Evidence map›Paper›PMID 31568525›Full record

ArticlePLoS computational biology2019

Telescope: Characterization of the retrotranscriptome by accurate estimation of transposable element expression.

Matthew L Bendall, Miguel de Mulder, Luis Pedro Iñiguez, Aarón Lecanda-Sánchez, Marcos Pérez-Losada, Mario A Ostrowski, R Brad Jones, Lubbertus C F Mulder, Gustavo Reyes-Terán, Keith A Crandall and 2 more

Abstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 136 papers.

0numbers the graph read from it
0cells of the map it votes in
136citing papers in PubMed
–field-weighted citation impact
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

136 citing papers in PubMed.

  1. Trial
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  11. Characterization of Cellular Senescence in Primary Human Astrocytes.bioRxiv : the preprint server for biology · 2026
    Article
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76 more citing papers are in PubMed but not listed here.

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

12 authors.

Matthew L BendallComputational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America.ORCID 0000-0001-9816-5425
Miguel de MulderDivision of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America.ORCID 0000-0002-8026-7076
Luis Pedro IñiguezDivision of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America.ORCID 0000-0002-1470-9024
Aarón Lecanda-SánchezCenter for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.
Marcos Pérez-LosadaComputational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America.
Mario A OstrowskiDepartment of Immunology, University of Toronto, Toronto, Ontario, Canada.ORCID 0000-0002-7369-1936
R Brad JonesDivision of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America.
Lubbertus C F MulderDepartment of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Gustavo Reyes-TeránCenter for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.
Keith A CrandallComputational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America.ORCID 0000-0002-0836-3389
Christopher E OrmsbyCenter for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.
Douglas F NixonDivision of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America.ORCID 0000-0002-2801-1786

Funding

SWG 2: Cure Research Scientific Working GroupP30AI117970 · NIAID · GEORGE WASHINGTON UNIVERSITY · PI Italo Mocchetti · 2015 to 2026
$29.6M
Clinical and Translational Science Institute at Childrens NationalUL1TR001876 · NCATS · CHILDREN'S RESEARCH INSTITUTE · PI BELL, MICHAEL J · 2016 to 2021
$25.6M
Human Endogenous Retroelements in HIV ImmunopathogenesisR01AI076059 · NIAID · WEILL MEDICAL COLL OF CORNELL UNIV · PI NIXON, DOUGLAS F · 2009 to 2017
$3.9M
HIV induced anti-cancer HERV immunity in prostate, breast and colon cancersR01CA206488 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI NIXON, DOUGLAS F · 2016 to 2020
$2.2M
Impact of HERV-K expression on HIV-1 life cycleR01GM113886 · NIGMS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MULDER, LUBBERTUS C · 2014 to 2018
$1.8M
NCATS NIH HHS UL1 TR001876NCI NIH HHS R01 CA206488NIAID NIH HHS P30 AI117970NIAID NIH HHS R01 AI076059NIGMS NIH HHS R01 GM113886
6 · The paper itself

Abstract

Characterization of Human Endogenous Retrovirus (HERV) expression within the transcriptomic landscape using RNA-seq is complicated by uncertainty in fragment assignment because of sequence similarity. We present Telescope, a computational software tool that provides accurate estimation of transposable element expression (retrotranscriptome) resolved to specific genomic locations. Telescope directly addresses uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model. We demonstrate the utility of our approach through single locus analysis of HERV expression in 13 ENCODE cell types. When examined at this resolution, we find that the magnitude and breadth of the retrotranscriptome can be vastly different among cell types. Furthermore, our approach is robust to differences in sequencing technology and demonstrates that the retrotranscriptome has potential to be used for cell type identification. We compared our tool with other approaches for quantifying transposable element (TE) expression, and found that Telescope has the greatest resolution, as it estimates expression at specific TE insertions rather than at the TE subfamily level. Telescope performs highly accurate quantification of the retrotranscriptomic landscape in RNA-seq experiments, revealing a differential complexity in the transposable element biology of complex systems not previously observed. Telescope is available at https://github.com/mlbendall/telescope.

Indexed as

SoftwareCell LineComputational BiologyCytological TechniquesDNA Transposable ElementsEndogenous RetrovirusesGene Expression ProfilingHumansOrgan SpecificitySequence Analysis, RNATranscriptomeDNA Transposable Elements

Identifiers

PMID31568525
PMCPMC6786656

What OpenQuestion holds

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Registered trials

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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.