Evidence map›Paper›PMID 41055236›Full record

ArticleRNA biology2025

DeepRNA-Reg: a deep-learning based approach for comparative analysis of CLIP experiments.

Harshaan Sekhon, Robin Kageyama, Neil T Sprenkle, Hannah C Happ, Eric J Wigton, Heather H Pua, K Mark Ansel

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in RNA biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Harshaan SekhonDepartment of Microbiology & Immunology and Sandler Asthma Basic Research Center, University of California San Francisco, San Francisco, CA, USA.
Robin KageyamaDepartment of Microbiology & Immunology and Sandler Asthma Basic Research Center, University of California San Francisco, San Francisco, CA, USA.
Neil T SprenkleDepartment of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA.
Hannah C HappDepartment of Microbiology & Immunology and Sandler Asthma Basic Research Center, University of California San Francisco, San Francisco, CA, USA.
Eric J WigtonDepartment of Microbiology & Immunology and Sandler Asthma Basic Research Center, University of California San Francisco, San Francisco, CA, USA.
Heather H PuaDepartment of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA.
K Mark AnselDepartment of Microbiology & Immunology and Sandler Asthma Basic Research Center, University of California San Francisco, San Francisco, CA, USA.ORCID 0000-0003-4840-9879

Funding

Role of miRNAs in Th2-Driven inflammation in AsthmaP01HL107202 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WOODRUFF, PRESCOTT G · 2012 to 2023
$23.3M
Role of miRNAs in Th2-Driven inflammation in AsthmaR01HL109102 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Karl Mark Ansel · 2011 to 2026
$5.5M
Extracellular RNA Communication in Lung InflammationDP2HL152426 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PUA, HEATHER H · 2019 to 2019
$2.5M
MiR-23/27/24 Control of Adipose Tissue Macrophage ActivationR21AI156292 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PUA, HEATHER H · 2021 to 2022
$487k
Global analysis of T cell post-transcriptional regulatory elementsR21AI128047 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ANSEL, KARL MARK · 2018 to 2019
$440k
NHLBI NIH HHS DP2 HL152426NHLBI NIH HHS P01 HL107202NHLBI NIH HHS R01 HL109102NIAID NIH HHS R21 AI128047NIAID NIH HHS R21 AI156292
6 · The paper itself

Abstract

DeepRNA-Reg employs advances in deep learning to enable high-fidelity comparative analysis of paired datasets of high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). In a HITS-CLIP experimental paradigm where Ago2 targeting is selectively perturbed via gene knock-out of a microRNA cluster, DeepRNA-Reg offers a superior prediction set when compared with the current best prescription for differential HITS-CLIP analysis. Furthermore, DeepRNA-Reg predictions adhered better to the ground-truth of RNA primary and secondary structural motifs that enable miRNA-mediated targeting of RNA. In the tested data sets, DeepRNA-Reg uncovered novel mediators in the mechanism of microRNA-mediated restraint of type-2 immunity in T-Helper 2 cells. In a comparative analysis, DeepRNA-Reg predictions show greater translatability across distinct biological milieux, offering prediction sets with wide applicability for investigators.

Indexed as

Computational BiologyDeep LearningHigh-Throughput Nucleotide SequencingImmunoprecipitationMicroRNAsRNASequence Analysis, RNAAnimalsArgonaute ProteinsHumansArgonaute ProteinsMicroRNAsRNAdeep learningDifferential HITS-CLIPRNA-binding-protein (RBP)

Identifiers

PMID41055236
PMCPMC12505516

What OpenQuestion holds

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Registered trials

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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.