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Three-dimensional genome structures of single sensory neurons in mouse visual and olfactory systems

Nature Structural & Molecular Biology volume 26, pages 297–307 (2019)Cite this article

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Abstract

Sensory neurons in the mouse eye and nose have unusual chromatin organization. Here we report their three-dimensional (3D) genome structure at 20-kilobase (kb) resolution, achieved by applying our recently developed diploid chromatin conformation capture (Dip-C) method to 409 single cells from the retina and the main olfactory epithelium of adult and newborn mice. The 3D genome of rod photoreceptors exhibited inverted radial distribution of euchromatin and heterochromatin compared with that of other cell types, whose nuclear periphery is mainly heterochromatin. Such genome-wide inversion is not observed in olfactory sensory neurons (OSNs). However, OSNs exhibited an interior bias for olfactory receptor (OR) genes and enhancers, in clear contrast to non-neuronal cells. Each OSN harbored multiple aggregates of OR genes and enhancers from different chromosomes. We also observed structural heterogeneity of the protocadherin gene cluster. This type of genome organization may provide the structural basis of the ‘one-neuron, one-receptor’ rule of olfaction.

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Fig. 1: Dip-C of single sensory neurons from the mouse eye and nose.
Fig. 2: 3D genome structures of rod photoreceptors.
Fig. 3: 3D genome structure in the MOE.
Fig. 4: Interchromosomal contacts between OR genes and their enhancers.
Fig. 5: 3D aggregation of OR genes and their enhancers.
Fig. 6: 3D structures of the clustered protocadherin locus.

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Data availability

Raw and processed data are deposited with GEO Series accession code GSE121791. All other data are available from the corresponding author upon reasonable request.

Code availability

Codes are available on GitHub as updates to the existing ‘dip-c’ and ‘hickit’ packages24: https://github.com/tanlongzhi/dip-c and https://github.com/lh3/hickit

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Acknowledgements

The authors thank X. Jin for advice on mouse breeding, the Bauer Core Facility at Harvard University—in particular Z. Niziolek—for flow sorting, H. Li for updating the ‘hickit’ package and helpful discussions, A. Chapman for advice on handling 96-well plates, and S. Lomvardas and R. Cao for helpful discussions. This work was supported by Beijing Advanced Innovation Center for Genomics at Peking University, and a generous gift grant from Xianhong Wu to Harvard University.

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Author notes

  1. These authors contributed equally: Longzhi Tan, Dong Xing.

Authors and Affiliations

  1. Department of Chemistry & Chemical Biology, Harvard University, Cambridge, MA, USA

    Longzhi Tan, Dong Xing, Nicholas Daley & X. Sunney Xie

  2. Belmont Hill School, Belmont, MA, USA

    Nicholas Daley

  3. Beijing Advanced Innovation Center for Genomics, Peking University, Beijing, China

    X. Sunney Xie

  4. Biomedical Pioneering Innovation Center, Peking University, Beijing, China

    X. Sunney Xie

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  1. Longzhi Tan
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Contributions

L.T., D.X., N.D., and X.S.X. designed the experiments. L.T., D.X., and N.D. performed the experiments. L.T. and N.D. analyzed the data. L.T. and X.S.X. wrote the manuscript.

Corresponding author

Correspondence to X. Sunney Xie.

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Competing interests

L.T., D.X., and X.S.X. are inventors on the patent WO2018217912A1 filed by President and Fellows of Harvard College that covers META and Dip-C.

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Integrated supplementary information

Supplementary Figure 1 Representative single-cell contact maps.

a, Histogram of the numbers of chromatin contacts per cell. The bin size is 10 k. Note that the number of contacts is affected by the method of whole-genome amplification (META is roughly two times homemade Nextera), the cell type, and in some cases, recent lots of Qiagen protease that may damage DNA. b, Contact maps from 4 single cells of different types. Cells are chosen randomly.

