Neuron-specific signatures in the chromosomal connectome associated with schizophrenia risk

Rajarajan, Prashanth; Borrman, Tyler; Liao, Will; Schrode, Nadine; Flaherty, Erin; Casiño, Charlize; Powell, Samuel K.; Yashaswini, Chittampalli; LaMarca, Elizabeth A.; Kassim, Bibi; Javidfar, Behnam; Espeso-Gil, Sergio; Li, Aiqun; Won, Hyejung; Geschwind, Daniel H.; Ho, Seok‐Man; MacDonald, Matthew L.; Hoffman, Gabriel E.; Roussos, Panos; Zhang, Bin; Hahn, Chang-Gyu; Weng, Zhiping; Brennand, Kristen J.; Akbarian, Schahram

doi:10.1126/science.aat4311

Cited by 188 publications

(219 citation statements)

References 67 publications

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“…1A-C). These numbers are in line with the low number of reported ct-links experimentally observed for NPC, neurons, and K562 cells [15,16], and indicates that cell-type specific EP links constitute only a small portion of the EP links that are active in any particular cell type. CT-FOCS predicted EP links are on average shared across 3, 1.65, and 2.5 cell types in ENCODE, Roadmap, and FANTOM5 datasets ( Supplementary Fig.…”

Section: Figure 1 Outline Of the Ct-focs Algorithmsupporting

confidence: 79%

“…Third, the average number of CT-links per cell type was 167 in ENCDOE, 234 in Roadmap, and 414 in FANTOM5, respectively ( Table 1). While these numbers are very low, considering that ENCODE reported a total of ~3M regulatory elements [19], they are in line with the small number of cell type-specific EP links reported previously for NPC, neuron, and K562 cells [15,16]. Fourth, each promoter was linked to ~2 enhancers on average (and a maximum of 9) in each cell type.…”

Section: Columnsupporting

confidence: 79%

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CT-FOCS: a novel method for inferring cell type-specific enhancer-promoter maps

Hait

Elkon

Shamir

2019

Preprint

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Spatiotemporal gene expression patterns are governed to a large extent by enhancer elements, typically located distally from their target genes. Identification of enhancerpromoter (EP) links that are specific and functional in individual cell types is a key challenge in understanding gene regulation. We introduce CT-FOCS, a new statistical inference method that utilizes multiple replicates per cell type to infer cell type-specific EP links. Computationally predicted EP links are usually benchmarked against experimentally determined chromatin interaction measured by ChIA-PET. We expand this validation scheme by introducing the concept of connected loop set, which combines loops that overlap in their anchor sites. Analzying 1,366 samples from ENCODE, Roadmap epigenomics and FANTOM5, CT-FOCS inferred highly cell type-specific EP links more accurately than a state-of-the-art method. We illustrate how our inferred EP links drive cell type-specific gene expression and regulation.TargetFinder [13]. All these methods rely on data of multiple chromatin marks and expression data for the studied cell types.The JEME algorithm finds global and cell type-active EP links (but not necessarily cell typespecific) using only 1-5 different omics data types [14]. Each reported EP link is given a score denoting tendency to be active in a given cell type. JEME reports an average of 4,095 active EP links per cell type, and most of these may be nonspecific.Several recent studies aimed at finding ct-links experimentally. Rajarajan et al. [15] used insitu HiC and schizophrenia risk locus to identify 1,702 and 442 neuronal progenitor cell (NPC) specific and neuron specific 3D chromatin interactions for 386 and 385 genes, respectively. Some of the NPC and neuron-specific interactions may be enhancer-promoter interactions (or ct-links). Gasperini et al. [16] used CRISPR screening to perturb 5,920 human candidate enhancers that may affect gene expression at the single-cell level in combination with eQTL analysis, and identified 664 EP links covering 479 genes enriched with K562-specific genes and lineage-specific transcription factors (TFs; reviewed in [17]). Remarkably, both studies reported far fewer links than JEME, indicating that only a small portion of EP links that are active in a cell type are specific for it.Here, we introduce CT-FOCS (Cell Type FDR-corrected OLS with Cross-validation and Shrinkage), a novel method for inferring ct-links from large-scale compendia of hundreds of cell types measured by a single omic technique (e.g., DNase Hypersensitive Sites sequencing; DHS-seq). It is built upon our previously published method, FOCS [18], which infers global EP links that show high correlation between the enhancer and the promoter activity patterns across many samples. Given the omic profile for a set of cell types, each one with replicates, CT-FOCS uses linear mixed effect models (LMMs) to infer ct-links. CT-FOCS was applied on public DNase Hypersensitive Sites (DHS) profiles from ENCODE and Roadmap Epigenomics [19][20][21], and ca...

