Up, down, and out: optimized libraries for CRISPRa, CRISPRi, and CRISPR-knockout genetic screens

ABSTRACTAdvances in CRISPR-Cas9 technology have enabled the flexible modulation of gene expression at large scale. In particular, the creation of genome-wide libraries for CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) has allowed gene function to be systematically interrogated. Here, we evaluate numerous CRISPRko libraries and show that our recently-described CRISPRko library (Brunello) is more effective than previously published libraries at distinguishing essential and non-essential genes, providing approximately the same perturbation-level performance improvement over GeCKO libraries as GeCKO provided over RNAi. Additionally, we developed genome-wide libraries for CRISPRi (Dolcetto) and CRISPRa (Calabrese). Negative selection screens showed that Dolcetto substantially outperforms existing CRISPRi libraries with fewer sgRNAs per gene and achieves comparable performance to CRISPRko in the detection of gold-standard essential genes. We also conducted positive selection CRISPRa screens and show that Calabrese outperforms the SAM library approach at detecting vemurafenib resistance genes. We further compare CRISPRa to genome-scale libraries of open reading frames (ORFs). Together, these libraries represent a suite of genome-wide tools to efficiently interrogate gene function with multiple modalities.tracr

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MIC-Drop: A platform for large-scale in vivo CRISPR screens

Science ◽

10.1126/science.abi8870 ◽

2021 ◽

pp. eabi8870

Author(s):

Saba Parvez ◽

Chelsea Herdman ◽

Manu Beerens ◽

Korak Chakraborti ◽

Zachary P. Harmer ◽

...

Keyword(s):

Large Scale ◽

Cultured Cells ◽

Cardiac Development ◽

Droplet Microfluidics ◽

Model Organisms ◽

Genetic Screens ◽

Large Numbers ◽

And Function ◽

Genome Scale

CRISPR-Cas9 can be scaled up for large-scale screens in cultured cells, but CRISPR screens in animals have been challenging because generating, validating, and keeping track of large numbers of mutant animals is prohibitive. Here, we report Multiplexed Intermixed CRISPR Droplets (MIC-Drop), a platform combining droplet microfluidics, single-needle en masse CRISPR ribonucleoprotein injections, and DNA barcoding to enable large-scale functional genetic screens in zebrafish. The platform can efficiently identify genes responsible for morphological or behavioral phenotypes. In one application, we show MIC-Drop can identify small molecule targets. Furthermore, in a MIC-Drop screen of 188 poorly characterized genes, we discover several genes important for cardiac development and function. With the potential to scale to thousands of genes, MIC-Drop enables genome-scale reverse-genetic screens in model organisms.

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Mutant resources for functional genomics in Dictyostelium discoideum using REMI-seq technology

BMC Biology ◽

10.1186/s12915-021-01108-y ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Nicole Gruenheit ◽

Amy Baldwin ◽

Balint Stewart ◽

Sarah Jaques ◽

Thomas Keller ◽

...

Keyword(s):

Dictyostelium Discoideum ◽

High Throughput ◽

Gene Function ◽

Evolutionary Biology ◽

Large Scale ◽

Function Analysis ◽

Model Systems ◽

Genome Wide ◽

The Social ◽

Drug Resistance Marker

Abstract Background Genomes can be sequenced with relative ease, but ascribing gene function remains a major challenge. Genetically tractable model systems are crucial to meet this challenge. One powerful model is the social amoeba Dictyostelium discoideum, a eukaryotic microbe widely used to study diverse questions in the cell, developmental and evolutionary biology. Results We describe REMI-seq, an adaptation of Tn-seq, which allows high throughput, en masse, and quantitative identification of the genomic site of insertion of a drug resistance marker after restriction enzyme-mediated integration. We use REMI-seq to develop tools which greatly enhance the efficiency with which the sequence, transcriptome or proteome variation can be linked to phenotype in D. discoideum. These comprise (1) a near genome-wide resource of individual mutants and (2) a defined pool of ‘barcoded’ mutants to allow large-scale parallel phenotypic analyses. These resources are freely available and easily accessible through the REMI-seq website that also provides comprehensive guidance and pipelines for data analysis. We demonstrate that integrating these resources allows novel regulators of cell migration, phagocytosis and macropinocytosis to be rapidly identified. Conclusions We present methods and resources, generated using REMI-seq, for high throughput gene function analysis in a key model system.

