formula:

Distij= v=1nXvi- Xvj2

where i and j represent the cuO/CymR and tetO/TetR spot, respectively, and n the number of dimensions.

Relative displacement

The relative position of spot1 (CymRGFP) with respect to spot2 (TetRtTom) for the vth dimension was calculated as follows:

Xvi^=(Xvi Xvj)

The relative displacement was then calculated as the change is the relative position of spot 1.

Dispt= v=1n(Xvi^(t) Xvi^(t1))2

where t is the current frame and n is the number of dimensions.

Autocorrelaton analysis

Autocorrelation values were calculated according to the formula

Aτ= EDt- μDt+τ- μσ2

where Dt represents distance at time t, τ is the time lag, μ and σ2 are the average and variance of 3D distance measured across the cell population, and E is the expected (i.e. average) value. Confidence intervals were computed by bootstrapping and recalculating Aτ across 1000 simulations to estimate 95% confidence.

Distribution distances and clustering

The distance between 3D distance probability distributions from two cell lines or cell types was computed using earth mover’s distance (EMD). Briefly, the earth mover’s distance is the minimum cost to convert one probability distribution to the other over a defined region. We calculated pairwise EMD for each 3D probability distribution using the R package earthmovdist. Complete-linkage hierachical clustering was then performed to generate a dendrogram.

MS2 signal identification and quantification

3D time-lapse images of tdMS2cp-tagRFP-Tx2 were converted into 2D images by maximum Z projection. For each Sox2 locus considered for analysis, a 20 × 20 pixel region centered on the XY tracking position of the cuO/CymR spot, reflecting the position of the Sox2 promoter region, was analyzed for each frame. If tracking information was missing for a given frame, the position coordinates from the nearest frame were used. This 20 × 20 region was used for parameter estimation for 2D Gaussian fitting using the equation:

fx,y=Ae-x-xo22σx2+ (y-yo)22σy2+C

where A (Gaussian height), xo,yo (location of Gaussian peak), σx2,σy2 (Gaussian variance), and C(offset) are all estimated parameters. Initial estimate of the offset was defined as the median pixel value in the ROI, A was estimated as the maximum pixel value minus the estimated offset, σx2 and σy2 were estimated as 1, and xo,yo was estimated as the location of the brightest pixel in the ROI. These initial estimates were used attempt a Gaussian fit on a 10x10 pixel region centered on the estimated Gaussian position. We constrained the potential Gaussian fit to have a minimum height of 10% above background fluorescence, a fit position of no more than 3 pixels from the estimated position, and a width of no more than 4. Successful Gaussian fits were filtered for likelihood to reflect true MS2 signal using a k-nearest neighbor model trained on manually classified data and 4 parameters of the fit (A, σx2, σy2, and an R2 value). Furthermore, frames were also required to have at least one neighboring frame (± 3 frames) also demonstrate MS2 signal, eliminating high frequency noise. Time points which passed these filter steps were assigned a relative MS2 Signal based on:

Signal=A+CNormalization Factor

were the normalization factor was the median pixel value for the 20 × 20 pixel ROI across all timepoints. For time points that did not pass filter, MS2 signal was taken as the median value of the 20 × 20 ROI for the current frame normalized as above.

Sox2 burst classification

Sox2 burst initiation events were classified as frames positive for MS2 signal (see above) that lack MS2 positive classifications for the preceding three frames. All frames spanning the burst initiation and the last positive MS2 classification prior to the next burst initiation were labeled as one burst event.

Aligned Sox2 burst analysis

To align our MS2 data across all Sox2 bursts, a defined window was sampled for each burst centered on the burst initiation event. We subsequently generated a randomly sampled control comparison for this analysis by randomly shuffling the frames labeled as burst initiation events and repeating the analysis. Mean distances or MS2 signal were then calculated based on relative frame compared to the burst initiation event. Confidence intervals were computed by bootstrapping and recalculating the mean value for each relative frame across 1000 simulations to estimate 95% confidence.

Browser tracks

Unless wiggle files were available as part of the accession, sequencing read archives (SRA) were downloaded from NCBI and reads were aligned to the mm9 mouse genome using Bowtie (Langmead et al., 2009, RRID:SCR_005476) as part of the Galaxy platform (Afgan et al., 2018, RRID:SCR_006281). Sequences were extended by 200 bp and allocated into 25 bp bins to generate wiggle files. HiC data were visualized using JuiceBox (Durand et al., 2016). Browser tracks were visualized on the UCSC Genome browser (Kent et al., 2002, RRID:SCR_005780).

References

  1. 1
  2. 2
    Molecular Biology of the Cell
    1. B Alberts
    2. AD Johnson
    3. J Lewis
    4. D Morgan
    5. M Raff
    6. K Roberts
    7. P Walter
    (2014)
    W. W. Norton & Company.
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19
  20. 20
  21. 21
  22. 22
  23. 23
  24. 24
  25. 25
  26. 26
  27. 27
  28. 28
  29. 29
  30. 30
  31. 31
  32. 32
  33. 33
  34. 34
  35. 35
    Computer control of microscopes using µmanager
    1. A Edelstein
    2. N Amodaj
    3. K Hoover
    4. R Vale
    5. N Stuurman
    (2010)
    Current Protocols in Molecular Biology, Chapter 14, 10.1002/0471142727.mb1420s92, 20890901.
  36. 36
  37. 37
  38. 38
  39. 39
  40. 40
  41. 41
  42. 42
  43. 43
  44. 44
  45. 45
  46. 46
  47. 47
  48. 48
  49. 49
  50. 50
  51. 51
  52. 52
  53. 53
  54. 54
  55. 55
  56. 56
  57. 57
  58. 58
  59. 59
  60. 60
  61. 61
  62. 62
  63. 63
  64. 64
  65. 65
  66. 66
  67. 67
  68. 68
  69. 69
  70. 70
  71. 71
  72. 72
  73. 73
  74. 74
  75. 75
  76. 76
  77. 77
  78. 78
  79. 79
  80. 80
  81. 81
  82. 82
  83. 83
  84. 84
  85. 85
  86. 86
  87. 87
    Sox2 roles in neural stem cells
    1. LH Pevny
    2. SK Nicolis
    (2010)
    The International Journal of Biochemistry & Cell Biology 42:421–424.
    https://doi.org/10.1016/j.biocel.2009.08.018
  88. 88
  89. 89
  90. 90
    A unique chromatin signature uncovers early developmental enhancers in humans
    1. A Rada-Iglesias
    2. R Bajpai
    3. T Swigut
    4. SA Brugmann
    5. RA Flynn
    6. J Wysocka
    (2011)
    Nature, 470, 10.1038/nature09692, 21160473.
  91. 91
  92. 92
  93. 93
  94. 94
  95. 95
  96. 96
  97. 97
  98. 98
  99. 99
  100. 100
  101. 101
  102. 102
  103. 103
  104. 104
  105. 105
  106. 106
  107. 107
  108. 108
  109. 109
  110. 110
  111. 111
  112. 112
  113. 113
  114. 114
  115. 115
  116. 116
  117. 117
  118. 118
  119. 119
    Sox2 regulatory sequences direct expression of a (beta)-geo transgene to telencephalic neural stem cells and precursors of the mouse embryo, revealing regionalization of gene expression in CNS stem cells
    1. MV Zappone
    2. R Galli
    3. R Catena
    4. N Meani
    5. S De Biasi
    6. E Mattei
    7. C Tiveron
    8. AL Vescovi
    9. R Lovell-Badge
    10. S Ottolenghi
    11. SK Nicolis
    (2000)
    Development 127:2367–2382.
  120. 120
  121. 121
  122. 122

