Neurons Refine the Caenorhabditis elegans Body Plan by Directing Axial Patterning by Wnts
Bibliographic record
Abstract
Metazoans display remarkable conservation of gene families, including growth factors, yet somehow these genes are used in different ways to generate tremendous morphological diversity. While variations in the magnitude and spatio-temporal aspects of signaling by a growth factor can generate different body patterns, how these signaling variations are organized and coordinated during development is unclear. Basic body plans are organized by the end of gastrulation and are refined as limbs, organs, and nervous systems co-develop. Despite their proximity to developing tissues, neurons are primarily thought to act after development, on behavior. Here, we show that in Caenorhabditis elegans, the axonal projections of neurons regulate tissue progenitor responses to Wnts so that certain organs develop with the correct morphology at the right axial positions. We find that foreshortening of the posteriorly directed axons of the two canal-associated neurons (CANs) disrupts mid-body vulval morphology, and produces ectopic vulval tissue in the posterior epidermis, in a Wnt-dependent manner. We also provide evidence that suggests that the posterior CAN axons modulate the location and strength of Wnt signaling along the anterior-posterior axis by employing a Ror family Wnt receptor to bind posteriorly derived Wnts, and hence, refine their distributions. Surprisingly, despite high levels of Ror expression in many other cells, these cells cannot substitute for the CAN axons in patterning the epidermis, nor can cells expressing a secreted Wnt inhibitor, SFRP-1. Thus, unmyelinated axon tracts are critical for patterning the C. elegans body. Our findings suggest that the evolution of neurons not only improved metazoans by increasing behavioral complexity, but also by expanding the diversity of developmental patterns generated by growth factors such as Wnts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".