Detect-seq, a chemical labeling and biotin pull-down approach for the unbiased and genome-wide off-target evaluation of programmable cytosine base editors

Zhixin Lei, Haowei Meng, Xichen Rao, Huanan Zhao, Chengqi Yi

Published: 2023-06-04 DOI: 10.1038/s41596-023-00837-4

Cytosine Base Editors

Detect-seq

Off-target Evaluation

Enrichment Strategy

Bioinformatic Pipeline

AI 解读

Extraction of nuclei from archived postmortem tissues for single-nucleus sequencing applications

High-quality and robust protein quantification in large clinical/pharmaceutical cohorts with IonStar proteomics investigation

Longitudinal interrogation of sympathetic neural circuits and hemodynamics in preclinical models

Experimental modulation of physiological force application on leg joint neurons in intactDrosophila melanogaster

Combining surface-accessible Ag and Au colloidal nanomaterials with SERS for in situ analysis of molecule–metal interactions in complex solution environments

Generation of mouse–human chimeric embryos

Labeling and tracking of immune cells in ex vivo human skin

Large-scale preparation of fluorescence multiplex host cell reactivation (FM-HCR) reporters

Mutate-and-chemical-shift-fingerprint (MCSF) to characterize excited states in RNA using NMR spectroscopy

Comprehensive multi-attribute method workflow for biotherapeutic characterization and current good manufacturing practices testing

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Programmable cytosine base editors show promising approaches for correcting pathogenic mutations; yet, their off-target effects have been of great concern. Detect-seq (dU-detection enabled by C-to-T transition during sequencing) is an unbiased, sensitive
Introduction
Materials
Procedure
Troubleshooting
Timing
Anticipated results
References
ACKNOWLEDGMENTS

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Detect-seq, a chemical labeling and biotin pull-down approach for the unbiased and genome-wide off-target evaluation of programmable cytosine base editors

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