Multiplexed genome engineering by Cas12a and CRISPR arrays encoded on single transcripts

Abstract

The ability to modify multiple genetic elements simultaneously would help to elucidate and control the gene interactions and networks underlying complex cellular functions. However, current genome engineering technologies are limited in both the number and the type of perturbations that can be performed simultaneously. Here, we demonstrate that both Cas12a and a clustered regularly interspaced short palindromic repeat (CRISPR) array can be encoded in a single transcript by adding a stabilizer tertiary RNA structure. By leveraging this system, we illustrate constitutive, conditional, inducible, orthogonal and multiplexed genome engineering of endogenous targets using up to 25 individual CRISPR RNAs delivered on a single plasmid. Our method provides a powerful platform to investigate and orchestrate the sophisticated genetic programs underlying complex cell behaviors.

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Fig. 1: Simultaneous control of protein and crRNA expression from Pol II promoters.
Fig. 2: Multiplexed genome editing by SiT-Cas12a.
Fig. 3: Multiplexed transcriptional repression using SiT-Cas12a-[Repr].
Fig. 4: Multiplexed transcriptional activation using SiT-Cas12a.
Fig. 5: Orthogonal transcriptional gene regulation and editing.
Fig. 6: Multiplexed orthogonal gene editing and transcriptional activation.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. The datasets generated during the current study are available in the NCBI Sequence Read Archive (BioProject ID PRJNA530879). The data sets generated and/or analysed during the current study are available from the corresponding author upon reasonable request. The custom scripts used for the described data analysis areavailable on the Platt Laboratory website (http://www.platt.ethz.ch).

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Acknowledgements

We thank the entire Platt Laboratory for productive discussions; C. Beisel, E. Burcklen, K. Eschbach, I. Nissen and M. Kohler from the Genomics Facility Basel for assistance in Illumina sequencing. This project was supported by the Swiss National Science Foundation, ETH domain Personalized Health and Related Technologies, Brain and Behavior Research Foundation, the National Centres of Competence—Molecular Systems Engineering and ETH Zurich. C.C.C. was supported by the ETH Postdoctoral Fellowship.

Author information

C.C.C., N.R.W. and R.J.P. conceived and designed the experiments. C.C.C. and N.R.W. performed the experiments and analyzed the data. A.J.S analyzed the deep sequencing data. D.I. analyzed the RNA-seq data. C.C.C., N.R.W. and R.J.P. wrote the manuscript. All authors reviewed the paper and provided comments.

Correspondence to Randall J. Platt.

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The authors declare no competing interests.

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Peer review information: Nicole Rusk was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Integrated supplementary information

Supplementary Fig. 1 Constitutive, conditional and inducible gene editing with SiT-Cas12a.

A. Quantification of gene editing efficiencies by constitutive SiT-Cas12a construct. Values represent mean ± s.e.m., n = 3 independent experiments. B. Quantification of gene editing efficiencies by conditional SiT-Cas12a (SiT-Cas12a-[Cond]) construct. Values represent mean ± s.e.m., n = 3 independent experiments. C. Quantification of gene editing efficiencies by inducible SiT-Cas12a (SiT-Cas12a-[Ind]) construct in either Tet-Off or Tet-On configuration. Values represent mean ± s.e.m., n = 3 independent experiments.

Supplementary Fig. 2 Quantification of SiT-Cas12a-induced gene mutations.

A. Quantification of relative Cas12a mRNA expression in either Cas12a, SiT-Cas12a or SiT-rdCas12a expressing cells. Values represent mean ± s.e.m., n = 3 independent experiments. B. Schematic of the CD47 locus and the target position of crRNA used. C. Quantification of SiT-Cas12a gene editing efficiencies using either single (crRNA 1–10), double (crRNAs 1-2, 3-4, 5-6, 7-8, 9-10), or multiple (comprising crRNA from 4 to 9 or from 1 to 10) spacer sequences targeting the CD47 gene. Values represent mean ± s.e.m., n = 3 independent experiments. D. Quantification of indel size distribution generated in CD47 locus using a CRISPR array containing 10 distinct spacer sequences. Similar results for n = 3 independent experiments. E. Quantification of mutation position distribution generated in CD47 locus using a CRISPR array containing 10 distinct spacer sequences. Similar results for n = 3 independent experiments. F. Quantification of position-dependent deletion size generated in CD47 locus using a CRISPR array containing 10 distinct spacer sequences. Similar results for n = 3 independent experiments. G. Quantification of position-dependent insertion size generated in CD47 locus using a CRISPR array containing 10 distinct spacer sequences. Similar results for n = 3 independent experiments.

Supplementary Fig. 3 Generation of SiT-Cas12a-based lentiviral vector.

