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Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing

Nature Neuroscience volume 21, pages 1670–1679 (2018)Cite this article

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Abstract

In females with X-linked genetic disorders, wild-type and mutant cells coexist within brain tissue because of X-chromosome inactivation, posing challenges for interpreting the effects of X-linked mutant alleles on gene expression. We present a single-nucleus RNA sequencing approach that resolves mosaicism by using single-nucleotide polymorphisms in genes expressed in cis with the X-linked mutation to determine which nuclei express the mutant allele even when the mutant gene is not detected. This approach enables gene expression comparisons between mutant and wild-type cells within the same individual, eliminating variability introduced by comparisons to controls with different genetic backgrounds. We apply this approach to mosaic female mouse models and humans with Rett syndrome, an X-linked neurodevelopmental disorder caused by mutations in the gene encoding the methyl-DNA-binding protein MECP2, and observe that cell-type-specific DNA methylation predicts the degree of gene upregulation in MECP2-mutant neurons. This approach can be broadly applied to study gene expression in mosaic X-linked disorders.

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Fig. 1: Single-cell SNP sequencing in a female mouse model of Rett syndrome.
Fig. 2: Single-nucleus SNP sequencing of human Rett brain tissue.
Fig. 3: Cell-type-specific DNA methylation patterns predict gene misregulation in Rett syndrome.
Fig. 4: Characterization of MECP2-regulated genes in human and mouse.

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Data availability

All sequencing data reported in this study have been deposited in the NCBI Gene Expression Omnibus under accession GSE113673.

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Acknowledgements

D. Harmin assisted with data processing and scripting. H. Gabel provided thoughtful comments on the manuscript, and A. Ratner provided technical assistance. The single-cell methylation data was graciously provided by C. Luo and J. Ecker. We thank the Rett Syndrome Research Trust for support of this work, along with NIH K08NS101064 (WR), F32NS101739 (LDB), and R01NS048276 (MEG). We are also grateful to donor families and the Harvard Brain Bank for providing tissue from brain donors with Rett syndrome.

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Author notes

  1. These authors contributed equally: William Renthal, Lisa D. Boxer.

Authors and Affiliations

  1. Department of Neurobiology, Harvard Medical School, Boston, MA, USA

    William Renthal, Lisa D. Boxer, Sinisa Hrvatin, Emmy Li, Andrew Silberfeld, M. Aurel Nagy, Eric C. Griffith, Thomas Vierbuchen & Michael E. Greenberg

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  1. William Renthal
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Contributions

W.R. and L.D.B. conceived, designed, and performed all experiments and analyzed all data. S.H. developed the cell dissociation protocol. E.L. designed and performed gene-specific library preparations. S.H., A.S., and T.V. designed and performed FACS experiments. M.A.N. mapped sequencing data. W.R., L.D.B., E.C.G., and M.E.G. wrote the manuscript. M.E.G. advised on all aspects of the study.

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Correspondence to Michael E. Greenberg.

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M.E.G. is on the Board of Directors and holds equity in Allergan, plc.

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Integrated supplementary information

Supplementary Figure 1 Identification of SNPs in cis with the mutant Mecp2 allele.

Tracks of sequencing reads from 6 wild-type (WT) and 6 MeCP2 KO (KO) hemizygous male mice at the indicated genomic locus. The reference sequence is displayed in gray; single nucleotide polymorphisms (SNPs) A or G, are displayed by green or orange, respectively. The four 129/OlaHsd SNPs shown are clearly linked to the Mecp2-mutant locus and are only present in MeCP2 KO mice. This line has been backcrossed by Jackson labs > 38 times, which indicates these regions are very closely linked even though they are 1.5–1.7 megabases from the MeCP2 locus. We find that these SNPs are conserved across multiple generations of male hemizygous and female heterozygous mice and thus could be confidently used to distinguish Mecp2-mutant from wild-type cells in scRNA-seq datasets.

Supplementary Figure 2 Single-cell sequencing of Mecp2+/– mice.

(a) Graph clustering (t-SNE) plot of 12,451 cells from visual cortex. Colors represent cell types as indicated in legend. (b) The number of cells for which a transcriptotype could be assigned based on their expression of single nucleotide polymorphisms.

Supplementary Figure 3 Single-cell sequencing of 8-week-old male Mecp2–/y mice.

