The CRISPR/Cas9 system recently emerged as the golden standard for targeted genome editing. The simplicity of this technique has enabled the high-throughput set-up of CRISPR/Cas9-based experiments. Analysing these experiments however, is a challenging and time-consuming task. Next-Generation Sequencing (NGS) has been replacing standard techniques such as the T7 Endonuclease I assay, due to its high capacity, sensitivity and ever-decreasing cost. However, the analysis of large amounts of NGS data is a significant hiatus in the otherwise advanced field of CRISPR/Cas9. In this work, we present and evaluate a straightforward tool, BATCH-GE, that performs batch analysis of NGS data for the assessment of knock-out and knock-in genome editing experiments.
BATCH-GE shows a number of important advantages over the current NGS-based genome-editing analysis methods. The tool’s most striking asset and improvement, is that it allows for batchwise analysis of a large number of samples. Furthermore, BATCH-GE is implemented as a freely available script, and is therefore available for further optimization by the user. Besides, it can run either within a server environment or on a stand-alone computer, providing an ensured availability. In addition, the user is only required to complete two simple input files, containing easy-to-determine variables that provide the user with the necessary flexibility. Lastly, BATCH-GE enables the assessment of both indel generation as well as HDR-mediated precise genome editing experiments.
BATCH-GE generates four comprehensive text files. The first file lists genomic region, type, length and frequency of every detected indel variant, providing a detailed overview of all sequence alterations. In the second file, a distinctive analysis of full and partial HDR events is carried out. Third, general indel and repair rates are summarized, enabling a quick and straightforward evaluation of the overall mutation efficiency. In the fourth file, URLs are provided to visualize the reads in the UCSC genome browser, offering the possibility to look into the specific sequence alterations.
To evaluate the performance of BATCH-GE, the tool was used for genome editing assessment in two zebrafish experiments, covering sgRNA efficiency testing and precise genome editing via HDR, validating that BATCH-GE is a new and reliable tool for the analysis of NGS-derived genome editing data and contributes to a faster, more informative and flexible analysis of multiple genome editing experiments.