Optimised metrics for CRISPR-KO screens with second-generation gRNA libraries

Abstract Genome-wide CRISPR-based knockout (CRISPR-KO) screening is an emerging technique which enables systematic genetic analysis of a cellular or molecular phenotype in question. Continuous improvements, such as modifications to the guide RNA (gRNA) scaffold and the development of gRNA on-target...

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Main Authors: Swee Hoe Ong, Yilong Li, Hiroko Koike-Yusa, Kosuke Yusa
Format: Article
Language:English
Published: Nature Publishing Group 2017-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-017-07827-z
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spelling doaj-bf61f265b7c34397b4f245df7adcb64e2020-12-08T02:57:52ZengNature Publishing GroupScientific Reports2045-23222017-08-017111010.1038/s41598-017-07827-zOptimised metrics for CRISPR-KO screens with second-generation gRNA librariesSwee Hoe Ong0Yilong Li1Hiroko Koike-Yusa2Kosuke Yusa3Wellcome Trust Sanger InstituteWellcome Trust Sanger InstituteWellcome Trust Sanger InstituteWellcome Trust Sanger InstituteAbstract Genome-wide CRISPR-based knockout (CRISPR-KO) screening is an emerging technique which enables systematic genetic analysis of a cellular or molecular phenotype in question. Continuous improvements, such as modifications to the guide RNA (gRNA) scaffold and the development of gRNA on-target prediction algorithms, have since been made to increase their screening performance. We compared the performance of three available second-generation human genome-wide CRISPR-KO libraries that included at least one of the improvements, and examined the effect of gRNA scaffold, number of gRNAs per gene and number of replicates on screen performance. We identified duplicated screens using a library with 6 gRNAs per gene as providing the best trade-off. Despite the improvements, we found that each improved library still has library-specific false negatives and, for the first time, estimated the false negative rates of CRISPR-KO screens, which are between 10% and 20%. Our newly-defined optimal screening parameters would be helpful in designing screens and constructing bespoke gRNA libraries.https://doi.org/10.1038/s41598-017-07827-z
collection DOAJ
language English
format Article
sources DOAJ
author Swee Hoe Ong
Yilong Li
Hiroko Koike-Yusa
Kosuke Yusa
spellingShingle Swee Hoe Ong
Yilong Li
Hiroko Koike-Yusa
Kosuke Yusa
Optimised metrics for CRISPR-KO screens with second-generation gRNA libraries
Scientific Reports
author_facet Swee Hoe Ong
Yilong Li
Hiroko Koike-Yusa
Kosuke Yusa
author_sort Swee Hoe Ong
title Optimised metrics for CRISPR-KO screens with second-generation gRNA libraries
title_short Optimised metrics for CRISPR-KO screens with second-generation gRNA libraries
title_full Optimised metrics for CRISPR-KO screens with second-generation gRNA libraries
title_fullStr Optimised metrics for CRISPR-KO screens with second-generation gRNA libraries
title_full_unstemmed Optimised metrics for CRISPR-KO screens with second-generation gRNA libraries
title_sort optimised metrics for crispr-ko screens with second-generation grna libraries
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2017-08-01
description Abstract Genome-wide CRISPR-based knockout (CRISPR-KO) screening is an emerging technique which enables systematic genetic analysis of a cellular or molecular phenotype in question. Continuous improvements, such as modifications to the guide RNA (gRNA) scaffold and the development of gRNA on-target prediction algorithms, have since been made to increase their screening performance. We compared the performance of three available second-generation human genome-wide CRISPR-KO libraries that included at least one of the improvements, and examined the effect of gRNA scaffold, number of gRNAs per gene and number of replicates on screen performance. We identified duplicated screens using a library with 6 gRNAs per gene as providing the best trade-off. Despite the improvements, we found that each improved library still has library-specific false negatives and, for the first time, estimated the false negative rates of CRISPR-KO screens, which are between 10% and 20%. Our newly-defined optimal screening parameters would be helpful in designing screens and constructing bespoke gRNA libraries.
url https://doi.org/10.1038/s41598-017-07827-z
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AT hirokokoikeyusa optimisedmetricsforcrisprkoscreenswithsecondgenerationgrnalibraries
AT kosukeyusa optimisedmetricsforcrisprkoscreenswithsecondgenerationgrnalibraries
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