Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

An inducible CRISPR-interference library for genetic interrogation of Saccharomyces cerevisiae biology

ABSTRACT: Genome-scale CRISPR interference (CRISPRi) is widely utilized to study cellular processes in a variety of organisms. To date, a genome-wide CRISPRi library, optimized for targeting the Saccharomyces cerevisiae genome, has not been presented. Here, we have generated a comprehensive, inducible CRISPRi library, based on spacer design rules optimized for yeast. We have validated this library for genome-wide interrogation of gene function across a variety of applications, including accurate discovery of haploinsufficient genes and identification of enzymatic and regulatory genes involved in adenine and arginine biosynthesis. The comprehensive nature of the library also revealed refined spacer design parameters for transcriptional repression, including location, nucleosome occupancy and nucleotide features. CRISPRi screens using this library can identify genes and pathways with high precision and low false discovery rate across a variety of experimental conditions, enabling rapid and reliable genome-wide assessment of genetic function and interactions in S. cerevisiae.

ORGANISM(S): Escherichia coli Saccharomyces cerevisiae

PROVIDER: GSE159409 | GEO | 2020/11/27

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

MitoKO: A library of base editors for precise ablation of all protein-coding genes in the mouse mitochondrial genome

Project description:We design and apply a highly optimized library of double-stranded DNA deaminase (DddA)-derived cytosine base editors (DdCBEs) - MitoKO - to precisely ablate every mtDNA protein coding gene in the mouse mitochondrial genome

2023-05-24 | GSE202643 | GEO

Improved prediction of bacterial CRISPRi guide efficiency from depletion screens through mixed-effect machine learning and data integration

Project description:CRISPR interference (CRISPRi), the targeting of a catalytically dead Cas protein to block transcription, is the leading technique to silence gene expression in bacteria. However, design rules for CRISPRi remain poorly defined, limiting predictable design for gene interrogation, pathway manipulation, and high-throughput screens. Here we develop a best-in-class prediction algorithm for guide silencing efficiency by systematically investigating factors influencing guide depletion in multiple genome-wide essentiality screens, with the surprising discovery that gene-specific features such as transcriptional activity substantially impact prediction of guide activity. Accounting for these features as part of algorithm development allowed us to develop a mixed-effect random forest regression model that provides better estimates of guide efficiency than existing methods, as demonstrated in an independent saturating screen. We further applied methods from explainable AI to extract interpretable design rules from the model, such as sequence preferences in the vicinity of the PAM distinct from those previously described for genome engineering applications. Our approach provides a blueprint for the development of predictive models for CRISPR technologies where only indirect measurements of guide activity are available.

2023-12-19 | GSE196911 | GEO

Comparison of non-specific transcriptional effects of CRISPRi effector proteins by RNA-seq

Project description:CRISPR interference (CRISPRi) genetic screens use programmable repression of gene expression to systematically explore questions in cell biology and genetics. However, wider adoption of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and lack of consensus on the choice of CRISPRi effector proteins. Here, we address these challenges to present next-generation CRISPRi sgRNA libraries and effectors. First, we combine empiric sgRNA selection with a dual sgRNA library design to generate an ultra-compact, highly active CRISPRi sgRNA library. Next, we rigorously compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides an optimal balance between strong on-target knockdown and minimal nonspecific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines which stably express Zim3-dCas9 and demonstrate robust on-target knockdown across these cell lines. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

2022-06-03 | GSE205147 | GEO

Comparison of dual sgRNA library versus Dolcetto by Perturb-seq

2022-06-04 | GSE205310 | GEO

CRISPR-based screening of small RNA modulators of bile susceptibility in Bacteroides thetaiotaomicron

Project description:Microbiota-centric interventions are limited by our incomplete understanding of the gene functions of many of its constituent species. This applies in particular to small RNAs (sRNAs), which are emerging as important regulators in microbiota species yet tend to be missed by traditional functional genomics approaches. Here, we establish CRISPR interference (CRISPRi) in the abundant microbiota member Bac-teroides thetaiotaomicron for genome-wide sRNA screens. By assessing the abundance of different pro-tospacer-adjacent motifs, we identify the Prevotella bryantii B14 Cas12a as a suitable nuclease for CRISPR screens in these bacteria and generate an inducible Cas12a expression system. Using a luciferase reporter strain, we infer guide design rules for and use this knowledge to assemble a computational pipeline for automated gRNA design. By subjecting the resulting guide library to a phenotypic screen, we uncover the previously uncharacterized sRNA BTnc167 to increase susceptibility to bile salts, likely through the regulation of genes involved in Bacteroides cell surface structure. Our work lays the groundwork for systematically uncovering hidden functions of bacterial sRNAs under a variety of con-ditions and, generally, to unlock the genetic potential of these major human gut mutualists.

