# Computational tools for precision genome editing

> **NIH NIH R01** · BOSTON CHILDREN'S HOSPITAL · 2024 · $802,221

## Abstract

PROJECT SUMMARY
This project proposes to develop and refine computational tools to advance the safety and efficacy of genome
editing, addressing the critical need for precise quantification and prediction of on- and off-target effects. Genome
editing technologies have the potential to revolutionize the treatment and prevention of disease by enabling
precise modifications to DNA sequences. However, their clinical application is currently limited by significant
challenges in detecting and avoiding off-target effects, as well as quantifying and understanding the
heterogeneity of on-target edits. In Aim 1, we will enhance the capabilities of our recently developed tool,
CRISPRme, which predicts off-target effects across diverse human genomes. We propose to develop a new
tool, CRISPRus, which will leverage variation graphs, complete genomes, and pangenomes to provide a more
comprehensive understanding of potential off-target effects. Aim 2 will focus on the characterization of complex
on-target editing outcomes. We will develop and refine tools to enable accurate quantification from long-read
and single-anchor sequencing methods. This will provide a more detailed and nuanced understanding of the
outcomes of genome editing, including the potential for complex, multi-site edits. In Aim 3, we will tackle the
statistical challenges inherent in quantifying genome editing events. We propose to develop DE-CRISPR, a
comprehensive framework that will provide simulations and statistical models to assess the significance of editing
events at the locus, repair-pathway, and individual allele levels. This will enable researchers to design
experiments with adequate power to detect editing events and to interpret their results with greater confidence
and precision. Accompanying these aims, we will produce comprehensive benchmark datasets, including of 6
editing approaches in 6 donors; comparing nuclease, base, and prime editing; comparing approaches across a
range of anticipated specificity; targeting primary clinically relevant cells of unknown genotype (a real-world
scenario) and cell lines with complete telomere-to-telomere genome assemblies described. The deliverables of
this project, a comprehensive toolkit of computational tools including CRISPRus, CRISPRessoPE, CRISPRuni,
CRISPRlungo and DE-CRISPR, will empower researchers to more safely and effectively harness the power of
genome editing technologies. This work is essential to ensuring the robustness and reproducibility of genome
editing, ultimately promoting the safety and efficacy of therapeutic development. By addressing current
limitations in genome editing off-target prediction, complex edit characterization, and statistical analysis, we aim
to keep pace with advances in genome editing technology and contribute to the realization of its full therapeutic
potential.

## Key facts

- **NIH application ID:** 10905723
- **Project number:** 1R01HG013618-01
- **Recipient organization:** BOSTON CHILDREN'S HOSPITAL
- **Principal Investigator:** Daniel Evan Bauer
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $802,221
- **Award type:** 1
- **Project period:** 2024-07-15 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10905723

## Citation

> US National Institutes of Health, RePORTER application 10905723, Computational tools for precision genome editing (1R01HG013618-01). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10905723. Licensed CC0.

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