Optimised Methods for Cleavage of Target Sequences

Abstract

The invention provides methods of selecting guide RNA sequences, and the use of such sequences in CRISPR-Cas gene editing of a target sequence. In particular, the invention relates to a method of selecting guide RNA sequences, based on the determined frequencies of editing outcomes, which in one case result in low mosaicism and in another case result in large deletions or knockouts.

Claims

1. A method of selecting one or more guide RNA sequences for use in CRISPR-Cas editing of a nucleic acid sequence, the method comprising: identifying a plurality of guide RNA sequences which target the nucleic acid sequence; determining the frequency of editing outcomes for each of the plurality of guide RNA sequences; and selecting one or more guide RNA sequences for which the frequency of the most abundant editing outcome is determined to be at least 2-fold greater than the frequency of the second most abundant editing outcome.

2. The method according to claim 1, wherein the frequency of editing outcomes for each of the plurality of guide RNA sequences are determined using a computer model.

3. The method according to claim 1 or claim 2, wherein the nucleic acid sequence is a gene sequence and the method further comprises, prior to identifying the plurality of guide RNA sequences, identifying the primary transcript(s) of the gene.

4. The method according to any preceding claim, further comprising selecting the guide RNA sequences which target a region located in the first approximately 50% of a gene.

5. The method according to any preceding claim, further comprising excluding any guide RNA sequences which target orphan exons that are not present in all major transcripts of a gene.

6. The method according to any preceding claim, wherein the method further comprises selecting the guide RNA sequences which are predicted to result in a frameshifting mutation.

7. The method according to any preceding claim, further comprising assigning each guide RNA sequence an off-target score and excluding any guide RNA sequences with a score below a predetermined threshold.

8. The method according to any preceding claim, further comprising assigning each guide RNA sequence an on-target activity score on-target activity score, and excluding any guide RNA sequences with a score below a predetermined threshold.

9. The method according to any preceding claim, further comprising generating a guide RNA molecule comprising a guide RNA sequence selected using the method of any one of claims 1 to 8.

10. The method according to claim 9, wherein the guide RNA molecule is a single guide RNA.

11. The method according to any preceding claim, further comprising using one or more guide RNA molecules, comprising one or more guide RNA sequences selected, to edit target sequences in a test population of cells, and determining the editing outcomes associated with each guide RNA sequence in the cells.

12. The method according to claim 11 further comprising selecting from the one or more guide RNA molecules those guide RNA molecules that most consistently cause the predicted most abundant outcome in cells of the test population.

13. A method of selecting a pair of guide RNA sequences for use in CRISPR-Cas editing of a nucleic acid sequence, the method comprising: identifying a plurality of guide RNA sequences which target the 5′ and 3′ flanks surrounding the nucleic acid sequence; determining the frequency of editing outcomes for each of the plurality of guide RNA sequences; and selecting a pair of guide RNA sequences comprising a first guide RNA which targets the 5′ flank and a second guide RNA which targets the 3′ flank, wherein for each guide RNA the frequency of the most abundant editing outcome is determined to be less than 4 fold greater than the frequency of the second most abundant editing outcome.

14. A method according to claim 13, further comprising any of the features of claims 2-12.

15. A method for editing a nucleic acid sequence in an organism, a cell or a population of cells, or in a cell-free expression system, the method comprising exposing double-stranded (dsDNA) comprising the nucleic acid sequence to a Cas endonuclease and a guide RNA molecule which is capable of directing the Cas endonuclease to the target sequence within the nucleic acid sequence, wherein the guide RNA molecule comprises a guide RNA sequence which, when used in CRISPR-Cas editing, results in (or is predicted to result in, e.g. by a computer model), a major editing outcome having a frequency which is at least 2-fold greater than the second most abundant editing outcome.

16. The method according to claim 13, wherein the guide RNA molecule comprises a guide RNA sequence selected according to a method of any one of claims 1 to 12.

17. The method according to claim 13 or claim 14, further comprising introducing the guide RNA molecule and the DNA endonuclease into the cell or cells.

18. The method according to any one of claims 1 to 15, wherein the Cas endonuclease cleaves a target sequence within the nucleic acid sequence so as to produce a double strand break.

19. The method according to claim 16, wherein the Cas endonuclease is a Cas9 endonuclease.

20. The method according to any one of claims 13 to 17, wherein the organism, cell or population of cells is eukaryotic.

21. The method according to claim 18, wherein the organism, cell or population of cells is from an animal, fungus or plant, preferably the organism, cell or population of cells is mammalian.

22. The method according to claim 19, wherein the cell is a zygote or the population of cells form a zygote.

23. The method according to claim 20, wherein the method further comprises transferring the embryo into a recipient female animal for gestation, optionally wherein the embryo is cultured to a later stage of development prior to transfer.

24. The method according to any one of claims 13 to 21, wherein the method is for generating a non-mosaic transgenic animal.

25. The method according to claim 22, wherein the animal is a rodent, a rabbit, sheep, goat, horse, cow, pig, dog, cat, chicken, or a primate.

26. A method for editing a nucleic acid sequence in an organism, a cell or a population of cells, or in a cell-free expression system, the method comprising exposing double-stranded (dsDNA) comprising the nucleic acid sequence to a Cas endonuclease and a pair of guide RNA molecules which are capable of directing the Cas endonuclease to target the 5′ and 3′ flanks surrounding the nucleic acid sequence, wherein the pair of guide RNA molecules comprises a first guide RNA and a second guide RNA which, when used in CRISPR-Cas editing, result in (or are predicted to result in, e.g. by a computer model), a major editing outcome having a frequency which is less than 4 fold greater than the frequency of the second most abundant editing outcome.

