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BBA - Molecular Cell Research

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CRISPR-based genomic loci labeling revealed ordered spatial organization ofchromatin in living diploid human cellsDong-Ge Guoa,b,c, Dian-Bing Wangb, Chong Liub,c, Song Lub, Yu Houb,c, Xian-En Zhangb,a,c,⁎

a State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 4300071, Chinab National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, Chinac University of Chinese Academy of Sciences, Beijing 100049, China

A R T I C L E I N F O

Keywords:ChromatinLive cellsSpatial organizationCRISPR/dCas9Molecular imaging

A B S T R A C T

The eukaryotic genome is compacted in the form of chromatin within the nucleus. Whether the spatial dis-tribution of the genome is ordered or not has been a longstanding question. Answering this question wouldenable us to understand nuclear organization and cellular processes more deeply. Here, we applied a modifiedCRISPR/dCas9 system to label the randomly selected genomic loci in diploid living cells, which were visualizedby high-resolution wide-field imaging. To analyze the spatial positions of three pairs of genomic loci, three setsof parameters were progressively measured: i) the linear distance between alleles; ii) the radial distribution ofthe genomic loci; and iii) the linear distances between three pairs of genomic loci on nonhomologous chro-mosomes. By accurate labeling, geometric measuring and statistical analysis, we demonstrated that the dis-tribution of these genomic loci in the 3D space of the nucleus is relatively stable in both late G1 and early Sphases. Collectively, our data provided visual evidence in live cells, which implies the orderly spatial organi-zation of chromatin in the nucleus. The combination of orderliness and flexibility ensures the methodical andefficient operation of complex life systems. How the nucleus adopts this ordered 3D structure in living cells isthought-provoking.

1. Introduction

Human genomic DNA is approximately 2 meter long and is arrangedinto 46 chromosomes that are crowded into a nucleus that is 10–20 μmin diameter and that executes a series of cellular processes, such as DNAreplication, transcription and regulation and cell division. During theseprocesses, the DNA undergoes morphological changes such as folding,compression and unfolding in an unparalleled and extremely delicateprocess of self-regulation. To achieve this goal, the chromatin cannot bedisorganized in such a small space as the nucleus, but whether chro-matin is spatially well organized in the nucleus is a question of interestin cell biology.

Two approaches have been used to date for exploring the three-dimensional (3D) spatial structure of chromatin: fluorescence in situhybridization (FISH) and the lac operator/lac repressor (lacO/lacI)system. FISH determines the location and spatial distance of two or

more genomic loci by fluorescent labeling [1]. Early studies using thismethod observed chromosome territories in the interphase nucleus,that is, the occupation of different spatial positions in the nucleus bydifferent chromosomes, and found that the distribution of chromosomesand gene loci was not randomly organized [2–4]. The development ofoligo-paint probes and super-resolution imaging improved the sensi-tivity and specificity of FISH labeling. Due to its obvious advantages,FISH has been widely used to observe physical locations of genes orchromosomes at the single-cell level, including imaging of nucleargenome nanostructures and unveiling chromatin conformation acrosstopologically associated domains in individual cells [5,6]. However,FISH is mainly used in fixed cells, not live cells. In addition, the thermaldenaturation process required for FISH probe hybridization may in-fluence the integrity of the genome [7,8]. The lacO/lacI system allowsthe imaging of specific genomic loci in live cells. Briefly, tens to hun-dreds of lacO repeats are stably inserted adjacent to a gene of interest.

https://doi.org/10.1016/j.bbamcr.2019.07.013Received 8 May 2019; Received in revised form 5 July 2019; Accepted 23 July 2019

Abbreviations: CRISPR, clustered regularly interspaced short palindromic repeat; dCas9, deactivated CRISPR-associated protein 9; sgRNA, small guide RNA; PAM,protospacer-adjacent motif; 3D, three-dimensional; FISH, fluorescence in situ hybridization; Hi-C, high throughput chromosome conformation capture; NC, centroidof the nucleus; IMR90, human embryonic lung fibroblasts; Mbp, megabase pair

⁎ Corresponding author at: National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academyof Sciences, Beijing 100101, China.

E-mail address: zhangxe@ibp.ac.cn (X.-E. Zhang).

BBA - Molecular Cell Research 1866 (2019) 118518

Available online 31 July 20190167-4889/ © 2019 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).

T

The lac repressor lacI fused to a fluorescent protein specifically binds tolacO repeats and enables the visualization of the target genomic loci.The lacO/lacI system offers time-resolved information about genomedynamics [9] but requires the insertion of numerous exogenous repeatsequences into the genome, which may also influence the naturalstructure of the genome to some extent.

Another approach that has some relevance to this topic is 3Dgenomics, which has introduced chromosome conformational capture;e.g., Hi-C. This technology allows modeling of the entire 3D genomeorganization by chromatin-chromatin interactions and provides in-formation about conserved structural features within the genome, in-cluding loops, topologically associated domains and active or inactivecompartments [10–14]. The method is a critical means to understandthe folding and compression of the chromosomes, although the re-sulting 3D genome model needs further experimental validation[15,16].

In recent years, the CRISPR/dCas9 system has been developed forimaging specific genomic loci in live cells. dCas9 is an endonuclease-deactivated Cas9 protein that can bind small guide RNA (sgRNA); thedCas9-sgRNA complex specifically binds the target DNA loci throughbase pairing and PAM sequence recognition. The labeling of the targetDNA loci can be realized by fluorescent proteins that are fused to dCas9[17,18] or to the coating proteins that bind to the RNA aptamer in-serted in the sgRNA [19,20]. The method features easy to operate,nonintrusive, sensitive, multilocus labeling and is applicable to livecells, although the off-target problem still needs to be solved. Studiesrelated to the current topic include the most recent progress usingcancer cells, such as measuring the distances between multiple loci onchromosome 19 in U2OS cells [21], the distances between multiple locion different chromosomes and the periphery of the nucleus in HeLacells [22], and the distances between multiple loci on different chro-mosomes and their positional relation to nucleoli in hTERT-RPE-1 cells[23]. However, the genome of cancer cells is often abnormal, con-taining chromosomal inversions, translocations, deletions and aneu-ploidy, in particular. Therefore, it is vital to illuminate the spatial or-ganization of chromatin in normal diploid cells.

