Germ granule localization of nematode Argonaute WAGO-4 ensures fidelity in small RNA loading
Bibliographic record
Abstract
Germ granules are liquid-like condensates that regulate small RNA pathways and gene expression, ensuring genome stability and fertility in animals. In C. elegans, several Argonaute proteins, central players of small RNA pathways, localize to germ granules, yet the functional significance of this spatial enrichment remains unclear. Here, we disrupted the localization of the Argonaute WAGO-4 to germ granules by introducing targeted mutations in the FG repeats of Vasa-like GLH proteins. These mutations did not disrupt overall germ granule architecture but significantly reduced WAGO-4 partitioning, leading to its predominant localization in the cytoplasm. Functional analyses revealed that this mislocalization partially compromised WAGO-4 activity, resulting in reduced WAGO-4 binding of small RNAs targeting specific genes, particularly those not co-regulated by the Argonaute CSR-1. This selective effect highlights the importance of WAGO-4's spatial localization for efficient small RNA loading and gene regulation. Our findings demonstrate that germ granules serve as specialized compartments that fine-tune Argonaute function, emphasizing the role of phase-separated condensates in modulating RNA pathways and gene regulatory networks.
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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 | 0.001 |
| 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".