Compact CRISPR genetic screens enabled by improved guide RNA library cloning

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Abstract

CRISPR genome editing approaches theoretically enable researchers to define the function of each human gene in specific cell types, but challenges remain to efficiently perform genetic perturbations in relevant models. In this work, we develop a library cloning protocol that increases sgRNA uniformity and greatly reduces bias in existing genome-wide libraries. We demonstrate that our libraries can achieve equivalent or better statistical power compared to previously reported screens using an order of magnitude fewer cells. This improved cloning protocol enables genome-scale CRISPR screens in technically challenging cell models and screen formats.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-023-03132-3.

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Most cited references 53

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clusterProfiler: an R package for comparing biological themes among gene clusters.

Guangchuang Yu, Li-Gen Wang, Yanyan Han … (2012)

Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

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KEGG: kyoto encyclopedia of genes and genomes.

M Kanehisa (2000)

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).

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Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

Da Huang, Brad T. Sherman, Richard A. Lempicki (2009)

DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.

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Author and article information

Contributors

Eric D. Chow:

ORCID: http://orcid.org/0000-0001-8079-918X

eric.chow@ucsf.edu

Journal

Journal ID (nlm-ta): Genome Biol

Journal ID (iso-abbrev): Genome Biol

Title: Genome Biology

Publisher: BioMed Central (London )

ISSN (Print): 1474-7596

ISSN (Electronic): 1474-760X

Publication date (Electronic): 19 January 2024

Publication date PMC-release: 19 January 2024

Publication date Collection: 2024

Volume: 25

Electronic Location Identifier: 25

Affiliations

[1 ]Laboratory for Genomics Research, San Francisco, CA 94158 USA

[2 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Department of Biochemistry and Biophysics, , University of California, ; San Francisco, San Francisco, CA 94158 USA

[3 ]GRID grid.418019.5, ISNI 0000 0004 0393 4335, GSK, ; San Francisco, CA 94158 USA

Author information

Lauren D. Enriquez http://orcid.org/0000-0002-8587-6532

Scot Federman http://orcid.org/0000-0001-8712-3131

Amy Y. Chang http://orcid.org/0000-0001-9993-6658

Rachel Mace http://orcid.org/0000-0002-7176-9189

Kaivalya Shevade http://orcid.org/0000-0001-5681-3260

Laralynne Przybyla http://orcid.org/0000-0002-8598-4779

Eric D. Chow http://orcid.org/0000-0001-8079-918X

Article

Publisher ID: 3132

DOI: 10.1186/s13059-023-03132-3

PMC ID: 10797759

PubMed ID: 38243310

SO-VID: 97dd979f-5f57-4f23-97f2-3bb40beff489

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 9 June 2023

Date accepted : 29 November 2023

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ScienceOpen disciplines: Genetics

Keywords: crispr screening,library cloning,guide library,ipsc-derived crispr screening,primary cell crispr screening

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ScienceOpen disciplines: Genetics

Keywords: crispr screening, library cloning, guide library, ipsc-derived crispr screening, primary cell crispr screening

Compact CRISPR genetic screens enabled by improved guide RNA library cloning

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Supplementary Information

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RNA drug delivery

Most cited references 53

clusterProfiler: an R package for comparing biological themes among gene clusters.

KEGG: kyoto encyclopedia of genes and genomes.

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

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