Evidence map›Paper›PMID 38637632›Full record

ReviewNature reviews. Genetics2024

Nuclear mRNA decay: regulatory networks that control gene expression.

Xavier Rambout, Lynne E Maquat

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

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  20. Functional and structural characterization ofFrontiers in endocrinology · 2026
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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

2 authors.

Xavier RamboutDepartment of Biochemistry and Biophysics, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA. xavier_rambout@urmc.rochester.edu.ORCID 0000-0002-5147-2863
Lynne E MaquatDepartment of Biochemistry and Biophysics, School of Medicine and Dentistry, University of Rochester, Rochester, NY, USA. lynne_maquat@urmc.rochester.edu.ORCID 0000-0002-2789-2075

Funding

REGULATION OF SELENOPROTEIN RNA METABOLISMR01GM059614 · NIGMS · UNIVERSITY OF ROCHESTER · PI MAQUAT, LYNNE E · 1999 to 2022
$9.1M
Regulation of Normal and Defective Human GenesR37GM074593 · NIGMS · UNIVERSITY OF ROCHESTER · PI MAQUAT, LYNNE E · 2014 to 2023
$4.8M
Nonsense-mediated mRNA decay and beyondR35GM149268 · NIGMS · UNIVERSITY OF ROCHESTER · PI Lynne E Maquat · 2023 to 2026
$3.1M
Role of a novel PGC-1α isoform in gene transcriptionR21AG075368 · NIA · UNIVERSITY OF ROCHESTER · PI RAMBOUT, XAVIER · 2022 to 2023
$424k
American Heart Association-American Stroke Association 854100NIA NIH HHS R21 AG075368NIGMS NIH HHS R01 GM059614NIGMS NIH HHS R35 GM149268NIGMS NIH HHS R37 GM074593
6 · The paper itself

Abstract

Proper regulation of mRNA production in the nucleus is critical for the maintenance of cellular homoeostasis during adaptation to internal and environmental cues. Over the past 25 years, it has become clear that the nuclear machineries governing gene transcription, pre-mRNA processing, pre-mRNA and mRNA decay, and mRNA export to the cytoplasm are inextricably linked to control the quality and quantity of mRNAs available for translation. More recently, an ever-expanding diversity of new mechanisms by which nuclear RNA decay factors finely tune the expression of protein-encoding genes have been uncovered. Here, we review the current understanding of how mammalian cells shape their protein-encoding potential by regulating the decay of pre-mRNAs and mRNAs in the nucleus.

Indexed as

Cell NucleusGene Expression RegulationGene Regulatory NetworksRNA, MessengerRNA StabilityAnimalsHumansRNA PrecursorsRNA, MessengerRNA Precursors

Identifiers

PMID38637632
PMCPMC11408106

What OpenQuestion holds

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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.