Evidence map›Paper›PMID 32710631›Full record

ArticleNucleic acids research2020

The RNA exosome shapes the expression of key protein-coding genes.

Mengjun Wu, Evdoxia Karadoulama, Marta Lloret-Llinares, Jerome Olivier Rouviere, Christian Skov Vaagensø, Martin Moravec, Bingnan Li, Jingwen Wang, Guifen Wu, Maria Gockert and 3 more

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

12 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
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  5. Review
  6. A data-driven genome annotation approach for cassava.The Plant journal : for cell and molecular biology · 2024
    Article
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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

13 authors at 4 institutions in 3 countries.

Mengjun WuThe Bioinformatics Centre, Department of Biology and Biotech and Research Innovation Centre, University of Copenhagen, Ole Maaløes Vej 5, DK2200 Copenhagen N, Denmark.
Evdoxia KaradoulamaThe Bioinformatics Centre, Department of Biology and Biotech and Research Innovation Centre, University of Copenhagen, Ole Maaløes Vej 5, DK2200 Copenhagen N, Denmark.
Marta Lloret-LlinaresDepartment of Molecular Biology and Genetics, Aarhus University, C.F. Møllers Alle 3, Building 1130, Aarhus 8000, Denmark.
Jerome Olivier RouviereDepartment of Molecular Biology and Genetics, Aarhus University, C.F. Møllers Alle 3, Building 1130, Aarhus 8000, Denmark.
Christian Skov VaagensøThe Bioinformatics Centre, Department of Biology and Biotech and Research Innovation Centre, University of Copenhagen, Ole Maaløes Vej 5, DK2200 Copenhagen N, Denmark.
Martin MoravecDepartment of Molecular Biology and Genetics, Aarhus University, C.F. Møllers Alle 3, Building 1130, Aarhus 8000, Denmark.
Bingnan LiSciLifeLab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna 171 65, Sweden.
Jingwen WangSciLifeLab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna 171 65, Sweden.
Guifen WuDepartment of Molecular Biology and Genetics, Aarhus University, C.F. Møllers Alle 3, Building 1130, Aarhus 8000, Denmark.
Maria GockertDepartment of Molecular Biology and Genetics, Aarhus University, C.F. Møllers Alle 3, Building 1130, Aarhus 8000, Denmark.
Vicent PelechanoSciLifeLab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna 171 65, Sweden.
Torben Heick JensenDepartment of Molecular Biology and Genetics, Aarhus University, C.F. Møllers Alle 3, Building 1130, Aarhus 8000, Denmark.
Albin SandelinThe Bioinformatics Centre, Department of Biology and Biotech and Research Innovation Centre, University of Copenhagen, Ole Maaløes Vej 5, DK2200 Copenhagen N, Denmark.
Aarhus University · DKUniversity of Copenhagen · DKScience for Life Laboratory · SEEuropean Bioinformatics Institute · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ribonucleolytic exosome complex is central for nuclear RNA degradation, primarily targeting non-coding RNAs. Still, the nuclear exosome could have protein-coding (pc) gene-specific regulatory activities. By depleting an exosome core component, or components of exosome adaptor complexes, we identify ∼2900 transcription start sites (TSSs) from within pc genes that produce exosome-sensitive transcripts. At least 1000 of these overlap with annotated mRNA TSSs and a considerable portion of their transcripts share the annotated mRNA 3' end. We identify two types of pc-genes, both employing a single, annotated TSS across cells, but the first type primarily produces full-length, exosome-sensitive transcripts, whereas the second primarily produces prematurely terminated transcripts. Genes within the former type often belong to immediate early response transcription factors, while genes within the latter are likely transcribed as a consequence of their proximity to upstream TSSs on the opposite strand. Conversely, when genes have multiple active TSSs, alternative TSSs that produce exosome-sensitive transcripts typically do not contribute substantially to overall gene expression, and most such transcripts are prematurely terminated. Our results display a complex landscape of sense transcription within pc-genes and imply a direct role for nuclear RNA turnover in the regulation of a subset of pc-genes.

Indexed as

Transcription Initiation SiteExosomesGene Expression RegulationGenome, HumanHeLa CellsHumansMolecular Sequence AnnotationOpen Reading FramesRNARNA, MessengerRNA StabilityRNA, UntranslatedRNARNA, MessengerRNA, Untranslated

Identifiers

PMID32710631
PMCPMC7470964
OpenAlexW3043907830

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.