This document provides an overview of genome editing techniques such as CRISPR/Cas9 and rAAV and considerations for their use. It discusses how CRISPR/Cas9 and rAAV work to edit genomes and compares their advantages. Key factors for CRISPR gene editing are discussed such as gRNA design, donor design, and screening/validation approaches. The document also summarizes research optimizing CRISPR gene editing through improvements like testing different donor lengths and modifications. The goal is to translate genetic information into personalized medicines by leveraging tools like CRISPR and rAAV.
CRISPR, rAAV and the new landscape of molecular cell biology
1. CRISPR, rAAV and the new landscape of molecular cell biology
Genome Editing Comes of Age
Normal human karyotype
HeLa cell karyotype
www.horizondiscovery.com
2. Genome Editing Comes of Age
Jan Hryca, MSc (Leipzig University)
• Business Development - Europe
• J.hryca@horizondiscovery.com
• +44 1223 20 47 42
Chris Thorne, PhD (Liverpool University)
• Gene Editing Community Specialist
• c.thorne@horizondiscovery.com
• +44 1223 204799
3. Genome Editing Comes of Age
Horizon Discovery - Experts in Genome Editing
• Integrated products and services built on genome editing applicable across the drug
development continuum
• Deep roots in academia (with many existing colaborations through CoE program)
Our Mission
To translate the human genome and accelerate the discovery of personalised
medicines
Our Approach
Leveraging genome editing across to speed the translation of genetic observations
into clinical outcomes
4. Genome Editing Comes of Age
Gene Targeting Techniques – an overview
Genome Editing Tools
• rAAV
• CRISPR/Cas9
Key Considerations for Gene Editing
Genome Editing at scale
• High through Knock-out Cell Line Generation
• Genome Wide sgRNA Synthetic Lethality Screening
6. Gene targeting techniques – an overview
Approach
Gain of
function
Loss of
function
Endogenous
expression
Long-term
stability
Off-target
integrations
Time vs. Cost
Transient over-expression Yes No No No No Low
Stable over-expression Yes No No Yes*
Random
integration
Med/Low
Transient RNAi No Yes No No No Low
Stable RNAi No Yes No Yes*
Random
integration
Med/Low
Dominant negative over-
expression
No Yes No No** No Low
* Assuming viral promoter methylation does not occur
** Commonly transient vectors
7. Gene targeting techniques – an overview
Approach
Gain of
function
Loss of
function
Endogenous
expression
Long-term
stability
Off-target
integrations
Time vs. Cost
Transient over-expression Yes No No No No Low
Stable over-expression Yes No No Yes*
Random
integration
Med/Low
Transient RNAi No Yes No No No Low
Stable RNAi No Yes No Yes*
Random
integration
Med/Low
Dominant negative over-
expression
No Yes No No** No Low
Nuclease-Based Genome
Editing
Yes Yes Yes Yes Varies Low-High
rAAV-Based Genome Editing Yes Yes Yes Yes Controlled Med
8. 8
Endogenous targeting of PIK3CA
Large growth induction phenotype
Transforming alone
Milder growth induction phenotype
Non-transforming alone
Di Nicolantonio et al., PNAS, Dec. 2008Isakoff et al., Cancer Research, Jan 2006
9. 9
Endogenous targeting of KRAS
Konishi et al (2007) - Endogenous knock-in of KRAS G12V does not transform cells, unlike KRAS G12V
overexpression
KRAS G12V overexpression is not a physiological model
12. Genome Editing: The Right Tool For The Right Outcome
rAAV
• High precision / low thru-put
• Any locus, wide cell tropism
• Well validated, KI focus
Zinc Fingers
• Med precision / med thru-put
• Good genome coverage
• Well validated / KO Focus
CRISPR
• New but high potential
• Capable of multi-gene targeting
• Simple RNA-directed cleavage
• Combinable with AAV
Great for knock-outs Great for heterozygous
knock-ins
13. rAAV: How Does It Work?
Nature Genetics 18, 325 - 330 (1998)
AAV = Adeno Associated Virus (ssDNA)
14. Crispr (cr) RNA + trans-activating (tra) crRNA combined = single guide (sg)
RNA
CRISPR/Cas9: How Does It Work?
