Evidence map›Paper›PMID 32075555›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2020

Human transposon insertion profiling by sequencing (TIPseq) to map LINE-1 insertions in single cells.

Wilson McKerrow, Zuojian Tang, Jared P Steranka, Lindsay M Payer, Jef D Boeke, David Keefe, David Fenyö, Kathleen H Burns, Chunhong Liu

Open access · bronzeAbstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Crossroads between transposons and gene regulation.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Wilson McKerrowInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, USA.
Zuojian TangInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, USA.
Jared P SterankaDepartment of Pathology, Johns Hopkins University School of Medicine, 733N Broadway, Baltimore, MD 21205, USA.
Lindsay M PayerDepartment of Pathology, Johns Hopkins University School of Medicine, 733N Broadway, Baltimore, MD 21205, USA.
Jef D BoekeInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, USA.
David KeefeDepartment of Obstetrics and Gynecology, New York University Langone School of Medicine, 462 First Avenue, New York, NY 10016, USA.
David FenyöInstitute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, USA.
Kathleen H BurnsDepartment of Pathology, Johns Hopkins University School of Medicine, 733N Broadway, Baltimore, MD 21205, USA.
Chunhong LiuDepartment of Pathology, Johns Hopkins University School of Medicine, 733N Broadway, Baltimore, MD 21205, USA.
Johns Hopkins University · USNew York University · USNYU Langone Health · US

Funding

Somatic Activation of Retrotransposition: A New Molecular Mechanism of Aging?P01AG051449 · NIA · BROWN UNIVERSITY · PI Jef D BOEKE · 2016 to 2026
$30.4M
Exonizaton of Alu Insertion PolymorphismsR01GM124531 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI BURNS, KATHLEEN H, FLOREA, LILIANA D · 2017 to 2020
$1.3M
NIA NIH HHS P01 AG051449NIGMS NIH HHS R01 GM124531
6 · The paper itself

Abstract

Long interspersed element-1 (LINE-1, L1) sequences, which comprise about 17% of human genome, are the product of one of the most active types of mobile DNAs in modern humans. LINE-1 insertion alleles can cause inherited and de novo genetic diseases, and LINE-1-encoded proteins are highly expressed in some cancers. Genome-wide LINE-1 mapping in single cells could be useful for defining somatic and germline retrotransposition rates, and for enabling studies to characterize tumour heterogeneity, relate insertions to transcriptional and epigenetic effects at the cellular level, or describe cellular phylogenies in development. Our laboratories have reported a genome-wide LINE-1 insertion site mapping method for bulk DNA, named transposon insertion profiling by sequencing (TIPseq). There have been significant barriers applying LINE-1 mapping to single cells, owing to the chimeric artefacts and features of repetitive sequences. Here, we optimize a modified TIPseq protocol and show its utility for LINE-1 mapping in single lymphoblastoid cells. Results from single-cell TIPseq experiments compare well to known LINE-1 insertions found by whole-genome sequencing and TIPseq on bulk DNA. Among the several approaches we tested, whole-genome amplification by multiple displacement amplification followed by restriction enzyme digestion, vectorette ligation and LINE-1-targeted PCR had the best assay performance. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

Indexed as

Mutagenesis, InsertionalCell LineDNA Transposable ElementsHumansLong Interspersed Nucleotide ElementsSequence Analysis, DNASingle-Cell AnalysisDNA Transposable Elementsmobile genetic elementretrotransposonsomatic mosaicismTIPseqtumour heterogeneitywhole-genome amplification

Identifiers

PMID32075555
PMCPMC7061987
OpenAlexW3004433656

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.