Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Escherichia coli Mus musculus Homo sapiens

PROVIDER: GSE197539 | GEO | 2022/02/28

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [MPRA]

Project description:Determining causal variants for autoimmune disease is an enormous challenge - 90% of autoimmune disease-associated variants are non-coding and there are often 10s-100s are in tight linkage disequilibrium with the causal variant(s), making identification of the true causal variants difficult. Using massively parallel reporter assays in a T cell line, we prioritized variants that enriched highly for likely causal variants according to statistical fine-mapping. We followed up on one of the prioritized variants, rs72928038 in the BACH2 locus, which had a high effect size, finding that it regulates Bach2 expression in a human T cell line. We created mice containing a small deletion over this non-coding variant, and have tested mutant vs. WT antigen-specific T cells for their responses during acute viral infection. In the context of rs72928038-deleted mice (termed Bach218del), we found an increase in effector T cell differentiation, which highlights a potential role for rs72928038 in modulating effector T cell differentiation in the context of autoimmune disease.

2022-03-02 | GSE197538 | GEO

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [BaseEditing]

2022-03-02 | GSE197537 | GEO

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [scRNA-seq]

2022-03-02 | GSE194424 | GEO

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells

Project description:Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells

| PRJNA810855 | ENA

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [MPRA]

Project description:Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [MPRA]

| PRJNA810856 | ENA

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [BaseEditing]

Project description:Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [BaseEditing]

| PRJNA810857 | ENA

Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [scRNA-seq]

Project description:Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells [scRNA-seq]

| PRJNA800476 | ENA

cepip: context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes.

Project description:It remains challenging to predict regulatory variants in particular tissues or cell types due to highly context-specific gene regulation. By connecting large-scale epigenomic profiles to expression quantitative trait loci (eQTLs) in a wide range of human tissues/cell types, we identify critical chromatin features that predict variant regulatory potential. We present cepip, a joint likelihood framework, for estimating a variant's regulatory probability in a context-dependent manner. Our method exhibits significant GWAS signal enrichment and is superior to existing cell type-specific methods. Furthermore, using phenotypically relevant epigenomes to weight the GWAS single-nucleotide polymorphisms, we improve the statistical power of the gene-based association test.

| S-EPMC5356314 | biostudies-literature

Context-specific effects of genetic variants associated with autoimmune disease.

Project description:Autoimmune diseases such as rheumatoid arthritis and coeliac disease are typical examples of complex genetic diseases caused by a combination of genetic and non-genetic risk factors. Insight into the genetic risk factors (single nucleotide polymorphisms (SNPs)) has increased since genome-wide association studies (GWAS) became possible in 2007 and, for individual diseases, SNPs can now explain some 15-50% of genetic risk. GWAS have also shown that some 50% of the genetic risk factors for individual autoimmune diseases overlap between different diseases. Thus, shared risk factors may converge to pathways that, when perturbed by genetic variation, predispose to autoimmunity in general. This raises the question of what determines disease specificity, and suggests that identical risk factors may have different effects in various autoimmune diseases. Addressing this question requires translation of genetic risk factors to causal genes and then to molecular and cellular pathways. Since?>90% of the genetic risk factors are found in the non-coding part of the genome (i.e. outside the exons of protein-coding genes) and can have an impact on gene regulation, there is an urgent need to better understand the non-coding part of the genome. Here, we will outline the methods being used to unravel the gene regulatory networks perturbed in autoimmune diseases and the importance of doing this in the relevant cell types. We will highlight findings in coeliac disease, which manifests in the small intestine, to demonstrate how cell type and disease context can impact on the consequences of genetic risk factors.

| S-EPMC5886469 | biostudies-literature

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease.

Project description:Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes.

| S-EPMC6502852 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data