In this study, a similar CRISPR/dCas9 labeling system was con-structed with reference to Shao et al. [19] (Fig. 1A, B). The total lengthof the sgRNA was approximately 160 nt, and its scaffold contained atarget DNA binding region, a dCas9 binding region and two aptamerhairpins (MS2 or PP7). The binding proteins of MS2 and PP7 are MCPand PCP, respectively, each fused with one fluorescent protein (EGFP ormCherry) for illuminating different genomic loci. A high-resolutionwide-field imaging system was adopted for three reasons: i) it allows touse lower illumination intensity that causes less damage to cells; ii)lower illumination intensity results in a lower photobleaching andphototoxicity; and iii) it provides a fast photograph speed whileachieves sufficiently high-quality images for the purpose of this study.To reveal the natural spatial organization of chromatin in the nucleus,the karyotype must be normal. We therefore used diploid human em-bryonic lung fibroblast cells (Supplemental Fig. 1) in cell cycle inter-phase (late G1 phase), in which the nuclear materials are relativelystable. The spatial distribution of three pairs of loci on nonhomologouschromosomes was analyzed geometrically. The data acquired include i)the linear distance between alleles; ii) the linear distance between themidpoint of an allele and the periphery of the nucleus; iii) the lineardistance between the midpoint of an allele and the 3D centroid of thenucleus (NC) determined by Imaris software; and iv) the distance be-tween the midpoints of two genomic loci on nonhomologous chromo-somes. These analyses help us understand the spatial distribution ofgenomic loci in the nucleus.

Due to the diversity in the shape and size of nuclei in different cells,the data cannot be compared directly. Therefore, the data were nor-malized, considering the flat-ellipsoid shape of the nucleus, as follows:

=ND d/R

=R 2r

=r (abc)1/3

Here, ND is the normalized distance (μm); d is the linear distance(μm) measured between two alleles, between the midpoint of an alleleand the periphery of the nucleus, between the midpoint of the allele andthe NC, or between the midpoints of two genomic loci on non-homologous chromosomes; R is the geometrical equivalent diameter ofthe ellipsoid nucleus (μm); r is the geometrical equivalent radius ofellipsoid nucleus (μm); and a, b and c are the semi-axis length (μm) inthe x, y and z axial directions of the nucleus, respectively.

2. Materials and methods

2.1. Plasmid construction

The sgRNA targeting sequences for C3, C14, C19 and CX and thesequences for PCR primers were synthesized by Sango Biotechnology.For the construction of pLVX-dCas9-puro, the sequence of NLSSV40-dCas9-NLSSV40 was amplified from pSLQ1645-dCas9-EGFP (Addgene,#51023) and then cloned into the pLVX lentiviral vector containing aCMV promoter with XhoI and XbaI sites. For the construction of thesgRNA expression vector, the sgRNA oligos (Supplementary Table S1)were annealed into the pLH lentiviral vector containing a hU6 promoterby replacing the lethal gene ccdB between two BbsI sites [18]. MS2 orPP7 hairpins were appended to stem loop 2 and the tetraloop of thesgRNA scaffold. For the construction of the RNA aptamer bindingprotein expression vector, the sequence of MCP (MS2 binding protein)was linked to EGFP-NLSSV40, and the sequence of PCP (PP7 bindingprotein) was linked to mCherry-NLSSV40. Then, sequences coding MCP-EGFP-NLSSV40 and PCP-mCherry-NLSSV40 were cloned into the pHAGElentiviral vector containing an EF1a promoter at the MluI and XbaI sites.For the construction of mTagBFP2-LaminB1, the sequence encodingLaminB1-mTagBFP2 was cloned into a pHAGE lentiviral vector con-taining the CMV promoter by MluI and NotI sites. All of the constructedplasmids were validated by sequencing.

2.2. Cell lines

Human embryonic kidney 293T cells (kind gift from the Guang-XiaGao laboratory, Institute of Biophysics, Chinese Academy of Sciences)and human cervical cancer (HeLa) cells (kind gift from the Hai-YingHang laboratory, Institute of Biophysics, Chinese Academy of Sciences)were cultured in Dulbecco-modified Eagle's minimum essential medium(DMEM, Lonza) with high glucose, 10% (vol/vol) fetal bovine serum(FBS, Biological Industries) and 1% penicillin-streptomycin (LifeTechnologies). The human embryo lung fibroblast cell line IMR90 waskindly provided by the Stem Cell Bank of Chinese Academy of Sciencesand was cultured in MEM medium (Invitrogen) containing 10% FBS(Gibco), 1% Gluta-max (Invitrogen), 1% NEAA (Invitrogen), 1% sodiumpyruvate (Invitrogen) and 1% penicillin-streptomycin. All cells wereincubated at 37 °C and 5% CO2 in a humidified incubator. The cell lineswere PCR tested for mycoplasma contamination (TransGen Biotech).

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Fig. 1. Fluorescence labeling of endogenous genomic loci with high sensitivity in IMR90 cells. A) Schematic of the RNA-aptamer-based CRISPR/dCas9 labelingsystem. The sgRNA was tagged with MS2 or PP7 aptamer and directed dCas9 to the targeted locus. The corresponding coating proteins MCP and PCP were fused toEGFP and mCherry, respectively. (B) Construction of three components of the labeling system. dCas9 was fused with nuclear localization signals (NLSs) at its 5′ endand 3′ end and expressed under the control of the cytomegalovirus promoter. The sgRNA tagged with the RNA aptamer was expressed under a human U6 promoter.The fusion proteins MCPEGFP and PCP-mCherry were expressed under an EF1a promoter. All components were delivered into IMR90 cells via lentiviral infection. (C)To verify the fluorescently labeled loci in IMR90 cells, an MS2-PP7 stem loop was cloned to determine whether the fluorescent proteins generated overlappingsignals. For both C3 and C14, the fluorochromes were completely merged. The normalized line intensity profiles along the arrow show that both the EGFP andmCherry channels form two merged peaks. Scale bars, 5 μm. (D) Dual-color imaging of C3 and C14, C3 and C19, and C3 and CX in the late G1 and early S phases,respectively. C3 (red) was labeled by sgC3-2XPP7; C14, C19 and CX were labeled by sgRNA-2XMS2; and the nuclear membrane was labeled with laminB1-mTagBFP2(blue). Scale bars, 5 μm. (E) The FACS analysis of the cell cycle at late G1 phase and early S phase are shown, as well as the percentages of cells at G1, S and G2.