16. Cas9 Wild type Cas9 Nickase (Cas9n)
Induces double strand break Only “nicks” a single strand
Only requires single gRNA
Requires two guide RNAs for reasonable
activity
Concerns about off-target specificity Reduced likelihood of off-target events
High efficiency of cleavage
Especially good for random indels (= KO)
Guide efficiency dictated by efficiency of
the weakest gRNA
Nishimasu et al Cell
CRISPR/Cas9: How Does It Work?
17. Hsu et al. Cell. 2014
CRISPR/Cas9: What can you do?
18. Genome Editing: As Simple As…
... HOWEVER …
Cell Line
Screen for clones
Engineered cells!
Genome Editing Vector
19. Key Considerations For CRISPR Gene Editing
Gene Target Specifics
Cell Line
gRNA Design
gRNA Activity
Donor Design
Screening
Validation
20. Key Considerations For CRISPR Gene Editing
Gene Target Specifics
Cell Line
gRNA Design
gRNA Activity
Donor Design
Screening
Validation
Normal human karyotype
HeLa cell karyotype
Gene copy number
Effect of modification on growth
24. Key Considerations For CRISPR Gene Editing
Gene Target Specifics
Cell Line
gRNA Design
gRNA Activity
Donor Design
Screening
Validation
Number of gRNAs
gRNA activity measurement
NT
Cas9
wt
only
4uncut
1 52 3
gRNA
200
300
400
500
100
600
+ve
700
200
300
400
500
100
600
700
25. Key Considerations For CRISPR Gene Editing
Gene Target Specifics
Cell Line
gRNA Design
gRNA Activity
Donor Design
Screening
Validation
Donor sequence modifications
Modification effects on expression or splicing
Size and type of donor (AAV, oligo, plasmid)
Selection based strategies
Cas9 Cut Site
Genomic
Sequence
Donor Sequence
containing mutation
26. Technology Development at Horizon: Combining rAAV + CRISPR
Can we combine technologies for improved efficiency?
Tested using a reporter cell-line harbouring an inactivating mutation in GFP
Correction donor-vector supplied either as dsPlasmid, ssDNA oligos, or ssDNA rAAV
rAAV = the most efficient donor vector (50 fold)
%Greencells(FACs)
27. Technology Development at Horizon: Systematic improvements
Donor lengths: sODNs ranging from 50-200nt, with single phosthothioate modifications at
both outer nucleotides
100nt ssODN is optimal
4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 0 1 8 0 2 0 0
0 .0
0 .5
1 .0
1 .5
H R e ffic ie n c y u s in g s s O D N s o f d iffe r e n t le n g th s
O lig o le n g th (N T )
Efficiency(%)
4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 0 1 8 0 2 0 0
0
5
1 0
1 5
T ra n s fe c tio n e ffic ie n c y u s in g 1 0 p m o l s s O D N
O ligo length (N T )
Transfection%(RFP)
Size Oligo Sequence
50 C*ACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCC*C
70 T*CCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTG*C
90 T*GATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACC*A
110 A*CAGTTATGTTGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCACTACCTGAG*C
130 T*TTTTGCTCTACAGTTATGTTGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCACTACCTGAGCACCCAGTCC*G
150 G*TATCTGGTATTTTTGCTCTACAGTTATGTTGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCACTACCTGAGCACCCAGTCCGCCCTGAGCA*A
170 T*AAGCCTGCAGTATCTGGTATTTTTGCTCTACAGTTATGTTGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCACTACCTGAGCACCCAGTCCGCCCTGAGCAAAGACCCCAA*C
200 A*AATGTCTTTATAAATAAGCCTGCAGTATCTGGTATTTTTGCTCTACAGTTATGTTGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCACTACCTGAGCACCCAGTCCGCCCTGAGCAAAGACCCCAACGAGAAGCGCGATCA*C
GFP Mutation, PAM mutation
28. Technology Development at Horizon: Systematic improvements
Donor modifications: number and position of phosphothioate medications
Only 3’ PTO modifications required for ssODNs tested
Oligo Sequence
None TGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCA
5' PTO T*GATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCA
3' PTO TGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACC*A
5+3 PTO T*GATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACC*A
Mut Flank TGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACT*A*C*C*AGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCA
Mut Flank + 5+3 PTO T*GATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACT*A*C*C*AGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACC*A
3x5' PTO T*G*A*TGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCA
3x3' PTO TGATGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAA*C*C*A
3x5'+3' PTO T*G*A*TGGTTCTTCCATCTTCCCACAGCTGGCCGACCACTACCAGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAACCA
Mut Flank + 3x5'+3' PTO T*G*A*TGGTTCTTCCATCTTCCCACAGCTGGCCGACCACT*A*C*C*AGCAGAACACACCCATCGGCGACGGCCCCGTGCTGCTGCCCGACAA*C*C*A
GFP Mutation, PAM mutation