27. A method according to claim 26 further comprising any of the features of claims 16-25.

28. Cells, cell populations and non-human organisms obtained by the methods of any one of claims 15-27.

Description

[0141] Embodiments of the invention will now be described by way of example and with reference to the accompanying figures in which:

[0142] FIG. 1A is a graph showing microhomology strength plotted as a function of precision in double strand break (dsb) repair for the Vsig4 gene. Precision can be understood as the predictability of the repair outcome;

[0143] FIG. 1B is a graph showing microhomology strength plotted against most frequent genotype (M.F.gt) for the Vsig4 gene. High microhomology reduces the spectrum and complexity of repair results, giving rise to more consistent outcomes;

[0144] FIG. 2A is a graph showing the predicted editing outcomes of Vsig4 CRISPR design versus the frequency of each edit, a 7 bp deletion has by far the highest frequency;

[0145] FIG. 2B(A) is a chart showing the results of a representative example of creating a CRISPR murine model generated without attention to microhomology at the target site. Half of the pups born were unedited and half were mosaic;

[0146] FIG. 2B(B) is a chart showing the outcome of creation of a CRISPR murine model when knowledge of microhomology was applied. Less than half of mice born were unedited or mosaic. The majority (21/38) were non-mosaic and experiment-ready;

[0147] FIG. 2C shows the results of DNA sequence analysis of individual tissues in three representative genetically modified mice. The same insertions and deletions (7 bp deletion, 2 bp insertion, 1 bp deletion) were observed throughout different tissues that originated from disparate developmental lineages;

[0148] FIG. 2D shows representative data of direct germline transmission of edits. Oocytes from an edited female were fertilized by a wild type (WT) male and cultured to the blastocyst stage before lysis and sequence analysis. Blastocysts showed inheritance of the genetic modification in every case. As expected, inheritance followed a pattern characteristic of a sex-linked gene;

[0149] FIG. 3 depicts the results from breeding a trio of mice comprised of a wild-type male and two non-mosaic females with Vsig4 modifications, to assess germline transmission. The resultant pups all contained edits in a pattern consistent with an X-linked gene. All males showed complete editing while the females were heterozygous for the gene edit. Importantly, there were no entirely wild type mice or unexpected gene edits in the litter, indicating complete transmissibility of genome modification;

[0150] FIG. 4 shows that the method of the invention performed with respect to Vsig4 is repeatable and generalisable to other genes. The pie charts show aggregated data from performing the method of the invention exploiting local DNA sequence in genes Vsig4, Ccr1, and Prdm14, compared with a chart showing the data for traditional methods that ignore local DNA sequence features in genes Hmga1, HMga1-ps, and Hmga2;

[0151] FIG. 5 shows the functional analysis of a Prdm14 knock out for which there is a phenotypic effect (A) Testes and ovarian tissue from genotyped Prdm14−/− mice were excised and weighed. Statistical analyses were performed using a Students T-test, yielding P=9.4×10-9 (Testicle) and P=2.2×10-4 (Ovary). (B) Visualisation of testicular tissue. (C) Microscopic observation of spermatids (red asterisk) in wt but not in Prdm14−/− males;

[0152] FIG. 6 shows the ability to use the method of the invention to enhance large deletions by analysing DNA microhomology, (A) Homozygous large deletions can be enhanced by targeting regions of low local microhomology, giving rise to non-mosaic animals. (B) Preliminary data using the gene Ddx3y shows that regions of low microhomology more frequently result in biallelic large deletions compared to targeting regions of high microhomology, (C) and (D) Pie charts showing the raw data for performing the same methodology in the gene Gata1. In (C) from left to right: Pie chart of overall mosaicism for Gata1 model, ‘non-mosaic’ is when a single editing outcome was present for both editing sites. These editing outcomes include indels and the desired deletion; Pie chart for mosaicism for Gata1 model when only looking at a low microhomology guide RNA pair. These editing outcomes include indels and the desired deletion; Pie chart for mosaicism for Gata1 model when only looking at a high microhomology guide RNA pair. These editing outcomes include indels and the desired deletion. In (D) from left to right: Pie chart of large deletions present in all Gata1 edited mice. Large deletions, indels, and unedited mice are compared (Not indicative of mosaicism); Pie chart of large deletions present in Gata1 mice generated using a low microhomology guide RNA pair; Pie chart of large deletions present in Gata1 mice generated using a high microhomology guide RNA pair;

[0153] FIG. 7 shows efficient Cas9 editing of primary human T cells without loss of viability. HEK293T and primary human T cells were edited with guides designed against CTLA4 using the method of the invention (A) Editing efficiency of increasing amounts of Cas9:sgRNA targeting CTLA4 in HEK293T cells and primary human T cells (n=3, technical replicates, error bars=SD, ns=nonsignificant). Efficiency was measured by determining the proportion of cells that have indels that led to a frameshift in the protein-coding region compared to the unedited control. (B) T cell viability recorded 3 days post edit. The % viability was calculated as the percentage of live cells/mL to total cells/m L;

