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Related Concept Videos

CRISPR/Cas9 Genome Editing01:28

CRISPR/Cas9 Genome Editing

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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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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.
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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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Updated: Jul 13, 2025

CRISPR Guide RNA Cloning for Mammalian Systems
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Predicting CRISPR-Cas12a guide efficiency for targeting using machine learning.

Aidan O'Brien1,2, Denis C Bauer2,3,4, Gaetan Burgio1

  • 1Division of Genome Science and Cancer and The Shine-Dalgarno Centre for RNA Innovation, The John Curtin School of Medical Research, College of Health and Medicine, The Australian National University, Canberra, ACT, Australia.

Plos One
|October 17, 2023
PubMed
Summary
This summary is machine-generated.

Cas12a genome editing shows improved guide RNA efficiency prediction by analyzing nucleotide bias and mismatches near the PAM site. Machine learning enhances accuracy by over 15%, but more data is needed for reliable off-target predictions.

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Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • CRISPR-Cas technology, including Cas9, has transformed biological research.
  • Cas12a is a promising alternative to Cas9 for editing AT-rich genomes.
  • Accurate prediction of guide RNA efficiency for Cas12a remains a challenge.

Approach:

  • Conducted a computational meta-analysis of Cas12a target and off-target cleavage.
  • Investigated the role of nucleotide bias and mismatches relative to the PAM site.
  • Developed a Random Forest machine learning model incorporating these features.

Key Points:

  • Cas12a cleavage behavior is influenced by nucleotide bias and PAM-site mismatches.
  • The developed machine learning model improves guide RNA efficiency prediction accuracy by at least 15% over existing methods.
  • Identified nucleotide bias and mismatches as critical factors for Cas12a targeting.

Conclusions:

  • The study presents a novel computational approach to enhance Cas12a guide RNA efficiency prediction.
  • The findings highlight the importance of sequence context, particularly nucleotide bias and PAM interactions.
  • Further research requires more extensive datasets and rigorous benchmarking for robust prediction of Cas12a efficiency and off-target effects.