Transposon insertion profiling by sequencing (TIPseq) for mapping LINE-1 insertions in the human genome View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Jared P. Steranka, Zuojian Tang, Mark Grivainis, Cheng Ran Lisa Huang, Lindsay M. Payer, Fernanda O. R. Rego, Thiago Luiz Araujo Miller, Pedro A. F. Galante, Sitharam Ramaswami, Adriana Heguy, David Fenyö, Jef D. Boeke, Kathleen H. Burns

ABSTRACT

Background: Transposable elements make up a significant portion of the human genome. Accurately locating these mobile DNAs is vital to understand their role as a source of structural variation and somatic mutation. To this end, laboratories have developed strategies to selectively amplify or otherwise enrich transposable element insertion sites in genomic DNA. Results: Here we describe a technique, Transposon Insertion Profiling by sequencing (TIPseq), to map Long INterspersed Element 1 (LINE-1, L1) retrotransposon insertions in the human genome. This method uses vectorette PCR to amplify species-specific L1 (L1PA1) insertion sites followed by paired-end Illumina sequencing. In addition to providing a step-by-step molecular biology protocol, we offer users a guide to our pipeline for data analysis, TIPseqHunter. Our recent studies in pancreatic and ovarian cancer demonstrate the ability of TIPseq to identify invariant (fixed), polymorphic (inherited variants), as well as somatically-acquired L1 insertions that distinguish cancer genomes from a patient's constitutional make-up. Conclusions: TIPseq provides an approach for amplifying evolutionarily young, active transposable element insertion sites from genomic DNA. Our rationale and variations on this protocol may be useful to those mapping L1 and other mobile elements in complex genomes. More... »

PAGES

8

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13100-019-0148-5

DOI

http://dx.doi.org/10.1186/s13100-019-0148-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112646020

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30899333


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13100-019-0148-5'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13100-019-0148-5'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13100-019-0148-5'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13100-019-0148-5'


 

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295 Institute for Systems Genetics, NYU Langone Health, 10016, New York, NY, USA
296 rdf:type schema:Organization
297 https://www.grid.ac/institutes/grid.21107.35 schema:alternateName Johns Hopkins University
298 schema:name Department of Pathology, Johns Hopkins University School of Medicine, 21205, Baltimore, MD, USA
299 McKusick–Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 21205, Baltimore, MD, USA
300 rdf:type schema:Organization
301 https://www.grid.ac/institutes/grid.413471.4 schema:alternateName Hospital Sírio-Libanês
302 schema:name Centro de Oncologia Molecular, Hospital Sírio-Libanês, São Paulo, Brazil
303 Departamento de Bioquímica, Instituto de Química, Universidade de São Paul, São Paulo, Brazil
304 rdf:type schema:Organization
 




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