Evidence map›Paper›PMID 38622358›Full record

ArticleBriefings in bioinformatics2024

Understanding YTHDF2-mediated mRNA degradation by m6A-BERT-Deg.

Ting-He Zhang, Sumin Jo, Michelle Zhang, Kai Wang, Shou-Jiang Gao, Yufei Huang

Open access · goldAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 7 citations in OpenAlex.

  1. mArXiv · 2026
    Article
  2. Review
  3. Systematic identification of tissue-conserved mbioRxiv : the preprint server for biology · 2026
    Article
  4. Review
  5. Article
  6. METTL3-mediated mMolecular biology reports · 2025
    Review
  7. Article
  8. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Ting-He ZhangCancer Virology Program, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA 15232, USA.ORCID 0000-0002-4595-6167
Sumin JoCancer Virology Program, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA 15232, USA.
Michelle ZhangDepartment of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX, 78249, USA.
Kai WangRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Shou-Jiang GaoCancer Virology Program, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA 15232, USA.
Yufei HuangCancer Virology Program, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, PA 15232, USA.
University of Pittsburgh · USChildren's Hospital of Philadelphia · USThe University of Texas at San Antonio · US

Funding

Cell Model for KSHV Infection and Genetic ManipulationR01CA096512 · NCI · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Shou-Jiang Gao · 2003 to 2026
$7.4M
Regulation of KSHV replication by N6-methyladenosine (m6A) - Diversity SupplementR01CA124332 · NCI · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GAO, SHOU-JIANG · 2007 to 2025
$5.0M
Novel bioinformatics methods to detect DNA and RNA modifications using Nanopore long-read sequencingR01HG013359 · NHGRI · CHILDREN'S HOSP OF PHILADELPHIA · PI Kai Wang · 2023 to 2026
$2.8M
m6A-suite: an informatics pipeline and resource for elucidating roles of m6A epitranscriptome in cancerU01CA279618 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HUANG, YUFEI · 2023 to 2025
$1.8M
Uncovering the epitranscriptome regulatory codes using machine learningSC3GM136594 · NIGMS · UNIVERSITY OF TEXAS SAN ANTONIO · PI ZHANG, JIANQIU · 2020 to 2023
$435k
NCI NIH HHS R01 CA096512NCI NIH HHS R01 CA124332NCI NIH HHS U01 CA279618NHGRI NIH HHS R01 HG013359NIGMS NIH HHS SC3 GM136594
6 · The paper itself

Abstract

N6-methyladenosine (m6A) is the most abundant mRNA modification within mammalian cells, holding pivotal significance in the regulation of mRNA stability, translation and splicing. Furthermore, it plays a critical role in the regulation of RNA degradation by primarily recruiting the YTHDF2 reader protein. However, the selective regulation of mRNA decay of the m6A-methylated mRNA through YTHDF2 binding is poorly understood. To improve our understanding, we developed m6A-BERT-Deg, a BERT model adapted for predicting YTHDF2-mediated degradation of m6A-methylated mRNAs. We meticulously assembled a high-quality training dataset by integrating multiple data sources for the HeLa cell line. To overcome the limitation of small training samples, we employed a pre-training-fine-tuning strategy by first performing a self-supervised pre-training of the model on 427 760 unlabeled m6A site sequences. The test results demonstrated the importance of this pre-training strategy in enabling m6A-BERT-Deg to outperform other benchmark models. We further conducted a comprehensive model interpretation and revealed a surprising finding that the presence of co-factors in proximity to m6A sites may disrupt YTHDF2-mediated mRNA degradation, subsequently enhancing mRNA stability. We also extended our analyses to the HEK293 cell line, shedding light on the context-dependent YTHDF2-mediated mRNA degradation.

Indexed as

AdenineRNA-Binding ProteinsTranscription FactorsAnimalsHEK293 CellsHeLa CellsHumansRNA, MessengerRNA Stability6-methyladenineAdenineRNA-Binding ProteinsRNA, MessengerTranscription FactorsYTHDF2 protein, humandeep learningm6A-BERTm6A modificationmRNA degradationYTHDF2

Identifiers

PMID38622358
PMCPMC11018547
OpenAlexW4394853432

What Socratic 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 Socratic graph.