The three-dimensional landscape of chromatin accessibility in Alzheimer’s disease

Abstract

Much is still unknown about the neurobiology of Alzheimer’s disease (AD). To better understand AD, we generated 636 ATAC-seq libraries from cases and controls to construct detailed genomewide chromatin accessibility maps of neurons and non-neurons from two AD-affected brain regions, the entorhinal cortex and superior temporal gyrus. By analyzing a total of 19.6 billion read pairs, we expanded the known repertoire of regulatory sequences in the human brain. Multi-omic data integration associated global patterns of chromatin accessibility with gene expression and identified cell-specific enhancer-promoter interactions. Using inter-individual variation in chromatin accessibility, we define cis-regulatory domains capturing the 3D structure of the genome. Multifaceted analyses uncovered disease associated perturbations impacting chromatin accessibility, transcription factor regulatory networks and the 3D genome, and implicated transcriptional dysregulation in AD. Overall, we applied a systematic approach to understand the role of the 3D genome in AD and to illuminate novel disease biology that can advance diagnosis and therapy.

Genetics of the human microglia regulome refines Alzheimer’s disease risk loci

“…S7a-b). To evaluate the cell type specificity of the E-P interactions observed in microglia, we compared them to E-P pairs identified in broad neuronal (38,233 pairs) and non-neuronal (37,056 pairs) cell populations 14 . In total, 23.6% (5,781 out of 24,459) microglia E-P interactions were shared with either neurons or non-neurons (Fig.…”

Acetylated Chromatin Domains Link Chromosomal Organization to Cell- and Circuit-level Dysfunction in Schizophrenia and Bipolar Disorder

“…We wondered whether such type of clustering in disease-sensitive CRD interaction map reflects a common signature in terms of spatial genome organization based on Hi-C chromosomal interaction or cell type-and developmental stage-specific regulation, or a combination thereof. To explore this, we first systematically created a resource of annotations of CRDs to a) cell types using PFC reference sample-based H3K27ac ChIP-seq resources for glutamatergic projection neurons, gabaergic interneurons and oligodendrocytes (Table S8) 28 b) developmental stages as fetal vs adult using the data for epigenetic trajectories of human cortical development 29 , and c) chromosomal A and B compartments by utilizing the PFC NeuN+ Hi-C datasets 23 (Methods, Figure S13). Remarkably, one cluster in the CRD interaction map in three groups labeled as 'cluster 3'(SCZ H3K27ac NeuN+ in Figure 4C, SCZ H3K27ac Tissue in Figure S14A and BD H3K27ac Tissue in Figure S14B), was overwhelmingly comprised of 78%-99% hyperacetylated domains harboring more glutamatergic (GLU) specific CRDs than GABAergic (GABA) CRDs.…”

“…CRDs span spatial clustering of chromatin peaks that extends across 10 4 -10 6 base pairs of linear genome sequence and integrate into local chromosomal conformation landscapes 21,22 . Similar approaches have been successfully applied to open chromatin regions in postmortem brains from donors with Alzheimer's disease 23 .…”

“…Integrating neuron-specific chromosomal conformation assayed by Hi-C from NeuN + sorted nuclei from PFC from a set of reference brains (N=6; 3F/3M) 23,26 , allowed us to evaluate whether CRDs provide a submodular organization within higher-order chromatin structures such as the topologically associating domains (TADs) computed from Hi-C chromosomal conformation mappings. Examining Hi-C and H3K27ac CRD structure in the 2MB of sequence surrounding GATB (Glutamyl-TRNA Amidotransferase Subunit B), a locus contributing to the heritability of cognitive traits and educational attainment 27 , reveals CRD landscapes embedded in the chromosomal TAD architecture (Figure 3C).…”

Genetic variation in correlated regulatory regions of immunity

“…To understand gene expression regulatory machinery and eQTLs upstream mechanisms, studies have analyzed the inter-individual variation of histone modifications, using ChIP-seq data [11,12] to discover the existence of coordinated activity of sets of regulatory elements, called Cis-Regulatory Domains (CRDs). Others have leveraged population variation of chromatin accessibility using ATAC-seq libraries [13,14,15,16], as it explains 70% of gene expression variance. Since DNA methylation is thought to influence chromatin structure [17] and gene expression when located in regulatory regions [18], the study of DNA methylation variability across a population [19] also provides tools to infer the mechanisms underlying transcriptional regulation.…”