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2.3. Lentiviral production and transduction

First, 24 h before transfection, approximately 4 × 106 HEK293Tcells were seeded on 60 mm plates. For each plate, 1 μg pMD2.Gplasmid (Addgene, #12259), 1 μg psPAX2 (Addgene, #12260) and2.5 μg of lentiviral plasmid containing the gene of interest were co-transfected using Lipofectamine 3000 (Thermo Fisher Scientific) ac-cording to the manufacturer's instructions. Forty-eight hours post-transfection, lentiviruses were harvested from the supernatant and fil-tered with a 0.45 μm polyvinylidene fluoride filter (Millipore). Forlentiviral transduction, IMR90 cells seeded at 35 mm in glass-bottomdishes (Eppendorf) were infected with a mixture of lentiviral super-natant for 2 days.

2.4. Cell cycle synchronization

For CRISPR imaging of IMR90 cells in the late G1 phase and early Sphase, cells were seeded into 35 mm glass-bottom dishes (Eppendorf)24 h after infection with CRISPR lentivirus. The cells were treated with2 mM thymidine (Sigma) for 18 h, washed twice with prewarmed PBSand released into standard media for 9 h. The cells then underwent asecond thymidine treatment for 17 h to induce the cells synchronized tothe late G1 phase. After being released into standard media for 2 h, thecells were synchronized to the early S phase.

2.5. Karyotyping

The karyotype analysis of the IMR90 and HeLa cell lines was per-formed by Beijing Biocytogen Co., Ltd. using standard G band kar-yotype analysis with visual examination of the chromosome spread for32 metaphase nuclei.

2.6. Image acquisition and postprocessing

All 3D images of IMR90 cells were acquired on the Delta-VisionOMX V3 imaging system (GE Healthcare) with a 100× 1.4 NA oil-im-mersion objective (Olympus, UPlanSApo), solid-state multimode lasersat 405 nm (for mTagBFP2), 488 nm (for EGFP) and 561 nm (formCherry). The images were recorded with electron-multiplying charge-coupled device (CCD) cameras (Evolve 512×512, Photometrics). Serialz-stack sectioning was performed at 250 nm intervals in conventionalmode. The microscope was routinely calibrated with 100 nm fluor-escent spheres to calculate both the lateral and axial limits of imageresolution. The image stacks were reconstructed by SoftWoRx 6.1.1 (GEHealthcare) and further processed to obtain maximum-intensity pro-jections.

The conventional raw data were deconvoluted and processed inSoftWoRx 6.1.1. The reconstructed image datasets were then importedinto Imaris software (version 8.1.3, Bitplane, Concord, MA). Cell nu-clear detection and volume calculation were performed by surfacefunction based on the laminB1-mTagBFP2 fluorescence. The Spotfunction in Imaris automatically positioned the labeled genomic locibased on size and intensity thresholds. The 3D centroid of the nucleuswas calculated by a surface function after reconstruction of the 3Dshape of the nucleus. The measurement function calculated the distancebetween alleles on homologous and nonhomologous chromosomes, thedistance to the nuclear periphery and the distance to the nuclear cen-troid. All measurements were normalized to the nucleus size. All imagesare shown as maximum-intensity projections throughout the cell.

2.7. Statistical analysis

Data are represented as mean ± standard deviation (SD). Thenumbers of analyzed nuclei are mentioned in the text. In all statisticalanalyses, significance was determined using the unpaired t-test(***P < 0.0001, **P < 0.01, *P < 0.05). Plots and statistics were

generated in either GraphPad Prism version 6.00 or Origin 8.5.

3. Results

3.1. High-sensitivity fluorescence labeling of individual genomic loci

To achieve robust labeling, we selected target DNA loci with re-petitive sequences that have a period of > 30 bp and a copy numberof > 50 to ensure sufficient binding of the CRISPR/dCas9-fluorescentprotein complex. A genome-wide screening of chromosome-specificrepetitive DNAs found thousands of sites. Approximately 250 repetitivesequences met the search criteria. We randomly selected four loci lo-cated on chromosomes 3, 14, 19 and X, named C3, C14, C19 and CX(referred to as markers). Among them, the marker C14 is in the twelfthintron of the BRF1 gene, while C3, C19 and CX are in the intergenicregions of ACAP2 and PPP1R2, ZBTB45 and TRIM28, and PPP2R3B andSHOX, respectively. In addition, all of these loci are located in thesubtelomeric regions on their chromosomes, and each has nearly 100tandem repeats (Supplemental Fig. 2).

Due to the low transfection efficiency of liposomes in IMR90 cells,the lentiviral infection method was used. We coinfected a total of sixlentiviruses into IMR90 cells, with one containing dCas9, two con-taining coating protein (MCP or PCP)-fluorescent protein (EGFP ormCherry), two containing sgRNA-2×aptamer (MS2 or PP7), and onecontaining laminB1-mTagBFP2. After packaging into lentiviruses inHEK293T cells, the mixed lentiviral cocktail was applied to coinfectIMR90 cells. Fig. 1B shows the construction strategy of the CRISPR/dCas9 tagging system. NLS-encoded nuclear localization peptides wereemployed to guide dCas9 protein, MCP-EGFP and PCP-mCherry into thenucleus. Here, laminB1, a structural protein of the nuclear membrane,was fused to mTagBFP2 to visualize the nuclear morphology.

To verify the correctness of the labeling, we used sgRNA bearingdouble aptamers (MS2 and PP7) in the CRISPR/dCas9 labeling systemto investigate whether the recruited green fluorescent protein and redfluorescent protein were colocalized. The marker loci included the C3allele and C14 allele. The results are shown in Fig. 1C, where the greenchannel represents MCP-EGFP and the red channel represents PCP-mCherry. The fluorescent signals were clearly visible. The mergedimages completely coincided (also demonstrated by the line intensityprofiles shown in Fig. 1C far right), which proved that the labeling wassuccessful. We also designed sgRNA targets to telomere repeats, and thetelomere labeling was confirmed by colocalization with the telomericprotein TRF1 fused to mCherry (Supplemental Fig. 3).

