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Record W4404951253 · doi:10.26508/lsa.202403142

<i>N</i> -6-methyladenosine (m6A) promotes the nuclear retention of mRNAs with intact 5′ splice site motifs

2024· article· en· W4404951253 on OpenAlexafffund
Eliza S. Lee, Harrison W. Smith, Yifan E. Wang, Sean SJ Ihn, Letícia B. Oliveira, Nevraj S. Kejiou, Yijing Liang, Syed Nabeel‐Shah, Robert Y. Jomphe, Shuye Pu, Jack Greenblatt, Alexander F. Palazzo

Bibliographic record

VenueLife Science Alliance · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsN6-MethyladenosineRNARNA splicingChemistryPrecursor mRNACell biologyBiologyMolecular biologyBiochemistryDNAGene

Abstract

fetched live from OpenAlex

In humans, misprocessed mRNAs containing intact 5′ Splice Site (5′SS) motifs are nuclear retained and targeted for decay by ZFC3H1, a component of the Poly(A) Exosome Targeting complex, and U1-70K, a component of the U1 snRNP. In S. pombe , the ZFC3H1 homolog, Red1, binds to the YTH domain–containing protein Mmi1 and targets certain RNA transcripts to nuclear foci for nuclear retention and decay. Here we show that YTHDC1 and YTHDC2, two YTH domain-containing proteins that bind to N -6-methyladenosine (m6A) modified RNAs, interact with ZFC3H1 and U1-70K, and are required for the nuclear retention of mRNAs with intact 5′SS motifs. Disruption of m6A deposition inhibits both the nuclear retention of these transcripts and their accumulation in YTHDC1-enriched foci that are adjacent to nuclear speckles. Endogenous RNAs with intact 5′SS motifs, such as intronic poly-adenylated transcripts, tend to be m6A-modified at low levels. Thus, the m6A modification acts on a conserved quality control mechanism that targets misprocessed mRNAs for nuclear retention and decay.

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.

How this classification was reachedexpand

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes2
Has abstractyes

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