(a) Graph clustering (t-SNE) plot of 11,533 cells from visual cortex. Colors represent cell types as indicated in legend. (b) Total number of WT and KO cells sequenced that passed quality control (see methods). (c) Violin plot of normalized Mecp2 expression from WT or KO cells. Mecp2 expression is significantly reduced in the Mecp2 KO (****P < 0.0001, Mann-Whitney Utest, n = 4,560 WT cells and 6,973 KO cells), but it should be noted that only exons 3 and 4 are deleted in this mouse, so it is not unexpected that some remaining Mecp2 expression is detected (min and max represent range of data). (d) Venn diagram depicting the overlap between significantly up-regulated genes (FDR < 0.1, monocle2) in male Mecp2-/y excitatory neurons compared to wild-type control animals and the significantly up-regulated genes (FDR < 0.1, monocle2) in female Mecp2+/- excitatory mutant neurons compared to wild-type excitatory neurons from the same set of mice. There is significant overlap (hypergeometric test, P = 7.2 × 10−14). (e) Mean fold-change in gene expression of Mecp2-/y v WT excitatory neurons for genes with high mCA (top 25% mCA/CA, 50 gene bins, 10 gene step) or low mCA (bottom 66% mCA/CA, 100 gene bins, 10 gene step) binned according to gene length. (f) Mean fold-change in gene expression of Mecp2-/y excitatory neurons compared to WT controls binned according to the level of gene body DNA methylation (mCA/CA, 100 gene bins, 10 gene step). (g) Mean fold-change in gene expression of Mecp2-/y excitatory neurons compared to WT controls binned according to gene body MeCP2 ChIP enrichment (MeCP2 ChIP/input) obtained from CaMKIIα-positive WT excitatory neurons (MeCP2 ChIP1 and MeCP2 ChIP2 denote two individual MeCP2 ChIP experiments, 100 gene bins, 10 gene step). The lines in E-G represent mean fold-change in expression for genes binned as described; the ribbon is s.e.m. of each bin. Bins sizes were determined by the length of gene lists.

Supplementary Figure 4 Cell-type-specific neuronal and non-neuronal MeCP2-dependent gene misregulation in male Mecp2–/y mice.

While MeCP2 is most highly expressed in neurons, it is expressed in nearly all cell types and in the brain its mutation may contribute to dysfunction in glia and microglia as well51–54. (a) Venn diagram depicting the significantly up- and down-regulated genes that are expressed across all four cell types (FDR < 0.1, normalized expression > 0.1 in each cell type, 1230 cells sampled per cell type. Note that the corresponding supplementary tables have a greater number of significantly regulated genes in each cell type than the Venn diagrams because the tables do not require a minimum expression threshold across all cell types). We did sequence 112 WT and 154 KO astrocytes in these experiments, but differential expression analysis was underpowered compared to the other cell types. (b) Heatmap illustrating the relative mean expression level of significantly misregulated genes (columns) from (a) across each cell type (rows). (c) Preferential up-regulation of longer genes in certain mutant Mecp2 non-neuronal cell types such as oligodendrocytes and to a lesser degree vascular cells. Longer genes are more likely to be up-regulated in the absence of MeCP2 because they, on average, have more methylated cytosines within their gene bodies. Analysis of DNA methylation patterns in non-neuronal cell types will help interpret which genes are more likely to be direct targets of MeCP2. Graphs show mean fold-change in gene expression of Mecp2-/y cells of the indicated cell type versus WT cells of the same cell type (KO v WT) or two groups of cells randomly sampled irrespective of genotype (Random) binned according to gene length. The lines represent mean fold-change in expression for all expressed genes in 1000 gene bins with 100 gene steps; the ribbon is s.e.m. of each bin.

Supplementary Figure 5 Characterization of non-cell-autonomous effects in female Mecp2+/– mice.

