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Record W2531690304 · doi:10.1016/j.celrep.2016.09.049

MECP2 Is Post-transcriptionally Regulated during Human Neurodevelopment by Combinatorial Action of RNA-Binding Proteins and miRNAs

2016· article· en· W2531690304 on OpenAlexafffund
Deivid C. Rodrigues, Dae Sung Kim, Guang Yang, Kirill Zaslavsky, Kevin Ha, Rebecca S.F. Mok, P. Joel Ross, Melody Zhao, Alina Piekna, Wei Wei, Benjamin J. Blencowe, Quaid Morris, James Ellis

Bibliographic record

VenueCell Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsMECP2BiologyTranslation (biology)microRNARNA-binding proteinUntranslated regionRNAInduced pluripotent stem cellCell biologyMessenger RNATranslational regulationGene isoformThree prime untranslated regionEmbryonic stem cellGeneticsComputational biologyPhenotypeGene

Abstract

fetched live from OpenAlex

A progressive increase in MECP2 protein levels is a crucial and precisely regulated event during neurodevelopment, but the underlying mechanism is unclear. We report that MECP2 is regulated post-transcriptionally during in vitro differentiation of human embryonic stem cells (hESCs) into cortical neurons. Using reporters to identify functional RNA sequences in the MECP2 3' UTR and genetic manipulations to explore the role of interacting factors on endogenous MECP2, we discover combinatorial mechanisms that regulate RNA stability and translation. The RNA-binding protein PUM1 and pluripotent-specific microRNAs destabilize the long MECP2 3' UTR in hESCs. Hence, the 3' UTR appears to lengthen during differentiation as the long isoform becomes stable in neurons. Meanwhile, translation of MECP2 is repressed by TIA1 in hESCs until HuC predominates in neurons, resulting in a switch to translational enhancement. Ultimately, 3' UTR-directed translational fine-tuning differentially modulates MECP2 protein in the two cell types to levels appropriate for normal neurodevelopment.

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 score0.060
Threshold uncertainty score0.513

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 science0.0000.000
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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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

Citations68
Published2016
Admission routes2
Has abstractyes

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