Decision letter

  1. Robert H Singer
    Reviewing Editor; Albert Einstein College of Medicine, United States
  2. Kevin Struhl
    Senior Editor; Harvard Medical School, United States
  3. Zhe Liu
    Reviewer; Howard Hughes Medical Institute, Janelia Research Campus, United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "Live-cell imaging reveals enhancer-dependent Sox2 transcription in the absence of enhancer proximity" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Kevin Struhl as the Senior Editor. The following individual involved in review of your submission has agreed to reveal his identity: Zhe Liu (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

The work provides the first precise measurement of enhancer-promoter distances correlated with transcriptional output. Surprisingly, the proximity of the enhancer and promoter was not correlated with the output. This challenges current dogma that these two elements must come together to initiate transcription. The authors propose an activator hub model where factors are concentrated around the promoter in a large volume.

While the reviewers are positive about the work (one even thinks it is a "landmark"), they have a number of concerns, mainly centering in the accuracy of the distance measurements. Since these distances are critical to the argument and since the conclusion is heterodox, confidence in the measurements are essential. For instance, how was chromatic aberration corrected? They suggest additional controls to verify the measurements. An example would be to show the tagging did not affect the looped interactions by comparing 3C interactions between the experimental and wild type cells. Additional suggestions were to improve the text for clarity and accuracy in interpretation.

Please read through the suggestions for improvements and determine whether you can respond adequately within a few months. If so we will entertain a revised manuscript for review.

Reviewer #1:

This manuscript investigates the long held belief that distal enhancer sites must directly contact the promoter site to activate transcription. This required heroic genetic labeling of the endogenous Sox2 promoter, a Sox2 enhancer locus, as well as the messenger RNA being transcribed. They conclude by many analyses that the position separation between enhancer and promoter is not correlated with gene expression in contrast to the expectation of a direct contact between promoter and enhancers. They propose that recent observation of condensates of transcription factors, and or more complex delay models may be at play in the Sox2 locus investigated. This is an experimental tour de force that will prove important, prompt and guide many future experiments. The manuscript warrants publication in eLife. There are questions on the accuracy of the position measurements that should be addressed as a major concern as that will set a standard for how future measurements may be done; however these should be doable within the time frame allowed by the journal for a revision.

A major issue to be resolved is the question of how accurately the chromatin labeling arrays represent the Sox2 promoter and SCR positions. This becomes apparent when comparing the MS2 signal position to the Sox2 promoter marker position in 3 color imaging. The MS2 signal typically appears to be detected far from the Sox2 promoter signal. This may be due to technical reasons (different filter cube, time delay between Sox2/SCR and MS2 stacks) or represent actual spatial separation between the promoter chromatin label and the Sox2 gene position. This is particularly true since a 14kb separation in the deletion mutant appears to result in a typical separation of ~250nm and never below 100nm. The authors should provide a control for the positional accuracy of their chromatin labels with respect to the target sequence, e.g. co-staining of the actual target locus by DNA FISH or dCas9-based chromatin labeling.

Reviewer #2:

In this paper, Alexander and co-workers address the important topic and enhancer-promoter (E-P) contacts using the Sox2 gene in mESCs as a model. While there was a recent E-P live-cell imaging study in Drosophila from the Gregor group, the Gregor system was a bit artificial and genome organization is very different between mammals and flies. The present study by Alexander is therefore very important: To my knowledge, it is the first live-cell imaging study of E-P contacts in mammals. This is important, because Hi-C, which averages over cell populations and only generates a snapshot cannot readibly report on dynamics. Getting at the dynamics can only be achieved with live-cell imaging, which is what Alexander has now accomplished.

Other highlights include a nice general system for tagging DNA loci (though authors need to put plasmids on AddGene), nice controls (e.g. the other cell lines with similar distances and the 111 kb deletion), comparing mESCs and NPCs and the simultaneous MS2-readout to simultaneously look at transcription.

The findings are also surprising and will be of wide interest. I believe there is a strong possibility that this paper will be looked back upon in a couple of years as a landmark paper in the field and I believe it will be of very wide interest.

Nevertheless, I have a series of serious technical concerns, which should be addressed and I believe that authors should do one important control experiment: verify using a "C"-method that the E-P loop is not disrupted. Finally, given the technical concerns – some of which may not be fully addressable – the authors need to more clearly state the limitations of their work in the main text. Also, many imaging details that are crucial, are missing from the Materials and methods.

Activator hub model

In Figure 6H, authors propose an "activator hub model" where a large hub (maybe 200-400 nm?) activates over long distance. This is an interesting model. If it is true that it is so big, presumably many other genes would be inside of it. Are there other other genes within 1 Mb of Sox2 on the same chromosome? Are they ON or OFF and if some of them are OFF, how do they stay OFF if there is a large hub?

If the hub is a 400 nm cube and mouse ES cells are diploid, they should have 2 of these hubs and around 50k genes (since diploid). Using the typical volume of a nucleus (e.g. 8 μm cube), one gets total hub volume 0.128 μm3 and nuclear volume of 512 μm3, corresponding to 12.5 genes inside of the hubs. Is this realistic? Numbers chosen here are a bit random, but the point is that it seems a bit dangerous to have a large hyper-activating hub in the nucleus (like the LLPS studies the authors reference) since it would be likely to randomly contact genes that should be OFF – especially since chromatin moves around as the authors show. If this hub lasts for 10 minutes, how many random genes will bump into it? The nucleus is a pretty crowded environment. Can the authors discuss this a bit more clearly?

New tools to visualize DNA loci should be on AddGene.

In addition to the biological insight, a big impact of this paper will be the new tools the authors develop to insert TetO and CuO sites in the genome. The 2-step modular approach with attP, PhiC31, Bxb1 etc. is clever and the TetO and CuO plasmids will be generally useful. However, I could not find the AddGene Accession codes for these vectors. In the revised manuscript, the authors should deposit these plasmids to AddGene and include the accession numbers in the manuscript. Moreover, the authors should write a brief protocol on how to use the plasmids and attach it to the manuscript. This will greatly increase the impact of the paper and serve as a big positive contribution to the community.

Key control

It is very nice that authors verify that array insertion does not affect Sox2 expression according to qPCR. This is a really important control. However, the missing and equally important control is the verification that the Sox2-SCR looping interaction is not affected. Authors could argue that since SCR is required for expression, the fact that Sox2 qPCR is the same, suggests that looping level is not affected. But since the authors suggest that E-P loops don't directly affect transcription, this is no longer the case. Therefore, an essential (and straightforward) control experiment to do for the revised manuscript is a 3C-qPCR (or another C-type) experiment comparing Sox2-SCR E-P contacts in WT cells, cells with the arrays but without TetR and CymR and cells with arrays and also TetR and CymR.

