Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Perturb-seq]

ABSTRACT: Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Perturb-seq]

PROVIDER: PRJNA1183893 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR31295800.fastq.gz	Fastqsanger.gz
	SRR31295801.fastq.gz	Fastqsanger.gz
	SRR31295802.fastq.gz	Fastqsanger.gz
	SRR31295803.fastq.gz	Fastqsanger.gz
	SRR31295804.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 93

Similar Datasets

Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Hi-C]

Project description:Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Hi-C]

| PRJNA1183891 | ENA

Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [ATAC-seq]

Project description:Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [ATAC-seq]

| PRJNA1183888 | ENA

Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [RNA-seq]

Project description:Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [RNA-seq]

| PRJNA1183890 | ENA

Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Perturb-seq]

Project description:Heart failure is caused in part by cardiac remodeling processes that include the death of cardiac myocytes and their replacement by cardiac fibroblasts. We hypothesized that these two cell types may harbor epigenetic contexts in which heart disease-associated non-coding SNPs perturb gene expression relevant to disease. Accordingly, we generated high-resolution Hi-C data layered with functional genomic information to annotate and link putative distal regulatory elements in heart disease-associated loci to gene promoters. Our analysis identified several target genes with established roles in cardiac fibrosis and/or heart disease (GJA1, TBC1D32, CXCL12, IL6R, and FURIN). Perturb-seq in cardiac fibroblasts after knocking out putative regulatory elements confirmed regulatory relationships involving GJA1, CXCL12, and FURIN, in addition to changes in transcriptomic signatures associated with fibroblasts in heart failure. Our results demonstrate how integrative multi-omic approaches can delineate pathophysiologically relevant regulatory circuits that connect protein-coding genes to non-coding genetic variants associated with disease.

2025-06-16 | GSE281464 | GEO

Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [ATAC-seq]

2025-06-16 | GSE281462 | GEO

Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [RNA-seq]

2025-06-16 | GSE281465 | GEO

Dissecting Non-Coding GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Relevance to Heart Failure [Hi-C]

2025-06-16 | GSE281463 | GEO

Integration of Alzheimer’s GWAS, 3D genomics, and single-cell CRISPRi non-coding screen implicates causal variants in a microglial enhancer regulating TSPAN14. [RNA-Seq]

Project description:While GWAS have been successful in providing variant-to-trait associations for human complex diseases, functional dissection of the discovered loci has lagged behind. Here, we describe a variant-to-gene (V2G) mapping effort for Alzheimer’s disease (AD) to implicate causal variants and effector genes from the most recent AD GWAS meta-analyses (101 loci). We leveraged our genomics datasets comprising high-resolution promoter Capture C, ATAC-seq, and RNA-seq from brain-relevant cell types to fine-map AD GWAS variants, identifying 89 candidate causal SNPs and 69 effector genes. We then designed a single-cell CRISPRi screen to perturb candidate regulatory regions (n=74) and assess the transcriptional response in the human microglial cell line, HMC3. Our screen across ~97,000 cells identified 19 regulatory regions and 19 effector genes. We then elected to functionally dissect our top hit, the TSPAN14 locus, and we show that an intronic region containing AD-associated SNPs rs7080009, rs1870138, and rs1870137 is a microglia-specific enhancer, with the AD risk haplotype increasing its activity. CRISPR precise genomic deletion of this region decreases TSPAN14 expression, alters specific cellular pathways including cell adhesion, and decreases secreted levels of pro-inflammatory cytokines IL-6 and IL-8, which are known biomarkers of aging and AD. Our work provides a systematic framework to map GWAS signals to their effector genes for AD and other brain-related disorders, and provides robust leads to follow up with in-depth functional investigations.

2026-05-26 | GSE293119 | GEO

Integration of Alzheimer’s GWAS, 3D genomics, and single-cell CRISPRi non-coding screen implicates causal variants in a microglial enhancer regulating TSPAN14. [scRNA-Seq]

2026-05-26 | GSE293118 | GEO