Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Homo sapiens

ABSTRACT: Massively parallel assessment of human variants with base editor screens

PROVIDER: PRJNA638656 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR12397300.fastq.gz	Fastqsanger.gz
	SRR12397400.fastq.gz	Fastqsanger.gz
	SRR12397500.fastq.gz	Fastqsanger.gz
	SRR12397600.fastq.gz	Fastqsanger.gz
	SRR12397700.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 2414

Similar Datasets

Parallel functional assessment of m6A sites in human endodermal differentiation with base editor screens

Project description:Parallel functional assessment of m6A sites in human endodermal differentiation with base editor screens

| PRJNA746130 | ENA

Homo sapiens

Project description:Benchmarking of SpCas9 variants enables deeper base editor screens of BRCA1 and BCL2

| PRJNA753064 | ENA

Discovery of target genes and pathways of blood trait loci using pooled CRISPR screens and single cell RNA sequencing

Project description:The majority of variants associated with complex traits and common diseases identified by genome-wide association studies (GWAS) map to noncoding regions of the genome with unknown regulatory effects. By leveraging ancestrally diverse biobank-scale GWAS data, massively parallel CRISPR screens and single cell transcriptomic and proteomic sequencing, we discovered target genes of noncoding variants for blood trait loci. For 91 GWAS loci, we identified 124 target genes in cis, which were often — but not always — the closest genes to the fine-mapped variant. Using precise variant insertion via base editing, we connect specific variants with gene expression changes. We also identified trans-effect networks of noncoding loci when cis target genes encoded transcription factors or microRNAs, such as GFI1B and miR-142. Trans-regulatory networks were themselves enriched for fine-mapped GWAS variants, demonstrating polygenic contributions to complex traits. Co-expression clustering of GFI1B trans-target genes identifies gene networks specific to different blood cell fates and differentiation stages. This platform will enable massively parallel assays to characterize the target genes and mechanisms of human noncoding variants in both cis and trans.

2021-04-08 | GSE171452 | GEO

Massively parallel base editing to map variant effects in human hematopoiesis

Project description:Systematic evaluation of the impact of genetic variants is critical for the study and treatment of human physiology and disease. While specific mutations can be introduced by genome engineering, we still lack scalable approaches that are applicable to the important setting of primary cells, such as blood and immune cells. Here, we describe the development of massively parallel base-editing screens in human hematopoietic stem and progenitor cells. Such approaches enable functional screens for variant effects across any hematopoietic differentiation state. Moreover, they allow rich phenotyping through single-cell RNA sequencing readouts, and separately, characterization of editing outcomes through pooled single-cell genotyping. We efficiently design improved leukemia immunotherapy approaches, comprehensively identify non-coding variants modulating fetal hemoglobin expression, define mechanisms regulating hematopoietic differentiation, and probe the pathogenicity of uncharacterized disease-associated variants. These strategies will advance effective and high-throughput variant-to-function mapping in human hematopoiesis to identify the causes of diverse diseases.

2023-05-02 | GSE215253 | GEO

Homo sapiens

Project description:Mapping functional elements of the DNA damage response through base editor screens

| PRJNA1180293 | ENA

Homo sapiens

Project description:Assessment of Variant Abundance by Massively Parallel Sequencing for PTEN and TPMT

| PRJNA407953 | ENA

Multidimensional PTEN missense variant analysis reveals variant subgroups including potential dominant negatives

Project description:Determining the pathogenicity of human genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes will likely require generalizable, scalable assays. We previously developed Variant Abundance by Massively Parallel Sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance in a single experiment. Here, we reapplied VAMP-seq to quantify the abundances of additional PTEN missense variants which were missing from the original experiment.

2021-09-13 | GSE159469 | GEO

Benchmarking of SpCas9 variants enables deeper base editor screens of BRCA1 and BCL2

Project description:Benchmarking of SpCas9 variants enables deeper base editor screens of BRCA1 and BCL2

| PRJNA747943 | ENA

Assessment of Variant Abundance by Massively Parallel Sequencing for PTEN and TPMT

Project description:Determining the pathogenicity of human genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes will likely require generalizable, scalable assays. Here we describe Variant Abundance by Massively Parallel Sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance in a single experiment. We applied VAMP-seq to quantify the abundance of many thousands of single amino acid variants of two proteins, PTEN and TPMT, in which functional variants are clinically actionable.

2018-03-13 | GSE108727 | GEO

Homo sapiens immortalized MSCs: 3A6

Project description:Gene expression profiling of immortalized human mesenchymal stem cells with hTERT/E6/E7 transfected MSCs. hTERT may change gene expression in MSCs. Goal was to determine the gene expressions of immortalized MSCs.

2010-09-25 | GSE24338 | 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