(a) Mean fold-change in gene expression of wild-type excitatory neurons from female Mecp2-/+ mice (671 cells) compared to wild-type excitatory neurons from female Mecp2+/+ control mice (sampled 671 cells) binned according to gene body DNA methylation level derived from mouse excitatory neurons (Pearson’s r = 0.04, mCA/CA, 25 gene bins, 2 gene step). (b) Mean fold-change in gene expression of wild-type excitatory neurons from female Mecp2-/+ mice compared to wild-type excitatory neurons from female Mecp2+/+ control mice (Pearson’s r = 0.02, binned according to gene length (25 gene bins, 2 gene step). The correlations in A and B were not significantly different from the respective correlations observed when comparing sets of excitatory neurons obtained by combining randomly sampled wild-type neurons from both Mecp2+/+ and Mecp2+/- mice (A, permutation test, P = 0.55; B, permutation test, P = 0.73). The lines represent mean fold-change in expression for genes binned as described; the ribbon is s.e.m. of each bin.

Supplementary Figure 6 Rett syndrome donor characteristics.

(top) Table describing sex, age, MECP2 mutation, post-mortem interval (PMI) in hours (h), and the brain region dissected for the three Rett donors. Samples were obtained from the Harvard Brain Bank with approval from Rettsyndrome.org. (bottom) Schematic of MECP2 protein and its two major functional domains, the methyl-binding domain (MBD) and the transcriptional repression domain (TRD). All three donors harbored nonsense mutations at R255 located within the TRD.

Supplementary Figure 7 Marker gene expression in human single-nucleus RNA-sequencing cell types.

Heatmap of known marker genes for excitatory neurons (SLC17A7), interneurons (GAD1, VIP, PVALB, SST), oligodendrocytes (OLIG1), astrocytes (AQP4), microglia (C1QA), and endothelial cells (CLDN5). Each column represents an individual cell.

Supplementary Figure 8 Identification of allele-specific SNPs from Rett donor samples.

Heatmaps describe the number of RNA-seq reads from the MECP2high sorted nuclei of each donor (see methods) which contain the reference (REF) or alternate (ALT) sequence at the indicated SNP (rows of the heatmap).

Supplementary Figure 9 Single-nucleus RNA-sequencing of occipital cortex from three females with Rett syndrome.

(a) Graph clustering grouped nuclei from the three individuals based on their specific brain cell types. Nuclei clustered similarly regardless of MECP2 transcriptotype. Graph clustering was performed as described in the methods except that the significantly misregulated (FDR < 0.01, monocle2) genes in mutant excitatory neurons were omitted from the variable genes used to cluster the nuclei. (b) The number of significantly misregulated genes (FDR < 0.01, monocle2) in 953 randomly sampled excitatory neurons that have been matched to both the number and transcript depth of VIP interneurons. The mean and standard deviation of 10 iterations of excitatory neuron sampling are shown. The number of significantly misregulated genes (FDR < 0.01, monocle2) in VIP interneurons is shown as a comparison, indicating the greater number of genes detected in Fig. 2 is largely due to the number of neurons and reads detected.

Supplementary Figure 10 Correlation of MECP2-dependent gene expression with DNA methylation in individual Rett syndrome donors.

Significantly misregulated genes (FDR < 0.1, monocle2) were determined by comparing mutant and wild-type excitatory neurons within the same individual donor. For each of the three donors, the mean fold-change in gene expression between mutant and wild-type excitatory neurons within the same individual were compared to gene body DNA methylation level derived from human excitatory neurons (mCH/CH, 100 gene bins, 10 gene step). The lines in E-G represent mean fold-change in expression for genes binned as described; the ribbon is s.e.m. of each bin.

Supplementary Figure 11 MECP2-dependent gene expression in human excitatory neurons and VIP interneurons correlates with DNA methylation in the CG dinucleotide context.

(a-b) Mean fold-change in gene expression of R255X MECP2 nuclei compared to WT nuclei (R255X v WT) or of two groups that were randomly assigned transcriptotypes (Random) is binned according to gene body DNA methylation level (mCG/CG) derived specifically from their respective neuronal subtype. The lines represent mean fold-change in expression for genes binned as described; the ribbon is s.e.m. of each bin. Bin sizes were scaled based on the length of the respective gene lists. (a) Gene expression changes (FDR < 0.1, monocle2, genes > 10 kb) from R255X v WT or an equal number of genes from Random excitatory neurons is compared to patterns of DNA methylation (mCG/CG) from excitatory neurons (250 gene bins, 25 gene step). (b) Gene expression changes (FDR < 0.25, monocle2, genes > 10 kb) from R255X v WT or an equal number of genes from Random VIP interneurons is compared to patterns of DNA methylation (mCG/CG) from VIP interneurons (70 gene bins, 7 gene step). It is important to note that the first ~3 kb of gene bodies (on average) have significantly less DNA methylation than the remainder of the gene body, which for very short genes, will disproportionately reduce gene body methylation level even when 3’ regions of the gene body are highly methylated. Thus, gene length is likely contributing in part to the strong correlation observed between gene body mCG/CG level and MECP2-dependent gene upregulation. However, gene length probably does not account for the entire correlation between mCG/CG level and MECP2-dependent gene upregulation because mCG/CG level still predicts this effect in excitatory neurons for genes > 75 kb (Pearson’s r = 0.2; P < 0.001). Higher-resolution single-cell methylation data will help separate the effects of gene length and the fraction of gene body mCG/CG.

