Analysing long-read CRISPR experiments with CRISPRLungo

Long-read sequencing can characterize complex genome editing-induced DNA sequence changes such as large deletions, insertions and inversions that are difficult to detect using short-read sequencing. However, PCR amplification and sequencing errors complicate accurate variant detection, and existing analysis tools are not optimized for gene editing specific allelic outcomes. Here we present CRISPRLungo, a computational pipeline specifically designed for long-read amplicon sequencing of gene edited samples. CRISPRLungo incorporates unique molecular identifier-based error correction and statistical filtering to distinguish true editing events from background noise, enabling robust detection of small indels and structural variants. Through systematic benchmarking using simulated datasets, we demonstrate that CRISPRLungo outperforms existing approaches in both accuracy and read recovery. CRISPRLungo supports both Oxford Nanopore and PacBio platforms and identifies previously undetected structural variant edits such as inversions in published CRISPR datasets. To demonstrate allele-specific edit quantification, we applied CRISPRLungo to analyse edited primary cells from a patient harbouring compound heterozygous SBDS mutations, accurately quantifying SBDS editing outcomes despite contaminating reads from the homologous SBDSP1 pseudogene. To maximize accessibility, we developed a fully client-side web application requiring no installation, making advanced long-read analysis accessible to researchers regardless of computational expertise. CRISPRLungo is freely available at https://github.com/pinellolab/CRISPRLungo with a user-friendly web interface available at https://pinellolab.github.io/CRISPRLungo .

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Publication Details

Journal
Nature Biomedical Engineering
Published
2026-08-20
DOI
https://doi.org/10.1038/s41551-026-01776-7
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Analysing long-read CRISPR experiments with CRISPRLungo

Gue‐Ho Hwang, Akiko Shimamura, John Manis, Sébastien Levesque et al.
Nature Biomedical Engineering
CRISPR and Genetic Engineering
article

Analysing long-read CRISPR experiments with CRISPRLungo

Gue‐Ho Hwang, Akiko Shimamura, John Manis, Sébastien Levesque, Daniel E. Bauer, Timothy Barry, Benjamin Vyshedskiy, Luca Pinello, Jing Zeng
article en

Abstract

Long-read sequencing can characterize complex genome editing-induced DNA sequence changes such as large deletions, insertions and inversions that are difficult to detect using short-read sequencing. However, PCR amplification and sequencing errors complicate accurate variant detection, and existing analysis tools are not optimized for gene editing specific allelic outcomes. Here we present CRISPRLungo, a computational pipeline specifically designed for long-read amplicon sequencing of gene edited samples. CRISPRLungo incorporates unique molecular identifier-based error correction and statistical filtering to distinguish true editing events from background noise, enabling robust detection of small indels and structural variants. Through systematic benchmarking using simulated datasets, we demonstrate that CRISPRLungo outperforms existing approaches in both accuracy and read recovery. CRISPRLungo supports both Oxford Nanopore and PacBio platforms and identifies previously undetected structural variant edits such as inversions in published CRISPR datasets. To demonstrate allele-specific edit quantification, we applied CRISPRLungo to analyse edited primary cells from a patient harbouring compound heterozygous SBDS mutations, accurately quantifying SBDS editing outcomes despite contaminating reads from the homologous SBDSP1 pseudogene. To maximize accessibility, we developed a fully client-side web application requiring no installation, making advanced long-read analysis accessible to researchers regardless of computational expertise. CRISPRLungo is freely available at https://github.com/pinellolab/CRISPRLungo with a user-friendly web interface available at https://pinellolab.github.io/CRISPRLungo .

Nature Biomedical Engineering
Broad Institute (US), Brigham and Women's Hospital (US), Boston Children's Hospital (US), Harvard University (US), Massachusetts General Hospital (US), Dana-Farber Cancer Institute (US), Dana-Farber/Harvard Cancer Center (US), Center for Cancer Research (US), Harvard Stem Cell Institute (US), Hanyang University (KR)
Broad Institute, Manton Foundation, National Research Foundation, National Research Foundation of Korea, National Institutes of Health
Openalex Percentile: Top 17%
CRISPR and Genetic Engineering
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