Next, we paired C3 with three other loci (C14, C19 and CX) anddisplayed them together to obtain the required data (Fig. 1D). All thecell cultures were synchronized by the thymidine double blockingmethod (Fig. 1E). In the late G1 phase, the chromosomes did not re-plicate, and the allelic loci were located on a pair of homologouschromosomes, showing two marker signals of the same color. Therewere two pairs of marker signals in each cell: the red was the C3 locusand the green was the other three loci. After the thymidine blockadewas removed, the cells entered S phase; here, four pairs of markersignals appeared in each cell. This observation shows that the chro-mosomes began to replicate, and each marker signal was divided intotwo, located on sister chromatids adjacent to each other.

3.2. Analysis of linear distance between alleles

The linear distance between alleles can reflect the relative locationof homologous chromosomes in the nucleus (Fig. 2A). In the late G1phase, the linear distances between alleles for each marker were rela-tively stable. Among them, the distance between C3 alleles was thelargest (0.89 ± 0.41), followed by CX (0.87 ± 0.42), C14(0.71 ± 0.36) and C19 (0.70 ± 0.36) (Fig. 3A; Table 1). Next, weanalyzed the distribution of linear distances between alleles in the earlyS phase. In this phase, the chromosomes began to replicate, and each

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chromosome formed a pair of sister chromatids; thus, each markerbecame two. To calculate the distance between alleles, we first mea-sured the distance midpoint between the two markers on the newlygenerated sister chromatids and took the measured distance betweenthe two midpoints as the distance between the alleles in the early Sphase. The results showed that the distances between alleles were re-latively stable during the early S phase. The distance between C3 alleleswas the largest (0.87 ± 0.41), followed by CX (0.86 ± 0.27), C19(0.83 ± 0.46) and C14 (0.76 ± 0.34) (Fig. 3B; Table 1). The t-testresults showed that there was no significant difference in the distancebetween the marker signals examined in the late G1 phase and early Sphase (Supplemental Fig. 4; Table 2). This result indicates that the re-lative spatial positions between the tested alleles remained stableduring the test period.

3.3. Radial distribution of allele pairs in nuclei

To analyze the orientation of alleles in the nucleus, we comparedthe distance from the marker site to the periphery of the nucleus and tothe NC. Because we cannot distinguish pairs of homochromic markeralleles from each other, we calculated the radial distribution of allelepairs in the nucleus by taking the midpoints of the distance betweenalleles (Fig. 2B, C).

In the late G1 phase, the linear distances of C19, CX and C14 allelepairs to the periphery of the nucleus had a normal distribution, withmean values of 0.46 ± 0.15 μm, 0.36 ± 0.13 μm, and0.33 ± 0.12 μm, respectively. The linear distance from the C3 locus tothe periphery of the nucleus exhibited a nearly normal behavior, with a

mean value of 0.31 ± 0.13 μm (Fig. 4A, middle; Table 1). In the early Sphase, when the chromosomes had just completed replication, we firstcalculated the distance midpoints between the two marker signals onthe duplicated sister chromatids. Then, we measured the linear distancemidpoint between the midpoint of A1 and the midpoint of A2 andnamed it A′, and we finally took the distance d between A′ and thenucleus periphery to be the relative linear distance from one allele tothe periphery of the nucleus (Fig. 2B, right). The results showed that thedistances from the C19, CX, C14 and C3 allele pairs to the periphery ofthe nucleus also were in a normal distribution, with mean values of0.41 ± 0.15 μm, 0.38 ± 0.14 μm, 0.36 ± 0.12 μm, and0.31 ± 0.14 μm (Fig. 4B, middle; Table 1). The t-test showed that thedistances of all four genomic loci to the nuclear periphery had no sig-nificant difference in the late G1 phase and early S phases (Fig. 4C;Table 2).

In the late G1 phase, the results showed that the linear distancesfrom the C3, CX and C14 allele pairs to NC were normally distributed,with mean values of 0.43 ± 0.22 μm, 0.41 ± 0.20 μm and0.37 ± 0.19 μm, respectively. The linear distance from the C19 allelepair to NC was nearly normal, with a mean value of 0.37 ± 0.21 μm(Fig. 4A, bottom; Table 1). In the early S phase, we took the distance dbetween A' and NC as the relative linear distance from one allele to thenuclear centroid (Fig. 2C, right). The linear distances of allele pairs C3,C19, CX and C14 to NC were in a normal distribution, with mean valuesof 0.49 ± 0.22 μm, 0.41 ± 0.18 μm, 0.39 ± 0.17 μm, and0.30 ± 0.14 μm, respectively (Fig. 4B, bottom; Table 1). The t-testshowed that the distances from C3, C19 and CX to the nuclear centroidexhibited no significant difference in the late G1 phase and early S

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Fig. 2. Schematic of the 3D measurements per-formed in IMR90 cell nuclei. (A) The relative loca-tion of alleles was analyzed by measuring the lineardistance between alleles (A1 and A2) in the late G1phase (A, left) and early S phase (A, right). In theearly S phase, the A1 and A2 loci were replicatedand located on sister chromatids. The A1 midpointand A2 midpoint were used to represent the re-plicated A1 and A2, and the distance between thetwo midpoints was measured to represent the dis-tance between alleles in the early S phase. (B and C)Radial distributions of allele pairs were analyzed bymeasuring the distance from the midpoint of theallele pair to the periphery of the nucleus or thenuclear centroid at late G1 phase (B and C, left) andearly S phase (B and C, right), respectively. In theearly S phase, the midpoint of the allele pair wasmeasured and named A′. The distance from A′ to thenuclear periphery or NC was measured to representthe radial distance of the allele pair. (D) The spatialposition of genomic loci on nonhomologous chro-mosomes was analyzed by measuring the lineardistance between the two midpoints of each pair ofalleles in the late G1 phase (D, left) and early S phase(D, right), respectively. In the early S phase, themidpoints of the allele pairs were measured andnamed A′ and B′. The linear distance d between A′and B′ was measured.

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phase, while C14 showed a significant difference between late G1 andearly S phases (Fig. 4C; Table 2).

3.4. Spatial position of genomic loci on nonhomologous chromosomes

Here, we labeled four genomic loci on four nonhomologous chro-mosomes. They were divided into three groups: C3 and C14, C3 and

C19, and C3 and CX, with green and red labels, respectively. The lineardistances between the labeled signals were measured, which allowed usto analyze the spatial distribution of different genomic loci on non-homologous chromosomes.