Localization Precision

I am somewhat skeptical of the localization precision. It seems a bit weird that the X and Y values are so different. Also 10-15 nm is really high precision. It seems almost too good. I worry that even if the authors tried to use beads at lower light intensity, this could bias the calculation. It is also not clear how well a TetraSpeck bead approximates the unknown distribution of in vivo conformations of e.g. an 8 kb array inside a live cell. Is there any way the authors can use the TetO and CuO readouts to estimate the errors? E.g. in fixed cells?

Distance between Promoter and SCR and CuO and TetO arrays

The distance between the Sox2 E and P is quite high (17 kb). I totally get that it is tricky: if you put the arrays too close, they may interfere with function. If you put them too far away, they may not be good reporters and it is not obvious to me what the best distance would be. But given the wide distribution in Figure 2C yellow line, I believe the authors should emphasize a bit more in the main text that this introduces some uncertainty and is an important caveat.

Timescale of E-P loop and time-scale for MS2 appearance

One key thing I was missing was a discussion of the time-scale of E-P loops. E.g. recently there have been papers arguing that CTCF/cohesin loops are either stable or dynamic and it would be nice if the authors could discuss how their observations relate to this (even if they do not directly observe discrete E-P loops). For example, does the Sox2 loop occur inside a CTCF/Cohesin loop and can the authors compare to some of the CTCF/Cohesin timescales?

Along these lines, the analysis in Figure 6 is very important in that it tries to find a correlation between E-P distance and transcription. But although the result is negative, can the authors really exclude that E-P contact is necessary for Sox2 transcription.

Suppose the following scenario: E-P loops form and last for 10 seconds (but duration highly stochastic, sometimes 1 sec sometimes 100 sec). Soon after they break, Sox2 E and P move apart and the distance increases. The E-P loop even when the true distance is <50 nm, will show a broad distribution of distances similar to yellow line in Figure 2C. After E-P contact, Transcription factors, histone modifying enzymes, mediator, Brd4, p300, TBP, SAGA, TFIID and other factors are recruited but sequentially and with delay between each. This takes an unknown amount of time. Then Pol 2 is recruited. Pol 2 pauses for a bit and then begins transcribing. Since the MS2 reporter is 3', there is a very long delay between Pol 2 initiation and MS2/MCP-readout (the authors should calculate the expected time it takes from initiation to MS2 appearance using the estimated Pol II elongation speed and the length of the Sox2 modified gene and report this duration in the main text). For the sake of argument, let's say this process takes 7 min on average, but because of the many steps, each of which is stochastic, the duration is broadly distributed and heavy tailed such that it can take anywhere from 3 min to 15 min (or something like this).

In this scenario with: 1) very transient E-P contact measured using the very high localization uncertainty shown by the yellow line in Figure 2E; 2) highly stochastic and variable duration for in-between steps and 3) long and somewhat variable delay before MS2 appearance since reporter is 3' and 4) E-P contacts only produce transcription burst say 40% of the time. Would the authors really be able to detect a positive correlation using the analysis in Figure 6?

My sense is that the authors could not, though I would be happy to be persuaded otherwise by a careful quantitative analysis. This does not mean that the author's contribution is not highly valuable, but unless they can exclude this possibility, they should state explicitly in the main text or discussion that they cannot exclude that their analysis fails to detect the underlying E-P inducing Sox2 transcription.

Authors kind of sketch this in 6H top panel, but I found the discussion about these limitations unclear and lacking. It is much better to clearly state the limitations.

Encounter definition

Authors include a very nice control cell line, where 111 kb has been deleted between the pairs. This cell line is "always in encounter" in the sense that the CuO and TetO arrays are about as close as they would be in a bona-fide E-P loop. Looking at Figure 2C, it looks like the mean distance is 250 nm and the range is approximately 0-500 nm. That means that perfect E-P co-localization can nevertheless appear as 500 nm at low probability. But in Figure 4E, authors define encounter as 100 nm. If the mean E-P distance during an encounter is 250 nm (Figure 2C), defining the threshold to be 100 nm seems too restrictive.

Obviously, it is very interesting and informative to consider the probability of an encounter during a time window, but given the much larger mean distance for the control E-P loop cell line, 100 nm is too small. I am not sure how best to deal with this but current Figure 4E seems unfair.

One option would be for the authors to clearly state this limitation in the main text and then re-plot Figure 4E for multiple thresholds – e.g. 100, 150, 200, 250, 300, 350 nm. At the very least, they should also consider thresholds a little bigger than the mean E-P distance in the control cell line (yellow line in Figure 2C).

Information about imaging and the microscope

Technical information about the microscope and imaging protocol is extremely important to evaluate the study, but highly lacking.

What was the pixel size?

What were the emission filters?

How many z-stacks and how long exposure times?

What were the time-gaps between z-stacks? What was the physical distance between the z-stack?

I could not understand – did the authors collect all colors per plane and then move to the next plane or did authors do sequential all planes for each color and then acquire next color?

Authors must report duration of z-stacks?

How did authors correct for chromatic aberrations? Authors mention shifting position, but I could not understand what they did.

How did authors align color channels?

How did authors determine 3D positions? Was it PSF-fitting? If so, what was the PSF-model? Did they enforce symmetric XY PSF or allow asymmetric XY-PSF? Did they do MLE or LS fitting?

What were the settings used in TrackMate? Were gaps allowed?

Etc. Etc. Please provide all details in the Materials and methods since they are important.

Reviewer #3:

Large Picture:

A central model in the current understanding of gene regulation is that direct physical interactions between promoter and enhancer are required for transcriptional activation. It is widely believed that long-distance promoter-enhancer communications are realized in the form of chromatin looping. In this manuscript, the authors devise comprehensive live-cell imaging experiments to test this model using Sox2 locus and Sox2 control region (SCR) – a strong long-distance enhancer required for Sox2 expression. Specifically, by incorporating CuO and TetO arrays into Sox2 locus and SCR respectively, authors established a robust molecular imaging system to precisely quantify the physical distance between Sox2 and SCR in the nucleus of single living ES cells. Surprisingly, authors find no evidence supporting Sox2-SCR interactions in comparison with SCR-control loci pairs. And, consistent with DNA-FISH results on HoxD locus (Genes and Dev. 2014. 28: 2778-2791), authors also showed that upon ES cell differentiation, the genomic region containing Sox2 and SCR compacts as the distance between Sox2 and SCR becomes shorter. Most strikingly, author found no temporal correlation between Sox2 transcription bursting and the proximity of the SCR to Sox2 locus. These emerging results began to challenge the central model regarding DNA looping as the primary mechanism that mediates long-distance enhancer-promoter communications.

I found that the experiments done by authors are very well controlled and the results are timely for the field to move forward in search for alternative mechanisms. I would like to support the publication of the manuscript.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Live-cell imaging reveals enhancer-dependent Sox2 transcription in the absence of enhancer proximity" for further consideration at eLife. Your revised article has been favorably evaluated by Kevin Struhl (Senior Editor), a Reviewing Editor, and three reviewers.