[0154] FIG. 8 shows (A) Sequencing traces of healthy donor T cells edited with an sgRNA targeting CTLA4. The sgRNA target sequence is underlined in black. The contribution a particular edit within the pool of edited cells is shown. (B) The distribution of editing outcomes within the pool is seen. Greater than 70% of the edits are pure indicating that the level of mosaicism has been reduced to below 30%;

[0155] FIG. 9 shows (A) Comparison of editing efficiency between gRNAs designed using the method of the invention (Zygosity) and Sanger designed (benchmark) gRNAs to CTLA4, PD-1, LAG-3, PTPN2, DGK & HAVCR2 (also known as TIM3) in primary T-Cells. gRNAs designed according to the invention were more efficient as editing primary T-cells across 6 genes (P<0.005) (B) Comparison of knockout efficiency between gRNAs designed using the method of the invention (Zygosity) and Sanger designed (benchmark) gRNAs to CTLA4, PD-1, LAG-3, PTPN2, DGK & HAVCR2 in primary T-Cells. gRNAs designed using the method of the invention knocked out a higher portion of genes in primary T-cells when compared to Sanger designed guides (P<0.006) (C) Comparison of the extent of mosaicism between gRNAs designed using the method of the invention (Zygosity) and Sanger designed (benchmark) gRNAs to CTLA4, PD-1, LAG-3, PTPN2, DGK & HAVCR2 in primary T-Cells. gRNAs designed using the method of the invention resulted in decreased mosaicism (indicated by increased Purity (%)) in primary T-cells when compared to Sanger designed guides (P<0.006);

[0156] FIG. 10 shows the correlation between various computationally derived metrics describing guide performance (on-target, predicted frameshift frequency) with editing outcome derived from Sanger sequencing of edits. The data show that the best predictor of gene knockout efficiency is the frameshift metric as used in the present invention;

[0157] CRISPR editing using the guide RNA sequences selected in accordance with the methods of the invention may be carried out using the following protocols:

EXAMPLE PROTOCOL FOR EDITING EMBRYOS

[0158] 1. Order guide RNA sequences as synthetic modified single guide RNAs (sgRNAs) (e.g. from Merck);
2. Resuspend sgRNAs in water;
3. Have prepared in vitro fertilized mouse zygotes ready to electroporate at 3 hours post-insemination;
4. Complex 4.5 μg of sgRNA with 20 μg Cas9 protein (TrueCut V2, Invitrogen) in 60 μL Opti-MEM (Thermofisher) at room temperature for 20 minutes;
5. Transfer 50 μL of the complex solution to the CUY520P5 electrode of a NEPA21 electroporator;
6. Adjust the volume until the impedance is within the range of 0.48-0.52 kW;
7. Move Opti-MEM washed zygotes to the electroporation chamber;
8. Check impedance again;
9. Electroporate using parameters outlined in Table 1;
10. Remove zygotes from the electroporation chamber and place in KSOM solution for 30 minutes;
11. Wash zygotes with KSOM solution three times;
12. Return zygotes to fresh KSOM solution and culture until at least the two-cell stage, in some cases to the blastocyst stage;
13. Transfer to pseudo-pregnant recipient female mice.

TABLE-US-00001 TABLE 1 List of parameters for NEPA21 electroporation Set parameters Poring pulse Transfer pulse D. D. Length Interval Rate Length Interval Rate V (ms) (ms) No. (%) Polarity V (ms) (ms) No. (%) Polarity 200 2 50 4 10 + 20 50 50 5 40 +/−

EXAMPLE PROTOCOL FOR EDITING CELLS

[0159] 1. Order guide RNA sequences as synthetic modified single guide RNAs (sgRNAs) (e.g. from Merck);
2. Resuspend sgRNAs in water;
3. Complex 80 pmol of sgRNA and 4 ug of Cas9 protein (TrueCut V2, Invitrogen);
4. Harvest cells (˜400,000), pellet, wash with 1×PBS, and resuspend in 20 μL of appropriate electroporation buffer.
a. Cell count and volumes are appropriate for use with Lonza's 16-well cassette. Scale up and follow kit procedure when using different electroporation vessel;
b. Use Amaxa 4D nucleofector and purchase electroporation vessels and buffers through Lonza. Different buffers are optimized for different use with cell types;
c. Once cells have been mixed with electroporation buffer, complete electroporation as soon as possible;
5. Mix cells with complexed sgRNA and Cas9 protein and transfer to electroporation vessel;
6. Electroporate according to cell type specific program recommended by Lonza;
7. Add 80 μL of cell media to electroporation cassette and place in incubator for 10 minutes for cells to recover;
8. Put cells into 12 well plate that contains 1 mL of pre-warmed media;
9. Culture as desired.

EXAMPLE 1

[0160] Once thought random, the repair of the double stranded DNA break (DSB) induced by Cas9 cleavage of its target sequence has been recently shown to be non-random. Short areas of repetitive DNA sequence (microhomology) around the Cas9 cut site play a major role in how the DSB is repaired. As show in FIG. 1, there is a direct relationship between local microhomology and non-random repair, or precision, of a target sequence (FIG. 1A). The direct relationship allows us to understand and predict editing outcome de novo. DNA sequences with low microhomology repair to give a wide spectrum of editing outcomes in a manner that is difficult to predict. Higher microhomology correlates with a decreased spectrum of repair outcomes (FIG. 1B). Further, editing events may evolve over time through re-cutting of the target sequence and lead to mosaicism. The present inventors hypothesised that the relationship between double strand break repair and microhomology may be exploited in order to bias editing outcomes and reduce or eliminate mosaicism.

