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Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [MPRA]

ABSTRACT: Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [MPRA]

PROVIDER: PRJNA563094 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR10051426.fastq.gz	Fastqsanger.gz
	SRR10051427.fastq.gz	Fastqsanger.gz
	SRR10051428.fastq.gz	Fastqsanger.gz
	SRR10051429.fastq.gz	Fastqsanger.gz
	SRR10051430.fastq.gz	Fastqsanger.gz

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Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits

Project description:Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits

| PRJNA563093 | ENA

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [MPRA]

Project description:Genome-wide association studies have associated thousands of genetic variants with complex traits and diseases, but pinpointing the causal variant(s) among those in tight linkage disequilibrium with each associated variant remains a major challenge. Here, we used seven experimental assays to characterize all common variants at the multiple disease-associated TNFAIP3 locus in three disease-relevant immune cell types, based on a set of features related to regulatory potential. Trait/disease-associated variants were enriched among SNPs prioritized based on either: (1) residing within CRISPRi-sensitive regulatory regions, or (2) localizing in a chromatin accessible region while displaying allele-specific reporter activity. Of the 15 trait/disease-associated haplotypes at TNFAIP3, 9 had at least one variant meeting one or both of these criteria, with 3 of these haplotypes having a single prioritized variant. 5 of the 9 prioritized variants were further supported by genetic fine-mapping in our and other studies. Our work provides evidence for the efficacy and limitations of strategies for prioritizing disease- and trait-associated genetic variants.

2020-02-11 | GSE136702 | GEO

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [ATAC-seq]

Project description:Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [ATAC-seq]

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Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [CRISPR guide-seq]

Project description:Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [CRISPR guide-seq]

| PRJNA563074 | ENA

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [ATAC-seq]

2020-02-11 | GSE136686 | GEO

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [CRISPR guide-seq]

2020-02-11 | GSE136693 | GEO

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-02-11 | GSE136703 | GEO

Systematic Functional Dissection of Common Genetic Variation Affecting Red Blood Cell Traits [MPRA]

Project description:Genome-wide association studies (GWAS) have successfully identified thousands of associations between common genetic variants and human disease phenotypes, but the majority of these variants are non-coding, often requiring genetic fine-mapping, epigenomic profiling, and individual reporter assays to delineate potential causal variants. We employ a massively parallel reporter assay (MPRA) to simultaneously screen 2,756 variants in strong linkage disequilibrium with 75 sentinel variants associated with red blood cell traits. We show that this assay identifies elements with endogenous erythroid regulatory activity. Across 23 sentinel variants, we conservatively identified 32 MPRA functional variants (MFVs). We used targeted genome editing to demonstrate endogenous enhancer activity across 3 MFVs that predominantly affect the transcription of SMIM1, RBM38, and CD164. Functional follow-up of RBM38 delineates a key role for this gene in the alternative splicing program occurring during terminal erythropoiesis. Finally, we provide evidence for how common GWAS-nominated variants can disrupt cell-type-specific transcriptional regulatory pathways.

2016-10-07 | GSE87711 | GEO

MPRA in primary human macrophages

Project description:We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases. We used a functional approach (massively-parallel reporter assay; MPRA) to first identify active enhancers at the locus in primary human macrophages, and then determine if candidate variants within these regulatory regions might alter enhancer activity. In doing so, we discovered a mechanism that orchestrates macrophage responses during chronic inflammation and delineated how the risk haplotype increases expression of the causal gene, ETS2.

2024-05-01 | GSE229472 | GEO

FABIO: TWAS fine-mapping to prioritize causal genes for binary traits.

Project description:Transcriptome-wide association studies (TWAS) have emerged as a powerful tool for identifying gene-trait associations by integrating gene expression mapping studies with genome-wide association studies (GWAS). While most existing TWAS approaches focus on marginal analyses through examining one gene at a time, recent developments in TWAS fine-mapping methods enable the joint modeling of multiple genes to refine the identification of potentially causal ones. However, these fine-mapping methods have primarily focused on modeling quantitative traits and examining local genomic regions, leading to potentially suboptimal performance. Here, we present FABIO, a TWAS fine-mapping method specifically designed for binary traits that is capable of modeling all genes jointly on an entire chromosome. FABIO employs a probit model to directly link the genetically regulated expression (GReX) of genes to binary outcomes while taking into account the GReX correlation among all genes residing on a chromosome. As a result, FABIO effectively controls false discoveries while offering substantial power gains over existing TWAS fine-mapping approaches. We performed extensive simulations to evaluate the performance of FABIO and applied it for in-depth analyses of six binary disease traits in the UK Biobank. In the real datasets, FABIO significantly reduced the size of the causal gene sets by 27.9%-36.9% over existing approaches across traits. Leveraging its improved power, FABIO successfully prioritized multiple potentially causal genes associated with the diseases, including GATA3 for asthma, ABCG2 for gout, and SH2B3 for hypertension. Overall, FABIO represents an effective tool for TWAS fine-mapping of disease traits.

| S-EPMC11649093 | biostudies-literature

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