The manuscript is acceptable but there are some remaining issues that need to be addressed. In short, the reviewers would like to see some additional comments regarding the lateral resolution and the inclusion of some of the raw data.

Reviewer #1:

I think given the time frame the authors appropriately addressed the concerns raised.

The authors should provide some of the raw uncorrected video.

Reviewer #2:

We are satisfied with the revisions. This was a valiant effort, and the authors satisfied most of the requests. We believe that manuscript is vastly enriched.

One remaining issue it the claimed lateral resolution. Here the authors use a published method to estimate it that is providing a result that seems out of scale compared to what is typically achieved. I could not pinpoint what is wrong and therefore cannot comment more. Perhaps one way for the authors to explain their number would be to comment and provide their own rational comparing this value to other papers and explain how they improved it so much. Also it would be important to comment on the validity of the tool they use to localize a locus. This is important since other papers might use similar methods and will not necessarily achieve such results.

Because the lateral resolution issue will be a major problem to other labs trying to reproduce the data I would suggest that the authors prepare a set of raw videos that are representative of the dataset and their quantification of it so that others can use it as a benchmarking tool.

Reviewer #3:

This was a strong paper and, in the revision, authors have improved the manuscript more and satisfactorily addressed my concerns. I would support the publication of the paper in eLife.

https://doi.org/10.7554/eLife.41769.053

Author response

Please read through the suggestions for improvements and determine whether you can respond adequately within a few months. If so we will entertain a revised manuscript for review.

Reviewer #1:

This manuscript investigates the long held belief that distal enhancer sites must directly contact the promoter site to activate transcription. This required heroic genetic labeling of the endogenous Sox2 promoter, a Sox2 enhancer locus, as well as the messenger RNA being transcribed. They conclude by many analyses that the position separation between enhancer and promoter is not correlated with gene expression in contrast to the expectation of a direct contact between promoter and enhancers. They propose that recent observation of condensates of transcription factors, and or more complex delay models may be at play in the Sox2 locus investigated. This is an experimental tour de force that will prove important, prompt and guide many future experiments. The manuscript warrants publication in eLife. There are questions on the accuracy of the position measurements that should be addressed as a major concern as that will set a standard for how future measurements may be done; however these should be doable within the time frame allowed by the journal for a revision.

A major issue to be resolved is the question of how accurately the chromatin labeling arrays represent the Sox2 promoter and SCR positions. This becomes apparent when comparing the MS2 signal position to the Sox2 promoter marker position in 3 color imaging. The MS2 signal typically appears to be detected far from the Sox2 promoter signal. This may be due to technical reasons (different filter cube, time delay between Sox2/SCR and MS2 stacks) or represent actual spatial separation between the promoter chromatin label and the Sox2 gene position. This is particularly true since a 14kb separation in the deletion mutant appears to result in a typical separation of ~250nm and never below 100nm. The authors should provide a control for the positional accuracy of their chromatin labels with respect to the target sequence, e.g. co-staining of the actual target locus by DNA FISH or dCas9-based chromatin labeling.

We previously performed DNA FISH for the Sox2 locus using standard protocols and bacterial artificial chromosome (BAC) probes to validate the position of our repressor arrays. However, the reviewer’s suggested experiment is significantly more challenging because the regions being probed are only kilobases in size. We have attempted the DNA FISH experiments proposed by the reviewer in collaboration with the Huang lab, who have significant DNA FISH expertise, but we have thus far been unsuccessful in generating sufficient signal-to-noise for the small probes that this experiment demands. We expect the time necessary to optimize and troubleshoot the proposed experiments would push significantly beyond the window suggested for timely resubmission. Similarly, the reviewer’s suggestion of using dCas9 to label the Sox2 promoter or SCR is not feasible given the time constraints. Because the regions of interest are non-repetitive, 26-36 individual sgRNAs would need to be stably expressed in our ESC lines. These assays require extensive optimization and would not be possible to complete by the suggested deadline for resubmission. However, a number of the reviewers concerns can be addressed/explained without additional experiments.

The referenced discrepancy between the Sox2 promoter position and MS2 transcriptional bursts is likely to be explained by how the imaging was performed. Due to the presence of 3 distinct fluorophores in these cells and spectral overlap between tagRFP-T and JF646, fluorescence data for the GFP and JF646 channels were captured by first sweeping through z-positions with a multi-bandpass zET405/488/561/635m emission filter and toggling the 488nm and 640nm lasers at each z-plane to build up a 2-color z-stack for the position labels (i.e. cuO and tetO). Once this initial z-stack was completed, a distinct emission filter (ET610/60m) was placed in the light path, and an additional z-stack at identical z-positions was collected using the 561nm laser to capture tagRFP-T fluorescence. This optical configuration prevented bleedthrough from the JF646 fluorescence into the tagRFP-T images. However, this imaging setup resulted in substantial delays (~ 5 second) between measuring tagRFP-T fluorescence and GFP/JF646 for a given z-plane. Furthermore, the change in emission filter modifies the light path for tagRFP-T images as compared to GFP/JF646. Together, these factors call for caution in directly comparing the precise positional information gleaned from an MS2cp-tagRFP-T spot and, for instance, cuO/CymRHalo, though they are sufficiently accurate to constrain the region of the nucleus in which we probe for transcriptional bursts. These technical considerations are likely major contributors to the differences pointed out of the reviewer.

The central point of the reviewer’s concern is that there is some uncertainty regarding how well our labels report on the precise positions of the relevant genomic regions (e.g. tetO on the SCR and cuO on the Sox2 promoter). The most critical issue is how well the distances we measure relate to actual genomic separations of the probed regions. To address this consideration, we have developed and reported data for an appropriate control, the Sox2-del-SCR cell line. The 3D distances measured from this cell line support that our experimental setup can detect differences between the Sox2 locus and a “constitutively engaged” control. It also provides a measure of how closely the distance of our genetic labels (~14 kb combined from the enhancer and promoter) report on a configuration when the Sox2/SCR regions are in constitutive proximity (0 kb separation in the Sox2-del-SCR cell line and distance theoretically limited only by our localization precision). Thus, the separation distance for the Sox2-del-SCR ESC line gets at the underlying question raised by the reviewer. While the average separation value of ~250 nm in this line may appear large, we note that a study using CRISPR-Sirius to label repeats on human chromosome 19 report that the separation distance between two loci 4.6 kb apart demonstrated a wide range as well (20-350 nm, Ma et al., 2017, bioRxiv). It is true that due to the genetic distance between the cuO/tetO labels and the regions of interest (Sox2/SCR), our positional uncertainty in Sox2/SCR position is greater than that suggested by our localization precision (also discussed in response to reviewer 2, major comment 5). We have added text in the manuscript to better highlight these limitations (subsection “Visualization of the Sox2 Region in ESCs Reveals Minimal Evidence for Sox2/SCR Interactions”. However, these considerations do not compromise the major conclusions of the paper: 1) that the Sox2-SCR label pair shows no bias to proximity compared to equally-spaced controls and 2) that transcription show no bias towards Sox2-SCR proximity compared to non-transcribing time points.

