Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: High throughput CRISPR screening in JURKAT cell line

PROVIDER: PRJNA1154920 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR30501541_1.fastq.gz	Fastqsanger.gz
	SRR30501541_2.fastq.gz	Fastqsanger.gz
	SRR30501542_1.fastq.gz	Fastqsanger.gz
	SRR30501542_2.fastq.gz	Fastqsanger.gz
	SRR30501543_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 8

Similar Datasets

Homo sapiens

Project description:Homo Species Cell Line CRISPR Screening

| PRJNA1194966 | ENA

Transcriptional regulators of the amino acid response pathway in leukemia

Project description:CRISPR/Cas9-based genetic screening revealed ZBTB1 as a critical mediator of the response of T-ALL cells to asparagine deprivation. ZBTB1 regulates the transcription of ASNS, a transcriptional target of ATF4. Loss of ZBTB1 results in decreased transcription and expression of ASNS. ChIP-Sequencing reveals that both ATF4 and ZBTB1 enrich in the promoter of ASNS. This dataset contains the RNA-Seq, ChIP-Seq and ATAC-Seq data on three different cell lines (WT Jurkat cells, ZBTB1 knockout Jurkat cells and ZBTB1 knockout Jurkat cells expressing ZBTB1 cDNA) in support of these findings.

2020-03-31 | GSE145783 | GEO

10x 3’ scRNA-seq analysis on Jurkat cells post TCR acivation in CRISPR/Cas9 screening

Project description:By performing 10x 3’ scRNA-seq on Jurkat cells post TCR acivation in CRISPR/Cas9 screening, we want to investigate the compatibility of the A/G mixed capture sequence on multiple single cell RNA-seq platforms. By mimicking the adenylated endogenous mRNA, gRNA transcripts could be directly captured by poly(dT) primer during the reverse transcription, and serve as perturbation index in high identification rate.

2020-05-11 | GSE148820 | GEO

Homo sapiens

Project description:Homo Species Cell Line CRISPR Screening Sequence Reads

| PRJNA1196131 | ENA

CRISPR-Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome [SKBR3 DNase]

Project description:Large genome mapping consortia and thousands of genome-wide association studies have identified non-protein coding elements in the genome as a having a central role in tissue development, cell-type specification, response to environmental or pharmacologic signals, and susceptibility to most common diseases. However, decoding the function of the millions of putative regulatory elements discovered in these studies remains a primary challenge. New CRISPR/Cas9-based epigenome editing technologies have enabled the precise perturbation of the activity of specific regulatory elements. Here we describe CRISPR/Cas9-based Epigenomic Regulatory Element Screening (CERES) for high-throughput screening of regulatory element activity within the native genomic context. We perform both loss- and gain-of-function screens with complementary epigenome editing tools to identify known and unknown regulatory elements of medically relevant genes in human cells. The high-throughput functional annotation of putative regulatory elements by CERES constitutes a new platform for screening biological mechanisms that cannot be perturbed by traditional methods.

2017-03-23 | GSE96874 | GEO

Optimized minimal genome-wide human sgRNA library

Project description:To minimize the human genome-wide CRISPR/Cas9 library size, we established H-mLib which recruited a novel sgRNA design method and applied with dual plasmid based strategy. The performance of the H-mLib was benchmarked to other CRISPR libraries in a proliferation screening conducted in K562 cells. We also identified human core essential genes and cell-type specific essentials genes in K562 and Jurkat cells.

2023-07-18 | GSE223086 | GEO

Project description:Homo Species Cell Line CRISPR Screening Raw Sequence Reads

| PRJNA1196182 | ENA

Optimized CRISPR-Cas12a platform for combinatorial drop-out genetic screening (RNA-seq)

Project description:Combinatorial genetic perturbations have been utilized to identify synthetic sick/lethal genetic interactions for cancer drug target discovery. Current methods for high-throughput combinatorial genetic screening are inefficient and cumbersome. Here we developed a simple, robust, and high-performance CRISPR-Cas12a-based approach for unbiased, combinatorial genetic screening in cancer cells.

2020-06-08 | GSE141130 | GEO

CRISPR-Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome

Project description:This SuperSeries is composed of the SubSeries listed below. Large genome mapping consortia and thousands of genome-wide association studies have identified non-protein coding elements in the genome as a having a central role in tissue development, cell-type specification, response to environmental or pharmacologic signals, and susceptibility to most common diseases. However, decoding the function of the millions of putative regulatory elements discovered in these studies remains a primary challenge. New CRISPR/Cas9-based epigenome editing technologies have enabled the precise perturbation of the activity of specific regulatory elements. Here we describe CRISPR/Cas9-based Epigenomic Regulatory Element Screening (CERES) for high-throughput screening of regulatory element activity within the native genomic context. We perform both loss- and gain-of-function screens with complementary epigenome editing tools to identify known and unknown regulatory elements of medically relevant genes in human cells. The high-throughput functional annotation of putative regulatory elements by CERES constitutes a new platform for screening biological mechanisms that cannot be perturbed by traditional methods.

2017-03-23 | GSE96876 | GEO

Comprehensive profiling of activity and specificity of CRISPR/Cas9 under cellular environment by deep learning

Project description:This study aims to predict the activity and specificity of CRISPR/Cas9 by deep learning at genome-scale among different cell lines. Here, we have focused on embracing and modifying a system for evaluating SpCas9 activity of on-target and off-target using >1,000,000 guide RNAs (gRNAs) covering ~20,000 protein-coding genes and ~10,000 non-coding genes in synthetic constructs with a high-throughput manner. With the help of deep learning algorithms in the field of artificial intelligence, three prediction models with the best generalization performance now are constructed: Aidit_Cas9-ON, Aidit_Cas9-OFF, and Aidit_Cas9-DSB. Moreover, through systematically investigating the influence of diverse cellular environment on gRNA activity and specificity, we noticed that distinct features are favored from H1 cell line compared with the other 2 cell lines for on-target activity and the overall distribution of repair outcomes is markedly different across 3 cell lines, especially in Jurkat. Finally, we identify a key effect protein DNTT strongly influences editing outcomes induced by CRISPR/Cas9. We confirm that this study will greatly facilitate CRISPR-based genome editing.

2023-05-24 | GSE181774 | 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