[0161] In embryos, by leveraging the linear relationship between microhomology and both precision and consistency, it was surprisingly found that it is possible to constrain the spectrum of edits to one major outcome. Restricting the editing spectrum nullifies re-cutting based mosaicism by biasing editing to produce a single genotype. The combination of these two approaches allows us to produce non-mosaic, experiment-ready mice in one step.

Materials and Methods

CRISPR Guide Design

[0162] SpCas9 single guide RNAs for Vsig4 (ENSMUSG00000044206) were selected in accordance with the following protocol:

1. The primary transcript was identified using a publicly available genomics tool, enseumble.org;
2. All possible guide RNAs that target the coding sequence of Vsig4 were identified using the publicly available software FOREcasT, InDelphi or Lindel. Other suitable software includes UCSC Genome Browser, Deskgen.com, and CRISPOR;
3. Guide RNA sequences which targeted the second 50% of the gene were filtered out;
4. Guide RNA sequences were analysed using Lindel using the metric “Most Frequent Genotype (MF gt)” and the fold change between the most abundant editing outcome and the second most abundant editing outcome was calculated for each guide RNA sequence. The top 10 ranking guide sequences were selected;
5. Guide RNA sequences were ranked using Lindel using the metric “frameshift %”. Guides for which the major editing outcome was not a multiple of three were selected;
6. Guide RNA sequences were assigned an off-target score using the webtool Deskgen. Other suitable tools include UCSC Genome Browser and CRISPOR. The algorithm used by Deskgen and most other tools is that of Hsu et al., (Nature Biotechnology volume 31, pages 827-832(2013)). In the webtool Deskgen the scores range from 0 (many off targets) to 100 (no off targets). Guides with a score of less than 70 were filtered out;
7. Guide RNA sequences with undesirable on-target profiles were filtered out using Deskgen. which assigns a score of 0-100 based on the metric described by Doench et al., (Nature Biotechnology volume 34, pages 184-191(2016)). Guides having scores of more than 35 (which have been found to work well in vitro and in vivo) were selected;
8. The top three ranked guide RNA sequences were tested by carrying out CRISPR gene editing in mouse ES cells. Synthetic phosphorothioate-modified sgRNAs for Vsig4 were purchased from Merck (UK). Following editing, genomic DNA was then extracted and sequenced across the edited region using standard techniques to determine the editing percentages and distribution of edits. The information was analysed using the ICE v2 CRISPR Analysis Tool (Synthego).
9. The guide RNA sequence which was found to result in the least mosaicism was then used to generate transgenic mice.

Super-Ovulation

[0163] Female C57Bl6/J (Charles River, UK) at 10-14 weeks old were super-ovulated by intraperitoneal (ip) administration of 7.5 IU of Pregnant Mare Serum Gonadotropin (National Veterinary Services, 859448), followed by ip injection of 7.5 IU of Human Chorionic Gonadotropin (hCG) (National Veterinary Services, 804745) 48 hours later. Oocytes were harvested from the super-ovulated females 14-16 hours post-hCG injection.

In Vitro Fertilization (IVF)

[0164] Human Tubal Fluid (HTF) medium was prepared in water using the reagents listed in Table 2, and sterile filtered (0.2 μm).

TABLE-US-00002 TABLE 2 HTF medium components Final Merck Catalogue Reagent Concentration Number Sodium Chloride 101.6 mM S5886 Potassium Chloride 4.69 mM P5405 Magnesium Sulphate Heptahydrate 0.2 mM M7774 Monopotassium Phosphate 0.37 mM P5655 Calcium Chloride Dihydrate 2.04 mM C7902 Sodium bicarbonate 25 mM S5761 Glucose 2.78 mM G6152 Sodium pyruvate 0.33 mM P4562 Sodium lactate 60% syrup 21.4 mM L7900 Penicillin-G 0.075 g/L P4687 Streptomycin Sulphate 0.05 g/L S1277 Phenol Red (5%) 0.2 mL P0290 Bovine Serum Albumin (Embryo 4 g/L Tested)

[0165] 10 μL of cryopreserved sperm was added to 490 μL HTF medium containing 1.25 mM reduced L-glutathione (rGSH) (Merck, G-4251) in a 4 well tissue culture dish and pre-incubated for 45 min. Oocytes from super-ovulated females were harvested and transferred into the media containing the thawed sperm and incubated for 2 hours. Zygotes visibly showing a second polar body were collected and washed three times in pre-prepared KSOM solution (KSOM medium (Merck Millipore, MR-107-D) and 3 mg/mL bovine serum albumin (BSA) (Sigma-Aldrich, A-3311)). Zygotes were cultured in 1 mL KSOM solution until electroporation.

Embryo Electroporation

[0166] sgRNA target sequence as shown below (5′-3′):

TABLE-US-00003 Vsig4 guide: (SEQ ID No. 1) ATGATCCCCTGAGAGGCTAC

[0167] 4.5 ug of sgRNA was complexed with 20 μg TrueCut Cas9 protein v2 (Invitrogen) in 60 μL Opti-MEM (ThermoFisher) at room temperature for 20 min. 50 μL of this solution was transferred to the CUY520P5 electrode of a NEPA21 electroporator (Nepa Gene) and the volume was adjusted until the impedance was within range of 0.48-0.52 kΩ Opti-MEM washed zygotes were added to the electroporation chamber and the impedance was assessed again to ensure it fell within the range. The parameters for electroporation using the NEPA21 are shown in Table 1, above.

