Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [ADT]

ABSTRACT: SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [ADT]

PROVIDER: PRJNA999322 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity

Project description:SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity

| PRJNA999316 | ENA

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [VDJ]

Project description:SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [VDJ]

| PRJNA999324 | ENA

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [GEX]

Project description:SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [GEX]

| PRJNA999323 | ENA

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [ADT]

Project description:Pregnancy is a risk factor for increased severity of SARS-CoV-2 and other respiratory infections. The mechanisms underlying this risk have not been well-established, partly due to limited understanding of how pregnancy shapes and modulates immune responses. To gain insight into the roles of pregnancy in shaping the immune responses we collected peripheral blood mononuclear cells (PBMC) from 17 non-pregnant and 9 pregnant donors with various COVID severities and compared their immunological profiles.

2024-10-30 | GSE239449 | GEO

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [VDJ]

2024-10-30 | GSE239451 | GEO

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity [GEX]

2024-10-30 | GSE239450 | GEO

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity

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

2024-10-30 | GSE239452 | GEO

Novel Race-specific Genetic and Epigenetic Determinants of ADT-Resistance in African American Prostate Cancer

Project description:Purpose: The goals of this study is to compare NGS-derived Androgen Deprivation Therapy (ADT) resistant miRNome profiling to Androgen Deprivation Therapy (ADT) sensitive miRNome profile in African American prostate cancer cells and validate by reverse transcription polymerase chain reaction (qRT–PCR) methods. Method: Mirco-RNA were isolated from different CaP cells who were sensitive and resistant to Androgen Deprivation Therapy (ADT). Total micro-RNA were subjected to miRNA-Seq. Results: We performed whole miRNA-Seq analysis through paired-end deep sequencing to systematically investigate the molecular features of different CaP cell models- RC-77-N, RC-77T/E, RCC7T/E-ADT, RCC7T/E-CD133-plus, E006AA-hT and E006AA-hT-ADT. Conclusions: Our study represents the first detailed analysis of African American ADT resistant miRNome, with biologic replicates, generated by miRNA-seq technology.

2019-07-09 | GSE116636 | GEO

Comparative functional genomics identifies unique molecular features of EPSCs

Project description:Comparative functional genomics identifies unique molecular features of EPSCs

| PRJNA830833 | ENA

Race-specific transcriptome and Long non-coding RNA of ADT-resistant African-American prostate cancer cell models.

Project description:Purpose: The goals of this study are to compare NGS-derived Androgen Deprivation Therapy (ADT) resistant transcriptome to profiling (RNA-seq) to Androgen Deprivation Therapy (ADT) sensitive transcriptome in African American prostate cancer cells and validate by reverse transcription polymerase chain reaction (qRT–PCR) methods. Method: Total RNA was extracted from different CaP cell who were ADT sensitive and ADT resistance. Total RNA was subjected to whole transcriptome sequencing analysis. Sequence reads Results: We performed whole transcriptome RNA-Seq analysis through paired-end deep sequencing to systematically investigate the molecular features of different CaP cell models- RCC7/N, RCC7T/E, RCC7T/E-ADT, RCC7T/E-CD133, E006AA-hT and E006AA-hT-ADT We obtained an average of 23.85 million reads per sample, ranging from 22.86 to 24.93 million reads, with an average mapping rate of 98.29% to the reference human genome (UCSC version hg20). Next we performed Kal’s Z-test and generated Fold-Change (FC) values, p values and False Discovery Rate (FDR) values for measuring comparative gene expression profile. By applying stringent statistical threshold of greater than or equal to 2 FC, p value < 0.05 and FDR value < 1, we identified genes that were significantly differentially expressed in three different comparative groups. Conclusions: "Our study represents the first detailed analysis of African American ADT resistant transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. "

2019-07-09 | GSE115307 | 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