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Record W2612678746 · doi:10.18632/oncotarget.17813

Transcriptome profiling in preadipocytes identifies long noncoding RNAs as Sam68 targets

2017· article· en· W2612678746 on OpenAlexafffundabout
Naomi Li, Steven Hébert, Jingwen Song, Claudia L. Kleinman, Stéphane Richard

Bibliographic record

VenueOncotarget · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsMcGill UniversityJewish General Hospital
FundersFonds de Recherche du Québec - SantéCompute Canada
KeywordsHOTAIRTranscriptomeAdipogenesisBiologyLong non-coding RNAGeneCancer researchRNAGeneticsGene expression

Abstract

fetched live from OpenAlex

// Naomi Li 1, 2, 3 , Steven Hébert 1, 4 , Jingwen Song 1, 2, 3 , Claudia L. Kleinman 1, 4 and Stéphane Richard 1, 2, 3 1 Segal Cancer Center, Sir Mortimer B Davis Jewish General Hospital, Lady Davis Institute for Medical Research, Montréal, Québec H3T 1E2, Canada 2 Department of Medicine, McGill University, Montréal, Québec H3A 1A1, Canada 3 Department of Oncology, McGill University, Montréal, Québec H3A 1A1, Canada 4 Department of Human Genetics, McGill University, Montréal, Québec H3A 1B1, Canada Correspondence to: Stéphane Richard, email: stephane.richard@mcgill.ca Keywords: Sam68, RNA binding proteins, lncRNAs, preadipocytes, adipogenesis Received: January 05, 2017     Accepted: April 17, 2017     Published: May 11, 2017 ABSTRACT The KH-type RNA binding protein Sam68 is required for adipogenesis. We have previously shown that Sam68-deficient mice have a lean phenotype and are protected against dietary-induced obesity due to defects in mTOR and S6K1 alternative splicing. Herein we profiled the transcriptome of Sam68 wild type and deficient 3T3-L1 mouse preadipocytes. We identified 652 protein-coding genes and 9 ncRNAs that were significantly altered with the loss of Sam68. As expected, downregulated genes were significantly associated with GO terms linked to cell migration, motility, and fat cell differentiation, while upregulated genes were mostly associated with GO terms linked to neurogenesis. Of the lncRNAs, we identified Hotair , Mir155hg , as well as two new lncRNAs ( SR-lncRNA-1 and SR-lncRNA-2 ) that were regulated by Sam68, and contained consensus Sam68 binding sites. RNA stability assays showed that Sam68-deficiency decreased the half-life of Hotair, and increased the half-lives of Mir155hg and SR-lncRNA-2 , while the stability of SR-lncRNA-1 was unaffected. Depletion of Hotair and SR-lncRNA-1 in wild type 3T3-L1 cells led to defects in adipogenesis, whereas depletion of SR-lncRNA-2 in Sam68-deficient 3T3-L1 cells partially rescued the adipogenesis defect observed in these cells. Collectively, our findings define a new role for Sam68 as a regulator of lncRNAs during adipogenic differentiation.

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 categoriesMeta-epidemiology (narrow)
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 score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.319
Teacher spread0.302 · 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.

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

Citations16
Published2017
Admission routes3
Has abstractyes

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