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Three-dimensional genome restructuring across timescales of activity-induced neuronal gene expression

A Publisher Correction to this article was published on 23 July 2020

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Abstract

Neuronal activation induces rapid transcription of immediate early genes (IEGs) and longer-term chromatin remodeling around secondary response genes (SRGs). Here, we use high-resolution chromosome-conformation-capture carbon-copy sequencing (5C-seq) to elucidate the extent to which long-range chromatin loops are altered during short- and long-term changes in neural activity. We find that more than 10% of loops surrounding select IEGs, SRGs, and synaptic genes are induced de novo during cortical neuron activation. IEGs Fos and Arc connect to activity-dependent enhancers via singular short-range loops that form within 20 min after stimulation, prior to peak messenger RNA levels. By contrast, the SRG Bdnf engages in both pre-existing and activity-inducible loops that form within 1–6 h. We also show that common single-nucleotide variants that are associated with autism and schizophrenia are colocalized with distinct classes of activity-dependent, looped enhancers. Our data link architectural complexity to transcriptional kinetics and reveal the rapid timescale by which higher-order chromatin architecture reconfigures during neuronal stimulation.

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Fig. 1: Identification of dynamic and invariant looping interactions across neuronal activity states.
Fig. 2: Activity-induced enhancers connected to distal target genes via looping interactions predict activity-stimulated expression.
Fig. 3: Unique topological motifs underlie the activity-dependent transcriptional response.
Fig. 4: IEGs form shorter and less complex loops than SRGs.
Fig. 5: Activity-induced loops form before and persist after peak mRNA levels of IEGs.
Fig. 6: Neuropsychiatric disease-associated SNVs colocalize with long-range activity-induced and -decommissioned looped enhancers.

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Data availability

We have uploaded all data from this manuscript to the Gene Expression Omnibus (GEO) under accession number GSE131025.

Code availability

5C analysis code has been included as a supplementary zip file.

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Acknowledgements

We thank members of the Cremins laboratory for helpful discussions. J.E.P.-C. is a New York Stem Cell Foundation Robertson Investigator and an Alfred P. Sloan Foundation Fellow. This research was supported by the New York Stem Cell Foundation (J.E.P.-C.), the US National Institutes of Health (NIH) Director’s New Innovator Award from the National Institute of Mental Health (1DP2MH11024701, J.E.P.-C.), a National Institute of Mental Health grant (R01MH112766, J.D.S.), a Chan Zuckerberg Ben Barres Early Career Acceleration Award (J.D.S.), a 4D Nucleome Common Fund grant (1U01HL12999801, J.E.P.-C.), a joint NSF–NIGMS grant to support research at the interface of the biological and mathematical sciences (1562665, J.E.P.-C.), a Brain Research Foundation Fay Frank Seed Grant (J.E.P.-C.), a National Institute of Neurological Disorders and Stroke grant (R01NS114226, J.E.P.-C. and J.D.S.), and by National Science Foundation Graduate Research Fellowships under grant numbers DGE-1321851 (J.A.B.) and DGE-1321851 (L.R.F.).

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Authors and Affiliations

Authors

Contributions

J.A.B., E.D.P., J.D.S., and J.E.P.-C. designed the experiments. E.D.P. isolated, cultured, treated, and fixed cells. J.A.B. performed RNA-seq, ChIP–seq, and 5C assays. J.A.B. and L.R.F. called loops on 5C data. J.A.B., K.R.T., and H.C. called loops on Hi-C data. J.A.B. analyzed the intersection of loop calls, ChIP–seq, gene expression, and disease-associated genome variants. M.H.G. performed LD score regression. J.A.B. and K.F. analyzed short-term activity-induction experiments. J.A.B., J.D.S., and J.E.P.-C. wrote the manuscript.

Corresponding authors

Correspondence to Jason D. Shepherd or Jennifer E. Phillips-Cremins.

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The authors declare no competing interests.

