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. 2021 May 5:14:664912.
doi: 10.3389/fnmol.2021.664912. eCollection 2021.

Environmental Enrichment Induces Epigenomic and Genome Organization Changes Relevant for Cognition

Sergio Espeso-Gil  1   2   3 , Aliaksei Z Holik  1 , Sarah Bonnin  1 , Shalu Jhanwar  1   2 , Sandhya Chandrasekaran  4   5 , Roger Pique-Regi  6 , Júlia Albaigès-Ràfols  1   2 , Michael Maher  1   2   2 , Jon Permanyer  1 , Manuel Irimia  1   2   7 , Marc R Friedländer  8 , Meritxell Pons-Espinal  1   2 , Schahram Akbarian  5 , Mara Dierssen  1   2 , Philipp G Maass  3   9 , Charlotte N Hor  1   2 , Stephan Ossowski  1   2
Affiliations

Environmental Enrichment Induces Epigenomic and Genome Organization Changes Relevant for Cognition

Sergio Espeso-Gil et al. Front Mol Neurosci. .

Abstract

In early development, the environment triggers mnemonic epigenomic programs resulting in memory and learning experiences to confer cognitive phenotypes into adulthood. To uncover how environmental stimulation impacts the epigenome and genome organization, we used the paradigm of environmental enrichment (EE) in young mice constantly receiving novel stimulation. We profiled epigenome and chromatin architecture in whole cortex and sorted neurons by deep-sequencing techniques. Specifically, we studied chromatin accessibility, gene and protein regulation, and 3D genome conformation, combined with predicted enhancer and chromatin interactions. We identified increased chromatin accessibility, transcription factor binding including CTCF-mediated insulation, differential occupancy of H3K36me3 and H3K79me2, and changes in transcriptional programs required for neuronal development. EE stimuli led to local genome re-organization by inducing increased contacts between chromosomes 7 and 17 (inter-chromosomal). Our findings support the notion that EE-induced learning and memory processes are directly associated with the epigenome and genome organization.

Keywords: 3D genome organization; Hi-C; chromatin accessibility; environmental enrichment; epigenetics; inter-chromosomal contacts; learning; postnatal development.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Experimental study design. (A) After weaning (P21), mice were exposed to environmental enrichment (EE) for 7 days (P28), and 30 days (P51, Methods). (B) Experimental workflow. Cortical tissue was homogenized from five different animals and split for the following protocols: ATACseq/SONOseq, ChIP-seq, RNAseq, label free and iTRAQ proteomics, and in situ Hi-C (2 biological replicates per condition, Nt = 20 animals in total). Neuronal and glial populations were sorted by the neuronal marker NeuN (Rbfox3) and pyramidal neurons by Thy+ (Tg[Thy1-YFP] mice). NeuN+ and NeuN– (3 biological replicates per condition, Nt = 30 of animals; for Thy+ 2 individual biological replicates per condition, Nt = 4 animals; see Methods. (C) Datasets available per technique and per different cell population (dark gray).
FIGURE 2
FIGURE 2
EE epigenetic changes during postnatal development. (A) Genomic features studied in the present study: left, enhancers predicted by GEP (Jhanwar et al., 2018) (Nt = 347112), middle: promoters 1,500 bp up- and 500 bp down-stream of TSS (Nt = 113,286); right: gene body regions (Nt = 46,833; see Methods). (B–D) Summary of differential changes (%) upon EE of chromatin accessibility and epigenetic marks over the total number of features in (B) enhancers, (C) promoters, (D) and gene-body regions (FDR < 0.05). (E) Top 100 enhancers, (F) promoters, and (G) Gene-body regions scaled in RPKM of the most important marks. Blue = increased; red = decreased signal upon EE, black = CTL samples. (H,I) Cell deconvolution of transcription-associated gene body marks: H3K36me3 and H3K79me2 in both whole cortex, neuronal, and non-neuronal datasets. Marker gene profile score (MPG) represents the first principal component regarding gene expression of cell-specific genes curated from single-cell studies involving GABAergic and pyramidal neurons, astrocytes, oligodendrocytes, microglia and endothelial cells (Mancarci et al., 2017) (Methods Details). (J) Overlap of differential H3K79me2 enrichment at P51 of whole cortex with NeuN+ and NeuN– (at FDR < 0.05). (K) Time-course plot showing the progressive increase of differential binding sites (DBS) of H3K79me2 (P51 vs. P28) in CTL and EE samples (FDR < 0.05). (L) NeuN+ CTCF footprint plot. Y-axis corresponds to the Tn5 insertion rate over the background, x-axis distance in bp from the motif center (upper plot: bins over nucleotide position). Blue line designates increased CTCF binding in EE samples. Right plot: GO analysis (p-adj < 0.05 with Benjamini-Holchberg correction, Supplementary Table 2).
FIGURE 3
FIGURE 3
3D genome interaction changes upon EE. (A) Differential analysis of intra and inter-chromosomal interactions at 100 kb and 1 Mb, respectively (FDR < 0.05). (B) Significant chromatin loops computed with HICCUPs at 5 and 10 kb resolution (FDR < 0.05). (C) Manhattan plot of differential intra-chromosomal interactions at 100 kb. (D) Juicebox heatmaps at 250 kb showing the extraction of EE vs. CTL of inter-chromosomal interactions. (E) Circos-plot of differential inter-chromosomal interactions (blue arcs-increased interactions, pink-decreased) together with concentric bedfiles representing the differential analysis of ATACseq, H3K79me2, H3K36me3 and RNAseq at 1 MB using Diffreps (increased regions upon EE = blue, decreased = red). (F) GO analysis of genes in the differential inter-chromosomal interactions at 1 MB upon EE stimulation (p-adj < 0.05 Bonferroni-step down). (G,H) In silico chrom3D models for EE and CTL samples showing significant increase of inter-chromosomal interactions. (I) A/B compartmentalization measured by eigenvector scores in chromosomes 7, 8, and 17. *** denotes p≤0.001.
FIGURE 4
FIGURE 4
Data integration and EE implications in brain cognition. (A) Full intersection of differential changes induced by EE (FDR < 0.05). Pink arcs—differential expressed genes intersected with the rest of the data, blue proteomic, and green inter-chromosomal changes. (B) Intersection hits plot, representing the number of times each gene is represented in the current study. Dashed lines—genes > 4 times intersected. (C) SynGO analysis showing the enrichment of the most intersected genes which represent postsynaptic and presynaptic genes (right bar-plot, p-adj < 0.05). (D) String-db analysis interactome at 0.99 confidence of the most intersected genes. (E) Transcriptomic and proteomic changes represented in other differential sets at FDR < 0.05. “Pink + green” and “blue + green”—total percentages of transcriptomic and proteomic changes found in other differential datasets, where green specifically represents the portion of these changes found in inter-chromosomal changes. (F) Differential inter-chromosomal changes association with the rest of the marks (Npermutations = 100 k, **p < 0.01, *p < 0.05). (G) Pearson correlation of EE-induced epigenetic marks changes in enhancers and promoters with differentially expressed genes (DEG). (H) Differential inter-chromosomal changes association with human brain GWAS traits. Differential bins were lifted to the human genome for the permutation analysis (Npermutations = 100 k, **p < 0.01, *p < 0.05). To illustrate the likelihood of the results, an example of the random shuffling is provided bellow to show the strength of the analysis.
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