A Tendon Cell Specific RNAi Screen Reveals Novel Candidates Essential for Muscle Tendon Interaction
Bibliographic record
Abstract
Tendons are fibrous connective tissue which connect muscles to the skeletal elements thus acting as passive transmitters of force during locomotion and provide appropriate body posture. Tendon-derived cues, albeit poorly understood, are necessary for proper muscle guidance and attachment during development. In the present study, we used dorsal longitudinal muscles of Drosophila and their tendon attachment sites to unravel the molecular nature of interactions between muscles and tendons. We performed a genetic screen using RNAi-mediated knockdown in tendon cells to find out molecular players involved in the formation and maintenance of myotendinous junction and found 21 candidates out of 2507 RNAi lines screened. Of these, 19 were novel molecules in context of myotendinous system. Integrin-βPS and Talin, picked as candidates in this screen, are known to play important role in the cell-cell interaction and myotendinous junction formation validating our screen. We have found candidates with enzymatic function, transcription activity, cell adhesion, protein folding and intracellular transport function. Tango1, an ER exit protein involved in collagen secretion was identified as a candidate molecule involved in the formation of myotendinous junction. Tango1 knockdown was found to affect development of muscle attachment sites and formation of myotendinous junction. Tango1 was also found to be involved in secretion of Viking (Collagen type IV) and BM-40 from hemocytes and fat cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".