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

2020 ◽  
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).

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

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Eiru Kim ◽  
Traver Hart
Keyword(s):  
Dynamic Range ◽  
Quality Data ◽  
Loss Of Function ◽  
Genetic Screens ◽  
Gene Essentiality ◽  
Guide Rna ◽  
Genome Wide ◽  
And Performance ◽  
Improved Model ◽  
Sensitivity Specificity

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).

scholarly journals Minimal genome-wide human CRISPR-Cas9 library

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.

scholarly journals Minimal genome-wide human CRISPR-Cas9 library

2019 ◽  
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.

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

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

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

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.

scholarly journals In vivo CRISPR-Cas gene editing with no detectable genome-wide off-target mutations

2018 ◽  
Author(s):  
Pinar Akcakaya ◽  
Maggie L. Bobbin ◽  
Jimmy A. Guo ◽  
Jose M. Lopez ◽  
M. Kendell Clement ◽  
...  
Keyword(s):  
Genome Editing ◽  
Ex Vivo ◽  
Strong Support ◽  
Guide Rna ◽  
Genome Wide ◽  
Highly Sensitive ◽  
Further Development ◽  
Target Effects ◽  
Cas Gene

CRISPR-Cas genome-editing nucleases hold substantial promise for human therapeutics1–5 but identifying unwanted off-target mutations remains an important requirement for clinical translation6, 7. For ex vivo therapeutic applications, previously published cell-based genome-wide methods provide potentially useful strategies to identify and quantify these off-target mutation sites8–12. However, a well-validated method that can reliably identify off-targets in vivo has not been described to date, leaving the question of whether and how frequently these types of mutations occur. Here we describe Verification of In Vivo Off-targets (VIVO), a highly sensitive, unbiased, and generalizable strategy that we show can robustly identify genome-wide CRISPR-Cas nuclease off-target effects in vivo. To our knowledge, these studies provide the first demonstration that CRISPR-Cas nucleases can induce substantial off-target mutations in vivo, a result we obtained using a deliberately promiscuous guide RNA (gRNA). More importantly, we used VIVO to show that appropriately designed gRNAs can direct efficient in vivo editing without inducing detectable off-target mutations. Our findings provide strong support for and should encourage further development of in vivo genome editing therapeutic strategies.

scholarly journals No observable guide-RNA-independent off-target mutation induced by prime editor

2021 ◽  
Author(s):  
Runze Gao ◽  
Zhi-Can Fu ◽  
Xiangyang Li ◽  
Ying Wang ◽  
Jia Wei ◽  
...  
Keyword(s):  
Transcriptome Sequencing ◽  
High Specificity ◽  
Human Cells ◽  
Whole Genome ◽  
Guide Rna ◽  
Genome Wide ◽  
Target Sites ◽  
Whole Transcriptome Sequencing ◽  
Whole Transcriptome ◽  
Target Effects

Prime editor (PE) has been recently developed to induce efficient and precise on-target editing, whereas its guide RNA (gRNA)-independent off-target effects remain unknown. Here, we used whole-genome and whole-transcriptome sequencing to determine gRNA-independent off-target mutations in cells expanded from single colonies, in which PE generated precise editing at on-target sites. We found that PE triggered no observable gRNA-independent off-target mutation genome-wide or transcriptome-wide in transfected human cells, highlighting its high specificity.

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

2020 ◽  
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.

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

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.

scholarly journals beditor: A computational workflow for designing libraries of guide RNAs for CRISPR-mediated base editing

2018 ◽  
Author(s):  
Rohan Dandage ◽  
Philippe C Després ◽  
Nozomu Yachie ◽  
Christian R Landry
Keyword(s):  
A Priori ◽  
Maximum Activity ◽  
Base Editing ◽  
Guide Rna ◽  
Guide Rnas ◽  
Genome Wide ◽  
Disease Mutations ◽  
Computational Workflow ◽  
Activity Window ◽  
Target Effects

ABSTRACTCRISPR-mediated base editors have opened unique avenues for scar-free genome-wide mutagenesis. Here, we describe a comprehensive computational workflow called beditor that can be broadly adapted for designing guide RNA libraries with a range of CRISPR-mediated base editors, PAM recognition sequences and genomes of many species. Additionally, in order to assist users in selecting the best sets of guide RNAs for their experiments, a priori estimates, called beditor scores are calculated. These beditor scores are intended to select guide RNAs that conform to requirements for optimal base editing: the editable base falls within maximum activity window of the CRISPR-mediated base editor and produces non-confounding mutational effects with minimal predicted off-target effects. We demonstrate the utility of the software by designing guide RNAs for base-editing to create or remove thousands of clinically important human disease mutations.

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