Evidence map›Paper›PMID 33355230›Full record

ArticleGenome research2021

Transcript assembly improves expression quantification of transposable elements in single-cell RNA-seq data.

Wanqing Shao, Ting Wang

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed, 60 citations in OpenAlex.

  1. Review
  2. Article
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  5. Review
  6. Article
  7. Efficient profiling of total RNA in single cells with STORM-seq.bioRxiv : the preprint server for biology · 2025
    Article
  8. Article
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  12. Article
  13. Review
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  17. Review
  18. Article
  19. Article
  20. Transposon control as a checkpoint for tissue regeneration.Development (Cambridge, England) · 2022
    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

2 authors at 2 institutions in 1 country.

Wanqing ShaoDepartment of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA.ORCID 0000-0003-4234-2095
Ting WangDepartment of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA.ORCID 0000-0002-6800-242X
James S. McDonnell Foundation · USWashington University in St. Louis · US

Funding

Generation of novel cell type specific mouse genetic toolsU19MH114830 · NIMH · ALLEN INSTITUTE · PI ZENG, HONGKUI · 2017 to 2021
$64.7M
The WashU-UCSC-EBI Human Genome Reference Center."U41HG010972 · NHGRI · WASHINGTON UNIVERSITY · PI Ting Wang · 2019 to 2026
$24.9M
GENCODE: comprehensive reference genome annotation for human and mouseU24HG007234 · NHGRI · EUROPEAN MOLECULAR BIOLOGY LABORATORY · PI Fergal James Martin · 2021 to 2026
$16.1M
Center for Integrated Multi-modal and Multi-scale Nucleome ResearchUM1HG011585 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DULAC, CATHERINE, LEIN, ED · 2020 to 2024
$6.7M
THE WASHU TARGET ENVIRONMENTAL EPIGENOMICS DATA COORDINATION CENTERU24ES026699 · NIEHS · WASHINGTON UNIVERSITY · PI WANG, TING · 2016 to 2021
$5.2M
RESEARCH EDUCATION PROGRAM ON COMPUTATIONAL AND STATISTICAL TOOL DEVELOPMENT FOR ADDICTION GENETICSR25DA027995 · NIDA · WASHINGTON UNIVERSITY · PI MADDEN, PAMELA ANN, RICE, JOHN P. · 2009 to 2019
$4.3M
DECODING THE IMPACT OF TRANSPOSABLE ELEMENTS ON GENE REGULATIONR01HG007175 · NHGRI · WASHINGTON UNIVERSITY · PI WANG, TING · 2014 to 2021
$2.7M
Connecting transposable elements and regulatory innovation using ENCODE dataU01HG009391 · NHGRI · WASHINGTON UNIVERSITY · PI COHEN, BARAK A, FESCHOTTE, CEDRIC · 2017 to 2021
$2.4M
The WashU 4DN Network Data Coordination and Integration CenterU01CA200060 · NCI · WASHINGTON UNIVERSITY · PI WANG, TING · 2015 to 2019
$1.9M
NCI NIH HHS U01 CA200060NHGRI NIH HHS R01 HG007175NHGRI NIH HHS U01 HG009391NHGRI NIH HHS U24 HG007234NHGRI NIH HHS U41 HG010972NHGRI NIH HHS UM1 HG011585NIDA NIH HHS R25 DA027995NIEHS NIH HHS U24 ES026699NIMH NIH HHS U19 MH114830
6 · The paper itself

Abstract

Transposable elements (TEs) are an integral part of the host transcriptome. TE-containing noncoding RNAs (ncRNAs) show considerable tissue specificity and play important roles during development, including stem cell maintenance and cell differentiation. Recent advances in single-cell RNA-seq (scRNA-seq) revolutionized cell type-specific gene expression analysis. However, effective scRNA-seq quantification tools tailored for TEs are lacking, limiting our ability to dissect TE expression dynamics at single-cell resolution. To address this issue, we established a TE expression quantification pipeline that is compatible with scRNA-seq data generated across multiple technology platforms. We constructed TE-containing ncRNA references using bulk RNA-seq data and showed that quantifying TE expression at the transcript level effectively reduces noise. As proof of principle, we applied this strategy to mouse embryonic stem cells and successfully captured the expression profile of endogenous retroviruses in single cells. We further expanded our analysis to scRNA-seq data from early stages of mouse embryogenesis. Our results illustrated the dynamic TE expression at preimplantation stages and revealed 146 TE-containing ncRNA transcripts with substantial tissue specificity during gastrulation and early organogenesis.

Indexed as

DNA Transposable ElementsTranscriptomeAnimalsEmbryonic DevelopmentMiceOrganogenesisRNA-SeqRNA, UntranslatedSingle-Cell AnalysisDNA Transposable ElementsRNA, Untranslated

Identifiers

PMID33355230
PMCPMC7849386
OpenAlexW3116220714

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.