Identification and analysis of internal promoters in <i>Caenorhabditis elegans</i> operons
Bibliographic record
Abstract
The current Caenorhabditis elegans genomic annotation has many genes organized in operons. Using directionally stitched promoterGFP methodology, we have conducted the largest survey to date on the regulatory regions of annotated C. elegans operons and identified 65, over 25% of those studied, with internal promoters. We have termed these operons "hybrid operons." GFP expression patterns driven from internal promoters differ in tissue specificity from expression of operon promoters, and serial analysis of gene expression data reveals that there is a lack of expression correlation between genes in many hybrid operons. The average length of intergenic regions with putative promoter activity in hybrid operons is larger than previous estimates for operons as a whole. Genes with internal promoters are more commonly involved in gene duplications and have a significantly lower incidence of alternative splicing than genes without internal promoters, although we have observed almost all trans-splicing patterns in these two distinct groups. Finally, internal promoter constructs are able to rescue lethal knockout phenotypes, demonstrating their necessity in gene regulation and survival. Our work suggests that hybrid operons are common in the C. elegans genome and that internal promoters influence not only gene organization and expression but also operon evolution.
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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".