Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes

Song, Michael; Yang, Xiaoyu; Greenleaf, W; Maliskova, Lenka; Li, Bingkun; Jones, Ian; Wang, Chao; Jacob, Fadi; Wu, Ken; Traglia, Michela; Tam, Tsz Wai; Jamieson, Kirsty; Lu, Shaoping; Ming, Guo Li; Li, Yun; Yao, Jun; Weiss, Lauren A.; Dixon, Jesse R.; Judge, Luke M.; Conklin, Bruce R.; Song, Hongjun; Gan, Li; Shen, Yin

doi:10.1038/s41588-019-0472-1

Cited by 158 publications

(160 citation statements)

References 65 publications

(82 reference statements)

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“…To this end, several groups have employed Hi-C and its derivatives (e.g. promoter-capture Hi-C) to build higher-order chromatin interaction maps in iPSC-derived neurons and astrocytes 17,18 .…”

Section: Introductionmentioning

confidence: 99%

Neuronal and glial 3D chromatin architecture illustrates cellular etiology of brain disorders

Won

Mah

et al. 2020

Preprint

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Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks. We integrated genome-wide chromosome conformation in purified human neurons and glia with bulk and single cell transcriptomic and cell type-specific H3K27ac profiles to elucidate the gene regulatory landscape of two major cell classes in the brain. Frequently interacting regions (FIREs) and super-FIREs were strongly associated with cell type-specific gene expression. We linked enhancers in glutamatergic and GABAergic neurons to their cognate genes via neuronal chromatin interaction profiles. These cell-type-specific regulatory landscapes were then leveraged to gain insight into the cellular etiology of several brain disorders. We found that Alzheimer's disease (AD)-associated epigenetic dysregulation was linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia as a central cell type, suggesting that different cell types may confer risk to the disease via different genetic mechanisms. Moreover, neuronal subtype-specific annotation of genetic risk factors for schizophrenia and bipolar disorder identified shared (parvalbumin-expressing interneurons) and distinct cellular etiology (upper layer neurons for bipolar and deeper layer projection neurons for schizophrenia) between these two closely related psychiatric illnesses. Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders.

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Section: Introductionmentioning

confidence: 99%

Neuronal and glial 3D chromatin architecture illustrates cellular etiology of brain disorders

Won

Mah

et al. 2020

Preprint

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“…Validating distal regulatory elements in primary cells has historically been challenging, with most experiments to date performed using cell lines or iPSC-derived cells 10,42 . Here, we present CRISPRview, a novel approach combining CRISPRi, RNAscope, and immunostaining to validate enhancers in heterogeneous cultures of primary cells at the single cell level ( Fig.…”

Section: Resultsmentioning

confidence: 99%

3D Epigenomic Characterization Reveals Insights Into Gene Regulation and Lineage Specification During Corticogenesis

Song

Pebworth

Yang

et al. 2020

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47 48 Lineage-specific epigenomic changes during human corticogenesis have previously 49 remained elusive due to challenges with tissue heterogeneity and sample availability. 50 Here, we analyze cis-regulatory chromatin interactions, open chromatin regions, and 51 transcriptomes for radial glia, intermediate progenitor cells, excitatory neurons, and 52interneurons isolated from mid-gestational human brain samples. We show that 53 chromatin looping underlies transcriptional regulation for lineage-specific genes, with 54 transcription factor motifs, families of transposable elements, and disease-associated 55 variants enriched at distal interacting regions in a cell type-specific manner. A subset of 56 promoters exhibit unusually high degrees of chromatin interactivity, which we term super 57 interactive promoters. Super interactive promoters are enriched for critical lineage-58 specific genes, suggesting that interactions at these loci contribute to the fine-tuning of 59 cell type-specific transcription. Finally, we present CRISPRview, a novel approach for 60 validating distal interacting regions in primary cells. Our study presents the first 61 characterization of cell type-specific 3D epigenomic landscapes during human 62 corticogenesis, advancing our understanding of gene regulation and lineage specification 63 during human brain development. 64 65 Introduction 66 67The human cortex is a complex, heterogeneous structure that undergoes extensive 68 expansion during development, a process which is markedly different and features 69 distinct cell types from mouse cortical development. Previous studies utilized single cell 70 RNA sequencing (scRNA-seq) to unravel the transcriptomic diversity of the developing 71 cortex, revealing at least nine major cell types and up to 26 distinct subtypes in the dorsal 72 cortex alone 1,2 . Much of this diversity arises from cortical stem cells known as radial glia 73 (RG), whose cell bodies reside in the germinal zones (GZs) of the dorsal and ventral 74 cortex. In the dorsal cortex, RG divide asymmetrically to give rise to intermediate 75 progenitor cells (IPCs), which proliferate and differentiate into excitatory neurons (eNs) 3,4 . 76These newborn neurons undergo radial migration until they reach the cortical plate (CP), 77where they mature and undergo synaptogenesis 5 . Meanwhile, interneurons (iNs) 78 produced in the ventral cortex migrate tangentially into the dorsal cortex through the 79 marginal and germinal zones 6 . These processes result in a CP consisting primarily of eNs 80 and iNs and a GZ where all four cell types are intermixed. 81 82Dynamic changes in the epigenomic landscape have been shown to play a critical role in 83 development and cell fate commitment, for instance through the rewiring of physical 84 chromatin loops between promoters and distal regulatory elements 7 . These regulatory 85interactions are of particular interest as their dysregulation has been linked to complex 86 diseases and traits 8,9 . Despite their utility, detailed epigenomic character...