Similarly, since each pair of alleles in the same set of experiments isa homochromic marker, they cannot be distinguished from each other.We first measured the midpoints of the linear distance between two

Fig. 3. The spatial distribution of alleles was relatively stable in the late G1 phase and early S phase in IMR90 cell nuclei.Top, representative images of the labeled genomic loci C3, C14, C19 and CX, from left to right. All scale bars, 5 μm. Bottom, relative frequency of allelic distances. Allmeasurements were normalized to the cell nuclei. (A) The distributions displayed the normalized distances between alleles in the late G1 phase. n= 175 cells for C3,175 cells for C14, 77 cells for C19 and 65 cells for CX. (B) The distributions displayed the normalized distances between alleles in the early S phase. n= 47 cells forC3, 46 cells for C14, 49 cells for C19 and 48 cells for CX. Distance measurements were based on three independent experiments.

Table 1The quantitative results on distances measured at the late G1 phase and early S phase. The data were shown as mean ± standard deviation.

Cell cyclephase

Genomic loci Distance betweenalleles

Distance to nuclearperiphery

Distance to nuclearcentroid

Cell cyclephase

Genomic loci Distance between nonhomologouschromosomes

G1 C3 0.89 ± 0.41 0.31 ± 0.13 0.43 ± 0.22 G1 C3/C14 0.53 ± 0.30C14 0.71 ± 0.36 0.33 ± 0.12 0.37 ± 0.19 C3/C19 0.62 ± 0.33C19 0.70 ± 0.36 0.46 ± 0.15 0.37 ± 0.21 C3/CX 0.60 ± 0.34CX 0.87 ± 0.42 0.36 ± 0.13 0.41 ± 0.20

S C3 0.87 ± 0.41 0.31 ± 0.14 0.49 ± 0.22 S C3/C14 0.60 ± 0.30C14 0.76 ± 0.34 0.36 ± 0.12 0.30 ± 0.14 C3/C19 0.62 ± 0.26C19 0.83 ± 0.46 0.41 ± 0.15 0.41 ± 0.18 C3/CX 0.71 ± 0.38CX 0.86 ± 0.27 0.38 ± 0.14 0.39 ± 0.17

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pairs of marker signals (A1 and A2, B1 and B2) using the linear distancebetween two midpoints as the relative distance between two genomicloci in the late G1 phase (Fig. 2D, left). The results showed that thelinear distances between the three groups of loci were relatively stable.Among them, the distance between C3 and C19 was the largest(0.62 ± 0.33), followed by C3 and CX (0.60 ± 0.34), and C3 and C14(0.53 ± 0.30) (Fig. 4A; Table 1). In the early S phase, chromosomereplication divided each locus into two. We first calculated the distancemidpoints between the two marker signals on the duplicated sisterchromatids of each group and then calculated the distance midpointsbetween the two pairs (A1 midpoint and A2 midpoint, B1 midpoint andB2 midpoint), which were named A′ and B′, and finally took the dis-tance d between A′ and B′ as the relative linear distance between thetwo marker signals on the corresponding nonhomologous chromosomesin the early S phase (Fig. 2D, right). The results showed that the lineardistances between two genomic loci on nonhomologous chromosomeswere relatively stable in all three groups at the early S phase. Amongthem, the distance between C3 and CX was the largest (0.72 ± 0.38);the others are C3 and C19 (0.62 ± 0.26), and C3 and C14(0.60 ± 0.30), respectively (Fig. 4B; Table 1). A t-test showed thatthere was no significant difference in the linear distances between themarker signals measured in the late G1 phase and early S phase(Fig. 5C; Table 2), indicating that the linear distances between genomicloci on nonhomologous chromosomes remained stable during thisperiod.

4. Discussion

In eukaryotic nuclei, the hierarchical organization of the genomeundergoes a process of folding and compression from linear DNA andnucleosome structure to chromatin fibers and then to functional do-mains within chromosomes and the distinct chromosome territories[13,24]. This situation reveals that the extraordinary length of DNAlinear sequences exists in a narrow nuclear space through self-reg-ulating packing, which is reversible. We assume that the 3D spatialdistribution of chromatin during this phase should be orderly, that is,the spatial distribution of numerous chromatins in the nucleus shouldhave an intrinsic pattern; otherwise, it would be difficult to completecomplex and fine biological processes. However, proving this orderli-ness is very challenging. The FISH method yielded considerable data tocharacterize the arrangement of chromosomes or genes within the cellnucleus, indicating that their spatial distribution is nonrandom in fixedcells. What about the spatial organization of genomic loci in the nucleiof living cells? This question could be rationally answered throughaccurate gene labeling and spatial geometry analysis, as performed inthis study.

The genomic loci labeled here were randomly selected by bioin-formatics analysis to avoid selection bias. The C3, C14, C19 and CX lociare located on chromosomes of different lengths, autosomes and sexchromosomes, and the degenerate design is reasonable and feasible. If

the distance between alleles, nonalleles and their radial distribution inthe nucleus were measurable and predictable, the spatial geometricdistribution of the genome and chromatin represented by these genomicloci could be considered to be orderly in the nucleus. As described inthe Introduction section, similar research was carried out within cancercells. We found that the results of allele labeling in cancer cells wereoften chaotic due to the abnormal karyotype of cancer cells. Hence, wechose human diploid cells (human embryonic lung fibroblasts, IMR90),with cell cycle synchronization, and labeled genomic loci in interphaseof the cell cycle (late G1 and early S phases). However, since normalhuman diploid cells are not as easy to handle as cancer cells, the la-beling efficiency of plasmid transfection is often very low. By usinglentiviral infection instead, we obtained high labeling efficiency. Forthe off-target limitation of CRISPR/Cas9 mentioned before, our solu-tions were: i) selecting the labeling loci with nearly 100 repeat se-quences in a single locus, so that few off-target labeling events wereignored; and ii) excluding cells with incomplete or without labeling.

