LRRC50, a Conserved Ciliary Protein Implicated in Polycystic Kidney Disease
Bibliographic record
Abstract
Cilia perform essential motile and sensory functions central to many developmental and physiological processes. Disruption of their structure or function can have profound phenotypic consequences, and has been linked to left-right patterning and polycystic kidney disease. In a forward genetic screen for mutations affecting ciliary motility, we isolated zebrafish mutant hu255H. The mutation was found to disrupt an ortholog of the uncharacterized highly conserved human SDS22-like leucine-rich repeat(LRR)-containing protein LRRC50 (16q24.1) and Chlamydomonas Oda7p. Zebrafish lrrc50 is specifically expressed in all ciliated tissues. lrrc50(hu255H) mutants develop pronephric cysts with an increased proliferative index, severely reduced brush border, and disorganized pronephric cilia manifesting impaired localized fluid flow consistent with ciliary dysfunction. Electron microscopy analysis revealed ultrastructural irregularities of the dynein arms and misalignments of the outer-doublet microtubules on the ciliary axonemes, suggesting instability of the ciliary architecture in lrrc50(hu255H) mutants. TheSDS22-like leucine-rich repeats present in Lrrc50 are necessary for proper protein function, since injection of a deletion construct of the first LRR did not rescue the zebrafish mutant phenotype. Subcellular distribution of human LRRC50-EGFP in MDCK and HEK293T cells is diffusely cytoplasmic and concentrated at the mitotic spindle poles and cilium. LRRC50 RNAi knock-down in human proximal tubule HK-2 cells thoroughly recapitulated the zebrafish brush border and cilia phenotype, suggesting conservation of LRRC50 function between both species. In summary, we present the first genetic vertebrate model for lrrc50 function and propose LRRC50 to be a novel candidate gene for human cystic kidney disease, involved in regulation of microtubule-based cilia and actin-based brush border microvilli.
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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 | 0.000 | 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".