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“…To explore the biological interpretations of TWAS and GWAS-significant genes, we performed enrichment analysis in promoter-related chromatin interactions of four types of brain neurons 97 (iPSC-induced excitatory neurons, iPSC-derived hippocampal DG-like neurons, iPSC-induced lower motor neurons, and primary astrocytes), and also in high confident interactions of adult and fetal cortex 98 (Method). The raw p-values of Wilcoxon rank test for enrichment were summarized in Supplementary Table 15.…”

Section: Resultsmentioning

confidence: 99%

“…The chromatin interaction enrichments between significant and non-significant genes were tested using the Wilcoxon rank sum test. For the adult neural Promoter Capture Hi-C (PCHi-C), the enrichment of each gene was measured as the number of interactions overlapping gene with CHiCAGO Enrichment Score greater than 5 97 . The enrichment was tested separately in four cell types, including induced pluripotent stem cells (iPSC)-induced excitatory neurons, iPSC-derived hippocampal DG-like neurons, iPSC-induced lower motor neurons, and primary astrocytes.…”

Section: Methodsmentioning

confidence: 99%

Transcriptome-wide association analysis of 211 neuroimaging traits identifies new genes for brain structures and yields insights into the gene-level pleiotropy with other complex traits

Zhao

Shan

Yang

et al. 2019

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Structural and microstructural variations of human brain are heritable and highly polygenic traits, with hundreds of associated genes founded in recent genome-wide association studies (GWAS). Using gene expression data, transcriptome-wide association studies (TWAS) can prioritize these GWAS findings and also identify novel gene-trait associations. Here we performed TWAS analysis of 211 structural neuroimaging phenotypes in a discovery-validation analysis of six datasets. Using a cross-tissue approach, TWAS discovered 204 associated genes (86 new) exceeding Bonferroni significance threshold of 1.37*10−8 (adjusted for testing multiple phenotypes) in the UK Biobank (UKB) cohort, and validated 18 TWAS or previous GWAS-detected genes. The TWAS-significant genes of brain structures had been linked to a wide range of complex traits in different domains. Additional TWAS analysis of 11 cognitive and mental health traits detected 69 overlapping significant genes with brain structures, further characterizing the genetic overlaps among these brain-related traits. Through TWAS gene-based polygenic risk scores (PRS) prediction, we found that TWAS PRS gained substantial power in association analysis compared to conventional variant-based PRS, and up to 6.97% of phenotypic variance (p-value=7.56*10−31) in testing datasets can be explained by UKB TWAS-derived PRS. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.

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Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes

Cited by 158 publications

References 65 publications

Neuronal and glial 3D chromatin architecture illustrates cellular etiology of brain disorders

Neuronal and glial 3D chromatin architecture illustrates cellular etiology of brain disorders

3D Epigenomic Characterization Reveals Insights Into Gene Regulation and Lineage Specification During Corticogenesis

Transcriptome-wide association analysis of 211 neuroimaging traits identifies new genes for brain structures and yields insights into the gene-level pleiotropy with other complex traits

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