The statistical analysis of the measured data in this study presenteda mostly normal distribution, indicating that the spatial position ofthese genomic loci was relatively stable in the nucleus. There are atleast possible two explanations based on our knowledge. First, we foundthat the linear distance between alleles and the radial distribution ofgenomic loci in the nucleus were highly correlated with the size andgene density of their chromosomes (Table 3). It is clear that the lineardistance between alleles was positively correlated with chromosomalsize and negatively correlated with chromosomal gene density. Thelinear distance between alleles was longest at the C3 loci and shortest atthe C19 loci. Another fact is that the distances from the genomic loci tothe nuclear periphery are negatively correlated with chromosomal sizeand positively correlated with chromosomal gene density. Among them,the distance to the periphery of the nucleus was longest at the C19 lociand shortest at the C3 loci. Meanwhile, the distances from the genomicloci to the nuclear centroid were positively correlated with chromo-somal size and negatively correlated with chromosomal gene density,and the distance to the nucleus centroid was longest at the C3 loci andshortest at the C19 loci. These results agreed well with the earlierstudies on the radial distribution of heterochromatin and chromosometerritories using FISH [25–27]. In addition, similar to the distributionpattern of C3 and C14 loci in this study, their adjacent sites on DNAsequences, BCL6 (3q27) and IGH (14q32), were also preferentially en-riched at the periphery of the nucleus and the medial nuclear sub-volumes [28], suggesting that the intranuclear localization of genomicloci could be influenced by their adjacent DNA sequences and is likelyconserved in cells with different origins.

Furthermore, the stability of the spatial distribution of the genomicloci could be understood by studying the achievements of 3D-genomestudies. In recent years, numerous chromatin interactions have beenidentified in the genome by Hi-C technology, including long-range,short-range and adjacent interaction pairs. Based on these findings, 3Dgenome hierarchical structures were established that contained

Table 2Statistical comparison of the spatial distribution between late G1 phase and early S phase.

Distance P value

C3 C14 C19 CX C3/C14 C3/C19 C3/CX

Between alleles 0.72(175/47)

0.39(175/46)

0.08(77/49)

0.96(65/48)

To nuclear periphery 0.78(175/47)

0.12(175/46)

0.06(77/49)

0.38(65/48)

To nuclear centroid 0.12(175/47)

0.02*(175/46)

0.34(77/49)

0.51(65/48)

Between nonhomologous chromosomes 0.40(75/15)

0.93(77/17)

0.38(65/15)

Number of samples is shown in brackets (number of cells counted at the late G1 phase/number of cells counted in the early S phase). Significance levels are shown as pvalues from the unpaired t-test (***P < 0.0001, **P < 0.01, *P < 0.05).

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Fig. 4. The radial distribution of alleles was relatively stable in the late G1 and early S phases in the nuclei of IMR90 cells.(A) Top, representative images showing the radial position of the studied alleles in the nucleus (laminB1-mTagBFP2) at late G1 phase. Scale bars, 5 μm. Middle,relative frequency of the distance between alleles and the periphery of the nucleus. Bottom, relative frequency of the distance between allele and the nuclear centroid.n= 175 cells for C3, 175 cells for C14, 77 cells for C19 and 65 cells for CX. The distance was normalized to the nuclear sizes. (B) Top, representative images showingthe radial position of the studied alleles in the nucleus (laminB1-mTagBFP2) at the early S phase. Scale bars, 5 μm. Middle, relative frequency of the distance betweenalleles and the periphery of nucleus. Bottom, relative frequency of the distance between alleles and NC. n= 47 cells for C3, 46 cells for C14, 49 cells for C19 and 48cells for CX.

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chromatin compartments, topological associated domains and chro-matin loops [29]. In addition, chromatin 3D structure models werecomputed in mouse haploid embryonic stem cells, human

lymphoblastoid cells and peripheral blood mononuclear cells [30,31].We believe that the global chromatin interaction has a significant effecton the spatial distribution of chromatin in the nucleus. Although the

Fig. 5. The spatial positions of genomic loci on nonhomologous chromosomes were relatively stable in late G1 and early S phases in the IMR90 cell nuclei.Top, representative images of the labeled genomic loci C3, C14, C19 and CX, respectively, from left to right. All scale bars, 5 μm. Bottom, relative frequency of thelinear distances measured. (A) The distributions of the normalized distances of the three labeling groups in the late G1 phase. n= 75 cells for C3 and C14, 77 cells forC3 and C19, and 65 cells for C3 and CX. (B) The distributions display the normalized distances of the three labeling groups at the early S phase. n= 15 cells for C3and C14, 17 cells for C3 and C19, and 15 cells for C3 and CX.

Table 3Comparison of characteristics of chromosomes and distances between the selected genomic loci.

Issue Order Data and ranking

Chromosomal size (Mbp) Descending Chr3 (198.3) > ChrX (156) > Chr14 (107) > Chr19 (58.6)Chromosomal gene density (genes/Mbp) Ascending ChrX (5.39) < Chr3 (5.42) < Chr14 (7.66) < Chr19 (25.09)Linear distance between alleles Descending C3 > CX > C14 > C19Distance to nuclear periphery Ascending C3 < C14 < CX < C19Distance to nuclear centroid Descending C3 > CX > C14 > C19

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experimental validation of a large number of these interactions is ne-cessary [32], we deduce that the proposed models already showed thatthe 3D spatial distribution of the genome in the nucleus has an intrinsicpattern, and its driving force should mainly come from the overalloutput of intermolecular attraction and repulsion. The results obtainedby using randomly selected genomic loci and geometric analysis in ourstudy provided the visual evidence in live cells, strongly implying theorderly spatial distribution of chromatin in the nucleus.

Technically, differential labeling of a pair of alleles is not yet pos-sible in human cells. Thus, directly measuring their radial distributionand the distance to the genomic loci on nonhomologous chromosomescannot be achieved. In studies using FISH methods, the statisticalanalysis was performed with directly measured data [33,34]. However,our analysis showed that the radial distribution of a given genomiclocus is quite different from that of its allele, and mixing differentmeasurements for statistical analysis resulted in artificial errors (datanot shown). To solve this problem, we introduced the midpoint of al-leles to represent a pair of alleles. From the geometric point of view, theconfidence of the midpoint analysis method should be higher.

However, the relatively high standard deviation of our results in-dicates that in soft systems such as cells, the spatial distribution of thechromatin is not as stable as in other material systems, which might berelated to the dynamic process of the cell cycle and the real-time reg-ulatory mechanism within the nucleus. Even in interphase, dynamicbiological processes exist in the nucleus. The combination of orderlinessand flexibility ensures the methodical and efficient operation of com-plex life systems.

