Axon-specific mRNA translation shapes dopaminergic circuit development
Bibliographic record
Abstract
SUMMARY The precise organization of midbrain dopaminergic (mDA) projections is essential for motor and cognitive functions, and their disruption contributes to multiple brain disorders. Yet the molecular mechanism guiding the development of these projections remains poorly defined. Here, we used ribosome tagging (RiboTag) and specific mouse crossing strategies (DATIRES-Cre mice) to isolate ribosome-bound mRNAs specifically from mDA axons and to analyze their axonal translatomes across developmental stages. We found that early-stage axons are enriched in transcripts involved in axon guidance and growth, while mature axons predominantly translate mRNAs related to synaptic function. Among key candidates, we identified PlxnA4, which is locally translated into mDA axons and modulates arborization in response to Sema3a. Functional assays in vitro and in vivo revealed that Plxna4-mediated signaling regulates topographical axon targeting and innervation, particularly in the nigrostriatal pathway. Our results uncover a dynamic and compartment-specific regulation of mRNA translation in developing mDA neurons, offering mechanistic insight into circuit formation and providing new molecular targets to improve integration of grafted neurons in regenerative therapies for Parkinson’s disease.
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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".