Abstract
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 method for the off-target evaluation of programmable cytosine base editors. It profiles the editome by tracing the editing intermediate dU, which is introduced inside living cells and edited by programmable cytosine base editors. The genomic DNA is extracted, preprocessed and labeled by successive chemical and enzymatic reactions, followed by biotin pull-down to enrich the dU-containing loci for sequencing. Here, we describe a detailed protocol for performing the Detect-seq experiment, and a customized, open-source, bioinformatic pipeline for analyzing the characteristic Detect-seq data is also provided. Unlike those previous whole-genome sequencing-based methods, Detect-seq uses an enrichment strategy and hence is endowed with great sensitivity, a higher signal-to-noise ratio and no requirement for high sequencing depth. Furthermore, Detect-seq is widely applicable for both mitotic and postmitotic biological systems. The entire protocol typically takes 5 d from the genomic DNA extraction to sequencing and ~1 week for data analysis.
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Code availability
All custom codes for Detect-seq data analysis are deposited in GitHub (https://github.com/menghaowei/Detect-seq). To make it easier to repeat the data analysis process of Detect-seq, we also provide Snakemake workflow scripts in the GitHub repository.
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Acknowledgements
Bioinformatics analysis was performed on the High-Performance Computing Platform of the School of Life Sciences and High-Performance Computing Platform of the Center for Life Science. This work was supported by the National Key R&D Program (2019YFA0110900 and 2019YFA0802200), National Natural Science Foundation of China (nos. 21825701, 91953201, 92153303 and 22107006) and China Postdoctoral Science Foundation (2021M700238).
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Z.L., H.M. and C.Y. conceived and led the research. Z.L, H.M. and C.Y. wrote the manuscript with the help of X.R. and H.Z.
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Peking University has filed patent applications on Detect-seq described in this study, listing Z.L., H.M. and C.Y. as inventors.
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Nature Protocols thanks Sangsu Bae, Hui Yang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Key references using this protocol
Lei, Z. et al. Nat. Methods 18, 643–651 (2021): https://doi.org/10.1038/s41592-021-01172-w
Lei, Z. et al. Nature 606, 804–811 (2022): https://doi.org/10.1038/s41586-022-04836-5
Supplementary information
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
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Lei, Z., Meng, H., Rao, X. et al. Detect-seq, a chemical labeling and biotin pull-down approach for the unbiased and genome-wide off-target evaluation of programmable cytosine base editors. Nat Protoc 18, 2221–2255 (2023). https://doi.org/10.1038/s41596-023-00837-4
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DOI: https://doi.org/10.1038/s41596-023-00837-4
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