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

Hum Gene Ther Methods. 2012 Apr;23(2):111-8. doi: 10.1089/hgtb.2011.219. Epub 2012 May 4.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology / methods*
  • Genetic Therapy / methods*
  • Genetic Vectors / genetics*
  • High-Throughput Nucleotide Sequencing / methods*
  • High-Throughput Nucleotide Sequencing / trends
  • Humans
  • Lentivirus / genetics*
  • Mice
  • Rats
  • Software*
  • Virus Integration / genetics*