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Peer review information Nature Neuroscience thanks Hyejung Won and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Mapping genome folding across neural activity states.

a, Representative immunofluorescence images of DAPI (blue), MAP2 (green), PSD95 (magenta) signal across conditions. Results were consistent across 2 culture batches, 4 total 5C replicates, 3 RNA-seq replicates, and H3K27ac ChIP replicate analyzed. b,c, Fold change vs amplitude plots of RNA-seq data comparing the Bic vs Untreat conditions (b) and TTX vs Untreat conditions (c). d, Interaction frequency heatmaps of 1-3 Mb regions surrounding the Fos, Arc, Neurexin-1, and Neuroligin-3 genes (labeled in green) across embryonic stem (ES) cells, neural progenitor cells (NPCs), and cortical neurons (CNs) (data analyzed from Bonev+ 2017). e, Interaction frequency heatmaps of the regions presented in (a) across tetrodotoxin-treated (TTX), untreated, and bicuculline-treated (Bic) DIV16 cortical neurons.

Extended Data Fig. 2 Activity-induced loops are not present earlier in cortical neuron differentiation.

a, Zoom-in heatmaps of critical loops presented throughout the paper. From left to right the columns are Obs/Exp heatmaps of HiC (Bonev et al.) data from 1) embryonic stem (ES) cells, 2) neural progenitor cells (NPC), 3) cortical neurons (CN), followed by 5C interaction score heatmaps across the 4) TTX, 5) untreated, and 6) BIC treated conditions. Genes of interest in each zoom window, Figure panels where same loop is further analyzed, and loop classification are listed on left.

Extended Data Fig. 3 5C data correlateions cluster by condition.

a, b, Pearson’s correlation coefficients of background-normalized contact frequencies (‘observed/expected’) at activity-induced loops (a) and activity-invariant loops (b) across each pair of replicates. The N = 4 independent biological replicates for each condition were then hierarchically clustered based on correlation results.

Extended Data Fig. 4 Activity-induced and activity-invariant loops are reproducible across condition replicates.

a, Zoom-in interaction score heatmaps from each of the 12 5C replicates generated for critical loops presented throughout the paper. Genes of interest in each zoom window, Figure panels where same loop is further analyzed, and loop classification are listed on left.

Extended Data Fig. 5 Identifying dynamic looping across neural activity states.

a, Diagram of 5C processing pipeline used to call significant constitutive and dynamic loops (bottom right) starting from 5C interaction frequency counts for all pairs of 4 kb genomic bins within queried regions across 4 replicates (from two litter/culture batches) of each condition (top left). First the local domain background signal is quantified using a donut expected model (Rao + 2014) and removed from the interaction frequency signal. Probabilistic modeling converts these expected-normalized interaction frequencies to an ‘interaction score’ (bottom left). For a bin-bin pair to be classified as looping, its interaction score must fall above a given ‘significance threshold’. For a looping bin-bin pair to be classified as ‘Bic-only’ the minimum interaction score of the Bic replicates must exceed the maximum interaction score of the four TTX replicates by a given ‘difference threshold’ (Supplementary Methods). Looping pixels not classified as Bic- or TTX-only are classified as constitutive (top right). Bin-bin pairs of the same class are then grouped into clusters if they are directly adjacent; clusters below a selected size threshold are removed from looping classification (bottom right). See Methods for more details. b, Scatterplot of the background-normalized contact frequency (‘Observed/Expected’) counts of looping-classified pixels in TTX and Bic conditions.

Extended Data Fig. 6 Quantifying activity-dependent regulatory elements.

a, Spearman’s correlation coefficients for terms included in models (Fig. 2f-i). b, c, Results of promoter-only (b) and promoter plus nearest enhancer (c) models for only genes that form loops to classified enhancers within 5C regions. N = 45 genes analyzed. d, R2 values of models presented in (b-c). e, Coefficients of each explanatory variable term in models presented in (b-c). t-statistic p-values and standard errors represented via stars and error bars, respectively. fh, Acetylation heatmaps, pileups of classified activity-induced (f), activity-decommissioned (g), invariant (h) enhancers.

