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Evaluating Capture Sequence Performance for Single-cell CRISPR-activation Experiments

ABSTRACT: The combination of single-cell RNA sequencing with CRISPR inhibition/activation provides a high-throughput approach to simultaneously study the effects of hundreds if not thousands of gene perturbations in a single experiment. One recent development in CRISPR-based single-cell techniques introduces a feature barcoding technology which allows for the simultaneous capture of mRNA and gRNA from the same cell. This is achieved by introducing a capture sequence, whose complement can be incorporated into each gRNA, and which can be used to amplify these features prior to sequencing. However, with the technology in its infancy, there is little information available on how such experimental parameters can be optimised. To overcome this, we varied the capture sequence, capture sequence position and gRNA backbone to identify an optimal gRNA scaffold for CRISPR-activation gene perturbation studies. We provide a report on our screening approach along with our observations and recommendations for future use.

ORGANISM(S): Homo sapiens

PROVIDER: GSE164393 | GEO | 2021/01/08

REPOSITORIES: GEO

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Project description:Clustered regularly interspaced short palindromic repeat (CRISPR) RNA-guided nucleases have gathered considerable excitement as a tool for genome engineering. However, questions remain about the specificity of their target site recognition. Most previous studies have examined predicted off-target binding sites that differ from the perfect target site by one to four mismatches, which represent only a subset of genomic regions. Here, we used ChIP-seq to examine genome-wide CRISPR binding specificity at gRNA-specific and gRNA-independent sites. For two guide RNAs targeting the murine Snurf gene promoter, we observed very high binding specificity at the intended target site while off-target binding was observed at 2- to 6-fold lower intensities. We also identified significant gRNA-independent off-target binding. Interestingly, we found that these regions are highly enriched in the PAM site, a sequence required for target site recognition by CRISPR. To determine the relationship between Cas9 binding and endonuclease activity, we used targeted sequence capture as a high-throughput approach to survey a large number of the potential off-target sites identified by ChIP-seq or computational prediction. A high frequency of indels was observed at both target sites and one off-target site, while no cleavage activity could be detected at other ChIP-bound regions. Our results demonstrate that even a simple configuration of a Cas9:gRNA nuclease can support very specific DNA cleavage activity and that most interactions between the CRISPR nuclease complex and genomic PAM sites do not lead to DNA cleavage. ChIP-seq using dCas9 to determine genome-wide binding of CRISPR/Cas9 noED: Cas9 doublemutant protein without an effector domain KRAB: Cas9 doublemutant protein fused to the KRAB repressor domain S1 gRNA: guide RNA targeting GCTCCCTACGCATGCGTCCC(AGG) in the mouse genome S2 gRNA: guide RNA targeting AATGGCTCAGGTTTGTCGCG(CGG) in the mouse genome VEGFA TS3 gRNA: guide RNA targeting GGTGAGTGAGTGTGTGCGTG(TGG) in the human genome

Project description:Background: The CRISPR/Cas9 toolbox has recently been expanded to include approaches for modulating gene expression. To successfully build on this work, and apply it for answering biological questions, it is important to establish it in a broad range of circumstances. Genome-scale CRISPR interference (CRISPRi) has been used in human cells lines, however the rules for designing effective guide RNAs (gRNAs) in different organisms are not well known. We sought to determine rules that determine gRNA effectiveness at transcriptional repression in Saccharomyces cerevisiae. Results: We created an inducible single plasmid CRISPRi system for gene repression in yeast, and used it to analyze fitness effects of gRNAs under 18 small molecule treatments. Our approach correctly identified previously-described chemical-genetic interactions, as well as a new mechanism of suppressing fluconazole toxicity by repression of the ERG25 gene. Assessment of multiple target loci across treatments allowed us to determine generalizable features associated with gRNA efficacy. Guides that target regions with low nucleosome occupancy and high chromatin accessibility were clearly more effective. We also found the best region to target gRNAs was between the transcription start site (TSS) and 200bp upstream of the TSS. Finally, unlike nuclease-proficient Cas9 in human cells, point mutations were tolerated equally well by truncated (18 nt specificity sequence) and full length (20 nt) gRNAs, however, 18 nt gRNAs were generally less potent than full length gRNAs. Conclusions: Our results establish a powerful functional genomics screening method, provide rules for designing effective gRNAs for gene repression, and show that 18 nt and 20 nt gRNAs exhibit similar tolerance to mismatches in the target sequence. These findings will enable effective library design and genome-wide screening in many genetic backgrounds. An expression construct was created for inducible CRISPRi in yeast. Key features include ORFs expressing dCas9-Mxi1 and the tetracycline repressor (TetR), as well as a tetracycline inducible gRNA locus containing the RPR1 promoter with a TetO site, a NotI site for cloning new gRNA specificity sequences, and the constant part of the gRNA. When yeast containing this plasmid are grown in the absence of anhydrotetracycline (ATc) TetR binds the gRNA promoter and prevents PolIII from binding and transcribing the gRNA. This in turn prevents dCas9-Mxi1 from binding the target site. In the presence of ATc, TetR dissociates and gRNA is expressed, allowing dCas9-Mxi1 to bind its target locus, and repress gene expression. gRNA libraries were cloned into this construct and transformed into yeast to create pools. Experiments were conducted in which yeast pools were grown in inducing (+ATc) and non-inducing conditions (-ATc) in the presence of different drugs. After multiple generations of growth in these conditions, yeast plasmids were minipreped and the gRNA locus was PCRed and sequenced via MiSeq. Counts of each gRNA were compared in different conditions.

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Evaluating Capture Sequence Performance for Single-cell CRISPR-activation Experiments

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