eTALED_computational_analysis

This project provides relavant code for analyzing the efficient ABE of mitochondrial DNA

Author: Bao-Qing Gao

Email: gaobaoqing2019@sibs.ac.cn

---

1. Features

• Editing Efficiency Calculation scripts_for_base_substitution_analysis: Evaluates engineered ABE editing efficiency at target sites with the deep sequencing data.
• RNA Off-Target Effect Analysis scripts_for_RNA_editing_analysis: Detects potential off-target editing events with the whole-transcriptome sequencing data.
• Whole Nuclear Genome Off-Target Effect Analysis scripts_for_genome_editing_analysis: Detects potential off-target editing events with the whole nuclear genome sequencing data.
• Whole Mitochondrial Genome Off-Target Effect Analysis scripts_for_mitochondrial_genome_editing_analysis: Detects potential off-target editing events in whole mitochondrial genome with the deep sequencing data.

---

2. Prerequisites

Before running this analysis, install the following tools:

• CFBI: https://github.com/YangLab/CFBI
• RADAR: https://github.com/YangLab/RADAR
• BEIDOU: https://github.com/YangLab/BEIDOU

---

3. Usage

PART 1: Editing Efficiency Calculation

• Directory: scripts_for_base_substitution_analysis

  All original deep sequencing data used in this study can be accessed at the NCBI BioProject under the accession code PRJNA1223321. The provided code here serves as an example for reference.

• Constructing Index Files

  Before running the analysis, you need to construct index files. Refer to the index/ directory, which contains:

  • 20240220_deepseq_sample_name_mapping.csv:

    ID	Sample 1	Target site 1	Sample 2	Target site 2	...

  • ref_20240220.txt:

    Information
    Target site 1
    Sequence of target site 1
    Editing window for target site 1: Editing window sequence 1
    None
    None
    Target site 2
    Sequence of target site 2
    Editing window for target site 2: Editing window sequence 2
    None
    None
    ...

• Calculating Editing Efficiency

  Run

  sh CFBI_main.sh
  

PART 2: RNA Off-Target Effect Analysis

• Directory: scripts_for_RNA_editing_analysis

  All original whole-transcriptome sequencing data used in this study can be accessed at the NCBI BioProject under the accession code PRJNA1221787. The provided code here serves as an example for reference.

• Quality Control & Trim Reads

  Run

  sh work_QC_Trim.sh
  

• Whole-Transcriptome Off-Target Effect Analysis

  Run

  sh work_RADAR_parallel.sh
  

PART 3: Whole Nuclear Genome Off-Target Effect Analysis

• Directory: scripts_for_nuclear_genome_editing_analysis

  All original whole-genome sequencing data used in this study can be accessed at the NCBI BioProject under the accession code PRJNA1221509. The provided code here serves as an example for reference.

• Quality Control & Trim Reads

  Run

  sh work_QC_Trim.sh
  

• Whole Nuclear Genome Off-Target Effect Analysis

  Run

  sh work_BEIDOU.sh
  
  

PART 4: Whole Mitochondrial Genome Off-Target Effect Analysis

• Directory: scripts_for_mitochondrial_genome_editing_analysis

  All original deep sequencing data used in this study can be accessed at the NCBI BioProject under the accession code PRJNA1223321. The provided code here serves as an example for reference.

• Preparing Input Files

  Before running the analysis, you need to prepare input files. Refer to the input_files/ directory, which contains:

  • CFBI_output_files_test: The CFBI outputs from PART 1 were used to calculate mitochondrial genome-wide average off-target editing frequency. CFBI output files for several samples are provided in this directory for testing.

  • sample_edit_site.txt:

    Sample ID	Editing positon	Editing window

• Calculating Average Off-target Editing Frequency

  Run

  Rscript mit_offtarget.r
  

---

4. Citation

Fan Y#, Xu W#, Gao BQ#, Qin H, Wu X, Wei J, Ni Q, Zhou L, Xiang J, Wu J, Yang B, Yang L and Chen J*. Leveraging base excision repair for efficient adenine base editing of mitochondrial DNA. Nat Biotechnol, 2025 (Accepted in principle).