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Record W3213796560 · doi:10.1093/genetics/iyab177

The F-box protein Bard (CG14317) targets the Smaug RNA-binding protein for destruction during the <i>Drosophila</i> maternal-to-zygotic transition

2021· article· en· W3213796560 on OpenAlexafffund
Wen Xi Cao, Angelo Karaiskakis, Sichun Lin, Stéphane Angers, Howard D. Lipshitz

Bibliographic record

VenueGenetics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsBiologyMaternal to zygotic transitionDrosophila melanogasterGeneticsUbiquitin ligaseGeneDrosophila embryogenesisEmbryoTranscription (linguistics)ZygoteMolecular biologyCell biologyEmbryogenesisUbiquitin

Abstract

fetched live from OpenAlex

During the maternal-to-zygotic transition (MZT), which encompasses the earliest stages of animal embryogenesis, a subset of maternally supplied gene products is cleared, thus permitting activation of zygotic gene expression. In the Drosophila melanogaster embryo, the RNA-binding protein Smaug (SMG) plays an essential role in progression through the MZT by translationally repressing and destabilizing a large number of maternal mRNAs. The SMG protein itself is rapidly cleared at the end of the MZT by a Skp/Cullin/F-box (SCF) E3-ligase complex. Clearance of SMG requires zygotic transcription and is required for an orderly MZT. Here, we show that an F-box protein, which we name Bard (encoded by CG14317), is required for degradation of SMG. Bard is expressed zygotically and physically interacts with SMG at the end of the MZT, coincident with binding of the maternal SCF proteins, SkpA and Cullin1, and with degradation of SMG. shRNA-mediated knock-down of Bard or deletion of the bard gene in the early embryo results in stabilization of SMG protein, a phenotype that is rescued by transgenes expressing Bard. Bard thus times the clearance of SMG at the end of the MZT.

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 score0.006
Threshold uncertainty score0.727

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 studies0.0010.000
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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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

Citations13
Published2021
Admission routes2
Has abstractyes

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