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Record W4322488342 · doi:10.1101/2023.02.27.530189

Smaug regulates germ plasm synthesis and primordial germ cell number in Drosophila embryos by repressing the <i>oskar</i> and <i>bruno 1</i> mRNAs

2023· preprint· en· W4322488342 on OpenAlexafffund
Najeeb U. Siddiqui, Angelo Karaiskakis, Aaron L. Goldman, Whitby V.I. Eagle, Craig A. Smibert, Elizabeth R. Gavis, Howard D. Lipshitz

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Institutes of HealthHospital for Sick Children
KeywordsGerm plasmoskarGerm line developmentBiologyGerm cellEmbryoCell biologyTranslational regulationOocyteGermlineMessenger RNATranslation (biology)Ectopic expressionOogenesisGeneticsGene

Abstract

fetched live from OpenAlex

Abstract During Drosophila oogenesis, the Oskar (OSK) RNA-binding protein (RBP) determines the amount of germ plasm that assembles at the posterior pole of the oocyte. Here we identify the mechanisms that regulate the osk mRNA in the early embryo. We show that the Smaug (SMG) RBP is transported into the germ plasm of the early embryo where it accumulates in the germ granules. SMG binds to and represses translation of the osk mRNA itself as well as the bruno 1 ( bru1 ) mRNA, which encodes an RBP that we show promotes germ plasm production. Loss of SMG or mutation of SMG’s binding sites in the osk or bru1 mRNAs results in ectopic translation of these transcripts in the germ plasm and excess PGCs. SMG therefore triggers a post-transcriptional regulatory pathway that attenuates germ plasm synthesis in embryos, thus modulating the number of PGCs.

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 head0.007
GPT teacher head0.206
Teacher spread0.198 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicDevelopmental Biology and Gene RegulationFrench-language works237,207