The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer’s Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975).

Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks, which is necessary to understand the function of non-coding elements and the impact of non-coding genetic variation. Here we integrate genome-wide chromosome conformation data from purified neurons and glia with transcriptomic and enhancer profiles, to characterize the gene regulatory landscape of two major cell classes in the human brain. We then leverage cell-type-specific regulatory landscapes to gain insight into the cellular etiology of several brain disorders. We find that Alzheimer’s disease (AD)-associated epigenetic dysregulation is linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia, suggesting that different cell types may contribute to disease risk, via different mechanisms. Moreover, integration of glutamatergic and GABAergic regulatory maps with genetic risk factors for schizophrenia (SCZ) and bipolar disorder (BD) identifies shared (parvalbumin-expressing interneurons) and distinct cellular etiologies (upper layer neurons for BD, and deeper layer projection neurons for SCZ). Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders.

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Structural variants (SVs) contribute to many disorders, yet, functionally annotating them remains a major challenge. Here, we integrate SVs with RNA-sequencing from human postmortem brains to quantify their dosage and regulatory effects. We show that genic and regulatory SVs exist at significantly lower frequencies than intergenic SVs. Functional impact of copy number variants (CNVs) stems from both the proportion of genic and regulatory content altered and loss-of-function intolerance of the gene. We train a linear model to predict expression effects of rare CNVs and use it to annotate regulatory disruption of CNVs from 14,891 independent genome-sequenced individuals. Pathogenic deletions implicated in neurodevelopmental disorders show significantly more extreme regulatory disruption scores and if rank ordered would be prioritized higher than using frequency or length alone. This work shows the deleteriousness of regulatory SVs, particularly those altering CTCF sites and provides a simple approach for functionally annotating the regulatory consequences of CNVs.

T he brain, our most complex organ, is at the root of both the cognitive and behavioral repertoires that make us unique as a species and underlies susceptibility to neuropsychiatric disorders. Healthy brain development and neurological function rely on precise spatiotemporal regulation of the transcriptome, which varies substantially by brain region and cell type. Recent advances in the genetics of neuropsychiatric disorders reveal a highly polygenic risk architecture involving contributions of multiple common variants with small ef ects and rare variants with a range of ef ects. Because most of this genetic variation resides in noncoding regions of the genome, establishment of mechanistic links between variants and disease phenotypes is impeded by a lack of a comprehensive understanding of the regulatory and epigenomic landscape of the human brain.To address this matter, the PsychENCODE Consortium was established in 2015 by the National Institute of Mental Health (NIMH) to characterize the full spectrum of genomic elements active within the human brain and to elucidate their roles in development, evolution, and neuropsychiatric disorders. To reach this objective, a multidisciplinary team of investigators across 15 research institutes has generated an integrative atlas of the human brain by analyzing transcriptomic, epigenomic, and genomic data of postmortem adult and developing human brains at both the tissue and single-cell levels. Samples from more than 2000 individuals were phenotypically characterized as neurotypical or diagnosed with schizophrenia, autism spectrum disorder (ASD), or bipolar disorder.In Science, Science Translational Medicine, and Science Advances, we present manuscripts that provide insights into the biology of the developing, adult, and diseased human brain. These papers are organized around three fl agship articles, the fi rst analyzing human development, the second examining disease transcriptomes, and the third describing integration of tissue and single-cell data with deep-learning approaches.The consortium's integrative genomic analyses elucidate the mechanisms by which cellular diversity and patterns of gene

To explore modular organization of chromosomes in schizophrenia (SCZ) and bipolar disorder (BD), we applied 'population-scale' correlational structuring of 739 histone H3-lysine 27 acetylation and H3-lysine 4 trimethylation profiles, generated from the prefrontal cortex (PFC) of 568 cases and controls. Neuronal histone acetylomes and methylomes assembled as thousands of cis-regulatory domains (CRDs), revealing fine-grained, kilo- to megabase scale chromatin organization at higher resolution but firmly integrated into Hi-C chromosomal conformations. Large clusters of domains that were hyperacetylated in disease shared spatial positioning within the nucleus, predominantly regulating PFC projection neuron function and excitatory neurotransmission. Hypoacetylated domains were linked to inhibitory interneuron- and myelination-relevant genes. Chromosomal modular architecture is affected in SCZ and BD, with hyperacetylated domains showing unexpectedly strong convergences defined by cell type, nuclear topography, genetic risk, and active chromatin state across a wide developmental window.

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