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<p>Tracking-seq is a highly sensitive method for genome-wide detection of off-target effects in cells edited with diverse genome editing modalities, including Cas9, cytosine base editors, adenine base editors and prime editors. Since most genome editors induce DNA repair pathways and generate single-stranded DNA (ssDNA) intermediates, Tracking-seq leverages this process by tracking replication protein A—a key protein that binds and protects ssDNA—to identify on-target and off-target events. Here we provide a detailed protocol for Tracking-seq, covering genome editing of cells, extraction of replication protein A-bound ssDNA, sequencing library construction and data analysis using our custom computational tool Offtracker. Tracking-seq is applicable to various genome editing scenarios with low cell input, delivering high-performance results. The entire workflow, from genome editing to data analysis, can be completed within 1–2 weeks, making it a rapid solution for assessing genome-wide off-target activity.</p>

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Tracking-seq: a universal off-target detection approach for CRISPR–Cas genome editing

  • 期刊论文

  • 发表日期：

    2026年3月24日

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  • Runda Xu,
  • Tingting Cong,
  • Junsong Yuan,
  • Xuancheng Chen,
  • Yinqing Li,
  • Xun Lan,
  • Ming Zhu

摘要

Tracking-seq is a highly sensitive method for genome-wide detection of off-target effects in cells edited with diverse genome editing modalities, including Cas9, cytosine base editors, adenine base editors and prime editors. Since most genome editors induce DNA repair pathways and generate single-stranded DNA (ssDNA) intermediates, Tracking-seq leverages this process by tracking replication protein A—a key protein that binds and protects ssDNA—to identify on-target and off-target events. Here we provide a detailed protocol for Tracking-seq, covering genome editing of cells, extraction of replication protein A-bound ssDNA, sequencing library construction and data analysis using our custom computational tool Offtracker. Tracking-seq is applicable to various genome editing scenarios with low cell input, delivering high-performance results. The entire workflow, from genome editing to data analysis, can be completed within 1–2 weeks, making it a rapid solution for assessing genome-wide off-target activity.