Predicting CRISPR-Cas12a guide efficiency for targeting using machine learning

Genome editing through the development of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeat)–Cas technology has revolutionized many fields in biology. Beyond Cas9 nucleases, Cas12a (formerly Cpf1) has emerged as a promising alternative to Cas9 for editing AT-rich genomes. Despite the...

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Bibliographic Details
Published in:PloS one 2023-10, Vol.18 (10), p.e0292924-e0292924
Main Authors: O'Brien, Aidan, Bauer, Denis C, Burgio, Gaetan
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Analysis
Biology and Life Sciences
Computer and Information Sciences
Computer applications
CRISPR
Datasets
DNA binding proteins
Editing
Efficiency
Engineering and Technology
Enzymes
Genome editing
Genomes
Genomics
Learning algorithms
Machine learning
Mutation
Nuclease
Nucleases
Nucleotides
Physical Sciences
Research and Analysis Methods
Ribonucleic acid
RNA
Software
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Summary:Genome editing through the development of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeat)–Cas technology has revolutionized many fields in biology. Beyond Cas9 nucleases, Cas12a (formerly Cpf1) has emerged as a promising alternative to Cas9 for editing AT-rich genomes. Despite the promises, guide RNA efficiency prediction through computational tools search still lacks accuracy. Through a computational meta-analysis, here we report that Cas12a target and off-target cleavage behavior are a factor of nucleotide bias combined with nucleotide mismatches relative to the protospacer adjacent motif (PAM) site. These features helped to train a Random Forest machine learning model to improve the accuracy by at least 15% over existing algorithms to predict guide RNA efficiency for the Cas12a enzyme. Despite the progresses, our report underscores the need for more representative datasets and further benchmarking to reliably and accurately predict guide RNA efficiency and off-target effects for Cas12a enzymes.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0292924