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Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library

Identification of Functionally-Relevant Lentivirus Integration Sites in an Insertional Mutagenesis Cell Library

Published on: January 10, 2025

γ-TRIS: a graph-algorithm for comprehensive identification of vector genomic insertion sites.

Andrea Calabria¹, Stefano Beretta^2,3, Ivan Merelli³

¹San Raffaele Telethon Institute for Gene Therapy (SR-Tiget), IRCCS San Raffaele Scientific Institute, via Olgettina 60, 20132, Milan, Italy.

Bioinformatics (Oxford, England)

|October 8, 2019

Summary

This summary is machine-generated.

A new tool, gamma-TRIS, accurately identifies retroviral insertion sites in challenging genomic regions. This improves clonal tracking accuracy in gene therapy and viral infection studies.

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Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Published on: March 22, 2016

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Retroviral vectors integrate into host genomes, creating genetic marks essential for tracking cells in gene therapy and viral infections.
Accurate identification of retroviral insertion sites is crucial for monitoring genetically modified cells in vivo.
Current methods struggle with insertions in low complexity or repetitive genomic regions, leading to data loss and reduced study accuracy.

Purpose of the Study:

To develop a novel bioinformatics tool for identifying retroviral insertion sites, particularly in challenging genomic regions.
To improve the accuracy and predictive power of clonal tracking studies in gene therapy and viral infection research.

Main Methods:

Development of gamma-TRIS, a graph-based, genome-free alignment tool.
Utilizing gamma-TRIS to reanalyze existing clinical study data.

Main Results:

Gamma-TRIS successfully identifies retroviral insertion sites within low complexity and repetitive genomic regions.
Reanalysis of clinical studies using gamma-TRIS demonstrated enhanced clonal quantification and tracking capabilities.
Improved accuracy in mapping viral integration sites, overcoming limitations of previous methods.

Conclusions:

Gamma-TRIS offers a significant advancement in identifying retroviral insertion sites, especially in previously intractable genomic areas.
The tool enhances the reliability and scope of clonal tracking in gene therapy and viral infection monitoring.
This improved methodology facilitates more accurate assessments of therapeutic efficacy and disease progression.