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Record W2732659948 · doi:10.7554/elife.25751

An intersectional gene regulatory strategy defines subclass diversity of C. elegans motor neurons

2017· article· en· W2732659948 on OpenAlexaff
Paschalis Kratsios, Sze Yen Kerk, Catarina Catela, Joseph Liang, Berta Vidal, Emily A. Bayer, Weidong Feng, Estanisla Daniel De La Cruz, Laura Croci, G. Giacomo Consalez, Kota Mizumoto, Oliver Hobert

Bibliographic record

VenueeLife · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of British Columbia
FundersHuman Frontier Science ProgramNational Institute of Neurological Disorders and StrokeFondazione TelethonHoward Hughes Medical Institute
KeywordsSubclassBiologyHox geneMotor neuronCaenorhabditis elegansGeneGeneticsNeuroscienceNeuronSpinal cordGene expression

Abstract

fetched live from OpenAlex

A core principle of nervous system organization is the diversification of neuron classes into subclasses that share large sets of features but differ in select traits. We describe here a molecular mechanism necessary for motor neurons to acquire subclass-specific traits in the nematode Caenorhabditis elegans. Cholinergic motor neuron classes of the ventral nerve cord can be subdivided into subclasses along the anterior-posterior (A-P) axis based on synaptic connectivity patterns and molecular features. The conserved COE-type terminal selector UNC-3 not only controls the expression of traits shared by all members of a neuron class, but is also required for subclass-specific traits expressed along the A-P axis. UNC-3, which is not regionally restricted, requires region-specific cofactors in the form of Hox proteins to co-activate subclass-specific effector genes in post-mitotic motor neurons. This intersectional gene regulatory principle for neuronal subclass diversification may be conserved from nematodes to mice.

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 score0.382
Threshold uncertainty score0.550

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 head0.020
GPT teacher head0.250
Teacher spread0.230 · 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

Citations71
Published2017
Admission routes1
Has abstractyes

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