Rapid Changes in the Translatome during the Conversion of Growth Cones to Synaptic Terminals
Bibliographic record
Abstract
A common step in the formation of neural circuits is the conversion of growth cones to presynaptic terminals. Characterizing patterns of global gene expression during this process is problematic due to the cellular diversity of the brain and the complex temporal dynamics of development. Here, we take advantage of the synchronous conversion of Drosophila photoreceptor growth cones into presynaptic terminals to explore global changes in gene expression during presynaptic differentiation. Using a tandemly tagged ribosome trap (T-TRAP) and RNA sequencing (RNA-seq) at multiple developmental times, we observed dramatic changes in coding and non-coding RNAs with presynaptic differentiation. Marked changes in the mRNA encoding transmembrane and secreted proteins occurred preferentially. The 3' UTRs of transcripts encoding synaptic proteins were preferentially lengthened, and these extended UTRs were preferentially enriched for sites recognized by RNA binding proteins. These data provide a rich resource for uncovering the regulatory logic underlying presynaptic differentiation.
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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) | 0.001 | 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".