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

Supplementary information

Reporting Summary

Supplementary Table 1

Spike-in model sequence and qPCR primer sequence

Supplementary Table 2

An output example for the enrichment significance test results; this file is related to Fig. 4 and Step 51

Generation of mouse–human chimeric embryos

Genome-wide quantification of transcription factor binding at single-DNA-molecule resolution using methyl-transferase footprinting

Generation of CRISPR–Cas9-mediated genetic knockout human intestinal tissue–derived enteroid lines by lentivirus transduction and single-cell cloning

A puromycin-dependent activity-based sensing probe for histochemical staining of hydrogen peroxide in cells and animal tissues

Decoding personal biotic and abiotic airborne exposome

A clinically relevant model of focal embolic cerebral ischemia by thrombus and thrombolysis in rhesus monkeys

Bioengineering human intestinal mucosal grafts using patient-derived organoids, fibroblasts and scaffolds

Biomimetic tail-to-head terpene cyclizations using the resorcin[4]arene capsule catalyst

Neuroscience robotics for controlled induction and real-time assessment of hallucinations

Scanorama: integrating large and diverse single-cell transcriptomic datasets

Single-cell RNA sequencing (scRNA-seq)（单细胞RNA测序）

Data integration（数据集成）

Heterogeneity（异质性）

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References

Supplementary information

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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

Supplementary information

Reporting Summary

Supplementary Table 1

Supplementary Table 2

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