Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Massively parallel profiling of human regulatory variants in endothelial cells

ABSTRACT: Massively parallel profiling of human regulatory variants in endothelial cells

PROVIDER: PRJNA749770 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR15249900_1.fastq.gz	Fastqsanger.gz
	SRR15249900_2.fastq.gz	Fastqsanger.gz
	SRR15249901_1.fastq.gz	Fastqsanger.gz
	SRR15249901_2.fastq.gz	Fastqsanger.gz
	SRR15249902_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

Massively parallel profiling of human regulatory variants in endothelial cells

Project description:Genome-wide association studies (GWAS-s) have linked thousands of genetic variants with complex diseases and traits. However, most genetic variants identified reside in non-coding regions of the genome making it hard to predict and understand the molecular mechanisms underlying causal alleles. We have previously performed molecular Quantitative Trait Locus (molQTL) analysis for transcription factor binding, chromatin accessibility, and H3K27 acetylation across primary Human Aortic Endothelial Cell (HAEC) samples. Here we expand this analysis to study more than 30,000 genetic variants using the massively parallel reporter assay (MPRA) STARR-Seq in immortalized HAEC cells (teloHAEC). We demonstrate that more than 5,000 variants exhibit differential expression between alleles and identify ETS and AP-1 motifs as the strongest sequence attributes—and cell type-specific chromatin accessibility as the strongest epigenetic attribute—associated with allele-specific regulatory activity. Using interleukin 1-beta (IL1b) as a modulator of cell state and environment, we observe robust evidence for context-specific SNP effects, thereby underscoring the prevalence of GxE effects on noncoding variant function. We integrate results from molQTL mapping and STARR-seq with eQTL data from HAECs and GTEx tissues to fine-map functional non-coding SNPs at GWAS loci for vascular diseases.

2021-12-21 | GSE180846 | GEO

Massively parallel identification of cis-regulatory variants in yeast promoters

Project description:Massively parallel identification of cis-regulatory variants in yeast promoters

| PRJNA656111 | ENA

Massively parallel identification of cis-regulatory variants in yeast promoters - Experimental measurements

Project description:Sequence variation in regulatory DNA alters gene expression and shapes genetically complex traits. However, the identification of individual, causal regulatory variants is challenging. Here, we used a massively parallel reporter assay to measure the cis-regulatory consequences of 5,832 natural DNA variants in the promoters of 2,503 genes in the yeast Saccharomyces cerevisiae. We identified 451 causal variants, which underlie genetic loci known to affect gene expression. Several promoters harbored multiple causal variants. In five promoters, pairs of variants showed non-additive, epistatic interactions. Causal variants were enriched at conserved nucleotides, tended to have low derived allele frequency, and were depleted from promoters of essential genes, consistent with the action of negative selection. Causal variants were enriched for alterations in transcription factor binding sites. Models integrating these features provided modest, but statistically significant, ability to predict causal variants. This work revealed a complex molecular basis for cis-acting regulatory variation.

2020-08-31 | GSE155943 | GEO

Massively parallel identification of cis-regulatory variants in yeast promoters - Annotation runs

2020-08-31 | GSE155942 | GEO

Massively parallel identification of cis-regulatory variants in yeast promoters - Annotation runs

Project description:Massively parallel identification of cis-regulatory variants in yeast promoters - Annotation runs

| PRJNA656370 | ENA

Massively parallel identification of cis-regulatory variants in yeast promoters - Experimental measurements

Project description:Massively parallel identification of cis-regulatory variants in yeast promoters - Experimental measurements

| PRJNA656371 | ENA

Characterization of caffeine response regulatory variants in vascular endothelial cells

Project description:Genetic variants in gene regulatory sequences can modify gene expression and mediate the molecular response to environmental stimuli. In addition, genotype–environment interactions (GxE) contribute to complex traits such as cardiovascular disease. Caffeine is the most widely consumed stimulant and is known to produce a vascular response. To investigate GxE for caffeine, we treated vascular endothelial cells with caffeine and used a massively parallel reporter assay to measure allelic effects on gene regulation for over 43,000 genetic variants. We identified 665 variants with allelic effects on gene regulation and 6 variants that regulate the gene expression response to caffeine (GxE, false discovery rate [FDR] < 5%). When overlapping our GxE results with expression quantitative trait loci colocalized with coronary artery disease and hypertension, we dissected their regulatory mechanisms and showed a modulatory role for caffeine. Our results demonstrate that massively parallel reporter assay is a powerful approach to identify and molecularly characterize GxE in the specific context of caffeine consumption.

2024-02-26 | GSE221514 | GEO

Transcriptional-Regulatory Convergence Across Functional MDD Risk Variants Identified by Massively Parallel Reporter Assays

Project description:Transcriptional-Regulatory Convergence Across Functional MDD Risk Variants Identified by Massively Parallel Reporter Assays

| PRJNA704843 | ENA

Massively parallel functional testing of MSH2 missense variants conferring Lynch Syndrome risk

Project description:We performed a massively parallel screen in human HAP1 cells to identify loss-of-function missense variants in the key DNA mismatch repair factor MSH2. Resulting variant loss-of-function (LOF) scores are strongly concordant with previous functional evidence and available variant classification.

2020-12-23 | GSE162130 | GEO

An in vivo massively parallel platform for deciphering tissue-specific regulatory function [RNA]

Project description:Massively parallel reporter assays (MPRAs) have the potential to link differences in genome sequence, including genetic variants, to tissue-specific regulatory function. Whole-animal MPRA (WhAMPRA), where systemic intravenous AAV effectively transduces the plasmid MPRA library to mouse tissues. This technology simultaneously determines the transcriptional functions of hundreds of enhancers in vivo across multiple tissues

2025-03-24 | GSE223306 | GEO

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