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Section: Figure 1 Outline Of the Ct-focs Algorithmsupporting

confidence: 79%

Section: Columnsupporting

confidence: 79%

CT-FOCS: a novel method for inferring cell type-specific enhancer-promoter maps

Hait

Elkon

Shamir

2019

Preprint

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“…Cell type-specific promoter interactome maps thus provide insights into the epigenomic regulation of these cell types by linking putative enhancers and disease variants to target genes. A recent analysis of Hi-C chromatin loops using in vitro iPSC-derived neural progenitor cells, neurons and astrocytes identified dynamic chromatin reorganization during development and was used to generate an extended network of schizophrenia risk genes (82). Our approach of using proximity ligation coupled to an enrichment for promoter regions provided an 8.6-fold expansion in the number of detected neuronal chromatin loops.…”

Section: Discussionmentioning

confidence: 99%

Cell type-specific enhancer-promoter connectivity maps in the human brain and disease risk association

Nott¹,

Holtman²,

Coufal

et al. 2019

Preprint

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Identification of cell type-specific regulatory elements in the human brain enables interpretation of non-coding GWAS risk variants. AbstractUnique cell type-specific patterns of activated enhancers can be leveraged to interpret non-coding genetic variation associated with complex traits and diseases such as neurological and psychiatric disorders. Here, we have defined active promoters and enhancers for major cell types of the human brain. Whereas psychiatric disorders were primarily associated with regulatory regions in neurons, idiopathic Alzheimer's disease (AD) variants were largely confined to microglia enhancers. Interactome maps connecting GWAS variants in cell type-specific enhancers to gene promoters revealed an extended microglia gene network in AD. Deletion of a microglia-specific enhancer harboring ADrisk variants ablated BIN1 expression in microglia but not in neurons or astrocytes. These findings revise and expand the genes likely to be influenced by non-coding variants in AD and suggest the probable brain cell types in which they function. of neurons, microglia, astrocytes, oligodendrocytes and other cell types that reside within the brain (1-4). In contrast, transcriptional mechanisms that control their developmental and functional properties in health and disease remain less well understood. Studies in animal models have provided deep insights into conserved processes, but significant differences between species often limit the translatability of findings in model systems to humans (5).Genome-wide association studies (GWASs) provide a genetic approach to identifying molecular pathways involved in complex traits and diseases by defining associations between genetic variants and phenotypes of interest (6, 7). Large-scale GWASs have discovered hundreds of single nucleotide polymorphisms (SNPs) that are associated with the risk of neurological and psychiatric disorders. The vast majority of disease-risk genetic variants are located in non-coding regions of the genome (7) and the specific cell type (s) in which the disease-risk variants are active is often unclear. Furthermore, linkagedisequilibrium between disease-risk variants at GWAS significant loci complicates the identification of causal variants. Collectively, these limitations have hindered the assignment and interpretation of disease-risk genes.GWAS-identified risk variants that are located in non-coding regions of the genome can exert phenotypic effects through several mechanisms, including perturbation of transcriptional enhancers and promoters (6). While promoters provide the essential sites of transcriptional initiation of mRNAs, they are frequently not sufficient to direct appropriate developmental and signal-dependent levels of gene expression (8,9). This additional information is provided by enhancers, short regions of DNA that, when bound by transcription factors, enhance mRNA expression from target promoters. Enhancers can reside hundreds of thousands of base pairs away from their target gene and their function is generally consid...

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“…Several genes (321) were found to be potential targets for the regulators and have roles in various neurological functions such as synaptic activity and ion channel regulation. They also concluded that schizophrenia was primarily a neuronal disorder rather than glial [8]. …”

Section: Complicated Genetic Linksmentioning

confidence: 99%