Abstract: Application of genome editing for clinical therapy relies on the ability of the editing tool to make only the intended edits at the target site of the cells. In practice however, genetically engineered pool of cells always contains a mixture of unedited cells, cells with on-target edits and cells with unintended off-target edits. A sensitive genome-wide off-target nomination assay can be used to map out the location and frequency of such unintended edits. It is important that the assay can be scaled up to be high-throughput for wide spread use of gene editing tools. However, designing and optimizing an automated complex multi-day off-target nomination assay such as Change-Seq, One-Seq, Digenome-Seq etc. can be challenging. We approached the automation of one such assay, Change-Seq (Circularization for High-throughput Analysis of Nuclease Genome-wide Effects by Sequencing) by dividing the complex assay process into smaller, independent, and interchangeable modules. We have developed seven interchangeable modules that can be customized and assembled to automate the entire Change-Seq assay. Each module has their own independent statistical validation strategies and specification ranges rapidly generated with large number of experiments using our Prototype Cell Assay Measurement Platform (P-CAMP), built from a Hamilton MicroLab StarPlus and a modular instrument cabinet designed to expedite the automation of high-quality assay protocols. Once validated, these interchangeable modules can then be swiftly customized to create an optimal experimental design to assess the accuracy and precision of the measurement process and to identify the sources of variabilities within the assay. This will lead to generation of a robust, evidence-based measurement processes for other gene editing assays and will facilitate the transfer of measurement processes between automation systems.
.png)
.png)
