Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A CRISPR Resource for Individual, Combinatorial, or Multiplexed Gene Knockout.

ABSTRACT: We have combined a machine-learning approach with other strategies to optimize knockout efficiency with the CRISPR/Cas9 system. In addition, we have developed a multiplexed sgRNA expression strategy that promotes the functional ablation of single genes and allows for combinatorial targeting. These strategies have been combined to design and construct a genome-wide, sequence-verified, arrayed CRISPR library. This resource allows single-target or combinatorial genetic screens to be carried out at scale in a multiplexed or arrayed format. By conducting parallel loss-of-function screens, we compare our approach to existing sgRNA design and expression strategies.

SUBMITTER: Erard N

PROVIDER: S-EPMC5526787 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A CRISPR Resource for Individual, Combinatorial, or Multiplexed Gene Knockout.

Erard Nicolas N Knott Simon R V SRV Hannon Gregory J GJ

Molecular cell 20170701 2

We have combined a machine-learning approach with other strategies to optimize knockout efficiency with the CRISPR/Cas9 system. In addition, we have developed a multiplexed sgRNA expression strategy that promotes the functional ablation of single genes and allows for combinatorial targeting. These strategies have been combined to design and construct a genome-wide, sequence-verified, arrayed CRISPR library. This resource allows single-target or combinatorial genetic screens to be carried out at ...[more]

PMID: 28732207

Similar Datasets

An arrayed CRISPR library for individual, combinatorial and multiplexed gene knockout

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

2017-07-20 | GSE97434 | GEO

An arrayed CRISPR library for individual, combinatorial and multiplexed gene knockout III

Project description:We have combined a machine-learning approach with other strategies to optimize the efficiency of sgRNAs for CRISPR screens and have constructed a genome-wide, sequence-verified, arrayed CRISPR library. This incorporates expression strategies to facilitate multiplexed or combinatorial screening. By conducting parallel loss-of-function screens, we compare our approach to existing sgRNA design and expression strategies.

2017-07-20 | GSE97433 | GEO

An arrayed CRISPR library for individual, combinatorial and multiplexed gene knockout II

2017-07-20 | GSE97432 | GEO

An arrayed CRISPR library for individual, combinatorial and multiplexed gene knockout I

2017-07-20 | GSE97431 | GEO

An arrayed CRISPR library for individual, combinatorial and multiplexed gene knockout

Project description:An arrayed CRISPR library for individual, combinatorial and multiplexed gene knockout

| PRJNA381776 | ENA

Multiplexed CRISPR/Cas9 gene knockout with simple crRNA:tracrRNA co-transfection.

Project description:BackgroundCRISPR/Cas9 mediated gene knockout is a powerful tool for genome editing with the ability to target multiple genes simultaneously. Establishing an efficient, multiplexed gene knockout system using CRISPR/Cas9 that is both simple and robust in its application would further advance the adoption of CRISPR/Cas9 for genetic studies.ResultsIn this study, we present a simple, versatile and highly efficient method to achieve acute gene knockout with CRISPR/Cas9 using chemically synthesized crRNA and tracrRNA oligos. We demonstrate that co-transfection of the crRNA:tracrRNA duplex into Cas9-expressing cells leads to target gene mutation and loss of target protein expression in the majority of the cell population. We also show that delivering three crRNAs targeting EGFP, KRAS and PTEN in the same reaction leads to the simultaneous knockout of all three genes. Direct comparison of multiplexed gene targeting by crRNA:tracrRNA and by siRNA indicates that these two methods are comparable in their efficiency and kinetics of gene silencing.ConclusionsOur method is a convenient yet powerful tool to enable rapid and scalable gene knockout using CRISPR/Cas9 in mammalian cells.

| S-EPMC6528186 | biostudies-literature

CRISPR knockout screening identifies combinatorial drug targets in pancreatic cancer and models cellular drug response.

Project description:Predicting the response and identifying additional targets that will improve the efficacy of chemotherapy is a major goal in cancer research. Through large-scale in vivo and in vitro CRISPR knockout screens in pancreatic ductal adenocarcinoma cells, we identified genes whose genetic deletion or pharmacologic inhibition synergistically increase the cytotoxicity of MEK signaling inhibitors. Furthermore, we show that CRISPR viability scores combined with basal gene expression levels could model global cellular responses to the drug treatment. We develop drug response evaluation by in vivo CRISPR screening (DREBIC) method and validated its efficacy using large-scale experimental data from independent experiments. Comparative analyses demonstrate that DREBIC predicts drug response in cancer cells from a wide range of tissues with high accuracy and identifies therapeutic vulnerabilities of cancer-causing mutations to MEK inhibitors in various cancer types.

| S-EPMC6189038 | biostudies-literature

Multiplexed CRISPR technologies for gene editing and transcriptional regulation.

Project description:Multiplexed CRISPR technologies, in which numerous gRNAs or Cas enzymes are expressed at once, have facilitated powerful biological engineering applications, vastly enhancing the scope and efficiencies of genetic editing and transcriptional regulation. In this review, we discuss multiplexed CRISPR technologies and describe methods for the assembly, expression and processing of synthetic guide RNA arrays in vivo. Applications that benefit from multiplexed CRISPR technologies, including cellular recorders, genetic circuits, biosensors, combinatorial genetic perturbations, large-scale genome engineering and the rewiring of metabolic pathways, are highlighted. We also offer a glimpse of emerging challenges and emphasize experimental considerations for future studies.

| S-EPMC7062760 | biostudies-literature

Combinatorial CRISPR screen identifies fitness effects of gene paralogues.

Project description:Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. Our studies reveal the fitness effects of FAM50A/FAM50B in cancer cells.

| S-EPMC7910459 | biostudies-literature

Efficient gene knockout in goats using CRISPR/Cas9 system.

Project description:The CRISPR/Cas9 system has been adapted as an efficient genome editing tool in laboratory animals such as mice, rats, zebrafish and pigs. Here, we report that CRISPR/Cas9 mediated approach can efficiently induce monoallelic and biallelic gene knockout in goat primary fibroblasts. Four genes were disrupted simultaneously in goat fibroblasts by CRISPR/Cas9-mediated genome editing. The single-gene knockout fibroblasts were successfully used for somatic cell nuclear transfer (SCNT) and resulted in live-born goats harboring biallelic mutations. The CRISPR/Cas9 system represents a highly effective and facile platform for targeted editing of large animal genomes, which can be broadly applied to both biomedical and agricultural applications.

| S-EPMC4154755 | biostudies-literature

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