Improved analysis of CRISPR fitness screens and reduced off-target effects with the BAGEL2 gene essentiality classifier

Abstract Background Identifying essential genes in genome-wide loss-of-function screens is a critical step in functional genomics and cancer target finding. We previously described the Bayesian Analysis of Gene Essentiality (BAGEL) algorithm for accurate classification of gene essentiality from short hairpin RNA and CRISPR/Cas9 genome-wide genetic screens. Results We introduce an updated version, BAGEL2, which employs an improved model that offers a greater dynamic range of Bayes Factors, enabling detection of tumor suppressor genes; a multi-target correction that reduces false positives from off-target CRISPR guide RNA; and the implementation of a cross-validation strategy that improves performance ~ 10× over the prior bootstrap resampling approach. We also describe a metric for screen quality at the replicate level and demonstrate how different algorithms handle lower quality data in substantially different ways. Conclusions BAGEL2 substantially improves the sensitivity, specificity, and performance over BAGEL and establishes the new state of the art in the analysis of CRISPR knockout fitness screens. BAGEL2 is written in Python 3 and source code, along with all supporting files, are available on github (https://github.com/hart-lab/bagel).

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Improved analysis of CRISPR fitness screens and reduced off-target effects with the BAGEL2 gene essentiality classifier

10.1101/2020.05.30.125526 ◽

2020 ◽

Cited By ~ 2

Author(s):

Eiru Kim ◽

Traver Hart

Keyword(s):

Dynamic Range ◽

Quality Data ◽

Loss Of Function ◽

Genetic Screens ◽

Gene Essentiality ◽

Guide Rna ◽

Genome Wide ◽

Improved Model ◽

Target Effects

AbstractIdentifying essential genes in genome-wide loss of function screens is a critical step in functional genomics and cancer target finding. We previously described the Bayesian Analysis of Gene Essentiality (BAGEL) algorithm for accurate classification of gene essentiality from short hairpin RNA and CRISPR/Cas9 genome wide genetic screens. Here, we introduce an updated version, BAGEL2, which employs an improved model that offers greater dynamic range of Bayes Factors, enabling detection of tumor suppressor genes, and a multi-target correction that reduces false positives from off-target CRISPR guide RNA. We also suggest a metric for screen quality at the replicate level and demonstrate how different algorithms handle lower-quality data in substantially different ways. BAGEL2 is written in Python 3 and source code, along with all supporting files, are available on github (https://github.com/hart-lab/bagel).

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Minimal genome-wide human CRISPR-Cas9 library

Genome Biology ◽

10.1186/s13059-021-02268-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Emanuel Gonçalves ◽

Mark Thomas ◽

Fiona M. Behan ◽

Gabriele Picco ◽

Clare Pacini ◽

...

Keyword(s):

Large Scale ◽

Dynamic Range ◽

Loss Of Function ◽

Assay Sensitivity ◽

Guide Rna ◽

Minimal Genome ◽

Backward Compatibility ◽

Large Size ◽

Genome Wide ◽

Complex Models

AbstractCRISPR guide RNA libraries have been iteratively improved to provide increasingly efficient reagents, although their large size is a barrier for many applications. We design an optimised minimal genome-wide human CRISPR-Cas9 library (MinLibCas9) by mining existing large-scale gene loss-of-function datasets, resulting in a greater than 42% reduction in size compared to other CRISPR-Cas9 libraries while preserving assay sensitivity and specificity. MinLibCas9 provides backward compatibility with existing datasets, increases the dynamic range of CRISPR-Cas9 screens and extends their application to complex models and assays.

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Minimal genome-wide human CRISPR-Cas9 library

10.1101/848895 ◽

2019 ◽

Cited By ~ 1

Author(s):

Emanuel Gonçalves ◽

Mark Thomas ◽

Fiona M Behan ◽

Gabriele Picco ◽

Clare Pacini ◽

...

Keyword(s):

Large Scale ◽

Gene Loss ◽

Dynamic Range ◽

Loss Of Function ◽

Assay Sensitivity ◽

Guide Rna ◽

Minimal Genome ◽

Large Size ◽

Genome Wide ◽

Complex Models

AbstractCRISPR guide-RNA libraries have been iteratively optimised to provide increasingly efficient reagents, although their large size is a barrier for many applications. We designed an optimised minimal genome-wide human CRISPR-Cas9 library (MinLibCas9), by mining existing large-scale gene loss-of-function datasets, resulting in a greater than 42% reduction in size compared to other libraries while preserving assay sensitivity and specificity. MinLibCas9 increases the dynamic range of CRISPR-Cas9 loss-of-function screens and extends their application to complex models and assays.

