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Identification of Cancer Genes Based on De Novo Transposon Insertion Site Analysis Using RNA and DNA Sequencing

Aaron Sarver1,2

  • 1Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA. sarver@umn.edu.

Methods in Molecular Biology (Clifton, N.J.)
|December 14, 2018
PubMed

Insights

A new bioinformatics pipeline identifies cancer-causing transposon insertion sites in mouse genomes. This method aids in discovering novel cancer genes by analyzing both DNA and RNA sequencing data.

Area of Science:

  • Genetics
  • Bioinformatics
  • Cancer Research

Background:

  • Forward genetic screens using insertional mutagenesis are crucial for identifying cancer genes.
  • The Sleeping Beauty DNA transposon is widely used to induce mutations and cause cancer in murine models.
  • Accurate identification of transposon insertion sites is essential for cancer gene discovery.

Purpose of the Study:

  • To present a versatile bioinformatics pipeline for identifying transposon insertion sites.
  • To enable the detection of transposon-generated gene fusions in RNA sequencing data.
  • To facilitate direct identification of transposon insertion sites in DNA sequencing data.

Main Methods:

  • Development of a bioinformatics pipeline for analyzing sequencing data.
  • Application of the pipeline to RNA sequencing data for fusion identification.
  • Application of the pipeline to DNA sequencing data for direct insertion site identification.

Main Results:

  • The pipeline successfully identifies transposon-generated fusions in RNA-Seq data.
  • The pipeline accurately detects direct transposon insertion sites in DNA sequencing data.
  • The method is currently used to analyze Sleeping Beauty transposon insertions in the murine genome.

Conclusions:

  • The presented bioinformatics pipeline is effective for identifying transposon insertions.
  • This approach aids in the discovery of candidate cancer genes.
  • The method is adaptable for identifying any mobile genetic element in various genomes.
Keywords:
FusionInsertion siteRNA-SeqSeq-captureSequencingTransposon

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