Supplementary Figure 12 MECP2-dependent gene misregulation in individual Rett syndrome donors.

Heatmaps depict the genes that are significantly up-regulated (left) or down-regulated (right) (FDR < 0.1, monocle2) in any of the three individual donors from the analysis of differential expression between R255X MECP2-mutant and wild-type excitatory neuronal nuclei. Each row represents a single gene, and the color (see color bar) indicates the log2 fold-change in gene expression between R255X MECP2-mutant and wild-type excitatory neurons. Note that while we have focused our attention on human MECP2 target genes that are significantly misregulated in all three females with the MECP2 R255X mutation, many of these genes were misregulated in the same direction across the three individuals and may simply be below the threshold for statistical significance. It is also possible that the genes that are misregulated in only one or two of the donors could reflect individual differences in genetic background, environment, age, or disease severity. Future studies could incorporate an individual’s cell-type-specific DNA methylation patterns to help characterize individual differences in the direct effects of MECP2 on gene expression.

Supplementary Figure 13 Expression of conserved MECP2-regulated genes across neuronal and non-neuronal cell types.

The relative mean expression of 58 MECP2-repressed (left) and 84 MECP2-activated (right) genes that are commonly misregulated across human and mouse excitatory neurons (rows) is displayed for each cell type listed (columns). The gene expression data is obtained from www.mousebrain.org55, and normalized within each row (red = highest expression, blue = lowest expression). There is significant enrichment of these genes in additional neuronal subtypes (for example cholinergic neurons and peripheral sensory neurons [Supplementary Table 17]), so characterization of the DNA methylation patterns and MECP2-dependent gene expression in these additional cell types could also prove informative.

Supplementary Figure 14 Characterization of gene expression and DNA methylation in Mecp2-mutant mice and Rett syndrome brain donors.

(a) Mean fold-change in statistically significant gene expression (FDR < 0.1, monocle2) versus gene length between female Mecp2+/- mutant excitatory neurons and female Mecp2+/- WT excitatory neurons (KO v WT, Pearson’s r = 0.20) or of two groups of excitatory neurons that were randomly assigned transcriptotypes (Random, Pearson’s r = 0.03). The correlations between gene expression changes and gene length in KO v WT were significantly different from Random (permutation test, P < 0.001). (b) Mean fold-change in statistically significant gene expression (FDR < 0.01, monocle2) of R255X MECP2 excitatory neuronal nuclei compared to WT excitatory neuronal nuclei (R255X v WT, Pearson’s r = 0.07) or of two groups of excitatory neurons that were randomly assigned transcriptotypes (Random, Pearson’s r = 0.00) is binned according to gene length. The correlations between gene expression changes and gene length in R255X v WT were significantly different from Random (permutation test, P = 0.001). (c) Gene body DNA methylation level (mCH/CH) as a function of gene length in both excitatory neurons (red) and VIP interneurons (blue). The lines represent mean fold-change in gene expression (a,b) or mCH/CH (c) for genes binned according to gene length; the ribbon is s.e.m. of each bin. Bin sizes were scaled based on the length of the respective gene lists (A, 100 gene bins, 10 gene step B, 250 gene bins, 25 gene step, C, 1000 gene bins, 100 gene step).

Supplementary Figure 15 Correlation of MeCP2-dependent gene regulation with gene length and DNA methylation in neuronal nuclei.

