| Literature DB >> 28096347 |
Zuojian Tang1,2, Jared P Steranka3,4, Sisi Ma1, Mark Grivainis1,2, Nemanja Rodić3, Cheng Ran Lisa Huang4, Ie-Ming Shih3,5, Tian-Li Wang3, Jef D Boeke6, David Fenyö7,2, Kathleen H Burns8,4.
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 high-grade ovarian serous carcinoma.Entities:
Keywords: LINE-1; TIPseq; human; ovarian cancer; retrotransposon
Mesh:
Year: 2017 PMID: 28096347 PMCID: PMC5293032 DOI: 10.1073/pnas.1619797114
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205