Evidence map›Paper›PMID 25411354›Full record

ArticleRNA (New York, N.Y.)2015

Dissecting noncoding and pathogen RNA-protein interactomes.

Ryan A Flynn, Lance Martin, Robert C Spitale, Brian T Do, Selena M Sagan, Brian Zarnegar, Kun Qu, Paul A Khavari, Stephen R Quake, Peter Sarnow and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in RNA (New York, N.Y.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
4.3field-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

58 citing papers in PubMed, 79 citations in OpenAlex.

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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

11 authors at 4 institutions in 2 countries.

Ryan A FlynnProgram in Epithelial Biology, Stanford University School of Medicine, Stanford, California 94305, USA.
Lance MartinProgram in Epithelial Biology, Stanford University School of Medicine, Stanford, California 94305, USA Department of Bioengineering, Stanford University, Stanford, California 94305, USA.
Robert C SpitaleDepartment of Pharmaceutical Sciences, University of California, Irvine, Irvine, California 92697, USA.
Brian T DoProgram in Epithelial Biology, Stanford University School of Medicine, Stanford, California 94305, USA.
Selena M SaganDepartment of Microbiology and Immunology, McGill University, Montréal, QC H3A 2B4, Canada.
Brian ZarnegarProgram in Epithelial Biology, Stanford University School of Medicine, Stanford, California 94305, USA.
Kun QuProgram in Epithelial Biology, Stanford University School of Medicine, Stanford, California 94305, USA.
Paul A KhavariProgram in Epithelial Biology, Stanford University School of Medicine, Stanford, California 94305, USA.
Stephen R QuakeDepartment of Bioengineering, Stanford University, Stanford, California 94305, USA Department of Applied Physics, Stanford University, Stanford, California 94305, USA Howard Hughes Medical Institute, Stanford University, Stanford, California 94305, USA.
Peter SarnowDepartment of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California 94305, USA.
Howard Y ChangProgram in Epithelial Biology, Stanford University School of Medicine, Stanford, California 94305, USA Howard Hughes Medical Institute, Stanford University, Stanford, California 94305, USA howchang@stanford.edu.
Stanford University · USHoward Hughes Medical Institute · USMcGill University · CAUniversity of California, Irvine · US

Funding

Leveraging innovative technologies in basic and clinical cancer researchT32CA009302 · NCI · STANFORD UNIVERSITY · PI LAURA D ATTARDI, Aaron M Newman · 1985 to 2026
$19.1M
Signaling Regulators of Epithelial Homeostasis and NeoplasiaR01AR049737 · NIAMS · STANFORD UNIVERSITY · PI PAUL KHAVARI · 2004 to 2026
$7.1M
Roles for microRNA-122 in hepatitis C virus RNA amplificationR01AI069000 · NIAID · STANFORD UNIVERSITY · PI SARNOW, PETER · 2006 to 2022
$6.2M
Structural Motifs in RNAR01HG004361 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2007 to 2018
$4.7M
Canadian Institutes of Health ResearchHoward Hughes Medical InstituteNCI NIH HHS 5T32-CA09302NCI NIH HHS T32 CA009302NHGRI NIH HHS R01 HG004361NHGRI NIH HHS R01-HG004361NIAID NIH HHS R01 AI069000NIAID NIH HHS R01-AI069000NIAMS NIH HHS R01 AR049737
6 · The paper itself

Abstract

RNA-protein interactions are central to biological regulation. Cross-linking immunoprecipitation (CLIP)-seq is a powerful tool for genome-wide interrogation of RNA-protein interactomes, but current CLIP methods are limited by challenging biochemical steps and fail to detect many classes of noncoding and nonhuman RNAs. Here we present FAST-iCLIP, an integrated pipeline with improved CLIP biochemistry and an automated informatic pipeline for comprehensive analysis across protein coding, noncoding, repetitive, retroviral, and nonhuman transcriptomes. FAST-iCLIP of Poly-C binding protein 2 (PCBP2) showed that PCBP2-bound CU-rich motifs in different topologies to recognize mRNAs and noncoding RNAs with distinct biological functions. FAST-iCLIP of PCBP2 in hepatitis C virus-infected cells enabled a joint analysis of the PCBP2 interactome with host and viral RNAs and their interplay. These results show that FAST-iCLIP can be used to rapidly discover and decipher mechanisms of RNA-protein recognition across the diversity of human and pathogen RNAs.

Indexed as

Gene Expression ProfilingBase SequenceCell Line, TumorConsensus SequenceHepacivirusHost-Pathogen InteractionsHumansImmunoprecipitationProtein BindingRNA-Binding ProteinsRNA, MessengerRNA, UntranslatedRNA, ViralTranscriptomeRNA-Binding ProteinsRNA, MessengerRNA, UntranslatedRNA, Viralgenomicsnoncoding RNARNA–protein interactionsvirology

Identifiers

PMID25411354
PMCPMC4274633
OpenAlexW2101975193

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.