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Spatiotemporal allele organization by allele-specific CRISPR live-cell imaging (SNP-CLING)

Nature Structural & Molecular Biologyvolume 25pages176184 (2018) | Download Citation



Imaging and chromatin capture techniques have provided important insights into our understanding of nuclear organization. A limitation of these techniques is the inability to resolve allele-specific spatiotemporal properties of genomic loci in living cells. Here, we describe an allele-specific CRISPR live-cell DNA imaging technique (SNP-CLING) to provide the first comprehensive insights into allelic positioning across space and time in mouse embryonic stem cells and fibroblasts. With 3D imaging, we studied alleles on different chromosomes in relation to one another and relative to nuclear substructures such as the nucleolus. We find that alleles maintain similar positions relative to each other and the nucleolus; however, loci occupy unique positions. To monitor spatiotemporal dynamics by SNP-CLING, we performed 4D imaging and determined that alleles are either stably positioned or fluctuating during cell state transitions, such as apoptosis. SNP-CLING is a universally applicable technique that enables the dissection of allele-specific spatiotemporal genome organization in live cells.

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We thank all of the Rinn laboratory members for thoughtful discussions and intellectual input. The study was supported by U01 DA040612-01, P01 GM09911, HHMI Faculty Scholars Program (J.L.R), and the ‘Deutsche Forschungsgemeinschaft (DFG)’, supported P.G.M (MA5028/1-3 and MA5028/1-1). M. B. Goldring (Weill Cornell Medical College) kindly provided C28/I2 cells. We thank S. Terclavers (Zeiss) and D. Richardson (Harvard Center for Biological Imaging, HCBI, Cambridge) for their support optimizing Airyscan microscopy, J. P. Lewandowski (Harvard University) for generating 129S1/CAST MEFs, and J. Engreitz (Broad Institute) for providing 129S1/CAST mESCs.

Author information

Author notes

    • David M. Shechner

    Present address: Department of Pharmacology, The University of Washington, Seattle, WA, USA

    • John L. Rinn

    Present address: Department of Biochemistry, University of Colorado, BioFrontiers, Boulder, CO, USA


  1. Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA

    • Philipp G. Maass
    • , A. Rasim Barutcu
    • , David M. Shechner
    • , Catherine L. Weiner
    • , Marta Melé
    •  & John L. Rinn
  2. Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA

    • David M. Shechner
    • , Catherine L. Weiner
    •  & John L. Rinn
  3. Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA

    • A. Rasim Barutcu
    • , David M. Shechner
    • , Catherine L. Weiner
    • , Marta Melé
    •  & John L. Rinn
  4. Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA, USA

    • John L. Rinn


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P.G.M. and J.L.R. conceived the study. P.G.M. performed the experiments and wrote the manuscript with J.L.R and A.R.B. C.L.W. performed the mESC experiments, M.M. analyzed the availability of suitable SNP-CLING SNPs, and D.M.S. provided intellectual input and plasmids.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Philipp G. Maass or John L. Rinn.

Integrated supplementary information

  1. Supplementary Figure 1 Genotypization of SNP-CLING sgRNAs.

    (a) Genome-wide distribution of suitable SNPs for SNP-CLING in human (mean distance = 181 bp, hg38), and in mouse (mean distance 332 bp, mm10, medians with 25th to 75th percentiles, 1.5x interquartile ranges, outliers = black dots). (b) Total numbers of suitable SNPs in human and mouse, and intergenic / intragenic distributions. (c) Heterozygous SNP substitutions in the second or third nucleotide of the PAM-sequences determined the usability of every sgRNA in SNP-CLING experiments on 129S1/CAST cells. For each allele, two sgRNAs specifically labelled every locus.

  2. Supplementary Figure 2 Confirmation of live-cell imaging and CLING’s specificity.

    (a) Very low laser usage implicates less bleaching and phototoxic effects, ensuring the viability of the cells during time-lapse imaging. Thus, we used a power meter to convert linearly the laser output that is set in percent units in the operating ZEN black software (Zeiss) to µWatt (µW). The grey regions in the plots indicate the bandwidths that were used in all SNP-CLING or CLING experiments. Since a cell has a self-power of ~7 µW, the used laser power was suitable for live cell imaging. The laser at 405 nm was used to image Hoechst 33342 9 (n = 1, Pearson’s correlation). (b) 458 nm were used to visualize GFP fluorescence of the nucleolus (n = 1) and (c) 514 nm for mVenus (n = 1, Pearson’s correlation). (d) mCherry was excited with a 594 nm laser (n = 1, Pearson’s correlation). (e) CLING-signals were characterized in detail to get an impression of the variety of accumulated foci in the nucleus, as well as in the cytosol, in the presence or absence of sgRNAs or dCas9. A sgRNA recognizing telomere sequences was used to establish the transient transfection conditions (n = 10), (Chen, Gilbert et al. 2013). (f) Cytosolic signals in addition to nuclear foci occurred very rarely in some cells, independent of the used sgRNA pool (2/10 nuclei, n = 3, arrowheads = CLING signals of FIRRE and non-specific signals). (g) Transfections without the sgRNA pool generated hazy and cloudy signals throughout the nucleus. Accumulated nuclear punctae were not found (n = 10). (h) In very rare cases one or two foci were observed in a transfection without dCas9 (0.5/10 nuclei, n = 4, arrowheads = CLING signals of CISTR-ACT). (i) An alternating order of MS2-PP7-MS2-PP7 stemloops was cloned into a plasmid to determine whether or not the fluorochromes generated signals that overlap. We used the telomeres sgRNA and determined that the fluorochromes bound specifically. At every foci, both fluorochromes were detected as totally overlapped and mixed signals, as it was previously shown for other fluorochromes and repetitive sequences (Ma, Tu et al. 2016).

