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

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 114; no. 5; pp. E733 - E740
• Main Authors: Tang, Zuojian, Steranka, Jared P., Ma, Sisi, Grivainis, Mark, Rodić, Nemanja, Huang, Cheng Ran Lisa, Shih, Ie-Ming, Wang, Tian-Li, Boeke, Jef D., Fenyö, David, Burns, Kathleen H.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 31.01.2017
• Series: PNAS Plus
• Subjects: Biological Sciences; Genomes; Mammals; Mutation; Ovarian cancer; PNAS Plus; Reliability; LINE-1; retrotransposon; TIPseq; ovarian cancer; human
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1619797114

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 high-grade ovarian serous carcinoma.