Discrepancies in indel software resolution with somatic CRISPR/Cas9 tumorigenesis models

Area of Science:

• Genomic engineering and molecular biology.
• Cancer research, specifically tumor modeling.
• Bioinformatics and computational biology.

Background:

• CRISPR/Cas9 technology is a powerful tool for in vivo genomic engineering.
• Accurate characterization of insertions and deletions (indels) is crucial for CRISPR/Cas9 applications.
• Existing indel analysis software has not been systematically compared for somatic in vivo mouse models.

Purpose of the Study:

• To compare the performance of four different indel analysis software platforms.
• To evaluate software variability in analyzing CRISPR/Cas9-induced indels from somatic in vivo mouse models.
• To assess the impact of software choice on indel characterization in a malignant peripheral nerve sheath tumor (MPNST) model.

Main Methods:

• Utilized sequencing data from CRISPR/Cas9-mediated Nf1 gene editing in a mouse model.
• Applied four distinct publicly available indel analysis software platforms to the same dataset.
• Directly compared the number, size, and frequency of indels reported by each platform.

Main Results:

• Observed significant variability in indel detection across the four software platforms.
• Reported discrepancies in the number, size, and frequency of indels.
• Variability was particularly pronounced for larger indels, common in in vivo tumor models.

Conclusions:

• The choice of indel analysis software significantly impacts the interpretation of CRISPR/Cas9 editing outcomes.
• High variability necessitates careful selection of analysis platforms tailored to specific experimental contexts, especially for in vivo models.
• Findings underscore the need for standardized or validated methods for indel analysis in complex biological systems like tumor models.