[0168] Zygotes were removed from the electroporation chamber and placed into KSOM solution for 30 min. The zygotes were washed with KSOM solution three times, returned to fresh KSOM solution and cultured until they reached the two-cell stage.

Embryo Transfer

[0169] Female CD1 mice (Charles River, UK) were mated with vasectomised males. Two-cell stage embryos were surgically transferred into the oviduct of pseudo-pregnant recipient females, 10 embryos per oviduct, 20 embryos per female.

Genotyping and Deconvolution of Editing Outcome

[0170] Zygotes were cultured in KSOM solution to blastocyst stage where the zona pellucida was removed using Tyrode's Solution (Sigma-Aldrich, T-1788) and the samples lysed in extraction reagent (Quanta, 84158). DNA was extracted from tissue (ear biopsy, lung, heart, liver, or testicle) using E.Z.N.A. Tissue DNA Kit (Omega, D3396-01). PCR amplification of the region surrounding Vsig4 sgRNA target sites was performed using the following primers (5′-3′):

TABLE-US-00004 Vsig4-F: (SEQ ID No. 2) CCTAACTCTCACATAATATT Vsig4-R: (SEQ ID No. 3) ATTACAGAGAACCTATGTAC

[0171] PCR amplification from tissue samples was performed using Q5 High Fidelity DNA polymerase and master mix (NEB). Vsig4 cycling conditions: 98° C. for 30 seconds, 35 cycles of (98° C. for 10 seconds, 50° C. for 30 seconds, and 72° C. for 45 seconds), and 72° C. for 5 min.

[0172] PCR amplification from blastocyst samples was performed using Phusion polymerase and HF buffer (NEB). Vsig4 cycling conditions: 98° C. for 3 min, 35 cycles of (98° C. for 30 seconds, 50° C. for 30 seconds, and 72° C. for 45 seconds), and 72° C. for 5 minutes.

[0173] PCR samples were cleaned up using the QIAquick PCR Purification kit (Qiagen) and Sanger sequenced (Eurofins Genomics). Sequence deconvolution of the sanger traces were determined using the Inference of CRISPR Edits (ICE) tool (Sythego).

Results

[0174] By constraining CRISPR activity to regions of high microhomology within the X-linked gene, V-set and immunoglobulin containing 4 (Vsig4), it was demonstrated that mosaicism can be eliminated. Single guide RNA (sgRNA) was pre-complexed with Streptococcus pyogenes Cas9 (SpCas9) protein, and the complex was electroporated into in vitro fertilized zygotes at three hours post insemination. Zygotes were transferred into pseudopregnant female recipient mice for live birth. Pups were genotyped from ear biopsies by PCR amplification around the targeted cut site, Sanger sequencing, and deconvolution to identify mosaicism. Over half (21/38, 55%) of pups were non-mosaic. Comparatively, other studies conducted in the lab have resulted in only mosaic or non-edited animals (FIG. 2A). The extent of editing in disparate tissues was determined by extracting DNA from organs that derived from different developmental lineages. Tissue was extracted from the liver, epidermis, heart, and testicles which originate from the endoderm, ectoderm, mesoderm, and germ cells respectively. The entire organ was digested and the DNA was extracted and analysed. All animals analysed (N=7) had identical editing outcomes throughout the tissues, indicating that mosaicism was efficiently eradicated across all developmental linages (FIG. 2B(B)).

[0175] Creation of non-mosaic founder animals who transmit their induced genetic modifications to the next generation is critical to rapidly create a breeding. To test this, oocytes from a non-mosaic female that contained a 7 base pair (bp) deletion were in vitro fertilized with sperm from a wild type male and the resultant zygotes were cultured until the blastocyst stage. Seven blastocysts were individually collected, lysed, and analysed for presence of the genetic modification. Two of the seven blastocysts had a genotype of 50% wild type and 50% 7 bp deletion, while the remaining five contained only the 7 bp deletion (FIG. 2C). The inheritance pattern is characteristic of a sex-linked gene, like Vsig4. Germline transmission was further characterized by setting up a breeding trio comprised of a wild type male and two edited females (FIG. 3). All examined animals were able to pass their genetic modification onto the next generation.

EXAMPLE 2

[0176] The same methodology as used in the Vsig4 gene described above was repeated in other genes: Ccr1 and Prdm14. SpCas9 single guide RNAs for Ccr1 and Prdm14 were designed as above. By extending the method of the invention into other models, it is demonstrated that the methodology is generalisable. In each instance where the method was tested, non-mosaic, experimental cohorts were produced.

[0177] Importantly, the Ccr1 experiment was performed on a complex genetic background (Trp53R172H/Pdx1-Cre), demonstrating that the approach works on pre-established disease models, not only in wild type genetic contexts. Prdm14 plays a key role in the specification of the primordial germ cell (PGC); mutation results in sterility. Thus, Prdm14−/− lines cannot be established and bred, however a cohort of non-mosaic Prdm14−/− lines can be produced on demand using the method of the invention. Results for these experiments are shown in FIG. 4. Results for the Prdm14−/− with respect to phenotype are shown in FIG. 5.

