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Record W2891879622 · doi:10.1371/journal.pone.0203781

A genetic mosaic screen identifies genes modulating Notch signaling in Drosophila

2018· article· en· W2891879622 on OpenAlexfundno aff
Luming Ren, Dongqing Mo, Yunlong Li, Tong Liu, Huan Yin, Na Jiang, Junzheng Zhang

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsnot available
FundersChinese Universities Scientific FundInstitute of GeneticsNational Natural Science Foundation of China
KeywordsNotch signaling pathwayHes3 signaling axisBiologyDrosophila melanogasterNotch proteinsSignal transductionCell biologyGeneticsGeneTranscription factorMulticellular organismGenetic screenPhenotype

Abstract

fetched live from OpenAlex

Notch signaling is conserved in most multicellular organisms and plays critical roles during animal development. The core components and major signal transduction mechanism of Notch signaling have been extensively studied. However, our understanding of how Notch signaling activity is regulated in diverse developmental processes still remains incomplete. Here, we report a genetic mosaic screen in Drosophila melanogaster that leads to identification of Notch signali ng modulators during wing development. We discovered a group of genes required for the formation of the fly wing margin, a developmental process that is strictly dependent on the balanced Notch signaling activity. These genes encode transcription factors, protein phosphatases, vacuolar ATPases and factors required for RNA transport, stability, and translation. Our data support the view that Notch signaling is controlled through a wide range of molecular processes. These results also provide foundations for further study by showing that Me31B and Wdr62 function as two novel modulators of Notch signaling activity.

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 score0.023
Threshold uncertainty score0.505

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 head0.025
GPT teacher head0.234
Teacher spread0.210 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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