Fine tuning of RFX/DAF-19-regulated target gene expression through binding to multiple sites in Caenorhabditis elegans
Bibliographic record
Abstract
In humans, mutations of a growing list of regulatory factor X (RFX) target genes have been associated with devastating genetics disease conditions including ciliopathies. However, mechanisms underlying RFX transcription factors (TFs)-mediated gene expression regulation, especially differential gene expression regulation, are largely unknown. In this study, we explore the functional significance of the co-existence of multiple X-box motifs in regulating differential gene expression in Caenorhabditis elegans. We hypothesize that the effect of multiple X-box motifs is not a simple summation of binding effect to individual X-box motifs located within a same gene. To test this hypothesis, we identified eight C. elegans genes that contain two or more X-box motifs using comparative genomics. We examined one of these genes, F25B4.2, which contains two 15-bp X-box motifs. F25B4.2 expression in ciliated neurons is driven by the proximal motif and its expression is repressed by the distal motif. Our data suggest that two X-box motifs cooperate together to regulate the expression of F25B4.2 in location and intensity. We propose that multiple X-box motifs might be required to tune specific expression level. Our identification of genes with multiple X-box motifs will also improve our understanding of RFX/DAF-19-mediated regulation in C. elegans and in other organisms including humans.
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 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 | 0.000 | 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) | 0.001 | 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".