A. Schematic of a single transcript lentivirus architecture containing both Cas12a and a CRISPR array in different orientations and its effect on lentivirus production. The transcript encodes for: Cas12a (yellow rectangle); Triplex, a tertiary RNA structural motif (small purple rectangle); direct repeat (DR, grey square); spacer (blue square). The (+)-strand RNA contains a recognizable direct repeat prone to Cas12a-mediated cleavage, preventing functional assembly of virions. On the contrary, direct repeats positioned in inverted orientation are not recognized by Cas12a enabling lentivirus production. B. Schematic of a single transcript lentivirus architecture containing both EGFP and mRNA stabilizer sequences in inverted orientation. The transcript encodes for: EGFP (green rectangle); Woodchuck Hepatitis Virus Posttranscriptional Regulatory Element (WPRE) (small blue rectangle); and a polyadenylation sequence (Poly(A), lilac rectangle). C. Validation of single transcript lentivirus architecture in the inverted orientation. Values represent mean ± s.e.m., n = 3 independent experiments. D. Quantification of percentage of EGFP-positive cells by single transcript lentivirus architectures in the inverted orientation. Values represent mean ± s.e.m., n = 3 independent experiments. E. Quantification of gene editing efficiencies by SiT-Cas12a-based lentivirus harbouring 10 distinct spacer sequences targeting the CD47 gene. Values represent mean ± s.e.m., n = 3 independent experiments.

Supplementary Fig. 4 Multiplexed gene editing with SiT-Cas12a.

A. Quantification of residual CD47-positive cells after SiT-Cas12a-mediated gene editing using single or multiple (10) crRNAs targeting the CD47 gene. Similar results for n = 3 independent experiments. B. Quantification of single, double and triple-negative cells after SiT-Cas12a-mediated gene editing using single or multiple (4) crRNAs targeting the CD47, CD97, and CD166 genes. Values represent mean ± s.e.m., n = 3 independent experiments.

Supplementary Fig. 5 Optimization and characterization of a SiT-Cas12a transcriptional repressor.

A. Schematic of Cas12a transcriptional repressors. Cas12a (yellow rectangle) and repression domain fused (RD, blue rectangle) are indicated. B. Quantification of relative RNA expression for 4 distinct genes (EEA1, RAB5, PIK3C3, RAB7A) using ddCas12a fused with either 1 (KRAB1), 2 (KRAB2) or 3 ([Repr]) KRAB domains and in combination with different crRNA array concentrations. Values represent mean ± s.e.m., n = 3 independent experiments. C. Quantification of relative RNA expression for 2 distinct genes (RAB5A, RAB11A) as a function of the distance between the target and the transcription start site (TSS). Values represent mean ± s.e.m., n = 3 independent experiments.

Supplementary Fig. 6 Optimization and characterization of a SiT-Cas12a transcriptional activator.

A. Schematic of Cas12a transcriptional activators. Cas12a (yellow rectangle) and transactivation domains fused (TAD) are indicated. B. Quantification of relative HBB RNA expression using different Cas12a transcriptional activation domain fusion protein. Values represent mean ± s.e.m., n = 3 independent experiments. C. Quantification of relative RNA expression for 4 distinct genes (IL1B, ASCL1, ZFP42, IL1R2) using ddCas12a fusion proteins (VP128, VPR, [Activ]) in combination with different crRNA array concentrations. Values represent mean ± s.e.m., n = 3 independent experiments. D. Quantification of relative RNA expression of 2 distinct genes (HBB, ASCL1) as a function of the distance between the target and the transcription start site (TSS). Values represent mean ± s.e.m., n = 3 independent experiments. E. Quantification of relative RNA expression as a function of basal gene expression for 10 distinct genes (IL1B, ADRB2, HBB, IL1R2, CCR4, ASCL1, ZFP42, CHRM4, CCR10, HTR6) induced by SiT-Cas12a-[Activ] and 20 distinct spacers targeting those 10 genes. Similar results for n = 3 independent experiments.

Supplementary Fig. 7 Orthogonal genome engineering in the SiT-Cas12a context.

A. Small RNA-seq alignment showing mature short crRNAs (15 bp). B. Quantification of mature crRNAs. n = 2 independent experiments. C. Quantification of relative RNA expression of 4 distinct genes (EEA1, RAB5, PIK3C3, RAB7A) using SiT-ddCas12a-[Repr]. Results from 2 distinct CRISPR arrays are represented. Values represent mean ± s.e.m., n = 3 independent experiments. D. Quantification of relative RNA expression of 2 distinct genes (IL1B, ASCL1) using either SiT-ddCas12a-p65-HSF1 or SiT-ddCas12a-[Activ]. Results from 2 distinct CRISPR arrays are represented. Values represent mean ± s.e.m., n = 3 independent experiments. E. Quantification of relative RNA expression of 2 distinct genes (IL1B, ASCL1) using SiT-ddLbCas12a-VPR. Results from 2 distinct CRISPR arrays are represented. Values represent mean ± s.e.m., n = 3 independent experiments.

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