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Efficient strategies for screening large-scale genetic interaction networks

10.1101/159632 ◽

2017 ◽

Cited By ~ 6

Author(s):

Raamesh Deshpande ◽

Justin Nelson ◽

Scott W. Simpkins ◽

Michael Costanzo ◽

Jeff S. Piotrowski ◽

...

Keyword(s):

Large Scale ◽

Optimal Algorithm ◽

Genetic Interaction ◽

Genetic Screens ◽

Chemical Genetic ◽

Genome Wide ◽

Powerful Approach ◽

Interaction Screening ◽

Genetic Interaction Data

Large-scale genetic interaction screening is a powerful approach for unbiased characterization of gene function and understanding systems-level cellular organization. While genome-wide screens are desirable as they provide the most comprehensive interaction profiles, they are resource and time-intensive and sometimes infeasible, depending on the species and experimental platform. For these scenarios, optimal methods for more efficient screening while still producing the maximal amount of information from the resulting profiles are of interest.To address this problem, we developed an optimal algorithm, called COMPRESS-GI, which selects a small but informative set of genes that captures most of the functional information contained within genome-wide genetic interaction profiles. The utility of this algorithm is demonstrated through an application of the approach to define a diagnostic mutant set for large-scale chemical genetic screens, where more than 13,000 compound screens were achieved through the increased throughput enabled by the approach. COMPRESS-GI can be broadly applied for directing genetic interaction screens in other contexts, including in species with little or no prior genetic-interaction data.

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Large-Scale Functional Genomic Analysis of Sporulation and Meiosis in Saccharomyces cerevisiae

Genetics ◽

10.1093/genetics/163.1.47 ◽

2003 ◽

Vol 163 (1) ◽

pp. 47-54 ◽

Cited By ~ 5

Author(s):

Akon H Enyenihi ◽

William S Saunders

Keyword(s):

Saccharomyces Cerevisiae ◽

Large Scale ◽

Single Gene ◽

Genomic Analysis ◽

Essential Genes ◽

Open Reading Frames ◽

Functional Genomic Analysis ◽

Phenotypic Screen ◽

Mutant Bank ◽

Late Stages

Abstract We have used a single-gene deletion mutant bank to identify the genes required for meiosis and sporulation among 4323 nonessential Saccharomyces cerevisiae annotated open reading frames (ORFs). Three hundred thirty-four sporulation-essential genes were identified, including 78 novel ORFs and 115 known genes without previously described sporulation defects in the comprehensive Saccharomyces Genome (SGD) or Yeast Proteome (YPD) phenotype databases. We have further divided the uncharacterized sporulation-essential genes into early, middle, and late stages of meiosis according to their requirement for IME1 induction and nuclear division. We believe this represents a nearly complete identification of the genes uniquely required for this complex cellular pathway. The set of genes identified in this phenotypic screen shows only limited overlap with those identified by expression-based studies.

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CEN-tools: An integrative platform to identify the ‘contexts’ of essential genes

10.1101/2020.05.10.087668 ◽

2020 ◽

Author(s):

Sumana Sharma ◽

Cansu Dincer ◽

Paula Weidemüller ◽

Gavin J Wright ◽

Evangelia Petsalaki

Keyword(s):

Large Scale ◽

Therapeutic Interventions ◽

Genetic Screens ◽

Protein Protein Interaction ◽

Dependency Networks ◽

A Cell ◽

Genetic And Environmental Factors ◽

Context Specific ◽

Systematic Identification ◽

Genome Scale

I.ABSTRACTAn emerging theme from large-scale genetic screens that identify genes essential for fitness of a cell, is that essentiality of a given gene is highly context-specific and depends on a number of genetic and environmental factors. Identification of such contexts could be the key to defining the function of the gene and also to develop novel therapeutic interventions. Here we present CEN-tools (Context-specific Essentiality Network-tools), a website and an accompanying python package, in which users can interrogate the essentiality of a gene from large-scale genome-scale CRISPR screens in a number of biological contexts including tissue of origin, mutation profiles, expression levels, and drug response levels. We show that CEN-tools is suitable for both the systematic identification of genetic dependencies as well as for targeted queries into the dependencies of specific user-selected genes. The associations between genes and a given context within CEN-tools are represented as dependency networks (CENs) and we demonstrate the utility of these networks in elucidating novel gene functions. In addition, we integrate the dependency networks with existing protein-protein interaction networks to reveal context-dependent essential cellular pathways in cancer cells. Together, we demonstrate the applicability of CEN-tools in aiding the current efforts to define the human cellular dependency map.

