Nrl is dispensable for specification of rod photoreceptors in adult zebrafish contrasting a deeply conserved requirement earlier in ontogeny
Bibliographic record
Abstract
Abstract The transcription factor NRL (Neural Retinal Leucine-zipper) has been canonized, appropriately enough, as the master regulator of photoreceptor cell fate in the retina. NRL is necessary and sufficient to specify rod cell fate and to preclude cone cell fate in mice. By engineering zebrafish we tested if NRL function has conserved roles beyond mammals or beyond nocturnal species, i.e. in a vertebrate possessing a greater and more typical diversity of cone sub-types. Here, transgenic expression of a Nrl homolog from zebrafish or mouse was sufficient to convert developing zebrafish cones into rod photoreceptors. Zebrafish nrl -/- mutants lacked rods (and had excess UV-sensitive cones) as young larvae, thus the conservation of Nrl function between mice and zebrafish appears sound. These data inform hypotheses of photoreceptor evolution through the Nocturnal Bottleneck, suggesting that a capacity to favor nocturnal vision is a property of NRL that predates the emergence of early mammals. Strikingly, however, rods were abundant in adult nrl -/- null mutant zebrafish. Rods developed in adults despite Nrl protein being undetectable. Therefore a yet-to-be-revealed non-canonical pathway independent of nrl is able to specify the fate of some rod photoreceptors. Highlights - Nrl is conserved and sufficient to specify rod photoreceptors in zebrafish retina - Nrl is necessary for rod photoreceptors in early ontogeny of zebrafish larvae - Zebrafish Nrl is functionally conserved with mouse and human NRL - Remarkably, Nrl is dispensable for rod specification in adult zebrafish
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".