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 language||English (US)|
|Journal||Proceedings of the National Academy of Sciences of the United States of America|
|State||Published - Jan 31 2017|
Bibliographical noteFunding Information:
This work was supported by the Sol Goldman Pancreatic Cancer Research Center and the Health, Empowerment, Research, and Awareness Women's Cancer Foundation (N.R.); a Burroughs Wellcome Fund Career Award for Biomedical Scientists Program (K.H.B.); US NIH Awards R01CA161210 (to J.D.B.), R01CA163705 (to K.H.B.), and R01GM103999 (to K.H.B.); as well as National Institute of General Medical Sciences Center for Systems Biology of Retrotransposition Grant P50GM107632 (to K.H.B. and J.D.B.).
- Ovarian cancer