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Record W4391469336 · doi:10.1101/2024.01.30.578077

Both the transcriptional activator, Bcd, and transcriptional repressor, Cic, form small mobile oligomeric clusters in early fly embryo nuclei

2024· preprint· en· W4391469336 on OpenAlexafffund
Lili Zhang, Lydia Hodgins, Shariful Sakib, Ahmad Mahmood, Carmina Angelica Perez-Romero, Robert A. Marmion, Nathalie Dostatni, Cécile Fradin

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du CanadaUniversities Space Research AssociationMcMaster University
KeywordsDrosophila embryogenesisRepressorBiologyTranscriptional regulationTranscription (linguistics)GeneticsTranscription factorPopulationActivator (genetics)Cell biologyChromatinGeneEmbryoYY1Gene expressionPromoter

Abstract

fetched live from OpenAlex

ABSTRACT Transcription factors play an essential role in pattern formation during early embryo development, generating a strikingly fast and precise transcriptional response that results in sharp gene expression boundaries. To characterize the steps leading up to transcription, we performed a side-by-side comparison of the nuclear dynamics of two morphogens, a transcriptional activator, Bicoid (Bcd), and a transcriptional repressor, Capicua (Cic), both involved in body patterning along the anterior-posterior axis of the early Drosophila embryo. We used a combination of fluorescence recovery after photobleaching, fluorescence correlation spectroscopy, and single particle tracking to access a wide range of dynamical timescales. Despite their opposite effects on gene transcription, we find that Bcd and Cic have very similar nuclear dynamics, characterized by the co-existence of a freely diffusing monomer population with a number of oligomeric clusters, which range from low stoichiometry and high mobility clusters to larger, DNA-bound hubs. Our observations are consistent with the inclusion of both Bcd and Cic into transcriptional hubs or condensates, while putting constraints on the mechanism by which these form. These results fit in with the recent proposal that many transcription factors might share a common search strategy for target genes regulatory regions that makes use of their large unstructured regions, and may eventually help explain how the transcriptional response they elicit can be at the same time so fast and so precise. SIGNIFICANCE By conducting a comparative study of the nuclear dynamics of Bicoid (a transcriptional activator) and Capicua (a transcriptional repressor) in the Drosophila embryo, we have uncovered a striking similarity in their behaviours. Despite their divergent roles in transcription, both proteins have a propensity to form oligomeric species ranging from highly mobile, low stoichiometry clusters to larger, DNA-bound hubs. Such findings impose new constraints on the existing models of gene regulation by transcription factors, particularly in aspects related to target search and oligomeric binding to gene regulatory regions needed to explain the rapid and precise transcriptional response observed in developmental processes.

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 score0.002
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 head0.008
GPT teacher head0.200
Teacher spread0.191 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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