5. Conclusion

In summary, using the CRISPR/dCas9 gene labeling method, wedescribed, for the first time, the spatial location relationships of 3 pairsof genome loci in the interphase (late G1 phase and early S phase)nucleus of diploid living cells. The experimental results showed that thedistances between alleles or between markers representing non-homologous chromosomes were relatively stable in the nucleus, in-dicating that the spatial geometrical structure of chromatin in the nu-cleus is not random and disordered. These results collectively constituteevidence implying that the spatial organization of chromatin is rela-tively ordered in diploid cells at the interphase of the cell cycle. This isimportant for cells to carry out their complex life processes. We believethe stable spatial distribution of chromatin organization in the nucleusis due to the global chromatin interaction driven by the overall outputof intermolecular interaction and repulsion, as well as self-regulation ofintracellular processes that remain unclear.

Transparency document

The Transparency document associated with this article can befound, in online version.

Acknowledgements

The authors gratefully acknowledge the technical assistance of theIBP protein science technical platform staffs Shuoguo Li for high-re-solution wide-field imaging, Yun Feng for Imaris software, Junying Jiaand Shuang Sun for FACS. We would like to thank Zhe Li, Guang Li, andLing-Yue Huang for their advice and help in bioinformatics and ex-periments.

Funding sources

This work was supported by the Strategic Priority Research Programof the Chinese Academy of Sciences, China (grant numberXDB29050100); the National Key Research and Development Programof China, China (grant number 2017YFA0205503).

Declaration of competing interest

The authors declare that they have no conflicts of interest.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbamcr.2019.07.013.

References

[1] P.R. Langersafer, M. Levine, D.C. Ward, Immunological method for mapping geneson Drosophila polytene chromosomes, Proc. Natl. Acad. Sci. U. S. A. 79 (1982)4381–4385, https://doi.org/10.1073/pnas.79.14.4381.

[2] T. Cremer, C. Cremer, Rise, fall and resurrection of chromosome territories: a his-torical perspective Part II. Fall and resurrection of chromosome territories duringthe 1950S to 1980s. Part III. Chromosome territories and the functional nucleararchitecture: experiments and models from the 1990s to the present, Eur. J.Histochem. 50 (2006) 223–272, https://doi.org/10.4081/995.

[3] J.A. Croft, J.M. Bridger, S. Boyle, P. Perry, P. Teague, W.A. Bickmore, Differences inthe localization and morphology of chromosomes in the human nucleus, J. Cell Biol.145 (1999) 1119–1131, https://doi.org/10.1083/jcb.145.6.1119.

[4] K.J. Meaburn, T. Misteli, Cell biology - chromosome territories, Nature 445 (2007)379–381, https://doi.org/10.1038/445379a.

[5] Y. Weiland, P. Lemmer, C. Cremer, Combining FISH with localisation microscopy:super-resolution imaging of nuclear genome nanostructures, Chromosom. Res. 19(2011) 5–23, https://doi.org/10.1007/s10577-010-9171-6.

[6] B. Bintu, L.J. Mateo, J.H. Su, N.A. Sinnott-Armstrong, M. Parker, S. Kinrot,K. Yamaya, A.N. Boettiger, X. Zhuang, Super-resolution chromatin tracing revealsdomains and cooperative interactions in single cells, Science, 362, (2018), https://doi.org/10.1126/science.aau1783.

[7] J.M. Levsky, R.H. Singer, Fluorescence in situ hybridization: past, present and fu-ture, J. Cell Sci. 116 (2003) 2833–2838, https://doi.org/10.1242/jcs.00633.

[8] R.R. Swiger, J.D. Tucker, Fluorescence in situ hybridization: a brief review,Environ. Mol. Mutagen. 27 (1996) 245–254, https://doi.org/10.1002/(SICI)1098-2280(1996)27:4<245::AID-EM1>3.0.CO;2-C.

[9] V. Roukos, T.C. Voss, C.K. Schmidt, S. Lee, D. Wangsa, T. Misteli, Spatial dynamicsof chromosome translocations in living cells, Science 341 (2013) 660–664, https://doi.org/10.1126/science.1237150.

[10] J.R. Dixon, S. Selvaraj, F. Yue, A. Kim, Y. Li, Y. Shen, M. Hu, J.S. Liu, B. Ren,Topological domains in mammalian genomes identified by analysis of chromatininteractions, Nature 485 (2012) 376–380, https://doi.org/10.1038/nature11082.

[11] E. Lieberman-Aiden, N.L. van Berkum, L. Williams, M. Imakaev, T. Ragoczy,A. Telling, I. Amit, B.R. Lajoie, P.J. Sabo, M.O. Dorschner, R. Sandstrom,B. Bernstein, M.A. Bender, M. Groudine, A. Gnirke, J. Stamatoyannopoulos,L.A. Mirny, E.S. Lander, J. Dekker, Comprehensive mapping of long-range inter-actions reveals folding principles of the human genome, Science 326 (2009)289–293, https://doi.org/10.1126/science.1181369.

[12] E.P. Nora, B.R. Lajoie, E.G. Schulz, L. Giorgetti, I. Okamoto, N. Servant, T. Piolot,N.L. van Berkum, J. Meisig, J. Sedat, J. Gribnau, E. Barillot, N. Bluthgen, J. Dekker,E. Heard, Spatial partitioning of the regulatory landscape of the X-inactivationcentre, Nature 485 (2012) 381–385, https://doi.org/10.1038/nature11049.

[13] S.S.P. Rao, M.H. Huntley, N.C. Durand, E.K. Stamenova, I.D. Bochkov,J.T. Robinson, A.L. Sanborn, I. Machol, A.D. Omer, E.S. Lander, E.L. Aiden, A 3Dmap of the human genome at kilobase resolution reveals principles of chromatinlooping, Cell 159 (2014) 1665–1680, https://doi.org/10.1016/j.cell.2014.11.021.

[14] T. Sexton, E. Yaffe, E. Kenigsberg, F. Bantignies, B. Leblanc, M. Hoichman,H. Parrinello, A. Tanay, G. Cavalli, Three-dimensional folding and functional or-ganization principles of the Drosophila genome, Cell 148 (2012) 458–472, https://doi.org/10.1016/j.cell.2012.01.010.