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Abstract 403: CRISPR/Cas9 genome-wide sgRNA libraries for loss-of-function and gain-of-function genetic screens

10.1158/1538-7445.am2017-403 ◽

2017 ◽

Author(s):

Donato Tedesco ◽

Paul Diehl ◽

Mikhail Makhanov ◽

Sylvain Baron ◽

Alex Chenchik

Keyword(s):

Loss Of Function ◽

Genetic Screens ◽

Gain Of Function ◽

Genome Wide

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A simplified transposon mutagenesis method to perform phenotypic forward genetic screens in cultured cells

10.1101/598474 ◽

2019 ◽

Author(s):

Charlotte R. Feddersen ◽

Lexy S. Wadsworth ◽

Eliot Y. Zhu ◽

Hayley R. Vaughn ◽

Andrew P. Voigt ◽

...

Keyword(s):

Cultured Cells ◽

Sequence Data ◽

Sleeping Beauty ◽

Transposon Mutagenesis ◽

Loss Of Function ◽

Genetic Screens ◽

Sleeping Beauty Transposon ◽

Genome Wide ◽

Forward Genetic Screens ◽

The Impact

AbstractThe introduction of genome-wide shRNA and CRISPR libraries has facilitated cell-based screens to identify loss-of-function mutations associated with a phenotype of interest. Approaches to perform analogous gain-of-function screens are less common, although some reports have utilized arrayed viral expression libraries or the CRISPR activation system. However, a variety of technical and logistical challenges make these approaches difficult for many labs to execute. In addition, genome-wide shRNA or CRISPR libraries typically contain of hundreds of thousands of individual engineered elements, and the associated complexity creates issues with replication and reproducibility for these methods. Here we describe a simple, reproducible approach using the Sleeping Beauty transposon system to perform phenotypic cell-based genetic screens. This approach employs only three plasmids to perform unbiased, whole-genome transposon mutagenesis. We also describe a ligation-mediated PCR method that can be used in conjunction with the included software tools to map raw sequence data, identify candidate genes associated with phenotypes of interest, and predict the impact of recurrent transposon insertions on candidate gene function. Finally, we demonstrate the high reproducibility of our approach by having three individuals perform independent replicates of a mutagenesis screen to identify drivers of vemurafenib resistance in cultured melanoma cells. Collectively, our work establishes a facile, adaptable method that can be performed by labs of any size to perform robust, genome-wide screens to identify genes that influence phenotypes of interest.

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Natural selection influenced the genetic architecture of brain structure, behavioral and neuropsychiatric traits

10.1101/2020.02.26.966531 ◽

2020 ◽

Cited By ~ 1

Author(s):

Frank R Wendt ◽

Gita A Pathak ◽

Cassie Overstreet ◽

Daniel S Tylee ◽

Joel Gelernter ◽

...

Keyword(s):

Natural Selection ◽

Complex Traits ◽

Association Studies ◽

Model Fit ◽

Human Populations ◽

Genome Wide Association Studies ◽

Loss Of Function ◽

Risk Alleles ◽

Genome Wide ◽

Improved Model

AbstractNatural selection has shaped the phenotypic characteristics of human populations. Genome-wide association studies (GWAS) have elucidated contributions of thousands of common variants with small effects on an individual’s predisposition to complex traits (polygenicity), as well as wide-spread sharing of risk alleles across traits in the human phenome (pleiotropy). It remains unclear how the pervasive effects of natural selection influence polygenicity in brain-related traits. We investigate these effects by annotating the genome with measures of background (BGS) and positive selection, indications of Neanderthal introgression, measures of functional significance including loss-of-function (LoF) intolerant and genic regions, and genotype networks in 75 brain-related traits. Evidence of natural selection was determined using binary annotations of top 2%, 1%, and 0.5% of selection scores genome-wide. We detected enrichment (q<0.05) of SNP-heritability at loci with elevated BGS (7 phenotypes) and in genic (34 phenotypes) and LoF-intolerant regions (67 phenotypes). BGS (top 2%) significantly predicted effect size variance for trait-associated loci (σ2 parameter) in 75 brain-related traits (β=4.39×10−5, p=1.43×10−5, model r2=0.548). By including the number of DSM-5 diagnostic combinations per psychiatric disorder, we substantially improved model fit (σ2 ~ BTop2% × Genic × diagnostic combinations; model r2=0.661). We show that GWAS with larger variance in risk locus effect sizes are collectively predicted by the effects of loci under strong BGS and in regulatory regions of the genome. We further show that diagnostic complexity exacerbates this relationship and perhaps dampens the ability to detect psychiatric risk loci.

