Bioinformatic clonality analysis of next-generation sequencing-derived viral vector integration sites

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Anne Arens - , German Cancer Research Center (DKFZ) (Author)
  • Jens Uwe Appelt - , German Cancer Research Center (DKFZ) (Author)
  • Cynthia C. Bartholomae - , German Cancer Research Center (DKFZ) (Author)
  • Richard Gabriel - , German Cancer Research Center (DKFZ) (Author)
  • Anna Paruzynski - , German Cancer Research Center (DKFZ) (Author)
  • Derek Gustafson - , German Cancer Research Center (DKFZ) (Author)
  • Nathalie Cartier - , Université Paris Cité (Author)
  • Patrick Aubourg - , Université Paris Cité (Author)
  • Annette Deichmann - , German Cancer Research Center (DKFZ) (Author)
  • Hanno Glimm - , German Cancer Research Center, partner site Dresden, National Center for Tumor Diseases Dresden, National Center for Tumor Diseases (NCT) Heidelberg (Author)
  • Christof Von Kalle - , German Cancer Research Center (DKFZ) (Author)
  • Manfred Schmidt - , German Cancer Research Center (DKFZ) (Author)

Abstract

Clonality analysis of viral vector-transduced cell populations represents a convincing approach to dissect the physiology of tissue and organ regeneration, to monitor the fate of individual gene-corrected cells in vivo, and to assess vector biosafety. With the decoding of mammalian genomes and the introduction of next-generation sequencing technologies, the demand for automated bioinformatic analysis tools that can rapidly process and annotate vector integration sites is rising. Here, we provide a publicly accessible, graphical user interface-guided automated bioinformatic high-throughput integration site analysis pipeline. Its performance and key features are illustrated on pyrosequenced linear amplification-mediated PCR products derived from one patient previously enrolled in the first lentiviral vector clinical gene therapy study. Analysis includes trimming of vector genome junctions, alignment of genomic sequence fragments to the host genome for the identification of integration sites, and the annotation of nearby genomic elements. Most importantly, clinically relevant features comprise the determination of identical integration sites with respect to different time points or cell lineages, as well as the retrieval of the most prominent cell clones and common integration sites. The resulting output is summarized in tables within a convenient spreadsheet and can be further processed by researchers without profound bioinformatic knowledge.

Details

Original languageEnglish
Pages (from-to)111-118
Number of pages8
JournalHuman gene therapy : Methods
Volume23
Issue number2
Publication statusPublished - 1 Apr 2012
Peer-reviewedYes

External IDs

PubMed 22559057
ORCID /0009-0003-2782-8190/work/198593735