Extended Data Fig. 7 Assessing activity-dependent regulation using murine HiC (Bonev et al.33) loop calls.

a, Expression (TPM) of the transcripts whose promoters intersect each looping class. P-values presented calculated using two-tailed Wilcoxon signed-rank test. b, Expression (log2(TPM)) of the genes whose promoters fall opposite activity-induced (class 2) and activity-decommissioned (class 3) enhancers in genome-wide cortical neuron loops, original data from Bonev et al.33. Number of genes in each class (a, b) listed as N = above boxes. Boxes in a-b range from lower to upper quartile with median line, whiskers extend to min/max data point within 1.5*interquartile range. c, Number of loops called in HiC data obtained from embryonic stem cells (ES), neural progenitor cells (NPCs), and cortical neurons (CN) (Bonev et al.33). c,d, Interaction frequency heatmaps (top) and thresholded loop calls (bottom) for a ~2.5 Mb region surrounding the Synaptotagmin1 Syt1 gene. d,e, Expression (log2(TPM)) of the genes whose promoters fall opposite activity-induced (class 2) and activity-decommissioned (class 3) enhancers in genome-wide cortical neuron loops, original data from Bonev et al.33. Number of genes in each class listed above boxes. The remaining gene ontology terms passing the FDR < 0.05 threshold for class 2 (a) which could not be presented in Fig. 3. N = 2139 Class 2 genes, enrichment calculated using Webgestalt65. f, (Left) Gene ontology enrichment ratios for class 3 genes parsed by expression into activity downregulated (Bic/TTX < 2/3), activity invariant (5/6 < Bic/TTX < 6/5), and activity upregulated (Bic/TTX > 3/2) groups. (Right) Genes found in the ‘regulation of trans-synaptic signaling’ and ‘synapse organization’ GO terms enriched in activity downregulated class 3 genes.

Extended Data Fig. 8 Expression of Bdnf transcripts.

a, Depiction of the 12 RefSeq transcript isoforms of the Bdnf gene, above which we annotate the 8 promoters as in Hong et al., Neuron, 2008. b, Expression strip plots of each Bdnf isoform, organized in columns by shared promoter. N = 3, mean lines plotted. c, Boxplots overlaid by strip plots of count of opposing looping anchors that contain an activity-dependent enhancer for rapid immediate early genes (rIEGs, as defined as rPRGs in Tyssowski et al.9), translation-independent SRGs (tiSRGs, defined as dPRGs in Tyssowski et al.9), translation-dependent SRGs (tdSRGs, defined as SRGs in Tyssowski et al.9), and all genes. Boxes range from lower to upper quartile with median line, whiskers extend to min/max data point within 1.5*interquartile range.

Extended Data Fig. 9 Verification of the eRNA signature captures enhancer activity dynamics.

a, Genome browser view of ~50 kb window surrounding the Fos gene. Rows from top to bottom present: 1) RNA signal in active neurons from Kim et al. 12, 2) RNA signal in inactive neurons from Kim et al. 12, 3) RNA signal from neurons in the Bic condition, 4) RNA signal from neurons in the TTX condition, 5) H3K27ac ChIP-seq signal from neurons in the Bic condition, 6) H3K27ac ChIP-seq signal from neurons in the TTX condition. b, RNA-seq signatures at enhancers near Fos across 0, 5, 20, 60, and 360 minutes of acute neuron activation.

Extended Data Fig. 10 Foxp1 and Slc4a10 fall opposite disease-associated variants in conserved classified loops.

a, Number of loops called in HiC data obtained from human fetal cortical plate (CP) and germinal zone (GZ) tissue (Won et al.41). b, Interaction frequency heatmap (left) and thresholded loop calls (right) of the 2.5 Mb region surrounding the Bdnf gene in human cortical plate (CP) fetal tissue. ce, Human (c) and mouse (d) interaction frequency heatmaps of a 2 Mb region surrounding the Foxp1 gene. The expression of the looping Foxp1 isoform labeled in green in (d) is plotted in (e). fh, Human (f) and mouse (g) interaction frequency heatmaps of a < 2 Mb region surrounding the Slc4a10 gene (green), followed by expression of its 5 expressed isoforms (h). N = 3 RNA-seq replicates in (e,h), mean lines plotted.

Supplementary information

Supplementary Information

Supplementary Tables 1, 2, 5 and 7.

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Supplementary Table

Supplemental Tables 3, 4, 6, 8–19.

Supplementary Software

Custom 5C Analysis Scripts.

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Beagan, J.A., Pastuzyn, E.D., Fernandez, L.R. et al. Three-dimensional genome restructuring across timescales of activity-induced neuronal gene expression. Nat Neurosci 23, 707–717 (2020). https://doi.org/10.1038/s41593-020-0634-6

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