The Homeobox Genes of Caenorhabditis elegans and Insights into Their Spatio-Temporal Expression Dynamics during Embryogenesis
Bibliographic record
Abstract
Homeobox genes play crucial roles for the development of multicellular eukaryotes. We have generated a revised list of all homeobox genes for Caenorhabditis elegans and provide a nomenclature for the previously unnamed ones. We show that, out of 103 homeobox genes, 70 are co-orthologous to human homeobox genes. 14 are highly divergent, lacking an obvious ortholog even in other Caenorhabditis species. One of these homeobox genes encodes 12 homeodomains, while three other highly divergent homeobox genes encode a novel type of double homeodomain, termed HOCHOB. To understand how transcription factors regulate cell fate during development, precise spatio-temporal expression data need to be obtained. Using a new imaging framework that we developed, Endrov, we have generated spatio-temporal expression profiles during embryogenesis of over 60 homeobox genes, as well as a number of other developmental control genes using GFP reporters. We used dynamic feedback during recording to automatically adjust the camera exposure time in order to increase the dynamic range beyond the limitations of the camera. We have applied the new framework to examine homeobox gene expression patterns and provide an analysis of these patterns. The methods we developed to analyze and quantify expression data are not only suitable for C. elegans, but can be applied to other model systems or even to tissue culture systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".