Reviewer #2:

In this paper, Alexander and co-workers address the important topic and enhancer-promoter (E-P) contacts using the Sox2 gene in mESCs as a model. While there was a recent E-P live-cell imaging study in Drosophila from the Gregor group, the Gregor system was a bit artificial and genome organization is very different between mammals and flies. The present study by Alexander is therefore very important: To my knowledge, it is the first live-cell imaging study of E-P contacts in mammals. This is important, because Hi-C, which averages over cell populations and only generates a snapshot cannot readibly report on dynamics. Getting at the dynamics can only be achieved with live-cell imaging, which is what Alexander has now accomplished.

Other highlights include a nice general system for tagging DNA loci (though authors need to put plasmids on AddGene), nice controls (e.g. the other cell lines with similar distances and the 111 kb deletion), comparing mESCs and NPCs and the simultaneous MS2-readout to simultaneously look at transcription.

The findings are also surprising and will be of wide interest. I believe there is a strong possibility that this paper will be looked back upon in a couple of years as a landmark paper in the field and I believe it will be of very wide interest.

Nevertheless, I have a series of serious technical concerns, which should be addressed and I believe that authors should do one important control experiment: verify using a "C"-method that the E-P loop is not disrupted. Finally, given the technical concerns – some of which may not be fully addressable – the authors need to more clearly state the limitations of their work in the main text. Also, many imaging details that are crucial, are missing from the Materials and methods.

Activator hub model

In Figure 6H, authors propose an "activator hub model" where a large hub (maybe 200-400 nm?) activates over long distance. This is an interesting model. If it is true that it is so big, presumably many other genes would be inside of it. Are there other other genes within 1 Mb of Sox2 on the same chromosome? Are they ON or OFF and if some of them are OFF, how do they stay OFF if there is a large hub?

If the hub is a 400 nm cube and mouse ES cells are diploid, they should have 2 of these hubs and around 50k genes (since diploid). Using the typical volume of a nucleus (e.g. 8 μm cube), one gets total hub volume 0.128 μm3 and nuclear volume of 512 μm3, corresponding to 12.5 genes inside of the hubs. Is this realistic? Numbers chosen here are a bit random, but the point is that it seems a bit dangerous to have a large hyper-activating hub in the nucleus (like the LLPS studies the authors reference) since it would be likely to randomly contact genes that should be OFF – especially since chromatin moves around as the authors show. If this hub lasts for 10 minutes, how many random genes will bump into it? The nucleus is a pretty crowded environment. Can the authors discuss this a bit more clearly?

We agree with the reviewer that the “activator hub model” leaves many unanswered questions. Perhaps most important, as the reviewer mentions, it is unclear how specificity in regulation would be achieved by such a mechanism. In addition, how long-lived these hubs persist and what factors would be involved are also important unknowns. We do not have good answers to these questions. It could be that additional binding events occur with specificity at the Sox2 promoter and are essential to achieve regulated activation (i.e. the hub is permissive for activation). The reviewer’s concern that many genes could be spatially nearby and in danger of being non-specifically activated is reasonable. However, this scenario may be reduced by Sox2’s isolated genomic context. In mice, Sox2’s nearest protein-coding gene neighbors are ~570kb and 1.1Mb away in the centromeric and telomeric directions, respectively. Perhaps a hub mechanism is restricted to genes that are isolated within the genome. We don’t want to speculate too broadly in the text about all the factors of this model given that its is merely a hypothesis (for which we have no affirmatory data ourselves) and there are other potential models that are consistent with our observations. We have added some text to the Discussion that attempts to frame some of the important open questions in the hub model that the reviewer has raised (fourth paragraph).

Of interest, we have begun to investigate this mechanism by visualizing the mediator component Med1 using Med1-GFP reagents from Sabari et al., 2018. We do see several large (> 500 nm) and persistent (tens of minutes) aggregates of Med1-GFP fluorescence in the nucleus. Our very preliminary data suggests that these large aggregates are not enriched at the Sox2 locus, regardless of transcription status. Thus, it does not appear that Sox2 is activated by a very large hub of Mediator based on these findings. However, this is analysis for a single factor, and recent studies have suggested activators upstream (i.e. Brd4) and downstream (i.e. RNAP) of Mediator have this capacity as well. It will be interesting to similarly probe these other factors to determine if SCR is likely to communicate with Sox2 via local concentration of activator proteins. However, to date, the “hub” model for SCR function is unvalidated.

New tools to visualize DNA loci should be on AddGene.

In addition to the biological insight, a big impact of this paper will be the new tools the authors develop to insert TetO and CuO sites in the genome. The 2-step modular approach with attP, PhiC31, Bxb1 etc. is clever and the TetO and CuO plasmids will be generally useful. However, I could not find the AddGene Accession codes for these vectors. In the revised manuscript, the authors should deposit these plasmids to AddGene and include the accession numbers in the manuscript. Moreover, the authors should write a brief protocol on how to use the plasmids and attach it to the manuscript. This will greatly increase the impact of the paper and serve as a big positive contribution to the community.

We have deposited key plasmids for cuO and tetO targeting and CymR/TetR fusions on addGene. A detailed protocol for using the attP system to target the cuO and tetO arrays to the mouse genome in embryonic stem cells can be access on addGene along with these plasmids. This protocol has also been added as Supplementary File 1.

Key control

It is very nice that authors verify that array insertion does not affect Sox2 expression according to qPCR. This is a really important control. However, the missing and equally important control is the verification that the Sox2-SCR looping interaction is not affected. Authors could argue that since SCR is required for expression, the fact that Sox2 qPCR is the same, suggests that looping level is not affected. But since the authors suggest that E-P loops don't directly affect transcription, this is no longer the case. Therefore, an essential (and straightforward) control experiment to do for the revised manuscript is a 3C-qPCR (or another C-type) experiment comparing Sox2-SCR E-P contacts in WT cells, cells with the arrays but without TetR and CymR and cells with arrays and also TetR and CymR.

We agree with the reviewer that this is an important control to include in our study. Therefore, we collaborated with the laboratory of Yin Shen, who have experience studying 3D contacts of the Sox2 locus in embryonic stem cells using 3C-derivatives. With their help, we have included 4C analysis of Sox2 promoter contacts in unmodified 129/Cast ESCs, ESCs with the cuO and tetO labels integrated adjacent to the Sox2 promoter and SCR, respectively, and the cuO- and tetO-labeled cell line above that also expresses CymR-GFP and TetR-tdTom. We find that these modified cell lines still show clear evidence of the enriched Sox2-SCR contacts that have been previously described and that are present in the unmodified control. Furthermore, by using allele-specific polymorphisms within the SCR region, we find 4C signal at the SCR does not have allelic bias in our modified cell lines. The modified 129 allele contributes approximately half of the detected contacts between Sox2 and SCR in our cell lines. These data demonstrate that Sox2-SCR contacts are not impacted in the cell lines used in to our study. These data have been incorporated into a new supplemental figure, Figure 1—figure supplement 3.

