We have created a software tool that uses a DNA sequence input, and designs a list of gRNA sequences as output. These gRNAs will bind to their target DNA with a strength specified by the user, as a percentage of the maximum binding strength of the dCas9 protein to that DNA site. It also calculates the approximate structure of the gRNA and displays first the ones which disturb the Cas9 handle the least. To achieve these outcomes, it incorporates open source code from RNAfold [1] and code developed by Iman Farasat and Howard M. Salis [2], generously provided by them. The aim is to use this tool for de novo design of CRISPR-repressed (CRISPRi) and CRISPR activated (CRISPRa) promoters, as there is currently no method available for designing promoter sequences of pre-defined repression/ activation strengths.

The fold change is the fold difference in gene expression between the case when the dCas9 is bound to the promoter and when it's not bound. Since binding of dCas9 in a CRISPRi system prevents transcription by blocking access to the promoter, the strength of binding of dCas9 determines the fold-repression.

To estimate the relation between these, data from two papers is used. For a given DNA sequence one paper presents the fold change in binding of dCas9 for different number of mutations [3]. The second paper presents the repression activity of a single mutation at different locations[4].

In both cases the RNA:DNA binding is calculated with the Cas9Calculator and then plotted on a logarithmic scale against the fold change (Fig. 1) or one over the repression activity, respectively (Fig. 2). With the exception of few points, correlations seems to be linear and hence the relation is fitted with the following formula:𝑃=𝑒^(−𝛽(𝑚𝑎𝑥𝐺−𝐺))

Where maxG is the Gibson free energy when there are no mismatches and G is the energy for the software-designed sequence. P is the fold change between the two states. The coefficient %beta = 1.003074571 is the average of all individual coefficients satisfying the formula (with the exception of the few points noted above).

Our aim is to launch a web-based tool which will run the code described above in real time making it easier to use, and reaching a wider range of users. So far, a web interface has been created and the code has been successfully hosted on a webserver kindly provided by the Institute of Systems & Synthetic Biology (iSSB), Genopole, France (See snapshots Fig. 3,4,5). The tool could be further improved by increasing its precision or decreasing the time it takes to return results. This could happen by fitting the data from section 2 with a different function or developing a more efficient algorithm for creating gRNA sequences. While the idea behind this tool is simple, it could still be very effective in tunable engineering of CRISPR/Cas9 systems.

The tool is currently available at http://rikpu.lnx.warwick.ac.uk/ and http://warwickigem2016.issb.genopole.fr *We thank Warwick ITS and iSSB for hosting our web tool, and especially thank David Smyth (Warwick) and Joan Hérisson (iSSB) for all the help.