TABLE-US-00005 Ccr1 sgRNA: (SEQ ID NO 4) CTCTCTGGGTTTTATTACCT Prdm14 sgRNA: (SEQ ID NO 5) GGTCAATGCCAGCGAAGTGA

TABLE-US-00006 Gene Primer-Forward Primer-Reverse Ccr1 ATGGAGATTTCAG CCTTCCTTCTCAC ATTTCACAGAA TGGGTCTT (SEQ ID NO 6) (SEQ ID NO 7) Prdm TAAATCCTCTCT TTTCCTGTAGCA 14 AGGGACTG TGCTTTTA (SEQ ID NO 8) (SEQ ID NO 9)

EXAMPLE 3

[0178] Furthermore, the inventors have investigated the use of the method of the invention not only to predict which guide RNA to use to enhance a single editing outcome but also to predict which pairs of guide RNAs should be used to achieve a large deletion.

[0179] It may be desirable to generate models that harbour large genomic deletions, either to explore functions of the deleted region, or as an alternative approach to generate a gene knockout. The inventors believe that DNA regions which repair into many editing outcomes (mosaic) incur a delay during the repair process as the cell searches for a compatible (local) sequence to repair the insult when compared to DNA regions which repair into a single, dominant editing outcome (non-mosaic). By using two guide RNAs flanking a desired genomic region that exploit this proposed repair delay it should enhance the efficiency of large deletion events.

[0180] The Y-linked spermatogenesis regulator, Ddx3y, was targeted for knockout. CRISPR designs were constrained to regions surrounding a critical exon of Ddx3y, such that removal of the exon would move the coding sequence out of frame. Pairs of guide RNAs were designed that target regions of either high or low microhomology that were predicted to result in few or many editing outcomes respectively using the guide design protocol above (FIG. 6A). To select the gRNAs which target regions of high microhomology, the same method as above was used. To select guide RNAs which target regions of low microhomology, step 4 in the design method above comprised selecting the bottom 10 gRNAs, step 5 is omitted, step 8 comprised selecting the bottom 3 gRNAs, and the final step comprised selecting the gRNA which was found to result in the highest mosaicism. This was done for both 5′ flank and the 3′ flank regions surrounding the DNA sequence to be deleted.

[0181] Zygotes were edited in vitro as explained above, using both a gRNA that targets the 3′ flank and a gRNA that targets the 5′ flank of the intervening DNA sequence to be deleted, and analysed by PCR as explained above and sequencing individual blastocysts. The data show that both conditions generated deletion events, however more were generated in the low microhomology group (63% vs 28%) (FIG. 6B). These data show that low microhomology flanking pairs of guide RNAs enhance the excision of intervening DNA sequence.

[0182] The concept of using pairs of gRNAs which target regions of low microhomology to enhance deletions was further investigated in the context of the gene Gata1. FIGS. 6C and 6D show the results. FIG. 6D in particular shows that using pairs of gRNAs targeted to regions of low microhomology generates a greater proportion of large deletions than targeting pairs of gRNAs to high microhomology regions.

TABLE-US-00007 DDX3y_5′_HMH sgRNA: (SEQ ID NO 10) TCCAGTGTCTATCACTGTAC DDX3y_3′_HMH sgRNA: (SEQ ID NO 11) TAGTAAATTCTTAGGTAAGT DDX3y_5′_LMH sgRNA: (SEQ ID NO 12) CCCAGTACAGTGATAGACAC DDX3y_3′_LMH sgRNA: (SEQ ID NO 13) AATCTTAACTTAGCAAAGTC Gata1_5′_HMH sgRNA: (SEQ ID NO 14) GCCGCAGTAACAGGCTGTCT Gata1_3′_HMH sgRNA: (SEQ ID NO 15) ACGCCAGCTCTGGCCTGCTC Gata1_5′_LMH sgRNA: (SEQ ID NO 16) CTGTCTTGGGGCTGGGGGGC Gata1_3′_LMH sgRNA: (SEQ ID NO 17) CCAGAGCTGGCGTAAGCCCC

TABLE-US-00008 Gene Primer-Forward Primer-Reverse Gata1 TGTCCCTGCTGCT GTTGGACCTGTAT TTCTGTC GCGCGTG (SEQ ID NO 18) (SEQ ID NO 19) DDX3y TACCAAGCCACA AATCCGGGCCACA TTTGTAGCTC GCTTCTTGT (SEQ ID CC (SEQ ID NO 20) NO 21)

EXAMPLE 4

[0183] CRISPR-Cas9 editing of CAR-T cells suffers from generalised inefficiency/toxicity and mosaicism. In this context, both these factors serve to limit the therapeutic potential and safety profile of these next generation therapies. The method of the invention was further used to generate a SpCas9 single guide RNA to an intron in CTLA4 and tested in HEK293T and in primary human T cells.

TABLE-US-00009 CTLA4_intron sgRNA: (SEQ ID NO 22) TGAGGATCTGGATAACTAAG

TABLE-US-00010 Gene Primer-Forward Primer-Reverse CTLA4_intr CTCTGTATTCCAGGGCC CAGTGAAATGGCTT on AGC (SEQ ID NO 23) TGCTCA (SEQ ID NO 24)

Method to Stimulate PBMC Cells

[0184] Anti-CD3 antibody (Biolegend) was diluted to a final concentration of 5 μg/mL in sterile PBS and 50 μL per well was added to 3×96 well plates. Incubate plates at 37° C. for 2 hours. Wash each plate 3× with 200 μL PBS. Revive PBMC cells (Cambridge Bioscience) in 7 mL of warmed media (RPMI glutamax 21875-034, 10% HI-FBS, 1.75 μL BME). Centrifuge 3×5 min at 425 g. Resuspend final pellet in 10 mL media and count cells. Create cell suspension that contains cells at a concentration of 60,000 cells/200 μL, anti-CD28 antibody (Biolegend) to a final concentration of 5 μg/mL, and IL2 (Biolegend) to a final concentration of 20 ng/mL. Dispense cell suspension into prepared 96 well plates—60,000 cells/well and 200 μL/well. Leave in incubator 72 hours.

