NDLI: Genome-scale CRISPR screening at high sensitivity with an empirically designed sgRNA library

Content Provider	Springer Nature : BioMed Central
Author	Henkel, Luisa Rauscher, Benedikt Schmitt, Barbara Winter, Jan Boutros, Michael
Abstract	Background In recent years, large-scale genetic screens using the CRISPR/Cas9 system have emerged as scalable approaches able to interrogate gene function with unprecedented efficiency and specificity in various biological contexts. By this means, functional dependencies on both the protein-coding and noncoding genome of numerous cell types in different organisms have been interrogated. However, screening designs vary greatly and criteria for optimal experimental implementation and library composition are still emerging. Given their broad utility in functionally annotating genomes, the application and interpretation of genome-scale CRISPR screens would greatly benefit from consistent and optimal design criteria. Results We report advantages of conducting viability screens in selected Cas9 single-cell clones in contrast to Cas9 bulk populations. We further systematically analyzed published CRISPR screens in human cells to identify single-guide (sg) RNAs with consistent high on-target and low off-target activity. Selected guides were collected in a novel genome-scale sgRNA library, which efficiently identifies core and context-dependent essential genes. Conclusion We show how empirically designed libraries in combination with an optimized experimental design increase the dynamic range in gene essentiality screens at reduced library coverage.
Related Links	https://bmcbiol.biomedcentral.com/counter/pdf/10.1186/s12915-020-00905-1.pdf
Ending Page	21
Page Count	21
Starting Page	1
File Format	HTM / HTML
ISSN	17417007
DOI	10.1186/s12915-020-00905-1
Journal	BMC Biology
Issue Number	1
Volume Number	18
Language	English
Publisher	BioMed Central
Publisher Date	2020-11-23
Access Restriction	Open
Subject Keyword	Life Sciences CRISPR/Cas9 Genetic screens sgRNA design Gene essentiality Functional genomics
Content Type	Text
Resource Type	Article
Subject	Ecology, Evolution, Behavior and Systematics Structural Biology Biochemistry, Genetics and Molecular Biology Plant Science Biotechnology Physiology Agricultural and Biological Sciences Cell Biology Developmental Biology
Journal Impact Factor	4.4/2023
5-Year Journal Impact Factor	5.4/2023

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