2023-06-27 | GSE235620 | GEO

Accurate Design of Translational Output by a Neural Network Model of Ribosome Distribution

Project description:We present a ribosome profiling data set from S. cerevisiae as part of a larger study that models the elongation rate along transcripts as a function of local sequence neighborhoods. We then apply this model to design coding sequences that are optimized for translational output.

2017-11-07 | GSE106572 | GEO

Project description:Genome-wide CRISPRi screen in E. coli MG1655 using the EcoWG1 library

| PRJNA592950 | ENA

A CRISPRi system for efficient and rapid gene knockdown in Caulobacter crescentus

Project description:CRISPR interference (CRISPRi) is a powerful new tool used in different organisms that provides a fast, specific, and reliable way to knockdown gene expression. Caulobacter crescentus is a well-studied model bacterium, and although a variety of genetic tools have been developed, it currently takes several weeks to delete or deplete individual genes, which significantly limits genetic studies. Here, we optimized a CRISPRi approach to specifically downregulate the expression of genes in C. crescentus. Although the Streptococcus pyogenes CRISPRi system commonly used in other organisms does not work efficiently in Caulobacter, we demonstrate that a catalytically-dead version of Cas9 (dCas9) derived from the type II CRISPR3 module of Streptococcus thermophilus or from Streptococcus pasteurianus can each be effectively used in Caulobacter. We show that these CRISPRi systems can be used to rapidly and inducibly deplete ctrA or gcrA, two essential well-studied genes in Caulobacter, in either asynchronous or synchronized populations of cells. Additionally, we demonstrate the ability to multiplex CRISPRi-based gene knockdowns, opening new possibilities for systematic genetic interaction studies in Caulobacter.

2020-01-23 | GSE139521 | GEO

Mining novel gene targets for improving tolerance to furfural and acetic acid in Yarrowia lipolytica using whole-genome clustered regularly interspaced short palindromic repeats interference library

Project description:In this study, a whole-genome CRISPRi library was developed in Y. lipolytica and applied for enforcing the tolerance to furfural and acetic acid. Several novel gene targets were discovered through NGS before and after screening. And to analyze the tolerance mechanism caused by transcriptional repression of the most prominent gene targets, the transcriptome and proteomics were performed.

2024-03-31 | PXD051116 | iProX

IPTG-induced CRISPRi repression of firefly luciferase in Streptococcus pneumoniae

Project description:Genome-wide screens have discovered a large set of essential genes in the human pathogen Streptococcus pneumoniae. However, the function of many essential genes is still unknown, hampering vaccine and drug development programs. Based on results from transposon-sequencing (Tn-Seq), we refined the list of essential genes in S. pneumoniae serotype 2 strain D39. Next, we created a knockdown library targeting all 391 potentially essential genes using CRISPR interference (CRISPRi). Using high-content microscopy screening, we searched for essential genes of unknown function with clear phenotypes in cell morphology upon CRISPRi-based depletion. We identified SPD1416 and SPD1417 (named to MurT and GatD, respectively) as essential peptidoglycan synthesis proteins and we show that SPD1198 and SPD1197 (named to TarP and TarQ, respectively) are responsible for the polymerization of teichoic acid (TA) precursors. This knowledge enabled us to reconstruct the unique pneumococcal TA biosynthetic pathway. Our CRISPRi library provides a valuable tool for characterization of pneumococcal genes and pathways and revealed several promising antibiotic targets. This RNA-Seq dataset is aimed to show that induction of the CRISPRi system very selectively represses its target gene, firefly luciferase, without other observable transcriptional effects.

2017-03-03 | GSE89763 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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