Evidence map›Paper›PMID 40777850›Full record

ArticleFrontiers in genome editing2025

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

Ettore Rocchi, Federico Magnani, Gastone Castellani, Antonio Carusillo, Martina Tarozzi

Abstract read
In one paragraph

Article in Frontiers in genome editing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ettore Rocchi *Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Federico Magnani *Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Gastone CastellaniDepartment of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Antonio Carusillo *Alia Therapeutics, Trento, Italy.
Martina Tarozzi *Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: 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. Methods: 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. Results: 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. Discussion: 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.

Indexed as

allele-specificbioinformaticsbioinformatic softwareCRISPR/Cas9genome editingPAMPAM comparison

Identifiers

PMID40777850
PMCPMC12328375

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.