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Runx1 Shapes the Chromatin Landscape Via a Cascade of Direct and Indirect Targets

10.1101/2020.09.25.313767 ◽

2020 ◽

Author(s):

Matthew R. Hass ◽

Daniel Brisette ◽

Sreeja Parameswaran ◽

Mario Pujato ◽

Omer Donmez ◽

...

Keyword(s):

Transcription Factor ◽

Large Scale ◽

Chromatin Accessibility ◽

Open Chromatin ◽

Genome Wide ◽

Related Transcription Factor ◽

Indirect Consequence ◽

Genome Scale ◽

Upregulated Genes ◽

Transcription Factor 1

AbstractRunt-related transcription factor 1 (Runx1) can act as both an activator and a repressor. Here we show that CRISPR-mediated deletion of Runx1 in an embryonic kidney-derived cell (mK4) results in large-scale genome-wide changes to chromatin accessibility and gene expression. Open chromatin regions near down-regulated loci are enriched for Runx sites, remain bound by Runx2, but lose chromatin accessibility and expression in Runx1 knockout cells. Unexpectedly, regions near upregulated genes are depleted of Runx sites and are instead enriched for Zeb transcription factor binding sites. Re-expressing Zeb2 in Runx1 knockout cells restores suppression. These data confirm that Runx1 activity is uniquely needed to maintain open chromatin at many loci, and demonstrate that genome-scale derepression is an indirect consequence of losing Runx1-dependent Zeb expression.

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Genome-wide CRISPR-dCas9 screens inE. coliidentify essential genes and phage host factors

10.1101/308916 ◽

2018 ◽

Cited By ~ 4

Author(s):

François Rousset ◽

Lun Cui ◽

Elise Siouve ◽

Florence Depardieu ◽

David Bikard

Keyword(s):

High Throughput ◽

Essential Genes ◽

Host Factors ◽

Null Mutant ◽

Genetic Screens ◽

E Coli ◽

Colanic Acid ◽

Genome Wide ◽

A Genome

AbstractHigh-throughput genetic screens are powerful methods to identify genes linked to a given phenotype. The catalytic null mutant of the Cas9 RNA-guided nuclease (dCas9) can be conveniently used to silence genes of interest in a method also known as CRISPRi. Here, we report a genome-wide CRISPR-dCas9 screen using a pool of ~ 92,000 sgRNAs which target random positions in the chromosome ofE. coli. We first investigate the utility of this method for the prediction of essential genes and various unusual features in the genome ofE. coli. We then apply the screen to discoverE. coligenes required by phages λ, T4 and 186 to kill their host. In particular, we show that colanic acid capsule is a barrier to all three phages. Finally, cloning the library on a plasmid that can be packaged by λ enables to identify genes required for the formation of functional λ capsids. This study demonstrates the usefulness and convenience of pooled genome-wide CRISPR-dCas9 screens in bacteria in order to identify genes linked to a given phenotype.

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Reconciling high-throughput gene essentiality data with metabolic network reconstructions

10.1101/415448 ◽

2018 ◽

Cited By ~ 2

Author(s):

Anna S. Blazier ◽

Jason A. Papin

Keyword(s):

