Multiple-gene targeting and mismatch tolerance can confound analysis of genome-wide pooled CRISPR screens

BackgroundGenome-wide loss-of-function screens using the CRISPR/Cas9 system allow the efficient discovery of cancer cell vulnerabilities. While several studies have focused on correcting for DNA cleavage toxicity biases associated with copy number alterations, the effects of sgRNAs co-targeting multiple genomic loci in CRISPR screens have not been discussed.ResultsIn this work, we analyze CRISPR essentiality screen data from 391 cancer cell lines to characterize biases induced by multi-target sgRNAs. We investigate two types of multi-targets: on-targets predicted through perfect sequence complementarity and off-targets predicted through sequence complementarity with up to two nucleotide mismatches. We find that the number of on-targets and off-targets both increase sgRNA activity in a cell line-specific manner and that existing additive models of gene knockout effects fail at capturing genetic interactions that may occur between co-targeted genes. We use synthetic lethality between paralog genes to show that genetic interactions can introduce biases in essentiality scores estimated from multi-target sgRNAs. We further show that single-mismatch tolerant sgRNAs can confound the analysis of gene essentiality and lead to incorrect co-essentiality functional networks. Lastly, we also find that single nucleotide polymorphisms located in protospacer regions can impair on-target activity as a result of mismatch tolerance.ConclusionWe show the impact of multi-target effects on estimating cancer cell dependencies and the impact of off-target effects caused by mismatch tolerance in sgRNA-DNA binding.

[1]  Alan Ashworth,et al.  Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy , 2005, Nature.

[2]  D. Durocher,et al.  High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities , 2015, Cell.

[3]  S. Dave,et al.  Gene essentiality landscape and druggable oncogenic dependencies in herpesviral primary effusion lymphoma , 2018, Nature Communications.

[4]  Neville E. Sanjana,et al.  Improved vectors and genome-wide libraries for CRISPR screening , 2014, Nature Methods.

[5]  Peng Jiang,et al.  Improved design and analysis of CRISPR knockout screens , 2018, Bioinform..

[6]  Adam P. Rosebrock,et al.  A global genetic interaction network maps a wiring diagram of cellular function , 2016, Science.

[7]  Joshua M. Korn,et al.  CRISPR Screens Provide a Comprehensive Assessment of Cancer Vulnerabilities but Generate False-Positive Hits for Highly Amplified Genomic Regions. , 2016, Cancer discovery.

[8]  Xiongbin Lu,et al.  Abstract A36: TP53 loss creates therapeutic vulnerability in colorectal cancer , 2017 .

[9]  Martin J. Aryee,et al.  GUIDE-Seq enables genome-wide profiling of off-target cleavage by CRISPR-Cas nucleases , 2014, Nature Biotechnology.

[10]  Paralog buffering contributes to the variable essentiality of genes in cancer cell lines , 2019, PLoS genetics.

[11]  Jong-il Kim,et al.  Digenome-seq: genome-wide profiling of CRISPR-Cas9 off-target effects in human cells , 2015, Nature Methods.

[12]  Bronwen L. Aken,et al.  GENCODE: The reference human genome annotation for The ENCODE Project , 2012, Genome research.

[13]  Jean-Claude Tardif,et al.  Human genetic variation alters CRISPR-Cas9 on- and off-targeting specificity at therapeutically implicated loci , 2017, Proceedings of the National Academy of Sciences.

[14]  E. Lander,et al.  Identification and characterization of essential genes in the human genome , 2015, Science.

[15]  Antoine de Weck,et al.  Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening , 2017, Cell.

[16]  Clifford A. Meyer,et al.  Sequence determinants of improved CRISPR sgRNA design , 2015, Genome research.

[17]  D. Morgens,et al.  Systematic comparison of CRISPR-Cas9 and RNAi screens for essential genes , 2016, Nature Biotechnology.

[18]  Henriette O'Geen,et al.  A genome-wide analysis of Cas9 binding specificity using ChIP-seq and targeted sequence capture , 2014, bioRxiv.

[19]  Gaelen T. Hess,et al.  Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens , 2017, Nature Communications.

[20]  Michael P Snyder,et al.  Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements , 2019, Nature Communications.

[21]  T. Golub,et al.  Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting. , 2016, Cancer discovery.

[22]  Meagan E. Sullender,et al.  Rational design of highly active sgRNAs for CRISPR-Cas9–mediated gene inactivation , 2014, Nature Biotechnology.

[23]  Neville E. Sanjana,et al.  High-throughput functional genomics using CRISPR–Cas9 , 2015, Nature Reviews Genetics.

