The <i>lin-4</i> MicroRNA Targets the LIN-14 Transcription Factor to Inhibit Netrin-Mediated Axon Attraction
Bibliographic record
Abstract
miR-125 microRNAs, such as lin-4 in Caenorhabditis elegans, were among the first microRNAs discovered, are phylogenetically conserved, and have been implicated in regulating developmental timing. Here, we showed that loss-of-function mutations in lin-4 microRNA increased axon attraction mediated by the netrin homolog UNC-6. The absence of lin-4 microRNA suppressed the axon guidance defects of anterior ventral microtubule (AVM) neurons caused by loss-of-function mutations in slt-1, which encodes a repulsive guidance cue. Selective expression of lin-4 microRNA in AVM neurons of lin-4-null animals indicated that the effect of lin-4 on AVM axon guidance was cell-autonomous. Promoter reporter analysis suggested that lin-4 was likely expressed strongly in AVM neurons during the developmental time frame that the axons are guided to their targets. In contrast, the lin-4 reporter was barely detectable in anterior lateral microtubule (ALM) neurons, axon guidance of which is insensitive to netrin. In AVM neurons, the transcription factor LIN-14, a target of lin-4 microRNA, stimulated UNC-6-mediated ventral guidance of the AVM axon. LIN-14 promoted attraction of the AVM axon through the UNC-6 receptor UNC-40 [the worm homolog of vertebrate Deleted in Colorectal Cancer (DCC)] and its cofactor MADD-2, which signals through both the UNC-34 (Ena) and the CED-10 (Rac1) downstream pathways. LIN-14 stimulated UNC-6-mediated axon attraction in part by increasing UNC-40 abundance. Our study indicated that lin-4 microRNA reduced the activity of LIN-14 to terminate UNC-6-mediated axon guidance of AVM neurons.
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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 | 0.001 |
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".