Evidence map›Paper›PMID 41285791›Full record

ArticleNature communications2025

The implications of alternative splicing regulation for maximum lifespan.

Wei Jiang, Sika Zheng, Liang Chen

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Wei JiangDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
Sika ZhengDivision of Biomedical Sciences, School of Medicine, University of California, Riverside, CA, USA. sikaz@ucr.edu.ORCID http://orcid.org/0000-0002-0573-4981
Liang ChenDepartment of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA. liang.chen@usc.edu.ORCID http://orcid.org/0000-0001-6164-4553

Funding

Genetic control mechanisms of long-term neuronal survivalR01NS139485 · NINDS · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI Sika Zheng · 2024 to 2026
$1.9M
NINDS NIH HHS R01 NS139485U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) R01NS139485
6 · The paper itself

Abstract

Mammalian maximum lifespan (MLS) varies over a hundred-fold, yet the molecular mechanisms underlying this diversity remain unclear. We present a cross-species analysis of alternative splicing (AS) across six tissues in 26 mammals, identifying hundreds of conserved AS events significantly associated with MLS, with the brain containing twice as many tissue-specific events as peripheral tissues. MLS-AS events are enriched in pathways related to mRNA processing, stress response, neuronal functions, and epigenetic regulation, and are largely distinct from genes whose expression correlates with MLS, indicating that AS captures unique lifespan-related signals. The brain exhibits certain associations divergent from peripheral tissues and reduced overlap with body mass (BM)-associated splicing; neither is observed at the gene expression level. While MLS- and age-associated AS events show limited overlap, the shared events are enriched in intrinsically disordered protein regions, suggesting a role in protein flexibility and stress adaptability. Furthermore, MLS-associated AS events display stronger RNA-binding protein (RBP) motif coordination than age-associated ones, highlighting a more genetically programmed adaptation for lifespan determination, in contrast to the more variable splicing changes seen with chronological aging. These findings suggest alternative splicing as a distinct, transcription-independent axis of lifespan regulation, offering insights into the molecular basis of longevity.

Indexed as

Alternative SplicingLongevityMammalsAgingAnimalsBrainHumansMiceRNA-Binding ProteinsRNA, MessengerRNA-Binding ProteinsRNA, Messenger

Identifiers

PMID41285791
PMCPMC12644568

What OpenQuestion holds

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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.