Localization Precision

I am somewhat skeptical of the localization precision. It seems a bit weird that the X and Y values are so different. Also 10-15 nm is really high precision. It seems almost too good. I worry that even if the authors tried to use beads at lower light intensity, this could bias the calculation. It is also not clear how well a TetraSpeck bead approximates the unknown distribution of in vivo conformations of e.g. an 8 kb array inside a live cell. Is there any way the authors can use the TetO and CuO readouts to estimate the errors? E.g. in fixed cells?

We have performed localization analysis of fixed cells as the reviewer suggests to determine localization precision in a cellular context at the fluorescent levels achievable for our experiments. Briefly, Sox2-SCR ESCs were fixed in 4% paraformaldehyde for 5 minutes and subsequently imaged using the same microscopy setup and imaging conditions as live-cell microscopy. Images were denoised and processed as described for our live-cell datasets. Subsequently, 10-14 loci were tracked for 72 frames, and position uncertainty was estimated by calculating the standard deviation of positions in the X, Y, and Z dimensions for blocks of 5 consecutive measurements. This windowed approach helps minimize position uncertainty caused by stage drift throughout the imaging period. These analyses demonstrate the values reported using the fluorescent bead method may underestimate accuracy, as the median uncertainty (i.e. standard deviation) improved for all dimensions when using fixed cells. The fixed cell analysis may improve our localization precision due to residual local diffusion experienced by beads confined in a 2% agarose gel. See author response image 1.

Author response image 1

Thus, these new analyses corroborate the reported precision values of position localization and suggest the bead values may be conservative.

Distance between Promoter and SCR and CuO and TetO arrays

The distance between the Sox2 E and P is quite high (17 kb). I totally get that it is tricky: if you put the arrays too close, they may interfere with function. If you put them too far away, they may not be good reporters and it is not obvious to me what the best distance would be. But given the wide distribution in Figure 2C yellow line, I believe the authors should emphasize a bit more in the main text that this introduces some uncertainty and is an important caveat.

We agree that this is a confounding factor that we don’t emphasize enough in the original manuscript. We have added language in the main text that highlights this source of uncertainty (subsection “Visualization of the Sox2 Region in ESCs Reveals Minimal Evidence for Sox2/SCR Interactions”).

Timescale of E-P loop and time-scale for MS2 appearance

One key thing I was missing was a discussion of the time-scale of E-P loops. E.g. recently there have been papers arguing that CTCF/cohesin loops are either stable or dynamic and it would be nice if the authors could discuss how their observations relate to this (even if they do not directly observe discrete E-P loops). For example, does the Sox2 loop occur inside a CTCF/Cohesin loop and can the authors compare to some of the CTCF/Cohesin timescales?

We feel a discussion of E-P looping time scales would be problematic in the current paper because our data does not provide robust insights regarding individual enhancer-promoter interactions. Thus, any discussion of these features would be based solely on the literature the reviewer mentions or require substantial speculation on our part. For instance, how long-lived might Sox2-SCR contacts be based on our data? This is difficult to say given that identifying time periods of interaction/contacts in our data has not been possible. Given these challenges (and the surprising nature of our observations), we have focused our discussion to features of the locus that we can directly measure (e.g. proximity).

Along these lines, the analysis in Figure 6 is very important in that it tries to find a correlation between E-P distance and transcription. But although the result is negative, can the authors really exclude that E-P contact is necessary for Sox2 transcription.

Suppose the following scenario: E-P loops form and last for 10 seconds (but duration highly stochastic, sometimes 1 sec sometimes 100 sec). Soon after they break, Sox2 E and P move apart and the distance increases. The E-P loop even when the true distance is <50 nm, will show a broad distribution of distances similar to yellow line in Figure 2C. After E-P contact, Transcription factors, histone modifying enzymes, mediator, Brd4, p300, TBP, SAGA, TFIID and other factors are recruited but sequentially and with delay between each. This takes an unknown amount of time. Then Pol 2 is recruited. Pol 2 pauses for a bit and then begins transcribing. Since the MS2 reporter is 3', there is a very long delay between Pol 2 initiation and MS2/MCP-readout (the authors should calculate the expected time it takes from initiation to MS2 appearance using the estimated Pol II elongation speed and the length of the Sox2 modified gene and report this duration in the main text). For the sake of argument, let's say this process takes 7 min on average, but because of the many steps, each of which is stochastic, the duration is broadly distributed and heavy tailed such that it can take anywhere from 3 min to 15 min (or something like this).

In this scenario with: 1) very transient E-P contact measured using the very high localization uncertainty shown by the yellow line in Figure 2E; 2) highly stochastic and variable duration for in-between steps and 3) long and somewhat variable delay before MS2 appearance since reporter is 3' and 4) E-P contacts only produce transcription burst say 40% of the time. Would the authors really be able to detect a positive correlation using the analysis in Figure 6?

My sense is that the authors could not, though I would be happy to be persuaded otherwise by a careful quantitative analysis. This does not mean that the author's contribution is not highly valuable, but unless they can exclude this possibility, they should state explicitly in the main text or discussion that they cannot exclude that their analysis fails to detect the underlying E-P inducing Sox2 transcription.

Authors kind of sketch this in 6H top panel, but I found the discussion about these limitations unclear and lacking. It is much better to clearly state the limitations.

It is difficult for our data for formally exclude such scenarios, because of the uncertainty regarding critical parameters in the reviewer’s hypothetical. For instance, depending on how many steps exist between E-P engagement and how long-lived (and variable) these steps are, such a model may be reconcilable with our observations. However, we believe that by orienting the community towards these types of models, our observations will greatly inform the conversation regarding enhancer mechanism of action. Our data provides the strongest evidence against a tight temporal coupling between E-P engagement and transcriptional activity. Indeed, this simple model is supported by the only other live-cell imaging study of enhancer-promoter communication (Chen et al., 2018), which demonstrates robust and immediate changes in distance upon transcription. Thus, it is important that our data suggest such a simple relationship between E-P contacts and transcription is unlikely to explain Sox2 regulation. We are careful not to exclude the possibility that E-P contacts are involved in some capacity. Instead we emphasize that enhancer proximity (a parameter we can directly measure) do not correlate with transcription in time. Our data argue against a short, defined temporal lag between EP interactions and transcription (Figure 6E). We cannot rule out a very long or variable time lag between EP contacts and transcription from our analysis. We have added text within the Discussion (second paragraph) to expand on the reviewer’s comment and clarify how enhancer-promoter contacts could be involved in directing Sox2 transcription.

Encounter definition

Authors include a very nice control cell line, where 111 kb has been deleted between the pairs. This cell line is "always in encounter" in the sense that the CuO and TetO arrays are about as close as they would be in a bona-fide E-P loop. Looking at Figure 2C, it looks like the mean distance is 250 nm and the range is approximately 0-500 nm. That means that perfect E-P co-localization can nevertheless appear as 500 nm at low probability. But in Figure 4E, authors define encounter as 100 nm. If the mean E-P distance during an encounter is 250 nm (Figure 2C), defining the threshold to be 100 nm seems too restrictive.