N
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5
'P
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O
3
'P
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O5
+
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0 .0
0 .5
1 .0
Targetingfrequency(GFP%)
H R e ffic ie n c y u s in g s s O D N s w ith v a r y in g n u m b e r s a n d p o s ito n s o f
p h o s p h t io la t e p r o t e c t e d n u c le o t id e s
2 5
)
T r a n s fe c tio n e ffic ie n c y u s in g s s O D N s w ith v a r y in g n u m b e r s a n d p o s it o n s o f
p h o s p h t io la t e p r o t e c t e d n u c le o t id e s
N
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0 .5
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N
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n
k
+
3
x
5
+
3
P
T
O
0
5
1 0
1 5
2 0
2 5
Transfection%(RFP)
T r a n s fe c tio n e ffic ie n c y u s in g s s O D N s w ith v a r y in g n u m b e r s a n d p o s it o n s o f
p h o s p h t io la t e p r o t e c t e d n u c le o t id e s
29. Introducing gUIDEBook™ - Coming soon!
Supports all Cas9 nuclease
variants
Advanced tools for knock-in
design
Comprehensive gRNA scoring
• Off target
• Activity
Full integration with annotated
reference genomes
Flexible and easy to use
30. Key Considerations For CRISPR Gene Editing
Gene Target Specifics
Cell Line
gRNA Design
gRNA Activity
Donor Design
Screening
Validation
Donor sequence modifications
Modification effects on expression or splicing
Size and type of donor (AAV, oligo, plasmid)
Selection based strategies
(+/+)
(+/-)
(-/-)
(KI/-)
(KI/+)
(KI/KI)
31. Key Considerations For CRISPR Gene Editing
Gene Target Specifics
Cell Line
gRNA Design
gRNA Activity
Donor Design
Screening
Validation
Number of cells to screen
Screening strategy
Modifications on different alleles
Homozygous or heterozygous
modifications versus mixed cultures
% cells targeted
32. Key Considerations For CRISPR Gene Editing
Gene Target Specifics
Cell Line
gRNA Design
gRNA Activity
Donor Design
Screening
Validation
Confirmatory genotyping strategies
Off-target site analysis
Modification expression
Contamination
Heterozygous knock-in
Wild type
33. Key Considerations For CRISPR Gene Editing
Gene Target Specifics
Cell Line
gRNA Design
gRNA Activity
Donor Design
Screening
Validation
How many copies?
Is it suitable?
What’s my goal? (Precision vs Efficiency)
Does my guide cut?
Have I minimised re-cutting?
How many clones to find a positive?
Is my engineering as expected?
34. Genome Editing Comes of Age
Gene Targeting Techniques – an overview
Genome Editing Tools
• rAAV
• CRISPR/Cas9
Key Considerations for Gene Editing
Genome Editing at scale
• High through Knock-out Cell Line Generation
• Genome Wide sgRNA Synthetic Lethality Screening
35. High throughput knock-out cell line generation
(Near) Haploid human cell lines
• Near-haploid (diploid for chr8, and chr15)
• Isolated from CML patient
• Myeloid lineage
• Suspension cells
KBM-7
HAP1
• Near-haploid (diploid for chr15)
• Derived from KBM-7
• Fibroblast like
• Adherent cells
36. Unambiguous genotyping
Defined copy number Knowledge base
RNA sequencing
- Predict suitability
as cellular model
Essentiality dataset
- Predict success rate
for knockouts
Haploid
High efficiency
Diploid
- Knockouts
- Defined mutations
High throughput knock-out cell line generation
Advantages of Haploid Cells
37. Wildtype TCCTTTGCGGAGAGCTGCAAGCCGGTGCAGCAG
||||||||||| ||||||||||||||
Knockout TCCTTTGCGGA--------AGCCGGTGCAGCAG
Wildtype SerPheAlaGluSerCysLysProValGlnGln
Knockout SerPheAlaGlu AlaGlyAlaAla
Exon 1
DNA sequencing
Exon 2
Cas9 cleavage
High throughput knock-out cell line generation
CRISPR/Cas9 allows rapid and high efficiency targeting
39. Lentivirally delivered sgRNA can drive efficient cleavage of target genomic
sequences for use in whole genome screens
Use massively-parallel next-gen sequencing to assess results
Possible addition/replacement to RNAi screens
Genome Wide sgRNA Screening
41. We are combining CRISPR and isogenic cell lines to perform
CRISPR-based Synthetic Lethality Screens
sgRNA technology will be transformational for both Target ID and early-stage Validation
4
Synthetic lethal target ID via sgRNA screening
42. Ready-made knock-out X-MAN® cell lines
X-MAN® - gene X Mutant And Normal cell line
Advantages:
• Genetically verified
• More than 3,000 available clones already available, in a variety of cell line backgrounds
• Quick and easy way to get first data on gene of interest
• Available with validated gRNAs to use with your own human cell line of choice.