Method for Electroporation of Stimulated Cells

[0185] Count cells and record viability. Only proceed with electroporation when the viability is over 65%. Complex 3 μg of TrueCut Cas9 protein v2 (Invitrogen) with 60 pmol of synthetic guide RNA (Synthego) at room temperature for 20 minutes. Pellet cells, wash with PBS, and pellet again. Resuspend cells in P3+ buffer (Lonza) at 200,000 cells per sample, mix with the Cas9/guide RNA complex and add 20 μL of this to the electroporation cuvette. Electroporate using program EO 115, incubate at 37° C. for 10 minutes and transfer to pre-warmed 24 well plates that contain a solution of 1 mL media with 20 ng/mL IL2 per well. Leave cells for 72 hours in the incubator before harvesting for analysis.

[0186] The inventors found that the generated guide RNA was highly efficient at gene editing over a broad concentration range, and across two cell types. The generated guide RNA had 90% gene editing efficiency of primary, patient-derived T cells levels comparable to the ubiquitous HEK293T cancer cell line (FIG. 7A); and cellular viability was maintained across the concentration range (FIG. 7B). Furthermore, the guide RNA also reduced mosaicism in primary T-cells as the vast majority of editing (70%) was a +1 bp insertion, the level of mosaicism was reduced to below 30% (FIGS. 8A and 8B).

[0187] Further guide RNAs were designed using the method of the invention for the genes CTLA4 (as above), PD-1(PDCD1), LAG-3, PTPN2, DGK & HAVCR2 in primary T-Cells, and their editing efficiency, knockout efficiency and purity were compared to gRNAs designed by a prior method; the Sanger (FIGS. 9A, B and C) method described in Tzelepis et al. Cell Reports, Volume 17, Issue 4, 18 Oct. 2016. The gRNAs designed by the method of the invention were more effective.

TABLE-US-00011 TABLE of sgRNAs designed using either the method of the invention or the prior Sanger method: sgRNAs designed sgRNAs using the designed method of SEQ using a SEQ the ID prior ID Gene invention NO Gene method NO CTLA4_1 CATAAAGCC 25 CTLA4_6 TCCATGCTAG 55 ATGGCTTGC CAATGCACG CT CTLA4_2 TGAACCTGG 26 CTLA4_7 CACAAAGCTG 56 CTACCAGGA GCGATGCCT CC CTLA4_3 CTCAGCTGA 27 CTLA4_8 CTGCCGAAGC 57 ACCTGGCTA ACTGTCACC CC CTLA4_4 AGGGCCAG 28 CTLA4_9 TGTGCGGCAA 58 GTCCTGGTA CCTACATGA GCC CTLA4_5 CCTTGGATTT 29 CTLA4_10 TTCACTTGATT 59 CAGCGGCAC TCCACTGG A PTPN2_11 CTCTTCTATG 30 PTPN2_16 GTGGATCACC 60 TCAACTAAA GCAGGCCCA C PTPN2_12 CATGCCCAC 31 PTPN2_17 GGGACTCCAA 61 CACCATCGA AATCTGGCC GC PTPN2_13 CTCTTCGAA 32 PTPN2_18 CGCATTGTGG 62 CTCCCGCTC AGAAAGAAT GA PTPN2_14 GTTCAGCAT 33 PTPN2_19 AGTTTAGTTG 63 GACAACTGC ACATAGAAG TT PTPN2_15 TTGACATAG 34 PTPN2_20 CATGACTATC 64 AAGAGGCAC CTCATAGAG AA DGKB_21 TCTCTGGAG 35 DGKB_26 ACATAGGTCT 65 GAATGGATT TGATGCAAG CA DGKB_22 CTGGAGGAA 36 DGKB_27 TCGAGCCACA 66 TGGATTCAA CAGCGCTCA GG DGKB_23 GGTAAAATA 37 DGKB_28 GAACATGCTG 67 TGGTCCTTC ATTGGCGTG AA DGKB_24 ATGTGACTG 38 DGKB_29 CGTCCCATGC 68 TGGACCTTT AGAACGTGA GA DGKB_25 GGCACTTAT 39 DGKB_30 TCGCCTTTAT 69 CACACTTGG GACACGGAT TT Lag3_31 CGCCGGCGA 40 Lag3_36 GCTCATCCAG 70 GTACCGCGC CTGGACGCG CG Lag3_32 GGCTGAGGT 41 Lag3_37 GTCCCGCCCC 71 CCCGGTGGT ACATACTCG GT Lag3_33 AGGAGGGC 42 Lag3_38 TGCATTGGTT 72 GCCGCCGGG CCGGAACCG TGA Lag3_34 CGCTATGGC 43 Lag3_39 ATGGGGGGA 73 TGCGCCCAG CTCCCGGACA CC Lag3_35 CCCTGAGGT 44 Lag3_40 GAGGAAGCTT 74 GCACCGCGG TCCGCTAAG CG HAVCR2_41 AATGTGACT 45 HAVCR2_46 CTCTCTGCCG 75 CTAGCAGAC AGTCGGTGC AG HAVCR2_42 TGTGTTTGA 46 HAVCR2_47 ATGTGACTCT 76 ATGTGGCAA AGCAGACAG CG HAVCR2_43 TCTCTGCCG 47 HAVCR2_48 TAAATGGGGA 77 AGTCGGTGC TTTCCGCAA AG HAVCR2_44 GGTGTAGAA 48 HAVCR2_49 GTGTTTGAAT 78 GCAGGGCA GTGGCAACG GAT HAVCR2_45 AGAAGTGGA 49 HAVCR2_50 ACGGGCACG 79 ATACAGAGC AGGTTCCCTG GG PDCD1_51 AGGGTTTGGA 50 PDCD1_56 GACGTTACCT 80 ACTGGCCGGC CGTGCGGCC PDCD1_52 GGTGCTGCT 51 PDCD1_57 CTCTCTTTGAT 81 AGTCTGGGT CTGCGCCT CC PDCD1_53 GCTTGTCCG 52 PDCD1_58 GTTGGGCAGT 82 TCTGGTTGC TGTGTGACA TG PDCD1_54 AGCTTGTCC 53 PDCD1_59 AGCTTGTCCG 83 GTCTGGTTG TCTGGTTGC CT PDCD1_55 GACGTTACC 54 PDCDl_60 CCTTCGGTCA 84 TCGTGCGGC CCACGAGCA CC