Supplementary Figure 2 Representative single-cell contact maps after haplotype imputation.

Similar to Supplementary Fig. 1, but after resolving the two haplotypes of each chromosome. Note that imputation is inefficient for chromosome X in Cell 136, because SNPs are sparse on chromosome X in the mouse strain B6D2F1/J.

Supplementary Figure 3 Additional information about principle component analysis (PCA) of single-cell chromatin compartment values.

a, Percentage of explained variance for the first 35 principal components (PCs). The fact that the top few PCs only explained a relatively small fraction of the total variance is consistent with previous observations that chromatin compartment is intrinsically heterogeneous even within the same cell type (Science. 43, 924–928, 2018; Nature. 547, 61–67, 2017). b, PCA is not qualitatively affected by down-sampling contacts, excluding cells, and changing the bin size. Similar to Fig. 1b, but down-sampled to 20 k (left) or 100 k (right) contacts per cell before performing PCA. In the right panels, cells with < 100 k contacts (60 out of 409, or 15%) were excluded. In the bottom right panel, compartment values were calculated per 100-kb in rather than 1-Mb.

Supplementary Figure 4 Average compartment values near cell-type-specific genes.

In Fig. 1d, the average compartment value was calculated from the 1-Mb bins that contain midpoints of cell-type-specific genes. Here each 1-Mb bin was shifted a certain amount (x axis), upstream or downstream, from gene midpoints. The median values of 5 cell types are shown.

Supplementary Figure 5 Cross sections of all rods and retinal precursors, colored by CpG frequency.

Similar to Fig. 2a, but for all rods and retinal precursors.

Supplementary Figure 6 Large-scale domains of radial positioning are consistent with large-scale patterns in bulk Hi-C.

a, Similar to Fig. 3c top (mature OSNs), but with intrachromosomal contact maps from bulk Hi-C data (red heatmap; normalization: balanced). b, c, Zoom-in views of two chromosomes.

Supplementary Figure 7 Quantification of OR-OR contact strengths is not affected if ORs near enhancers are excluded.

Similar to Fig. 4a and Fig. 4b but excluding ORs within 200 kb or 500 kb of any enhancers.

Supplementary Figure 8 Stochastic aggregation of a subset of ORs and enhancers in each mature OSN and unknown MOE cell.

a, The number of enhancers (left), the number of enhancers from other chromosomes (middle), and the number of chromosomes of enhancers (right) within 2.5 particle radii (~150 nm) of each enhancer. In each heat map, rows and columns are sorted by their average values. b, Similar to a but near each OR. c, d, Similar to a and b (on the same scales) for non-neuronal MOE cells.

Supplementary Figure 9 Most quantification of OR-OR and enhancer-enhancer aggregation is not affected by the distance threshold.

Similar to Fig. 5a and Fig. 5c, but with a distance threshold of 1.5 (~100 nm; left), 5.0 (~300 nm; middle), or 10.0 (~600 nm; right) particle radii instead of 2.5 particle radii (~150 nm).

Supplementary Figure 10 Interchromosomal interactions of the clustered protocadherin locus.

a, Probability for each 200-kb bin along the genome to be within 7.5 particle radii (~450 nm) from the centroid (chromosome 18: 37,431,420 bp) of clustered protocadherin promoters. For each bin, 3D distances from the two parental alleles were considered as two separate data points. b, Zoom-in views of two chromosomes.

Supplementary information

Supplementary Figures, Supplementary Table and Supplementary Notes

Supplementary Figures 1–10, Supplementary Table 1 and Supplementary Notes 1–3

Reporting Summary

Supplementary Dataset 1

Information about each single cell

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Tan, L., Xing, D., Daley, N. et al. Three-dimensional genome structures of single sensory neurons in mouse visual and olfactory systems. Nat Struct Mol Biol 26, 297–307 (2019). https://doi.org/10.1038/s41594-019-0205-2

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