More Information: www.horizon-genomics.com/
Bromodomain
40 genes
Autophagy
15 genes
mTOR pathway
50 genes
Kinases
350 genes
HATs/HDACs
15 genes
DNA damage
50 genes
RAB GTPases
15 genes
Deubiquitinases
80 genes
43. GENASSIST: CRISPR and rAAV enabled gene editing
Cas9 Vectors
• Wild type and nickase
• Separate or combined with guide
Guide RNA
• Single or double guides
• Available OTS for in-lab cloning
• Custom guide generation available with validation
Donors
• Available OTS for in-lab cloning
• Plasmid or rAAV format
• Custom donor generation available
Cell Lines
• CRISPR-ready cell lines
• 550+ OTS cell line menu available for further gene editing
Services
• Viral encapsulation of rAAV donor
• Project design support
• On-going expert scientific support
44. Your Horizon Contact:
Horizon Discovery Group plc, 7100 Cambridge Research Park, Waterbeach, Cambridge, CB25 9TL, United Kingdom
Tel: +44 (0) 1223 655 580 (Reception / Front desk) Fax: +44 (0) 1223 655 581 Email: info@horizondiscovery.com Web: www.horizondiscovery.com
Jan Hryca
Business Development - Europe
J.hryca@horizondiscovery.com
+44 1223 204 742
Chris Thorne PhD
Gene Editing Specialist
c.thorne@horizondiscovery.com
+44 1223 204 799
45. Useful Resources
From Horizon
Free gRNAs in Cas9 wild type vector – www.horizondiscovery.com/guidebook
Technical manuals for working with CRISPR - http://www.horizondiscovery.com/talk-to-us/technical-
manuals
In the Literature
Exploring the importance of offset and overhand for nickase -
http://www.cell.com/cell/abstract/S0092-8674(13)01015-5
sgRNA whole genome screening:
• Shalem et al - http://www.sciencemag.org/content/343/6166/84.short
• Wang et al - http://www.sciencemag.org/content/343/6166/80.abstract
On the web
Feng Zhang on Game Changing Therapeutic Technology (Link to Feng’s Video)
Guide design - http://crispr.mit.edu/
CRISPR Google Group - https://groups.google.com/forum/#!forum/crispr
Editor's Notes
In a translational context we hope that by answering that question we will be able to is to characterise the genetics that drive disease, and indeed develop drugs and diagnostics that are personalised to patients.
Genome editing provides the link between the information here, and this outcome here, by allowing scientists to recapitulate specific genetic alterations in any gene in any living tissue to probe function, develop disease models and identify therapeutic strategies
Human cell lines containing the Kras G12V knock-in do not exhibit many of the phenotypes observed in overexpressing lines, and make the case for this being a more physiological model for elucidating the contribution of oncogenic Kras in human cancer cells.
So to return to my picture, not only do we now have unparalleled access to genetic information, but we now have the tools to most accurately understand what this genetic information – with genome editing allowing us to explore the genetic drivers of disease in physiological models.
AAV is a single-stranded, linear DNA virus with a a 4.7 kb genome which for the purpose of genome editing is replaced almost in entirety with the targeting vector sequence (except for the iTRs)
It is in effect a highly effective DNA delivery mechanism
After entry of the vector into the cell, target-specific homologous DNA is believed to activate and recruit HR-dependent repair factors
can induce HR at rates approximately 1,000 times greater than plasmid based double stranded DNA vectors, but the mechanism by which it achieves this is still largely unknown
By including a selection cassette can select for cells that have integrated the targeting vector, and then screen for clones which have undergone targeted insertion rather than random integration, which will generally be around 1%.
