Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus (ChIP-seq)

ABSTRACT: Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus (ChIP-seq)

PROVIDER: PRJNA733666 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR14685356_1.fastq.gz	Fastqsanger.gz
	SRR14685356_2.fastq.gz	Fastqsanger.gz
	SRR14685357_1.fastq.gz	Fastqsanger.gz
	SRR14685357_2.fastq.gz	Fastqsanger.gz
	SRR14685358_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus

Project description:To identify a causative variant and effector gene responsible for a 2-fold increased risk of severe COVID-19, a multi-omics platform was deployed. A combination of ATAC-seq, ChIP-seq, Micro Capture-C and NuTi Capture-C were used to characterize a range of cell types, including epithelial, fibroblast, endothelial, immune and erythroid cells.

2021-08-13 | GSE175791 | GEO

Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus

Project description:Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus

| PRJNA733663 | ENA

Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus (MCC)

Project description:Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus (MCC)

| PRJNA733668 | ENA

Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus (ATAC-seq)

Project description:Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus (ATAC-seq)

| PRJNA733669 | ENA

Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals.

Project description:Individuals infected with the SARS-CoV-2 virus present with a wide variety of phenotypes ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe COVID-19 phenotype. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the severe COVID-19 phenotype. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform an locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify 4 introgressed alleles that are strong functional candidates for driving the association between this locus and the severe COVID-19. These variants likely drive the locus’ impact on severity by putatively modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.

2023-02-09 | GSE176233 | GEO

Multiple Early Factors Anticipate Post-Acute COVID-19 Sequelae

Project description:Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

2022-02-01 | E-MTAB-10129 | biostudies-arrayexpress

COVID-19 Outbreak

Project description:COVID-19 Outbreak

| PRJNA615625 | ENA

covid-19 study

Project description:covid-19 study

| PRJEB43387 | ENA

Unresolved Immune Dysfunction is Lethal in Both COVID-19 and non-COVID-19 Sepsis

Project description:In this prospective observational cohort study, we found transcriptional evidence that persistent immune dysfunction was associated with 28-day mortality in both COVID-19 and non-COVID-19 septic patients. COVID-19 patients had an early antiviral response but became indistinguishable on a gene expression level from non-COVID-19 sepsis patients a week later. Early treatment of COVID-19 and non-COVID-19 sepsis ICU patients should focus on pathogen control, but both patient groups also require novel immunomodulatory treatments, particularly later during ICU hospitalization, independent of admission diagnosis. Some T1 samples were uploaded in GSE185263 and were not re-uploaded in this series.

2023-03-24 | GSE222393 | GEO

RNA-seq of RBC depleted whole blood from COVID-19 patients and controls

Project description:Red blood cells (RBC) depleted whole blood from COVID-19 patients and controls was harvested and processed in order to performed 10X single cell RNA-seq. For COVID-19 patients 2 samples 10 days a part were analyzed.

2020-08-21 | E-MTAB-9221 | biostudies-arrayexpress

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