Early on in our CRISPR use at Horizon, we learned that that when it comes to guide RNA design not all sgRNAs are created equal. In fact what makes a good guide is still the topic of a great deal of research in the field – and aside of the consensus that a guide with a guanine at position -1 is more likely to have a higher activity, we are still a way from being 100% confident in predicting in silico guide activity in vitro/vivo.
And if you’re working with CRISPR in the lab, finding out that your guide has little or no activity after four weeks plus of transfecting, single cell diluting and clone screening (and the associated reagents costs) is both painful and (happily) avoidable - with a small amount of up front gRNA validation.
With this in mind here are some of the things you can do when design guide RNAs to maximise your chances of gene editing success…
Begin with “pre-validated” guide RNAs
Despite the relatively short amount of time that CRISPR has been around, its adoption rate has been staggering, as evidenced by the number of publications that contain the word CRISPR accelerating dramatically since 2013 (see chart).
As such there are now many papers detailing guide sequences that have worked in specific experiments. Efforts are now being made to catalogue “validated” guides – one example is QuiltData.
It’s worth keeping in mind that guide activity is likely to be influenced by context – i.e. the accessibility of that gene in that cell line – and so the most efficient guide in one system might not be the most efficient in another.
However, a guide known to work is an excellent starting point, and with this in mind, you can now buy our knockout cell lines in combination with the guide RNAs used to generate them.
Finally, published library screens also provide some insights into active guides, and in fact it is these screens that have been used to propose algorithms for guide activity. This is because a proportion of the guide library targets essential genes, and so scientists have been able to use level of depletion of these guides as a proxy for their activity (See Wang et al and Xu et al).
They have then in turn looked for patterns in the sequences of the most effective guides – for example multiple papers have now observed in their data that a guanine at position -1 (proximal to the PAM site) is a good predictor of guide activity.
Which leads onto my next point…
Select guides with a high predicted activity
While predicting guide activity is not yet an exact science, the predicted activity score can be combined with potential off target score to short list guide choices.
There are now a number of papers that have used different types of CRISPR screen to propose sequence contributors to guide activity. While these are not yet a guarantee of a working guide (see aforementioned tissue specific behaviour), choosing a guide (or multiple guides) with a high predicted activity score is a sensible starting point.
Select multiple guide RNAs for validation
Because it’s not yet possible to predict guide activity with 100% certainty, it’s good practice to select multiple guides (3-5) that are designed to achieve the same outcome.
For example, if you’re aiming to generate a knockout then guides can be sited in different exons to avoid locus specific effects. If you’re knocking in then you’re more constrained, as it is desirable to have the cut site as close as possible to the site of knockin – nevertheless, if possible guides can be selected from different strands and upstream and downstream of the target site.
These guides can then be tested in vitro and the best taken forward to for genome editing.
Validate your guides in vitro
Validating the activity of any new guides, especially if you’re working in a new tissue or cell line background, is good practice.
Given the time intensive nature of gene engineering, the relatively straightforward and quick (<1 week) process of gRNA validation can save weeks of cell culture and hours of bench time. Further to this a clear idea of gRNA activity will provide insights into how many clones need to be screened to identify a positive.
There are now a variety of options available to scientists looking to validate guides – check out our article on validation approaches to learn more.
Have a contingency plan
Despite any amount of planning, biology being what it is means that sometimes there can be un-anticipated problems. As such it’s always a good idea to have a contingency.
For example at Horizon we always run two different guides in parallel for our Hap1 knockouts, assessing clones from only one experiment in the first instance, and then the second if we fail to identify targeted cells.
Similarly, plating out extra plates of single clones for potential screening is easier than having to go back to the cultured cells and re-transfect.
At Horizon we recognise that our Hap1 cell line may not be the first choice of model for all experiments. However, our ready-made and on-demand knockouts supplied with validated guide RNAs offer both an excellent contingency, and the reagents to hit the ground running when it comes to generating your own knockout cell line.