<i>Caenorhabditis elegans</i>DYF-2, an Orthologue of Human WDR19, Is a Component of the Intraflagellar Transport Machinery in Sensory Cilia
Bibliographic record
Abstract
The intraflagellar transport (IFT) machinery required to build functional cilia consists of a multisubunit complex whose molecular composition, organization, and function are poorly understood. Here, we describe a novel tryptophan-aspartic acid (WD) repeat (WDR) containing IFT protein from Caenorhabditis elegans, DYF-2, that plays a critical role in maintaining the structural and functional integrity of the IFT machinery. We determined the identity of the dyf-2 gene by transgenic rescue of mutant phenotypes and by sequencing of mutant alleles. Loss of DYF-2 function selectively affects the assembly and motility of different IFT components and leads to defects in cilia structure and chemosensation in the nematode. Based on these observations, and the analysis of DYF-2 movement in a Bardet-Biedl syndrome mutant with partially disrupted IFT particles, we conclude that DYF-2 can associate with IFT particle complex B. At the same time, mutations in dyf-2 can interfere with the function of complex A components, suggesting an important role of this protein in the assembly of the IFT particle as a whole. Importantly, the mouse orthologue of DYF-2, WDR19, also localizes to cilia, pointing to an important evolutionarily conserved role for this WDR protein in cilia development and function.
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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) | 0.000 | 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 | 0.001 |
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".