BATCH-GE: Analysis of NGS Data for Genome Editing Assessment

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 system is widely adopted for genomic locus modification across diverse model systems.
• CRISPR-Cas9 facilitates genome-wide interrogation of gene function, driving advancements in life sciences and potential clinical applications.

Purpose of the Study:

• To introduce BATCH-GE, a bioinformatics tool designed for analyzing next-generation sequencing (NGS) data from genome editing experiments.
• To provide a flexible and user-friendly solution for processing large datasets generated by CRISPR-Cas9 applications.

Main Methods:

• Utilized next-generation sequencing (NGS) to generate high-throughput data from CRISPR-Cas9 experiments.
• Developed and applied the BATCH-GE bioinformatics tool for the analysis of NGS reads.
• Implemented algorithms to detect indel mutations and other precise genome editing events.

Main Results:

• BATCH-GE effectively detects and reports various genome editing events, including indel mutations.
• The tool calculates mutagenesis efficiencies for numerous samples concurrently.
• Demonstrated the tool's utility in handling large volumes of NGS data from genome editing studies.

Conclusions:

• BATCH-GE is a valuable and efficient tool for analyzing NGS data in the context of CRISPR-Cas9 genome editing.
• The software facilitates the exploration of CRISPR-Cas9 experimental outcomes, supporting fundamental research and clinical translation.
• The availability of user-friendly bioinformatics tools like BATCH-GE is crucial for advancing genome editing research.