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GO-CRISPR: a highly controlled workflow to discover gene essentiality in loss-of-function screens

10.1101/2020.06.04.134841 ◽

2020 ◽

Author(s):

Pirunthan Perampalam ◽

James I. McDonald ◽

Frederick A. Dick

Keyword(s):

Software Package ◽

Dynamic Range ◽

Superior Performance ◽

Screening Methods ◽

High Grade ◽

Serous Ovarian Cancer ◽

Loss Of Function ◽

Cellular Mechanisms ◽

Sequence Detection ◽

Genome Wide

SUMMARYGenome-wide CRISPR screens are an effective discovery tool for genes that underlie diverse cellular mechanisms that can be scored through cell fitness. Loss-of-function screens are particularly challenging compared to gain-of-function because of the limited dynamic range of decreased sgRNA sequence detection. Here we describe Guide-Only control CRISPR (GO-CRISPR), an improved loss-of-function screening workflow, and its companion software package, Toolset for the Ranked Analysis of GO-CRISPR Screens (TRACS). We demonstrate a typical GO-CRISPR workflow in a non-proliferative 3D spheroid model of dormant high grade serous ovarian cancer and demonstrate superior performance to standard screening methods. The unique integration of the pooled sgRNA library quality and guide-only controls allows TRACS to identify novel molecular pathways that were previously unidentified in tumor dormancy. Together, GO-CRISPR and TRACS can robustly improve the discovery of essential genes in challenging biological scenarios.

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Minimized double guide RNA libraries enable scale-limited CRISPR/Cas9 screens

10.1101/859652 ◽

2019 ◽

Cited By ~ 3

Author(s):

Elin Madli Peets ◽

Luca Crepaldi ◽

Yan Zhou ◽

Felicity Allen ◽

Rasa Elmentaite ◽

...

Keyword(s):

High Performance ◽

Genetic Screens ◽

Screen Design ◽

Guide Rna ◽

Genome Wide ◽

Reagent Cost ◽

Induced Pluripotent ◽

Cellular Phenotypes ◽

Per Gene ◽

Do So

Genetic screens based on CRISPR/Cas technology are a powerful tool for understanding cellular phenotypes. However, the coverage and replicate requirements result in large experiment sizes, which are limiting when samples are scarce, or the protocols are expensive and laborious. Here, we present an approach to reduce the scale of genome-wide perturbation screens up to fivefold without sacrificing performance. To do so, we deliver two randomly paired gRNAs into each cell, and rely on recent advances in gRNA design, as well as availability of gRNA effect measurements, to reduce the number of gRNAs per gene. We designed a human genome-wide library that has effective size of 30,000 constructs, yet targets each gene with three gRNAs. Our minimized double guide RNA library gives similar results to a standard single gRNA one, but using substantially fewer cells. We demonstrate that genome-wide screens can be optimized in a demanding model of induced pluripotent stem cells, reducing reagent cost 70% per replicate compared to conventional approach, while retaining high performance. The screen design and the reduction in scale it provides will enable functional genomics experiments across many possible combinations of environments and genetic backgrounds, as well as in hard to obtain and culture primary cells.

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Pooled analysis of radiation hybrids identifies loci for growth and drug action in mammalian cells

10.1101/2019.12.16.877365 ◽

2019 ◽

Author(s):

Arshad H. Khan ◽

Andy Lin ◽

Richard T. Wang ◽

Joshua S. Bloom ◽

Kenneth Lange ◽

...

Keyword(s):

Mammalian Cells ◽

Single Gene ◽

Pooled Analysis ◽

Loss Of Function ◽

Genetic Screens ◽

Gene Copies ◽

Radiation Hybrids ◽

Genome Wide ◽

Low Pass ◽

Mammalian Genetic

AbstractGenetic screens in mammalian cells commonly focus on loss-of-function approaches. To evaluate the phenotypic consequences of extra gene copies, we used bulk segregant analysis (BSA) of radiation hybrid (RH) cells. We constructed six pools of RH cells, each consisting of ~2500 independent clones, and placed the pools under selection in media with or without paclitaxel. Low pass sequencing identified 859 growth loci, 38 paclitaxel loci, 62 interaction loci and 3 loci for mitochondrial abundance at genome-wide significance. Resolution was measured as ~30 kb, close to single-gene. Divergent properties were displayed by the RH-BSA growth genes compared to those from loss-of-function screens, refuting the balance hypothesis. In addition, enhanced retention of human centromeres in the RH pools suggests a new approach to functional dissection of these chromosomal elements. Pooled analysis of RH cells showed high power and resolution and should be a useful addition to the mammalian genetic toolkit.

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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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