CRISPR/Cas9 gene editing is based on a microbial restriction system, which ordinarily functions effectively as an immune system in these organisms, but that has been harnessed for genome targeting.
The beauty of the system is that unlike protein binding based technologies such as Zinc Fingers and TALENs which require complex protein engineering, the design rules are very simple, and it is this fact that is allowing CRISPR to take genome engineering from a relatively niche persuit to the mainstream scientific community.
The system itself is comprised of three key components
the Cas9 protein, which cuts/cleaves the DNA and
Two RNAs - a crispr RNA contains a sequence homologous to the target site and a trans-activating crisprRNA (or TracrRNA) which recruits the nuclease/crispr complex
For genome editing, the crisperRNA and TraceRNA are generally now constructed together into a single guideRNA or sgRNA
Genome editing is elicited through hybridization of the sgRNA with its matching genomic sequence, and the recruitment of the Cas9, which cleaves at the target site. This then cuts the dsDNA, triggering repair by either the low fidelity NHEJ pathway, or by HDR in the presence of an exogenous donor sequence.
The design rules for CRISPR are straightforward, as you require only a 23 nucleotide sequence that ends in an NGG motif – known as the protospacer associated motif (or PAM site).
Of this 23bases, only the first 20 are included in the guide target sequence which is appended to the tracrRNA “fixed scaffold” and together comprise the gRNA.
So as the only requirement is this NGG, on average eligible PAM sites can be found every 12bp, although this will depends on sequence
Several tools for gRNA design – HD has our own. One of the key considerations is what is the off target potential of my guide – very often even a 23 base pair sequence will be found elsewhere in the enormity of the genome, and even if an exact match isn’t observed there may be instances of homology with a few mismatches.
In fact the specificity of the CRISPR system remains a concern for researchers, especially where minimising off target modifications is critical, such as those working in the field of gene therapy.
Various approaches are being taken improve specificity - Interestingly recent work by Keith Joung’s lab has shown using a 17bp target region can reduce some of the off target potential that guides have
Another approach has been to mutate the nuclease such that it will only nick one strand of the dsDNA, a nickase form of the protein. Nicks will in general be repaired by the base excision repair pathway which is significantly higher fidelity than NHEJ.
Targeting strategies using the nickase are designed with two gRNAs, one to recruit the nickase to each strand of the DNA, only after which a DSB will be introduced.
This increase in specificity is unfortunately at the expense of some efficiency at you’re at the mercy of your weakest guide in the pair
The design of CRISPR system is simple and Genome editing might appear as simple as:
Identifying a gRNA target sequence
Ordering an oligo with the target sequence and cloning it into a gRNA vector
Transfecting cells with the gRNA + Cas9
+ Voila!
well… is not always that simple, there are things you need to consider
And as we are running gene editing projects every day at Horizon we’ve learnt from experience that there are various ways that things can go wrong if you don’t consider the following,
and I want to briefly run through each of these one at a time.
The first group of considerations regard the quirks of your specific target gene
How many copies of your gene exist in your cell line?
Many of us use transformed human cell lines – there aren’t many that actually come with a normal copy number of 2. For many, many, years people using HeLa cells - quadroploid – see pic = mess -Their karyotype is very different from wild type and they might have multiple copies of an allele
It is important to understand YOUR cell line.
Do you need to modify all alleles present?
Would KO of one allele and modification of the other be viable/acceptable? This is something that happens frequently with CRISPR.
When you make the modification do you expect it affect the growth of the cells?
When the gene alteration we are trying to make don’t seem to be able to be isolated and then they tell us expts with shRNAs show viability of cells affected by modification
The second category, and this is probable the one that causes us here at Horizon the most trouble/has required a lot of hard-won expertise - the suitability of the cell line. For example:
Need to get DNA into cells. Does your cell transfect/electroporate well? Should you transduce instead?
Can the cell line be single cell dilute (SCD)? (Single cell or as in Top panel = triplicate stuck together – takes a long time to separate artefacts) And have it come back at reasonable growth levels? Even if the cell line grows very well, it might not tolerate single cell dilution and you need to find the most suitable conditions to let the cell line grow
What is the doubling time? Optimal growth conditions?
