# CATS: a bioinformatic tool for automated Cas9 nucleases activity comparison in clinically relevant contexts

## TL;DR

CATS is a new tool that helps scientists compare different Cas9 enzymes for gene editing by finding common target sites and considering disease-related mutations.

## Contribution

CATS introduces an automated method to compare Cas9 nucleases by identifying overlapping PAM sites and allele-specific targets using ClinVar data.

## Key findings

- CATS automates the detection of overlapping PAM sequences across Cas9 variants.
- The tool identifies allele-specific targets arising from pathogenic mutations.
- CATS reduces experimental design time and supports precise genetic therapies.

## Abstract

With the growing number of Cas9 nucleases available to genetic engineers, selecting the most suitable one for a given application can be challenging. A major complication arises from the differing protospacer adjacent motif (PAM) sequence requirements of each Cas9 variant, which makes direct comparisons difficult. To ensure a fair comparison, it is essential to identify common target sites that are not biased by the natural genetic landscape of the chosen target.

To address this challenge, we developed CATS (Comparing Cas9 Activities by Target Superimposition), a novel bioinformatic tool. CATS automates the detection of overlapping PAM sequences across different Cas9 nucleases and identifies allele-specific targets, particularly those arising from pathogenic mutations. One of the key parameters in CATS is the proximity of PAM sites, which helps minimize sequence composition bias. The tool integrates data from continuously updated sources and includes ClinVar information to facilitate the targeting of disease-causing mutations.

CATS significantly reduces the time and effort required for CRISPR/Cas9 experimental design. It streamlines the comparison of Cas9 nucleases with different PAM requirements, enabling researchers to select the most appropriate nuclease for their specific target. The tool’s automation, speed, and user-friendly interface make it accessible to researchers regardless of their computational expertise.

By enabling the identification of overlapping PAMs and allele-specific targets, CATS supports the implementation of Cas9-based applications in both research and clinical settings. Its ability to incorporate genetic variants makes it particularly useful for designing therapeutic approaches that selectively target mutated alleles while sparing healthy ones. Ultimately, CATS contributes to the development of more effective and precise genetic therapies.