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Related Concept Videos

CRISPR/Cas9 Genome Editing01:28

CRISPR/Cas9 Genome Editing

220
The CRISPR-Cas system serves as a bacterial defense mechanism against invading genetic elements such as viruses and plasmids, forming the foundation for its adaptation as a powerful genome-editing tool. Originally discovered in prokaryotes, this system has been repurposed to revolutionize genetic engineering across a wide range of organisms, including plants, animals, and humans. The core component, Cas9, is an endonuclease derived from Streptococcus pyogenes, capable of introducing...
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CRISPR01:59

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Genome editing technologies allow scientists to modify an organism’s DNA via the addition, removal, or rearrangement of genetic material at specific genomic locations. These types of techniques could potentially be used to cure genetic disorders such as hemophilia and sickle cell anemia. One popular and widely used DNA-editing research tool that could lead to safe and effective cures for genetic disorders is the CRISPR-Cas9 system. CRISPR-Cas9 stands for Clustered Regularly Interspaced...
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CRISPR and crRNAs02:53

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Bacteria and archaea are susceptible to viral infections just like eukaryotes; therefore, they have developed a unique adaptive immune system to protect themselves. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) are present in more than 45% of known bacteria and 90% of known archaea.
The CRISPR-Cas system stores a copy of foreign DNA in the host genome and uses it to identify the foreign DNA upon reinfection. CRISPR-Cas has three different...
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Related Experiment Video

Updated: Sep 11, 2025

CIRCLE-Seq for Interrogation of Off-Target Gene Editing
08:23

CIRCLE-Seq for Interrogation of Off-Target Gene Editing

Published on: November 1, 2024

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Predicting CRISPR Cas9 Off-Target Activities With a Two-Stage Deep Learning Framework.

Tianshan Zhang, Bei Jiang, Guang Yang

    IEEE Transactions on Computational Biology and Bioinformatics
    |August 14, 2025
    PubMed
    Summary
    This summary is machine-generated.

    We developed CAF-Net, a deep learning framework to predict CRISPR-Cas9 off-target activities. This method addresses label imbalance issues in guide RNA design for enhanced genome engineering accuracy.

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    Area of Science:

    • Genomics
    • Molecular Biology
    • Bioinformatics

    Background:

    • The CRISPR-Cas9 system is a powerful tool for eukaryotic genome engineering.
    • Off-target activities of Cas9 guide RNA pose a significant challenge, potentially leading to unintended mutations.
    • Existing methods for predicting off-target sites struggle with label imbalance due to numerous potential sites.

    Purpose of the Study:

    • To develop an accurate deep learning framework for predicting CRISPR-Cas9 off-target activities.
    • To address the label imbalance problem inherent in off-target prediction for guide RNA design.

    Main Methods:

    • Developed CAF-Net (Cas9 Augmentation and Finetune Network), a deep learning framework.
    • Pretrained an embedding model to extract features from target and guide RNA sequences.
    • Applied data augmentation to extracted features and finetuned the model with synthetic samples.

    Main Results:

    • CAF-Net effectively predicts off-target activities of CRISPR-Cas9.
    • The framework demonstrates robust performance on established datasets.
    • The data augmentation and finetuning strategy mitigates label imbalance issues.

    Conclusions:

    • CAF-Net offers a novel and effective solution for predicting CRISPR-Cas9 off-target activities.
    • The developed framework enhances the accuracy and reliability of guide RNA design.
    • This approach has significant implications for safe and precise genome engineering applications.