Evidence map›Paper›PMID 32673562›Full record

ArticleCell systems2020

RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus.

Kevin E Wu, Furqan M Fazal, Kevin R Parker, James Zou, Howard Y Chang

Open access · hybridAbstract read
In one paragraph

Article in Cell systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 5% 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

113 citing papers in PubMed, 1 synthesis or guideline pooled it, 156 citations in OpenAlex.

  1. Pooled it
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  10. Post-Acute Sequelae and Mitochondrial Aberration in SARS-CoV-2 Infection.International journal of molecular sciences · 2024
    Review
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53 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Kevin E WuDepartment of Computer Science, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA; Center for Personal and Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA 94305, USA.
Furqan M FazalCenter for Personal and Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA 94305, USA.
Kevin R ParkerCenter for Personal and Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA 94305, USA.
James ZouDepartment of Computer Science, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address: jamesz@stanford.edu.
Howard Y ChangCenter for Personal and Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address: howchang@stanford.edu.
Stanford University · USHoward Hughes Medical Institute · US

Funding

INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
Center for Personal Dynamic RegulomesRM1HG007735 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2019 to 2023
$13.8M
Role of Single Cell mRNA Variation in Systems Associated Electrically Excitable CU01MH098953 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI EBERWINE, JAMES H, KIM, JUNHYONG · 2012 to 2016
$11.4M
Center for Sub-Cellular GenomicsRM1HG010023 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI EBERWINE, JAMES H, KIM, JUNHYONG · 2018 to 2022
$11.0M
Stanford Medicine Center for Longevity and Healthy Aging Research Education CoreP30AG059307 · NIA · STANFORD UNIVERSITY · PI PERIYAKOIL, VYJEYANTHI S · 2018 to 2025
$4.9M
Structural Motifs in RNAR01HG004361 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2007 to 2018
$4.7M
Revealing Principles of Subcellular RNA Localization by Proximity LabelingR00HG010910 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI FAZAL, FURQAN · 2021 to 2023
$747k
Developing data tools to reduce CVD disparities via Health Information ExchangesR21MD012867 · NIMHD · STANFORD UNIVERSITY · PI ZOU, JAMES · 2018 to 2019
$420k
Revealing Principles of Subcellular RNA Localization by Proximity LabelingK99HG010910 · NHGRI · STANFORD UNIVERSITY · PI FAZAL, FURQAN · 2019 to 2020
$223k
NHGRI NIH HHS K99 HG010910NHGRI NIH HHS R00 HG010910NHGRI NIH HHS R01 HG004361NHGRI NIH HHS RM1 HG007735NHGRI NIH HHS RM1 HG010023NHGRI NIH HHS T32 HG000044NIA NIH HHS P30 AG059307NIMHD NIH HHS R21 MD012867NIMH NIH HHS U01 MH098953
6 · The paper itself

Abstract

SARS-CoV-2 genomic and subgenomic RNA (sgRNA) transcripts hijack the host cell's machinery. Subcellular localization of its viral RNA could, thus, play important roles in viral replication and host antiviral immune response. We perform computational modeling of SARS-CoV-2 viral RNA subcellular residency across eight subcellular neighborhoods. We compare hundreds of SARS-CoV-2 genomes with the human transcriptome and other coronaviruses. We predict the SARS-CoV-2 RNA genome and sgRNAs to be enriched toward the host mitochondrial matrix and nucleolus, and that the 5' and 3' viral untranslated regions contain the strongest, most distinct localization signals. We interpret the mitochondrial residency signal as an indicator of intracellular RNA trafficking with respect to double-membrane vesicles, a critical stage in the coronavirus life cycle. Our computational analysis serves as a hypothesis generation tool to suggest models for SARS-CoV-2 biology and inform experimental efforts to combat the virus. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.

Indexed as

BetacoronavirusCell NucleolusCoronavirus InfectionsCOVID-19Databases, GeneticGenome, ViralHumansMachine LearningMitochondriaModels, GeneticPandemicsPneumonia, ViralRNA, ViralSARS-CoV-2RNA, ViralAPEX-seqCOX4double-membrane vesiclehypothesis generationmachine learning modelproximity labellingSARS-CoV-2viral RNA localization

Identifiers

PMID32673562
PMCPMC7305881
OpenAlexW3036702593

What OpenQuestion holds

Textmetadata
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.