Evidence map›Paper›PMID 19468299›Full record

ArticlePLoS biology2009

Aberrant herpesvirus-induced polyadenylation correlates with cellular messenger RNA destruction.

Yeon J Lee, Britt A Glaunsinger

Open access · goldAbstract read
In one paragraph

Article in PLoS biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

86 citing papers in PubMed, 118 citations in OpenAlex.

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26 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

2 authors at 1 institution in 1 country.

Yeon J LeeDepartment of Plant and Microbial Biology, University of California Berkeley, Berkeley, California, United States of America.
Britt A Glaunsinger
University of California, Berkeley · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Regulation of messenger RNA (mRNA) stability plays critical roles in controlling gene expression, ensuring transcript fidelity, and allowing cells to respond to environmental cues. Unregulated enhancement of mRNA turnover could therefore dampen cellular responses to such signals. Indeed, several herpesviruses instigate widespread destruction of cellular mRNAs to block host gene expression and evade immune detection. Kaposi's sarcoma-associated herpesvirus (KSHV) promotes this phenotype via the activity of its viral SOX protein, although the mechanism of SOX-induced mRNA turnover has remained unknown, given its apparent lack of intrinsic ribonuclease activity. Here, we report that KSHV SOX stimulates cellular transcriptome turnover via a unique mechanism involving aberrant polyadenylation. Transcripts in SOX-expressing cells exhibit extended poly(A) polymerase II-generated poly(A) tails and polyadenylation-linked mRNA turnover. SOX-induced polyadenylation changes correlate with its RNA turnover function, and inhibition of poly(A) tail formation blocks SOX activity. Both nuclear and cytoplasmic poly(A) binding proteins are critical cellular cofactors for SOX function, the latter of which undergoes striking nuclear relocalization by SOX. SOX-induced mRNA turnover therefore represents both a novel mechanism of host shutoff as well as a new model system to probe the regulation of poly(A) tail-stimulated mRNA turnover in mammalian cells.

Indexed as

Cell LineFluorescent Antibody TechniqueHerpesvirus 8, HumanHumansIn Situ HybridizationPolyadenylationPolymerase Chain ReactionRNA, MessengerRNA StabilityViral ProteinsRNA, MessengerViral Proteins

Identifiers

PMID19468299
PMCPMC2680333
OpenAlexW2090204598

What OpenQuestion holds

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LicenceCC BY
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.