Looked at whole panel of media formulations, additives, diff seeding densities..(see panel on bottom gives example of taking 1 particularly hard cell line and trying a range of conditions to find the conditions most suitable for SCD
Now let’s get to the most interesting part the guide RNA design
gRNA design:
A very important consideration is What source you are using for your genomic sequence?
Even a single base discrepancy can be the difference between success and failure with CRISPR and most of these other technologies. It is important that you know what the target looks like IN YOUR cell line. We therefore highly recommend that you sequence all alleles in your cell line so you know what you are targeting. 1bp or 2bp difference will have a big effect on whether you are going to be able to make an effective change. Imperative that you make sure you understand your target region so that your guides are appropriately designed to your real sequence. That’s one of the strengths of the gUIDEbook guide design system that we have developed jointly with Desktop Genetics – see example of output in slide – need to use it to identify potential guides and figure out how close are they to the modification want to make? Distance does matter!
How close is the guide to the desired mutation?
Distance is important, particularly for something like a point mutation. The closer the cut is to the change you want to make the most effective will be the guide.
What are the potential off-target considerations?
We pay a lot of attention to this at Horizon, the design algorithm takes into account all the sites that are obviously a perfect match and up to 1, 2, 3, or 4bp mismatched potential off effects elsewhere in the genome. Sometimes, can’t avoid; common to have some mismatches but need to know if in coding or non-coding. If non-coding is it in a regulatory region?
Data suggests that two nicks that result in a 5’ overhang are most efficient at being modified
It has also been shown that the distance or “offset” between the two guides is important for efficiency.
Once you have guide designs it can pay dividends to validate their activity before hand.
The accepted wisdom is to design 5 guides (or 10 if using pairs). Activity can be assessed semi quantitatively using the Surveyor assay.
This done, you can then take just one or two forward for gene targeting in your cell line of choice.
Donor must be sufficiently different to prevent re-cutting
Include silent mutations
However, consider effects on expression on splicing
Also to consider is nature of donor – selection? Delivery method?
If you can imagine, even if you dsb is repaired by the HDR pathway, unless your donor is sufficiently different from you guide target sequence, you’re at high risk of having your modified allele further modified with CRISPR cuts and indels.
It is highly recommended therefore to include with your donor silent mutations in the guide target sequence.
If you alter the donor, in a coding region like our hypothetical example, how will codon substitutions affect the outcome? Will expression or splicing be affected? How big a donor do you need, how many changes are you introducing – where do you derive donor from? For targeting, every single bp important…also impt. on the donor side of things - want to introduce as few changes as possible in donor in order to achieve highest efficiencies.
Can use selection but need to be careful as introducing another ORF.
So you can see, there’s a lot to consider and a lot of value in working with a company that can do much more than just providing plasmids
Between our personal expertise and through our design tool we have implemented a donor design module that helps us to design the perfect donor for your project, and which will be stable and in-frame.
Historically Horizon’s tool of choice for gene editing was rAAV – for reasons not yet fully understood rAAV is very good at stimulating HDR, and so the system is perfect for introducing very precise modifications into the genome.
However, in general these modifications will only be introduced onto a single allele, which means that whilst it’s a great system for knock-in’s it lacks the efficiency of nucleases when it comes to knock-outs.
What we’re able to do now however is combined our experience with rAAV with CRISPR – evidence in the literature suggests that DSBs can stimulate HDR by rAAV, and we’ve found that by combining a cut with CRISPR and rAAV delivery of the donor we can improve efficiency of HDR by 50 fold.
In this case we have an in house testing system, a cell line containing a mutant (non-fluoresecent) GFP, and we can measure efficiency of targeting by rescue of fluoresence in FACS.
Historically Horizon’s tool of choice for gene editing was rAAV – for reasons not yet fully understood rAAV is very good at stimulating HDR, and so the system is perfect for introducing very precise modifications into the genome.
However, in general these modifications will only be introduced onto a single allele, which means that whilst it’s a great system for knock-in’s it lacks the efficiency of nucleases when it comes to knock-outs.
What we’re able to do now however is combined our experience with rAAV with CRISPR – evidence in the literature suggests that DSBs can stimulate HDR by rAAV, and we’ve found that by combining a cut with CRISPR and rAAV delivery of the donor we can improve efficiency of HDR by 50 fold.
In this case we have an in house testing system, a cell line containing a mutant (non-fluoresecent) GFP, and we can measure efficiency of targeting by rescue of fluoresence in FACS.