Pseudomonas Aeruginosa ◽

Metabolic Network ◽

High Throughput ◽

Large Scale ◽

Essential Genes ◽

Growth And Survival ◽

Gene Essentiality ◽

Model Driven ◽

Functional Explanations ◽

Genome Scale

AbstractThe identification of genes essential for bacterial growth and survival represents a promising strategy for the discovery of antimicrobial targets. Essential genes can be identified on a genome-scale using transposon mutagenesis approaches; however, variability between screens and challenges with interpretation of essentiality data hinder the identification of both condition-independent and condition-dependent essential genes. To illustrate the scope of these challenges, we perform a large-scale comparison of multiple published Pseudomonas aeruginosa gene essentiality datasets, revealing substantial differences between the screens. We then contextualize essentiality using genome-scale metabolic network reconstructions and demonstrate the utility of this approach in providing functional explanations for essentiality and reconciling differences between screens. Genome-scale metabolic network reconstructions also enable a high-throughput, quantitative analysis to assess the impact of media conditions on the identification of condition-independent essential genes. Our computational model-driven analysis provides mechanistic insight into essentiality and contributes novel insights for design of future gene essentiality screens and the identification of core metabolic processes.Author SummaryWith the rise of antibiotic resistance, there is a growing need to discover new therapeutic targets to treat bacterial infections. One attractive strategy is to target genes that are essential for growth and survival. Essential genes can be identified with transposon mutagenesis approaches; however, variability between screens and challenges with interpretation of essentiality data hinder the identification and analysis of essential genes. We performed a large-scale comparison of multiple gene essentiality screens of the microbial pathogen Pseudomonas aeruginosa. We implemented a computational model-driven approach to provide functional explanations for essentiality and reconcile differences between screens. The integration of computational modeling with high-throughput experimental screens may enable the identification of drug targets with high-confidence and provide greater understanding for the development of novel therapeutic strategies.

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Engineering digitizer circuits for chemical and genetic screens in human cells

Nature Communications ◽

10.1038/s41467-021-26359-9 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Nicole M. Wong ◽

Elizabeth Frias ◽

Frederic D. Sigoillot ◽

Justin H. Letendre ◽

Marc Hild ◽

...

Keyword(s):

Large Scale ◽

Dynamic Range ◽

Genetic Screens ◽

Genetic Circuits ◽

Transient Responses ◽

Reporter Activity ◽

Genome Wide ◽

Pathway Activation ◽

Crispr Screen ◽

Or Genes

AbstractCell-based transcriptional reporters are invaluable in high-throughput compound and CRISPR screens for identifying compounds or genes that can impact a pathway of interest. However, many transcriptional reporters have weak activities and transient responses. This can result in overlooking therapeutic targets and compounds that are difficult to detect, necessitating the resource-consuming process of running multiple screens at various timepoints. Here, we present RADAR, a digitizer circuit for amplifying reporter activity and retaining memory of pathway activation. Reporting on the AP-1 pathway, our circuit identifies compounds with known activity against PKC-related pathways and shows an enhanced dynamic range with improved sensitivity compared to a classical reporter in compound screens. In the first genome-wide pooled CRISPR screen for the AP-1 pathway, RADAR identifies canonical genes from the MAPK and PKC pathways, as well as non-canonical regulators. Thus, our scalable system highlights the benefit and versatility of using genetic circuits in large-scale cell-based screening.

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A genome-scale CRISPR interference guide library enables comprehensive phenotypic profiling in yeast

BMC Genomics ◽

10.1186/s12864-021-07518-0 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Nicholas J. McGlincy ◽

Zuriah A. Meacham ◽

Kendra K. Reynaud ◽

Ryan Muller ◽

Rachel Baum ◽

...

Keyword(s):

In Vitro Transcription ◽

Essential Genes ◽

Competitive Growth ◽

Loss Of Function ◽

Design Rules ◽

Growth Defects ◽

Genome Wide ◽

A Genome ◽

Genome Scale

Abstract Background CRISPR/Cas9-mediated transcriptional interference (CRISPRi) enables programmable gene knock-down, yielding loss-of-function phenotypes for nearly any gene. Effective, inducible CRISPRi has been demonstrated in budding yeast, and genome-scale guide libraries enable systematic, genome-wide genetic analysis. Results We present a comprehensive yeast CRISPRi library, based on empirical design rules, containing 10 distinct guides for most genes. Competitive growth after pooled transformation revealed strong fitness defects for most essential genes, verifying that the library provides comprehensive genome coverage. We used the relative growth defects caused by different guides targeting essential genes to further refine yeast CRISPRi design rules. In order to obtain more accurate and robust guide abundance measurements in pooled screens, we link guides with random nucleotide barcodes and carry out linear amplification by in vitro transcription. Conclusions Taken together, we demonstrate a broadly useful platform for comprehensive, high-precision CRISPRi screening in yeast.

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