Literature DB >> 34929203

Isling: A Tool for Detecting Integration of Wild-Type Viruses and Clinical Vectors.

Suzanne Scott1, Claus V Hallwirth2, Felix Hartkopf3, Susanna Grigson4, Yatish Jain5, Ian E Alexander6, Denis C Bauer7, Laurence O W Wilson8.   

Abstract

Detecting viral and vector integration events is a key step when investigating interactions between viral and host genomes. This is relevant in several fields, including virology, cancer research and gene therapy. For example, investigating integrations of wild-type viruses such as human papillomavirus and hepatitis B virus has proven to be crucial for understanding the role of these integrations in cancer. Furthermore, identifying the extent of vector integration is vital for determining the potential for genotoxicity in gene therapies. To address these questions, we developed isling, the first tool specifically designed for identifying viral integrations in both wild-type and vector from next-generation sequencing data. Isling addresses complexities in integration behaviour including integration of fragmented genomes and integration junctions with ambiguous locations in a host or vector genome, and can also flag possible vector recombinations. We show that isling is up to 1.6-fold faster and up to 170% more accurate than other viral integration tools, and performs well on both simulated and real datasets. Isling is therefore an efficient and application-agnostic tool that will enable a broad range of investigations into viral and vector integration. These include comparisons between integrations of wild-type viruses and gene therapy vectors, as well as assessing the genotoxicity of vectors and understanding the role of viruses in cancer. Crown
Copyright © 2021. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  bioinformatics; cancer; gene therapy; genotoxicity; virology

Mesh:

Year:  2021        PMID: 34929203     DOI: 10.1016/j.jmb.2021.167408

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  1 in total

1.  A bioinformatic pipeline for simulating viral integration data.

Authors:  Suzanne Scott; Susanna Grigson; Felix Hartkopf; Claus V Hallwirth; Ian E Alexander; Denis C Bauer; Laurence O W Wilson
Journal:  Data Brief       Date:  2022-04-10
  1 in total

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