[15] A.D. Schmitt, M. Hu, B. Ren, Genome-wide mapping and analysis of chromosomearchitecture, Nat Rev Mol Cell Bio 17 (2016) 743–755, https://doi.org/10.1038/nrm.2016.104.

[16] R.A. Beagrie, A. Pombo, Cell cycle: continuous chromatin changes, Nature 547(2017) 34–35, https://doi.org/10.1038/547034a.

[17] B. Chen, L.A. Gilbert, B.A. Cimini, J. Schnitzbauer, W. Zhang, G.W. Li, J. Park,E.H. Blackburn, J.S. Weissman, L.S. Qi, B. Huang, Dynamic imaging of genomic lociin living human cells by an optimized CRISPR/Cas system, Cell 155 (2013)1479–1491, https://doi.org/10.1016/j.cell.2013.12.001.

[18] H.H. Ma, A. Naseri, P. Reyes-Gutierrez, S.A. Wolfe, S.J. Zhang, T. Pederson,Multicolor CRISPR labeling of chromosomal loci in human cells, Proc. Natl. Acad.Sci. U. S. A. 112 (2015) 3002–3007, https://doi.org/10.1073/pnas.1420024112.

[19] S.P. Shao, W.W. Zhang, H. Hu, B.X. Xue, J.S. Qin, C.Y. Sun, Y.A. Sun, W.S. Wei,Y.J. Sun, Long-term dual-color tracking of genomic loci by modified sgRNAs of theCRISPR/Cas9 system, Nucleic Acids Res, 44, (2016), https://doi.org/10.1093/nar/gkw066.

[20] S.Y. Wang, J.H. Su, F. Zhang, X.W. Zhuang, An RNA-aptamer-based two-colorCRISPR labeling system, Sci Rep-Uk, 6, (2016), https://doi.org/10.1038/srep26857.

[21] H.H. Ma, L.C. Tu, A. Naseri, Y.C. Chung, D. Grunwald, S.J. Zhang, T. Pederson, RNAscaffolds for signal amplification in genome imaging, Nat Methods 15 (2018)928–931, https://doi.org/10.1038/s41592-018-0174-0.

D.-G. Guo, et al. BBA - Molecular Cell Research 1866 (2019) 118518

10

[22] R. Stanyte, J. Nuebler, C. Blaukopf, R. Hoefler, R. Stocsits, J.M. Peters,D.W. Gerlich, Dynamics of sister chromatid resolution during cell cycle progression,J. Cell Biol. 217 (2018) 1985–2004, https://doi.org/10.1083/jcb.201801157.

[23] P.G. Maass, A.R. Barutcu, D.M. Shechner, C.L. Weiner, M. Mele, J.L. Rinn,Spatiotemporal allele organization by allele-specific CRISPR live-cell imaging (SNP-CLING), Nat Struct Mol Biol 25 (2018) 176–184, https://doi.org/10.1038/s41594-017-0015-3.

[24] G. Bascom, T. Schlick, Linking chromatin fibers to gene folding by hierarchicallooping, Biophys. J. 112 (2017) 434–445, https://doi.org/10.1016/j.bpj.2017.01.003.

[25] S. Boyle, S. Gilchrist, J.M. Bridger, N.L. Mahy, J.A. Ellis, W.A. Bickmore, The spatialorganization of human chromosomes within the nuclei of normal and emerin-mu-tant cells, Hum. Mol. Genet. 10 (2001) 211–219, https://doi.org/10.1093/hmg/10.3.211.

[26] R. Mayer, A. Brero, J. von Hase, T. Schroeder, T. Cremer, S. Dietzel, Commonthemes and cell type specific variations of higher order chromatin arrangements inthe mouse, Bmc Cell Biol, 6, (2005), https://doi.org/10.1186/1471-2121-6-44.

[27] C. Hepperger, A. Mannes, J. Merz, J. Peters, S. Dietzel, Three-dimensional posi-tioning of genes in mouse cell nuclei, Chromosoma 117 (2008) 535–551, https://doi.org/10.1007/s00412-008-0168-2.

[28] J.J. Roix, P.G. McQueen, P.J. Munson, L.A. Parada, T. Misteli, Spatial proximity oftranslocation-prone gene loci in human lymphomas, Nat. Genet. 34 (2003)287–291, https://doi.org/10.1038/ng1177.

[29] M. Yu, B. Ren, The three-dimensional organization of mammalian genomes, AnnuRev Cell Dev Biol. 33 (2017) 265–289, https://doi.org/10.1146/annurev-cellbio-100616-060531.

[30] T.J. Stevens, D. Lando, S. Basu, L.P. Atkinson, Y. Cao, S.F. Lee, M. Leeb,K.J. Wohlfahrt, W. Boucher, A. O’Shaughnessy-Kirwan, J. Cramard, A.J. Faure,M. Ralser, E. Blanco, L. Morey, M. Sanso, M.G.S. Palayret, B. Lehner, L. Di Croce,A. Wutz, B. Hendrich, D.E.D. Klenerman, Laue, 3D structures of individual mam-malian genomes studied by single-cell Hi-C, Nature 544 (2017) 59–64, https://doi.org/10.1038/nature21429.

[31] L.Z. Tan, D. Xing, C.H. Chang, H. Li, S. Xie, Three-dimensional genome structures ofsingle diploid human cells, Science 361 (2018) 924–928, https://doi.org/10.1126/science.aat5641.

[32] V.I. Risca, W.J. Greenleaf, Unraveling the 3D genome: genomics tools for multiscaleexploration, Trends Genet. 31 (2015) 357–372, https://doi.org/10.1016/j.tig.2015.03.010.

[33] M. Cremer, J. von Hase, T. Volm, A. Brero, G. Kreth, J. Walter, C. Fischer, I. Solovei,C. Cremer, T. Cremer, Non-random radial higher-order chromatin arrangements innuclei of diploid human cells, Chromosom. Res. 9 (2001) 541–567, https://doi.org/10.1023/A:1012495201697.

[34] C.S. Osborne, L. Chakalova, J.A. Mitchell, A. Horton, A.L. Wood, D.J. Bolland,A.E. Corcoran, P. Fraser, Myc dynamically and preferentially relocates to a tran-scription factory occupied by Igh, PLoS Biol. 5 (2007) 1763–1772, https://doi.org/10.1371/journal.pbio.0050192.

D.-G. Guo, et al. BBA - Molecular Cell Research 1866 (2019) 118518

11