Caenorhabditis elegans cisRED: a catalogue of conserved genomic elements
Bibliographic record
Abstract
The availability of completely sequenced genomes from eight species of nematodes has provided an opportunity to identify novel cis-regulatory elements in the promoter regions of Caenorhabditis elegans transcripts using comparative genomics. We determined orthologues for C. elegans transcripts in C. briggsae, C. remanei, C. brenneri, C. japonica, Pristionchus pacificus, Brugia malayi and Trichinella spiralis using the WABA alignment algorithm. We pooled the upstream region of each transcript in C. elegans with the upstream regions of its orthologues and identified conserved DNA sequence elements by de novo motif discovery. In total, we discovered 158 017 novel conserved motifs upstream of 3847 C. elegans transcripts for which three or more orthologues were available, and identified 82% of 44 experimentally proven regulatory elements from ORegAnno. We annotated 26% of the motifs as similar to known binding sequences of transcription factors from ORegAnno, TRANSFAC and JASPAR. This is the first catalogue of annotated conserved upstream elements for nematodes and can be used to find putative regulatory elements, improve gene models, discover novel RNA genes, and understand the evolution of transcription factors and their binding sites in phylum Nematoda. The annotated motifs provide novel binding site candidates for both characterized transcription factors and orthologues of characterized mammalian transcription factors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".