Johnson et al. recently reported that MeCP2 mutations cause the downregulation of long gene mRNA, in neuronal nuclei, and that these long gene transcripts are subsequently up-regulated in the cytoplasm through an as yet undescribed post-transcriptional mechanism56. However, in this study56 the association between gene body DNA methylation and changes in gene expression was not analyzed. (a-c) Reanalysis of gene expression differences between biotin-tagged Mecp2R106W/y excitatory neurons (mutant) and biotin-tagged WT MeCP2 excitatory neurons (WT) from Johnson et al. shows that genes with high levels of DNA methylation are preferentially up-regulated in the nuclei of male biotin-tagged Mecp2-mutant mice compared to wild-type controls. Mean fold-change of significantly regulated gene expression (FDR < 0.1, mutant versus WT) in male (A, 50 gene bins, 5 gene step) or female (b, 30 gene bins, 3 gene step) Mecp2 knockin mice binned according to the fraction of excitatory neuron DNA methylation (mCA/CA)57. Male gene expression compares separate mutant and wild-type control mice, while the female gene expression compares mutant and wild-type cells within the same animal. (c) Mean fold-change in significantly regulated gene expression (FDR < 0.1, female mutant versus WT) for genes with high levels of DNA methylation (top 50% mCA/CA) or low levels of DNA methylation (bottom 50% mCA/CA) binned according to gene length (20 gene bins, 2 gene step). The lines represent mean fold-change in expression for genes binned as described; the ribbon is s.e.m. of each bin.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–15

Reporting Summary

Supplementary Note

Supplementary Table 1

Female Mecp2+/– mutant (593 cells from 5 mice) vs. Mecp2+/– wild-type excitatory neurons (593 cells sampled from 5 mice).

Supplementary Table 2

Male Mecp2–/y (1,230 cells) vs. Mecp2+/y (1,230 cells) excitatory neurons.

Supplementary Table 3

Male Mecp2–/y (1,230 cells) vs. Mecp2+/y (1,230 cells) endothelial cells.

Supplementary Table 4

Male Mecp2–/y (1,230 cells) vs. Mecp2+/y (1,230 cells) Microglia.

Supplementary Table 5

Male Mecp2–/y (1,230 cells) vs. Mecp2+/y (1,230 cells) Oligodendrocytes.

Supplementary Table 6

Female Mecp2+/– wild-type excitatory neurons (671 cells from 5 mice) vs. female Mecp2+/+ wild-type excitatory neurons (671 cells sampled from 4 mice).

Supplementary Table 7

Female Rett syndrome donors 1–3 combined: mutant excitatory neurons (5,809 nuclei) vs. wild-type excitatory neurons (5,152 nuclei).

Supplementary Table 8

Female Rett syndrome donors 1–3 combined: mutant VIP interneurons (552 nuclei) vs. wild-type VIP interneurons (401 nuclei).

Supplementary Table 9

Female Rett syndrome donor 1: mutant (1,243 nuclei) vs. wild-type (1,157 nuclei) excitatory neurons.

Supplementary Table 10

Female Rett syndrome donor 1: mutant (157 nuclei) vs. wild-type (127 nuclei) VIP interneurons.

Supplementary Table 11

Female Rett syndrome donor 2: mutant (1,533 nuclei) vs. wild-type (1,650 nuclei) excitatory neurons.

Supplementary Table 12

Female Rett syndrome donor 2: mutant (103 nuclei) vs. wild-type (113 nuclei) VIP interneurons.

Supplementary Table 13

Female Rett syndrome donor 3: mutant (3,033 nuclei) vs. wild-type (2,345 nuclei) excitatory neurons.

Supplementary Table 14

Female Rett syndrome donor 3: mutant (292 nuclei) vs. wild-type (161 nuclei) VIP interneurons.

Supplementary Table 15

Female Rett syndrome donors 1–3: Table for heatmap in Supplementary Fig. 12.

Supplementary Table 16

Overlap lists between MECP2-regulated genes in human and mouse.

Supplementary Table 17

Cell type enrichment scores for conserved MECP2 regulated genes (160,796 cells) displayed in Supplementary Fig. 13 heatmap. Enrichment scores calculated by permutation.

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Renthal, W., Boxer, L.D., Hrvatin, S. et al. Characterization of human mosaic Rett syndrome brain tissue by single-nucleus RNA sequencing. Nat Neurosci 21, 1670–1679 (2018). https://doi.org/10.1038/s41593-018-0270-6

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