Obviously, it is very interesting and informative to consider the probability of an encounter during a time window, but given the much larger mean distance for the control E-P loop cell line, 100 nm is too small. I am not sure how best to deal with this but current Figure 4E seems unfair.

One option would be for the authors to clearly state this limitation in the main text and then re-plot Figure 4E for multiple thresholds – e.g. 100, 150, 200, 250, 300, 350 nm. At the very least, they should also consider thresholds a little bigger than the mean E-P distance in the control cell line (yellow line in Figure 2C).

The purpose of this analysis is to explore how the slow rate of chromosomal conformation turnover observed at the Sox2 locus would affect the availability of two chromosomal loci for specific interactions or encounters. The reviewer is correct that this is perhaps most interesting when thinking about an enhancer-promoter pair, but we are not explicitly testing the interaction frequency of the Sox2 promoter and SCR element in this analysis.

This is because, as stated above, it has been difficult to identify individual E-P contacts from our data. Given this limitation, we have instead focused on how the observed dynamics of chromatin influence the encounter frequency of two chromosomal loci generally. In this context, we are interested in the encounter frequency of the tetO and cuO labels themselves rather than using these labels to report on Sox2/SCR encounter frequency. When considering the cuO and tetO label positions themselves, our uncertainty in their positions approaches our localization precision reported in Figure 2—figure supplement 2. The reviewer is correct that threshold for what we label an encounter is arbitrary, and the dependence that encounter frequency has on initial conformation should be robust to the selection of this threshold. We have added clarifying text for this section (subsection “Slow Sox2 Locus Conformation Dynamics Lead to Limited Exploration and Variable Enhancer Encounters”) in an attempt to better frame this analysis and have added the reviewer’s suggested analysis of multiple thresholds for each cuO/tetO label pair (Figure 4E). We have also included this analysis for the Control-Control and SCR-Control cell lines. We observed a consistent trend across label pairs and threshold values. See author response image 2.

Author response image 2

Information about imaging and the microscope

Technical information about the microscope and imaging protocol is extremely important to evaluate the study, but highly lacking.

We have added additional details in the Materials and methods to include the important imaging details requested (sections Live-Cell Microscopy, Image Processing, and Image Analysis).

What was the pixel size?

91nm

What were the emission filters?

How many z-stacks and how long exposure times?

What were the time-gaps between z-stacks? What was the physical distance between the z-stack?

cuO/tetO: 30ms exposures, 300nm between slices, 21-28 slices in z-stack, 20s between time points

cuO/tetO/MS2: 30ms exposure (cuO/tetO) and 50ms exposure (MS2), 300nm between slices, 28-30 slices in z-stack, 30s between time points

I could not understand – did the authors collect all colors per plane and then move to the next plane or did authors do sequential all planes for each color and then acquire next color?

cuO/tetO: All colors were collected per plane prior to moving to next plane. That is Z1-C1, Z1-C2, Z2-C1, Z2-C2, etc..

cuO/tetO/MS2: Green and Far-red colors collected per plane prior to moving to next plane. Red (MS2) was then collected for each plane in second z-stack. That is Z1-C1, Z1-C3, Z2-C1, Z2-C3, …, Zlast-C1, Zlast-C3, Z1-C2, Z2-C2, …, Zlast-C2

Authors must report duration of z-stacks?

cuO/tetO: A single z-stack with 2 color imaging at 30ms exposures is completed in 1.63s.

How did authors correct for chromatic aberrations? Authors mention shifting position, but I could not understand what they did.

Chromatic aberration was a common concern from all reviewers. Thus, we have provided more information regarding how we adjusted our analysis to account for chromatic aberration below. We have also provided additional details in the Materials and methods section of the resubmitted manuscript.

We corrected for chromatic aberration by collecting a single z-stack of TetraSpeck fluorescent beads (ThermoFisher #T7279) embedded in 2% agrose using the 488 nm, 561 nm, and 640 nm laser. Positions of the beads were determined using TrackMate using the Laplacian of Gaussian spot detector. We then visualized these differences. In the plots in Author response image 3, the y-axis shows the difference between positions of the same bead in the red vs. green channel. The x-axis shows the position of the bead within the field of view (X and Y) or within the Z-stack (Z).

Author response image 3

In most cases, we see the differences between red and green positions do not change much with position (the slope of the fit line is ~0), in which case the y-intercept gives the average offset due to chromatic aberration. From this, we can quickly see that chromatic aberration is most severe in the Z dimension. However, in some cases, we do observe position dependent effects. These were mostly found for dimensional shifts dependent on the bead location in that dimension (chromatic shift in X direction dependent on X position, etc.). Thus, we utilized the following linear models to apply a chromatic correction across our data.

Correction of X position

corrected_green_position (um) = (0.00027 * green_X_position (um) + 0.00728)

Correction of Y position

corrected_green_position (um) = (0.00028 * green_Y_position (um) – 0.00303)

Correction of Z position

corrected_green_position (um) = (-0.00139 * green_Z_position (um) – 0.1954)

Our data also allows us to perform a sanity check for the effectiveness of our chromatic aberration corrections. cuO-tetO distances in 1D space (X distance, Y distance, and Z distance) in an ideal system (no chromatic aberration) are expected to be normally distributed with a mean of 0. Thus, we can look to see if our corrections bring our measured cuO-tetO distance closer to this ideal. This is assessed in Author response image 4.

Author response image 4

These corrections do well in recentering the data towards 0, validating our corrections.

Green and Far-Red Position Difference

We performed a similar analysis to determine the chromatic aberration between the green and far-red channels utilized for CymR-Halox2 and TetR-GFPx2 simultaneous imaging, Author response image 5.

Author response image 5

As before, we fit linear models for each dimension to correct the green position for chromatic aberration relative to far-red.

Correction of X position

corrected_green_position (um) = (-0.0005 * green_X_position (um) + 0.02553)

Correction of Y position

corrected_green_position (um) = (-0.00044 * green_Y_position (um) + 0.01949)

Correction of Z position

corrected_green_position (um) = (-0.00325 * green_Z_position (um) – 0.15869)

We also evaluate how our corrected values change the calculated values for X, Y, and Z distances in Author response image 6.

Author response image 6

Again, our corrections shift the distributions towards 0. We note these corrections are not as successful in eliminating deviations from 0 as the corrections applied to the CymRGFP/ TetR-tdTom datasets. This may derive from a larger stochastic deviaton from zero in the CymR-Halox2/TetR-GFPx2 dataset, due to the lower number of measurements included.

CymR-Halox2/TetR-GFPx2: (34170)

CymR-GFP/TetR-tdTom: (91962)

As an alternative method for chromatic aberration correction, we can apply a correction across the dataset to force the distances in X, Y, and Z to be centered at zero. Applying this correction to our data does not change any of the findings reported in the manuscript.

How did authors align color channels?

No additional alignment of color channels was performed except the correction applied for chromatic aberration. The channels used to calculate cuO and tetO positions (green and red/far-red) use the same filter and dichroic mirror and so have identical optical paths. Distinct fluorescence images are captured by toggling the laser used as input.

