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Record W4411465227 · doi:10.1002/ctm2.70369

Splicing to keep splicing: A feedback system for cellular homeostasis and state transition

2025· review· en· W4411465227 on OpenAlex
Zhonghao Guo, Xurui Zhang, Yachen Li, Yule Chen, Yungang Xu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical and Translational Medicine · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsMcGill University
FundersKey Research and Development Projects of Shaanxi ProvinceNational Natural Science Foundation of China
KeywordsRNA splicingAlternative splicingmicroRNABiologyComputational biologySpliceosomeGene isoformGeneGeneticsRNA

Abstract

fetched live from OpenAlex

BACKGROUND: Alternative splicing (AS) plays a crucial role in regulating gene expression and governing proteomic diversity by generating multiple protein isoforms from a single gene. Increasing evidence has highlighted the regulation for pre-mRNA splicing of the splicing factors (SFs). This review aims to examine featured mechanisms and examples of SF regulation by AS, focusing on paradigmatic feedback loops and their biological implications. MAIN BODY OF THE ABSTRACT: We specifically focus on the autoregulation and inter-regulation of SFs through AS machinery. These interactions give rise to a feedback system, where the negative feedback loops aid in maintaining cellular homeostasis, and the positive feedback loops play roles in triggering cellular state transitions. We examine the growing evidence highlighting the specific mechanisms employed by SFs to autoregulate their own splicing, including AS-coupled nonsense-mediated mRNA decay (AS-NMD), nuclear retention, and alternative 3'UTR regulation. We showcase the influence of AS feedback in amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and cancer. Furthermore, we discuss how master splicing factors can dominantly orchestrate splicing cascades, leading to widespread impacts in cellular processes. We also discuss how non-coding RNAs, particularly circular RNAs and microRNAs, engage in the splicing regulatory networks. Lastly, we showcase how negative and positive feedback loops can collaboratively achieve remarkable biological functions during the cell fate decision. SHORT CONCLUSION: This review highlights the regulation of SFs by AS, providing enriched information for future investigations that aim at deciphering the intricate interplay within splicing regulatory networks. KEY POINTS: Negative feedback of alternative splicing maintains cellular homeostasis. Positive feedback of alternative splicing triggers cellular state transitions. Alternative splicing forms integrated feedback networks with circRNAs and microRNAs to reciprocally regulate their expression and function. The coordinated interplay of distinct splicing feedback mechanisms orchestrates precise cell fate transitions. Future directions and therapeutic possibilities that could transform alternative splicing research into treatments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.397
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it