IS-Seq: a bioinformatics pipeline for integration sites analysis with comprehensive abundance quantification methods.

Area of Science:

• Bioinformatics
• Gene Therapy
• Genomics

Background:

• Integration site (IS) analysis is essential for evaluating gene therapy (GT) safety and efficacy in preclinical and clinical studies.
• Existing bioinformatics pipelines for IS analysis have limitations, particularly in incorporating unique molecular identifiers (UMIs) for accurate abundance estimation.
• There is a need for integrated pipelines that can handle diverse IS retrieval methods and offer multiple quantification options.

Purpose of the Study:

• To develop and present IS-Seq, a novel bioinformatics pipeline for comprehensive IS analysis.
• To enable processing of data from both restriction site-based and sonication-based IS retrieval methods.
• To provide and compare various abundance estimation methods, including UMI-based quantification.

Main Methods:

• IS-Seq processes paired-end sequencing data from various IS retrieval methods.
• The pipeline supports multiple abundance estimation techniques: read-based, fragment-based, and UMI-based.
• Performance was validated against the INSPIIRED workflow and through simulation studies and wet-lab assessments.

Main Results:

• IS-Seq successfully processes data from diverse IS collection methods.
• The pipeline integrates read-based, fragment-based, and UMI-based abundance estimation.
• UMI quantification demonstrated superior accuracy compared to sonication fragment counts in clinically relevant scenarios.

Conclusions:

• IS-Seq offers a versatile and integrated platform for IS analysis in gene therapy research.
• Unique molecular identifier (UMI) quantification provides more accurate IS abundance estimations than traditional sonication fragment counts.
• The developed pipeline aids in the safety and efficacy assessment of gene therapy applications.