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Record W2096398908 · doi:10.1186/gb-2007-8-7-r135

Cell-specific microarray profiling experiments reveal a comprehensive picture of gene expression in the C. elegans nervous system

2007· article· en· W2096398908 on OpenAlexaff
Stephen E. Von Stetina, Joseph D. Watson, Rebecca M. Fox, Kellen Olszewski, William C. Spencer, Peter J. Roy, David M. Miller

Bibliographic record

VenueGenome biology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Human Genome Research InstituteNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Cancer InstituteNational Institutes of HealthNational Eye InstituteVanderbilt University
KeywordsBiologyHuman geneticsGene expression profilingMicroarrayComputational biologyGeneGeneticsDNA microarrayMicroarray analysis techniquesGene expressionCaenorhabditis elegans

Abstract

fetched live from OpenAlex

BACKGROUND: With its fully sequenced genome and simple, well-defined nervous system, the nematode Caenorhabditis elegans offers a unique opportunity to correlate gene expression with neuronal differentiation. The lineal origin, cellular morphology and synaptic connectivity of each of the 302 neurons are known. In many instances, specific behaviors can be attributed to particular neurons or circuits. Here we describe microarray-based methods that monitor gene expression in C. elegans neurons and, thereby, link comprehensive profiles of neuronal transcription to key developmental and functional properties of the nervous system. RESULTS: We employed complementary microarray-based strategies to profile gene expression in the embryonic and larval nervous systems. In the MAPCeL (Microarray Profiling C. elegans cells) method, we used fluorescence activated cell sorting (FACS) to isolate GFP-tagged embryonic neurons for microarray analysis. To profile the larval nervous system, we used the mRNA-tagging technique in which an epitope-labeled mRNA binding protein (FLAG-PAB-1) was transgenically expressed in neurons for immunoprecipitation of cell-specific transcripts. These combined approaches identified approximately 2,500 mRNAs that are highly enriched in either the embryonic or larval C. elegans nervous system. These data are validated in part by the detection of gene classes (for example, transcription factors, ion channels, synaptic vesicle components) with established roles in neuronal development or function. Of particular interest are 19 conserved transcripts of unknown function that are also expressed in the mammalian brain. In addition to utilizing these profiling approaches to define stage-specific gene expression, we also applied the mRNA-tagging method to fingerprint a specific neuron type, the A-class group of cholinergic motor neurons, during early larval development. A comparison of these data to a MAPCeL profile of embryonic A-class motor neurons identified genes with common functions in both types of A-class motor neurons as well as transcripts with roles specific to each motor neuron type. CONCLUSION: We describe microarray-based strategies for generating expression profiles of embryonic and larval C. elegans neurons. These methods can be applied to particular neurons at specific developmental stages and, therefore, provide an unprecedented opportunity to obtain spatially and temporally defined snapshots of gene expression in a simple model nervous system.

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 score0.016
Threshold uncertainty score0.679

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 head0.016
GPT teacher head0.247
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

Citations128
Published2007
Admission routes1
Has abstractyes

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