Multiplex CRISPR Editing
Also known as: multiplexed genome editing, multi-target CRISPR
The simultaneous targeting of multiple genomic loci using arrays of guide RNAs and CRISPR-Cas nucleases, enabling parallel construction of complex genetic circuit architectures.
Multiplex CRISPR Editing is the simultaneous use of multiple guide RNAs with CRISPR-Cas systems to modify several genomic loci in parallel, accelerating the construction and optimization of complex genetic circuits 1.
How It Works
In multiplex CRISPR editing, an array of guide RNAs — each targeting a different genomic site — is expressed alongside a Cas nuclease. The guides direct the nuclease to make cuts or modifications at all target sites simultaneously. This enables parallel gene knockouts, insertions, and regulatory modifications that would otherwise require sequential rounds of engineering.
Cong et al. demonstrated the first multiplex genome editing in mammalian cells, showing that co-delivery of multiple guide RNAs with Cas9 could modify several loci in a single experiment 1. For bacterial synthetic biology, Reis et al. developed nonrepetitive extra-long sgRNA arrays that enabled simultaneous repression of up to twelve genes using CRISPRi, avoiding the recombination problems that plague repetitive guide arrays 2.
Multiplex editing is particularly valuable for circuit construction because complex circuits require modifications at many loci — inserting circuit components, deleting competing pathways, and tuning regulatory elements. It is also essential for combinatorial pathway optimization, where libraries of modifications across multiple genes are screened to identify optimal configurations.
Computational Considerations
Guide RNA design algorithms score candidates for on-target efficiency and off-target specificity across the entire genome, using sequence features and machine learning models trained on large-scale editing datasets. Array design tools optimize guide ordering and spacing to minimize recombination between repetitive sequences. Combinatorial design-of-experiment frameworks plan multiplexed editing libraries that maximize coverage of the design space with minimal experimental effort 2.
Woolf Software builds computational tools for genetic circuit design and biological system simulation. Get in touch.
Computational guide RNA design tools score off-target activity across the genome and optimize multiplexed arrays for minimal crosstalk. Machine learning models predict editing efficiency at each locus to maximize simultaneous multi-site modification rates.
Related Terms
References
- Cong L, Ran FA, Cox D, et al.. Multiplex genome engineering using CRISPR/Cas systems . Science (2013) DOI
- Reis AC, Halper SM, Vezeau GE, Cetnar DP, Hossain A, Clauer PR, Salis HM.. Simultaneous repression of multiple bacterial genes using nonrepetitive extra-long sgRNA arrays . Nature Biotechnology (2019) DOI