Historically Horizon’s tool of choice for gene editing was rAAV – for reasons not yet fully understood rAAV is very good at stimulating HDR, and so the system is perfect for introducing very precise modifications into the genome.
However, in general these modifications will only be introduced onto a single allele, which means that whilst it’s a great system for knock-in’s it lacks the efficiency of nucleases when it comes to knock-outs.
What we’re able to do now however is combined our experience with rAAV with CRISPR – evidence in the literature suggests that DSBs can stimulate HDR by rAAV, and we’ve found that by combining a cut with CRISPR and rAAV delivery of the donor we can improve efficiency of HDR by 50 fold.
In this case we have an in hosue testing system, a cell line containing a mutant (non-fluoresecent) GFP, and we can measure efficiency of targeting by rescue of fluoresence in FACS.
Desktop Genetics, in partnership with Horizon, has developed the premiere software platform tailored for CRISPR/Cas9 experiments
Complete guide design capabilities for all common nucleases, including Fok1 fused dCas9
Advanced tools for knock-in design (donors and optimal guide designs specifically for KIs)
Comprehensive multiple scoring dimensions to iform experimental prediction
Full integration with annotated reference genomes for accurate guide design
Stores experimental outcomes to continuously improve gRNA design
Flexible and simple user interface with collaboration tools and vendor integration
What is your like probability of your targeting desired event?
Armed with all the above information on the nature of the cell line, your transfection efficiency and your guide activity, you next consideration will be how many cells do you need to screen to have a chance of finding a positive.
In our case, as we’re looking for a single modified allele which at best will be ¼ of those cells that have been targeted we will need to scale up our screen accordingly.
The method you use to screen will depend largely on the modification your introducing – if for example you’re inserting a tag, you can screen using PCR at that locus.
If you’re introducing a framshift that will disrupt a restriction site, this can be used.
Finally, in many knock-outs the modification on each allele will be different, and so the surveyor assay can be used.
Finally, once you have identified a clone or clones that you believe contain your desired mutation the ultimate step is the validate these.
Of most interest is certainly going to be the nature of the modifications introduced at your target site – whether for example insertion deletions are present on all of your alleles, and if so, whether they result in frameshifts.
You may also wish to assess the off-target cutting in your clones, whether mutations have been introduced at your prediced off target sites, and you can do this using sequencing.
Finally, there are various other factors that will be critical to the utility of your cell line. Does the modification express (if it’s a knock-in) or not (if it’s a knock-out). Does your cell line remain genomically stable over multiple passages. And finally, given the length of time cells must remain in culture, and also the degree of handling we always test our engineered lines for contamination with mycoplasma and other microbes.
In summary If we however, try to consider them in the context of a hypothetical experimental goal this might help, and so for the sake of this example lets say we want to introduce a point mutation the coding sequence of a single allele of a gene, and we want to use CRISPR to make this happen
Further to this we….
Recent data from Feng Zhang’s and Eric Lander/David Sabatini’s laboratories indicate lentivirally delivered sgRNA can drive efficient enough cleavage of target genomic sequences that the technology can be used for whole genome screens
Results can then be assessed using next generation sequencing, with each sgRNA effectively acting as a bar code
This style of screen will complement or replace si or shRNA screens of a similar nature
SO the principal is that you synthesis a guide or guides against every gene in the genome, with the aim being that that guide is capable of disrupting the coding sequence of the gene and knocking it out.
These guides are cloned into a lentiviral delivery system to generate what has become known as a lentiCRISPR library
You can use this library to transduce cells, and by using the guides themselves as barcodes ask the question which guides are enriched when treated with a drug for example vs my control cell. This for example would tell you which knock-outs promotes resistance to this drug
In the case of the two papers on the previous slide, the proof of concept was to look for those genes that are essential.
Cancer is a genetic disease
Genome sequencing has generated 100’s of potential targets for cancer therapy
However, most targets are rare and poorly characterised
Most of them can’t be drugged directly e.g., tumour suppressors
If tumour suppressor loss is the prime cancer initiating event, agents exploiting this loss may assist with overcoming tumour heterogeneity
Systematic de-orphaning required to find key druggable downstream targets - exploiting co-dependence or synthetic lethality
Vectors
gRNA design services
Donor services and expertise in knock-ins
Services – viral encapsulation, project design support, expert support