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Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer

  • Zuojian Tang
  • , Jared P. Steranka
  • , Sisi Ma
  • , Mark Grivainis
  • , Nemanja Rodić
  • , Cheng Ran Lisa Huang
  • , Ie Ming Shih
  • , Tian Li Wang
  • , Jef D. Boeke*
  • , David Fenyö
  • , Kathleen H. Burns
  • *Corresponding author for this work
  • New York University
  • Johns Hopkins University
  • University of Minnesota Twin Cities
  • Yale University
  • Atlas Venture

Research output: Contribution to journal › Journal Article › peer-review

79 Scopus citations

Abstract

Mammalian genomes are replete with interspersed repeats reflecting the activity of transposable elements. These mobile DNAs are self-propagating, and their continued transposition is a source of both heritable structural variation as well as somatic mutation in human genomes. Tailored approaches to map these sequences are useful to identify insertion alleles. Here, we describe in detail a strategy to amplify and sequence long interspersed element-1 (LINE-1, L1) retrotransposon insertions selectively in the human genome, transposon insertion profiling by next-generation sequencing (TIPseq). We also report the development of a machine-learning-based computational pipeline, TIPseqHunter, to identify insertion sites with high precision and reliability. We demonstrate the utility of this approach to detect somatic retrotransposition events in highgrade ovarian serous carcinoma.

Original languageEnglish
Pages (from-to)E733-E740
JournalProceedings of the National Academy of Sciences of the United States of America
Volume114
Issue number5
DOIs
StatePublished - 31 01 2017
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Human
  • LINE-1
  • Ovarian cancer
  • Retrotransposon
  • TIPseq

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