  3. Supplementary Figure 3 Signal processing and CLING’s specificity.

    Signal processing of all acquired SNP-CLING images in (a) mESCs cells, in (b) mEFs, and CLING images in (c) RPE-1 cells. Arrowheads depict specific and non-specific CLING foci. The images collected on the LSM880+Airyscan have increased sensitivity (4-8 x) due to the 32 channel gallium arsenide phosphide photomultiplier tube (GaAsP-PMT) area detector that collects a pinhole-plane image at every scan position (Huff 2015). This increased sensitivity results in detection of both specific and background fluorochrome-derived signals in each image, which can be differentiated in post-acquisition image processing (described below and in methods). The number, sizes and brightness of non-specific background signals vary depending on the expression of the transfected fluorescent proteins and the imaging conditions (laser power, see Figure S2). The number of visible signals corresponding with the known number of alleles in a given cell line were obvious in the live view. For post-acquisition image analysis, z-stack planes were first merged by performing a maximum intensity projection (MIP). The ‘best fit’ analysis option was used to preliminarily adjust intensity thresholds. X-Y dimensions at this stage are shown in the top row. In sequential manual adjustment steps, signal from background haze, random fluorescent protein accumulation, and/or potential off-target dCas9 binding events were removed (second and third row). Signals present in final processed images (bottom row) correspond to expected karyotypes: (a) a single signal for the sole Firre locus and a single signal for the allele-specifically labeled Ypel4 locus were detected in male mESCs; (b) a single signal for the allele-specifically labeled Firre locus was detected in female mEFs; (c) two signals for either the CISTR-ACT or the FIRRE loci were detected in diploid RPE-1 cells (Darrow, Huntley et al. 2016). To investigate the difference in signal intensities between specific and non-specific signals in all cell types, we calculated the relative signal intensities by generating the median intensity of all detected signals in a given nucleus. The median intensity was used to normalize all detected signals. The intensities as ratios are represented as bar graphs below the corresponding image and show that the specific signals were the brightest. Of note, specific signal intensities were at least two-fold higher than non-specific signals. In validation experiments without the transfection of sgRNAs, no bright nuclear foci were detected (see Figure S2g). (d, e) We also measured the three-dimensional sizes (x, y, z dimensions) of all foci detected by the ‘best fit’ analysis. The signals that corresponded with processed specific signals were the biggest signals, as can be seen in represented image panel (d). We further quantified the difference in signal size with measurements from at least 30 nuclei (e). The specific ‘biggest’ signals were present in 12.7±1.98 z-stack planes (each 0.17 µm), in comparison to the smaller background signals that were detected in 5.3±1.5 planes. In all instances, the brightest and biggest signals correspond to the known number of alleles in RPE-1, mESCs and mEFs. (f) To further address CLING’s specificity, we quantified signals of CISTR-ACT, XIST, and SOX9 in human RPE-1 cells in the presence and absence of dCas9. As expected, dCas9’s presence dramatically increased the occurrence of specific signals. On average, 30 % of transfected cells showed the expected diploid status (two signals), whilst some cells showed only one signal, and ˜30 % of transfected cells showed either no or many signals. (g) In SNP-CLING, we determined a specific separation between the parental alleles in 83 % of the imaged nuclei in hybrid 129S1/CAST MEFs. The remaining 17 % of cells showed either no or multiple signals of the second allele, or cross-labeling of one of the two alleles. Of the 83 % of cells, 12 % showed two foci, indicating mitotic stage G2. (h) Haploid signals of sgRNAs targeting either the 129S1 (75 %) or CAST (90 %) allele determined SNP-CLING’s specificity in hybrid 129S1/CAST MEFs. (i) The co-localization frequency (78 %) of targeting CISTR-ACT with orthologous MS2 and PP7 sgRNA pools was highly specific in RPE-1 cells. (j) In ˜6 of 10 cells, a clear separation between XIST and TSIX was achieved (no co-localization) in RPE-1 cells. The heterochromatin formation of the inactive X chromosome and different chromatin compaction rates may also influence the spatial distances between two given loci.

  4. Supplementary Figure 4 SNP-CLING signals of mouse loci.

    (a) Gene-density (Gencode vM9) and chromosomal sizes (mm10) of the mouse genome. Loci on chromosome 1 (large chromosome), chromosome 7 and 11 (gene-rich chromosomes), chromosome 15 (gene-poor / small chromosome), and chromosome 18 (gene-poor / small chromosome), and Firre on chromosome X, were selected for SNP-CLING experiments. (b) Examples of allele-specific SNP-CLING signals (separate channels) of maternal and paternal loci in combination with rRNA staining of the nucleoli in female 129S1/CAST mEFs (n = 10, arrowheads = specific SNP-CLING foci of maternal and paternal alleles, or CLING foci for chr. 18 Puf-Pum1-iRFP670).

  5. Supplementary Figure 5 CLING signals of mouse and human loci.

    Examples of labeling various human and mouse loci with sgRNA pools. Four different sgRNAs were mixed in combinations of three to determine the best set for imaging (arrowheads = specific CLING foci). Before relevant experiments, the use of each sgRNA pool was specifically tested for (a) mouse loci in male mESCs (Firre on chromosome X was therefore detected as single voxel, n = 10), and (b) for coding genes in human in human RPE-1 or C28/I2 cells (n = 10).

  6. Supplementary Figure 6 Data points of individual samples of figure 5.

    (a) Individual data points of figure 5b, (b) = figure 5c, (c) = figure 5d, (d) = figure 5h, (e) = figure 5i, (f) = figure 5k, (g) = figure 5l.

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