Evidence map›Paper›PMID 38982239›Full record

ReviewNature reviews. Genetics2024

Decoding protein-RNA interactions using CLIP-based methodologies.

Joy S Xiang, Danielle M Schafer, Katherine L Rothamel, Gene W Yeo

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 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

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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

4 authors.

Joy S Xiang *Division of Biomedical Sciences, UC Riverside, Riverside, CA, USA.ORCID 0000-0002-6400-1876
Danielle M Schafer *Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, USA.
Katherine L RothamelDepartment of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, USA.
Gene W YeoDepartment of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, USA. geneyeo@ucsd.edu.ORCID 0000-0002-0799-6037

Funding

Functional RNA elements in the human genomeR01HG004659 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Kevin Daniel Corbett, Eugene Wei-Ming Yeo · 2008 to 2026
$12.4M
A Comprehensive Functional Map of Human Protein-RNA InteractionsU41HG009889 · NHGRI · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI GRAVELEY, BRENTON R. · 2018 to 2021
$9.4M
A comprehensive binding and functional map of human RNA-binding proteinsU24HG009889 · NHGRI · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI GRAVELEY, BRENTON R., YEO, EUGENE WEI-MING · 2022 to 2025
$5.5M
NHGRI NIH HHS R01 HG004659NHGRI NIH HHS U24 HG009889NHGRI NIH HHS U41 HG009889
6 · The paper itself

Abstract

Protein-RNA interactions are central to all RNA processing events, with pivotal roles in the regulation of gene expression and cellular functions. Dysregulation of these interactions has been increasingly linked to the pathogenesis of human diseases. High-throughput approaches to identify RNA-binding proteins and their binding sites on RNA - in particular, ultraviolet crosslinking followed by immunoprecipitation (CLIP) - have helped to map the RNA interactome, yielding transcriptome-wide protein-RNA atlases that have contributed to key mechanistic insights into gene expression and gene-regulatory networks. Here, we review these recent advances, explore the effects of cellular context on RNA binding, and discuss how these insights are shaping our understanding of cellular biology. We also review the potential therapeutic applications arising from new knowledge of protein-RNA interactions.

Indexed as

ImmunoprecipitationRNARNA-Binding ProteinsAnimalsBinding SitesHumansProtein BindingRNARNA-Binding Proteins

Identifiers

PMID38982239
PMCPMC12356153

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.