[24]  L. Chin,et al.  Passenger Deletions Generate Therapeutic Vulnerabilities in Cancer , 2012, Nature.

[25]  Joshua M. Korn,et al.  Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs , 2008, Nature Genetics.

[26]  J. Moffat,et al.  Measuring error rates in genomic perturbation screens: gold standards for human functional genomics , 2014, bioRxiv.

[27]  Ellen T. Gelfand,et al.  Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies , 2014, Scientific Data.

[28]  Jin-Soo Kim,et al.  Genome-wide target specificities of CRISPR-Cas9 nucleases revealed by multiplex Digenome-seq , 2016, Genome research.

[29]  Prasenjit Dey,et al.  Genomic deletion of malic enzyme 2 confers collateral lethality in pancreatic cancer , 2017, Nature.

[30]  D. Durocher,et al.  Evaluation and Design of Genome-Wide CRISPR/SpCas9 Knockout Screens , 2017, G3: Genes, Genomes, Genetics.

[31]  Genetic variation may confound analysis of CRISPR-Cas9 off-target mutations , 2018, Cell Discovery.

[32]  Anushya Muruganujan,et al.  PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements , 2016, Nucleic Acids Res..

[33]  Eli J. Fine,et al.  DNA targeting specificity of RNA-guided Cas9 nucleases , 2013, Nature Biotechnology.

[34]  C. Roberts,et al.  Functional epigenetics approach identifies BRM/SMARCA2 as a critical synthetic lethal target in BRG1-deficient cancers , 2014, Proceedings of the National Academy of Sciences.

[35]  Gang Bao,et al.  CRISPR/Cas9 systems have off-target activity with insertions or deletions between target DNA and guide RNA sequences , 2014, Nucleic acids research.

[36]  T. J. Terpstra,et al.  The asymptotic normality and consistency of kendall's test against trend, when ties are present in one ranking , 1952 .

[37]  A. R. Jonckheere,et al.  A DISTRIBUTION-FREE k-SAMPLE TEST AGAINST ORDERED ALTERNATIVES , 1954 .

[38]  Ann E. Sizemore,et al.  Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells , 2017, Nature Genetics.

[39]  Ted Natoli,et al.  Evaluation of RNAi and CRISPR technologies by large-scale gene expression profiling in the Connectivity Map , 2017, bioRxiv.

[40]  Z. Strezoska,et al.  Systematic analysis of CRISPR-Cas9 mismatch tolerance reveals low levels of off-target activity. , 2015, Journal of biotechnology.

[41]  J. Micol,et al.  Understanding synergy in genetic interactions. , 2009, Trends in genetics : TIG.

[42]  Matthew C. Canver,et al.  Variant-aware saturating mutagenesis using multiple Cas9 nucleases identifies regulatory elements at trait-associated loci , 2017, Nature Genetics.

[43]  L. Vecchione,et al.  Importance of genetic screens in precision oncology , 2019, ESMO Open.

[44]  C. Landry,et al.  Paralog dependency indirectly affects the robustness of human cells , 2019, Molecular systems biology.

[45]  Jill P. Mesirov,et al.  Cancer Vulnerabilities Unveiled by Genomic Loss , 2012, Cell.

[46]  J. Joung,et al.  Defining and improving the genome-wide specificities of CRISPR–Cas9 nucleases , 2016, Nature Reviews Genetics.

[47]  Eiru Kim,et al.  Hierarchical organization of the human cell from a cancer coessentiality network , 2018, bioRxiv.

[48]  Cole Trapnell,et al.  Ultrafast and memory-efficient alignment of short DNA sequences to the human genome , 2009, Genome Biology.

[49]  Z. Modrušan,et al.  PRC2-mediated repression of SMARCA2 predicts EZH2 inhibitor activity in SWI/SNF mutant tumors , 2017, Proceedings of the National Academy of Sciences of the United States of America.

[50]  J. Keith Joung,et al.  High frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells , 2013, Nature Biotechnology.

[51]  Raphaella W. L. So,et al.  Application of CRISPR genetic screens to investigate neurological diseases , 2019, Molecular Neurodegeneration.

[52]  Meagan E. Sullender,et al.  Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9 , 2015, Nature Biotechnology.

[53]  D. H. Kim,et al.  Myosin regulatory light chains are required to maintain the stability of myosin II and cellular integrity. , 2011, The Biochemical journal.

[54]  David A. Scott,et al.  Implications of human genetic variation in CRISPR-based therapeutic genome editing , 2017, Nature Medicine.