Deploying MMEJ using MENdel in precision gene editing applications for gene therapy and functional genomics

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Non-homologous end joining (NHEJ) is a common but error-prone DNA repair pathway following double-strand breaks (DSBs).
• Microhomology-mediated end joining (MMEJ) offers more predictable outcomes for gene editing applications.
• Accurate prediction of MMEJ events is crucial for functional genomics and therapeutic development.

Purpose of the Study:

• To compare the efficacy of existing algorithms (MENTHU, inDelphi, Lindel) in predicting MMEJ-repaired genotypes (PreMAs).
• To develop a novel, more accurate algorithm for predicting MMEJ repair outcomes.
• To estimate the frequency of targetable DSBs for gene discovery and therapeutic applications.

Main Methods:

• Evaluated MENTHU, inDelphi, and Lindel on a dataset of 5,885 Cas9-mediated DSB repair events in mouse embryonic stem cells.
• Developed MENdel by combining MENTHU and Lindel algorithms.
• Assessed the frequency of frameshift-inducing DSBs in vertebrate coding regions using MENdel.

Main Results:

• MENTHU identified 46% of PreMAs, significantly outperforming inDelphi and Lindel.
• Lindel uniquely predicted single-base insertions.
• The novel MENdel algorithm demonstrated superior predictive coverage of homogeneous out-of-frame mutations.
• MENdel analysis revealed a high frequency (87-91%) of early frameshift-inducing DSBs in vertebrate coding regions.

Conclusions:

• MENdel provides a significant advancement in predicting MMEJ repair outcomes for gene editing.
• The algorithm facilitates large-scale reverse genetics screening by enabling MMEJ at scale.
• MENdel's predictive power supports the viability of loss-of-function gene editing therapeutics.