MétaCan
Menu
Back to cohort
Record W2150499711 · doi:10.1242/jcs.141788

A role for the CB-associated SUMO isopeptidase USPL1 in RNAPII-mediated snRNA transcription

2014· article· en· W2150499711 on OpenAlexfundno aff
Saskia Hutten, Georgia Chachami, Ulrike Winter, Frauke Melchior, Angus I. Lamond

Bibliographic record

VenueJournal of Cell Science · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsnot available
FundersWellcome TrustUniversity of DundeeUniversity of OttawaAlexander von Humboldt-Stiftung
KeywordssnRNPCajal bodyBiologySmall nuclear RNACell biologySpliceosomePrp24RNA splicingRNA polymerase IIGene knockdownTranscription (linguistics)Small nuclear ribonucleoproteinGeneticsRNAGene expressionGeneNon-coding RNA

Abstract

fetched live from OpenAlex

Cajal bodies are nuclear structures that are involved in biogenesis of snRNPs and snoRNPs, maintenance of telomeres and processing of histone mRNA. Recently, the SUMO isopeptidase USPL1 was identified as a component of Cajal bodies that is essential for cellular growth and Cajal body integrity. However, a cellular function for USPL1 is so far unknown. Here, we use RNAi-mediated knockdown in human cells in combination with biochemical and fluorescence microscopy approaches to investigate the function of USPL1 and its link to Cajal bodies. We demonstrate that levels of snRNAs transcribed by RNA polymerase (RNAP) II are reduced upon knockdown of USPL1 and that downstream processes such as snRNP assembly and pre-mRNA splicing are compromised. Importantly, we find that USPL1 associates directly with U snRNA loci and that it interacts and colocalises with components of the Little Elongation Complex, which is involved in RNAPII-mediated snRNA transcription. Thus, our data indicate that USPL1 plays a key role in RNAPII-mediated snRNA transcription.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.258
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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

Citations51
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cell ScienceSame topicRNA Research and SplicingFrench-language works237,207