TABLE-US-00012 TABLE of primers used for each gene: SEQ SEQ Primer- ID Primer- ID Gene Forward NO Reverse NO CTLA4: AAAGTCCTTGAT 85 AGGCATTC 86 1, 2, TCTGTGTGGGT TTCCCACA 3, 4, 5 ATTTCCC CTLA4: TAGAAGGCAGA 87 GGTTAGCACT 88 6, 7, 8, 9, AGGGCTTGC CCAGAGCGAG 10 PTPN2: 20 TGGCTGACCAT 89 ATATCCAAAGC 90 AGATACCTCCA CACTGTCAAAG C PTPN2: GTCACAATGGC 91 AGAAGCATAAG 92 11, 15, 19 TAATGTGCTACA CAGCACTCTGT A PTPN2: GGTTCCTACCCA 93 TCTTGGAGATG 94 14, 18 AGTTTGTCTCT AAAGGTCTGCA A PTPN2: GGGATTGTCAG 95 AGCTACCAGGA 96 16, 17 AAAACAAATGG AGAAAAACACC AAA T DGKB: GGTTGACCACC 97 TGGAGAGCCTC 98 21, 22 AATTTTCCCTT TTGCTTTAGAT AT DGKB: CATGACGATGG 99 GCTGAAGACTT 100 28, 29 CTTGGGGTA GGAAAATGTCC TT DGKB: 25, CACCAAGCCATT 101 CACGTCTTC 102 26, 27 TGGCAGTC AGTGTGGGT GA DGKB: GTCACAGAAGC 103 GCATCTCCAGC 104 23, 24 TGCTAGATGGT AAAATTGCCC HAVCR2: AGCGAATCATC 105 TGGGGCCTGTT 106 41, 42, 44,  CTCCAAACAG AAACTTTAGGT 45, 47, 48, 49, 50 HAVCR2: TTGTGTGGCTGT 107 CCAGTCCAGGG 108 43, 46 TAGTTCCGC TCAGTCAGAA DGKB: 30 GAACCCCCTAA 109 TTTTAGCTGC 110 CAGAGACCC CATAGGGTGG TC PTPN2: CAGCGCTCTCCC 111 GCCCCGAGCGA 112 12, 13 CGGATCG GAGGCTAGA LAG3: 32 GCAGCCGCTTT 113 GCAAGCGAGGG 114 GGGTGGCTC CAGGGAGACT LAG3: ACACCCGTGCC 115 CGTGCTTCGGG 116 31, 33, 34,  GGTCCTCTG GGCACCTTC 35, 36, 37 LAG3: CCAGTGGGCTG 117 CCCACAGCAAT 118 38, 39, 40 ATGAAGTCT GACGTAGGC PDCD1: GGGTGAGCTGAG 119 GTGCGCCTG 120 53, 54, 57, CCGGTCC GCTCCTATT 58, 59, 60 GTCCC PDCD1: 51, CTCTGTATTCC 121 CAGTGAAAT 122 52, 55, 56 AGGGCCAGC GGCTTTGC TCA

[0188] Therefore the method of the invention is capable of enabling efficient editing of patient derived T-cells while reducing mosaicism.

[0189] The inventors have demonstrated the ability to control mosaicism through rational design of guide RNA. Advantageously, this allows for direct creation of animals with homogenous edits throughout all tissues and with the ability to pass engineered edits to the next generation. This method can be used to rapidly create experiment-ready mouse models of disease in a fraction of the time and using minimal amounts of animals. The inventors have further demonstrated the ability to control mosaicism in human cells of therapeutic significance. Specifically the inventors have used the method herein to edit primary human T-cells in a controlled manner, thereby rapidly creating homogenous populations of cells which can be used directly for therapy.

[0190] In addition, the inventors have demonstrated the ability, not only to create homogenous edits, but also to use the method to create desired large deletions in mice by targeting regions of low microhomology. Thereby providing an efficient alternative approach to generate gene knockout models.