How did authors determine 3D positions? Was it PSF-fitting? If so, what was the PSF-model? Did they enforce symmetric XY PSF or allow asymmetric XY-PSF? Did they do MLE or LS fitting?

We used the Laplacian of Gaussian detector available from TrackMate with sub-pixel localization enabled. From TrackMate v3.7.0: This detector applies a LoG (Laplacian of Gaussian) filter to the image, with a σ suited to the blob estimated size. Calculations are made in Fourier space. The maxima in the filtered image are searched for, and maxima too close from each other are suppressed. A quadratic fitting scheme allows to do sub-pixel localization.

What were the settings used in TrackMate? Were gaps allowed?

We did allow gap closing of no more than 3 frames in the assembly of tracks. We have added this and other details regarding the TrackMate settings used in the Materials and methods section Image Analysis.

[Editors' note: further revisions were requested prior to acceptance, as described below.]

The manuscript is acceptable but there are some remaining issues that need to be addressed. In short, the reviewers would like to see some additional comments regarding the lateral resolution and the inclusion of some of the raw data.

We are pleased that the reviewer was impressed with the precision of our measurements. We took a lot of effort in both the cell line generation (where the appropriate level of repressor expression was important in getting the best signal-to-noise), during the imaging (where the rapid piezo-controlled z drive and triggered acquisition gave us the needed speed for a rapid 3D acquisition for accurate measurement of loci position), and in our data analysis platform—where the same Trackmate algorithm that is used for single-particle tracking (Tinevez et al., 2017) performed well for assaying loci position. We have explained each of these points in our Materials and methods and also include several raw and denoised data stacks (deposited in the Zenodo data repository doi: 10.5281/zenodo.2658814 https://zenodo.org/record/2658814#.XNDLAhNKjyw) so the readers can get a sense for the quality of our raw data and so can use this to replicate our full analysis pipeline.

We chose not to specifically discuss why our data is better than what is typically achieved by others in the main text, because although the quality of our analysis may be better than some other papers in the field, it is certainly not unprecedented for tracking chromosomal loci, where several previous papers have achieved as good or better precision as our work:

40 nm precision in 3-dimensions for lacO:lacI-GFP, Marshall et al., 1997

15-30 nm precision in x, y, and z for lacO:lacI-GFP and tetO:tetR-mCheery, PMID: 29296501

25 nm precision in 3-dimensions for lacO:lacI-GFP, PMID: 27410730

As with these other reports, we were able to achieve this precision despite using standard fluorescence acquisition by using the Gaussian distribution of photons from each label collected by the camera to determine the center of fluorescence with subpixel precision. Thus, we are doing super-resolution localization in a manner similar to that performed for STORM/PALM, where precisions as high as 5 nm have been reported (PMID: 16028892), and 10-75 nm resolution in XY and Z is common for single-molecules (PMID: 26546293).

https://doi.org/10.7554/eLife.41769.054

Article and author information

Author details

  1. Jeffrey M Alexander

    Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2258-5738
  2. Juan Guan

    Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    Contribution
    Software, Methodology, Writing—review and editing
    Competing interests
    No competing interests declared
  3. Bingkun Li

    Institute for Human Genetics, University of California, San Francisco, San Francisco, United States
    Contribution
    Formal analysis, Visualization, Writing—review and editing
    Competing interests
    No competing interests declared
  4. Lenka Maliskova

    Institute for Human Genetics, University of California, San Francisco, San Francisco, United States
    Contribution
    Investigation, Writing—review and editing
    Competing interests
    No competing interests declared
  5. Michael Song

    1. Institute for Human Genetics, University of California, San Francisco, San Francisco, United States
    2. Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, United States
    Contribution
    Formal analysis, Investigation, Visualization, Writing—review and editing
    Competing interests
    No competing interests declared
  6. Yin Shen

    1. Institute for Human Genetics, University of California, San Francisco, San Francisco, United States
    2. Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, San Francisco, United States
    3. Department of Neurology, University of California, San Francisco, San Francisco, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Writing—review and editing
    Competing interests
    No competing interests declared
  7. Bo Huang

    1. Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
    2. Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    3. Chan Zuckerberg Biohub, San Francisco, United States
    Contribution
    Supervision, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1704-4141
  8. Stavros Lomvardas

    1. Department of Biochemistry and Molecular Biophysics, Columbia University, New York City, United States
    2. Mortimer B Zuckerman Mind Brain and Behavior Institute, Columbia University, New York City, United States
    Contribution
    Supervision, Funding acquisition, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7668-3026
  9. Orion D Weiner

    1. Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    2. Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Writing—review and editing
    For correspondence
    orion.weiner@ucsf.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1778-6543

Funding

American Heart Association (16POST309100006)

  • Jeffrey M Alexander

National Institute of General Medical Sciences (R35GM118167)

  • Orion D. Weiner

National Institute on Deafness and Other Communication Disorders (R01DC013560)

  • Stavros Lomvardas

National Institute of Biomedical Imaging and Bioengineering (R21EB022787)

  • Orion D. Weiner

National Institute of Biomedical Imaging and Bioengineering (R21EB021453)

  • Bo Huang

W. M. Keck Foundation (Medical Research Grant)

  • Bo Huang

National Human Genome Research Institute (R21HG010065)

  • Yin Shen

National Human Genome Research Institute (UM1HG009402)

  • Yin Shen

National Institute of General Medical Sciences (T32GM007175)

  • Michael Song

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Elphege Nora, Geoffrey Fudenberg, Brian Black, and members of the Lomvardas and Weiner labs for helpful discussion; Elphege Nora, Benoit Bruneau, and Kirstin Meyer for a critical reading of the manuscript; Lena Bengtsson for experimental help and technical assistance; and Edith Heard, Patrick Devine, Feng Zhang, Elphege Nora, Michele Calos, Robert Singer, Philippe Soriano, Barbara Panning, Ali Brivanlou and Luke Lavis for helpful reagents. This work was supported by an American Heart Association Postdoctoral Fellowship (#16POST309100006, JMA); NIH Grants R21EB022787 (ODW), R35GM118167 (ODW), R01DC013560 (SL), T32GM007175 (MS), R21HG010065 (YS), UM1HG009402 (YS), and R21EB021453 (BH); and the WM Keck Foundation Medical Research Grant (BH). BH is a Chan Zuckerberg Biohub Investigator.

Senior Editor

  1. Kevin Struhl, Harvard Medical School, United States

Reviewing Editor

  1. Robert H Singer, Albert Einstein College of Medicine, United States

Reviewer

  1. Zhe Liu, Howard Hughes Medical Institute, Janelia Research Campus, United States

Publication history

  1. Received: September 6, 2018
  2. Accepted: May 8, 2019
  3. Version of Record published: May 24, 2019 (version 1)

Copyright

© 2019, Alexander et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,353
    Page views
  • 269
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Chromosomes and Gene Expression
    2. Genetics and Genomics
    Michael P Meers et al.
    Research Advance
    1. Chromosomes and Gene Expression
    Madhusudhan Srinivasan et al.
    Research Article